Skoove is not being mentioned in this article, by my opinion this is not enough for Digital PR to have positive impact for us. It has a potential to go broad, but if we are not being mentioned, only linked I think the value of this link without contextual surrounding will be very low for both our SEO and brand reputation efforts.

Analysis done by Skoove and Datapulse, as we want to be mentioned high in the article.

I am really missing Skoove being mentioned in the methodology, what was our role here? Why would anyone give us link or a mention or citation, if we are only mentioned once?

In order to benefit from brand awareness, it would be really nice having Skoove expert being quoted, insteas of a musician. In general, mentioning Skoove in a way that we really participated in this campaign would be really important for us.

Same comment here, seems to be really relevant to Indian media potentially, but our performance and earnings in that market are not giving enough reasons to highlight it.

It would be great if one of our core markets is at the beginning of the article, instead of India and Costa Rica, as we also potentially want to be published in those. At least France or Spain for example.

Unique cultural aspects of Benin traditions. Enjoy local market bargains. Learn about voodoo beliefs. Prepare for the fascinating moto-taxis known as "zem."

A new initiative called the WorkerBee pool. Where users can delegate their WORKERBEE tokens to support a witness. While earning BEE tokens without any fees.

Learn the alchemical concept of "the son of the Sun and Moon." As a symbol of the union of opposites. See the transformative journey to an unknowable source.

Fund smaller projects within the Hive community. Using the Shark Tank Community for project pitches. Also, the #hiveproject hashtag to increase visibility.

Single-cell proteomics: From Protein Variation to Biological Functions

Presentation by Prof. Nikolai Slavov at the MRC Protein Phosphorylation and Ubiquitylation Unit, Dundee University: Technological and biological frontiers for single-cell proteomics: From Protein Variation to Biological Functions. The presented research was performed at Slavov Laboratory, Northeastern University and Parallel Squared Technology Institute.

https://youtu.be/8nhjKSTqeOs?si=kq_eYIjEnpQBmH4Q

It seems in group C; the samples are "most different" at V5. Though no specific taxa or topics are found here (further down in the report)

Some assignments are going to be from a general understanding but always pay attention to the text or to your instructor presenting the assignments.

it is important to do research and engage yourself into the material you are writing about to get your message across effectively.

PF Chang’s Menu with Prices https://pfchangmenu.com/

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Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Manuscript number: RC-2025-02879 Corresponding author(s): Matteo Allegretti; Alia dos Santos

1. General Statements

In this study, we investigated the effects of paclitaxel on both healthy and cancerous cells, focusing on alterations in nuclear architecture. Our novel findings show that:

• Paclitaxel-induced microtubule reorganisation during interphase alters the perinuclear distribution of actin and vimentin. The formation of extensive microtubule bundles, in paclitaxel or following GFP-Tau overexpression, coincides with nuclear shape deformation, loss of regulation of nuclear envelope spacing, and alteration of the nuclear lamina.

• Paclitaxel treatment reduces Lamin A/C protein levels via a SUN2-dependent mechanism. SUN2, which links the lamina to the cytoskeleton, undergoes ubiquitination and consequent degradation following paclitaxel exposure.

• Lamin A/C expression, frequently dysregulated in cancer cells, is a key determinant of cellular sensitivity to, and recovery from, paclitaxel treatment.

Collectively, our data support a model in which paclitaxel disrupts nuclear architecture through two mechanisms: (i) aberrant nuclear-cytoskeletal coupling during interphase, and (ii) multimicronucleation following defective mitotic exit. This represents an additional mode of action for paclitaxel beyond its well-established mechanism of mitotic arrest.

We thank the reviewers for their time and constructive feedback. We have carefully considered all comments and have carried out a full revision. The updated manuscript now includes additional data showing:

• Overexpression of microtubule-associated protein Tau causes similar nuclear aberration phenotypes to paclitaxel. This supports our hypothesis that increased microtubule bundling directly leads to nuclear disruption in paclitaxel during interphase.

• Paclitaxel's effects on nuclear shape and Lamin A/C and SUN2 expression levels occur independently of cell division.

• Reduced levels of Lamin A/C and SUN2 upon paclitaxel treatment occur at the protein level via ubiquitination of SUN2.

• The effects of paclitaxel on the nucleus are conserved in breast cancer cells.

Full Revision

We have also edited our text and added further detail to clarify points raised by the reviewers. We believe that our revised manuscript is overall more complete, solid and compelling thanks to the reviewers' comments.

1. Point-by-point description of the revisions

Reviewer #1 Evidence, reproducibility and clarity

This description of the down-regulation of the expression of lamin A/C upon treatment with paclitaxel and its sensitivity to SUN2 is quite interesting but still somehow preliminary. It is unclear whether this effect involves the regulation of gene expression, or of the stability of the proteins. How SUN2 mediates this effect is still unknown.

We thank the reviewer for this valuable comment. To elucidate the mechanism behind the decrease in Lamin A/C and SUN2 levels, we have now performed several additional experiments. First, we performed RT-qPCR to quantify mRNA levels of these genes, relative to the housekeeping gene GAPDH (Supplementary Figure 3B and O). The levels of SUN2 and LMNA mRNA remained the same between control and paclitaxel-treated cells, indicating that this effect instead occurs at the protein level. We have also tested post-translational modifications as a potential regulatory mechanism for Lamin A/C and SUN2. In addition to the phosphorylation of Ser404 which we had already tested (Supplementary Figure 3C), we have now included additional Phos-tag gel and Western blotting data showing that the overall phosphorylation status of Lamin A/C is not affected by paclitaxel (Supplementary Figure 3E and F). We also pulled-down Lamin A/C from cell lysates and then Western blotted for polyubiquitin and acetyl-lysine, which showed that the ubiquitination and acetylation states of Lamin A/C are also not affected by paclitaxel (Supplementary Figure 3G-I). However, Western blots for polyubiquitin of SUN2 pulled down from cell lysates showed that paclitaxel treatment results in significant SUN2 ubiquitination (Figure 3M and N). Therefore, we propose that the downregulation of SUN2 following paclitaxel treatment occurs by ubiquitin-mediated proteolysis.

The roles of free tubulins and polymerized microtubules, and thus the potential role of paclitaxel, need to be uncovered.

We addressed this important point by using an alternative method to stabilise/bundle microtubules in interphase, namely by overexpressing GFP-Tau, as suggested by reviewer 2. Following GFP- Tau overexpression, large microtubule bundles were observed throughout the cytoplasm (Figure 4A), and this resulted in a significant decrease in nuclear solidity (Figure 4B). Furthermore, in cells where microtubule bundles extensively contacted the nucleus, the nuclear lamina became unevenly distributed and appeared patchy (Figure 4C). This supports our hypothesis that the aberrations to nuclear shape and Lamin A/C localisation in paclitaxel-treated cells are due to the presence of microtubules bundles surrounding the nucleus.

The doses of paclitaxel at which occur the effects described in the paper are not fully consistent with all the conclusions. Most experiments have been done at 5 nM. However, at this dose the effect of lamin A/C over or down expression on the growth (differences in the slopes of the curves in Figure 4A) are not fully convincing and not fully consistent with the clear effect on viability as well (in addition, duration of treatments before assessing vialbility are not specified). At 1 nM, cell growth is reduced and the rescuing effect of lamin over-expression is much more clear (Fig 4A), and the nucleus deformation clear (Fig 2A) but this dose has no effect on lamin A/C expression (Fig 3C), which questions how lamins impact nucleus shape and cell survival. Cytoskeleton reorganisation in these conditions is not described although it could clarify the respective role of force production (suggested in figure 1) and nuclei resistance (shown in figure 2) in paclitaxel sensitivity.

We thank the reviewer for raising this important point. We have addressed this by conducting additional repeats for the cell confluency measurements to increase the statistical power of our experiments (Figure 5A). Our data now show that GFP-lamin A/C had a statistically significant effect on rescuing cell growth at both 1 nM and 5 nM paclitaxel, while Lamin A/C knockdown exacerbated the inhibition of cell growth at 5 nM paclitaxel but not 1 nM paclitaxel (Figure 5A). In addition, we note that the duration of paclitaxel treatment before assessing viability was specified in the figure legend: "Bar graph comparing cell viability between wild-type (red), GFP-Lamin A/C overexpression (green), and Lamin A/C knockdown (blue) cells following 20 h incubation in 0, 1, 5, or 10 nM paclitaxel." We also repeated cell viability analysis after 48 h incubation in paclitaxel instead of 20 h to allow for a longer time for differences to take effect (Figure 5B).

We also added figures showing the cytoskeletal reorganisation at both 1 and 10 nM in addition to 0 and 5 nM (Supplementary Figure 1A) showing that microtubule bundling and condensation of actin into puncta correlated with increased paclitaxel concentration. Vimentin colocalised well with microtubules at all concentrations.

We have also included in our results section further clarification for the use of 5nM paclitaxel in this study. The new section reads as follows: "Experiments were performed at 5 nM paclitaxel (with additional experiments to determine dose relationships at 1 and 10 nM) because this aligns with previous studies7,14,24. Furthermore, previous analysis of patient plasma reveals that typical concentrations are within the low nanomolar range8, and concentrations of 5-10 nM are required in cell culture to reach the same intracellular concentrations observed in vivo in patient tumours9. This aligns with in vitro cytotoxic studies of paclitaxel in eight human tumour cell lines which show that paclitaxel's IC50 ranges between 2.5 and 7.5 nM41."

Finally, although the absence of role of mitotic arrest is clear from the data, the defective reorganisation of the nucleus after mitosis still suggest that the effect of paclitaxel is not independent of mitosis.

We thank the reviewer for pointing out the need for clarification in the wording of our manuscript. We have reworded the title and relevant sections of our abstract, introduction, and discussion to make it clearer that the effects of paclitaxel on the nucleus are due to a combination of aberrant nuclear cytoskeletal coupling during interphase and multimicronucleation following mitotic slippage. We have also added additional data in support of the effect of paclitaxel on nuclear architecture during interphase. For this, we used serum-starved cells (which divide only very slowly such that the majority of cells do not pass through mitosis during the 16 h incubation in paclitaxel [Supplementary Figure 2D]). Our new data confirmed that paclitaxel's effects on nuclear solidity, and Lamin A/C and SUN2 proteins levels can occur independently of cell division (Figure 2C; Figure 3H-J). Finally, when we overexpressed GFP-Tau (as discussed above) we observed similar aberrations to nuclear solidity and Lamin A/C localisation. This indicates that these effects occur due to microtubule bundling in interphase, especially as in our study GFP-Tau did not lead to multimicronucleation or appear to affect mitosis (Figure 4).

Below are the main changes to the text regarding the interphase effect of paclitaxel:

• Title: "Paclitaxel compromises nuclear integrity in interphase through SUN2-mediated cytoskeletal coupling"

• Abstract: "Overall, our data supports nuclear architecture disruption, caused by both aberrant nuclear-cytoskeletal coupling during interphase and exit from defective mitosis, as an additional mechanism for paclitaxel beyond mitotic arrest."

• Introduction: "Here we propose that cancer cells have increased vulnerability to paclitaxel both during interphase and following aberrant mitosis due to pre-existing defects in their NE and nuclear lamina."

• Discussion: "Overall, our work builds on previous studies investigating loss of nuclear integrity as an anti-cancer mechanism of paclitaxel separate from mitotic arrest14,20,21. We propose that cancer cells show increased sensitivity to nuclear deformation induced by aberrant nuclear-cytoskeletal coupling and multimicronucleation following mitotic slippage. Therefore, we conclude that paclitaxel functions in interphase as well as mitosis, elucidating how slowly growing tumours are targeted."

minor: a more thorough introduction of known data about dose response of cells in culture and in vivo would help understanding the range of concentrations used in this study.

As mentioned above, we have now included additional information in our Results section to clarify our paclitaxel dose range: "Experiments were performed at 5 nM paclitaxel (with additional experiments to determine dose relationships at 1 and 10 nM) because this aligns with previous studies7,14,24. Furthermore, previous analysis of patient plasma reveals that typical concentrations are within the low nanomolar range8, and concentrations of 5-10 nM are required in cell culture to reach the same intracellular concentrations observed in vivo in patient tumours9. This aligns with in vitro cytotoxic studies of paclitaxel in eight human tumour cell lines which show that paclitaxel's IC50 ranges between 2.5 and 7.5 nM41."

Significance

In this manuscript, Hale and colleagues describe the effect of paclitaxel on nucleus deformation and cell survival. They showed that 5nM of paclitaxel induces nucleus fragmentation, cytoskeleton reorganisation, reduced expression of LaminA/C and SUN2, and reduced cell growth and viability. They also showed that these effects could be at least partly compensated by the over-expression of lamin A/C. As fairly acknowledged by the authors, the induction of nuclear deformation in paclitaxel-treated cells, and the increased sensitivity to paclitaxel of cells expressing low level of lamin A/C are not novel (reference #14). Here the authors provided more details on the cytoskeleton changes and nuclear membrane deformation upon paclitaxel treatment. The effect of lamin A/C over and down expression on cell growth and survival are not fully convincing, as further discussed below. The most novel part is the observation that paclitaxel can induce the down-regulation of the expression of lamin A/C and that this effect is mediated by SUN2.

We appreciate the reviewer's summary and thank them for their time. We believe our comprehensive revisions have addressed all comments, strengthening the manuscript and making it more robust and compelling.

Reviewer #2 Evidence, reproducibility and clarity This study investigates the effects of the chemotherapeutic drug paclitaxel on nuclear-cytoskeletal coupling during interphase, claiming a novel mechanism for its anti-cancer activity. The study uses hTERT-immortalized human fibroblasts. After paclitaxel exposure, a suite of state- of-the-art imaging modalities visualizes changes in the cytoskeleton and nuclear architecture. These include STORM imaging and a large number of FIB-SEM tomograms.

We thank the reviewer for the summary and for highlighting our efforts in using the latest imaging technical advances.

Major comments:

The authors make a major claim that in addition to the somewhat well-described mechanism of paclitaxel on mitosis, they have discovered 'an alternative, poorly characterised mechanism in interphase'.

However, none of the data proves that the effects shown are independent of mitosis. To the contrary, measurements are presented 48 hours after paclitaxel treatment starts, after which it can be assumed that 100% of cells have completed at least one mitotic event. The appearance of micronuclei evidences this, as discussed by the authors shortly. It looks like most of the results shown are based on botched mitosis or, more specifically, errors on nuclear assembly upon exit from mitosis rather than a specific effect of paclitaxel on interphase. The readouts the authors show just happen to be measurements while the cells are in interphase.

Alternative hypotheses are missing throughout the manuscript, and so are critical controls and interpretations.

We thank the reviewer for highlighting the lack of clarity in our wording. We have revised the title, abstract and relevant sections of the introduction and discussion to clarify our message that the effects of paclitaxel on the nucleus arise from a combination of aberrant nuclear-cytoskeletal coupling during interphase and multimicronucleation following exit from defective mitosis. We have also included additional data where we used slow-dividing, serum-starved cells (under these conditions, the majority of cells do not undergo mitosis during the 16 h incubation in paclitaxel [Supplementary Figure 2D]). Our new data show that even in these cells there is a clear effect of paclitaxel on nuclear solidity, and Lamin A/C and SUN2 protein levels, further supporting our hypothesis that these phenotypes can occur independently of cell division (Figure 2C; Figure 3H-J). Furthermore, we performed additional experiments where we used overexpression of GFP-Tau as an alternative method of stabilising microtubules in interphase and observed similar aberrations to nuclear solidity and Lamin A/C localisation. As GFP-Tau overexpression did not lead to micronucleation or appear to affect mitosis, these data support the hypothesis that nuclear aberrations occur due to microtubule bundling in interphase (Figure 4). We discuss these experiments in more detail below. Finally, we have reworded the introduction to better introduce alternative hypotheses and mechanisms for paclitaxel's activity.

The authors claim that 'Previously, the anti-cancer activity of paclitaxel was thought to rely mostly on the activation of the mitotic checkpoint through disruption of microtubule dynamics, ultimately resulting in apoptosis.' The authors may have overlooked much of the existing literature on the topic, including many recent manuscripts from Xiang-Xi Xu's and another lab.

We would like to note that the paper from Xiang-Xi Xu's lab (Smith et al, 2021) was cited in our original manuscript (reference 14 in both the original and revised manuscripts). We have now also included additional review articles from the Xiang-Xi Xu lab (PMID:36368286 20 and PMID: 35048083 21). Furthermore, we have clarified the wording in both the introduction and discussion to better reflect the current understanding of paclitaxel's mechanism and alternative hypotheses.

The data, e.g. in Figure 1, does not hold up to the first alternative hypothesis, e.g. that paclitaxel stabilizes microtubules and that excessive mechanical bundling of microtubules induces major changes to cell shape and mechanical stress on the nucleus. Even the simplest controls for this effect (the application of an alternative MT stabilizing drug or the overexpression of an MT stabilizer, e.g., tau).

We thank the reviewer for suggesting this control experiment using the microtubule stabiliser Tau. We have now included these experiments in the revised version of the manuscript (Figure 4). The overexpression of GFP-Tau supports our hypothesis that cytoskeletal reorganisation in paclitaxel exerts mechanical stress on the nucleus during interphase, resulting in nuclear deformation and aberrations to the nuclear lamina. In particular, GFP-Tau overexpression resulted in large microtubule bundles throughout the cytoplasm (Figure 4A). Notably, in cells where these bundles extensively contacted the nucleus, we observed a significant decrease in nuclear solidity (Figure 4B) accompanied by changes in nuclear lamina organisation, including a patchy lamina phenotype, similar to that induced by paclitaxel (Figure 4C).

The focus on nuclear lamina seems somewhat arbitrary and adjacent to previously published work by other groups. What would happen if the authors stained for focal adhesion markers? There would probably be a major change in number and distribution. Would the authors conclude that paclitaxel exerts a specific effect on focal adhesions? Or would the conclusion be that microtubule stabilization and the following mechanical disruption induce pleiotropic effects in cells? Which effects are significant for paclitaxel function on cancer cells?

We thank the reviewer for raising important points regarding the specificity of paclitaxel's effects. We agree that microtubule stabilisation can induce myriad cellular changes, including alterations to focal adhesions and other cytoskeletal components. Our focus on Lamin A/C and nuclear morphology is grounded both in the established clinical relevance of nuclear mechanics in cancer and builds on mechanistic work from other groups.

Lamin A/C expression is commonly altered in cancer, and nuclear morphology is frequently used in cancer diagnosis35. Lamin A/C also plays a crucial role in regulating nuclear mechanics32 and, importantly, determines cell sensitivity to paclitaxel14. However, the mechanism by which Lamin A/C determines sensitivity of cancer cells to paclitaxel is unclear.

Our data are consistent with Lamin A/C being a determinant of paclitaxel survival sensitivity. We also provide evidence that paclitaxel itself reduces Lamin A/C protein levels and disrupts its organisation at the nuclear envelope. We directly link these effects to microtubule bundling around the nucleus and degradation of force-sensing LINC component SUN2, highlighting the importance of nuclear architecture and mechanics to overall cellular function. Furthermore, we show that recovery from paclitaxel treatment depends on Lamin A/C expression levels. This has clinical relevance, as unlike cancer cells, healthy tissue with non-aberrant lamina would be able to selectively recover from paclitaxel treatment.

Minor comments:

While I understand the difficulty of the experiments and the effort the authors have put into producing FIB-SEM tomograms, I am not sure they are helping their study or adding anything beyond the light microscopy images. Some of the images may even be in the way, such as supplementary Figure 6, which lacks in quality, controls, and interpretation. Do I see a lot of mitochondria in that slice?

We agree with the reviewer that Supplementary Figure 6 does not add significant value to the manuscript and thank the reviewer for pointing this out. We have removed it from the manuscript accordingly.

I may have overlooked it, but has the number of cells from which lamellae have been produced been stated?

We thank the reviewer for pointing out the missing information. For our cryo-ET experiments, we collected data from 9 lamellae from paclitaxel-treated cells and 6 lamellae from control cells, with each lamella derived from a single cell. This information has now been added to the figure legend (Figure 2F).

Significance

The significance of studying the effect of paclitaxel, the most successful chemotherapy drug, should be broad and of interest to basic researchers and clinicians.

As outlined above, I believe that major concerns about the design and interpretation of the study hamper its significance and advancements.

We appreciate the reviewer's concerns and have performed major revisions to strengthen the significance of our study. Specifically, we conducted two key sets of experiments to validate our original conclusions: serum starvation to control for the effects of cell division, and overexpression of the microtubule stabiliser Tau to demonstrate that paclitaxel can affect the nucleus via its microtubule bundling activity in interphase.

By elucidating the mechanistic link between microtubule stabilisation and nuclear-cytoskeletal coupling, our findings contribute to our understanding of paclitaxel's multifaceted actions in cancer cells.

My areas of expertise could be broadly defined as Cell Biology, Cytoskeleton, Microtubules, and Structural Biology.

Reviewer #3 Evidence, reproducibility and clarity The manuscript presents interesting new ideas for the mechanism of an old drug, taxol, which has been studied for the last 40 years.

We thank the reviewer for the positive feedback.

Although similar ideas are published, which may be suitable to be cited? • Paclitaxel resistance related to nuclear envelope structural sturdiness. Smith ER, Wang JQ, Yang DH, Xu XX. Drug Resist Updat. 2022 Dec;65:100881. doi: 10.1016/j.drup.2022.100881. Epub 2022 Oct 15. PMID: 36368286 Review. • Breaking malignant nuclei as a non-mitotic mechanism of taxol/paclitaxel. Smith ER, Xu XX. J Cancer Biol. 2021;2(4):86-93. doi: 10.46439/cancerbiology.2.031. PMID: 35048083 Free PMC article.

We thank the reviewer for bringing to our attention these important review articles. In our initial manuscript, we only cited the original paper (14, also reference 14 in the original manuscript). We have now included citations to the suggested publications (20,21).

We would also like to emphasise how our manuscript distinguishes itself from the work of Smith et al.14,20,21:

• Cell-type focus: In their study 14, Smith et al. examined the effect of paclitaxel on malignant ovarian cancer cells and proposed that paclitaxel's effects on the nucleus are limited to cancer cells. However, our data extends these findings by demonstrating paclitaxel's effects in both cancerous and non-cancerous backgrounds.

• Cytoskeletal reorganisation: Smith et al. show reorganisation of microtubules in paclitaxel-treated cells14. Our data show re-organisation of other cytoskeletal components, including F-actin and vimentin.

• Multimicronucleation: Smith et al. propose that paclitaxel-induced multimicronucleation occurs independently of cell division14. Although we observe progressive nuclear abnormalities during interphase over the course of paclitaxel treatment, our data do not support this conclusion; we find that multimicronucleation occurs only following mitosis.

• Direct link between microtubule bundling and nuclear aberrations: We show that nuclear aberrations caused by paclitaxel during interphase (distinct from multimicronucleation) are directly linked to microtubule bundling around the nucleus, suggesting they result from mechanical disruption and altered force propagation.

• Lamin A/C regulation: Consistent with Smith et al.14, we show that Lamin A/C depletion leads to increased sensitivity to paclitaxel treatment. However, we further demonstrate that paclitaxel itself leads to reduced levels of Lamin A/C and that this effect occurs independently of mitosis and is mediated via force-sensing LINC component SUN2. Upon SUN2 knockdown, Lamin A/C levels are no longer affected by paclitaxel treatment.

• Recovery: Finally, our work reveals that cells expressing low levels of Lamin A/C recover less efficiently after paclitaxel removal. This might help explain how cancer cells could be more susceptible to paclitaxel.

Only one cell line was used in all the experiments? "Human telomerase reverse transcriptase (hTERT) immortalised human fibroblasts" ? The cells used are not very relevant to cancer cells (carcinomas) that are treated with paclitaxel. It is not clear if the observations and conclusions will be able to be generalized to cancer cells.

We thank the reviewer for this comment. Our initial study aimed to understand the effects of paclitaxel on nuclear architecture in non-aberrant backgrounds. To show that the observed effects of paclitaxel are also applicable to cancer cells, we have now repeated our main experiments using MDA-MB-231 human breast cancer cells (Supplementary Figure 1B; Supplementary Figure 3P-T). Similar to our findings in human fibroblasts, paclitaxel treatment of MDA-MB-231 led to cytoskeletal reorganisation (Supplementary Figure 1B), a decrease in nuclear solidity (Supplementary Figure 3P), aberrant (patchy) localisation of Lamin A/C (Supplementary Figure 3Q), and a reduction in Lamin A/C and SUN2 levels (Supplementary Figure 3R-T).

"Fig. 1. (B) STORM imaging of α-tubulin immunofluorescence in cells fixed after 16 h incubation in control media or 5 nM paclitaxel. Lower panels show α-tubulin clusters generated with HDBSCAN analysis. Scale bars = 10 μm." It needs explanation of what is meaning of the different color lines in the lower panels, just different filaments?

We have added further detail to the figure legend for clarification: "Lower panels show α-tubulin clusters generated with HDBSCAN analysis. Different colours distinguish individual α-tubulin clusters, representing individual microtubule filaments or filament bundles."

Generally, the figures need additional description to be clear.

We have added further clarification and detail to our figure legends.

"Figure 3 - Paclitaxel results in aberrations to the nuclear lamina." The sentence seems not to be well constructed. "Paclitaxel treatment causes ..."?

We changed this sentence to: "Figure 3 - Paclitaxel treatment results in aberrant organisation of the nuclear lamina and decreased Lamin A/C levels via SUN2."

Lamin A and C levels are different in different images (Fig. 3B, H): some Lamin A is higher, and sometime Lamin C is higher? This may possibly due to culture condition or subtle difference in sample handling?.

We thank the reviewer for pointing this out and we agree that the ratio of Lamin A to Lamin C can vary with culture conditions. To confirm that paclitaxel treatment reduces total Lamin A/C levels regardless of this ratio, we repeated the Western blot analysis in three additional biological replicates using cells in which Lamin C levels exceeded Lamin A levels. These experiments confirmed a comparable decrease in total Lamin A/C levels. Figure 3B and 3C have been updated accordingly.

Also, the effect on Lamin A/C and SUN2 levels are not significant of robust.

Decreased Lamin A/C and SUN2 levels following paclitaxel treatment were consistently seen across three or more biological repeats (Figure 3B-C), and this could be replicated in a different cell type (MDA-MB-231) (Supplementary Figure 3R-T). Furthermore, Western blotting results are consistent with the patchy Lamin A/C distribution observed using confocal and STORM following paclitaxel treatment (Figure 3A; Supplementary Figure 3A), where Lamin A/C appears to be absent from discrete areas of the lamina.

Any mechanisms are speculated for the reason for the reduction?

We have now included additional data which aims to shed light on the mechanism behind the decrease in Lamin A/C and SUN2 levels following paclitaxel treatment. We found that SUN2 is selectively degraded during paclitaxel treatment. Immunoprecipitation of SUN2 followed by Western blotting against Polyubiquitin C showed increased SUN2 ubiquitination in paclitaxel (Figure 3M and N). Furthermore, in our original manuscript, we showed that Lamina A/C levels remained unaltered during paclitaxel treatment in cells where SUN2 had been knocked down. We propose that changes in microtubule organisation affect force propagation to Lamin A/C specifically via SUN2 and that this leads to Lamina A/C removal and depletion. Future work will be needed to fully understand this mechanism.

In addition to the findings described above, we report no significant changes in mRNA levels for LMNA or SUN2 in paclitaxel (Supplementary Figure 3B and O). Phos-tag gels followed by Western blotting analysis for Lamin A/C also did not detect changes to the overall phosphorylation status of Lamin A/C due to paclitaxel treatment. This is in agreement with our initial data showing no changes to Lamin A/C Ser 404 phosphorylation levels (Supplementary Figure 3E and F). Finally, Lamin A/C immunoprecipitation experiments followed by Western blotting for Polyubiquitin C and acetyl-lysine showed no significant changes in the ubiquitination and acetylation state of Lamin A/C in paclitaxel-treated cells (Supplementary Figure 3G-I).

Also, the about 50% reduction in protein level is difficult to be convincing as an explanation of nuclear disruption.

The nuclear lamina and LINC complex proteins play a critical role in regulating nuclear integrity, stiffness and mechanical responsiveness to external forces28,31-33,54,75, as well as in maintaining the nuclear intermembrane distance69,74. In particular, SUN-domain proteins physically bridge the nuclear lamina to the cytoskeleton through interactions with Nesprins, thereby preserving the perinuclear space distance30,69,74. Mutations in Lamins have been shown to disrupt chromatin organization, alter gene expression, and compromise nuclear structural integrity, and experiments with LMNA knockout cells reveal that nuclear mechanical fragility is closely coupled to nuclear deformation47. Furthermore, nuclear-cytoskeletal coupling is essential during processes such as cell migration, where cells undergo stretching and compression of the nucleus; weakening or loss of the lamina in such cases compromises cell movement47,73. In our work, we show that alterations to nuclear Lamin A/C and SUN2 by paclitaxel treatment coincide with nuclear deformations (Figure 2A-D, F, G; Figure 3A-D, F, G; Supplementary Figure 3A, P-T) and that these deformations are reversible following paclitaxel removal (Supplementary Figure 4B-D). Our experiments also demonstrate that Lamin A/C expression levels significantly influence cell growth, cell viability, and cell recovery in paclitaxel (Figure 5). Therefore, drawing on current literature and our results, we propose that, during interphase, paclitaxel induces severe nuclear aberrations through the combined effects of: i) increased cytoskeletal forces on the NE caused by microtubule bundling; ii) loss of ~50% Lamin A/C and SUN2; iii) reorganisation of nucleo-cytoskeletal components.

Significance

The manuscript presents interesting new ideas for the mechanism of an old drug, taxol, which has been studied for the last 40 years.

The data may be improved to provide stronger support.

Additional cell lines (of cancer or epithelial origin) may be repeated to confirm the generality of the observation and conclusions.?

We thank the reviewer for the feedback and valuable suggestions. In response, we have included experiments using human breast cancer cell line MDA-MB-231 to further corroborate our findings and interpretations. We believe these additions have improved the clarity, robustness and impact of our manuscript, and we are grateful for the reviewer's contributions to its improvement.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #3

Evidence, reproducibility and clarity

The manuscript presents interesting new ideas for the mechanism of an old drug, taxol, which has been studied for the last 40 years. Although similar ideas are published, which may be suitable to be cited?

• Paclitaxel resistance related to nuclear envelope structural sturdiness. Smith ER, Wang JQ, Yang DH, Xu XX. Drug Resist Updat. 2022 Dec;65:100881. doi: 10.1016/j.drup.2022.100881. Epub 2022 Oct 15. PMID: 36368286 Review.
• Breaking malignant nuclei as a non-mitotic mechanism of taxol/paclitaxel. Smith ER, Xu XX. J Cancer Biol. 2021;2(4):86-93. doi: 10.46439/cancerbiology.2.031. PMID: 35048083 Free PMC article.

Only one cell line was used in all the experiments? "Human telomerase reverse transcriptase (hTERT) immortalised human fibroblasts" ? The cells used are not very relevant to cancer cells (carcinomas) that are treated with paclitaxel. It is not clear if the observations and conclusions will be able to be generalized to cancer cells.

"Fig. 1. (B) STORM imaging of α-tubulin immunofluorescence in cells fixed after 16 h incubation in control media or 5 nM paclitaxel. Lower panels show α-tubulin clusters generated with HDBSCAN analysis. Scale bars = 10 μm." It needs explanation of what is meaning of the different color lines in the lower panels, just different filaments?

Generally, the figures need additional description to be clear.

"Figure 3 - Paclitaxel results in aberrations to the nuclear lamina." The sentence seems not to be well constructed. "Paclitaxel treatment causes ..."?

Lamin A and C levels are different in different images (Fig. 3B, H): some Lamin A is higher, and sometime Lamin C is higher? This may possibly due to culture condition or subtle difference in sample handling?. Also, the effect on Lamin A/C and SUN2 levels are not significant of robust. Any mechanisms are speculated for the reason for the reduction? Also, the about 50% reduction in protein level is difficult to be convincing as an explanation of nuclear disruption.

Significance

The manuscript presents interesting new ideas for the mechanism of an old drug, taxol, which has been studied for the last 40 years.

The data may be improved to provide stronger support.

Additional cell lines (of cancer or epithelial origin) may be repeated to confirm the generality of the observation and conclusions.?

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

This study investigates the effects of the chemotherapeutic drug paclitaxel on nuclear-cytoskeletal coupling during interphase, claiming a novel mechanism for its anti-cancer activity. The study uses hTERT-immortalized human fibroblasts. After paclitaxel exposure, a suite of state-of-the-art imaging modalities visualizes changes in the cytoskeleton and nuclear architecture. These include STORM imaging and a large number of FIB-SEM tomograms.

Major comments:

The authors make a major claim that in addition to the somewhat well-described mechanism of paclitaxel on mitosis, they have discovered 'an alternative, poorly characterised mechanism in interphase'.

However, none of the data proves that the effects shown are independent of mitosis. To the contrary, measurements are presented 48 hours after paclitaxel treatment starts, after which it can be assumed that 100% of cells have completed at least one mitotic event. The appearance of micronuclei evidences this, as discussed by the authors shortly. It looks like most of the results shown are based on botched mitosis or, more specifically, errors on nuclear assembly upon exit from mitosis rather than a specific effect of paclitaxel on interphase. The readouts the authors show just happen to be measurements while the cells are in interphase.

Alternative hypotheses are missing throughout the manuscript, and so are critical controls and interpretations.

The authors claim that 'Previously, the anti-cancer activity of paclitaxel was thought to rely mostly on the activation of the mitotic checkpoint through disruption of microtubule dynamics, ultimately resulting in apoptosis.' The authors may have overlooked much of the existing literature on the topic, including many recent manuscripts from Xiang-Xi Xu's and another lab.

The data, e.g. in Figure 1, does not hold up to the first alternative hypothesis, e.g. that paclitaxel stabilizes microtubules and that excessive mechanical bundling of microtubules induces major changes to cell shape and mechanical stress on the nucleus. Even the simplest controls for this effect (the application of an alternative MT stabilizing drug or the overexpression of an MT stabilizer, e.g., tau).

The focus on nuclear lamina seems somewhat arbitrary and adjacent to previously published work by other groups. What would happen if the authors stained for focal adhesion markers? There would probably be a major change in number and distribution. Would the authors conclude that paclitaxel exerts a specific effect on focal adhesions? Or would the conclusion be that microtubule stabilization and the following mechanical disruption induce pleiotropic effects in cells? Which effects are significant for paclitaxel function on cancer cells?

Minor comments:

While I understand the difficulty of the experiments and the effort the authors have put into producing FIB-SEM tomograms, I am not sure they are helping their study or adding anything beyond the light microscopy images. Some of the images may even be in the way, such as supplementary Figure 6, which lacks in quality, controls, and interpretation. Do I see a lot of mitochondria in that slice?

I may have overlooked it, but has the number of cells from which lamellae have been produced been stated?

Significance

The significance of studying the effect of paclitaxel, the most successful chemotherapy drug, should be broad and of interest to basic researchers and clinicians.

As outlined above, I believe that major concerns about the design and interpretation of the study hamper its significance and advancements.

My areas of expertise could be broadly defined as Cell Biology, Cytoskeleton, Microtubules, and Structural Biology.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #1

Evidence, reproducibility and clarity

This description of the down-regulation of the expression of lamin A/C upon treatment with paclitaxel and its sensitivity to SUN2 is quite interesting but still somehow preliminary. It is unclear whether this effect involves the regulation of gene expression, or of the stability of the proteins. How SUN2 mediates this effect is still unknown. The roles of free tubulins and polymerized microtubules, and thus the potential role of paclitaxel, need to be uncovered.

The doses of paclitaxel at which occur the effects described in the paper are not fully consistent with all the conclusions. Most experiments have been done at 5 nM. However, at this dose the effect of lamin A/C over or down expression on the growth (differences in the slopes of the curves in Figure 4A) are not fully convincing and not fully consistent with the clear effect on viability as well (in addition, duration of treatments before assessing vialbility are not specified). At 1 nM, cell growth is reduced and the rescuing effect of lamin over-expression is much more clear (Fig 4A), and the nucleus deformation clear (Fig 2A) but this dose has no effect on lamin A/C expression (Fig 3C), which questions how lamins impact nucleus shape and cell survival. Cytoskeleton reorganisation in these conditions is not described although it could clarify the respective role of force production (suggested in figure 1) and nuclei resistance (shown in figure 2) in paclitaxel sensitivity.

Finally, although the absence of role of mitotic arrest is clear from the data, the defective reorganisation of the nucleus after mitosis still suggest that the effect of paclitaxel is not independent of mitosis.

minor: a more thorough introduction of known data about dose response of cells in culture and in vivo would help understanding the range of concentrations used in this study.

Significance

In this manuscript, Hale and colleagues describe the effect of paclitaxel on nucleus deformation and cell survival. They showed that 5nM of paclitaxel induces nucleus fragmentation, cytoskeleton reorganisation, reduced expression of LaminA/C and SUN2, and reduced cell growth and viability. They also showed that these effects could be at least partly compensated by the over-expression of lamin A/C. As fairly acknowledged by the authors, the induction of nuclear deformation in paclitaxel-treated cells, and the increased sensitivity to paclitaxel of cells expressing low level of lamin A/C are not novel (reference #14). Here the authors provided more details on the cytoskeleton changes and nuclear membrane deformation upon paclitaxel treatment. The effect of lamin A/C over and down expression on cell growth and survival are not fully convincing, as further discussed below. The most novel part is the observation that paclitaxel can induce the down-regulation of the expression of lamin A/C and that this effect is mediated by SUN2.

eLife Assessment

This manuscript uses modeling approaches to provide mechanistic insight into the structural and dynamic properties of enhancer-promoter interactions in Drosophila. Given the interest in this field, this is a timely approach, and the results give useful insights by providing predictions about the processivity of cohesin loop extrusion in Drosophila and concluding that the compartmental interaction strength is poised near criticality in the coil-globule phase space. The evidence provided to support some of the conclusions is, however, incomplete and would be strengthened by better considering some of the caveats in the data used to constrain the models, such as the use of "homie" genetic elements in the dynamic data. There is insufficient evidence provided for the dynamics being criticality-driven, and in addition, consideration of alternative models would further strengthen the conclusions of the manuscript.

Reviewer #1 (Public review):

Summary:

This computational study investigates the physical mechanisms underlying enhancer-promoter (E-P) interactions across genomic distances in Drosophila chromosomes, motivated by a previously published study that revealed unexpectedly frequent long-range contacts challenging classical polymer models. The authors performed coarse-grained polymer simulations testing three chromatin organization models: ideal polymers, loop extrusion, and compartmental segregation, comparing their predictions to experimental Hi-C contact maps, mean E-P distances, and two-locus mean-squared displacement dynamics. They found that compartmental segregation best captured both the structural and dynamic features observed experimentally, while neither ideal chains nor loop extrusion alone could reproduce all experimental observables. The combination of compartmental segregation with loop extrusion further improved agreement with experimental data, suggesting these mechanisms might be involved in Drosophila chromatin organization.

Strengths:

The paper has two primary strengths:

(1) The simulations are based on biologically interpretable mechanisms (compartmentalization and loop extrusion), which may facilitate making specific experimentally testable predictions.

(2) The work uses a systematic approach to increase model complexity by directly fitting to data, first establishing that simple models fail to capture the data until arriving at a more complex model that does capture the data.

Weaknesses:

I have two major concerns (detailed below) and multiple minor concerns.

Major concerns:

(1) While the upside of the mechanistic simulations is that they are interpretable, the downside is that specific choices for the considered mechanism were made, and conclusions drawn from it are necessarily biased by the initial choices. In this paper, only two mechanisms were considered: loop extrusion and compartmentalization. Yet, it is not clear why these are the most likely underlying mechanisms that might determine the chromosome dynamics. Indeed, previous work (not cited in this paper) showed that Drosophila chromosome structure is not determined by loop extrusion: https://elifesciences.org/articles/94070.

This should be acknowledged, and the main reasons for choosing these particular mechanisms should be laid out. The conclusions of the paper must then necessarily always be seen under the caveat that only these two mechanisms were considered.

(2) Even within the framework of the approach, insufficient evidence is given to support the title of the paper "Criticality-driven enhancer-promoter dynamics in Drosophila chromosomes" for two reasons:

(a) The fact that the best-fit parameters are near a coil-globule transition does not mean that the resulting dynamics are criticality-driven. To claim criticality, one would usually expect much more direct evidence, such as diverging correlation lengths. Furthermore, it would need to be shown that the key features of the dynamics (which should be defined, presumably the static and dynamic exponents) indeed depend on the parameters being at this transition. i.e., when tuning the simulations away from this parameter point, does the behaviour disappear? Only in this case can it be claimed that the behaviour is driven by this phenomenon.

(b) The results section actually contains no mention of the coil-globule transition, and it is not clear in what way the parameters are close to this transition.

Thus, three things are necessary:

(i) How the parameters are close to the transition needs to be explained in detail.

(ii) The divergence of observed dynamics whenever the parameters are tuned away from the transition needs to be demonstrated.

(iii) Even if 1 and 2 are fulfilled, a more careful title should be chosen, such as "Polymer simulations near the coil-globule transition are consistent with enhancer-promoter dynamics in Drosophila chromosomes."

Many of the results in the figures and results section are rather repetitive and could be compressed. The main result of Figure 1 - that the data are not described by an ideal chain - was already fully shown and established in the original paper from which the data are taken. Figure 2 is a negative result with near-identical panels to Figure 3. Figure 4B is hard to interpret.

The paper makes no concrete suggestions for new experiments to test the hypotheses formulated. Since the paper can only claim that the simulations are consistent with the data, it would significantly strengthen the paper if testable predictions could be made.

Reviewer #2 (Public review):

Summary:

In this work, Ganesh and colleagues use experimental data from Hi-C and from live-cell imaging to evaluate different polymer models of 3D genome organization in Drosophila based on both structural and dynamic properties. The authors consider several leading hypotheses, which are examined sequentially in increasing level of complexity - from the minimal Rouse polymer, to a model combining sequence-specific compartmentalization and loop-extrusion without extrusion blockers. They conclude that the combination of both compartmentalization and loop-extrusion gives the best agreement with the data. Their analysis also leads to concrete predictions about the processivity of cohesin loop extrusion in Drosophila, and a conclusion that the compartmental interaction strength is poised near criticality in the coil-globule phase space.

Strengths:

There is considerable interest in the field in understanding the mechanisms responsible for the 3D spatial organization genome and the dynamic movement of the genome, which has major implications for our understanding of long-range transcriptional regulation and other genome behaviors. The live-cell experimental work on which this study draws highlights the limitations of existing models to explain even the dynamic behaviors observed in the data, further exciting interest in further exploration. Therefore, this paper seeks to address an important gap in the field. The work is written in a well-organized, well-illustrated fashion. The text and figures are nicely integrated, easy to read, and explain challenging concepts with elegance and brevity in a manner that will be accessible to a broad audience.

Weaknesses:

The validity and utility of these conclusions are, in my view, substantially undermined by what appears to be unappreciated peculiarities of the live-cell data set that was used to constrain the model. The live-cell data comes from embryos were edited in a way that intentionally substantively changed both the 3D genome structure and dynamics specifically at the loci which are imaged, a case which is not at all explained by any of the models suggested nor acknowledged in the current work, nor compatible with the Hi-C data that simultaneously used to explain these models. As these ignored synthetic alterations have been previously shown to be determinative of transcriptional activity, the relevance of the author's work to transcriptional control (a prime motivation in the introduction) is unclear.

The agreement in 3D organization, as represented in chromosome-scale contact frequency heatmaps, is substantially less impressive than the agreement seen in prior work with similar models. This discrepancy appears to be due in part to the unappreciated effects of the mentioned in the previous limitation, as well as inappropriate choices in metrics used to evaluate agreement. It is also not particularly surprising that combining more models, with more free parameters, results in an improvement in the quality of fit.

Some major results, including both theoretical works and experimental ones, are ignored, despite their relevance to the stated objective of the work. The current manuscript and analysis could be improved substantially by a consideration of these works.

I describe these issues in more detail below.

Major issues:

(1) The genetic element "homie" is present in a subset of the data: The experimental data used in this analysis come from different fly lines, half of which have been edited explicitly to alter genome structure and consequent transcriptional behavior, yet the authors are trying to fit with a common model - a problem which substantially undermines the utility of the analysis.

Specifically, the authors evaluate the various models/simulations by comparing them to Hi-C from wildtype Drosophila embryos on the chromosome scale and 3D distances and dynamics from live cell imaging in genetically edited embryos, to a series of models in turn. The exercise fatally overlooks a critical fact, (admittedly not easily noticed in the work from Bruckner et al), that the fly embryos used for nearly all their analyses contain not only fluorescent labels, but also contain two copies of a powerful genetic sequence, "homie", known for its ability to dramatically change the 3D organization and dynamics of the genome. Whether or not the fluorescent labels themselves used in the study further alter structure and dynamics is not entirely clear (and will require further work beyond the scope of either study), but at least these fluorescent labels aren't known to dramatically affect 3D structure and dynamics the way homie is. The critical problem is that adding or removing the "homie", as shown in a collection of prior works I describe below in more detail, dramatically affects structure, dynamics, and gene expression. Whether or not the genome contains two distal cis-linked copies of homie fundamentally changes genome structure and dynamics, so to use one dataset which has this edit (the live-cell data) and one dataset which lacks it (the Hi-C data) is, in some sense, to guarantee failure of any model to match all the data.

If the authors had chosen instead to focus exclusively on the 'no homie' genetic lines in the Brukner data, they would have a much smaller dataset (just 2 distances), which would not cover all the length scales of interest, but it would at least be a dataset not known to be contradictory to the Hi-C. The two 'no homie' lines make much more plausible candidates for the sort of generalizable polymer dynamics these authors seek to explain, as will hopefully be made more clear by a brief review of what is known about homie. I next describe the published data that support these conclusions about how homie affects 3D genome spatial organization and dynamics:

What is "homie" and how does it affect 3D genome distances, dynamics, and gene expression?

The genetic element "homie" was named by James Jaynes' lab ( Fujioka...Jaynes 2009) in reference to its remarkable "homing" ability - a fascinating and still poorly understood biological observation that some genetic sequences from Drosophila, when cloned on plasmids and reintegrated into the genome with p-elements, had a remarkable propensity to re-integrate near their endogenous sequence, (Hama et al., 1990; Kassis, 2002; Taillebourg and Dura, 1999; Bender and Hudson, 2000; Fujioka...Jaynes 2009). By contrast, most genetic elements tend to incorporate at random across the genome in such assays (with some bias for active chromatin).

The Jaynes lab subsequently showed that flies carrying two copies of homie, one integrated in cis, ~140 kb distal from the endogenous element, formed preferential cis contacts with one another. Indeed, if a promoter and reporter gene were included at this distal integration site, the reporter gene would activate gene expression in the pattern normally seen by the gene, even-skipped. The endogenous copy of homie marks one border of ~16 kb mini-TAD which contains the even-skipped gene, (eve), and its developmental enhancers, so this functional interaction provides further evidence of physical proximity (as was also shown by 3C by Jaynes (Fujioka..., Schedl, Jaynes 2016), and later with elegant live imaging, by Jaynes and Gregor (Chen 2018)).

Critically, if either copy of homie is deleted or substantially mutated, the 3D proximity is lost (Fujioka 2016, Chen 2018, Bruckner 2023), and the expression of the transgene is dramatically reduced (at 58 kb) or lost. Given the author's motivation of understanding "E-P" interactions, the fact that the increased 3D proximity provided by homie is as essential for transcription as the promoter itself at the ~150 kb distance, underscores that these are not negligible changes.

These effects can be seen by plotting the data from Bruckner 2023, which includes data from labels with separations of 58 kb and ~150 kb "no homie" as well as homie. Unfortunately, the authors don't plot this data in the manuscript in the comparison of 3D distances, though the two-point MSD can be seen in Figure S13C, and laudably, the data is made public in a well-annotated repository on Zenodo, noted in the study. Note that the distance data in Figure S13 were filtered to exclude the transcriptionally off state, and are thus not the quantity the current authors are interested in. If they plot the published data for no homie, they will see the clear effect on the average 3D distance, R(s), and a somewhat stronger effect on the contact frequency P(s), which causes significant deviation from the trend-line followed by the homie-containing data.

(2) The agreement between the "best performing" simulations for all models and the Hi-C data is not on par with prior studies using similar approaches, apparently due to some erroneous choices in how the optimization is carried out:

Hi-C-comparison

The 'best fit' simulation Hi-C looks strikingly different from the biological data in all comparisons, with clearly lower agreement than other authors have shown using highly similar methods (e.g., Shi and Thirumalai 2023; Di Pierro et al. 2017; Nuebler et al. 2018; Esposito et al. 2022; Conte et al. 2022), among many others. I believe this results from a few issues with how the current authors select and evaluate the data in their work:

(a) Most works have used Pearson's correlation rather than Spearman's correlation when comparing simulation and Hi-C contact frequencies. Pearson's correlation is more appropriate when we expect the values to be linearly related, which they should be in this case, as they are constructed indeed to be measuring the same thing (contact frequency), just derived from two different methods. Spearman's correlation would have been justifiable for comparing how transcription output correlates with contact frequency. This may fix the bafflingly low correlations reported at lower adhesion values in Figure S2C.

(b) Choice of adhesion strengths - The Hi-C map comparison in Figure 3 strongly suggests that a much more striking visual agreement would have been achieved if much weaker (but still non-zero) homotypic monomer affinity had been selected. In the authors' simulation, the monomer state (A/B identity) strongly dominates polymer position, resulting in the visual appearance of an almost black-and-white checkerboard. The data, meanwhile, look like a weak checkerboard superimposed on the polymer.

(c) A further confounding problem is the aforementioned issue that the Hi-C data don't come from the edited cell lines, and that the interaction of the two Homie sites is vastly stronger than the compartment interactions of this region of the genome.

(3) Some important concepts from the field are ignored:

The crumpled/fractal globule model is widely discussed in the literature (including the work containing the data used in this study) - its exclusion from this analysis thus appears as a substantial gap/oversight:

A natural alternative to the much-discussed Rouse polymer model is the "crumpled polymer" (Grosberg et al. 1988; Grosberg 2016; Halverson et al. 2011; Halverson et al. 2011), also known as the "fractal globule" (Lieberman-Aiden et al. 2009; Mirny 2011; Dekker and Mirny 2016; Boettiger et al. 2016), much discussed for the way it captures the ⅓ scaling of R(s), found for much of the genome (or, equivalently, the -1 exponent of the probability of contact as a function of genome separation, P(s)). Given the 1/3rd scaling in the data, and the fact that the original authors highlighted the crumpled model in addition to the Rouse model, it seems that this comparison would be instructive and the lack of discussion an oversight. Moreover, while prior works (e.g., Buckner, Gregor, 2023) used some traditional simplifying assumptions to estimate the MSD and relaxation time scaling of this model, I believe a more rigorous analysis with explicit simulations (as in Figure 1 for the Rouse model) would be instructive for the crumpled polymer simulations. Note the crumpled globule is not necessarily the same as the globule in the coil-globule transition discussed here - it requires some assumptions about non-entanglement to stay trapped in the meta-stable state which has the 1/3rd R(s) scaling that is indicative of this model, and not the 1/2 exhibited by equilibrium globules (for s<< length of the polymer) and dilute polymers alike.

While the fit in Figure 2 appears to get closer to the 1/3rd exponent (B= 0.32), this appears to be a largely coincidental allusion of agreement - the simulation data in truth shows a systematic deviation, returning to the 1/2 scaling for distances from 500 kb to whole chromosomes. This feature is not very evident as the authors restrict the analysis to only the few points available in the experimental data, though had they tested intervening distances I expect they would show log-log P(s) is nonlinear (non-powerlaw) for distances less than the typical loop length up to a few fold larger than the loop length, and thereafter returns to the scaling provided by the 'base' polymer behavior. This appears to be Rouse-like in these authors' model, with R(s) going like 1/2, even though the data are closer to 1/3rd, as indeed most published simulated P(s) curves based on loop extrusion - e.g., (Fudenberg et al. 2016; Nuebler et al. 2018). In this vein, it would be instructive to the readers if the authors would include additional predictions from the simulation on the plot that lie at genomic separation distances not tested in the data, to better appreciate the predictions.

Minor issues

(1) I think it is too misleading to only describe the experimental data from Brukner as "E-P" interactions from Drosophila. It is important to note somewhere that this is not an endogenous interaction with a functional role in Drosophila - it is a synthetic interaction between enhancers in the vicinity of the eve gene and a synthetic promoter placed at a variable distance away. The uniformity is elegant - (it is the same pair of elements being studied at all distances), but also provides limited scope for generalization as suggested by the current text. Moreover, the enhancers were not directly labeled; rather, the 3D position of nascent RNA transcribed from eve was tracked with an RNA-binding protein and used as a proxy for the 3D position of the enhancers. There is not an individual enhancer at the eve locus that interacts with the transgene, but rather a collection of enhancers is distributed at different positions throughout the entire TAD, which contains eve, and must form separate loops to reach eve. Indeed, it was previously reported that differences in the local position of these enhancers, relative to eve, affect their ability to interact with the distal reporter gene and the endogenous eve gene (Chen 2018). There is also reported competition between these enhancers and the distal gene, which further complicates the analysis (especially since the state of eve and of its enhancers varies among the different cells as a function of stripe position) - see Chen 2018. All of this is ignored in the current work, despite the assertion of the application to understanding E-P interaction. A detailed discussion of these issues is not necessary, but I fear that ignoring them entirely is to invite further confusion and error.

(2) I believe this sentence is overstated, given available data: " TAD borders are characterized by transitions between epigenetic states rather than by preferentially-bound CTCF [4, 23, 24]." Indeed, this claim has been repeatedly made in the literature as cited here. However, other data clearly demonstrate a strong enrichment of CTCF at TAD borders (and at epigenetic borders, which in Drosophila have a high correspondence with TAD borders, as the authors have already appropriately noted). See, for example, Figure 4 of Sexton Cell 2012, and compare to Figure 2 of Dixon 2012. Of minor note, CTCF peaks co-occupied by the Zinc Finger TF CP190 are more likely to be TAD borders than CTCF alone. How big a species-specific difference this is remains unclear, as it appears some mammalian CTCF-marked TAD boundaries may be co-occupied by additional ZNFs. While plenty of Drosophila TAD boundaries indeed lack CTCF, many are marked by CTCF, this is enriched relative to what would be expected by chance (or relative to the alignment of other TFs, like Twist or Eve with TAD boundaries), and it has been shown that CTCF loss is sufficient to remove a subset of these, see for example Figure 5 of (Kaushal et al. 2021) (though it is possible, most will require mutation of the all the border-associated factors that collectively bind many of the borders, dCTCF, CP190, mod(mdg4) and others).

(3) This assertion is overstated given available data: "Although TAD boundaries in Drosophila are often associated with insulator proteins [20], there is no direct evidence that these elements block LEFs in vivo. Therefore, we did not impose boundary constraints in our simulations; LEFs were allowed to move freely unless stalled by collisions with other LEFs, with the possibility of crossover.". Deletion of insulator in Drosophila that lie within a common epigenetic state leads to fusion of TADs (e.g., Mateo et al., 2019 - deletion of the CTCF-marked Fub insulator, in posterior tissues where both flanks of Fub are active; Kaushal, 2021, has examples as well). Loss of CTCF causes a small number of TADs to fuse as measured by Hi-C. This is far from 'direct evidence that insulators block LEFs' - as the authors have already noted, even the idea that cohesin extrudes loops in Drosophila in the first place is indeed controversial. However, LEF activity and stalling at insulators would provide a very natural explanation of why chromatin in a shared epigenetic state should form distinct TADs, and why these TADs should fuse upon insulator deletion. Justifying the lack of stalling sites based on empirical data is thus not very convincing to this reviewer. I believe it would be more apt to simply describe this as a simplifying assumption, rather than the above phrase, which may be misleading.

Author response:

We thank the editors and the reviewers for their constructive comments, which have greatly helped us identify key areas to strengthen the manuscript. We acknowledge the validity of the major points raised, and we plan the following revisions:

Criticality

As suggested by Reviewer #1, we will carefully examine whether the dynamics we observe are indeed poised near criticality. We will perform additional analyses to assess how structural and dynamic features change when parameters are tuned away from the coil–globule transition, and we will revise the title and text to ensure that our claims are appropriately moderated.

Role of the homie element

We agree with Reviewer #2 that the presence of homie elements introduces major modifications to chromosome structure and dynamics. We initially considered that this factor might even explain the paradox described in Gregor’s work. In the first phase of our study, we carried out simulations including homie elements and found that the potential confounding effects are largely resolved if we restrict the analysis to trajectories prior to encounters between the two homie copies. We will include these simulations and expand the discussion accordingly in the revised version.

Comparison to Hi-C data

Both reviewers noted a visual discrepancy between experimental and simulated Hi-C maps. We will address this by testing alternative similarity measures (e.g., Pearson correlation, as suggested) and by exploring parameter ranges that may improve the agreement.<br /> Together, these modifications will strengthen the manuscript, clarify the scope of our conclusions, and directly address the reviewers’ central concerns.

eLife Assessment

This paper explores the role of extracellular vesicles in providing extracellular matrix signals for migration of vascular smooth muscle cells. The evidence, based on cell culture experiments and supporting imaging of human samples, is mostly convincing. The paper will be valuable for researchers investigating cell migration during vessel repair and atherogenesis.

Reviewer #1 (Public review):

In this revised submission from Kapustin et al., the authors have made significant changes to the manuscript. Namely, the authors have addressed several of the major issues with the original submission, providing a more concrete link between fibronectin and the secretion of extracellular vesicles. Additionally, the authors have moderated some of the conclusions to better suit the rigor of the experimental results and limitations of their approach. Generally, the findings convey an interesting cell autonomous pathway in which smooth muscle cells sense fibronectin, which canonically is a proinflammatory substrate with activating properties in many tissues. Fibronectin-mediated integrin signaling stimulates secretion of small extracellular vesicles containing collagen VI which is deposited into the surrounding extracellular matrix. Collagen VI itself gleaned from extracellular vesicle secretion seems to further alter smooth muscle cell morphodynamics. For this later finding, much of the mechanism behind collagen VI vesicle loading and secretion has yet to be worked out. The authors provide evidence of extracellular vesicles containing collagen VI trapped in fibronectin in atherosclerotic plaques providing a nice validation of their in vitro findings in a diseased human cohort. Some limitations do still exist in the manuscript in its current form such as the assessment of the vesicle origins, contents and their association with the actin cytoskeleton; however, the rigor and execution are much improved from the preceding version. Overall, the pathobiology underlying vascular smooth muscle remodeling in disease states is a critical area of research that warrants further exploration.

Reviewer #2 (Public review):

The findings in the current manuscript are interesting and valuable contributions to the fields of vascular biology and extracellular vesicle-related mechanisms. They suggest a potential role for smooth muscle cell-derived extracellular vesicles in presenting Type VI collagen to cells to orchestrate their migration, with proposed relevance to aberrant smooth muscle cell movements in the progression of atherosclerotic lesions. A wide range of assays are utilized to test various aspects of this working model, with the resulting data being largely solid and supporting several of the interpretations articulated by the authors. The revised manuscript has adequately addressed key weaknesses.

The authors present data suggesting a working model in which vascular smooth muscle cells (vSMCs) are stimulated by fibronectin (FN) to generate small extracellular vesicles (sEVs) that harbor Type VI Collagen (collagen VI). These collagen VI-associated sEVs are suggested to accumulate in the extracellular matrix (ECM) and influence cell migration and adhesion dynamics, potentially contributing to disease progression in atherosclerosis. Majors strengths of this manuscript include robust imaging data and the inclusion of human-derived samples in their analysis. The authors also make a reasonable attempt to provide data to support the potential existence of these mechanistic connections, though some minor questions remain regarding data interpretation. The authors largely achieved their aims of finding evidence consistent with their interpretations, and they have presented logical support for their conclusions while acknowledging important limitations and caveats to their current study. This work will likely have a sustained impact on the field of sEV biology and potential intersections with vascular biology, including their methodology e.g., imaging approaches. As biologists continue to explore the role of sEVs in physiological and pathological processes, this work raises an interesting aspect that must be considered more broadly, and that is, what is the role of sEVs that are ECM-associated and not necessarily internalized by recipient cells? Are there discrete mechanisms that govern their role in maintaining and/or disrupting normal physiological processes? This manuscript makes an attempt to address these unresolved yet critical questions.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Summary

In this investigation Kapustin et al. demonstrate that vascular smooth muscle cells (VSMCs) exposed to the extracellular matrix fibronectin stimulates the release of small extracellular vesicles (sEVs). The authors provide experimental evidence that stimulation of the actin cytoskeleton boosts sEV secretion and posit that sEVs harbor both fibronectin and collagen IV protein themselves which also, in turn, alter cell migration parameters. It is well established that fibronectin is associated with increased cell migration and adherence; therefore, this association with VSMCs is not novel.

The reviewer is correct that FN has been associated with migration and adherence in previous studies.  However we have extended these observations to show that the extracellular fibronectin matrix stimulates small extracellular vesicle (sEVs) secretion by modulating the actin cytoskeleton. We also showed that sEVs are trapped in the extracellular matrix and that by presenting collagen VI induce early focal adhesion formation, reduce excessive cellular spreading and guide cell invasion directionality though a 3D matrix. Hence, sEVs mediate cell-matrix cross talk and change cell behaviour in the context of fibronectin matrix. This is critically important for vasculature where regulated VSMC invasion is essential for repair with its deregulation leading to pathology.

The authors purport that sEV are largely born of filopodia origin; however, this data is not well executed and seems generally at odds with the presented data.

Our experimental data showed that CD63 MVs are associated with filopodia in fixed and live cells (Fig 2E, 2F and Video S1) and that inhibition of filopodia formation using the formin inhibitor, SMIFH2 reduced sEV secretion on FN (Fig 2B). However, we agree with the reviewer that further studies are required to connect sEV secretion to filopodia.  To address this we have provided further data analysis but also toned down our conclusions regarding this point: . Changes include:

(1) Title: Matrix-associated extracellular vesicles modulate smooth muscle cell adhesion and directionality by presenting collagen VI.

(2) Results, section title: 2. FN-induced sEV secretion is modulated by Arp2/3 and formin-dependent actin cytoskeleton remodelling

(3) Results, page 6 Line 27-44 and conclusion page 7, Ln 3 “Interestingly, CD63+ MVBs can be observed in filopodia-like structures suggesting that sEV secretion can also occur spatially via cellular protrusion-like filopodia but more studies are needed to confirm this hypothesis.”

(4) Discussion, page 12, line 19. “Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells.”

Similarly, the effect of sEVs on parameters of cell migration has almost no magnitude of effect, making mechanism exploration somewhat nebulous.

VSMC are mesenchymal-type cells with a low migration rate and we agree that the changes in the motility are not of great magnitude even for the positive controls suggesting that this is a complex, multifactorial process for VSMCs. In our experiments we collected data from >5000 individual cells to measure the average speed and found that fibronectin matrix on its own increased VSMC speed from ~0.61 um/min to ~0.68 μm/min (~12% raise) which was statistically significant (Fig 5A). Addition of a sEV inhibitor caused a modest but significant decrease in cellular speed. Interestingly, addition of ECM-associated sEVs did not influence cell speed in 2D or 3D assays. However in a 3D model we observed a 22% change in cell directionality (Fig 5G) and  a 235% change in cell alignment index (FMI, Fig 5H) which we believe is very strong evidence that VSMC-derived sEVs are involved in a regulation of VSMC invasion directionality.  These data are also in agreement with sEV effects in tumour cells (Sung et al., 2015) though this previous study did not identify the factor driving the directionality and we think our Collagen VI data extends significantly these previous observations. 

Results, page 9: “Hence, ECM-associated sEVs have modest influence on VSMC speed but influence VSMC invasion directionality.”.  

Lastly, the proposed mechanism of VSMCs responding to, and depositing, ECM proteins via sEVs was not rigorously executed; again, making the conclusions challenging for the reader to interpret.

We appreciate the reviewer’s comment regarding the mechanistic aspects of VSMCs responding to and depositing ECM proteins via sEVs. In our revised manuscript, we have expanded the data demonstrating that sEVs can be retained within the extracellular matrix (see Figs 3A, 3B, S3A, S3B). Additionally, we show that collagen VI is present on the surface of sEVs, where it may modulate cell adhesion and influence the directionality of cell invasion (Fig 7E). Our results further indicate that both fibronectin (FN) and collagen VI can be recycled through multivesicular bodies (see Figs S3C, S3D, S3E–S3G). However, we acknowledge that the precise mechanisms governing the selective loading of ECM proteins onto sEVs, as well as the specific contributions of sEVs to overall ECM organization, remain to be fully elucidated and warrant further investigation. Based on our current evidence, we propose that collagen VI–loaded sEVs act primarily in a signaling capacity by modulating focal adhesion formation but are not directly involved in ECM structural remodeling.

Results, page 7: To quantify ECM-trapped sEVs we applied a modified protocol for the sequential extraction of extracellular proteins using salt buffer (0.5M NaCl) to release sEVs which are loosely-attached to ECM via ionic interactions, followed by 4M guanidine HCl buffer (GuHCl) treatment to solubilize strongly-bound sEVs (Fig S3A) [42]. We quantified total sEV and characterised the sEV tetraspanin profile in conditioned media, and the 0.5M NaCl and GuHCl fractions using ExoView. The total particle count showed that EVs are both loosely bound and strongly trapped within the ECM. sEV tetraspanin profiling showed differences between these 3 EV populations.  While there was close similarity between the conditioned media and the 0.5M NaCl fraction with high abundance of CD63+/CD81+ sEVs as well as CD63+/CD81+/CD9+ in both fractions (Fig S3A). In contrast, the GuHCl fraction was particularly enriched with CD63+ and CD63+/CD81+ sEVs with very low abundance of CD9+ EVs (Fig S3A). The abundance of CD63+/CD81+ sEVs was confirmed independently by a CD63+ bead capture assay in the media and loosely bound fractions (Fig S3B).

Results, page 7: We previously found that the serum protein prothrombin binds to the sEV surface both in the media and MVB lumen showing it is recycled in sEVs and catalyses thrombogenesis being on the sEV surface43. So we investigated whether FN can also be associated with sEV surface where it can be directly involved in sEV-cell cross-talk43.   We treated serum-deprived primary human aortic VSMCs with FN-Alexa568 and found that it was endocytosed and subsequently delivered to early and late endosomes together with fetuin A, another abundant serum protein that is a recycled sEV cargo and elevated in plaques (Figs S3C and S3D). CD63 visualisation with a different fluorophore (Alexa488) confirmed FN colocalization with CD63+ MVBs (Fig S3E). Next, we stained non-serum deprived VSMC cultured in normal growth media (RPMI supplemented with 20% FBS) with an anti-FN antibody and observed colocalization of CD63 and serum-derived FN.  Co-localisation was reducd likely due to competitive bulk protein uptake by non-deprived cells (Fig S3F). Notably, when we compared FN distribution in sparsely growing VSMCs versus confluent cells we found that FN intracellular spots, as well as colocalization with CD63, completely disappeared in the confluent state (Fig S3F and S3G). This correlated with nearly complete loss of CD63+/CD81+ sEV secretion by the confluent cells indicating that confluence abrogates intracellular FN trafficking as well as sEV secretion by VSMCs (Fig S3H). Finally, FN could be co-purified with sEVs from VSMC conditioned media (Fig S3I) and detected on the surface of sEVs by flow cytometry confirming its loading and secretion via sEVs (Fig 3C).

Results: page 10  Collagen VI was the most abundant protein in VSMC-derived sEVs (Fig 7B, Table S7) and  was previously implicated in the interaction with the proteoglycan NG2[53] and suppression of cell spreading on FN[54]. To confirm the presence of collagen VI in ECM-associated sEVs we analysed sEVs extracted from the 3D matrix using 0.5M NaCl treatment and showed that both collagen VI and FN are present (Fig 7D). Next, we analysed the distribution of collagen VI using dot-blot. Alix staining was bright only upon permeabilization of sEV indicating that it is preferentially a luminal protein (Fig 7E). On the contrary, CD63 staining was similar in both conditions showing that it is surface protein (Fig 7E). Interestingly, collagen VI staining revealed that 40% of the protein is located on the outside surface with 60% in the sEV lumen (Fig 7E). 

Discussion page 12. “In fact, we observed that an extensive secretion of sEVs effectively ceased protrusion activity; also VSMCs acquired a rounded morphology when “hovering” over the FN matrix decorated with sEVs (data not shown). Hence, it will be interesting in future studies to investigate whether sEVs can stimulate Rho activity by presenting adhesion modulators—particularly collagen VI—on their surface, thereby guiding cell directionality during invasion..”

Discussion, page 14 “In summary, cooperative activation of integrin signalling and F-actin cytoskeleton pathways results in the secretion of sEVs which associate with the ECM and play a signalling role by controling FA formation and cell-ECM crosstalk. Further studies are needed to test these mechanisms across various cell types and ECM matrices.     

Strengths

The authors provide a comprehensive battery of cytoskeletal experiments to test how fibronectin and sEVs impact both sEV release and vascular smooth muscle cell migratory activation.

We appreciate this comment reflecting our efforts to apply a range of orthogonal methods to show the role of the integrin/actin cytoskeleton in ECM-stimulated sEV secretion.

Weaknesses

Unfortunately, this article suffers from many weaknesses. First, the rigor of the experimental approach is low, which calls into question the merit of the conclusions. In this vein, there is a lack of proper controls or inclusion of experiments addressing alternative explanations for the phenotype or lack thereof.

We acknowledge this comment and agree that there was not sufficient evidence to conclude that sEV secretion occurs via filopodia despite the microscopy/inhibitory data so this claim has now been excluded from the study. However we believe that our experimental data does clearly show that FN stimulates the secretion of collagenVI-loaded sEVs which are trapped by the ECM and have the capacity to modulate VSMC adhesion and invasion directionality. To support this, we have now extended the dataset in the revised version:

(1) In addition to the use of inhibitors and live cell analysis we have added quantitative data confirming that a large proportion of CD63+ endosomes are associated with F-actin/cortactin tails and this colocalization is increased upon the inhibition of sEV secretion with 3-OMS (Fig  2D, Fig S2B).

(2) We developed a method to extract ECM-associated sEVs and quantified/characterized these using ExoView Assays further confirming significant sEV entrapment by the ECM (Figs 3B, S3A, S3B).    

(3) We extended the controls to confirm FN delivery to CD63+ endosomes and showed that FN recycling is stopped upon reaching cell confluence (Figs S3F, S3G and Fig S3H).

(4) We included more intensive characterisation of human atherosclerotic plaque morphology (H&E, Masson’s trichrome staining, Orcein, elastin fibers staining) to confirm predominant accumulation of sEV in the neointima (Figs S4A, S4B and S4C). We also excluded an endothelial origin for the  CD81+ sEVs (Fig 4G).

(5) We included individual cellular tracks to the 2D migration analysis to confirm the statistical significance and concluded that ECM-associated sEVs regulate cell invasion directionality but not the cell speed (Figs 5A and 5B).

(6) We showed surface localisation of collagen VI on sEVs confirming that it can activate signalling pathways leading to early FA formation on the FN matrix  (Figs 7D and 7E).

(7) We included alternative explanations for some of our data in the discussion.      

Reviewer #2 (Public Review):

Extracellular vesicles have recently gained significant attention across a wide variety of fields, and they have therefore been implicated in numerous physiological and pathophysiological processes. When such a discovery and an explosion of interest occur in science, there is often much excitement and hope for answers to mechanisms that have remained elusive and poorly understood. Unfortunately, there is an equal amount of hype and overstatement that may also be put forth in the name of "impact", but this temptation must be avoided so that scientists and the broader public are not misled by overreaching interpretations and statements that lack rigorous and fully convincing evidence.

Thank you for your comment and we agree that investigating sEVs is particularly challenging due to the their heterogeneity and nano-size, as well as complex biogenesis mechanisms. ECM-associated sEVs is a very new direction for the EV field but one that is particularly relevant to the vasculature where cells must invade through a thick ECM and where the accumulation of ECM-bound EVs is a unique and documented phenomenon.  To further strengthen out conclusions we have included new data to support our statements but also excluded statements re: filopodia as the origin of sEVs, that are out of scope of our study and need to be investigated further.

The study presented by Kapustin et al. is certainly intriguing and timely, and it offers an interesting working hypothesis for the fields of extracellular vesicles and vascular biology to consider. The authors do a reasonable job at detecting these small extracellular vesicles, though some aspects of data presentation are missing such as full Western blots with accompanying size markers for the viewer to more fully appreciate that data and comparisons being made (see Figures 1 and 7).

We agree with the reviewer and have now included molecular weight markers (Fig 1F, 7C, 7D, S3I, S4E) and provided all original western blot scans (uncropped and unedited) to the eLife editor. 

Much of the imaging data from cell-based experiments is strong and conducted with many cutting-edge tools and approaches. That said, the static images and the dynamic imaging fall short of being fully convincing that the small extracellular vesicles found in the neighboring extracellular matrix are indeed being deposited there via the smooth muscle cell filopodia. Many of the lines of evidence presented suggest that this could occur, but alternative hypotheses also exist that were not fully ruled out, such as the ECM-deposited vesicles were secreted more from the soma and/or the lamellipodia that are also emitted and retracted from the cells. In particular, the authors show very nice dynamic imaging (Supplementary Figure S2A and Supplemental Video S1) that is interpreted as "extracellular vesicles being released from the cell" and these are seen as "bursts" of fluorescent signal; however, none of these appear to occur in filopodia as they appear within the cell proper (a "burst" of signal vs. a more intense "streak" of signal), which would be a stronger and more consistent observation predicted by the working model proposed by the authors.

Our live and fixed cell microscope data as well as inhibitor analysis showed that sEV secretion can be associated with the filopodia. However we agree with the reviewer that the data generated using pHluoron GFP marker clearly indicate that the majority of sEVs are secreted from the cell soma toward the ECM:

To reflect this, we have added further changes:

(1) Title: Matrix-associated extracellular vesicles modulate smooth muscle cell adhesion and directionality by presenting collagen VI.

(2) Results, section title: 2. FN-induced sEV secretion is modulated by Arp2/3 and formin-dependent actin cytoskeleton remodelling

(3)  Results, page 6 Line 27-36 “Formins and the Arp2/3 complex play a crucial role in the formation of filopodia, a cellular protrusion required for sensing the extracellular environment and cell-ECM interactions36. To test whether MVBs can be delivered to filopodia, we stained VSMCs for Myosin-10 (Myo10)37. We observed no difference between total filopodia number per cell on plastic or FN matrices (n=18±8 and n=14±3, respectively) however the presence of endogenous CD63+ MVBs along the Myo10-positive filopodia were observed in both conditions (Fig 2E, arrows). Filopodia have been implicated in sEV capture and delivery to endocytosis “hot-spots”38, so next we examined the directionality of CD63+ MVB movement in filopodia by overexpressing Myo10-GFP and CD63-RFP in live VSMCs. Importantly, we observed anterograde MVB transport toward the filopodia tip (Fig 2F and Supplementary Video S2) indicative of MVB secretion”.

(4) Results, page 6, Ln 37-44 “We also attempted to visualise sEV release in filopodia using CD63-pHluorin where fluorescence is only observed upon the fusion of MVBs with the plasma membrane39. Using total internal reflection fluorescence microscopy (TIRF) we observed the typical “burst”-like appearance of sEV secretion at the cell-ECM interface in full agreement with an earlier report showing MVB recruitment to invadopodia-like structures in tumor cells18 (Fig S2B and Supplementary Video S1). Although we also observed an intense CD63-pHluorin staining along filopodia-like structures we were not able to detect typical “burst”-like events to confirm sEV secretion in filopodia. (Fig S2C and Supplemental Video S1)”.

(5) Results, page 7 Ln 3 “Interestingly, CD63+ MVBs can be observed in filopodia-like structures suggesting that sEV secretion can also occur spatially via cellular protrusion-like filopodia but more studies are needed to confirm this hypothesis.”

(6) Discussion, page 12, line 19. “Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells.”

Imaging of related human samples is certainly a strength of the paper, and the authors are commended for attempting to connect the findings from their cell culture experiments to an important clinical scenario. However, the marker selected for marking extracellular vesicles is CD81, which has been described as present on the endothelium of atherosclerotic plaques with a proposed role in the recruitment of monocytes into diseased arteries (Rohlena et al. Cardiovasc Res 2009). More data should address this potentially confounding interpretation of the signals presented in images within Figure 4.

We thank the reviewer for this insightful comment that the  sEV marker CD81 can originate from endothelial cells in agreement with Rohlena et al., 2009.   To address this we investigated the spatial overlap between CD81 and the endothelial marker, CD31. We observed very strong CD81 staining in the intact endothelial cell (intima) layer and occasional CD31 positive cells in the neointima. Importantly, quantification of colocalization confirmed that 80% of CD81 in the neointima does not overlap with CD31 excluding an endothelial origin of these sEVs. (Fig 4G).  Moreover, we included complete morphological characterisation of the atherosclerotic plaques confirming that CD81 sEVs were primarily observed in the neointima where VSMCs constitute the cellular majority (Fig S4A, S4B, S4C and S4D).

On a conceptual level, the idea that the small extracellular vesicles contain Type VI Collagen, and this element of their cargo is modulating smooth muscle cell migration, is an intriguing aspect of the authors' working model. Nevertheless, the evidence supporting this potential mechanism does not quite fit together as presented. It is not entirely clear how the collagen VI within the vesicles is somehow accessed by the smooth muscle cell filopodia during migration. Are the vesicles lysed open once on the extracellular matrix? If so, what is the proposed mechanism for that to occur? If not, how are the adhesion molecules on the smooth muscle cell surface engaging the collagen VI fibers that are contained within the vesicles? This aspect of the model does not quite fit together with the proposed mechanism and may be an interesting speculative interpretation, warranting further investigation, but it should not be considered a strong conclusion with sufficient convincing data supporting this idea.

We thank the reviewer for their insightful comments regarding the mechanism by which collagen VI associated with sEVs could modulate smooth muscle cell adhesion and migration. To clarify, our new data suggest that collagen VI is predominantly present on the surface of the sEVs, as evidenced by Fig 7E. This surface localization strongly implies that collagen VI can be directly accessed by cell surface adhesion receptors, without the need for vesicle lysis or opening. While we cannot entirely rule out all alternative mechanisms, we consider vesicle rupture or lysis within the extracellular matrix to be a highly unlikely route for collagen VI exposure, given the known stability of sEVs under physiological conditions. We have added these points to clarify:

(1) Results, page 10, Ln 45 “To confirm the presence of collagen VI in ECM-associated sEVs we analysed sEVs extracted from the 3D matrix using 0.5M NaCl treatment and showed that both collagen VI and FN are present (Fig 7D). Next, we analysed the distribution of collagen VI using dot-blot. Alix staining was bright only upon permeabilization of sEV indicating that it is preferentially a luminal protein (Fig 7E). On the contrary, CD63 staining was similar in both conditions showing that it is surface protein (Fig 7E). Interestingly, collagen VI staining revealed that 40% of the protein is located on the outside surface with 60% in the sEV lumen (Fig 7E).”

(2) Discussion, page 13, Ln 2 “Hence, it will be interesting in future studies to investigate whether sEVs can stimulate Rho activity by presenting adhesion modulators—particularly collagen VI—on their surface, thereby guiding cell directionality during invasion..”

(3) Discussion, page 14, Ln 30: In addition to collagen VI the unique adhesion cluster in VSMC-derived sEVS also includes EGF-like repeat and discoidin I-like domain-containing protein (EDIL3), transforming growth factor-beta-induced protein ig-h3 (TGFBI) and the lectin galactoside-binding soluble 3 binding protein (LGALS3BP) and these proteins are also directly implicated in activation of integrin signalling and cellular invasiveness85-87. Although we found that collagen VI plays the key role in sEV-induced early formation of FAs in VSMCs, it is tempting to speculate that the high sEV efficacy in stimulating FA formation is driven by cooperative action of this unique adhesion complex on the sEVs surface and targeting this novel sEV-dependent mechanism of VSMC invasion may open-up new therapeutic opportunities to modulate atherosclerotic plaque development or even to prevent undesired VSMC motility in restenosis.    .   

(4) Abstract Figure

On a technical level, some of the statistical analysis is not readily understood from the data presented. It is very much appreciated that the authors show many of the graphs with technical and biological replicate values in addition to the means and standard deviations (though this is not clearly stated in all figure legends). However, in figures such as Figure 5, there are bars shown and indicated to be different by statistical comparison (see panel B in Figure 5). It is not clear how the values for Group 1 (no FN, no 3-OMS, no sEV) are statistically different (denoted by three asterisks but no p value provided in the legend) than Group 3 (no FN, 3-OMS added, no sEV), when their means and standard deviations appear almost identical. If this is an oversight, this needs to be corrected. If this is truly the outcome, further explanation is warranted. A higher level of transparency in such instances would certainly go a long way in helping address the current crisis of mistrust within the scientific community and at the interface with society at-large.

We thank the reviewer for their careful reading and important comments on the statistical analysis. We acknowledge that the technical and biological replicate data were not clearly reported in all figure legends and that the statistical approach for Figures 5A and 5B required clarification. In response, we have made several changes for greater transparency and rigor:

First, we have now explicitly included the numbers of biological replicates (N) and technical replicates (n) in all relevant figure legends for Figures 1–7. In addition, the number of individual cell tracks is now annotated for the migration/invasion analyses, along with the mean values for each dataset.

Upon review, we found that the original statistical analyses for Figures 5A and 5B were conducted using pooled averaged data. To address this, we have repeated the statistical tests using pooled individual cell track data, applying the Kruskal–Wallis test with Dunn’s multiple comparison correction. This more stringent approach revealed revised p-values, which are now indicated in Figures 5A and 5B.

With these corrections, we reconfirm our major findings: In the 2D model, fibronectin (FN) coating promotes VSMC velocity, while inhibition of sEV secretion with 3-OMS leads to reduced cell speed (Fig. 5A). Addition of sEVs to the ECM had no effect on VSMC speed at baseline but did rescue cell speed and distance in the presence of 3-OMS, consistent with EVs acting primarily on invasion directionality rather than speed in both 2D and 3D models (Fig. 5A, 5D). Furthermore, sEVs continue to significantly impact VSMC invasion directionality (Figs. 5G, 5H), in agreement with previous reports in tumor cells (Sung et al., 2015).

In summary, we have implemented the following revisions:

(1) Figures 5A and 5B: Individual cell track data are now shown, and statistical analyses have been repeated using the Kruskal–Wallis test with Dunn’s multiple comparisons.

(2) Figure legends and results sections: Numbers of biological and technical replicates, as well as individual data points, are now clearly stated.

Results, page 9, line 14: The text has been updated to clarify the statistical approach and major findings as described above.

We hope that these changes address the reviewer’s concerns and improve the transparency and reproducibility of our data presentation

Reviewer #1 (Recommendations For The Authors):

We are very thankful for the comprehensive review and comments which helped to improve our data.

Figure 1.<br /> The authors clearly show that FN stimulation (immobilized or cell-derived) promotes sEV secretion via canonical integrin pathways. FN is a promigratory substrate, hence its extensive use as a cell adhesion aid; thus one could assume that simply plating on FN induces a pro-migratory phenotype (later data supports this notion). Does the addition of growth factors also increase sEV release? An endogenous function of FN is siloing of various GFs during clot formation. Also, FAK and SRC networks intersect with canonical RTK signaling in terms of promoting Rac1, CDC42 and other migration mediators. The reason I believe this is important is because the data could be interpreted in two ways: 1) FN induces pro-migration signaling and then sEVs are released, or visa versa, FN induces sEV release and migration is initiated. GF supplementation in the absence of FN would clarify this relationship.

We thank the reviewer for this insightful comment regarding the possible role of growth factors (GFs) and the mechanistic relationship between FN stimulation, sEV secretion, and cell migration. We agree that FN is a well-established promoter of cell migration, and it is important to distinguish whether FN directly induces a pro-migratory phenotype or does so via sEV-mediated signaling.

Our data show that FN stimulation markedly increases VSMC motility, as reflected by enhanced cell speed (Fig. 5A), an increased number of focal adhesions (Fig. 6E), and facilitated centripetal movement of FAs (Fig. 6F). Interestingly, ECM-associated sEVs appear to play a complementary but distinct role: they do not significantly affect cell migration speed (Fig. 5A) but instead guide cell invasion directionality (Figs. 5G, 5H), reduce the number of FAs per cell (Fig. 6E), and promote early peripheral FA formation (Fig. 6F). In light of these findings, we have updated our graphical abstract to reflect the unique cross-talk mediated by sEVs between VSMCs and the ECM.

Regarding the influence of growth factors, we acknowledge that FN can bind and present different GFs, which could also contribute to changes in sEV secretion. Although our inhibition studies and integrin-blocking antibody results support a primary role for β1 integrin activation and actin assembly in triggering sEV secretion, we cannot entirely exclude the possibility that FN-bound growth factors play a role in this process. We have now incorporated this point into the discussion to address the reviewer’s suggestion.

Discussion, page 14 , Ln 7 “Although our small inhibitors and integrin modulating antibody data clearly indicate that β1 activation triggers sEV secretion via activation of actin assembly we cannot fully rule out that FN may also be modulating growth factor activity which in turn contributes to sEV secretion by VSMCs²³.  Excessive collagen and elastin matrix breakdown in atheroma has been tightly linked to acute coronary events hence it will be interesting to study the possible link between sEV secretion and plaque stability as sEV-dependent invasion is also likely to influence the necessary ECM degradation induced by invading cells⁹⁶

Figure 2.<br /> • The authors provide no evidence (or references) that SMIFH2 or CK666 halts filopodia extensions.

Thank you for this important note. We have included the corresponding references:

Results, page 5: “So next we tested the contribution of Arp2/3 and formins by using the small molecule inhibitors, CK666 and SMIFH2, respectively31, 32”.  

• Is there an increase in filopodia density when plated on FN vs plastic? Similarly, if there are more filopodia present is that associated with more sEV? Please provide evidence in this regard.

We agree that connecting the number of filopodia with the secretion level of sEVs may be an important clue if sEV secretion can be driven by FN-induced filopodia formation. However, Myosin10 staining to quantify filopodia (Fig 2E) showed no difference between VSMCs plated on plastic versus FN matrix. Therefore, we agree with the reviewer that the filopodia contribution to sEV secretion needs to be investigated further.  This idea is reflected in the following comments:

(1) Results, page 6, Ln 29 “We observed no difference between total filopodia number per cell on plastic or FN matrices (n=18±8 and n=14±3, respectively) however the presence of endogenous CD63+ MVBs along the Myo10-positive filopodia were observed in both conditions (Fig 2E, arrows).

(2) Results, page 6, Ln 37 “We also attempted to visualise sEV release in filopodia using CD63-pHluorin where fluorescence is only observed upon the fusion of MVBs with the plasma membrane39. Using total internal reflection fluorescence microscopy (TIRF) we observed the typical “burst”-like appearance of sEV secretion at the cell-ECM interface in full agreement with an earlier report showing MVB recruitment to invadopodia-like structures in tumor cells18 (Fig S2B and Supplementary Video S1). Although we also observed an intense CD63-pHluorin staining along filopodia-like structures we were not able to detect typical “burst”-like events to confirm sEV secretion in filopodia. (Fig S2C and Supplemental Video S1)..”

(3) Discussion, page 12, Ln 15 : “Focal complexes either disassemble or mature into the elongated centripetally located FAs48. In turn, these mature FAs anchor the ECM to actin stress fibres and the traction force generated by actomyosin-mediated contractility pulls the FAs rearward and the cell body forward12, 13. Here we report that β1 integrin activation triggers sEV release followed by sEV entrapment by the ECM. Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells..”

As hinted above, this data could be interpreted in the light of generally inhibiting cell migration to blunt sEV shedding. Does cell confluence affect sEV release? If cells are cultured to 100% confluency this would limit filopodia formation regardless of ECM type. If sEV secretion remains elevated on FN in this culture condition it would suggest a lack of dependency on filopodia.

We thank the reviewer for this thoughtful suggestion regarding the influence of cell confluence on sEV release and filopodia formation. To directly address this hypothesis, we performed additional experiments comparing VSMCs cultured at low and high confluency. As described in the revised Results (page 7, line 39), we found that high cellular confluency reduced FN recycling, as indicated by the marked decrease in intracellular FN-positive spots and loss of colocalization with CD63 (Figs S3F, S3G). Importantly, this was accompanied by a significant reduction in CD63+/CD81+ sEV secretion by confluent cells (Fig S3H). These results suggest that VSMC confluence, which suppresses filopodia formation, nearly abolishes both intracellular FN trafficking and sEV secretion, even in the presence of FN. Thus, under our experimental conditions, sEV secretion by VSMCs appears to be closely linked to dynamic cell–matrix interactions and is dramatically reduced when these processes are limited by confluence:

(1) Results, page 7, Ln 39 : “Notably, when we compared FN distribution in sparsely growing VSMCs versus confluent cells we found that FN intracellular spots, as well as colocalization with CD63, completely disappeared in the confluent state (Fig S3F and S3G). This correlated with nearly complete loss of CD63+/CD81+ sEV secretion by the confluent cells indicating that confluence abrogates intracellular FN trafficking as well as sEV secretion by VSMCs (Fig S3H)..  

• Inhibition of branched actin polymerization has been shown to reduce both exocytic and endocytic activity. Thus, it is hard to interpret the results of Fig. 2B than anything more than a generalized effect of losing actin.

We thank the reviewer for this important point regarding the broad cellular functions of branched actin polymerization, and agree that generalized actin loss can influence both exocytic and endocytic pathways. To address this, we performed additional experiments and analyses to better define the relationship between branched actin structures and sEV-related processes in VSMCs.

As described in the revised Results (page 6), we overexpressed ARPC2-GFP (an Arp2/3 subunit) together with F-tractin-RFP in VSMCs and carried out live-cell imaging. This approach revealed that Arp2/3 and F-actin organize into lamellipodial scaffolds at the cell cortex, as expected (Fig. S2A; Supplementary Video S2). Additionally, and more unexpectedly, we observed numerous Arp2/3– and F-actin–positive dynamic spots within the VSMC cytoplasm. These structures resemble actin comet tails seen in other systems, previously implicated in endosomal propulsion (Fig. S2A, arrow; Supplementary Video S2).

Quantitative analysis confirmed that a substantial fraction of these dynamic F-actin/cortactin spots colocalized with CD63+ endosomes (Fig. 2D), and that these structures are indeed branched actin tails based on cortactin immunostaining. Furthermore, inhibition of SMPD3 (with 3-OMS) induced enlarged cortactin/F-actin/CD63+ complexes, morphologically similar to invadopodia (Fig. 2D, arrowheads), supporting a functional link between actin branching and MVB dynamics.

To quantify the association, we calculated Manders’ colocalization coefficients for F-actin tails and CD63+ endosomal structures in fixed VSMCs, observing that ~50% of F-actin tails were associated with ~13% of endosomes. Upon 3-OMS treatment, this overlap increased further (Fig. S2B).

Finally, using live-cell imaging (Fig 2C; Supplementary Video S4), we directly observed CD63+ MVBs being propelled through the cytoplasm by Arp2/3-driven actin tails, suggesting a mechanistic role for branched actin assembly in MVB intracellular transport, rather than a generalized effect of actin disruption alone.

We believe these combined data reinforce a more specific mechanistic role for Arp2/3-mediated branched actin in MVB/endosome transport and, consequently, in sEV secretion in VSMCs—over and above an indirect effect of global actin loss. We hope these additional experiments and quantitative analyses address the reviewer’s concern and clarify the functional relevance of branched actin structures to sEV trafficking:

(1) Results, page 6, Ln 3 “As regulators of branched actin assembly, the Arp2/3 complex and cortactin are thought to contribute to sEV secretion in tumour cells by mediating MVB intracellular transport and plasma membrane docking[28, 33]. Therefore, we overexpressed the Arp2/3 subunit, ARPC2-GFP and the F-actin marker, F-tractin-RFP in VSMCs and performed live-cell imaging. As expected, Arp2/3 and F-actin bundles formed a distinct lamellipodia scaffold in the cellular cortex (Fig S2A and Supplementary Video S2). Unexpectedly, we also observed numerous  Arp2/3/F-actin positive spots moving  through the VSMC cytoplasm that resembled previously described endosome actin tails observed in Xenopus eggs[33] and parasite infected cells where actin comet tails propel parasites via filopodia to neighbouring cells[34, 35] (Fig S2A, arrow, and Supplementary Video S2). Analysis of the intracellular distribution of Arp2/3 and CD63-positive endosomes in VSMCs showed CD63-MVB propulsion by the F-actin tail in live cells (Fig 2C and Supplementary Video S4).”

(2) Results, New data Fig 2D, page 6, Ln 14. “we observed numerous F-actin spots in fixed VSMCs that were positive both for F-actin and cortactin indicating that these are branched-actin tails (Fig 2D). Moreover, cortactin/F-actin spots colocalised with CD63+ endosomes and addition of the SMPD3 inhibitor, 3-OMS, induced the appearance of enlarged doughnut-like cortactin/F-actin/CD63 complexes resembling invadopodia-like structures similar to those observed in tumour cells (Fig 2D, arrowheads)[18].”

(3) Results, New data Fig S2B, page 6, Ln 19 “To quantify CD63 overlap with the actin tail-like structures, we extracted round-shaped actin structures and calculated the thresholded Manders colocalization coefficient (Fig S2B).  We observed overlap between F-actin tails and CD63 as well as close proximity of these markers in fixed VSMCs (Fig S2B). Approximately 50% of the F-actin tails were associated with 13% of all endosomes (tM1=0.44±0.23 and tM2= 0.13±0.06, respectively, N=3). Addition of 3-OMS enhanced this overlap further (tM1=0.75±0.18 and tM2=0.25±0.09) suggesting that Arp2/3-driven branched F-actin tails are involved in CD63+ MVB intracellular transport in VSMCs”

• In video 1 the author states (lines 8-9; pg6) "intense CD63 staining along filopodia" Although, there is some fluorescence (not strong) in these structures, there was no visible exocytic activity. This data is more suggestive that sEVs (marked by CD63) are not associated with filopodia. The following conclusion statement the authors make is overreaching given this result.

We thank the reviewer for this careful observation and agree that the previous conclusion regarding sEV release from filopodia was overstated. In response, we have revised both the Results and Discussion sections to more accurately reflect the data..

(1) Results, page 6, Ln37 “We also attempted to visualise sEV release in filopodia using CD63-pHluorin where fluorescence is only observed upon the fusion of MVBs with the plasma membrane39. Using total internal reflection fluorescence microscopy (TIRF) we observed the typical “burst”-like appearance of sEV secretion at the cell-ECM interface in full agreement with an earlier report showing MVB recruitment to invadopodia-like structures in tumor cells18 (Fig S2B and Supplementary Video S1). Although we also observed an intense CD63-pHluorin staining along filopodia-like structures we were not able to detect typical “burst”-like events to confirm sEV secretion in filopodia. (Fig S2C and Supplemental Video S1)..”

(2) Discussion, page 12, Ln19 “Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells.”. 

• Fig 2D and video 2 are wholly unconvincing with regard to sEV secretion sites. The authors could use their CD63-pHluroin construct to count exocytic events in the filopodia vs the whole cell. Given the movie, I have a suspicion this would not be significant. The authors could also perform staining CD63 in non-permeabilized cells to capture and count exocytic events at the plasma membrane as well as their location between groups.

We thank the reviewer for these constructive suggestions and their critical assessment of our current data regarding the sites of sEV secretion. We agree that our CD63-pHluorin approach clearly indicates sEV secretion events in the soma at the cell–ECM interface, while we did not observe comparable events in filopodia. Accordingly, we have clarified these points in the revised manuscript.

(1) Results, page 6, Ln37 “We also attempted to visualise sEV release in filopodia using CD63-pHluorin where fluorescence is only observed upon the fusion of MVBs with the plasma membrane39. Using total internal reflection fluorescence microscopy (TIRF) we observed the typical “burst”-like appearance of sEV secretion at the cell-ECM interface in full agreement with an earlier report showing MVB recruitment to invadopodia-like structures in tumor cells18 (Fig S2B and Supplementary Video S1). Although we also observed an intense CD63-pHluorin staining along filopodia-like structures we were not able to detect typical “burst”-like events to confirm sEV secretion in filopodia. (Fig S2C and Supplemental Video S1)..”

(2) Discussion, page 12, Ln19 “Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells.”. 

• Fig. 2E and video 4. Again, the conclusions drawn from this data are very strained. First, no co-localization quantification is presented on the proportion of CD63 vesicles with actin. Once again, the movie, if anything convinces the reader that 95-99% of all CD63 vesicles are not associated with actin; therefore, this is an unlikely mechanism of transport.

We thank the reviewer for this valuable comment and for highlighting the need for quantitative co-localization analysis. In response, we developed a method to systematically quantify F-actin and CD63 co-localization in fixed VSMCs, as now presented in new Figures 2D and S2B. We acknowledge that the majority of CD63+ endosomes are not associated with F-actin, consistent with the reviewer’s interpretation. However, our quantitative data now show that a specific subpopulation of MVBs appears to utilize this actin-based mechanism for transport. We believe this addresses the concern and more accurately reflects the prevalence and significance of the mechanism described.

(1) Results, page 6 , Ln 19. “To quantify CD63 overlap with the actin tail-like structures, we extracted round-shaped actin structures and calculated the thresholded Manders colocalization coefficient (Fig S2B).  We observed overlap between F-actin tails and CD63 as well as close proximity of these markers in fixed VSMCs (Fig S2B). Approximately 50% of the F-actin tails were associated with 13% of all endosomes (tM1=0.44±0.23 and tM2= 0.13±0.06, respectively, N=3). Addition of 3-OMS enhanced this overlap further (tM1=0.75+/-0.18 and tM2=0.25+/-0.09) suggesting that Arp2/3-driven branched F-actin tails are involved in CD63+ MVB intracellular transport in VSMCs.”

• Are there perturbations that increase filopodia numbers? A gain of function experiment would be valuable here.

We thank the reviewer for this important suggestion regarding the potential value of gain-of-function experiments to clarify filopodia’s contribution to sEV release. In agreement with the reviewer’s scepticism, we have removed statements linking filopodia to sEV release from both the title and abstract to avoid overinterpretation. At present, our understanding of filopodia biology and the lack of robust tools to selectively and substantially increase filopodia numbers in VSMCs prevent us from directly addressing this question through gain-of-function assays. We acknowledge that future studies using established methods—such as overexpression of filopodia-inducing proteins (e.g., mDia2 or fascin)—could provide insight into whether an increased number of filopodia affects sEV release. However, such experiments are beyond the scope of the current manuscript. We have made the following changes to clarify these points:

(1) Results, page 6, Ln37 “We also attempted to visualise sEV release in filopodia using CD63-pHluorin where fluorescence is only observed upon the fusion of MVBs with the plasma membrane39. Using total internal reflection fluorescence microscopy (TIRF) we observed the typical “burst”-like appearance of sEV secretion at the cell-ECM interface in full agreement with an earlier report showing MVB recruitment to invadopodia-like structures in tumor cells18 (Fig S2B and Supplementary Video S1). Although we also observed an intense CD63-pHluorin staining along filopodia-like structures we were not able to detect typical “burst”-like events to confirm sEV secretion in filopodia. (Fig S2C and Supplemental Video S1)..”

(2) Discussion, page 12, Ln19 “Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells.”. 

Figure 3<br /> • Fig 3A. The CD63 staining is strongly associated with the entire plasma membrane. How are the authors distinguishing between normal membrane shedding and bona fida sEVs based on this staining alone (?)- this is insufficient as all membrane structures are seemingly positive. Additionally, there are very few sEVs in scrutinizing the provided images. For the "sEV secretion, fold change" graphs in previous figures, could the authors provide absolute values, or an indication of what these values are in absolute terms?

We thank the reviewer for raising this important point regarding the specificity of CD63 staining and the need to distinguish bona fide sEVs from membrane fragments or general membrane shedding. We agree that CD63 staining alone at the plasma membrane or in the extracellular matrix is not sufficient to unequivocally identify sEVs. To address this, we employed several complementary approaches to rigorously characterize ECM-associated sEVs:

First, using high-resolution iSIM imaging, we confirmed the association of CD63-positive particles specifically with the FN-rich matrix, and demonstrated that SMPD3 knockdown significantly reduced the number of CD63+ particles in the matrix (Fig. 3B; revised from Fig. S3A).

Second, by incubating FN matrices with purified and fluorescently labeled sEVs, we directly observed efficient entrapment of these labeled sEVs within the matrices (Fig. 3E), confirming that sEVs can interact with and be retained by the ECM.

Third, we developed and applied a sequential extraction protocol using mild salt buffer (0.5M NaCl) and strong denaturant (4M guanidine HCl) to selectively extract ECM-associated sEVs based on the strength of their association (see new Figs. S3A and S3B). Extracted vesicles were then characterized by ExoView analysis, which demonstrated a tetraspanin profile (CD63+/CD81+/CD9+) closely matching that of sEVs from conditioned media, providing evidence that these particles are true sEVs and not merely membrane debris. We also found that the more weakly bound (NaCl-extracted) fraction closely resembles media-derived sEVs, while the strongly bound (GuHCl-extracted) fraction is more enriched in CD63+ and CD63+/CD81+ sEVs but contains very few CD9+ vesicles, further supporting distinct extracellular vesicle subpopulations within the ECM.

In addition, the abundance of CD63+/CD81+ sEVs in both media and ECM-derived fractions was independently validated by CD63 bead-capture assay (Fig. S3B).

We hope these clarifications and the expanded data set address the reviewer’s concerns about sEV identification and quantification in the extracellular matrix:

(1) Results, page 7, Ln 16. To quantify ECM-trapped sEVs we applied a modified protocol for the sequential extraction of extracellular proteins using salt buffer (0.5M NaCl) to release sEVs which are loosely-attached to ECM via ionic interactions, followed by 4M guanidine HCl buffer (GuHCl) treatment to solubilize strongly-bound sEVs (Fig S3A) 42. We quantified total sEV and characterised the sEV tetraspanin profile in conditioned media, and the 0.5M NaCl and GuHCl fractions using ExoView. The total particle count showed that EVs are both loosely bound and strongly trapped within the ECM. sEV tetraspanin profiling showed differences between these 3 EV populations.  While there was close similarity between the conditioned media and the 0.5M NaCl fraction with high abundance of CD63+/CD81+ sEVs as well as CD63+/CD81+/CD9+ in both fractions (Fig S3A). In contrast, the GuHCl fraction was particularly enriched with CD63+ and CD63+/CD81+ sEVs with very low abundance of CD9+ EVs (Fig S3A). The abundance of CD63+/CD81+ sEVs was confirmed independently by a CD63+ bead capture assay in the media and loosely bound fractions (Fig S3B).

• A control of fig 3b would be helpful to parse out random uptake of extracellular debris verses targeted sEV internalization. It would be helpful if the authors added particles of similar size to that of the sEVs to test whether these structures are endocytosed/micropinocytosed at similar levels.

We thank the reviewer for this useful suggestion regarding the need for better controls to distinguish specific sEV uptake from nonspecific internalization of extracellular debris or similarly sized particles. As a comparison, in our study we analyzed the uptake of both sEVs and serum proteins such as fibronectin and fetuin-A (Figs S3C and S3D), and observed similar patterns of intracellular trafficking. However, we acknowledge that inert nanoparticles or beads of a similar size to sEVs could serve as potential controls to assess nonspecific micropinocytosis or endocytosis.

It is important to note, however, that the uptake of sEVs is strongly influenced by their surface protein composition and the so-called “protein corona.” Recent work from Prof. Khuloud T. Al-Jamal’s group underscores that exosome uptake mechanisms may be highly specific (Liam-Or et al., 2024), and studies from Mattias Belting’s lab have also shown the importance of heparan sulfate proteoglycans in exosome endocytosis (Cerezo-Magana et al., 2021). As a result, uptake comparisons with inert particles or beads may not fully recapitulate the specificity of sEV internalization, and distinct nanoparticle classes may rely on different uptake pathways.

Figure 4<br /> • Fig. 4E,F,G. How are the authors determining the neointima and media compartments without ancillary staining for basement membrane or endothelial markers? Anatomic specific markers need to be incorporated here for the reader to evaluate the specificity of the FN and CD81 staining. It is also hard to understand the severity of the atherosclerotic lesion without a companion H&E cross section.

We thank the reviewer for highlighting the need for more rigorous characterization of atherosclerotic lesion architecture and anatomical compartments in our study. In response, we have incorporated additional histological analyses and now provide ancillary staining and companion images to enable clear identification of the neointima and medial compartments, as well as to assess lesion severity (see new Figs S4A–S4D):

(1)Results, page  8, Ln 28. . “To test if FN associates with sEV markers in atherosclerosis, we investigated the spatial association of FN with sEV markers using the sEV-specific marker CD81. Staining of atherosclerotic plaques with haematoxylin and eosin revealed well-defined regions with the neointima as well as tunica media layers formed by phenotypically transitioned or contractile VSMCs, respectively (Fig S4A). Masson's trichrome staining of atherosclerotic plaques showed abundant haemorrhages in the neointima, and sporadic haemorrhages in the tunica media (Fig S4B). Staining of atherosclerotic plaques with orcein indicated weak connective tissue staining in the atheroma with a confluent extracellular lipid core, and strong specific staining at the tunica media containing elastic fibres which correlated well with the intact elastin fibrils in the tunica media (Figs S4C and S4D). Using this clear morphological demarcation, we found that FN accumulated both in the neointima and the tunica media where it was significantly colocalised with the sEV marker, CD81 (Fig. 4D, 4E and 4F). Notably CD81 and FN colocalization was particularly prominent in cell-free, matrix-rich plaque regions (Figs. 4E and 4F).”

• Figs s4c, S4d- proper controls are not provided. Again, a non-FN internalization control as well as a 4oC cold block negative control is required to interpret this data.

We thank the reviewer for this valuable suggestion. To enhance the rigor of our internalization assays, we have now included several additional controls using alternative treatments, fluorophore combinations, and internalization conditions:

a) We performed FN-Alexa568 uptake assays, followed by immunostaining for CD63 with a distinct fluorophore (Alexa488), to confirm the colocalization of internalized FN with CD63+ endosomal compartments in VSMCs (new Fig. S3E).

b) We also stained VSMCs, cultured under normal growth conditions, with an anti-FN antibody to visualize intracellular serum-derived FN and again observed colocalization with CD63 (new Figs. S3F and S3G). Notably, in cells grown to confluence, we observed a complete loss of intracellular FN staining and FN/CD63 colocalization, suggesting that FN recycling is prominent in sparse, motile cells, but not in confluent populations.

These additional controls strengthen our conclusions regarding FN internalization pathways and the conditions under which FN trafficking to the endosomal system occurs:

(1) Results, page 7, Ln 31  We treated serum-deprived primary human aortic VSMCs with FN-Alexa568 and found that it was endocytosed and subsequently delivered to early and late endosomes together with fetuin A, another abundant serum protein that is a recycled sEV cargo and elevated in plaques (Figs S3C and S3D). CD63 visualisation with a different fluorophore (Alexa488) confirmed FN colocalization with CD63+ MVBs (Fig S3E). Next, we stained non-serum deprived VSMC cultured in normal growth media (RPMI supplemented with 20% FBS) with an anti-FN antibody and observed colocalization of CD63 and serum-derived FN.  Co-localisation was reduced likely due to competitive bulk protein uptake by non-deprived cells (Fig S3F). Notably, when we compared FN distribution in sparsely growing VSMCs versus confluent cells we found that FN intracellular spots, as well as colocalization with CD63, completely disappeared in the confluent state (Fig S3F and S3G)..

• Can the authors please provide live and fixed imaging of FN and CD63-mediate filopodial secretion to amply support their conclusions.

We have observed CD63 MVBs in both fixed (Fig 2E) and live VSMCs (Fig 2F) yet we agree that further studies are required to establish the contribution of filopodia to sEV secretion. Therefore, we have added the following changes:

(1) Results, page 6, Ln37 “We also attempted to visualise sEV release in filopodia using CD63-pHluorin where fluorescence is only observed upon the fusion of MVBs with the plasma membrane39. Using total internal reflection fluorescence microscopy (TIRF) we observed the typical “burst”-like appearance of sEV secretion at the cell-ECM interface in full agreement with an earlier report showing MVB recruitment to invadopodia-like structures in tumor cells18 (Fig S2B and Supplementary Video S1). Although we also observed an intense CD63-pHluorin staining along filopodia-like structures we were not able to detect typical “burst”-like events to confirm sEV secretion in filopodia. (Fig S2C and Supplemental Video S1)..”

(2) Discussion, page 12, Ln19 “Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells.”. 

Figure 5

• Fig. 5A,B. The authors claim that sEV supplementation enhances VSMC migration speed and distance. The provided graphs show only a marginal increase in speed with sEV addition (A) but, concerningly, there is a four-star significant difference between the FN condition compared with FN+sEV (B) while the means appear the same. How are these conditions statistically different? The statistics seem off for these comparisons.

We thank the reviewer for highlighting concerns regarding the statistical analysis in Figures 5A and 5B. In response, we have carefully re-examined our data and statistical approach to ensure accuracy and transparency.

First, we have now included all individual cell migration tracks in the data representation for these figures. The statistical tests were repeated using the Kruskal–Wallis test with Dunn’s multiple comparison correction across all groups. This more stringent analysis confirmed our key findings: fibronectin (FN) stimulates VSMC migration speed, while inhibition of sEV secretion (with 3-OMS) reduces cellular speed (Fig. 5A). Addition of exogenous ECM-associated sEVs modestly restored cell speed in the presence of 3-OMS, but had no effect on baseline migration speed in 2D or 3D models (Figs. 5A, 5D).

Regarding the four-star significance observed in the original Fig. 5B, the previous result reflected an analysis based on pooled group averages, which may have overstated marginal differences. The revised analysis, based on individual cell tracks, does not support a substantial difference between FN and FN+sEV groups. The revised p-values and comparisons are now provided directly on the figures and described in the figure legends. We also clearly report the numbers of biological replicates, technical replicates, and individual data points for every condition.

Further, the modest effect of ECM-associated sEVs on speed is consistent with our observation that sEVs influence invasion directionality rather than baseline migration velocity, in agreement with previous findings in tumor models (Sung et al., 2015).

The manuscript has been revised accordingly, with updates in:

(1) Figures 5A and 5B: Individual cell track data are now shown, and statistical analyses have been repeated using the Kruskal–Wallis test with Dunn’s multiple comparisons.

(2) Figure legends and results sections: Numbers of biological and technical replicates, as well as individual data points, are now clearly stated.

(3) Results, page 9, line 14:  “FN as a cargo in sEVs promotes FA formation in tumour cells and increases cell speed14, 15. As we found that FN is loaded into VSMC-derived sEVs we hypothesized that ECM-entrapped sEVs can enhance cell migration by increasing cell adhesion and FA formation in the context of a FN-rich ECM. Therefore, we tested the effect of sEV deposition onto the FN matrix on VSMC migration in 2D and 3D models. We found that FN coating promoted VSMC velocity and inhibition of bulk sEV secretion with 3-OMS reduced VSMC speed in a 2D single-cell migration model (Figs. 5A, 5B) in agreement with previous studies using tumour cells14, 15. However, addition of sEVs to the ECM had no effect on VSMC speed at baseline but rescued cell speed and distance in the presence of the sEV secretion inhibitor, 3-OMS suggesting the EVs are not primarily regulating cell speed (Figs 5A and 5B).”

(4) Results, page 9, Ln 29 “Hence, ECM-associated sEVs have modest influence on VSMC speed but influence VSMC invasion directionality.”.

We hope that these changes address the reviewer’s concerns and improve the transparency and reproducibility of our data presentation

• Fig d-h. Generally, the magnitude of the difference between the presented conditions are biologically insignificant. Several of the graphs show a four-star difference with means that appear equivalent with overlapping error bars. Do the authors conclude that a 0.1%, or less, effect between groups is biologically meaningful?

We thank the reviewer for drawing attention to the apparent mismatch between statistical significance and biological relevance in Figures 5d–h. In response, we have reanalyzed the data using individual cell tracks and more stringent non-parametric statistical tests, as described above. This reanalysis confirmed that the magnitude of differences in migration speed and related parameters between the groups is minimal and not biologically meaningful. Thus, we no longer claim that sEVs significantly affect VSMC migration speed under these conditions in either 2D or 3D assays. Our revised manuscript now accurately reflects this finding in both the Results and Discussion sections, and the updated figures and legends clarify the true extent of any differences observed.

Figure 6

• Generally, the author's logic for looking into adhesion, focal adhesion and traction forces is hard to follow. If there are sEV-mediated migration differences, then there would inexorably be focal adhesion alterations. However, the data indicates few differences brought on by sEVs, which speaks to the lack of migration differences presented in Fig. 5. Overall, the sEV migration phenotype has so little of an effect, to then search for a mechanism seems destine to not turn up anything significant.

We thank the reviewer for highlighting the importance of connecting the observed phenotypic effects of sEVs to the investigation of adhesion and focal adhesion mechanisms. While our revised analysis confirms that sEVs have little to no effect on VSMC migration speed or distance in 2D and 3D models, we did observe a robust effect of sEVs on the directionality of cell invasion (Figs. 5G and 5H). This prompted us to look more closely at pathways involved in cell guidance rather than bulk cell motility.

Our proteomic comparison between larger EVs (10K fraction) and sEVs (100K fraction) revealed a unique adhesion complex present specifically on the sEVs—comprising collagen VI, TGFBI, LGALS3BP, and EDIL3 (Figs. 7A–C)—each of which has previously been implicated in integrin signaling, cell adhesion, or invasion. Functional blocking and knockdown studies further identified collagen VI as a key mediator in the regulation of cell adhesion and invasion directionality influenced by sEVs (Figs. 7F and 7I).

In response to this mechanistic insight, we have modified the graphical abstract and discussion to clarify our approach:

We now explicitly state that our focus has shifted from analyzing baseline migration speed to mechanisms guiding invasion directionality, in line with our key phenotypic findings.We highlight that the unique adhesion cluster identified on sEVs—including collagen VI and its cooperative partners—provides a strong mechanistic rationale for examining focal adhesion dynamics and ECM interactions, even in the absence of changes in migration velocity.Discussion excerpts (pages 13–14) have been updated to reflect this rationale and to summarize the potential significance of these findings for vascular biology and disease.

We hope this clarifies the logic underlying our approach and justifies the mechanistic studies performed in this context:

(1) Discussion, page 13, Ln 2  “Hence, it will be interesting in future studies to investigate whether sEVs can stimulate Rho activity by presenting adhesion modulators—particularly collagen VI—on their surface, thereby guiding cell directionality during invasion.”

(2) Discussion, page 13, Ln 30  “In addition to collagen VI the unique adhesion cluster in VSMC-derived sEVS also includes EGF-like repeat and discoidin I-like domain-containing protein (EDIL3), transforming growth factor-beta-induced protein ig-h3 (TGFBI) and the lectin galactoside-binding soluble 3 binding protein (LGALS3BP) and these proteins are also directly implicated in activation of integrin signalling and cellular invasiveness85-87. Although we found that collagen VI plays the key role in sEV-induced early formation of FAs in VSMCs, it is tempting to speculate that the high sEV efficacy in stimulating FA formation is driven by cooperative action of this unique adhesion complex on the sEVs surface and targeting this novel sEV-dependent mechanism of VSMC invasion may open-up new therapeutic opportunities to modulate atherosclerotic plaque development or even to prevent undesired VSMC motility in restenosis”.    . 

(3) Discussion, page 14, Ln 14 “In summary, cooperative activation of integrin signalling and F-actin cytoskeleton pathways results in the secretion of sEVs which associate with the ECM and play a signalling role by controlling FA formation and cell-ECM crosstalk. Further studies are needed to test these mechanisms across various cell types and ECM matrices.     ”.    

Figure 7<br /> • The authors need to provide additional evidence Col IV is harbored in sEVs and not a contaminant of sEV isolation as VSMCs secrete a copious amount of this in culture. For instance, IHC of isolated sEVs stained for CD63 and Col IV as well as single cell staining of the same sort.

We thank the reviewer for this important comment regarding the specificity of collagen VI detection in sEVs. To ensure that collagen VI is associated with bona fide sEVs—rather than being a contaminant resulting from high extracellular abundance—we performed a comparative analysis of vesicles isolated from the same conditioned media. Both proteomic mass spectrometry and western blotting revealed that collagen VI was exclusively present in the small EV (100K pellet) fraction and not in the larger EVs (10K pellet), as shown in Figs. 7B and 7C. Collagen VI was further identified in sEVs extracted from the ECM using our salt/guanidine protocol (new Fig. 7D).

Reviewer #2 (Recommendations For The Authors):

The authors have presented a nice collection of data with strong approaches to address their hypotheses. Nevertheless, an additional section within the Discussion would be welcome in addressing the potential limitations and important caveats to be considered alongside their study. These caveats and limitations could be reshaped by additional data supporting the ideas that: (1) small extracellular vesicles can be directly observed during their secretion from filopodia, (2) CD81 labeling in tissue can be interpreted clearly as extracellular vesicles and not the cell surface of other cell types (co-staining with an endothelial cell marker such as PECAM-1 perhaps), and (3) collagen VI within the vesicles is somehow accessed by adhesion molecules on the cell surface of migrating cells.

We thank the reviewer for these important suggestions and we have now added further studies and modified our conclusions to reflect the data more accurately:

(1) Results. Page 6, Ln37  “We also attempted to visualise sEV release in filopodia using CD63-pHluorin where fluorescence is only observed upon the fusion of MVBs with the plasma membrane39. Using total internal reflection fluorescence microscopy (TIRF) we observed the typical “burst”-like appearance of sEV secretion at the cell-ECM interface in full agreement with an earlier report showing MVB recruitment to invadopodia-like structures in tumor cells18 (Fig S2B and Supplementary Video S1). Although we also observed an intense CD63-pHluorin staining along filopodia-like structures we were not able to detect typical “burst”-like events to confirm sEV secretion in filopodia. (Fig S2C and Supplemental Video S1)”..  

(2) Discussion, page 12, Ln18: “Here we report that β1 integrin activation triggers sEV release followed by sEV entrapment by the ECM. Curiously we observed CD63+ MVB transport toward the filopodia tips as well as inhibition of sEV-secretion with filopodia formation inhibitors suggesting that sEV secretion can be directly linked to filopodia but further studies are needed to define the contribution of this pathway to the overall sEV secretion by cells”..

We quantified the colocalization of CD81 and CD31 to exclude the endothelial cell origin of sEVs and extended the characterisation of the atherosclerotic matrix as well as highlighting any limitations to interpretation ie re  CD81 ECM localisation: 

(1) Results, page 8, Ln 43 “An enhanced expression of CD81 by endothelial cells in early atheroma has been previously reported so to study the contribution of CD81+ sEVs derived from endothelial cells  we investigated the localisation of CD31 and CD8145. In agreement with a previous study, we found that the majority of CD31 colocalises with CD81 (Thresholded Mander's split colocalization coefficient 0.54±0.11, N=6) indicating that endothelial cells express CD81 (Fig 4G)45. However, only a minor fraction of total CD81 colocalised with CD31 (Thresholded Mander's split colocalization coefficient 0.24±0.06, N=6) confirming that the majority of CD81 in the neointima is originating from the most abundant VSMCs.. 

(2) Results, page 8, Ln 28: “To test if FN associates with sEV markers in atherosclerosis, we investigated the spatial association of FN with sEV markers using the sEV-specific marker CD81. Staining of atherosclerotic plaques with haematoxylin and eosin revealed well-defined regions with the neointima as well as tunica media layers formed by phenotypically transitioned or contractile VSMCs, respectively (Fig S4A). Masson's trichrome staining of atherosclerotic plaques showed abundant haemorrhages in the neointima, and sporadic haemorrhages in the tunica media (Fig S4B). Staining of atherosclerotic plaques with orcein indicated weak connective tissue staining in the atheroma with a confluent extracellular lipid core, and strong specific staining at the tunica media containing elastic fibres which correlated well with the intact elastin fibrils in the tunica media (Figs S4C and S4D). Using this clear morphological demarcation, we found that FN accumulated both in the neointima and the tunica media where it was significantly colocalised with the sEV marker, CD81 (Fig. 4D, 4E and 4F). Notably CD81 and FN colocalization was particularly prominent in cell-free, matrix-rich plaque regions (Figs. 4E and 4F). .”

We showed that collagen VI is presented on the surface of sEVs:

(1) Results, page 10, Ln43: “Collagen VI was the most abundant protein in VSMC-derived sEVs (Fig 7B, Table S7) and  was previously implicated in the interaction with the proteoglycan NG253 and suppression of cell spreading on FN54. To confirm the presence of collagen VI in ECM-associated sEVs we analysed sEVs extracted from the 3D matrix using 0.5M NaCl treatment and showed that both collagen VI and FN are present (Fig 7D). Next, we analysed the distribution of collagen VI using dot-blot. Alix staining was bright only upon permeabilization of sEV indicating that it is preferentially a luminal protein (Fig 7E). On the contrary, CD63 staining was similar in both conditions showing that it is surface protein (Fig 7E). Interestingly, collagen VI staining revealed that 40% of the protein is located on the outside surface with 60% in the sEV lumen (Fig 7E)

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Concerning! He's bought the brand washing attempts of big corps... am I being, rash? Is there no way out for Microsoft? Yes there is: One that doesn't include buying Activision despite being rotten? Profiting from endless games like CoD and Candy Crush? One that doesn't invest in data centers for AI that crush the global South? One that doesn't invest heavily in AAA titles like Halo, including its marketing, only to make a fraction of the investment sponsoring indies (and then laying them off)?

Then, no. I am not being rash. Microsoft owns a greedy ecosystem that includes Word and Excel. It asks people to pay for Windows licenses at 200€. Tried to do a Netflix with Xbox Game Pass. A big problem is that almost everyone knows Microsoft. Who knows Annapurna?

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"... before first using the device"

DOI: 10.1158/2767-9764.CRC-25-0171

Resource: The Cancer Genome Atlas (RRID:SCR_003193)

Curator: @scibot

SciCrunch record: RRID:SCR_003193

What is this?

DOI: 10.1007/s12672-025-03497-w

Resource: The Immunology Database and Analysis Portal (ImmPort) (RRID:SCR_012804)

Curator: @scibot

SciCrunch record: RRID:SCR_012804

What is this?

eLife Assessment

Decron and colleagues combine common psychiatric treatments with a probabilistic reward learning task and trial-by-trial ratings of affect, confidence, and engagement. Using computational cognitive modeling, they show that, while both treatments serve to counter negative biases in affect and confidence, cognitive distancing and antidepressant medication have dissociable effects on subjective evaluations and reward-based choice behavior. This work provides convincing evidence regarding an important line of investigation into the dynamic integration of affect, cognition, and learning.

Reviewer #1 (Public review):

Summary:

This study examines how two common psychiatric treatments, antidepressant medication and cognitive distancing, influence baseline levels and moment-to-moment changes in happiness, confidence, and engagement during a reinforcement learning task. Combining a probabilistic selection task, trial-by-trial affect ratings, psychiatric questionnaires, and computational modeling, the authors demonstrate that each treatment has distinct effects on affective dynamics. Notably, the results highlight the key role of affective biases in how people with mental health conditions experience and update their feelings over time, and suggest that interventions like cognitive distancing and antidepressant medication may work, at least in part, by shifting these biases.

Strengths:

(1) Addresses an important question: how common psychiatric treatments impact affective biases, with potential translational relevance for understanding and improving mental health interventions.

(2) The introduction is strong, clear, and accessible, making the study approachable for readers less familiar with the underlying literature.

(3) Utilizes a large sample that is broadly representative of the UK population in terms of age and psychiatric symptom history, enhancing generalizability.

(4) Employs a theory-driven computational modeling framework that links learning processes with subjective emotional experiences.

(5) Uses cross-validation to support the robustness and generalizability of model comparisons and findings.

Weaknesses:

The authors acknowledge the limitations in the discussion section.

Additional questions:

(1) Group Balance & Screening for Medication Use: How many participants in the cognitive distancing and control groups were taking antidepressant medication? Why wasn't medication use included as part of the screening to ensure both groups had a similar number of participants taking medication?

(2) Assessment of the Practice of Cognitive Distancing: Is there a direct or more objective method to evaluate whether participants actively engaged in cognitive distancing during the task, and to what extent? Currently, the study infers engagement indirectly through the outcomes, but does not include explicit measures of participants' use of the technique. Would including self-report check-ins throughout the task, asking participants whether they were actively engaging in cognitive distancing, have been useful? However, including frequent self-report check-ins would increase procedural differences between groups, making perhaps the tasks less comparable beyond the intended treatment manipulation. Maybe incorporating a question at the end of the task, asking how much they engaged in cognitive distancing, could offer a useful measure of subjective engagement without overly disrupting the task flow.

Conclusion:

This study advances our understanding of the mechanisms underlying mental health interventions. The combination of computational modeling with behavioral and affective data offers a powerful framework for understanding how treatments influence affective biases and dynamics. These findings are of broad interest across clinical and mental health sciences, cognitive and affective research, and applied translational fields focused on improving psychological well-being.

Reviewer #2 (Public review):

In this paper, Dercon and colleagues report on affective changes related to components of reinforcement learning and on the effects of brief training in psychological distancing and participants' self-reported antidepressant use. About 1,000 participants were assessed online, with half randomized to a brief training in psychological distancing with reminders to distance during the subsequent reinforcement learning (RL) task. Participants completed a battery of psychiatric questionnaires and answered questions about medication use, with about 14% of participants reporting current antidepressant use. All participants completed the RL task and rated their happiness, confidence, engagement, and (at the end of each block of trials) fatigue throughout the task. Computational models were used to estimate trial-by-trial values of expected value and prediction error and to assess the effects of these values on self-reported affect. Participants' affect ratings decreased over time, and participants with higher psychiatric symptoms (particularly anxiety/depressive symptoms) showed lower baseline affect and greater decreases in affect. Participants randomized to the distancing intervention and who reported antidepressant use differed in their affective ratings: distancing reduced the reductions in happiness over time, while antidepressant use was related to higher baseline happiness. Distancing also reduced the effects of trial-level expected value on happiness, while antidepressant use was related to a more enduring effect of trial-level values on happiness.

Overall, this is an interesting paper with strong methods and an interesting approach. That psychiatric symptoms and cognitive distancing are related to affective ratings is not terribly novel; the relationship with antidepressant use is a bit more novel. The extension of the mood model to an RL task is a new contribution, as is the relationship of these effects with psychologically related manipulations.

One major concern is the inference that can be drawn from the two "treatments": one is a brief instruction in a component of psychotherapy, and one is ongoing use of medication. The former is not a treatment in and of itself, but a (presumably) active ingredient of one. How to interpret antidepressant use as measured is unclear, e.g., are the residual symptoms in these participants an early indicator of treatment resistance? Are these participants with better access to health care? Are they receiving antidepressants for a mental health issue?

There are some clarifications needed in the affect model as well.

Reviewer #3 (Public review):

Summary:

The present manuscript investigates and proposes different mechanisms for the effects of two therapeutic approaches - cognitive distancing technique and use of antidepressants - on subjective ratings of happiness, confidence, and task engagement, and on the influence of such subjective experiences on choice behavior. Both approaches were found to link to changes in affective state dynamics in a choice task, specifically reduced drift (cognitive distancing) and increased baseline (antidepressant use). Results also suggest that cognitive distancing may reduce the weighing of recent expected values in the happiness model, while antidepressant use may reduce forgetting of choices and outcomes.

Strengths:

This is a timely topic and a significant contribution to ongoing efforts to improve our mechanistic understanding of psychopathology and devise effective novel interventions. The relevance of the manuscript's central question is clear, and the links to previous literature and the broader field of computational psychiatry are well established. The modelling approaches are thoughtful and rigorously tested, with appropriate model checks and persuasive evidence that modelling complements the theoretical argument and empirical findings.

Weaknesses:

Some vagueness and lack of clarity in theoretical mechanisms and interpretation of results leave outstanding questions regarding (a) the specific links drawn between affective biases, therapies aimed at mitigating them, and mental health function, and (b) the structure and assumptions of the modelling, and how they support the manuscript's central claims. Broadly, I do not fully understand the distinction between how choice behavior vs. affect are impacted separately or together by cognitive distancing. Clarification on this point is needed, possibly through a more explicit proposal of a mechanism (or several alternative mechanisms?) in the introduction and more explicit interpretation of the modelling results in the context of the cyclical choice-affect mechanism.

(1) Theoretical framework and proposed mechanisms

The link between affective biases and negative thinking patterns is a bit unclear. The authors seem to make a causal claim that "affective biases are precipitated and maintained by negative thinking patterns", but it is unclear what precisely these negative patterns are; earlier in the same paragraph, they state that affective biases "cause low mood" and possibly shift choices toward those that maintain low mood. So the directionality of the mechanism here is unclear - possibly explaining a bit more of the cyclic nature of this mechanism, and maybe clarifying what "negative thinking patterns" refer to will be helpful.

More generally, this link between affect and choices, especially given the modelling results later on, should be clarified further. What is the mechanism by which these two impact each other? How do the models of choice and affect ratings in the RL task test this mechanism? I'm not quite sure the paper answers these questions clearly right now.

The authors also seem to implicitly make the claim that symptoms of mental ill-health are at least in part related to choice behavior. I find this a persuasive claim generally; however, it is understated and undersupported in the introduction, to the point where a reader may need to rely on significant prior knowledge to understand why mitigating the impact of affective biases on choice behavior would make sense as the target of therapeutic interventions. This is a core tenet of the paper, and it would be beneficial to clarify this earlier on.

It would be helpful to interpret a bit more clearly the findings from 3.4. on decreased drift in all three subjective assessments in the cognitive distancing group. What is the proposed mechanism for this? The discussion mentions that "attenuated declines [...] over time, [add] to our previously reported findings that this psychotherapeutic technique alters aspects of reward learning" - but this is vague and I do not understand, if an explanation for how this happens is offered, what that explanation is. Given the strong correlation of the drift with fatigue, is the explanation that cognitive distancing mitigates affect drift under fatigue? Or is this merely reporting the result without an interpretation around potential mechanisms?

(Relatedly, aside from possibly explaining the drift parameter, do the fatigue ratings link with choice behavior in any way? Is it possible that the cognitive distancing was helping participants improve choices under fatigue?)

(2) Task Structure and Modelling

It is unclear what counted as a "rewarding" vs. "unrewarding" trial in the model. From my understanding of the task description, participants obtained positive or no reward (no losses), and verbal feedback, Correct/Incorrect. But given the probabilistic nature of the task, it follows that even some correct choices likely had unrewarding results. Was the verbal feedback still "Correct" in those cases, but with no points shown? I did not see any discussion on whether it is the #points earned or the verbal feedback that is considered a reward in the model. I am assuming the former, but based on previous literature, likely both play a role; so it would be interesting - and possibly necessary to strengthen the paper's argument - to see a model that assigns value to positive/negative feedback and earned points separately.

From a theory perspective, it's interesting that the authors chose to assume separate learning rates for rewarding and non-rewarding trials. Why not, for example, separate reward sensitivity parameters? E.g., rather than a scaling parameter on the PE, a parameter modifying the r term inside the PE equation to, perhaps, assign different values to positive and zero points? (While I think overall the math works out similarly at the fitting time, this type of model should be less flexible on scaling the expected value and more flexible on scaling the actual #points / the subjective experience of the obtained verbal feedback, which seems more in line with the theoretical argument made in the introduction). The introduction explicitly states that negative biases "may cause low mood by making outcomes appear less rewarding" - which in modelling equations seems more likely to translate to different reward-perception biases, and not different learning rates. Alternatively, one might incorporate a perseveration parameter (e.g., similar to Collins et al. 2014) that would also accomplish a negative bias. Either of these two mechanisms seems perhaps worth testing out in a model - especially in a model that defines more clearly what rewarding vs. unrewarding may mean to the participant.

If I understand correctly, the affect ratings models assume that the Q-value and the PE independently impact rating (so they have different weights, w2 and w3), but there is no parameter allowing for different impact for perceived rewarding and unrewarding outcomes? (I may be misreading equations 4-5, but if not, Q-value and PE impact the model via static rather than dynamic parameters.) Given the joint RL-affect fit, this seems to carry the assumption that any perceptual processing differences leading to different subjective perceptions of reward associated with each outcome only impact choice behavior, but not affect? (whereas affect is more broadly impacted, if I'm understanding this correctly, just by the magnitude of the values and PEs?) This is an interesting assumption, and the authors seem to have tested it a bit more in the Supplementary material, as shown in Figure S4. I'm wondering why this was excluded from the main text - it seems like the more flexible model found some potentially interesting differences which may be worth including, especially as they might shed additional insight into the influence of cognitive distancing on the cyclical choice-affect mechanisms proposed.

Minor comments:

If fatigue ratings were strongly associated with drift in the best-fitting model (as per page 13), I wonder if it would make sense to use those fatigue ratings as a proxy rather than allow the parameter to vary freely? (This does not in any way detract from the winning model's explanatory power, but if a parameter seems to be strongly explained by a variable we have empirical data for, it's not clear what extra benefit is earned by having that parameter in the model).

♖🌌💬/🌐/🎭/gyuri/♒

peer-to-peer writing

If only we could have that in an atuonomous setting that would be the right counterballance

Gives a good target date

Are you really prepared to accept these terms?

Learners who regularly tell stories become aware of how an audience affects a telling, and they carry that awareness into their writing.

The ways of other cultures, both ancient and living, acquire honor in story.

I find this very interesting for the reason being is when you tell a story you tell it with pride and with and confidence and the truth.

I wouldn’t completely agree with this unless the story teller is reliable by having actual evidence.

Is this done through observation of the child or teen?

I agree with this quotation because listening and telling a story allows rhetorical appeals to work better than reading and writing. This allows us to have a better visual and understanding of the story.

I agree with this because we know the history of the world through story telling. Humans have used it for thousands of years. One example is Ancient Egypt.

They view the Native Americans as heathens and they are at war with them currently. I interpret this to mean that even though Native American tribes practiced religion they did not recognize their religions and therefore called them heathens (someone who doesn't practice religion). This adds context to the territory source on colonies and how the puritans tried to make the Native Americans convert to their religion because they believed it was the only right religion. This provides early context for colonists making Native Americans convert to Christianity and making their languages and religions illegal.

They want to receive praise from God for offering a day of peace where pilgrims and natives can feast together. I interpret this to mean that they view God as kind and forgiven and therefore think he will favor them if they behave similarly even though they view them as heathens. This helps me understand how they interacted with the Native Americans and how they thought about God at the time and what interpretations they used. This provides changes over time with what we know celebrate Thanksgiving as and how it originally started.

Q: What does Oates mean by "the theater itself has no memory"? That new plays erase the presence of old ones which makes theater fleeting and forgettable? And if that's the case then why isn't prose fiction so much superior? As prose fiction conveys messages that stay with the reader and change their everyday lives.

I really appreciate this perspective. I have never thought of poetry as very straightforward and have in fact been frustrated with the vague and ambiguous nature of poetry, but this argument about poetry being a heightened form of communication is really resonating with me.

She tried to clean away what was wrong but it only revealed more flaws. I interpret to mean that she tried to ignore what was wrong but when she moved on from it more problems continued to arise. I'm not sure this line has a historical context since it's most likely about another person but it is a good line of poetry. I am using context to determine this is not directly related to another historical event due to the personal implications of it.

She is saying he is unfit for being seen in the light. I interpret this as having a religious context since stepping into the light usually means finding faith and going to the light is in reference to heaven. The tertiary source on colonies talked about how puritans and Catholics didn't get along so this could be because of a religious difference between the people. The context of what was happening with puritans in New England helped me better understand what she could be talking about in this poem

a very important note on persuasive speeches and essays, you cannot fall into logical fallacies. They confuse the listeners and discount your purpose.

Many times these can vary based on the physiological aspects of the human body as well. Hormones, comfortability, sleep patterns, etc. If I haven't gotten much sleep, as many college students do. Scheduling a speech early in the morning at a college may result in a small turnout based on the college student body. Scheduling it in the afternoon may benefit more, eg, knowing your audience

Audience analysis is all about understanding who you’re talking to so your message hits home. The general purpose of a speech is basically why you’re giving it—whether it’s to inform, persuade, or entertain. To narrow down your topic, you can zoom in on a smaller piece or find a unique angle that fits your listeners. Your specific purpose statement is what you want your audience to learn or do by the end. And your thesis is just a quick summary of the main point you want to get across.

All four of these domains are extremely important when creating any type of media. You want them to be correct, have meaning, depth, and understanding. If you just post things to get attention without knowing the intent behind a message what good does that do for you or society. It loses value.

When Indigenous media art is produced by "Western" practitioners I feel that it just loses genuine essence of artwork. Its just fabricated because they enjoy the design or they think its sooooo pretty. Which yes they are but because it is Indigenous art it shifts the narrative in a sense that every single sign, symbol, color , and shape, chosen and created has deep rooting meaning to them. It isn't the same.

It's striking to me that authors with such an ambitious proposal (culturally responsive teaching across the curriculum with massive character development in teachers) would land on such a familiar and safe intervention (PDs and interventions in teaching practices). We're talking about structural oppression - why are interventions focused on teachers instead of structures?

Thank goodness we are acknowledging the vast amount of work the kind of teaching described here would require. Thinking about implementing this in a district that served, say, two main linguistic communities would be daunting. My district serves 7-10 wholly unique cultural and linguistic communities in a city that encourages the development of semi-isolated cultural enclaves under the banner of multiculturalism. I can't imagine implementing this without significant structural changes at the district level, and maybe even at the city level? Again, I am struck by questions about the environmental prerequisites for culturally responsive teaching.

takes away from those who went through the process, as well as educational environments with integrity

what is the point of paying for higher education if it is "not relevant" to your life?

How is it that he got away with using AI for the vast majority of his assignments if he only put in "20%" of his own voice?

let's remove this

Should be $1. Let me confirm in the thread.

Not needed

Le guin contrasts the importance of the “ source” or “ tool to carry water” as bottle of gin or wine, a container alcohol. I wonder if that’s because of the standard and the fact alcohol, was in a sense a status since it was sought after in society historically.

claims of the need of recognition of some extent, quickly follows up with how the reasoning dwindles by following up with a contrast of potato, which was a common house hold item and food supply.

She criticizes the idea that storytelling must always be warlike with winners and losers.

Fiction shows that humanity has a place in the bigger picture, not as the main focus but as a piece of it.

The "wimps and klutzes" are the real people rather than the heroes that are common in many stories, unrealistic and not relatable. The little pebbles are interesting to include; what could be meant by the tiny grains? Small actions or maybe personality traits?

elaborate I guess general research topics are more fundamental and tend to have longer lifespan?

elaborate

elaborate

this is what happen to the PS project?

why these scale with frontier?

Words aren't just labels they shape feeling and behaviors A quote I liked from the passage "Language is not just how we express thoughts - it creates the grooves we think in" - William Haviland

• Language influences and determines our thoughts
• culture also shapes our language

Newspeak- a way to strip down language and limit it for example- if no one knew what rebellion meant then they how could you understand a actual rebellion happeneing

I like that behavior therapy focuses on why behaviors happen, not just the behaviors themselves. Changing what reinforces a behavior makes sense for real change. The teamwork in setting clear goals feels important, especially when clients start with vague ideas. I’m curious how therapists help make those goals more concrete.

I think AI in sports will have a negative impact because it takes away the human side of the game that makes it exciting. The Washington Post said that MLB’s new ball-strike challenge system takes about “17 seconds,” and even though that’s quick, it still slows things down and changes the flow. I believe that rational decisions are a part of the game. I also don’t think other sports, like the NFL, should bring in AI to fix human errors, because the mistakes and arguments are part of what makes sports fun to watch. If AI gets too involved, games could start to feel robotic and less real. When it comes to jobs, I believe AI will start making a big impact before 2030. I also think people underestimate how many jobs AI can do, because it’s not just in tech, it could take over customer service, driving, and even some parts of healthcare.

I hope that in the future CBT can be improved to provide help to more people and save those who are suffering from mental torture.

This can not only strengthen the role of CBT but also provide psychological help to people from ethnic minorities.

This makes me curious of how each branch of CBT actually plays out in real therapy sessions. What specific techniques or ideas set them apart? It’d be interesting to see examples of how therapists use these different approaches depending on the client or issue at hand. I wonder if some work better for certain issues than others.

I didn’t realize how much CBT focuses on helping people interpret what’s happening around them, not just change in their thought process. This makes me think that emotions necessarily aren’t the problem, more so how we appraise the situations. It’s interesting that distorted thinking can cause either too much or too little emotional reaction. I’m starting to see how CBT is more about building self-awareness and flexibility than just “fixing” thoughts.

1. I anticipate being in college for 2-4 years to become a labor and delivery nurse.
2. I would probably have to take about 3-5 per term to finish in my time period. 3.I think the most difficult part will be making time for everything
3. I do believe I can overcome any difficulties that will come my way.

2

1

Probably the work and staying committed. With life going different directions just makes it hard on some people like me.

I plan to be in college for as long as I need to be! In order to get to the point that I want to be in.

estimate your study hours.

Reflects on which descriptions fits best and how it affects things like studying or getting work done.

Attempts to improve the region must include Black Americans. Tied into the broader historical context of the post-Reconstruction South, where the Black population played a crucial economic role, especially in agriculture and labor. Highlighting demographics and economic reality, Washington is arguing for inclusion based on practicality, not just for justice.

The passage used a metaphor urging both Black American and White Southerners to focus on building economic and social progress through cooperation rather than migration or conflict. This reflects Washington’s philosophy of accommodationism, which prioritized vocational training and economic self-reliance over immediate demands for civil rights. It can be contrasted with W.E.B. Du Bois’s later advocacy in The Souls of Black Folk (1903), where Du Bois criticizes Washington for accepting segregation and disenfranchisement in exchange for economic opportunity.

According to the reading, Mentor support teacher emotionally professionally, and socially, I can build confidence, belonging, and efficacy.Novice teacher go through emotional stages initial enthusiasm, we can help with their anxiety/doubts in this way their ngrowth nprofessional.

Key areas of support: classroom management, curriculum, student engagement, parent communication, and school environment. Challenges for mentors: balancing guidance with autonomy, managing time effectively, and avoiding the perception that mentoring is only for inexperienced teachers. Best practices: observation, feedback, co-teaching, building trust, promoting reflection, and fostering autonomy. Useful tools: checklists, journals, a continuum of support, observation techniques, and goal-setting reflection.

Mentors provide support in emotional, professional, and social areas (fostering confidence, a sense of belonging, and effectiveness). Beginning teachers go through various emotional stages: initial enthusiasm (anxiety/doubt ,professional growth.)

This looks pretty straightforward. I hope that I can pull off and A in this class.

I wonder if this means like right before 11:30 AM or 11:59?

I’m pro AI because it makes life easier, and like The Washington Post said, “wages of workers with AI skills were 56 percent higher than those without.” There are already so many people and businesses that use AI to create profit. I do not think we will see AI fully take over ever, I believe we as humans will always be superior to AI. I do expect insane growth before 2030 since it’s already moving so fast. I don’t think it will ever plateau, there will always be new discoveries and improvements. A lot of people are already training in AI to keep up, which shows how big it is becoming. It is not perfect now, but it’s only going to get more useful. Overall, AI is going to keep growing and changing the way we live and work.

This comment showcases how criminality among the high strata of society can legitimize the idea of criminality in and of itself. If the supposed pillars of your community are engaged in criminal action, then why shouldn't you be too?

Lupsha breaks here with a common opinion on the origin of criminality and states his thesis: that American crime is caused by cultural forces rather than material scarcity.

This is very unique. I haven’t really been in a class where there was a TA shadowing or being super helpful in a college class setting. Also, I’m relieved the class isn’t mainly based off of how well you do on a test because I often have test anxiety, but really try my very best in participating in helping others.

This connects to what I’ve learned about how our mindset shapes everything like thoughts, feelings, even how our body reacts. It’s cool that CBT breaks that down into actual skills like exposure and emotional regulation. I’m especially interested in how the science supports all of it!

she was pretty fed up with him for like falling out with everyone.

7<br /> 00:05:09

Excerpt Explanation in English: In this excerpt, the speaker expresses frustration towards someone (likely a male) who has been having conflicts with various people. The phrase "pretty fed up" indicates a strong sense of annoyance or weariness. The use of "like" suggests an informal tone, emphasizing the speaker's emotional reaction. This situation could indicate a pattern of behavior, where the person in question may be causing disruptions in their social or relational circles, leading to the speaker's exasperation.

中文翻译及解释： 在这个摘录中，发言者对一个人（很可能是男性）与周围人发生冲突感到沮丧。术语“pretty fed up”表明了一种强烈的烦躁或厌倦感。“like”的使用暗示了非正式的语气，强调了发言者的情感反应。这种情况可能表明一种行为模式，即这个人可能在他们的社交或人际圈中造成了干扰，导致发言者感到厌烦。

example of claim

example of claim

perspective

main claim

example of claim

amendments for the abolition of slavery

title

start new line- will increase list to 14 SLOs

I think that in order to learn properly that their dose need to be a lot of communication from students and teachers so that were all on the same page.

Her feeling this way is understandable. When you put your all into something and don't achieve what you wanted, it can lower your confidence. It can effect anyone after so long of trying.

I agree with this. The way things are comprehended and read can vary so much because of how different we all are.

important

important I guess he realized this by examing the behaviors and output of LLMs. Then what happens next is that it inspires him about the intermediate thinking chains of thoughts

nice

important

This shows us the impact he made on kids when it comes to learning.

Using this strategy to learn to read at such a young age shows how smart he really was.

The connection he made to the world just from a book reminds me of when my little brother first started reading. The excitement he got out of reading a sentence correctly made me happy.

Although these ideas are characterizing the important aspects and main ideas of technology and learning they are seeming to get lengthier and stretching the common knowledge of technology and making it a bit complicated to understand.

Based on the reading and the information presented from the early definitions to this definition I believe this one catches the true interests and accurately describes what technology is used for. For example by mentioning performance improvement, management and resources we can dive into the main reasons we use technology. Which are to help us progress , improve our learning, and create new ideas with previous known information.

This is a very good point utilizing the words learning and teaching rather than instruction adds objective understanding and an overall connection. For example instruction has been seen before as teacher or student led informal explanation. Rather than when we use teaching and learning it expands the idea that we are always learning and creating new ideas.

Would these visual instruction include moving pictures, movies and projector slides that they used to utilize in the classroom? As we move into the later years we have also added PowerPoint and google slides how we were able to add our pictures so technology has really come far in the visual aspect.

Hey everyone! I think the professor wants us to use the course group since I noticed she posted a question there for us to reflect on. If you’re seeing this, just click 'Public ⌄' and select the 6015 group.

Learning Design and Application: the study and application of practices, the goal being to empower learners to learn new, and strengthen their skills and implement them when needed. (I leaned heavily on the 2023 AECT definition for my definition and field name because I think it demonstrated the emphasis on learning rather than instruction, which resonated with me. I also stayed away from mentioning any mediums such as human instructors or technologies.)

I like this quote a lot

I can't wait for this paper especially because I feel like there is such an wide variety of musicals and brodways to choose from to reflect on. And I'm interested to hear everyones different takes on the shows they choose to reflect on.

Allusion; Romeo makes reference to Rosaline being unable to bear children because she has Dian's wit who is also the Goddess of chastity. He before mentions she will not be hit by Cupid's arrow which means she is can't fall in love as well.

Benvolio recounts noticing Romeo underneath the sycamore tree which prompts Romeo to make a run for it in to the nearby woods. He further mentions that following his own inclination, he didn't chase after him and was happy to leave Romeo alone as he fled from him.

This comment made me question why he chose to personify the Montague's as dogs and how does Sampson view others outside of this narrow lens?

important and impressive advice

important

Making your comments to your classmates constructive and focused will overall help you and your classmates when it comes to work ethic of the class. Not only are you showing you understand the material but also helping others understand it.

I feel like this is a fair way to grade for a C. getting a C is to do the bare minimum of work and if your not putting in much effort in the class you should not get a higher grade. With the topic of the class I believe that it would be helpful to do more than just the minimum to fully understand.

Wait, upon further research, while the boy's actions were cruel. They were defending the world against the underworld. "anti-heros" maybe?

I may be biased, but Hunahpu and Xbalanque sound like pure evil. I may be reading the text incorrectly.

Geez, was with the death and destruction of these men and boys. Why do they hate each other so much that they resort to murder?

This entire page exudes the essence of Cain and Abel from the Bible.

The boys are determined to kill their father, Seven Macaw. They appear to be full of themselves and believe they are more powerful and superior than the elders. Greed and selfishness have taken over their minds, possibly leading to delusions of grandeur.

The Gods "purged" or "cleansed" what they created to start a new, better race. Sounds like Christianity of Noah's ark again.

A floor, this connects to Christianity of Noah's ark and the great flood of 40 days and 40 nights. Interesting.

Other words: some humans are worthless, ungrateful, meat sacks, a waste of time and cognitive energy, or not worth claiming at birth.

The humans who were created had children of their own, but they didn’t take the time to realize or see in awe what was given as gifts. The gods must see the humans during this time as ungrateful or even spoiled.

important

The word, "tore" is an example of bias and slant because it tries to show that Cassidy is more powerful because he is in a position to rip someone else's work apart. It makes one think of the teacher/student or parent/child role where the more powerful person would be the one who is able to tear a plan apart. This also comes on the heals of 3 quotes that are sensational in themselves because they use words like "insane", "(Sanders) he would know nothing about this," and likens the idea to elementary school student government. All of these are meant to minimize Sanders as a serious person and minimize the issue a flippant and silly.

This quote tries to put a spin on Sanders' bill the make it seem ridiculous and not worthy of anyone's serious consideration. Weekend at Bernies is a comedic movie where ridiculous things happen, and it is chaotic and silly. By making this connection before any information is presented, it clearly shows that this article will not be looking at both sides of the issue objectively.

This faulty logic takes Shapiro's quote out of context. The authors is trying to make the connection that because Shapiro doesn't agree that people should retire after age 65, that he wants them to "work until they drop dead." There is no explanation to Shapiro's reasoning, and assumes a conclusion that is not supported by the facts

Again, this is sensationalism and unsubstantiate claims. There is no facts to support this, but uses incredibly emotive language to make the situation dire- that because the US is working too much, people have "lost control of their lives."

These are facts, but these touch on the concepts of bias by omission, and story choice. These concepts ARE being looked at in some European countries. However, the structure of the German, Portuguese, and French economies and cultures are very different to the US's. By choosing these countries without examining the forcing that are leading to these pursuits, it is disingenuous. They are omitting the critical information to give context to their decisions, and they are choosing stories of countries that support their position and deliberately not choosing stories that have a 40hour plus week.

This part of the article is slant and sensationalism. The slant is where it says, "if that weren't enough," whereby the author is trying to make you feel like of course you would agree with the prior sentences about not wanting to work and that everyone else works less. It is sensationalism because without facts or statistics, it uses words like "erratic schedules," "dismal situation," and "strange that politicians never speak to this widespread desire." These words are trying to evoke strong emotions and outrage. What they do not have is answers to questions like, how do we know there are erratic schedules? What is dismal? What do politicians say about productivity, pay and the workweek in the US?

New media really shapes how we show ourselves and interact with people these days. It helps us stay connected and find groups that share our interests, no matter where we are. But at the same time, it can sometimes lead to confusion or make face-to-face time less common. Online friendships might not always feel as real, and that can make people feel lonely. So, while new media has its perks, it also brings some challenges to how we see ourselves and relate to others.

New media lets people participate in democracy in new and powerful ways by sharing their views more easily. It can boost important voices, but at the same time, false information can spread quickly. Protecting creators’ rights online is important, though it’s tricky to find the right balance with making content accessible. Issues like content filtering and surveillance bring up serious concerns about privacy and control over information. Overall, new media has great potential but also challenges that require careful thought about what’s fair and ethical.

New media began with things like newspapers and TV but has since shifted to digital platforms such as social media and streaming. Unlike the older forms, new media lets people interact and respond in real time, making communication feel more personal. It gives everyone a chance to create and share content, helping people connect worldwide. This shift has made communication more social and community-focused. In short, new media is a lot more interactive than traditional media ever was.

The photos in this comment are an excellent illustration of an important point. Does anyone except McHale make packs with conical hipbelts?

Important points. McHale elaborates a bit about the conical shape of his belts on his website.

Most media outlets are controlled by a handful of big corporations, which can limit the range of voices and stories available. While media plays a big role in connecting people globally, it sometimes favors certain perspectives over others. There’s often a lack of diversity in how different groups are portrayed, which can reinforce stereotypes. Being media literate means learning to question who created the message and what their intentions might be. This skill helps us see through bias and better understand the information we encounter every day.

Mass media serves important roles like keeping people informed, providing entertainment, and shaping public opinion. It controls what information gets shared, acting as a gatekeeper between events and the audience. The hypodermic needle theory suggests media messages hit viewers directly and cause immediate effects. Other theories, like media effects and cultivation theory, explain how consistent exposure to media slowly changes how people view reality. Overall, media has a big influence on both what we know and how we see the world around us.

Back in the print age, books and newspapers made spreading information much easier and more common. Later, the audiovisual era brought radio, TV, and movies, adding sound and visuals that made messages more lively. Then came the Internet and digital media, which changed everything by giving people instant access to info and connecting folks around the world. Mass media plays a big role in shaping what we think, our culture, and how we get our news and entertainment. As new types of media pop up, older ones shift and change to keep up with the times.

Problems generally involve a specific challenge, some hurdles to work through, and a clear goal to reach. When groups tackle problems, they usually start by figuring out what the problem is, then dig deeper to understand it better. After that, they come up with different ideas, talk through the options, and finally decide on the best way forward. Groups can make decisions in different ways sometimes by voting, sometimes by finding a solution everyone agrees on, or sometimes the leader steps in to choose. The way decisions get made often depends on the personalities involved, who has influence, and any time limits the group faces.

In groups, task roles are about making sure the work gets done, like planning and keeping everyone focused. Maintenance roles help everyone get along by encouraging each other and sorting out any conflicts. Then there are negative roles that cause trouble, like someone who always criticizes or tries to control the conversation. These behaviors can slow the group down or create tension. Knowing about these roles helps groups stay on track and deal with any issues that come up.

People step into leadership roles for all sorts of reasons some are just naturally inclined, others pick up the skills over time, and sometimes it’s the situation that pushes someone to lead. There are different leadership styles too some leaders like to take charge and make all the decisions, some prefer to get everyone involved, and others give people a lot of freedom to do their own thing. Leaders also rely on different kinds of power, like the authority their position gives them, the knowledge they have, or simply the trust and respect others feel toward them. Different styles and sources of power fit better depending on the group and the challenges they face. Understanding these differences helps explain why certain leaders click with their teams while others don’t.

It makes sense!

I.e., Multiple items that come from a donor/organization should be kept together

What are enumerative & faceted systems? We need examples in layman's terms

KOP is the means by which we organize the data; how are we sorting it?

KOS are the systems used to organize the knowledge, which KOP is the more hands on work part. Dewey decimal vs Library of Congress

I.e., it's pointless if the user doesn't understand how to retrieve the info

Neat that environment could influence it

Group cohesion is basically how connected people feel to each other, while group climate is the overall mood or feel of the group. When people feel close and bonded, the group usually has a more positive and relaxed atmosphere. New members learn the group’s culture and expectations through socialization, which helps them fit in and work well with others. Sometimes people go along with the group to fit in, but if everyone just agrees without thinking, it can lead to poor decisions, which is called groupthink. Groups deal with different kinds of conflicts like disagreements about the task, personal issues, or how things should be done and handling these well means keeping communication open and focusing on solving problems.

Groups usually go through a few stages as people start working together. At first, in the forming stage, everyone’s just getting to know each other and figuring out what the group is about, which can feel a little awkward. Then comes storming, where disagreements and clashes happen as people share their opinions and test out roles. After that, in the norming stage, things calm down, the group agrees on how to work together, and trust starts to build. Finally, during the performing stage, the group works smoothly and gets stuff done.

When speaking on radio or TV, it’s important to be clear and get straight to the point since people can’t see your expressions. A good spokesperson stays calm, sounds confident, and keeps their message simple and easy to follow. Crisis communication pros jump in during emergencies to share accurate info fast and help maintain trust. They have to think on their feet and keep everyone updated when things get tough. In the end, being prepared and communicating well under pressure are what really count.

Talking to different people at work means you need to adjust how you communicate, whether it’s your boss, teammates, staff, or clients. Being comfortable with intercultural communication really helps when you’re working with people from different backgrounds. When it’s time for questions, keeping calm and giving clear answers goes a long way. For business presentations, staying organized and sticking to the main points keeps things moving and holds attention. Basically, understanding who you’re talking to and being prepared makes all the difference.

When you’re presenting, it’s smart to adjust your style depending on the subject. For arts and humanities, storytelling really connects with people, but social sciences lean more on data and real-life examples. In education and training, keeping things clear and interactive helps hold attention. Science and technical talks need to be detailed and often use visuals to break down tricky ideas. At academic conferences, it’s all about being clear, professional, and ready to answer questions so you come across as confident.

When you’re giving a ceremonial speech, it’s important to be genuine, keep your message simple, and really connect with the people listening. Whether you’re introducing someone, giving an award, or delivering a eulogy, being sincere and sticking to the main point makes a big difference. For a “This I Believe” speech, sharing your own experiences helps show what really matters to you. Public advocacy is about using your voice to push for change or shine a light on important topics. At the end of the day, good speaking is all about inspiring and moving your audience

I would move this section up so it sits right underneath the introduction paragraph

When it comes to giveaways or events you're a part of, is it possible to have pop ups on your website at all? Or you could add a banner at the top of your page so it's not a part of your regular home page.

I would also have a look at your general navigation to make it easy for people to check out all your offers. Rather than listing them all on the home page, I'd build and 'everything' page where you touch on all your workshops and courses, and people can click through to the individual offers from there.

In this paragraph, I would set the scene for what people expects but leave who you are for your about section. I'd explore the power of healing through creativity, and how everything you do is centered around this idea

Here’s a more natural, conversational version for you:

When trying to persuade, people usually build trust, use solid facts, and connect emotionally. Speakers earn credibility by being honest and showing they understand their audience. Logical arguments focus on clear evidence, while emotional appeals tap into how people feel. Cognitive dissonance is that uncomfortable feeling when what someone believes doesn’t match up with new info, pushing them to rethink things. Overall, persuasion works best when it speaks to what people really need or care about.

Inductive reasoning means you take specific examples and use them to figure out a general idea, while deductive reasoning starts with a general rule and applies it to a specific situation. Causal reasoning is all about figuring out what caused something to happen. To tell if these types of reasoning hold up, you look for strong evidence and clear logic. Some common mistakes, called fallacies, include jumping to conclusions or attacking the person instead of their argument. Knowing about these slip-ups helps you argue better and spot when others aren’t making solid points.

An argument works by making a main point, backing it up with evidence, and explaining why that evidence supports the point. When picking a topic to persuade people, it’s best to choose something that matters to you and your audience. You also want to adjust your message depending on whether your listeners already agree, disagree, or aren’t sure. Persuasive speeches usually focus on proving facts, values, or suggesting actions people should take. Organizing your speech in a way that fits your topic like showing a problem and a solution helps get your point across clearly.

Informative speeches usually focus on things like how to do something, explaining events or ideas, or talking about people and places. It’s key to research well and find reliable info and examples that back up what you say. You can share info by defining, describing, explaining how something works, or showing how to do it. To keep people interested, don’t try to convince them, avoid dumping too much info at once, and keep things engaging. That way, your audience is more likely to follow along and remember what you said.

Using facial expressions and making eye contact helps you build a connection with your audience and show your emotions. How you stand, move, and use your hands can add life to your message and highlight important points. Dressing nicely and looking professional helps people trust you more. Things like slides or props make your ideas clearer and stick better in people’s minds. When you put all these things together, your speech feels more real and keeps people interested.

Changing up your tone, pitch, and volume keeps your speech from getting dull and helps grab people’s attention. Talking clearly, not too fast, and knowing when to pause makes it easier for folks to follow what you’re saying. The way you use your voice plays a big role in how believable and confident you come across. If you sound confident and expressive, people are more likely to trust you. But if you mumble or rush through, you might lose people or seem less credible.