1. Aug 2026
  2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    A Phase II Evaluation of the Efficacy and Safety of Sacituzumab Govitecan in Patients with Recurrent Uterine Cancer
    3
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430211/
  3. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Comprehensive Genomic and Transcriptomic Characterization of MTAP Loss across Advanced Solid Tumors
    7
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430230/
  4. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Integrated Multiomic Profiling Enhances Risk Stratification and Prognostication in Canine Osteosarcoma
    20
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430567/
  5. www.datapulseresearch.com www.datapulseresearch.com
    The European Salary Ladder | DataPulse Research
    5
    1. Annevonpetersdorff 05 Aug 2026
      Base pay only,

      in the table above, below the graph it says the yellow line is "the median wage itself" - I assume that that means median wage across EU, as in EU median wage, right? I think we should have this info in the legend as well.

    2. Annevonpetersdorff 05 Aug 2026
      Maltese MPs hold a genuinely part-time mandate, parliament sits only Monday to Wednesday, and Malta's own standards watchdog has proposed a full-time option with higher pay for exactly that reason.

      Now this reason I find more plausible to include. We should double check if this is not also something that holds true for other countries. Also: what is Malta's own standards watchdog?

    3. Annevonpetersdorff 05 Aug 2026
      it is calculated against the EU-harmonised full-time median, and Malta's own national median (which blends full-time and part-time workers, a large share of them women) is materially lower, against which the same MP pay of €25,947 a year sits above the median, at 1.24 to 1.37 times.

      I am not sure I understand. the 0.9 in Malta are calculated against the EU harmonised full-time median? And this is done because Maltas own national median blends full time and part time workers and is therefore lower? Is that not the case for many /all countries?? If i understand correctly I feel like it would be more honest to use the national median.

    4. Annevonpetersdorff 05 Aug 2026
      A head of government's pay ranges from 2.3 times the national median wage at the bottom of the EU table to 12.7 times at the top, in Hungary. Members of parliament span an even wider stage: from Malta, where MPs on a part-time mandate earn close to the median, to Portugal, where they earn four times it. This study climbs the whole European income ladder, from the statutory minimum wage through the politicians who set its rules to the highest-paid CEOs, then pools all 27 national ladders into one: a single income ranking for 450 million Europeans. Where do you stand on it?

      simplify sentences aqnd make this paragraph shorter. wait until I have feedback on title/byline to see how to best align those two elements with this paragraph

    5. Annevonpetersdorff 05 Aug 2026
      The European Salary Ladder What it takes to reach the top 1% in 27 countries, and where you stand among 450 million Europeans A head of government's pay ranges from 2.3 times the national median wage at the bottom of the EU table to 12.7 times at the top, in Hungary. Members of parliament span an even wider stage: from Malta, where MPs on a part-time mandate earn close to the median, to Portugal, where they earn four times it. This study climbs the whole European income ladder, from the statutory minimum wage through the politicians who set its rules to the highest-paid CEOs, then pools all 27 national ladders into one: a single income ranking for 450 million Europeans. Where do you stand on it?

      This now feels a bit fragmented. The headlin and byline talks about European Salary ladders and then its mainly about POliticians salary. Ask nico in how far we are "married" to teh title bc of what he pitched. depending on his answer I would search for a different title/byline.

    Visit annotations in context

    Annotators

    URL

    datapulseresearch.com/p/dp-salary-ladder-v02/
  6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Phase I trial of Ipatasertib plus Atezolizumab enhances PI3K/AKT pathway immune responses in solid tumors and refractory glioblastoma
    17
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430223/
  7. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    First-In-Human Trial of Encapsulated Cells Constitutively Expressing Localized IL2 in Patients with High-Grade Serous Ovarian Carcinoma
    5
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430228/
  8. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Benralizumab for Eosinophil-Related Cutaneous Adverse Events of Anticancer Therapy: A Phase II Trial
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430216/
  9. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Low muscle density is associated with morbidity and systemic inflammation in colorectal cancer, independent of tumor factors
    2
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430222/
  10. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    A quantitative framework to assess the potential of earlier cancer detection to improve cancer survival
    3
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13430215/
  11. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Mouse Offspring Exposed to Preeclampsia/Eclampsia-like Symptoms Exhibit Cerebral Hypoperfusion & Mild Cognitive Impairment at 2 months of age
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13431237/
  12. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Development and regulatory approval of Kal91.3: combining advanced conventional breeding with genetic engineering to create a cold sweetening‑resistant chip‑processing potato
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC13432818/
  13. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    A silent Kv channel subunit shapes PV neuron action potential waveform and short-term synaptic plasticity during high-frequency firing
    4
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC12890855/
  14. 54.241.53.176 54.241.53.176
    '-html.html
    20
    Visit annotations in context

    Tags

    Annotators

    URL

    54.241.53.176/b66822b2907bb6d00b9e83a81725f62d71cd041a/'-html.html
  15. learninglab.gitlabpages.inria.fr learninglab.gitlabpages.inria.fr
    Ionic App
    13
    1. mariais 05 Aug 2026

      Exploring and reusing Open research Data - Learning assessment : Question 1 : suppress the capital to "metadata" in the question Question 3 : licence

    7. mariais 05 Aug 2026

      Introducing Open Science - Learning Assessment - question 1 : maybe explain what is CEI ? or replace it by "Ada's institute" ? Or just generalize : "Which statement best reflects the open Sceicne policy adopted in many research institutes?"

    10. mariais 05 Aug 2026
      Findable Data and metadata should be easy to locate for both humans and automated systems. Machine-readable metadata is essential here. Accessible Once found, users need to understand how to access the data, possibly including authentication and authorisation.  Interoperable The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.  Reusable The goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described and properly licensed so that they can be replicated and/or combined across different settings.

      Maybe suppress the table and present the principles as paragraphs ?

    Visit annotations in context

    Annotators

    URL

    learninglab.gitlabpages.inria.fr/epoc/epoc-web-preview/epoc/preview/E-020-OSTrails1
  16. www.crafins.com www.crafins.com
    Die beste Software für den internationalen Onlinehandel 2026: 5 Systeme für Sprachen, Kanäle, Währungen und Steuern im Vergleich
    2
    1. Elias_GetCited 05 Aug 2026
      4. Odoo Odoo S.A., Grand Rosière (Belgien) · Open-Source-ERP · Einstiegspreis 19,90 Euro je Nutzer und Monat im ersten Jahr, danach 24,90 Euro Odoo hat die größte Steuer- und Lokalisierungstiefe im Vergleich, und zwar mit Abstand. Die Dokumentation der Version 19 führt 103 Länder mit eigener Steuerlokalisierung, 45 davon mit ausführlicher Länderseite. Wer in mehreren Ländern eine Gesellschaft führt, bekommt je Gesellschaft den passenden Kontenrahmen in derselben Datenbank, für Deutschland SKR03 und SKR04 samt zweistufigem DATEV-Export. Für den EU-Fernverkauf liegt das Modul l10n_eu_oss quelloffen im Kern: 2.317 hinterlegte Steuersatz-Zuordnungen über 29 Herkunfts- und 27 EU-Zielländer, aus denen Odoo die Steuerpositionen für jedes Zielland erzeugt. Am Auftrag greift der richtige Satz dann automatisch, im Shop, sobald der Kunde seine Rechnungsadresse hinterlegt hat. Die Buchhaltung mit diesen Berichten gehört zur Enterprise-Edition, und dort verlässt die fertige OSS-Auswertung das System als PDF, XLSX oder XML zur Abgabe beim Bundeszentralamt. Ideal für: Unternehmen mit Gesellschaften in mehreren Ländern, die Buchhaltung und Steuer im selben System führen wollen.

      we need to mention here that they are an open source and require much more technical know how and resouces. check if that is true please, but then add that sentence

    2. Elias_GetCited 05 Aug 2026
      griert sind genau sieben Dienstleister, im Kern die deutschsprachigen plus UPS, und Zollinhaltserklärungen erzeugt das System für DHL-Sendungen

      die deutschsparchigen plus UPS says nothing, what does this mean

    Visit annotations in context

    Annotators

    URL

    crafins.com/p/po-v03-sd/
  17. www.iranicaonline.org www.iranicaonline.org
    ESFANDĪĀR (Kayanian prince)
    1
    1. lemmona 05 Aug 2026
      信仰的捍卫者。虽然在世俗文学中，埃斯凡迪亚尔最广为人知的是他与罗斯塔姆的战斗，但在琐罗亚斯德教的文献中，他被描绘成最早皈依该信仰的人之一，并与扎雷尔一起成为该信仰最热忱的捍卫者。在《阿维斯塔》中，埃斯凡迪亚尔位列信仰的捍卫者之列，他们的神圣灵魂（fravašī）受到赞扬（Yt . 13.103）。他还参与了先知的几个奇迹。当戈什塔斯普那匹无与伦比的骏马患上一种疾病，导致它的腿缩回腹部时，他向琐罗亚斯德祈求治愈它（Dēnkard 9.22.2；Molé，1967，第186页，注70）。先知提出了几个条件，其中之一是伊斯凡迪亚尔必须成为信仰的捍卫者（《丹卡德》 7.4.70；莫莱，1967，第110页）。巴赫拉姆·帕日杜的《扎拉托什特纳玛》详细阐述了这个传说（第942行及以下；《维齐尔卡德·迪·德尼格》，第18页；莫莱，1967，第132页；参见沙赫拉斯坦尼，第一卷，第285-289页，他引用了杰哈尼的记载提及了这一奇迹，但没有提及伊斯凡迪亚尔的名字；托尔卡译，第186-188页）。在另一个奇迹中，先知将布尔岑米尔之火（参见ĀDŪR BURZĒN-MIHR）放在戈什塔斯普、贾马斯普和伊斯凡迪亚尔手中，却没有烧伤他们。在其他地方，戈什塔斯普向琐罗亚斯德祈求四个恩惠，但先知只同意将它们赐予四个不同的人。结果，戈什塔斯普获得了关于他在米努（mīnū，即来世）中的位置的知识；贾马斯普获得了对过去、现在和未来所有事件的认知；帕绍坦获得了永生；而伊斯凡迪亚尔则变得刀枪不入，拥有了“铜身”（ rūyīn-tan，字面意思是“铜身”），“以至于任何锋利的刀（kārd）都无法伤害他的身体”（《琐罗亚斯德传》，第1162行及以下；《维齐尔卡德·迪尼格》，第19页）。伊斯凡迪亚尔的生平。此处提供的概要版本依据《列王纪》记载，并参考了其他资料补充细节。

      铜身，指的是无法伤害自己。

      Robot
    Visit annotations in context

    Tags

    Annotators

    URL

    iranicaonline.org/articles/esfandiar-1-son-gostasp/
  18. Local file Local file
    Translanguaging in Multilingual Families: Evidence from Cyprus, Estonia and Sweden
    1
    1. MileyM 05 Aug 2026
      This effort serves as a form of resistance against globaliza-tion and the enduring impact of colonialism

      how translanguaging helps immigrant families.

    Annotators

  19. wenku-strategy-ppt-sdpic.bj.bcebos.com wenku-strategy-ppt-sdpic.bj.bcebos.com
    公考古代史“通关秘籍”——从对外交流到农业的脉络地图 - 学习笔记
    9
    Visit annotations in context

    Annotators

    URL

    wenku-strategy-ppt-sdpic.bj.bcebos.com/simplelearn/test20260706/log_id_4703704982187148928/chapter_0_for_share.html
  20. www.biorxiv.org www.biorxiv.org
    Improved short nascent strand sequencing (iSNS-seq) enhances DNA replication origin detection and reduces non-origin biases
    4
    1. EMBOpress 05 Aug 2026

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

      Learn more at Review Commons

      Reply to the reviewers

      Reply to the reviewers:

      We thank the three reviewers for their thoughtful and constructive comments, which have helped us to better explain our arguments and strengthen the manuscript. In this revision, we have clarified several points raised in the initial review and added new evidence that we believe further supports our conclusions.

      Point-by-point responses:

      Reviewer #1:

      _Additional in vitro experiment using artificial R-loop structures as substrate for lambda-exonuclease could prove the efficacy of the nuclease to digest through R-loop structures._

      We agree this experiment would be the cleanest way to demonstrate λ-exo's behavior on an R-loop substrate under defined biochemical conditions, and we would have liked to include it. However, this work originated in a laboratory that has since been closed due retirement, and further wet-lab experimentation is not feasible for this revision.

      Nonetheless, the manuscript already provides strong convergent evidence for RNA:DNA hybrid-mediated obstruction, short of this direct reconstitution. First, in vivo colocalization analysis shows that tSNS-seq (but not iSNS-seq) signal is enriched at S1-DRIP-seq and S9.6 ChIP-seq sites in an RNase H-sensitive manner, directly implicating RNA:DNA hybrids at the genomic loci where tSNS-seq peaks form. The reciprocal is also true, RNA:DNA hybrid signal is enriched at tSNS-seq sites, but not iSNS-seq sites (nor at known origins), in an RNase H-sensitive matter. Second, this obstruction signature is not a yeast-specific artifact of our analysis. The same asymmetric, tRNA/snoRNA-anchored peak shape is present in independently generated tSNS-seq datasets from Drosophila and C. elegans. In fact, C. elegans shows this artifact is in the non-replicating control, and is eliminated in the RNase control. Furthermore, a recent publication using (strand-specific) tSNS-seq in Trypanosoma bruceireports that large majority (90%) of its peaks map to R-loops (Stanojcic et al. 2026), although they report it as mapping true replication origins, not as a demonstration of the artifact. Finally, we added an analysis comparing R-loops mapped by RIAN-seq in mouse (Li et al. 2025) and two independently generated mouse tSNS-seq datasets (Cayrou et al. 2015 and Pratto et al.2021) that show strong correlation. Taken together, this is not one experiment pointing to hybrid-mediated blockage, but a repeated, multiple-species in vivo-validated pattern observed in tSNS-seq by multiple independent laboratories.

      What our data cannot do is isolate the enzyme's behavior on a defined R-loop substrate in vitro, separate from all other cellular context. That is a distinct and narrower question from whether hybrid-mediated obstruction explains the peaks we observe. The latter is what the convergent evidence above addresses. Future work can nail down the exact enzymology and conditions needed to replicate this in vitro.

      In Fig. 1C, there seems to be a minor increase of lambda-exo activity on R10D30 substrate in the Tris-HCI buffer compared to Glycine-KOH buffer, maybe a quantification using the loading control (D20) would help.

      As suggested by the reviewer, we have quantified band intensities for the RNA-DNA chimera (R10D30), the G4 oligo (D10G427D23), and the all-DNA control (D25) shown in Fig. 1C, normalized to the D20 loading control at each timepoint (new Supplementary Figure S5). As this gel-based densitometry is semi-quantitative at best, the values below should be interpreted as indicative rather than precise measurements; nonetheless, they confirm the reviewer's observation: the RNA-DNA chimera was digested to a somewhat greater extent in Tris-HCl (35% signal remaining at 16 h) than in Glycine-KOH (65% remaining). We have revised the Results text to report these values explicitly and to clarify our claim. The relevant passage in the Results now reads: "However, the entire oligo (D10G427D23) was digested in Tris-HCl buffer very efficiently, with barely visible bands after as early as 1 h of λ-exo digestion (1% remaining at 16 h, comparable to the D25 control). The RNA-DNA chimera (R10D30) was digested slowly in both buffers over the 16 h time course, though to a somewhat greater extent in Tris-HCl (35% remaining) than in Glycine-KOH (65% remaining). This shows that RNA-primers offer partial, but not full, protection from λ-exo digestion in either buffer, distinct from the buffer-dependent protection conferred by G-rich DNA in glycine-KOH buffer. Thus, conditions for better digestion through G4-containing DNA in Tris-HCl buffer may be more suitable for mapping origins with SNS-seq."

      We further note that this observation does not bear on the final iSNS-seq protocol, since iSNS-seq relies on 5'-OH rather than 5' RNA to protect nascent strands from λ-exo digestion. The buffer-dependent difference in RNA-primer protection described here is therefore relevant only to the mechanistic characterization of λ-exo behavior in Fig. 1C, and does not affect the enrichment logic or performance of iSNS-seq itself.

      In Fig. 2D, lower panel, the digestion time of RecJf at different units were not indicated.

      We thank the reviewer for catching this point. We have revised the Figure 2D legend to remove this ambiguity, clarifying that the top panel shows a RecJf timecourse, while the bottom panel shows a titration of RecJf units (0–300 U) at a fixed 16 h digestion time.

      In Fig. 3B, since SNS-seq detect fired origins, an overlap of iSNS rep 1 and iSNS rep 2 peaks with confirmed origins from OriDB that are also early and efficient origins may yield a higher percentage of overlap.

      We thank the reviewer for this suggestion. Rather than stratifying discrete peak-overlap percentages, which are sensitive to peak-calling thresholds and tend to understate genuine concordance, we assessed this using continuous signal enrichment at OriDB-confirmed origins, that were stratified into quartiles by annotated origin efficiency (Hawkins et al., 2013) (see modified Fig. 3C). Both iSNS-seq replicates showed a clear trend of increasing median signal from the least to the most efficient origin quartile. This is consistent with the expected behavior of SNS-seq, which detects origins in proportion to their firing frequency in the asynchronous population, and we now state this explicitly in the manuscript.

      In Fig. 3D, in addition to showing the tSNS and iSNS data on ChrIV with indicated known origins, showing at the same time the corresponding FORK-seq, OK-seq, and ORC ChIP signal will give a more comprehensive view of the performance of different origin mapping methods.

      We agree with the reviewer that including complementary origin-mapping datasets alongside tSNS-seq and iSNS-seq would provide a more comprehensive view of method performance. We have added FORK-seq initiation site midpoints, ORC ChIP-seq signal, and OK-seq origin efficiency metric (OEM) signal to Fig. 3D, alongside the tSNS-seq and iSNS-seq tracks and annotated known origins on Chr IV. In addition, we have added close-up views of the tSNS-seq and iSNS-seq tracks around three selected origins in Fig. 3D, which highlight that the prominent tSNS-seq peaks do not align with known origins, in contrast to iSNS-seq.

      In Fig. 5F, in supporting the model, a comparison of tSNS-seq peak with known budding yeast DRIP-seq datasets would help to see if the tSNS method indeed enrich for RNA:DNA hybrid signals.

      We agree with the reviewer that a direct comparison to known R-loop maps would substantially strengthen the proposed model. We have added this analysis, described briefly below, in a new Results subsection and Figure 6.

      We obtained raw, publicly deposited budding yeast S1-DRIP-seq and S9.6 ChIP-seq data, including RNase H-treated and RNase H-deficient (RNase HΔ) conditions, and called peaks from these datasets ourselves using our own pipeline, so that all datasets were processed identically. A new heatmap colocalization figure (Fig. 6A) shows that tSNS-seq (but not iSNS-seq) signal is clearly elevated at these R-loop peaks, most strongly in the RNase HΔ condition and abolished in RNase-treated controls, consistent with genuine RNA:DNA hybrid dependence. The reciprocal analysis confirms this specificity: R-loop signal is concentrated at tSNS-seq peaks, but shows no enrichment at iSNS-seq, OK-seq, or FORK-seq peaks, or at confirmed origins. R-loop signal is also enriched at tRNA, snoRNA, and snRNA genes, mirroring the tSNS-seq enrichment pattern at these same loci. Together, these results directly demonstrate that tSNS-seq peaks colocalize with bona fide R-loops rather than replication origins, supporting the model in Fig. 5F.

      Finally, to test whether this observation generalizes beyond yeast, we correlated published mouse RIAN-seq signal — an antibody-free, nuclease-based R-loop mapping method developed independently of SNS-seq — with two independent mouse tSNS-seq-type datasets (Cayrou et al. 2015; Pratto et al. 2021). tSNS-seq enrichment correlated significantly with RIAN-seq R-loop signal across replicates and genomic scales, indicating that the same hybrid-mediated obstruction mechanism likely operates in a mammalian system as well. Moreover, analyses of tSNS-seq signal in Drosophila and C. elegans confirms that the enrichment bias at tRNA sites also exists in those systems. The C. elegans data shows it is not dependent on DNA replication, and is dependent on RNA, just like in yeast.

      _Reviewer #2:_

      The authors' sugestion that tSNS miscalling of origins may be due to the presence of RNA:DNA hybrids is largely persuasive in theoretical terms but is, surpisingly, untested. The first issue that is unexamined in whether or not RNA:DNA hybrids would survive the two rounds of 95 degree denaturation that are central to both froms of SNS; can the auhtors comment or provide evidence?

      Second, it is important that the authors test their proposal (Fig.5) of RNA:DNA hybrids being the cause of at least some non-origin tSNS signal by mapping the correspondance of their SNS-seq data with the locations of RNA:DNA hybrids, since there are several forms of such mapping available for S. cervisiae (eg using S9.6 antiserum DRIP-seq, or RNaseH1 ChIP-seq).

      We thank the reviewer for raising these two important points, both of which push us to be more precise about what our model does and does not claim.

      On denaturation and hybrid survival: We agree this is a critical point to clarify, and we think it reflects a distinction we had not made explicit enough in the original submission. We are not proposing that in vivo-formed R-loops survive the 95°C denaturation steps intact. That would indeed be difficult to reconcile with the protocol. Rather, our data suggest that the highly abundant RNA species themselves (tRNAs, snoRNAs) survive denaturation as free single-stranded RNA and re-anneal with their complementary genomic DNA strand at, or before, the λ-exo digestion step, which is carried out at 37°C over an extended overnight incubation. This reannealed RNA:DNA hybrid is what we propose obstructs λ-exo in tSNS-seq. Indeed, the preservation of this RNA throughout the protocol until the λ-exo step is a built-in feature of the traditional protocol, since the RNA is only hydrolyzed after the λ-exo digestion is complete. We have added the following sentence to the Discussion to make this explicit: “Importantly, we do not propose that in vivo R-loops survive the denaturation steps of the iSNS-seq protocol. Rather, we propose that RNA:DNA hybrids reform in vitro after denaturation at genomic loci that are prone to R-loop formation. The likelihood of hybrid reformation would be expected to increase with local RNA abundance. These reformed hybrids would then selectively block λ-exo digestion, producing the characteristic asymmetric enrichments observed in tSNS-seq.”

      On testing correspondence with mapped RNA:DNA hybrids: We agree, and we have added a new Results subsection and Figure 6 to directly test this. We generated a new heatmap colocalization figure (Fig. 6A) comparing tSNS-seq and iSNS-seq signal against published budding yeast S1-DRIP-seq and S9.6 ChIP-seq maps, including RNase-treated controls. tSNS-seq signal is clearly elevated over R-loop sites identified by these orthogonal methods, but not peaks called from RNase-treated controls; iSNS-seq signal is flat over both R-loop and control peak sites. We also performed the reciprocal analysis and see that R-loop signal is highly concentrated at tSNS-seq peaks, but not iSNS-seq peaks (Fig. 6B). Importantly, this RNA:DNA hybrid enrichment signal at tSNS-seq peaks is abolished in the RNase H-treated controls and enhanced in RNase deficient mutants that accumulate R-loops, both consistent with genuine RNA:DNA hybrid dependence. Finally, we demonstrate that, like tSNS-seq, the R-loop signal is also highly enriched at tRNA, snoRNA, and snRNA genes (Fig 6C). Analyses of tSNS-seq signal in Drosophila and C. elegans shows this SNS enrichment bias at tRNA sites also exists in those systems. Importantly, the C. elegans data shows it is not dependent on DNA replication, and is dependent on RNA, and is thereby consistent with the RNA:DNA enrichment artifact we discovered in yeast.

      As a further, independent test of generalizability, we correlated tSNS-seq signal with RIAN-seq (which maps R-loops genome-wide) using two published mouse datasets: the original tSNS-seq data from Cayrou et al. 2015 and the strand-specific tSNS-seq data from Pratto et al. 2021. We found a significant positive correlation with RIAN-seq R-loop signal in both, indicating the same mechanism operates in a mammalian system (Figure 6D, E). We also note in the Discussion that a recent report (preprint at the time of this review, Stanojcic et al. 2026) similarly found that 90% of tSNS-seq peaks in Trypanosoma bruceioverlap with mapped R-loops, providing independent, multiple-species support for this interpretation.

      Fig.S7. Can the authors comments on the poor reproducibility between SNS-seq replicates? Though there isa four-fold increase in concordance between iSNS experments compared with tSNS, 80% of potetial origins are missed; can this be explained? In this regard, is the statment 'Both of the iSNS-seq samples showed signal enrichment around most of the confirmed origins' correct: while Fig.3C gives this impression, Fig.3B appears to diagree.____

      We agree the original Fig. 3B (Euler diagram) understated the reproducibility of iSNS-seq and, on reflection, we do not think it was the appropriate metric to lead with. Euler/peak-set overlap is a binary, threshold-dependent measure. Peaks that fall just above the calling threshold in one replicate and just below it in the other are counted as fully discordant even when the underlying signal is well correlated. We have moved the Euler diagram to the supplement (Fig. S9) and replaced Fig. 3B with a cross-replicate F1 curve, and cross-replicate signal heatmaps. Together these analyses show that concordance between replicates is graded and substantially above what the fixed-threshold Euler comparison implied. We have revised the text accordingly, and noted that the aggregate enrichment is not fully captured by peak-overlap statistics for the reasons above.

      The same failure mode of overlap analysis applies to overlap of iSNS (or tSNS) peaks with known origins. While the SNS signal may be fully correlated with origin positions and even origin efficiency, parameter choices in peak calling and using binary overlap statistics can mask the underlying concordance of the data with known replication origins. Moreover, the list of known replication origins, even confirmed origins, is not a list of origins most likely to be active. SNS methods can only detect active origins. Therefore, we assessed concordance of the SNS methods with origin efficiency using signal enrichment at OriDB-confirmed origins that were stratified into quartiles by annotated origin efficiency (Hawkins et al., 2013) (see modified Fig. 3C). Both iSNS-seq replicates showed a clear trend of increasing enrichment signal from the least to the most efficient origin quartile. This is consistent with the expected behavior of SNS-seq, which detect origins in proportion to their firing frequency in the asynchronous population, and we now state this explicitly in the manuscript.

      Given the very nice data in Figs.1 and 2 showing the confounding effect of G4s on tSNS, can the authors comment on why G4s show little overlap with either SNS-seq mapping in Fig.4, and why they saw no increase in tSNS-seq or iSNS-seq signal over G4 motifs in Supplementary Figure S9B? Might this indicate that the in vitro work does not translate well to in vivo mapping?

      We agree this warranted comment and have expanded the Discussion accordingly. We were ourselves somewhat surprised not to see a higher genome-wide G4 signal, though not entirely so. This is not evidence that the in vitro work fails to translate in vivo: the same λ-exo bias has been shown to manifest genome-wide in human cells (Foulk et al. 2015). Rather, we suggest the limited yeast signal likely reflects yeast-specific properties, which has a genome with more uniform local GC content than human (new Supplementary Figure S22), far fewer G4 motifs overall (Wu et al. 2021), and possibly less stable G4 folding in vivo (Tran et al. 2011). Moreover, the G4s in the human genome are non-randomly clustered in the GC-rich isochores, which compounds the G4 bias further with the known GC bias of Lambda exonuclease. These points are now made in the revised manuscript.

      The known G4 problem was the basis for searching for better buffer conditions in this study. While we found conditions that eliminate the G4 bias in vitro, the yeast genome did not provide ample opportunity to test this. However, the yeast genome ultimately allowed us to discover a possibly more dominant systematic bias, which is the correlation with tRNA and other high copy number RNA species that likely form RNA:DNA hybrids in vitro. Moreover, the lack of G4s allows a clean separation of G4s and R-loops, features that are highly correlated in the human genome.

      A requirement to validate the interesting suggestion that RNA:DNA hybrids are a cause of tSNS-seq miscalling of origins; this should be a combination of in vitro tests and colocalisation of tSNS-seq signal and RNA:DNA signal in vivo using available datasets (eg DRIP-seq).

      We agree that a direct in vitro biochemical demonstration that λ-exo digestion is specifically obstructed by an RNA:DNA hybrid substrate would further strengthen this model. However, as the laboratory where the wet-lab work for this study was performed has since been closed due to retirement, additional experiments of this kind are not feasible for this revision. We have instead addressed this request through a combination of new in vivo colocalization analyses, and an additional line of convergent evidence from the literature, which together we believe make a compelling case for the model.

      First, we have now added direct in vivo colocalization evidence: a new heatmap figure (Fig. 6A) comparing tSNS-seq and iSNS-seq signal to published budding yeast S1-DRIP-seq and S9.6 ChIP-seq maps, with RNase H-treated controls. tSNS-seq signal is clearly elevated over R-loop sites identified by these orthogonal methods, but not peaks called from RNase-treated controls; iSNS-seq signal is flat over both R-loop and control peak sites. Importantly, this RNA:DNA hybrid enrichment signal at tSNS-seq peaks is abolished in the RNase H-treated controls and enhanced in RNase deficient mutants that accumulate R-loops, both consistent with genuine RNA:DNA hybrid dependence. Finally, we demonstrate that, like tSNS-seq, the R-loop signal is also highly enriched at tRNA, snoRNA, and snRNA genes (Fig. 6C). Analyses of tSNS-seq signal in Drosophila and C. elegans shows this SNS enrichment bias at tRNA sites also exists in those systems. Importantly, the C. elegans data shows it is not dependent on DNA replication, and is dependent on RNA, and is thereby consistent with the RNA:DNA enrichment artifact we discovered in yeast.

      Second, we further demonstate that R-loop and tSNS-seq correlation extends to mouse as well. A novel R-loop mapping method RIAN-seq (Li et al. 2025) uses λ-exo, together with nuclease P1 and T5 exonuclease, to selectively degrade single-stranded RNA, single-stranded DNA, and double-stranded DNA from digested genomic DNA, while RNA:DNA hybrids resist this treatment and are selectively recovered. That λ-exo digestion is used as one of the core enzymatic steps to enrich for RNA:DNA hybrid-containing DNA is itself a genome-wide demonstration that λ-exo activity is impeded by RNA:DNA hybrid structures. Building on this, we correlated tSNS-seq signal against RIAN-seq signal using two independent published mouse tSNS-seq datasets (Cayrou et al. 2015 and Pratto et al. 2021) and found significant positive correlation in both, directly linking λ-exo obstruction by RNA:DNA hybrids to tSNS-seq peak formation in an independent system (Fig. 6D, E).

      Finally, a recent study (Stanojcic et al. 2026) using tSNS-seq on trypanosomes noted the majority (90%) of their peaks were associated with R-loop structures. Thus, we can defensibly conclude that this correlation is seen in yeast, C. elegans, Drosophila, mouse, and trypanosome datasets.

      An explanation and/or comment on the low reproducibility and low signal-to-noise ratio of iSNS-seq; specifically, although it improves on tSNS, does it provide accurate origin prediction?

      We do not believe reproducibility is in fact poor; the discrete peak-overlap metric we originally used was overly conservative (although still significantly above random). On signal-to-noise: we have added FRiP-vs-cumulative-ranked-peaks curve (Fig. 3E) showing that both iSNS-seq and tSNS-seq achieves higher than random raw FRiP. While tSNS-seq achieved higher FRiP, the iSNS-seq shows greater specific enrichment (SN/PPV against OriDB) at real origins. This is because the majority of tSNS-seq reads are in tRNA-associated non-origin peaks. In other words, tSNS-seq's apparently favorable S:N is driven in large part by non-origin enrichment (e.g., R-loop-forming loci), consistent with our RNA:DNA hybrid-mediated bias hypothesis. In contrast, iSNS-seq's lower overall S:N reflects the removal of much of that strong non-origin signal, leaving a smaller but more origin-specific signal. Whereas the non-origin biases are strongly present in a sample, nascent strands from a replication origin are very rare in the sample in comparison; present only in the fraction of S-phase cells in an asynchronous population where the nascent origin-proximal DNA is Comment on the lack of in vivo evidence, from available mapping data, for the confounding effect of G4s seen in the in vitro experiments.

      In vivo evidence for this λ-exo bias does exist in human cells (Foulk et al. 2015). Its absence in our yeast mapping data is better explained by yeast-specific genomic features than by the effect being artifactual, or in vitro-only. We have revised explicit comment on this in the Discussion:

      “Given the clear G4-mediated λ-exo obstruction we observed in traditional conditions in vitro, as well as previously demonstrated genome-wide blockage at G4s in human cells and preference of λ-exo for AT-rich over GC-rich DNA (Foulk et al 2015), we were somewhat surprised not to observe a higher proportion of G4-overlapping fragments in tSNS-seq compared to iSNS-seq. However, this is not entirely unexpected for several reasons. First, the budding yeast genome is markedly more uniform than the human genome: local GC content (100 bp bins) spans a 10th–90th percentile range of 30–46% in yeast versus 26–55% in human (Supplementary Figure S22). In fact, the yeast genome has roughly half the variation of GC content found in the human genome as measured by standard deviation and median absolute deviation (MAD) (Supplementary Figure S18). Budding yeast also has substantially fewer G4 motifs than humans, both in absolute number and as a proportion of the genome (Wu et al. 2021), limiting the opportunity for a genome-wide G4 signal to emerge regardless of any per-motif blocking effect. Finally, we cannot rule out that budding yeast G4 motifs simply form less stable quadruplexes, as has been shown for yeast telomeric G4s specifically (Tran et al. 2011).”.

      Reviewer #3:

      While the method developed (iSNS-seq) appears to improve aspects of the previously used method (tSNS-seq), poor signal-to-noise ratios and reproducibility are major concerns. The signal-to-noise ratio of iSNS-seq, as shown in Figure 3D, appears low. The authors should discuss what practical consequences this has for the applicability of the method, especially in species with less well-defined/efficient origins, and how it affects the reliability of peak calling, and overlap with known origins. Consistently, the overlap of called peaks between biological replicates of iSNS-seq is relatively low (Fig3B). This raises a concern for the usability of the method, the interpretation of the genome-wide data and the quality metrics provided. The authors should discuss these issues.

      We have added a Discussion paragraph addressing this directly. Because the intrinsic signal-to-noise ceiling of SNS-seq-type methods scales with the size and firing efficiency/synchrony of the origin population (as detailed in our existing calculation based on Cadoret et al. (2008)), we now state explicitly that applying iSNS-seq to organisms or cell populations with less efficient, less synchronized, or less well-defined origins than budding yeast should be expected to yield correspondingly lower signal-to-noise and reduced peak-calling reliability, with a likely higher false-negative rate for genuine origins. We now acknowledge the need for further optimization to improve the underlying SNS:background ratio before extending the method to other organisms.

      On reproducibility: the original Fig. 3B (Euler diagram) understated the reproducibility of iSNS-seq and, on reflection, we do not think it was the appropriate metric to lead with. Euler/peak-set overlap is a binary, threshold-dependent measure. Peaks that fall just above the calling threshold in one replicate and just below it in the other are counted as fully discordant even when the underlying signal is well correlated. We have moved the Euler diagram to the supplement (Fig. S9) and replaced Fig. 3B with a cross-replicate F1 curve, and cross-replicate signal heatmaps. Together these analyses show that concordance between replicates is graded and substantially above what the fixed-threshold Euler comparison implied.

      We have replaced the Euler-diagram comparison with a graded, cross-replicate F1 analysis (new Fig. 3B) and supplementary correlation/Jaccard metrics, which show reproducibility is substantially above random for both methods and is in fact tighter for iSNS-seq than tSNS-seq at the level of peak-height correlation.

      Related to the above, please explain/discuss the rationale behind retaining all peaks, even the ones observed in only one of the biological replicates, when comparing called peaks to confirmed ORIs. In Figure 3B, clarify what are the percentages depicted.

      We agree with the reviewer that this point deserves fuller explanation, and we address the two parts in turn.

      Rationale for retaining single-replicate peaks. Origin firing is stochastic across an asynchronous population, and any single replicate is a depth-limited sample of the true origin population rather than an exhaustive one. Requiring a peak to be called in both replicates before comparing it to OriDB would systematically discard true origins that happen to be under-sampled in one replicate, artificially inflating apparent PPV at the direct cost of sensitivity. Since our goal in this analysis was to characterize each method's raw concordance with known origins, we compared each replicate's full peak set to OriDB independently.

      What the percentages in the diagram represent. We have moved this Euler diagram comparison from the main text to Supplementary Figure S9. We have clarified the legend of Supplementary Figure S9 (formerly Figure 3B) to read: "Percentages represent the fraction of the total combined peaks across all three sets being compared (i.e., the union of iSNS-seq rep 1, iSNS-seq rep 2, and confirmed ORIs for panel A; tSNS-seq rep 1, tSNS-seq rep 2, and confirmed ORIs for panel B) that fall into each region of the diagram."

      Why this analysis was moved to the supplement. Binary overlap statistics of this kind are informative but limited: they collapse a continuous relationship (signal strength versus origin identity) into a single threshold-dependent yes/no call, and are sensitive to peak-calling parameters. Moreover, the list of OriDB-confirmed origins is not itself a list of the origins most likely to be active in a given asynchronous population: most methods can only ever detect origins that actually fired, so a "true" origin that failed to overlap a peak may simply reflect biological non-firing rather than a false negative of the method.

      For these reasons, we chose to complement the overlap-based comparison with an analysis that queries origin correspondence directly against the experimental signal rather than against a binarized peak call. Specifically, we stratified OriDB-confirmed origins into quartiles by annotated origin efficiency (Hawkins et al., 2013) and examined SNS signal enrichment across quartiles (modified Fig. 3C). Both iSNS-seq replicates show a clear, monotonic increase in enrichment signal from the lowest to the highest efficiency quartile. This is the expected behavior for a method that detects origins in proportion to their firing frequency in an asynchronous population. We now state this rationale explicitly in the manuscript text: “To assess the reproducibility of iSNS-seq and tSNS-seq more rigorously than a fixed-threshold peak-overlap comparison allows […] Because this approach evaluates concordance at every possible rank cutoff rather than a single arbitrary threshold, it is not subject to the same sensitivity to near-threshold peaks that limits discrete overlap statistics such as Euler diagrams (Supplementary Figure S9).”

      The title and abstract do not accurately convey the limitations of the improved method and must be rephrased.

      We thank the reviewer for this comment and have revised the abstract accordingly. Specifically, we have (1) clarified that our benchmarking was conducted in S. cerevisiae precisely because it offers a well-defined set of confirmed origins for direct comparison, (2) made explicit that our enrichment claims are relative to traditional SNS-seq rather than absolute, and (3) added language framing this work as a proof-of-concept benchmark, with extension to metazoan systems as a next step rather than a claim already established here. We believe these changes address the concern while accurately reflecting what our data show.

      We have retained the title, as we believe "enhances DNA replication origin detection and reduces non-origin biases" is a comparative claim relative to traditional SNS-seq, which is directly supported by our benchmarking data, and does not imply resolution of broader field-wide inconsistencies in origin mapping.

      One of the manuscript's central mechanistic claims is that residual cellular RNA reanneals to genomic DNA, creating RNA:DNA hybrids that obstruct λ-exonuclease digestion. While the presented data from cells are consistent with this model, the manuscript lacks a direct biochemical demonstration of hybrid-mediated obstruction in a controlled system. The manuscript would benefit from in vitro studies corroborating this conclusion, using the in vitro system established.

      We agree this would be a valuable addition, and in principle the in vitro system established in this study (Fig. 1, 2) is well suited to such a test. However, the laboratory where this wet-lab work was performed has since been closed due to retirement, and we are unable to carry out new biochemical experiments of this kind for this revision.

      We believe the manuscript already provides convergent evidence for RNA:DNA hybrid-mediated obstruction, short of this direct reconstitution. First, our in vivo colocalization analysis shows that tSNS-seq (but not iSNS-seq) signal is enriched at S1-DRIP-seq and S9.6 ChIP-seq sites in an RNase H-sensitive manner, directly implicating RNA:DNA hybrids at the genomic loci where tSNS-seq peaks form. Second, this obstruction signature is not a yeast-specific artifact of our analysis. The same asymmetric, tRNA/snoRNA-anchored peak shape is present in independently generated tSNS-seq datasets from Drosophilaand C. elegans. Furthermore, a recent publication using stranded tSNS-seq in Trypanosoma brucei reports that a large majority (90%) of its peaks map to R-loops (Stanojcic et al. 2026). Finally, we added an analysis comparing R-loops mapped by RIAN-seq in mouse (Li et al. 2025) and two independently generated mouse tSNS-seq datasets (Cayrou et al. 2015 and Pratto et al. 2021) that show strong correlation. Taken together, this is not one experiment pointing to hybrid-mediated blockage, but a repeated, cross-species in vivo-validated pattern observed in tSNS-seq by multiple independent laboratories. The distinct contribution of our yeast experiments is that a well-defined set of confirmed origins allowed us, for the first time, to directly distinguish genuine replication signal from this R-loop-associated background.

      What our data cannot do is isolate the enzyme's behavior on a defined R-loop substrate in vitro, separate from all other cellular context. That is a distinct and narrower question from whether hybrid-mediated obstruction explains the peaks we observe. The latter is what the convergent evidence above addresses. Future work can nail down the exact enzymology and conditions needed to replicate this in vitro.

      Currently, the RNA-dependence of the tRNA/snoRNA-associated obstruction signal is inferred from indirect evidence (UMAP clustering, feature overlap, peak shape) plus a re-analysis of an RNase-treated control from a previously published C. elegans dataset, not from a control generated within the authors' own yeast system, where the paper's primary genome-wide claims are made. Including such controls would be required to provide direct evidence for this central mechanistic claim.

      We appreciate the opportunity to clarify this, as we believe we already have exactly this control within our own yeast dataset. iSNS-seq itself functions as this RNA-dependence control for tSNS-seq: unlike tSNS-seq, the iSNS-seq protocol includes an RNA hydrolysis step (NaOH) performed before λ-exo digestion, removing the RNA that would otherwise be available to reanneal and form obstructing RNA:DNA hybrids. Both tSNS-seq and iSNS-seq are generated from the same size-selected input material from the same yeast cultures, differing specifically in whether RNA is retained (tSNS-seq) or hydrolyzed (iSNS-seq) prior to the λ-exo step (see Fig 3A, which is now improved to clarify this point). The result is a matched, within-system, RNA-present versus RNA-removed comparison, generated entirely in our own hands in budding yeast: tSNS-seq (RNA intact) shows strong signal and peak enrichment at tRNA/snoRNA loci, while iSNS-seq (RNA hydrolyzed) shows essentially none (Fig. 5). This is, in effect, an RNase-equivalent control built directly into our primary experimental design, rather than one requiring a separate treatment arm.

      We have clarified this point explicitly in the Discussion by noting that the tSNS-seq vs. iSNS-seq comparison itself constitutes the within-system RNA-dependence control, complementing the new yeast S1-DRIP-seq/S9.6 ChIP-seq RNase H colocalization analysis (Fig. 6A-C), which independently corroborates this at the level of orthogonal R-loop mapping methods.

      A substantial portion of the in vitro biochemical work (Figure 1B-C, E, Figure 2B-C with BKGmimic) is dedicated to establishing that G4 motifs cause significant λ-exo obstruction in glycine-KOH buffer, and that the Tris-HCl buffer switch resolves this. However, the genome-wide finding that G4 motif overlap is nearly identical between tSNS-seq and iSNS-seq (4-5% in both), with no significant differences in signal over G4 motifs in either dataset, requires clarification/discussion.

      We have clarified this in the expanded Discussion. We note it was somewhat surprising to us as well not to observe more obstruction in tSNS-seq samples. However, our data is consistent with prior human work showing the same λ-exo bias (Foulk et al. 2015), combined with the yeast genome's comparative GC uniformity (new Supplementary Figure S22) and its markedly lower G4 motif density (Wu et al. 2021), and possibly less stable yeast G4 folding (Tran et al. 2011). We believe these factors sufficiently explain why a robust in vitro effect does not produce a differential genome-wide signal in this organism.

      The documented G4 bias was a motivation to find new buffer conditions in the first place, and our further study of this problem highlighted something important for the field even if it doesn’t matter for the yeast genome: RNA primers are less effective at protecting downstream DNA than G4 motifs. Moreover, that observation led us to inventing a way where nascent strands were more strongly protected than G4s by using the 5’-OH after purposeful RNA hydrolysis. Finally, RNA hydrolysis led to the discovery that there is a major RNA-dependent bias in tSNS-seq. Thus, the paper documents the journey and key insights that led to the iSNS-seq protocol, and major findings in this study regarding the tSNS-seq protocol.

      None of the gel-based panels in Figure 1 (B, C, E) or Figure 2D state whether the result shown is from a single experiment or is representative of multiple independent experiments. Please state explicitly, for each gel-based panel, whether it represents a single experiment or is representative of repeated independent experiments (and if the latter, how many).

      We agree with the reviewer that this information was missing and should be stated explicitly. The gel panels in Figures 1B, 1C, 1E, and 2D arise from an extensive experimental search (for buffer conditions and additives) that would increase digestion through G4 motifs while preserving the RNA-DNA chimera, during which these conditions were tested many times over the course of the study. Across this large number of experiments testing different buffers and additives, the same core observations consistently emerged: (1) -exo digests through the RNA-DNA chimera, (2) -exo has difficulty digesting through G4 motifs in Glycine-KOH buffer, but not in Tris-HCl, (3) a 5'-OH end protects DNA from -exo digestion much more effectively than an RNA primer, and (4) RecJf does not digest through a 5' RNA end (or through G4 motifs), but can reduce background DNA levels. The panels shown are representative of these consistently observed outcomes, which are also consistent with the overall findings presented throughout the manuscript. We have added a statement to this effect in the Methods and to each relevant figure legend.

      In the Introduction section, the authors state: "...traditional SNS-seq enriches non-origin DNA that appears to originate from RNA:DNA hybrids due to contaminating RNA, while failing to enrich known replication origins above random expectation." Replace the term "contaminating RNA" with the term "residual cellular RNA", accurately conveying that this is endogenous RNA persisting through the protocol.

      We thank the reviewer raising this point. We corrected the sentence accordingly, which now reads: “[…]traditional SNS-seq enriches non-origin DNA that appears to originate from RNA:DNA hybrids due to residual cellular RNA, while failing to enrich known replication origins above random expectation.”

      The sentence describing that "the RNA-DNA chimera was not digested when 5' phosphorylation by PNK was performed prior to RNA degradation, rather than after the removal of the RNA primer by NaOH" introduces the PNK/NaOH order-of-operations logic before this concept has been explained to the reader, the significance of treatment order is not established until two sections later. A minimal fix would be adding a forward-referencing clause or relocating this result to a later paragraph.

      We agree that the result appeared to be out of place. We have relocated a slightly modified version of this sentence to a later paragraph, just before explaining the Figure 1C experimental logic. The relocated part now reads: “When characterizing λ-exo properties in vitro, we found that the RNA-DNA chimera was not digested when 5' phosphorylation by PNK was performed prior to RNA degradation, rather than after the removal of the RNA primer by NaOH (Supplementary Figure S4D); also confirming that a 5' phosphate is required for λ-exo activity. This result prompted us to further assess how hydrolyzing RNA primers to obtain 5'-OH DNA protects short nascent strand (SNS) DNA from λ-exo digestion compared to 5'-phosphorylated DNA, and to devise an experiment that varied the order of RNA hydrolysis (NaOH) and phosphorylation (T4 polynucleotide kinase, PNK) (Figure 1D).”

      In Figure 2D. (top panel), please state the amount of λ-exo used to perform this experiment in the corresponding figure legend.

      We believe there may be a small mix-up here: Figure 2D shows RecJf digestion throughout (top and bottom panels) and λ-exo was not used in either. However, we agree with the underlying point: the amount of RecJf used in the top panel (timecourse) was not stated in the legend. We have corrected this omission and, as also noted in a related minor comment from Reviewer 1, revised the Figure 2D legend overall for clarity, now stating explicitly that the top panel shows a timecourse of RecJf digestion (with hours indicated) and the bottom panel shows a titration of RecJf units (0–300 U) over a fixed 16 h digestion.

      In Figure 2D. where sonicated, heat-denatured yeast genomic DNA is used as a substrate, please explain how this DNA is prepared and if residual cellular RNA reannealing to complementary genomic sequences would/would not be expected in this prep. Discuss with respect to the RecJf experiments shown.

      The sonicated genomic DNA substrate in Figure 2D (bottom panel) was RNase-treated prior to RecJf digestion, which removes cellular RNA and precludes RNA reannealing to complementary genomic sequences in this specific preparation. We acknowledge that RNase treatment means this experiment does not fully replicate the RNA content of genomic DNA in an actual iSNS-seq reaction, where residual cellular RNA is present. However, we note that in the iSNS-seq workflow, RecJf digestion is used solely as an additional bulk genomic DNA clean-up step prior to λ-exonuclease digestion. Any genomic DNA fragments that resist RecJf digestion due to reannealed residual RNA would still be subject to the downstream PNK, NaOH, and λ-exonuclease steps that carry out the primary enrichment for origin-proximal SNS molecules. We have modifed the Results section to clarify this point: “[…] RecJf significantly reduced the levels of yeast genomic DNA that had been sonicated to the average SNS size range (0.5--2.0 kb), RNase-treated, and denatured by heat (Figure 2D bottom panel). Note that in the iSNS-seq workflow, RecJf digestion serves as an additional bulk gDNA clean-up step upstream of λ-exo digestion. Any genomic DNA species that escape RecJf digestion, including those potentially protected by reannealed residual RNA, remain subject to the subsequent PNK, NaOH (that hydrolyzes residual RNA), and λ-exo steps that establish specificity for SNS molecules.”

      PeerReviewed
    2. EMBOpress 05 Aug 2026

      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

      Summary

      The authors of the paper "Improved short nascent strand sequencing (iSNS-seq) enhances DNA replication origin detection and reduces non-origin biases" investigate the biochemical basis of short nascent strand sequencing (SNS-seq), a widely used method for mapping DNA replication origins genome-wide. SNS-seq relies on λ-exonuclease digestion of genomic DNA, while retaining short nascent strands, which are protected by their 5' RNA primer. Despite its widespread use, SNS-seq has not been rigorously validated in a system with well-characterized replication origins and has often shown limited concordance with alternative origin-mapping approaches. Using a series of in vitro biochemical assays, the authors demonstrate that the key assumptions underlying SNS-seq are not well supported, G4 quadruplexes show strong protection against λ-exo digestion, while 5' RNA primers provide only partial protection. Based on these findings, the authors have developed an improved protocol (iSNS-seq) that achieves noticeably higher in vitro enrichment of nascent DNA than the traditional protocol. The authors then benchmark traditional SNS-seq (tSNS-seq) against iSNS-seq genome-wide in budding yeast (S. cerevisiae), a system with well-curated origin annotations. iSNS-seq appears to outperform tSNS-seq in sensitivity and precision against confirmed origins. The study also shows that tSNS-seq has a very poor performance for origin mapping in budding yeast and identifies a major source of false-positive signals in tSNS-seq, λ-exonuclease obstruction by RNA: DNA hybrids formed between residual cellular RNA and complementary genomic DNA during denaturation. The manuscript convincingly shows that tSNS-seq has important limitations for origin mapping and that iSNS-seq represents a meaningful improvement over the traditional protocol and resolves several of its biases. None-the-less, the signal-to-noise ratio of the improved method appears low and reproducible calling of peaks problematic. Furthermore, the data provided show that iSNS-seq under-performs relative to available alternative methods for nascent strand mapping.

      Major comments

      1. While the method developed (iSNS-seq) appears to improve aspects of the previously used method (tSNS-seq), poor signal-to-noise ratios and reproducibility are major concerns. The signal-to-noise ratio of iSNS-seq, as shown in Figure 3D, appears low. The authors should discuss what practical consequences this has for the applicability of the method, especially in species with less well-defined/efficient origins, and how it affects the reliability of peak calling, and overlap with known origins. Consistently, the overlap of called peaks between biological replicates of iSNS-seq is relatively low (Fig3B). This raises a concern for the usability of the method, the interpretation of the genome-wide data and the quality metrics provided. The authors should discuss these issues.
      2. Related to the above, please explain/discuss the rationale behind retaining all peaks, even the ones observed in only one of the biological replicates, when comparing called peaks to confirmed ORIs. In Figure 3B, clarify what are the percentages depicted.
      3. The title and abstract do not accurately convey the limitations of the improved method and must be rephrased.
      4. One of the manuscript's central mechanistic claims is that residual cellular RNA reanneals to genomic DNA, creating RNA:DNA hybrids that obstruct λ-exonuclease digestion. While the presented data from cells are consistent with this model, the manuscript lacks a direct biochemical demonstration of hybrid-mediated obstruction in a controlled system. The manuscript would benefit from in vitro studies corroborating this conclusion, using the in vitro system established.
      5. Currently, the RNA-dependence of the tRNA/snoRNA-associated obstruction signal is inferred from indirect evidence (UMAP clustering, feature overlap, peak shape) plus a re-analysis of an RNase-treated control from a previously published C. elegans dataset, not from a control generated within the authors' own yeast system, where the paper's primary genome-wide claims are made. Including such controls would be required to provide direct evidence for this central mechanistic claim.
      6. A substantial portion of the in vitro biochemical work (Figure 1B-C, E, Figure 2B-C with BKGmimic) is dedicated to establishing that G4 motifs cause significant λ-exo obstruction in glycine-KOH buffer, and that the Tris-HCl buffer switch resolves this. However, the genome-wide finding that G4 motif overlap is nearly identical between tSNS-seq and iSNS-seq (4-5% in both), with no significant differences in signal over G4 motifs in either dataset, requires clarification/discussion.
      7. None of the gel-based panels in Figure 1 (B, C, E) or Figure 2D state whether the result shown is from a single experiment or is representative of multiple independent experiments. Please state explicitly, for each gel-based panel, whether it represents a single experiment or is representative of repeated independent experiments (and if the latter, how many).

      Minor comments

      1. In the Introduction section, the authors state: "...traditional SNS-seq enriches non-origin DNA that appears to originate from RNA:DNA hybrids due to contaminating RNA, while failing to enrich known replication origins above random expectation." Replace the term "contaminating RNA" with the term "residual cellular RNA", accurately conveying that this is endogenous RNA persisting through the protocol.
      2. The sentence describing that "the RNA-DNA chimera was not digested when 5' phosphorylation by PNK was performed prior to RNA degradation, rather than after the removal of the RNA primer by NaOH" introduces the PNK/NaOH order-of-operations logic before this concept has been explained to the reader, the significance of treatment order is not established until two sections later. A minimal fix would be adding a forward-referencing clause or relocating this result to a later paragraph.
      3. In Figure 2D. (top panel), please state the amount of λ-exo used to perform this experiment in the corresponding figure legend.
      4. In Figure 2D. where sonicated, heat-denatured yeast genomic DNA is used as a substrate, please explain how this DNA is prepared and if residual cellular RNA reannealing to complementary genomic sequences would/would not be expected in this prep. Discuss with respect to the RecJf experiments shown.

      Significance

      This is a carefully executed and methodologically interesting study. Its principal strength is the use of budding yeast as a bench marking system for direct validation of SNS-seq peaks, the demonstration that there is a very small overlap between origins mapped by the traditional method and known origins in this well characterized system and the discovery of a specific, mechanistically coherent, and cross-species-reproducible artifact (RNA:DNA hybrid-mediated λ-exo obstruction) that provides an explanation for the observed low overlap of replication origin mapping by tSNSseq and alternative techniques. These findings are important for interpreting origin mapping studies in different organisms, including metazoa. In addition, the manuscript uses a well-controlled, quantitative in vitro biochemical assays to improve SNS-seq, and analysis in budding yeast shows that indeed the ability of this method to identify origins is improved over the traditional protocol. However, the low signal to noise ratio of the new method and rather low reproducibility between biological replicates, in a system (budding yeast) with well-defined and efficient origins, limits the applicability of the improved method for origin mapping. The improved method appears to be considerably underperforming against other available methods for mapping origins. Overall, this is a carefully executed study that would be of interest to an audience interested in origin mapping techniques in different species.

      Advance

      To our knowledge, this is the first study to benchmark SNS-seq against the well-characterized set of replication origins of yeast, despite the method being used for many years in different species. This is an important and overdue technical advance. Beyond the benchmarking itself, the identification of RNA: DNA hybrid-mediated obstruction as a systematic bias is a mechanistic finding that is notable. The identification of such biases is a conceptual contribution with implications reaching beyond this paper's own experiments, since it calls into question a standard control used throughout the published literature. The advance is primarily methodological and mechanistic, with secondary conceptual implications for ongoing debates over metazoan replication origins, since the paper raises legitimate doubt on whether SNS-seq-derived signals represent genuine origins.

      PeerReviewed
    3. EMBOpress 05 Aug 2026

      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 is very nice paper, which combines meticulous in vitro and in vivo experiments to provide two new insights into a widely used approach - SNS-seq - to map DNA replication origins. The first insight is to detail a key limitation in traditional SNS-seq (tSNS), which leads to very substantial off-target mapping, resulting in predictions of origins that are not origins and, very likely, explaining the poor correspodance of this approach with orthogonal means of origin mapping in metazoans. Second, through carefully executed in vitro analysis, the authors provide a updated form of SNS-seq (iSNS) that more accurately predicts origins in yeast, where mutiple lines of evidence have provided a carefully curated list of origins; as result, the authors provide a new approach to origin mapping that should be widely applicable. I have one major issue and two minor issues with the work.

      Major issue.

      The authors' sugestion that tSNS miscalling of origins may be due to the presence of RNA:DNA hybrids is largely persuasive in theoretical terms but is, surpisingly, untested. The first issue that is unexamined in whether or not RNA:DNA hybrids would survive the two rounds of 95 degree denaturation that are central to both froms of SNS; can the auhtors comment or provide evidence? Second, it is important that the authors test their proposal (Fig.5) of RNA:DNA hybrids being the cause of at least some non-origin tSNS signal by mapping the correspondance of their SNS-seq data with the locations of RNA:DNA hybrids, since there are several forms of such mapping available for S. cervisiae (eg using S9.6 antiserum DRIP-seq, or RNaseH1 ChIP-seq).

      Minor comments.

      1. Fig.S7. Can the authors comments on the poor reproducibility between SNS-seq replicates? Though there isa four-fold increase in concordance between iSNS experments compared with tSNS, 80% of potetial origins are missed; can this be explained? In this regard, is the statment 'Both of the iSNS-seq samples showed signal enrichment around most of the confirmed origins' correct: while Fig.3C gives this impression, Fig.3B appears to diagree.
      2. Given the very nice data in Figs.1 and 2 showing the confounding effect of G4s on tSNS, can the authors comment on why G4s show little overlap with either SNS-seq mapping in Fig.4, and why they saw no increase in tSNS-seq or iSNS-seq signal over G4 motifs in Supplementary Figure S9B? Might this indicate that the in vitro work does not translate well to in vivo mapping?

      Referees cross-commenting

      From my reading of the three reviews, there are three overlapping issues that are brought up and should be addressed:

      1. A requirement to validate the interesting suggestion that RNA:DNA hybrids are a cause of tSNS-seq miscalling of origins; this should be a combination of in vitro tests and colocalisation of tSNS-seq signal and RNA:DNA signal in vivo using available datasets (eg DRIP-seq).
      2. An explanation and/or comment on the low reproducibility and low signal-to-noise ratio of iSNS-seq; specifically, although it improves on tSNS, does it provide accurate origin prediction?
      3. Comment on the lack of in vivo evidence, from available mapping data, for the confounding effect of G4s seen in the in vitro experiments.

      Significance

      This is a meticulously performed study with only some relatively minor issues needing resolved before publication, merely requiring new analysis and not new experiments. The work provides an important clarification on the shortcomings of a widely used strategy to map sites of DNA replication and, moreover, provides an updated and improved approach that should be widely adopted. This work will be of interest to researchers in the broad and fundamental field of DNA replication.

      PeerReviewed
    4. EMBOpress 05 Aug 2026

      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 #1

      Evidence, reproducibility and clarity

      Previous studies have shown that different origin mapping techniques could produce diverging results, introducing debate over whether metazoan origins are discrete or dispersed. Methods like SNS-seq and INI-seq suggested discrete initiation sites, whereas OK-seq, bubble-seq, and EdU/BrdU incorporated origin mapping suggested broad initiation zones with more dispersed initiation sites. Attempts to reconcile the diverged results presuppose that the discrete signals detected by SNS-seq represent bona fide replication intermediates. In this study, the authors set out to investigate the sensitivity and precision of traditional SNS-seq method, using budding yeast as the model organism, given that its replication origins are well known and defined with confidence. They addressed major known issues of lambda-exonuclease digestion in the traditional SNS-seq protocol, such as decreased efficiency of digesting through G4 DNA structure, and limited protection of RNA-primed DNA sequence, and showed that traditional SNS-seq failed to detect known origins. In addition, the authors test improved conditions (iSNS) suggested by the in vitro experiments and demonstrated an enhanced detection rate of known origins in yeast. Finally, the data show that the false positive signal derived from tSNS-Seq are enriched for tRNAs, snRNAs and highly transcribed regions forming RNA:DNA hybrids that overall likely represent regions with secondary structure formation potential that are protected from traditional lambda exonuclease digestion conditions.<br /> Overall, the study is timely and the data presented are convincing and should be published given that traditional SNS-Seq has been used extensively in the past to map the origin landscape of multiple organisms. Therefore, it will be important to reconcile these results in the light of the findings of this paper.

      Major comments:

      • Are the claims and the conclusions supported by the data or do they require additional experiments or analyses to support them?

      The claims and the conclusion are supported by the data. - Please request additional experiments only if they are essential for the conclusions. Alternatively, ask the authors to qualify their claims as preliminary or speculative, or to remove them altogether.

      There are no additional experiments requested. - If you have constructive further reaching suggestions that could significantly improve the study but would open new lines of investigations, please label them as "OPTIONAL".

      There are a few further reaching suggestions listed in the minor comments section. - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated time investment for substantial experiments. - Are the data and the methods presented in such a way that they can be reproduced?

      Yes. They are. - Are the experiments adequately replicated and statistical analysis adequate?

      Yes. They are.

      Minor comments:

      • Specific experimental issues that are easily addressable.

      Additional in vitro experiment using artificial R-loop structures as substrate for lambda-exonuclease could prove the efficacy of the nuclease to digest through R-loop structures. - Are prior studies referenced appropriately?

      Yes. - Are the text and figures clear and accurate?

      Yes. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

      Yes. They are the followings:

      In Fig. 1C, there seems to be a minor increase of lambda-exo activity on R10D30 substrate in the Tris-HCI buffer compared to Glycine-KOH buffer, maybe a quantification using the loading control (D20) would help. In Fig. 2D, lower panel, the digestion time of RecJf at different units were not indicated. In Fig. 3B, since SNS-seq detect fired origins, an overlap of iSNS rep 1 and iSNS rep 2 peaks with confirmed origins from OriDB that are also early and efficient origins may yield a higher percentage of overlap. In Fig. 3D, in addition to showing the tSNS and iSNS data on ChrIV with indicated known origins, showing at the same time the corresponding FORK-seq, OK-seq, and ORC ChIP signal will give a more comprehensive view of the performance of different origin mapping methods. In Fig. 5F, in supporting the model, a comparison of tSNS-seq peak with known budding yeast DRIP-seq datasets would help to see if the tSNS method indeed enrich for RNA:DNA hybrid signals.

      Significance

      This study investigates the sensitivity and precision of traditional SNS-seq methods, questioning the interpretation of existing SNS-seq datasets, which help to reconcile discrepancies among different origin mapping datasets. It also provides a first improved SNS-seq methodology that is tested against bona fide replication origins identified in budding yeast, allowing subsequent improvement of the SNS-seq methodology.

      The following aspects are important:

      • General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed? The strengths in this study are the followings: It provided the first, and much improved SNS-seq dataset in budding yeast. It provided the first-ever assessment of traditional SNS-seq method using bona fide replication origins identified in budding yeast as quality control check, while at the same time established an improved SNS-seq method, again verified by quality control check using budding yeast origins. It demonstrated that traditional SNS-seq dataset may enrich a much lower percentage of replication origins, while having more false positive origins which are potential RNA:DNA hybrids. The aspect that could be improved or developed: More secondary DNA structures could be tested for lambda-exonuclease activity on them.
      • Advance: compare the study to the closest related results in the literature or highlight results reported for the first time to your knowledge; does the study extend the knowledge in the field and in which way? Describe the nature of the advance and the resulting insights (for example: conceptual, technical, clinical, mechanistic, functional,...). The study provides important insight on how to interpret the existing SNS-seq datasets and reconcile discrepancies among them. It provides immediate technical advance in SNS-seq sample preparation which could translate further to conceptual and mechanistic advance.
      • Audience: describe the type of audience ("specialized", "broad", "basic research", "translational/clinical", etc...) that will be interested or influenced by this research; how will this research be used by others; will it be of interest beyond the specific field? The audience will be basic researchers who work on DNA replication, particularly origin mapping.
      • Please define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. Replication origin regulation, RNA:DNA hybrids and Transcription-Replication Conflicts. I feel confident in evaluating all aspects of the paper.
      PeerReviewed
    Visit annotations in context

    Tags

    Annotators

    URL

    biorxiv.org/lookup/doi/10.64898/2025.12.22.696044
  21. aman.ai aman.ai
    Aman's AI Journal • Primers • Agents
    4
    2. rajatmodi62 05 Aug 2026
      Improvement

      one dude can reward hack itself so instead have two dudes one dude does solution other dude critiques it and they continue until the dude critiquiing it is fooled.

      suttons actor-critic model.

    Visit annotations in context

    Annotators

    URL

    aman.ai/primers/ai/agents/
  22. claude.ai claude.ai
    Claude
    1
    1. anon134 05 Aug 2026
      At 30–40 patients: random forest, gradient boosting

      these can capture non-linear interactions between features that logistic regression would miss. For example, maybe the relationship between damping and resonance shift only matters when Q factor is below a certain threshold. Trees find that automatically. The reason we can't do this at 15–20 is that these models have more free parameters and will fit noise in ways that are harder to detect and interpret.

    Visit annotations in context

    Annotators

    URL

    claude.ai/code
  23. projects.dylanwhitaker.co.uk projects.dylanwhitaker.co.uk
    1  Manuscript – The problem with the OME metric
    2
    2. dylanwhitaker 05 Aug 2026
      reported difference in opioid burden (red cross) compared to the de-novo calculated difference

      There is some difficulty in estimating the group means as show in the table above. Part of this reason is there is a lot of assumptions made. I have tried to apply blanket rules such as conversion values assume IV route, etc.

      I feel the difficult in re-calculating the study results perhaps weakens this section as it makes the de-novo estimates (green cross and orange whisker) look far off (such as for Hall 2025)

    Visit annotations in context

    Annotators

    URL

    projects.dylanwhitaker.co.uk/total-opioid-burden-metrics/manuscript
  24. newsletter.pragmaticengineer.com newsletter.pragmaticengineer.com
    Slow down to speed up: so much has changed in 6 months’ time
    1
    Visit annotations in context

    Annotators

    URL

    newsletter.pragmaticengineer.com/p/slow-down-to-speed-up
  25. laughing-bassoon-7p6pm2g.pages.github.io laughing-bassoon-7p6pm2g.pages.github.io
    Design Suggestion: DaaS Model Raster Export API - R&D Knowledge Base
    1
    Visit annotations in context

    Annotators

    URL

    laughing-bassoon-7p6pm2g.pages.github.io/data/drs/model-raster-export-api/
  26. localhost:8642 localhost:8642
    nsclc_v6_risk_report_external.md
    1
    1. Kang30 05 Aug 2026
      图 t18：风险 c-index forest（含 95% bootstrap CI 与置换 p，0.5 参考线）。CellPA 5-fold OOF c = 0.70（perm p = 0.011） 与 CellPA LOPO c = 0.68（perm p = 0.016） 两个评估协议下均显著；作为对照，仅用细胞类型成分、不含空间信息的 composition-logistic c = 0.551（perm p = 0.515，不显著）。即两种协议下 CellPA 的序数信号显著，而单靠成分不显著。

      我想知道这里的置信区间到底是5fold/LOPO 的范围还是bootstrap的抽样范围， 具体的计算可以一步一步演示一下吗？

    Visit annotations in context

    Annotators

    URL

    localhost:8642/.claude/worktrees/catagrate_3/claudedocs/nsclc_v6_risk/nsclc_v6_risk_report_external.md
  27. callyzer.co callyzer.co
    How to Spot Low-Quality Leads in 10 Seconds
    2
    Visit annotations in context

    Tags

    Annotators

    URL

    callyzer.co/blog/handling-festive-season-sales-dips-remotely/
  28. westernsydney.pressbooks.pub westernsydney.pressbooks.pub
    Nervous system
    10
    1. Lory 05 Aug 2026
      Figure 5.12. Comparison of a) Myelinated and b) Unmyelinated (or Demyelinated) Neurons © ConnorWrightUni is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate except need to put version number (4.0)

    2. Lory 05 Aug 2026
      Figure 5.10. Diagram of a Typical Neuron © US National Cancer Institute's Surveillance, Epidemiology and End Results (SEER) is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 5.11. Neuron_Classification © BruceBlaus is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate except need to put version number (3.0)

    3. Lory 05 Aug 2026
      Figure 5.9. Differences in the Parasympathetic Nervous System Between Predator and Prey Species. © Sunshineconnelly is licensed under a CC BY-SA (Attribution ShareAlike) license

      CC BY 3.0 as this is a reproduced image.

    4. Lory 05 Aug 2026
      Figure 5.8. Diagram Summarising the Peripheral Nervous System © Christinelmiller is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate except need to put version number (3.0)

    5. Lory 05 Aug 2026
      Figure 5.7. Diagram of a Horse Showing the Key Structures in the Peripheral Nervous System © Rlawson is licensed under a CC BY-ND (Attribution NoDerivatives)

      CC BY-SA 3.0, as this is a reproduced image.

    6. Lory 05 Aug 2026
      Figure 5.6. Diagram of a Reflex Arc © Ruth Lawson Otago Polytechnic is licensed under a CC BY-SA (Attribution ShareAlike) license

      Creative Commons Attribution 3.0 , as it is a reproduced image.

    7. Lory 05 Aug 2026
      Figure 5.5. Cross Section of Spinal Cord © OpenStax is licensed under a CC BY-SA (Attribution ShareAlike) license

      Creative Commons Attribution 4.0 , as this is a reproduced image.

    8. Lory 05 Aug 2026
      Figure 5.4. Diagram of a Primate Brain Indicating the Location of the Four Lobes © Camazine is licensed under a Public Domain license

      CC BY 3.0. The wikimedia version (which is used on this book( has been subsequently licenced as a CC BY 3.0. as the 1st original image is based on a public domain (Downstream effect of the licence).

    9. Lory 05 Aug 2026
      Figure 5.3. Anterior View of a Sheep Brain Dissected Midsagittally Along the Longitudinal Fissure © aaronbflickr is licensed under a CC BY (Attribution) license

      Creative Commons Attribution 2.0 Generic

    10. Lory 05 Aug 2026
      Figure 5.1. Diagram Showing the Three Protective Layers of the Meninges © OpenStax is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 5.2. Diagram Showing the Key Structures of the Primate Brain © Belomaad is licensed under a CC BY-SA (Attribution ShareAlike) license

      don't forget to put the CC version number please, which is 4.0

    Visit annotations in context

    Annotators

    URL

    westernsydney.pressbooks.pub/anatomyausspecies/chapter/nervous/
  29. indy.peergos.me indy.peergos.me
    /Wiki/Pad/b/about.html
    3
    3. indyweb 05 Aug 2026
      small chunks

      these chunks, unit of externalization of intuitive thoughts that form - deeply interconnected via intentionally transparent

      self-

      • creating
      • revealing
      • organizing
      • structure formulations

      forming emergent networks

      that are

      • permanent
      • evergreen
      • interplanetary

      not just linked data but - externalization of individual human intellect

      constructed to form networks connecting - people - individuals, communities and their colaboratories - their ideas

      both about their experiences, understanding and intents in forms that make them amenable to be - interpreted - procesed - recalled

      and all the work that is embodied in ther is re - sumable - called - visited - factored

      thorugh symmathetic conversations and co-laboration

      as intended rendered explicit

    Visit annotations in context

    Annotators

    URL

    indy.peergos.me/Wiki/Pad/b/about.html
  30. wenku-strategy-ppt-sdpic.bj.bcebos.com wenku-strategy-ppt-sdpic.bj.bcebos.com
    从辉煌到屈辱——中国古代水利与近代条约考点导航 - 学习笔记
    1
    1. skcs123 05 Aug 2026
      亚罗号事件

      看到亚罗号 ➡️ 想到亚瑟王/海上霸主 ➡️ 英国。 看到马神甫 ➡️ 想到马克龙/传教士 ➡️ 法国。

    Visit annotations in context

    Annotators

    URL

    wenku-strategy-ppt-sdpic.bj.bcebos.com/simplelearn/test20260706/log_id_4703702259310641804/chapter_0_for_share.html
  31. westernsydney.pressbooks.pub westernsydney.pressbooks.pub
    Skeletal system (MB and HS)
    17
    1. Lory 05 Aug 2026
      Figure 4.21. Koala (Phascolarctos cinereus) Distal Arm Showing the Hinge Joint at the Elbow © H. Stannard is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 4.22. Koala (Phascolarctos cinereus) Skull and Vertebrae Showing an an Example of a Pivot Joint © H. Stannard is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 4.23. Distal Limbs of the Ox (Left) and Horse (Right) Showing Different Types of Synovial Joints © H. Stannard is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 4.24. Koala (Phascolarctos cinereus) Ball and Socket Joint at the Hip © H. Stannard

      If original image, then accurate

    2. Lory 05 Aug 2026
      Figure 4.19. Synovial Joints Are the Only Joints That Have a Space or Synovial Cavity in the Joint © C. Molnar, and J. Gair is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 4.20. Different Types of Joints Allow Different Types of Movement © C. Molnar, and J. Gair is licensed under a CC BY-SA (Attribution ShareAlike) license

      can we embed the actual link of the image from the BC OER textbook? or is too much of a hassle?

    3. Lory 05 Aug 2026
      Figure 4.18. Eastern Grey Kangaroo (Macropus giganteus) Skull Showing Sutures (Fibrous Joints Found Only in the Skull) © H. Stannard

      original image?If it is, then accurate

    4. Lory 05 Aug 2026
      CC BY-ND (Attribution NoDerivatives) license

      is this under CC by ND or CC BY 4.0? as Servier Medical Art is licensed under CC BY 4.0

    5. Lory 05 Aug 2026
      Figure 4.13. The Patella of the Knee is an Example of a Sesamoid Bone © C. Molnar, and J. Gair is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 4.14. Compact Bone Tissue Consists of Osteons That are Aligned Parallel to the Long Axis of the Bone, and the Haversian Canal That Contains the Bone’s Blood Vessels and Nerve Fibres © C. Molnar, and J. Gair is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 4.15. Trabeculae in Spongy Bone are Arranged Such That One Side of the Bone Bears Tension and the Other Withstands Compression © C. Molnar, and J. Gair is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 4.16. Endochondral Ossification is the Process of Bone Development From Hyaline Cartilage © C. Molnar, and J. Gair is licensed under a CC BY-SA (Attribution ShareAlike) license

      see above comment. Also make sure that the CC version number is listed.

    6. Lory 05 Aug 2026
      Figure 4.12. Diagram of the Long Bone © C. Molnar, and J. Gair is licensed under a CC BY-SA (Attribution ShareAlike) license

      see above comment

    7. Lory 05 Aug 2026
      Figure 4.11. Diagram Showing Different Types of Bones: Flat, Irregular, Long, Short, and Sesamoid

      can we embed the actual link of the image from the BC OER textbook? or is too much of a hassle?

    8. Lory 05 Aug 2026
      Figure 4.10. Bones of the Pelvic Limb of Eastern Grey Kangaroo (Macropus giganteus) © H. Hillewaert is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate, just version number needed

    9. Lory 05 Aug 2026
      Figure 4.9. Bones of the Carpal Region of the Orangutan, Dog, Swine, Cattle, Tapir and Horse (Left to Right) © Meyers Konversionlexikon 1888 is licensed under a Public Domain license

      accurate

    10. Lory 05 Aug 2026
      Figure 4.8. Anatomy of the Forelimb of the Human, Bird and Bat, Showing Variation in the Humerus, Radius, Ulna, Carpals, Metacarpals and Phalanges © Arizona Board of Regents/ASU Ask A Biologist adapted by H. Stannard is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate adapted attributon. need version no

    11. Lory 05 Aug 2026
      Figure 4.6. The Vertebral Column Consists of Cervical, Thoracic, Lumbar, Sacral and Caudal (Coccygeal – in Primates) Vertebrae © Sunshineconnelly is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate. pls put version number

    12. Lory 05 Aug 2026
      Figure 4.7. Bird Skeleton Showing the Keel Bone (Coloured Blue)

      accurate attribution for adapted image. just needs the version number of license please

    16. Lory 05 Aug 2026
      Figure 4.2. Muscles Attached to the Exoskeleton of the Halloween Crab (Gecarcinus quadratus) Allow it to Move © Bhny is licensed under a Public Domain license

      accurate

    17. Lory 05 Aug 2026
      Figure 4.1. The Skeleton of the Red-Knobbed Sea Star (Protoreaster linckii) is an Example of a Hydrostatic Skeleton © Amada44 is licensed under a CC BY (Attribution) license

      version number

    Visit annotations in context

    Annotators

    URL

    westernsydney.pressbooks.pub/anatomyausspecies/chapter/skeletal/
  32. wenku-strategy-ppt-sdpic.bj.bcebos.com wenku-strategy-ppt-sdpic.bj.bcebos.com
    近代中国救亡图存与古代文学思潮的深度逻辑重构 - 学习笔记
    3
    Visit annotations in context

    Annotators

    URL

    wenku-strategy-ppt-sdpic.bj.bcebos.com/simplelearn/test20260706/log_id_4808192574051377756/chapter_0_for_share.html
  33. www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
    Exome Sequencing of 47 Chinese Families with Cone-Rod Dystrophy: Mutations in 25 Known Causative Genes
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    ncbi.nlm.nih.gov/pmc/articles/PMC3679152/
  34. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Photorefractive keratectomy in a patient with Stargardt disease: Case report
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC12093004/
  35. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov
    Protein interactions and disease phenotypes in the ABC transporter superfamily
    1
    1. Vibhor 05 Aug 2026
      In humans, clinical studies have implicated mutations in 19 of the 48 known ABC transporters in diseases such as cystic fibrosis and adrenoleukodystrophy.

      Annotating here since the article is a PDF.

      This variant is mentioned in table 2 as a "disease associated mutation", but only as being present in the NBD/NBD interface. No further details are provided.

      NoEvidence ClinVarID: 99455 CA227399 automated_hgnc:34 automated_hgnc_source:CAID ClinGen ABCA4 Annotations
    Visit annotations in context

    Tags

    Annotators

    URL

    pubmed.ncbi.nlm.nih.gov/17990484/
  36. oce-ovid-com.libproxy.lib.unc.edu oce-ovid-com.libproxy.lib.unc.edu
    STARGARDT DISEASE: Beyond Flecks and Atrophy
    1
    1. Vibhor 05 Aug 2026
      Patients older than 60 years or with ocular comorbidities such as diabetic retinopathy, uveitis, or glaucoma were excluded. From the remaining list, subjects for whom high-resolution SD-OCT imaging was available were selected. A review of the patient imaging and medical records was performed to identify those who received a clinical diagnosis of Stargardt macular dystrophy based on their clinical phenotype, including color fundus, infrared, FAF, and fluorescein angiography images and electroretinographic findings. 12

      Case#: P3, male, 16yo at report, 9yo at dx, US with Indian ethnicity

      DiseaseAssertion: Stargardt

      FamilyInfo: n/a

      CasePresentingHPOs:

      CaseHPOFreeText: BCVA (logMAR)= OD=20/160 (0.90), OS=20/125 (0.80)

      CaseNotHPOs:

      CaseNotHPOFreeText: ocular comorbidities such as diabetic retinopathy, uveitis, or glaucoma

      GenotypingMethod: "genetic testing"

      PreviouslyPublished: n/a

      Variant: c.2453G>A; c.4532C>A (p.Pro1511His)

      ClinVar: 99135

      CAID: CA227000

      SupplementalData: table 1

      CA227000 ClinVarID: 99135 CaseInfo Individual automated_hgnc:34 automated_hgnc_source:CAID ClinGen ABCA4 Annotations
    Visit annotations in context

    Tags

    Annotators

    URL

    oce-ovid-com.libproxy.lib.unc.edu/article/00006982-201712000-00019/HTML
  37. www.researchgate.net www.researchgate.net
    Genetic characterization of 1210 Japanese pedigrees with inherited retinal diseases by whole‐exome sequencing
    1
    1. Vibhor 05 Aug 2026
      Finally, we examined whether the phenotype‐associated known/candidate pathogenic variants could explain the patient's disease, andif the MAF in population‐matched control data (8.3kJPN) was relatedto disease prevalence. Patients were classified as “Solved” if theirgenotype was consistent with their clinical phenotype. Patients wereclassified as “Partially solved” when a heterozygous known/candidatepathogenic variant was detected in a recessive allele, but without anadditional variant in trans. Patients were categorized as “Unsolved” iftheir genotypes exhibited either no candidate pathogenic variants ormultiple heterozygous pathogenic variants that did not explain thephenotype clearly. Variants annotated as causal for solved patients arelisted in Supporting Information: Table S2. Novel variants identified inthis study are listed in the second sheet of Table S2. SupportingInformation: Table S3 shows the phenotypes and genotypes of solvedpatients.

      This variant is listed in supplementary tables S2 and S3. Proband KN-187 is a "solved" patient, meaning the phenotype matches the genotype. Compound heterozygous (c.6290C>T p.P2097L; c.6445C>T p.R2149X) male with Stargardt disease- all that is provided.

      SupplementalTable CaseInfo Individual CA341277621 ClinVarID: 1393961 CA227404 ClinVarID: 99460 automated_hgnc:34 automated_hgnc_source:CAID ClinGen ABCA4 Annotations
    Visit annotations in context

    Tags

    Annotators

    URL

    researchgate.net/profile/Kumiko-Kato-2/publication/364751657_Genetic_characterization_of_1210_Japanese_pedigrees_with_inherited_retinal_diseases_by_whole-exome_sequencing/links/6369a1c0431b1f53007b7e46/Genetic-characterization-of-1-210-Japanese-pedigrees-with-inherited-retinal-diseases-by-whole-exome-sequencing.pdf
  38. www.ajo.com www.ajo.com
    Genotype–Phenotype Correlations in a Spanish Cohort of 506 Families With Biallelic ABCA4 Pathogenic Variants
    1
    1. Vibhor 05 Aug 2026
      STGD1 was determined according to initial symptoms of VA loss; fundus images showing orange-yellow flecks in the retina, a beaten-bronze appearance; and normal or cone-altered ffERG results

      Case#: MD-0790, Spanish

      DiseaseAssertion: STGD1

      FamilyInfo: n/a

      CasePresentingHPOs:

      CaseHPOFreeText: "STGD1 was determined according to initial symptoms of VA loss; fundus images showing orange-yellow flecks in the retina, a beaten-bronze appearance; and normal or cone-altered ffERG results"

      CaseNotHPOs:

      CaseNotHPOFreeText:

      GenotypingMethod: Index cases were studied by different next-generation sequencing (NGS) strategies, including targeted gene panels, clinical exome, and/or whole-exome sequencing

      PreviouslyPublished: n/a

      Variant: c.1715G>C p.(Arg572Pro); c.4918C>T p.(Arg1640Trp)

      ClinVar: 99073

      CAID: CA226919

      SupplementalData: Table S1

      CaseInfo Individual SupplementalTable ClinVarID:99073 CAID:CA226919 automated_hgnc:34 automated_hgnc_source:CAID ClinGen ABCA4 Annotations
    Visit annotations in context

    Tags

    Annotators

    URL

    ajo.com/article/S0002-9394(20)30323-8/fulltext
  39. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Focal choroidal excavation in Stargardt’s dystrophy
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC7449287/
  40. www.ajo.com www.ajo.com
    mmc1.pdf
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    ajo.com/cms/10.1016/j.ajo.2020.06.027/attachment/2c3c8baa-ae3a-4cb6-a3ad-ae429569a986/mmc1.pdf
  41. www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
    Personalized genetic counseling for Stargardt disease: Offspring risk estimates based on variant severity
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    ncbi.nlm.nih.gov/pmc/articles/PMC8948157/
  42. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov
    A YAC contig encompassing the recessive Stargardt disease gene (STGD) on chromosome 1p
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pubmed.ncbi.nlm.nih.gov/8533764/
  43. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Subretinal Fibrosis in Stargardt's Disease with Fundus Flavimaculatus and ABCA4 Gene Mutation
    1
    1. Vibhor 05 Aug 2026
      Case 3

      Case#: Case 3, Sex: Male, Age:21

      DiseaseAssertion: STGD

      FamilyInfo: n/a

      CasePresentingHPOs:

      CaseHPOFreeText: Text mentions BCVA of 20/200 in both eyes. Pigmentary changes in macula associated with flecks, small inferior juxta-papillar area of subretinal fibrosis in right eye, left eye legion localized in posterior pole macula temporally. Instable fixation in right eye. Low retinal mean sensitivity in both eyes.

      CaseNotHPOs:n/a

      CaseNotHPOFreeText: Healthy ocular adnexa and specular transparent and 'in situ' lens. Visual acuity stable. Stable fixation in left eye.

      Genotyping Method: genetic analysis

      PreviouslyPublished: n/a

      Variant: Variant is a heterozygous mutation given as NM_000350.3(ABCA4):c.3212C>T (p.Ser1071Leu) / NM_000350.3(ABCA4):c.667A>C (p.Lys223Gln) / NM_000350.3(ABCA4):c.3607G>A (p.Gly1203Arg)

      ClinVar: Variation ID: 99208 / Variation ID: 845426/ Variation ID: 417989

      SupplementalData: n/a

      MultipleGeneVariants "Gene:ABCA4" HGNC:34 PMID:3341817 ClinVarID:99208 Zygosity:Heterozygous MacularFlecks DiseaseEntity:STGD1 automated_hgnc:34 automated_hgnc_source:hgnc_tag ClinGen ABCA4 Annotations
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC3551412/
  44. www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
    Targeted next-generation sequencing as a comprehensive test for Mendelian diseases: a cohort diagnostic study
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    ncbi.nlm.nih.gov/pmc/articles/PMC6076228/
  45. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov
    Expanding the Clinical and Molecular Heterogeneity of Nonsyndromic Inherited Retinal Dystrophies
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pubmed.ncbi.nlm.nih.gov/32036094/
  46. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Clinical and genetic investigations of three Moroccan families with retinitis pigmentosa phenotypes
    1
    1. Vibhor 05 Aug 2026
      Case 3: RP3.03

      Case#: RP3.03, 23yo, 21yo on set, Moroccan

      DiseaseAssertion: Retinitis Pigmentosa (RP19)

      FamilyInfo: Born into a consanguineous family, parents are unaffected, has five unaffected siblings

      CasePresentingHPOs: HP:0000505, HP:0007675, HP:0001133, HP:0007994, HP:0007843, HP:0000510, HP:0000580, HP:0007703

      CaseHPOFreeText: Abnormal epiretinal membrane formation, Altered ERG traces, rod and cone photoreceptor dysfunctions, hyper fuorescence ring surrounding macula and peripheral retina, absence of cystic spaces

      CaseNotHPOs: HP:0000551

      CaseNotHPOFreeText: Central vision loss

      Genotyping Method: Genomic DNA was extracted using QIAamp DND Blood Mini Kit, DNA underwent WES by BGI Tech Solutions, DNA was captured by MGIEasy Exome Capture V4 Probe Set, then Alligned using the Burrows-Wheeler Aligner and HaplotypeCaller of GAWK

      PreviouslyPublished: CRB1, PDE6B

      Variant: c.5908C>T, c.6148G>C

      ClinVar: 7892, 7884

      SupplementalData: Clinical data (table 1, figure 5), Genetic analysis (table 2), Patient Pedigree (figure 1.)

      Gene:ABCA4 HGNC:34 InheritancePattern:AutosomalRecessive DiseaseEntity:RP19 AlleleOrigin:Somatic Zygosity:CompoundHeterozygous MultipleGeneVariants FundusAutofluorescence NightBlindness DecreasedERGResponses PigmentaryRetinopathyAttenuatedVessels DecreasedPeripheralVision automated_hgnc:34 automated_hgnc_source:hgnc_tag ClinGen ABCA4 Annotations
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC7883928/
  47. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Novel mutations in c2orf71 causing an early onset form of cone-rod dystrophy: A molecular diagnosis after 20 years of clinical follow-up
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC6887784/
  48. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Expansion of the ABCA4-Associated Retinopathy Spectrum: Severe Variants Can be Associated With Early-Onset Severe Retinal Dystrophy
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC12147048/
  49. www.ncbi.nlm.nih.gov www.ncbi.nlm.nih.gov
    mRNA trans-splicing dual AAV vectors for (epi)genome editing and gene therapy
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    ncbi.nlm.nih.gov/pmc/articles/PMC10584818/
  50. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov
    Full-field ERG as a predictor of the natural course of ABCA4-associated retinal degenerations
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pmc.ncbi.nlm.nih.gov/articles/PMC5757858/
  51. www-sciencedirect-com.libproxy.lib.unc.edu www-sciencedirect-com.libproxy.lib.unc.edu
    Molecular genetics of cone-rod dystrophy in Chinese patients: New data from 61 probands and mutation overview of 163 probands
    1
    1. Vibhor 05 Aug 2026
      ABCA4ARc.[1957C > T];[4605insT]WESHuang et al., 2013cHuang et al., 2013c, Rivera et al., 2000

      Case#: QT959, Chinese

      DiseaseAssertion: Cone-rod dystrophy

      FamilyInfo: no pedigree provided for this family in this paper

      CasePresentingHPOs:

      CaseHPOFreeText:

      CaseNotHPOs:

      CaseNotHPOFreeText:

      PreviouslyPublished: 23776498-more phenotype information available there

      Variant: c.[1957C > T];[4605insT] on WES

      ClinVar: n/a

      CAID: CA645372205

      SupplementalData: n/a

      CA645372205 CaseInfo Individual PreviouslyPublished automated_hgnc:34 automated_hgnc_source:CAID ClinGen ABCA4 Annotations
    Visit annotations in context

    Tags

    Annotators

    URL

    www-sciencedirect-com.libproxy.lib.unc.edu/science/article/pii/S0014483516300458
  52. pubmed.ncbi.nlm.nih.gov pubmed.ncbi.nlm.nih.gov
    Complex inheritance of ABCR mutations in Stargardt disease: linkage disequilibrium, complex alleles, and pseudodominance
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    pubmed.ncbi.nlm.nih.gov/10746567/
  53. medium.com medium.com
    Cold Calling In India: Best Practices For Sales Teams
    1
    Visit annotations in context

    Tags

    Annotators

    URL

    medium.com/@callyzer/cold-calling-in-india-best-practices-for-sales-teams-9931bff0aefb
  54. www.biorxiv.org www.biorxiv.org
    Mechanically Compliant, Precision-Porous Brain Implants Reduce the Foreign Body Reaction and Guide Regeneration
    1
    Visit annotations in context

    Annotators

    URL

    biorxiv.org/content/10.64898/2026.03.24.713981v4
  55. westernsydney.pressbooks.pub westernsydney.pressbooks.pub
    Growth and Maturity (JO)
    9
    1. Lory 05 Aug 2026
      Figure 3.5. Formation of Body Plan From Three Layered Gastrula © K. V. Kardong adapted by J. Green-Barber is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 3.6. Comparison Between Weight of Newborn Marsupial and Weight of Mother © H. Tyndale-Biscoe adapted by J. Green-Barber is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 3.7. Stages of Marsupial Growth and Development © H. Tindale-Boscoe adapted by J. Green-Barber is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 3.8. Postnatal Growth © J. Old is licensed under a CC BY-SA (Attribution ShareAlike) licenseFigure 3.9. Measuring Wildlife Species © J. Cole, and J. Woinarski adapted by J. Green-Barber is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate

    2. Lory 05 Aug 2026
      Figure 3.15. Comparison of Muscle and Bone Weight in Dairy and Beef Cattle © M. Berg, and R. M. Butterfield adapted by J. Old is licensed under a CC BY-SA (Attribution ShareAlike) license

      accurate. please put CC BY-SA 4.0 (the number)

    3. Lory 05 Aug 2026
      Comparison of Monotreme, Marsupial and Eutherian Development From Zygote to Blastula © K. V. Kardong adapted by J. Green-Barber i

      Link of the original image?

    4. Lory 05 Aug 2026
      Figure 3.3 Images of Two Fish Species That Vary in the Length of Their Senescent Period © USFWSmidwest, Bureau of Land Management

      broken link

    5. Lory 05 Aug 2026
      Figure 3.14. Size Comparison of Dogs, Chihuahua Mix Compared to a Great Dane © Elf is licensed under a CC BY-SA (Attribution ShareAlike)

      Creative Commons Attribution-Share Alike 3.0

    6. Lory 05 Aug 2026
      Figure 3.13. Male Ibex Showing Allometric Growth of Horns © N. Farbiash is licensed under a CC BY-SA (Attribution ShareAlike) license

      Creative Commons Attribution 2.5 Generic

    8. Lory 05 Aug 2026
      Figure 3.11. Red Snapper (Lutjanus campechanus) Otolith © U.S. National Oceanic and Atmospheric Administration is licensed under a Public Domain license

      accurate

    9. Lory 05 Aug 2026
      Figure 3.5. Formation of Body Plan From Three Layered Gastrula © K. V. Kardong adapted by J. Green-Barber is licensed under a CC BY-SA (Attribution ShareAlike) license

      see above comment

    Visit annotations in context

    Annotators

    URL

    westernsydney.pressbooks.pub/anatomyausspecies/chapter/growth-and-maturity/
  56. 019f8ff9-72cd-78ff-b5bc-dca023e02b01-8080.eur-1.aiven.app 019f8ff9-72cd-78ff-b5bc-dca023e02b01-8080.eur-1.aiven.app
    Migration assessment
    1
    Visit annotations in context

    Annotators

    URL

    019f8ff9-72cd-78ff-b5bc-dca023e02b01-8080.eur-1.aiven.app/latest/migration-assistant/migration-phases/assessment/
  57. neuma.utalca.cl neuma.utalca.cl
    164-Texto del artículo-321-1-10-20211004.pdf
    2
    1. Quanto 05 Aug 2026
      la música como una práctica discursiva de género

      aunque no se haga a propósito, como aporta Citron (1993) apuntando que la música, sin las etiquetas, es sólo música, la música significa algo siempre en algún ámbito, puesto que mirada desde el contexto, como plantea Kermer (1985) y McClay (1991), estará sugeto a algún rol social, que sea una expresión económicoa y cultural del pensamiento popular del momento.

    Visit annotations in context

    Annotators

    URL

    neuma.utalca.cl/index.php/neuma/article/download/164/163/321
  58. automaton-media.com automaton-media.com
    428: Shibuya Scramble creator says visual novel games have reached a bit of an evolutionary “dead end,” but certain masterpieces have created potential for breakthroughs - AUTOMATON WEST
    1
    1. nafnlj 05 Aug 2026
      For example, a character that might have stood up for you in the first loop could be wanting to kill you in the second one. “The feeling of going through a world in which the law of cause and effect doesn’t matter – that is the core idea of a roguelike adventure game, and it’s a brand-new territory that most adventure games until now haven’t stepped into yet.”

      Jiro Ishii explaining how a "roguelike adventure" works as a visual novel.

      Visual Novel Design Visual Novels
    Visit annotations in context

    Tags

    Annotators

    URL

    automaton-media.com/en/news/482-shibuya-scramble-creator-says-visual-novel-games-have-reached-a-bit-of-an-evolutionary-dead-end-but-certain-masterpieces-have-created-potential-for-breakthroughs/