DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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DOI: 10.1002/cne.23690

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What is this?

DOI: 10.1002/cne.23684

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What is this?

DOI: 10.1002/cne.23687

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What is this?

DOI: 10.1002/cne.23687

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DOI: 10.1002/cne.23687

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DOI: 10.1002/cne.23687

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What is this?

DOI: 10.1002/cne.23687

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23683

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What is this?

DOI: 10.1002/cne.23676

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What is this?

DOI: 10.1002/cne.23672

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What is this?

DOI: 10.1002/cne.23672

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DOI: 10.1002/cne.23672

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DOI: 10.1002/cne.23672

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DOI: 10.1002/cne.23672

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What is this?

DOI: 10.1002/cne.23672

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What is this?

DOI: 10.1002/cne.23672

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What is this?

DOI: 10.1002/cne.23667

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What is this?

DOI: 10.1002/cne.23667

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What is this?

DOI: 10.1002/cne.23667

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What is this?

DOI: 10.1002/cne.23667

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What is this?

DOI: 10.1002/cne.23667

Resource: AB_10123643

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What is this?

DOI: 10.1002/cne.23667

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What is this?

DOI: 10.1002/cne.23667

Resource: (Swant Cat# 235, RRID:AB_10000343)

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What is this?

DOI: 10.1002/cne.23667

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What is this?

DOI: 10.1002/cne.23667

Resource: (Swant Cat# 300, RRID:AB_10000347)

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What is this?

DOI: 10.1002/cne.23668

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What is this?

DOI: 10.1002/cne.23668

Resource: AB_10562368

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What is this?

DOI: 10.1002/cne.23668

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What is this?

DOI: 10.1002/cne.23668

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What is this?

DOI: 10.1002/cne.23668

Resource: (Millipore Cat# MAB377, RRID:AB_2298772)

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What is this?

DOI: 10.1002/cne.23668

Resource: GraphPad Prism (RRID:SCR_002798)

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What is this?

DOI: 10.1002/cne.23668

Resource: (Santa Cruz Biotechnology Cat# sc-2004, RRID:AB_631746)

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What is this?

DOI: 10.1002/cne.23668

Resource: (Novus Cat# 26630002, RRID:AB_2092129)

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What is this?

DOI: 10.1002/cne.23668

Resource: (RGD Cat# 1302714,RRID:RGD_1302714)

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SciCrunch record: RRID:RGD_1302714

What is this?

DOI: 10.1002/cne.23668

Resource: (RGD Cat# 2312511,RRID:RGD_2312511)

Curator: @jcabotaj

SciCrunch record: RRID:RGD_2312511

What is this?

DOI: 10.1002/cne.23664

Resource: Fiji (RRID:SCR_002285)

Curator: @jcabotaj

SciCrunch record: RRID:SCR_002285

What is this?

DOI: 10.1002/cne.23664

Resource: (RGD Cat# 737929,RRID:RGD_737929)

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SciCrunch record: RRID:RGD_737929

What is this?

DOI: 10.1002/cne.23664

Resource: (ZIRC Cat# ZL1,RRID:ZIRC_ZL1)

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SciCrunch record: RRID:ZIRC_ZL1

What is this?

DOI: 10.1002/cne.23664

Resource: (IMSR Cat# JAX_000664,RRID:IMSR_JAX:000664)

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What is this?

DOI: 10.1002/cne.23665

Resource: (FUJIFILM Wako Pure Chemical Corporation Cat# 544-10001-WAKO, RRID:AB_664696)

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What is this?

DOI: 10.1002/cne.23665

Resource: (Abcam Cat# ab41489, RRID:AB_727049)

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What is this?

DOI: 10.1002/cne.23665

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What is this?

DOI: 10.1002/cne.23665

Resource: ImageJ (RRID:SCR_003070)

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What is this?

DOI: 10.1002/cne.23665

Resource: (Thermo Fisher Scientific Cat# S-21374, RRID:AB_2336066)

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SciCrunch record: RRID:AB_2336066

What is this?

DOI: 10.1002/cne.23665

Resource: (Abcam Cat# ab6876, RRID:AB_954958)

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What is this?

DOI: 10.1002/cne.23665

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What is this?

DOI: 10.1002/cne.23665

Resource: AB_10564074

Curator: @jcabotaj

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What is this?

DOI: 10.1002/cne.23665

Resource: AB_10561706

Curator: @jcabotaj

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What is this?

DOI: 10.1113/jphysiol.2014.281014

Resource: ImageJ (RRID:SCR_003070)

Curator: @gabimpine

SciCrunch record: RRID:SCR_003070

What is this?

DOI: 10.1113/jphysiol.2014.281014

Resource: (Thermo Fisher Scientific Cat# A10042, RRID:AB_2534017)

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SciCrunch record: RRID:AB_11180183

What is this?

DOI: 10.1113/jphysiol.2014.281014

Resource: (Jackson ImmunoResearch Labs Cat# 706-605-148, RRID:AB_2340476)

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What is this?

DOI: 10.1113/jphysiol.2014.281014

Resource: (Neuromics Cat# GP10108, RRID:AB_2283325)

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What is this?

DOI: 10.1113/jphysiol.2014.281014

Resource: (Alomone Labs Cat# APR-003, RRID:AB_2040054)

Curator: @gabimpine

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What is this?

DOI: 10.1002/glia.22756

Resource: AB_2313566

Curator: @jcabotaj

SciCrunch record: RRID:AB_2313566

What is this?

DOI: 10.1002/glia.22756

Resource: MED PC (RRID:SCR_012156)

Curator: @jcabotaj

SciCrunch record: RRID:SCR_012156

What is this?

DOI: 10.1002/glia.22756

Resource: SMART JUNIOR (RRID:SCR_012154)

Curator: @jcabotaj

SciCrunch record: RRID:SCR_012154

What is this?

DOI: 10.1002/glia.22756

Resource: LightCycler Software (RRID:SCR_012155)

Curator: @jcabotaj

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What is this?

DOI: 10.1002/glia.22756

Resource: (Millipore Cat# MAB1501, RRID:AB_2223041)

Curator: @jcabotaj

SciCrunch record: RRID:AB_2223041

What is this?

DOI: 10.1002/glia.22756

Resource: (Jackson ImmunoResearch Labs Cat# 111-035-003, RRID:AB_2313567)

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What is this?

DOI: 10.1002/glia.22756

Resource: (Cell Signaling Technology Cat# 2678, RRID:AB_2122301)

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SciCrunch record: RRID:AB_2122301

What is this?

DOI: 10.1111/ejn.12716

Resource: (Millipore Cat# AB144P-1ML, RRID:AB_262156)

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What is this?

DOI: 10.1111/ejn.12716

Resource: (Millipore Cat# MAB377, RRID:AB_2298772)

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SciCrunch record: RRID:AB_2298772

What is this?

Should this be applied to the GBM approach? Would it prevent it collapsing onto a spike at 0.42?

This is an annotation.

in --> into

This is definitely very exciting, but 10% is a lot when it comes to space, that could be a distance of lightyears. I am curious what is missing from the instruments currently available to be able to make more precise measurements.

Challenging the idea of "seeing is believing" and the idea of invisible matter must have been very controversial at the time and confusing to lots of people, but is now something we take for granted, despite the fact that we don't have a full understanding of it.

I saw a quote the other day that loosely said that everything sounds crazy until it's proven by science, and I think that really applies here. I also find it interesting that what people think is an impossibility at one point can very quickly become fact later. The idea that science is always evolving and changing is really interesting to me.

I would suggest adjusting punctuation for better readability. "In some cases, the accumulations are found inside structures, and often it is mixed with other material; for example, collapsed material".

How many other birds in different regions used the Milky Way to guide themselves but can't anymore? Although I'm curious how much this affects those birds, as they probably know where to go anyways instinctually or because of the many generations of birds flying south.

I am curious when the conscious decision was made to have protected spaces where development would be kept to a minimum in order to preserve the viewing of the sky.

I'm curious how many before Herschel and his sister tried and failed to discover how the milky way is laid out, and what set them apart from those before them, allowing them to get the job done.

It should be "the walls were one and a half mud bricks" wide.

It should be "another," instead of "an other," i.e., one word, no space.

what about the variant causes it to be optimized for flow cyt?

HES NOT LIKE OTHER BOYS-HE HAS THE ROMANTIC ERA FRUITINESS ABOUT HIM!

两个结果的原因是 net 有两个线性层

[(name, param.shape) for name, param in m.named_parameters()][0] 首先作为一个整体，获取列表的第一个元素，即第一个 (name, param.shape) 元组

然后对这个元祖进行解包！

net 是 net = nn.Sequential(nn.Linear(4, 8), nn.ReLU(), nn.Linear(8, 1))

nn.Linear 是一个全连接层（也称为线性层或密集层）。如果代码中有 if type(m) == nn.Linear: 这样的语句，它的意思是检查变量 m 是否是一个全连接层。

Prettily Painted Portable Typewriters by [[Robert Messenger]]

were there any OTUs that did not appear in the initial recipient community at detectable levels??

# of final reads / # of Tc sorted > 1 is that they mean

How do you determine where the "bacterial" sized particles should appear?

Set a gate for bacterial size on a bivariate SSC-A vs FSC-A plot for events of bacterial size by including the donor strain and excluding all events caused by a sterile pyrophosphate buffer control. Source: Klumper, 2018 Spring protocol handbook

"Did you put your name into the Goblet of Fire, Harry?" Dumbledore asked calmly. Reference: book.

And, the transition to the scene 😂

Part of the whole?

Metal af

Is he misunderstanding? Is this itself a translation problem?

oh, chill out

thunder-word sounds like melville

insults him?

What spirit?

The Whole = Creation = God?

"little god"

Woes of the educator

?? Free will?

Man is "little god" and has divine Reason

这是python的一个语法糖，net()实际上调用net.call()，而__call__()调用了forward

nn.ReLU()是构造了一个ReLU对象，并不是函数调用，而F.ReLU()是函数调用

这里也可以写成 return self.out(nn.ReLU()(self.hidden(X)) ，但是没有必要

In the provided code, the ReLU layer is applied as a function within the forward method, using F.relu(self.hidden(X)). This means that the ReLU activation is not explicitly recorded as a separate layer in the model's structure. Instead, it is applied directly to the output of the hidden layer during the forward pass.

If you want to explicitly include the ReLU layer in the model's structure, you can define it as a separate layer in the __init__ method and then use it in the forward method. Here's an example:

```python class MLP(nn.Module): def init(self): super().init() self.hidden = nn.Linear(20, 256) # 隐藏层 self.relu = nn.ReLU() # ReLU 层 self.out = nn.Linear(256, 10) # 输出层

def forward(self, X):
    return self.out(self.relu(self.hidden(X)))

```

In this version, the ReLU layer is explicitly defined and included in the model's structure.

Overall, I like the AI tools chapters and they are easy to read. I do think that they might need to be re-organized for a more logical progression of content, and that we can evaluate if some chapters that focus on only one specific tool should be maintained. If yes, do we need to find or write chapters for the (main) tools that are missing? Also, because they are coming from different sources, there is some repetition that we might need to address.

Can it be used for higher ed?

Higher ed focus?

Other coding specific tools might need to be included, such as GitHub Copilot, Debuild, etc.

Higher ed focus?

I would probably end with this chapter, since it is more mentoring related than teaching/instruction related.

Higher ed focus?

There are other platforms that could be mentioned in the area of creative storytelling: Character AI, Runway, Colossyan, etc...

Country-specific reference?

Higher ed focus?

I like to have a chapter for video tools, but maybe not just focusing on one? Or have other videos tools listed and summarized in the introductory chapters?

I like this chapter a lot because it focus on both the instructor side and the student side.

schöne diagnose, gut gebrüllt... und jetzt? wo ist der lösungsvorschlag?

10:00 "nach aussen für demokratie, aber sie machen immer genau das gegenteil."<br /> ihre lügen sind too big to fail. if you must lie then lie big. Greenwood - 180 Degrees.<br /> scheinheilig. sich immer rausreden auf "fahrlässigkeit" und "zufall".

Great and important chapter! I wonder if there are other tools to be listed under the 'research and effective source ID'.

Located on 7th floor of Alkek Library

Writing tool specific to craft e-mails. Should it be under writing tools?

Again, is it relevant for higher education?

NAWWWWWW SHE DID NOTTT (she fucking would. good characterization.)

Is this tool targeting higher education?

Reviewer #2 (Public Review):

Summary:

In the manuscript "Metabolic heterogeneity of colorectal cancer as a prognostic factor: insights gained from fluorescence lifetime imaging" by Komarova et al., the authors used fluorescence lifetime imaging and quantitative analysis to assess the metabolic heterogeneity of colorectal cancer. Generally, this work is logically well-designed, including in vitro and in vivo animal models and ex vivo patient samples. Although the key parameter (BI index) used in this study was already published by this group, it was shown that heterogeneity of patients' samples had associations with clinical characteristics of tumors. Additional samples from 8 patients were added to the data pool during the revision process, which is helpful and important for the conclusions that the authors are trying to draw. Overall, the revisions that the authors have made greatly strengthen this study.

Strengths:

(1) Solid experiments are performed and well-organized, including in vitro and in vivo animal models and ex vivo patient samples;

(2) Attempt and efforts to build the association between the metabolic heterogeneity and prognosis for colorectal cancer.

Weaknesses:

(1) Although additional data acquired from 8 patients were collected, maybe more patients should be involved in the future for reliable diagnosis and prognosis.

Author response:

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

Public Reviews:

Reviewer #1 (Public Review):

Summary:

In this study, Komarova et al. investigate the clinical prognostic ability of cell-level metabolic heterogeneity quantified via the fluorescence lifetime characteristics of NAD(P)H. Fluorescence lifetime imaging microscopy (FLIM) has been studied as a minimally invasive approach to measure cellular metabolism in live cell cultures, organoids, and animal models. Its clinical translation is spearheaded through macroscopic implementation approaches that are capable of large sampling areas and enable access to otherwise constrained spaces but lack cellular resolution for a one-to-one transition with traditional microscopy approaches, making the interpretation of the results a complicated task. The merit of this study primarily lies in its design by analyzing with the same instrumentation and approach colorectal samples in different research scenarios, namely in vitro cells, in vivo animal xenografts, and tumor tissue from human patients. These conform to a valuable dataset to explore the translational interpretation hurdles with samples of increasing levels of complexity. For human samples, the study specifically investigates the prediction ability of NAD(P)H fluorescence metrics for the binary classification of tumors of low and advanced stage, with and without metastasis, and low and high grade. They find that NAD(P)H fluorescence properties have a strong potential to distinguish between high- and low-grade tumors and a moderate ability to distinguish advanced-stage tumors from low-stage tumors. This study provides valuable results contributing to the deployment of minimally invasive optical imaging techniques to quantify tumor properties and potentially migrate into tools for human tumor characterization and clinical diagnosis.

Strengths:

The investigation of colorectal samples under multiple imaging scenarios with the same instrument and approach conforms to a valuable dataset that can facilitate the interpretation of results across the spectrum of sample complexity.

The manuscript provides a strong discussion reviewing studies that investigated cellular metabolism with FLIM and the metabolic heterogeneity of colorectal cancer in general.

The authors do a thorough acknowledgement of the experimental limitations of investigating human samples ex vivo, and the analytical limitation of manual segmentation, for which they provide a path forward for higher throughput analysis.

Weaknesses:

To substantiate the changes in fluorescence properties at the examined wavelength range (associated with NAD(P)H fluorescence) in relationship to metabolism, the study would strongly benefit from additional quantification of metabolic-associated metrics using currently established standard methods. This is especially interesting when discussing heterogeneity, which is presumably high within and between patients with colorectal cancer, and could help explain the particularities of each sample leading to a more in-depth analysis of the acquired valuable dataset.

In order to address this issue, we have performed immunohistochemical staining of the available tumor samples for the two standard metabolic markers GLUT3 and LDHA.

The results are included in Supplementary (Fig.S4). Discussion has been extended.

Additionally, NAD(P)H fluorescence does not provide a complete picture of the cell/tissue metabolic characteristics. Including, or discussing the implications of including fluorescence from flavins would comprise a more compelling dataset. These additional data would also enable the quantification of redox metrics, as briefly mentioned, which could positively contribute to the prognosis potential of metabolic heterogeneity.

We agree with the Reviewer that fluorescence from flavins could be helpful to obtain more complete data on cellular metabolic states. However, we lack to detect sufficiently intensive emission from flavins in colorectal cancer cells and tissues. The paragraph about flavins was added in Discussion and representative images - in Supplementary Material (Figure S5).

In the current form of the manuscript, there is a diluted interpretation and discussion of the results obtained from the random forest and SHAP analysis regarding the ability of the FLIM parameters to predict clinicopathological outcomes. This is, not only the main point the authors are trying to convey given the title and the stated goals, but also a novel result given the scarce availability of these type of data, which could have a remarkable impact on colorectal cancer in situ diagnosis and therapy monitoring. These data merit a more in-depth analysis of the different factors involved. In this context, the authors should clarify how is the "trend of association" quantified (lines 194 and 199).

We thank the Reviewer for this suggestion. The section has been updated with SHAP analysis using different parameters (dispersion D of t2, a1, tm and bimodality index BI of t2, a1, tm). It is now more clear that D-a1 is more strongly associated with clinicopathological outcomes compared with other variables. We have also added some biological interpretation of these results in the Discussion.

Reviewer #2 (Public Review):

Summary:

In the manuscript "Metabolic heterogeneity of colorectal cancer as a prognostic factor: insights gained from fluorescence lifetime imaging" by Komarova et al., the authors used fluorescence lifetime imaging and quantitative analysis to assess the metabolic heterogeneity of colorectal cancer. Generally, this work is logically well-designed, including in vitro and in vivo animal models and ex vivo patient samples. However, since the key parameter presented in this study, the BI index, is already published in a previous paper by this group (Shirshin et al., 2022), and the quantification method of metabolic heterogeneity has already been well (and even better) described in previous studies (such as the one by Heaster et al., 2019), the novelty of this study is doubted. Moreover, I am afraid that the way of data analysis and presentation in this study is not well done, which will be mentioned in detail in the following sections.

Strengths:

(1) Solid experiments are performed and well-organized, including in vitro and in vivo animal models and ex vivo patient samples.

(2) Attempt and efforts to build the association between the metabolic heterogeneity and prognosis for colorectal cancer.

Weaknesses:

(1) The human sample number (from 21 patients) is very limited. I wonder how the limited patient number could lead to reliable diagnosis and prognosis;.

Additional 8 samples of patients’ tumors collected while the manuscript was under review were added to the present data. We agree that the number is still limited to conclude about the prognostic value of cell-level metabolic heterogeneity. But at this point we can expect that this parameter will become a metric for prognosis. We will continue this study to collect more samples of colorectal tumors and expand the approach to different cancer types.

(2) The BI index or similar optical metrics have been well established by this and other groups; therefore, the novelty of this study is doubted.

The purpose of this research was to quantify and compare the cellular metabolic heterogeneity across the systems of different complexity - commercial cell lines, tumor xenografts and patients’ tumors - using previously established FLIM-based metrics. For the first time, using FLIM, it was shown that heterogeneity of patients’ samples is much higher than of laboratory models and that it has associations with clinical characteristics of the tumors - the stage and the grade. In addition, this study provides evidence that bimodality (BI) in the distribution of metabolic features in the cell population is less important than the width of the spread (the dispersion value D).

Some corrections have been made in the text on this point.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

The following comments should be addressed to strengthen the rigor and clarity of the manuscript.

(1) The ethical committee that approved the human studies should also be mentioned in the methods section, as was done with the animal studies.

Information about the ethics committee has been added in the Manuscript.

The study with the use of patients’ material was approved by the ethics committee of the Privolzhsky Research Medical University (approval № 09 from 30.06.2023).

(2) The captions in Figures 2 and 3 must be revised. In Figure 2, it seems the last 2 sentences for the description of (C) do not belong there, and instead, the last sentence in the description of (D) may need to be included in (C) instead. Figure 3 is similar.

The captions were revised.

(3) From supplement Figure S2 it seems that EpCam and vimentin staining were only done in two of the mouse tumor types. No further mention is made in the results or methods section. Is there any reason this was not performed in the other tumor types? Were the histology and IHC protocols the same for the mouse and human tumors?

The data on other tumor types and patients’ tumors have been added in Figure S3. Discussion was extended with the following paragraph.

One of the possible reasons for metabolic heterogeneity could be the presence of stromal cells or diversity of epithelial and mesenchymal phenotypes of cancer cells within a tumor. Immunohistochemical staining of tumors for EpCam (epithelial marker) and vimentin (mesenchymal marker) showed that the fraction of epithelial, EpCam-positive, cells was more than 90% in tumor xenografts and on average 76±10 % in patients’ tumors (Figure S3). However, the ratio of EpCam- to vimentin-positive cells in patients’ samples neither correlated with D-a1 nor with BI-a1, which means that the presence of cells with mesenchymal phenotype did not contribute to metabolic heterogeneity of tumors identified by NAD(P)H FLIM.

(4) Clarify the design of the experiments: The results come from 50 - 200 cells in each sample (except 30 in the CaCo2 cell culture) that were counted from 5 - 10 images acquired from each sample. There were 21 independent human samples. How many independent samples were included in the cell culture experiments and the mouse tumor models? Why is there an order of magnitude fewer cells included in the CaCo2 group compared to the other groups (Figure 1)? From the image (Figure 1A - CaCo2), it seems to be a highly populated type of sample, yet only 30 cells were quantified. What prevents the inclusion of the same number of cells to be quantified in each group for a more systematic evaluation?

We thank the Reviewer for this comment.

Cell culture experiments included two independent replicates for each cell line, the data from which were then combined. In animal experiments measurements were made in three mice (numbered 1-3 in Figure 2C) for each tumor type. We have made calculations for additional >100 cells of CaCo2 cell line. In the revised version the number of Caco2 cells is 146.

The text of the Manuscript was revised accordingly.

(5) Regarding references: Some claims throughout the text would benefit from an additional reference. For example: line 70 "Metabolic heterogeneity [...] is believed to have prognostic value"; line 121 " [...] the uniformity of cell metabolism in a culture, which is consistent with the general view on standard cell lines [...]". The clinical translational aspect (i.e., paragraph in line 255) warrants the inclusion of the efforts already done with FLIM imaging in the clinical setting both in vivo and ex vivo with point-spectroscopy and macroscopy imaging (e.g., Jo Lab, Marcu Lab, French Lab, and earlier work by Mycek and Richards-Kortum in colorectal cancer to name a few).

Additional references were added.

Reviewer #2 (Recommendations For The Authors):

(1) In the Introduction, line 85, the authors mention that "Specifically, the unbound state of NAD(P)H has a short lifetime (~0.4 ns) and is associated with glycolysis, while the protein-bound state has a long lifetime (~1.7-3.0 ns) and is associated with OXPHOS". I do not think this claim is appropriate. One cannot simply say that the unbound state is associated with glycolysis, nor that the bound state is associated with OXPHOS; both unbound and bound state are associated with almost all the metabolic pathways. Instead, the expression of "glycolytic/ OXPHOS shift", as authors used in other sections of this manuscript, is a more appropriate one in this case.

The text of the Introduction was revised.

(2) What are the biological implications of the bimodality index (BI)? Please provide specific insights.

Bimodal distribution indicates there are two separate and independent peaks in the population data. In the metabolic FLIM data, this indicates that there are two sub-populations of cells with different metabolic phenotypes. Previously, we have observed bimodal distribution in the population of chemotherapy treated cancer cells, where one sub-population was responsive (shifted metabolism) and the second - non-responsive (unchanged metabolism) [Shirshin et al., PNAS, 2022]. In the naive tumor, a number of factors have an impact on cellular metabolism, including genetics features and microenvironment, so it is difficult to determine which ones resulted in bimodality. Our data on correlation of bimodality (BI) with clinical characteristics of the tumors show that there are no associations between them. What really matters is the width of the parameter spread in the population. The early-stage tumors (T1, T2) were metabolically more heterogeneous than the late-stage ones (T3, T4). A degree of heterogeneity was also associated with differentiation state, a stage-independent prognostic factor in colorectal cancer where the lower grade correlates with better the prognosis. The early-stage tumors (T1, T2) and high-grade (G3) tumors had significantly higher dispersion of NAD(P)H-a1, compared with the late-stage (T3, T4) and low-grade ones (G1, G2). From the point of view of biological significance of heterogeneity, this means that in stressful and unfavorable conditions, to which the tumor cells are exposed, the spread of the parameter distribution in the population rather than the presence of several distinct clusters (modes) matters for adaptation and survival. The high diversity of cellular metabolic phenotypes provided the survival advantage, and so was observed in more aggressive (undifferentiated or poorly differentiated) and the least advanced tumors.

The discussion has been expanded on this account.

(3) Have you run statistics in Figure 1B? If yes, do you find any significance? The same question also applies to Figures 2C and 3C.

We performed statistical analysis to compare different cell lines in in vitro and in vivo models, the results obtained are presented in Table S4.

(4) Line 119, why is the BI threshold set at 1.1?

When setting the BI threshold at 1.1, we relied on the work by Wang et al, Cancer Informatics, 2009. The authors recommended the 1.1 cutoff as more reliable to select bimodally expressed genes. Further, we validated this BI threshold to identify chemotherapy responsive and non-responsive sub-populations of cancer cells (Shirshin et al. PNAS, 2022)

(5) Line 123, what does the high BI of mean lifetime stand for? Please provide biological implications and insights.

The sentence was removed because inclusion of additional CaCo2 cells (n=146) for quantification NAD(P)H FLIM data showed no bimodality in this cell culture.

(6) In the legend for Figure 2C, the authors mention that "the bimodality index (BI-a1) is shown above each box"; however, I do not see such values. It is also true for Figure 3C.

The legends for Fig. 2 and 3 were corrected.

(7) In Figure 2, t1-t3 were not explained and mentioned in the main text. What do they mean? Do they mean different time points or different tumors?

t1-t3 means different tumors in a group. Changes have been made to the figure - individual tumors are indicated by numbers.

(8) In Figure 3, what do p13, p15 and p16 mean? It is not clearly explained. If they just represent patients numbered 13, 15, and 16, then why are these patients chosen as representatives? Do they represent different stages or are they just chosen randomly?

Figure 3 was revised. Representative images were changed and a short description for each representative sample was included. In the revised version, representatives have been selected to show different stages and grades.

(9) In Figure 3, instead of showing the results for each patient, I would suggest that authors show representative results from tumors at different stages; or, at least, clearly indicate the specific information for each patient. I do not think that providing the patient number only without any patient-specific information is helpful.

Figure 3 was revised.

(10) The sample number (21 patients) is very limited. I wonder how the limited patient number could lead to reliable diagnosis and prognosis.

Additional eight samples were added. The text, figures and tables were revised accordingly.

(11) In Discussion, it would be helpful to compare the BI index used in this study with the previously developed OMI-index (Line 275).

We believe that BI index and OMI index describe different things and, therefore, it is hard to compare them. While BI index is used to describe the degree of the metabolic heterogeneity, OMI index is an integral parameter that includes redox ratio, mean fluorescence lifetimes of NAD(P)H and FAD, and rather indicates the metabolic state of a cell. In this sense it is more relevant to compare it with conventional redox ratio or Fluorescence Lifetime Redox Ratio (FLIRR) (H. Wallrabe et al., Segmented cell analyses to measure redox states of autofluorescent NAD(P)H, FAD & Trp in cancer cells by FLIM, Sci. Rep. 2018; 8: 79). The assessment of the heterogeneity of the FLIM parameters has been previously reported using the weighted heterogeneity (wH) index (Amy T. Shah et al, In Vivo Autofluorescence Imaging of Tumor Heterogeneity in Response to Treatment, Neoplasia 17, pp. 862–870 (2015). To the best of our knowledge, this is the only metric to quantify metabolic heterogeneity on the basis of FLIM data for today. A comparison of BI with the wH-index showed that the value of wH-index provides results similar to BI in the heterogeneity evaluation as demonstrated in our earlier paper (E.A. Shirshin et al, Label-free sensing of cells with fluorescence lifetime imaging: The quest for metabolic heterogeneity, PNAS 119 (9) e2118241119 (2022).  Yet, the BI provides dimensionless estimation on the inherent heterogeneity of a sample, and therefore it can be used to compare heterogeneity assessed by different decay parameters and FLIM data analysis methods. The limitation of using the OMI index for FLIM data analysis is the low intensity of the FAD signal, which was the case in our experiments.

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Reviewer #1 (Public Review):

Summary:

Starting from an unbiased search for somatic mutations (from COSMIC) likely disrupting binding of clinically approved antibodies the authors focus on mutations known to disrupt binding between two ERBB2 mutations and Pertuzamab. They use a combined computational and experimental strategy to nominate position which when mutated could result in restoring the therapeutic activity of the antibody. Using in vitro assays the authors confirm that the engineered antibody binds to the mutant ERBB2 and prevents ERBB3 phosphorylation

Strengths:

(1) In my assessment, the data sufficiently demonstrates that a modified version of Pertuzamab can bind both the wild-type and S310 mutant forms of ERBB2.

(2) The engineering strategy employed is rational and effectively combines computational and experimental techniques.

(3) Given the clinical activity of HER2-targeting ADCs, antibodies unaffected by ERBB2 mutations would be desired

Weaknesses:

(1) There is no data showing that the engineered antibody is equally specific as Pertuzamab i.e. that it does not bind to other (non-ERBB2) proteins.

(2) There is no data showing that the engineered antibody has the desired pharmacokinetics/pharmacodynamics properties or efficacy in vivo.

(3) Computational approaches are only used to design a phage-screen library, but not used to prioritize mutations that are likely to improve binding (e.g. based on predicted impact on the stability of the interaction). A demonstration how computational pre-screening or lead optimization can improve the time-intensive process would be a welcome advance.

Comments on revised version:

I have nothing to add beyond my first review, because no substantial changes, additional experiments and/or data, have been made to the manuscript.

for - search - google - participatory system mapping and MuSIASEM

search - google - participatory system mapping and MuSIASEM - https://www.google.com/search?q=participatory+system+mapping+and+MuSIASEM&sca_esv=de3e428f524f6eaa&sxsrf=ADLYWIK8vYVFLcmHv4nSxvSg-qEGT2lXQg%3A1722527927661&ei=t7CrZqWBKPqmhbIPl62nkAk&ved=0ahUKEwjluPnJlNSHAxV6U0EAHZfWCZIQ4dUDCBA&uact=5&oq=participatory+system+mapping+and+MuSIASEM&gs_lp=Egxnd3Mtd2l6LXNlcnAaAhgCIilwYXJ0aWNpcGF0b3J5IHN5c3RlbSBtYXBwaW5nIGFuZCBNdVNJQVNFTTIFECEYoAFIoIaJBVAAWMuCiQVwCXgBkAEAmAHdBKABsowBqgEJMy0zNS4xMC4yuAEDyAEA-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-AUYigUYiwPCAhcQLhiABBjwAxixAxiDARioAxiLAxibA8ICFBAuGIAEGLEDGIMBGKgDGIsDGJsDwgIHEAAYAxiLA8ICERAuGIAEGLEDGKgDGIsDGJsDwgINEAAYgAQYsQMYRhj5AcICJxAAGIAEGLEDGEYY-QEYlwUYjAUY3QQYRhj5ARj0Axj1Axj2A9gBAsICCxAAGIAEGIYDGIoFwgIGEAAYFhgewgIIEAAYFhgeGA_CAggQABiABBiiBMICBRAhGJ8FwgIHECEYoAEYCpgDA7oGBggBEAEYAboGBggCEAEYE5IHCzkuMy0zNS4xMS4xoAfflwM&sclient=gws-wiz-serp

search results returned - of interest

I would not focus an entire chapter to one image AI tool. It would be more consistent to have a chapter for image tools where we list and briefly describe all of them.

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question - participatory system mapper -tweak for people centered and Indyweb provenance? - Could we tweak it for Indyweb to simultanously map - people and - their ideas with - provenance

BIOmastodonte

Should we list some resources for blogs, conferences, etc.?

BIOmastodonte

https://mastogizmos.com/wmt.html

https://mastogizmos.com/bmhs.html

I did an excellent LinkedIn Learning course only to generate ChatGBT prompts. Can we list resources like that?

Would be useful to lost which tools can be used to 'generate research ideas', which tools can be used to 'find relevant information', etc...

Are listed prices updated? Do we need to mention the price or just say that there are free and paid subscriptions?

Because the chapters are coming from different sources, there is some repetition, such as ChatGPT and Grammarly. Leave like that or not?

Current free version is ChatGBT 4o

Update to 2024?

For coding, should mention: GitHub Copilot and Debuild

Other writing tools that could be mentioned and/or included: Copy.ai, Andi, Twain, Compose AI, etc.

Current free version is ChatGBT 4o

Should be updated to Summer 2024, and add additional tools on the list accordingly.

for - participatory system mapping - tool

https://www.youtube.com/watch?v=dzAvABEvHLY

Author response:

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

Reviewer #1 (Recommendations For The Authors):

We would like to see the major conclusions constrained to better fit the data presented in the manuscript. Speed is only a single performance metric of a very complicated, very diverse system of locomotion.

If the authors would like to maintain the broader conclusions, the study should be repeated with a number of different performance metrics to shore up the manuscript's results. Particularly with efficiency, speed is not a reliable measure of efficiency to begin with, so this needs to be explored in a more targeted and appropriate manner.

We agree with Reviewer 1 that we should be more precise about the fitness metrics used and more constrained about the conclusions. Considering the points raised in each paragraph, we’ve modified the text as follows:

- [line 17] “... to test the necessity of both traits for sustained and effective displacement on the ground.”

- [starting on line 105] “We generate the robot’s sample using an artificial evolutionary process that selects for better locomotion ability - defined as higher average speed as it is a proxy for organisms with sustained and effective displacement.”

- [starting on line 287] “We also found that different gravitational environments require different shape structures to optimize locomotion average speed.”

- [starting on line 311] “This consistency is evidence that a small number of sparsely connected modules is a morphological computation principle for an organism’s optimized average speed.”

- [starting on line 348] “Beyond that, extending the tests for other important aspects of locomotion behavior - as noise on the ground, energetic costs, and maneuverability - by using other locomotion metrics - as energy efficiency, stability margin, and dissipated power (Paez and Melo, 2014; Aoi et al., 2016 ) - would also be relevant to evaluate the principle’s robustness.”

- [starting on line 524] “As the robots with the highest average speed are the ones that succeed in maximizing displacement and having robust dynamics (they will not tumble with time), we defined $\bar s$ as the fitness value using it as a proxy of successful directed locomotion. Selecting for bodies that maximize speed is a common locomotion bias in natural selection, as both predators and prey and thus fecundity and mortality depend on it (Alexander, 2006). Other measures - such as energy efficiency - can capture distinct important aspects of the locomotion complexity (Paez and Melo, 2014) and would be worthy of investigating in future work.”

Paper Premise/Mission Statement: As defined in the abstract and also called out in the text starting on line 59 is "investigate whether symmetry and modularity are features of an organism's shape need [authors italics] to have for better-directed locomotion..."

If we understood correctly the reviewer is asking for more precision in the statement. We modified the respective sentence in the following way:

- [line 62] “... need to have for optimizing average speed on the ground,”

Reviewer #2 (Recommendations For The Authors):

i) a lot of details that are in the captions should be moved in the main text;

Thank you for this comment. We reviewed all the captions and text making modifications to ensure that all the information in the captions is also present in the main text. Below, we highlighted some of the changes:

- [line 57] “Thus, locomotion on the ground is present in phylogenetically distant species (such as the maned wolf and frogfish in Figure 1A) and depends upon … “

- [starting on line 64] “Figure 1B shows a schematic representation of symmetry and modularity on the maned wolf and frogfish bodies.”

- [starting on line 277] “There is a negative correlation between the proportion of feet voxels and the robot’s locomotion transference capability when the robots go to an environment with higher gravity, i.e., water to mars (dark blue in Figure 5C), water to earth (light blue), and mars to earth (red) - with a Spearman correlation coefficients of r = -0.39, r = -0.43, and r = -0.32, respectively, all with p < 1e-08.”

ii) hypotheses should be spelled out more clearly;

We verified the experiments and certified that every experiment had a clear hypothesis statement in the original manuscript. Before each section defining the hypothesis and describing the experiment, we added the following statement:

- [starting on line 119] “ With this sample, we tested the hypotheses about the relationships between locomotion performance and body modularity and symmetry (Figure 1I).”

iii) performance metrics and other features should be better defined using mathematical terms if possible (for example, instability);

Thank you for the comment. We added a definition for instability in the text:

- [starting on line 218] “Nonetheless, locomotion requires a minimum instability - the dynamic possibility of translating the center of mass - in the direction axis to generate the necessary forward displacement (Bruijn et al., 2013; Nagarkar et al., 2021).”

Despite the different definitions of instability in literature (Bruijn et al., 2013, Paez and Melo, 2014; Aoi et al., 2016, Nagarkar et al., 2021), we didn’t find one mathematical definition that fits perfectly in our context.

Following the reviewer's comment, when necessary we expanded the definition for other features:

- [starting on line 199] “... the distribution of body weight. As the robots do not have sensory feedback abilities, the weight balance is defined as the body’s movement due to gravity forces (consequences of the weight distribution and surface contact points) (Benda et al., 1994). We hypothesized that the robots with the best directed locomotion ability would tend to have a symmetric body shape. A robot with a low XY shape symmetry (XY shape symmetry < 0.5) has a higher chance of having a poor weight balance, increasing the chance of the body tipping over, thus leading it to a lousy locomotion performance (blue dotted line in Figure 3C). “

iv)  more details regarding the simulations should be included;

We thank the reviewer for this comment. If we understood correctly the Reviewer 2 is asking for more details regarding: “a) the adequacy of the spatial resolution, whereby I failed to see a compelling argument regarding the completeness of 64 voxels; b) the realism of the oscillatory patterns, whereby all the voxels are set to oscillate at the same, constant, frequency of 2Hz; and c) the accuracy of simulations in water where added mass effects seem to be neglected.”. We modified the text to better satisfy these concern:

a) [starting on line 96] “We choose to first explore exhaustively the $4^3$ space dimension, as it is the minimal possible space that allows meaningful body plans. We also did control experiments within 6^3 and 8^3 to check for dimension size effects.”

- [starting on line 432] “We did control experiments with robots within 6³ and 8³ dimensions to check for dimension size effects - and we found that the results found in 4³ remained valid. We choose to focus our analysis in the 4³ design space because we consider it the minimum coarse-grain to approach the biological question about the contingency of shape outcomes pressured for locomotion. Smaller spaces do not allow sufficient complexity in the body structures, and increasing spatial resolution reduces the extensiveness of the investigated search space.”

b) [starting on line 451] “… we used a fixed oscillation frequency of 𝑓 = 2 Hz (Kriegman et al.,2020). A fixed frequency value reduces the number of degrees of freedom in the search for solutions, but in return, it narrows the direct connection between the simulated organisms and animals. Exploring different frequency values in future work would be important to investigate the impact of varied oscillatory frequencies in the shape solutions for directed locomotion.”

c) The environment we call “water” is not an accurate modeling of aquatic habitats as we didn’t simulate essential forces such as draff effects. This choice is explained in text starting on line 110: “In the water-like environment the bodies have nullifying body weight but do not have drag effects. We did not add drag in our simulations because our aim is to study just the body weight influences in locomotion independently of other forces.”

v) a full paragraph about limitations should be included in the discussions, focusing on both simulation aspects (for example, the use of simple spring elements in the voxels) and theoretical assumptions (for example, addressing the potential role of non-locomotion-related aspects).

We thank the reviewer for the comment. We edited some paragraphs of the discussion section to make more explicit some limitations of our work:

[starting on line 398] “We expect that including other important aspects of an animal's body as a developmental process and sensory functions could influence the shape's outcomes with other layers of principles. Although we based our simulations on an already successful transference of \textit{in silico} behavior to organisms made of biological tissue

\citep{kriegman_scalable_2020}, there is an intrinsic gap between spring-mass robots modeling and animal’s bodies that is worthy of exploring to ensure the generality of our results. Other methods, such as the inclusion of rigid body elements in the simulation (possible in Voxelyze), the use of finite element modeling (FEM) (Coevoet et al., 2019), and the construction of physical robots (Aguilar et al., 2016), are important complements to this work. Beyond that, principles on other scales as in the genotypes (Johnston et al., 2022) and in other behavioral phenotypes (Gomez-Marin et al., 2016) could also be investigated.”

To address the potential role of non-locomotion-related aspects, we revised the section

“Discussion - Contingency of evolutionary outcomes” where we discussed other functional and biological roles:

[starting on line 354 ] “Here we investigate how a specific functional cause - optimization of average speed during directed locomotion on the ground - externally defines the phenotypic space of shape possibilities.”

[starting on line 359] “For simplification purposes, we choose to not explicitly control other important factors of locomotion (i.e., energy consumption, maneuverability) that nonlinearly interact during locomotion. In future studies, it would be important to conduct similar studies on a wider range of factors to study the shape and dynamic principles in different conditions.“

Reviewer #2 (Public Review):

This work makes substantial progress towards understanding physical aspects of formation locomotion, notably the hydrodynamic stability of groups of flappers and the modifications to energy costs associated with flow interactions.

Major strengths pertain to the fact that this topic is timely, interesting and complex, and the authors have advanced the understanding through their characterizations.

The weaknesses may relate to the many idealizations employed in the simulations and models, which may raise questions about how to interpret their results and whether the outcomes hold generally. But given the complexity of the problem, simplifications are necessary. The authors have certainly provided a clear presentation with appropriate details and caveats that will help the reader extract the main messages and form their own conclusions.

Overall, the work is a positive addition to the growing set of studies into schooling, flocking and related problems where unsteady flow interactions lead to interesting collective effects.

Marcus said that the Toledo Hem Sealer application is impressive and would be good website content

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reply to u/IamOkei at https://new.reddit.com/r/Zettelkasten/comments/1eg8jhe/how_different_is_bob_dotos_a_system_for_writing/?%24deep_link=true&correlation_id=f06f9a20-472b-4d1d-9820-65a28e4efb04&post_fullname=t3_1eg8jhe&post_index=0&ref=email_digest&ref_campaign=email_digest&ref_source=email&utm_content=post_title&%243p=e_as&utm_medium=Email%20Amazon%20SES

Doto's book is far more focused, well-written, and actually edited. Scheper's less well written and in need of heavy editing. Save yourself the extra 400 pages and spend that time practicing the craft instead.

If you were starting from scratch without any knowledge of the area, I would highly recommend Doto's work, possibly mention Ahrens in passing, and not suffer anyone to mention Scheper's book. If you're an academic, I would recommend Umberto Eco or perhaps if a historian, one of the many books on historical method like Barzun, Gottschalk, or Goutor.

As background, both Scheper and Doto sent me pre-publication drafts of their work-in-progress to read. I've also read the majority of other books, papers, articles, and works in the space over the past 150+ years including nearly 100% of the references footnoted the two texts referenced. See also: https://boffosocko.com/research/zettelkasten-commonplace-books-and-note-taking-collection/

ernst wolff for president ...<br /> aber ernsthaft, was würde ernst wolff machen wenn er alle freiheiten hätte?<br /> was würde er machen gegen übervölkerung, rohstoffmangel, degeneration?

Decirlo de manera más clara.

Decirlo con palabras más llanas y claras.

Aclarar o quitar

con mayor calidad del dato

Para garantizar que las conclusiones sean sólidas, compararemos ~~en profundidad~~ las herramientas.

Borrar.

Este ya no es nuestro objetivo. Sino el de analizar la calidad de los microdatos extraídos.

When I clicked on "introduction" in the A16 unit book, it jumps to MZ Sitewide, and users need to use the backwards button to return to A16. This is consistent with the way in which other pages are open and users may get lost. I suggest to keep it consistent, i.e., open link in tab.

Delete one period

This commentary and the testing referenced is Yesco's justification for calculating and applying Case B wind load with much less eccentricity than Figure 29.3-1 requires.

Yesco has suggested that because the force coefficients were divided by 0.85 (normal gust factor), when determining the pressure for flexible signs with frequency less than 1 Hz, we should multiply by 0.85.

Citizens, not users.

I like that. I've been grasping for a generic alternative to 'user' that is less generic than 'person' and this hits a sweet spot.

4:00 "gewaltfantasien laut aussprechen ist eine straftat"<br /> nein, zu sagen "ich werde den scheiss habek wegballern" ist KEINE straftat.<br /> deutsche sind nur zu blöd für redefreiheit... hirntotes scheissvolk >: (

In this section, it is unclear what it mean by "markers" and "control points." Since the grammar is in progress, it is probably a good idea to explain briefly here.

Change this

Hello

In this section, it is unclear what the lines and arrows on the maps mean. I suppose it will be explained in the Grammar, but since it is in progress, it might be good idea to briefly explain it here.