Dear Dr. Friedrich,

Thank you very much for submitting your manuscript "Resilience of three-dimensional sinusoidal networks in liver tissue" for consideration at PLOS Computational Biology.

As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. In light of the reviews (below this email), we would like to invite the resubmission of a revised version that takes into account the reviewers' comments.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

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[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

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Thank you again for your submission. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Daniel A Beard

Deputy Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: In their article ``Resilience of three-dimensional sinusoidal networks in liver tissue,'' Karschau and co-workers investigate the structure and topology of sinusoidal networks in the liver. Based on data from their Ref. 13, the authors construct an algorithm for in-silico generation of arbitrarily large transport networks with the same

statistical properties as their real data. They consider both geometry (position of branch points as quantified through a radial distribution function) and topology (node degree and edge length distribution). In a second step, the authors include nematic alignment into their generation algorithm.

Based on their statistical model, the authors proceed to characterize resilience of their statistical and real networks to removal of edges. They find that while the networks are generically resilient to removal

of random edges, the loss of certain high-flow edges can lead to larger damage, as quantified by a loss in overall hydraulic permeability. Furthermore, the authors find that weak nematic alignment of the edges

with overall flow direction can increase permeability while retaining robustness.

The paper is generally well-written and interesting. The network generation method appears to be sound in terms of results.

However, I have a few concerns and remarks regarding details.

(*) While the authors employ multi-objective optimization techniques to find a Pareto front of trade-offs between their objectives, this Pareto front is then never actually used. In fact, after re-scaling the objectives appropriately, the authors end up simply averaging the individual objectives.

Given that the goal was to reproduce the statistics of their real data, scaling and averaging seems to be the most straightforward and direct fitting method.

I suspect that the normalization involving utopia and nadir points is of relevance here, but why these are chosen should be made more clear. So, while the Pareto terminology is interesting, it seems to me that

it might not actually needed to obtain the results in the paper. This is consistent with the authors' observation that their algorithm is robust with respect to choice of alpha.

(*) The authors conclude that ``weakly nematic networks optimize performance without compromising resilience.'' While the authors' results support this statement, here, Pareto methods would appear to be actually the appropriate tool for quantification. In an objective space comprising performance and permeability-at-risk, networks with weak nematic alignment should be on the Pareto front,

and those without should not be Pareto efficient.

(*) The authors mention that flows in their simulated networks are very inhomogeneous, contrary to intuition.

Is it possible that this inhomogeneity is related to their choice of pressure boundary conditions?

More specifically, what motivates the choice of fixing pressures instead of flows at the boundaries, and would fixing boundary flows lead to more homogeneous bulk flows?

(*) While available in Ref. 13, it would be useful to briefly mention again the size of the original data set in terms of both number of samples and size of the networks. How much larger than the real networks are

the authors' artificial ones? How large is the statistical advantage of using artificial networks over

the real data?

(*) The plots in Fig. 1 DEF suggest that the real data does not provide particularly smooth distributions (in particular for the edge lengths). What precautions have been taken to avoid overfitting of statistical

fluctuations in the data? How large is the error in the PDFs obtained from the real data?

Minor typos:

author summary:

vene, leafs -> vein, leaves

p. 10: extend -> extent

Reviewer #2: uploaded as an attachment

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Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: None

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Reviewer #1: No

Reviewer #2: Yes: Andrew D. Marquis

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

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Attachments

Attachment

Submitted filename: My_review.docx

Dear PD Dr. Friedrich,

Thank you very much for submitting your manuscript "Resilience of three-dimensional sinusoidal networks in liver tissue" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. 

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Daniel A Beard

Deputy Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: I am satisfied with the changes made by the authors and recommend publication.

If the authors would like to add the new supplemental figures they mentioned at a later stage that could be good, but I feel that the paper is sufficiently well supported at this time.

Reviewer #2:

General

              Overall, the authors have done an excellent job with this resubmission. I am particularly impressed with the addition of the minimal model of an adaptive network, and the additional details on Pareto optimality brought up by the other reviewer. I only have one major critique and have identified a few typos and clarity suggestions. Treat my typo and clarity suggestions as optional. This is an interesting and well-done study and I am looking forward to seeing it published.

Critiques

• In the “Minimal model for adaptive edge weights” section, you describe a model that regulates edge permeability in a way that is dependent upon edge current going below a set point (I*). How was this set point determined? Are the results sensitive to the choice of set point, I*?

Typos and clarity suggestions

• In the 7^th paragraph of the introduction, you say “Permeabilities allow to efficiently … ”, and I think meant to say “Permeabilities allow us to efficiently …”
• In the 4^th paragraph of the “A network generation algorithm for spatial networks” section, you say “which is in particular robust …”, and I think meant to say “which is particularly robust …”
• In the first paragraph of the “Discussion and Outlook” section, you say “We drew advantage …” and I think meant to say “We took advantage …”
• In the 6^th paragraph of the “Discussion and Outlook” section, you say “may facilitate a more homogenous distribution instead.” – I think you can delete the word “instead” from this sentence
• In the “Permeability-at-risk if low-current edges removed” section, I think the section could be re-named “Permeability-at-risk if low-current edges are removed”
• In the “Permeability-at-risk if low-current edges removed” section, you say “However, if together …” and I think you meant to say “However, if performed together”
• In equation S3, it appears that kappa_0 cancels out. Is this case?
  • Your reasoning behind the use of kappa/kappa_0 as a criterion to constrain the change in permeability by a factor of 4 is sound, but perhaps you can express equations S3 as a piecewise function where dkappa_j/dt = -rho kappa (I* - |I_j|) if 0.25 < kappa/kappa_0 < 4, and dkappa_j/dt = 0 otherwise

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Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: Yes

**********

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Andrew D. Marquis

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, PLOS recommends that you deposit laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/ploscompbiol/s/submission-guidelines#loc-materials-and-methods

Dear PD Dr. Friedrich,

We are pleased to inform you that your manuscript 'Resilience of three-dimensional sinusoidal networks in liver tissue' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. 

Best regards,

Daniel A Beard

Deputy Editor

PLOS Computational Biology

Daniel Beard

Deputy Editor

PLOS Computational Biology

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