Learning to see colours: Biologically relevant virtual staining for adipocyte cell images

Håkan Wieslander; Ankit Gupta; Ebba Bergman; Erik Hallström; Philip John Harrison

doi:10.1371/journal.pone.0258546

Peer Review History

Original SubmissionMay 11, 2021
30 Jun 2021 Decision Letter - Chi-Hua Chen, Editor Transfer Alert This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present. PONE-D-21-15339 Learning to see colours: generating biologically relevant fluorescent labels from bright-field images PLOS ONE Dear Dr. Harrison, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Jul 26 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. 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Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: PONE-D-21-15339 In this manuscript, the authors apply the established approach of label-free microscopy to an adipocyte dataset with two . They modify previous deep-learning approaches using a variation on deep learning called Learning Using Privileged Information. They also use a feature-based approach to evaluate generated images, rather than the pixel-based approaches used in previous label-free work. There are a three significant issues with this manuscript that need to be addressed. First, relevant prior work is not cited (as itemized below). Second, the authors did not compare their approach to current state-of-the-art methods Without these comparisons it is unclear whether or not the manuscript contributes an advance to the field. Third, the images used in the study are not being made publicly available as required by journal policy. Major issues: 1. The title, abstract and introduction are largely written as if the authors invented the approach of label-free microscopy, which is not correct. All should be modified to make clear the relationship of their work to prior work clear. 2. The authors briefly mention Christiansen et al 2018 but do not mention the even more relevant papers from the Allen Institute for Cell Science (Johnson et al (2017) [https://arxiv.org/abs/1705.00092] and Ounkomol et al (2018) [https://doi.org/10.1038/s41592-018-0111-2]. They do not compare their approach to these state-of-the-art methods, which could been done either by applying the open source Allen Institute for Cell Science software to their images, or by applying their method to the publicly available images used by Ounkomol et al. 3. The idea of using features to evaluate synthetic images has been described previously by Zhao & Murphy (2007) [https://doi.org/10.1002/cyto.a.20487]. 4. While using features is appropriate, the authors should also calculate pixel-wise correlations in order to be able to compare their results to the previous work. 5. In order to enable others to reproduce and possibly improve upon the work and to comply with PLoS ONE policy, all images used in the study should be made publicly available. This reviewer strongly urges that the manuscript not be published without making the images freely available. ****** 6. 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 [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment 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. Registration is free. 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 PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0258546.r001
Revision 1
24 Jul 2021 Author Response Dear reviewer, Thank you for carefully going through our manuscript. Please find our responses to your comments below. In the revised manuscript we have made updates in line with your comments. Best regards, Philip J Harrison PONE-D-21-15339 Learning to see colours: generating biologically relevant fluorescent labels from bright-field images Review Comments to the Author Reviewer #1: PONE-D-21-15339 In this manuscript, the authors apply the established approach of label-free microscopy to an adipocyte dataset with two . They modify previous deep-learning approaches using a variation on deep learning called Learning Using Privileged Information. They also use a feature-based approach to evaluate generated images, rather than the pixel-based approaches used in previous label-free work. There are a three significant issues with this manuscript that need to be addressed. First, relevant prior work is not cited (as itemized below). Second, the authors did not compare their approach to current state-of-the-art methods Without these comparisons it is unclear whether or not the manuscript contributes an advance to the field. Third, the images used in the study are not being made publicly available as required by journal policy. Major issues: 1. The title, abstract and introduction are largely written as if the authors invented the approach of label-free microscopy, which is not correct. All should be modified to make clear the relationship of their work to prior work clear. We did not intent to make it sound like we had invented label-free microscopy. We have added text in the abstract and references to additional articles (see response to your next comment) to deal with this concern. 2. The authors briefly mention Christiansen et al 2018 but do not mention the even more relevant papers from the Allen Institute for Cell Science (Johnson et al (2017) [https://arxiv.org/abs/1705.00092] and Ounkomol et al (2018) [https://doi.org/10.1038/s41592-018-0111-2]. They do not compare their approach to these state-of-the-art methods, which could been done either by applying the open source Allen Institute for Cell Science software to their images, or by applying their method to the publicly available images used by Ounkomol et al. We agree that these two papers should have been cited in our manuscript. The Johnson et al paper we had not previously come across. Thank you for pointing out this paper to us, their method was interesting. We have added references to these two paper (see lines 66-72). Concerning comparing our method to other state-of-the-art methods: As we tailored our methods to each imaging channel and our specific adipocyte image data, focusing on the derived features, and were not trying to devise a general method that would work for all virtual staining, we believe it would be difficult to devise a fair comparison. We can not directly apply these alternative methods directly to our dataset without making modifications to them. For instance, the Allen Institute for Cell Science software was developed for 3D reconstructions, not 2D as was our case. We have updated the text on line 102 to emphasize that we have build this method specifically for our adipocyte cell image data. It is also the case that our method was actually compared against 7 other state-of-the-art methods in the competition organised by AstraZeneca and AI Sweden that we won. The 7 other teams used a variety of different and current approaches for the virtual staining. AstraZeneca and AISweden are in the process of writing a paper about the competition and the modelling solutions used by the competing teams. Unfortunately, this paper has not yet been completed nor published. 3. The idea of using features to evaluate synthetic images has been described previously by Zhao & Murphy (2007) [https://doi.org/10.1002/cyto.a.20487]. Thank you for bringing this paper to our attention, we have included a reference to it on lines 100-101. 4. While using features is appropriate, the authors should also calculate pixel-wise correlations in order to be able to compare their results to the previous work. See previous response concerning comparing to other methods. We do however still report our pixel-level performance (MAEs) in Tables 2 and 3. 5. In order to enable others to reproduce and possibly improve upon the work and to comply with PLoS ONE policy, all images used in the study should be made publicly available. This reviewer strongly urges that the manuscript not be published without making the images freely available. We would really like to make this data available, but unfortunately there are legal restrictions that make this impossible at the current time. At present access to the data can be requested from AI Sweden, although a sample of the data is freely available at https://www.ai.se/en/node/81535/adipocyte-cell-imaging-challenge. Attachments Attachment Submitted filename: Responses to Reviewer.pdf https://doi.org/10.1371/journal.pone.0258546.r002
13 Aug 2021 Decision Letter - Chi-Hua Chen, Editor PONE-D-21-15339R1 Learning to see colours: generating biologically relevant fluorescent labels from bright-field images PLOS ONE Dear Dr. Harrison, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Sep 27 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Chi-Hua Chen, Ph.D. Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: (No Response) ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The authors have made a few welcome additions based upon my previous comments. They have decided not to compare their method to previous methods. While I understand their choice, in the absence of such a comparison the methodological significance of the work remains unknown. Therefore the work is best described as the application of an existing approach to a different cell type. I therefore strongly feel that the title is not appropriate and should be changed to something like “Development of label-free microscopy models for adipocytes”. ****** 7. 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 [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment 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. Registration is free. 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 PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0258546.r003
Revision 2
23 Aug 2021 Author Response RESPONSE TO EDITOR I am pleased to resubmit the original paper by Håkan Wieslander, Ankit Gupta, Ebba Bergman, Erik Hallström and Philip J Harrison for publication consideration in PLOS ONE. This paper was originally entitled “Learning to see colours: generating biologically relevant fluorescent labels from bright-field images”, but in response to the reviewer’s suggestion we have now changed the title to “Learning to see colours: biologically relevant virtual staining for adipocyte cell images”. We have reviewed our reference list to ensure that it is complete and correct. None of the cited papers have been retracted. We hope you find our revised manuscript suitable for publication in PLOS ONE. RESPONSE TO REVIEWER We agree, in light of your comments, and those you made on the first draft of our manuscript that a less general title would be better. We have therefore changed the title of our manuscript to “Learning to see colours: biologically relevant virtual staining for adipocyte cell images”. Attachments Attachment Submitted filename: 2nd_responses_to_reviewer.pdf https://doi.org/10.1371/journal.pone.0258546.r004
30 Sep 2021 Decision Letter - Chi-Hua Chen, Editor Learning to see colours: biologically relevant virtual staining for adipocyte cell images PONE-D-21-15339R2 Dear Dr. Harrison, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Chi-Hua Chen, Ph.D. Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: (No Response) ****** 7. 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 https://doi.org/10.1371/journal.pone.0258546.r005
Formally Accepted
7 Oct 2021 Acceptance Letter - Chi-Hua Chen, Editor PONE-D-21-15339R2 Learning to see colours: biologically relevant virtual staining for adipocyte cell images Dear Dr. Harrison: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Professor Chi-Hua Chen Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0258546.r006

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