-->PONE-D-25-45349-->-->Advancing Poultry Health: A Meta-Analysis of Epitope-Based and Peptide-Based Vaccines Against Avian Pathogenic E. coli with Machine Learning Insights-->-->PLOS ONE

Dear Dr. Ali,

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.

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We look forward to receiving your revised manuscript.

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Arindam Mitra

Academic Editor

PLOS ONE

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Additional Editor Comments:

Please revise the manuscript in line with the comments of the reviewers in a point by point manner.

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Reviewers' comments:

Reviewer's Responses to Questions-->

-->Comments to the Author

1. 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

Reviewer #2: Yes

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-->2. Has the statistical analysis been performed appropriately and rigorously? -->

Reviewer #1: No

Reviewer #2: Yes

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-->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: Yes

Reviewer #2: Yes

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-->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

Reviewer #2: Yes

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-->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: The reviewer's comments are well-noted. Many similar topics exist in review articles on this subject. Therefore, the meta-analysis should emphasize which specific findings it contributes. The article seems suitable for publication regardless.

Please consider the following points for revision:

1. The manuscript provides a weak explanation of the fundamental definition of machine learning (ML) and its application in the study, particularly within the methods section. The authors mention using ML for the "Study Selection Process." However, the legality of this application for selection requires clarification. Using third-party application programming interfaces is generally acceptable, unlike certain generative AI tools currently prevalent. The description lacks clarity on whether the team developed the ML process internally, as it omits the specific algorithms used. The authors must confirm these details and remember that ML and AI have distinct definitions.

2. The authors must confirm and clarify the statement: "For the purposes of this review, 'machine learning' was defined as a data-driven approach in which an algorithm learns patterns from input data (e.g., supervised, unsupervised, or deep learning methods)." The description fails to mention the programming language or software tools used to build the data extraction process with ML.

3. The writing in the "Materials and Methods" section suggests possible use of AI for editing, leading to typographical errors like: "Each domain was assessed as "low risk," "high risk," or "unclear risk," " The authors should carefully review the entire section.

4. In this reviewer's opinion, the article presents a standard meta-analysis. The use of ML appears limited to automating selection and data extraction, while the core analysis techniques follow conventional meta-analysis approaches. The authors should confirm this point and adjust the title and "Materials and Methods" section to reflect accurately the role of ML and AI.

5. The manuscript repeats the full explanation for abbreviations, such as "outer membrane vesicles (OMVs)," multiple times. The authors should review and correct this pattern for all abbreviations used.

6. Figure 1, the PRISMA-P flowchart, should specify the reasons for excluding records during the screening. Eliminating 219 articles due to "different objectives" suggests a significant weakness in the initial keyword strategy. A more precise keyword selection would likely have prevented such a large-scale exclusion for that reason. The authors must provide a better explanation for these exclusions.

7. The abstract's graphical representation mentions vaccine effectiveness results, but the manuscript contains no corresponding forest plots. The reported parameters are also surprisingly limited to only two, raising questions about the difficulty of compiling data related to core vaccine effectiveness outcomes.

8. The manuscript must follow proper scientific nomenclature. For example, after the first full mention of "Escherichia coli," subsequent references should use the abbreviated form "E. coli." The authors should check the entire text for this issue.

The authors have no further comments but should perform a comprehensive check of the entire manuscript. The methods section requires significant strengthening. Please also double-check all author names and affiliations for accuracy, ensure reference citations are correct, and perform a final, thorough proofread.

Reviewer #2: Dear Authors,

Your manuscript addresses a timely topic with valuable insights on APEC vaccines and machine learning applications. Clarification of meta-analysis methodology, data reporting, and the specific contribution of machine learning would strengthen rigor, transparency, and scientific impact.

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Reviewer #1: Yes: Mohammad Miftakhus Sholikin

Reviewer #2: No

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Attachments

Attachment

Submitted filename: Peer Review.PONE-D-25-45349.docx

Advancing Poultry Health: A Meta-Analysis of Epitope-Based and Peptide-Based Vaccines Against Avian Pathogenic E. coli with Machine Learning Insights

PONE-D-25-45349R1

Dear Dr. Ali,

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.

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Kind regards,

Yung-Fu Chang

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

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-->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

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-->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: Yes

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-->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

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-->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 additional comments are provided. The authors have adequately revised the manuscript. However, they should recheck the names, affiliations, and corresponding author to ensure accuracy and consistency. The authors should also carefully review the manuscript to confirm the scientific logic and conduct an independent proofreading of the entire text.

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-->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: Yes: Mohammad Miftakhus Sholikin

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