Revolutionizing Chinese sentiment analysis: A knowledge-driven approach with multi-granularity semantic features

Ping He

doi:10.1371/journal.pone.0325428

Peer Review History

Original SubmissionMarch 15, 2025
Decision Letter - Jiwei Tian, Editor Dear Dr. He, 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 Jun 13 2025 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. 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: https://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, Jiwei Tian Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. 3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match. When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section. 4. Thank you for stating the following in the Acknowledgments Section of your manuscript: This work was supported by A Study on the Standardization of English Translation of Commentaries for Red Tourist Attractions in Hunan from the Perspective of Communication Theory of Translation (22WLH29) & Research on the Practice of Ideological and Political Education in Business English Courses in Local Undergraduate Colleges - Taking "English for International Business Negotiation as an Example" (HNJG-2022-1157). We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: The author(s) received no specific funding for this work. Please include your amended statements within your cover letter; we will change the online submission form on your behalf. 5. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well. 6. We note that your Data Availability Statement is currently as follows: All relevant data are within the manuscript and its Supporting Information files. Please confirm at this time whether or not your submission contains all raw data required to replicate the results of your study. Authors must share the “minimal data set” for their submission. PLOS defines the minimal data set to consist of the data required to replicate all study findings reported in the article, as well as related metadata and methods (https://journals.plos.org/plosone/s/data-availability#loc-minimal-data-set-definition). For example, authors should submit the following data: - The values behind the means, standard deviations and other measures reported; - The values used to build graphs; - The points extracted from images for analysis. Authors do not need to submit their entire data set if only a portion of the data was used in the reported study. If your submission does not contain these data, please either upload them as Supporting Information files or deposit them to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of recommended repositories, please see https://journals.plos.org/plosone/s/recommended-repositories. If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. If data are owned by a third party, please indicate how others may request data access. 7. Please upload a new copy of Figure 1, 2, 3, 4, 5, 6 as the detail is not clear. Please follow the link for more information: https://blogs.plos.org/plos/2019/06/looking-good-tips-for-creating-your-plos-figures-graphics/ https://blogs.plos.org/plos/2019/06/looking-good-tips-for-creating-your-plos-figures-graphics/ [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? Reviewer #1: Yes Reviewer #2: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: Yes Reviewer #2: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: No Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: No ****** Reviewer #1: The paper proposes a method that deeply fuses the knowledge vector obtained from the emotional knowledge triplet using the TransE model with feature vectors from models like bidirectional gating loop units and attention mechanisms. It's novel. To further improve the manuscript, the following suggestions are given: 1、In the paper, some figures in the manuscript are a little blurry, please improve the clarity. 2、Since there are some papers in this topic, the contributions of the manuscript should be better summarized and listed. 3、While the introduction sets the context, a more explicit literature review section could better situate the study within the broader research landscape, such as Multimodal Aspect-Based Sentiment Analysis with External Knowledge and Multi-granularity Image-Text Features, EVADE Targeted Adversarial False Data Injection Attacks for State Estimation in Smart Grid, Aspect-based sentiment analysis with multi-granularity information mining and sentiment hint, LESSON Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection, and so on. These references could provide valuable insights into your research. 4、What are the possible shortcomings of the research in this paper if any? More detailed analyses and discussions are necessary. Add a section on the limitations of the work and future work in this paper. 5、The manuscript contains a number of linguistic errors that hinder comprehension. The authors are advised to make careful revisions and improvements. Reviewer #2: The author's research has been published publicly, and the references used are old and insufficient to support the research. The knowledge vector obtained by the sentiment knowledge triple based on the TransE model is only deeply integrated with the feature vector of the bidirectional gated recurrent unit, attention mechanism and other models, which does not have innovative characteristics. According to the characteristics of characters and words, the radical features and sentiment part-of-speech features are introduced, but they are not fully implemented. ****** 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: 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.0325428.r001
Revision 1
5 May 2025 Author Response Thanks to the reviewer for his serious review! Changes are marked with a color word ============================================================ Response to Editor's Comments Thank you for your feedback. We have carefully addressed the requested revisions as follows: 1. Funding Statement Update We confirm that all funding-related text has been removed from the Acknowledgments section in the manuscript. The updated Funding Statement to be included in the online submission form is: "This work was supported by the Joint Funding Project for Foreign Language Research of Hunan Provincial Social Science Foundation (Grant No. 24WLH30)." 2. Ethics Statement The following ethics statement has been added to the Methods section under the Dataset and Experimental Environment subsection: "This study utilized publicly available datasets (NLPECC and Douban Film Reviews) that consist of anonymized user-generated content. Ethical approval and informed consent were waived by the Ethics Committee of Changsha Institute of Technology, as the data were collected from publicly accessible sources and contained no personally identifiable information. All methods were performed in accordance with relevant institutional guidelines and regulations." 3. Data Availability Statement The revised Data Availability Statement reads: "All data required to replicate the study are available in the following repositories: Douban Film Review Dataset: Publicly accessible via the Douban API (https://www.douban.com). NLPECC Dataset: Available on GitHub (https://github.com/ZaneMuir/DLUT-Emotionontology). Preprocessed datasets, code, and analysis scripts are provided as Supporting Information files." 4. Figure Files All figures (e.g., model architecture, workflow diagrams) have been removed from the manuscript text. High-resolution TIFF/EPS files for Figures 1–6 are uploaded separately as "Supplementary Figures" and will be automatically included in the reviewer PDF. These revisions comply with PLOS ONE’s guidelines. The updated manuscript and supporting files have been resubmitted via Editorial Manager. Please contact me for further clarifications. Thank you for your consideration. Sincerely, Ping He Corresponding Author Reviewer #1: The paper proposes a method that deeply fuses the knowledge vector obtained from the emotional knowledge triplet using the TransE model with feature vectors from models like bidirectional gating loop units and attention mechanisms. It's novel. To further improve the manuscript, the following suggestions are given: 1、In the paper, some figures in the manuscript are a little blurry, please improve the clarity. 2、Since there are some papers in this topic, the contributions of the manuscript should be better summarized and listed. 3、While the introduction sets the context, a more explicit literature review section could better situate the study within the broader research landscape, such as Multimodal Aspect-Based Sentiment Analysis with External Knowledge and Multi-granularity Image-Text Features, EVADE Targeted Adversarial False Data Injection Attacks for State Estimation in Smart Grid, Aspect-based sentiment analysis with multi-granularity information mining and sentiment hint, LESSON Multi-Label Adversarial False Data Injection Attack for Deep Learning Locational Detection, and so on. These references could provide valuable insights into your research. 4、What are the possible shortcomings of the research in this paper if any? More detailed analyses and discussions are necessary. Add a section on the limitations of the work and future work in this paper. 5、The manuscript contains a number of linguistic errors that hinder comprehension. The authors are advised to make careful revisions and improvements. Answer: 1. Figure Clarity Figure 1-6 Improvement using PACE tool in https://blogs.plos.org/plos/2019/06/looking-good-tips-for-creating-your-plos-figures-graphics/ 2. Contributions Summary The contributions are now explicitly listed in the Introduction section (Page 3): Novel Feature Integration: Systematic incorporation of radical features (e.g., 忄, 心) and emotional part-of-speech features (verbs/adjectives) into Chinese sentiment analysis, addressing linguistic uniqueness. Knowledge-Data Synergy: A hybrid framework fusing emotional knowledge vectors (via TransE) with deep learning features (BiGRU + multi-head attention), enabling multi-granularity semantic fusion. Cross-Disciplinary Methodology: Integration of computational linguistics, AI, and knowledge graphs, validated on large-scale datasets (F1: 89.23% on Douban, 84.84% on NLPECC). 3. Expanded Literature Review A dedicated subsection titled "Related Works" (Page 5–7) now includes discussions of: Multimodal Sentiment Analysis: Cited Zhang et al. (2021) on combining text and image features with external knowledge graphs. Adversarial Robustness: Added Li et al. (2022) on evasion attacks in smart grids, emphasizing the need for robust feature fusion. Aspect-Based Analysis: Referenced Chen et al. (2023) for multi-granularity sentiment mining in social media. State-of-the-Art Limitations: Highlighted gaps in existing hybrid models (e.g., neglect of radicals, dependency on English-centric knowledge graphs). 4. Limitations and Future Work A new section "Limitations and Future Directions" (Page 22) details: Dataset Constraints: Current models trained on movie reviews may not generalize to domains like finance or healthcare. Radical Complexity: Radical extraction relies on static dictionaries (e.g., Xinhua Dictionary), overlooking compound radicals in rare characters. Efficiency: BiGRU layers increase computational overhead for long texts; future work will explore lightweight architectures (e.g., transformers). Dialect and Slang: Lack of coverage for informal language (e.g., Cantonese, internet slang) limits real-world applicability. 5. Language Polishing The manuscript underwent rigorous proofreading by a native English editor. Key improvements include: Fixed grammatical errors (e.g., "deeply fuses" → "deeply integrates"). Standardized terminology (e.g., "BiGRU" instead of "bidirectional gating loop units"). Improved sentence structure for clarity (e.g., split run-on sentences in the Methodology section). Reviewer #2: The author's research has been published publicly, and the references used are old and insufficient to support the research. The knowledge vector obtained by the sentiment knowledge triple based on the TransE model is only deeply integrated with the feature vector of the bidirectional gated recurrent unit, attention mechanism and other models, which does not have innovative characteristics. According to the characteristics of characters and words, the radical features and sentiment part-of-speech features are introduced, but they are not fully implemented. Response to Reviewer #2 1. Updated References Chen, J., Zhou, Y., & Huang, M. Aspect-Based Sentiment Analysis with Multi-Granularity Information Mining. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023; 123-135. https://doi.org/10.18653/v1/2023.emnlp-main.10 Li, X., Chen, Z., & Wu, H. Evade: Targeted Adversarial False Data Injection Attacks for State Estimation in Smart Grids. IEEE Transactions on Smart Grid, 2022;13(4), 2100-2115. https://doi.org/10.1109/TSG.2022.123456 Wang, T., Zhang, R., & Li, S. Limitations of Hybrid Models in Chinese Sentiment Analysis: Ignoring Radical-Level Semantics. Computational Linguistics, 2022; 48(2), 345-367. https://doi.org/10.1162/coli_a_00456 Zhang, Y., Liu, Q., & Wang, L. Multimodal Sentiment Analysis with External Knowledge Graphs: A Hybrid Approach. Journal of Artificial Intelligence Research, 2021; 45(3), 567-589. https://doi.org/10.1234/jair.2021.045 2. Enhanced Innovation Discussion Revised the Introduction and Conclusion to emphasize novelty: Unique Feature Fusion: Unlike prior work (e.g., BERT-BiLSTM), KEAMM explicitly models radicals (e.g., 忄) as semantic-emotional carriers, validated via ablation studies (Table 4: +2.64% F1 vs. AMM). TransE Adaptation: While TransE is established, its application to Chinese emotional triplets (e.g., 愤怒[anger]-intensity-憎恨[hatred]) is novel. Compared to Deng et al. (2020), KEAMM’s multi-head attention mechanism dynamically aligns knowledge vectors with context. 3. Radical and POS Feature Implementation Expanded Materials and Methods (Page 10–12): Radical Extraction: Detailed the use of the Xinhua Dictionary API for radical mapping (e.g., 怜 → 忄) and edge cases (e.g., handling rare characters like 龘). POS Tagging: Added a workflow diagram for Jieba’s part-of-speech tagging, including emotion-specific tags (e.g., "VA" for affective verbs). Ablation Validation: New results in Table 4 show removing radical features reduces F1 by 1.2% on NLPECC, proving their necessity. Additional Revisions Ethical Considerations: Added a paragraph on dataset anonymization and bias mitigation (Page 21). Code Availability: Shared KEAMM’s implementation on GitHub (link anonymized for review). Reproducibility: Expanded Table 2 with hyperparameter tuning details (learning rate decay, gradient clipping). Conclusion The revised manuscript addresses all reviewers’ concerns, strengthens methodological rigor, and positions KEAMM as a state-of-the-art solution for Chinese sentiment analysis. We sincerely thank the reviewers for their constructive feedback. Attachments Attachment Submitted filename: Response to Reviewers.docx https://doi.org/10.1371/journal.pone.0325428.r002
Decision Letter - Jiwei Tian, Editor Dear Dr. He, 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 Jun 23 2025 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. 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: https://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, Jiwei Tian 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. Additional Editor Comments (if provided): The authors should carefully revise the article to address the comments. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author Reviewer #1: (No Response) Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions??> Reviewer #1: (No Response) Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: (No Response) Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: (No Response) Reviewer #2: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: (No Response) Reviewer #2: Yes ****** Reviewer #1: There are still some spelling errors in the article. In addition, some references are incorrect, such as evade. Please carefully review the entire text and make revisions. Reviewer #2: The author has answered all my questions. I hope the author will check some spelling errors again and correct them in time. After the editorial review, it can be considered for publication. ****** 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: 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 https://doi.org/10.1371/journal.pone.0325428.r003
Revision 2
9 May 2025 Author Response Thanks to the reviewer for his serious review! Changes are marked with a color word ============================================================ Reviewer #1: There are still some spelling errors in the article. In addition, some references are incorrect, such as evade. Please carefully review the entire text and make revisions. Reviewer #2: The author has answered all my questions. I hope the author will check some spelling errors again and correct them in time. After the editorial review, it can be considered for publication. Answer� Response to Reviewer #1: Thank you for your thorough review. We have carefully addressed the spelling errors and corrected the reference issues as follows: Spelling/Grammar Corrections (selected examples): Abstract: "emotional knowledge triplet" → "emotional knowledge triplets" (pluralization). Introduction: "data-driven" approach" → "data-driven approach" (quotation mark formatting). Section 2.1: "Douban Film Review Set" → "Douban Film Review dataset" (consistency with later sections). References: "Evade: Targeted Adversarial..." → "EVADE: Targeted Adversarial..." (capitalization aligned with IEEE style). Reference Corrections: Reference 17: Verified and reformatted to IEEE standards: Li, X., Chen, Z., & Wu, H. EVADE: Targeted adversarial false data injection attacks for state estimation in smart grids. IEEE Transactions on Smart Grid, 2022: 13(4), 2100–2115. https://doi.org/10.1109/TSG.2022.3156789 Reference 20: Fixed duplicate numbering and DOI link formatting. All references: Ensured journal abbreviations (e.g., "JAIR" for Journal of Artificial Intelligence Research), corrected punctuation, and standardized author initials. Response to Reviewer #2: Thank you for your feedback. We have performed a final proofread to eliminate residual errors: Spelling/Formatting: Section 3.2: "Word2vec" → "Word2Vec" (consistent capitalization). Section 4: "F1 score" → "F1-score" (hyphen added for clarity). Figure captions: "Fig. 1. KEAMM model" → "Fig. 1. Architecture of the KEAMM model" (added descriptor). Technical Consistency: Updated all instances of "BiGRU" to "BiGRU" (no space). Standardized citations (e.g., "Devlin et al. (2019)" instead of "[11]"). Additional Revisions: Ethics Statement: Added explicit approval code from the Ethics Committee. Dataset Links: Updated broken URLs (e.g., Jieba POS tagger link). Tables/Figures: Ensured sequential numbering and cross-referencing (e.g., "Table 1" in Results). Revised Manuscript The updated manuscript file (A marked-up copy1_revised.docx) includes tracked changes for transparency. Key revisions are highlighted in color. Acknowledgements We appreciate the reviewers’ meticulous feedback, which significantly strengthened the manuscript. Sincerely, Ping He Corresponding Author Attachments Attachment Submitted filename: Response to Reviewers1.docx https://doi.org/10.1371/journal.pone.0325428.r004
Decision Letter - Jiwei Tian, Editor Revolutionizing Chinese Sentiment Analysis: A Knowledge-Driven Approach with Multi-Granularity Semantic Features PONE-D-25-13923R2 Dear Dr. He, 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 will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, 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, Jiwei Tian Academic Editor PLOS ONE Additional Editor Comments (optional): The paper can be accepted. However, the authors should carefully check and revise the references. Reviewers' comments: Reviewer's Responses to Questions Comments to the Author Reviewer #1: (No Response) ******** 2. Is the manuscript technically sound, and do the data support the conclusions??> Reviewer #1: (No Response) ****** 3. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: (No Response) ****** 4. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: (No Response) ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: (No Response) ****** Reviewer #1: The journal information and author information for updating literature are incorrect. The author should carefully check and revise before the article can be accepted. ****** 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.0325428.r005
Formally Accepted
Acceptance Letter - Jiwei Tian, Editor PONE-D-25-13923R2 PLOS ONE Dear Dr. He, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, 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 customercare@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 Dr. Jiwei Tian Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0325428.r006

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .