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Many thanks for addressing the previous comments from the two reviewers. They are both content with your responses.
[# PeerJ Staff Note - this decision was reviewed and approved by Paula Soares, a PeerJ Section Editor covering this Section #]
Upon careful consideration of the revised manuscript, I am impressed by the substantial improvements made, effectively elevating its quality to fulfill our publication criteria. The authors' dedication to addressing the feedback received previously is praiseworthy, resulting in a manuscript that convincingly justifies its acceptance. I wholeheartedly endorse its publication and am enthusiastic about its potential impact on our field of research.
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I have no further comments as the authors have properly addressed my previous comments in the revised version of the manuscript.
Your manuscript has been reviewed by two experts in the field, each of whom have raised a number of different issues that you will need to address by revising the manuscript. Please note that Reviewer 2 has provided their comments as a separate file, which I have attached here.
I hope you find the reviewer comments constructive and helpful.
**PeerJ Staff Note:** Please ensure that all review, editorial, and staff comments are addressed in a response letter and that any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate.
The study brings a significant contribution towards understanding pyroptosis's role in HNSCC, potentially influencing chemotherapy approaches. The introduced multi-gene model is quite fascinating and deserves more in-depth study. Yet, addressing the raised concerns about statistical depth, clarity in visualization, logic in research, and experiment specifics would greatly bolster the manuscript's impact and trustworthiness. I reckon it could be ready for publication post the advised minor tweaks.
1. A deeper dive into the survival analysis details, especially around the Cox proportional hazards model's assumptions and their verification, would solidify the statistical findings' foundation.
2. Adding confidence intervals to the Kaplan-Meier survival plots can offer a clearer picture of survival probabilities over time, enhancing data interpretation.
3. Considering your innovative four-gene pyroptosis model for HNSCC, the study 'A four-pseudogene classifier identified by machine learning serves as a novel prognostic marker for survival of osteosarcoma' could be very pertinent. Their method of crafting a prognostic model via machine learning and pseudogene analysis might offer insightful parallels and insights. Mentioning this research could enrich your model's discussion, spotlighting its wider impact and innovative aspect.
4. The paper suggests a new four-gene pyroptosis model but lacks a full discussion on why these genes were picked over others. Delving into the biological significance and selection logic for these genes would enhance the paper's logical progression and scientific grounding.
More precise details on cell culture conditions, like specific passage numbers for in vitro tests, are crucial for reproducibility and contextual understanding of the experiments' outcomes.
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The research question is well defined but not well studied using the current experimental design. The rationality in gene selection should be better explained. Otherwise, other bioinformatics methods should be applied to identify best performing models for predicting the response to chemotherapy.
Some results should be described and interpreted properly.
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