Title page and abstract

Submit an editable manuscript in clear English. Provide a separate title page with the full title, author names, institutional affiliations and countries, the corresponding author’s contact information and available ORCID identifiers. Identify the article type and provide the text word count and the number of figures and tables. Place identifying funding, acknowledgment and contribution details on this file for double-anonymous review.

Research and systematic review abstracts should use Background, Methods, Results and Conclusions. Include the study design, relevant sample size, principal estimates and uncertainty, and a conclusion consistent with the results. Give the trial registration identifier when applicable. Avoid unsupported priority claims or conclusions based only on statistical significance. Supply three to six specific keywords, using MeSH terms where suitable.

Main text and reproducibility

• Introduction: identify the scientific problem, the evidence gap and the objective or hypothesis.
• Methods: describe design, setting, selection criteria, experimental procedures, materials, outcome definitions, ethical authorization and analysis in sufficient detail for assessment and replication.
• Results: report the findings in the planned sequence, including relevant exclusions, missing observations and negative results. Distinguish prespecified from exploratory analyses.
• Discussion: interpret findings against prior evidence, address methodological limitations and uncertainty, and explain the appropriate biological or clinical implications.

For patient-derived tissues, organoids, xenografts and cell-based experiments, document source, consent or authorization, model characteristics, authentication and contamination testing as appropriate. Identify key reagents by supplier and catalog number and include RRIDs where available. Report drug identity, exposure conditions and relevant controls. Public-dataset studies must identify accessions, sample selection and the relationship between discovery and validation cohorts.

Statistics and quantitative claims

Define the experimental unit and distinguish independent biological samples from repeated measurements. Explain sample-size reasoning, allocation, blinding, exclusions and missing-data handling. Identify statistical tests and their assumptions, effect measures, confidence intervals and correction for multiple comparisons. Give exact P values where appropriate and avoid treating technical replicates as independent biological observations.

Survival analyses should define endpoints, follow-up, censoring and the relevant model assumptions. Predictive models require a transparent development and evaluation procedure, clinically meaningful performance measures and an assessment of overfitting. Training, tuning and test datasets must be separated at the appropriate patient or study level.

Figures, tables and supplementary files

Number figures and tables in order of citation. Supply complete legends defining abbreviations, sample sizes, replicates, error bars and statistical comparisons. Tables should be editable. Use legible labels, accessible colors and appropriate units. Provide original uncropped blots and other source images needed to verify the displayed findings. Do not include identifiable patient material without explicit publication consent.

Supplementary files should have descriptive names and be cited in the text. Explain their contents and provide usable formats. Consult Image & Data Integrity for image preparation requirements.

References and declarations

Use a consistent Vancouver-style numbered reference system, numbered in order of first citation. Check authors, titles, journal details, dates and persistent identifiers against the original sources. Mark preprints clearly and avoid citing retracted work as valid evidence without explaining its status.

Provide separate statements for ethical approval, consent to participate and consent for publication where relevant, funding and sponsor roles, competing interests, author contributions, data and code availability, and relevant AI use. Submit the applicable reporting checklist. Before uploading files, consult Submission Checklist.