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Reporting quality of animal research in journals that published the ARRIVE 1.0 or ARRIVE 2.0 guidelines: a cross-sectional analysis of 943 studies.
Cardiovasc Diagn Ther
December 2024
Editorial Office, AME Publishing Company, Hong Kong, China.
Background: The adherence to the Animals in Research: Reporting In Vivo Experiments (ARRIVE) guidelines across the journals that initially published the guidelines and if adherence has improved since the guidelines update, remains unknown. We aimed to quantify the level of adherence and analyze factors that might influence reporting quality among these journals.
Methods: This cross-sectional study retrospectively analyzed interventional animal experiments published in journals that released ARRIVE 1.
Immunogenomic determinants of exceptional response to immune checkpoint inhibition in renal cell carcinoma.
Nat Cancer
January 2025
Department of Hematopoietic Biology and Malignancy, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Immune checkpoint inhibitors can lead to 'exceptional', durable responses in a subset of persons. However, the molecular basis of exceptional response (ER) to immunotherapy in metastatic clear cell renal cell carcinoma (mccRCC) has not been well characterized. Here we analyzed pretherapy genomic and transcriptomic data in treatment-naive persons with mccRCC treated with standard-of-care immunotherapies: (1) combination of programmed cell death protein and ligand 1 (PD1/PDL1) and cytotoxic T lymphocyte-associated protein 4 inhibitors (IO/IO) or (2) combination of PD1/PDL1 and vascular endothelial growth factor (VEGF) receptor inhibitors (IO/VEGF).
View Article and Find Full Text PDFEditorial Comment on "Optimizing Care for Women through Gynecologic Organ Considerations During Cystectomy: A Pre-Operative Checklist of Important Considerations".
Urology
January 2025
Columbia University Irving Medical Center, Department of Urology. Electronic address:
The TRIPOD-LLM reporting guideline for studies using large language models.
Nat Med
January 2025
Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
Large language models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present transparent reporting of a multivariable model for individual prognosis or diagnosis (TRIPOD)-LLM, an extension of the TRIPOD + artificial intelligence statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion.
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