PRECISE TBI Model Catalog: Increasing Accessibility and Reproducibility in TBI research

Area of Science:

• Neuroscience
• Biomedical Research
• Data Science

Background:

• Preclinical traumatic brain injury (TBI) research faces challenges in clinical translation due to fragmented resources and inconsistent reporting of experimental variables.
• Existing experimental models for TBI vary significantly in mechanism, parameters, species, and age, hindering cross-study comparisons and reproducibility.

Purpose of the Study:

• To introduce the PRECISE-TBI model catalog, a centralized and queryable resource for consolidating metadata from published preclinical TBI studies.
• To enhance transparency, reproducibility, and data sharing in TBI research by integrating curated annotations and linking to protocols and datasets.

Main Methods:

• Developed a centralized catalog by integrating curated annotations from over 450 published preclinical TBI studies.
• Consolidated metadata including age, sex, strain, model type, device, and injury parameters for each study.
• Linked catalog entries to available protocols and datasets to promote FAIR data principles.

Main Results:

• Analysis revealed initial gaps in reporting critical variables such as device, age, and weight.
• Reporting of sex has improved significantly, with over 90% of recent studies including this information.
• Strain reporting is generally consistent, particularly for the C57 mice substrain.

Conclusions:

• The PRECISE-TBI model catalog serves as a valuable tool for enhancing study design and reproducibility in preclinical TBI research.
• The catalog facilitates cross-study comparisons, identifies reporting gaps, and connects literature to essential resources like protocols and datasets.
• This initiative advances FAIR data principles within the TBI research community.