Spatial transcriptomic profiling of thalamic gene expression alterations following traumatic brain injury in male cFosTRAP2 mice using the CHIMERA model
Bibliographic record
Abstract
STUDY PURPOSE: Traumatic Brain Injury (TBI) is a leading cause of global death and disability. Heterogeneity in impact intensity, injury subtype and subsequent clinical presentation poses great challenges in development of therapeutic targets. Furthermore, translational biomarkers and temporal molecular signatures limit the relevance of animal models to human TBI. We used the Closed Head Impact Model of Engineered Rotational Acceleration (CHIMERA) model of impact-acceleration injury to investigate TBI-induced gene expression changes in male cFosTRAP2 mice (aged 3-4 months). A mild TBI was induced using CHIMERA where no skull fracture, structural damage or vascular haemorrhages was caused. DATA COLLECTED: We investigated transcriptomic changes in male cFosTRAP2 mouse brain at 7 days after a mild CHIMERA injury (2.1J impact energy) using 10x genomics Visium spatial transcriptomics technology (n=2 Sham, n=2 TBI). Spatial gene expression data was acquired from 2 sections (bregma -1.80mm and -3.2 mm) from each mouse brain and analyzed using the Seurat R package. We obtained transcriptomic information with strong replicate reproducibility for 55 micron circular regions tiling entire brain sections (2 sections/mouse/condition; 4992 sequenced regions/section; ~40,000 RNA-seq datasets). The dataset of greater than 1B reads yielded cell clusters with region-specific dysregulation of genes and a subset of data representing CHIMERA TBI responsive regions is presented here. The fold changes presented in this dataset are derived from pooled Visium data, where spots from all animals within each experimental group were integrated using Seurat prior to clustering and differential expression analysis. Thus, the reported average log2 fold changes reflect group level (pooled) expression patterns rather than per animal averages. All raw and processed spatial transcriptomics data, including per sample Visium outputs, are available through the NCBI Gene Expression Omnibus under accession number GSE282909. This repository includes count matrices, spatial coordinates, and sample-level metadata to enable independent reanalysis. DATA USAGE NOTES:
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".