Widespread and cell-type-specific transcriptomic reorganization following mild traumatic brain injury
Bibliographic record
Abstract
Knowledge of how traumatic brain injury (TBI) alters the brain is urgently needed. A major challenge to this understanding is that TBI is a multiscale problem capable of evoking a host of perturbations across the brain and often presents large subject-to-subject variability. To circumvent these challenges, here, we employ the murine closed-head impact model of engineered rotational acceleration (CHIMERA) TBI model to produce mild, diffuse TBI reproducibly across mice in the subacute phase and apply spatial transcriptomics to study the multiscale effects of TBI. In doing so, we identify generalizable signatures of TBI that are present across brain regions, as well as a variety of brain-region- and cell-type-specific dysregulation. This dysregulation includes unexpected susceptibility of astrocytes in the molecular layer of the dentate gyrus, as well as dramatic gene expression changes in neurons of the thalamus. Ultimately, our work here helps to distill the multiscale complexity of TBI into interpretable brain regions, cell types, and molecular sequelae.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".