Characterization of the transcriptome and TCR of brain and cerebrospinal fluid infiltrated CD8+ T cells in an Alzheimer’s disease mouse model
Bibliographic record
Abstract
Abstract Alzheimer’s disease (AD) is a common form of dementia characterized by the accumulation of protein aggregates in the brain of older adults. It has been observed that CD8+ T cells, particularly CD8+ TEMRA cells, infiltrate the brain and cerebrospinal fluid (CSF) of AD patients. However, the precise role of these cells in the development and progression of AD is not well understood. In this study, we used single-cell RNA sequencing (scRNAseq) and single-cell T cell receptor sequencing (scTCRseq) to examine the CD8+ T cells in the brain and CSF of a mouse model of AD (5xFAD) and its wild-type (WT) littermate controls. The AD mice (age 40–70 weeks) used in our experiments have developed memory deficits. Our analysis revealed a significant increase in the number of CD8+ T cells in the brain and CSF of AD mice compared to WT controls (n=4, p<0.05). Furthermore, these cells displayed a distinct transcriptome profile characterized by increased expression of inflammatory pathways, compared to WT mice. Through TCR sequence analysis, we also observed significant clonal expansion of CD8+ T cells in AD mice compared to WT mice. These findings provide a starting point for further investigation into the role of infiltrating CD8+ T cells in the pathogenesis of AD in this mouse model.
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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 | 0.001 | 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 | 0.001 |
| 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".