Microglial heterogeneity in aging and Alzheimer's disease: Is sex relevant?
Bibliographic record
Abstract
Neurodegenerative diseases and their associated cognitive decline are known to be more prevalent during aging. Recent evidence has uncovered the role of microglia, the immunocompetent cells of the brain, in dysfunctions linked to neurodegenerative diseases such as is Alzheimer's disease (AD). Similar to other pathologies, AD is shown to be sex-biased, with females being more at risk compared to males. While the mechanisms driving this prevalence are still unclear, emerging data suggest the sex differences present in microglia throughout life might lead to different responses of these cells in both health and disease. Furthermore, microglial cells have recently been recognized as a deeply heterogeneous population, with multiple subsets and/or phenotypes stemming from diverse parameters such as age, sex or state of health. Therefore, this review discusses microglial heterogeneity during aging in both basal conditions and AD with a focus on existing sex differences in this process.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".