Ultrastructural features of psychological stress resilience in the brain: a microglial perspective
Bibliographic record
Abstract
Psychological stress is the major risk factor for major depressive disorder. Sustained stress causes changes in behaviour, brain connectivity and in its cells and organelles. Resilience to stress is understood as the ability to recover from stress in a positive way or the resistance to the negative effects of psychological stress. Microglia, the resident immune cells of the brain, are known players of stress susceptibility, but less is known about their role in stress resilience and the cellular changes involved. Ultrastructural analysis has been a useful tool in the study of microglia and their function across contexts of health and disease. Despite increased access to electron microscopy, the interpretation of electron micrographs remains much less accessible. In this review, we will first present microglia and the concepts of psychological stress susceptibility and resilience. Afterwards, we will describe ultrastructural analysis, notably of microglia, as a readout to study the mechanisms underlying psychological stress resilience. Lastly, we will cover nutritional ketosis as a therapeutic intervention that was shown to be effective in promoting psychological stress resilience as well as modifying microglial function and ultrastructure.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".