Microglia as a Hub for Suicide Neuropathology: Future Investigation and Prevention Targets
Bibliographic record
Abstract
Suicide is a complex public health challenge associated worldwide with one death every 40 s. Research advances in the neuropathology of suicidal behaviors (SB) have defined discrete brain changes which may hold the key to suicide prevention. Physiological differences in microglia, the resident immune cells of the brain, are present in post-mortem tissue samples of individuals who died by suicide. Furthermore, microglia are mechanistically implicated in the outcomes of important risk factors for SB, including early-life adversity, stressful life events, and psychiatric disorders. SB risk factors result in inflammatory and oxidative stress activities which could converge to microglial synaptic remodeling affecting susceptibility or resistance to SB. To push further this perspective, in this Review we summarize current areas of opportunity that could untangle the functional participation of microglia in the context of suicide. Our discussion centers around microglial state diversity in respect to morphology, gene and protein expression, as well as function, depending on various factors, namely brain region, age, and sex.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".