A post-mortem investigation of the locus coeruleus-noradrenergic system in resilience to childhood abuse
Bibliographic record
Abstract
Abstract Childhood abuse (CA) is one of the strongest lifetime predictors of major depressive disorder (MDD) and suicide. However, some individuals exposed to CA are resilient, avoiding the development of psychopathology. Recently, the locus coeruleus-noradrenergic (LC-NE) system has been involved in resilience following stressful events at adulthood. We investigated how a history of CA affects the integrity of the LC-NE system at the molecular and cellular level in human post-mortem brain samples of depressed suicides, and whether differential neurobiological mechanisms can be revealed in resilient individuals. Anatomical analysis revealed that CA-induced MDD and suicide is associated with decrease in LC-NE neurons density. RNA sequencing of laser captured LC-NE neurons highlighted differentially expressed genes, principally in the RES-CA group. Resilience to CA involves specific neurobiological adaptations in the LC-NE system that potentially protect against the loss of LC-NE neurons and the negative long-term outcome of CA-induced depression and suicide. Our results provide insights into potential therapeutic targets for preventing or treating CA-induced MDD.
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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".