Localization and Quantification of Pro-Opiomelanocortin mRNA and Glucocorticoid Receptor mRNA in Pituitaries of Suicide Victims
Bibliographic record
Abstract
Suicidal behavior has been associated with hypothalamic-pituitary-adrenal overactivity in humans, as measured by increased corticosteroid secretion. To investigate whether this overactivity is reflected at the pituitary level, we have studied the localization of pro-opiomelanocortin (POMC) mRNA, and glucocorticoid receptor (GR) mRNA, in human anterior pituitaries, and quantified these messages relative to controls. Pituitaries from 7 suicide victims and 11 cardiac deaths were sectioned into 10-microns slides, stained with thionin and processed for in situ hybridization using a riboprobe complementary to human POMC mRNA. To correct for possible postmortem cell loss, hybridization with P1B15, a cDNA complementary to rat cyclophillin mRNA, was used in adjacent sections. POMC mRNA containing cells were found to be localized in clusters and were highly associated with corticotropin-releasing hormone (CRH) receptors. In contrast, GR mRNA containing cells were distributed through the pituitary, although areas of increased density were associated with POMC mRNA cells. Quantification with a computerized image analysis system revealed a 25% increase in POMC message in suicide victims. Analysis of the corticotrophic cell clumps showed that the suicide victims had higher POMC mRNA density per cell (p = 0.04) and larger corticotrophic cell size (p = 0.04) than the cardiac death victims. No differences in GR mRNA were detected between the two groups, although GR and POMC mRNA levels were highly and significantly correlated (r = 0.8, p < 0.001). There were no differences in P1B15 message between the two groups. We conclude that in situ hybridization is a useful tool to study gene regulation in human neuroendocrine tissue and that suicide victims show evidence of chronic hypothalamic-pituitary-adrenal axis activation.
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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 | 0.000 |
| 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".