Evidence of Reduced Agmatine Concentrations in the Cerebral Cortex of Suicides
Bibliographic record
Abstract
Background: The polyamines are a group of ubiquitous low-molecular-weight aliphatic molecules that play an essential role in various physiological functions of the mammalian CNS. Previous literature has indicated alterations in the expression of polyamine-related genes in the brains of individuals who died by suicide, including downregulation of spermidine/spermine N1-acetyltransferase, a key enzyme involved in polyamine catabolism. One such polyamine, agmatine, has been shown to act as an antidepressant in animal models of depressive-like behavior. However, agmatine concentrations have not been explored in postmortem human brain of individuals who died by suicide. Methods: To measure agmatine in postmortem human brain tissue, we employed our previously published high-resolution capillary gas chromatography in combination with mass spectrometry method. Using this method, we analyzed agmatine levels in a total of 120 tissue samples from Brodmann areas 4, 11, and 44 of 40 male subjects comprising controls (n=13), individuals who died by suicide and met criteria for major depressive disorder (n=14), and subjects who died by suicide and did not meet criteria for major depressive disorder (n=13). Results: Agmatine fell within the expected nanomolar range and was significantly reduced in the cortex of suicides, irrespective of meeting criteria for major depressive disorder compared with controls. Conclusions: This is the first gas chromatography-mass spectrometry study to analyze agmatine concentrations in human postmortem brain of individuals who died by suicide. These results add to our mechanistic understanding of the role that the polyamine stress response pathway may play in the neurobiology of major depression and/or suicide.
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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".