Extended Evaluation of Serotonin Transporter Gene Functional Polymorphisms in Subjects with Post-Stroke Depression
Bibliographic record
Abstract
OBJECTIVE: As an extension of our previous observation, relating a serotonin transporter gene-linked promoter region (5-HTTLPR) diallelic functional polymorphism (short [S] and long [L] alleles) to the risk of post-stroke major depression (PSD), this study investigated the role of 2 other functional polymorphisms of the serotonin transporter gene (5-HTT) in the same sample of subjects with PSD. METHOD: In a clinical sample of 26 patients with PSD and 25 unrelated nondepressed stroke patients of Caucasian descent, we examined the frequencies of a functional single nucleotide variant (A/G) within the promoter region (rs25531) and located in L (16-repeat) and S (14-repeat) alleles of 5-HTTLPR, and a variable number tandem repeat (VNTR) polymorphism in intron 2. RESULTS: There were significant intergroup differences in the allelic frequencies of 5-HTTLPR/rs25531 (SA, LA, and LG) (P < 0.05) and in the combined frequencies of lower-expressing alleles (SA and LG) and higher-expressing alleles (LA) (P < 0.025) between subjects with PSD and nondepressed stroke. However, the differences in the combined frequencies of lower-expressing (SA/SA, SA/LG, and LG/LG), intermediate-expressing (SA/LA and LA/LG), and higher-expressing (LA/LA) genotypes of 5-HTTLPR were not significant. Further, no significant intergroup differences were found in the allelic and genotypic frequencies of the intron 2 VNTR. CONCLUSIONS: These findings strengthen the support for an association between PSD and lower-expressing alleles of 5-HTTLPR.
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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 | 0.001 |
| 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".