Chronic effects of venlafaxine on synaptophysin and neuronal cell adhesion molecule in the hippocampus of cerebral ischemic miceThis paper is one of a selection of papers published in this special issue entitled “Second International Symposium on Recent Advances in Basic, Clinical, and Social Medicine” and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Venlafaxine, a novel antidepressant, inhibits serontonin and norepinephrine reuptake in the presynaptic cleft. Unlike typical selective serontonin reuptake inhibitors (SSRIs), venlafaxine may have modulatory effects on nerve terminals and neuronal plasticity. Our preliminary data found that 5 mg.kg-1.d-1 of venlafaxine treatment prevented decreased synaptophysin (SYP) in the hippocampus, which results from chronic restrained stress in the rat model. The present study investigates whether venlafaxine regulates alterations of synaptophysin and neuronal cell adhesion molecule (NCAM) in a post-stroke depression mouse model. We compared the expression level of SYP and NCAM in the hippocampus of global cerebral ischemic (GCI) mice treated with different doses of venlafaxine using immunohistological and Western blot analysis. Pre-treatment with intraperitoneal injection of venlafaxine (2.5 and 5.0 mg.kg-1.d-1) for 14 days significantly prevented the decrease of SYP in the hilus area of the hippocampus in vehicle-treated GCI mice. NCAM was significantly higher in the hippocampus of vehicle-treated GCI mice, and pretreatment with venlafaxine prevented alterations of NCAM, with the high-dose venlafaxine group comparable with vehicle-sham mice. The results suggest the alteration of neuronal remodeling proteins in the hippocampus may be an underlying mechanism of venlafaxine in treating post-stroke depression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".