Beneficial Pleiotropic Antidepressive Effects of Cardiovascular Disease Risk Factor Interventions in the Metabolic Syndrome
Bibliographic record
Abstract
Background Although the increased prevalence and severity of clinical depression and elevated cardiovascular disease risk represent 2 vexing public health issues, the growing awareness of their combined presentation compounds the challenge. The obese Zucker rat, a model of the metabolic syndrome, spontaneously develops significant depressive symptoms in parallel with the progression of the metabolic syndrome and, thus, represents a compelling model for study. The primary objective was to assess the impact on both cardiovascular outcomes, specifically vascular structure and function, and depressive symptoms in obese Zucker rats after aggressive treatment for cardiovascular disease risk factors with long‐term exercise or targeted pharmacological interventions. Methods and Results We chronically treated obese Zucker rats with clinically relevant interventions against cardiovascular disease risk factors to determine impacts on vascular outcomes and depressive symptom severity. While most of the interventions (chronic exercise, anti‐hypertensive, the interventions (long‐term exercise, antihypertensive, antidyslipidemia, and antidiabetic) were differentially effective at improving vascular outcomes, only those that also resulted in a significant improvement to oxidant stress, inflammation, arachidonic acid metabolism (prostacyclin versus thromboxane A 2 ), and their associated sequelae were effective at also blunting depressive symptom severity. Using multivariable analyses, discrimination between the effectiveness of treatment groups to maintain behavioral outcomes appeared to be dependent on breaking the cycle of inflammation and oxidant stress, with the associated outcomes of improving endothelial metabolism and both cerebral and peripheral vascular structure and function. Conclusions This initial study provides a compelling framework from which to further interrogate the links between cardiovascular disease risk factors and depressive symptoms and suggests mechanistic links and potentially effective avenues for intervention.
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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".