Beneficial Pleiotropic Anti‐Depressive Effects of Cardiovascular Disease Risk Factor Interventions in Metabolic Syndrome
Bibliographic record
Abstract
While the increased prevalence and severity of clinical depression and elevated cardiovascular disease risk represent two vexing public health issues, the growing awareness of their combined presentation presents a special challenge for not only integrated health outcomes, but also for effective treatment. The obese Zucker rat (OZR), a model of the metabolic syndrome with significant elevations in CVD risk spontaneously develops significant depressive symptoms in parallel with the progression of the metabolic syndrome; thus representing a particularly compelling model for study. To begin to interrogate relationships between CVD risk factors and depressive symptom severity, we chronically treated OZR with traditional clinically relevant interventions against CVD risk to determine impacts on not only vascular function but also on behavioral outcomes and depressive symptom severity. While most of the interventions (chronic exercise, anti‐hypertensive, anti‐dyslipidemia, anti‐diabetic) were differentially effective at improving vascular function, only those interventions that also resulted in a significant improvement to oxidant stress, inflammation and arachidonic acid metabolism (PGI 2 vs. TxA 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 was dependent upon maintaining arachidonic acid metabolism and vascular oxidant stress together, with preventing changes in vascular stiffness, mean arterial pressure and plasma cortisol concentration (together) also being important. This initial study provides for a very compelling framework from which to further interrogate the links between CVD risk and cognitive/behavioral status, and begins to provide insight into mechanistic links and potentially effective avenues for intervention. Support or Funding Information National Institutes of Health, American Heart Association
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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 | 0.001 |
| 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".