Assessing Sex Differences in Metabolic Disease on Vasculopathy Using the Vascular Health Index
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Investigation into vascular health and disease across elevated risk conditions has been intensively studied for many years. However, the ability to understand integrated vascular health status has been challenging, as most previous work has focused on specific outcomes, interventions, or potential mechanistic links. While these efforts have revealed many factors contributing to vasculopathy, challenges remain for comparing results across research groups, models, and conditions to understand vascular health status. In the present study, our objective was to quantify sex-dependent differences in peripheral and cerebral vascular health across metabolic disease. METHODS: Utilizing the vascular health index (VHI), a validated metric allowing for simultaneous assessment of vascular reactivity/endothelial function, vascular wall mechanics, and microvessel density within cerebral and skeletal muscle networks, we focus on the impact of elevated metabolic disease risk between male and female obese Zucker rats (OZR). In addition, we study VHI in female OZR following ovariectomy (OVX), with all outcomes compared to results from "healthy" lean Zucker rats (LZRs). RESULTS: Across all ages, male and female LZR demonstrated comparable VHI, although increased metabolic disease risk reduced both skeletal muscle and cerebral VHI in male OZR more rapidly, and to a greater extent, as compared to female OZR. Protection for VHI for female OZR with elevated disease risk was dependent on intact sex hormone cycling, as OVX in female OZR removed protection in VHI compared to normal female OZR. CONCLUSION: These results indicate that sex-based protections in peripheral and cerebral vascular health with metabolic disease in female OZR (versus males) are present at multiple levels of resolution and are dependent on normal female sex hormone cycling.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it