Vascular regenerative cell content in South Asians: the key learnings
Bibliographic record
Abstract
PURPOSE OF REVIEW: We aim to provide a comprehensive examination of the literature linking elevated rates of cardiovascular disease (CVD) in individuals of South Asian ethnicity with the severity of circulating vascular regenerative cell exhaustion. RECENT FINDINGS: Recent findings have demonstrated reduced bioavailability of pro-vascular progenitor cell subsets in individuals with T2D and obesity. Depletion of vascular regenerative cells in the bone marrow - coupled with decreased mobilization into circulation - can negatively impact the capacity for vascular repair and exacerbate CVD risk. Several recent studies have established that although South Asian individuals possess similar inflammatory cell burden compared with other ethnicities, they exhibit marked decreases in vessel regenerative hematopoietic progenitor cells and monocyte subsets. Validation of these findings and investigation the functional capacity of vascular regenerative cell subsets to mediate vessel repair is highly warranted. SUMMARY: Vascular regenerative cells play a key role coordinating angiogenic and arteriogenic vessel remodelling. Recent studies have demonstrated that South Asian individuals with T2D show severe depletion in circulating vascular regenerative cell subsets. Because the reversal of vascular regenerative cell exhaustion by current glucose-lowering pharmaceutical agents has recently been documented, early intervention to bolster vascular regenerative cell content may prevent CVD co-morbidities in South Asian individuals with cardiometabolic disease.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".