Reductions in Microvascular Function can be Detected by Near‐infrared Spectroscopy (NIRS) following Ischemia‐Reperfusion in Early Postmenopausal Women
Bibliographic record
Abstract
The onset of menopause and accompanying changes to ovarian hormones often precedes endothelial dysfunction in women. In particular, accelerated impairments in microvascular function coincides with the loss of estrogen, as does impaired endothelial resilience to ischemia‐reperfusion (IR) injury. In early postmenopausal women (4 ± 1 years since menopause), we tested the hypothesis that the NIRS‐derived measurement of vascular responsiveness (reoxygenation slope, %.s −1 ) in the forearm could detect reductions in microvascular function following whole‐arm IR injury. In conjunction, brachial artery flow‐mediated dilation (FMD) and shear rate (area under curve; AUC peak ) were measured. Thirteen healthy, normotensive (116 ± 11/72 ± 9 mmHg) postmenopausal women (57 ± 3 years) were tested before (Pre IR ), after (Post IR ), and 15 minutes following IR (Post 15 ). The IR injury was achieved by inflating a cuff around the upper‐arm to 250 mmHg for 20 min followed by 15 min of reperfusion. The NIRS‐derived reoxygenation slope was lower Post IR (1.02 ± 0.56%.s −1 vs. 1.23 ± 0.64%.s −1 Pre IR ; p =0.04), but not at Post 15 (1.17 ± 0.51%.s −1 ; p =0.08). Brachial artery FMD was lower Post IR (3.57 ± 0.52% vs. 8.14 ± 2.44% Pre IR ; p < 0.001), but not at Post 15 (7.61 ± 1.89%; p = 0.54). Shear AUC peak were similar across tests ( p >0.05). Our findings suggest that the NIRS‐derived reoxygenation slope is a non‐invasive method that may detect transient impairments in forearm microvascular function, and may also be used to assess efficacy of therapeutic interventions in improving both vascular function and resilience in this population. Support or Funding Information Penn State Human Health and Development Endowment Award Schematic of study timeline Figure 1
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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 | 0.001 |
| 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".