Citrulline Supplementation Improves Microvascular Function and Muscle Strength in Middle-Aged and Older Adults with Type 2 Diabetes
Bibliographic record
Abstract
Background: Patients with type 2 diabetes (T2D) develop vascular complications due to arginine deficiency-induced microvascular endothelial dysfunction, which is related to the loss of muscle strength (MS) associated with aging. Thus, increased nitric oxide (NO)-mediated vasodilation may improve MS. We investigated the impact of the NO precursor citrulline on microvascular function (endothelial and muscle reactivity) and MS in T2D patients. Methods: Sixteen participants with T2D (53–72 years, nine females) were randomized to citrulline supplementation (CITS, 6 g/day) or placebo for 4 weeks prior to an 8-week washout period, followed by the opposite supplement for 4 weeks in a crossover trial. Endothelial function (log-transformed reactive hyperemia index, LnRHI), forearm muscle reactivity (near-infrared spectroscopy-derived tissue oxygen index (TOI) reperfusion indices), plasma arginine levels (ARG), and handgrip strength (HGSrel) and calf MS (CMSrel) adjusted for body weight were measured at baseline and 4 weeks for each condition. Results: CITS increased the LnRHI (∆0.11 ± 0.16 vs. ∆−0.08 ± 0.24, p < 0.05), TOI range (∆2.6 ± 3.3 vs. ∆−1.5 ± 4.8%, p < 0.01), TOI hyperemic response (∆1.2 ± 1.4 vs. ∆−0.6 ± 2.8%, p < 0.05), TOI 2 min area under the curve (∆154 ± 187 vs. ∆−41 ± 194%/s, p < 0.01), ARG (∆43 ± 28 vs. ∆1 ± 16μM/L, p < 0.001), CMS (∆1.5 ± 2.8 vs. ∆−0.3 ± 1.2 kg, p < 0.05), and CMSrel (∆0.02 ± 0.03 vs. ∆−0.01 ± 0.02 kg/kg, p < 0.01) compared to placebo. The improvements in LnRHI and CMSrel were correlated (r = 0.37, p < 0.05). Conclusions: This study showed that CITS improves microvascular endothelial function, muscle microvascular reactivity, and calf muscle strength in middle-aged and older patients with T2D.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".