Impact Of Caffeine On Exercising Forearm Blood Flow And VO2 In Type II Diabetes
Bibliographic record
Abstract
Evidence is emerging that exercise intolerance in persons with type II diabetes (T2D) may be partly due to a reduced muscle oxygen delivery. Furthermore, the reduced oxygen delivery may be due to a reduced ability of red blood cells (RBCs) to evoke ATP-mediated vasodilation in response to low oxygen. Additional evidence suggests that caffeine can enhance low oxygen-evoked ATP release from RBCs. PURPOSE: To determine 1) whether forearm blood flow (FBF), forearm oxygen consumption (VO2), and exercise tolerance during forearm exercise is reduced in persons with T2D compared to control (CON) subjects, and 2) whether these deficits are attenuated by caffeine ingestion. METHODS: T2D (n = 4) and CON (n = 4) subjects performed rhythmic forearm handgrip exercise at an intensity equivalent to 17.5 kg until "task failure" or 20 minutes of exercise was reached, after having consumed either a caffeine (5mg/kg; Caff) or placebo (Pl) capsule. FBF (Doppler and Echo ultrasound of the brachial artery), VO2 and lactate efflux (deep forearm vein blood sampling), and mean arterial pressure (MAP; finger photoplethysmography) were quantified at the end of each minute of exercise. RESULTS: Data are mean ±SE. Steady state FBF (ml/min) was similar across groups and treatment conditions (CONCaff 553.80 ± 82.35, CONPl 583.42 ± 112.62, T2DCaff 523.33 ± 105.39, T2DPl 569.08 ± 134.20, NS), and this was due to similar MAP and forearm vascular conductance (across groups and treatment conditions, NS). VO2 and Time to Task Failure (TTF) were not different between groups and treatment conditions (NS). However, there was a strong positive relationship between steady state FBF and TTF (r2=0.763) when examined across all subjects. CONCLUSIONS: In the exercise model utilized, persons with T2D do not have impaired cardiovascular responsiveness or reduced exercise tolerance, and caffeine did not enhance responses in either group. Differences in exercising MBF may be an underlying mechanism regarding differences in exercise tolerance across individuals, independent of disease status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".