Is There Enhanced Lymphatic Function in Upper Body Trained Females?
Bibliographic record
Abstract
BACKGROUND: Chronic physical activity results in adaptations in many aspects of human physiology, while specific training can directly influence structural changes. It remains unknown if habitual exercise influences upper extremity lymphatic function in females; thus, the purpose of this cross-sectional study was to compare different exercise stresses on lymphatic function in ten upper body trained females with ten untrained females. METHODS AND RESULTS: Participants underwent a maximal upper body aerobic test on an arm crank ergometer before undergoing three randomly assigned lymphatic stress tests. Lymphoscintigraphy was used to quantify lymphatic function. (99m)Tc-antimony colloid was injected into the third web space of each hand, followed by 1 min spot views taken with a gamma-radiation camera. The maximal stress test required individuals to repeat their initial maximal exercise test. The subjects were then imaged every 10 min until 60 min were reached. The submaximal stress test involved arm cranking for 2.5 min at 0.6 W x kg(-1), followed by 2.5 min of rest, repeated for 60 min. The final stress test was a 60 min seated resting session. The clearance rate (CR) and axillary uptake (AX) were determined. Only AX post maximal exercise was significantly different between trained and untrained, p=0.009. All other measures of lymphatic function between groups were similar. CONCLUSION: This study demonstrates no significant difference in lymphatic function between upper body trained and untrained females.
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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 | 0.000 |
| 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) | 0.006 | 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".