Local cold acclimation of the hand impairs thermal responses of the finger without improving hand neuromuscular function
Bibliographic record
Abstract
AIM: To investigate the effects of cold acclimation on the thermal response and neuromuscular function of the hand. METHODS: Ten healthy subjects [three female, seven male, age (mean +/- SD): 27.9 +/- 7.9 years] immersed their right hand in 8 degrees C water for 30 min, 5 days a week for 3 weeks. On the first and the last day, neuromuscular function of the first dorsal interosseus (FDI) muscle was tested. RESULTS: There was no significant change in maximal voluntary contraction strength or evoked contractile characteristics of the FDI after cold acclimation. Minimum finger temperature decreased significantly from 10.6 +/- 1.2 to 9.3 +/- 0.8 degrees C after 3 weeks (P < 0.01), with most of the decrease occurring after a single exposure. Mean finger temperature dropped significantly from 14.2 +/- 1.9 to 11.7 +/- 1.4 degrees C following cold acclimation (P < 0.05), with 90% of this adaptation occurring after 5 days. Onset time of cold-induced vasodilatation increased from 446 +/- 171 to 736 +/- 384 s (P < 0.05) and the amplitude decreased from 5.3 +/- 3.2 to 2.5 +/- 2.1 degrees C (P < 0.05). This was significantly different from the control group, who immersed their right hand on the first and last days only. CONCLUSION: These data suggest that cold acclimation does not enhance hand temperature or function but may put the hands at a greater risk of cold injury when exposed to the cold.
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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) | 0.001 | 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) | 0.003 | 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".