Noninvasive measurements to evaluate the effects of military training on the human autonomic nervous system
Bibliographic record
Abstract
Abstract Background: Chinese university freshmen receive 4-weeks military training that involved moderate to intense physical exercise. Studies have demonstrated heterogeneous effects of exercise on the autonomic nervous system. Objective: To evaluate the effects of training on the autonomic nervous system noninvasively using electrogastrograms, heart rate variability (HRV), pulse rate, and the sympathetic skin response (SSR). Methods: Twenty freshmen received all assessments in the fasting state and after a standard meal: (1) one week before the training, (2) at the end of the second week of the training, and (3) one week after the training. Results: (1) The training had a significant effect on meal-induced gastric pacemaker activity. Before the training, a standard meal did not increase the dominant frequency of gastric slow waves, but the frequency increased during and after the training; (2) The preprandial high frequency (HF), low frequency (LF), and very low frequency (VLF) components of heart rate variability decreased significantly after the training. The ratio of the LF and HF (LF/HF) of the heart rate variability (HRV) did not significantly change after a meal or training condition. The basal pulse rate did not change. The latencies of the sympathetic skin response (SSR), as measured in the arm muscle, increased in response to the training. Conclusion: Military training affects meal-induced changes in gastric pacemaker activity, causes a marked reduction of the vagal tone to the heart with maintenance of the vagal-sympathetic balance, and its effects on SSR may reflect a reduction in sympathetic tone.
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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) | 0.002 | 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".