Magnesium loss in magnesium deficient subjects with and without physical exercise during prolonged hypokinesia
Bibliographic record
Abstract
OBJECTIVE: To show the effect of hypokinesia (HK; diminished movement) on magnesium (Mg2+) loss in Mg2+ deficient subjects and the effect of physical exercise and on Mg2+ deficiency with and without physical exercise: Mg2+ balance, serum Mg2+ concentration and Mg2+ loss were measured. METHODS: Studies were conducted on 30 healthy male volunteers during a pre-experimental period of 30 days and an experimental period of 364 days. They were divided equally into three-groups: unrestricted active control subjects (UACS), continuous hypokinetic subjects (CHKS) and periodic hypokinetic subjects (PHKS). The UACS group ran average distances of 9.3 +/- 1.2 km.day-l; the CHKS group walked average distances of 0.9 +/- 0.2 km.day-l; and the PHKS group walked and ran average distances of 0.9 +/- 0.2 km and 9.3 +/- 1.2 km.day-l for 5-and 2-days per week, respectively. RESULTS: Mg2+ deficiency, serum Mg2+ level, fecal and urine Mg2+ loss increased (P < 0.05), in the PHKS and CHKS groups compared with their pre-experimental values and the values in the UACS group. However, serum Mg2+ concentration, urine and fecal Mg2+ loss and Mg2+ deficiency increased more (P < 0.05) in the PHKS group than in the CHKS group. CONCLUSIONS: Mg2+ deficiency is more evident with than without physical exercise and Mg2+ loss is exacerbated more with higher than lower Mg2+ deficiency. This indicates that Mg2+ deficiency with and without physical exercise and Mg2+ loss with higher and lower Mg2+ deficiency is due to inability of the body to use Mg2+ and more so when physically healthy subjects are submitted to prolonged periodic than continuous hypokinesia.
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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) | 0.001 | 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) | 0.001 | 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".