Phosphate balance in phosphate supplemented and unsupplemented healthy subjects during and after hypokinesia
Bibliographic record
Abstract
OBJECTIVE: To demonstrate the effect of hypokinesia (HK) and post-HK on phosphate (Pi) imbalance and use of Pi with different Pi imbalance and different Pi consumption: were measured Pi balance, plasma Pi level and Pi loss during HK. METHODS: Experiments were conducted during the pre-experimental period of 30 days, and the HK period of 364-days and post-HK period of 30-days. Forty healthy male volunteers 24.2 +/- 2.0 yr, were divided into four groups: unsupplemented active control subjects (UACS), unsupplemented hypokinetic subjects (UHKS), supplemented active control subjects (SACS), and supplemented hypokinetic subjects (SHKS). All SACS and SHKS were supplemented with 0.6 mmol dicalcium-phosphate per kg body weight daily. RESULTS: During HK, Pi imbalance, serum Pi and calcium (Ca2+) levels, fecal Pi loss, and urine Ca2+ and Pi loss increased (P < 0.05) in SHKS and UHKS compared with pre-experimental values and the values in their respective active controls (SACS and UACS). The measured parameters were changed (P < 0.05) more in SHKS than in UHKS. During the initial 20-days of post-HK, serum Pi and Ca2+ levels, fecal P loss, and urine Pi and Ca2+ losses decreased (P < 0.05), while Pi imbalance remained (P < 0.05) depressed in SHKS and UHKS compared with UACS and SACS. The measured parameters were changed (P < 0.05) more in SHKS than in UHKS. CONCLUSION: The greater Pi imbalance with than without Pi supplementation shows that the risk of higher Pi imbalance is directly related to the magnitude of Pi intake. The higher Pi loss with higher than lower Pi imbalance shows that the risk of greater Pi loss is directly related to the magnitude of Pi imbalance. It is concluded that Pi imbalance increases more when the Pi consumption is higher and that Pi loss increases more with higher than lower Pi imbalance indicating that during HK Pi imbalance is due to the inability of the body to use Pi but not to the Pi shortage in the diet.
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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) | 0.001 | 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".