The high dose of vitamin D supplementation combined with yoga training improve the leukocytes cell survival-related gene expression in breast cancer survivors
Bibliographic record
Abstract
BACKGROUND: This study aimed to examine the effect of yoga training combined with vitamin D supplementation on the expression of survival-related genes in leukocytes and psycho-physical status in breast cancer survivors. METHODS: Thirty breast cancer survivor women (age, 48 ± 8 yrs) were randomly assigned into three groups: high dose (4000 IU) of vitamin D supplementation (HD) (n = 10); yoga training with a high dose of vitamin D (Y + HD); (n = 10); yoga training with a low dose (2000 IU) of vitamin D (Y + LD) (n = 10). Participants performed the Hatha yoga style twice a week. Blood samples and a battery of psychological and physical tests were taken before and after the completion of interventions. Expression of p53, NF-κB, Bcl2, and Bax genes was measured in leukocytes. RESULTS: Body fat percentage (ηp2 = 0.36), shoulder flexibility (ηp2 = 0.38), Rockport walk tests (ηp2 = 0.49), and anxiety (ηp2 = 0.52) were significantly improved in both the Y + HD and Y + LD groups compared to the HD group (p < 0.05). P53 was significantly over-expressed in the Y + HD group while Bcl2 upregulated in both the Y + HD and Y + LD groups. NF-κB and Bax expression downregulated in all groups but were not statistically significant. CONCLUSION: yoga training combined with low and high doses of VD improved physical fitness and psychological measures while only in combination with a high dose of VD positively modified the leukocytes cell survival-related gene expression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".