DIETARY SUPPLEMENT REDUCES RADIATION-INDUCED MUSCLE DAMAGE
Bibliographic record
Abstract
Exposure to ionizing radiation (IR) is known to negatively impact musculoskeletal health. A Multi-Targeted Dietary Supplement (MTDS) has been formulated to protect against radiation-induced cellular damage. This study investigated the efficacy of this MTDS to ameliorate IR’s negative effects on skeletal muscle. Six experimental groups of ten-week-old male BALB/c mice were randomized (n=8/group) to either a control diet (CD) or the MTDS diet (MD). The MTDS was mixed into the CD, and mice were pre-fed the MD for 28 days. Each diet group was randomly divided into control (no irradiation) or an irradiated (IR) group and continued their respective diet until euthanized at day 21 or 28. IR-treated mice received 0.8 Gy fractions (day 0 and 14 or day 0, 7 and 14) for a cumulate dosage of 1.6 or 2.4 Gy, respectively. Tibialis anterior (TA), quadriceps, gastrocnemius and plantaris (GP), and soleus muscles were collected. Body weights remained unchanged at 1.6 Gy, while a reduction was observed at 2.4 Gy in the IR+CD group compared to the IR+MTDS group. The relative TA and GP muscle/body weight ratios were elevated in IR+CD groups, whereas the MD maintained lower muscle/body weight ratios. Cross-sectional area and min Feret values in the IR+CD were larger compared to control and the IR+MD groups demonstrating that the MTDS was protective against radiation-induced edema. Centrally-located nuclei (per mm2) in the IR+CD group were significantly elevated in both the TA and GP compared to control and the IR+MTDS group. Macrophage F4/80 staining showed a significant increase in macrophages within muscle fibers in the IR+CD groups, which was blunted by the MD. These results demonstrate that IR exposure leads to long-term negative changes on skeletal muscle and the MTDS attenuated these effects, positioning it as a potential therapeutic approach to IR exposure. Supported by the Canadian Space Agency.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 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".