Minimal muscle damage after a marathon and no influence of beetroot juice on inflammation and recovery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examined whether beetroot juice (BTJ) would attenuate inflammation and muscle damage following a marathon. Using a double blind, independent group design, 34 runners (each having completed ca. ∼16 previous marathons) consumed either BTJ or an isocaloric placebo (PLA) for 3 days following a marathon. Maximal isometric voluntary contractions (MIVC), countermovement jumps (CMJ), muscle soreness, serum cytokines, leucocytosis, creatine kinase (CK), high sensitivity C-reactive protein (hs-CRP), and aspartate aminotransferase (AST) were measured pre, post, and 2 days after the marathon. CMJ and MIVC were reduced after the marathon (P < 0.05), but no group differences were observed (P > 0.05). Muscle soreness was increased in the day after the marathon (BTJ; 45 ± 48 vs. PLA; 46 ± 39 mm) and had returned to baseline by day 2, irrespective of supplementation (P = 0.694). Cytokines (interleukin-6; IL-6, interleukin-8, tumour necrosis factor-α) were increased immediately post-marathon but apart from IL-6 had returned to baseline values by day 1 post. No interaction effects were evident for IL-6 (P = 0.213). Leucocytes increased 1.7-fold after the race and remained elevated 2 days post, irrespective of supplement (P < 0.0001). CK peaked at 1 day post marathon (BTJ: 965 ± 967, and PLA: 1141 ± 979 IU·L −1 ) and like AST and hs-CRP, was still elevated 2 days after the marathon (P < 0.05); however, no group differences were present for these variables. Beetroot juice did not attenuate inflammation or reduce muscle damage following a marathon, possibly because most of these indices were not markedly different from baseline values in the days after the marathon.
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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 | 0.000 |
| 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) | 0.000 | 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 it