Improving Body Composition May Reduce the Immune and Inflammatory Responses of Firefighters Working in the Heat
Bibliographic record
Abstract
OBJECTIVE: We hypothesized that different body composition and fitness of firefighters would affect immune and inflammatory activity after working in the heat. METHODS: Forty-two firefighters worked in the heat (100 ± 5 °C). Changes in leukocytes, platelets, tumor necrosis factor (TNF-α), and C-reactive protein (CRP) were analyzed based on body composition (DXA) and aerobic fitness (VO2max). RESULTS: Higher baseline leukocytes were observed for high body fat (P = 0.002) and low lean mass (P = 0.023) resulting in the highest peak values. Additionally, significantly lower values for TNF-α were observed with high lean mass at all time points. Platelets were unaffected by fitness or body composition. Furthermore, body mass index (BMI) and VO2max played no role. CONCLUSIONS: Minimizing body fat and increasing lean mass may reduce immune and inflammatory activity of firefighters in the heat.
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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 | 0.002 | 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 | 0.001 | 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".