Bibliographic record
Abstract
In their study on Th1 and Th17 hypercytokinemia in severe pandemic influenza, Bermejo-Martin and colleagues [1] observed significantly elevated levels of IL-17 and particularly IL-6 in critically ill patients. They also reported that up to 50% of critical care patients studied were obese. Correale and colleagues [2] indicate that activated vitamin D enhances the development of IL-10-producing cells and reduces the number of IL-6- and IL-17- secreting cells. Studies show that obese and overweight individuals are more likely to have an inadequate vitamin D status [3,4]. According to Louie and colleagues [5], diabetes and obesity were the most frequently identified underlying conditions in fatal pandemic 2009 influenza A (H1N1) infection cases older than age 20 years world wide. In addition, obese people usually have high calorie and low nutritional value diets. Aasheim and colleagues [6] showed that low concentrations of vitamin B-6, vitamin C, 25-hydroxyvitamin D, and vitamin E adjusted for lipids are prevalent in morbidly obese Norwegian patients seeking weight-loss treatment. It would be interesting to see if any of the critical cases observed in the study by Bermejo-Martin and colleagues were insufficient or deficient in vitamin D and/or other nutrients relevant for intracellular signaling involved in inflammation. If vitamin D plays a role in human general capacity to deal with infection and other diseases, then an increase in Th17 mediators in severe pandemic influenza patients could be, at least in part, related to vitamin D insufficiency/deficiency.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".