A bovine whey protein extract can induce the generation of regulatory T cells and shows potential to alleviate asthma symptoms in a murine asthma model
Bibliographic record
Abstract
The number of people with asthma has dramatically increased over the past few decades and the cost of care is more than $11·3 billion per year. The use of steroids is the major treatment to control asthma symptoms, but the side effects are often devastating. Seeking new drugs or new strategies to reduce the dose of steroid taken has always been an important task. A bovine whey protein extract (WPE), which is enriched in transforming growth factor-β (TGF-β), has been demonstrated to have the potential for reducing symptoms associated with mild-to-moderate T-helper cell type 1-mediated psoriasis in human subjects. However, whether WPE also has potential for inhibiting T-helper cell type 2 (Th2)-mediated disease remains unclear. In the present study, using a murine asthma model, we found that sensitised mice fed WPE daily, before they were challenged, resulted in reducing airway inflammation, serum ovalbumin-specific IgE, Th2-related cytokine production and airway hyperresponsiveness. Increase in the regulatory T cell (Treg) population in vitro and in vivo was observed when treated with WPE. According to the results from the TGF-β-blocking antibody study, we suggest that TGF-β is the main component that endows WPE with the potential to reduce the generation of Treg. Thus, the present data suggest that WPE has the potential to alleviate the symptoms of asthma by inducing the generation of Treg. Therefore, regular administration of WPE might be potentially beneficial for patients with asthma.
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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 | 0.001 | 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 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".