Effect of β-casein A2 cow milk supplementation on physical growth, inflammation, growth-related hormones, and nutritional biomarkers in stunted children
Bibliographic record
Abstract
PURPOSE: Previous studies have suggested that milk consumption can promote growth in children. However, limited studies have been performed on the effects of cow milk varieties, especially β-casein A2 milk. This study aims to investigate the effect of β-casein A2 cow milk supplementation on physical growth, inflammation, and growth-related hormone and nutritional biomarker profiles in growth-stunted children. METHODS: This is a quasi-experimental study with only one group and a pre-and posttest design. This research is divided into 3 stages: allele testing in the β-casein gene, processing into ready-to-drink milk, and a clinical trial. The participants were children aged 12-36 months who were given 200-mL β-casein A2 cow milk supplementation once a day for 3 months. The outcome assessments were physical growth (body weight and height), inflammation (tumor necrosis factor-alpha [TNF-α] and cortisol levels), and biological markers related to growth and nutrition (insulin-like growth factor-1 [IGF-1], growth hormone [GH], and transferrin) that were measured during pre-, mid (week 6)-, and post (week 12)-intervention periods. RESULTS: This study included 30 study participants. Significant body weight and height improvements were observed at week 6 and postintervention (week 12) compared to preintervention. There were significant reductions in the inflammation markers TNF-α and cortisol levels postintervention. Additionally, IGF-1 and GH levels increased significantly, and transferrin levels also rose, potentially reflecting improved nutritional status. CONCLUSION: This study suggests that β-casein A2 milk supplementation was associated with improvements in physical growth and related biomarkers in stunted children. Additionally, β-casein A2 milk may produce fewer BCM-7 metabolites compared to β-casein A1 milk, which has been hypothesized to be associated with certain adverse health outcomes. However, further controlled studies are needed to confirm its efficacy as a dietary intervention.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".