Effects of Lacticaseibacillus rhamnosus HA-114 probiotic supplementation on circulating IGFBP-2 levels during a calorie-restricted diet in overweight humans
Bibliographic record
Abstract
Gut microbiota influences energy homeostasis in part through circulating hormones. Insulin-like growth factor-binding protein (IGFBP)-2 is a biomarker whose increase in systemic circulation is associated with positive effects on body weight and metabolism. In a recent clinical trial, probiotic Lacticaseibacillus rhamnosus HA-114 supplementation showed positive effects on eating behaviors and insulin resistance in overweight participants undergoing a weight-loss intervention. In this context, this ancillary study aimed at assessing the impact of L. rhamnosus HA-114 supplementation on plasma IGFBP-2 levels in these individuals, and whether this modulation correlated with changes in fat mass, energy metabolism, and eating behaviors. Fasting plasma IGFBP-2 concentrations were quantified in 100 overweight or obese men and women enrolled in a 12-week diet-based weight reduction program (−500 kcal/day), in combination with probiotic L. rhamnosus HA-114 or placebo supplementation. Baseline and changes in circulating IGFBP-2 concentrations were correlated with anthropometric parameter, glucose and lipid metabolism, cardiorespiratory function and eating behaviors. On average, the intervention reduced BMI by 4.6 % and increased IGFBP-2 by 13 %, regardless of supplementation group. Individuals who presented an increase in IGFBP-2 levels had significantly greater reductions in BMI. Changes in IGFBP-2 levels were correlated with loss in fat mass (r = 0.2, p < 0.001) in the probiotic-supplemented group, but not with other metabolic parameters or eating behaviors. Baseline IGFBP-2 levels were not associated with weight loss or improvements in cardiometabolic parameters. Probiotic supplementation with L. rhamnosus HA-114 did not modulate plasma IGFBP-2 levels. Changes in IGFBP-2 levels were correlated with greater reductions in BMI, but not with other metabolic parameters or eating behaviors, indicating that the benefits of HA-114 on eating behaviors are likely independent of IGFBP-2. Additional changes in microbiota might be required to modulate IGFBP-2 and observe its associations with eating behaviors and cardiometabolic improvements.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".