Effect of a Probiotic Beverage Enriched with Cricket Proteins on the Gut Microbiota: Composition of Gut and Correlation with Nutritional Parameters
Bibliographic record
Abstract
The health and balance of the gut microbiota are known to be linked to diet composition and source, with fermented products and dietary proteins potentially providing an exceptional advantage for the gut. The purpose of this study was to evaluate the effect of protein hydrolysis, using a probiotic beverage enriched with either cricket protein (CP) or cricket protein hydrolysates (CP.Hs), on the composition of the gut microbiota of rats. Taxonomic characterization of the gut microbiota in fecal samples was carried out after a 14-day nutritional study to identify modifications induced by a CP- and CP.H-enriched fermented probiotic product. The results showed no significant differences (p > 0.05) in the diversity and richness of the gut microbiota among the groups fed with casein (positive control), CP-enriched, and fermented CP.H-enriched probiotic beverages; however, the overall composition of the microbiota was altered, with significant modifications in the relative abundance of several bacterial families and genera. In addition, fermented CP.H-enriched probiotic beverages could be related to the decrease in the number of potential pathogens such as Enterococcaceae. The association of gut microbiota with the nutritional parameters was determined and the results showed that digestibility and the protein efficiency ratio (PER) were highly associated with the abundance of several taxa.
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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) | 0.001 | 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 | 0.000 |
| 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".