Plasma Leucinemia Following a Leucine-Enriched Whey-Casein Blend in Younger and Mid-aged Adults
Bibliographic record
Abstract
Objectives: Atlantic mackerel (AM) is not commonly consumed in American diets.We previously demonstrated that AM has potential protective effects against DSS-induced colon damage in rats.This study aimed to investigate the role of AM in modulating the gut microbiome in DSS-treated rats.Methods: Three-week-old male Sprague Dawley rats were obtained from Charles River Laboratories.After a 1-week acclimation period, the rats were randomly assigned to six groups (n6 per group) and fed the AIN93G control diet, or the control diet supplemented with 1% or 5% AM for four weeks.This was followed by 1 week of treatment with either tap water or 3% DSS solution.Animals were then maintained on tap water for an additional week before necropsy.All animals were single-housed and given ad libitum access to food.Food intake was monitored weekly.Cecal contents were collected for microbiome profiling using 16S rRNA sequencing.Results: AM supplementation did not affect food intake or body weight in any of the groups.Cecal microbiome profiling revealed no significant differences in alpha or beta diversity across groups.At the phylum level, DSS treatment reduced the richness of Tenericutes in the control group, but this reduction was prevented in AM-fed groups.Furthermore, AM supplementation attenuated DSS-induced reductions in the richness of Porphyromonadaceae (unclassified), Clostridia (unclassified), Roseburia, and Lachnospiraceae incertae sedis.Conclusions: Atlantic mackerel (AM) supplementation protects against DSS-induced gut dysbiosis by preserving microbial richness and mitigating decreases in beneficial bacterial populations, such as Porphyromonadaceae, Clostridia, Roseburia, and Lachnospiraceae incertae sedis.These findings suggest that AM has potential as a dietary intervention to promote gut health and counteract inflammation-related microbiota dysbiosis.
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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 | 0.000 | 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".