Dietary fiber for the prevention of childhood obesity: a focus on the involvement of the gut microbiota
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Given the worldwide epidemic of overweight and obesity among children, evidence-based dietary recommendations are fundamentally important for obesity prevention. Although the significance of the human gut microbiome in shaping the physiological effects of diet and obesity has been widely recognized, nutritional therapeutics for the mitigation of pediatric obesity globally are only just starting to leverage advancements in the nutritional microbiology field. In this review, we extracted data from PubMed, EMBASE, Scopus, Web of Science, Google Scholar, CNKI, Cochrane Library and Wiley online library that focuses on the characterization of gut microbiota (including bacteria, fungi, viruses, and archaea) in children with obesity. We further review host-microbe interactions as mechanisms mediating the physiological effects of dietary fibers and how fibers alter the gut microbiota in children with obesity. Contemporary nutritional recommendations for the prevention of pediatric obesity are also discussed from a gut microbiological perspective. Finally, we propose an experimental framework for integrating gut microbiota into nutritional interventions for children with obesity and provide recommendations for the design of future studies on precision nutrition for pediatric obesity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it