Establishing a model for childhood obesity in adolescent pigs
Bibliographic record
Abstract
Summary Objective Rising worldwide prevalence of obesity and metabolic diseases in children has accentuated the importance of developing prevention and management strategies. The objective of this study was to establish a model for childhood obesity using high‐fat feeding of adolescent pigs, as pigs have a longer developmental period and are physiologically more similar to humans than rodents. Methods Crossbred pigs were fed a high‐fat diet (HFD) or low‐fat diet ( n = 6/treatment) from postnatal day 49 to 84. On postnatal day 84, an oral glucose tolerance test was performed, jugular blood sampled to determine lipopolysaccharide levels and plasma lipids, intestinal digesta collected to characterize microbial and metabolite composition and back fat and intestinal tissue assayed for gene expression. Results Five‐week HFD increased weight gain and back fat thickness, caused dyslipidaemia and impaired glucose tolerance and increased expression of genes in back fat suggesting inflammation. HFD pigs had distinct proximal colon microbiota with 48% reduction ( P < 0.05) in Bacteroidetes and increased expression of pro‐inflammatory genes interleukin‐18 and tumour necrosis factor in ileum ( P < 0.05). Conclusions These findings indicate that adolescent pigs should be considered a suitable model for childhood obesity, because short‐term HFD feeding is sufficient to induce obesity and glucose intolerance, recapitulating disease characteristics in adolescent pigs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".