Both low and high fat diets inconsistently induce obesity in C57BL/6J mice and obesity compromises adipose n‐3 fatty acid and zinc status
Bibliographic record
Abstract
The purpose of this study was to determine whether the inconsistency in development of diet induced obesity (DIO) in C57BL/6J mice is related to dietary fat level, or metabolic derangements associated with high weight gain, including variations in adipose tissue fatty acid composition and zinc status. C57BL/6J mice were randomized to either the low fat (LF; 7% soybean oil w/w, 16% kcal from fat) or high fat (HF; 9% soybean oil + 21% lard w/w, 55% kcal from fat) diet for 16 weeks. The diets were also controlled for zinc content. Mice were dichotomized by median weight into high (HBW) and low body weight (LBW) groups. The novel findings were that (i) even a LF diet produced obesity as HBW and LBW groups contained mice fed both HF and LF diets, (ii) adipose phospholipid n‐3 fatty acids were lower in HBW mice, despite diet composition, and (iii) HBW mice had lower concentrations of zinc in adipose and pancreatic tissue. These results suggest that DIO in C57BL/6J mice is not entirely dependent on a HF diet and that obesity, regardless of diet, results in an unfavourable adipose phospholipid n‐3 fatty acid and zinc status. [Supported by the Natural Sciences and Engineering Research Council (NSERC) and University of Manitoba Research Development Fund.]
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".