Characterizing an Animal Model of Anorexia Nervosa
Bibliographic record
Abstract
Anorexia Nervosa is a condition of severe under-nutrition characterized by alterations in multiple neuroendocrine axes. PURPOSE: To investigate the temporal changes in body composition and neuroendocrine hormones in food restricted rats, with and without access to running wheels, over a four week period. METHODS: Sixteen, 12 wk old, female Wistar rats were randomly divided into four groups: Control (C), Control/Wheel-Running (C/WR), Starved (S), and Starved/Wheel-Running (SWR). C animals were fed ad libitum, while S were food restricted with the goal of achieving 75% of body mass within the first two weeks with a maintenance phase for the final two weeks. Wheel running activity and food intake were measured constantly through-out the study, and IGF-1, leptin (ELISA) and body composition (DXA, GE Lunar Prodigy) were measured at baseline (B) and once a week ending at 4 weeks (T4). RESULTS: SWR animals demonstrated a rapid loss of body fat (BF) (B = 43.4±5.3g, T4 = 6.6±5.0g) tracked by significant decreases in both leptin (B = 12.5±1.48ng/mL, T4 = 1.8±0.12ng/mL) and IGF-1 (B = 184±13.2ng/mL, T4 = 44±5.8ng/mL). S animals demonstrated similar reductions in BF (B = 37.8g±3.8, T4 = 5.9g±2.4), leptin (B = 7.5±1.3ng/mL, T4 = 2.0±0.3ng/mL) and IGF-1 (B = 196±20.3ng/mL, T4 = 67±7.9ng/mL). C and CWR animals grew to roughly 110%-115% of their original body mass over the study and demonstrated similar increases in IGF-1 (C: B = 181.5±22.9ng/mL, T4 = 244±14.4ng/mL; CWR: B = 180±13.2ng/mL, T4 = 246±21.6ng/mL). However, despite an increase in body mass, wheel running resulted in a reduction in BF (CWR: B = 42.4±6.6g, T4 = 33.3±3.9g) while C animals gained BF (B = 38.2±9.83g, T4 = 46.9±10.1g). In both cases, leptin changed in parallel with BF (CWR: B = 16.4±1.6ng/mL±, T4 = 10.3±0.9ng/mL; C: B = 5.37±0.3ng/mL, T4 = 14.3±3.2ng/mL. CONCLUSION: These data demonstrate that changes in leptin occur rapidly upon initiation of food restriction tracking losses in BF, while adaptations in IGF-1 parallel changes in lean tissue. Wheel running did not prohibit weight gain in ad lib fed animals and resulted in modest reductions in body fat suggesting that investigation of a refeeding program for the food restricted animals that includes exercise is warranted and might not be counter-productive as previously thought.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".