Topiramate Reduces Energy and Fat Gains in Lean (<i>Fa/?</i>) and Obese (<i>fa/fa</i>) Zucker Rats
Bibliographic record
Abstract
OBJECTIVE: This study examined the effects of topiramate (TPM), a novel neurotherapeutic agent reported to reduce body weight in humans, on the components of energy balance in female Zucker rats. RESEARCH METHODS AND PROCEDURES: A 2 x 3 factorial experiment was performed in which two cohorts of Zucker rats differing in their phenotype (phenotype: lean, Fa/?; obese, fa/fa) were each divided into three groups defined by the dose of TPM administered (dose: TPM 0, vehicle; TPM 15, 15 mg/kg; TPM 60, 60 mg/kg). RESULTS: The reduction in body weight gain induced by TPM in both lean and obese rats reflected a decrease in total body energy gain, which was more evident in obese than in lean rats. Whereas TPM administration did not influence the intake of digestible energy in lean rats, it induced a reduction in food intake in obese animals. In lean, but not in obese rats, apparent energy expenditure (as calculated by the difference between energy intake and energy gain) was higher in rats treated with TPM than in animals administered the vehicle. The low dose of TPM decreased fat gain (with emphasis on subcutaneous fat) without affecting protein gain, whereas the high dose of the drug induced a reduction in both fat and protein gains. The effects of TPM on muscle and fat depot weights were representative of the global effects of TPM on whole body fat and protein gains. The calculated energetic efficiency (energy gain/energy intake) was decreased in both lean and obese rats after TPM treatment. TPM dose independently reduced hyperinsulinemia of obese rats, but it did not alter insulinemia of lean animals. DISCUSSION: The present results provide sound evidence for the ability of TPM to reduce fat and energy gains through reducing energetic efficiency in both lean and obese Zucker rats.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".