Sex-specific metabolic and central effects of GLP-1–estradiol conjugate in middle-aged rats on a standard or western diet
Bibliographic record
Abstract
Middle age represents a critical window for metabolic and cognitive health, particularly in the context of rising obesity and diabetes rates. Glucagon-like peptide-1 (GLP-1)-based therapies, which regulate blood glucose and body weight, show sex-specific effects, with estradiol potentiating their metabolic benefits. However, research on GLP-1's cognitive and neuroprotective roles has largely been conducted in males. Here, we investigated the effects of GLP-1 conjugated to estradiol (GE2) on metabolism, cognition, cytokine levels and neurogenesis in the dentate gyrus of middle-aged male and female rats fed a standard (SD) or Western (WD) diet. In both sexes, WD increased body weight and plasma leptin levels, regardless of sex. GE2 treatment led to weight loss, enhanced cued and contextual fear memory, reduced cytokine levels in the hippocampus in SD rats, and increased neurogenesis in the dorsal dentate gyrus (DG), regardless of sex. Sex-specific differences were observed in fat distribution, glucose regulation, central cytokine levels, and neuroplasticity after WD and GE2 treatment. In females only, GE2 reduced visceral (gonadal) fat, reduced cytokines in the dorsal hippocampus, and improved basal blood glucose in response to a WD. In males only, GE2 restored neurogenesis in the DG after WD exposure, and reduced cytokine levels in the amygdala. These findings suggest that although WD increased body weight and GE2 improved associative learning in both sexes, both WD and GE2 had differential affects on metabolic hormones, insulin regulation, cytokine levels and neuroplasticity. Our findings underscore the importance of sex-specific approaches in metabolic and neuroprotective therapeutics in middle age.
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How this classification was reachedexpand
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".