Early Obesity and Age‐Related Mimicry of Metabolic Syndrome in Female Mice with Sex Hormonal Imbalances
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship of early obesity to metabolic syndrome during sex hormonal imbalances in mutant female mice at different ages. RESEARCH METHODS AND PROCEDURES: Hormonal imbalances, accumulation and nature of adipose tissue, food intake, glucose tolerance, and expression of candidate genes and markers of inflammation were studied by comparing wild-type, null, and haploinsufficient follitropin receptor knockout female mice at different ages. RESULTS: Follitropin receptor deletion in mice produced null females that are infertile and haploinsufficient mice that undergo accelerated biological aging. Both types of mutants with sex hormonal imbalances have central obesity without hyperphagia, but circulating leptin is elevated. Adipocyte hyperplasia and hypertrophy is attributed to elevated peroxisome proliferator-activated receptor gamma expression. Adiponectin protein levels increase in fat tissue and plasma. Only mutants but not controls acquire age-dependent decline in glucose tolerance with high insulin and altered pancreatic beta cells. Changes in inflammation markers, decreased muscle insulin receptor phosphorylation, and increase of the enzyme protein tyrosine phosphatase 1B indicate insulin resistance. DISCUSSION: In this animal model, the chronological appearance of early obesity induced by hormonal imbalances culminates in characteristics that are attributable to metabolic syndrome, including cardiovascular abnormalities. Dissection of the depot-specific alterations and defining molecular interrelationships could help in developing targeted remedies and resolving complications and controversies related to health benefits and adversities of current hormone replacement therapy.
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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) | 0.000 | 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".