Human sex hormone-binding globulin does not provide metabolic protection against diet-induced obesity and dysglycemia in mice
Bibliographic record
Abstract
Background Sex hormone-binding globulin (SHBG) is the main transporter of sex hormones in most vertebrates. Low SHBG levels have been linked to increased risk for diabetes and metabolic syndrome. Polymorphisms of the SHBG gene linked to low SHBG protein levels also strongly predicted increased risk of type 2 diabetes, thus raising the possibility that SHBG may play a role in the pathogenesis of insulin resistance and diabetes. Aim To examine whether expression of human SHBG in mice may ameliorate the development of diabetes and metabolic syndrome in response to a high-fat diet (HFD). Methods Transgene mice expressing a human SHBG transgene ( SHBG+ ) ( N = 10/11; males/females) and their wild type littermates ( N = 12/8; males/females) were fed HFD for 4.5 months. Results HFD induced comparable obesity in control and SHBG+ mice. Male transgenes had higher muscle mass after 2–3.5 months HFD (0.43 ± 0.028 ( n = 4) vs 0.38 ± 0.053 g ( n = 7), P = 0.05). Fasting blood glucose, as well as insulin or HOMA-IR, was not different in transgenic vs wild-type males after 4–5 months HFD. Female transgenes had higher fasting glucose (152 ± 29 ( n = 7) vs 115 ± 27 mg/dL, P = 0.01 ( n = 8)), but mean insulin and HOMA-IR were not different. Likewise, insulin tolerance test and intra-peritoneal glucose tolerance test (GTT) were not different. Finally, SHBG + mice were not different from controls in terms of liver enzymes, serum triglyceride levels and blood pressure. Conclusion In mice with diet-induced obesity, human SHBG did not protect against development of obesity or dysglycemia.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".