Adiponectin gene therapy ameliorates high-fat, high-sucrose diet-induced metabolic perturbations in mice
Bibliographic record
Abstract
BACKGROUND AND DESIGN: Adiponectin is an adipokine secreted primarily from adipose tissue that can influence circulating plasma glucose and lipid levels through multiple mechanisms involving a variety of organs. In humans, reduced plasma adiponectin levels induced by obesity are associated with insulin resistance and type 2 diabetes, suggesting that low adiponectin levels may contribute the pathogenesis of obesity-related insulin resistance. METHODS AND RESULTS: The objective of the present study was to investigate whether gene therapy designed to elevate circulating adiponectin levels is a viable strategy for ameliorating insulin resistance in mice fed a high-fat, high-sucrose (HFHS) diet. Electroporation-mediated gene transfer of mouse adiponectin plasmid DNA into gastrocnemius muscle resulted in elevated serum levels of globular and high-molecular weight adiponectin compared with control mice treated with empty plasmid. In comparison to HFHS-fed mice receiving empty plasmid, mice receiving adiponectin gene therapy displayed significantly decreased weight gain following 13 weeks of HFHS diet associated with reduced fat accumulation, and exhibited increased oxygen consumption and locomotor activity as measured by indirect calorimetry, suggesting increased energy expenditure in these mice. Consistent with improved whole-body metabolism, mice receiving adiponectin gene therapy also had lower blood glucose and insulin levels, improved glucose tolerance and reduced hepatic gluconeogenesis compared with control mice. Furthermore, immunoblot analysis of livers from mice receiving adiponectin gene therapy showed an increase in insulin-stimulated phosphorylation of insulin signaling proteins. CONCLUSION: Based on these data, we conclude that adiponectin gene therapy ameliorates the metabolic abnormalities caused by feeding mice a HFHS diet and may be a potential therapeutic strategy to improve obesity-mediated impairments in insulin sensitivity.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".