Exercise‐Induced Amelioration of Diet‐Induced Obesity and Diabetes is Not Regulated by Irisin
Bibliographic record
Abstract
Physical inactivity is a primary modifiable risk factor for obesity and type 2 diabetes (T2D) – metabolic diseases that are rampant in pediatric and adult population. Endurance exercise has been shown to prevent and/or attenuate the onset and progression of obesity and T2D. The myokine 'irisin' (cleaved product of Fndc5 in response to endurance exercise) has been touted to play a role in this process but the data available thus far is controversial with respect to the efficacy of irisin. Thus, we sought to determine if irisin mediates the effect of exercise training on improving high fat diet‐induced obesity and diabetes. C57Bl/6 mice were fed high‐fat diet (HFD; 60% kcal from fat) for 6 months until the animals were hyperglycemic and glucose intolerant. Subsequently, the animals were divided into HFD control, endurance exercise (15 m/min X 60 mins X 5 days/week, END), or given intravenous injections of recombinant irisin (50 ng/kg/day, 3x/week, IR). Animals were treated for 8 weeks. END mice had lower body and inguinal fat weight, higher muscle mass, and improved glucose tolerance profile (P < 0.05). Treatment with IR had no effect on fasting glucose levels or bodyweight, but improved glucose tolerance (P < 0.05). IR mice also had a significant increase in brown fat mass, just like mice in the END group. There was a marked improvement Ucp1 expression, and COX activity in inguinal fat and quadriceps muscle in the END animals respectively (P < 0.05), which was absent in the IR group. Our data clearly reflect that while irisin plays a role in improving glucose tolerance, its effectiveness in rescuing symptoms of obesity and diabetes at the whole body level and browning of inguinal fat is limited. Supported by NSERC and CIHR.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".