Insulin Resistance Induced Elevations in Cardiac Glycogen are not Attenuated by Regular Exercise
Bibliographic record
Abstract
Glycogen is a central mediator of cellular homeostasis, insulin signaling and substrate utilization. Insulin resistance results in a doubling of cardiac glycogen stores, however, the mechanisms governing this increase are unknown. Elevated glycogen occurs by either the formation of new granules (proglycogen) or the expansion of existing glycogen stores (macroglycogen). Aims were to i) determine the nature of augmented glycogen stores in insulin resistance and ii) examine whether regular exercise attenuated this increase. Employing the db/db mouse model of type 2 diabetes, hearts were removed following 6wk of sedentary or regular treadmill exercise (EX) (1h/d, 5d/wk) in both control ( db/+) and db/db littermates. On the day of the study, mice were rested for 48h before cardiac muscle was collected and assessed for pro‐, macro‐ and total glycogen concentration (umol/g dw). In the sedentary groups, glycogen was elevated in db/db mice compared to db/+ (272±25 vs. 134±17). Macroglycogen contributed the largest proportion of this increase indicating the majority of diabetes‐induced cardiac glycogen was due to larger granule size rather than number. Unexpectedly, EX resulted in further increases rather than the normalization of glycogen stores in db/db but not db/+ (432±43 vs. 149±17). Additional glycogen in db/db from EX was equally distributed between pro‐ and macroglycogen. Data indicate insulin resistance results in an increase in cardiac glycogen stores that is not corrected by regular exercise. Rather, it appears that the mechanisms by which insulin resistance and exercise augment cardiac glycogen stores are distinct and additive. Supported by CIHR (DS) & Genome Alberta (JS).
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".