Streptozotocin induces G2 arrest in skeletal muscle myoblasts
Bibliographic record
Abstract
Much of our present knowledge concerning the pathogenesis and treatment of human type 1 diabetes is due to the study of animal models of diabetes. Despite the fact that the in vivo administration of streptozotocin (STZ) has been used extensively to induce pancreatic beta‐cell death and ultimately diabetes mellitus in many animal models, little is known about the direct effects of this compound on skeletal muscle function. In the present study, we demonstrate for the first time that acute as well as continuous exposure of skeletal muscle myoblasts to STZ (0.25 mg/ml‐3.0 mg/ml) significantly impaired their proliferative capacity in a dose‐dependent manner. To investigate the early immune responses associated with type 1 diabetes, repeated low dose administration of STZ has been utilized. Mimicking this, we exposed myoblasts to 0.25 mg/ml of STZ for 1 hour daily for 5 consecutive days. Within 24 hours, STZ exposure significantly decreased myoblast proliferation and this suppression remained throughout the experiment with proliferation rates decreased by 47.8 ± 5.1% (p ≤ 0.05) by day 5. Flow cytometric analysis demonstrated that STZ‐treated myoblasts are arrested in the G2/M phase of the cell cycle. In agreement with the effects on the beta‐cell, incubation of STZ treated myoblasts with dichlorofluorescein revealed an observable increase in reactive oxygen species (ROS). Furthermore, treatment with the powerful antioxidant alpha tocopherol (vitamin E, 50 μg/ml) was unable to alleviate the STZ‐induced proliferative inhibition. Taken together, these findings demonstrate that the effects of STZ are not solely specific to pancreatic beta‐cells and caution is warranted when utilizing this animal model to investigate the complications of diabetes in skeletal muscle growth and regeneration.
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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 | 0.000 |
| 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".