Mesenchymal stem cell therapy to promote peripheral tissue insulin sensitivity in the high‐fat fed, myocardial infarcted mouse
Bibliographic record
Abstract
OBJECTIVE Identify the influence of mesenchymal stem cell (MSC) therapy on peripheral tissue glucose utilization following a myocardial infarction (MI) and dietary‐induced insulin resistance (IR). METHODS C57BL6 mice were high‐fat fed (HFF) for eight weeks. Mice were then segregated into three groups: HFF‐SHAM mice, HFF‐MI+PBS mice undergoing coronary artery ligation to induce a MI followed by intramyocardial injection of phospho‐buffered saline and the HFF‐MI+MSC group receiving MSCs. HFF groups were age‐matched with chow‐fed mice. RESULTS Five weeks post‐MI, glucose utilization was assessed in the conscious, unrestrained mouse by employing a hyperinsulinemic‐euglycemic (insulin) clamp combined with administration of [14C]‐2‐deoxyglucose. The MSC‐treated, chow‐fed mice displayed elevated glucose uptake in the soleus muscle. High‐fat feeding enhanced the MSC‐effect on insulin sensitivity. Whole body insulin responsiveness was higher in the HFF‐MI+MSC, as indicated by a 1.6‐fold increase in glucose infusion rate compared to HFF‐SHAM mice (n=8–12). Also, tissue‐specific glucose uptake (μg/mg/min) was elevated in the soleus (0.95 vs 1.46; HFF‐SHAM vs. HFF‐MI+MSC), gastrocnemius (0.19 vs 0.27), vastus lateralis (0.11 vs 0.23) and adipose tissue (0.03 vs 0.05). CONCLUSIONS MSC transplantation represents a novel therapy for IR induced by diet and a MI. Funded by CIHR and Killam Trusts.
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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 | 0.000 | 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) | 0.001 | 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".