Restoration of fatty acid but not glucose utilization in the infarcted heart following stem cell therapy
Bibliographic record
Abstract
Aim To determine whether stem cell therapy reduces abnormal cardiac substrate utilization following a myocardial infarction (MI). Methods Three treatment groups, SHAM, MI and MI‐STEM receiving intramyocardial injection of mesenchymal stem cells. Echocardiography was performed at 0, 1 and 3wk. C57BL/6J mice underwent a hyperinsulinemic‐euglycemic clamp 4wk following treatment (n=8–11). To assess indices of whole body and cardiac long chain fatty acid (LFCA) and glucose utilization (R(f), R(g); umol/g wet weight/min), 2‐deoxy[(3)H]glucose and [125I]‐15‐(rho‐iodophenyl)‐3‐R,S‐methylpentadecanoic acid were administered. Both the peri‐infarct (PI) region and a non‐involved (NI) area of the left ventricle were examined. Results No differences in whole body substrate utilization or insulin sensitivity, as assessed by glucose infusion rate were apparent between treatments. In the PI region, MI resulted in declines in R(f) compared to SHAM (0.25 vs 0.44). This decline was mitigated in MI‐STEM (0.33 vs 0.44). In contrast, R(g) was diminished in both the MI and MI‐STEM groups in the PI (1.77 vs 2.0 vs 3.87) compared to the SHAM. Additionally, R(f) and R(g) in the NI was not different between groups. Conclusions Stem cell therapy assists in reducing the metabolic abnormalities following a MI. Specifically, it minimizes MI‐induced declines in R(f) but not R(g).
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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) | 0.001 | 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".