Inhibition of Cardiomyogenesis in Embryocarcinoma Cells Induced by Long-Term High Level of Glucose
Bibliographic record
Abstract
BACKGROUND/AIMS: Cardiac myocytes constitute the first differentiated cell type during mammalian heart formation with the ability to beat spontaneously and rhythmically. Hyperglycemia is a primary risk factor for cardiovascular disease in pre-gestational diabetes mellitus (PGDM). However, the impact that hyperglycemia has on cardiac progenitors or on precursors differentiation remains poorly understood. The aim of the present study is to investigate whether hyperglycemia affects cardiomyogenesis of embryocarcinoma cells. METHODS: P19CL6 cells differentiation induced by 1% DMSO was evaluated under either normal glucose (5.6 mmol/L) or high level of glucose concentrations (20 mmol/L or 40 mmol/L). To investigate the effect of long-term high level of glucose on cardiomyocytes differentiation, sarcomeric α-actinin, peroxisome proliferator-activated receptor coactivator-1 (PGC-1α), transcription factor GATA4 and Nkx2.5 were assessed by qRT-PCR analysis, western blot and immunofluorescence. RESULTS: We observed that long-term high level of glucose markedly reduced P19CL6 cells differentiation into cardiomyocytes. The change in PGC-1α expression was consistent with changes in cardiac muscle myosin expression after exposure to 20 mmol/L or 40 mmol/L of glucose. On the other hand, the high level of glucose concentration profoundly decreased both GATA4 and Nkx2-5 expressions from day 6 to day 12 after differentiation, which was induced by 1% DMSO. CONCLUSION: Our results elucidate that the effect resulting from the long-term exposure of cardiac progenitors to high level of glucose is associated with decreased expression of GATA4 and Nkx2.5, providing a novel mechanism by which high glucose is able to affect cell differentiation.
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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) | 0.001 | 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".