Deep phenotyping of a modified diabetic cardiomyopathy mouse model which reflects clinical disease progression
Bibliographic record
Abstract
Diabetic cardiomyopathy (DbCM) is a progressive disease and common complication of metabolic diabetes. It is characterised by onset of cardiac structural and functional impairments and can lead to direct development of clinical heart failure (HF) or predispose to hypertensive/ischaemic stress. DbCM is a complex disease which involves several metabolic and pathogenic factors. We characterised an established high-fat diet/streptozotocin (HFD/STZ)-induced DbCM model incorporating typical features of human disease to determine its suitability for preclinical evaluation of novel therapeutics prior to advancement to human trials. Male C57BL/6J mice were randomised to HFD and single-dose STZ (100 mg/kg) or control diet (CD) and vehicle. HFD/STZ mice developed type 2 diabetes mellitus (T2DM), reflected by high fasting blood glucose and HbA1c levels, reduced β-cell function, and increased insulin resistance without systolic blood pressure alteration. Furthermore, HFD/STZ mice displayed progressive diastolic dysfunction, evidenced by decreased MV E/A ratio, together with elevated chronic left ventricular (LV) filling pressure parameters, measured by left atrial (LA) area and LA volume, compared to controls, in parallel with LV hypertrophy and fibrosis. Monocyte trafficking into diabetic hearts was identified by single-nuclei RNA sequencing analysis, which revealed an interferon-α response in DbCM mice, whilst plasma proteomics confirmed the involvement of inflammatory processes with elevated plasma C-reactive protein in DbCM progression. Taken together, our HFD/STZ-induced DbCM model exhibits a unique DbCM pre-clinical phenotype reflecting a "triple-hit" of human DbCM features comprising (1) T2DM with insulin resistance, (2) progressive diastolic dysfunction and LV remodelling, and (3) metabolic inflammation. This improved HFD/STZ-induced DbCM model supports clinically relevant research on DbCM progression from early stages to cardiac dysfunction and remodelling as the basis for translational investigation.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".