The Dipeptidyl Peptidase 4 Substrate CXCL12 Has Opposing Cardiac Effects in Young Mice and Aged Diabetic Mice Mediated by Ca2+ Flux and Phosphoinositide 3-Kinase γ
Bibliographic record
Abstract
Blood glucose–lowering therapies can positively or negatively affect heart function in type 2 diabetes, or they can have neutral effects. Dipeptidyl peptidase 4 (DPP-4) inhibitors lower blood glucose by preventing the proteolytic inactivation of glucagon-like peptide 1 (GLP-1). However, GLP-1 is not the only peptide substrate of DPP-4. Here, we investigated the GLP-1–independent cardiac effects of DPP-4 substrates. Pointing to GLP-1 receptor (GLP-1R)–independent actions, DPP-4 inhibition prevented systolic dysfunction equally in pressure-overloaded wild-type and GLP-1R knockout mice. Likewise, DPP-4 inhibition or the DPP-4 substrates substance P or C-X-C motif chemokine ligand 12 (CXCL12) improved contractile recovery after no-flow ischemia in the hearts of otherwise healthy young adult mice. Either DPP-4 inhibition or CXCL12 increased phosphorylation of the Ca2+ regulatory protein phospholamban (PLN), and CXCL12 directly enhanced cardiomyocyte Ca2+ flux. In contrast, hearts of aged obese diabetic mice (which may better mimic the comorbid patient population) had diminished levels of PLN phosphorylation. In this setting, CXCL12 paradoxically impaired cardiac contractility in a phosphoinositide 3-kinase γ–dependent manner. These findings indicate that the cardiac effects of DPP-4 inhibition primarily occur through GLP-1R–independent processes and that ostensibly beneficial DPP-4 substrates can paradoxically worsen heart function in the presence of comorbid diabetes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".