Mitochondrial dysfunction in the type 2 diabetic heart is associated with alterations in spatially distinct mitochondrial proteomes
Bibliographic record
Abstract
Cardiac complications and heart failure are the leading cause of death in type 2 diabetic patients. Mitochondrial dysfunction is central in the pathogenesis of the type 2 diabetic heart. However, it is unclear whether this dysfunction is specific for a particular subcellular region. The purpose of this study was to determine whether mitochondrial dysfunction in the type 2 diabetic heart is specific to a spatially distinct subset of mitochondria. We investigated mitochondrial morphology, function, and proteomic composition of subsarcolemmal mitochondria (SSM) and interfibrillar mitochondria (IFM) in 18-wk-old db/db mice. Oxidative damage was assessed in subpopulations through the measurement of lipid peroxidation byproducts and nitrotyrosine residues. Proteomic profiles and posttranslational modifications were assessed in mitochondrial subpopulations using iTRAQ and multi-dimensional protein identification technologies, respectively. SSM from db/db hearts had altered morphology, including a decrease in size and internal complexity, whereas db/db IFM were increased in internal complexity. Db/db SSM displayed decreased state 3 respiration rates, electron transport chain activities, ATP synthase activities, and mitochondrial membrane potential and increased oxidative damage, with no change in IFM. Proteomic assessment revealed a greater impact on db/db SSM compared with db/db IFM. Inner mitochondrial membrane proteins, including electron transport chain, ATP synthesis, and mitochondrial protein import machinery, were predominantly decreased. We provide evidence that mitochondrial dysfunction in the type 2 diabetic heart is associated with a specific subcellular locale. Furthermore, mitochondrial morphological and functional indexes are impacted differently during type 2 diabetic insult and may result from the modulation of spatially distinct mitochondrial proteomes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".