Methods for Assessing Mitochondrial Function in Diabetes
Bibliographic record
Abstract
A growing body of research is investigating the potential contribution of mitochondrial function to the etiology of type 2 diabetes. Numerous in vitro, in situ, and in vivo methodologies are available to examine various aspects of mitochondrial function, each requiring an understanding of their principles, advantages, and limitations. This review provides investigators with a critical overview of the strengths, limitations and critical experimental parameters to consider when selecting and conducting studies on mitochondrial function. In vitro (isolated mitochondria) and in situ (permeabilized cells/tissue) approaches provide direct access to the mitochondria, allowing for study of mitochondrial bioenergetics and redox function under defined substrate conditions. Several experimental parameters must be tightly controlled, including assay media, temperature, oxygen concentration, and in the case of permeabilized skeletal muscle, the contractile state of the fibers. Recently developed technology now offers the opportunity to measure oxygen consumption in intact cultured cells. Magnetic resonance spectroscopy provides the most direct way of assessing mitochondrial function in vivo with interpretations based on specific modeling approaches. The continuing rapid evolution of these technologies offers new and exciting opportunities for deciphering the potential role of mitochondrial function in the etiology and treatment of diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".