Mechanisms of antiretroviral therapy-induced mitochondrial dysfunction
Bibliographic record
Abstract
PURPOSE OF REVIEW: To discuss novel developments related to the mechanisms of antiretroviral therapy-related mitochondrial toxicity, describe some apparent paradoxes in the current understanding of this field, and present questions that should be addressed by future research. RECENT FINDINGS: The early polymerase gamma hypothesis states that nucleoside reverse transcriptase inhibitors can inhibit mitochondrial DNA replication and cause mitochondrial toxicity through mtDNA depletion. This mechanism is supported by a large body of evidence. Clinical manifestations of mitochondrial dysfunction are not always associated with mtDNA depletion. Increased mtDNA levels after nucleoside reverse transcriptase inhibitor exposure, as well as seemingly severe mtDNA depletion in individuals who show no clinical toxicity, have been reported. These and other observations suggest that additional mechanisms are involved in antiretroviral therapy toxicity, a notion supported by recent studies. Individuals given the same antiretroviral regimen can differ vastly with respect to the development of mitochondrial toxicity symptoms, reflecting interindividual variability. Some factors that may modulate this variability will be discussed. SUMMARY: Mitochondrial toxicity induced by nucleoside reverse transcriptase inhibitors and their metabolic intermediates is probably mediated through many direct and indirect mechanisms. Depending on the mechanisms at play, the long-term health consequences of this toxicity may vary.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".