Bibliographic record
Abstract
Objective: The most frequently encountered CNS damage in mitochondrial diseases is the presence of lesions revealed by MRI or CT in areas of the basal ganglia. Neuronal cell death in these areas (Leigh Disease) occurs, likely due to a combination of events resulting from inability to generate energy oxidatively. These include loss of energy charge, accumulation of hydrogen ions, increases in free Ca++ and increases in reactive oxygen species. Methods and Results: Analysis of MtDNA based disorders were used to compare what is known about metabolic control and generation of ATP in model systems. Comparison of threshold effects imposed by heteroplasmy give some insight into the plasticity of energy production systems. Comparison of the constraints imposed by various defects in the pyruvate dehydrogenase complex is also instructive in that relatively small changes are known to produce major sequelae with local biochemical consequences. The interruption of electron transport at complex I is especially prone to abnormalities in oxygen-free radical generation. Response to excessive superoxide generation by elevation of MnSOD is one of the defence mechanisms that can be employed to reduce such free radical effects. Recent generation of transgenic mice expressing modified DNA polymerase gamma have also shown that MtDNA mutation can have profound effects on the ageing process. Gene defects affecting mitochondrial fission, fusion and movement are also adding to the overall picture that many aspects of mitochondrial function are essential to the well-being of the CNS. Conclusion: This analysis of factors affecting mitochondrial energy metabolism and sequelae leading to cell death should lead to a better understanding of how we might focus our efforts to intervene in the neurodegenerative process.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".