LKB1-regulated adaptive mechanisms are essential for neuronal survival following mitochondrial dysfunction
Bibliographic record
Abstract
Mitochondrial dysfunction plays an important role in the etiology of neurodegenerative diseases. However, the progressive nature of neuronal loss in genetic models of mitochondrial dysfunction suggests the presence of compensatory mechanisms promoting neuronal survival under these conditions. Here, we identified the energy metabolism kinase LKB1 as a key regulator of the compensatory mechanisms activated in neurons, following mitochondrial dysfunction. To accomplish this, we have created an in vivo neurodegenerative model based on the deletion of the mitochondrial protein apoptosis-inducing factor (AIF) in postmitotic neurons. Loss of mitochondrial function caused by AIF deletion induced several adaptive mechanisms, including increased glycolysis and mitochondrial biogenesis. Importantly, the activation of these adaptive mechanisms was abrogated by the deletion of one allele of LKB1, resulting in impaired neuronal survival. Because loss of mitochondrial function is a central mechanism implicated in neurodegenerative diseases, modulation of LKB1-dependent pathways may represent an important strategy to preserve neuronal survival and function.
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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) | 0.001 | 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".