Altered Mitochondrial Morphology and Bioenergetics in a New Yeast Model Expressing Aβ42
Bibliographic record
Abstract
Alzheimer’s disease (AD) is an incurable, age-related neurological disorder, the most common form of dementia. Considering that AD is a multifactorial complex disease, simplified experimental models are required for its analysis. For this purpose, genetically modified Yarrowia lipolytica yeast strains expressing Aβ42 (the main biomarker of AD), eGFP-Aβ42, Aβ40, and eGFP-Aβ40 were constructed and examined. In contrast to the cells expressing eGFP and eGFP-Aβ40, retaining “normal” mitochondrial reticulum, eGFP-Aβ42 cells possessed a disturbed mitochondrial reticulum with fragmented mitochondria; this was partially restored by preincubation with a mitochondria-targeted antioxidant SkQThy. Aβ42 expression also elevated ROS production and cell death; low concentrations of SkQThy mitigated these effects. Aβ42 expression caused mitochondrial dysfunction as inferred from a loose coupling of respiration and phosphorylation, the decreased level of ATP production, and the enhanced rate of hydrogen peroxide formation. Therefore, we have obtained the same results described for other AD models. Based on an analysis of these and earlier data, we suggest that the mitochondrial fragmentation might be a biomarker of the earliest preclinical stage of AD with an effective therapy based on mitochondria- targeted antioxidants. The simple yeast model constructed can be a useful platform for the rapid screening of such compounds.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".