Autophagy and apoptosis dysfunction in neurodegenerative disorders
Bibliographic record
Abstract
Autophagy and apoptosis are basic physiologic processes contributing to the maintenance of cellular homeostasis. Autophagy encompasses pathways that target long-lived cytosolic proteins and damaged organelles. It involves a sequential set of events including double membrane formation, elongation, vesicle maturation and finally delivery of the targeted materials to the lysosome. Apoptotic cell death is best described through its morphology. It is characterized by cell rounding, membrane blebbing, cytoskeletal collapse, cytoplasmic condensation, and fragmentation, nuclear pyknosis, chromatin condensation/fragmentation, and formation of membrane-enveloped apoptotic bodies, that are rapidly phagocytosed by macrophages or neighboring cells. Neurodegenerative disorders are becoming increasingly prevalent, especially in the Western societies, with larger percentage of members living to an older age. They have to be seen not only as a health problem, but since they are care-intensive, they also carry a significant economic burden. Deregulation of autophagy plays a pivotal role in the etiology and/or progress of many of these diseases. Herein, we briefly review the latest findings that indicate the involvement of autophagy in neurodegenerative diseases. We provide a brief introduction to autophagy and apoptosis pathways focusing on the role of mitochondria and lysosomes. We then briefly highlight pathophysiology of common neurodegenerative disorders like Alzheimer's diseases, Parkinson's disease, Huntington's disease and Amyotrophic lateral sclerosis. Then, we describe functions of autophagy and apoptosis in brain homeostasis, especially in the context of the aforementioned disorders. Finally, we discuss different ways that autophagy and apoptosis modulation may be employed for therapeutic intervention during the maintenance of neurodegenerative disorders.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".