Autophagy Signaling Through Reactive Oxygen Species
Bibliographic record
Abstract
Autophagy is a degradative pathway that involves delivery of cytoplasmic components, including proteins, organelles, and invaded microbes to the lysosome for digestion. Autophagy is implicated in the pathology of various human diseases. The association of autophagy to inflammatory bowel diseases is consistent with recent discoveries of its role in immunity. A complex of signaling pathways control the induction of autophagy in different cellular contexts. Reactive oxygen species (ROS) are highly reactive oxygen free radicals or non-radical molecules that are generated by multiple mechanisms in cells, with the nicotinamide adenine dinucleotide phosphate (NADPH) oxidases and mitochondria as major cellular sources. These ROS are important signaling molecules that regulate many signal-transduction pathways and play critical roles in cell survival, death, and immune defenses. ROS were recently shown to activate starvation-induced autophagy, antibacterial autophagy, and autophagic cell death. Current findings implicate ROS in the regulation of autophagy through distinct mechanisms, depending on cell types and stimulation conditions. Conversely, autophagy can also suppress ROS production. Understanding the mechanisms behind ROS-induced autophagy will provide significant therapeutic implications for related diseases.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".