Oxidative stress, eryptosis and anemia: a pivotal mechanistic nexus in systemic diseases
Bibliographic record
Abstract
The average lifespan of circulating erythrocytes usually exceeds hundred days. Prior to that, however, erythrocytes may be exposed to oxidative stress in the circulation which could cause injury and trigger their suicidal death or eryptosis. Oxidative stress activates Ca 2+ ‐permeable nonselective cation channels in the cell membrane, thus, stimulating Ca 2+ entry and subsequent cell membrane scrambling resulting in phosphatidylserine exposure and activation of Ca 2+ ‐sensitive K + channels leading to K + exit, hyperpolarization, Cl − exit, and ultimately cell shrinkage due to loss of KC l and osmotically driven water. While the mechanistic link between oxidative stress and anemia remains ill‐defined, several diseases such as diabetes, hepatic failure, malignancy, chronic kidney disease and inflammation have been identified to display both increased oxidative stress as well as eryptosis. Recent compelling evidence suggests that oxidative stress is an important perpetrator in accelerating erythrocyte loss in different systemic conditions and an underlying mechanism for anemia associated with these pathological states. In the present review, we discuss the role of oxidative stress in reducing erythrocyte survival and provide novel insights into the possible use of antioxidants as putative antieryptotic and antianemic agents in a variety of systemic 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".