Signaling Integration of Hydrogen Sulfide and Iron on Cellular Functions
Bibliographic record
Abstract
Significance: Hydrogen sulfide (H 2 S) is an endogenous signaling molecule, regulating numerous physiological functions from vasorelaxation to neuromodulation. Iron is a well-known bioactive metal ion, being the central component of hemoglobin for oxygen transportation and participating in biomolecule degradation, redox balance, and enzymatic actions. The interplay between H 2 S and iron metabolisms and functions impacts significantly on the fate and wellness of different types of cells. Recent Advances: Iron level in vivo affects the production of H 2 S via nonenzymatic reactions. On the contrary, H 2 S quenches excessive iron inside the cells and regulates the redox status of iron. Critical Issues: Abnormal metabolisms of both iron and H 2 S are associated with various conditions and diseases such as iron overload, anemia, oxidative stress, and cardiovascular and neurodegenerative diseases. The molecular mechanisms for the interactions between H 2 S and iron are unsettled yet. Here we review signaling links of the production, metabolism, and their respective and integrative functions of H 2 S and iron in normalcy and diseases. Future Directions: Physiological and pathophysiological importance of H 2 S and iron as well as their therapeutic applications should be evaluated jointly, not separately. Future investigation should expand from iron-rich cells and tissues to the others, in which H 2 S and iron interaction has not received due attention. Antioxid. Redox Signal. 36, 275–293.
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 | 0.001 | 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) | 0.004 | 0.002 |
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".