Metabolic Imbalance of Homocysteine and Hydrogen Sulfide in Kidney Disease
Bibliographic record
Abstract
Homocysteine (Hcy) and hydrogen sulfide (H2S) are important molecules produced during the metabolism of sulfur-containing amino acids. Hcy metabolism is central to the supply of methyl groups that are essential for biological function. Hcy can be either regenerated to methionine or metabolized to cysteine, a precursor for glutathione synthesis. Cystathionine-β-synthase (CBS) and cystathionine-γ-lyase (CSE) play a crucial role in metabolizing Hcy to cysteine through the transsulfuration pathway. These two enzymes are also responsible for H2S generation through desulfuration reactions. H2S, at physiological levels serves as a gaseous mediator and has multifaceted effects. Metabolic imbalance of Hcy and H2S has been implicated in pathological conditions including oxidative stress, inflammation, cardiovascular and cerebral dysfunction, fatty liver disease and ischemiareperfusion injury. Organs such as liver, kidney, gut and pancreas contain all the enzymes that are required for Hcy metabolism. The kidney plays an important role in removing Hcy from the circulation. Hyperhomocysteinemia, a condition of elevated blood Hcy level, is a common clinical finding in patients with chronic kidney disease (CKD) or acute kidney injury (AKI), the latter is often caused by ischemia-reperfusion. This paper reviews exiting literatures regarding (1) the role of kidney in regulating Hcy and H2S metabolism; (2) disruption of sulfur-containing amino acid metabolism during ischemiareperfusion; (3) impact of metabolic imbalance of Hcy and H2S on kidney function. Better understanding of molecular mechanisms that regulate Hcy and H2S metabolism under physiological and pathophysiological conditions will help improve therapeutic strategies for patients with kidney disease or other organ injuries.
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".