Supersulfide biology and translational medicine for disease control
Bibliographic record
Abstract
For decades, the major focus of redox biology has been oxygen, the most abundant element on Earth. Molecular oxygen functions as the final electron acceptor in the mitochondrial respiratory chain, contributing to energy production in aerobic organisms. In addition, oxygen-derived reactive oxygen species including hydrogen peroxide and nitrogen free radicals, such as superoxide, hydroxyl radical and nitric oxide radical, undergo a complicated sequence of electron transfer reactions with other biomolecules, which lead to their modified physiological functions and diverse biological and pathophysiological consequences (e.g. oxidative stress). What is now evident is that oxygen accounts for only a small number of redox reactions in organisms and knowledge of biological redox reactions is still quite limited. This article reviews a new aspects of redox biology which is governed by redox-active sulfur-containing molecules-supersulfides. We define the term 'supersulfides' as sulfur species with catenated sulfur atoms. Supersulfides were determined to be abundant in all organisms, but their redox biological properties have remained largely unexplored. In fact, the unique chemical properties of supersulfides permit them to be readily ionized or radicalized, thereby allowing supersulfides to actively participate in redox reactions and antioxidant responses in cells. Accumulating evidence has demonstrated that supersulfides are indispensable for fundamental biological processes such as energy production, nucleic acid metabolism, protein translation and others. Moreover, manipulation of supersulfide levels was beneficial for pathogenesis of various diseases. Thus, supersulfide biology has opened a new era of disease control that includes potential applications to clinical diagnosis, prevention and therapeutics of diseases. LINKED ARTICLES: This article is part of a themed issue Recent Innovations in Targeting Redox Biology for Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v183.1/issuetoc.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".