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Record W4290989192 · doi:10.3389/fendo.2022.934231

Hydrogen sulfide: A new therapeutic target in vascular diseases

2022· review· en· W4290989192 on OpenAlexaff
Cuilin Zhu, Qing Liu, Xin Li, Ran Wei, Tongtong Ge, Xiufen Zheng, Bingjin Li, Kexiang Liu, Ranji Cui

Bibliographic record

VenueFrontiers in Endocrinology · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSulfur Compounds in Biology
Canadian institutionsWestern University
FundersPeople's Government of Jilin ProvinceChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsInflammationCrosstalkOxidative stressVascular smooth muscleHydrogen sulfideAngiogenesisMedicineCell functionApoptosisPathologicalFunction (biology)Cancer researchBioinformaticsCellCell biologyChemistryImmunologyBiologySmooth muscleInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Hydrogen sulfide (H2S) is one of most important gas transmitters. H2S modulates many physiological and pathological processes such as inflammation, oxidative stress and cell apoptosis that play a critical role in vascular function. Recently, solid evidence show that H2S is closely associated to various vascular diseases. However, specific function of H2S remains unclear. Therefore, in this review we systemically summarized the role of H2S in vascular diseases, including hypertension, atherosclerosis, inflammation and angiogenesis. In addition, this review also outlined a novel therapeutic perspective comprising crosstalk between H2S and smooth muscle cell function. Therefore, this review may provide new insight inH2S application clinically.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.026
GPT teacher head0.289
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations28
Published2022
Admission routes1
Has abstractyes

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