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Record W4402507150 · doi:10.1021/acs.jmedchem.4c01649

Discovery of SIRT1-Activating Hydrogen Sulfide Donating Derivatives for Efficient Resistant of Myocardial Ischemic Injury

2024· article· en· W4402507150 on OpenAlexaff
Shenglin Wang, Dongyan Feng, Weirenbo Wang, Chao Zheng, Chaowei Liang, Siqing Li, Haonan Li, Fanxing Xu, Hao Cao, Huiming Hua, Maosheng Cheng, Dahong Li

Bibliographic record

VenueJournal of Medicinal Chemistry · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSulfur Compounds in Biology
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersLiaoning Revitalization Talents ProgramDepartment of Education of Liaoning ProvinceNatural Science Foundation of Liaoning ProvinceNational Natural Science Foundation of China
KeywordsChemistryHydrogen sulfideMyocardial ischemiaSulfideCombinatorial chemistryMedicinal chemistryPharmacologyOrganic chemistryInternal medicineIschemiaSulfur

Abstract

fetched live from OpenAlex

Activating SIRT1 or promoting SIRT1 expression are both protective against myocardial ischemia. Combining these approaches would be an effective strategy for treating ischemic heart disease. Herein, we identified lead compounds with SIRT1 activation activity through screening the natural product library, and five series of H 2 S donating derivatives were designed and synthesized. Among them, compound 17 exerted an effective cardioprotective effect in vitro and in vivo . The addition of H 2 S scavenger attenuated the protective activity, emphasizing the critical involvement of H 2 S in the myocardial ischemia process. Interestingly, 17 exhibited stronger direct SIRT1 activative ability and induced higher SIRT1 expression capability compared to the lead. Furthermore, 17 attenuates oxidative stress-induced cardiomyocytes apoptosis by activating the SIRT1-PGC1α signaling pathway. Our study validated the promising potential of activating SIRT1 and promoting SIRT1 expression through H 2 S to improve cardiomyocytes function, providing novel insights into the protective mechanisms during the progression of ischemic heart disease.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.281
Teacher spread0.270 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations7
Published2024
Admission routes1
Has abstractyes

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