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Record W4324088606 · doi:10.9734/bpi/rdmms/v3/8999f

Hypertensive Nephropathy: Is Hydrogen Sulfide a Game Changer?

2023· book-chapter· en· W4324088606 on OpenAlexaff
George J. Dugbartey

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSulfur Compounds in Biology
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineNephropathyRenal functionHypertensive NephropathyDiseaseKidney diseaseNitric oxideMechanism (biology)Blood pressureIntensive care medicineKidneyInternal medicineEndocrinologyDiabetic nephropathyDiabetes mellitus

Abstract

fetched live from OpenAlex

Hypertension is a major public health problem globally. It is the most common cause of cardiovascular morbidities and mortalities, with a negative impact on renal function. Uncontrolled hypertension causes chronic kidney disease, which progresses to end-stage renal disease and eventually loss of renal function. Unfortunately, the mechanism underlying the pathogenesis of hypertension and its associated nephropathy is still poorly understood. Also worrying is the fact that despite conventional antihypertensive therapies, achievement of blood pressure control and preservation of renal function still remain a worldwide public health challenge in a significant subpopulation of hypertensive patients. This suggests the need for novel pharmacotherapeutic approaches to curb the problem. Hydrogen sulfide (H2S), the third established member of the gasotransmitter family after nitric oxide and carbon monoxide, has been recognized and established to possess antihypertensive and renoprotective properties, which may represent an important therapeutic alternative for hypertensive nephropathy. In this chapter, recent findings from preclinical studies about therapeutic effect of H2S against hypertensive nephropathy, and its future clinical use are discussed.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.008

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 head0.030
GPT teacher head0.244
Teacher spread0.214 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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