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Hydrogen Sulfide-Based Anti-Inflammatory and Chemopreventive Therapies: An Experimental Approach

2015· review· en· W1843702144 on OpenAlexafffund
Kyle L. Flannigan, John Wallace

Bibliographic record

VenueCurrent Pharmaceutical Design · 2015
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersCanadian Institutes of Health Research
KeywordsHydrogen sulfideGastrointestinal tractMedicinePharmacologyInflammationChemistryInternal medicine

Abstract

fetched live from OpenAlex

Hydrogen sulfide has potent anti-inflammatory and cytoprotective properties. In the gastrointestinal tract, hydrogen sulfide contributes significantly to mucosal defence and responses to injury. This includes promotion of resolution of inflammation and healing. Inhibition of hydrogen sulfide synthesis increases the susceptibility of the gastrointestinal mucosa to injury and delays healing processes. The beneficial effects of hydrogen sulfide have been exploited in the design of novel anti-inflammatory drugs that cause negligible gastrointestinal damage. Nonsteroidal anti-inflammatory drugs are known to be effective, when used chronically, in reducing the incidence of several types of cancer. However, the toxicity of these drugs, particularly in the gastrointestinal tract, greatly limits this use. On the other hand, the gastrointestinal-safe, hydrogen sulfide-releasing anti-inflammatories show great promise for chemoprevention of cancers. This paper reviews the evidence supporting important anti-inflammatory and cytoprotective effects of hydrogen sulfide, particularly in the gastrointestinal tract. Also reviewed are the approaches taken to develop safer anti-inflammatory and cancer chemopreventive drugs by exploiting the beneficial effects of hydrogen sulfide.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.997
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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 head0.306
GPT teacher head0.412
Teacher spread0.106 · 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 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

Citations21
Published2015
Admission routes2
Has abstractyes

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