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Record W4399217048 · doi:10.3390/antiox13060667

Pitavastatin Calcium Confers Fungicidal Properties to Fluconazole by Inhibiting Ubiquinone Biosynthesis and Generating Reactive Oxygen Species

2024· article· en· W4399217048 on OpenAlexaff
Wanqian Li, Yanru Feng, Zhe Feng, Li Wang, Malcolm Whiteway, Hui Lu, Yuanying Jiang

Bibliographic record

VenueAntioxidants · 2024
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsConcordia University
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsFluconazoleReactive oxygen speciesPharmacologyMicrobiologyFungicideCandida albicansBiologyChemistryBiochemistryAntifungal

Abstract

fetched live from OpenAlex

Fluconazole (FLC) is extensively employed for the prophylaxis and treatment of invasive fungal infections (IFIs). However, the fungistatic nature of FLC renders pathogenic fungi capable of developing tolerance towards it. Consequently, converting FLC into a fungicidal agent using adjuvants assumes significance to circumvent FLC resistance and the perpetuation of fungal infections. This drug repurposing study has successfully identified pitavastatin calcium (PIT) as a promising adjuvant for enhancing the fungicidal activity of FLC from a comprehensive library of 2372 FDA-approved drugs. PIT could render FLC fungicidal even at concentrations as low as 1 μM. The median lethal dose (LD50) of PIT was determined to be 103.6 mg/kg. We have discovered that PIT achieves its synergistic effect by inhibiting the activity of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase, thereby impeding ubiquinone biosynthesis, inducing reactive oxygen species (ROS) generation, triggering apoptosis, and disrupting Golgi function. We employed a Candida albicans strain that demonstrated a notable tolerance to FLC to infect mice and found that PIT effectively augmented the antifungal efficacy of FLC against IFIs. This study is an illustrative example of how FDA-approved drugs can effectively eliminate fungal tolerance to FLC.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.028
GPT teacher head0.254
Teacher spread0.226 · 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

Citations10
Published2024
Admission routes1
Has abstractyes

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