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Record W4416141157 · doi:10.25251/6m5ykw66

Successful In Vitro and In Vivo Treatment of Tinea Pedis with a Nitric Oxide-releasing Gel

2025· article· W4416141157 on OpenAlexaff
Harmanpreet Kaur, Najmeh Dorafshanian, James B. Martins, Simon Teskey, Chris Miller

Bibliographic record

VenueSKIN The Journal of Cutaneous Medicine · 2025
Typearticle
Language
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsResearch & Development Corporation
Fundersnot available
KeywordsTrichophyton rubrumNitric oxideIn vivoTrichophytonFungicideAntifungalRefractory (planetary science)

Abstract

fetched live from OpenAlex

Introduction: Tinea pedis (athlete’s foot) is among the most common superficial fungal infections worldwide, affecting up to 70% of individuals in their lifetime. Caused primarily by Trichophyton rubrum and Trichophyton interdigitale, it manifests as interdigital maceration, hyperkeratotic scaling, or vesiculobullous eruptions. Treatment is often complicated by increasing resistance to standard antifungal therapies. Nitric oxide (NO), a broad-spectrum antimicrobial with multiple cellular targets, represents a promising alternative. Previous work with a nitric oxide releasing solution (NORS) demonstrated fungicidal efficacy in keratin-rich environments and clinical utility in foot bath studies, but real-world application was limited by treatment logistics. This study evaluates a novel nitric oxide releasing gel (NORS-gel) designed for practical patient use. Aim: To investigate the antifungal efficacy, dermal penetration, mechanism of action, and preliminary clinical performance of NORS-gel in refractory tinea pedis. Methods: Antifungal activity was assessed against T. rubrum and T. mentagrophytes using (1) time-kill assays, (2) zone of inhibition tests across synthetic dermal membranes, and (3) scanning electron microscopy (SEM) for morphological effects. A single-patient case study evaluated safety, tolerability, and clinical efficacy. Treatment involved twice-daily topical application for one week, followed by once-daily use for four weeks. Symptom severity was measured using the Athlete’s Foot Severity Score (AFSS). Results: NORS-gel demonstrated rapid fungicidal activity, achieving complete kill of T. rubrum within one minute and T. mentagrophytes within an average of 2.8 minutes, while placebo had no effect. In dermal membrane assays, NORS-gel penetrated the synthetic barrier and maintained fungicidal efficacy, producing zones of inhibition 57% larger than those with Tolcylen and significantly outperforming tolnaftate, which failed to penetrate. SEM revealed extensive structural disruption, impaired hyphal formation, and fungal cell wall perforations, confirming a fungicidal—not fungistatic—mechanism. In the clinical case, a 37-year-old male with refractory interdigital tinea pedis unresponsive to terbinafine and clotrimazole achieved complete symptomatic resolution after five weeks. AFSS decreased from 24 at baseline to 0 at week 5. Adverse effects were limited to mild, transient yellow skin discoloration and dryness, managed with moisturizer. Conclusions: NORS-gel exhibited rapid, potent fungicidal activity in vitro, effective dermal penetration with sustained efficacy, and striking morphological disruption of fungal structures. Clinically, a refractory case of tinea pedis resolved completely within five weeks of treatment. Nitric oxide’s multifaceted antimicrobial mechanism may reduce risk of resistance development and confer added benefits in wound healing. While these findings are preliminary, they highlight the therapeutic potential of NORS-gel as a novel topical antifungal agent. Larger randomized controlled trials are warranted to confirm efficacy, optimize dosing regimens, and establish long-term safety. Sponsored: SaNOtize Research and Development Corporation

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.268
Teacher spread0.261 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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