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Record W2136253427 · doi:10.2174/138945005774912726

Fungal Infections of the Skin: Infection Process and Antimycotic Therapy

2005· review· en· W2136253427 on OpenAlexaff
Μ. Borgers, H. Degreef, G. Cauwenbergh

Bibliographic record

VenueCurrent Drug Targets · 2005
Typereview
Languageen
FieldMedicine
TopicNail Diseases and Treatments
Canadian institutionsBarrie Urology Group
Fundersnot available
KeywordsTerbinafineMiconazoleKetoconazoleGriseofulvinItraconazoleFluconazoleDermatologyErgosterolMicrobiologyMedicinePharmacologyTrichophytonMicrosporumChemistryBiologyAntifungalBiochemistry

Abstract

fetched live from OpenAlex

Dermatomycoses are among the most widespread and common superficial and cutaneous fungal infections in humans. These typically nonfatal conditions are difficult to treat, especially infections of the nail. Dermatomycoses are caused by filamentous fungi such as Trichophyton, Microsporum or Epidermophyton species. These filamentous fungi have a high affinity for keratin, an important component of hair, skin and nails, which are the primary areas of infection by dermatophytes. The antifungal agents currently marketed for dermatomycoses are mainly inhibitors of ergosterol biosynthesis, except for griseofulvin, which interferes with the cytoplasmic and nuclear microtubular system. Three different types of inhibitors of the ergosterol biosynthetic pathway have been proven to be effective in clinic: the azoles (e.g. topical miconazole and topical/oral ketoconazole, itraconazole and fluconazole), the allylamines (e.g. terbinafine) and morpholines (amorolfine). Even today more effective antifungal azoles with less adverse effects and short-term therapy are deemed necessary to treat dermatophytosis. A promising novel triazole compound in this respect is R126638, which showed potent in vitro and in vivo activity.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.004

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 head0.039
GPT teacher head0.384
Teacher spread0.344 · 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 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

Citations67
Published2005
Admission routes1
Has abstractyes

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