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Record W4402223683 · doi:10.21518/ms2024-328

Clinical and epidemiological aspects and modern approaches to the treatment of pityriasis versicolor

2024· article· en· W4402223683 on OpenAlexaff
E. V. Matushevskaya, М. А. Иванова, A. G. Shevchenko, E. V. Svirshchevskaya

Bibliographic record

VenueMeditsinskiy sovet = Medical Council · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicToxin Mechanisms and Immunotoxins
Canadian institutionsSKiN Health
Fundersnot available
KeywordsPityriasisEpidemiologyMedicineDermatologyPathology

Abstract

fetched live from OpenAlex

Pityriasis versicolor (tinea versicolor) lichen (PVL) is a fungal infection of the stratum corneum of the epidermis caused by the yeast-like fungus Malassezia ( Pityrosporum ), which is part of the normal microbiome of the skin. Malassezia yeast has a conditionally pathogenic potential, penetrating into the stratum corneum and causing the appearance of multicolored spots on the skin. Malassezia fungi are involved in the pathogenesis of head and neck dermatitis, seborrheic dermatitis and folliculitis. PVL occurs in both tropical and temperate climates and affects both sexes equally. There are no systematic data on the prevalence of this disease in the world, but it is known that in tropical climates, PVL is more common (up to 40% in Brazil) than in temperate zones (<1% in Sweden). In Russia, there are also no general epidemiological data on the prevalence of PVL in the available literature. In the Krasnodar Territory in 2022-2024, among patients who turned to a dermatovenerologist for skin peeling accompanied by itching, 28% were diagnosed with PVL. The disease is considered non-contagious and is treated with topical antifungal drugs. In severe cases, the use of systemic antimycotics is indicated, which reduces the duration of the treatment and prevents relapses of the disease. The review provides data on the pathogenesis and prevalence of the disease, as well as modern approaches to PVL therapy.

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)0.003
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.203
GPT teacher head0.302
Teacher spread0.099 · 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
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

Citations2
Published2024
Admission routes1
Has abstractyes

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