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Record W4410708230 · doi:10.17816/dv642248

Modern tendencies of influence on skin microbiome by means of dermatocosmetics: practical aspects of probiotic bacteria application in the composition of biotic complexes

2025· article· en· W4410708230 on OpenAlexaff
В. П. Адаскевич, Aleksei N. Gorodovich, D. V. Zaslavsky, В. А. Охлопков, И. О. Смирнова, А. В. Таганов, О. Б. Тамразова, I.L. Shlivko, Kristina D. Khazhomiya

Bibliographic record

VenueRussian Journal of Skin and Venereal Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsSKiN Health
Fundersnot available
KeywordsMicrobiomeArtBiologyBioinformatics

Abstract

fetched live from OpenAlex

In the last few decades, the number of studies on the microbiota and microbiome of living organisms inhabiting the skin has grown rapidly, and the contribution of the microbial community to the realization of skin functions and the pathogenesis of dermatoses is of great scientific and public interest. Understanding the contribution of skin dysbiosis to skin aging, sensitization, and the pathogenesis of chronic dermatoses has prompted the development of strategies aimed at correcting the skin microbiota. One of the directions of bacteriotherapy of skin diseases is the use of biotic complexes, which include metabiotics of human commensal bacteria and prebiotics. The use of biotic complexes allows to effectively modulate the skin microbiome and its barrier functions. A practical embodiment of the use of metabiotics of probiotic bacteria as part of biotic complexes was the development of active skin care systems containing lysates of probiotic microorganisms Lactococcus, Lactobacillus and Bifidobacterium and prebiotics trehalose and inulin. These products can be enhanced with active ingredients with proven efficacy, such as panthenol, jojoba oil, shea butter and others that provide skin cleansing, moisturizing and nourishing. The conducted studies have demonstrated the effectiveness and safety of products with enhanced formula as part of complex treatment of patients with atopic dermatitis. Their clinical effects are based on the restoration of the skin barrier (according to the dynamics of pH-metry, transepidermal water loss and skin elasticity), as well as normalization of the microbial composition of the skin (reduction in the frequency of identification of phylum, which belong to opportunistic microorganisms, and reduction in the frequency of identification of the Staphylococcaceae family, pathogenic representatives of which lead to increased inflammation and allergic reactions on the skin).

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.284
Teacher spread0.276 · 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 designObservational
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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