The use of medicinal cosmetics in the complete treatment of rosacea
Bibliographic record
Abstract
The aim of work is to carry out literature analysis about etiology and pathogenesis, classification and methods for rosacea correction, to conduct marketing research of the pharmaceutical market of medical cosmetics, to identify the main groups of biologically active substances in their composition.Materials and methods. In the course of the research we analyzed the pharmaceutical market of Ukraine for the availability of pharmaceutical cosmetics (price policy of the manufacturer) and the composition of biologically active substances.Results. The medicinal cosmetic products (MCP) for the skin prone to couperose and rosacea are represented by the products of Ukraine and foreign manufacturers - namely, France, Canada, Poland and Russia. French anti-cure agents are represented by the following companies: Avene, La Roche, Ducray, Uriage, Lierac, Nuxe, Ukrainian – Stop Cuperoz, Polish - Clarena, Canada by Galderma and Russian – Cora.When reviewing the biologically active components of MCP presented in the market it is evident that they include a large number of extracts, vitamins, essential oils, vegetable oils, organic acids, as well as proprietary complexes. Predominantly, these substances are anti-inflammatory, venotonic, anti-edema, reduce vascular permeability and strengthen the walls of capillaries. Gel, lotions, tonics, emulsions, milk, creams and thermal water are selected as cosmetic forms.Conclusions. On the basis of the literature analysis, the main causes of occurrence, pathogenesis of rosacea (couperose) and methods of its correction were established. Statistical and comparative methods were used in the research process. As a result of the research of the market of anticorrosion agents, it was established that MCP are represented by foreign manufacturers, the vast majority of which are French (75 %). 18.8 % of the data are made by manufacturers of Canada, Poland and Russia. Ukrainian MCP are represented by "PhytoBioTechnologies " – 6.25 %. As for dosage forms – creams prevail. There are also emulsions, tonics, milk, thermal water, masks, gels and lotions. There are groups of basic biologically active substances in the composition of MCP against couperose. Based on the research, the Ukrainian national market has the potential to introduce new medical forms, both national and foreign.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".