Efficacy and safety of mesoporosil treatment in enhancing skin firmness, hydration, and elasticity: An 84-day clinical trial
Bibliographic record
Abstract
Objectives Silicium (silicon), an essential trace element, plays a critical role in maintaining skin health, including collagen synthesis, hydration, and elasticity. Mesoporosil®, a novel bioavailable form of silicium, offers a promising solution for enhancing skin properties. This study evaluates the efficacy and safety of Mesoporosil® in improving skin firmness, hydration, and elasticity in women with aging skin. Materials and Methods This 84-day interventional study involved 22 female volunteers aged 40–66 years with moderate to severe facial aging and dry skin. Participants consumed one daily tablet of Mesoporosil® containing 14 mg of silicon. Assessments were conducted at baseline, day 28, day 56, and day 84. Primary outcomes included subjective improvements in skin firmness, hydration, elasticity, and radiance, assessed through a detailed 24-item questionnaire. Results All 22 participants completed the study without dropouts. Subjective assessments showed progressive improvements in skin parameters over the treatment period. Significant acceptance was observed on day 28 (55.8%), day 56 (62.7%), and day 84 (61.4%). Three sensory experience parameters – ease of oral intake, absence of aftertaste, and lack of gastric distress – met the 80% satisfaction threshold consistently. Skin firmness, hydration, wrinkle reduction, radiance, and elasticity showed cumulative enhancement over the 12 weeks. No adverse events or discomforts were reported, indicating excellent tolerance and safety of the supplement. Conclusion Mesoporosil® demonstrated significant efficacy in enhancing skin firmness, hydration, and elasticity, with high levels of participant satisfaction and excellent safety. These findings support the potential of Mesoporosil® as an effective supplement for promoting healthy aging in women with aging skin.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".