Potential anti-aging applications of microbial-derived surfactantsin cosmetic formulations
Bibliographic record
Abstract
The skin aging process is a complex interaction of genetic, epigenetic, and environmental factors, such as chemical pollution and UV radiation. There is growing evidence that biosurfactants, especially those of microbial origin, have distinct age-supportive effects through different mechanisms, such as stimulation of fibroblast growth, high antioxidant capacities, and favorable anti-inflammatory properties. With a growing financial contribution of more than 15 m€per year, microbial surfactants (MSs) display unique biological effects on the skin including improved cell mobility, better nutrient access, and facilitated cellular growth under harsh conditions. Their biodegradable nature, unusual surface activity, good safety profile and tolerance to high temperature and pH variations widen their potential spectrum in biomedical and pharmaceutical applications. MSs typically have lower critical micelle concentration (CMC) levels than chemical surfactants enhancing their effectiveness. As natural surfactants, MSs are considered possible "green" alternatives to synthetic surfactants with better biodegradability, sustainability, and beneficial functional properties. This review therefore aims to explore the potential impacts of MSs as anti-aging ingredients.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 teacher head, 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".