Secretomes as an emerging class of bioactive ingredients for enhanced cosmeceutical applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Skin ageing is predominantly caused by either intrinsic or extrinsic factors, leading to undesirable skin features. Advancements in both molecular and cellular fields have created possibilities in developing novel stem cell-derived active ingredients for cosmeceutical applications and the beauty industry. Mesenchymal stromal cell (MSC)-derived secretomes or conditioned media hold great promise for advancing skin repair and regeneration due to the presence of varying cytokines. These cytokines signal our cells and trigger biological mechanisms associated with anti-inflammatory, antioxidant, anti-ageing, proliferative and immunomodulatory effects. In this review, we discuss the potential of MSC secretomes as novel biomaterials for skincare and rejuvenation by illustrating their mechanism of action related to wound healing, anti-ageing and whitening properties. The advantages and disadvantages of secretomes are compared with both plant-based and animal-derived extracts. In addition, this paper reviews the current safety standards, regulations, market products and research work related to the cosmeceutical applications of secretomes along with strategies to maintain and improve the therapeutic efficacy and production of secretomes. The future outlook of beauty industry is also presented. Lastly, we highlight significant challenges to be addressed for the clinical realization of MSC secretomes-based skin therapies as well as providing perspectives for the future direction of secretomes.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it