108 ANTI-AGEING
250 200 150 100 50 0
+247%
Control Aged HDF■ Treated Aged HDF (Althaea rosea stem cell active at 0.025%) +260%
+259% +203% ■
dermocosmetic and biohacking concepts in this new plant stem cell-based active that selectively eliminates skin cellular senescence, thus providing the next-level efficacy, selectivity, and sustainability aspects that the global well-ageing market demands. As demonstrated in this article, this active
+54% +24% ADAMTS2
Collagen post translational modification
COL1A2 Type I collagen
(most abundant type in the skin)
FBN2
Involved in fibrillin
biosynthesis HAS3 Involved in
hyaluronic acid biosynthesis
Increased expression of genes involved in ECM biosynthesis MMP7
Contributes to the breakdown of ECM proteins
MMP9
Contributes to the breakdown of ECM proteins
+29% GM-CSF
Inflammatory response inductor
Decreased expression of genes involved in ECM degradation
Figure 4: The activation of senolysis promotes the right modulation of the expression of genes involved in the ECM remodelling of senescent HDFs
■ -6.7%* wrinkle volume ■ -5.7 years less in the periocular area (proven by skin profilometry analysis– see Figure 5) Furthermore, the visual apparent age of the same panel of 70 healthy female subjects was thoroughly studied in vivo thanks to a cutting- edge system based on artificial intelligence (AI). This age estimation module consists of a
machine learning system that, based on image data, predicts the age of subjects in a controlled environment. To create an efficient system for apparent age estimation, an ensemble of different convolutional neural networks (CNNs) was used to extract information from each of the analysed pictures. The age detection model was initially
trained using 55,134 images from 13,617 subjects with ages ranging from 16 to 77 years old. The source data in our study consists of 207 videos showing the evolution of the subjects during different stages of treatment (D0-D28-D56). These videos were recorded in full HD at 30
frames per second (FPS) and have an average duration of 36 seconds, with a total of 223,560 images analysed. These CNNs firstly isolate and crop the subject’s face from the image to eliminate possible background noise with a face
D0
2% Althaea rosea stem cell axctive (Vol1)
Placebo (Vol25)
Height (µm) -500 -400 -300 -200 -100 0 100 200 300 400
detector, and then that portion of the image containing the subject’s face is fed to three different models that estimate the age of the subject. The results obtained from this AI analysis
show how the apparent age decreased by approximately 3.26 years in the group treated with the active versus the group treated with placebo at the end of treatment (56 days). In fact, the difference was already of 1.04 years less in the treated group than in the placebo group after only 28 days. It is thanks to this last calculation that
Provital could estimate the change in the visual apparent age of all volunteers, thus proving the well-ageing power of the Althaea rosea stem cells active through AI.
Conclusion Provital anticipated the effect of the current fervour for life in the ever-increasing mature segment of the population, and combined nature and science to capture the essence of this new immortality in a brand-new approach to well-ageing: Dermohacking Cosmetics. Provital’s Althaea rosea stem cells active, appears as the first of its kind, blending both
D28 D56
ingredient induces the selective apoptosis of senescent cells, creating a senolytic effect on dermal fibroblasts that subsequently leads to a series of positive biological consequences for ageing skin. It is by selectively triggering this senolytic mechanism that the Althea rosea stem cell active appears as an undeniable ‘dermohacker’, with such a significant improvement on ageing skin that the apparent age calculated for all volunteers using an AI system decreased over three years on average versus placebo after treatment.
PC
References 1. Horton JS, Priest NK. Silicon Valley’s quest for immortality – and its worrying sacrifices. The Conversation UK (University of Bath) [Internet]. 2018.
https://theconversation.com/ silicon-valleys-quest-for-immortality-and- its-worrying-sacrifices-101405
2. López-Otín C, Blasco MA, Partridge L, Serrano M Kroemer G. Hallmarks of aging: An expanding universe. Cell. 2022. https://doi. org/10.1016/j.cell.2022.11.001
3. Campisi J. Aging, cellular senescence, and cancer. Annu. Rev. Physiol. 2013;75:685–705
4. Serrano M. Ageing: Tools to eliminate senescent cells. Nature. 2017;545(7654):294– 6
5. Manzano D, Perez-Aso M, Bosch J, Martínez- Teipel B. Senolysis, a cutting-edge strategy for healthy skin ageing, is activated by Althaea rosea stem cells. 2020;1–12
6. Waaijer MEC, Gunn DA, Adams PD, Pawlikowski JS, Griffiths CEM, van Heemst D et al. P16INK4a Positive Cells in Human Skin Are Indicative of Local Elastic Fiber Morphology, Facial Wrinkling, and Perceived Age. Journals of Gerontology. Series A: Biological Sciences and Medical Sciences. 2016;71(8):1022–8
7. Dimri GP, Lee X, Basile G, Acosta M, Scott G, Roskelley C et al. A biomarker that identifies senescent human cells in culture and in aging skin in vivo. Proc. Natl. Acad. Sci. USA. 1995;92(20):9363–7
8. Waldera Lupa DM, Kalfalah F, Safferling K, Boukamp P, Poschmann G, Volpi E et al. Characterization of Skin Aging-Associated Secreted Proteins (SAASP) Produced by Dermal Fibroblasts Isolated from Intrinsically Aged Human Skin. Journal of Investigative Dermatology. [Internet]. 2015;135(8):1954–68
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Figure 5: The active’s anti-wrinkle effect is significant and visible (Primos 3D images of two volunteers’ periocular area)
PERSONAL CARE April 2023
11. Mylonas A, O’Loghlen A. Cellular Senescence and Ageing: Mechanisms and Interventions. Frontiers in Aging. 2022;3(March):1–10
www.personalcaremagazine.com
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