Chia Hua Liang1, Chuan Wei Liu2, Xiu Xiang Wei2, Yung Hsiang Lin3, Yung Kai Lin4 and Chi Fu Chiang3*
Received: October 17, 2022; Published: November 15, 2022
*Corresponding author: Chi Fu Chiang, Research & Design Center, TCI CO. Ltd., Taipei, Taiwan
DOI: 10.26717/BJSTR.2022.47.007455
The combination of Chinese herbal medicine and fish collagen has the function of skin anti-aging. However, there are few clinical studies on whether the health care products composed of hydrolyzed fish collagen, pitaya, rosa rugosa, and H. pluvialis, gamma aminobutyric acid have skin anti-aging effects. This study used LISAVEI collagen beverage composed of fish collagen, pitaya, rosa rugosa, H. pluvialis and GABA, to explore whether collagen beverage can improve skin and sleep condition. The study recruited 50 subjects and divided into a placebo group (n =30) and a LISAVEI collagen beverage group (n = 30) for 8 weeks and then examined skin and sleep condition at 0, 4, 8 weeks. The results showed that collagen, elasticity, brightness, moisture significantly increased by 5.9%, 1.8%, 2.2%, 3.7% respectively, compared to placebo group, and pores, melanin, redness decreased by 8.1%, 4.4 %, 2.5 % respectively, compared to the placebo group. And the subjects felt that the overall skin and sleep condition improved by questionnaire. LISAVEI collagen beverage rich in hydrolyzed fish collagen, pitaya, rosa rugosa, H. pluvialis and GABA can improve skin and sleep.
Keywords: Hydrolyzed Fish Collagen; Pitaya Extract; Rosa Rugosa; Haematococcus Pluvialis; Gamma Aminobutyric Acid; Skin
Aging is a global trend, and the most obvious change after aging is the change of skin appearance (Clatici, et al. [1]). Therefore, active ingredients that delay skin aging are particularly attractive. Nowadays, many products on the market focus on natural ingredients, and the demand for natural ingredients is increasing day by day. Traditional Chinese herbal medicines are mainly made from natural plants (Goyal, et al. [2]). Chinese herbal medicines and natural animal products have the effect of treating skin diseases, sun protection, and enhancing skin nutrition (Pu, et al. [3]). Therefore, now it’s mainstream in the market that the addition of Chinese herbal extracts into health foods and cosmetics. Skin appearance depends on the collagen skeleton, for instance, wrinkle formation has been associated to decreased collagen synthesis and increased collagenase activity (Sanchez, et al. [4]). Some approaches to prevent or retard the apparition of wrinkles in humans are to use cosmetics or to intake nutritional supplements which help to maintain collagen molecules in the skin at optimum (Sanchez, et al. [4]). Some of these products include, as an active ingredient, collagen or hydrolyzed collagen. Traditional sources of collagen for cosmetics are skins and hides from pigs and cows (Leon Lopez, et al. [5]). However, nowadays, collagen from marine origin is preferred, since it is free from animal species, causing religious concerns (Lim, et al. [6]). Fish collagen is more easily absorbed than porcine collagen, has a low molecular weight, and is preferable to the industry due to low inflammatory reactions. Also, type I collagen is abundant in marine organisms (Lim, et al. [6]). Pitaya belongs to the plant of triangular prism cactus genus, with high nutritional ingredients are rich in polysaccharide composition (Luu, et al. [7]). In the stem of Pitaya, it has many health benefits to human skin by using of extraction and manufacturing, which are widely used in various healthy foods for cosmetic products, not only anthocyanins, flavonoids, polyphenols but also other ingredients, they may provide good the effect on the health for human physiology (Anand Swarup, et al. [8]).
Rosa rugosa, a member of Rosaceae, which is widely planted all over the world and distributed in many places in China. R. rugosa is often used in the field of food and medicine (Xie, et al. [9]). Its petals and buds are often used to make flower tea, jam, fruit wine or other food. Some studies reported that R. rugosa application in cosmetics has the effects of antioxidant, anti-aging, whitening, moisturizing. R. rugosa contains a lot of flavonoids, polyphenols, polysaccharides and other components, suggesting R. rugosa as a potential anti-aging and anti-aging plant (Andrzej Cendrowski, et al. [10]). Haematococcus pluvialis is a freshwater species of Chlorophyta from the family Haematococcaceae (Suseela, et al. [11]). Astaxanthin is one kind of carotenoid, and it is the strongest antioxidant activity among the natural materials (Suseela, et al. [11]). H. pluvialis has the highest astaxanthin content, which is important in aquaculture, and cosmetics (Pertiwi, et al. [12]). H. pluvialis has high antioxidant activity, can remove free radicals, stimulate immune response, and has anti-cancer effects, which has high medical value (Pertiwi, et al. [12]). In addition, γ-aminobutyric acid (GABA) was discovered in the extract of mammalian brain and identified to be an inhibitory neurotransmitter (Smart, et al. [13]). GABA works not only as a mediator in the neuronal system but is also involved in the skin (Galanopoulou [14]). The study had showed that GABA stimulated the synthesis of hyaluronic acid (HA) and enhanced the survival rate of the dermal fibroblasts when fibroblasts were exposed to H2O2, an oxidative stress agent (Ito, et al. [15]). Clinical study showed that GABA can increase skin elasticity and improve sleep (Hokazono, et al. [16]). However, there was still not much clinical studies on hydrolyzed fish collagen, pitaya, rosa rugosa, H. pluvialis and GABA for skin. In this study, we used LISAVEI collagen beverage, formulated primarily with hydrolyzed fish collagen, pitaya, rosa rugosa, H. pluvialis and GABA, to explore whether LISAVEI collagen beverage can improve skin condition. The study recruited 50 subjects and divided into a placebo group (n =30) and a LISAVEI collagen beverage group (n = 30) for 8 weeks and then examined skin and sleep condition at 0, 4, 8 weeks.
Clinical Trial Design The clinical study had been approved by Human Trial Committee of Antai Hospital (TSMH-IRB 21-102-B), and the study had been registered on ClinicalTrials.gov Identifier: NCT05182814. Sixty adult subjects were recruited in this trial between August 2021 and May 2022. Informed consent was obtained from all subjects before the study at Chia Nan University of Pharmacy and Science. The subjects were divided into a placebo group (n=30) and a collagen beverage group (n=30). Each subject was informed about intaking a bottle of collagen beverage labeled 50ml or a placebo drink daily for 8 weeks and was not allowed to take any other supplement during the intervention period. Inclusion criteria included: healthy men and women aged > 20. The exclusion criteria included: 1. Skin disease, liver cirrhosis, or chronic renal failure 2. Allergy to cosmetics, drugs, or foods 3. Pregnant and breastfeeding 4. Taking chronic drugs 5. People who had any cosmetic procedures (intense pulse light, medical peelings, or laser therapy) before 4 weeks of the study. Test Sample LISAVEI collagen beverage contains 10% hydrolyzed fish collagen, 4% pitaya, 0.4% gamma aminobutyric acid, 0.02% rosa rugosa, and 0.0002% H. pluvialis, sucralose, citric acid, water. Placebo beverage contains sucralose, citric acid, and water. Clinical Skin Efficacy Assessment Skin brightness was measured using a skin color difference analyzer (Chroma Meter MM500, Minolta, Japan). The standard colorimetric method formulated by the CIE (Commission Internationale de L’Eclariage) system is used to obtain the quantification of the color L* value. L* value - the value range is: 0-100, which is a gray scale, and the higher the value, the brighter it is. Detection position: the upper cheek. Skin redness was detected using a skin color difference analyzer (Chroma Meter MM500, Minolta, Japan). The standard colorimetric method developed by the CIE (Commission Internationale de L’Eclariage) system is used to obtain the quantitative a* value of the color. The higher the a* value, the more red and inflamed the skin. Detection position: the upper cheek. Skin melanin was detected using the Schute skin tester (Soft Plus, Callegari 1930, Italy). Skin red and melanin levels were analyzed using dual wavelength measurement 505 nm green light and 875 nm infrared light. Detection position: the upper cheek. Skin moisture was measured using a skin moisture meter Corneometer CM825, CK, Germany. Based on the amperometric method, the skin’s moisturizing ability is tested. Detection position: the upper cheek. Skin elasticity was measured using Cutometer MPA580, CK, Germany. Using the principle of negative pressure suction, the performance of skin elasticity is detected, and the restoring force is measured through the different depths of light penetrating the skin and the resistance caused by the skin being inhaled by negative pressure. Detection position: the upper cheek. Skin transepidermal water loss was measured using a transepidermal water loss meter (Tewameter TM300, CK, Germany). The structural integrity of the stratum corneum of the skin is inferred from the evapotranspiration of the skin. Detection position: the upper cheek. Skin wrinkles were detected using VISIA Micro-Analysis Skin Image Analyzer (VISIATM Complexion Analysis, U.S.A). Closed face photo studio (unified light source), and 36-million-pixel photo images, analyze and compare image data. Using standard white light to detect changes in skin shade, quantify the distribution and number of skin wrinkles. Dark green represents deeper wrinkles, light green is the opposite. Detection position: full face. Skin texture was detected using VISIA Micro-Analysis Skin Image Analyzer (VISIATM Complexion Analysis, U.S.A). Closed face photo studio (unified light source), and 36-million-pixel camera images, analysis and comparison of image data. Measure skin smoothness using standard white light to detect changes in skin shading. The raised parts of the skin surface are shown in yellow, the concave parts are shown in blue, and the less yellow and blue, the smoother the skin surface. Detection position: full face.Skin pores were detected using VISIA Micro-Analysis Skin Image Analyzer (VISIATM Complexion Analysis, U.S.A). Closed face studio (unified light source). Use standard white light and 36 million pixels to take pictures, analyze and compare image data. Use standard white light to detect the shadows produced by the sunken skin pores to evaluate the number of pores and the location of their subdivisions. Detection position: full face. Skin collagen was detected using a subcutaneous collagen scanner (DermaLab® Series SkinLab Combo, Cortex Denmark. High-frequency ultrasound imaging instrument was used to scan subcutaneous collagen to quantify collagen density. Detection location: on the upper cheek. Clinical Sleep Assessment Measures of sleep disturbances included self-reported insomnia symptoms and sleep duration. Information about perceived symptoms of insomnia was obtained by self-report using the Insomnia Self-assessment Inventory (ISAI) questionnaire, which was designed by the World Health Organization worldwide project on sleep and health. Each question was scored with a 4-point (0–4) Likert-type scale. For the sleep status of the subjects before and after taking the product, the ISAI was used to investigate. The total score of 5-9 points was judged as mild sleep disorder, and the total score of more than 10 points was sleep disorder. Statistical Analysis Before and after comparison within the group was performed by Student’s t test. *, p 0.05 indicates a statistically significant difference. Values are percent change compared to the control group.
Soon after March 2020 lockdown, with the online education switch, one research article pointed out that “students reported stress, anxiety, being worried about getting sick (COVID-19), and changes in their mental health” [12]. Yet, as stated by in this case report, mental health disorders are to be socially interpreted as ‘normal’ while individual cases are to be treated by physicians. Taking into account that Internet use has not been clearly proved to be directly responsible for social anxiety rise [5,13] it remains to look after other emotional encounters that are eventually accountable for [7]. The first assumption of this report is that, during lockdowns, universities created ad-hoc educational fields (social arenas) using computer communication technologies. I called this social arena circumstantial or facilitational as they perform a sort of social interaction similar to modern medical advocacy [14]. The ill person is isolated, yet it participates in the social interactions due to communication technologies. Online social arenas substitute face-to-face interaction and facilitate human interaction through computer mediated technology. They have good educational potential. Students were home but they were inattentive as they performed usual educational tasks for longer time than they did for usual in-person education. For some, “at the beginning I felt as in a permanent vacation, being able to stay all day with my family, and I felt safe from the virus.” On the other hand, as one student in the University of Bucharest stated, “pandemic stole two years of my life” as online interaction was time consuming. However, one of his/her colleague mentioned that “I liked that I had so much time, and I could do so many activities and take care of myself. I liked that I learned to use the technology better” [6]. One could notice that such idiosyncrasies offer genuine symptoms of stress and anxiety.
Quantitative data illustrates online interactions but does not clarify whether they increase stress and social anxiety or not. A number of subjects exposed to online education confirmed improved social interaction as one female student stated that “I did not attend classes before, as I was anxious and shy, so online was better and my relationship with professors had improved. ”Yet, similar qualitative answer stated the opposite “I didn’t like that it was impersonal, and I was away from colleagues and professors [6].” Therefore, second assumption of this report is that online content, delivery method and time spent are eventually responsible for the amount of stress and anxiety surge in college students’ population during COVID-19 lockdown. Some 80 % of subjects in this research complained about overtime spent online. Yet, in spite of more time they spent online with instructors and colleagues, 64 % of them missed face-to-face interaction with colleagues and friends. At the same time 37 % of students mentioned less satisfaction with content while 42 % perceived increased homework as not being really necessary. All of these were recorded against 48 % technology use acceptance and 60 % favorable attitude towards Internet technology use [12]. Further research is expected to confirm students feel good with computer technology yet online education does not abuse their convenience.
Limitations apply to this report. Data is extracted from larger research the author made [6]. Sub-samples are relevant for university students’cohort they were selected from. Same limitation applies for discussion of results. Yet, conclusions are submitted with the anticipation they are useful for other interested parts. Interruption of in-person education confirmed important role communication technology plays as digital substitute of human interaction. For the stress and social anxiety that presumably escalated during COVID-19 this report has found no explicit evidence communication technology to be responsible. A good part of the individual pathology is associated with the ‘normal’ or anticipated occurrence during pandemics. Other things being equal, people aged 15 to 29 use more often than other groups Internet communication technology as avoidance of face-to-face interaction. Yet content delivered, methods used as well increased homework and extra time spent online presented the potential to raise individual pathologies of stress, depression and social anxiety disorder for up to 25 % of subjects exposed to online education. It is up to various cultural and social contexts to diminish this subsidiarity to more appropriate levels. Applications to make delivery routines more suitable for students, adapting educational content for online use, extensions to smartphones to encourage mobility, increase Internet outlets availability, proportionate homework and adapting time to human needs are just a few suggestions in order to make online education more enjoyable and useful.
This research received no funds.
University of Bucharest # SAS 562-2022
Informed consent was obtained from all subjects involved in the study.
Not applicable.
The author declares no conflict of interest.