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Background: The skin condition of women is different at different ages, and skin surface lipids are also different. According to the "7–7 theory" of the Huangdi Neijing, the physiological condition of women changes significantly every 7 years, and women aged 22–28 are in the "4–7" stage as mentioned in the "7–7 theory" of the Huangdi Neijing. Women's skin is in different states at different ages and produces different lipids. Objectives: To explore the key lipids that contribute to skin differences between women aged 22–28 and 29–35 years, and to explore the relationship with physiological parameters and daily routine. Methods: Differential lipids were detected and screened between 22–28 year old (group D1) and 29–35 year old (group D2) dry‐skinned women using UPLC‐Q‐TOF‐MS and correlated between the two groups with questionnaires and physiological parameters based on basic information, lifestyle habits, work situation, and emotional stress. Results: The results showed that all of the eight major classes of lipids had the highest expression in the D2 group, with the largest differences in glycerophospholipids, glycerol esters, and fatty acids. The BMI value of D2 group was higher than that of D1 group, the skin elasticity index (R2) and brightness index (L, a, ITA values) were lower than that of D1 group, and Cer (d18:0/16:0) was positively correlated with the R2, L, a, and ITA, and LMSP01080056 (N,N‐dimethyl‐Safingol) was positively correlated with the b‐value, the LMSPGP03020013, LMSPGP03020014, LMSP03020024 were significantly negatively correlated with R2. Conclusions: Cer(d18:0/16:0) is a neurosphingol that inhibits elastase expression. N,N‐dimethyl‐Safingol readily undergoes oxidation to form yellow‐brown solids. The macromolecular structure and excessive carbonyl structure of [LMGP0302] are susceptible to cross‐linking and carbonyl stress reactions, which accelerate skin aging and reduce skin elasticity, and thus, they may be key lipids contributing to skin differences between the two age groups. [ABSTRACT FROM AUTHOR]

Background: The worldwide prevalence of "sensitive skin" group is estimated at being close to 40%. The main trigger for sensitive skin is the misuse of cosmetics products. Majority of the in vitro studies on cosmetic ingredients developed for topical application to the skin are not able to describe sensory irritation, such as stinging, burning, itching, and tingling. Besides, most of the in vivo tests often encounter problems such as limited number of subjects and usage scenarios deviate from reality. Objective: A gradient boosting algorithm is adopted in our context to integrate multisource of information including skin types, sensory response, and cosmetics ingredients to predict sensory irritation. Method: In this study, online comments were preprocessed to construct a multi‐dimensional structured data including skin types, sensory response, and cosmetics ingredients. A gradient boosting regression model was developed where sensory response was predicted based on the abovementioned structured input. The predictions were validated by in vivo test and were shown favorably when comparing with the state‐of‐the‐art results from related works. Result: 46 007 samples were collected after data cleaning and were used in model developing. Results showed that the model was capable to predict the sensory response of 16 skin types to different ingredients (R = 0.71, P < 10−10). In addition, this model was validated using data from in vivo studies and presented a value of 75% on specificity, 88.9% on sensitivity, and 82.4% on accuracy. Conclusion: Our approach that is based on a variant of the gradient boosting algorithm provided an adequate solution for understanding the sensory irritation of cosmetic ingredients. [ABSTRACT FROM AUTHOR]

Background: The current knowledge about potential risk factors for atopic dermatitis (AD) is primarily based on the structure and function of the stratum corneum, which is characterized by osmotic defects and abnormal antibacterial function. There are no studies on the difference between facial lipids in infants with AD and healthy infants. Aims: We sought to explore significantly different lipid markers for infants with AD presenting with lesions and healthy infants aged 0‐2 years to guide treatment strategies. Methods: Twenty‐eight patient infants with AD and 32 healthy infants were recruited. Each infant received its surface skin lipids (SSL) on the right cheek. The components of skin lipids were measured by ultra‐performance liquid chromatography‐quadrupoletime‐of‐flight mass spectrometry (UPLC‐Q‐TOF‐MS) to explore significantly different lipid markers by analyzing the detection results using orthogonal partial least squares analysis(OPLS‐DA). Results: There were clear distinctions in the components of SSL between the two groups. Twenty‐nine significantly different lipid markers (P ≤.05) were found. Conclusion: This study confirmed that there were significant differences in the components of the SSL between AD infants with lesions and healthy infants, but also found lipid types, lipid contents, and lipid structures as AD‐related risks. [ABSTRACT FROM AUTHOR]

Background: Benzo(a)pyrene, a major environmental pollutant, is known to accelerate skin aging through oxidative stress, increase the production of inflammatory mediators, and cause skin cancer. Lentinan, prepared from Lentinus edodes (Shiitake mushroom), has been reported to exhibit anti‐coagulant, anti‐viral, anti‐cancer, anti‐tumor, and anti‐coagulant effects. However, the effect of lentinan on human keratinocytes treated with benzo(a)pyrene is unknown. Aims: The aim of this study was to explore whether lentinan inhibits benzo(a)pyrene‐induced oxidative stress and inflammatory cytokine production in human keratinocytes. Methods: We investigated the effect of lentinan on benzo(a)pyrene‐induced oxidative stress indicators (malondialdehyde, superoxide dismutase, and glutathione peroxidase) in human immortalized keratinocytes (HaCaT cells). We also assessed the production of inflammatory factors interleukin‐8 and chemokine ligand‐2 induced by benzo(a)pyrene exposure at both mRNA and protein levels. Results: Lentinan inhibited oxidative stress induced by benzo(a)pyrene, as shown by the concentration‐dependent reduction in reactive oxygen species in HaCaT cells. In addition, malondialdehyde levels were reduced to 53% of those of cells treated with benzo(a)pyrene without lentinan. The activities of superoxide dismutase and glutathione peroxidase were approximately 18‐ and 2.7‐fold higher in benzo(a)pyrene‐treated cells with lentinan than in those without lentinan. Moreover, lentinan significantly reduced interleukin‐8 and chemokine ligand‐2 mRNA and protein levels. Conclusions: These findings suggest that lentinan has two biological activities that are potentially useful for managing inflammatory skin diseases or disorders related to oxidative stress induced by benzo(a)pyrene. Therefore, cosmetics containing L edodes have promising dermatological applications, with potential utility in protecting the skin against environmental pollutants. [ABSTRACT FROM AUTHOR]

Background: Sensitive skin refers to skin that tends to be highly responsive to stimuli such as physical, chemical, and psychological. Psychological factors play an important role in the pathology of sensitive skin. Objective: This study investigated lipid difference between sensitive skin caused by psychological stress and normal skin, followed by construction of a support vector machine (SVM). Methods: A noninvasive method was used to collect lipid samples from the skin surface. Ultra‐performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC‐Q‐TOF‐MS) technique and partial least squares‐discriminant analysis (PLS‐DA) was used to screen for differential lipids. A correlation analysis was performed on differential lipids, and a support vector model was established based on the differential lipids. Results: Twelve differential lipids were obtained, and the most differentiating species were triacylglycerols (TGs), followed by monounsaturated fatty acids (MUFAs), saturated fatty acids (SFAs), diacylglycerols (DGs), and 6‐hydroxysphingosine levels. Triglyceride, SFA, and MUFA species showed a high correlation, and the support vector machine (SVM) differentiation model based on differential lipids had a 100% accuracy rate. Conclusion: Psychological stress may cause damage to the permeability and antimicrobial barriers of the skin, thereby resulting in sensitive skin. Differentiation models based on SVMs have good prospects for distinguishing sensitive skin caused by psychological stress. [ABSTRACT FROM AUTHOR]

Background/Aims: Healthy skin harbors numerous microbes known to maintain its health and prevent attacks from external pathogens. The influence of chemical preservatives commonly used in cosmetic products on facial resident flora remains poorly characterized. In this study, we aimed to investigate the antibacterial activity of five such preservatives on in vitro cultivated skin‐resident bacteria. Methods: Both Gram‐positive and Gram‐negative bacteria were isolated on blood agar, tryptic soy agar, and nutrient agar; Gram‐negative bacteria were then selected on Hank's balanced salt solution containing antibiotics and Reasoner's 2A. The minimum inhibitory concentrations (MICs) of methylisothiazolinone (MTI), iodopropynyl butylcarbamate (IPBC), ethylhexylglycerin (EHG), methylparaben (MP), and phenoxyethanol (PE) were estimated for nine facial resident bacteria, Escherichia coli, and Staphylococcus aureus using serial broth dilution in vitro. Results: The maximum test concentrations coincided with the upper limits set by the "Cosmetic Safety and Technical Specification" (2015 edition, China). Nine facial resident bacteria were isolated from 14 healthy adults: Staphylococcus epidermidis, Staphylococcus capitis, Kocuria, Micrococcus luteus, Bacillus, Acinetobacter, Pseudomonas parafulva, Pseudomonas oleovorans, and Roseomonas cervicalis. MTI and IPBC displayed the strongest effect on all tested strains (MICs ≤0.01%), followed by EHG and MP (MICs ≤0.3%), and finally PE with the weakest effect (MIC ≤1%). Conclusion: The five chemical preservatives assayed inhibited survival of the nine facial resident bacteria isolates, when tested at the maximum allowed limit. The corresponding MICs will provide a reference for the effective utilization of these compounds in product formulations. [ABSTRACT FROM AUTHOR]