The skin functions as a physical barrier against entry of pathogens while concomitantly supporting a myriad of commensal organisms. The characterization of these microbial communities has enhanced our knowledge of the ecology of organisms present in normal skin, and studies have begun to illuminate the intimate relationship between the host and resident microbes. The cutaneous innate and adaptive immune responses can modulate skin microbiota, while simultaneously, the microbiota educates the host immune system. A crucial element of the innate immune response is mast cells, which reside strategically in tissues that are commonly exposed to the external environment, such as the skin and mucosae. Mast cells are present on the frontline of defense against pathogens, suggesting they may play an important role in fostering the host-microbiota relationship. In this review, we highlight findings regarding the interaction between skin microbiota and mast cells and the resulting outcomes in skin homeostasis.
Architectural Accessibility ; Ecology ; Foster Home Care ; Homeostasis ; Immune System ; Immunity, Innate ; Mast Cells* ; Microbiota* ; Mucous Membrane ; Skin*

The skin functions as a physical barrier against entry of pathogens while concomitantly supporting a myriad of commensal organisms. The characterization of these microbial communities has enhanced our knowledge of the ecology of organisms present in normal skin, and studies have begun to illuminate the intimate relationship between the host and resident microbes. The cutaneous innate and adaptive immune responses can modulate skin microbiota, while simultaneously, the microbiota educates the host immune system. A crucial element of the innate immune response is mast cells, which reside strategically in tissues that are commonly exposed to the external environment, such as the skin and mucosae. Mast cells are present on the frontline of defense against pathogens, suggesting they may play an important role in fostering the host-microbiota relationship. In this review, we highlight findings regarding the interaction between skin microbiota and mast cells and the resulting outcomes in skin homeostasis.
Architectural Accessibility ; Ecology ; Foster Home Care ; Homeostasis ; Immune System ; Immunity, Innate ; Mast Cells* ; Microbiota* ; Mucous Membrane ; Skin*

Obesity that caused by high-fat diet, heredity, drinking, or lack of exercise is related to metabolic syndrome, insulin resistance, type 2 diabetes and cardiovascular disease and it becomes a serious social problem. Although obesity shows low-grade chronic inflammation which induces from immune response in adipose tissue, relation between inflammation and pathogenesis of obesity has not been incompletely understood. Therefore, study for immune response in obesity is essential to design effective therapeutic strategy.
Adipose Tissue ; Cardiovascular Diseases ; Diet, High-Fat ; Drinking ; Heredity ; Inflammation* ; Insulin Resistance ; Obesity* ; Social Problems

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Purpose: This study aimed to examine the level of digital health literacy and identify factors associated with digital health literacy among older adults living alone in South Korea. Methods: A cross-sectional study was conducted on 140 older adults aged 65 and above who live alone. Descriptive statistics and non-parametric methods were used to explore the relationship between digital health literacy and independent variables. A generalized linear model was used to identify factors associated with digital health literacy. Results: Among 140 smartphone-owning older adults living alone, 52.1% were using the Internet via digital devices, and the participants’ average digital health literacy score was 6.64±7.46. Univariate analysis results showed significant differences in digital health literacy according to age, education level, and multimorbidity. The factors associated with digital health literacy were identified as gender (B=−0.36, p=.031), age (B=−0.06, p<.001), education level (B=0.12, p<.001), and sleep problems (B=−0.06, p=.006). Conclusion Despite widespread Internet and smartphone use, older adults living alone with chronic diseases showed low levels of digital health literacy, which were significantly associated with gender, age, education level, and sleep problems. Enhancing digital health literacy among vulnerable populations is crucial for the effective implementation of digital health services. Collaborative efforts, including tailored digital health interventions to enhance the digital health literacy of vulnerable populations and supportive policies, are essential to bridge the digital divide and promote health equity.

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Purpose: This study aimed to examine the level of digital health literacy and identify factors associated with digital health literacy among older adults living alone in South Korea. Methods: A cross-sectional study was conducted on 140 older adults aged 65 and above who live alone. Descriptive statistics and non-parametric methods were used to explore the relationship between digital health literacy and independent variables. A generalized linear model was used to identify factors associated with digital health literacy. Results: Among 140 smartphone-owning older adults living alone, 52.1% were using the Internet via digital devices, and the participants’ average digital health literacy score was 6.64±7.46. Univariate analysis results showed significant differences in digital health literacy according to age, education level, and multimorbidity. The factors associated with digital health literacy were identified as gender (B=−0.36, p=.031), age (B=−0.06, p<.001), education level (B=0.12, p<.001), and sleep problems (B=−0.06, p=.006). Conclusion Despite widespread Internet and smartphone use, older adults living alone with chronic diseases showed low levels of digital health literacy, which were significantly associated with gender, age, education level, and sleep problems. Enhancing digital health literacy among vulnerable populations is crucial for the effective implementation of digital health services. Collaborative efforts, including tailored digital health interventions to enhance the digital health literacy of vulnerable populations and supportive policies, are essential to bridge the digital divide and promote health equity.

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.

Purpose: This study aimed to examine the level of digital health literacy and identify factors associated with digital health literacy among older adults living alone in South Korea. Methods: A cross-sectional study was conducted on 140 older adults aged 65 and above who live alone. Descriptive statistics and non-parametric methods were used to explore the relationship between digital health literacy and independent variables. A generalized linear model was used to identify factors associated with digital health literacy. Results: Among 140 smartphone-owning older adults living alone, 52.1% were using the Internet via digital devices, and the participants’ average digital health literacy score was 6.64±7.46. Univariate analysis results showed significant differences in digital health literacy according to age, education level, and multimorbidity. The factors associated with digital health literacy were identified as gender (B=−0.36, p=.031), age (B=−0.06, p<.001), education level (B=0.12, p<.001), and sleep problems (B=−0.06, p=.006). Conclusion Despite widespread Internet and smartphone use, older adults living alone with chronic diseases showed low levels of digital health literacy, which were significantly associated with gender, age, education level, and sleep problems. Enhancing digital health literacy among vulnerable populations is crucial for the effective implementation of digital health services. Collaborative efforts, including tailored digital health interventions to enhance the digital health literacy of vulnerable populations and supportive policies, are essential to bridge the digital divide and promote health equity.

Objective: While using digital technologies for social health is widely acknowledged, the relationship between loneliness, social isolation, and digital health literacy remains unknown. This study aimed to assess the levels of loneliness, social isolation, and digital health literacy in older women living alone and to explore the associations between these factors. Methods: In August 2021, a cross-sectional survey was conducted on 145 older women living alone, selected using convenience sampling. The study used the University of California, Los Angeles Loneliness Scale (version 3), Lubben Social Network Scale-6, and Digital Health Technology Literacy-Assessment Questionnaire. The collected data were analyzed using descriptive statistics, the Mann–Whitney U test, the Kruskal–Wallis test, Spearman’s rho correlation, and a generalized linear model (GLM). Results: Of the participants, 22.8% (n=33) reported moderate loneliness, 20.7% (n=30) reported severe loneliness, and 36.6% (n=53) were at risk for social isolation. The mean digital health literacy score among participants was 4.85 (SD=6.92), which is relatively low. Importantly, our findings using a GLM to control for covariates revealed a significant association between loneliness (B=-0.013, p=0.018) and digital health literacy. Conclusion The increased loneliness experienced during the pandemic may contribute to low digital health literacy, alienating these individuals from the benefits of digital technologies. Therefore, in developing digital health programs or policies, it is imperative to consider the psychosocial status of individuals, including loneliness, while enhancing digital health literacy.