Dataset Information

Microbiome in Healthy Women Between Two Districts With Different Air Quality Index.

ABSTRACT: Although the diversity and abundance of skin microbiome are mainly determined by intrinsic factors, including gender, age, anatomical site, and ethnicity, we question whether facial microbiome could be affected by long-term exposure to airborne pollution. Using 16S ribosomal RNA (rRNA) gene amplicon sequencing, we analyzed the facial bacterial microbiome of healthy and young Chinese women (25-35 years old) between two districts with different air quality indices (AQIs) in Zhejiang Province. The overall microbiome structure was obviously different between these two districts. It revealed an increase in both the abundance and diversity of facial bacterial microbiome in Hangzhou (HZ) with higher AQI compared with those in Yunhe (YH) with lower AQI. Linear discriminant analysis (LDA) and Lefse analysis identified a total of 45 genera showing significant overrepresentation in the HZ group. Furthermore, PICRUSt analysis showed that functional pathways associated with metabolism of saturated fatty acid were relatively more predominant in the HZ group, whereas those with DNA repair or mitochondrial DNA replication were more predominant in the YH group. Our present data can provide useful information for further researches on the composition and function of the skin microbiome related to air pollution factors as well as for the development of therapeutic agents targeting the microbes and their metabolites to resist damages of airborne pollutants.

SUBMITTER: Wu Y

PROVIDER: S-EPMC7604314 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Microbiome in Healthy Women Between Two Districts With Different Air Quality Index.

Wu Yinhua Y Wang Zujin Z Zhang Yu Y Ruan Liming L Li Ang A Liu Xiaoyan X

Frontiers in microbiology 20201019

Although the diversity and abundance of skin microbiome are mainly determined by intrinsic factors, including gender, age, anatomical site, and ethnicity, we question whether facial microbiome could be affected by long-term exposure to airborne pollution. Using 16S ribosomal RNA (rRNA) gene amplicon sequencing, we analyzed the facial bacterial microbiome of healthy and young Chinese women (25-35 years old) between two districts with different air quality indices (AQIs) in Zhejiang Province. The ...[more]

PMID: 33193129

Similar Datasets

Project description:IntroductionThe aging population presents both unique challenges and opportunities for societies around the world. To develop an effective healthy aging strategy, a tool for assessing aging process is needed. Numerous attempts to quantify the aging process have been made. However, there is still a challenge in developing and choosing a good enough score that is easy to apply, has a construct of variables that are available in most nationwide surveys for comparable results, and at the same time reflects the aging process of older individuals. The purpose of this study is to present our approach to construct a comparable Healthy Aging Index (HAI).Materials and methodsIn Latvia, data from Wave 8 of the Survey of Health, Aging and Retirement in Europe (SHARE), involving 420 respondents, were used. For comparative analysis, data from a HL20 study on the health and wellbeing of the older adults in Iceland, which included 1,033 respondents, were used.ResultsFor Latvia, 13 items were selected, and for Iceland, nine items were selected. We constructed the HAI with four similar subscales for both countries-"Autonomy," "Health," "Wellbeing," and "Activities," and an additional subscale "Cognitive" for Latvia. We found matching items in all four subscales. For the Autonomy subscale, they were related to difficulties with everyday and daily tasks. In the Health subscale, the only matching item was self-rated physical health. One item related to loneliness was found for the Wellbeing subscale and one item related to social participation for the Activities subscale.DiscussionIn our study, we found evidence for the successful construction of a HAI in two different datasets. The strength of our construct lies in the use of data from one of the largest social science panel studies in Europe (SHARE). As we were able to apply the construct to the Icelandic study, we believe that items presented in our approach are available in other population-based studies as well, and, therefore, can be easily replicated by others. By examining the existing SHARE data, HAI could be used to analyze long-term changes and could provide a foundation for comparing and monitoring the evolution of aging over time as well as comparing the aging process across societies. This is required for the authorities to conduct further analyses, proposals, and action plans in support of healthy aging.

Project description:With the ongoing challenge of air pollution posing serious health and environmental threats, particularly in rapidly industrializing regions, accurate forecasting and effective pollutant identification are crucial for enhancing public health and ecological stability. This study aimed to optimize air quality management through the prediction of the Air Quality Index (AQI) and identification of air pollutants. Our study spans nine representative cities (Hohhot, Yinchuan, Lanzhou, Beijing, Taiyuan, Xi'an, Shanghai, Nanjing, Wuhan) in China, with data collected from January 1, 2015, to November 30, 2021. We proposed a new model for daily AQI prediction, termed VMD-CSA-CNN-LSTM, which employed advanced machine learning techniques, including convolutional neural networks (CNN) and long short-term memory (LSTM) networks, and leveraged the chameleon swarm algorithm (CSA) for hyperparameter optimization, integrated through a variational mode decomposition approach. The model was developed using data from Lanzhou, with a split ratio of 8:1:1 into training, validation, and test sets, achieving an RMSE of 2.25, MAPE of 0.02, adjusted R-squared of 98.91%, and training efficiency of 5.31%. The model was further externally validated in the other eight cities, yielding comparable results, with an adjusted R-squared above 96%, MAPE below 0.1, and RMSE below 7.5. Additionally, we employed a random forest algorithm to identify the primary pollutants contributing to AQI levels. Our results indicated that PM2.5 was the most significant pollutant in Beijing, Taiyuan, and Xi'an, while PM10 was dominant in Hohhot, Yinchuan, and Lanzhou. In Shanghai, Nanjing, and Wuhan, both PM2.5 and PM10 were critical, with ozone also identified as a major air pollutant. This study not only advances the predictive accuracy of AQI models but also aids policymakers by providing a reliable tool for air quality management and strategic planning aimed at pollution reduction. The integration of these advanced computational techniques into environmental monitoring practices offers a promising avenue for enhancing air quality and mitigating pollution-related risks.

Project description:The human salivary microbial community plays a crucial role in local and systemic diseases. Biological and lifestyle factors such as menstrual cycle, oral hygiene, and smoking have been documented to impact this community. However, while hormonal contraceptives are the most prescribed drug in healthy women and intimate partners play key roles in microbial exchange between humans, their impact on the salivary microbiome of women of reproductive age have been understudied. Additionally, the role of other lifestyle factors such as diet, allergies, age, and stress on the saliva microbiome of the general population is not well understood. Here, we studied the salivary microbiome of 255 healthy women of reproductive age using self-sampling kits and 16S rRNA amplicon sequencing combined with questionnaires on lifestyle and host-related parameters. A preserved salivary bacterial community of 12 genera (Actinobacillus, Actinomyces, Alloprevotella, Campylobacter, Fusobacterium, Gemella, Granulicatella, Leptotrichia, Neisseria, Prevotella, Streptococcus, and Veillonella) was identified. Contrary to what we expected, the number of intimate partners or specific contraceptive use did not have a major impact on these bacterial communities. However, recent use of oral antibiotics was associated with a significant decrease in richness at genus level and increase in mean relative abundances of several taxa. Being stressed or nervous was associated with a significantly increased richness of the salivary microbiome at the level of amplicon sequencing variants . Nevertheless, these associations with host-related and lifestyle variables only appeared to be subtle, suggesting that the salivary microbiome is mainly driven by the buccal environment and health status of an individual. IMPORTANCE The salivary microbiome has been proven to play a crucial role in local and systemic diseases. Moreover, the effects of biological and lifestyle factors such as oral hygiene and smoking on this microbial community have already been explored. However, what was not yet well understood was the natural variation of the saliva microbiome in healthy women and how this is associated with specific use of hormonal contraception and with the number of different sexual partners with whom microbiome exchange is expected regularly. In this paper, we characterized the salivary microbiome of 255 healthy women of reproductive age using an in-depth questionnaire and self-sampling kits. Using the large metadata set, we were able to investigate the associations of several host-related and lifestyle variables with the salivary microbiome profiles. Our study shows a high preservation between individuals.

Dataset Information

Microbiome in Healthy Women Between Two Districts With Different Air Quality Index.

Publications

Microbiome in Healthy Women Between Two Districts With Different Air Quality Index.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets