Single-cell RNA sequencing in diabetic kidney disease: a literature review.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD), and its pathogenesis has not been clarified. Current research suggests that DKD involves multiple cell types and extra-renal factors, and it is particularly important to clarify the pathogenesis and identify new therapeutic targets. Single-cell RNA sequencing (scRNA-seq) technology is high-throughput sequencing of the transcriptomes of individual cells at the single-cell level, which is an effective technology for exploring the development of diseases by comparing genetic information, reflecting the differences in genetic information between cells, and identifying different cell subpopulations.

Parental Pressure on Child Body Image, BMI, Body Image Dissatisfaction Associated with Eating Disorders in School-Age Children in China: A Path Analysis.

Background: Children's eating behaviors, body shape and body image cognition may be more susceptible to the influence of their parents, but these influences may be weakened with age. There may be different association pathways between parental pressure on children's body image (PPCBI), body mass index (BMI), body image dissatisfaction (BID) and eating disorders (EDs) among children and adolescents at different developmental stages.

Methods: The stratified cluster sampling method (Stratified by grade, and took the classes as clusters) was used to select 486 students aged 8-15 years in two 9-year schools.

Physical activity and eating behaviors patterns associated with high blood pressure among Chinese children and adolescents.

Background: Physical activity and eating behavior are associated with hypertension in children and adolescents. Revealing the associations between physical activity patterns, eating behavior patterns and high blood pressure (HBP) could help improve the problem of hypertension from the actual children's physical activities and eating behaviors.

Methods: A total of 687 students aged 8-15 years were selected from two nine-year primary and secondary schools using stratified cluster random sampling method.

Parental Stress on Children's Appearance, Body Dissatisfaction, and Eating Behaviours in Chinese Children: A Pathway Analysis.

Purpose: This study aimed to analyze the association pathways of parental stress on children's appearance, body dissatisfaction, and eating behaviours in Chinese children and adolescents.

Patients And Methods: The children aged 8-15 years were selected from 2 nine-year schools using stratified cluster random sampling. The appearance-related social stress questionnaire and the body dissatisfaction subscale of EDI-1 were used to investigate parental stress on children's appearance and body dissatisfaction, respectively.

Associations between negative gender attitudes and eating behaviors in Chinese children and adolescents.

Background: Negative gender cognitive attitudes (disliking one's own gender or wanting to be the opposite gender) and unhealthy eating behaviors have become common in Chinese children and adolescents. The aim of this study was to analyze the associations between negative gender attitudes and eating behaviors among Chinese children and adolescents.

Methods: Primary and secondary school students aged 8-15 years were selected as participants using a stratified cluster random sampling method.

Automated clinical coding: what, why, and where we are?

Clinical coding is the task of transforming medical information in a patient's health records into structured codes so that they can be used for statistical analysis. This is a cognitive and time-consuming task that follows a standard process in order to achieve a high level of consistency. Clinical coding could potentially be supported by an automated system to improve the efficiency and accuracy of the process.

Maximizing Coverage Quality with Budget Constrained in Mobile Crowd-Sensing Network for Environmental Monitoring Applications.

The Mobile Crowd-sensing Network is a novel cyber-physical-social network which has received great attention recently and can be used as a powerful tool to monitor the phenomenon of the field of interest. Due to the limited budget, how to choose appropriate participants to maximize the coverage quality is one of the most important issues when the mobile crowd-sensing network applies to practical application, such as air quality monitoring. In this paper, given the number of available participants, the traverse path and the reward of each participant, we investigate the problem of how to choose suitable participants to monitor an environment of a critical region by a crowd-sensing network, while the total rewards for all selected participants is not larger than the limited budget.

Forecasting smog-related health hazard based on social media and physical sensor.

Smog disasters are becoming more and more frequent and may cause severe consequences on the environment and public health, especially in urban areas. Social media as a real-time urban data source has become an increasingly effective channel to observe people׳s reactions on smog-related health hazard. It can be used to capture possible smog-related public health disasters in its early stage.

Social Media Meets Big Urban Data: A Case Study of Urban Waterlogging Analysis.

With the design and development of smart cities, opportunities as well as challenges arise at the moment. For this purpose, lots of data need to be obtained. Nevertheless, circumstances vary in different cities due to the variant infrastructures and populations, which leads to the data sparsity.

ELM Meets Urban Big Data Analysis: Case Studies.

In the latest years, the rapid progress of urban computing has engendered big issues, which creates both opportunities and challenges. The heterogeneous and big volume of data and the big difference between physical and virtual worlds have resulted in lots of problems in quickly solving practical problems in urban computing. In this paper, we propose a general application framework of ELM for urban computing.

Semantic Framework of Internet of Things for Smart Cities: Case Studies.

In recent years, the advancement of sensor technology has led to the generation of heterogeneous Internet-of-Things (IoT) data by smart cities. Thus, the development and deployment of various aspects of IoT-based applications are necessary to mine the potential value of data to the benefit of people and their lives. However, the variety, volume, heterogeneity, and real-time nature of data obtained from smart cities pose considerable challenges.

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query.