Development of an Internet-based Product-related Child Injury Textual Data Platform (IPCITDP) in China.

Background: Internet-based media stories provide valuable information for emerging risks of product-related child injury prevention and control, but critical methodological challenges and high costs of data acquisition and processing restrict practical use by stakeholders.

Methods: We constructed a data platform through literature reviews and multi-round research group discussions. Developed components included standard search strategies, filtering criteria, textual document classification, information extraction standards and a keyword dictionary.

Product-related injury morbidity among Americans aged 0-19 years, 2001-2020.

Introduction: This study examined changes in product-related injury morbidity among under-20 Americans between 2001 and 2020.

Method: Product-related injury morbidity data came from the National Electronic Injury Surveillance System (NEISS). Using age-standardized morbidity rates, the authors performed Joinpoint regression models to identify time periods with significant changes between 2001 and 2020 and quantified the annual magnitude of morbidity changes with annual percent changes (APCs) in rates and 95 % confidence intervals (CIs).

ARTCDP: An automated data platform for monitoring emerging patterns concerning road traffic crashes in China.

Online media reports provide valuable information for road traffic injury prevention, but technical challenges concerning data acquisition and processing limit analysis and interpretation of such data. Integrating injury epidemiology theory and big data technology, we developed a data platform consisting of four layers (data acquisition, data processing, application and data storage) to automatically collect reports from online Chinese media concerning road traffic crashes every 24 h. We built a text classification model using 20,000 manually annotated news stories based on the Bidirectional Encoder Representations from Transformers (BERT) and then used natural language processing algorithms to extract data concerning 27 structured variables from the news sources.

Coding quality of deaths and its impact on elderly unintentional fall mortality data from 1990 to 2019: a retrospective analysis of the WHO Mortality Database.

Background: Several studies have assessed the reporting quality of all-cause mortality data from the WHO Mortality Database, but little is known about coding quality and its impact on elderly unintentional fall mortality data worldwide. We aimed to assess the coding quality of deaths and its impact on elderly unintentional fall mortality.

Methods: Using data from the WHO Mortality Database, 1990-2019, we calculated the number of countries/territories that had mortality data in the database, and the proportion of deaths with five types of problematic codes based on the 10th International Classification of Disease (unspecified deaths, injury deaths with undetermined intent, unspecified unintentional injury, unintentional falls with unspecified mechanism, unintentional falls with unknown occurrence place).

Media Reports about Violence against Medical Care Providers in China.

Improper, unprofessional, or misleading media reports about violence against medical care providers (typically doctors and nurses) may provoke copycat incidents. To examine whether media reports about violence against medical care providers in China follow professional journalism recommendations, we identified 10 influential incidents of violence against medical care providers in China through a systematic strategy and used standardized internet-based search techniques to retrieve media reports about these events from 2007-2017. Reports were evaluated independently by trained coders to assess adherence to professional journalism recommendations using a 14-item checklist.

Changes in Six-Month Prevalence of Circulatory System Diseases among People Aged 20 Years and Older between 2013 and 2018 in Hunan, China.

Recent changes in population-based prevalence for circulatory system diseases (CSDs) remain unreported either nationally or locally for China. Data were from the two-round health service household interview survey of Hunan Province, China, in 2013 and 2018. A Rao-Scott chi-square test was performed to examine prevalence differences across socio-demographic variables.

Road traffic injury mortality and morbidity by country development status, 2011-2017.

Purpose: This research examined road traffic injury mortality and morbidity disparities across of country development status, and discussed the possibility of reducing country disparities by various actions to accelerate the pace of achieving Sustainable Development Goals target 3.6 - to halve the number of global deaths and injuries from road traffic accidents by 2020.

Methods: Data for road traffic mortality, morbidity, and socio-demographic index (SDI) were extracted by country from the estimates of the Global Burden of Disease study, and the implementation of the three types of national actions (legislation, prioritized vehicle safety standards, and trauma-related post-crash care service) were extracted from the Global Status Report on Road Safety by World Health Organization.

DeepHE: Accurately predicting human essential genes based on deep learning.

Accurately predicting essential genes using computational methods can greatly reduce the effort in finding them via wet experiments at both time and resource scales, and further accelerate the process of drug discovery. Several computational methods have been proposed for predicting essential genes in model organisms by integrating multiple biological data sources either via centrality measures or machine learning based methods. However, the methods aiming to predict human essential genes are still limited and the performance still need improve.

Unsafe Bicycling Behavior in Changsha, China: A Video-Based Observational Study.

The recent emergence of shared bikes has inspired renewed use of bicycles in urban China. However, incidence rates of unsafe cycling behaviors have not been reported using objective methods. We designed a video-based observational study in Changsha, China to estimate the incidence of five unsafe bicycling behaviors among both shared and personal bike riders and examine incidence differences across types of riders and cycling areas.

Data on unsafe riding behaviors among 1960 shared bicycle riders in urban China.

This data article quantifies the extent of shared bicycle riding risks for shared-bicycle riders in urban China. The data were collected through a WeChat-based online survey, with a valid sample of 1960 respondents. It reports the basic descriptive statistics through eight tables concerning various unsafe shared bicycle riding behaviors, and complete frequency data from riders concerning eight unsafe riding behaviors.

Unsafe riding behaviors of shared-bicycle riders in urban China: A retrospective survey.

Shared-bicycle use has skyrocketed in urban China, but little is known about the safety of bicycle users. The Chinese popular media reports multiple risky riding behaviors among shared bicycle riders, but scientific research on the topic is lacking. Therefore, we conducted a retrospective WeChat-based online survey to examine how often shared bicycle riders report engaging in risky cycling behaviors in urban China.

Needs Analysis for a Parenting App to Prevent Unintentional Injury in Newborn Babies and Toddlers: Focus Group and Survey Study Among Chinese Caregivers.

Background: With the growing popularity of mobile health technology, app-based interventions delivered by smartphone have become an increasingly important strategy toward injury prevention.

Objective: This study aimed to develop a framework supporting the design of an app-based intervention to prevent unintentional injury, targeted for caregivers of Chinese children aged 0 to 6 years.

Methods: A theory-based mixed-method study, including focus groups and Web-based quantitative survey, was performed.

Are Bus Company Regulations Associated with Crash Risk? Findings from a Retrospective Survey in Four Chinese Cities.

Bus crashes are common in urban China, and bus company regulations are hypothesized to be related to bus crash risk. We conducted a retrospective survey to examine the association in four large Chinese cities (Changsha, Shenzhen, Fuzhou, and Wuhan). Four types of bus crashes were considered: (a) passengers injured while riding the bus; (b) bus colliding with or scraping other motor vehicles; (c) bus colliding with non-motorized vehicles or pedestrians; and (d) bus damaging public facilities.

Predicting essential proteins by integrating orthology, gene expressions, and PPI networks.

Identifying essential proteins is very important for understanding the minimal requirements of cellular life and finding human disease genes as well as potential drug targets. Experimental methods for identifying essential proteins are often costly, time-consuming, and laborious. Many computational methods for such task have been proposed based on the topological properties of protein-protein interaction networks (PINs).

Evaluating the Effectiveness of Implementing a More Severe Drunk-Driving Law in China: Findings from Two Open Access Data Sources.

In 2011, China implemented a more severe drunk-driving law. This study evaluated the effectiveness of the law on road traffic morbidity and mortality attributed to alcohol use. Data were from two open-access data sources, the Global Burden of Disease (GBD) 2015 update and police data.

An ensemble framework for identifying essential proteins.

Background: Many centrality measures have been proposed to mine and characterize the correlations between network topological properties and protein essentiality. However, most of them show limited prediction accuracy, and the number of common predicted essential proteins by different methods is very small.

Results: In this paper, an ensemble framework is proposed which integrates gene expression data and protein-protein interaction networks (PINs).

A new method for the discovery of essential proteins.

Background: Experimental methods for the identification of essential proteins are always costly, time-consuming, and laborious. It is a challenging task to find protein essentiality only through experiments. With the development of high throughput technologies, a vast amount of protein-protein interactions are available, which enable the identification of essential proteins from the network level.