Burden of Stroke Attributable to Nonoptimal Temperature in 204 Countries and Territories: A Population-Based Study, 1990-2019.

BACKGROUND AND OBJECTIVES: Stroke attributable to nonoptimal temperature needs more attention with dramatic climate change. The aim of this study was to estimate the global burden and distribution characteristics of the burden. METHODS: In this ecological study, we collected data from the Climate Research Unit Gridded Time Series, the World Bank databases, and the Global Burden of Diseases study to estimate the distribution of burden. We used the joinpoint model, decomposition analysis, age-period-cohort model, panel data analysis, and health inequality analysis to assess the different types of stroke burden attributable to different climatic conditions. RESULTS: The burden of stroke attributable to nonoptimal temperature continued to grow, and aging was a key factor in this increase. In 2019, 521,031 (95% uncertainty interval [UI] 402,433-663,996) deaths and 9,423,649 (95% UI 7,207,660-12,055,172) disability-adjusted life years [DALYs] attributable to stroke due to nonoptimal temperature were recorded globally. Globally, men (age-standardized mortality rate [ASMR] 7.70, 95% UI 5.80-9.73; age-standardized DALY rate [ASDR] 139.69, 95% UI 102.96-178.54 in 2019) had a heavier burden than women (ASMR 5.89, 95% UI 4.50-7.60; ASDR 96.02, 95% UI 72.62-123.85 in 2019). Central Asia (ASMR 18.12, 95% UI 13.40-24.53; ASDR 327.35, 95% UI 240.24-440.61 in 2019) had the heaviest burden at the regional level. In the national level, North Macedonia (ASMR 32.97, 95% UI 20.57-47.44 in 2019) and Mongolia (ASDR 568.54, 95% UI 242.03-1,031.14 in 2019) had the highest ASMR/ASDR, respectively. Low temperature currently contributes to the main burden (deaths 474,002, 95% UI 355,077-606,537; DALYs 8,357,198, 95% UI 6,186,217-10,801,911 attributable to low temperature vs deaths 48,030, 95% UI 5,630-104,370; DALYs 1,089,329, 95% UI 112,690-2,375,345 attributable to high temperature in 2019). However, the burden due to high temperature has increased rapidly, especially among people aged older than 10 years, and was disproportionately concentrated in low sociodemographic index (SDI) regions such as Africa. In addition, the rapid increase in the stroke burden due to high temperature in Central Asia also requires special attention. DISCUSSION: This is the first study to assess the global stroke burden attributed to nonoptimal temperature. The dramatic increase in the burden due to high temperature requires special attention, especially in low-SDI countries.

Burden of cardiovascular disease among elderly: based on the Global Burden of Disease Study 2019.

BACKGROUND: The burden of elderly cardiovascular disease (CVD) has received increasing attention with population ageing worldwide. AIMS: We reported on the global CVD burden in elderly individuals over 70, 1990-2019. METHODS AND RESULTS: Based on the Global Burden of Disease Study 2019, elderly CVD burden data were analysed. Temporal burden trends were analysed with the joinpoint model. The slope index and concentration index were used to evaluate health inequality. From 1990 to 2019, the global elderly CVD incidence, prevalence, death, and disability-adjusted life year rates generally decreased. However, the current burden remains high. The rapid growth in burden in parts of sub-Saharan Africa and Asia is a cause for concern. Countries with a higher socio-demographic index (SDI) have generally seen a greater decrease in burden, while countries with a lower SDI have generally experienced increases or smaller declines in burden. Health inequality analysis confirmed that the burden was gradually concentrating towards countries with a low SDI. Among the different CVDs, ischaemic heart disease causes the greatest burden in elderly individuals. Most CVD burdens increase with age, but stroke and peripheral vascular disease show markedly different distributional characteristics. In addition, the burden of hypertensive heart disease shows an unusual shift towards high-SDI countries. High systolic blood pressure was consistently the leading risk factor for CVD among elderly individuals. CONCLUSION: The burden of CVD in older people remains severe and generally tends to shift to lower-SDI countries. Policymakers need to take targeted measures to reduce its harm.

Global Burden and Its Association with Socioeconomic Development Status of Meningitis Caused by Specific Pathogens over the Past 30 years: A Population-Based Study.

BACKGROUND: Meningitis is a severe and fatal neurological disease and causes lots of disease burden. The purpose of this study was to assess the global, regional, and national burdens and trends of meningitis by age, sex, and etiology. METHODS: Data on the burden of meningitis were collected from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. R and Joinpoint were used for statistical analysis and charting. RESULTS: In 2019, meningitis caused 236,222 deaths and 15,649,865 years of life lost (YLL) worldwide. The age-standardized death rate and age-standardized YLL rate of meningitis were 3.29 and 225, which decreased steadily. Burden change was mainly driven by epidemiological changes. Regionally, meningitis burden was the highest in Sub-Saharan Africa. Burden of disease increasingly concentrated in low sociodemographic index countries, and this was most pronounced in meningitis caused by N. meningitidis. Countries such as Mali, Nigeria, Sierra Leone, etc., especially need to enhance the rational allocation of public health resources to reduce the disease burden. Children and men were more likely to be affected by meningitis. PM2.5 was found to be an important risk factor. CONCLUSIONS: This study provides the first comprehensive understanding of the global disease burden of meningitis caused by specific pathogens and highlights policy priorities to protect human health worldwide, with particular attention to vulnerable regions, susceptible populations, environmental factors, and specific pathogens.

Multilevel Classification of Users' Needs in Chinese Online Medical and Health Communities: Model Development and Evaluation Based on Graph Convolutional Network.

BACKGROUND: Online medical and health communities provide a platform for internet users to share experiences and ask questions about medical and health issues. However, there are problems in these communities, such as the low accuracy of the classification of users' questions and the uneven health literacy of users, which affect the accuracy of user retrieval and the professionalism of the medical personnel answering the question. In this context, it is essential to study more effective classification methods of users' information needs. OBJECTIVE: Most online medical and health communities tend to provide only disease-type labels, which do not give a comprehensive summary of users' needs. The study aims to construct a multilevel classification framework based on the graph convolutional network (GCN) model for users' needs in online medical and health communities so that users can perform more targeted information retrieval. METHODS: Using the Chinese online medical and health community "Qiuyi" as an example, we crawled questions posted by users in the "Cardiovascular Disease" section as the data source. First, the disease types involved in the problem data were segmented by manual coding to generate the first-level label. Second, the needs were identified by K-means clustering to generate the users' information needs label as the second-level label. Finally, by constructing a GCN model, users' questions were automatically classified, thus realizing the multilevel classification of users' needs. RESULTS: Based on the empirical research of questions posted by users in the "Cardiovascular Disease" section of Qiuyi, the hierarchical classification of users' questions (data) was realized. The classification models designed in the study achieved accuracy, precision, recall, and F1-score of 0.6265, 0.6328, 0.5788, and 0.5912, respectively. Compared with the traditional machine learning method naïve Bayes and the deep learning method hierarchical text classification convolutional neural network, our classification model showed better performance. At the same time, we also performed a single-level classification experiment on users' needs, which in comparison with the multilevel classification model exhibited a great improvement. CONCLUSIONS: A multilevel classification framework has been designed based on the GCN model. The results demonstrated that the method is effective in classifying users' information needs in online medical and health communities. At the same time, users with different diseases have different directions for information needs, which plays an important role in providing diversified and targeted services to the online medical and health community. Our method is also applicable to other similar disease classifications.

Advances in Optical Sensing and Bioanalysis Enabled by 3D Printing.

The recent explosion of 3D printing applications in scientific literature has expanded the speed and effectiveness of analytical technological development. 3D printing allows for manufacture that is simply designed in software and printed in-house with nearly no constraints on geometry, and analytical methodologies can thus be prototyped and optimized with little difficulty. The versatility of methods and materials available allows the analytical chemist or biologist to fine-tune both the structural and functional portions of their apparatus. This flexibility has more recently been extended to optical-based bioanalysis, with higher resolution techniques and new printing materials opening the door for a wider variety of optical components, plasmonic surfaces, optical interfaces, and biomimetic systems that can be made in the laboratory. There have been discussions and reviews of various aspects of 3D printing technologies in analytical chemistry; this Review highlights recent literature and trends in their applications to optical sensing and bioanalysis.

Silver decahedral nanoparticles empowered SPR imaging-SELEX for high throughput screening of aptamers with real-time assessment.

A highly efficient method for aptamer screening with real-time monitoring of the SELEX process was described by silver decahedra nanoparticles (Ag10-NPs) enhanced surface plasmon resonance imaging (SPRI). A microarray chip was developed by immobilization of target protein (Lactoferrin (Lac)) and control proteins (α-lactalbumin (α), ß-lactoglobulin (ß), casein, and bovine serum albumin (BSA)) on the biochip surface. Ag10-NPs were conjugated with an ssDNA library (lib) (Ag10-NPs-library) that consisted of a central 40 nt randomized sequence and a 20 nt fixed primer sequence. Introduction of the Ag10-NPs-library to the SPRI flow channels drastically increased the sensitivity of SPRI signal for real-time monitoring of SELEX. The work allows rapid screening of potential targets, and yields nine aptamers with high affinity (nanomolar range) for Lac after only six-rounds of selection. The aptamer Lac 13-26 was then further tested by SPRI, and the results demonstrated that the aptamer had the capacity to be ultra-sensitive for specific detection of Lac. The novel SPRI-SELEX method demonstrated here showed many advantages of real-time evaluation, high throughput, and high efficiency.

Efficient label-free chemiluminescent immunosensor based on dual functional cupric oxide nanorods as peroxidase mimics.

Dual-functional cupric oxide nanorods (CuONRs) as peroxidase mimics are proposed for the development of a flow-through, label-free chemiluminescent (CL) immunosensor. Forming the basis of this cost-efficient, label-free immunoassay, CuONRs, synthesized using a simple hydrothermal method, were deposited onto epoxy-activated standard glass slides, followed by immobilization of biotinylated capture antibodies through a streptavidin bridge. The CuONRs possess excellent catalytic activity, along with high stability as a solid support. Antigens could then be introduced to the sensing system, forming large immunocomplexes that prevent CL substrate access to the surface, thereby reducing the CL signal in a concentration dependent fashion. Using carcinoembryonic antigen (CEA) as a model analyte, the proposed label-free immunosensor was able to rapidly determine CEA with a wide linear range of 0.1-60ngmL-1 and a low detection limit of 0.05ngmL-1. This nanozyme-based immunosensor is simple, sensitive, cost-efficient, and has the potential to be a very promising platform for fast and efficient biosensing applications.

[Assessment of eco-economic system sustainable development of Liaoning province based on emergy analysis].

By constructing an evaluation system based on emergy analysis which included emergy flow, source of emergy index, social subsystem evaluation index, economic subsystem evaluation index, natural subsystem evaluation index and composite index, the development and sustainability of the eco-economic system of Liaoning Province between 2000 and 2010 were evaluated. The result showed that from 2000 to 2010, the total used emergy increased from 3440.12 x 10(20) sej to 7636.33 x 10(20) sej, among which the proportion of the nonrenewable emergy in 2010 occupied the most in the total by 68.6% , and the emergy per capita increased from 8.32 x 10(15) sej to 17.96 x 10(15) sej. The emergy self-support ratio in the system was generally higher, while it dropped from 91.1% in 2000 to 79.9% in 2010. The emergy loading ratio increased from 3.22 to 7.80, the emergy sustainable index dropped from 3.47 to 0.64, and the emergy index for sustainable development decreased from 6.73 to 1.56. It suggested the eco-economic system of Liaoning Province presented an unsustainable development trend. The development level of Liaoning in 2010 merely equaled to the level of Japan and America in the 1980s.

Ultrathin calcinated films on a gold surface for highly effective laser desorption/ionization of biomolecules.

We report a nanoscale calcinated silicate film fabricated on a gold substrate for highly effective, matrix-free laser desorption ionization mass spectrometry (LDI-MS) analysis of biomolecules. The calcinated film is prepared by a layer-by-layer (LbL) deposition/calcination process wherein the thickness of the silicate layer and its surface properties are precisely controlled. The film exhibits outstanding efficiency in LDI-MS with extremely low background noise in the low-mass region, allowing for effective analysis of low mass samples and detection of large biomolecules including amino acids, peptides, and proteins. Additional advantages for the calcinated film include ease of preparation and modification, high reproducibility, low cost, and excellent reusability. Experimental parameters that influence LDI on calcinated films have been systemically investigated. Presence of citric acid in the sample significantly enhances LDI performance by facilitating protonation of the analyte and reducing fragmentation. The wetting property and surface roughness appear to be important factors that manipulate LDI performance of the analytes. This new substrate presents a marked advance in the development of matrix-free mass spectrometric methods and is uniquely suited for analysis of biomolecules over a broad mass range with high sensitivity. It may open new avenues for developing novel technology platforms upon integration with existing methods in microfluidics and optics.