Evaluating the impact of COVID-19 outbreak on hepatitis B and forecasting the epidemiological trend in mainland China: a causal analysis.

Background: It is uncertain how COVID-19 outbreak influences the hepatitis B epidemics. This study aims to evaluate the effects on hepatitis B owing to the COVID-19 outbreak and forecast the hepatitis B epidemiological trend in mainland China to speed up the course of the "End viral hepatitis Strategy".

Methods: We estimated the causal impacts and created a forecast through adopting monthly notifications of hepatitis B each year from 2005 to 2020 in mainland China using the Bayesian structural time series (BSTS) method.

HMFT: Hyperspectral and Multispectral Image Fusion Super-Resolution Method Based on Efficient Transformer and Spatial-Spectral Attention Mechanism.

Due to the imaging mechanism of hyperspectral images, the spatial resolution of the resulting images is low. An effective method to solve this problem is to fuse the low-resolution hyperspectral image (LR-HSI) with the high-resolution multispectral image (HR-MSI) to generate the high-resolution hyperspectral image (HR-HSI). Currently, the state-of-the-art fusion approach is based on convolutional neural networks (CNN), and few have attempted to use Transformer, which shows impressive performance on advanced vision tasks.

Exploring the influence of COVID-19 on the spread of hand, foot, and mouth disease with an automatic machine learning prediction model.

Hand, foot, and mouth disease (HFMD) is an important public health problem and has received concern worldwide. Moreover, the coronavirus disease 2019 (COVID-19) epidemic also increases the difficulty of understanding and predicting the prevalence of HFMD. The purpose is to prove the usability and applicability of the automatic machine learning (Auto-ML) algorithm in predicting the epidemic trend of HFMD and to explore the influence of COVID-19 on the spread of HFMD.

A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA.

This prevalence of coronavirus disease 2019 (COVID-19) has become one of the most serious public health crises. Tree-based machine learning methods, with the advantages of high efficiency, and strong interpretability, have been widely used in predicting diseases. A data-driven interpretable ensemble framework based on tree models was designed to forecast daily new cases of COVID-19 in the USA and to determine the important factors related to COVID-19.

Nuclear Radiation Knowledge and Anxiety Levels among Residents around a Nuclear Power Plant in Liaoning Province, China.

Awareness of radiation-related knowledge (RRK) and nuclear energy-related knowledge (NERK) among residents around a nuclear power plant (NPP), as well as their concerns about a NPP, were investigated. A face-to-face survey was conducted among 1,775 residents within 30 km around the NPP in Liaoning Province, China. A single-item Likert scale, Spearman's/Pearson's correlation coefficients, Student's t-test, ANOVA, and multiple-linear regression analysis were employed.

Prognostic significance of long noncoding RNA HOTAIR in hepatocellular carcinoma: A protocol for systematic review and meta-analysis.

Background: Homeobox transcript antisense intergenic RNA (HOTAIR), a long noncoding RNA, has been reported to associate with the prognosis of patients with hepatocellular carcinoma (HCC) in several studies, however, the definite conclusion has not been obtained for conflicting results across different studies. The aim of this study is to determine the association of HOTAIR expression with overall survival, progression-free survival, and clinical features in HCC.

Methods: PubMed, Cochrane Library, and Embase will be comprehensively searched to seek the relevant studies.

Dual-Path Residual "Shrinkage" Network for Side-Scan Sonar Image Classification.

The underwater environment is complicated and changeable and contains many noises, making it difficult to detect a particular object in the underwater environment. At present, the main seabed detection technology explores the seabed environment with sonar equipment. However, the characteristics of underwater sonar imaging (e.

Vehicle Detection in Remote Sensing Image Based on Machine Vision.

Target detection in remote sensing images is very challenging research. Followed by the recent development of deep learning, the target detection algorithm has obtained large and fast growth. However, in the application of remote sensing images, due to the small target, wide range, small texture, and complex background, the existing target detection methods cannot achieve people's hope.

Time series analysis of hemorrhagic fever with renal syndrome in mainland China by using an XGBoost forecasting model.

Background: Hemorrhagic fever with renal syndrome (HFRS) is still attracting public attention because of its outbreak in various cities in China. Predicting future outbreaks or epidemics disease based on past incidence data can help health departments take targeted measures to prevent diseases in advance. In this study, we propose a multistep prediction strategy based on extreme gradient boosting (XGBoost) for HFRS as an extension of the one-step prediction model.

Trends of Annual Whole-body Occupational Radiation Exposure for Industrial Practices in China (2009-2018).

The national status and dose trends on the occupational exposure to ionizing radiation in industrial practices for 2009-2018 in China are presented in terms of seven occupational categories. A total of 504,538 industrial radiation workers were monitored for the period 2009-2018, with a continuous increase in the number of workers from 23,789 in 2009 to 66,017 in 2018. The annual average effective doses were 0.

Neonatal Crohn's disease with Oral ulcer as the first symptom caused by a compound heterozygote mutation in IL-10RA: a case report.

Objective: To investigate the clinical and genetic characteristics of neonatal Crohn's disease (CD), improve recognition of neonatal CD, and reduce the number of patients that are missed or misdiagnosed.

Methods: A 10-day-old Chinese girl with oral ulcers was admitted to the Department of Neonatology. She later developed a rash and perianal disease, but without diarrhea and stool abnormalities.

Antecedent infections in Guillain-Barré syndrome: a single-center, prospective study.

Objective: To investigate the spectrum of antecedent infections in Chinese patients with Guillain-Barré syndrome (GBS) and analyze the infections-related clinical phenotypes locally.

Methods: A prospective case-control study of 150 patients diagnosed with GBS and age- and sex-matched neurological and healthy controls was performed to investigate recent infections of 14 pathogens serologically and collect the clinical data during a follow-up of 12 months.

Results: In total, 53% of patients with GBS had a positive serology for recent infection, including Campylobacter jejuni (27%), influenza A (17%) and B (16%), hepatitis A virus (5%), dengue virus (3%), cytomegalovirus (3%), Epstein-Barr virus (3%), Mycoplasma pneumoniae (2%), herpes simplex virus (2%), varicella-zoster virus (1%), and rubella virus (1%).

Oxymatrine can attenuate pathological deficits of Alzheimer's disease mice through regulation of neuroinflammation.

Alzheimer's disease (AD) is a common neurodegenerative disorder characterized by progressive learning and cognitive damage. Several hypotheses such as amyloid cascade hypothesis, hyper-phosphorylated τ hypothesis, and energy metabolism hypothesis have been proposed to elucidate the disease. However, the exact mechanism of AD remains unclear and current therapeutic strategies are miserable.

Oxymatrine attenuates cognitive deficits through SIRT1-mediated autophagy in ischemic stroke.

To investigate if oxymatrine could ameliorate hippocampus ischemia/reperfusion (I/R) injury induced in rats and explore the possible mechanism. Rats were randomly divided into four groups: sham group, I/R group, I/R + OMT-treated group, I/R + Vehicle-treated group. Oxymatrine or vehicle solution was intraperitoneally injected OMT (150 mg/kg) 60 min before renal ischemia respectively.

Effect of erythropoietin combined with hypothermia on serum tau protein levels and neurodevelopmental outcome in neonates with hypoxic-ischemic encephalopathy.

Although hypothermia therapy is effective to treat neonatal hypoxic-ischemic encephalopathy, many neonatal patients die or suffer from severe neurological dysfunction. Erythropoietin is considered one of the most promising neuroprotective agents. We hypothesized that erythropoietin combined with hypothermia will improve efficacy of neonatal hypoxic-ischemic encephalopathy treatment.

IgG-degrading enzyme of Streptococcus pyogenes (IdeS) prevents disease progression and facilitates improvement in a rabbit model of Guillain-Barré syndrome.

Autoantibodies binding to peripheral nerves followed by complement deposition and membrane attack complex formation results in nerve damage in Guillain-Barré syndrome (GBS). Strategies to remove the pathogenic autoantibodies or block the complement deposition benefit most patients with GBS. Immunoglobulin G-degrading enzyme of Streptococcus pyogenes (IdeS) is a cysteine protease which cleaves IgG antibodies into F(ab') and Fc fragments.