Estimation of pathological subtypes in subsolid lung nodules using artificial intelligence.

Objective: This study aimed to investigate the value of artificial intelligence (AI) for distinguishing pathological subtypes of invasive pulmonary adenocarcinomas in patients with subsolid nodules (SSNs).

Materials And Methods: This retrospective study included 110 consecutive patients with 120 SSNs. The qualitative and quantitative imaging characteristics of SSNs were extracted automatically using an artificially intelligent assessment system.

A nomogram to predict severe COVID-19 patients with increased pulmonary lesions in early days.

Objectives: This study aimed to predict severe coronavirus disease 2019 (COVID-19) progression in patients with increased pneumonia lesions in the early days. A simplified nomogram was developed utilizing artificial intelligence (AI)-based quantified computed tomography (CT).

Methods: From 17 December 2019 to 20 February 2020, a total of 246 patients were confirmed COVID-19 infected in Jingzhou Central Hospital, Hubei Province, China.

Perspective view of allogeneic IgG tumor immunotherapy.

Allogeneic tumors are eradicated by host immunity; however, it is unknown how it is initiated until the report in Nature by Yaron Carmi et al. in 2015. Currently, we know that allogeneic tumors are eradicated by allogeneic IgG via dendritic cells.

Global, regional, and national time trends in incidence for tuberculosis, 1990-2019: An age-period-cohort analysis for the Global Burden of Disease 2019 study.

Background: Tuberculosis (TB) represents a significant global health concern, being the leading cause of mortality from a single infectious agent worldwide. The investigation of TB incidence and epidemiological trends is critical for evaluating the effectiveness of control strategies and identifying ongoing challenges.

Objectives: This study presents the trend in TB incidence across 204 countries and regions over a 30-year period.

Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer.

Background: Over the past few years, research into the pathogenesis of colon cancer has progressed rapidly, and cuproptosis is an emerging mode of cellular apoptosis. Exploring the relationship between colon cancer and cuproptosis benefits in identifying novel biomarkers and even improving the outcome of the disease.

Aim: To look at the prognostic relationship between colon cancer and the genes associated with cuproptosis and the immune system in patients.

Improving diagnostic performance of rib fractures for the night shift in radiology department using a computer-aided diagnosis system based on deep learning: A clinical retrospective study.

Objective: To investigate the application value of a computer-aided diagnosis (CAD) system based on deep learning (DL) of rib fractures for night shifts in radiology department.

Methods: Chest computed tomography (CT) images and structured reports were retrospectively selected from the picture archiving and communication system (PACS) for 2,332 blunt chest trauma patients. In all CT imaging examinations, two on-duty radiologists (radiologists I and II) completed reports using three different reading patterns namely, P1 = independent reading during the day shift; P2 = independent reading during the night shift; and P3 = reading with the aid of a CAD system as the concurrent reader during the night shift.

Integrated assessment of land-to-river Cd fluxes and riverine Cd loads using SWAT-HM to guide management strategies.

In 2011, China invested US$9.8 billion to combat the severe heavy metal pollution in the Xiang River basin (XRB), aiming to reduce 50% of the 2008 industrial metal emissions by 2015. However, river pollution mitigation requires a holistic accounting of both point and diffuse sources, yet the detailed land-to-river metal fluxes in the XRB remain unclear.

Screening of potential hub genes involved in Cutaneous Leishmaniasis infection via bioinformatics analysis.

Background: Cutaneous Leishmaniasis (CL) is the most common clinical form of leishmaniasis. Despite its low mortality, CL deserves further attention because its pathogenesis is currently no well-known or well-researched.

Methods: We downloaded the gene expression datasets of GSE55664 and GSE63931 with respect to leishmaniasis from the Gene Expression Synthesis (GEO) database.

China economy-wide material flow account database from 1990 to 2020.

Material utilisation has been playing a fundamental role in economic development, but meanwhile, it may have environmental and social consequences. Given China's rapid economic growth, understanding China's material utilisation patterns would inform decisions for researchers and policymakers. However, fragmented data from multiple statistical sources hinder us from comprehensively portraying China's material utilisation dynamics.

Effects of purifiers on the airborne transmission of droplets inside a bus.

During an airborne infectious disease outbreak, bus passengers can be easily infected by the dispersion of exhaled droplets from an infected passenger. Therefore, measures to control the transport of droplets are necessary, such as a mask or purifier. The current research examined aerosol transport in a bus with air-conditioning.

Artificial intelligence for stepwise diagnosis and monitoring of COVID-19.

Background: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial intelligence system based on deep learning (DL) and federated learning (FL) for the diagnosis, monitoring, and prediction of a patient's clinical course.

Methods: CT imaging derived from 6 different multicenter cohorts were used for stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data.

Investigation of hub gene associated with the infection of Staphylococcus aureus via weighted gene co-expression network analysis.

Introduction: Staphylococcus aureus is a gram-positive bacterium that causes serious infection. With the increasing resistance of bacteria to current antibiotics, it is necessary to learn more about the molecular mechanism and cellular pathways involved in the Staphylococcus aureus infection.

Methods: We downloaded the GSE33341 dataset from the GEO database and applied the weighted gene co-expression network analysis (WGCNA), from which we obtained some critical modules.

China material stocks and flows account for 1978-2018.

As the world's top material consumer, China has created intense pressure on national or global demand for natural resources. Building an accurate material stocks and flows account of China is a prerequisite for promoting sustainable resource management. However, there is no annually, officially published material stocks and flows data in China.

A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study.

Objective: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed.

Methods: Total 400 COVID-19 patients with underlying health conditions were retrospectively recruited from 4 centers, including 54 dead cases (labeled as poor outcomes) and 346 patients discharged or hospitalized for at least 7 days since initial CT scan.

Spatial-temporal characteristics and driving factors of the human health impacts of five industrial aquatic toxic metals in China.

With the rapid advancement of industrialization without effective supervision, industrial aquatic toxic metal (TM) emissions pose threats to human health in China. Due to differences in socioeconomic development, the regional disparity of industrial aquatic TM emissions is obvious nationwide. In this study, the human health impacts (HHIs) of industrial aquatic TM emissions (i.

China's industrial gray water footprint assessment and implications for investment in industrial wastewater treatment.

Industrial wastewater is the largest contributor of toxic pollutants and third-largest contributor of nutrients to bodies of water in China, and understanding the characteristics of such pollution is important for water pollution control. In this study, the industrial gray water footprint (GWF) of each industry sector in China's 31 provinces in 2015 was calculated to identify the pollution characteristics of industrial wastewater discharge and determine how to efficiently allocate investment to pollution reduction. We show that the total industrial GWF of China was 300 billion m in 2015 and that the major pollutants were petroleum pollutant (PP), ammonia nitrogen (NH-N), volatile phenol (VP), and chemical oxygen demand (COD).

CCN2, connective tissue growth factor, stimulates collagen deposition by gingival fibroblasts via module 3 and alpha6- and beta1 integrins.

CCN2, (connective tissue growth factor, CTGF) is a matricellular factor associated with fibrosis that plays an important role in the production and maintenance of fibrotic lesions. Increased collagen deposition and accumulation is a common feature of fibrotic tissues. The mechanisms by which CCN2/CTGF contributes to fibrosis are not well understood.