EncephalApp stroop test versus electronic number connection test-A for screening minimal hepatic encephalopathy in patients with liver cirrhosis: a comparative study.

OBJECTIVES: Minimal hepatic encephalopathy (MHE) is a common neuropsychiatric complication of liver cirrhosis. Both EncephalApp Stroop test (EncephalApp) and electronic number connection test-A (eNCT-A) are novel computerised psychometric tests for MHE screening. We aimed to compare the efficiency, convenience, accessibility, and acceptability of EncephalApp with that of eNCT-A for MHE screening in cirrhotic patients. METHODS: Ninety-five patients with hepatitis B-induced liver cirrhosis were included and respectively tested by the psychometric hepatic encephalopathy score (PHES), EncephalApp, and eNCT-A. Using PHES as the gold standard for MHE diagnosis, the efficiency of EncephalApp and eNCT-A for MHE screening were respectively analysed by the receiver operating characteristic (ROC) curve, and the areas under the ROC curve (AUROC) were compared. The convenience, accessibility, and acceptability of PHES, EncephalApp and eNCT-A were respectively evaluated by the 5-point Likert scale. RESULTS: Fifty-two (55%) of included cirrhotic patients were diagnosed with MHE. The EncephalApp had a sensitivity of 84.6%, a specificity of 74.4%, and an AUROC of 0.836. Meanwhile, the eNCT-A had a sensitivity of 78.8%, a specificity of 83.7%, and an AUROC of 0.845. No significant difference in AUROC was detected between the EncephalApp and eNCT-A (p = .453). Compared with the EncephalApp, the eNCT-A presented better convenience and higher acceptability in cirrhotic patients undergoing MHE screening (p = .019 and p < .001, respectively). CONCLUSIONS: As with the EncephalApp, the eNCT-A will be a potential home monitoring and point-of-care tool for cirrhotic patients at high risk of MHE.

Risk of Coronavirus Disease 2019 Transmission in Train Passengers: an Epidemiological and Modeling Study.

BACKGROUND: Train travel is a common mode of public transport across the globe; however, the risk of coronavirus disease 2019 (COVID-19) transmission among individual train passengers remains unclear. METHODS: We quantified the transmission risk of COVID-19 on high-speed train passengers using data from 2334 index patients and 72 093 close contacts who had co-travel times of 0-8 hours from 19 December 2019 through 6 March 2020 in China. We analyzed the spatial and temporal distribution of COVID-19 transmission among train passengers to elucidate the associations between infection, spatial distance, and co-travel time. RESULTS: The attack rate in train passengers on seats within a distance of 3 rows and 5 columns of the index patient varied from 0 to 10.3% (95% confidence interval [CI], 5.3%-19.0%), with a mean of 0.32% (95% CI, .29%-.37%). Passengers in seats on the same row (including the adjacent passengers to the index patient) as the index patient had an average attack rate of 1.5% (95% CI, 1.3%-1.8%), higher than that in other rows (0.14% [95% CI, .11%-.17%]), with a relative risk (RR) of 11.2 (95% CI, 8.6-14.6). Travelers adjacent to the index patient had the highest attack rate (3.5% [95% CI, 2.9%-4.3%]) of COVID-19 infection (RR, 18.0 [95% CI, 13.9-23.4]) among all seats. The attack rate decreased with increasing distance, but increased with increasing co-travel time. The attack rate increased on average by 0.15% (P = .005) per hour of co-travel; for passengers in adjacent seats, this increase was 1.3% (P = .008), the highest among all seats considered. CONCLUSIONS: COVID-19 has a high transmission risk among train passengers, but this risk shows significant differences with co-travel time and seat location. During disease outbreaks, when traveling on public transportation in confined spaces such as trains, measures should be taken to reduce the risk of transmission, including increasing seat distance, reducing passenger density, and use of personal hygiene protection.

BI-FedGNN: Federated graph neural networks framework based on Bayesian inference.

The development of the Industrial Internet of Things (IIoT) in recent years has resulted in an increase in the amount of data generated by connected devices, creating new opportunities to enhance the quality of service for machine learning in the IIoT through data sharing. Graph neural networks (GNNs) are the most popular technique in machine learning at the moment because they can learn extremely precise node representations from graph-structured data. Due to privacy issues and legal restrictions of clients in industrial IoT, it is not permissible to directly concentrate vast real-world graph-structured datasets for training on GNNs. To resolve the aforementioned difficulties, this paper proposes a federal graph learning framework based on Bayesian inference (BI-FedGNN) that performs effectively in the presence of noisy graph structure information or missing strong relational edges. BI-FedGNN extends Bayesian Inference (BI) to the process of Federal Graph Learning (FGL), adding random samples with weights and biases to the client-side local model training process, improving the accuracy and generalization ability of FGL in the training process by rendering the graph structure data involved in GNNs training more similar to the graph structure data existing in the real world. Through extensive experimental tests, the results show that BI-FedGNN has about 0.5%-5.0% accuracy improvement over other baselines of federal graph learning. In order to expand the applicability of BI-FedGNN, experiments are carried out on heterogeneous graph datasets, and the results indicate that BI-FedGNN can also have at least 1.4% improvement in classification accuracy.

Esophageal cancer-related gene 4 inhibits gastric cancer growth and metastasis by upregulating Krüppel-like factor 2 expression.

Background: There are a large number of people suffering from gastric cancer (GC) worldwide, so the study of biomarkers for GC is urgently needed. This study aimed to investigate the role of esophageal cancer-related gene 4 (ECRG4) in the growth, metastasis, and prognosis of GC and the possible underlying mechanism. Methods: The expression of ECRG4 was detected in GC tissues by quantitative polymerase chain reaction (PCR), Western blot, and immunohistochemistry. The relationships between ECRG4 expression and clinicopathological parameters of patients with GC were statistically analyzed, and Kaplan-Meier prognosis and survival curves of the patients were plotted. ECRG4 was overexpressed in the human gastric adenocarcinoma cell line (AGS) and human GC cell line 27 (HGC27), and the in vivo effects of ECRG4 overexpression on the growth, invasion, and metastasis of GC were analyzed and verified in nude mice. To identify the downstream transcription factors potentially regulated by ECRG4, ribonucleic acid (RNA) sequencing and differential gene expression analysis were performed on ECRG4-overexpressing cells. Quantitative PCR, Western blot, and immunohistochemistry were used to detect the expression of the downstream transcription factors targeted by ECRG4 in GC. Results: The ECRG4 mRNA and protein expression levels were low in GC tissues and were associated with a poor prognosis. Least absolute shrinkage and selection operator (LASSO) Cox regression and Kaplan-Meier survival analyses showed that patients with low ECRG4 expression had worse prognosis and survival. Overexpression of ECRG4 inhibited the proliferation, metastasis, and invasion of GC cells. RNA sequencing analysis showed that overexpression of ECRG4 induced the upregulation of Krüppel-like factor 2. Conclusions: Our findings show that ECRG4 promotes GC progression via Krüppel-like factor 2 signaling and highlight ECRG4 as a potential GC biomarker and therapeutic target.

Comparison of Th1 and Th2 cytokines production in ovine lymph nodes during early pregnancy.

As a fetal allograft to the mother, early conceptus regulates the intrauterine immune and systemic immune responses during early pregnancy in sheep. However, expression of T helper 1 (Th1) and Th2 cytokines in maternal lymph nodes is unclear during early pregnancy in sheep. In this study, inguinal lymph nodes were obtained on day 16 of the estrous cycle and on days 13, 16 and 25 of pregnancy (n = 4 for each group) in ewes, and qRT-PCR, western blot and immunohistochemistry were used to compare the expression of Th1 and Th2 cytokines in the lymph nodes. Our results showed that there were the highest levels of Th1 cytokines (IFN-γ, TNF-ß and IL-2) and Th2 cytokines (IL-4, IL-5, IL-6 and IL-10) in the lymph nodes on day 13 or 16 of pregnancy. Furthermore, there were a downregulation of TNF-ß and IL-2 and an upregulation of IL-5 and IL-10 on day 25 of pregnancy compared with that in nonpregnancy, with no significant difference in the expression of IFN-γ, IL-4, and IL-6 between the ewes on day 25 of pregnancy and nonpregnancy. The immunohistochemistry results showed that the IL-2 and IL-10 proteins were limited to the subcapsular sinus and trabeculae in the cortex, lymph sinus. In conclusion, early pregnancy exerted its effects on the lymph node and induced a Th2-biased response, which was essential for a normal pregnancy in sheep.

Expression of interferon-stimulated gene 15-kDa protein, cyclooxygenase (COX) 1, COX-2, aldo-keto reductase family 1, member B1, and prostaglandin E synthase in the spleen during early pregnancy in sheep.

The spleen is a unique lymphoid organ that plays a key role in immune regulation. Interferon-tau induces upregulation of interferon-stimulated gene 15-kDa protein (ISG15) in the uterus during early pregnancy in sheep. Prostaglandins (PGs) have important effects in both the activation and the inhibition of immune response through an autocrine and paracrine manner. In this study, splenic samples were obtained at Day 16 of the estrous cycle, and Days 13, 16, and 25 of pregnancy from ewes, and the expression of ISG15 and PG synthases, including cyclooxygenase 1 (COX-1), COX-2, PGE synthase (PTGES), and PGF synthase (aldo-keto reductase family 1, member B1, AKR1B1), was detected through quantitative real-time PCR, western blot, and immunohistochemistry analysis. Our results showed that there was upregulation of COX-2 mRNA and protein at Day 25 of pregnancy, and ISG15 mRNA and conjugated proteins, and AKR1B1 mRNA and dimer at Days 16 and 25 of pregnancy. COX-2 and AKR1B1 proteins were limited to the capsule, trabeculae, and splenic cords. However, the expression of COX-1 and PTGES was not affected by early pregnancy. In conclusion, ISG15-conjugated proteins, COX-2 and AKR1B1 upregulated in maternal spleen during early pregnancy, which may be beneficial for the placentation in sheep.