From X-efficiency to Bank Profitability: An Analysis for Chinese Commercial Banks

Using data from 2010-2015 of 151 banks, this study first exams the X-efficiency of Chinese commercial banks under the SFA estimator and finds out their efficiency is on an upward trend which is in line with other literature. Their average X-efficiency is relatively high (0.8761) and there are scale economies and minimum efficiency scale in Chinese banks. Then this study uses bank-specific factors, industry-specific factors and macroeconomic factors to analysis the determinants of bank profitability in GMM model. The results show that both size and Z-score positively affect bank profitability while capital level and liquidity negatively associated with bank performance. Furthermore, Chinese commercial banks are greatly influenced by external factors with market concentration, banking sector development and stock market development all bring positive effects on profitability. However, GDP growth adversely affect bank performance. The results denote increasing credit risk, high regulatory costs, inadequate competition, and high volatility among Chinese banking sector

Bridging the Gap between Laboratory and Field Experiments in American Eel Detection Using Transfer Learning and Convolutional Neural Network

An automatic system that utilizes data analytics and machine learning to identify adult American eel in data obtained by imaging sonars is created in this study. Wavelet transform has been applied to de-noise the ARIS sonar data and a convolutional neural network model has been built to classify eels and non-eel objects. Because of the unbalanced amounts of data in laboratory and field experiments, a transfer learning strategy is implemented to fine-tune the convolutional neural network model so that it performs well for both the laboratory and field data. The proposed system can provide important information to develop mitigation strategies for safe passage of out-migrating eels at hydroelectric facilities

Electrostatic spray ionization from 384-well microtiter plates for mass spectrometry analysis based enzyme assay and drug metabolism screening

We have realized the direct ionization of samples from wells of microtiter plates under atmospheric conditions for mass spectrometry analysis without any liquid delivery system or any additional interface. The microtiter plate is a commercially available 384-well plate without any modification, working as a container and an emitter for electrostatic spray ionization of analytes. The approach provides high throughput for the large batches of reactions and both the qualitative and quantitative analysis of a single compound or mixture. The limits of detection in small drug molecules, peptides and proteins are similar in comparison with standard direct infusion electrospray ionization. The analysis time per well is only seconds. These analytical merits benefit many microtiter plate-based studies such as combinatorial chemistry and high throughput screening in enzyme assay or drug metabolism. Herein, we illustrate the application in enzyme assay using tyrosine oxidation catalyzed by tyrosinase in the presence or absence of inhibitors. The potential application in drug development is also demonstrated with cytochrome P450-catalyzed metabolic reactions of two drugs in microtiter plates followed with direct ESTASI-MS/MS based characterization of the metabolism products

Comprehensive bulk and single-cell transcriptome profiling give useful insights into the characteristics of osteoarthritis associated synovial macrophages

BackgroundOsteoarthritis (OA) is a common chronic joint disease, but the association between molecular and cellular events and the pathogenic process of OA remains unclear.ObjectiveThe study aimed to identify key molecular and cellular events in the processes of immune infiltration of the synovium in OA and to provide potential diagnostic and therapeutic targets.MethodsTo identify the common differential expression genes and function analysis in OA, we compared the expression between normal and OA samples and analyzed the protein–protein interaction (PPI). Additionally, immune infiltration analysis was used to explore the differences in common immune cell types, and Gene Set Variation Analysis (GSVA) analysis was applied to analyze the status of pathways between OA and normal groups. Furthermore, the optimal diagnostic biomarkers for OA were identified by least absolute shrinkage and selection operator (LASSO) models. Finally, the key role of biomarkers in OA synovitis microenvironment was discussed through single cell and Scissor analysis.ResultsA total of 172 DEGs (differentially expressed genes) associated with osteoarticular synovitis were identified, and these genes mainly enriched eight functional categories. In addition, immune infiltration analysis found that four immune cell types, including Macrophage, B cell memory, B cell, and Mast cell were significantly correlated with OA, and LASSO analysis showed that Macrophage were the best diagnostic biomarkers of immune infiltration in OA. Furthermore, using scRNA-seq dataset, we also analyzed the cell communication patterns of Macrophage in the OA synovial inflammatory microenvironment and found that CCL, MIF, and TNF signaling pathways were the mainly cellular communication pathways. Finally, Scissor analysis identified a population of M2-like Macrophages with high expression of CD163 and LYVE1, which has strong anti-inflammatory ability and showed that the TNF gene may play an important role in the synovial microenvironment of OA.ConclusionOverall, Macrophage is the best diagnostic marker of immune infiltration in osteoarticular synovitis, and it can communicate with other cells mainly through CCL, TNF, and MIF signaling pathways in microenvironment. In addition, TNF gene may play an important role in the development of synovitis

Associations between maternal complications during pregnancy and childhood asthma: a retrospective cohort study

© 2023 The Authors. Published by the European Respiratory Society. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://openres.ersjournals.com/content/9/2/00548-2022Background Studies on the associations between maternal complications during pregnancy and childhood asthma are exclusively conducted in Western countries. The findings are mixed and may not be translated to other populations. We aimed to investigate the associations among the Chinese population and to determine whether the associations were mediated through pre-term birth, caesarean delivery, low birthweight and not breastfeeding in the first 6 months. Methods We conducted a retrospective cohort study of 166 772 children in Guangzhou, China. Information on maternal gestational hypertension, gestational diabetes and gestational anaemia during pregnancy was extracted from medical records. Ever-diagnosis of asthma in children aged 6–12 years was obtained by questionnaire. Logistic regression models and mediation analyses were used to estimate the adjusted odds ratios (aORs) and 95% confidence intervals for childhood asthma. Results Gestational hypertension, gestational diabetes and gestational anaemia during pregnancy were associated with an increased risk of ever-diagnosed childhood asthma: aOR 1.48 (95% CI 1.37–1.60), 1.71 (95% CI 1.65–1.78) and 1.34 (95% CI 1.26–1.45), respectively. A stronger association was observed for two or three gestational complications (aOR 2.02 (95% CI 1.93–2.16)) than one gestational complication (aOR 1.64 (95% CI 1.52–1.77)). The aOR for the three gestational complications was 1.35 (95% CI 1.26–1.45), 1.63 (95% CI 1.58–1.70) and 1.32 (95% CI 1.24–1.43), respectively, after controlling for the mediators, including pre-term birth, caesarean delivery, low birthweight and not breastfeeding in the first 6 months. Conclusions Gestational hypertension, gestational diabetes and gestational anaemia were associated with childhood asthma, and the associations were partially explained by the mediation effects.This study was supported by National Natural Science Foundation of China (82073571 and 81773457 to J. Tang).Published versio

Secure Payment Authentication That Provides Strong Customer Authentication

Multi-factor verification steps currently used for authenticating online purchases, e.g., one-time codes sent to a phone, can prove to be a hurdle for some customers. This disclosure describes a strong customer authentication technique, referred to as secure payment authentication (SPA), that enables users to authenticate online transactions using device-bound tokens. Authentication is driven by payment service providers, and a simple device unlock can confirm a transaction. Strong customer authentication is made possible with just a single (or even zero) click. Cross-device authentication can be enabled, such that a customer can authenticate themselves on a payment app on a mobile device while performing transactions on a second device such as a laptop, etc

SRSF1 modulates PTPMT1 alternative splicing to regulate lung cancer cell radioresistance

Background Radioresistance is the major cause of cancer treatment failure. Additionally, splicing dysregulation plays critical roles in tumorigenesis. However, the involvement of alternative splicing in resistance of cancer cells to radiotherapy remains elusive. We sought to investigate the key role of the splicing factor SRSF1 in the radioresistance in lung cancer. Methods Lung cancer cell lines, xenograft mice models, and RNA-seq were employed to study the detailed mechanisms of SRSF1 in lung cancer radioresistance. Clinical tumor tissues and TCGA dataset were utilized to determine the expression levels of distinct SRSF1-regulated splicing isoforms. KM-plotter was applied to analyze the survival of cancer patients with various levels of SRSF1-regulated splicing isoforms. Findings Splicing factors were screened to identify their roles in radioresistance, and SRSF1 was found to be involved in radioresistance in cancer cells. The level of SRSF1 is elevated in irradiation treated lung cancer cells, whereas knockdown of SRSF1 sensitizes cancer cells to irradiation. Mechanistically, SRSF1 modulates various cancer-related splicing events, particularly the splicing of PTPMT1, a PTEN-like mitochondrial phosphatase. Reduced SRSF1 favors the production of short isoforms of PTPMT1 upon irradiation, which in turn promotes phosphorylation of AMPK, thereby inducing DNA double-strand break to sensitize cancer cells to irradiation. Additionally, the level of the short isoform of PTPMT1 is decreased in cancer samples, which is correlated to cancer patients' survival. Conclusions Our study provides mechanistic analyses of aberrant splicing in radioresistance in lung cancer cells, and establishes SRSF1 as a potential therapeutic target for sensitization of patients to radiotherapy