A Stable Triazole-Based Covalent Gel for Long-Term Cycling Zn Anode in Zinc-Ion Batteries.

In this work, a functional covalent gel material is developed to resolve the severe dendritic growth and hydrogen evolution reaction toward Zn/electrolyte interface in aqueous zinc-ion batteries (ZIBs). A covalent gel layer with superior durability forms homogeneously on the surface of Zn foil. The covalent gel with triazole functional groups can uniformize the transport of Zn2+ due to the interactions between Zn2+ ions and the triazole groups in the covalent gel. As a consequence, the symmetrical battery with triazole covalent gel maintains stable Zn plating/stripping for over 3000 h at 1 mA cm-2 and 1 mAh cm-2 , and the full cell combined with a V2 O5 cathode operates steadily and continuously for at least 1800 cycles at 5 A g-1 with a capacity retention rate of 67.0%. This work provides a train of thought to develop stable covalent gels for the protection of zinc anode toward high-performance ZIBs.

Research on Area of Uncertainty of Underwater Moving Target Based on Stochastic Maneuvering Motion Model.

Considering the influence of measurement error on target state estimation, there is an uncertain dispersion region for target position estimate, that is, the area of uncertainty (AOU, area of uncertainty). In underwater target tracking, the state estimation is point estimation without AOU estimation and its accuracy is poor in the early stage because of large measurement errors. Fast tracking with higher accuracy and AOU estimation are of great significance to time-sensitive target tracking. To improve the state estimation accuracy in the early stage, and estimate the AOU, a method of AOU estimation of underwater moving target is presented based on a stochastic maneuvering motion (SMM, stochastic maneuvering motion) model. The stochastic maneuvering motion model is established based on the Langevin equation to reflect the movement characteristics of an underwater moving target. Then, the target state is estimated with a noise adaptive Kalman filter by constructing the measurement equation and state equation according to measurement error characteristic and stochastic maneuvering model. Based on the physical significance of the error covariance matrix from the Kalman filter, the parameters of AOU are deduced. Simulation results of underwater target tracking and AOU estimation are presented to demonstrate the relative performance of the proposed algorithm compared with the adaptive Kalman filter. It is clearly shown from the results that SMM tracking algorithm achieves higher accuracy of state estimation in the initial stage of tracking, and the predicted AOU is consistent with the actual distribution of underwater moving targets while yielding more concentrated distribution, which reveals that estimated AOU can be precisely represented by the confidence ellipses. The presented approach and obtained results may be useful in time-sensitive target threat analysis and weapon strike applications.

Combined application of chromatographic techniques for the separation of phenolic compounds from Stenoloma chusanum Ching.

High-speed countercurrent chromatography combined with preparative high-performance liquid chromatography was successfully used to separate seven phenolic compounds from Stenoloma chusanum Ching. A biphasic solvent system composed of hexane/ethyl acetate/methanol/water (1:2:1:2, v/v) was used for the first step high-speed countercurrent chromatography separation in elution-extrusion mode. A mobile phase composed of acetonitrile (18%) and pure water (82%) was used for further preparative high-performance liquid chromatography purification. In total, the combined separation yielded seven compounds, including 3,4-dihydroxy benzoic acid, 3,4-dihydroxy benzaldehyde, esculetin, caffeic acid, syringic acid, luteolin, and apigenin, at a purity of over 90%. Esculetin was separated from Stenoloma chusanum Ching for the first time. The results suggest that the proposed combination method is a useful strategy for separating compounds from complex samples.

Noninvasive Models to Assess Liver Inflammation and Fibrosis in Chronic HBV Infected Patients with Normal or Mildly Elevated Alanine Transaminase Levels: Which One Is Most Suitable?

The prevalence of substantial inflammation or fibrosis in treatment-naïve patients with chronic hepatitis B (CHB) and normal alanine transaminase (ALT) levels is high. A retrospective analysis was conducted on 559 consecutive patients with hepatitis B virus infection, who underwent liver biopsy, to investigate the value of noninvasive models based on routine serum markers for evaluating liver histology in CHB patients with normal or mildly elevated ALT levels and to provide treatment guidance. After comparing 55 models, we identified the top three models that exhibited excellent performance. The APGA model, based on the area under the receiver operating characteristic curve (AUROC), demonstrated a superior ability to evaluate significant (AUROC = 0.750) and advanced fibrosis (AUROC = 0.832) and demonstrated a good performance in assessing liver inflammation (AUROCs = 0.779 and 0.874 for stages G ≥ 2 and G ≥ 3, respectively). APGA also exhibited significant correlations with liver inflammation and fibrosis stage (correlation coefficients, 0.452 and 0.405, respectively (p < 0.001)). When the patients were stratified into groups based on HBeAg status and ALT level, APGA consistently outperformed the other 54 models. The other top two models, GAPI and XIE, also outperformed models based on other chronic hepatitis diseases. APGA may be the most suitable option for detecting liver fibrosis and inflammation in Chinese patients with CHB.

Expression profile of microRNAs in patients with decompensated cirrhosis by small RNA deep sequencing.

INTRODUCTION AND OBJECTIVE: Decompensated cirrhosis (DCC) is a more advanced stage of liver cirrhosis (LC). It is important to identify biomarkers to predict DCC progression. The aim of this study was to analyze microRNA (miRNA) profiles of whole blood involved in the DCC process to gain a better understanding of the molecular mechanisms underlying its development. MATERIALS AND METHODS: RNA-Seq analysis of blood samples from a discovery set, including four DCC patients and four LC individuals, was performed to identify differentially expressed miRNAs. The selected differentially expressed miRNAs were validated by using an independent validation set. RESULTS: In this study, a total of 1,036 miRNAs were identified in whole blood samples. Forty differentially expressed miRNAs were identified, including 24 upregulated and 16 downregulated miRNAs. The expression levels of three upregulated miRNAs (hsa-miR-20b-5p, hsa-miR-421, and hsa-miR-1307-3p) and two downregulated miRNAs (hsa-miR-139-5p and hsa-miR-150-5p) were validated by quantitative reverse transcriptase polymerase chain reaction. The receiver operator characteristic curve for the logistic regression model based on hsa-miR-20b-5p, hsa-miR-421, and hsa-miR-150-5p could distinguish DCC patients with excellent diagnostic accuracy (area under the curve: 0.981, p < 0.01). CONCLUSION: The miRNA expression profiles in patients with DCC and LC controls suggested that miR-20b-5p, miR-421, and miR-150-5p could be potential biomarkers and therapeutic targets for this condition.

Development and Validation of an ICU-Venous Thromboembolism Prediction Model Using Machine Learning Approaches: A Multicenter Study.

Purpose: The purpose of this study was to establish and validate machine learning-based models for predicting the risk of venous thromboembolism (VTE) in intensive care unit (ICU) patients. Patients and Methods: The clinical data of 1494 ICU patients who underwent Doppler ultrasonography or venography between December 2020 and March 2023 were extracted from three tertiary hospitals. The Boruta algorithm was used to screen the essential variables associated with VTE. Five machine learning algorithms were employed: Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), and Logistic Regression (LR). Hyperparameter optimization was conducted on the predictive model of the training dataset. The performance in the validation dataset was measured using indicators, including the area under curve (AUC) of the receiver operating characteristic (ROC) curve, specificity, and F1 score. Finally, the optimal model was interpreted using the SHapley Additive exPlanation (SHAP) package. Results: The incidence of VTE among the ICU patients in this study was 26.04%. We screened 19 crucial features for the risk prediction model development. Among the five models, the RF model performed best, with an AUC of 0.788 (95% CI: 0.738-0.838), an accuracy of 0.759 (95% CI: 0.709-0.809), a sensitivity of 0.633, and a Brier score of 0.166. Conclusion: A machine learning-based model for prediction of VTE in ICU patients were successfully developed, which could assist clinical medical staff in identifying high-risk populations for VTE in the early stages so that prevention measures can be implemented to reduce the burden on the ICU patients.

A case of chronic wounds caused by Sporothrix schenckii infection was rapidly detected by metagenomic next generation sequencing.

The dimorphic fungus Sporothrix schenckii is widely distributed in soil, vegetation, and decaying organic matter, and can cause sporotrichosis when the patient's skin trauma was exposed to contaminated material with Sporothrix spp. The cases of Sporothrix schenckii infection in chronic wounds are rarely reported. Here we reported a 53-year-old male construction worker who was admitted to our hospital on July 9, 2022, without underlying disease presented with a painless subcutaneous hard nodule on his right calf, which later ulcerated and oozed, with an enlarged wound and no fever during the course of the disease. His procalcitonin, C-reactive protein, erythrocyte sedimentation rate increased, and necrotic histopathology suggested chronic granulomatous inflammation. Then his necrotic tissue and pus were sent for metagenomic next generation sequencing(mNGS), the result reported Sporothrix schenckii after 43 hours, which was consistent with the result of culture after 18 days. mNGS might be more useful and valuable in diseases such as sporotrichosis where it is difficult to see the yeast cells in the tissues.

Dynamics of a stochastic hepatitis B virus transmission model with media coverage and a case study of China.

Hepatitis B virus (HBV) infection is a global public health problem and there are 257 million people living with chronic HBV infection throughout the world. In this paper, we investigate the dynamics of a stochastic HBV transmission model with media coverage and saturated incidence rate. Firstly, we prove the existence and uniqueness of positive solution for the stochastic model. Then the condition on the extinction of HBV infection is obtained, which implies that media coverage helps to control the disease spread and the noise intensities on the acute and chronic HBV infection play a key role in disease eradication. Furthermore, we verify that the system has a unique stationary distribution under certain conditions, and the disease will prevail from the biological perspective. Numerical simulations are conducted to illustrate our theoretical results intuitively. As a case study, we fit our model to the available hepatitis B data of mainland China from 2005 to 2021.

Spirometra mansoni sparganosis identified by metagenomic next-generation sequencing: a case report.

A 30-year-old male patient had a cyst on the left hip and progressive enlargement for more than 2 months. Combined blood tests, magnetic resonance imaging, and pathology findings, cysticercosis infection was suspected. However, the treatment for cysticercosis was ineffective. We conducted a metagenomic next-generation sequencing (mNGS) analysis on the formalin-fixed, paraffin-embedded specimen of the patient's surgically excised tissue, and the results suggested Spirometra mansoni, mNGS was further confirmed by polymerase chain reaction and phylogenetic analysis of cytochrome c oxidase subunit 1 (cox1) gene. Based on these results, we found that mNGS provided a better method of diagnosing parasitic infections.

Effect of piston texture at inclination and eccentricity work conditions on damping characteristics of a hydraulic shock absorber.

In order to accurately predict the damping characteristics of a hydraulic shock absorber under piston inclination and eccentricity conditions, especially, considering effects of piston surface construction. In present work, taking account of piston slight inclination and eccentricity, a more detailed mathematical model was developed to estimate effects of piston texture on damping characteristics. Based on the mathematical models of reservoir and compression stroke coupled with Reynolds equation, a new damping force model was developed, which analyzed effects of piston structure on damping characteristics. The mathematical models of piston texture, piston slight inclination, piston eccentricity and combinations of three cases are developed to analyzed in detailed effects of piston texture at different work conditions on damping characteristics. The results shown that the friction force of piston increases parabolically with increasing depth ratio, and that of piston increases linearly with increasing area ratio. Piston textures have little effects on damping characteristics at specific structural parameters conditions when piston normal operation, however, textures of slight inclined and eccentric piston have great effects. As a result, piston textures might cause high damping force, destroyed comfort and safety. Therefore, it is necessary that effects of piston surface construction were precisely predicted on damping characteristics under different work conditions. The results might provide a new insight for the design of hydraulic shock absorber and investigation of vehicle system dynamics.

Nitrogen-Rich Porous Organic Polymers with Supported Ag Nanoparticles for Efficient CO2 Conversion.

As CO2 emissions increase and the global climate deteriorates, converting CO2 into valuable chemicals has become a topic of wide concern. The development of multifunctional catalysts for efficient CO2 conversion remains a major challenge. Herein, two porous organic polymers (NPOPs) functionalized with covalent triazine and triazole N-heterocycles are synthesized through the copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) reaction. The NPOPs have an abundant microporous content and high specific surface area, which confer them excellent CO2 affinities with a CO2 adsorption capacity of 84.0 mg g-1 and 63.7 mg g-1, respectively, at 273 K and 0.1 MPa. After wet impregnation and in situ reductions, Ag nanoparticles were supported in the NPOPs to obtain Ag@NPOPs with high dispersion and small particle size. The Ag@NPOPs were applied to high-value conversion reactions of CO2 with propargylic amines and terminal alkynes under mild reaction conditions. The carboxylative cyclization transformation of propargylic amine into 2-oxazolidinone and the carboxylation transformation of terminal alkynes into phenylpropiolic acid had the highest TOF values of 1125.1 and 90.9 h-1, respectively. The Ag@NPOP-1 was recycled and used five times without any significant decrease in catalytic activity, showing excellent catalytic stability and durability.

Integrated Analysis of mRNA and lncRNA Expression Profiles Reveals Regulatory Networks Associated with Decompensated Cirrhosis.

The stage of decompensation is termed end-stage liver cirrhosis. Patients with decompensated cirrhosis (DCC) often have a variety of comorbidities that contribute to exacerbation of the disease and its high mortality rate. By comparing differential gene expression, transcriptomic analysis is useful for exploring relevant functional changes during disease progression. The purpose of this study was to identify differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in patients with decompensated cirrhosis and to further explore the functions as well as interactions between lncRNAs and mRNAs. Four patients with decompensated cirrhosis and four controls with liver cirrhosis were recruited in this study. RNA was isolated from peripheral blood mononuclear cells, and RNA-seq was used for transcriptome analysis. The functions of differentially expressed mRNAs were revealed by Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a regulatory network was also constructed. A total of 1046 differentially expressed mRNAs and 1175 lncRNAs were identified between the decompensated cirrhosis patients and cirrhosis controls. Functional enrichment analyses indicated enrichment of genes involved in pathways related to inflammation and cellular metabolic activities. In addition, the findings suggested that the phagosome/endosome/autophagy-lysosome pathway might play an important role in cirrhotic decompensation. In summary, this study identified differentially expressed mRNAs (DE-mRNAs) and DE-lncRNAs and predicted the biological processes and signaling pathways involved in cirrhotic decompensation, which might provide new ideas for further revealing the molecular mechanism of DCC pathogenesis.

Comprehensive analysis of the MIR4435-2HG/miR-1-3p/MMP9/miR-29-3p/DUXAP8 ceRNA network axis in hepatocellular carcinoma.

A growing number of studies have shown that competitive endogenous RNA (ceRNA) regulatory networks might play important roles during the process of hepatocellular carcinoma (HCC). This study assessed the role of the ceRNA network in immune cell infiltration in HCC. Immune-related gene sets were downloaded from Molecular Signatures Database, and differentially expressed genes were screened based on TCGA HCC transcriptome data. The corresponding miRNAs with low expression and good prognostic implications, and the corresponding lncRNAs with high expression and poor prognostic were identified to construct ceRNA networks. The networks were utilized for clinical correlation analysis and risk model construction, and the CIBERSORT algorithm was applied to assess immune cell infiltration. In this study, the mRNA-miRNA-lncRNA model was used to construct a ceRNA network in HCC using immune-related differentially expressed mRNAs. Assessment of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis in HCC showed that a high risk/poor prognosis was significantly correlated with tumor stage and invasion depth. MMP9 was positively correlated with resting M0 macrophages and NK cells and negatively correlated with activated mast cells, resting mast cells, monocytes and activated NK cells. DUXAP8 was positively correlated with M2 macrophages and negatively correlated with MIR4435-2HG, which was positively correlated with M2 macrophages and negatively correlated with activated mast cells, CD8 T cells and follicular helper T cells. The correlation of the MIR4435-2HG/hsa-miR-1-3p/MMP9/hsa-miR-29-3p/DUXAP8 ceRNA network axis with immune cell infiltration provides further information on the mechanism of HCC development. The result might improve our understanding the interactions between immune related genes and non-coding RNAs in the occurrence and development of HCC, and the relevant RNAs might be used as diagnostic and prognostic biomarkers and molecular targets in HCC patients.

MicroRNA-590-3p relieves hypoxia/reoxygenation induced cardiomyocytes apoptosis and autophagy by targeting HIF-1α.

Autophagy and apoptosis are key factors in myocardial ischemia/reperfusion (I/R) injury. MicroRNAs (miRNAs or miRs) participate in occurrence and development of myocardial I/R injury by regulating autophagy and apoptosis. The purpose of the present study was to investigate the role of miR-590-3p in the regulation of autophagy and apoptosis in hypoxia/reoxygenation (H/R)-treated cardiomyocytes. Following 6 h hypoxia and 6 h reoxygenation in primary rat cardiomyocytes, miR-590-3p was downregulated. Transfection of miR-590-3p mimic inhibited the increased autophagy and apoptosis following H/R treatment. Subsequent experiments demonstrated that miR-590-3p regulated induction of autophagy and apoptosis by targeting hypoxia inducible factor (HIF)-1α. Forced expression of HIF-1α rescued the protective effect of miR-590-3p on H/R-induced cardiomyocytes. In summary, the present study showed that miR-590-3p exhibited a protective effect on H/R-induced cardiomyocyte injury and may be a novel target for the treatment of myocardial ischemia disease.

The aberrant expressions of MACC1, ZEB1, and KLF4 in hepatocellular carcinoma and their clinical significance.

BACKGROUND AND OBJECTIVE: Metastasis-associated in colon cancer-1 (MACC1) is involved in the progression and metastasis of various cancers. Zinc finger E-box-binding homeobox 1 (ZEB1) is a key transcriptional factor of the epithelial-mesenchymal transition (EMT) that is involved in the migration and invasion of cancer cells. Kruppel-like factor 4 (KLF4) is a tumor suppressor that can inhibit tumor cell proliferation, migration, and metastasis. The purpose of this study was to investigate the expressions and clinical significance of MACC1, ZEB1, and KLF4 in hepatocellular carcinoma (HCC). METHODS: We analyzed the expressions of MACC1, ZEB1, and KLF4 in 153 HCC specimens and their corresponding control specimens. The patients' clinicopathological and follow-up data were also collected. RESULTS: The rates of positive expression of MACC1 and ZEB1 were significantly higher in the HCC specimens than in the control specimens, and their expressions were positively associated with the number of tumors, grades of differentiation, lymph node metastasis (LNM), and tumor-node-metastasis (TNM) stages. Inversely, the rate of positive expression of KLF4 was significantly lower in the HCC specimens than it was in the control specimens, and its expression was negatively correlated with the number of tumors, grades of differentiation, LNM, and TNM stages. The patients who expressed MACC1 or ZEB1 had a reduced overall survival (OS) when compared with patients not expressing these proteins. However, the patients who expressed KLF4 had an increased OS when compared with patients who did not show any KLF4 expression. A multivariate analysis indicated that the expressions of MACC1, ZEB1, and KLF4 and tumor size, LNM, as well as the TNM stages were independent, prognostic factors for HCC patients. CONCLUSIONS: Therefore, positive expressions of MACC1, ZEB1, and KLF4 should be correlated with the duration of OS in patients with HCC and considered promising prognostic biomarkers, as well as potential therapeutic targets for HCC.