Vetting undesirable behaviors in android apps with permission use analysis

Android platform adopts permissions to protect sensitive resources from untrusted apps. However, after permissions are granted by users at install time, apps could use these permissions (sensitive resources) with no further restrictions. Thus, recent years have witnessed the explosion of undesirable behaviors in Android apps. An important part in the defense is the accurate analysis of Android apps. However, traditional syscall-based analysis techniques are not well-suited for Android, because they could not capture critical interactions between the application and the Android system. This paper presents VetDroid, a dynamic analysis platform for reconstructing sensitive behaviors in Android apps from a novel permission use perspective. VetDroid features a systematic frame-work to effectively construct permission use behaviors, i.e., how applications use permissions to access (sensitive) system resources, and how these acquired permission-sensitive resources are further utilized by the application. With permission use behaviors, security analysts can easily examine the internal sensitive behaviors of an app. Using real-world Android malware, we show that VetDroid can clearly reconstruct fine-grained malicious behaviors to ease malware analysis. We further apply VetDroid to 1,249 top free apps in Google Play. VetDroid can assist in finding more information leaks than TaintDroid [24], a state-of-the-art technique. In addition, we show howwe can use VetDroid to analyze fine-grained causes of information leaks that TaintDroid cannot reveal. Finally, we show that VetDroid can help identify subtle vulnerabilities in some (top free) applications otherwise hard to detect

Numerical analysis and experiment on pressure of polished Z-tube with abrasive flow

Aiming at the problem that the complex parts are difficult to process precisely, a flexible processing method, abrasive flow technology, is proposed. Based on the FLUENT software, a realizable k-ε model was adopted and a Z-tube was used as the research object for numerical analysis. Parameters such as turbulence intensity, turbulent kinetic energy, and flow field pressure under different inlet pressures were simulated and discussed. The simulation results show that with the increase of inlet pressure, the turbulence intensity, turbulent kinetic energy and fluid pressure also increase, and the turbulent effect of the fluid is more obvious, which indicates that the processing effect of the abrasive flow will be better, and the final experiment will be performed. The experimental results are consistent with the simulation results, and the accuracy of the numerical simulation is proved. The abrasive grain flow processing technology is effectively verified

A Review of the Extraction and Functional Properties of Soybean Protein components

Glycinin and β-conglycinin are the major protein components of soybean, which are different in their structure. The preparation process can cause varying degrees of changes in the structures of glycinin and β-conglycinin. In this paper, a brief overview of the structures of various soybean protein components is given, with a focus on the preparation process of soybean proteins. Moreover, the mechanism for the effect of the structure of soybean protein components on their functions is summarized. This review is expected to provide a reference for the quality control of soybean and soybean protein products

Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data

Background: The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs). Methods: scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays. Results: The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines. Conclusions: We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice

Inhibition the ubiquitination of ENaC and Na,K-ATPase with erythropoietin promotes alveolar fluid clearance in sepsis-induced acute respiratory distress syndrome

Sepsis-induced acute respiratory distress syndrome (ARDS) causes significant fatalities worldwide and lacks pharmacological intervention. Alveolar fluid clearance (AFC) plays a pivotal role in the remission of ARDS and is markedly impaired in the pathogenesis of ARDS. Here, we demonstrated that erythropoietin could effectively ameliorate lung injury manifestations and lethality, restore lung function and promote AFC in a rat model of lipopolysaccharide (LPS)-induced ARDS. Moreover, it was proven that EPO-induced restoration of AFC occurs through triggering the total protein expression of ENaC and Na,K-ATPase channels, enhancing their protein abundance in the membrane, and suppressing their ubiquitination for degeneration. Mechanistically, the data indicated the possible involvement of EPOR/JAK2/STAT3/SGK1/Nedd4–2 signaling in this process, and the pharmacological inhibition of the pathway markedly eliminated the stimulating effects of EPO on ENaC and Na,K-ATPase, and subsequently reversed the augmentation of AFC by EPO. Consistently, in vitro studies of alveolar epithelial cells paralleled with that EPO upregulated the expression of ENaC and Na,K-ATPase, and patch-clamp studies further demonstrated that EPO substantially strengthened sodium ion currents. Collectively, EPO could effectively promote AFC by improving ENaC and Na,K-ATPase protein expression and abundance in the membrane, dependent on inhibition of ENaC and Na,K-ATPase ubiquitination, and resulting in diminishing LPS-associated lung injuries

Integrated multi-omics identified the novel intratumor microbiome-derived subtypes and signature to predict the outcome, tumor microenvironment heterogeneity, and immunotherapy response for pancreatic cancer patients

Background: The extremely malignant tumour known as pancreatic cancer (PC) lacks efficient prognostic markers and treatment strategies. The microbiome is crucial to how cancer develops and responds to treatment. Our study was conducted in order to better understand how PC patients’ microbiomes influence their outcome, tumour microenvironment, and responsiveness to immunotherapy.Methods: We integrated transcriptome and microbiome data of PC and used univariable Cox regression and Kaplan–Meier method for screening the prognostic microbes. Then intratumor microbiome-derived subtypes were identified using consensus clustering. We utilized LASSO and Cox regression to build the microbe-related model for predicting the prognosis of PC, and utilized eight algorithms to assess the immune microenvironment feature. The OncoPredict package was utilized to predict drug treatment response. We utilized qRT-PCR to verify gene expression and single-cell analysis to reveal the composition of PC tumour microenvironment.Results: We obtained a total of 26 prognostic genera in PC. And PC samples were divided into two microbiome-related subtypes: Mcluster A and B. Compared with Mcluster A, patients in Mcluster B had a worse prognosis and higher TNM stage and pathological grade. Immune analysis revealed that neutrophils, regulatory T cell, CD8+ T cell, macrophages M1 and M2, cancer associated fibroblasts, myeloid dendritic cell, and activated mast cell had remarkably higher infiltrated levels within the tumour microenvironment of Mcluster B. Patients in Mcluster A were more likely to benefit from CTLA-4 blockers and were highly sensitive to 5-fluorouracil, cisplatin, gemcitabine, irinotecan, oxaliplatin, and epirubicin. Moreover, we built a microbe-derived model to assess the outcome. The ROC curves showed that the microbe-related model has good predictive performance. The expression of LAMA3 and LIPH was markedly increased within pancreatic tumour tissues and was linked to advanced stage and poor prognosis. Single-cell analysis indicated that besides cancer cells, the tumour microenvironment of PC was also rich in monocytes/macrophages, endothelial cells, and fibroblasts. LIPH and LAMA3 exhibited relatively higher expression in cancer cells and neutrophils.Conclusion: The intratumor microbiome-derived subtypes and signature in PC were first established, and our study provided novel perspectives on PC prognostic indicators and treatment options