Knockdown of DEAD-box 51 inhibits tumor growth of esophageal squamous cell carcinoma via the PI3K/AKT pathway

BACKGROUND Esophageal squamous cell carcinoma(ESCC)is one of the most prevalent malignancies that seriously threaten people’s health worldwide.DEAD-box helicase 51(DDX51)is a member of the DEAD-box(DDX)RNA helicase family,and drives or inhibits tumor progression in multiple cancer types.AIM To determine whether DDX51 affects the biological behavior of ESCC.METHODS The expression of DDX51 in ESCC tumor tissues and adjacent normal tissues was detected by Immunohistochemistry(IHC)analyses and quantitative PCR(qPCR).We knocked down DDX51 in ESCC cell lines by using a small interfering RNA(siRNA)transfection.The proliferation,apoptosis,and mobility of DDX51 siRNAtransfected cells were detected.The effect of DDX51 on the phosphoinositide 3-kinase(PI3K)/AKT pathway was investigated by western blot analysis.A mouse xenograft model was established to investigate the effects of DDX51 knockdown on ESCC tumor growth.RESULTS DDX51 exhibited high expression in ESCC tissues compared with normal tissues and represented a poor prognosis in patients with ESCC.Knockdown of DDX51 induced inhibition of ESCC cell proliferation and promoted apoptosis.Moreover,DDX51 siRNA-expressing cells also exhibited lower migration and invasion rates.Investigations into the underlying mechanisms suggested that DDX51 knock down induced inactivation of the PI3K/AKT pathway,including decreased phosphorylation levels of phosphate and tensin homolog,PI3K,AKT,and mammalian target of rapamycin.Rescue experiments demonstrated that the AKT activator insulin-like growth factor 1 could reverse the inhibitory effects of DDX51 on ESCC malignant development.Finally,we injected DDX51 siRNA-transfected TE-1 cells into an animal model,which resulted in slower tumor growth.CONCLUSION Our study suggests for the first time that DDX51 promotes cancer cell proliferation by regulating the PI3K/AKT pathway;thus,DDX51 might be a therapeutic target for ESCC.     

Mechanism of action of Orthosiphon stamineus against non-alcoholic fatty liver disease: Insights from systems pharmacology and molecular docking approaches

Non-alcoholic fatty liver disease (NAFLD) is one of the most common complications of a metabolic syndrome caused by excessive accumulation of fat in the liver. Orthosiphon stamineus also known as Orthosiphon aristatus is a medicinal plant with possible potential beneficial effects on various metabolic disorders. This study aims to investigate the in vitro inhibitory effects of O. stamineus on hepatic fat accumulation and to further use the computational systems pharmacology approach to identify the pharmacokinetic properties of the bioactive compounds of O. stamineus and to predict their molecular mechanisms against NAFLD. Methods: The effects of an ethanolic extract of O. stamineus leaves on cytotoxicity, fat accumulation and antioxidant activity were assessed using HepG2 cells. The bioactive compounds of O. stamineus were identified using LC/MS and two bioinformatics databases, namely the Traditional Chinese Medicine Integrated Database (TCMID) and the Bioinformatics Analysis Tool for the Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM). Pathway enrichment analysis was performed on the predicted targets of the bioactive compounds to provide a systematic overview of the molecular mechanism of action, while molecular docking was used to validate the predicted targets. Results: A total of 27 bioactive compounds corresponding to 50 potential NAFLD-related targets were identified. O. stamineus exerts its anti-NAFLD effects by modulating a variety of cellular processes, including oxidative stress, mitochondrial β-oxidation, inflammatory signalling pathways, insulin signalling, and fatty acid homeostasis pathways. O. stamineus is significantly targeting many oxidative stress regulators, including JNK, mammalian target of rapamycin (mTOR), NFKB1, PPAR, and AKT1. Molecular docking analysis confirmed the expected high affinity for the potential targets, while the in vitro assay indicates the ability of O. stamineus to inhibit hepatic fat accumulation. Conclusion: Using the computational systems pharmacology approach, the potentially beneficial effect of O. stamineus in NAFLD was indicated through the combination of multiple compounds, multiple targets, and multicellular components.     

基于预算的公立医院成本费用目标管理研究

基于预算的公立医院成本费用目标管理,兼具年度预算的资金管控与月度目标的执行进度管控,其信息系统设计的关键点是数据信息抓取、传递、回馈、监督,形成事前预算、事中分析执行、事后反馈的成本费用管控模式,实现提质、增效、降耗的管控目的,使公立医院的发展由“规模扩张”型的成长阶段平稳过渡到精细化、质量效益型的成本管理阶段。     

Automatic segmentation of thoracic CT images using three deep learning models

PurposeDeep learning (DL) techniques are widely used in medical imaging and in particular for segmentation. Indeed, manual segmentation of organs at risk (OARs) is time-consuming and suffers from inter- and intra-observer segmentation variability. Image segmentation using DL has given very promising results. In this work, we present and compare the results of segmentation of OARs and a clinical target volume (CTV) in thoracic CT images using three DL models.Materials and methodsWe used CT images of 52 patients with breast cancer from a public dataset. Automatic segmentation of the lungs, the heart and a CTV was performed using three models based on the U-Net architecture. Three metrics were used to quantify and compare the segmentation results obtained with these models: the Dice similarity coefficient (DSC), the Jaccard coefficient (J) and the Hausdorff distance (HD).ResultsThe obtained values of DSC, J and HD were presented for each segmented organ and for the three models. Examples of automatic segmentation were presented and compared to the corresponding ground truth delineations. Our values were also compared to recent results obtained by other authors.ConclusionThe performance of three DL models was evaluated for the delineation of the lungs, the heart and a CTV. This study showed clearly that these 2D models based on the U-Net architecture can be used to delineate organs in CT images with a good performance compared to other models. Generally, the three models present similar performances. Using a dataset with more CT images, the three models should give better results.     

ArgD of Mycobacterium tuberculosis is a functional N-acetylornithine aminotransferase with moonlighting function as an effective immune modulator

Mycobacterium tuberculosis (M. tuberculosis) encodes an essential enzyme acetyl ornithine aminotransferase ArgD (Rv1655) of arginine biosynthetic pathway which plays crucial role in M. tuberculosis growth and survival. ArgD catalyzes the reversible conversion of N-acetylornithine and 2 oxoglutarate into glutamate-5-semialdehyde and L-glutamate. It also possesses succinyl diaminopimelate aminotransferase activity and can thus carry out the corresponding step in lysine biosynthesis. These essential roles played by ArgD in amino acid biosynthetic pathways highlight it as an important metabolic chokepoint thus an important drug target. We showed that M. tuberculosis ArgD rescues the growth of ΔargD E. coli grown in minimal media validating its functional importance. Phylogenetic analysis of M. tuberculosis ArgD showed homology with proteins in gram positive bacteria, pathogenic and non-pathogenic mycobacteria suggesting the essentiality of this protein. ArgD is a secretory protein that could be utilized by M. tuberculosis to modulate host innate immunity as its moonlighting function. In-silico analysis predicted it to be a highly antigenic protein. The recombinant ArgD protein when exposed to macrophage cells induced enhanced production of pro-inflammatory cytokines TNF, IL6 and IL12 in a dose dependent manner. ArgD also induced the increased production of innate immune effector molecule NOS2 and NO in macrophages. We also demonstrated ArgD mediated activation of the canonical NFkB pathway. Notably, we also show that ArgD is a specific TLR4 agonist involved in the activation of pro-inflammatory signaling for sustained production of effector cytokines. Intriguingly, ArgD protein treatment activated macrophages to acquire the M1 phenotype through the increased surface expression of MHCII and costimulatory molecules CD80 and CD86. ArgD induced robust B-cell response in immunized mice, validating its antigenicity potential as predicted by the in-silico analysis. These properties of M. tuberculosis ArgD signify its functional plasticity that could be exploited as a possible drug target to combat tuberculosis.     

Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR

Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance. oncoEnrichR differs from general gene set analysis frameworks through the integration of an extensive set of prior knowledge specifically relevant for cancer, including ranked gene-tumor type associations, literature-supported proto-oncogene and tumor suppressor gene annotations, target druggability data, regulatory interactions, synthetic lethality predictions, as well as prognostic associations, gene aberrations and co-expression patterns across tumor types. The software produces a structured and user-friendly analysis report as its main output, where versions of all underlying data resources are explicitly logged, the latter being a critical component for reproducible science. We demonstrate the usefulness of oncoEnrichR through interrogation of two candidate lists from proteomic and CRISPR screens. oncoEnrichR is freely available as a web-based service hosted by the Galaxy platform ( https://oncotools.elixir.no ), and can also be accessed as a stand-alone R package ( https://github.com/sigven/oncoEnrichR ).     

Renal Neoplasia in Tuberous Sclerosis: A Study of 41 Patients

ObjectiveTo study the clinical features and identify unique renal neoplasia subtypes and their prognostic implications in individuals with tuberous sclerosis complex (TSC).Patients and MethodsThe Mayo Clinic nephrectomy registry included 37 patients with TSC diagnosed between 1970 and 2018. Four additional patients were identified from the pathology consultation and autopsy files. All available renal tumors were further characterized using immunohistochemistry and fluorescence in situ hybridization. Clinicopathologic features and follow-up were obtained from the medical record. The American Association for Cancer Research Project GENIE registry was accessed using cBioPortal for molecular profiling of angiomyolipoma (AML).ResultsA total of 276 renal tumors from 41 patients were analyzed. Renal tumors were classified into 9 distinct morphological subtypes, with AML predominating (238 [86%]). Interestingly, all these tumors acted in a benign fashion except one renal cell carcinoma with clear cells and fibromyomatous stroma and one epithelioid AML that metastasized. Molecular profiling studies revealed that epithelioid AMLs were enriched for alterations of TP53, RB1, and ATRX. Eight patients died of direct complications of TSC, including 3 of end-stage renal disease. To date, none have died of a renal epithelial neoplasm.ConclusionThe identification of unique renal neoplasia subtypes may provide important clues to establish a diagnosis of TSC, and in the somatic setting, this finding has important implications for accurate prognostication. These tumors tend to be indolent, and only 2 of 276 tumors in our study exhibited metastatic behavior. Our results support multidisciplinary management with a focus on preservation of renal function.     

缺氧诱导因子-1α参与肝纤维化形成机制研究进展

目的 肝纤维化是一种由于反复肝损伤而导致肝组织细胞外基质过多沉积导致的疾病。缺氧损伤为肝损伤的一部分,缺氧诱导因子-1α(HIF-1α)是响应缺氧应激的关键转录因子,在肝纤维化组织和活化的肝星状细胞(HSC)表达显著增加。目前,通过对大量HIF-1α依赖性基因和信号通路的研究,确认这些基因及其通路的变化参与肝纤维化发展过程,并可能在肝纤维化发生发展过程中起关键作用。本文综述了HIF-1α相关的信号通路参与肝纤维化发展的相关机制,并对上游影响HIF-1α合成和降解的相关信号通路进行了阐述,为其作为新型治疗靶点的可能潜力提供依据。