Liver cancer is one of the world's largest causes of death to humans. It is a difficult task and time consuming to identify the cancer tissue manually in the present scenario. The segmentation of liver lesions in CT images can be used to assess the tumor load, plan treatments predict, and monitor the clinical response. In this paper, the Hybridized Fully Convolutional Neural Network (HFCNN) has been proposed for liver tumor segmentation, which has been modeled mathematically to resolve the current issue of liver cancer. For semantic segmentation, HFCNN has been used as a powerful tool for liver cancer analysis. Whereas the CT-based lesion-type definition defines the diagnosis and therapeutic strategy, the distinction between cancer and non-cancer lesions is crucial. It demands highly qualified experience, expertise, and resources. However, a deep end-to-end learning approach to help discrimination in abdominal CT images of the liver between liver metastases of colorectal cancer and benign cysts has been analyzed. Our method includes the successful extraction of features from Inception combined with residual and pre-trained weights. Feature maps have been consistent with the original image voxel features, and The importance of features seemed to represent the most relevant imaging criteria for every class. This deep learning system shows the concept of illumination portions of the decision-making process of a pre-trained deep neural network, through an analysis of inner layers and the description of features that lead to predictions.

A simple, rapid and environment-friendly technique of single-drop liquid-phase microextraction has been developed for the determination of sulfonamides in environmental water. Several important parameters including stirring rate, extraction solvent, extraction pH, salinity and extraction time were optimized to maximize the extract efficiency. Extraction solvent 1-octyl-3-methylimidazolium hexafluorophosphate [C(8) MIM][PF(6) ] ionic liquid showed better extraction efficiency than 1-butyl-3-methylimidazolium hexafluorophosphate [C(4) MIM][PF(6) ] and 1-octanol. The optimum experimental conditions were: pH, 4.5; sodium chloride content, 36% w/v; extraction time, 20 min. This method provided low detection limits (0.5-1 ng/mL), good repeatability (the RSD ranging from 4.2 to 9.9%, n=5) and wide linear range (1-1500 ng/mL), with determination coefficients (r(2) ) higher than 0.9989 for all the target compounds. Real sample analysis showed relative recoveries between 63.5 and 115.8% for all the target compounds.

Objective: Primary closure of the common bile duct (CBD) after laparoscopic CBD exploration (LCBDE) is a technical challenge. The present study was performed to evaluate the safety and effectiveness of this surgical method. Methods: This retrospective study of surgical efficacy and safety involved 79 patients who underwent primary CBD closure with a knotless unidirectional barbed suture or traditional T-tube drainage after LCBDE for CBD stones. Results: The average suturing time, operation time, and postoperative hospital stay were significantly shorter in the primary closure group than T-tube group. There were no significant differences in the mean diameter of the CBD, number of stones, or incidence of postoperative complications between the two groups. No patients developed recurrence of CBD stones during the median follow-up of 21.5 months. Conclusions: After LCBDE and intraoperative choledochoscopy, primary closure with knotless unidirectional barbed sutures is a safe and effective therapeutic option for patients with cholelithiasis and concurrent CBD stones. This is especially true when the CBD is dilated more than 8 mm.

Aims: Krüppel-like Factor 9 (KLF9) is a transcription factor that regulates multiple disease processes. Studies have focused on the role of KLF9 in the redox system. In this study, we aimed to explore the effect of KLF9 on diabetic cardiomyopathy. Methods and Results: Cardiac-specific overexpression or silencing of KLF9 in C57BL/6 J mice was induced with an adeno-associated virus 9 (AAV9) delivery system. Mice were also subjected to streptozotocin injection to establish a diabetic cardiomyopathy model. In addition, neonatal rat cardiomyocytes were used to assess the possible role of KLF9 in vitro by incubation with KLF9 adenovirus or small interfering RNA against KLF9. To clarify the involvement of peroxisome proliferator-activated receptors (PPARγ), mice were subjected to GW9662 injection to inhibit PPARγ. KLF9 was upregulated in the hearts of mice with diabetic cardiomyopathy and in cardiomyocytes. In addition, KLF9 overexpression in the heart deteriorated cardiac function and aggravated hypertrophic fibrosis, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. Conversely, cardiac-specific silencing of KLF9 ameliorated cardiac dysfunction and alleviated hypertrophy, fibrosis, the cardiac inflammatory response and oxidative stress. In vitro, KLF9 silencing in cardiomyocytes enhanced inflammatory cytokine release and oxidative stress; KLF9 overexpression increased these detrimental responses. Moreover, KLF9 was found to regulate the transcription of PPARγ, which suppressed the expression and nuclear translocation of nuclear Factor E2-related Factor 2 (NRF2). In mice injected with a PPARγ inhibitor, the protective effects of KLF9 knockdown on diabetic cardiomyopathy were counteracted by GW9662 injection. Conclusions: KLF9 aggravates cardiac dysfunction, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. KLF9 may become a therapeutic target for diabetic cardiomyopathy.

Background Long non-coding RNAs (lncRNAs) are defined as non-coding RNA (ncRNA) with transcripts longer than 200 nucleotides with tissue specificity. Recently it has been found participate in cancer tumorigenesis and progression via transcriptional regulation, post-transcriptional regulation and epigenetic gene regulation. Competitive endogenous RNA (ceRNA) hypothesis assume that lncRNAs compete the target RNA by sponging the common miRNA response elements (MREs) to complete the post-transcriptional regulation. To explore the function and mechanisms of lncRNAs as ceRNAs in gastric cancer (GC), this study performed a genome-wide analysis. Methods The lncRNAs, mRNAs and microRNAs (miRNAs) profiles of 375 GC samples and 32 normal samples were obtained from The Cancer Genome Atlas (TCGA) Stomach Adenocarcinoma (STAD) datasets. The data was standardized with a cross match in the miRBase (a database at http://www.mirbase.org/ ), which made 365 samples as the analysis objects. We identify differentially expressed RNAs (DERNAs), including differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs) and differentially expressed lncRNAs (DElncRNAs) by applying edge R package with thresholds of |log 2 FC| >2 and false discovery rate (FDR) <0.01. The potential RNAs for the gastric ceRNA network were screened out from the DERNAs based on “ceRNA hypothesis”. The further construction of the network and analysis of its topological properties were performed by Cytoscape. Gene oncology (GO) function enrichment was analyzed by BINGO plugin of Cytoscape. Survival analysis was estimated according to Kaplan-Meier curve analysis. Results The constructed gastric ceRNA network involved 61 mRNAs, 44 lncRNAs and 22 miRNAs. Five lncRNAs out of the DElncRNAs, namely MIR100HG, MAGI2-AS3, AC080038.1, AC010478.1 and MEF2C-AS1, were found mostly involved in the network. The lncRNA AL139147 were detected negatively correlated with overall survival (log-rank, P<0.05). Conclusions In conclusion, our study identified promising lncRNAs, which might be potential diagnostic biomarker and therapeutic targets and contribute to further understanding of the ceRNA pathogenesis in GC and guide for further investigation.