Nashphilipsen3833

Identifying relationships between genetic variations and their clinical presentations has been challenged by the heterogeneous causes of a disease. It is imperative to unveil the relationship between the high-dimensional genetic manifestations and the clinical presentations, while taking into account the possible heterogeneity of the study subjects.We proposed a novel supervised clustering algorithm using penalized mixture regression model, called component-wise sparse mixture regression (CSMR), to deal with the challenges in studying the heterogeneous relationships between high-dimensional genetic features and a phenotype. The algorithm was adapted from the classification expectation maximization algorithm, which offers a novel supervised solution to the clustering problem, with substantial improvement on both the computational efficiency and biological interpretability. Experimental evaluation on simulated benchmark datasets demonstrated that the CSMR can accurately identify the subspaces on which subset of features are explanatory to the response variables, and it outperformed the baseline methods. Application of CSMR on a drug sensitivity dataset again demonstrated the superior performance of CSMR over the others, where CSMR is powerful in recapitulating the distinct subgroups hidden in the pool of cell lines with regards to their coping mechanisms to different drugs. CSMR represents a big data analysis tool with the potential to resolve the complexity of translating the clinical representations of the disease to the real causes underpinning it. We believe that it will bring new understanding to the molecular basis of a disease and could be of special relevance in the growing field of personalized medicine.Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases. Identifying disease-related miRNAs as new biomarkers can promote the development of disease pathology and clinical medicine. However, designing biological experiments to validate disease-related miRNAs is usually time-consuming and expensive. Therefore, it is urgent to design effective computational methods for predicting potential miRNA-disease associations. Inspired by the great progress of graph neural networks in link prediction, we propose a novel graph auto-encoder model, named GAEMDA, to identify the potential miRNA-disease associations in an end-to-end manner. More specifically, the GAEMDA model applies a graph neural networks-based encoder, which contains aggregator function and multi-layer perceptron for aggregating nodes' neighborhood information, to generate the low-dimensional embeddings of miRNA and disease nodes and realize the effective fusion of heterogeneous information. Then, the embeddings of miRNA and disease nodes are fed into a bilinear decoder to identify the potential links between miRNA and disease nodes. The experimental results indicate that GAEMDA achieves the average area under the curve of $93.56\pm 0.44\%$ under 5-fold cross-validation. Besides, we further carried out case studies on colon neoplasms, esophageal neoplasms and kidney neoplasms. As a result, 48 of the top 50 predicted miRNAs associated with these diseases are confirmed by the database of differentially expressed miRNAs in human cancers and microRNA deregulation in human disease database, respectively. The satisfactory prediction performance suggests that GAEMDA model could serve as a reliable tool to guide the following researches on the regulatory role of miRNAs. Besides, the source codes are available at https//github.com/chimianbuhetang/GAEMDA.

This study aimed to investigate whether everolimus (EVR) affects long-term survival after liver transplantation (LT) in patients with hepatocellular carcinoma (HCC).

The data from 303 consecutive patients with HCC who had undergone LT from January 2012 to July 2018 were retrospectively reviewed. The patients were divided into two groups 1) patients treated with EVR in combination with calcineurin inhibitors (CNIs) (EVR group; n=114) and 2) patients treated with CNI-based therapy without EVR (Non-EVR group; n=189). Time to recurrence (TTR) and overall survival (OS) after propensity score (PS) matching were compared between the groups, and prognostic factors for TTR and OS were evaluated.

The EVR group exhibited more aggressive tumor biology than the Non-EVR group, such as a higher number of tumors (P = 0.003), a higher prevalence of microscopic vascular invasion (P = 0.017) and exceeding Milan criteria (P = 0.029). Compared with the PS-matched Non-EVR group, the PS-matched EVR group had significantly better TTR (P < 0.001) and OS (P < 0.001). In multivariate analysis, EVR was identified as an independent prognostic factor for TTR (hazard ratio [HR]=0.248; P = 0.001) and OS (HR=0.145; P < 0.001).

Combined with CNIs, EVR has the potential to prolong long-term survival in patients undergoing LT for HCC. These findings warrant further investigation in a well-designed prospective study.

Combined with CNIs, EVR has the potential to prolong long-term survival in patients undergoing LT for HCC. These findings warrant further investigation in a well-designed prospective study.

The widely accepted treatment option of a traumatic carotid cavernous fistula (TCCF) has been detachable balloon or coils based fistula occlusion. Recently, covered stent implantation has been proving an excellent results. The purpose of this study is to investigate our experiences with first line choice of covered stent implantation for TCCF at level 1 regional trauma center.

From November 2004 to February 2020, 19 covered stents were used for treatment of 19 TCCF patients. Among them, 15 cases were first line treatment using covered stents. Clinical and angiographic data were retrospectively reviewed.

Procedures were technically successful in all 15 cases (100%). Immediate angiographic results after procedure were total occlusion in 12 patients (80%). All patients except two expired patients had image follow-up (mean 15 months). Recurred symptomatic three patients underwent additional treatments and achieved complete occlusion. Mean clinical follow-up duration was 32 months and results were modified Rankin Scale 1-2 in five, 3-4 in five, and 5 in three patients.

The covered stent could be considered as fist line treatment option for treating TCCF patients especially in unstable vital sign. Larger samples and expanded follow-up are required to further develop their specifications and indications.

The covered stent could be considered as fist line treatment option for treating TCCF patients especially in unstable vital sign. Larger samples and expanded follow-up are required to further develop their specifications and indications.Background Intravital microscopy is an emerging technique in life science with applications in kidney research. Longitudinal observation of (patho-)physiological processes in living mice is possible in the smallest functional unit of the kidney, a single nephron (sn). In particular, effects on glomerular filtration rate (GFR) - a key parameter of renal function - can be assessed. Methods After intravenous injection of a freely filtered, non-resorbable, fluorescent dye in C57BL/6 mice, a time series was captured by multiphoton microsopy. Filtration was observed from the glomerular capillaries to the proximal tubule (PT) and the tubular signal intensity shift was analyzed to calculate the snGFR. Results Previously described methods for snGFR analysis relied on two manually defined measurement points in the PT and the tubular volume was merely estimated in 2D images. We present an extended image processing workflow by adding continuous measurement of intensity along the PT in every frame of the time series using ImageJ. Automatic modelling of actual PT volume in a 3D dataset replaced 2D volume estimation. Subsequent data analysis in R, with a calculation of intensity shifts in every frame and normalization against tubular volume, allowed exact assessment of snGFR by linear regression. Linsitinib research buy Repeated analysis of image data obtained in healthy mice showed a striking increase of reproducibility by reduction of user interaction. Conclusions These improvements in image processing and data analysis maximize the reliability of a sophisticated intravital microscopy technique for the precise assessment of snGFR, a highly relevant predictor of kidney function.

This study was conducted to evaluate the effects of the supplementation of diets of broiler chickens with hot-melt extruded CuSO4 (HME-Cu) on their growth performance, nutrient digestibility, gut microbiota, small intestinal morphology, meat quality, and copper (Cu) bioavailability.

A total of 225 broilers (Ross 308), one-day old and initial weight 39.14 g, were weighed and distributed between 15 cages (15 birds per cage) in a completely randomized experimental design with 3 treatments (diets) and 5 replicates per treatment. Cages were allotted to three treatments including control (without supplemental Cu), IN-Cu (16 mg/kg of CuSO4), and HME-Cu (16 mg/kg of HME processed CuSO4).

The HME-Cu treatment tended to increase the overall body weight gain (BWG) (p<0.10). The apparent digestibility of Cu was increased by supplementation of HME-Cu at phase 2 (p<0.05). The Escherichia coli (E. coli) count in cecum tended to decrease with the supplementation with Cu (p<0.10). In addition, the HME-Cu treatme and the physiological function of Cu in broilers. However, supplementation of Cu in HME form improved the meat quality and the bioavailability of Cu.

The aim of this study was to evaluate the effect of marinating turkey meat with buttermilk and acid whey on the technological traits and microbiological quality of the product.

Slices of turkey meat muscles were marinated for 12 hours in buttermilk (n=30), acid whey (n=30) and comparatively, in lemon juice (n=30). The control group (n=30) consisted of unmarinated slices of turkey breast muscles. Physical parameters (pH, WHC, colour L*a*b*, shear force, weight loss) were assessed and quantitative and qualitative microbiological evaluation of raw and roasted products was performed. The microbiological parameters were determined as the total viable counts of mesophilic aerobic bacteria, of the Enterobacteriaceae family, and Pseudomonas spp. Bacterial identification was performed by MALDI-TOF MS.

Marinating turkey meat in buttermilk and whey compared to marinating in lemon juice and the control sample resulted in a higher (p<0.05) degree of yellow color saturation (b*) and a reduction (p<0.05) in the number of mesophilic aerobic bacteria, Pseudomonas spp. and Enterobacteriaceae family as well as the number of identified mesophilic aerobic bacteria in both raw and roasted samples. The lowest (p<0.05) shear force values were found in products marinated in whey.

The use of buttermilk and acid whey as a marinade for meat increases the microbiological safety of the product compared to marinating in lemon juice, while maintaining good technological features of the product.

The use of buttermilk and acid whey as a marinade for meat increases the microbiological safety of the product compared to marinating in lemon juice, while maintaining good technological features of the product.