Byskovlist0465

86%, an average Dice coefficient of 95.64%, an average volumetric overlap error (VOE) of 8.28%, an average relative volume difference (RVD) of -0.41%, and an average Hausdorff distance (HD) of 26.60mm were achieved.

This study demonstrates that liver segmentation, even when lesions are present in CT images, can be efficiently performed using a cascade approach and including a reconstruction step based on deep convolutional neural networks.

This study demonstrates that liver segmentation, even when lesions are present in CT images, can be efficiently performed using a cascade approach and including a reconstruction step based on deep convolutional neural networks.Emotion recognition is a vital but challenging step in creating passive brain-computer interface applications. In recent years, many studies on electroencephalogram (EEG)-based emotion recognition have been conducted. Ensemble learning has been widely used in emotion recognition because of its superior accuracy and generalization. In this study, we proposed a novel ensemble learning method based on multiple objective particle swarm optimization for subject-independent EEG-based emotion recognition. First, we used a 4 s sliding time window with a 2 s overlap to extract 13 different features from EEG signals and construct a feature vector. Then, we employed L1 regularization to select effective features. Second, a model selection method was applied to choose the optimal basic analysis submodels. Afterward, we proposed an ensemble operator that converts the classification results of a single model from discrete values to continuous values to better characterize the classification results. Subsequently, multiple objective particle swarm optimization was adopted to confirm the optimal parameters of the ensemble learning model. Finally, we conducted extensive experiments on two public datasets DEAP and SEED. Considering the generalization of the model, we applied leave-one-subject-out cross-validation to evaluate the performance of the model. The experimental results demonstrate that the proposed method achieves a better recognition performance than single methods, commonly used ensemble learning methods, and state-of-the-art methods. The average accuracies for arousal and valence are 65.70% and 64.22%, respectively, on the DEAP database, and the average accuracy on the SEED database is 84.44%.

A new coronavirus disease named COVID-19, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is rapidly spreading worldwide. However, there is currently no effective drug to fight COVID-19.

In this study, we developed a Virus-Drug Association (VDA) identification framework (VDA-RWLRLS) combining unbalanced bi-Random Walk, Laplacian Regularized Least Squares, molecular docking, and molecular dynamics simulation to find clues for the treatment of COVID-19. First, virus similarity and drug similarity are computed based on genomic sequences, chemical structures, and Gaussian association profiles. GS-9674 nmr Second, an unbalanced bi-random walk is implemented on the virus network and the drug network, respectively. Third, the results of the random walks are taken as the input of Laplacian regularized least squares to compute the association score for each virus-drug pair. Fourth, the final associations are characterized by integrating the predictions from the virus network and the drug network. Finaltribute to preventing COVID-19 transmission.

Type 1 diabetes (T1D) is an autoimmune disease characterized by impaired immune tolerance to β-cell antigens and progressive destruction of insulin-producing β-cells. Animal models have provided valuable insights for understanding the etiology and pathogenesis of this disease, but they fall short of reflecting the extensive heterogeneity of the disease in humans, which is contributed by various combinations of risk gene alleles and unique environmental factors. Collectively, these factors have been used to define subgroups of patients, termed endotypes, with distinct predominating disease characteristics.

Here, we review the gaps filled by these models in understanding the intricate involvement and regulation of the immune system in human T1D pathogenesis. We describe the various models developed so far and the scientific questions that have been addressed using them. Finally, we discuss the limitations of these models, primarily ascribed to hosting a human immune system (HIS) in a xenogeneic recipient, a systems.Ulcerative colitis (UC) specifically affects the colon and rectum through multifactorial mechanisms associated with genetic alterations, environmental factors, microbiota, and mucosal immune dysregulation. In patients with corticosteroid-refractory UC, current therapies primarily employ antibodies against tumor necrosis factor-α, α4β7 integrin, and interleukin (IL)-12/23 p40; and a small-molecule Janus kinase inhibitor. Despite these revolutionary molecular targeting therapies introduced during the last two decades, 30%-55% of patients fail to respond such molecular targeting agents in the induction phase, requiring changes in treatment. Here we review basic and clinical research aimed to address this problem, focusing on the pathogenic effects of cytokines produced by innate and adaptive immune cells. For example, IL-1β, IL-6, tumor necrosis factor-α, T helper (Th) 1-, Th2-, and Th17-associated cytokines are expressed at relatively higher levels in the intestinal tissues of patients with UC. However, their expression levels depend on disease stage and patient characteristics. The complex pathology of UC may induce differences in responses to therapy. The findings of such studies strongly support the argument that future targeted therapies must focus on differences in cytokine levels associated with the stages of UC as well as on the distinct cytokine expression profiles of individual patients.Granulomatosis with polyangiitis (GPA) is a systemic autoimmune disorder classified among the anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) and characterized by a triad of upper and lower respiratory tract disease, systemic vasculitis involving small-to-medium vessels and renal manifestations. Mass lesions, also described as inflammatory lesions, pseudotumor or tumour-like masses, are uncommon manifestations of GPA and are often called granuloma since histology examination shows granulomatous inflammation and rarely vasculitis. Masses could represent a localized manifestation of GPA or develop as part of a systemic disease. Unusual clinical presentation together with nonspecific radiological and histological features may delay the correct diagnosis leading to disease progression and organ damage. Diagnosis of GPA in such cases may be challenging and malignancy or infections must be considered as alternative diagnostic options. Here we reviewed all the different sites where mass lesions were reported in GPA, focusing on atypical localization, and summarized current therapeutic options and their different outcomes. We retrieved and discussed the cases reported since 2010, bearing in mind the advances in the therapeutic management of AAV patients in the last decade, namely biological therapy such as rituximab. Despite treatment regimens with glucocorticoids and immunosuppressive agents, mass lesions have a refractory course in a high proportion of patients. Invasive surgical procedures may be considered only when drug therapy fails.Chronic pain is the leading cause of life years lived with disability worldwide. The aetiology of most chronic pain conditions has remained poorly understood and there is a dearth of effective therapies. The WHO ICD-11 has categorised unexplained chronic pain states as 'chronic primary pains' (CPP), which are further defined by their association with significant distress and/or dysfunction. The new mechanistic term, 'nociplasticic pain' has been developed to illustrate their presumed generation by a structurally intact, but abnormally functioning nociceptive system. Recently, researchers have unravelled the surprising, ubiquitous presence of pain-sensitising autoantibodies in four investigated CPP indicating autoimmune causation. In persistent complex regional pain syndrome, fibromyalgia syndrome, chronic post-traumatic limb pain, and non-inflammatory joint pain associated with rheumatoid arthritis, passive transfer experiments have shown that either IgG or IgM antibodies from patient-donors cause symptoms upon injection to rodents that closely resemble those of the clinical disorders. Targets of antibody-binding and downstream effects vary between conditions, and more research is needed to elucidate the molecular and cellular details. The central nervous system appears largely unaffected by antibody binding, suggesting that the clinically evident CNS symptoms associated with CPP might arise downstream of peripheral processes. In this narrative review pertinent findings are described, and it is suggested that additional symptom-based disorders might be examined for the contribution of antibody-mediated autoimmune mechanisms.Zoo-archaeological and genetic evidence suggest that pigs were domesticated independently in Central China and Eastern Anatolia along with the development of agricultural communities and civilizations. However, the genetic history of domestic pigs, especially in China, has not been fully explored. In this study, we generated 42 complete mitochondrial DNA sequences from ∼7500- to 2750-year-old individuals from the Yellow River basin. Our results show that the maternal genetic continuity of East Asian domestic pigs dates back to at least the Early to Middle Neolithic. In contrast, the Near Eastern ancestry in European domestic pigs saw a near-complete genomic replacement by the European wild boar. The majority of East Asian domestic pigs share close haplotypes, and the most recent common ancestor of most branches dates back to less than 20,000 years before present, inferred using new substitution rates of whole mitogenomes or combined protein-coding regions. Two major population expansion events of East Asian domestic pigs coincided with changes in climate, widespread adoption of introduced crops, and the development of agrarian societies. These findings add to our understanding of the maternal genetic composition and help to complete the picture of domestic pig evolutionary history in East Asia.The latest studies on the epidemiology of diverse types of cancers have located in the scene the relevance of liver tumors, particularly hepatocellular carcinoma (HCC). HCC is a life-threatening malignancy triggered by chronic exposure to hepatitis B and C viruses, excessive alcohol intake, hepatic lipid droplet accumulation, and aflatoxins that lead to persistent liver damage. The occurrence of such etiological risk factors deeply marks the variability in the incidence of HCC worldwide reflected by geography, ethnicity, age, and lifestyle factors influenced by cultural aspects. New perspectives on the primary risk factors and their potential gene-environment interactions (GxE) have been well-addressed in some cancers; however, it continues to be a partially characterized issue in liver malignancies. In this review, the epidemiology of the risk factors for HCC are described enhancing the GxE interactions identified in Mexico, which could mark the risk of this liver malignancy among the population and the measures needed to revert them.