MeMo: a web tool for prediction of protein methylation modifications

Protein methylation is an important and reversible post-translational modification of proteins (PTMs), which governs cellular dynamics and plasticity. Experimental identification of the methylation site is labor-intensive and often limited by the availability of reagents, such as methyl-specific antibodies and optimization of enzymatic reaction. Computational analysis may facilitate the identification of potential methylation sites with ease and provide insight for further experimentation. Here we present a novel protein methylation prediction web server named MeMo, protein methylation modification prediction, implemented in Support Vector Machines (SVMs). Our present analysis is primarily focused on methylation on lysine and arginine, two major protein methylation sites. However, our computational platform can be easily extended into the analyses of other amino acids. The accuracies for prediction of protein methylation on lysine and arginine have reached 67.1 and 86.7%, respectively. Thus, the MeMo system is a novel tool for predicting protein methylation and may prove useful in the study of protein methylation function and dynamics. The MeMo web server is available at:

NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm

BACKGROUND: Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. RESULTS: In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed) and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM), also have been employed and compared with NBA-Palm. CONCLUSION: Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from:

Research progress in neuroimmune disorders in atopic dermatitis

Atopic dermatitis (AD) is a chronic inflammatory skin disease with the highest incidence in the world. The main clinical manifestations are eczema-like skin lesions, pruritus and xeroderma. Recent studies have revealed that sensory neurons in the skin lesions of AD patients can interact abnormally with keratinocytes (KC) and immune cells, leading to neuroimmune disorders. Among them, there are two types of sensory neurons involved in neuroimmune disorders, including histaminergic and non-histaminergic sensory neurons. In neuroimmune disorders, KC and immune cells activate sensory neurons to induce pruritus by secreting proinflammatory cytokines such as interleukin-4 (IL-4), IL-13, IL-31, IL-33, and thymic stromal lymphopoietin, as well as chemokines such as C-X-C motif chemokine ligand 12 (CXCL12) and CXCL10. In addition, neuropeptides such as nerve growth factor, brain-derived neurotrophic factor and artemin secreted by KC and immune cells can induce overgrowth of sensory neurons, thereby promoting neuroimmune disorders. At the same time, the excessive release of neuropeptides such as calcitonin gene-related peptide and substance P by sensory neurons can act on KC and immune cells, thereby aggravating skin inflammation. In recent years, many drugs targeting neuroimmune disorders are in preclinical studies, clinical trials and other stages, or have been marketed for the treatment of AD. Among them, our research group has found that lidocaine, a local anesthetic, can target neuroimmune disorders and relieve pruritus and skin inflammation in AD patients. At present, the role of neuroimmune disorders in AD has not been systematically discussed. Based on this, this article reviews the types of sensory neurons involved in neuroimmune disorders, the role of KC, immune cells and sensory neurons in neuroimmune disorders, as well as the therapeutic strategies targeting neuroimmune disorders

Annual surveys for point-prevalence of healthcare-associated infection in a tertiary hospital in Beijing, China, 2012-2014

Background: This study aimed to investigate the prevalence of healthcare-associated infection (HAI) in the China-Japan Friendship Hospital, a tertiary level hospital in Beijing, China. Methods: We defined HAI using the criteria established by the Ministry of Health of the People's Republic of China. Three cross-sectional surveys were conducted from 2012 to 2014. Inpatients who had been hospitalized for at least 48 h were surveyed. Information on HAI prevalence, isolated pathogens and use of antibiotics were collected. Logistic regression models were used to assess the associations between HAI and potential risk factors. Results: During three cross-sectional surveys, a total number of 4,029 patients were included (1,233 patients in 2012, 1,220 patients in 2013 and 1,576 patients in 2014). The overall prevalence of patients with HAI was 3.6 % (95 % confidence interval (CI) 3.1 %-4.2 %). Respiratory tract infections were the most common type (64.7 %) of HAIs, followed by urinary tract infections (12.6 %) and bloodstream infections (5.4 %). HAI occurrences were significantly associated with male sex (odds ratio (OR) = 2.25, 95 % CI 1.53-3.32), age over 85 years (OR = 4.74, 95 % CI 2.54-8.83), hospitalization in the intensive care units (ICUs) (OR = 2.42, 95 % CI 1.31-4.49), indwelling urinary catheter (OR = 4.21, 95 % CI 2.46-7.20) and mechanical ventilation (OR = 2.31, 95 % CI 1.30-4.09). Gram-negative bacteria were found to be the most isolated pathogens (67.1 %), with gram-positive bacteria and fungi accounted for 20.3 % and 10.5 %, respectively. Antibiotics were administered to 34.3 % of the included patients over the study period. Conclusions: The overall HAI prevalence in our hospital is similar to previous studies that were conducted in other areas of China, and the respiratory tract infection should be the priority in HAI reduction control within China. We should focus HAI reduction efforts on patients with advanced age, hospitalization in the ICU and indwelling devices.SCI(E)[email protected]

Doubly Stochastic Neighbor Embedding on Spheres

Stochastic Neighbor Embedding (SNE) methods minimize the divergence between the similarity matrix of a high-dimensional data set and its counterpart from a low-dimensional embedding, leading to widely applied tools for data visualization. Despite their popularity, the current SNE methods experience a crowding problem when the data include highly imbalanced similarities. This implies that the data points with higher total similarity tend to get crowded around the display center. To solve this problem, we introduce a fast normalization method and normalize the similarity matrix to be doubly stochastic such that all the data points have equal total similarities. Furthermore, we show empirically and theoretically that the doubly stochasticity constraint often leads to embeddings which are approximately spherical. This suggests replacing a flat space with spheres as the embedding space. The spherical embedding eliminates the discrepancy between the center and the periphery in visualization, which efficiently resolves the crowding problem. We compared the proposed method (DOSNES) with the state-of-the-art SNE method on three real-world datasets and the results clearly indicate that our method is more favorable in terms of visualization quality. DOSNES is freely available at http://yaolubrain.github.io/dosnes/. (C) 2019 The Authors. Published by Elsevier B.V.Peer reviewe

Integration of residents' experiences into economic planning process of coastal villages: Evidence from the Greater Hangzhou Bay Rim Area

Public value is gaining prominence from both academics and politicians with regards to China's rural development. However, rural planning authorities and practitioners showed limited confidence on public, which manifests as few public perceptions were integrated into the planning documents. This study explores the potential role of residents' experiences in illustrating local economic development within the context of coastal villages in which economic and industries are rapidly transforming. Two case studies from within the locale of the Greater Hangzhou Bay Rim Area are used in this article to examine the gap between residents' experiences and the actual economic development that has occurred. The main findings suggest that rural residents can directly reflect upon both current and historic trends of local economic development. Moreover, household income satisfaction (HIS) is a comprehensive notion of residents' experiences, and indicates social and economic sustainability of industrial transformation, or "thriving business", that have been highlighted in coastal villages. Public experiences could therefore act as a valid and accessible evidence for planners in rural economic planning in China and other developing countries

Genome-Wide Association Mapping for Tomato Volatiles Positively Contributing to Tomato Flavor

Tomato volatiles, mainly derived from essential nutrients and health-promoting precursors, affect tomato flavor. Taste volatiles present a major challenge for flavor improvement and quality breeding. In this study, we performed genome-wide association studies (GWAS) to investigate potential chromosome regions associated with the tomato flavor volatiles. We observed significant variation (1200x) among the selected 28 most important volatiles in tomato based on their concentration and odor threshold importance across our sampled accessions. Using 174 tomato accessions, GWAS identified 125 significant associations (P<0.005) among 182 SSR markers and 28 volatiles (27 volatiles with at least one significant association). Several significant associations were co-localized in previously identified quantitative trait loci (QTL). This result provides new potential candidate loci affecting the metabolism of several volatiles