Hederagenol improves multiple sclerosis by modulating Th17 cell differentiation.

Multiple sclerosis (MS) is a common autoimmune illness that is difficult to treat. The upregulation of Th17 cells is critical in the pathological process of MS. Hederagenol (Hed) has been shown to lower IL-17 levels, although its role in MS pathophysiology is uncertain. In this study, we explore whether Hed could ameliorate MS by modulating Th17 cell differentiation, with the goal of identifying new treatment targets for MS. The experimental autoimmune encephalomyelitis (EAE) mouse model was conducted and Hed was intraperitoneally injected into mice. The weight was recorded and the clinical symptom grade was assessed. Hematoxylin-eosin staining was carried out to determine the extent of inflammation in the spinal cord and liver. The luxol Fast Blue staining was performed to detect the pathological changes in the myelin sheath. Nerve damage was detected using NeuN immunofluorescence staining and terminal deoxynucleotidyl transferase dUTP nick-end labeling staining. Immunohistology approaches were used to study alterations in immune cells in the spinal cord. The proportions of T cell subsets in the spleens were analyzed by flow cytometry. RORγt levels were measured using quantitative real-time PCR or Western blot. The activity of the RORγt promoter was analyzed by Chromatin immunoprecipitation. Hed administration reduced the clinical symptom grade of EAE mice, as well as the inflammatory infiltration, demyelination, and cell disorder of the spinal cord, while having no discernible effect on the mouse weight. In addition, Hed treatment significantly reduced the number of T cells, particularly Th17 cells in the spinal cord and spleen-isolated CD4+ T cells. Hed lowered the RORγt levels in spleens and CD4+ T cells and overexpression of RORγt reversed the inhibitory effect of Hed on Th17 differentiation. Hed decreased nerve injury by modulating Th17 differentiation through the RORγt promoter. Hed regulates Th17 differentiation by reducing RORγt promoter activity, which reduces nerve injury and alleviates EAE.

The Deep Learning-Based Recommender System "Pubmender" for Choosing a Biomedical Publication Venue: Development and Validation Study.

BACKGROUND: It is of great importance for researchers to publish research results in high-quality journals. However, it is often challenging to choose the most suitable publication venue, given the exponential growth of journals and conferences. Although recommender systems have achieved success in promoting movies, music, and products, very few studies have explored recommendation of publication venues, especially for biomedical research. No recommender system exists that can specifically recommend journals in PubMed, the largest collection of biomedical literature. OBJECTIVE: We aimed to propose a publication recommender system, named Pubmender, to suggest suitable PubMed journals based on a paper's abstract. METHODS: In Pubmender, pretrained word2vec was first used to construct the start-up feature space. Subsequently, a deep convolutional neural network was constructed to achieve a high-level representation of abstracts, and a fully connected softmax model was adopted to recommend the best journals. RESULTS: We collected 880,165 papers from 1130 journals in PubMed Central and extracted abstracts from these papers as an empirical dataset. We compared different recommendation models such as Cavnar-Trenkle on the Microsoft Academic Search (MAS) engine, a collaborative filtering-based recommender system for the digital library of the Association for Computing Machinery (ACM) and CiteSeer. We found the accuracy of our system for the top 10 recommendations to be 87.0%, 22.9%, and 196.0% higher than that of MAS, ACM, and CiteSeer, respectively. In addition, we compared our system with Journal Finder and Journal Suggester, which are tools of Elsevier and Springer, respectively, that help authors find suitable journals in their series. The results revealed that the accuracy of our system was 329% higher than that of Journal Finder and 406% higher than that of Journal Suggester for the top 10 recommendations. Our web service is freely available at https://www.keaml.cn:8081/. CONCLUSIONS: Our deep learning-based recommender system can suggest an appropriate journal list to help biomedical scientists and clinicians choose suitable venues for their papers.

Veganism does not reduce the risk of the metabolic syndrome in a Taiwanese cohort.

The purpose of the present study was to assess the risk of the metabolic syndrome (MS) with vegan, pescovegetarian, lactovegetarian and nonvegetarian diets in Taiwan. The design was a retrospective cohort study using secondary data analysis from a Taiwan longitudinal health check-up database provided by MJ Health Screening Center during 1996-2006. A total of 93209 participants were classified as vegans (n=1116), pescovegetarians (n=2461), lactovegetarians (n=4313) and nonvegetarians (n=85319) by food frequency list of self-administered questionnaire at baseline. The association between MS or MS components and different dietary groups was evaluated using Cox proportional-hazards regression models with adjustment for confounders. During the mean 3.75 years of follow up, a total 8006 MS incident cases occurred and the incidence of MS was 229 (95% CI, 224, 234) per 10000 person year. Compared with vegans, hazard ratios of MS for nonvegetarians, pescovegetarians, lactovegetarians were 0.75 (95% CI, 0.64, 0.88), 0.68 (95% CI, 0.55, 0.83) and 0.81 (95% CI, 0.67, 0.97) after adjusting for sex, age, education status, smoking status, drinking status, physical activity at work and leisure, respectively. As for MS components, nonvegetarians and pescovegetarians had 0.72 (95% CI, 0.62, 0.84), 0.70 (95% CI, 0.57, 0.84) times risk of developing low high density lipoprotein cholesterol (HDL-C), while nonvegetarians had 1.16 (95% CI, 1.02, 1.32) times risk of developing high fasting plasma glucose. Our data suggest that the vegan diets did not decrease the risk of metabolic syndrome compared with pescovegetarian, lactovegetarian and nonvegetarian diets in a Taiwanese cohort.

Incidence, clinical features and impact on anti-tuberculosis treatment of anti-tuberculosis drug induced liver injury (ATLI) in China.

BACKGROUND: Anti-tuberculosis drug induced liver injury (ATLI) is emerging as a significant threat to tuberculosis control in China, though limited data is available about the burden of ATLI at population level. This study aimed to estimate the incidence of ATLI, to better understand its clinical features, and to evaluate its impact on anti-tuberculosis (TB) treatment in China. METHODOLOGY/PRINCIPAL FINDINGS: In a population-based prospective study, we monitored 4,304 TB patients receiving directly observed treatment strategy (DOTS) treatment, and found that 106 patients developed ATLI with a cumulative incidence of 2.55% (95% Confidence Interval [CI], 2.04%-3.06%). Nausea, vomiting and anorexia were the top three most frequently observed symptoms. There were 35 (33.02%) ATLI patients with no symptoms, including 8 with severe hepatotoxicity. Regarding the prognosis of ATLI, 84 cases (79.25%) recovered, 18 (16.98%) improved, 2 (1.89%) failed to respond to the treatment with continued elevation of serum alanine aminotransferase, and 2 (1.89%) died as result of ATLI. Of all the ATLI cases, 74 (69.81%) cases changed their anti-TB treatment, including 4 (3.77%) cases with medication administration change, 21 (19.81%) cases with drugs replacement, 54 (50.94%) cases with therapy interruption, and 12 (11.32%) cases who discontinued therapy. In terms of treatment outcomes, 53 (51.46%) cases had TB cured in time, 48 (46.60%) cases had therapy prolonged, and 2 (1.94%) cases died. Compared with non-ATLI patients, ATLI patients had a 9.25-fold (95%CI, 5.69-15.05) risk of unsuccessful anti-TB treatment outcomes and a 2.11-fold (95%CI, 1.23-3.60) risk of prolonged intensive treatment phase. CONCLUSIONS/SIGNIFICANCE: ATLI could considerably impact the outcomes of anti-TB treatment. Given the incidence of ATLI and the size of TB population in China, the negative impact is substantial. Therefore, more research and efforts are warranted in order to enhance the diagnosis and the prevention of ATLI.