Protective Effect of FTY720 on Several Markers of Liver Injury Induced by Concanavalin A in Mice

AbstractBackground2-Amino-2-[2-(4-octylphenyl)ethyl] propane-1,3-diol hydrochloride (FTY720) is a novel agent with protective effect on several markers of liver injury. It is a chemical substance derived by modifying myriocin from the ascomycete Isaria sinclairii. It has been reported that FTY720 is able to treat autoimmune encephalomyelitis, renal cancer, asthma, and multiple sclerosis. More potent clinical applications of FTY720 need to be investigated.ObjectiveThe aim of this study was to evaluate the protective effect of FTY720 on several markers of experimental liver injury and to investigate the possible mechanism of action.MethodsConcanavalin A (Con A) at a dose of 15 mg/kg was intravenously. injected in mice, and 10 days before the Con A challenge, 1 mg/kg, 3 mg/kg, and 6 mg/kg of FTY720 were administered to mice. The liver injury was monitored biochemically by measuring serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) and tumor necrosis factor-α (TNF-α) levels. TNF-α and nuclear factor-κB (NF-κB) in liver tissue were detected by Western blot analysis.ResultsFTY720, when administered intragastrically for 10 days in mice with Con A–induced liver injury, dose-dependently reduced serum ALT and AST and TNF-α levels. The differences were statistically significant (P ≤ 0.05). It was also found that FTY720 decreases TNF-α and NF-κB protein expression in liver tissue.ConclusionsFTY720 is able to improve several markers of Con A–induced liver injury in mice, including serum ALT, serum AST, TNF-α, and NF-κB, which might be at least in part related to its ability to reduce TNF-α/NF-κB cascade activity

Market reaction to seasoned offerings in China

YesThis study examines stock market reaction to the announcement of various forms of seasoned issues in China. Our empirical evidence demonstrates that market reactions differ in ways that suggest a difference between management's internal assessment and the market's assessment of the stock price. The market responds unfavourably to the announcement, notably in the case of rights issues and also with regard to open offers. Private placements experience an unfavourable pre‐announcement reaction, which contrasts with the favourable reaction after the event. Convertible bond issues generate positive excess returns consistent with the market's confidence that they can help to align management and shareholders’ interests. Further investigation shows that market reaction is related to factors specific to the issuer and issue by reference to the period immediately surrounding the issue. Specifically, ownership concentration, agency matters connected with equity offerings, investor protection connected with fund allocation and security pricing, and the influence of powerful moneyed interests together provide an instructive insight into market reaction. Institutional inefficiency pertaining to underwriting, auditing, analysts’ forecasts and credit ratings are found to have a weak association with market price, consistent with due public scepticism concerning management and their gatekeepers

A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III

We established a method on measuring the \dzdzb mixing parameter $y$ for BESIII experiment at the BEPCII $e^+e^-$ collider. In this method, the doubly tagged $\psi(3770) \to D^0 \overline{D^0}$ events, with one $D$ decays to CP-eigenstates and the other $D$ decays semileptonically, are used to reconstruct the signals. Since this analysis requires good $e/\pi$ separation, a likelihood approach, which combines the $dE/dx$, time of flight and the electromagnetic shower detectors information, is used for particle identification. We estimate the sensitivity of the measurement of $y$ to be 0.007 based on a $20fb^{-1}$ fully simulated MC sample.Comment: 6 pages, 7 figure

Improving sentiment analysis via sentence type classification using BiLSTM-CRF and CNN

Different types of sentences express sentiment in very different ways. Traditional sentence-level sentiment classification research focuses on one-technique-fits-all solution or only centers on one special type of sentences. In this paper, we propose a divide-and-conquer approach which first classifies sentences into different types, then performs sentiment analysis separately on sentences from each type. Specifically, we find that sentences tend to be more complex if they contain more sentiment targets. Thus, we propose to first apply a neural network based sequence model to classify opinionated sentences into three types according to the number of targets appeared in a sentence. Each group of sentences is then fed into a one-dimensional convolutional neural network separately for sentiment classification. Our approach has been evaluated on four sentiment classification datasets and compared with a wide range of baselines. Experimental results show that: (1) sentence type classification can improve the performance of sentence-level sentiment analysis; (2) the proposed approach achieves state-of-the-art results on several benchmarking datasets

Role of NRP1 in Bladder Cancer Pathogenesis and Progression

Bladder urothelial carcinoma (BC) is a fatal invasive malignancy and the most common malignancy of the urinary system. In the current study, we investigated the function and mechanisms of Neuropilin-1 (NRP1), the co-receptor for vascular endothelial growth factor, in BC pathogenesis and progression. The expression of NRP1 was evaluated using data extracted from GEO and HPA databases and examined in BC cell lines. The effect on proliferation, apoptosis, angiogenesis, migration, and invasion of BC cells were validated after NRP1 knockdown. After identifying differentially expressed genes (DEGs) induced by NRP1 silencing, GO/KEGG and IPA® bioinformatics analyses were performed and specific predicted pathways and targets were confirmed in vitro. Additionally, the co-expressed genes and ceRNA network were predicted using data downloaded from CCLE and TCGA databases, respectively. High expression of NRP1 was observed in BC tissues and cells. NRP1 knockdown promoted apoptosis and suppressed proliferation, angiogenesis, migration, and invasion of BC cells. Additionally, after NRP1 silencing the activity of MAPK signaling and molecular mechanisms of cancer pathways were predicted by KEGG and IPA® pathway analysis and validated using western blot in BC cells. NRP1 knockdown also affected various biological functions, including antiviral response, immune response, cell cycle, proliferation and migration of cells, and neovascularisation. Furthermore, the main upstream molecule of the DEGs induced by NRP1 knockdown may be NUPR1, and NRP1 was also the downstream target of NUPR1 and essential for regulation of FOXP3 expression to activate neovascularisation. DCBLD2 was positively regulated by NRP1, and PPAR signaling was significantly associated with low NRP1 expression. We also found that NRP1 was a predicted target of miR-204, miR-143, miR-145, and miR-195 in BC development. Our data provide evidence for the biological function and molecular aetiology of NRP1 in BC and for the first time demonstrated an association between NRP1 and NUPR1, FOXP3, and DCBLD2. Specifically, downregulation of NRP1 contributes to BC progression, which is associated with activation of MAPK signaling and molecular mechanisms involved in cancer pathways. Therefore, NRP1 may serve as a target for new therapeutic strategies to treat BC and other cancers

A multidimensional platform for the purification of non-coding RNA species

A renewed interest in non-coding RNA (ncRNA) has led to the discovery of novel RNA species and post-transcriptional ribonucleoside modifications, and an emerging appreciation for the role of ncRNA in RNA epigenetics. Although much can be learned by amplification-based analysis of ncRNA sequence and quantity, there is a significant need for direct analysis of RNA, which has led to numerous methods for purification of specific ncRNA molecules. However, no single method allows purification of the full range of cellular ncRNA species. To this end, we developed a multidimensional chromatographic platform to resolve, isolate and quantify all canonical ncRNAs in a single sample of cells or tissue, as well as novel ncRNA species. The applicability of the platform is demonstrated in analyses of ncRNA from bacteria, human cells and plasmodium-infected reticulocytes, as well as a viral RNA genome. Among the many potential applications of this platform are a system-level analysis of the dozens of modified ribonucleosides in ncRNA, characterization of novel long ncRNA species, enhanced detection of rare transcript variants and analysis of viral genomes.Singapore-MIT Alliance for Research and TechnologyNational Institute of Environmental Health Sciences (ES017010)National Institute of Environmental Health Sciences (ES002109

Development and validation of a nomogram for assessing survival in patients with COVID-19 pneumonia

Background: The outbreak of coronavirus disease (COVID-19) in 2019 has spread worldwide and continues to cause great threat to peoples’ health as well as put pressure on the accessibility of medical systems. Early prediction of survival of hospitalized patients will help the clinical management of COVID-19, but such a prediction model which is reliable and valid is still lacking. Methods: We retrospectively enrolled 628 confirmed cases of COVID-19 using positive RT-PCR tests for SARS-CoV-2 in Tongji Hospital in Wuhan, China. These patients were randomly grouped into a training cohort (60%) and a validation cohort (40%). In the training cohort, least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression analysis were utilized to identify prognostic factors for in-hospital survival of patients with COVID-19. A nomogram based on the three variables was built for clinical use. Areas under the ROC curves (AUC), concordance index (C-index) and calibration curve were used to evaluate the efficiency of the nomogram in both the training and validation cohorts. Results: Hypertension, higher neutrophil-to-lymphocyte ratio and increased NT-proBNP value were found to be significantly associated with poorer prognosis in hospitalized patients with COVID-19. The three predictors were further used to build a prediction nomogram. The C-index of the nomogram in the training and validation cohorts was 0.901 and 0.892, respectively. The AUC in the training cohort was 0.922 for 14- day and 0.919 for 21-day probability of in-hospital survival, while in the validation cohort was 0.922 and 0.881, respectively. Moreover, the calibration curve for 14- day and 21-day survival also showed high coherence between the predicted and actual probability of survival. Conclusion: We managed to build a predictive model and constructed a nomogram for predicting in-hospital survival of patients with COVID-19. This model represents good performance and might be utilized clinically in the management of COVID-19. Keywords: Coronavirus; COVID-19; nomogram; prediction; surviva