Characterization and Comparative Analysis of Small RNAs in Three Small RNA Libraries of the Brown Planthopper (Nilaparvata lugens)

BACKGROUND: The brown planthopper (BPH), Nilaparvata lugens (Stå;l), which belongs to Homopteran, Delphacidae, is one of the most serious and destructive pests of rice. Feeding BPH with homologous dsRNA in vitro can lead to the death of BPH, which gives a valuable clue to the prevention and control of this pest, however, we know little about its small RNA world. METHODOLOGY/PRINCIPAL FINDINGS: Small RNA libraries for three developmental stages of BPH (CX-male adult, CC-female adult, CY-last instar female nymph) had been constructed and sequenced. It revealed a prolific small RNA world of BPH. We obtained a final list of 452 (CX), 430 (CC), and 381 (CY) conserved microRNAs (miRNAs), respectively, as well as a total of 71 new miRNAs in the three libraries. All the miRNAs had their own expression profiles in the three libraries. The phylogenic evolution of the miRNA families in BPH was consistent with other species. The new miRNA sequences demonstrated some base biases. CONCLUSION: Our study discovered a large number of small RNAs through deep sequencing of three small RNA libraries of BPH. Many animal-conserved miRNA families as well as some novel miRNAs have been detected in our libraries. This is the first achievement to discover the small RNA world of BPH. A lot of new valuable information about BPH small RNAs has been revealed which was helpful for studying insect molecular biology and insect resistant research

The Tractor and Semitrailer Routing Considering Carbon Dioxide Emissions

The incorporation of the minimization of carbon dioxide (CO2) emissions in the VRP is important to logistics companies. The paper deals with the tractor and semitrailer routing problem with full truckload between any two depots of the network; an integer programming model with the objective of minimizing CO2 emissions per ton-kilometer is proposed. A two-stage approach with the same core steps of the simulated annealing (SA) in both stages is designed. The number of tractors is provided in the first stage and the CO2 emissions per ton-kilometer are then optimized in the second stage. Computational experiments on small-scale randomly generated instances supported the feasibility and validity of the heuristic algorithm. To a practical-scale problem, the SA algorithm can provide advice on the number of tractors, the routes, and the location of the central depot to realize CO2 emissions decrease

Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

Potential crowd flow prediction for new planned transportation sites is a fundamental task for urban planners and administrators. Intuitively, the potential crowd flow of the new coming site can be implied by exploring the nearby sites. However, the transportation modes of nearby sites (e.g. bus stations, bicycle stations) might be different from the target site (e.g. subway station), which results in severe data scarcity issues. To this end, we propose a data driven approach, named MOHER, to predict the potential crowd flow in a certain mode for a new planned site. Specifically, we first identify the neighbor regions of the target site by examining the geographical proximity as well as the urban function similarity. Then, to aggregate these heterogeneous relations, we devise a cross-mode relational GCN, a novel relation-specific transformation model, which can learn not only the correlations but also the differences between different transportation modes. Afterward, we design an aggregator for inductive potential flow representation. Finally, an LTSM module is used for sequential flow prediction. Extensive experiments on real-world data sets demonstrate the superiority of the MOHER framework compared with the state-of-the-art algorithms.Comment: Accepted by the 35th AAAI Conference on Artificial Intelligence (AAAI 2021

Optimization of Extraction Process of Polysaccharide from Sophora japonica by Compound Enzyme Method and Its Antioxidant Activity

Objective: Sophora japonica polysaccharides were extracted by compound enzyme method, and the extraction process was optimized. The antioxidant activity in vitro was evaluated. Methods: The effects of addition amount of compound enzyme, pH, proportion of compound enzyme and enzymatic hydrolysis time on the extraction yield were investigated by single factor experiment. On the basic of single factor experiment, response surface method was used to determine the optimal extraction parameters of Sophora japonica polysaccharide. Compared with VC, the antioxidant activity of Sophora japonica polysaccharides was investigated by measuring the scavenging rate of DPPH· and ABTS+· and the total reducing power. Results: The optimal extraction parameters of Sophora japonica polysaccharides were as follows: The addition amount of compound enzyme was 23.8 mg/g, pH4.8, and the ratio of pectinase to cellulase was 0.912:1. Under this process, the yield of Sophora japonica polysaccharides was 10.71%, and the extracted polysaccharide showed good scavenging ability for DPPH· and ABTS+·. When the concentration of the polysaccharide solution was 2.8 mg/mL, the scavenging rate of DPPH· and ABTS+· reached 94.19% and 99.79% of VC at the same concentration, respectively, and the total reducing power reached 75.99% of VC. Conclution: Sophora japonica polysaccharide could be effectively extracted by compound enzymatic method and its antioxidant activity could be improved, which provided a theoretical reference for the development of functional food of Sophora japonica polysaccharide

A study of clinical and serological correlation of early myocardial injury in elderly patients infected with the Omicron variant

IntroductionMyocardial injury in elderly Omicron variant patients is a leading cause of severe disease and death. This study focuses on elucidating the clinical characteristics and potential risk factors associated with myocardial injury in elderly patients infected with the Omicron variant.MethodsMyocardial injury was defined based on elevated cardiac troponin concentrations exceeding the 99th percentile upper reference limit. Among 772 elderly Omicron-infected patients, categorized into myocardial injury (n = 263) and non-myocardial injury (n = 509) groups. The stratified log-rank statistic was used to compare the probability of patients developing intensive care. Receiver operating characteristic curves were used to determine the best cut-off values of clinical and laboratory data for predicting myocardial injury. Univariate and multivariate logistic regression was adopted to analyze the risk factors for myocardial injury.ResultsThe occurrence of myocardial injury in Omicron variant-infected geriatric patients was up to 34.07% and these patients may have a higher rate of requiring intensive care (P < 0.05). By comparing myocardial injury patients with non-myocardial injury patients, notable differences were observed in age, pre-existing medical conditions (e.g., hypertension, coronary heart disease, cerebrovascular disease, arrhythmia, chronic kidney disease, and heart failure), and various laboratory biomarkers, including cycle threshold-ORF1ab gene (Ct-ORF1ab), cycle threshold-N gene (Ct-N), white blood cell count, neutrophil (NEUT) count, NEUT%, lymphocyte (LYM) count, LYM%, and D-dimer, interleukin-6, procalcitonin, C-reactive protein, serum amyloid A, total protein, lactate dehydrogenase, aspartate aminotransferase, glomerular filtration rate, blood urea nitrogen, and serum creatinine (sCr) levels (P < 0.05). Furthermore, in the multivariable logistic regression, we identified potential risk factors for myocardial injury in Omicron variant–infected elderly patients, including advanced age, pre-existing coronary artery disease, interleukin-6 > 22.69 pg/ml, procalcitonin > 0.0435 ng/ml, D-dimer > 0.615 mg/L, and sCr > 81.30 μmol/L.ConclusionThis study revealed the clinical characteristics and potential risk factors associated with myocardial injury that enable early diagnosis of myocardial injury in Omicron variant-infected elderly patients, providing important reference indicators for early diagnosis and timely clinical intervention

PRIMA-1Met suppresses colorectal cancer independent of p53 by targeting MEK

This work was supported by Grant No. 81201779 (Hua Xiong) from the National Natural Science Youth Foundation; Grant No. 81502118 (Yanmei Zou) from the National Natural Science Youth Foundation; Grant No. 2014CFB250 (Yanmei Zou) from the Natural Science Foundation of Hubei Province; Grant No. 81372434 (Huihua Xiong) from the National Natural Science Foundation.PRIMA-1Met is the methylated PRIMA-1 (p53 reactivation and induction of massive apoptosis) and could restore tumor suppressor function of mutant p53 and induce p53 dependent apoptosis in cancer cells harboring mutant p53. However, p53 independent activity of PRIMA-1Met remains elusive. Here we reported that PRIMA-1Met attenuated colorectal cancer cell growth irrespective of p53 status. Kinase profiling revealed that mitogen-activated or extracellular signal-related protein kinase (MEK) might be a potential target of PRIMA-1Met. Pull-down binding and ATP competitive assay showed that PRIMA-1Met directly bound MEK in vitro and in cells. Furthermore, the direct binding sites of PRIMA-1Met were explored by using a computational docking model. Treatment of colorectal cancer cells with PRIMA-1Met inhibited p53-independent phosphorylation of MEK, which in turn impaired anchorage-independent cell growth in vitro. Moreover, PRIMA-1Met suppressed colorectal cancer growth in xenograft mouse model by inhibiting MEK1 activity. Taken together, our findings demonstrate a novel p53-independent activity of PRIMA-1Met to inhibit MEK and suppress colorectal cancer growth.Publisher PDFPeer reviewe