Serological Investigation of Swine Reproductive Failure Diseases in Some Large-Scale Pig Farms in Henan Province

[ Objective] To investigate the prevalence situation of swine reproductive failure diseases in Henan Province and provide reference for the immunization and prevention of swine reproductive failure diseases. [ Method] Between May 2009 and April 2010, all serum samples from the Henan Agriculture University, Animal Disease Detection and Diagnosis Center were detected, including 6 825 serum samples for detecting classical swine fever （CSF） antibody, 2 609 for porcine reproductive and respiratory syndrome （PRRS） antibody, 1 177 for pseudorabies rabies virus gE （PRV） antibody, 123 for porcine parvovirus （PPV） antibody and 53 for chlamydiosis antibody. [ Result] The antibody positive rates of sere for de- tecting above five diseases were 63.28%, 61.44%, 25.49%, 39.84% and 5.66%, respectively. [ Conclusion] The immunization and prevention of CSF, PRRS, PPV and PR in Henan Province needs to be strengthened urgently, and the chlamvdiosis has been effectively controlled.

Dynamic analysis of a sexually transmitted disease model on complex networks

In this paper,a sexually transmitted disease model is proposed on complex networks,where contacts between humans are treated as a scale-free social network.There are three groups in our model,which are dangerous male,non-dangerous male,and female.By mathematical analysis,we obtain the basic reproduction number for the existence of endemic equilibrium and study the effects of various immunization schemes about different groups.Furthermore,numerical simulations are undertaken to verify more conclusions.

In-vitro vs in-vivo Inoculation: Screening for Resistance of Australian Rice Genotypes Against Blast Fungus

To assist with rapid screening for rice blast resistance as a precursor in a breeding program, the susceptibility to rice blast of 13 rice genotypes from Australia was evaluated in May to June 2013 using three distinct inoculation methods（spot, filter paper and standard methods） at seedling, vegetative and reproductive stages. The results revealed that the spot and filter paper inoculation methods were successful in discerning susceptibility to the rice blast disease（P ≤ 0.05）. Disease susceptibility declined significantly from the vegetative to reproductive stages. The standard method was conducted at three different stages for pot plants grown inside the mist house. However, low temperatures did not produce disease symptoms except in a few genotypes. Among the 13 rice genotypes screened, AAT9 expressed a highly resistant response, and AAT4, AAT6, AAT10, AAT11, AAT13, AAT17 and AAT18 expressed resistance at various stages. The results will be useful for selecting elite genotypes for disease tolerance where rice blast is prevalent. In addition, the resistant genotypes can serve as a gene pool used in breeding programmes to develop new resistant genotypes.

Revisiting classical SIR modelling in light of the COVID-19 pandemic

Background:Classical infectious disease models during epidemics have widespread usage,from predicting the probability of new infections to developing vaccination plans for informing policy decisions and public health responses.However,it is important to correctly classify reported data and understand how this impacts estimation of model parameters.The COVID-19 pandemic has provided an abundant amount of data that allow for thorough testing of disease modelling assumptions,as well as how we think about classical infectious disease modelling paradigms.Objective:We aim to assess the appropriateness of model parameter estimates and preiction results in classical infectious disease compartmental modelling frameworks given available data types(infected,active,quarantined,and recovered cases)for situations where just one data type is available to fit the model.Our main focus is on how model prediction results are dependent on data being assigned to the right model compartment.Methods:We first use simulated data to explore parameter reliability and prediction capability with three formulations of the classical Susceptible-Infected-Removed(SIR)modelling framework.We then explore two applications with reported data to assess which data and models are sufficient for reliable model parameter estimation and prediction accuracy:a classical influenza outbreak in a boarding school in England and COVID-19 data from the fall of 2020 in Missoula County,Montana,USA.Results:We demonstrated the magnitude of parameter estimation errors and subsequent prediction errors resulting from data misclassification to model compartments with simulated data.We showed that prediction accuracy in each formulation of the classical disease modelling framework was largely determined by correct data classification versus misclassification.Using a classical example of influenza epidemics in an England boarding school,we argue that the Susceptible-Infected-Quarantined-Recovered(SIQR)model is more appropriate than the commonly employed SIR model given the data collected(number of active cases).Similarly,we show in the COVID-19 disease model example that reported active cases could be used inappropriately in the SIR modelling framework if treated as infected.Conclusions:We demonstrate the role of misclassification of disease data and thus the importance of correctly classifying reported data to the proper compartment using both simulated and real data.For both a classical influenza data set and a COVID-19 case data set,we demonstrate the implications of using the“right”data in the“wrong”model.The importance of correctly classifying reported data will have downstream impacts on predictions of number of infections,as well as minimal vaccination requirements.

Advances of Long Noncoding RNAs-mediated Regulation in Reproduction

Objective： Advances in genomics and molecular biology have led to the discovery of a large group of uncharacterized long noncoding RNAs （lncRNAs）. Emerging evidence indicated that many lncRNAs function in multiple biological processes and its dysregulation otten causes diseases. Recent studies suggested that almost all regulatory lncRNAs interact with biological macromolecules such as DNA, RNA, and protein. LncRNAs regulate gene expression mainly on three levels, including epigenetic modification, transcription, and posttranscription, through DNA methylation, histone modification, and chromatin remodeling. LncRNAs can also affect the development of diseases and tllerefore be used to diagnose and treat diseases. With new sequencing and microarray techniques, hundreds oflncRNAs involved in reproductive disorders have been identified, but their functions in these disorders are undefined. Data Sources： This review was based on articles published in PubMed databases up to July 10, 2017, with the tbllowing keywords： ＂long noncoding RNAs＂, ＂＇LncRNA＂, ＂placentation＂, and ＂＇reproductive diseases＂. Study Selection： Original articles and reviews on the topics were selected. Results： LncRNAs widely participate in various physiological and pathological processes as a new class of important regulatory/＇,actors. In spermatogenesis, spermatocytes divide and differentiate into mature spermatozoa. The whole process is elaborately regulated by the expression of phase-specific genes that involve many strains of lncRNAs. Literature showed that IncRNA in reproductive cumulus cells may contribute to the regulation of oocyte maturation, fertilization, and embryo development. Conclusions： LncRNA has been found to play a role in the development of reproduction. Meanwhile, we reviewed the studies on how lncRNAs participate in reproductive disorders, which provides a basis fbr the study of [ncRNA in reproduction regulation.

Effects of clenbuterol on the expression of adiponectin in 3T3-L1 adipocytes

Objective adiponectin Methods To investigate the effects of clenbuterol （CLB） on the expression of （ADP） in adipocytes. 3T3-L1 pre-adipocytes were induced into mature adipocytes, and then randomly divided into four groups based on doses of CLB： 0 12mol/L （group A, as the control）, 0.5 12mol/L （group B, low-dose group）, 5 μmol/L （group C, mid-dose group）, and 50 μmol/L （group D, high-dose group）, respectively. These four groups were cultured for both 12 h and 24 h. After CLB exposure, the effects of CLB on the expression of ADP in adipocytes were detected by qPCR and Western blotting analysis, and cell viability was quantified by the methyl thiazolyl tetrazolium assay. Results At 12 h, there was no difference in the expression of ADP between group A and group B or C （P〉0.05）. With the increase of CLB doses, the expression level of ADP in group D was lower than that in group A （P〈0.01）. After 24 h of incubation, compared with group A, there was a greater decrease in the expression of ADP in group B （P〈0.05）, and this suppression was more remarkable in group C or D （P〈O.O1）. At 12 h, viability of the cells in group B had no difference compared with group A （P〉 0.05）. A significant decrease of cell viability was counted in group C or D （P〈0.05）. At 24 h, with the increasing doses of CLB, viability of the cells showed more severe decrease in three experimental groups compared with the control （P〈0.01）. Conclusion After CLB exposure, the expression of ADP could be down-regulated and the decrease was more severe with the increasing doses of CLB.