Probing the pan-genome of Listeria monocytogenes: new insights into intraspecific niche expansion and genomic diversification

Bacterial pathogens often show significant intraspecific variations in ecological fitness, host preference and pathogenic potential to cause infectious disease. The species of Listeria monocytogenes, a facultative intracellular pathogen and the causative agent of human listeriosis, consists of at least three distinct genetic lineages. Two of these lineages predominantly cause human sporadic and epidemic infections, whereas the third lineage has never been implicated in human disease outbreaks despite its overall conservation of many known virulence factors. Here we compare the genomes of 26 L. monocytogenes strains representing the three lineages based on both in silico comparative genomic analysis and high-density, pan-genomic DNA array hybridizations. We uncover 86 genes and 8 small regulatory RNAs that likely make L. monocytogenes lineages differ in carbohydrate utilization and stress resistance during their residence in natural habitats and passage through the host gastrointestinal tract. We also identify 2,330 to 2,456 core genes that define this species along with an open pan-genome pool that contains more than 4,052 genes. Phylogenomic reconstructions based on 3,560 homologous groups allowed robust estimation of phylogenetic relatedness among L. monocytogenes strains. Our pan-genome approach enables accurate co-analysis of DNA sequence and hybridization array data for both core gene estimation and phylogenomics. Application of our method to the pan-genome of L. monocytogenes sheds new insights into the intraspecific niche expansion and evolution of this important foodborne pathogen.https://doi.org/10.1186/1471-2164-11-50

Reproductive toxicity of low level bisphenol A exposures in a two-generation zebrafish assay: Evidence of male-specific effects

Bisphenol A (BPA), a high-volume chemical used to make polycarbonate plastic and epoxy resins, is a ubiquitous contaminant in environment and human body. To investigate the reproductive effects of long-term exposure to low concentrations of BPA, a two-generation study was conducted using the aquatic model species of zebrafish. Our findings revealed that exposure to 1 nM (0.228 μg/L) BPA for continuous two generations resulted in female-biased sex ratio in both F1 and F2 adult population, decreased sperm density, and decreased sperm quality as measured by motility, velocity, ATP content and lipid peroxidation in F1 and F2 males. Females were less sensitive to BPA exposures than males as no adverse effects were found in female gonads or gametes. Delayed hatching at 48 hpf and increased malformation and mortality were found in the offspring from BPA exposed F2, but not F1 parents. Most importantly, the adverse effect on larval development and survival from BPA exposed F2 parents was paternal-specific, resulting mainly from BPA exposed males. Subsequent transcription analysis of F2 male gonads revealed dysregulated mitochondrial biogenesis and significant activation of non-canonical Wnt/planar cell polarity and Wnt/Calcium signaling pathways. Gene expression analysis of larvae from BPA exposed F2 parents showed significant reduced expression of DNA methyltransferases such as dnmt1, dnmt3, and dnmt5. In conclusion, low level BPA exposures for continuous two generations not only affects sex ratio and sperm quantity/quality in F1 and F2 adults, reproductive success in offspring from F2 parents, but also perturbs various molecular pathways potentially contributing to these BPA induced male-specific reproductive defects.This is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/aquatic-toxicology/Keywords: Wnt signaling, BPA, Zebrafish, Chronic exposure, Sperm, Mitochondrial biogenesisKeywords: Wnt signaling, BPA, Zebrafish, Chronic exposure, Sperm, Mitochondrial biogenesi

Group structures facilitate emergency evacuation

The motion of pedestrian crowds can be described as if they are subject to “social forces”. Grouping, as a common phenomenon in pedestrian behaviors, plays a decisive role in affecting evacuation efficiency. Here we propose two different group evacuation (GE) regimes, namely the leaderless GE and leadership GE, to explore the evacuation dynamics of group-structured pedestrians. Simulation results show that elevating sizes or numbers of these groups can promote evacuation efficiency when individuals all try to move fast, in contrast to the case of small desired velocities. More importantly, with the same group size and group number, leadership GE outperforms leaderless GE, implying the positive effect of adopting appropriate community leaders. We hope that these observations could provide some insight into pedestrians' collective action during the evacuation process

A Questionnaire Survey on the Sense of Educational and Social Equities among College Students in China

The sense of equity reflects how fair a domain is as evaluated by those engaging in that domain. It is very meaningful to explore the sense of equity among college students, which are a special group of people. This study carried out a questionnaire survey on the sense of equity among 982 college students in China, from the perspectives of educational equity and social equity. The questions were validated by the 27/73 quantile method, and the survey results were analyzed through one-way analysis of variance (one-way ANOVA). The results showed that the college students could evaluate the sense of equity rather accurately and generally had a higher sense of equity, but failed to sense the social outcome equity well; their sense of social equity was lower than the sense of educational equity; the sense of equity varied between college students in different majors: the science majors had a lower sense of equity than those majoring in liberal arts; some college students had a misunderstanding of equity

A Limited-Memory BFGS Algorithm Based on a Trust-Region Quadratic Model for Large-Scale Nonlinear Equations.

In this paper, a trust-region algorithm is proposed for large-scale nonlinear equations, where the limited-memory BFGS (L-M-BFGS) update matrix is used in the trust-region subproblem to improve the effectiveness of the algorithm for large-scale problems. The global convergence of the presented method is established under suitable conditions. The numerical results of the test problems show that the method is competitive with the norm method

Analysis on Management of Job Burnout of Counselors in Chinese Colleges Based on Game Theory

In Chinese colleges, counselors need to simultaneously engage in teaching and management. The dual responsibilities make them probe to job burnout. To solve the problem, this paper puts forward assumptions about the behavior, income, and cost of counselors, and sets up a game model of burnout governance for college counselors. On this basis, the game between the college and counselors was analyzed under multiple scenarios: the two parties make completely independent decisions; the college is the first mover in the decision-making—— namely the equilibrium of the mixed strategy. Suppose a few colleges decide to improve the counselor management system. Based on the evolutionary game model, the authors discussed the influence of the improvement on all the colleges. The results show that the rational choices of the two parties should be “the college reforms the counselor management system”, while “the counselors work actively and avoid job burnout”; if a few colleges decide to improve the counselor management system, all the other colleges will follow suit, which leads to an improvement of efficient incentive system for college counselors. The research results provide a good reference for the burnout governance of college counselors

Proteomics of the Honeydew from the Brown Planthopper and Green Rice Leafhopper Reveal They Are Rich in Proteins from Insects, Rice Plant and Bacteria

Honeydew is a watery fluid excreted by plant sap-feeding insects. It is a waste product for the insect hosts. However, it plays important roles for other organisms, such as serving as a nutritional source for beneficial insects and bacteria, as well as elicitors and effectors modulating plant responses. In this study, shotgun LC–MS/MS analyses were used to identify the proteins in the honeydew from two important rice hemipteran pests, the brown planthopper (Nilaparvata lugens, BPH) and green rice leafhopper (Nephotettix cincticeps, GRH). A total of 277 and 210 proteins annotated to insect proteins were identified in the BPH and GRH honeydews, respectively. These included saliva proteins that may have similar functions as the saliva proteins, such as calcium-binding proteins and apolipophorin, involved in rice plant defenses. Additionally, a total of 52 and 32 Oryza proteins were identified in the BPH and GRH honeydews, respectively, some of which are involved in the plant immune system, such as Pathogen-Related Protein 10, ascorbate peroxidase, thioredoxin and glutaredoxin. Coincidently, 570 and 494 bacteria proteins were identified from the BPH and GRH honeydews, respectively, which included several well-known proteins involved in the plant immune system: elongation factor Tu, flagellin, GroEL and cold-shock proteins. The results of our study indicate that the insect honeydew is a complex fluid cocktail that contains abundant proteins from insects, plants and microbes, which may be involved in the multitrophic interactions of plants–insects–microbes

All-Dielectric Meta-Surface for Multispectral Photography by Theta Modulation

The traditional theta modulator encodes input information by superimposing Ronchi sub-gratings, which is extremely easy to cause spatial channel overlap that results in bands mixing. In this case, we present an all-dielectric theta modulation meta-surface with a new encoding method, which separates red, green, blue, and achromatic spatial channels on the focal plane. The meta-surface ensures that the positions of focal points are relatively consistent while focusing energy into the sub-wavelength regions. Our study offers a way to facilitate device miniaturization and system integration, which may have an important application in compact multispectral photography only with one detector

Machine learning models based on quantitative dynamic contrast-enhanced MRI parameters assess the expression levels of CD3+, CD4+, and CD8+ tumor-infiltrating lymphocytes in advanced gastric carcinoma

ObjectiveTo explore the effectiveness of machine learning classifiers based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the expression levels of CD3+, CD4+, and CD8+ tumor-infiltrating lymphocytes (TILs) in patients with advanced gastric cancer (AGC).MethodsThis study investigated 103 patients with confirmed AGC through DCE-MRI and immunohistochemical staining. Immunohistochemical staining was used to evaluate CD3+, CD4+, and CD8+ T-cell expression. Utilizing Omni Kinetics software, radiomics features (Ktrans, Kep, and Ve) were extracted and underwent selection via variance threshold, SelectKBest, and LASSO methods. Logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost) are the four classifiers used to build four machine learning (ML) models, and their performance was evaluated using 10-fold cross-validation. The model’s performance was evaluated and compared using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value.ResultsIn terms of CD3+, CD4+, and CD8+ T lymphocyte prediction models, the random forest model outperformed the other classifier models in terms of CD4+ and CD8+ T cell prediction, with AUCs of 0.913 and 0.970 on the training set and 0.904 and 0.908 on the validation set, respectively. In terms of CD3+ T cell prediction, the logistic regression model fared the best, with AUCs on the training and validation sets of 0.872 and 0.817, respectively.ConclusionMachine learning classifiers based on DCE-MRI have the potential to accurately predict CD3+, CD4+, and CD8+ tumor-infiltrating lymphocyte expression levels in patients with AGC