Immunopharmacology: a new frontier

Immunopharmacology is a hybrid science which has been founded upon the principles, theory, and technical developments of both immunology and pharmacology, but which has a unique identity incorporating both basic and applied areas of research. Basic immunopharmacological research is concerned with the underlying mechanisms by which endogenous and synthetic chemicals interact with the cells of the immune system. Important areas of research include the actions of chemicals such as lymphokines, cytokines, complement, kinins, autacoids, drugs, and even neuropeptides on immune function. Applied immunopharmacology is concerned with the development and testing of new immunomodulatory drugs which will be of benefit to clinical medicine but also as basic research tools. In the past, the two fields of immunology and pharmacology have contributed to each other in many significant ways. Immunology has contributed to pharmacological research by the development of antibodies which are frequently used today as specific probes for the quantitative and qualitative analysis of many different classes of chemicals of interest. Pharmacology has contributed to the field of immunology by providing basic pharmacological information on subjects such as the mediators of hypersensitivity reactions and inflammation. In the future, the truly hybrid field of immunopharmacology promises to have an expanding role in clinical medicine and basic research. This prediction is based on the observation that recombinant lymphokines and newly discovered immunomodulatory substances have begun to enter the clinic in ever increasing numbers. Future immunopharmacological research will include the study of the pharmacology of these lymphokines but also the rational development of new drugs that act as antagonists or agonists for the endogenous lymphokines that normally regulate the immune response.(ABSTRACT TRUNCATED AT 250 WORDS)     

A Segmental Semi Markov Model for protein secondary structure prediction

Hidden Markov Models (HMMs) are practical tools which provide probabilistic base for protein secondary structure prediction. In these models, usually, only the information of the left hand side of an amino acid is considered. Accordingly, these models seem to be inefficient with respect to long range correlations. In this work we discuss a Segmental Semi Markov Model (SSMM) in which the information of both sides of amino acids are considered. It is assumed and seemed reasonable that the information on both sides of an amino acid can provide a suitable tool for measuring dependencies. We consider these dependencies by dividing them into shorter dependencies. Each of these dependency models can be applied for estimating the probability of segments in structural classes. Several conditional probabilities concerning dependency of an amino acid to the residues appeared on its both sides are considered. Based on these conditional probabilities a weighted model is obtained to calculate the probability of each segment in a structure. This results in 2.27% increase in prediction accuracy in comparison with the ordinary Segmental Semi Markov Models, SSMMs. We also compare the performance of our model with that of the Segmental Semi Markov Model introduced by Schmidler et al. [C.S. Schmidler, J.S. Liu, D.L. Brutlag, Bayesian segmentation of protein secondary structure, J. Comp. Biol. 7(1/2) (2000) 233-248]. The calculations show that the overall prediction accuracy of our model is higher than the SSMM introduced by Schmidler.     

基于手机健身数据的城市街道健康服务功能研究

城市街道是城市空间的基本单元,承载着多元的城市生活。本研究基于手机APP共享的健身数据,以街道线性体育活动为研究对象,从健康视角认知街道空间属性和特征。运用VGI-GIS的方法,在信息矢量化和可视化的基础上,从时间和空间2个维度,对城市街道的健康服务功能进行描述。基于运动热点空间的分布格局,研究在空间集聚、建成环境和人群收入3个层面上进行分析。结果表明,街道的空间连续性对健身活动有促进作用,大型公园和高校对健身活动有巨大的吸引力,公交站点对健身活动有多方面的影响,不同收入阶层健身活动差异明显。多元化的热点空间模式为提升街道的健康性提供了因地制宜的可能性。以健康为导向的城市设计探索采用临时封闭街道,在商业和办公区域周边增设户外体育设施等措施,提升街道的健康服务功能。     

内生驱动因素对景感意愿度差异的影响——从城市公园斑块-廊道-基质景观角度

城市绿色空间与人的健康息息相关,新发展阶段人们对城市绿色空间建设提出了更高要求,来满足日益增长的美好生活需要。优化城市绿色空间,维持、提升和增加城市生态系统服务,是景感生态学研究的使命之一,然而以往研究鲜有从人自身的人格属性角度探讨内生驱动因素在景观感知和景观评价中的影响。以景感意愿度作为衡量景观感知和需求的指标,探究内生驱动因素对人的景观感知和行为偏好选择的影响,提出内生驱动因素对人在不同景观类型中的感受存在差异,而且这种差异影响到个体的行为偏好这一假设。以杭州市主城区5座城市公园的"斑块-廊道-基质"景观作为研究对象,以MBTI量表所得的人格类型作为内生驱动因素,将内生驱动因素与景观和行为偏好选择进行有序回归分析,探讨其对景感意愿度的影响。结果表明：基质景观中受访者景感意愿度最强烈,其次为斑块景观,廊道景观中景感意愿度最低;在斑块景观中,ESFP （外向-感官-感性-自然）型、ENFP （外向-畅想-感性-自然）型、ESFJ （外向-感官-感性-控制）型和INFP （内向-畅想-感性-自然）型的人格类型对景感意愿度具有显著相关关系;在廊道景观中,有14种人格类型对景感意愿度具有显著相关关系;在基质景观中,有9种人格类型对景感意愿度具有显著相关关系。研究结果证实了内生驱动因素影响着人们的景感意愿度。在城市景观生态评价、规划和景感营造,以及生态系统服务研究中,不仅需要考虑生态环境因素和人的社会属性,还应考虑到人的内在属性特征,将景感意愿度和内生驱动因素纳入生态规划中。     

A Meta-Analysis of Self-Reported Achievement Goals and Nonself-Report Performance across Three Achievement Domains (Work,Sports, and Education)

During the past three decades, the achievement goal approach to achievement motivation has emerged as an influential area of research, and is dedicated to understanding the reasons behind the individual’s drive to achieve competence and performance. However, the current literature on achievement goals is segmented rather than integrated. That is, citations across the three major and distinct achievement domains (work, education, and sports) are more the exception than the rule and similarities and differences between findings for the different achievement domains have yet to be tested. The purpose of the present study was to examine the relationships between self-reported achievement goals and nonself-report performance through meta-analysis, and the moderating potential of achievement domain. Identifying achievement domain as moderator improves our understanding to which contexts we can (not) generalize conclusions to, it helps to understand seemingly inconsistent findings, and opens avenues for future research on the underlying processes. Because the achievement goal (AG) measure used in a study is partially confounded with achievement domain, we examined the moderating role of this variable as well. Our findings suggest that – overall – approach goals (either mastery or performance) were associated positively with performance attainment, whereas avoidance goals (either mastery or performance) were associated negatively with performance attainment. These relationships were moderated by achievement domain. For example, relative to the education or work domain, in the sports domain, we did not observe negative correlations between avoidance goals and performance. The absence of statistical moderation due to AG measure suggests that the observed moderation of achievement domain cannot be explained by the AG measure utilized. We suggest further steps to integrate the achievement goal literature, and accordingly, to broaden and deepen understanding of performance attainment in competence-relevant settings, including the workplace, the sports field, and the classroom.     

Bayesian sample size determination using commensurate priors to leverage preexperimental data

This paper develops Bayesian sample size formulae for experiments comparing two groups, where relevant preexperimental information from multiple sources can be incorporated in a robust prior to support both the design and analysis. We use commensurate predictive priors for borrowing of information and further place Gamma mixture priors on the precisions to account for preliminary belief about the pairwise (in)commensurability between parameters that underpin the historical and new experiments. Averaged over the probability space of the new experimental data, appropriate sample sizes are found according to criteria that control certain aspects of the posterior distribution, such as the coverage probability or length of a defined density region. Our Bayesian methodology can be applied to circumstances that compare two normal means, proportions, or event times. When nuisance parameters (such as variance) in the new experiment are unknown, a prior distribution can further be specified based on preexperimental data. Exact solutions are available based on most of the criteria considered for Bayesian sample size determination, while a search procedure is described in cases for which there are no closed-form expressions. We illustrate the application of our sample size formulae in the design of clinical trials, where pretrial information is available to be leveraged. Hypothetical data examples, motivated by a rare-disease trial with an elicited expert prior opinion, and a comprehensive performance evaluation of the proposed methodology are presented.     

Use of the glycemic index: effects on feeding patterns and exercise performance

The focus of this paper is on the glycemic index (GI) that provides effectual information on planning nutritional strategies for carbohydrate (CHO) supplementation in exercise. Related research has suggested that the GI can be used as a reference guide for the selection of an ideal CHO supplement in sports nutrition. Recently, the manipulation of GI of CHO supplementation in optimizing athletic performance has provided an exciting new research area in sports nutrition. There is a growing evidence to support the use of the GI in planning the nutritional strategies for CHO supplementation in sports. The optimum CHO availability for exercise has been demonstrated by manipulating the GI of CHO. Research has shown that a low GI CHO-rich meal is a suitable CHO source before prolonged exercise in order to promote the availability of the sustained CHO. In contrast, a high GI CHO-rich meal appears to be beneficial for glycogen storage after the exercise by promoting greater glucose and insulin responses. The prescribed feeding patterns of CHO intake during recovery and prior to exercise on glycogen re-synthesis and exercise metabolism have been studied in the literature. However, the studies on the subject are still limited, leaving some open questions waiting for further empirical evidences. The most significant question is whether CHO supplementation before and after exercise is beneficial when consumed as large feedings or as a series of snacks. Further research is needed on the effect of feeding patterns on exercise performance.     

A Comparison of Two Recorders for Obtaining In-flight Heart Rate Data

Measurement of mental workload has been widely used for evaluation of aircraft design, mission analysis and assessment of pilot performance during flight operations. Heart rate is the psychophysiological measure that has been most frequently used for this purpose. The risk of interference with flight safety and pilot performance, as well as the generally constrained access to flights, make it difficult for researchers to collect in-flight heart rate data. Thus, this study was carried out to investigate whether small, non-intrusive sports recorders can be used for in-flight data collection for research purposes. Data was collected from real and simulated flights with student pilots using the Polar Team System sports recorder and the Vitaport II, a clinical and research recording device. Comparison of the data shows that in-flight heart rate data from the smaller and less intrusive sports recorder have a correlation of.981 with that from the clinical recorder, thus indicating that the sports recorder is reliable and cost-effective for obtaining heart rate data for many research situations.     

Are all prey created equal? A review and synthesis of differential predation on prey in substandard condition

Our understanding of predator-prey interactions in fishes has been influenced largely by research assuming that the condition of the participants is normal. However, fish populations today often reside in anthropogenically altered environments and are subjected to many kinds of stressors, which may reduce their ecological performance by adversely affecting their morphology, physiology, or behaviour. One consequence is that either the predator or prey, or both, may be in a substandard condition at the time of an interaction. We reviewed the literature on predator-prey interactions in fishes where substandard prey were used as experimental groups. Although most of this research indicates that such prey are significantly more vulnerable to predation, prey condition has rarely been considered in ecological theory regarding predator-prey interactions. The causal mechanisms for increased vulnerability of substandard prey to predation include a failure to detect predators, lapses in decision-making, poor fast-start performance, inability to shoal effectively, and increased prey conspicuousness. Despite some problems associated with empirical predator-prey studies using substandard prey, their results can have theoretical and applied uses, such as in ecological modelling or justification of corrective measures to be implemented in the wild. There is a need for more corroborative field experimentation, a better understanding of the causal mechanisms behind differential predation, and increased incorporation of prey condition into the research of predator-prey modellers and theoreticians. If the concept of prey condition is considered in predator-prey interactions, our understanding of how such interactions influence the structure and dynamics of fish communities is likely to change, which should prove beneficial to aquatic ecosystems.     

Current status of transcriptional regulation systems

Many attempts have been undertaken to control transgene activity in mammalian cells. This is of importance for both applied biotechnology and basic research activities. State of the art regulatory systems use elements for transgene regulation which are unrelated to host regulatory networks and thus do not interfere with endogenous activities. Most of these regulation systems consist of transregulators and transregulator responding promoter elements that are derived from non mammalian origin. Apart from the tetracycline (Tet) regulated system which is most widely used for conditional gene expression at the moment, a number of new systems were created. These systems have been significantly refined and their performance makes them suitable for regulating transgenes not only in cellular systems but also in transgenic animals and for human therapeutic use.     

Computational fluid dynamics analysis of cyclist aerodynamics: Performance of different turbulence-modelling and boundary-layer modelling approaches

This study aims at assessing the accuracy of computational fluid dynamics (CFD) for applications in sports aerodynamics, for example for drag predictions of swimmers, cyclists or skiers, by evaluating the applied numerical modelling techniques by means of detailed validation experiments. In this study, a wind-tunnel experiment on a scale model of a cyclist (scale 1:2) is presented. Apart from three-component forces and moments, also high-resolution surface pressure measurements on the scale model’s surface, i.e. at 115 locations, are performed to provide detailed information on the flow field. These data are used to compare the performance of different turbulence-modelling techniques, such as steady Reynolds-averaged Navier–Stokes (RANS), with several k–ε and k–ω turbulence models, and unsteady large-eddy simulation (LES), and also boundary-layer modelling techniques, namely wall functions and low-Reynolds number modelling (LRNM). The commercial CFD code Fluent 6.3 is used for the simulations. The RANS shear-stress transport (SST) k–ω model shows the best overall performance, followed by the more computationally expensive LES. Furthermore, LRNM is clearly preferred over wall functions to model the boundary layer. This study showed that there are more accurate alternatives for evaluating flow around bluff bodies with CFD than the standard k–ε model combined with wall functions, which is often used in CFD studies in sports.     

Data mining on DNA sequences of hepatitis B virus

Extraction of meaningful information from large experimental data sets is a key element in bioinformatics research. One of the challenges is to identify genomic markers in Hepatitis B Virus (HBV) that are associated with HCC (liver cancer) development by comparing the complete genomic sequences of HBV among patients with HCC and those without HCC. In this study, a data mining framework, which includes molecular evolution analysis, clustering, feature selection, classifier learning, and classification, is introduced. Our research group has collected HBV DNA sequences, either genotype B or C, from over 200 patients specifically for this project. In the molecular evolution analysis and clustering, three subgroups have been identified in genotype C and a clustering method has been developed to separate the subgroups. In the feature selection process, potential markers are selected based on Information Gain for further classifier learning. Then, meaningful rules are learned by our algorithm called the Rule Learning, which is based on Evolutionary Algorithm. Also, a new classification method by Nonlinear Integral has been developed. Good performance of this method comes from the use of the fuzzy measure and the relevant nonlinear integral. The nonadditivity of the fuzzy measure reflects the importance of the feature attributes as well as their interactions. These two classifiers give explicit information on the importance of the individual mutated sites and their interactions toward the classification (potential causes of liver cancer in our case). A thorough comparison study of these two methods with existing methods is detailed. For genotype B, genotype C subgroups C1, C2, and C3, important mutation markers (sites) have been found, respectively. These two classification methods have been applied to classify never-seen-before examples for validation. The results show that the classification methods have more than 70 percent accuracy and 80 percent sensitivity for most data sets, which are considered high as an initial scanning method for liver cancer diagnosis.     

Sclerostin concentrations in athletes: role of load and gender

Bone mass is the net product of formation and resorption, which are closely regulated by the equilibrium between endogenous/exogenous factors. Sclerostin inhibits the Wnt canonical signaling and is considered an anti-anabolic factor. We compared sclerostin serum concentrations between genders in athletes belonging to different sport disciplines, characterized by a different weight-bearing, and in their sedentary counterparts in order to study the possible link between bone metabolism in athletes and its peripheral concentration. We also compared sclerostin levels with bone alkaline phosphatase activity, a marker of bone formation. Sixty-one elite athletes, belonging to weight-bearing (15 male rugby players, 11 male enduro racers, 8 female basketball players), high-impact (6 male tennis players, 8 female ice skaters), non weight-bearing sports (13 male cyclists) and 16 sedentary controls were enrolled. Higher levels of sclerostin were found in females. Sclerostin was higher in weight-bearing than in non-weight-bearing disciplines in males. Significant inverse age-related correlation was found. Higher bone alkaline phosphatase activity was observed in females. The young adult elite athlete represents a peculiar physiologic model for studying sclerostin behavior: the applied load increased the marker concentrations, testifying a high bone turnover rate; however, a gender effect is evident.     

Quantifying the Performance of Individual Players in a Team Activity

Background

Teamwork is a fundamental aspect of many human activities, from business to art and from sports to science. Recent research suggest that team work is of crucial importance to cutting-edge scientific research, but little is known about how teamwork leads to greater creativity. Indeed, for many team activities, it is not even clear how to assign credit to individual team members. Remarkably, at least in the context of sports, there is usually a broad consensus on who are the top performers and on what qualifies as an outstanding performance.

Methodology/Principal Findings

In order to determine how individual features can be quantified, and as a test bed for other team-based human activities, we analyze the performance of players in the European Cup 2008 soccer tournament. We develop a network approach that provides a powerful quantification of the contributions of individual players and of overall team performance.

Conclusions/Significance

We hypothesize that generalizations of our approach could be useful in other contexts where quantification of the contributions of individual team members is important.     

Statistical equivalent of the classical TDT for quantitative traits and multivariate phenotypes

Clinical end-point traits are usually governed by quantitative precursors. Hence, there is active research interest in developing statistical methods for association mapping of quantitative traits. Unlike population-based tests for association, family-based tests for transmission disequilibrium are protected against population stratification. In this study, we propose a logistic regression model to test the association for quantitative traits based on a trio design. We show that the method can be viewed as a direct extension of the classical transmission diequilibrium test for binary traits to quantitative traits. We evaluate the performance of our method using extensive simulations and compare it with an existing method, family-based association test. We found that the two methods yield comparable powers if all families are considered. However, unlike FBAT, which yields an inflated rate of false positives when noninformative trios with all three individuals’ heterozygous are removed, our method maintains the correct size without compromising too much on power. We show that our method can be easily modified to incorporate multivariate phenotypes. Here, we applied this method to analyse a quantitative endophenotype associated with alcoholism.     

Testosterone and sport: current perspectives

Testosterone and other anabolic-androgenic steroids enhance athletic performance in men and women. As a result, exogenous androgen is banned from most competitive sports. However, due to variability in endogenous secretion, and similarities with exogenous testosterone, it has been challenging to establish allowable limits for testosterone in competition. Endogenous androgen production is dynamically regulated by both exercise and winning in competition. Furthermore, testosterone may promote athletic performance, not only through its long-term anabolic actions, but also through rapid effects on behavior. In women, excess production of endogenous testosterone due to inborn disorders of sexual development (DSD) may convey a competitive advantage. For many years, female competitors have been subject to tests of sexual genotype and phenotype known as gender verification. Although gender verification has not identified any normal man competing as a woman, this process has identified women athletes with DSD. As understanding of DSD has expanded in recent years, women with DSD are increasingly able to continue athletic competition.     

A dermal niche for multipotent adult skin-derived precursor cells

A fundamental question in stem cell research is whether cultured multipotent adult stem cells represent endogenous multipotent precursor cells. Here we address this question, focusing on SKPs, a cultured adult stem cell from the dermis that generates both neural and mesodermal progeny. We show that SKPs derive from endogenous adult dermal precursors that exhibit properties similar to embryonic neural-crest stem cells. We demonstrate that these endogenous SKPs can first be isolated from skin during embryogenesis and that they persist into adulthood, with a niche in the papillae of hair and whisker follicles. Furthermore, lineage analysis indicates that both hair and whisker follicle dermal papillae contain neural-crest-derived cells, and that SKPs from the whisker pad are of neural-crest origin. We propose that SKPs represent an endogenous embryonic precursor cell that arises in peripheral tissues such as skin during development and maintains multipotency into adulthood.     

The protective role of endogenous bacterial communities in chironomid egg masses and larvae

Insects of the family Chironomidae, also known as chironomids, are distributed worldwide in a variety of water habitats. These insects display a wide range of tolerance toward metals and organic pollutions. Bacterial species known for their ability to degrade toxicants were identified from chironomid egg masses, leading to the hypothesis that bacteria may contribute to the survival of chironomids in polluted environments. To gain a better understanding of the bacterial communities that inhabit chironomids, the endogenous bacteria of egg masses and larvae were studied by 454-pyrosequencing. The microbial community of the egg masses was distinct from that of the larval stage, most likely due to the presence of one dominant bacterial Firmicutes taxon, which consisted of 28% of the total sequence reads from the larvae. This taxon may be an insect symbiont. The bacterial communities of both the egg masses and the larvae were found to include operational taxonomic units, which were closely related to species known as toxicant degraders. Furthermore, various bacterial species with the ability to detoxify metals were isolated from egg masses and larvae. Koch-like postulates were applied to demonstrate that chironomid endogenous bacterial species protect the insect from toxic heavy metals. We conclude that chironomids, which are considered pollution tolerant, are inhabited by stable endogenous bacterial communities that have a role in protecting their hosts from toxicants. This phenomenon, in which bacteria enable the continued existence of their host in hostile environments, may not be restricted only to chironomids.