Identification of molecular genetic factors that influence migraine

Migraine is a common neurological disorder with a strong genetic basis. However, the complex nature of the disorder has meant that few genes or susceptibility loci have been identified and replicated consistently to confirm their involvement in migraine. Approaches to genetic studies of the disorder have included analysis of the rare migraine subtype, familial hemiplegic migraine with several causal genes identified for this severe subtype. However, the exact genetic contributors to the more common migraine subtypes are still to be deciphered. Genome-wide studies such as genome-wide association studies and linkage analysis as well as candidate genes studies have been employed to investigate genes involved in common migraine. Neurological, hormonal and vascular genes are all considered key factors in the pathophysiology of migraine and are a focus of many of these studies. It is clear that the influence of individual genes on the expression of this disorder will vary. Furthermore, the disorder may be dependent on gene–gene and gene–environment interactions that have not yet been considered. In addition, identifying susceptibility genes may require phenotyping methods outside of the International Classification of Headache Disorders II criteria, such as trait component analysis and latent class analysis to better define the ambit of migraine expression.     

Gene expression data analysis

Microarrays are one of the latest breakthroughs in experimental molecular biology, which allow monitoring of gene expression for tens of thousands of genes in parallel and are already producing huge amounts of valuable data. Analysis and handling of such data is becoming one of the major bottlenecks in the utilization of the technology. The raw microarray data are images, which have to be transformed into gene expression matrices, tables where rows represent genes, columns represent various samples such as tissues or experimental conditions, and numbers in each cell characterize the expression level of the particular gene in the particular sample. These matrices have to be analyzed further if any knowledge about the underlying biological processes is to be extracted. In this paper we concentrate on discussing bioinformatics methods used for such analysis. We briefly discuss supervised and unsupervised data analysis and its applications, such as predicting gene function classes and cancer classification as well as some possible future directions.     

Immigration,remittances, and transnational social capital formation: a Cuban case study

Social capital takes on distinctive meaning in the context of large-scale immigration from poor to rich countries. In this article, characteristics of social capital embedded in transnational networks and norms, conditions conducive to the formation of such networks, and effects such networks have are extrapolated from an analysis of how and why cross-border relations among Cuban-Americans and Cubans in their homeland have changed since the 1959 Castro-led revolution. The transnational social capital generating benefit on which the study focuses is remittances. Remittances are of growing global importance to less developed countries, and in some countries they generate more revenue than foreign aid and foreign investment. The analysis addresses a range of unintended as well as intended consequences remittances may have.     

Separation methods for anthraquinone related anti-cancer drugs

The quinoid anthracycline-related anti-cancer agents represent an important group of anti-tumour drugs with a wide spectrum of activity. We review here some of the separation techniques used for the analysis of anthracyclines and related compounds. In this review we have covered a range of compounds from the early anthracycline antibiotics such as doxorubicin to the more recent anthracenediones and anthrapyrazoles such as mitoxantrone and losoxantrone, respectively. We also include novel compounds such as AQ4N and C1311, both awaiting clinical trial. Separations of the anthraquinone related anti-cancer agents are predominantly by HPLC. These separation techniques have been used for a variety of applications including drug stability, protein binding and therapeutic drug monitoring as well as detailed pharmacokinetic and metabolic studies. Pharmacokinetics, and therefore drug analysis, plays a central role in both the development of new agents and also leads to a better understanding of clinically established agents in this class. Sample preparation and extraction methods including solid-phase and liquid–liquid extraction have also been highlighted. Many anthraquinone related compounds are highly coloured and fluoresce. They are suitable for a range of detection methods including UV–Vis, electrochemical and fluorescence. The methods described are used for sometimes complex separations that are needed for the evaluation of such compounds in biological samples.     

Congenic mice: cutting tools for complex immune disorders

Autoimmune diseases are, in general, under complex genetic control and subject to strong interactions between genetics and the environment. Greater knowledge of the underlying genetics will provide immunologists with a framework for study of the immune dysregulation that occurs in such diseases. Ascertaining the number of genes that are involved and their characterization have, however, proven to be difficult. Improved methods of genetic analysis and the availability of a draft sequence of the complete mouse genome have markedly improved the outlook for such research, and they have emphasized the advantages of mice as a model system. In this review, we provide an overview of the genetic analysis of autoimmune diseases and of the crucial role of congenic and consomic mouse strains in such research.     

Improved properties of systems for computer-assisted motility analysis]

For a number of years, computer-assisted methods have been employed for the motility analysis of spermatozoa. In addition to a number of advantages, such as short processing time and good reproducibility, they have certain shortcomings in the recognition and tracking of spermatozoa at high densities. For example, sperm cells and contaminating particles of the same size cannot be distinguished. The tracking of crossing sperm cell trajectories is also a problem. For this reason, procedures that are free from such shortcomings have been introduced. Their application leads to an improvement in the performance of computer-assisted semen analysis methods.     

Proteomics applied to exercise physiology: a cutting-edge technology

Exercise research has always drawn the attention of the scientific community because it can be widely applied to sport training, health improvement, and disease prevention. For many years numerous tools have been used to investigate the several physiological adaptations induced by exercise stimuli. Nowadays a closer look at the molecular mechanisms underlying metabolic pathways and muscular and cardiovascular adaptation to exercise are among the new trends in exercise physiology research. Considering this, to further understand these adaptations as well as pathology attenuation by exercise, several studies have been conducted using molecular investigations, and this trend looks set to continue. Through enormous biotechnological advances, proteomic tools have facilitated protein analysis within complex biological samples such as plasma and tissue, commonly used in exercise research. Until now, classic proteomic tools such as one- and two-dimensional polyacrylamide gel electrophoresis have been used as standard approaches to investigate proteome modulation by exercise. Furthermore, other recently developed in gel tools such as differential gel electrophoresis (DIGE) and gel-free techniques such as the protein labeling methods (ICAT, SILAC, and iTRAQ) have empowered proteomic quantitative analysis, which may successfully benefit exercise proteomic research. However, despite the three decades of 2-DE development, neither classic nor novel proteomic tools have been convincingly explored by exercise researchers. To this end, this review gives an overview of the directions in which exercise-proteome research is moving and examines the main tools that can be used as a novel strategy in exercise physiology investigation.     

Rapid antibody biosensor assays for environmental analysis

Traditionally, biosensor development has focused on molecules with a defined metabolic role that can be exploited by enzyme-based systems. Antibodies have the ability to move beyond this range of analytes, and are particularly useful in detecting small, hapten molecules. Electrochemically based biosensor developments have been less fruitful in this regard, as enzyme labelling is required, and such assays require the separation from bound and unbound species. These separations and the removal of background signals result in the increased complexity of the assay format, making it unsuitable for rapid sensor analysis. We have developed an electrochemical sensor based on antibodies that does not require the separation of bound and unbound molecules in a competition immunoassay format. This removes the need for several washing and separation steps as is normally employed in this type of assay. This allows single-step immunoassays to be performed using this system, and also allows for the real-time monitoring of antibody-antigen interactions. We have shown that such assays are possible in both batch and flow-injection formats and we are currently developing an assay for the pesticide atrazine. Tentative results show that analysis with this system is possible in the p.p.m. to p.p.b. range.     

Increased frequencies of aberrant sperm as indicators of mutagenic damage in mice.

We have tested the effects of TEM in 3 strains of mice using the sperm morphology assay. In addition, we have made an attempt to evaluate this test system with respect to experimental design, statistical problems and possible interlaboratory differences. Treatment with TEM results in significant increases in the percent of abnormally shaped sperm. These increases are readily detectable in sperm treated as spermatocytes and spermatogonial stages. Our data indicate possible problems associated with inter-laboratory variation in slide analysis. We have found that despite the introduction of such sources of variation, our data were consistent with respect to the effects of TEM. Another area of concern in the sperm morphology test is the presence of "outlier" animals. In our study, such animals comprised 4% of the total number of animals considered. Statistical analysis of the slides from these animals have shown that this problem can be dealt with and that when recognized as such, "outliers" do not effect the outcome of the sperm morphology assay.     

Two-trait-locus linkage analysis: a powerful strategy for mapping complex genetic traits.

Recent advances in molecular biology have provided geneticists with ever-increasing numbers of highly polymorphic genetic markers that have made possible linkage mapping of loci responsible for many human diseases. However, nearly all diseases mapped to date follow clear Mendelian, single-locus segregation patterns. In contrast, many common familial diseases such as diabetes, psoriasis, several forms of cancer, and schizophrenia are familial and appear to have a genetic component but do not exhibit simple Mendelian transmission. More complex models are required to explain the genetics of these important diseases. In this paper, we explore two-trait-locus, two-marker-locus linkage analysis in which two trait loci are mapped simultaneously to separate genetic markers. We compare the utility of this approach to standard one-trait-locus, one-marker-locus linkage analysis with and without allowance for heterogeneity. We also compare the utility of the two-trait-locus, two-marker-locus analysis to two-trait-locus, one-marker-locus linkage analysis. For common diseases, pedigrees are often bilineal, with disease genes entering via two or more unrelated pedigree members. Since such pedigrees often are avoided in linkage studies, we also investigate the relative information content of unilineal and bilineal pedigrees. For the dominant-or-recessive and threshold models that we consider, we find that two-trait-locus, two-marker-locus linkage analysis can provide substantially more linkage information, as measured by expected maximum lod score, than standard one-trait-locus, one-marker-locus methods, even allowing for heterogeneity, while, for a dominant-or-dominant generating model, one-locus models that allow for heterogeneity extract essentially as much information as the two-trait-locus methods. For these three models, we also find that bilineal pedigrees provide sufficient linkage information to warrant their inclusion in such studies. We also discuss strategies for assessing the significance of the two linkages assumed in two-trait-locus, two-marker-locus models.     

Engineering approaches to control and design the in vitro environment towards the reconstruction of organs

In vitro experimental models pertaining to human cells are considered essential for most biological experiments, such as drug development and analysis of disease mechanisms, because of their genetic consistency and ease for detailed and long-term analysis. Recent development of organoid cultures, such as intestine, liver, and kidney cultures, greatly promotes the potential of in vitro experiments. However, conventional culture methods that use manual pipetting have limitations in regenerating complex biosystems. Our body autonomously organizes cells to form a specific tissue shape, and the self-organization process occurs in an extremely systematic manner. In order to emulate this sophisticated process in vitro; first, methodologies for cell culture and organization of in vitro systems need to be updated; second, understanding the self-organizing system is a crucial issue. In this review, recent advancements in engineering technologies to control the microenvironment during cell culture are introduced. Both static and dynamic control have been developed for decades in engineering fields, and the means by which such technologies can help to elucidate and design a biosystem is discussed.     

Gene expression data analysis

Microarrays are one of the latest breakthroughs in experimental molecular biology, which allow monitoring of gene expression for tens of thousands of genes in parallel and are already producing huge amounts of valuable data. Analysis and handling of such data is becoming one of the major bottlenecks in the utilization of the technology. The raw microarray data are images, which have to be transformed into gene expression matrices--tables where rows represent genes, columns represent various samples such as tissues or experimental conditions, and numbers in each cell characterize the expression level of the particular gene in the particular sample. These matrices have to be analyzed further, if any knowledge about the underlying biological processes is to be extracted. In this paper we concentrate on discussing bioinformatics methods used for such analysis. We briefly discuss supervised and unsupervised data analysis and its applications, such as predicting gene function classes and cancer classification. Then we discuss how the gene expression matrix can be used to predict putative regulatory signals in the genome sequences. In conclusion we discuss some possible future directions.     

Global whole-cell FTICR mass spectrometric proteomics analysis of the heat shock response in the radioresistant bacterium Deinococcus radiodurans

The results of previous studies indicated that D. radiodurans mounts a regulated protective response to heat shock, and that expression of more than 130 genes, including classical chaperones such as the groESL and dnaKJ operons and proteases such as clpB are induced in response to elevated temperature. In addition, previous qualitative whole-cell mass spectrometric studies conducted under heat shock conditions indicated global changes in the D. radiodurans proteome. To enable the discovery of novel heat shock inducible proteins as well as gain greater biological insight into the classical heat shock response at the protein level, we undertook the global whole-cell FTICR mass spectrometric proteomics study reported here. We have greatly increased the power of this approach by conducting a large number of replicate experiments in addition to taking a semiquantitative approach to data analysis, finding good reproducibility between replicates. Through this analysis, we have identified with high confidence a core set of classical heat shock proteins whose expression increases dramatically and reproducibly in response to elevated temperature. In addition, we have found that the heat shock proteome includes a large number of induced proteins that have not been identified previously as heat responsive, and have therefore been designated as candidate responders. Finally, our results are consistent with the hypothesis that elevated temperature stress could lead to cross-protection against other related stresses.     

经济系统物质流分析研究述评

作为研究经济系统物质代谢的重要方法,经济系统物质流分析方法近年来在资源与环境管理领域得到了广泛的应用,理论发展非常迅速。对经济系统物质流分析进行了系统综述,以期为更深入的理论研究提供参考。系统回顾了经济系统物质流分析的发展历史,介绍了其核算框架和指标体系。重点对经济系统物质流分析的研究现状进行了总结和述评,研究表明:(1)在经济系统物质流分析指标的核算研究方面:国家层面的核算研究多、方法较为成熟,而区域层面的核算研究尚未形成成熟的核算框架;针对直接流指标的核算研究多,而包含间接流或隐藏流的综合指标的核算方法研究不足;(2)在经济系统物质流分析指标的变化原因研究方面,目前的研究较少,研究方法包括分解分析法和回归分析法:前者多基于IPAT方程的直接分解法,难以考察经济系统内部的结构和技术的变化对经济系统物质流分析指标的影响,而后者则在所识别的经济系统物质流分析指标的影响因素方面具有较大差异。提出了经济系统物质流分析的未来研究方向。     

Understanding flux in plant metabolic networks

The revolutionary growth in our ability to identify the 'parts list' of cellular infrastructure in plants in detail, and to alter it with precision, challenges us to develop methods to quantify how these parts function. For components of metabolism, this means mapping fluxes at the level of metabolic networks. Advances in experimental, analytical and software tools for metabolic flux analysis now allow maps of the fluxes through central metabolism to be obtained from the results of stable-isotope-labeling experiments. Such maps have led to notable successes in understanding and engineering metabolic function in microorganisms. Recent studies in plants are giving insight into particular fluxes, such as those of the pentose phosphate pathway, and into general phenomena, such as substrate- or futile-cycles and compartmentation. The importance of experimental design and statistical analysis have been illustrated, and analyses of fluxes in heterotrophic plant tissues have been carried out recently.     

Chromosomal rearrangements,genome reorganization,and speciation

Historical analysis of studying chromosome changes in evolution allows better understanding of the current level of research in this area. Reorganizations of the genetic system due to chromosomal rearrangements have important evolutionary consequences and may lead to speciation. Despite the complexity of evaluating the primacy of chromosome changes in speciation events, such phenomena are possible and occur in nature, as recent studies have demonstrated.     

Applications of commercial biosensors in clinical,food, environmental,and biothreat/biowarfare analyses

The lack of specific, low-cost, rapid, sensitive, and easy detection of biomolecules has resulted in the development of biosensor technology. Innovations in biosensor technology have enabled many biosensors to be commercialized and have enabled biomolecules to be detected onsite. Moreover, the emerging technologies of lab-on-a-chip microdevices and nanosensors offer opportunities for the development of new biosensors with much better performance. Biosensors were first introduced into the laboratory by Clark and Lyons. They developed the first glucose biosensor for laboratory conditions. Then in 1973, a glucose biosensor was commercialized by Yellow Springs Instruments. The commercial biosensors have small size and simple construction and they are ideal for point-of-care biosensing. In addition to glucose, a wide variety of metabolites such as lactate, cholesterol, and creatinine can be detected by using commercial biosensors. Like the glucose biosensors (tests) other commercial tests such as for pregnancy (hCG), Escherichia coli O157, influenza A and B viruses, Helicobacter pylori, human immunodeficiency virus, tuberculosis, and malaria have achieved success. Apart from their use in clinical analysis, commercial tests are also used in environmental (such as biochemical oxygen demand, nitrate, pesticide), food (such as glutamate, glutamine, sucrose, lactose, alcohol, ascorbic acid), and biothreat/biowarfare (Bacillus anthracis, Salmonella, Botulinum toxin) analysis. In this review, commercial biosensors in clinical, environmental, food, and biowarfare analysis are summarized and the commercial biosensors are compared in terms of their important characteristics. This is the first review in which all the commercially available tests are compiled together.     

A modified method for whole exome resequencing from minimal amounts of starting DNA

Next generation DNA sequencing (NGS) technologies have revolutionized the pace at which whole genome and exome sequences can be generated. However, despite these advances, many of the methods for targeted resequencing, such as the generation of high-depth exome sequences, are somewhat limited by the relatively large amounts of starting DNA that are normally required. In the case of tumour analysis this is particularly pertinent as many tumour biopsies often return submicrogram quantities of DNA, especially when tumours are microdissected prior to analysis. Here, we present a method for exome capture and resequencing using as little as 50 ng of starting DNA. The sequencing libraries generated by this minimal starting amount (MSA-Cap) method generate datasets that are comparable to standard amount (SA) whole exome libraries that use three micrograms of starting DNA. This method, which can be performed in most laboratories using commonly available reagents, has the potential to enhance large scale profiling efforts such as the resequencing of tumour exomes.