Stem cell biology and drug discovery

There are many reasons to be interested in stem cells, one of the most prominent being their potential use in finding better drugs to treat human disease. This article focuses on how this may be implemented. Recent advances in the production of reprogrammed adult cells and their regulated differentiation to disease-relevant cells are presented, and diseases that have been modeled using these methods are discussed. Remaining difficulties are highlighted, as are new therapeutic insights that have emerged.     

The East Indian Diaspora in Costa Rica: Inbreeding Avoidance, Marriage Patterns, and Cultural Survival

Anthropologists have long been interested in the survival of Indian cultural traits in the New World. In this article, we present results of an ongoing project with a Costa Rican community that descends from East Indian indentured servants. We focus on the group's marriage patterns and how these patterns might have helped keep the community as a cohesive ethnic group. We investigate the group's level of inbreeding by computing the inbreeding coefficient using two different methods. We show that the community has been successful at keeping its inbreeding low, despite its small size, by allowing marriage with nonmembers of the community. We propose that unless consanguineous marriages are allowed virtually all of the community's marriages will be with noncommunity members. Absorption into tourism, as well as the community's staunch avoidance of consanguineous marriages and virtually universal marriage with noncommunity members, will likely contribute to their disappearance as a viable ethnic group.     

Bayesian data analysis in population ecology: motivations,methods, and benefits

During the 20th century ecologists largely relied on the frequentist system of inference for the analysis of their data. However, in the past few decades ecologists have become increasingly interested in the use of Bayesian methods of data analysis. In this article I provide guidance to ecologists who would like to decide whether Bayesian methods can be used to improve their conclusions and predictions. I begin by providing a concise summary of Bayesian methods of analysis, including a comparison of differences between Bayesian and frequentist approaches to inference when using hierarchical models. Next I provide a list of problems where Bayesian methods of analysis may arguably be preferred over frequentist methods. These problems are usually encountered in analyses based on hierarchical models of data. I describe the essentials required for applying modern methods of Bayesian computation, and I use real-world examples to illustrate these methods. I conclude by summarizing what I perceive to be the main strengths and weaknesses of using Bayesian methods to solve ecological inference problems.     

Cognitive neuroscience and the law

Advances in cognitive neuroscience now allow us to use physiological techniques to measure and assess mental states under a growing set of circumstances. The implication of this growing ability has not been lost on the western legal community. If biologists can accurately measure mental state, then legal conflicts that turn on the true mental states of individuals might well be resolvable with techniques ranging from electroencephalography to functional magnetic resonance imaging. Therefore, legal practitioners have increasingly sought to employ cognitive neuroscientific methods and data as evidence to influence legal proceedings. This poses a risk, because these scientific methodologies have largely been designed and validated for experimental use only. Their subsequent use in legal proceedings is an application for which they were not intended, and for which those methods are inadequately tested. We propose that neurobiologists, who might inadvertently contribute to this situation, should be aware of how their papers will be read by the legal community and should play a more active role in educating and engaging with that community.     

Microbial genome mining for accelerated natural products discovery: is a renaissance in the making?

Microbial genome mining is a rapidly developing approach to discover new and novel secondary metabolites for drug discovery. Many advances have been made in the past decade to facilitate genome mining, and these are reviewed in this Special Issue of the Journal of Industrial Microbiology and Biotechnology. In this Introductory Review, we discuss the concept of genome mining and why it is important for the revitalization of natural product discovery; what microbes show the most promise for focused genome mining; how microbial genomes can be mined; how genome mining can be leveraged with other technologies; how progress on genome mining can be accelerated; and who should fund future progress in this promising field. We direct interested readers to more focused reviews on the individual topics in this Special Issue for more detailed summaries on the current state-of-the-art.     

Interspecific Interactions between Primates,Birds, Bats,and Squirrels May Affect Community Composition on Borneo

For several decades, primatologists have been interested in understanding how sympatric primate species are able to coexist. Most of our understanding of primate community ecology derives from the assumption that these animals interact predominantly with other primates. In this study, we investigate to what extent multiple community assembly hypotheses consistent with this assumption are supported when tested with communities of primates in isolation versus with communities of primates, birds, bats, and squirrels together. We focus on vertebrate communities on the island of Borneo, where we examine the determinants of presence or absence of species, and how these communities are structured. We test for checkerboard distributions, guild proportionality, and Fox's assembly rule for favored states, and predict that statistical signals reflecting interactions between ecologically similar species will be stronger when nonprimate taxa are included in analyses. We found strong support for checkerboard distributions in several communities, particularly when taxonomic groups were combined, and after controlling for habitat effects. We found evidence of guild proportionality in some communities, but did not find significant support for Fox's assembly rule in any of the communities examined. These results demonstrate the presence of vertebrate community structure that is ecologically determined rather than randomly generated, which is a finding consistent with the interpretation that interactions within and between these taxonomic groups may have shaped species composition in these communities. This research highlights the importance of considering the broader vertebrate communities with which primates co‐occur, and so we urge primatologists to explicitly consider nonprimate taxa in the study of primate ecology. Am. J. Primatol. 75:170‐185, 2013. © 2012 Wiley Periodicals, Inc.     

Improving the Network Scale-Up Estimator: Incorporating Means of Sums,Recursive Back Estimation,and Sampling Weights

Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM) provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations) via traditional survey tools such as telephone or mail surveys—by asking a representative sample to estimate the number of people they know who are members of such a “hidden” subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation “trimming” to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights.     

Conjugation of plasminogen activators and fibrin-specific antibodies to improve thrombolytic therapeutic agents.

Here we have reviewed chemical and recombinant approaches to the construction of hybrid molecules that combine a "targeting" antibody and an "effector" enzyme activity. There are advantages and disadvantages to both chemical and recombinant methods, and one goal of this review has been to elucidate these so that the appropriate method can be used by those interested in using hybrid molecules to study questions of basic or therapeutic importance. The system studied in greatest detail has as its goal the targeting of a plasminogen activator to an occlusive intravascular thrombus. We have, therefore, used this system as an example of currently available approaches. Now that these methodologies have been studied and put into use, it is anticipated that this principle will be generalized both to other therapeutic applications, as well as to the design and construction of molecules that will allow more basic questions to be addressed.     

Simulation and study of the geometric parameters in the inguinal area and the genesis of inguinal hernias

We are interested in studying the genesis of a very common pathology: the human inguinal hernia. How the human inguinal hernia appears is not definitively clear, but it is accepted that it is caused by a combination of mechanical and biochemical alterations, and that muscular simulation plays an important role in this. This study proposes a model to explain how some physical parameters affect the ability to simulate the region dynamically and how these parameters are involved in generating inguinal hernias. We are particularly interested in understanding the mechanical alterations in the inguinal region because little is known about them or how they behave dynamically. Our model corroborates the most important theories regarding the generation of inguinal hernias and is an initial approach to numerically evaluating this affection.     

Simulation and study of the geometric parameters in the inguinal area and the genesis of inguinal hernias

We are interested in studying the genesis of a very common pathology: the human inguinal hernia. How the human inguinal hernia appears is not definitively clear, but it is accepted that it is caused by a combination of mechanical and biochemical alterations, and that muscular simulation plays an important role in this. This study proposes a model to explain how some physical parameters affect the ability to simulate the region dynamically and how these parameters are involved in generating inguinal hernias. We are particularly interested in understanding the mechanical alterations in the inguinal region because little is known about them or how they behave dynamically. Our model corroborates the most important theories regarding the generation of inguinal hernias and is an initial approach to numerically evaluating this affection.     

Contemporary linkages between EMG, kinetics and stroke rehabilitation.

EMG and kinetic measures have been primary tools in the study of movement and have provided the foundation for much of the work presented in this journal. Recently, novel ways of combining these tools have provided opportunities to examine elements of motor learning and brain plasticity. This presentation reviews the quantification of EMG within the context of transcranial magnetic stimulation. This vehicle permits acquisition of measures that are fundamental to examining prospects for cortical reorganization among patients with stroke and employs a therapeutic approach called "constraint induced therapy" as a model to demonstrate the interpretation of changes in EMG measures among patients with stroke. Moreover, interfacing novel uses of kinetic measurements during functional task performances is highlighted to illustrate how EMG and kinetics can provide further insight into mechanisms related to reacquisition of movement and concomitant changes in plasticity. Clinicians and researchers interested in expanding their use of these measurement tools are encouraged to learn more about application possibilities.     

A general framework for two-stage analysis of genome-wide association studies and its application to case-control studies

Two-stage analyses of genome-wide association studies have been proposed as a means to improving power for designs including family-based association and gene-environment interaction testing. In these analyses, all markers are first screened via a statistic that may not be robust to an underlying assumption, and the markers thus selected are then analyzed in a second stage with a test that is independent from the first stage and is robust to the assumption in question. We give a general formulation of two-stage designs and show how one can use this formulation both to derive existing methods and to improve upon them, opening up a range of possible further applications. We show how using simple regression models in conjunction with external data such as average trait values can improve the power of genome-wide association studies. We focus on case-control studies and show how it is possible to use allele frequencies derived from an external reference to derive a powerful two-stage analysis. An illustration involving the Wellcome Trust Case-Control Consortium data shows several genome-wide-significant associations, subsequently validated, that were not significant in the standard analysis. We give some analytic properties of the methods and discuss some underlying principles.     

Multipoint estimation of genetic maps for human trisomies with one parent or other partial data

Centromeric-mapping methods have been used to investigate the association between altered recombination and meiotic nondisjunction in humans. For trisomies, current methods are based on the genotypes from a trisomic offspring and both parents. Because it is sometimes difficult to obtain samples from both parents and because the ability to use sources of DNA previously not available (e.g., stored paraffin-embedded pathological samples) has increased, we have been interested in creating similar maps for trisomic populations in which one of the parents of the trisomic individual is unavailable for genotyping. In this paper, we derive multipoint likelihoods for both missing-parent data and conventional two-parent data. We find that likelihoods for two-parent data and for data generated without a sample from the correctly disjoining parent can be maximized in exactly the same way but also that missing-parent data has a high frequency of partial data of the same sort produced by intercross matings. Previously published centromeric-mapping methods use incorrect likelihoods for intercross matings and thus can perform poorly on missing-parent data. We wrote a FORTRAN program to maximize our multipoint likelihoods and used it in simulation studies to demonstrate the biases in the previous methods.     

Domain-based identification and analysis of glutamate receptor ion channels and their relatives in prokaryotes

Voltage-gated and ligand-gated ion channels are used in eukaryotic organisms for the purpose of electrochemical signaling. There are prokaryotic homologues to major eukaryotic channels of these sorts, including voltage-gated sodium, potassium, and calcium channels, Ach-receptor and glutamate-receptor channels. The prokaryotic homologues have been less well characterized functionally than their eukaryotic counterparts. In this study we identify likely prokaryotic functional counterparts of eukaryotic glutamate receptor channels by comprehensive analysis of the prokaryotic sequences in the context of known functional domains present in the eukaryotic members of this family. In particular, we searched the nonredundant protein database for all proteins containing the following motif: the two sections of the extracellular glutamate binding domain flanking two transmembrane helices. We discovered 100 prokaryotic sequences containing this motif, with a wide variety of functional annotations. Two groups within this family have the same topology as eukaryotic glutamate receptor channels. Group 1 has a potassium-like selectivity filter. Group 2 is most closely related to eukaryotic glutamate receptor channels. We present analysis of the functional domain architecture for the group of 100, a putative phylogenetic tree, comparison of the protein phylogeny with the corresponding species phylogeny, consideration of the distribution of these proteins among classes of prokaryotes, and orthologous relationships between prokaryotic and human glutamate receptor channels. We introduce a construct called the Evolutionary Domain Network, which represents a putative pathway of domain rearrangements underlying the domain composition of present channels. We believe that scientists interested in ion channels in general, and ligand-gated ion channels in particular, will be interested in this work. The work should also be of interest to bioinformatics researchers who are interested in the use of functional domain-based analysis in evolutionary and functional discovery.     

Hydroponics: A Versatile System to Study Nutrient Allocation and Plant Responses to Nutrient Availability and Exposure to Toxic Elements

Hydroponic systems have been utilized as one of the standard methods for plant biology research and are also used in commercial production for several crops, including lettuce and tomato. Within the plant research community, numerous hydroponic systems have been designed to study plant responses to biotic and abiotic stresses. Here we present a hydroponic protocol that can be easily implemented in laboratories interested in pursuing studies on plant mineral nutrition.This protocol describes the hydroponic system set up in detail and the preparation of plant material for successful experiments. Most of the materials described in this protocol can be found outside scientific supply companies, making the set up for hydroponic experiments less expensive and convenient.The use of a hydroponic growth system is most advantageous in situations where the nutrient media need to be well controlled and when intact roots need to be harvested for downstream applications. We also demonstrate how nutrient concentrations can be modified to induce plant responses to both essential nutrients and toxic non-essential elements.     

Public health: Youth substance use and abuse: challenges and strategies for identification and intervention

Public health initiatives to distribute nicotine replacement therapy free of charge as a means of promoting smoking cessation are ongoing. Are there enough smokers interested in using nicotine replacement therapy to have a substantial impact on the prevalence of smoking if this aid were distributed free to all interested smokers? We conducted a telephone survey of 825 randomly selected daily smokers aged 18 years or older who had smoked at least 10 cigarettes per day at some point in their lives. Overall, 58.9% of the respondents said they would be interested in nicotine replacement therapy if it were offered for free. Of those interested, almost all (93.8%) said that they would use the nicotine replacement therapy to help them quit for good. There were differences in the levels of interest: smokers who intended to quit were more interested in using the nicotine replacement therapy than those who planned to reduce or maintain their smoking.Nicotine replacement therapy significantly increases a smoker''s chances of quitting.¹ It is widely available in Canada and can be obtained over the counter, usually at a cost to the consumer. Several public health initiatives have explored the advantages of free distribution of nicotine replacement therapy as a means of promoting smoking cessation.^2,3 Based on the popularity of these mass distribution efforts, it has been suggested that giving free nicotine replacement therapy to all interested smokers could have an important impact on the prevalence of smoking.²This statement assumes that a substantial proportion of smokers would actually be interested in receiving free nicotine replacement therapy and would use it in an attempt to quit. Previous studies^4,5 have reported a high level of interest among smokers; however, their results may reflect a response bias rather than a true intention to use nicotine replacement therapy. Health care professionals need to know how receptive smokers are to using nicotine replacement therapy. We sought to evaluate smokers'' attitudes by asking novel questions about their interest in receiving free nicotine replacement therapy and what they would do if they received it.     

Designs for single- or multiple-agent phase I trials

Phase I trials of cytotoxic agents in oncology are usually dose-finding studies that involve a single cytotoxic agent. Many statistical methods have been proposed for these trials, all of which are based on the assumption of a monotonic dose-toxicity curve. For single-agent trials, this is a valid assumption. In many trials, however, investigators are interested in finding the maximally tolerated dose based on escalating multiple cytotoxic agents. When there are multiple agents, monotonicity of the dose-toxicity curve is not clearly defined. In this article we present a design for phase I trials in which the toxicity probabilities follow a partial order, meaning that there are pairs of treatments for which the ordering of the toxicity probabilities is not known at the start of the trial. We compare the new design to existing methods for simple orders and investigate the properties of the design for two partial orders.     

Calculating Ordinal Regression Models in SAS and S‐Plus

Although a number of regression models for ordinal responses have been proposed, these models are not widely known and applied in epidemiology and biomedical research. Overviews of these models are either highly technical or consider only a small part of this class of models so that it is difficult to understand the features of the models and to recognize important relations between them. In this paper we give an overview of logistic regression models for ordinal data based upon cumulative and conditional probabilities. We show how the most popular ordinal regression models, namely the proportional odds model and the continuation ratio model, are embedded in the framework of generalized linear models. We describe the characteristics and interpretations of these models and show how the calculations can be performed by means of SAS and S‐Plus. We illustrate and compare the methods by applying them to data of a study investigating the effect of several risk factors on diabetic retinopathy. A special aspect is the violation of the usual assumption of equal slopes which makes the correct application of standard models impossible. We show how to use extensions of the standard models to work adequately with this situation.     

Utility of mass spectrometry for proteome analysis: part II. Ion-activation methods,statistics, bioinformatics and annotation

This is the second article in a series, intended as a tutorial to provide the interested reader with an overview of the concepts not covered in part I, such as: the principles of ion-activation methods, the ability of mass-spectrometric methods to interface with various proteomic strategies, analysis techniques, bioinformatics and data interpretation and annotation. Although these are different topics, it is important that a reader has a basic and collective understanding of all of them for an overall appreciation of how to carry out and analyze a proteomic experiment. Different ion-activation methods for MS/MS, such as collision-induced dissociation (including postsource decay) and surface-induced dissociation, electron capture and electron-transfer dissociation, infrared multiphoton and blackbody infrared radiative dissociation have been discussed since they are used in proteomic research. The high dimensionality of data generated from proteomic studies requires an understanding of the underlying analytical procedures used to obtain these data, as well as the development of improved bioinformatics tools and data-mining approaches for efficient and accurate statistical analyses of biological samples from healthy and diseased individuals, in addition to determining the utility of the interpreted data. Currently available strategies for the analysis of the proteome by mass spectrometry, such as those employed for the analysis of substantially purified proteins and complex peptide mixtures, as well as hypothesis-driven strategies, have been elaborated upon. Processing steps prior to the analysis of mass spectrometry data, statistics and the several informatics steps currently used for the analysis of shotgun proteomic experiments, as well as proteomics ontology, are also discussed.