Evaluation of copper, iron and lead substitution techniques in elasmobranch age determination

Copper and lead substitution reactions were found to be useful in demonstrating growth patterns in vertebrae from several elasmobranch species. In contrast, iron substitution was ineffective in detecting variations in vertebral mineralization. The present study provides two alternative methods for elasmobranch age determination that may prove useful when traditional methods are deemed ineffective. However, species-specific variations in the efficiency of these methods reemphasize the observation that different types of vertebrae often require different methods of staining.     

Genetic Mapping in Escherichia coli K-12 by Radiation-Induced Crossing-Over

Conventional methods for chromosomal mapping in Escherichia coli are (i) interruption of matings to obtain minimum marker entry times, (ii) linkage analysis of recombinants, and (iii) cotransduction. Method (i) has a resolution of about 0.5 min (5 x 10(4) nucleotides) and is not useful for distances less than about 1 min; methods (ii) and (iii) are capable of better resolution but are generally not very reproducible and no general theory is available for translating crossing-over and cotransduction frequencies into physical chromosomal distances. We found that when merozygotes are irradiated (X rays or ultraviolet light) soon after marker transfer, high linkage values (0.8 to 1.0) between nearby marker pairs decrease with radiation dose to 0.5. Our results are quantitatively consistent with the idea that radiations induce crossing-over lesions proportional to dose, and the number of such lesions between two markers is proportional to the physical separation of the markers in the range that can also be measured by interruption of mating (0.5 to 4.0 min). Additivity relations among markers are also satisfied. We used this technique to measure the distances (0.1 to 1.0 min) between several pairs of closely linked markers.     

Comparisons of multivariate analytical techniques for use in pre-quaternary plant paleoecology

Multivariate analyses are often used in ecology and have proved to be useful in plant paleoecology and palynology. A variety of different methods are available, but these methods have different mathematical bases and different assumptions about the data to be analyzed, which must be kept in mind when analyzing a particular data set. This paper presents the results of a comparative study of different methods used to analyze a set of fossil megaspore data from the Cretaceous Dakota Formation and discusses the methods from the point of view of the peculiarities of fossil plant data.

Since fossil plant data are often not normally distributed, non-metric methods, such as those based on rank-order or presence/absence, can be useful. The Spearman Rank Order Correlation Coefficient, when used with unweighted pair group average cluster analysis and non-metric multidimensional scaling, was found to give results that were more satisfactory than those obtained using other distance measures. If the investigator wishes to take absolute abundances into account, then minimum-variance cluster analysis and detrended correspondence analysis can be recommended, although the data may need to be log-transformed to reduce skewness. Principal components analysis gave the least satisfactory results. No one method can be considered “the best”; different methods should be used with different types of data. Any investigator using these methods is strongly urged to investigate different methods, their mathematical bases and assumptions and their performance on a certain data set before making a final choice as to the method to use in analyzing the data.     

Magnetic resonance spectroscopy detectable metabolomic fingerprint of response to antineoplastic treatment

Targeted therapeutic approaches are increasingly being implemented in the clinic, but early detection of response frequently presents a challenge as many new therapies lead to inhibition of tumor growth rather than tumor shrinkage. Development of novel non-invasive methods to monitor response to treatment is therefore needed. Magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging are non-invasive imaging methods that can be employed to monitor metabolism, and previous studies indicate that these methods can be useful for monitoring the metabolic consequences of treatment that are associated with early drug target modulation. However, single-metabolite biomarkers are often not specific to a particular therapy. Here we used an unbiased 1H MRS-based metabolomics approach to investigate the overall metabolic consequences of treatment with the phosphoinositide 3-kinase inhibitor LY294002 and the heat shock protein 90 inhibitor 17AAG in prostate and breast cancer cell lines. LY294002 treatment resulted in decreased intracellular lactate, alanine fumarate, phosphocholine and glutathione. Following 17AAG treatment, decreased intracellular lactate, alanine, fumarate and glutamine were also observed but phosphocholine accumulated in every case. Furthermore, citrate, which is typically observed in normal prostate tissue but not in tumors, increased following 17AAG treatment in prostate cells. This approach is likely to provide further information about the complex interactions between signaling and metabolic pathways. It also highlights the potential of MRS-based metabolomics to identify metabolic signatures that can specifically inform on molecular drug action.     

Analysis of DNA-RNA hybridization data using the scatchard plot

DNA-RNA hybridization experiments, especially in eukaryotic systems, are complicated by such factors as large genome size and the difficulty of separating RNA fractions. Current analytical methods can lead to erroneous conclusions since heterogeneity is often obscured and data in the most useful concentration ranges are not readily obtainable. Some of these difficulties can be overcome by using a Scatchard plot which is superior to other methods in preventing common misinterpretations of data resulting from heterogeneous RNA samples or non-specific reaction.     

Comparison and critical evaluation of PCR-mediated methods to walk along the sequence of genomic DNA

Although researchers can access information on the entire genomic DNA sequence of typical research organisms, convenient genome walking methods in the laboratory are still needed. For the analysis of microorganisms, these methods are especially useful because the available genetic information is often scarce or limited. Many genomic walking methods are based on the polymerase chain reaction (PCR), and useful methods have been developed. This report reviews the methodologies of PCR-mediated genomic walking methods and evaluates their efficiency and usefulness to help microbiologists to select the appropriate method for each target microorganism. The concept and specific features, such as advantages and disadvantages, of five major PCR-mediated genomic walking methods (random PCR, inverse PCR, panhandle PCR, cassette PCR, and rapid amplification of genomic ends) are briefly described. The improved methods and their characteristics are listed, and a report of experimental comparison of such methods is also introduced briefly. Each of these methods has both advantages and disadvantages, and there is a trade-off between the specificity of target amplification and the ease of the method. The cassette PCR seems to be a standard method, but suitable method should be selected in consideration of the characteristics of the material.     

Use of a Battery of Chemical and Ecotoxicological Methods for the Assessment of the Efficacy of Wastewater Treatment Processes to Remove Estrogenic Potency

Endocrine Disrupting Compounds pose a substantial risk to the aquatic environment. Ethinylestradiol (EE2) and estrone (E1) have recently been included in a watch list of environmental pollutants under the European Water Framework Directive. Municipal wastewater treatment plants are major contributors to the estrogenic potency of surface waters. Much of the estrogenic potency of wastewater treatment plant (WWTP) effluents can be attributed to the discharge of steroid estrogens including estradiol (E2), EE2 and E1 due to incomplete removal of these substances at the treatment plant. An evaluation of the efficacy of wastewater treatment processes requires the quantitative determination of individual substances most often undertaken using chemical analysis methods. Most frequently used methods include Gas Chromatography-Mass Spectrometry (GCMS/MS) or Liquid Chromatography-Mass Spectrometry (LCMS/MS) using multiple reaction monitoring (MRM). Although very useful for regulatory purposes, targeted chemical analysis can only provide data on the compounds (and specific metabolites) monitored. Ecotoxicology methods additionally ensure that any by-products produced or unknown estrogenic compounds present are also assessed via measurement of their biological activity. A number of in vitro bioassays including the Yeast Estrogen Screen (YES) are available to measure the estrogenic activity of wastewater samples. Chemical analysis in conjunction with in vivo and in vitro bioassays provides a useful toolbox for assessment of the efficacy and suitability of wastewater treatment processes with respect to estrogenic endocrine disrupting compounds. This paper utilizes a battery of chemical and ecotoxicology tests to assess conventional, advanced and emerging wastewater treatment processes in laboratory and field studies.     

SMRT Sequencing of Long Tandem Nucleotide Repeats in SCA10 Reveals Unique Insight of Repeat Expansion Structure

A large, non-coding ATTCT repeat expansion causes the neurodegenerative disorder, spinocerebellar ataxia type 10 (SCA10). In a subset of SCA10 patients, interruption motifs are present at the 5’ end of the expansion and strongly correlate with epileptic seizures. Thus, interruption motifs are a predictor of the epileptic phenotype and are hypothesized to act as a phenotypic modifier in SCA10. Yet, the exact internal sequence structure of SCA10 expansions remains unknown due to limitations in current technologies for sequencing across long extended tracts of tandem nucleotide repeats. We used the third generation sequencing technology, Single Molecule Real Time (SMRT) sequencing, to obtain full-length contiguous expansion sequences, ranging from 2.5 to 4.4 kb in length, from three SCA10 patients with different clinical presentations. We obtained sequence spanning the entire length of the expansion and identified the structure of known and novel interruption motifs within the SCA10 expansion. The exact interruption patterns in expanded SCA10 alleles will allow us to further investigate the potential contributions of these interrupting sequences to the pathogenic modification leading to the epilepsy phenotype in SCA10. Our results also demonstrate that SMRT sequencing is useful for deciphering long tandem repeats that pose as “gaps” in the human genome sequence.     

An empirical Bayesian approach for identifying differential coexpression in high-throughput experiments

A common goal of microarray and related high-throughput genomic experiments is to identify genes that vary across biological condition. Most often this is accomplished by identifying genes with changes in mean expression level, so called differentially expressed (DE) genes, and a number of effective methods for identifying DE genes have been developed. Although useful, these approaches do not accommodate other types of differential regulation. An important example concerns differential coexpression (DC). Investigations of this class of genes are hampered by the large cardinality of the space to be interrogated as well as by influential outliers. As a result, existing DC approaches are often underpowered, exceedingly prone to false discoveries, and/or computationally intractable for even a moderately large number of pairs. To address this, an empirical Bayesian approach for identifying DC gene pairs is developed. The approach provides a false discovery rate controlled list of significant DC gene pairs without sacrificing power. It is applicable within a single study as well as across multiple studies. Computations are greatly facilitated by a modification to the expectation-maximization algorithm and a procedural heuristic. Simulations suggest that the proposed approach outperforms existing methods in far less computational time; and case study results suggest that the approach will likely prove to be a useful complement to current DE methods in high-throughput genomic studies.     

Choriocarcinoma after Hydatidiform Mole. Studies Related to Effectiveness of Follow-up Practice after Hydatidiform Mole

Chemotherapy, in conjunction with other methods of treatment, was used in 100 patients with invasive hydatidiform mole or choriocarcinoma following mole. When treatment was instituted within two to six months of the antecedent mole serious drug resistance was not encountered, drug toxicity was slight, the duration of treatment was comparatively short, and sustained remissions were obtained in 57 out of 60 patients. When the start of chemotherapy was delayed beyond six months drug resistance occurred in many instances, toxicity was often severe, the duration of treatment was much longer, and sustained remissions were obtained in 22 out of 40 patients.The practice of giving prophylactic chemotherapy to all patients with mole is not established as effective or safe. Differences in the social background to hydatidiform mole in different geographical areas may be such that conclusions based on evidence from one area are not necessarily applicable to another.Careful follow-up after mole remains essential, though present methods often fail to ensure recognition of choriocarcinoma while it is still curable. Standard qualitative and quantitative methods for detecting the continued excretion of chorionic gonadotrophin, though useful, are sometimes too insensitive. It is suggested that to supplement local arrangements some form of centralized or regionalized follow-up service based on notification of patients with hydatidiform mole, and making use of radioimmunoassays for chorionic gonadotrophin, could reduce deaths attributable to late diagnosis.     

Confidence intervals for the difference in the success rates of two treatments in the analysis of correlated binary responses

In clinical studies, we often compare the success rates of two treatment groups where post‐treatment responses of subjects within clusters are usually correlated. To estimate the difference between the success rates, interval estimation procedures that do not account for this intraclass correlation are likely inappropriate. To address this issue, we propose three interval procedures by direct extensions of recently proposed methods for independent binary data based on the concepts of design effect and effective sample size used in sample surveys. Each of them is then evaluated with four competing variance estimates. We also extend three existing methods recommended for complex survey data using different weighting schemes required for those three existing methods. An extensive simulation study is conducted for the purposes of evaluating and comparing the performance of the proposed methods in terms of coverage and expected width. The interval estimation procedures are illustrated using three examples in clinical and social science studies. Our analytic arguments and numerical studies suggest that the methods proposed in this work may be useful in clustered data analyses.     

Testing for heterogeneity in the utility of a surrogate marker

In studies that require long-term and/or costly follow-up of participants to evaluate a treatment, there is often interest in identifying and using a surrogate marker to evaluate the treatment effect. While several statistical methods have been proposed to evaluate potential surrogate markers, available methods generally do not account for or address the potential for a surrogate to vary in utility or strength by patient characteristics. Previous work examining surrogate markers has indicated that there may be such heterogeneity, that is, that a surrogate marker may be useful (with respect to capturing the treatment effect on the primary outcome) for some subgroups, but not for others. This heterogeneity is important to understand, particularly if the surrogate is to be used in a future trial to replace the primary outcome. In this paper, we propose an approach and estimation procedures to measure the surrogate strength as a function of a baseline covariate W and thus examine potential heterogeneity in the utility of the surrogate marker with respect to W. Within a potential outcome framework, we quantify the surrogate strength/utility using the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate. We propose testing procedures to test for evidence of heterogeneity, examine finite sample performance of these methods via simulation, and illustrate the methods using AIDS clinical trial data.     

Review of treatment methods to remove Wolbachia bacteria from arthropods

Wolbachia are intracellular bacteria that infect numerous and diverse arthropod species including economic pests of crops and disease vectors affecting livestock and humans. Research on these symbionts has identified profound effects of Wolbachia on their hosts with possible application in pest control. Such research often requires methods to cure infections. To facilitate future research on these bacteria, we reviewed the Wolbachia literature to summarize results of 110 studies spanning 62 taxa that report on treatment methods and outcomes. Application of tetracycline in diet is the most common method and is typically successful. Rifampicin is secondarily used, and may be successful when tetracycline is not. Elevated temperatures can be used to eliminate infections, but is not often used. Rearing hosts under crowded conditions or starvation has been shown to reduce Wolbachia titre which affects maternal transmission. Application of treatment methods has a number of considerations with possible implications for the interpretation of data. This review is intended to alert the reader to treatment options and potential non-target effects.     

Stabilizing effects of interruptions on trinucleotide repeat expansions in Saccharomyces cerevisiae

In most trinucleotide repeat (TNR) diseases, the primary factor determining the likelihood of expansions is the length of the TNR. In some diseases, however, stable alleles contain one to three base pair substitutions that interrupt the TNR tract. The unexpected stability of these alleles compared to the frequent expansions of perfect TNRs suggested that interruptions somehow block expansions and that expansions occur only upon loss of at least one interruption. The work in this study uses a yeast genetic assay to examine the mechanism of stabilization conferred by two interruptions of a 25-repeat tract. Expansion rates are reduced up to 90-fold compared to an uninterrupted allele. Stabilization is greatest when the interruption is replicated early on the lagging strand, relative to the rest of the TNR. Although expansions are infrequent, they are often polar, gaining new DNA within the largest available stretch of perfect repeats. Surprisingly, interruptions are always retained and sometimes even duplicated, suggesting that expansion in yeast cells can proceed without loss of the interruption. These findings support a stabilization model in which interruptions contribute in cis to reduce hairpin formation during TNR replication and thus inhibit expansion rates.     

Prediction of calcium-binding sites by combining loop-modeling with machine learning

Background  

Protein ligand-binding sites in the apo state exhibit structural flexibility. This flexibility often frustrates methods for structure-based recognition of these sites because it leads to the absence of electron density for these critical regions, particularly when they are in surface loops. Methods for recognizing functional sites in these missing loops would be useful for recovering additional functional information.     

Propensity score methods for time-dependent cluster confounding

In observational studies, subjects are often nested within clusters. In medical studies, patients are often treated by doctors and therefore patients are regarded as nested or clustered within doctors. A concern that arises with clustered data is that cluster-level characteristics (e.g., characteristics of the doctor) are associated with both treatment selection and patient outcomes, resulting in cluster-level confounding. Measuring and modeling cluster attributes can be difficult and statistical methods exist to control for all unmeasured cluster characteristics. An assumption of these methods however is that characteristics of the cluster and the effects of those characteristics on the outcome (as well as probability of treatment assignment when using covariate balancing methods) are constant over time. In this paper, we consider methods that relax this assumption and allow for estimation of treatment effects in the presence of unmeasured time-dependent cluster confounding. The methods are based on matching with the propensity score and incorporate unmeasured time-specific cluster effects by performing matching within clusters or using fixed- or random-cluster effects in the propensity score model. The methods are illustrated using data to compare the effectiveness of two total hip devices with respect to survival of the device and a simulation study is performed that compares the proposed methods. One method that was found to perform well is matching within surgeon clusters partitioned by time. Considerations in implementing the proposed methods are discussed.     

Molecular scale architecture: engineered three- and four-way junctions

Biomolecular self-assembly provides a basis for the bottom-up construction of useful and diverse nanoscale architectures. DNA is commonly used to create these assemblies and is often exploited as a lattice or an array. Although geometrically rigid and highly predictable, these sheets of repetitive constructs often lack the ability to be enzymatically manipulated or elongated by standard biochemical techniques. Here, we describe two approaches for the construction of position-controlled, molecular-scale, discrete, three- and four-way DNA junctions. The first approach for constructing these junctions relies on the use of nonmigrating cruciforms generated from synthetic oligonucleotides to which large, biologically generated, double-stranded DNA segments are enzymatically ligated. The second approach utilitizes the DNA methyltransferase-based SMILing (sequence-specific methyltransferase-induced labeling of DNA) method to site-specifically incorporate a biotin within biologically derived DNA. Streptavidin is then used to form junctions between unique DNA strands. The resultant assemblies have precise and predetermined connections with lengths that can be varied by enzymatic or hybridization techniques, or geometrically controlled with standard DNA functionalization methods. These junctions are positioned with single nucleotide resolution on large, micrometer-length templates. Both approaches generate DNA assemblies which are fully compatible with standard recombinant methods and thus provide a novel basis for nanoengineering applications.     

Neutralizing antibodies associated with viremia control in a subset of individuals after treatment of acute human immunodeficiency virus type 1 infection

Immediate treatment of acute human immunodeficiency virus type 1 (HIV-1) infection has been associated with subsequent control of viremia in a subset of patients after therapy cessation, but the immune responses contributing to control have not been fully defined. Here we examined neutralizing antibodies as a correlate of viremia control following treatment interruption in HIV-1-infected individuals in whom highly active antiretriviral therapy (HAART) was initiated during early seroconversion and who remained on therapy for 1 to 3 years. Immediately following treatment interruption, neutralizing antibodies were undetectable with T-cell-line adapted strains and the autologous primary HIV-1 isolate in seven of nine subjects. Env- and Gag-specific antibodies as measured by enzyme-linked immunosorbent assay were also low or undetectable at this time. Despite this apparent poor maturation of the virus-specific B-cell response during HAART, autologous neutralizing antibodies emerged rapidly and correlated with a spontaneous downregulation in rebound viremia following treatment interruption in three subjects. Control of rebound viremia was seen in other subjects in the absence of detectable neutralizing antibodies. The results indicate that virus-specific B-cell priming occurs despite the early institution of HAART, allowing rapid secondary neutralizing-antibody production following treatment interruption in a subset of individuals. Since early HAART limits viral diversification, we hypothesize that potent neutralizing-antibody responses to autologous virus are able to mature and that in some persons these responses contribute to the control of plasma viremia after treatment cessation.     

Genetic approaches to the study of protein-protein interactions.

This article describes genetic approaches to the study of heterologous protein-protein interactions, focusing on the yeast Saccharomyces cerevisiae as a useful eukaryotic model system. Several methods are described that can be used to search for new interactions, including extragenic suppression, multicopy suppression, synthetic lethality, and transdominant inhibition. Strategies for screening, genetic characterization, and clone identification are described, along with recent examples from the literature. In addition, genetic methods are discussed that can be used to further characterize a newly discovered protein-protein interaction. These include the creation of mutant libraries of a given protein by chemical mutagenesis or polymerase chain reaction, the production of dominant-negative mutants, and strategies for introducing these mutant alleles back into yeast for analysis. Although these genetic methods are quite powerful, they are often just a starting point for further biochemical or cell biological experiments.