Detection of noncontingent feedback in EMG biofeedback

Noncontingent feedback is frequently used as a placebo control procedure in biofeedback research. Researchers, however, have criticized this procedure for lacking credibility because of easy detection. The present study examined detection of false feedback in biofeedback with EMG. Contingent feedback (CF), truly random false feedback (FF), and controlled false feedback (CFF) groups were compared for changes in EMG levels, report of inaccurate feedback, and report of learning muscle activity reduction. The results indicated that FF procedures are easily detected; therefore, differences found between the FF and CF groups may be influenced by extraneous variables. The CFF group did not detect false feedback, but subjects reported some suspicions in later trials. With more trials, CFF may have also been detected. These results indicate a need for more attention to appropriate placebo control procedures in evaluating the parameters and efficacy of biofeedback.     

Detection of noncontingent feedback in EMG biofeedback

Noncontingent feedback is frequently used as a placebo control procedure in biofeedback research. Researchers, however, have criticized this procedure for lacking credibility because of easy detection. The present study examined detection of false feedback in biofeedback with EMG. Contingent feedback (CF), truly random false feedback (FF), and controlled false feedback (CFF) groups were compared for changes in EMG levels, report of inaccurate feedback, and report of learning muscle activity reduction. The results indicated that FF procedures are easily detected; therefore, difference found between the FF and CF groups may be influenced by extraneous variables. The CFF group did not detect false feedback, but subjects reported some suspicions in later trials. With more trials, CFF may have also been detected. These results indicate a need for more attention to appropriate placebo control procedures in evaluating the parameters and efficacy of biofeedback.     

How could static telepathology improve diagnosis in neuropathology?

The present paper reports our experience with, and our opinion of static telepathology as applied to neuropathology by means of the PHAROS acquisition system and conventional telephone data transmission (modem). The classical procedure of expert consultation based on surface mailing of histological slides is routinely performed, especially in highly specialized fields of pathology. Telepathology is an easy means of sharing scientific expertise at international level and could thus improve diagnosis particularly in neuropathology, where certain tumor types are very rare and complex to diagnose. Dynamic telepathology allows the referring pathologist to capture by himself images supporting their diagnosis. Using static telepathology the pathologist could be limited in diagnosis by problems in fields selection. We devoted a whole year to collecting all the technical parameters characterizing the use of digitized neuropathological data files in order to investigate the feasibility of telepathology and the extent to which its use could improve diagnoses. Our results on a series of 38 histological brain examinations illustrate how we successfully established an international connection between two departments of pathology in Belgium and the USA. The referring pathologists gave diagnoses in 35 cases and deferred only 3. Despite a time-consuming procedure for the telepathology session of a few cases, this tool provides easy access to expert diagnosis and real-time discussion, both of which are of considerable interest and offer significant improvements in neuropathology.     

Empirical Bayes screening of many p-values with applications to microarray studies

MOTIVATION: Statistical tests for the detection of differentially expressed genes lead to a large collection of p-values one for each gene comparison. Without any further adjustment, these p-values may lead to a large number of false positives, simply because the number of genes to be tested is huge, which might mean wastage of laboratory resources. To account for multiple hypotheses, these p-values are typically adjusted using a single step method or a step-down method in order to achieve an overall control of the error rate (the so-called familywise error rate). In many applications, this may lead to an overly conservative strategy leading to too few genes being flagged. RESULTS: In this paper we introduce a novel empirical Bayes screening (EBS) technique to inspect a large number of p-values in an effort to detect additional positive cases. In effect, each case borrows strength from an overall picture of the alternative hypotheses computed from all the p-values, while the entire procedure is calibrated by a step-down method so that the familywise error rate at the complete null hypothesis is still controlled. It is shown that the EBS has substantially higher sensitivity than the standard step-down approach for multiple comparison at the cost of a modest increase in the false discovery rate (FDR). The EBS procedure also compares favorably when compared with existing FDR control procedures for multiple testing. The EBS procedure is particularly useful in situations where it is important to identify all possible potentially positive cases which can be subjected to further confirmatory testing in order to eliminate the false positives. We illustrated this screening procedure using a data set on human colorectal cancer where we show that the EBS method detected additional genes related to colon cancer that were missed by other methods.This novel empirical Bayes procedure is advantageous over our earlier proposed empirical Bayes adjustments due to the following reasons: (i) it offers an automatic screening of the p-values the user may obtain from a univariate (i.e., gene by gene) analysis package making it extremely easy to use for a non-statistician, (ii) since it applies to the p-values, the tests do not have to be t-tests; in particular they could be F-tests which might arise in certain ANOVA formulations with expression data or even nonparametric tests, (iii) the empirical Bayes adjustment uses nonparametric function estimation techniques to estimate the marginal density of the transformed p-values rather than using a parametric model for the prior distribution and is therefore robust against model mis-specification. AVAILABILITY: R code for EBS is available from the authors upon request. SUPPLEMENTARY INFORMATION: http://www.stat.uga.edu/~datta/EBS/supp.htm     

Rapid identification of <Emphasis Type="Italic">Salmo trutta</Emphasis> lineages by multiplex PCR utilizing primers tailored to discriminate single nucleotide polymorphisms (SNPs) of the mitochondrial control region

Analyses of the mtDNA control region sequence variation of the brown trout Salmo trutta through its distribution range have demonstrated five distinct phylogenetic lineages. In this work we report the design and implementation of a rapid and accurate molecular diagnostic procedure which allows the assignment of all major phylogenetic lineages. Our method relies on multiplex PCR that discriminates diagnostic single nucleotide polymorphisms (SNPs) characteristic of each lineage. The method is straightforward and easy to set up, involves a single reaction, yields data easy to interpret and does not pose significant risk for false positive/negative lineage assignment of a given individual. Panagotis K. Apostolou and Andreas Georgiadis contributed equally to this work.     

特发性全身性癫痫的临床与磁共振波谱研究进展

特发性全身性癫痫（idiopathic generalized epilepsy,IGE）是一组症状复杂的临床症候群,易漏诊、误诊,且发病机制尚未完全阐明。以往的研究仅限于动物实验的方法检测其脑内的代谢变化,现在随着磁共振波谱（Magnetic Resonance Spectroscopy,MRS）的应用。无创地从生化代谢水平上研究活体已成为现实,为这一类疾病的研究打开了新的局面。文章综述了IGE的分类、亚型、临床特点及近几年来MRS在这一领域中的研究成果。     

Generalized method for probability-based peptide and protein identification from tandem mass spectrometry data and sequence database searching

Tandem mass spectrometry-based proteomics is currently in great demand of computational methods that facilitate the elimination of likely false positives in peptide and protein identification. In the last few years, a number of new peptide identification programs have been described, but scores or other significance measures reported by these programs cannot always be directly translated into an easy to interpret error rate measurement such as the false discovery rate. In this work we used generalized lambda distributions to model frequency distributions of database search scores computed by MASCOT, X!TANDEM with k-score plug-in, OMSSA, and InsPecT. From these distributions, we could successfully estimate p values and false discovery rates with high accuracy. From the set of peptide assignments reported by any of these engines, we also defined a generic protein scoring scheme that enabled accurate estimation of protein-level p values by simulation of random score distributions that was also found to yield good estimates of protein-level false discovery rate. The performance of these methods was evaluated by searching four freely available data sets ranging from 40,000 to 285,000 MS/MS spectra.     

On the estimation of false positives in peptide identifications using decoy search strategy

False positive control/estimate in peptide identifications by MS is of critical importance for reliable inference at the protein level and downstream bioinformatics analysis. Approaches based on search against decoy databases have become popular for its conceptual simplicity and easy implementation. Although various decoy search strategies have been proposed, few studies have investigated their difference in performance. With datasets collected on a mixture of model proteins, we demonstrate that a single search against the target database coupled with its reversed version offers a good balance between performance and simplicity. In particular, both the accuracy of the estimate of the number of false positives and sensitivity is at least comparable to other procedures examined in this study. It is also shown that scrambling while preserving frequency of amino acid words can potentially improve the accuracy of false positive estimate, though more studies are needed to investigate the optimal scrambling procedure for specific condition and the variation of the estimate across repeated scrambling.     

Quick and easy yeast transformation using the LiAc/SS carrier DNA/PEG method

Here, we describe a quick and easy version of the lithium acetate/single-stranded carrier DNA/PEG method of transformation for Saccharomyces cerevisiae. This method can be performed when only a few transformants are needed. The procedure can take less than an hour, depending on the duration of the heat shock. It can be used to transform yeast cells from various stages of growth and storage. Cells can be transformed from freshly grown cells as well as cells stored on a plate at room temperature or in a refrigerator.     

Analysis of a simulated microarray dataset: Comparison of methods for data normalisation and detection of differential expression (Open Access publication)

Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as was correction for multiple testing. Most variety in performance resulted from differing approaches to data quality and the use of different statistical tests. Very few of the methods used any kind of background correction. A number of approaches achieved a success rate of 95% or above, with relatively small numbers of false positives and negatives. Applying stringent spot selection criteria and elimination of data did not improve the false positive rate and greatly increased the false negative rate. However, most approaches performed well, and it is encouraging that widely available techniques can achieve such good results on a very noisy data set.     

Reliable genotyping of samples with very low DNA quantities using PCR.

Our purpose was to identify an experimental procedure using PCR that provides a reliable genotype at a microsatellite locus using only a few picograms of template DNA. Under these circumstances, it is possible (i) that one allele of a heterozygous individual will not be detected and (ii) that PCR-generated alleles or 'false alleles' will arise. A mathematical model has been developed to account for stochastic events when pipetting template DNA in a very dilute DNA extract and computer simulations have been performed. Laboratory experiments were also carried out using DNA extracted from a bear feces sample to determine if experimental results correlate with the mathematical model. The results of 150 typing experiments are consistent with the proposed model. Based on this model and the level of observed false alleles, an experimental procedure using the multiple tubes approach is proposed to obtain reliable genotypes with a confidence level of 99%. This multiple tubes procedure should be systematically used when genotyping nuclear loci of ancient or forensic samples, museum specimens and hair or feces of free ranging animals.     

大数量序列的PCR保守引物设计实践

引物设计前的序列的全面检索,未注释序列的归类,经多序列比对求带有模糊碱基代码标识(IUPAC ambiguity codes)的共有序列,对设计高质量的引物至关重要,是引物设计过程的难点。目前,综合性核酸序列分析软件,单功能应用软件,在解决上述问题时均显不足。应用互联网提供的在线生物应用程序实践了一种多程序组合使用设计大数量序列的保守引物的方法,探讨了实现大数量序列的保守引物设计的一般流程。     

Measurement of phenylalanine hydroxylating activity in vivo

A gas chromatographic-mass spectrometric method was developed for analyzing phenylalanine and tyrosine (Tyr) in plasma and brain. With this procedure, we were able to show that¹⁸O₂ is incorporated into Tyr in vivo and that the presence of¹⁸O-Tyr in plasma is a relative measure of phenylalanine hydroxylating activity. Treatment withp-chlorophenylalanine decreases the¹⁸O incorporation into Tyr. Because of the simplicity of the procedure and its easy adaptability to human studies, the incorporation of¹⁸O₂ into endogenous constituents might serve as a useful diagnostic procedure for some metabolic disorders, such as phenylketonuria. These results also indicate that labeling with¹⁸O cannot be used to measure the turnover rate of brain catecholamines as previously proposed.     

Composite Technique for Regional Neurochemical Studies: Measurement of Energy and Neurotransmitter Metabolites in Single Tissue Sample

A combined method is described for the determination of various metabolites from a single tissue sample of the brain. It comprises a quick inactivation of cerebral enzymes by microwave irradiation, easy separation of the desired brain regions, and perchloric acid extraction of tissue substances, which are assayed either by specific enzymatic techniques or by HPLC with electrochemical detection. The obtained values of most energy and neurotransmitter metabolites in the brain are in agreement with those reported using other methods. However, this technique, in contrast to the brain freezing in vitro or freeze-blowing, provides a more efficient procedure for rapid arrest of cerebral metabolism even in the deep brain structures and is therefore suitable for detection of early changes particularly those occurring in experimental pathological conditions such as ischemia.     

Cytodiagnosis of filarial infections from an endemic area

OBJECTIVE: To throw light on cytologic findings as a possible mode of diagnosis of lymphatic filariasis. STUDY DESIGN: Filariasis has worldwide distribution, but lymphatic filariasis predominantly affects tropical and subtropical regions. Demonstration of microfilaremia, the specific test for diagnosis of lymphatic filariasis, often shows false negative results in endemic areas. The present study, done in an endemic area, showed the presence of microfilariae or adult worms of Wuchereria bancrofti in fine needle aspirates collected from amicrofilariaemic cases. In a few cases the discovery was incidental. A total 4,534 cases undergoing cytologic evaluation were carefully screened for the presence of adult worms or larvae, irrespective of clinical diagnosis. Microfilariae were demonstrated in both clinically suspected cases of filariasis and asymptomatic cases. RESULTS: A total of 1 positive cases were found; in 4 cases the clinical diagnosis was lymphatic filariasis, and 7 cases were asymptomatic. All 11 cases were amicrofilariaemic. CONCLUSION: Various sophisticated investigations are used for diagnosis of lymphatic filariasis without microfilaremia. Fine needle aspiration cytology, being a cheap, simple and easy procedure, may have some role in this field, but further detailed studies are needed before any final claim.     

Application of partial restriction procedure in both shotgun and non-random strategies for nucleotide sequencing

Partial digestion of a target DNA fragment with 4-bp-recognition restriction enzymes followed by a forced ligation to an M13 vector was employed for the construction of a subfragment library. The library can be used for either shotgun or non-random nucleotide sequencing. Application of the partial digests generated with the 4-bp recognition restriction enzymes instead of DNase I in the improved non-random strategy for nucleotide sequencing (Li and Wu, 1987) made the procedure as easy as that of the random strategy. The library can also be used in shotgun nucleotide sequencing directly, and few self-ligated subfragments were found. The usefulness of this procedure was demonstrated by the sequencing of a goat 6.5-kb EcoRI fragment, which is located 5' to the globin gene.     

Cluster-Based Statistics for Brain Connectivity in Correlation with Behavioral Measures

Graph theoretical approaches have successfully revealed abnormality in brain connectivity, in particular, for contrasting patients from healthy controls. Besides the group comparison analysis, a correlational study is also challenging. In studies with patients, for example, finding brain connections that indeed deepen specific symptoms is interesting. The correlational study is also beneficial since it does not require controls, which are often difficult to find, especially for old-age patients with cognitive impairment where controls could also have cognitive deficits due to normal ageing. However, one of the major difficulties in such correlational studies is too conservative multiple comparison correction. In this paper, we propose a novel method for identifying brain connections that are correlated with a specific cognitive behavior by employing cluster-based statistics, which is less conservative than other methods, such as Bonferroni correction, false discovery rate procedure, and extreme statistics. Our method is based on the insight that multiple brain connections, rather than a single connection, are responsible for abnormal behaviors. Given brain connectivity data, we first compute a partial correlation coefficient between every edge and the behavioral measure. Then we group together neighboring connections with strong correlation into clusters and calculate their maximum sizes. This procedure is repeated for randomly permuted assignments of behavioral measures. Significance levels of the identified sub-networks are estimated from the null distribution of the cluster sizes. This method is independent of network construction methods: either structural or functional network can be used in association with any behavioral measures. We further demonstrated the efficacy of our method using patients with subcortical vascular cognitive impairment. We identified sub-networks that are correlated with the disease severity by exploiting diffusion tensor imaging techniques. The identified sub-networks were consistent with the previous clinical findings having valid significance level, while other methods did not assert any significant findings.     

Misattribution, false recognition and the sins of memory

Memory is sometimes a troublemaker. Schacter has classified memory's transgressions into seven fundamental 'sins': transience, absent-mindedness, blocking, misattribution, suggestibility, bias and persistence. This paper focuses on one memory sin, misattribution, that is implicated in false or illusory recognition of episodes that never occurred. We present data from cognitive, neuropsychological and neuroimaging studies that illuminate aspects of misattribution and false recognition. We first discuss cognitive research examining possible mechanisms of misattribution associated with false recognition. We also consider ways in which false recognition can be reduced or avoided, focusing in particular on the role of distinctive information. We next turn to neuropsychological research concerning patients with amnesia and Alzheimer's disease that reveals conditions under which such patients are less susceptible to false recognition than are healthy controls, thus providing clues about the brain mechanisms that drive false recognition. We then consider neuroimaging studies concerned with the neural correlates of true and false recognition, examining when the two forms of recognition can and cannot be distinguished on the basis of brain activity. Finally, we argue that even though misattribution and other memory sins are annoying and even dangerous, they can also be viewed as by-products of adaptive features of memory.     

Quantitative trait Loci analysis using the false discovery rate

False discovery rate control has become an essential tool in any study that has a very large multiplicity problem. False discovery rate-controlling procedures have also been found to be very effective in QTL analysis, ensuring reproducible results with few falsely discovered linkages and offering increased power to discover QTL, although their acceptance has been slower than in microarray analysis, for example. The reason is partly because the methodological aspects of applying the false discovery rate to QTL mapping are not well developed. Our aim in this work is to lay a solid foundation for the use of the false discovery rate in QTL mapping. We review the false discovery rate criterion, the appropriate interpretation of the FDR, and alternative formulations of the FDR that appeared in the statistical and genetics literature. We discuss important features of the FDR approach, some stemming from new developments in FDR theory and methodology, which deem it especially useful in linkage analysis. We review false discovery rate-controlling procedures--the BH, the resampling procedure, and the adaptive two-stage procedure-and discuss the validity of these procedures in single- and multiple-trait QTL mapping. Finally we argue that the control of the false discovery rate has an important role in suggesting, indicating the significance of, and confirming QTL and present guidelines for its use.