Meta-analysis of prevalence

Meta-analysis is a method to obtain a weighted average of results from various studies. In addition to pooling effect sizes, meta-analysis can also be used to estimate disease frequencies, such as incidence and prevalence. In this article we present methods for the meta-analysis of prevalence. We discuss the logit and double arcsine transformations to stabilise the variance. We note the special situation of multiple category prevalence, and propose solutions to the problems that arise. We describe the implementation of these methods in the MetaXL software, and present a simulation study and the example of multiple sclerosis from the Global Burden of Disease 2010 project. We conclude that the double arcsine transformation is preferred over the logit, and that the MetaXL implementation of multiple category prevalence is an improvement in the methodology of the meta-analysis of prevalence.

Whole-genome linkage analysis of rheumatoid arthritis susceptibility loci in 252 affected sibling pairs in the United Kingdom

Objective. To undertake a systematic wholegenome screen to identify regions exhibiting genetic linkage to rheumatoid arthritis (RA). Methods. Two hundred fifty-two RA-affected sibling pairs from 182 UK families were genotyped using 365 highly informative microsatellite markers. Microsatellite genotyping was performed using fluorescent polymerase chain reaction primers and semiautomated DNA sequencing technology. Linkage analysis was undertaken using MAPMAKER/SIBS for single-point and multipoint analysis. Results. Significant linkage (maximum logarithm of odds score 4.7 [P = 0.000003] at marker D6S276, 1 cM from HLA-DRB1) was identified around the major histocompatibility complex (MHC) region on chromosome 6. Suggestive linkage (P < 7.4 × 10-4) was identified on chromosome 6q by single- and multipoint analysis. Ten other sites of nominal linkage (P < 0.05) were identified on chromosomes 3p, 4q, 7p, 2 regions of 10q, 2 regions of 14q, 16p, 21q, and Xq by single-point analysis and on 3 sites (1q, 14q, and 14q) by multipoint analysis. Conclusion. Linkage to the MHC region was confirmed. Eleven non-HLA regions demonstrated evidence of suggestive or nominal linkage, but none reached the genome-wide threshold for significant linkage (P = 2.2 × 10-5). Results of previous genome screens have suggested that 6 of these regions may be involved in RA susceptibility.

Combined analysis of three whole genome linkage scans for Ankylosing Spondylitis

Objective. Ankylosing spondylitis (AS) is a debilitating chronic inflammatory condition with a high degree of familiality (λs=82) and heritability (>90%) that primarily affects spinal and sacroiliac joints. Whole genome scans for linkage to AS phenotypes have been conducted, although results have been inconsistent between studies and all have had modest sample sizes. One potential solution to these issues is to combine data from multiple studies in a retrospective meta-analysis. Methods: The International Genetics of Ankylosing Spondylitis Consortium combined data from three whole genome linkage scans for AS (n=3744 subjects) to determine chromosomal markers that show evidence of linkage with disease. Linkage markers typed in different centres were integrated into a consensus map to facilitate effective data pooling. We performed a weighted meta-analysis to combine the linkage results, and compared them with the three individual scans and a combined pooled scan. Results: In addition to the expected region surrounding the HLA-B27 gene on chromosome 6, we determined that several marker regions showed significant evidence of linkage with disease status. Regions on chromosome 10q and 16q achieved 'suggestive' evidence of linkage, and regions on chromosomes 1q, 3q, 5q, 6q, 9q, 17q and 19q showed at least nominal linkage in two or more scans and in the weighted meta-analysis. Regions previously associated with AS on chromosome 2q (the IL-1 gene cluster) and 22q (CYP2D6) exhibited nominal linkage in the meta-analysis, providing further statistical support for their involvement in susceptibility to AS. Conclusion: These findings provide a useful guide for future studies aiming to identify the genes involved in this highly heritable condition. . Published by on behalf of the British Society for Rheumatology.

Thin-Layer Chromatography with Ultraviolet and Mass Spectrometric Detection: From Preparative-Layer to Miniaturized Ultra-Thin-Layer Technique

The present challenge in drug discovery is to synthesize new compounds efficiently in minimal time. The trend is towards carefully designed and well-characterized compound libraries because fast and effective synthesis methods easily produce thousands of new compounds. The need for rapid and reliable analysis methods is increased at the same time. Quality assessment, including the identification and purity tests, is highly important since false (negative or positive) results, for instance in tests of biological activity or determination of early-ADME parameters in vitro (the pharmacokinetic study of drug absorption, distribution, metabolism, and excretion), must be avoided. This thesis summarizes the principles of classical planar chromatographic separation combined with ultraviolet (UV) and mass spectrometric (MS) detection, and introduces powerful, rapid, easy, low-cost, and alternative tools and techniques for qualitative and quantitative analysis of small drug or drug-like molecules. High performance thin-layer chromatography (HPTLC) was introduced and evaluated for fast semi-quantitative assessment of the purity of synthesis target compounds. HPTLC methods were compared with the liquid chromatography (LC) methods. Electrospray ionization mass spectrometry (ESI MS) and atmospheric pressure matrix-assisted laser desorption/ionization MS (AP MALDI MS) were used to identify and confirm the product zones on the plate. AP MALDI MS was rapid, and easy to carry out directly on the plate without scraping. The PLC method was used to isolate target compounds from crude synthesized products and purify them for bioactivity and preliminary ADME tests. Ultra-thin-layer chromatography (UTLC) with AP MALDI MS and desorption electrospray ionization mass spectrometry (DESI MS) was introduced and studied for the first time. Because of the thinner adsorbent layer, the monolithic UTLC plate provided 10 100 times better sensitivity in MALDI analysis than did HPTLC plates. The limits of detection (LODs) down to low picomole range were demonstrated for UTLC AP MALDI and UTLC DESI MS. In a comparison of AP and vacuum MALDI MS detection for UTLC plates, desorption from the irregular surface of the plates with the combination of an external AP MALDI ion source and an ion trap instrument provided clearly less variation in mass accuracy than the vacuum MALDI time-of-flight (TOF) instrument. The performance of the two-dimensional (2D) UTLC separation with AP MALDI MS method was studied for the first time. The influence of the urine matrix on the separation and the repeatability was evaluated with benzodiazepines as model substances in human urine. The applicability of 2D UTLC AP MALDI MS was demonstrated in the detection of metabolites in an authentic urine sample.

Identification of Isoflavonoid Metabolites in Humans

Epidemiological studies have associated high soy intake with a lowered risk for certain hormone-dependent diseases, such as breast and prostate cancers, osteoporosis, and cardiovascular disease. Soy is a rich source of isoflavones, diphenolic plant compounds that have been shown to possess several biological activities. Soy is not part of the traditional Western diet, but many dietary supplements are commercially available in order to provide the proposed beneficial health effects of isoflavones without changing the original diet. These supplements are usually manufactured from extracts of soy or red clover, which is another important source of isoflavones. However, until recently, detailed studies of the metabolism of these compounds in humans have been lacking. The aim of this study was to identify urinary metabolites of isoflavones originating from soy or red clover using gas chromatography - mass spectrometry (GC-MS). To examine metabolism, soy and red clover supplementation studies with human volunteers were carried out. In addition, the metabolism of isoflavones was investigated in vitro by identification of metabolites formed during a 24-h fermentation of pure isoflavones with a human fecal inoculum. Qualitative methods for identification and analysis of isoflavone metabolites in urine and fecal fermentation samples by GC-MS were developed. Moreover, a detailed investigation of fragmentation of isoflavonoids in electron ionization mass spectrometry (EIMS) was carried out by means of synthetic reference compounds and deuterated trimethylsilyl derivatives. After isoflavone supplementation, 18 new metabolites of isoflavones were identified in human urine samples. The most abundant urinary metabolites of soy isoflavones daidzein, genistein, and glycitein were found to be the reduced metabolites, i.e. analogous isoflavanones, a-methyldeoxybenzoins, and isoflavans. Metabolites having additional hydroxyl and/or methoxy substituents, or their reduced analogs, were also identified. The main metabolites of red clover isoflavones formononetin and biochanin A were identified as daidzein and genistein. In addition, reduced and hydroxylated metabolites of formononetin and biochanin A were identified; however, they occurred at much lower levels in urine samples than daidzein or genistein or their reduced metabolites. The results of this study show that the metabolism of isoflavones is diverse. More studies are needed to determine whether the new isoflavonoid metabolites identified here have biological activities that contribute to the proposed beneficial effects of isoflavones on human health. Another task is to develop validated quantitative methods to determine the actual levels of isoflavones and their metabolites in biological matrices in order to assess the role of isoflavones in prevention of chronic diseases.

Human action recognition from video sequences

This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential.

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.

Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer

Nucleosides in human urine and serum have frequently been studied as a possible biomedical marker for cancer, acquired immune deficiency syndrome (AIDS) and the whole-body turnover of RNAs. Fifteen normal and modified nucleosides were determined in 69 urine and 42 serum samples using high-performance liquid chromatography (HPLC). Artificial neural networks have been used as a powerful pattern recognition tool to distinguish cancer patients from healthy persons. The recognition rate for the training set reached 100%. In the validating set, 95.8 and 92.9% of people were correctly classified into cancer patients and healthy persons when urine and serum were used as the sample for measuring the nucleosides. The results show that the artificial neural network technique is better than principal component analysis for the classification of healthy persons and cancer patients based on nucleoside data. (C) 2002 Elsevier Science B.V. All rights reserved.

Enantioseparation of Dioxopromethazine Hydrochloride in Urine with Liquid-Liquid Extraction by CE-ECL Detection

Capillary electrophoresis coupled with electrochemiluminescence detection was developed for the separation and determination of dioxopromethazine hydrochloride (DPZ) enantiomers. Performance parameters of the proposed method were evaluated. An improved separation of DPZ enantiomers could be achieved after adding boric acid to buffer. The enantiomers were completely separated with running buffer of 16.5 mM beta-CD in 25 mM tris-H3PO4-40 mM H3BO3 at pH 2.5. The proposed method was successfully applied to the separation and determination of DPZ enantiomers in human urine with a liquid-liquid extraction procedure.

Determination of atenolol and metoprolol by capillary electrophoresis with Tris(2,2 '-bipyridyl)ruthenium(II) electrochemiluminescence detection

Capillary electrophoresis (CE) coupling with a tris(2,2'-bipyridyl)ruthenium(II) (Ru(bpy)(3)(2+)) electrochemiluminescence (ECL) detection technique was developed for the analysis of two 8-blockers, atenolol (AT) and metoprolol (ME). The parameters that influence the separation and detection, including the buffer pH and concentration, the separation voltage, the detection potential and Ru(bpy)(3)(2+) concentration, were optimized in detail. The calibration curve was linear over a concentration range of two or three orders of magnitude for the two beta-blockers. The detection limits for AT and ME were 0.075 and 0.005 mu M (S/N = 3). The relative standard deviations (n = 8) of the ECL intensity and the migration time were 2.65 and 0.22% for AT, 2.82 and 0.34% for ME, respectively. The proposed method was applied to determine AT and ME in spiked urine samples; satisfactory results were obtained.

Determination of reserpine in urine by capillary electrophoresis with electrochemiluminescence detection

A fast and sensitive approach to detect reserpine in urine using micellar electrokinetic capillary chromatography with electrochemiluminescence (ECL) of Ru(bpy)(3)(2+) detection is described. Using a 25 mum i.d. capillary as separation column, the ECL detector was coupled to the capillary in the absence of an electric field decoupler. Field-amplified injection was used to minimize the effect of ionic strength in the sample and to achieve high sensitivity. In this way, the sample was analyzed directly without any pretreatment. The method was validated for reserpine in the urine over the range of 1 x 10(-6) - 1 x 10(-4) mol/L with a correlation coefficient of 0.996. The RSD for reserpine at a level of 5 mumol/L was 4.3%. The LOD (S/N = 3) was estimated to be 7.0 x 10(-8) mol/L. The average recoveries for 10 mumol/L reserpine spiked in human urine were 94%.

The use of CE-electrochemiluminescence with ionic liquid for the determination of bioactive constituents in Chinese traditional medicine

CE/tris(2,2-bipyridyl) ruthenium(ll) (Ru(bpy)(3)(2+)) electrochemiluminescence (ECL), CEECL, with an ionic liquid (IL) detection system was established for the determination of bioactive constituents in Chinese traditional medicine opium poppy which contain large amounts of coexistent substances. A minimal sample pretreatment which involves a one-step extraction approach avoids both sample loss and environmental pollution. As the nearby hydroxyl groups in some alkaloid such as morphine may react with borate to form complexes and IL, as a high-conductivity additive in running buffer, could cause an enhanced field-amplified effect of electrokinetic injection. Running buffer containing 25 mM borax-8 mM 1-ethyl-3-methylimidazolium tetrafluoroborate (EMImBF(4)) IL (pH 9.18) was used which resulted in significant changes in separation selectivity and obvious enhancement in ECL intensities for those alkaloids with similar structures. Sensitive detection could be achieved when the distance between the Pt working electrode and the outlet of separation capillary was set at 150 mu m and the stainless steel cannula was fixed approximately 1 cm away from the outlet of the capillary. Quantitative analysis of four alkaloids was achieved at a detection voltage of 1.2 V and a separation voltage of 15 kV in less than 7 min.

Chinese herb medicines analyses by capillary electrophoresis with amperometric detection

Capillary electrophoresis (CE) with amperometric detection (AD) has been widely used in various fields of analytical science, especially in the pharmaceutical industry recently due to its high separation efficiency and low detection limit. The determination of active ingredients in Chinese herb medicines by CE-AD is of great importance in developing the researches on pharmacology of herbs, quantitative analysis and quality control. Analyses of the effective components in Chinese herb medicines and compound Chinese herb medicine by CE-AD are reviewed in this paper. In contrast with other analysis methods, the advantage of CE-AD is discussed. The development in analyses of traditional Chinese medicine (TCM) by CE-AD in future is mentioned.

毛细管电泳安培检测法在中草药分析中的应用

Capillary electrophoresis (CE) with amperometric detection (AD) has been widely used in various fields of analytical science, especially in the pharmaceutical industry recently due to its high separation efficiency and low detection limit. The determination of active ingredients in Chinese herb medicines by CE-AD is of great importance in developing the researches on pharmacology of herbs, quantitative analysis and quality control. Analyses of the effective components in Chinese herb medicines and compound Chinese herb medicine by CE-AD are reviewed in this paper. In contrast with other analysis methods, the advantage of CE-AD is discussed. The development in analyses of traditional Chinese medicine (TCM) by CE-AD in future is mentioned.