Using historical data to detect temporal changes in the abundances of intertidal species on Irish shores

An historical data set, collected in 1958 by Southward and Crisp, was used as a baseline for detecting change in the abundances of species in the rocky intertidal of Ireland. In 2003, the abundances of each of 27 species was assessed using the same methodologies (ACFOR [which stands for the categories: abundant, common, frequent, occasional and rare] abundance scales) at 63 shores examined in the historical study. Comparison of the ACFOR data over a 45-year period, between the historical survey and re-survey, showed statistically significant changes in the abundances of 12 of the 27 species examined. Two species (one classed as northern and one introduced) increased significantly in abundance while ten species (five classed as northern, one classed as southern and four broadly distributed) decreased in abundance. The possible reasons for the changes in species abundances were assessed not only in the context of anthropogenic effects, such as climate change and commercial exploitation, but also of operator error. The error or differences recorded among operators (i.e. research scientists) when assessing species abundance using ACFOR categories was quantified on four shores. Significant change detected in three of the 12 species fell within the margin of operator error. This effect of operator may have also contributed to the results of no change in the other 15 species between the two census periods. It was not possible to determine the effect of operator on our results, which can increase the occurrence of a false positive (Type 1) or of a false negative (Type 2) outcome

Coccolithophore bloom detection in the north east Atlantic using SeaWiFS: Algorithm description, application and sensitivity analysis

Coccolithophores are the largest source of calcium carbonate in the oceans and are considered to play an important role in oceanic carbon cycles. Current methods to detect the presence of coccolithophore blooms from Earth observation data often produce high numbers of false positives in shelf seas and coastal zones due to the spectral similarity between coccolithophores and other suspended particulates. Current methods are therefore unable to characterise the bloom events in shelf seas and coastal zones, despite the importance of these phytoplankton in the global carbon cycle. A novel approach to detect the presence of coccolithophore blooms from Earth observation data is presented. The method builds upon previous optical work and uses a statistical framework to combine spectral, spatial and temporal information to produce maps of coccolithophore bloom extent. Validation and verification results for an area of the north east Atlantic are presented using an in situ database (N = 432) and all available SeaWiFS data for 2003 and 2004. Verification results show that the approach produces a temporal seasonal signal consistent with biological studies of these phytoplankton. Validation using the in situ coccolithophore cell count database shows a high correct recognition rate of 80% and a low false-positive rate of 0.14 (in comparison to 63% and 0.34 respectively for the established, purely spectral approach). To guide its broader use, a full sensitivity analysis for the algorithm parameters is presented.

Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data

The detection of dense harmful algal blooms (HABs) by satellite remote sensing is usually based on analysis of chlorophyll-a as a proxy. However, this approach does not provide information about the potential harm of bloom, nor can it identify the dominant species. The developed HAB risk classification method employs a fully automatic data-driven approach to identify key characteristics of water leaving radiances and derived quantities, and to classify pixels into “harmful”, “non-harmful” and “no bloom” categories using Linear Discriminant Analysis (LDA). Discrimination accuracy is increased through the use of spectral ratios of water leaving radiances, absorption and backscattering. To reduce the false alarm rate the data that cannot be reliably classified are automatically labelled as “unknown”. This method can be trained on different HAB species or extended to new sensors and then applied to generate independent HAB risk maps; these can be fused with other sensors to fill gaps or improve spatial or temporal resolution. The HAB discrimination technique has obtained accurate results on MODIS and MERIS data, correctly identifying 89% of Phaeocystis globosa HABs in the southern North Sea and 88% of Karenia mikimotoi blooms in the Western English Channel. A linear transformation of the ocean colour discriminants is used to estimate harmful cell counts, demonstrating greater accuracy than if based on chlorophyll-a; this will facilitate its integration into a HAB early warning system operating in the southern North Sea.

Repeated measures screening for down's syndrome

Objective To demonstrate the potential value of screening for Down's Syndrome using highly correlated repeated measures of serum markers taken in the first and second trimesters of pregnancy. Design A Monte Carlo simulation study. Population Detection rates and false positive rates relating to the maternal age distribution of England and Wales for the period 1996 to 1998 were obtained using marker distributions from the SURUSS study. Results Screening using first trimester nuchal translucency and repeated measures of uE3 and PAPP-A in the first and second trimester has an estimated false positive rate of 0.3% for an 85% detection rate. This should be compared with the integrated test with an estimated false positive rate of 1.2% for the same detection rate. Conclusionsâ?? The performance of repeated measures screening tests, and their acceptability to women, should be assessed in further prospective studies.

Genetic association analyses of non-synonymous single nucleotide polymorphisms in diabetic nephropathy

Aims/hypothesis: Diabetic nephropathy, characterised by persistent proteinuria, hypertension and progressive kidney failure, affects a subset of susceptible individuals with diabetes. It is also a leading cause of end-stage renal disease (ESRD). Non-synonymous (ns) single nucleotide polymorphisms (SNPs) have been reported to contribute to genetic susceptibility in both monogenic disorders and common complex diseases. The objective of this study was to investigate whether nsSNPs are involved in susceptibility to diabetic nephropathy using a case-control design.

Methods: White type 1 diabetic patients with (cases) and without (controls) nephropathy from eight centres in the UK and Ireland were genotyped for a selected subset of nsSNPs using Illumina's GoldenGate BeadArray assay. A ? 2 test for trend, stratified by centre, was used to assess differences in genotype distribution between cases and controls. Genomic control was used to adjust for possible inflation of test statistics, and the False Discovery Rate method was used to account for multiple testing.

Results: We assessed 1,111 nsSNPs for association with diabetic nephropathy in 1,711 individuals with type 1 diabetes (894 cases, 817 controls). A number of SNPs demonstrated a significant difference in genotype distribution between groups before but not after correction for multiple testing. Furthermore, neither subgroup analysis (diabetic nephropathy with ESRD or diabetic nephropathy without ESRD) nor stratification by duration of diabetes revealed any significant differences between groups.

Conclusions/interpretation: The nsSNPs investigated in this study do not appear to contribute significantly to the development of diabetic nephropathy in patients with type 1 diabetes.

The impact of newly identified loci on coronary heart disease, stroke and total mortality in the MORGAM prospective cohorts

Recently, genome wide association studies (GWAS) have identified a number of single nucleotide polymorphisms (SNPs) as being associated with coronary heart disease (CHD). We estimated the effect of these SNPs on incident CHD, stroke and total mortality in the prospective cohorts of the MORGAM Project. We studied cohorts from Finland, Sweden, France and Northern Ireland (total N=33,282, including 1,436 incident CHD events and 571 incident stroke events). The lead SNPs at seven loci identified thus far and additional SNPs (in total 42) were genotyped using a case-cohort design.We estimated the effect of the SNPs on disease history at baseline, disease events during follow-up and classic risk factors. Multiple testing was taken into account using false discovery rate (FDR) analysis. SNP rs1333049 on chromosome 9p21.3 was associated with both CHD and stroke (HR5=.20, 95% CI 1.08-1.34 for incident CHD events and 1.15, 0.99-1.34 for incident stroke). SNP rs11670734 (19q12) was associated with total mortality and stroke. SNP rs2146807 (10q11.21) showed some association with the fatality of acute coronary event. SNP rs2943634 (2q36.3) was associated with high density lipoprotein (HDL) cholesterol and SNPs rs599839, rs4970834 (1p13.3) and rs17228212 (15q22.23) were associated with non-HDL cholesterol. SNPs rs2943634 (2q36.3) and rs12525353 (6q25.1) were associated with blood pressure. These findings underline the need for replication studies in prospective settings and confirm the candidacy of several SNPs that may play a role in the etiology of cardiovascular disease.

Towards accurate estimation of the proportion of true null hypotheses in multiple testing

Background

Biomedical researchers are now often faced with situations where it is necessary to test a large number of hypotheses simultaneously, eg, in comparative gene expression studies using high-throughput microarray technology. To properly control false positive errors the FDR (false discovery rate) approach has become widely used in multiple testing. The accurate estimation of FDR requires the proportion of true null hypotheses being accurately estimated. To date many methods for estimating this quantity have been proposed. Typically when a new method is introduced, some simulations are carried out to show the improved accuracy of the new method. However, the simulations are often very limited to covering only a few points in the parameter space.

Results

Here I have carried out extensive in silico experiments to compare some commonly used methods for estimating the proportion of true null hypotheses. The coverage of these simulations is unprecedented thorough over the parameter space compared to typical simulation studies in the literature. Thus this work enables us to draw conclusions globally as to the performance of these different methods. It was found that a very simple method gives the most accurate estimation in a dominantly large area of the parameter space. Given its simplicity and its overall superior accuracy I recommend its use as the first choice for estimating the proportion of true null hypotheses in multiple testing.

Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement

The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available. 

Monoclonal antibody-based ELISA for the quantification of nitrofuran metabolite 3-amino-2-oxazolidinone in tissues using a simplified sample preparation

A sensitive and specific monoclonal ELISA for the determination of tissue bound furazolidone metabolite 3-amino-2-oxazolidinone (AOZ) is described. The procedure enables the detection of AOZ in matrix supernatant after homogenisation, protease treatment, acid hydrolysis and derivatisation of AOZ released from the tissue by o-nitrobenzaldehyde. The formed p-nitrophenyl 3-amino-2-oxazolidinone (NPAOZ) is determined by ELISA calibrated with matrix-matched standards in the concentration range of 0.05-5.0 mu g l(-1). The assay was validated according to criteria set down by Commission Decision 2002/657/EC for the performance and validation of analytical methods for chemical residues. Detection capability, set on the basis of acceptance of no false negative results, was 0.4 mu g kg(-1) for shrimp, poultry, beef and pork muscle. This sensitivity approaches the established confirmatory LC-MS/MS able to quantify tissue-bound AOZ at levels as low as 0.3 mu g kg(-1). An excellent correlation of results obtained by ELISA and LC/MS-MS within the concentration range 0-32.1 mu g kg(-1) was found in the naturally contaminated shrimp samples (r = 0.999, n = 8). A similar con-elation was found for the incurred poultry samples within the concentration range of 0-10.5 mu g kg(-1) (r = 0.99, n = 8). (c) 2005 Elsevier B.V All rights reserved.

Improved Detection of Mycobacterium bovis Infection in Bovine Lymph Node Tissue Using Immunomagnetic Separation (IMS)-Based Methods

Immunomagnetic separation (IMS) can selectively isolate and concentrate Mycobacterium bovis cells from lymph node tissue to facilitate subsequent detection by PCR (IMS-PCR) or culture (IMS-MGIT). This study describes application of these novel IMS-based methods to test for M. bovis in a survey of 280 bovine lymph nodes (206 visibly lesioned (VL), 74 non-visibly lesioned (NVL)) collected at slaughter as part of the Northern Ireland bovine TB eradication programme. Their performance was evaluated relative to culture. Overall, 174 (62.1%) lymph node samples tested positive by culture, 162 (57.8%) by IMS-PCR (targeting IS6110), and 196 (70.0%) by IMS-MGIT culture. Twelve (6.9%) of the 174 culture positive lymph node samples were not detected by either of the IMS-based methods. However, an additional 78 M. bovis positive lymph node samples (26 (12.6%) VL and 54 (73.0%) NVL) were detected by the IMS-based methods and not by culture. When low numbers of viable M. bovis are present in lymph nodes (e.g. in NVLs of skin test reactor cattle) decontamination prior to culture may adversely affect viability, leading to false negative culture results. In contrast, IMS specifically captures whole M. bovis cells (live, dead or potentially dormant) which are not subject to any deleterious treatment before detection by PCR or MGIT culture. During this study only 2.7% of NVL lymph nodes tested culture positive, whereas 73% of the same samples tested M. bovis positive by the IMS-based tests. Results clearly demonstrate that not only are the IMS-based methods more rapid but they have greater detection sensitivity than the culture approach currently used for the detection of M. bovis infection in cattle.. Adoption of the IMS-based methods for lymph node testing would have the potential to improve M. bovis detection in clinical samples.

Balancing Inflammatory, Lipid, and Xenobiotic Signaling Pathways by VSL#3, a Biotherapeutic Agent, in the Treatment of Inflammatory Bowel Disease

Background: The interleukin 10 knockout mouse (IL10-KO) is a model of human inflammatory bowel disease (IBD) used to Study host microbial interactions and the action of potential therapeutics. Using Affymetrix data analysis, important signaling pathways and transcription factors relevant to gut inflammation and antiinflammatory probiotics were identified.

Methods: Affymetrix microarray analysis on both wildtype (WT) and IL10-KO mice orally administered with and without the probiotic VSL#3 was performed and the results validated by real-time polymerase chain reaction (PCR), immunocytochemistry, proteomics, and histopathology. Changes in metabolically active bacteria were assessed with denaturing gradient gel electrophoresis (DGGE).

Results: Inflammation in IL10-KO mice was characterized by differential regulation of inflammatory, nuclear receptor, lipid, and xenobiotic signaling pathways. Probiotic intervention resulted in downregulation of CXCL9 (fold change [FC] = -3.98, false discovery rate [FDR] = 0.019), CXCL10 (FC = -4.83, FDR = 0.0008), CCL5 (FC -3.47 FDR = 0.017), T-cell activation (Itgal [FC = -4.72, FDR = 0.00009], Itgae [FC = -2.54 FDR = 0.0044]) and the autophagy gene IRGM (FC = -1.94, FDR = 0.01), a recently identified susceptibility gene in human IBD. Consistent with a marked reduction in integrins, probiotic treatment decreased the number of CCL5+ CD3+ double-positive T Cells and upregulated galectin2, which triggers apoptosis of activated T cells. Importantly, genes associated with lipid and PPAR signaling (PPAR alpha [FC = 2.36, FDR = 0.043], PPARGC1 alpha [FC 2.58, FDR = 0.016], Nrld2 [FC = 3.11, FDR = 0.0067]) were also upregulated. Altered microbial diversity was noted in probiotic-treated mice.

Conclusions: Bioinformatics analysis revealed important immune response. phagocytic and inflammatory pathways dominated by elevation of T-helper cell 1 type (TH1) transcription factors in IL10-KO mice. Probiotic intervention resulted in a site-specific reduction of these pathways but importantly upregulated PPAR, xenobiotic, and lipid signaling genes. potential antagonists of NF-kappa B inflammatory pathways.

Comparison of Wavelet Transform and Time-Domain Analysis of Second Trimester Uterine Artery Doppler Waveforms in Screening for Pre-Eclampsia

The aim of this study was to compare time-domain waveform analysis of second-trimester uterine artery Doppler using the resistance index (RI) with waveform analysis using a mathematical tool known as wavelet transform for the prediction of pre-eclampsia (PE). This was a retrospective, nested case-cohort study of 336 women, 37 of whom subsequently developed PE. Uterine artery Doppler waveforms were analysed using both RI and waveform analysis. The utility of these indices in screening for PE was then evaluated using receiver operating characteristic curves. There were significant differences in uterine artery RI between the PE women and those with normal pregnancy outcome. After wavelet analysis, significant difference in the mean amplitude in wavelet frequency band 4 was noted between the 2 groups. The sensitivity for both Doppler RI and frequency band 4 for the detection of PE at a 10% false-positive rate was 45%. This small study demonstrates the application of wavelet transform analysis of uterine artery Doppler waveforms in screening for PE. Further prospective studies are needed in order to clearly define if this analytical approach to waveform analysis may have the potential to improve the detection of PE by uterine artery Doppler screening.

Dual-colour HER2/chromosome 17 chromogenic in situ hybridisation assay enables accurate assessment of HER2 genomic status in gastric cancer and has potential utility in HER2 testing of biopsy samples

Determination of HER2 protein expression by immunohistochemistry (IHC) and genomic status by fluorescent in situ hybridisation (FISH) are important in identifying a subset of high HER2-expressing gastric cancers that might respond to trastuzumab. Although FISH is considered the standard for determination of HER2 genomic status, brightfield ISH is being increasingly recognised as a viable alternative. Also, the impact of HER2 protein expression/genomic heterogeneity on the accuracy of HER2 testing has not been well studied in the context of gastric biopsy samples.

Haplotype association analysis of genes within the WNT signalling pathways in diabetic nephropathy

Background: Renal interstitial fibrosis and glomerular sclerosis are hallmarks of diabetic nephropathy (DN) and several studies have implicated members of the WNT pathways in these pathological processes. This study comprehensively examined common genetic variation within the WNT pathway for association with DN.

Methods: Genes within the WNT pathways were selected on the basis of nominal significance and consistent direction of effect in the GENIE meta-analysis dataset. Common SNPs and common haplotypes were examined within the selected WNT pathway genes in a white population with type 1 diabetes, discordant for DN (cases: n = 718; controls: n = 749). SNPs were genotyped using Sequenom or Taqman assays. Association analyses were performed using PLINK, to compare allele and haplotype frequencies in cases and controls. Correction for multiple testing was performed by either permutation testing or using false discovery rate.

Results: A logistic regression model including collection centre, duration of diabetes, and average HbA1c as covariates highlighted three SNPs in GSK3B (rs17810235, rs17471, rs334543), two in DAAM1 (rs1253192, rs1252906) and one in NFAT5 (rs17297207) as being significantly (P< 0.05) associated with DN, however these SNPs did not remain significant after correction for multiple testing. Logistic regression of haplotypes, with ESRD as the outcome, and pairwise interaction analyses did not yield any significant results after correction for multiple testing.

Conclusions: These results indicate that both common SNPs and common haplotypes of WNT pathway genes are not strongly associated with DN. However, this does not completely exclude these or the WNT pathways from association with DN, as unidentified rare genetic or copy number variants could still contribute towards the genetic architecture of DN.© 2013 Kavanagh et al.; licensee BioMed Central Ltd.

Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21 856) and multiple sclerosis (MS) (n=43 879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16 731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.Molecular Psychiatry advance online publication, 28 January 2014; doi:10.1038/mp.2013.195.