A microbiome analysis of equine peripheral dental caries using next generation sequencing.

BACKGROUND: Although, peripheral caries (PC) affects almost half of UK horses, no comprehensive microbiological study has been performed on this disorder. As a high proportion of oral bacteria cannot be conventionally cultured, molecular microbiological techniques such as Next Generation Sequencing are required to examine the complex oral bacteria community. OBJECTIVES: To identify the microbiota involved in equine PC, including comparing microbiota at the more commonly and severely affected three caudal cheek teeth with the less commonly affected three rostral cheek teeth. STUDY DESIGN AND METHODS: Equine dental plaque samples were collected from the palatal aspects of cheek teeth of 63 horses. DNA was isolated and amplified using PCR, targeting the V4 region of the 16S rRNA gene and Next Generation Sequencing of these gene amplicons was performed. The acquired data were processed and analysed using Mothur and R. RESULTS: Streptococcus species was the genus most commonly associated with equine PC, whereas Gemella species was the genus most associated with the control group. In a further analysis where the rostral and caudal cheek teeth were compared with each other and with the control group. Veillonella species was the most commonly associated genus with PC of the rostral cheek teeth, Streptococcus species was the most associated genus with the caudal cheek teeth, and Corynebacterium with the control group. MAIN LIMITATIONS: Some bacteria can have multiple heterogeneous copies of the 16S rRNA gene, which can affect the estimation of their relative abundance. CONCLUSIONS: Similar to caries studies in other species, acidogenic and aciduric microorganisms including Streptococcus species were found to be associated with equine peripheral caries.

Clustering.

Clustering techniques are used to arrange genes in some natural way, that is, to organize genes into groups or clusters with similar behavior across relevant tissue samples (or cell lines). These techniques can also be applied to tissues rather than genes. Methods such as hierarchical agglomerative clustering, k-means clustering, the self-organizing map, and model-based methods have been used. Here we focus on mixtures of normals to provide a model-based clustering of tissue samples (gene signatures) and of gene profiles, including time-course gene expression data.

Factors affecting the efficiency of aerosolized salbutamol delivery via a metered dose inhaler and equine spacer device.

Despite frequent use of metered dose inhalers (MDIs) and spacers in equine practice, limited information exists on the efficiency of aerosol delivery using such devices. We determined the particle size distribution within an MDI-generated salbutamol aerosol delivered via an equine spacer using 'best practice' delivery technique and assessed the effect of variations in MDI use technique (shaking prior to each actuation, rapid repetitive actuations, and MDI angulation) on aerosol delivery efficiency. Under optimal conditions, only 53(±18) µg salbutamol per 100 µg actuation was delivered beyond the spacer. Although this aerosol had a high [89.6% (±2.4)] fine particle (<5 µm) fraction, and a low mass median aerodynamic diameter [2.52 (±0.29) µm], and particle size variability [geometric SD - 1.66 (±0.16) µm], within all particle size fractions, there was a high coefficient of variance (31-79%) of the percentage salbutamol delivered between experimental runs, thus impeding any effort to predict drug delivery to the patient during equine inhalation therapy. Despite observable trends and with the exception of minor statistically significant changes in the least abundant particle sizes, none of the deviations from a 'best practice' delivery technique significantly altered the relative salbutamol delivery beyond the spacer, a finding which has potential relevance with regard to maintaining user compliance.

An epidemiological survey on the prevalence of equine peripheral dental caries in the United Kingdom and possible risk factors for its development.

BACKGROUND: Equine peripheral caries (PC) is an increasingly recognised disorder that causes premature wear of teeth and dental fractures and thus has major welfare implications. Little information is available on its prevalence or severity in UK horses and there are no proven associations with any risk factors. OBJECTIVES: To document the prevalence of PC over a wide area of the UK, assess its intraoral distribution and severity in affected horses and examine for potential risk factors for its development. STUDY DESIGN: Cross sectional study. METHODS: Experienced personnel were recruited for a UK wide dental survey on their patients during dental examinations. Established guidelines were used for grading PC. Frequency of PC occurrence was compared between teeth and dental arcades using McNemar's tests. Potential risk factors for PC were screened using univariable logistic regression prior to building a multivariable model. RESULTS: A total of 706 horses were examined by 25 participants, showing a 51.7% prevalence of PC (365/706). Some regional differences in prevalence were found. The PC primarily affected the cheek teeth with the 12 caudal being significantly more commonly affected than the 12 rostral cheek teeth. Most of the hypothesised risk factors including age, breed, sex, time at pasture and feeding of silage (haylage) were unproven. A limited association with moderate levels of concentrate feeding was observed. The presence of concurrent dental abnormalities were significantly associated with the likelihood of having PC. MAIN LIMITATIONS: Not all regions in UK were included and there may be inconsistencies between examiners. CONCLUSIONS: Peripheral caries is common in British horses, primarily affecting the caudal cheek teeth. There was limited evidence of an association between feeding and PC. The association between PC and concurrent dental disorders indicates that these should be addressed in affected horses.

Meta-analysis of the diagnostic accuracy of laparoscopic ultrasonography and intraoperative cholangiography in detection of common bile duct stones.

Introduction During laparoscopic cholecystectomy, intraoperative cholangiography (IOC) is currently regarded as the gold standard in the detection of choledocholithiasis. Laparoscopic ultrasonography (LUS) is an attractive alternative with several potential advantages. Methods A systematic review was undertaken of the published literature comparing LUS with IOC in the assessment of common bile duct (CBD) stones. Results Twenty-one comparative studies were analysed. There were 4,566 patients in the IOC group and 5,044 in the LUS group. The combined sensitivity and specificity of IOC in the detection of CBD stones were 0.87 (95% confidence interval [CI]: 0.83-0.89) and 0.98 (95% CI: 0.98-0.98) respectively with a pooled area under the curve (AUC) of 0.985 and a diagnostic odds ratio (OR) of 260.65 (95% CI: 160.44-423.45). This compares with a sensitivity and specificity for LUS of 0.90 (95% CI: 0.87-0.92) and 0.99 (95% CI: 0.99-0.99) respectively with a pooled AUC of 0.982 and a diagnostic OR of 765.15 (95% CI: 450.78-1,298.76). LUS appeared to be more successful in terms of coming to a clinical decision regarding CBD stones than IOC (random effects, risk ratio: 0.95, 95% CI: 0.93-0.98, df=20, z=-3.7, p<0.005). Furthermore, LUS took less time (random effects, standardised mean difference: 0.95, 95% CI: 0.93-0.98, df=20, z=-3.7, p<0.005). Conclusions LUS is comparable with IOC in the detection of CBD stones. The main advantages of LUS are that it does not involve ionising radiation, is quicker to perform, has a lower failure rate and can be repeated during the procedure as required.

A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.

The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of computational methods for identifying cell populations in multidimensional flow cytometry data. Here we report the results of FlowCAP-IV where algorithms from seven different research groups predicted the time to progression to AIDS among a cohort of 384 HIV+ subjects, using antigen-stimulated peripheral blood mononuclear cell (PBMC) samples analyzed with a 14-color staining panel. Two approaches (FlowReMi.1 and flowDensity-flowType-RchyOptimyx) provided statistically significant predictive value in the blinded test set. Manual validation of submitted results indicated that unbiased analysis of single cell phenotypes could reveal unexpected cell types that correlated with outcomes of interest in high dimensional flow cytometry datasets.

Toxicology study assessing efficacy and safety of repeated administration of lipid/DNA complexes to mouse lung.

For gene therapy to improve lung function in cystic fibrosis (CF) subjects, repeated administration of the gene transfer agent over the lifetime of patients is likely to be necessary. This requirement limits the utility of adenoviral and adeno-associated viral vectors (both previously evaluated in CF gene therapy trials) because of induced adaptive immune responses that render repeated dosing ineffective. For CF gene therapy trials, non-viral vectors are currently the only viable option. We previously showed that the cationic lipid formulation GL67A is the most efficient of several non-viral vectors analysed for airway gene transfer. Here, we assessed the efficacy and safety of administering 12 inhaled doses of GL67A complexed with pGM169, a CpG-free plasmid encoding human CFTR complementary DNA, into mice. We show that repeated administration of pGM169/GL67A to murine lungs is feasible, safe and achieves reproducible, dose-related and persistent gene expression (>140 days after each dose) using an aerosol generated by a clinically relevant nebuliser. This study supports progression into the first non-viral multidose lung trial in CF patients.

BrdU pulse labelling in vivo to characterise cell proliferation during regeneration and repair following injury to the airway wall in sheep.

The response of S-phase cells labelled with bromodeoxyuridine (BrdU) in sheep airways undergoing repair in response to endobronchial brush biopsy was investigated in this study. Separate sites within the airway tree of anaesthetised sheep were biopsied at intervals prior to pulse labelling with BrdU, which was administered one hour prior to euthanasia. Both brushed and spatially disparate unbrushed (control) sites were carefully mapped, dissected, and processed to facilitate histological analysis of BrdU labelling. Our study indicated that the number and location of BrdU-labelled cells varied according to the age of the repairing injury. There was little evidence of cell proliferation in either control airway tissues or airway tissues examined six hours after injury. However, by days 1 and 3, BrdU-labelled cells were increased in number in the airway wall, both at the damaged site and in the regions flanking either side of the injury. Thereafter, cell proliferative activity largely declined by day 7 after injury, when consistent evidence of remodelling in the airway wall could be appreciated. This study successfully demonstrated the effectiveness of in vivo pulse labelling in tracking cell proliferation during repair which has a potential value in exploring the therapeutic utility of stem cell approaches in relevant lung disease models.

Clustering of gene expression data via normal mixture models.

There are two distinct but related clustering problems with microarray data. One problem concerns the clustering of the tissue samples (gene signatures) on the basis of the genes; the other concerns the clustering of the genes on the basis of the tissues (gene profiles). The clusters of tissues so obtained in the first problem can play a useful role in the discovery and understanding of new subclasses of diseases. The clusters of genes obtained in the second problem can be used to search for genetic pathways or groups of genes that might be regulated together. Also, in the first problem, we may wish first to summarize the information in the very large number of genes by clustering them into groups (of hyperspherical shape), which can be represented by some metagenes, such as the group sample means. We can then carry out the clustering of the tissues in terms of these metagenes. We focus here on mixtures of normals to provide a model-based clustering of tissue samples (gene signatures) and of gene profiles.

Testing for group structure in high-dimensional data.

With the use of finite mixture models for the clustering of a data set, the crucial question of how many clusters there are in the data can be addressed by testing for the smallest number of components in the mixture model compatible with the data. We investigate the performance of a resampling approach to this latter problem in the context of high-dimensional data, where the number of variables p is extremely large relative to the number of observations n. In order to be able to fit normal mixture models to such data, some form of dimension reduction has to be performed. This raises the question of whether a practically significant bias results if the bootstrapping is undertaken solely on the basis of the reduced dimensional form of the data, rather than using the full data from which to draw the bootstrap sample replications.

Analysis of airway epithelial regeneration and repair following endobronchial brush biopsy in sheep.

Understanding the fundamental processes involved in repairing the airway wall following injury is fundamental to understanding the way in which these processes are perturbed during disease pathology. Indeed complex diseases such as asthma and chronic obstructive pulmonary disease (COPD) have at their core evidence of airway wall remodeling processes that play a crucial functional role in these diseases. The authors sought to understand the dynamic cellular events that occur during bronchial airway epithelial repair in sheep. The injury was induced by endobronchial brush biopsy (BBr), a process that causes epithelial débridement and induces a consequential repair process. In addition, the current experimental protocol allowed for the time-dependent changes in airway wall morphology to be studied both within and between animals. The initial débridement was followed by evidence of dedifferentiation in the intact epithelium at the wound margins, followed by proliferation of cells both within the epithelium and in the deeper wall structures, notably in association with the submucosal glands and smooth muscle bundles. Seven days after injury, although the airway wall was thickened at the site of damage, the epithelial layer was intact, with evidence of redifferentiation. These studies, in demonstrating broad agreement with previous studies in small animals, indicate the wider relevance of this system as a comparative model and should provide a solid basis upon which to further characterize the critical cellular and molecular interactions that underlie both effective restitution and pathological repair.

Pre-clinical evaluation of three non-viral gene transfer agents for cystic fibrosis after aerosol delivery to the ovine lung.

We use both large and small animal models in our pre-clinical evaluation of gene transfer agents (GTAs) for cystic fibrosis (CF) gene therapy. Here, we report the use of a large animal model to assess three non-viral GTAs: 25 kDa-branched polyethyleneimine (PEI), the cationic liposome (GL67A) and compacted DNA nanoparticle formulated with polyethylene glycol-substituted lysine 30-mer. GTAs complexed with plasmids expressing human cystic fibrosis transmembrane conductance regulator (CFTR) complementary DNA were administered to the sheep lung (n=8 per group) by aerosol. All GTAs gave evidence of gene transfer and expression 1 day after treatment. Vector-derived mRNA was expressed in lung tissues, including epithelial cell-enriched bronchial brushing samples, with median group values reaching 1-10% of endogenous CFTR mRNA levels. GL67A gave the highest levels of expression. Human CFTR protein was detected in small airway epithelial cells in some animals treated with GL67A (two out of eight) and PEI (one out of eight). Bronchoalveolar lavage neutrophilia, lung histology and elevated serum haptoglobin levels indicated that gene delivery was associated with mild local and systemic inflammation. Our conclusion was that GL67A was the best non-viral GTA currently available for aerosol delivery to the sheep lung, led to the selection of GL67A as our lead GTA for clinical trials in CF patients.

Validation of recombinant Sendai virus in a non-natural host model.

We have previously shown that recombinant Sendai virus (SeV) vector, derived from murine parainfluenza virus, is one of the most efficient vectors for airway gene transfer. We have also shown that SeV-mediated transfection on second administration, although reduced by 60% when compared with levels achieved after a single dose, is still high because of the efficient transfection achieved by SeV vector in murine airways. Here, we show that these levels further decrease on subsequent doses. In addition, we validated SeV vector repeat administration in a non-natural host model, the sheep. As part of these studies we first assessed viral stability in a Pari LC Plus nebuliser, a polyethylene catheter (PEC) and the Trudell AeroProbe. We also compared the distribution of gene expression after PEC and Trudell AeroProbe administration and quantified virus shedding after sheep transduction. In addition, we show that bronchial brushings and biopsies, collected in anaesthetized sheep, can be used to assess SeV-mediated gene expression over time. Similar to mice, gene expression in sheep was transient and had returned to baseline values by day 14. In conclusion, the SeV vector should be strongly considered for lung-related applications requiring a single administration of the vector even though it might not be suitable for diseases requiring repeat administration.

Healthcare issues of detainees in police custody in London, UK.

Little is known about the general healthcare needs of detainees in police custody. The aims of this study were to: determine the level of general health issues, diseases and/or pathology for detainees in police custody, and to determine how well those general health issues, diseases and/or pathology are being managed. This was done by a detailed analysis of healthcare issues of a cohort of detainees and reviewing intended and prescribed medication needs with current medication availability. In August 2007, a prospective detailed, anonymised, structured questionnaire survey was undertaken of 201 detainees in police custody in London, UK. Of these 83.6% consented to participate in the study. 85.1% of subjects were male; mean age was 33.9 years; 70.8% had English as a first language; 13.7% were of no fixed abode; 70.2% were registered with a general practitioner (primary care physician); 25% were already in contact with other healthcare teams; 7.1% had previously been sectioned under the Mental Health Act 1983; 16.7% had previously intentionally self-injured; 33.9% were dependent on heroin, 33.9% on crack cocaine; 25% on alcohol, 16.6% on benzodiazepines and 63.1% on cigarettes. 56% of subjects had active medical conditions; of those with active medical conditions 74% were prescribed medication for those medical conditions; only 3/70 had their medication available. 28/70 were not taking medication regularly, and many were not taking it at all. Three subjects who had deep vein thromboses were not taking their prescribed anticoagulants and six subjects with severe mental health issues were not taking their anti-psychotic medication. Mental health issues and depression predominated, but there was a very large range of mixed diseases and pathology. Asthma, epilepsy, diabetes, deep vein thrombosis, pulmonary embolism, hepatitis, and hypertension were all represented. The study has achieved its aims and has also shown that--in part because of the chaotic lifestyle of many detainees--appropriate care was not being rendered, thereby, putting both detainee, and potentially others coming into contact with them, at risk.

A tutorial in genetic epidemiology and some considerations in statistical modeling

A new door has been opened to health professionals since the completion of the map of the human genome was announced in 2003, coinciding with the 50th anniversary of the discovery of the DNA helical structure by Watson and Crick in 1953. The continuous updating of the technology has enabled scientists to simultaneously analyze thousands of variables for genome analysis. These advances have created new opportunities to locate genes, to assess the gene-gene relationship, to measure the gene-environment interaction, to describe gene products, and to evaluate the gene-disease relationship. In epidemiology, new strategies have been developed to determine cause-effect relationship in case-control studies and cohort studies. With the information provided by the Human Genome Project, new epidemiological designs and new statistical methodology have been developed. The addition of molecular biology to traditional epidemiological approaches has given birth to a new discipline known as genetic epidemiology. The objective of this paper is to provide an introduction to concepts needed for assessing the association between genes and specific diseases in population based studies. Firstly, a description of the genetic concepts is presented as a framework for the epidemiological designs and the statistical procedures that have been utilized in genetic epidemiology. Then, a description of the different designs in genetic epidemiology is presented with the most recent publications. Finally, some considerations in the statistical analysis for genetic epidemiology are discussed.

Application of gene shaving and mixture models to cluster microarray gene expression data.

Researchers are frequently faced with the analysis of microarray data of a relatively large number of genes using a small number of tissue samples. We examine the application of two statistical methods for clustering such microarray expression data: EMMIX-GENE and GeneClust. EMMIX-GENE is a mixture-model based clustering approach, designed primarily to cluster tissue samples on the basis of the genes. GeneClust is an implementation of the gene shaving methodology, motivated by research to identify distinct sets of genes for which variation in expression could be related to a biological property of the tissue samples. We illustrate the use of these two methods in the analysis of Affymetrix oligonucleotide arrays of well-known data sets from colon tissue samples with and without tumors, and of tumor tissue samples from patients with leukemia. Although the two approaches have been developed from different perspectives, the results demonstrate a clear correspondence between gene clusters produced by GeneClust and EMMIX-GENE for the colon tissue data. It is demonstrated, for the case of ribosomal proteins and smooth muscle genes in the colon data set, that both methods can classify genes into co-regulated families. It is further demonstrated that tissue types (tumor and normal) can be separated on the basis of subtle distributed patterns of genes. Application to the leukemia tissue data produces a division of tissues corresponding closely to the external classification, acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL), for both methods. In addition, we also identify genes specific for the subgroup of ALL-Tcell samples. Overall, we find that the gene shaving method produces gene clusters at great speed; allows variable cluster sizes and can incorporate partial or full supervision; and finds clusters of genes in which the gene expression varies greatly over the tissue samples while maintaining a high level of coherence between the gene expression profiles. The intent of the EMMIX-GENE method is to cluster the tissue samples. It performs a filtering step that results in a subset of relevant genes, followed by gene clustering, and then tissue clustering, and is favorable in its accuracy of ranking the clusters produced.

A mixture model with random-effects components for clustering correlated gene-expression profiles.

MOTIVATION: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. RESULTS: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation)and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too. AVAILABILITY: A Fortran program blue called EMMIX-WIRE (EM-based MIXture analysis WIth Random Effects) is available on request from the corresponding author.

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays.

MOTIVATION: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. RESULTS: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

Preclinical analysis of the analinoquinazoline AG1478, a specific small molecule inhibitor of EGF receptor tyrosine kinase.

The tyrphostin 4-(3-chloroanilino)-6,7-dimethoxyquinazoline (AG1478) is a potent and specific inhibitor of EGFR tyrosine kinase whose favourable preclinical profile supports progression towards clinical trials. Microphysiometric evaluation revealed a short (<24 min) effective inhibition of cellular receptor response to EGF challenge in BaF/ERX cells indicating a need to maintain sustained levels of inhibitor. Initial pharmacokinetic evaluation in mice of novel AG1478 formulations in a beta-cyclodextrin (Captisol) showed monoexponential elimination from plasma (half-life 30 min) following subcutaneous administration. A two-fold dose escalation gave a 2.4-fold increase in the total AUC. Bolus i.v. and 6 h continuous infusion were investigated in rats to mimic a more clinically relevant administration regimen. Drug elimination following bolus i.v. administration was biphasic (terminal elimination half-life 30-48 min). The linear relationship between dose and AUC(0-->infinity) (r2=0.979) enabled the prediction of infusion rates and doses for sustained delivery using continuous 6 h infusions, where steady state was reached in 120 min. Plasma levels of AG1478>10 microM were achieved over the duration of the infusion. At the lowest dose, plasma drug levels after the cessation of infusion declined with a half-life of approximately 43 min. EGFR activity, measured both by autophosphorylation and downstream signalling, was inhibited in a dose-dependent manner by injection of AG1478 in mice bearing xenografts of the human glioblastoma cell line U87MG.delta2-7, which expresses a constitutively active variant of the EGF receptor. Taken together, these experiments provide essential data to assess the anti-tumour efficacy of AG1478 and will assist in the rational design of dose regimens for clinical studies.

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis.

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulae for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.