Predictive Modeling for Diagnostic Tests with High Specificity, but Low Sensitivity: A Study of the Glycerol Test in Patients with Suspected Menière’s Disease

A high specificity does not ensure that the expected benefit of a diagnostic test outweighs its cost. Problems arise, in particular, when the investigation is expensive, the prevalence of a positive test result is relatively small for the candidate patients, and the sensitivity of the test is low so that the information provided by a negative result is virtually negligible. The consequence may be that a potentially useful test does not gain broader acceptance. Here we show how predictive modeling can help to identify patients for whom the ratio of expected benefit and cost reaches an acceptable level so that testing these patients is reasonable even though testing all patients might be considered wasteful. Our application example is based on a retrospective study of the glycerol test, which is used to corroborate a suspected diagnosis of Menière’s disease. Using the pretest hearing thresholds at up to 10 frequencies, predictions were made by K-nearest neighbor classification or logistic regression. Both methods estimate, based on results from previous patients, the posterior probability that performing the considered test in a new patient will have a positive outcome. The quality of the prediction was evaluated using leave-one-out cross-validation, making various assumptions about the costs and benefits of testing. With reference to all 356 cases, the probability of a positive test result was almost 0.4. For subpopulations selected by K-nearest neighbor classification, which was clearly superior to logistic regression, this probability could be increased up to about 0.6. Thus, the odds of a positive test result were more than doubled

Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery

Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Clustering analysis has a growing role in the study of co-expressed genes for gene discovery. Conventional binary and fuzzy clustering do not embrace the biological reality that some genes may be irrelevant for a problem and not be assigned to a cluster, while other genes may participate in several biological functions and should simultaneously belong to multiple clusters. Also, these algorithms cannot generate tight clusters that focus on their cores or wide clusters that overlap and contain all possibly relevant genes. In this paper, a new clustering paradigm is proposed. In this paradigm, all three eventualities of a gene being exclusively assigned to a single cluster, being assigned to multiple clusters, and being not assigned to any cluster are possible. These possibilities are realised through the primary novelty of the introduction of tunable binarization techniques. Results from multiple clustering experiments are aggregated to generate one fuzzy consensus partition matrix (CoPaM), which is then binarized to obtain the final binary partitions. This is referred to as Binarization of Consensus Partition Matrices (Bi-CoPaM). The method has been tested with a set of synthetic datasets and a set of five real yeast cell-cycle datasets. The results demonstrate its validity in generating relevant tight, wide, and complementary clusters that can meet requirements of different gene discovery studies.National Institute for Health Researc

Robust Estimators in Generalized Pareto Models

This paper deals with optimally-robust parameter estimation in generalized Pareto distributions (GPDs). These arise naturally in many situations where one is interested in the behavior of extreme events as motivated by the Pickands-Balkema-de Haan extreme value theorem (PBHT). The application we have in mind is calculation of the regulatory capital required by Basel II for a bank to cover operational risk. In this context the tail behavior of the underlying distribution is crucial. This is where extreme value theory enters, suggesting to estimate these high quantiles parameterically using, e.g. GPDs. Robust statistics in this context offers procedures bounding the influence of single observations, so provides reliable inference in the presence of moderate deviations from the distributional model assumptions, respectively from the mechanisms underlying the PBHT.Comment: 26pages, 6 figure

Ischaemic strokes in patients with pulmonary arteriovenous malformations and hereditary hemorrhagic telangiectasia: associations with iron deficiency and platelets.

<div><p>Background</p><p>Pulmonary first pass filtration of particles marginally exceeding ∼7 µm (the size of a red blood cell) is used routinely in diagnostics, and allows cellular aggregates forming or entering the circulation in the preceding cardiac cycle to lodge safely in pulmonary capillaries/arterioles. Pulmonary arteriovenous malformations compromise capillary bed filtration, and are commonly associated with ischaemic stroke. Cohorts with CT-scan evident malformations associated with the highest contrast echocardiographic shunt grades are known to be at higher stroke risk. Our goal was to identify within this broad grouping, which patients were at higher risk of stroke.</p><p>Methodology</p><p>497 consecutive patients with CT-proven pulmonary arteriovenous malformations due to hereditary haemorrhagic telangiectasia were studied. Relationships with radiologically-confirmed clinical ischaemic stroke were examined using logistic regression, receiver operating characteristic analyses, and platelet studies.</p><p>Principal Findings</p><p>Sixty-one individuals (12.3%) had acute, non-iatrogenic ischaemic clinical strokes at a median age of 52 (IQR 41–63) years. In crude and age-adjusted logistic regression, stroke risk was associated not with venous thromboemboli or conventional neurovascular risk factors, but with low serum iron (adjusted odds ratio 0.96 [95% confidence intervals 0.92, 1.00]), and more weakly with low oxygen saturations reflecting a larger right-to-left shunt (adjusted OR 0.96 [0.92, 1.01]). For the same pulmonary arteriovenous malformations, the stroke risk would approximately double with serum iron 6 µmol/L compared to mid-normal range (7–27 µmol/L). Platelet studies confirmed overlooked data that iron deficiency is associated with exuberant platelet aggregation to serotonin (5HT), correcting following iron treatment. By MANOVA, adjusting for participant and 5HT, iron or ferritin explained 14% of the variance in log-transformed aggregation-rate (p = 0.039/p = 0.021).</p><p>Significance</p><p>These data suggest that patients with compromised pulmonary capillary filtration due to pulmonary arteriovenous malformations are at increased risk of ischaemic stroke if they are iron deficient, and that mechanisms are likely to include enhanced aggregation of circulating platelets.</p></div

UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

Модернізація стоматологічної установки УС- 30

Background: The novel chemokine CXCL17 acts as chemoattractant for monocytes, macrophages and dendritic cells. CXCL17 also has a role in angiogenesis of importance for tumour development. Methods: Expression of CXCL17, CXCL10, CXCL9 and CCL2 was assessed in primary colon cancer tumours, colon carcinoma cell lines and normal colon tissue at mRNA and protein levels by real-time qRT-PCR, immunohistochemistry, two-colour immunofluorescence and immunomorphometry. Results: CXCL17 mRNA was expressed at 8000 times higher levels in primary tumours than in normal colon (P&lt;0.0001). CXCL17 protein was seen in 17.2% of cells in tumours as compared with 0.07% in normal colon (P = 0.0002). CXCL10, CXCL9 and CCL2 mRNAs were elevated in tumours but did not reach the levels of CXCL17. CXCL17 and CCL2 mRNA levels were significantly correlated in tumours. Concordant with the mRNA results, CXCL10-and CXCL9-positive cells were detected in tumour tissue, but at significantly lower numbers than CXCL17. Two-colour immunofluorescence and single-colour staining of consecutive sections for CXCL17 and the epithelial cell markers carcinoembryonic antigen and BerEP4 demonstrated that colon carcinoma tumour cells indeed expressed CXCL17. Conclusions: CXCL17 is ectopically expressed in primary colon cancer tumours. As CXCL17 enhances angiogenesis and attracts immune cells, its expression could be informative for prognosis in colon cancer patients

Maxillary Tuberosity Reconstruction with Transport Distraction Osteogenesis

Severe bone loss due to pathology in the maxillary tuberosity region is a challenging problem both surgically and prosthetically. Large bone grafts have a poor survival rate due to the delicate bony architecture in this area and presence of the maxillary sinus. Our case presentation describes a new technique for reconstructing severe bony defect in the maxillary tuberosity with horizontal distraction osteogenesis in a 45-year-old man. A 4 × 6 × 3 cm cyst was discovered in the left maxillary molar region and enucleated. Three months postoperatively, the area had a severe bone defect extending to the zygomatic buttress superiorly and hamular notch posteriorly. Three months later, a bone segment including the right upper second premolar was osteotomised and distracted horizontally. The bone segment was distracted 15 mm distally. After consolidation, implants were placed when the distractor was removed. A fixed denture was loaded over the implants after 3 months. Complete alveolar bone loss extending to the cranial base can be reconstructed with transport distraction osteogenesis. Distalisation of the alveolar bone segment adjacent to the bony defect is an easy method for reconstructing such severe defects