In vitro activity of fosfomycin against extended-spectrum-beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae: comparison of susceptibility testing procedures

The agar dilution, broth microdilution, and disk diffusion methods were compared to determine the in vitro susceptibility of 428 extended-spectrum-beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae to fosfomycin. Fosfomycin showed very high activity against all ESBL-producing strains. Excellent agreement between the three susceptibility methods was found for E. coli, whereas marked discrepancies were observed for K. pneumoniae.

Detection of ingested cocaine-filled packets: comparison of filtered back projection CT with adaptive statistical iterative reconstructed images

Purpose: To evaluate the diagnostic value and image quality of CT with filtered back projection (FBP) compared with adaptive statistical iterative reconstructed images (ASIR) in body stuffers with ingested cocaine-filled packets.Methods and Materials: Twenty-nine body stuffers (mean age 31.9 years, 3 women) suspected for ingestion of cocaine-filled packets underwent routine-dose 64-row multidetector CT with FBP (120kV, pitch 1.375, 100-300 mA and automatic tube current modulation (auto mA), rotation time 0.7sec, collimation 2.5mm), secondarily reconstructed with 30 % and 60 % ASIR. In 13 (44.83%) out of the body stuffers cocaine-filled packets were detected, confirmed by exact analysis of the faecal content including verification of the number (range 1-25). Three radiologists independently and blindly evaluated anonymous CT examinations (29 FBP-CT and 68 ASIR-CT) for the presence and number of cocaine-filled packets indicating observers' confidence, and graded them for diagnostic quality, image noise, and sharpness. Sensitivity, specificity, area under the receiver operating curve (ROC) Az and interobserver agreement between the 3 radiologists for FBP-CT and ASIR-CT were calculated.Results: The increase of the percentage of ASIR significantly diminished the objective image noise (p<0.001). Overall sensitivity and specificity for the detection of the cocaine-filled packets were 87.72% and 76.15%, respectively. The difference of ROC area Az between the different reconstruction techniques was significant (p= 0.0101), that is 0.938 for FBP-CT, 0.916 for 30 % ASIR-CT, and 0.894 for 60 % ASIR-CT.Conclusion: Despite the evident image noise reduction obtained by ASIR, the diagnostic value for detecting cocaine-filled packets decreases, depending on the applied ASIR percentage.

Analysis of TNFAIP3, a feedback inhibitor of nuclear factor-κB and the neighbor intergenic 6q23 region in rheumatoid arthritis susceptibility

INTRODUCTION Genome-wide association studies of rheumatoid arthritis (RA) have identified an association of the disease with a 6q23 region devoid of genes. TNFAIP3, an RA candidate gene, flanks this region, and polymorphisms in both the TNFAIP3 gene and the intergenic region are associated with systemic lupus erythematosus. We hypothesized that there is a similar association with RA, including polymorphisms in TNFAIP3 and the intergenic region. METHODS To test this hypothesis, we selected tag-single nucleotide polymorphisms (SNPs) in both loci. They were analyzed in 1,651 patients with RA and 1,619 control individuals of Spanish ancestry. RESULTS Weak evidence of association was found both in the 6q23 intergenic region and in the TNFAIP3 locus. The rs582757 SNP and a common haplotype in the TNFAIP3 locus exhibited association with RA. In the intergenic region, two SNPs were associated, namely rs609438 and rs13207033. The latter was only associated in patients with anti-citrullinated peptide antibodies. Overall, statistical association was best explained by the interdependent contribution of SNPs from the two loci TNFAIP3 and the 6q23 intergenic region. CONCLUSIONS Our data are consistent with the hypothesis that several RA genetic factors exist in the 6q23 region, including polymorphisms in the TNFAIP3 gene, like that previously described for systemic lupus erythematosus.

Postmortem circulation: a new model for testing endovascular devices and training clinicians in their use.

The development of new medical devices, such as aortic valves, requires numerous preliminary studies on animals and training of personnel on cadavers before the devices can be used in patients. Postmortem circulation, a technique used for postmortem angiography, allows the vascular system to be reperfused in a way similar to that in living persons. This technique is used for postmortem investigations to visualize the human vascular system and to make vascular diagnoses. Specific material for reperfusing a human body was developed recently. Our aim was to investigate whether postmortem circulation that imitates in vivo conditions allows for the testing of medical materials on cadavers. We did this by delivering an aortic valve using minimally invasive methods. Postmortem circulation was established in eight corpses to recreate an environment as close as possible to in vivo conditions. Mobile fluoroscopy and a percutaneous catheterization technique were used to deliver the material to the correct place. Once the valve was implanted, the heart and primary vessels were extracted to confirm its position. Postmortem circulation proved to be essential in several of the cadavers because it helped the clinicians to deliver the material and improve their implantation techniques. Due to the intravascular circulation, sites with substantial arteriosclerotic stenosis could be bypassed, which would have been impossible without perfusion. Although originally developed for postmortem investigations, this reperfusion technique could be useful for testing new medical devices intended for living patients.

Statistical modeling on (α, +∞)

Observations in daily practice are sometimes registered as positive values larger then a given threshold α. The sample space is in this case the interval (α,+∞), α & 0, which can be structured as a real Euclidean space in different ways. This fact opens the door to alternative statistical models depending not only on the assumed distribution function, but also on the metric which is considered as appropriate, i.e. the way differences are measured, and thus variability

Statistical modeling on coordinates

This paper is a first draft of the principle of statistical modelling on coordinates. Several causes —which would be long to detail—have led to this situation close to the deadline for submitting papers to CODAWORK’03. The main of them is the fast development of the approach along thelast months, which let appear previous drafts as obsolete. The present paper contains the essential parts of the state of the art of this approach from my point of view. I would like to acknowledge many clarifying discussions with the group of people working in this field in Girona, Barcelona, Carrick Castle, Firenze, Berlin, G¨ottingen, and Freiberg. They have given a lot of suggestions and ideas. Nevertheless, there might be still errors or unclear aspects which are exclusively my fault. I hope this contribution serves as a basis for further discussions and new developments

Testing of Diagnostic Methods for Detection of Influenza Virusfor Optimal Performance in the Context of an Influenza Surveillance Network

Influenza surveillance networks must detect early the viruses that will cause the forthcoming annual epidemics and isolate the strains for further characterization. We obtained the highest sensitivity (95.4%) with a diagnostic tool that combined a shell-vial assay and reverse transcription-PCR on cell culture supernatants at 48 h, and indeed, recovered the strain

Robust regression in biological assay: application to the evaluation of alternative experimental techniques.

Robust Huber type regression and testing of linear hypotheses are adapted to statistical analysis of parallel line and slope ratio assays. They are applied in the evaluation of results of several experiments carried out in order to compare and validate alternatives to animal experimentation based on embryo and cell cultures. Computational procedures necessary for the application of robust methods of analysis used the conversational statistical package ROBSYS. Special commands for the analysis of parallel line and slope ratio assays have been added to ROBSYS.

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

The agreement between ipsative and normative questionnaires using compositional data analysis techniques

The main instrument used in psychological measurement is the self-report questionnaire. One of its majordrawbacks however is its susceptibility to response biases. A known strategy to control these biases hasbeen the use of so-called ipsative items. Ipsative items are items that require the respondent to makebetween-scale comparisons within each item. The selected option determines to which scale the weight ofthe answer is attributed. Consequently in questionnaires only consisting of ipsative items everyrespondent is allotted an equal amount, i.e. the total score, that each can distribute differently over thescales. Therefore this type of response format yields data that can be considered compositional from itsinception.Methodological oriented psychologists have heavily criticized this type of item format, since the resultingdata is also marked by the associated unfavourable statistical properties. Nevertheless, clinicians havekept using these questionnaires to their satisfaction. This investigation therefore aims to evaluate bothpositions and addresses the similarities and differences between the two data collection methods. Theultimate objective is to formulate a guideline when to use which type of item format.The comparison is based on data obtained with both an ipsative and normative version of threepsychological questionnaires, which were administered to 502 first-year students in psychology accordingto a balanced within-subjects design. Previous research only compared the direct ipsative scale scoreswith the derived ipsative scale scores. The use of compositional data analysis techniques also enables oneto compare derived normative score ratios with direct normative score ratios. The addition of the secondcomparison not only offers the advantage of a better-balanced research strategy. In principle it also allowsfor parametric testing in the evaluation

Testing the validity of a set of diagnostic criteria for sensory neuronopathies: a francophone collaborative study.

There are no validated criteria for the diagnosis of sensory neuronopathy (SNN) yet. In a preliminary monocenter study a set of criteria relying on clinical and electrophysiological data showed good sensitivity and specificity for a diagnosis of probable SNN. The aim of this study was to test these criteria on a French multicenter study. 210 patients with sensory neuropathies from 15 francophone reference centers for neuromuscular diseases were included in the study with an expert diagnosis of non-SNN, SNN or suspected SNN according to the investigations performed in these centers. Diagnosis was obtained independently from the set of criteria to be tested. The expert diagnosis was taken as the reference against which the proposed SNN criteria were tested. The set relied on clinical and electrophysiological data easily obtainable with routine investigations. 9/61 (16.4 %) of non-SNN patients, 23/36 (63.9 %) of suspected SNN, and 102/113 (90.3 %) of SNN patients according to the expert diagnosis were classified as SNN by the criteria. The SNN criteria tested against the expert diagnosis in the SNN and non-SNN groups had 90.3 % (102/113) sensitivity, 85.2 % (52/61) specificity, 91.9 % (102/111) positive predictive value, and 82.5 % (52/63) negative predictive value. Discordance between the expert diagnosis and the SNN criteria occurred in 20 cases. After analysis of these cases, 11 could be reallocated to a correct diagnosis in accordance with the SNN criteria. The proposed criteria may be useful for the diagnosis of probable SNN in patients with sensory neuropathy. They can be reached with simple clinical and paraclinical investigations.

A compositional statistical analysis of capital stock

Most of economic literature has presented its analysis under the assumption of homogeneous capital stock.However, capital composition differs across countries. What has been the pattern of capital compositionassociated with World economies? We make an exploratory statistical analysis based on compositional datatransformed by Aitchinson logratio transformations and we use tools for visualizing and measuring statisticalestimators of association among the components. The goal is to detect distinctive patterns in the composition.As initial findings could be cited that:1. Sectorial components behaved in a correlated way, building industries on one side and , in a lessclear view, equipment industries on the other.2. Full sample estimation shows a negative correlation between durable goods component andother buildings component and between transportation and building industries components.3. Countries with zeros in some components are mainly low income countries at the bottom of theincome category and behaved in a extreme way distorting main results observed in the fullsample.4. After removing these extreme cases, conclusions seem not very sensitive to the presence ofanother isolated cases

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Modern statistical models for forensic fingerprint examinations : a critical review

Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.

One person with two DNA profiles: a(nother) case of mosaicism or chimerism.

Nuclear DNA markers, such as short tandem repeats (STR), are widely used for crime investigation and paternity testing. STR were used to determine whether a piece of tissue regurgitated by a dog was part of the penis of a dead, emasculated, man. Unexpectedly, when analyzing the recovered material and a blood sample from the deceased, five out of the 18 loci differed. According to the results, one could have concluded that these samples originated from two different persons. However, taking into account contextual information and data from complementary genetic analyses, the most likely hypothesis was that the deceased was a genetic mosaic or a chimera. Within a forensic genetic context, such genetic peculiarities may prevent associating the perpetrator of an offense with a stain left at a crime scene or lead to false paternity exclusions. Fast recognition of mosaics or chimeras, adapted sampling scheme, as well as careful interpretation of the data should allow avoiding such pitfalls.