Caries prevalence in skeletal series: is it possible to compare?

Because of the relationship with subsistence, dental caries is a central issue in paleopathological research. Usually, comparisons between caries prevalence exhibited in different skeletal series are made. Dietary variation is the most common explanation for cavities prevalence. The aim of this paper is to verify if it is possible to compare caries prevalence reported on papers for archaeological skeletal series. Another goal is to determine if other factors besides diet are implicated in dental cavity prevalence explanation. Twenty six papers about dental health with caries prevalences published from 1999 to 2004 were analyzed for completeness. This assessment includes carious lesion diagnosis and characteristics, age, sex and size characteristics of samples, and prevalence calculation method. The majority of the analyzed papers do not provide adequate information in the topics listed above. Only very few implicated factors other than diet as a contributor to caries lesions development.

CD30 in PTCLS: correlation between RNA and protein levels in a large european series from the LYSA

Introduction: CD22 is expressed on most B-non-Hodgkin lymphomas (NHL); inotuzumab ozogamicin (INO) is an anti-CD22 antibody conjugated to calicheamicin. This study evaluated the safety and tolerability of INO plus R-CVP in patients (pts) with relapsed/refractory CD22+ B-NHL. Efficacy data were also collected. Methods: Part 1 of this open-label study identified a maximum tolerated dose (MTD) of INO 0.8mg/m,2 on day 2 plus R-CVP (rituximab 375mg/m,2 cyclophosphamide 750mg/m,2 and vincristine 1.4mg/m,2 on day 1; prednisone 40mg/m,2 on days 1-5) every 21 days. Subsequently, pts were enrolled in the MTD confirmation cohort (part 2, n = 10), which required a dose-limiting toxicity rate of <33% in cycle 1 and <4 pts discontinuing prior to cycle 3 due to an adverse event (AE) in the MTD expansion cohort (part 3, n = 22), which explored preliminary activity. Results: Parts 2 and 3 enrolled 32 pts: 16 pts with diffuse large B-cell lymphoma, 15 with follicular lymphoma and one with mantle cell lymphoma. Median age was 64.5 years (range 44-81 years); 34% of pts had 1 prior regimen, 34% had 2, 28% had ≥3 and 3% had none (median 2; range 0-6).Median treatment duration was five cycles (range 1-6). Part 2 confirmed the MTD as standard dose R-CVP plus INO 0.8mg/m,2; 2/10 pts had a dose-limiting toxicity (grade 3 increased ALT/AST, grade 4 neutropenia requiring G-CSF). One pt discontinued because of an AE prior to cycle 3. Common treatment-related AEs were thrombocytopenia (78%), neutropenia (66%), fatigue (50%), leukopenia (50%), nausea (41%) and lymphopenia (38%); common grade 3/4 AEs were neutropenia (63%), thrombocytopenia (53%), leukopenia (38%) and lymphopenia (31%). There was one case of treatment-related fatal pneumonia with grade 4 neutropenia. Ten pts discontinued treatment due to AEs; thrombocytopenia/delayed platelet recovery was the leading cause (grade 1/2, n = 6; grade 3/4, n = 3). Objective response rate (ORR) was 77% (n = 24/31 evaluable pts), including 26% (n=8/31) with complete response (CR); three pts had stable disease. Of the pts with follicular lymphoma, ORR was 100% (n = 15/15), including seven pts with CR. Of the pts with diffuse large B-cell lymphoma, ORR was 60% (n = 9/16), including one pt with CR. Conclusions: Results suggest that INOplus R-CVP has acceptable toxicity and promising activity in relapsed/refractory CD22+ B-NHL. The most common grade 3/4 AEs were hematologic. Follow-up for progression-free and overall survival is ongoing.

Effect on mood of subthalamic DBS for Parkinson's disease: a consecutive series of 24 patients

A series of 24 consecutive PD patients were prospectively studied prior to and within 6 months postoperatively for mood, motor, and cognitive status to investigate the effects on mood of subthalamic deep brain stimulation (DBS) in PD. In six patients (25%), mood state worsened significantly, and three were transiently suicidal despite clear motor improvement. Caregivers and patients should be educated about the potential impact of this neurosurgical procedure on mood.

Comprehensive analysis of RET common and rare variant patientsin a series of Spanish Hirschsprung patients confirms a synergistic effect of both kinds of events

Background. RET is the major gene associated to Hirschsprung disease (HSCR) with differential contributions of its rare and common, coding and noncoding mutations to the multifactorial nature of this pathology. In the present study, we have performed a comprehensive study of our HSCR series evaluating the involvement of both RET rare variants (RVs) and common variants (CVs) in the context of the disease. Methods. RET mutational screening was performed by dHPLC and direct sequencing for the identification of RVs. In addition Taqman technology was applied for the genotyping of 3 RET CVs previously associated to HSCR, including a variant lying in an enhancer domain within RET intron 1 (rs2435357). Statistical analyses were performed using the SPSS v.17.0 to analyze the distribution of the variants. Results. Our results confirm the strongest association to HSCR for the "enhancer" variant, and demonstrate a significantly higher impact of it in male versus female patients. Integration of the RET RVs and CVs analysis showed that in 91.66% of cases with both kinds of mutational events, the enhancer allele is in trans with the allele bearing the RET RV. Conclusions. A gender effect exists on both the transmission and distribution of rare coding and common HSCR causing mutations. In addition, these RET CVs and RVs seem to act in a synergistic way leading to HSCR phenotype.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Social network measures for "nosduocentered" networks, their predictive power on performance

Our purpose in this article is to define a network structure which is based on two egos instead of the egocentered (one ego) or the complete network (n egos). We describe the characteristics and properties for this kind of network which we call “nosduocentered network”, comparing it with complete and egocentered networks. The key point for this kind of network is that relations exist between the two main egos and all alters, but relations among others are not observed. After that, we use new social network measures adapted to the nosduocentered network, some of which are based on measures for complete networks such as degree, betweenness, closeness centrality or density, while some others are tailormade for nosduocentered networks. We specify three regression models to predict research performance of PhD students based on these social network measures for different networks such as advice, collaboration, emotional support and trust. Data used are from Slovenian PhD students and their s

Infections after PRK could have a happy ending: a series of three cases.

BACKGROUND: Infectious keratitis after PRK remains a rare but potentially devastating complication. HISTORY AND SIGNS: Medical records of 3 male patients with infectious keratitis after uneventful PRK for myopia and astigmatism were reviewed retrospectively. PRK was performed using the Wavelight Allegretto excimer laser. Postoperative care included a bandage contact lens (BCL) for 5 days, topical antibiotics, ketorolac, and artificial tears. THERAPY AND OUTCOME: Keratitis presented 2 - 4 days postoperatively. In one case, each culture was negative (case 1), and was positive for Streptococcus pneumoniae (case 2) and Staphylococcus aureus (case 3). Final BSCVA (best spectacle corrected visual acuity) after intensive antibiotic treatment and removal of BCL were 1.0 (case 1), 0.9 (case 2) and 0.3 correctable to 0.8 with pinhole (case 3). CONCLUSIONS: Postoperative broad-spectrum antibiotics are mandatory after PRK to prevent infectious keratitis. However, resistant organisms are more and more common. The presence of a bandage soft contact lens after surgery is an unfavourable element that may increase risk of infection. Based on our case series, we suggest limiting soft contact lens wear during the two postoperative days even if the corneal ulceration is not healed.

Compositional Data Analysis with R

R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computingand graphics. The environment in which many classical and modern statistical techniques havebeen implemented, but many are supplied as packages. There are 8 standard packages and many moreare available through the cran family of Internet sites http://cran.r-project.org .We started to develop a library of functions in R to support the analysis of mixtures and our goal isa MixeR package for compositional data analysis that provides support foroperations on compositions: perturbation and power multiplication, subcomposition with or withoutresiduals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances,compositional Kullback-Leibler divergence etc.graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features:barycenter, geometric mean of the data set, the percentiles lines, marking and coloring ofsubsets of the data set, theirs geometric means, notation of individual data in the set . . .dealing with zeros and missing values in compositional data sets with R procedures for simpleand multiplicative replacement strategy,the time series analysis of compositional data.We’ll present the current status of MixeR development and illustrate its use on selected data sets

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.

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts