Biomedical subjects

C Furlanello

Publications and source records attributed to C Furlanello.

4 recordsLinked to original sources

PubMed1998

Cardiac arrest and sudden death in competitive athletes with arrhythmogenic right ventricular dysplasia.

Arrhythmogenic right ventricular dysplasia (ARVD) is a predisposing factor for sport-related cardiac arrest (CA), sudden cardiac death (SD), and life-threatening ventricular tachyarrhythmias (VT). The aim of this study was the assessment of athletes with ARVD, particularly the CA survivors. From 1974 to January 1996, 1642 competitive athletes (aver. 25.5 yr.), 136 of whom were top level athletes (TLA), were studied for important arrhythmic manifestations. All athletes underwent an individualised study protocol including a series of non invasive and invasive diagnostic techniques. One hundred and one athletes (90 males, 11 females, aver. 25.9 yr.) were diagnosed as being affected by ARVD on the basis of the WHO/ISFC criteria. The same percentage (about 6%) of ARVD is present in both the general arrhythmic athletes population and in the subgroup of TLA. Prevalence of ARVD among athletes with CA or SD is high (respectively 23% and 25%), confirming the observation that ARVD is one of the major causes of SD in Italian athletes. All CA were athletic activity related, indicating the potentiality of exercise as a cause of electrical destabilisation in subjects with ARVD. In athletes with documented ARVD intense sport activity has to be proscribed. In athletes at risk of CA or SD an aggressive treatment, ICD implantation and RF catheter ablation must be taken into consideration.

Adult↗

PubMed1997

Ixodes ricinus (Acari: Ixodidae) infestation on roe deer (Capreolus capreolus) in Trentino, Italian Alps.

The most important tick-deer system potentially supporting the epidemiology of Lyme disease in the Italian Alps is that regarding Ixodes ricinus (L.) and roe deer (Capreolus capreolus L.). In this study, the pattern of tick infestation on 562 male roe deer harvested in September 1994 in 56 game districts of Trentino, Northern Italy, was assessed. The prevalence and density of infestation by I. ricinus were analyzed by a model based on classification and regression trees (CART), using both discrete and continuous variables concerning environmental and host parameters. The model discriminated attitude and host density as the 2 variables having the greatest effect on the prevalence and density of infestation of deer; the levels of infestation were higher at an altitude below 1125 m or at roe deer densities over 8.5 head per 100 ha. The density of tick infestation tended to be higher in older roe deer.

Age Factors↗

PubMed1996

Classification tree methods for analysis of mesoscale distribution of Ixodes ricinus (Acari:Ixodidae) in Trentino, Italian Alps.

Cases of Lyme disease and tick-borne encephalitis were recognized recently in the Province of Trento, Italian Alps. Assessment of areas of potential risk for these tick-borne diseases is carried out by a model based on classification and regression trees (CART), using both discrete and continuous variables. Data on Ixodes ricinus (L.) occurrence resulted from extensive sampling carried out by standard methods in 99 sites over an area of approximately 2,700 km2 in the Province of Trento. A series of environmental parameters were recorded from each site and population densities of roe deer, Capreolus capreolus (L.), were considered. The CART model discriminates 2 variables that appear to have the greatest effect on the mesoscale occurrence of ticks: altitude and geological substratum, with a drastic decrease of tick frequency above an altitude of approximately 1,100 m and on volcanic substrata. The model is effective in identifying the mesoscale areas at greater potential risk, with a relatively low sampling effort.

Animals↗

PubMedDate not supplied

An accelerated procedure for recursive feature ranking on microarray data.

We describe a new wrapper algorithm for fast feature ranking in classification problems. The Entropy-based Recursive Feature Elimination (E-RFE) method eliminates chunks of uninteresting features according to the entropy of the weights distribution of a SVM classifier. With specific regard to DNA microarray datasets, the method is designed to support computationally intensive model selection in classification problems in which the number of features is much larger than the number of samples. We test E-RFE on synthetic and real data sets, comparing it with other SVM-based methods. The speed-up obtained with E-RFE supports predictive modeling on high dimensional microarray data.

Oligonucleotide Array Sequence Analysis↗