Using non–invasive genetic techniques to assist in maned wolf conservation in a remnant fragment of the Brazilian Cerrado

The maned wolf is a South American canid considered a keystone species of the Cerrado. We performed a genetic assessment of maned wolves that inhabit a small remnant fragment of the Cerrado in Brazil. We collected 84 fecal samples over a year and also included two tissue samples from road–killed animals. We successfully identified the species, sex, and individuals using molecular markers. Using microsatellite loci analysis we identified 13 different individuals, eight females and five males. The genetic variability level found and the high number of individuals detected indicates the presence of an open population

HbA1c variability as an independent correlate of nephropathy, but not retinopathy, in patients with type 2 diabetes: The renal insufficiency and cardiovascular events (RIACE) Italian Multicenter Study

OBJECTIVE: To examine the association of hemoglobin (Hb) A1c variability with microvascular complications in the large cohort of subjects with type 2 diabetes from the Renal Insufficiency And Cardiovascular Events (RIACE) Italian Multicenter Study. RESEARCH DESIGN AND METHODS: Serial (3-5) HbA1c values collected in a 2-year period before enrollment were available from 8,260 subjects from 9 centers (of 15,773 patients from 19 centers). HbA1c variability was measured as the intraindividual SD of 4.52 \ub1 0.76 values. Diabetic retinopathy (DR) was assessed by dilated funduscopy. Chronic kidney disease (CKD) was defined based on albuminuria, as measured by immunonephelometry or immunoturbidimetry, and estimated glomerular filtration rate (eGFR) was calculated from serum creatinine. RESULTS: Median and interquartile range of average HbA1c (HbA1c-MEAN) and HbA1c-SD were 7.57% (6.86-8.38) and 0.46% (0.29-0.74), respectively. The highest prevalence of microalbuminuria, macroalbuminuria, reduced eGFR, albuminuric CKD phenotypes, and advanced DR was observed when both HbA1c parameters were above the median and the lowest when both were below the median. Logistic regression analyses showed that HbA1c-SD adds to HbA1c-MEAN as an independent correlate of microalbuminuria and stages 1-2 CKD and is an independent predictor of macroalbuminuria, reduced eGFR, and stages 3-5 albuminuric CKD, whereas HbA1c-MEAN is not. The opposite was found for DR, whereas neither HbA1c-MEAN nor HbA1c-SD affected nonalbuminuric CKD. CONCLUSIONS: In patients with type 2 diabetes, HbA1c variability affects (albuminuric) CKD more than average HbA1c, whereas only the latter parameter affects DR, thus suggesting a variable effect of these measures on microvascular complications

Transient massive hyperlipidaemia in a type 2 diabetic subject

A 50-year-old man, in apparently good health, was referred to the Lipid Center of San Luigi Gonzaga Hospital, Orbassano (Turin, Italy), by his primary care physician (PCP) because clinical tests at the time of blood donation showed milky plasma with serious hypertriglyceridaemia (>5000 mg/dl) and hyperglycaemia (381 mg/dl), diagnostic for diabetes. It was not possible to perform further blood chemical analyses because hypertriglyceridaemia would have provided abnormal results. The patient entered the hospital to prevent acute pancreatitis, which is often associated with severe hypertriglyceridaemi

A Hybrid Spam Detection Method Based on Unstructured Datasets

This document is the accepted manuscript version of the following article: Shao, Y., Trovati, M., Shi, Q. et al. Soft Comput (2017) 21: 233. The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-015-1959-z. © Springer-Verlag Berlin Heidelberg 2015.The identification of non-genuine or malicious messages poses a variety of challenges due to the continuous changes in the techniques utilised by cyber-criminals. In this article, we propose a hybrid detection method based on a combination of image and text spam recognition techniques. In particular, the former is based on sparse representation-based classification, which focuses on the global and local image features, and a dictionary learning technique to achieve a spam and a ham sub-dictionary. On the other hand, the textual analysis is based on semantic properties of documents to assess the level of maliciousness. More specifically, we are able to distinguish between meta-spam and real spam. Experimental results show the accuracy and potential of our approach.Peer reviewedFinal Accepted Versio

Modelling the radiation action for the estimation of biological effects in humans

It is well known that ionizing radiation can induce biological effects at different levels, from DNA, chromosomes and cells up to tissues, organs and entire organisms. Theoretical models and Monte Carlo codes, especially those based on radiation track structure, can be of great help to elucidate the underlying mechanisms and to perform reliable predictions where data are lacking. In this work we will present and discuss a mechanistic ab initio model and a Monte Carlo code able to simulate the induction of chromosome aberrations (CAs) in human cells. This endpoint is particularly relevant, since some aberration types can lead to cell death, while others can lead to cell conversion to malignancy. The model is based on the hypothesis that only clustered lesions (CLs) of the DNA double-helix can evolve into aberrations. Simulated dose-response curves for CAs induced by different radiation types (including heavy ions) will be shown, together with applications to cancer risk estimation and biodosimetry. In this framework, we will also discuss examples of medical applications - including astronauts' exposure to space radiation - obtained with the FLUKA code, also taking into account the role of nuclear interactions

The FLUKA Code: An Overview

FLUKA is a multipurpose Monte Carlo code which can transport a variety of particles over a wide energy range in complex geometries. The code is a joint project of INFN and CERN: part of its development is also supported by the University of Houston and NASA. FLUKA is successfully applied in several fields, including but not only, particle physics, cosmic ray physics, dosimetry, radioprotection, hadron therapy, space radiation, accelerator design and neutronics. The code is the standard tool used at CERN for dosimetry, radioprotection and beam-machine interaction studies. Here we give a glimpse into the code physics models with a particular emphasis to the hadronic and nuclear sector