Bayesian estimation of range for microsatellite loci.

Microsatellite loci have become important in population genetics because of their high level of polymorphism in natural populations, very frequent occurrence throughout the genome, and apparently high mutation rate. Observed repeat numbers (alleles size) in natural populations and expectations based on computer simulations suggest that the range of repeat numbers at a microsatellite locus is restricted. This range is a key parameter that should be properly estimated in order to proceed with calculations of divergence times in phylogenetic studies and to better investigate the within- and between-population variability. The 'plug-in' estimate of range based on the minimum and maximum value observed in a sample is not satisfactory because of the relatively large number of alleles in comparison with typical sample sizes. In this paper, a set of data from 30 dinucleotide microsatellite loci is analysed under the assumption of independence among loci. Bayesian inference on range for one locus is obtained by assuming that constraints on range values exist as sharp bounds. Closed-form calculations and robustness revealed by our analysis suggest that the proposed Bayesian approach might be routinely used by researchers to classify microsatellite loci according to the estimated value of their allelic range

Chain Graph Models to Elicit the Structure of a Bayesian Network

Bayesian networks are possibly the most successful graphical models to build decision support systems. Building the structure of large networks is still a challenging task, but Bayesian methods are particularly suited to exploit experts’ degree of belief in a quantitative way while learning the network structure from data. In this paper details are provided about how to build a prior distribution on the space of network structures by eliciting a chain graph model on structural reference features. Several structural features expected to be often useful during the elicitation are described. The statistical background needed to effectively use this approach is summarized, and some potential pitfalls are illustrated. Finally, a few seminal contributions from the literature are reformulated in terms of structural features

on prefermentative maceration techniques statistical analysis of sensory descriptors in sangiovese wine

SummaryThe analysis of wine sensory descriptors is a fundamental step in the improvement of wine making, because the procedures are judged just before bottled wine is ready for consumption. Despite several contributions in the literature, traditional analysis of variance methods are not adequate to analyse sensory descriptors, because they are defined on ordinal scales. In this paper, we exploit cumulative link mixed models in a three-way full factorial design to assess the effect of prefermentative maceration, temperature and saignée on wine sensory descriptors. Using cumulative link mixed models, the bias introduced by assessors' judgement and the ordinal scale of sensory descriptors are taken into account. The results were the following: the application of prefermentative maceration techniques did not lead to an improvement in the sensory profile of wines after a year from bottling; wines treated with saignée showed greater intensity in olfactive descriptors; and higher fermentation temperatures resulted in wines that were generally more concentrated

Conditional independence relations among biological markers may improve clinical decision as in the case of triple negative breast cancers

The associations existing among different biomarkers are important in clinical settings because they contribute to the characterisation of specific pathways related to the natural history of the disease, genetic and environmental determinants. Despite the availability of binary/linear (or at least monotonic) correlation indices, the full exploitation of molecular information depends on the knowledge of direct/indirect conditional independence (and eventually causal) relationships among biomarkers, and with target variables in the population of interest. In other words, that depends on inferences which are performed on the joint multivariate distribution of markers and target variables. Graphical models, such as Bayesian Networks, are well suited to this purpose. Therefore, we reconsidered a previously published case study on classical biomarkers in breast cancer, namely estrogen receptor (ER), progesterone receptor (PR), a proliferative index (Ki67/MIB-1) and to protein HER2/neu (NEU) and p53, to infer conditional independence relations existing in the joint distribution by inferring (learning) the structure of graphs entailing those relations of independence. We also examined the conditional distribution of a special molecular phenotype, called triple-negative, in which ER, PR and NEU were absent. We confirmed that ER is a key marker and we found that it was able to define subpopulations of patients characterized by different conditional independence relations among biomarkers. We also found a preliminary evidence that, given a triple-negative profile, the distribution of p53 protein is mostly supported in 'zero' and 'high' states providing useful information in selecting patients that could benefit from an adjuvant anthracyclines/alkylating agent-based chemotherapy

A human-neutral large carnivore? No patterns in the body mass of gray wolves across a gradient of anthropization

The gray wolf (Canis lupus) expanded its distribution in Europe over the last few decades. To better understand the extent to which wolves could re-occupy their historical range, it is important to test if anthropization can affect their fitness-related traits. After having accounted for ecologically relevant confounders, we assessed how anthropization influenced i) the growth of wolves during their first year of age (n = 53), ii) sexual dimorphism between male and female adult wolves (n = 121), in a sample of individuals that had been found dead in Italy between 1999 and 2021. Wolves in anthropized areas have a smaller overall variation in their body mass, during their first year of age. Because they already have slightly higher body weight at 3–5 months, possibly due to the availability of human-derived food sources. The difference in the body weight of adult females and males slightly increases with anthropization. However, this happens because of an increase in the body mass of males only, possibly due to sex-specific differences in dispersal and/or to “dispersal phenotypes”. Anthropization in Italy does not seem to have any clear, nor large, effect on the body mass of wolves. As body mass is in turn linked to important processes, like survival and reproduction, our findings indicates that wolves could potentially re-occupy most of their historical range in Europe, as anthropized landscapes do not seem to constrain such of an important life-history trait. Wolf management could therefore be needed across vast spatial scales and in anthropized areas prone to social conflicts

Irradiation and SPS Beam Tests of the Alice1LHCb Pixel Chip

The Alice1LHCb front-end chip has been designed for the ALICE pixel and the LHCb RICH detectors. It is fabricated in a commercial 0.25 µm CMOS technology, with special design techniques to obtain radiation tolerance. The chip has been irradiated with low energy protons and heavy ions, to determine the cross-section for Single Event Upsets (SEU), and with X-rays to evaluate the sensitivity to total ionising dose. We report the results of those measurements. We also report preliminary results of measurements done with 150 GeV pions at the CERN SPS