Copy number variant scan in more than four thousand Holstein cows bred in Lombardy, Italy.

Copy Number Variants (CNV) are modifications affecting the genome sequence of DNA, for instance, they can be duplications or deletions of a considerable number of base pairs (i.e., greater than 1000 bp and up to millions of bp). Their impact on the variation of the phenotypic traits has been widely demonstrated. In addition, CNVs are a class of markers useful to identify the genetic biodiversity among populations related to adaptation to the environment. The aim of this study was to detect CNVs in more than four thousand Holstein cows, using information derived by a genotyping done with the GGP (GeneSeek Genomic Profiler) bovine 100K SNP chip. To detect CNV the SVS 8.9 software was used, then CNV regions (CNVRs) were detected. A total of 123,814 CNVs (4,150 non redundant) were called and aggregated into 1,397 CNVRs. The PCA results obtained using the CNVs information, showed that there is some variability among animals. For many genes annotated within the CNVRs, the role in immune response is well known, as well as their association with important and economic traits object of selection in Holstein, such as milk production and quality, udder conformation and body morphology. Comparison with reference revealed unique CNVRs of the Holstein breed, and others in common with Jersey and Brown. The information regarding CNVs represents a valuable resource to understand how this class of markers may improve the accuracy in prediction of genomic value, nowadays solely based on SNPs markers.

Integration of the cancer-related inflammatory response as a stratifying biomarker of survival in hepatocellular carcinoma treated with sorafenib.

BACKGROUND AND AIMS: Response to sorafenib is highly variable in hepatocellular carcinoma (HCC). Baseline inflammatory parameters and treatment toxicities may improve survival prediction in patients on sorafenib therapy. RESULTS: 442 patients with advanced stage HCC on sorafenib were recruited (follow-up 5096 person-months at risk). 88% had BCLC stage B or greater HCC and 72.3% had Child-Pugh A cirrhosis. On Cox multivariate regression, previously-treated HCC (HR 0.579, 95% CI 0.385-0.872, p=0.009), Cancer of Liver Italian Program (CLIP) score (HR 1.723, 95% CI 1.462-2.047, p<0.0001), baseline red cell distribution width (RDW; HR 1.234, 95% CI 1.115-1.290, p<0.0001) and neutrophil to lymphocyte ratio (NLR; HR 1.218, 95% CI 1.108-1.322, p<0.0001) were significant independent risks for shorter survival, whilst sorafenib-related diarrhoea was associated with prolonged survival (HR 0.533, 95% CI 0.373-0.763, p=0.001). The combination of RD-CLIP score (CLIP score multiplied by RDW) ≥ 70 and no treatment-related diarrhoea had good utility for predicting 3-month survival (AUC of 0.808 (95% CI 0.734-0.882), positive predictive value of 86.4% and negative predictive value of 83.3%), compared with CLIP (AUC=0.642) or BCLC score alone (AUC=0.579). RD-CLIP score ≥ 35 and no treatment-related diarrhoea had an AUC of 0.787 for predicting 12-month survival. METHODS: Patients with HCC were consecutively recruited from three tertiary centres (Japan, Italy and UK) and clinical data were prospectively collected. The primary study endpoint was overall survival (OS) after commencing sorafenib. CONCLUSION: The novel prognostic index of CLIP score combined with inflammatory marker RDW and treatment-related diarrhoea has good accuracy for predicting overall, 3 month and 12 month survival in patients on sorafenib.

Locating bomb factories by detecting hydrogen peroxide.

The analytical capability to detect hydrogen peroxide vapour can play a key role in localizing a site where a H2O2 based Improvised Explosive (IE) is manufactured. In security activities it is very important to obtain information in a short time. For this reason, an analytical method to be used in security activity needs portable devices. The authors have developed the first analytical method based on a portable luminometer, specifically designed and validated to locate IE manufacturing sites using quantitative on-site vapour analysis for H2O2. The method was tested both indoor and outdoor. The results demonstrate that the detection of H2O2 vapours could allow police forces to locate the site, while terrorists are preparing an attack. The collected data are also very important in developing new sensors, able to give an early alarm if located at a proper distance from a site where an H2O2 based IE is prepared.

The potential of spectral and hyperspectral-imaging techniques for bacterial detection in food: A case study on lactic acid bacteria.

Official methods for the detection of bacteria are based on culture techniques. These methods have limitations such as time consumption, cost, detection limits and the impossibility to analyse a large number of samples. For these reasons, the development of rapid, low-cost and non-destructive analytical methods is a task of growing interest. In the present study, the capability of spectral and hyperspectral techniques to detect bacterial surface contamination was investigated preliminarily on gel cultures, and subsequently on sliced cooked ham. In more detail, two species of lactic acid bacteria (LAB) were considered, namely Lactobacillus curvatus and Lactobacillus sakei, both of which are responsible for common alterations in sliced cooked ham. Three techniques were investigated, with different equipment, respectively: a macroscopic hyperspectral scanner operating in the NIR (10,470-5880cm(-1)) region, a FT-NIR spectrophotometer equipped with a transmission arm as the sampling tool, working in the 12,500-5800cm(-1) region, and a FT-MIR microscopy operating in the 4000-675cm(-1) region. Multivariate exploratory data analysis, in particular principal component analysis (PCA), was applied in order to extract useful information from original data and from hyperspectrograms. The results obtained demonstrate that the spectroscopic and imaging techniques investigated can represent an effective and sensitive tool to detect surface bacterial contamination in samples and, in particular, to recognise species to which bacteria belong.

Altered glucose metabolism rather than naive type 2 diabetes mellitus (T2DM) is related to vitamin D status in severe obesity.

CONTEXT: The last decades have provided insights into vitamin D physiology linked to glucose homeostasis. Uncertainties remain in obesity due to its intrinsic effects on vitamin D and glucose tolerance. OBJECTIVES: To assess the relationship between vitamin D and glucose abnormalities in severely obese individuals previously unknown to suffer from abnormal glucose metabolism. SETTING: Tertiary care centre. PATIENTS: 524 obese patients (50.3 ± 14.9 yrs; BMI, 47.7 ± 7.3 kg/m2) screened by OGTT, HbA1c and the lipid profile. Vitamin D status was assessed by 25(OH)D3, PTH and electrolyte levels. 25(OH)D3 deficiency/insufficiency were set at 20 and 30 ng/ml, respectively. All comparative and regression analyses were controlled for age, BMI and gender. RESULTS: The prevalence of vitamin D deficiency/insufficiency and secondary hyperparathyroidism were 95% and 50.8%, respectively. Normal glucose tolerance (NGT), impaired fasting glucose (IFG) or impaired glucose tolerance (IGT), and type 2 diabetes mellitus (T2DM) were found in 37.8%, 40.5% and 21.7% of cases, respectively. Large variations in metabolic parameters were seen across categories of vitamin D status, but the only significant differences were found for C-peptide, tryglicerides, LDL- and HDL-cholesterol levels (p < 0.05 for all). The prevalence of vitamin D deficiency was documented to be slightly but significantly more frequent in glucose-intolerant patients (IFG + IGT + T2DM) compared to the -normotolerant counterpart (87% vs. 80%, p < 0.05). In partial correlation analyses, there was no association between vitamin D levels and glucose-related markers but for HbA1c (r = -0.091, p < 0.05), and both basal and OGTT-stimulated insulin levels (r = 0.097 and r = 0.099; p < 0.05 for all). Vitamin D levels were also correlated to HDL-cholesterol (r = 0.13, p = 0.002). Multivariate regression analysis inclusive of vitamin D, age, BMI, gender and fat mass as independent variables, showed that vitamin D was capable of predicting HbA1c levels (ß = -0.101, p < 0.05). CONCLUSIONS: Given the inherent effect of obesity on vitamin D and glucose homeostasis, current data suggest a potential independent role for vitamin D in the regulation of glucose metabolism in a setting of obese patients previously unknown to harbour glucose metabolism abnormalities.

Handling large datasets of hyperspectral images: reducing data size without loss of useful information.

Hyperspectral Imaging (HSI) is gaining increasing interest in the field of analytical chemistry, since this fast and non-destructive technique allows one to easily acquire a large amount of spectral and spatial information on a wide number of samples in very short times. However, the large size of hyperspectral image data often limits the possible uses of this technique, due to the difficulty of evaluating many samples altogether, for example when one needs to consider a representative number of samples for the implementation of on-line applications. In order to solve this problem, we propose a novel chemometric strategy aimed to significantly reduce the dataset size, which allows to analyze in a completely automated way from tens up to hundreds of hyperspectral images altogether, without losing neither spectral nor spatial information. The approach essentially consists in compressing each hyperspectral image into a signal, named hyperspectrogram, which is created by combining several quantities obtained by applying PCA to each single hyperspectral image. Hyperspectrograms can then be used as a compact set of descriptors and subjected to blind analysis techniques. Moreover, a further improvement of both data compression and calibration/classification performances can be achieved by applying proper variable selection methods to the hyperspectrograms. A visual evaluation of the correctness of the choices made by the algorithm can be obtained by representing the selected features back into the original image domain. Likewise, the interpretation of the chemical information underlying the selected regions of the hyperspectrograms related to the loadings is enabled by projecting them in the original spectral domain. Examples of applications of the hyperspectrogram-based approach to hyperspectral images of food samples in the NIR range (1000-1700 nm) and in the vis-NIR range (400-1000 nm), facing a calibration and a defect detection issue respectively, demonstrate the effectiveness of the proposed approach.