Multivariate meta-analysis of QTL mapping studies

A large number of quantitative trait loci (QTLs) for milk production and quality traits in dairy cattle has been reported in literature. The large amount of information available could be exploited by meta-analyses to draw more general conclusions from results obtained in different experimental conditions (animals, statistical methodologies). QTL meta-analyses have been carried out to estimate the distribution of QTL effects in livestock and to find consensus on QTL position. In this study, multivariate dimension reduction techniques are used to analyse a database of dairy cattle QTL published results, in order to extract latent variables able to characterise the research. A total of 92 papers by 72 authors were found on 25 scientific Journals for the period January 1995-February 2008. More than thirty parameters were picked up from the articles. To overcome the problem of different map location, the flanking markers were mapped on release 4.1 of the Bos taurus genome sequence (www.ensembl. org). Their position was retrieved from public databases and, when absent, was calculated in silico by blasting (http://blast.wustl.edu/) the markers’ nucleotide sequence against the genomic sequence. Records were discarded if flanking markers or P-values were not available. After these edits, the final archive consisted of 1,162 records. Seven selected variables were analysed both with the Factor Analysis (FA), combined with the varimax rotation technique, and Principal Component Analysis (PCA). FA was able to explain 68% of the original variability with 3 latent factors: the first factor extracted was highly associated (factor loading of 0.98) to marker location along the chromosome and could be considered as a marker map index; the second factor showed factor loadings of 0.74 and 0.84 related to the variable number of animals involved and year of the experiment, respectively, and it can be regarded as an indicator of the dimension of the study; the third factor was correlated to the significance level of the statistical test (0.78), number of families (0.63), and, negatively, to the marker density (-0.43). It can be named as index of power of the experiment. Same patterns can be observed in the eigenvectors of PCA. Four PCs were able to explain about 80% of the original variance. The first two PCs basically underlined accurately the same structure found with the first two factors in FA, whereas PC3 and PC4 summarized the structure of F3. The score that each QTL gets on each Factor or PC could be useful to classify the original QTL records and make them more comparable once that the redundancy of information has been removed

Evaluation of the accuracy of a patient-specific instrumentation

Patient-specific instruments (PSI) has been introduced with the aim to reduce the overall costs of the implants, minimizing the size and number of instruments required, and also reducing surgery time. The aim of this study was to perform a review of the current literature, as well as to report about our personal experience, to assess reliability and accuracy of patient specific instrument system in total knee arthroplasty (TKA). A literature review was conducted of PSI system reviewing articles related to coronal alignment, clinical knee and function scores, cost, patient satisfaction and complications. Studies have reported incidences of coronal alignment ≥3° from neutral in TKAs performed with patient-specific cutting guides ranging from 6% to 31%. PSI seem not to be able to result in the same degree of accuracy as for the CAS system, while comparing well with standard manual technique with respect to component positioning and overall lower axis, in particular in the sagittal plane. In cases in which custom-made cutting jigs were used, we recommend performing an accurate control of the alignment before and after any cuts and in any further step of the procedure, in order to avoid possible outliers

A CNN-based fusion method for feature extraction from sentinel data

Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. A possible alternative is to benefit from weather-insensitive synthetic aperture radar (SAR) images. In many real-world applications, critical decisions are made based on some informative optical or radar features related to items such as water, vegetation or soil. Under cloudy conditions, however, optical-based features are not available, and they are commonly reconstructed through linear interpolation between data available at temporally-close time instants. In this work, we propose to estimate missing optical features through data fusion and deep-learning. Several sources of information are taken into account—optical sequences, SAR sequences, digital elevation model—so as to exploit both temporal and cross-sensor dependencies. Based on these data and a tiny cloud-free fraction of the target image, a compact convolutional neural network (CNN) is trained to perform the desired estimation. To validate the proposed approach, we focus on the estimation of the normalized difference vegetation index (NDVI), using coupled Sentinel-1 and Sentinel-2 time-series acquired over an agricultural region of Burkina Faso from May–November 2016. Several fusion schemes are considered, causal and non-causal, single-sensor or joint-sensor, corresponding to different operating conditions. Experimental results are very promising, showing a significant gain over baseline methods according to all performance indicators

Pacemaker-detected severe sleep apnea predicts new-onset atrial fibrillation

Sleep apnea (SA) diagnosed on overnight polysomnography is a risk factor for atrial fibrillation (AF). Advanced pacemakers are now able to monitor intrathoracic impedance for automatic detection of SA events

Genomic signatures of adaptive introgression from European mouflon into domestic sheep

Mouflon (Ovis aries musimon) became extinct from mainland Europe after the Neolithic, but remnant populations from the Mediterranean islands of Corsica and Sardinia have been used for reintroductions across Europe since the 19th-century. Mouflon x sheep hybrids are larger-bodied than mouflon, potentially showing increased male reproductive success, but little is known about genomic levels of admixture, or about the adaptive significance of introgression between resident mouflon and local sheep breeds. Here we analysed Ovine medium-density SNP array genotypes of 92 mouflon from six geographic regions, along with data from 330 individuals of 16 domestic sheep breeds. We found lower levels of genetic diversity in mouflon than in domestic sheep, consistent with past bottlenecks in mouflon. Introgression signals were bidirectional and affected most mouflon and sheep populations, being strongest in one Sardinian mouflon population. Developing and using a novel approach to identify chromosomal regions with consistent introgression signals, we infer adaptive introgression from mouflon to domestic sheep related to immunity mechanisms, but not in the opposite direction. Further, we infer that Soay and Sarda sheep carry introgressed mouflon alleles involved in bitter taste perception and/or innate immunity. Our results illustrate the potential for adaptive introgression even among recently diverged populations

Circulating hsa-miR-5096 predicts 18F-FDG PET/CT positivity and modulates somatostatin receptor 2 expression: a novel miR-based assay for pancreatic neuroendocrine tumors

Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) are rare diseases encompassing pancreatic (PanNETs) and ileal NETs (SINETs), characterized by heterogeneous somatostatin receptors (SSTRs) expression. Treatments for inoperable GEP-NETs are limited, and SSTR-targeted Peptide Receptor Radionuclide Therapy (PRRT) achieves variable responses. Prognostic biomarkers for the management of GEP-NET patients are required. 18F-FDG uptake is a prognostic indicator of aggressiveness in GEP-NETs. This study aims to identify circulating and measurable prognostic miRNAs associated with 18FFDG- PET/CT status, higher risk and lower response to PRRT

Genetic diversity of Italian goat breeds assessed with a medium-density SNP chip

Background: Among the European countries, Italy counts the largest number of local goat breeds. Thanks to the recent availability of a medium-density SNP (single nucleotide polymorphism) chip for goat, the genetic diversity of Italian goat populations was characterized by genotyping samples from 14 Italian goat breeds that originate from different geographical areas with more than 50 000 SNPs evenly distributed on the genome. Results: Analysis of the genotyping data revealed high levels of genetic polymorphism and an underlying North-south geographic pattern of genetic diversity that was highlighted by both the first dimension of the multi-dimensional scaling plot and the Neighbour network reconstruction. We observed a moderate and weak population structure in Northern and Central-Southern breeds, respectively, with pairwise FST values between breeds ranging from 0.013 to 0.164 and 7.49 % of the total variance assigned to the between-breed level. Only 2.11 % of the variance explained the clustering of breeds into geographical groups (Northern, Central and Southern Italy and Islands). Conclusions: Our results indicate that the present-day genetic diversity of Italian goat populations was shaped by the combined effects of drift, presence or lack of gene flow and, to some extent, by the consequences of traditional management systems and recent demographic history. Our findings may constitute the starting point for the development of marker-assisted approaches, to better address future breeding and management policies in a species that is particularly relevant for the medium-and long-term sustainability of marginal regions

Clinical heterogeneity and diagnostic delay of autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy syndrome

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Off-label use of combined antiretroviral therapy, analysis of data collected by the Italian Register for HIV-1 infection in paediatrics in a large cohort of children

Background: Early start of highly active antiretroviral therapy (HAART) in perinatally HIV-1 infected children is the optimal strategy to prevent immunological and clinical deterioration. To date, according to EMA, only 35% of antiretroviral drugs are licenced in children  25%. At last check, during the off label regimen, the 80% (40/50) of patients had an undetectable VL, and 90% (45/50) of them displayed CD4 + T lymphocyte percentage > 25%. The most widely used off-label drugs were: dolutegravir/abacavir/lamivudine (16%; 8/50), emtricitbine/tenofovir disoproxil (22%; 11/50), lopinavir/ritonavir (20%; 10/50) and elvitegravir/cobicistat/emtricitabine/ tenofovir alafenamide (10%; 10/50). At logistic regression analysis, detectable VL before starting the current HAART regimen was a risk factor for receiving an off-label therapy (OR: 2.41; 95% CI 1.13-5.19; p = 0.024). Moreover, children < 2 years of age were at increased risk for receiving off-label HAART with respect to older children (OR: 3.24; 95% CI 1063-7.3; p = 0.001). Even if our safety data regarding off-label regimens where poor, no adverse event was reported. Conclusion: The prescription of an off-label HAART regimen in perinatally HIV-1 infected children was common, in particular in children with detectable VL despite previous HAART and in younger children, especially those receiving their first regimen. Our data suggest similar proportions of virological and immunological successes at last check among children receiving off-label or on-label HAART. Larger studies are needed to better clarify efficacy and safety of off-label HAART regimens in children, in order to allow the enlargement of on-label prescription in children