Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds

Background The objective of the present study was to test the ability of the partial least squares regression technique to impute genotypes from low density single nucleotide polymorphisms (SNP) panels i.e. 3K or 7K to a high density panel with 50K SNP. No pedigree information was used. Methods Data consisted of 2093 Holstein, 749 Brown Swiss and 479 Simmental bulls genotyped with the Illumina 50K Beadchip. First, a single-breed approach was applied by using only data from Holstein animals. Then, to enlarge the training population, data from the three breeds were combined and a multi-breed analysis was performed. Accuracies of genotypes imputed using the partial least squares regression method were compared with those obtained by using the Beagle software. The impact of genotype imputation on breeding value prediction was evaluated for milk yield, fat content and protein content. Results In the single-breed approach, the accuracy of imputation using partial least squares regression was around 90 and 94% for the 3K and 7K platforms, respectively; corresponding accuracies obtained with Beagle were around 85% and 90%. Moreover, computing time required by the partial least squares regression method was on average around 10 times lower than computing time required by Beagle. Using the partial least squares regression method in the multi-breed resulted in lower imputation accuracies than using single-breed data. The impact of the SNP-genotype imputation on the accuracy of direct genomic breeding values was small. The correlation between estimates of genetic merit obtained by using imputed versus actual genotypes was around 0.96 for the 7K chip. Conclusions Results of the present work suggested that the partial least squares regression imputation method could be useful to impute SNP genotypes when pedigree information is not available

Scaling of Wave-Packet Dynamics in an Intense Midinfrared Field

A theoretical investigation is presented that examines the wavelength scaling from near-visible (0.8 µm) to midinfrared (2 µm) of the photoelectron distribution and high harmonics generated by a "single" atom in an intense electromagnetic field. The calculations use a numerical solution of the time-dependent Schrödinger equation (TDSE) in argon and the strong-field approximation in helium. The scaling of electron energies (λ^2), harmonic cutoff (λ^2), and attochirp (λ^-1) agree with classical mechanics, but it is found that, surprisingly, the harmonic yield follows a λ^-(5-6) scaling at constant intensity. In addition, the TDSE results reveal an unexpected contribution from higher-order returns of the rescattering electron wave packet

Selective excitation of metastable atomic states by femto- and attosecond laser pulses

The possibility of achieving highly selective excitation of low metastable states of hydrogen and helium atoms by using short laser pulses with reasonable parameters is demonstrated theoretically. Interactions of atoms with the laser field are studied by solving the close-coupling equations without discretization. The parameters of laser pulses are calculated using different kinds of optimization procedures. For the excitation durations of hundreds of femtoseconds direct optimization of the parameters of one and two laser pulses with Gaussian envelopes is used to introduce a number of simple schemes of selective excitation. To treat the case of shorter excitation durations, optimal control theory is used and the calculated optimal fields are approximated by sequences of pulses with reasonable shapes. A new way to achieve selective excitation of metastable atomic states by using sequences of attosecond pulses is introduced.Comment: To be published in Phys. Rev. A, 10 pages, 3 figure

First Results from KamLAND: Evidence for Reactor Anti-Neutrino Disappearance

KamLAND has been used to measure the flux of $\bar{\nu}_e$'s from distant nuclear reactors. In an exposure of 162 ton$\cdot$yr (145.1 days) the ratio of the number of observed inverse $\beta$-decay events to the expected number of events without disappearance is $0.611\pm 0.085 {\rm (stat)} \pm 0.041 {\rm (syst)}$ for $\bar{\nu}_e$ energies $>$ 3.4 MeV. The deficit of events is inconsistent with the expected rate for standard $\bar{\nu}_e$ propagation at the 99.95% confidence level. In the context of two-flavor neutrino oscillations with CPT invariance, these results exclude all oscillation solutions but the `Large Mixing Angle' solution to the solar neutrino problem using reactor $\bar{\nu}_e$ sources.Comment: 6 pages, 6 figure

Ultraintense X-Ray Induced Ionization, Dissociation, and Frustrated Absorption in Molecular Nitrogen

Sequential multiple photoionization of the prototypical molecule N_2 is studied with femtosecond time resolution using the Linac Coherent Light Source (LCLS). A detailed picture of intense x-ray induced ionization and dissociation dynamics is revealed, including a molecular mechanism of frustrated absorption that suppresses the formation of high charge states at short pulse durations. The inverse scaling of the average target charge state with x-ray peak brightness has possible implications for single-pulse imaging applications

Semantic segmentation of conjunctiva region for non-invasive anemia detection applications

Technology is changing the future of healthcare, technology-supported non-invasive medical procedures are more preferable in the medical diagnosis. Anemia is one of the widespread diseases affecting the wellbeing of individuals around the world especially childbearing age women and children and addressing this issue with the advanced technology will reduce the prevalence in large numbers. The objective of this work is to perform segmentation of the conjunctiva region for non-invasive anemia detection applications using deep learning. The proposed U-Net Based Conjunctiva Segmentation Model (UNBCSM) uses fine-tuned U-Net architecture for effective semantic segmentation of conjunctiva from the digital eye images captured by consumer-grade cameras in an uncontrolled environment. The ground truth for this supervised learning was given as Pascal masks obtained by manual selection of conjunctiva pixels. Image augmentation and pre-processing was performed to increase the data size and the performance of the model. UNBCSM showed good segmentation results and exhibited a comparable value of Intersection over Union (IoU) score between the ground truth and the segmented mask of 96% and 85.7% for training and validation, respectively

Mapping gene associations in human mitochondria using clinical disease phenotypes

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes

Vocalization Induced CFos Expression in Marmoset Cortex

All non-human primates communicate with conspecifics using vocalizations, a system involving both the production and perception of species-specific vocal signals. Much of the work on the neural basis of primate vocal communication in cortex has focused on the sensory processing of vocalizations, while relatively little data are available for vocal production. Earlier physiological studies in squirrel monkeys had shed doubts on the involvement of primate cortex in vocal behaviors. The aim of the present study was to identify areas of common marmoset (Callithrix jacchus) cortex that are potentially involved in vocal communication. In this study, we quantified cFos expression in three areas of marmoset cortex – frontal, temporal (auditory), and medial temporal – under various vocal conditions. Specifically, we examined cFos expression in these cortical areas during the sensory, motor (vocal production), and sensory–motor components of vocal communication. Our results showed an increase in cFos expression in ventrolateral prefrontal cortex as well as the medial and lateral belt areas of auditory cortex in the vocal perception condition. In contrast, subjects in the vocal production condition resulted in increased cFos expression only in dorsal premotor cortex. During the sensory–motor condition (antiphonal calling), subjects exhibited cFos expression in each of the above areas, as well as increased expression in perirhinal cortex. Overall, these results suggest that various cortical areas outside primary auditory cortex are involved in primate vocal communication. These findings pave the way for further physiological studies of the neural basis of primate vocal communication

This advert makes me cry: Disclosure of emotional response to advertisement on Facebook

As social media is transforming how consumers interact with brands and how brand-related content is consumed, this paper aims to investigate if and how Facebook users express their emotions towards advertisements of brand share on the site. Seven hundred and three comments about the Lloyds 250th Anniversary advertisement on Facebook were analysed as positive, negative or neutral attitude towards the advert. Facebook users found the advertisement emotionally appealing and voluntarily report their emotion of love, pride and in some cases anger. The presence of an iconic image like the black horse and the cover music was found to be emotionally appealing. The background music as well aroused positive emotions and engaging. This study introduces the possibility of analysing Facebook comments on brand content to understand consumers’ emotional responses and attitudes to the brand. Managers can explore these opportunities to identify what consumers find interesting in advertisements and how best to develop their creative strategies. It also offers the opportunity to allocate resources better to engage consumers with creative advertisement. Unlike interviews or surveys, this is a pioneering study on measuring emotional responses to advertisement through users’ self-report on social media

Methodological advances in imaging intravital axonal transport.

Axonal transport is the active process whereby neurons transport cargoes such as organelles and proteins anterogradely from the cell body to the axon terminal and retrogradely in the opposite direction. Bi-directional transport in axons is absolutely essential for the functioning and survival of neurons and appears to be negatively impacted by both aging and diseases of the nervous system, such as Alzheimer's disease and amyotrophic lateral sclerosis. The movement of individual cargoes along axons has been studied in vitro in live neurons and tissue explants for a number of years; however, it is currently unclear as to whether these systems faithfully and consistently replicate the in vivo situation. A number of intravital techniques originally developed for studying diverse biological events have recently been adapted to monitor axonal transport in real-time in a range of live organisms and are providing novel insight into this dynamic process. Here, we highlight these methodological advances in intravital imaging of axonal transport, outlining key strengths and limitations while discussing findings, possible improvements, and outstanding questions