Nonlinear mixed-effects scalar-on-function models and variable selection

Abstract: This paper is motivated by our collaborative research and the aim is to model clinical assessments of upper limb function after stroke using 3D-position and 4D-orientation movement data. We present a new nonlinear mixed-effects scalar-on-function regression model with a Gaussian process prior focusing on the variable selection from a large number of candidates including both scalar and function variables. A novel variable selection algorithm has been developed, namely functional least angle regression. As it is essential for this algorithm, we studied the representation of functional variables with different methods and the correlation between a scalar and a group of mixed scalar and functional variables. We also propose a new stopping rule for practical use. This algorithm is efficient and accurate for both variable selection and parameter estimation even when the number of functional variables is very large and the variables are correlated. And thus the prediction provided by the algorithm is accurate. Our comprehensive simulation study showed that the method is superior to other existing variable selection methods. When the algorithm was applied to the analysis of the movement data, the use of the nonlinear random-effect model and the function variables significantly improved the prediction accuracy for the clinical assessment

Characterization of nonstructural protein 3 of a neurovirulent Japanese encephalitis virus strain isolated from a pig

<p>Abstract</p> <p>Background</p> <p>Japanese encephalitis virus (JEV), as a re-emerging virus that causes 10,000-15,000 human deaths from encephalitis in the world each year, has had a significant impact on public health. Pigs are the natural reservoirs of JEV and play an important role in the amplification, dispersal and epidemiology of JEV. The nonstructural protein 3 (NS3) of JEV possesses enzymatic activities of serine protease, helicase and nucleoside 5'-triphosphatase, and plays important roles in viral replication and pathogenesis.</p> <p>Results</p> <p>We characterized the NS3 protein of a neurovirulent strain of JEV (SH-JEV01) isolated from a field-infected pig. The NS3 gene of the JEV SH-JEV01 strain is 1857 bp in length and encodes protein of approximately 72 kDa with 99% amino acid sequence identity to that of the representative immunotype strain JaGAr 01. The NS3 protein was detectable 12 h post-infection in a mouse neuroblastoma cell line, Neuro-2a, and was distributed in the cytoplasm of cells infected with the SH-JEV01 strain of JEV. In the brain of mice infected with the SH-JEV01 strain of JEV, NS3 was detected in the cytoplasm of neuronal cells, including pyramidal neurons of the cerebrum, granule cells, small cells and Purkinje cells of the cerebellum.</p> <p>Conclusions</p> <p>The NS3 protein of a neurovirulent strain of JEV isolated from a pig was characterized. It is an approximately 72 kDa protein and distributed in the cytoplasm of infected cells. The Purkinje cell of the cerebellum is one of the target cells of JEV infection. Our data should provide some basic information for the study of the role of NS3 in the pathogenesis of JEV and the immune response.</p

The Meq oncoprotein of Marek's disease virus interacts with p53 and inhibits its transcriptional and apoptotic activities

<p>Abstract</p> <p>Background</p> <p>Marek's disease virus (MDV) is an oncogenic herpesvirus, which causes malignant lymphoma in chickens. The Meq protein of MDV, which is expressed abundantly in MDV-infected cells and in Marek's disease (MD) tumor cells, functions as a transcriptional activator and has been proposed to play an important role in oncogenic transformation. Preliminary studies demonstrated that Meq is able to bind p53 <it>in vitro</it>, as demonstrated using a protein-binding assay. This observation prompted us to examine whether the interaction between Meq and p53 occurs in cells, and to investigate the biological significance of this interaction.</p> <p>Results</p> <p>We confirmed first that Meq interacted directly with p53 using a yeast two-hybrid assay and an immunoprecipitation assay, and we investigated the biological significance of this interaction subsequently. Exogenous expression of Meq resulted in the inhibition of p53-mediated transcriptional activity and apoptosis, as analyzed using a p53 luciferase reporter assay and a TUNEL assay. The inhibitory effect of Meq on transcriptional activity mediated by p53 was dependent on the physical interaction between these two proteins, because a Meq deletion mutant that lacked the p53-binding region lost the ability to inhibit p53-mediated transcriptional activity and apoptosis. The Meq variants L-Meq and S-Meq, but not VS-Meq and ∆Meq, which were expressed in MD tumor cells and MDV-infected cells, exerted an inhibitory effect on p53 transcriptional activity. In addition, ∆Meq was found to act as a negative regulator of Meq.</p> <p>Conclusions</p> <p>The Meq oncoprotein interacts directly with p53 and inhibits p53-mediated transcriptional activity and apoptosis. These findings provide valuable insight into the molecular basis for the function of Meq in MDV oncogenesis.</p

Multispectral Palmprint Recognition Using a Quaternion Matrix

Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%

A Murine Rp1 Missense Mutation Causes Protein Mislocalization and Slowly Progressive Photoreceptor Degeneration

Mutations in the RP1 gene can cause retinitis pigmentosa. We identified a spontaneous L66P mutation caused by two adjacent point mutations in the Rp1 gene in a colony of C57BL/6J mice. Mice homozygous for the L66P mutation exhibited slow, progressive photoreceptor degeneration throughout their lifespan. Optical coherence tomography imaging found abnormal photoreceptor reflectivity at 1 month of age. Histology found shortening and disorganization of the photoreceptor inner and outer segments and progressive thinning of the outer nuclear layer. Electroretinogram a- and b-wave amplitudes were decreased with age. Western blot analysis found that the quantity and size of the mutated retinitis pigmentosa 1 (RP1) protein were normal. However, immunohistochemistry found that the mutant Rp1 protein partially mislocalized to the transition zone of the shortened axonemes. This mutation disrupted colocalization with cytoplasmic microtubules in vitro. In conclusion, the L66P mutation in the first doublecortin domain of the Rp1 gene impairs Rp1 protein localization and function, leading to abnormalities in photoreceptor outer segment structure and progressive photoreceptor degeneration. This is the first missense mutation in Rp1 shown to cause retinal degeneration. It provides a unique, slowly progressive photoreceptor degeneration model that mirrors the slow degeneration kinetics in most patients with retinitis pigmentosa

Adolescent transport and unintentional injuries: a systematic analysis using the Global Burden of Disease Study 2019

Background: Globally, transport and unintentional injuries persist as leading preventable causes of mortality and morbidity for adolescents. We sought to report comprehensive trends in injury-related mortality and morbidity for adolescents aged 10–24 years during the past three decades. Methods: Using the Global Burden of Disease, Injuries, and Risk Factors 2019 Study, we analysed mortality and disability-adjusted life-years (DALYs) attributed to transport and unintentional injuries for adolescents in 204 countries. Burden is reported in absolute numbers and age-standardised rates per 100 000 population by sex, age group (10–14, 15–19, and 20–24 years), and sociodemographic index (SDI) with 95% uncertainty intervals (UIs). We report percentage changes in deaths and DALYs between 1990 and 2019. Findings: In 2019, 369 061 deaths (of which 214 337 [58%] were transport related) and 31·1 million DALYs (of which 16·2 million [52%] were transport related) among adolescents aged 10–24 years were caused by transport and unintentional injuries combined. If compared with other causes, transport and unintentional injuries combined accounted for 25% of deaths and 14% of DALYs in 2019, and showed little improvement from 1990 when such injuries accounted for 26% of adolescent deaths and 17% of adolescent DALYs. Throughout adolescence, transport and unintentional injury fatality rates increased by age group. The unintentional injury burden was higher among males than females for all injury types, except for injuries related to fire, heat, and hot substances, or to adverse effects of medical treatment. From 1990 to 2019, global mortality rates declined by 34·4% (from 17·5 to 11·5 per 100 000) for transport injuries, and by 47·7% (from 15·9 to 8·3 per 100 000) for unintentional injuries. However, in low-SDI nations the absolute number of deaths increased (by 80·5% to 42 774 for transport injuries and by 39·4% to 31 961 for unintentional injuries). In the high-SDI quintile in 2010–19, the rate per 100 000 of transport injury DALYs was reduced by 16·7%, from 838 in 2010 to 699 in 2019. This was a substantially slower pace of reduction compared with the 48·5% reduction between 1990 and 2010, from 1626 per 100 000 in 1990 to 838 per 100 000 in 2010. Between 2010 and 2019, the rate of unintentional injury DALYs per 100 000 also remained largely unchanged in high-SDI countries (555 in 2010 vs 554 in 2019; 0·2% reduction). The number and rate of adolescent deaths and DALYs owing to environmental heat and cold exposure increased for the high-SDI quintile during 2010–19. Interpretation: As other causes of mortality are addressed, inadequate progress in reducing transport and unintentional injury mortality as a proportion of adolescent deaths becomes apparent. The relative shift in the burden of injury from high-SDI countries to low and low–middle-SDI countries necessitates focused action, including global donor, government, and industry investment in injury prevention. The persisting burden of DALYs related to transport and unintentional injuries indicates a need to prioritise innovative measures for the primary prevention of adolescent injury. Funding: Bill &amp; Melinda Gates Foundation