Detection of Variants in 15 Genes in 87 Unrelated Chinese Patients with Leber Congenital Amaurosis

BACKGROUND: Leber congenital amaurosis (LCA) is the earliest onset and most severe form of hereditary retinal dystrophy. So far, full spectrum of variations in the 15 genes known to cause LCA has not been systemically evaluated in East Asians. Therefore, we performed comprehensive detection of variants in these 15 genes in 87 unrelated Han Chinese patients with LCA. METHODOLOGY/PRINCIPAL FINDINGS: The 51 most frequently mutated exons and introns in the 15 genes were selected for an initial scan using cycle sequencing. All the remaining exons in 11 of the 15 genes were subsequently sequenced. Fifty-three different variants were identified in 44 of the 87 patients (50.6%), involving 78 of the 88 alleles (11 homozygous and 56 heterozygous variants). Of the 53 variants, 35 (66%) were novel pathogenic mutations. In these Chinese patients, variants in GUCY2D are the most common cause of LCA (16.1% cases), followed by CRB1 (11.5%), RPGRIP1 (8%), RPE65 (5.7%), SPATA7 (4.6%), CEP290 (4.6%), CRX (3.4%), LCA5 (2.3%), MERTK (2.3%), AIPL1 (1.1%), and RDH12 (1.1%). This differs from the variation spectrum described in other populations. An initial scan of 55 of 215 PCR amplicons, including 214 exons and 1 intron, detected 83.3% (65/78) of the mutant alleles ultimately found in these 87 patients. In addition, sequencing only 9 exons would detect over 50% of the identified variants and require less than 5% of the labor and cost of comprehensive sequencing for all exons. CONCLUSIONS/SIGNIFICANCE: Our results suggest that specific difference in the variation spectrum found in LCA patients from the Han Chinese and other populations are related by ethnicity. Sequencing exons in order of decreasing risk is a cost-effective way to identify causative mutations responsible for LCA, especially in the context of genetic counseling for individual patients in a clinical setting

Genome-wide identification and phylogenetic analysis of the ERF gene family in cucumbers

Members of the ERF transcription-factor family participate in a number of biological processes, viz., responses to hormones, adaptation to biotic and abiotic stress, metabolism regulation, beneficial symbiotic interactions, cell differentiation and developmental processes. So far, no tissue-expression profile of any cucumber ERF protein has been reported in detail. Recent completion of the cucumber full-genome sequence has come to facilitate, not only genome-wide analysis of ERF family members in cucumbers themselves, but also a comparative analysis with those in Arabidopsis and rice. In this study, 103 hypothetical ERF family genes in the cucumber genome were identified, phylogenetic analysis indicating their classification into 10 groups, designated I to X. Motif analysis further indicated that most of the conserved motifs outside the AP2/ERF domain, are selectively distributed among the specific clades in the phylogenetic tree. From chromosomal localization and genome distribution analysis, it appears that tandem-duplication may have contributed to CsERF gene expansion. Intron/exon structure analysis indicated that a few CsERFs still conserved the former intron-position patterns existent in the common ancestor of monocots and eudicots. Expression analysis revealed the widespread distribution of the cucumber ERF gene family within plant tissues, thereby implying the probability of their performing various roles therein. Furthermore, members of some groups presented mutually similar expression patterns that might be related to their phylogenetic groups

The effect of collisional quenching on the spatial distribution of atomic oxygen in an Ar APPJ operating in ambient air by TALIF

Cold atmospheric pressure plasma jets have attracted great interests due to their potential biomedical applications and material treatment. The effluent including ambient reactive species enables plasma jets to inactivate bacteria and contribute to wound healing. One of the important species is atomic oxygen as it is the precursor to the long lived ozone which is bactericidal and on its own atomic oxygen is believed to be important for material treatment. As the effluent including the atomic oxygen species blows toward the substrate, one requires the radial and axial distribution of atomic oxygen to be known accurately together with the gas velocity flow pattern to obtain the total flux which is important for the applications. In this work, the spatial profile of the absolute atomic oxygen density is obtained by two-photon absorption laser induced fluorescence (TALIF) in an Ar cold atmospheric pressure plasma jet operating in ambient air. Since the surrounding air diffused into the Ar effluent and contributed to the quenching of the O 3p 3PJ state, the spatial resolved air densities are obtained from Raman scattering measurements reported in previous work. This allows to calculate the spatial dependent collisional quenching rate for O 3p 3PJ state and recalculate the spatial O density profile from the recorded TALIF signal. Significant differences are found between the TALIF intensity radial profile and the actual O density profile under the conditions in this work and that illustrates that the correction of the entrainment of air into the plasma effluent is necessary

Gas flow characteristics of a time modulated APPJ : the effect of gas heating on flow dynamics

This work investigates the flow dynamics of a radio-frequency (RF) non-equilibrium argon atmospheric pressure plasma jet. The RF power is at a frequency of 50 Hz or 20 kHz. Combined flow pattern visualizations (obtained by shadowgraphy) and gas temperature distributions (obtained by Rayleigh scattering) are used to study the formation of transient vortex structures in initial flow field shortly after the plasma is switched on and off in the case of 50 Hz modulation. The transient vortex structures correlate well with observed temperature differences. Experimental results of the fast modulated (20 kHz) plasma jet that does not induce changes of the gas temperature are also presented. The latter result suggests that momentum transfer by ions does not have dominant effect on the flow pattern close to the tube. It is argued that the increased gas temperature and corresponding gas velocity increase at the tube exit due to the plasma heating increases the admixing of surrounding air and reduces the effective potential core length. With increasing plasma power a reduction of the effective potential core length is observed with a minimum length for 5.6 W after which the length extends again. Possible mechanisms related to viscosity effects and ionic momentum transfer are discussed

Video anomaly detection using deep incremental slow feature analysis network

Existing anomaly detection (AD) approaches rely on various hand‐crafted representations to represent video data and can be costly. The choice or designing of hand‐crafted representation can be difficult when faced with a new dataset without prior knowledge. Motivated by feature learning, e.g. deep leaning and the ability to directly learn useful representations and model high‐level abstraction from raw data, the authors investigate the possibility of using a universal approach. The objective is learning data‐driven high‐level representation for the task of video AD without relying on hand‐crafted representation. A deep incremental slow feature analysis (D‐IncSFA) network is constructed and applied to directly learning progressively abstract and global high‐level representations from raw data sequence. The D‐IncSFA network has the functionalities of both feature extractor and anomaly detector that make AD completion in one step. The proposed approach can precisely detect global anomaly such as crowd panic. To detect local anomaly, a set of anomaly maps, produced from the network at different scales, is used. The proposed approach is universal and convenient, working well in different types of scenarios with little human intervention and low memory and computational requirements. The advantages are validated by conducting extensive experiments on different challenge datasets

Optimizing over trained GNNs via symmetry breaking

Optimization over trained machine learning models has applications including: verification, minimizing neural acquisition functions, and integrating a trained surrogate into a larger decision-making problem. This paper formulates and solves optimization problems constrained by trained graph neural networks (GNNs). To circumvent the symmetry issue caused by graph isomorphism, we propose two types of symmetry-breaking constraints: one indexing a node 0 and one indexing the remaining nodes by lexicographically ordering their neighbor sets. To guarantee that adding these constraints will not remove all symmetric solutions, we construct a graph indexing algorithm and prove that the resulting graph indexing satisfies the proposed symmetry-breaking constraints. For the classical GNN architectures considered in this paper, optimizing over a GNN with a fixed graph is equivalent to optimizing over a dense neural network. Thus, we study the case where the input graph is not fixed, implying that each edge is a decision variable, and develop two mixed-integer optimization formulations. To test our symmetry-breaking strategies and optimization formulations, we consider an application in molecular design.Comment: 10 main pages, 27 with appendix, 9 figures, 7 table

Nitric oxide density distributions in the effluent of an RF argon APPJ : effect of gas flow rate and substrate

The effluent of an RF argon atmospheric pressure plasma jet, the so-called kinpen, is investigated with focus on the nitric-oxide (NO) distribution for laminar and turbulent flow regimes. An additional dry air gas curtain is applied around the plasma effluent to prevent interaction with the ambient humid air. By means of laser-induced fluorescence (LIF) the absolute spatially resolved NO density is measured as well as the rotational temperature and the air concentration. While in the laminar case, the transport of NO is attributed to thermal diffusion; in the turbulent case, turbulent mixing is responsible for air diffusion. Additionally, measurements with a molecular beam mass-spectrometer (MBMS) absolutely calibrated for NO are performed and compared with the LIF measurements. Discrepancies are explained by the contribution of the and to the MBMS NO signal. Finally, the effect of a conductive substrate in front of the plasma jet on the spatial distribution of NO and air diffusion is also investigate

Spatially resolved ozone densities and gas temperatures in a time modulated RF driven atmospheric pressure plasma jet : an analysis of the production and destruction mechanisms

In this work, a time modulated RF driven DBD-like atmospheric pressure plasma jet in Ar + 2%O2, operating at a time averaged power of 6.5 W is investigated. Spatially resolved ozone densities and gas temperatures are obtained by UV absorption and Rayleigh scattering, respectively. Significant gas heating in the core of the plasma up to 700 K is found and at the position of this increased gas temperature a depletion of the ozone density is found. The production and destruction reactions of O3 in the jet effluent as a function of the distance from the nozzle are obtained from a zero-dimensional chemical kinetics model in plug flow mode which considers relevant air chemistry due to air entrainment in the jet fluent. A comparison of the measurements and the models show that the depletion of O3 in the core of the plasma is mainly caused by an enhanced destruction of O3 due to a large atomic oxygen densit