High-throughput sequencing approaches for diagnosing hereditary bleeding and platelet disorders.

Hereditary bleeding and platelet disorders (BPDs) are characterized by marked genetic heterogeneity, far greater than previously appreciated. The list of genes involved in the regulation of megakaryopoiesis, platelet formation, platelet function and bleeding has been growing rapidly since the introduction of high-throughput sequencing (HTS) approaches in research. Thanks to the gradual adoption of HTS in diagnostic practice, these discoveries are improving the diagnostic yield for BPD patients, who may or may not present with bleeding problems and often have other clinical symptoms unrelated to the blood system. However, it was previously found that screening for all known etiologies gives a diagnostic yield of over 90% when the phenotype closely matches a known BPD but drops to 10% when the phenotype is indicative of a novel disorder. Thus, further research is needed to identify currently unknown etiologies for BPDs. Novel genes are likely to be found to be implicated in BPDs. New modes of inheritance, including digenic inheritance, are likely to play a role in some cases. Additionally, identifying and interpreting pathogenic variants outside exons is a looming challenge that can only be tackled with an improved understanding of the regulatory landscape of relevant cell types and with the transition from targeted sequencing to whole-genome sequencing in the clinic

ontologyX: a suite of R packages for working with ontological data

Ontologies are widely used constructs for encoding and analyzing biomedical data, but the absence of simple and consistent tools has made exploratory and systematic analysis of such data unnecessarily difficult. Here we present three packages which aim to simplify such procedures. The ontologyIndex package enables arbitrary ontologies to be read into R, supports representation of ontological objects by native R types, and provides a parsimonius set of performant functions for querying ontologies. ontologySimilarity and ontologyPlot extend ontologyIndex with functionality for straightforward visualization and semantic similarity calculations, including statistical routines. $\textbf{AVAILABILITY AND IMPLEMENTATION}$: ontologyIndex, ontologyPlot and ontologySimilarity are all available on the Comprehensive R Archive Network website under https://cran.r-project.org/web/packagesThis work was supported by National Institute for Health Research award RG65966 (D.G. and E.T.) and the Medical Research Council programme grant MC_UP_ 0801/1 (D.G. and S.R.)

Orbital Optimized Density Functional Theory for Electronic Excited States

Density functional theory (DFT) based modeling of electronic excited states is of importance for investigation of the photophysical/photochemical properties and spectroscopic characterization of large systems. The widely used linear response time-dependent DFT (TDDFT) approach is however not effective at modeling many types of excited states, including (but not limited to) charge-transfer states, doubly excited states and core-level excitations. In this perspective, we discuss state-specific orbital optimized (OO) DFT approaches as an alterative to TDDFT for electronic excited states. We motivate the use of OO-DFT methods and discuss reasons behind their relatively restricted historical usage (vs TDDFT). We subsequently highlight modern developments that address these factors and allow efficient and reliable OO-DFT computations. Several successful applications of OO-DFT for challenging electronic excitations are also presented, indicating their practical efficacy. OO-DFT approaches are thus increasingly becoming a useful route for computing excited states of large chemical systems. We conclude by discussing the limitations and challenges still facing OO-DFT methods, as well as some potential avenues for addressing them

Contribución al conocimiento de las comunidades bénticas de Mar del Plata

Se ha estudiado una zona restringida del litoral rocoso entre Playa Grande y Playa Chica (Mar del Plata, República Argentina). Fue objetivo principal determinar la zonación biocenológica en un área biogeográficamente interesante, por su aislamiento de otras regiones rocosas del litoral sudamericano. Se adoptó la terminología zonal de Pérés y Picard (1958) y los lincamientos generales fueron semejantes a un estudio anterior efectuado en Puerto Pardelas (Chubut, Argentina) (Olivier, Paternóster y Bastida, 1966). Las biocenosis que pueblan los pisos Supralitoral y Mediolitoral posibilitaron la diferenciación de los distintos horizontes.It has been studied a restricted rocky littoral zone between Playa Grande and Playa Chica (Argentine Republic, Mar del Plata). The main object was to determine the biocenological zonation in a biogeographycally interesting area, because of its isolation from the other rocky regions of the southamerican littoral. The Pérés and Picard (1958) zonal terminology was adopted and the general features were similar to a previous study done in Puerto Pardelas (Argentine, Chubut) (Olivier, Paternóster y Bastida, 1966). It was possible to distinguish the different horizons because of the biocenoses that occupy the Supralittoral and Medlilittoral levels

Extensive co-operation between the Epstein-Barr virus EBNA3 proteins in the manipulation of host gene expression and epigenetic chromatin modification.

Epstein-Barr virus (EBV) is able to drive the transformation of B-cells, resulting in the generation of lymphoblastoid cell lines (LCLs) in vitro. EBV nuclear proteins EBNA3A and EBNA3C are necessary for efficient transformation, while EBNA3B is dispensable. We describe a transcriptome analysis of BL31 cells infected with a series of EBNA3-knockout EBVs, including one deleted for all three EBNA3 genes. Using Affymetrix Exon 1.0 ST microarrays analysed with the MMBGX algorithm, we have identified over 1000 genes whose regulation by EBV requires one of the EBNA3s. Remarkably, a third of the genes identified require more than one EBNA3 for their regulation, predominantly EBNA3C co-operating with either EBNA3B, EBNA3A or both. The microarray was validated by real-time PCR, while ChIP analysis of a selection of co-operatively repressed promoters indicates a role for polycomb group complexes. Targets include genes involved in apoptosis, cell migration and B-cell differentiation, and show a highly significant but subtle alteration in genes involved in mitosis. In order to assess the relevance of the BL31 system to LCLs, we analysed the transcriptome of a set of EBNA3B knockout (3BKO) LCLs. Around a third of the genes whose expression level in LCLs was altered in the absence of EBNA3B were also altered in 3BKO-BL31 cell lines.Among these are TERT and TCL1A, implying that EBV-induced changes in the expression of these genes are not required for B-cell transformation. We also identify 26 genes that require both EBNA3A and EBNA3B for their regulation in LCLs. Together, this shows the complexity of the interaction between EBV and its host, whereby multiple EBNA3 proteins co-operate to modulate the behaviour of the host cell

A Fast Association Test for Identifying Pathogenic Variants Involved in Rare Diseases

We present a rapid and powerful inference procedure for identifying loci associated with rare hereditary disorders using Bayesian model comparison. Under a baseline model, disease risk is fixed across all individuals in a study. Under an association model, disease risk depends on a latent bipartition of rare variants into pathogenic and non-pathogenic variants, the number of pathogenic alleles that each individual carries, and the mode of inheritance. A parameter indicating presence of an association and the parameters representing the pathogenicity of each variant and the mode of inheritance can be inferred in a Bayesian framework. Variant-specific prior information derived from allele frequency databases, consequence prediction algorithms, or genomic datasets can be integrated into the inference. Association models can be fitted to different subsets of variants in a locus and compared using a model selection procedure. This procedure can improve inference if only a particular class of variants confers disease risk and can suggest particular disease etiologies related to that class. We show that our method, called BeviMed, is more powerful and informative than existing rare variant association methods in the context of dominant and recessive disorders. The high computational efficiency of our algorithm makes it feasible to test for associations in the large non-coding fraction of the genome. We have applied BeviMed to whole-genome sequencing data from 6,586 individuals with diverse rare diseases. We show that it can identify multiple loci involved in rare diseases, while correctly inferring the modes of inheritance, the likely pathogenic variants, and the variant classes responsible.This work was supported by NIHR award RG65966 (D.G. and E.T.) and the Medical Research Council program grant MC_UP_0801/1 (D.G. and S.R.)

Oxygen pressure measurement using singlet oxygen emission

Pressure sensitive paint (PSP) provides a visualization of two-dimensional pressure distributions on airfoil and model automobile surfaces. One type of PSP utilizes platinum tetra(pentafluorophenyl)porphine (PtTFPP) dissolved in a fluoro-polymer film. Since the intense 650 nm triplet emission of PtTFPP is quenched by ground state oxygen, it is possible to measure two-dimensional oxygen concentration from the 650 nm emission intensity using a Stern-Volmer-type relationship. This article reports an alternative luminescence method to measure oxygen concentration based on the porphyrin-sensitized 1270 nm singlet oxygen emission, which can be imaged with an InGaAs near infrared camera. This direct measurement of oxygen emission complements and further validates the oxygen measurement based on PtTFPP phosphorescence quenching. Initial success at obtaining a negative correlation between the 650nm PtTFPP emission and the 1270 nm O_2 emission in solution led us to additional two-dimensional film studies using surfaces coated with PtTFPP, MgTFPP, and H_2TFPP in polymers in a pressure and temperature controlled chamber

Photochemistry and magnetic resonance spectroscopy as probes of supramolecular structures and migration pathways of organic molecules and radicals adsorbed on zeolites

Magnetic resonance, surface area measurements and computational techniques have been integrated to elucidate the supramolecular photochemistry of two isomeric ketones adsorbed on two MFI zeolites (silicalite and ZSM-5) and to demonstrate that common factors proportional to the available external surface area operate to determine the measured parameters in each case

Enhancing Qubit Readout with Autoencoders

In addition to the need for stable and precisely controllable qubits, quantum computers take advantage of good readout schemes. Superconducting qubit states can be inferred from the readout signal transmitted through a dispersively coupled resonator. This work proposes a novel readout classification method for superconducting qubits based on a neural network pre-trained with an autoencoder approach. A neural network is pre-trained with qubit readout signals as autoencoders in order to extract relevant features from the data set. Afterwards, the pre-trained network inner layer values are used to perform a classification of the inputs in a supervised manner. We demonstrate that this method can enhance classification performance, particularly for short and long time measurements where more traditional methods present lower performance.Comment: 16 pages, 23 figure