CDH1 mutation distribution and type suggests genetic differences between the etiology of orofacial clefting and gastric cancer

Pathogenic variants in CDH1, encoding epithelial cadherin (E-cadherin), have been implicated in hereditary diffuse gastric cancer (HDGC), lobular breast cancer, and both syndromic and non-syndromic cleft lip/palate (CL/P). Despite the large number of CDH1 mutations described, the nature of the phenotypic consequence of such mutations is currently not able to be predicted, creating significant challenges for genetic counselling. This study collates the phenotype and molecular data for available CDH1 variants that have been classified, using the American College of Medical Genetics and Genomics criteria, as at least ‘likely pathogenic’, and correlates their molecular and structural characteristics to phenotype. We demonstrate that CDH1 variant type and location differ between HDGC and CL/P, and that there is clustering of CL/P variants within linker regions between the extracellular domains of the cadherin protein. While these differences do not provide for exact prediction of the phenotype for a given mutation, they may contribute to more accurate assessments of risk for HDGC or CL/P for individuals with specific CDH1 variants

Dental anomaly detection using intraoral photos via deep learning

Children with orofacial clefting (OFC) present with a wide range of dental anomalies. Identifying these anomalies is vital to understand their etiology and to discern the complex phenotypic spectrum of OFC. Such anomalies are currently identified using intra-oral exams by dentists, a costly and time-consuming process. We claim that automating the process of anomaly detection using deep neural networks (DNNs) could increase efficiency and provide reliable anomaly detection while potentially increasing the speed of research discovery. This study characterizes the use of` DNNs to identify dental anomalies by training a DNN model using intraoral photographs from the largest international cohort to date of children with nonsyndromic OFC and controls (OFC1). In this project, the intraoral images were submitted to a Convolutional Neural Network model to perform multi-label multi-class classification of 10 dental anomalies. The network predicts whether an individual exhibits any of the 10 anomalies and can do so significantly faster than a human rater can. For all but three anomalies, F1 scores suggest that our model performs competitively at anomaly detection when compared to a dentist with 8 years of clinical experience. In addition, we use saliency maps to provide a post-hoc interpretation for our model’s predictions. This enables dentists to examine and verify our model’s predictions.Fil: Ragodos, Ronilo. University of Iowa; Estados UnidosFil: Wang, Tong. University of Iowa; Estados UnidosFil: Padilla, Carmencita. University of the Philippines; FilipinasFil: Hecht, Jacqueline T.. University of Texas Health Science Center at Houston; Estados UnidosFil: Poletta, Fernando Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. CEMIC-CONICET. Centro de Educaciones Médicas e Investigaciones Clínicas "Norberto Quirno". CEMIC-CONICET; ArgentinaFil: Orioli, Ieda Maria. Universidade Federal do Rio de Janeiro; BrasilFil: Buxó, Carmen J.. Universidad de Puerto Rico; Puerto RicoFil: Butali, Azeez. University of Iowa; Estados UnidosFil: Valencia Ramirez, Consuelo. Fundación Clínica Noel; ColombiaFil: Restrepo Muñeton, Claudia. Fundación Clínica Noel; ColombiaFil: Wehby, George. University of Iowa; Estados UnidosFil: Weinberg, Seth M.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Marazita, Mary L.. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Moreno Uribe, Lina M.. University of Iowa; Estados UnidosFil: Howe, Brian J.. University of Iowa; Estados Unido

High rate, fast timing Glass RPC for the high {\eta} CMS muon detectors

The HL-LHC phase is designed to increase by an order of magnitude the amount of data to be collected by the LHC experiments. To achieve this goal in a reasonable time scale the instantaneous luminosity would also increase by an order of magnitude up to $6.10^{34} cm^{-2} s^{-1}$ . The region of the forward muon spectrometer ($|{\eta}| > 1.6$) is not equipped with RPC stations. The increase of the expected particles rate up to $2 kHz/cm^{2}$ (including a safety factor 3) motivates the installation of RPC chambers to guarantee redundancy with the CSC chambers already present. The actual RPC technology of CMS cannot sustain the expected background level. The new technology that will be chosen should have a high rate capability and provides a good spatial and timing resolution. A new generation of Glass-RPC (GRPC) using low-resistivity (LR) glass is proposed to equip at least the two most far away of the four high ${\eta}$ muon stations of CMS. First the design of small size prototypes and studies of their performance in high-rate particles flux is presented. Then the proposed designs for large size chambers and their fast-timing electronic readout are examined and preliminary results are provided.Comment: 14 pages, 11 figures, Conference proceeding for the 2016 Resistive Plate Chambers and Related Detector

Rare and Common Variants Conferring Risk of Tooth Agenesis

We present association results from a large genome-wide association study of tooth agenesis (TA) as well as selective TA, including 1,944 subjects with congenitally missing teeth, excluding third molars, and 338,554 controls, all of European ancestry. We also tested the association of previously identified risk variants, for timing of tooth eruption and orofacial clefts, with TA. We report associations between TA and 9 novel risk variants. Five of these variants associate with selective TA, including a variant conferring risk of orofacial clefts. These results contribute to a deeper understanding of the genetic architecture of tooth development and disease. The few variants previously associated with TA were uncovered through candidate gene studies guided by mouse knockouts. Knowing the etiology and clinical features of TA is important for planning oral rehabilitation that often involves an interdisciplinary approach

Constraints on the χ_(c1) versus χ_(c2) polarizations in proton-proton collisions at √s = 8 TeV

The polarizations of promptly produced χ_(c1) and χ_(c2) mesons are studied using data collected by the CMS experiment at the LHC, in proton-proton collisions at √s=8  TeV. The χ_c states are reconstructed via their radiative decays χ_c → J/ψγ, with the photons being measured through conversions to e⁺e⁻, which allows the two states to be well resolved. The polarizations are measured in the helicity frame, through the analysis of the χ_(c2) to χ_(c1) yield ratio as a function of the polar or azimuthal angle of the positive muon emitted in the J/ψ → μ⁺μ⁻ decay, in three bins of J/ψ transverse momentum. While no differences are seen between the two states in terms of azimuthal decay angle distributions, they are observed to have significantly different polar anisotropies. The measurement favors a scenario where at least one of the two states is strongly polarized along the helicity quantization axis, in agreement with nonrelativistic quantum chromodynamics predictions. This is the first measurement of significantly polarized quarkonia produced at high transverse momentum