Yukawa alignment from natural flavor conservation

We study the charged Higgs couplings to fermions in the "democratic" three-Higgs-doublet model, in which one doublet couples to down-type quarks, one to up-type quarks, and one to charged leptons. Flavor-changing neutral Higgs couplings are absent because the Glashow-Weinberg-Paschos condition for natural flavor conservation is in effect. We show that this model reproduces the coupling structure of the charged Higgs boson in the recently-proposed Yukawa-aligned two-Higgs-doublet model, with two subtle constraints that arise from the unitarity of the charged Higgs mixing matrix. Adding a fourth Higgs doublet with no couplings to fermions eliminates these constraints.Comment: 12 pages, no figures. v2: minor improvements to text, references added, submitted to PRD. v3: added appendix on 3HDM scalar potential, accepted by PR

Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images : a retrospective study

Background: Determining the status of molecular pathways and key mutations in colorectal cancer is crucial for optimal therapeutic decision making. We therefore aimed to develop a novel deep learning pipeline to predict the status of key molecular pathways and mutations from whole-slide images of haematoxylin and eosin-stained colorectal cancer slides as an alternative to current tests. Methods: In this retrospective study, we used 502 diagnostic slides of primary colorectal tumours from 499 patients in The Cancer Genome Atlas colon and rectal cancer (TCGA-CRC-DX) cohort and developed a weakly supervised deep learning framework involving three separate convolutional neural network models. Whole-slide images were divided into equally sized tiles and model 1 (ResNet18) extracted tumour tiles from non-tumour tiles. These tumour tiles were inputted into model 2 (adapted ResNet34), trained by iterative draw and rank sampling to calculate a prediction score for each tile that represented the likelihood of a tile belonging to the molecular labels of high mutation density (vs low mutation density), microsatellite instability (vs microsatellite stability), chromosomal instability (vs genomic stability), CpG island methylator phenotype (CIMP)-high (vs CIMP-low), BRAFmut (vs BRAFWT), TP53mut (vs TP53WT), and KRASWT (vs KRASmut). These scores were used to identify the top-ranked titles from each slide, and model 3 (HoVer-Net) segmented and classified the different types of cell nuclei in these tiles. We calculated the area under the convex hull of the receiver operating characteristic curve (AUROC) as a model performance measure and compared our results with those of previously published methods. Findings: Our iterative draw and rank sampling method yielded mean AUROCs for the prediction of hypermutation (0·81 [SD 0·03] vs 0·71), microsatellite instability (0·86 [0·04] vs 0·74), chromosomal instability (0·83 [0·02] vs 0·73), BRAFmut (0·79 [0·01] vs 0·66), and TP53mut (0·73 [0·02] vs 0·64) in the TCGA-CRC-DX cohort that were higher than those from previously published methods, and an AUROC for KRASmut that was similar to previously reported methods (0·60 [SD 0·04] vs 0·60). Mean AUROC for predicting CIMP-high status was 0·79 (SD 0·05). We found high proportions of tumour-infiltrating lymphocytes and necrotic tumour cells to be associated with microsatellite instability, and high proportions of tumour-infiltrating lymphocytes and a low proportion of necrotic tumour cells to be associated with hypermutation. Interpretation: After large-scale validation, our proposed algorithm for predicting clinically important mutations and molecular pathways, such as microsatellite instability, in colorectal cancer could be used to stratify patients for targeted therapies with potentially lower costs and quicker turnaround times than sequencing-based or immunohistochemistry-based approaches. Funding: The UK Medical Research Council

Searches for Double Beta Decay of 134^{134}Xe with EXO-200

Searches for double beta decay of $^{134}$Xe were performed with EXO-200, a single-phase liquid xenon detector designed to search for neutrinoless double beta decay of $^{136}$Xe. Using an exposure of $29.6\text{ kg}\!\cdot\!\text{yr}$, the lower limits of $\text{T}_{1/2}^{2\nu\beta\!\beta}>8.7\cdot10^{20}\text{ yr}$ and $\text{T}_{1/2}^{0\nu\beta\!\beta}>1.1\cdot10^{23}\text{ yr}$ at 90% confidence level were derived, with corresponding half-life sensitivities of $1.2\cdot10^{21}\text{ yr}$ and $1.9\cdot10^{23}\text{ yr}$. These limits exceed those in the literature for $^{134}$Xe, improving by factors of nearly $10^{5}$ and 2 for the two antineutrino and neutrinoless modes, respectively.Comment: 8 pages, 4 figure

Search for nucleon decays with EXO-200

A search for instability of nucleons bound in $^{136}$Xe nuclei is reported with 223 kg$\cdot$yr exposure of $^{136}$Xe in the EXO-200 experiment. Lifetime limits of 3.3$\times 10^{23}$ and 1.9$\times 10^{23}$ yrs are established for nucleon decay to $^{133}$Sb and $^{133}$Te, respectively. These are the most stringent to date, exceeding the prior decay limits by a factor of 9 and 7, respectively

An Intraocular Pressure Polygenic Risk Score Stratifies Multiple Primary Open-Angle Glaucoma Parameters Including Treatment Intensity

Purpose: To examine the combined effects of common genetic variants associated with intraocular pressure (IOP) on primary open-angle glaucoma (POAG) phenotype using a polygenic risk score (PRS) stratification. Design: Cross-sectional study. Participants: For the primary analysis, we examined the glaucoma phenotype of 2154 POAG patients enrolled in the Australian and New Zealand Registry of Advanced Glaucoma, including patients recruited from the United Kingdom. For replication, we examined an independent cohort of 624 early POAG patients. Methods Using IOP genome-wide association study summary statistics, we developed a PRS derived solely from IOP-associated variants and stratified POAG patients into 3 risk tiers. The lowest and highest quintiles of the score were set as the low- and high-risk groups, respectively, and the other quintiles were set as the intermediate risk group. Main Outcome Measures: Clinical glaucoma phenotype including maximum recorded IOP, age at diagnosis, number of family members affected by glaucoma, cup-to-disc ratio, visual field mean deviation, and treatment intensity. Results: A dose–response relationship was found between the IOP PRS and the maximum recorded IOP, with the high genetic risk group having a higher maximum IOP by 1.7 mmHg (standard deviation [SD], 0.62 mmHg) than the low genetic risk group (P = 0.006). Compared with the low genetic risk group, the high genetic risk group had a younger age of diagnosis by 3.7 years (SD, 1.0 years; P < 0.001), more family members affected by 0.46 members (SD, 0.11 members; P < 0.001), and higher rates of incisional surgery (odds ratio, 1.5; 95% confidence interval, 1.1–2.0; P = 0.007). No statistically significant difference was found in mean deviation. We further replicated the maximum IOP, number of family members affected by glaucoma, and treatment intensity (number of medications) results in the early POAG cohort (P ≤ 0.01). Conclusions: The IOP PRS was correlated positively with maximum IOP, disease severity, need for surgery, and number of affected family members. Genes acting via IOP-mediated pathways, when considered in aggregate, have clinically important and reproducible implications for glaucoma patients and their close family members

Feature biases in early word learning : network distinctiveness predicts age of acquisition

Do properties of a word’s features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on shared and non-shared features. Feature distinctiveness predicted order of acquisition across all measures; words that were further away from other words in the network space were learned earlier. The best distance measures were based only on non-shared features (object dissimilarity) and did not include shared features (object similarity). This indicates that shared features may play less of a role in early word learning than non-shared features. In addition, the strongest effects were found for visual form and surface features. Cluster analysis further revealed that this effect is a localized effect in the object feature space, where objects’ distances from their cluster centroid were inversely correlated with their age of acquisition. Together, these results suggest a role for feature distinctiveness in early word learning

Sensitivity and discovery potential of the proposed nEXO experiment to neutrinoless double beta decay

The next-generation Enriched Xenon Observatory (nEXO) is a proposed experiment to search for neutrinoless double beta ($0\nu\beta\beta$) decay in $^{136}$Xe with a target half-life sensitivity of approximately $10^{28}$ years using $5\times10^3$ kg of isotopically enriched liquid-xenon in a time projection chamber. This improvement of two orders of magnitude in sensitivity over current limits is obtained by a significant increase of the $^{136}$Xe mass, the monolithic and homogeneous configuration of the active medium, and the multi-parameter measurements of the interactions enabled by the time projection chamber. The detector concept and anticipated performance are presented based upon demonstrated realizable background rates.Comment: v2 as publishe

Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression

Glaucoma, a disease characterized by progressive optic nerve degeneration, can be prevented through timely diagnosis and treatment. We characterize optic nerve photographs of 67,040 UK Biobank participants and use a multitrait genetic model to identify risk loci for glaucoma. A glaucoma polygenic risk score (PRS) enables effective risk stratification in unselected glaucoma cases and modifies penetrance of the MYOC variant encoding p.Gln368Ter, the most common glaucoma-associated myocilin variant. In the unselected glaucoma population, individuals in the top PRS decile reach an absolute risk for glaucoma 10 years earlier than the bottom decile and are at 15-fold increased risk of developing advanced glaucoma (top 10% versus remaining 90%, odds ratio = 4.20). The PRS predicts glaucoma progression in prospectively monitored, early manifest glaucoma cases (P = 0.004) and surgical intervention in advanced disease (P = 3.6 × 10). This glaucoma PRS will facilitate the development of a personalized approach for earlier treatment of high-risk individuals, with less intensive monitoring and treatment being possible for lower-risk groups