Mining Entity Synonyms with Efficient Neural Set Generation

Mining entity synonym sets (i.e., sets of terms referring to the same entity) is an important task for many entity-leveraging applications. Previous work either rank terms based on their similarity to a given query term, or treats the problem as a two-phase task (i.e., detecting synonymy pairs, followed by organizing these pairs into synonym sets). However, these approaches fail to model the holistic semantics of a set and suffer from the error propagation issue. Here we propose a new framework, named SynSetMine, that efficiently generates entity synonym sets from a given vocabulary, using example sets from external knowledge bases as distant supervision. SynSetMine consists of two novel modules: (1) a set-instance classifier that jointly learns how to represent a permutation invariant synonym set and whether to include a new instance (i.e., a term) into the set, and (2) a set generation algorithm that enumerates the vocabulary only once and applies the learned set-instance classifier to detect all entity synonym sets in it. Experiments on three real datasets from different domains demonstrate both effectiveness and efficiency of SynSetMine for mining entity synonym sets.Comment: AAAI 2019 camera-ready versio

Functional study of a novel missense single-nucleotide variant of NUP107 in two daughters of Mexican origin with premature ovarian insufficiency.

BackgroundHypergonadotropic hypogonadism (HH) is a genetically heterogeneous disorder that usually presents with amenorrhea, atrophic ovaries, and low estrogen. Most cases of HH are idiopathic and nonsyndromic. Nucleoporin 107 (NUP107), a protein involved in transport between cytoplasm and nucleus with putative roles in meiosis/mitosis progression, was recently implicated as a cause of HH. We identified a NUP107 genetic variant in a nonconsanguineous family with two sisters affected with primary amenorrhea and HH, and generated a mouse model that carried the human variant.MethodsWe performed a high-resolution X-chromosome microarray and whole exome sequencing on parents and two sisters with HH to identify pathogenic variants. We generated a mouse model of candidate NUP107 variant using CRISPR/Cas9.ResultsWhole exome sequencing identified a novel and rare missense variant in the NUP107 gene (c.1063C>T, p.R355C) in both sisters with HH. In order to determine functional significance of this variant, we used CRISPR/Cas9 to introduce the human variant into the mouse genome. Mice with the homolog of the R355C variant, as well as the nine base pairs deletion in Nup107 had female subfertility.ConclusionsOur findings indicate that NUP107 R355C variant falls in the category of variant of unknown significance as the cause of HH and infertility

A Semi-Parametric Model Simultaneously Handling Unmeasured Confounding, Informative Cluster Size, and Truncation by Death with a Data Application in Medicare Claims

Nearly 300,000 older adults experience a hip fracture every year, the majority of which occur following a fall. Unfortunately, recovery after fall-related trauma such as hip fracture is poor, where older adults diagnosed with Alzheimer's Disease and Related Dementia (ADRD) spend a particularly long time in hospitals or rehabilitation facilities during the post-operative recuperation period. Because older adults value functional recovery and spending time at home versus facilities as key outcomes after hospitalization, identifying factors that influence days spent at home after hospitalization is imperative. While several individual-level factors have been identified, the characteristics of the treating hospital have recently been identified as contributors. However, few methodological rigorous approaches are available to help overcome potential sources of bias such as hospital-level unmeasured confounders, informative hospital size, and loss to follow-up due to death. This article develops a useful tool equipped with unsupervised learning to simultaneously handle statistical complexities that are often encountered in health services research, especially when using large administrative claims databases. The proposed estimator has a closed form, thus only requiring light computation load in a large-scale study. We further develop its asymptotic properties that can be used to make statistical inference in practice. Extensive simulation studies demonstrate superiority of the proposed estimator compared to existing estimators.Comment: Contact Emails: [email protected]

Examining the Role of Environmental Nonprofits in Shoreline Management for Coastal Resilience in Virginia

Environmental Nonprofits emerged over the years to attend to the environmental needs of communities and individuals, as well as address environmental issues that concern the public. These issues are usually those that have been neglected, given insufficient attention, or cannot be singularly handled by the government. In advocating for coastal resilience, environmental nonprofits have been identified in the literature as actors with critical roles in addressing coastal issues such as sea-level rise, flooding and shoreline management. In recent times, shoreline management has emerged as one of the foremost areas of focus expedient for the achievement of coastal resilience, and the role of environmental nonprofits in ensuring the management of shorelines is of crucial importance. This study seeks to examine the roles environment nonprofits play in shoreline management for coastal resilience in Virginia. Utilizing qualitative research methods, data from some environmental nonprofits in Virginia’s coastal communities will be collected and analyzed, with the aim of interpreting the roles they play in the management and stabilization of shorelines and elaborating on the impact and implications for environmental sustainability and coastal resilience.https://digitalcommons.odu.edu/gradposters2020_business/1003/thumbnail.jp

Minority Turnout and Representation under Cumulative Voting. An Experiment.

Under majoritarian election systems, securing participation and representation of minorities remains an open problem, made salient in the US by its history of voter suppression. One remedy recommended by the courts is Cumulative Voting (CV): each voter has as many votes as open positions and can cumulate votes on as few candidates as desired. Theory predicts that CV encourages the minority to overcome obstacles to voting: although each voter is treated equally, CV increases minority's turnout relative to the majority, and the minority's share of seats won. A lab experiment based on a costly voting design strongly supports both predictions

Identification of PBX1 Target Genes in Cancer Cells by Global Mapping of PBX1 Binding Sites

PBX1 is a TALE homeodomain transcription factor involved in organogenesis and tumorigenesis. Although it has been shown that ovarian, breast, and melanoma cancer cells depend on PBX1 for cell growth and survival, the molecular mechanism of how PBX1 promotes tumorigenesis remains unclear. Here, we applied an integrated approach by overlapping PBX1 ChIP-chip targets with the PBX1-regulated transcriptome in ovarian cancer cells to identify genes whose transcription was directly regulated by PBX1. We further determined if PBX1 target genes identified in ovarian cancer cells were co-overexpressed with PBX1 in carcinoma tissues. By analyzing TCGA gene expression microarray datasets from ovarian serous carcinomas, we found co-upregulation of PBX1 and a significant number of its direct target genes. Among the PBX1 target genes, a homeodomain protein MEOX1 whose DNA binding motif was enriched in PBX1-immunoprecipicated DNA sequences was selected for functional analysis. We demonstrated that MEOX1 protein interacts with PBX1 protein and inhibition of MEOX1 yields a similar growth inhibitory phenotype as PBX1 suppression. Furthermore, ectopically expressed MEOX1 functionally rescued the PBX1-withdrawn effect, suggesting MEOX1 mediates the cellular growth signal of PBX1. These results demonstrate that MEOX1 is a critical target gene and cofactor of PBX1 in ovarian cancers

Increasing Colonoscopy Compliance Using a Blood-Based Risk Assessment Test for Colorectal Cancer

ColonSentry® is a minimally invasive, blood-based risk assessment test for colorectal cancer. The test is used to increase patient compliance with colonoscopy. Many physicians have inquired about the incidence of non-malignant lesions found in patients after colonoscopy prompted by an increased risk score on the ColonSentry test. Here we report on the colonoscopy results of five patients with increased ColonSentry risk scores. Of those five patients, three were determined to have polyps, one of which was pre-malignant