Domain-specific language models and lexicons for tagging

AbstractAccurate and reliable part-of-speech tagging is useful for many Natural Language Processing (NLP) tasks that form the foundation of NLP-based approaches to information retrieval and data mining. In general, large annotated corpora are necessary to achieve desired part-of-speech tagger accuracy. We show that a large annotated general-English corpus is not sufficient for building a part-of-speech tagger model adequate for tagging documents from the medical domain. However, adding a quite small domain-specific corpus to a large general-English one boosts performance to over 92% accuracy from 87% in our studies. We also suggest a number of characteristics to quantify the similarities between a training corpus and the test data. These results give guidance for creating an appropriate corpus for building a part-of-speech tagger model that gives satisfactory accuracy results on a new domain at a relatively small cost

Therapeutic targeting of integrin αvβ6 in breast cancer

BACKGROUND: Integrin ?v?6 promotes migration, invasion, and survival of cancer cells; however, the relevance and role of ?v?6 has yet to be elucidated in breast cancer.METHODS: Protein expression of integrin subunit beta6 (?6) was measured in breast cancers by immunohistochemistry (n &gt; 2000) and ITGB6 mRNA expression measured in the Molecular Taxonomy of Breast Cancer International Consortium dataset. Overall survival was assessed using Kaplan Meier curves, and bioinformatics statistical analyses were performed (Cox proportional hazards model, Wald test, and Chi-square test of association). Using antibody (264RAD) blockade and siRNA knockdown of ?6 in breast cell lines, the role of ?v?6 in Human Epidermal Growth Factor Receptor 2 (HER2) biology (expression, proliferation, invasion, growth in vivo) was assessed by flow cytometry, MTT, Transwell invasion, proximity ligation assay, and xenografts (n ? 3), respectively. A student's t-test was used for two variables; three-plus variables used one-way analysis of variance with Bonferroni's Multiple Comparison Test. Xenograft growth was analyzed using linear mixed model analysis, followed by Wald testing and survival, analyzed using the Log-Rank test. All statistical tests were two sided.RESULTS: High expression of either the mRNA or protein for the integrin subunit ?6 was associated with very poor survival (HR = 1.60, 95% CI = 1.19 to 2.15, P = .002) and increased metastases to distant sites. Co-expression of ?6 and HER2 was associated with worse prognosis (HR = 1.97, 95% CI = 1.16 to 3.35, P = .01). Monotherapy with 264RAD or trastuzumab slowed growth of MCF-7/HER2-18 and BT-474 xenografts similarly (P &lt; .001), but combining 264RAD with trastuzumab effectively stopped tumor growth, even in trastuzumab-resistant MCF-7/HER2-18 xenografts.CONCLUSIONS: Targeting ?v?6 with 264RAD alone or in combination with trastuzumab may provide a novel therapy for treating high-risk and trastuzumab-resistant breast cancer patients.<br/

Pregnancy outcomes in a malaria-exposed Malian cohort of women of child-bearing age

In Sub-Saharan Africa, malaria continues to be associated with adverse pregnancy outcomes including stillbirth, early neonatal death, preterm delivery, and low birth weight. Current preventive measures are insufficient and new interventions are urgently needed. However, before such interventions can be tested in pregnant women, background information on pregnancy outcomes in this target population must be collected. We conducted an observational study in Ouélessébougou, Mali, a malaria-endemic area where first antenatal visit commonly occurs during the second trimester of pregnancy, hindering calculation of miscarriage rate in the population. To accurately determine the rate of miscarriage, 799 non-pregnant women of child-bearing age were enrolled and surveyed via monthly follow up visits that included pregnancy tests. Out of 505 women that completed the study, 364 became pregnant and 358 pregnancies were analyzed: 43 (12%) resulted in miscarriage, 28 (65.1%) occurred during the first trimester of pregnancy. We also determined rates of stillbirth, neonatal death, preterm delivery, and small for gestational age. The results showed high rate of miscarriage during the first trimester and established a basis to evaluate new interventions to prevent pregnancy malaria. This survey design enabled identification of first trimester miscarriages that are often missed by studies conducted in antenatal clinics.Clinical trial registration[https://clinicaltrials.gov/], identifier [NCT0297 4608]

Electrocardiographic Deep Learning for Predicting Post-Procedural Mortality

Background. Pre-operative risk assessments used in clinical practice are limited in their ability to identify risk for post-operative mortality. We hypothesize that electrocardiograms contain hidden risk markers that can help prognosticate post-operative mortality. Methods. In a derivation cohort of 45,969 pre-operative patients (age 59+- 19 years, 55 percent women), a deep learning algorithm was developed to leverage waveform signals from pre-operative ECGs to discriminate post-operative mortality. Model performance was assessed in a holdout internal test dataset and in two external hospital cohorts and compared with the Revised Cardiac Risk Index (RCRI) score. Results. In the derivation cohort, there were 1,452 deaths. The algorithm discriminates mortality with an AUC of 0.83 (95% CI 0.79-0.87) surpassing the discrimination of the RCRI score with an AUC of 0.67 (CI 0.61-0.72) in the held out test cohort. Patients determined to be high risk by the deep learning model's risk prediction had an unadjusted odds ratio (OR) of 8.83 (5.57-13.20) for post-operative mortality as compared to an unadjusted OR of 2.08 (CI 0.77-3.50) for post-operative mortality for RCRI greater than 2. The deep learning algorithm performed similarly for patients undergoing cardiac surgery with an AUC of 0.85 (CI 0.77-0.92), non-cardiac surgery with an AUC of 0.83 (0.79-0.88), and catherization or endoscopy suite procedures with an AUC of 0.76 (0.72-0.81). The algorithm similarly discriminated risk for mortality in two separate external validation cohorts from independent healthcare systems with AUCs of 0.79 (0.75-0.83) and 0.75 (0.74-0.76) respectively. Conclusion. The findings demonstrate how a novel deep learning algorithm, applied to pre-operative ECGs, can improve discrimination of post-operative mortality

Malaria in HIV-Infected Children Receiving HIV Protease-Inhibitor- Compared with Non-Nucleoside Reverse Transcriptase Inhibitor-Based Antiretroviral Therapy, IMPAACT P1068s, Substudy to P1060

HIV and malaria geographically overlap. HIV protease inhibitors kill malaria parasites in vitro and in vivo, but further evaluation in clinical studies is needed

TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data

Summary: TREAT (Targeted RE-sequencing Annotation Tool) is a tool for facile navigation and mining of the variants from both targeted resequencing and whole exome sequencing. It provides a rich integration of publicly available as well as in-house developed annotations and visualizations for variants, variant-hosting genes and host-gene pathways

Early and extensive CD55 loss from red blood cells supports a causal role in malarial anaemia

BACKGROUND\ud \ud Levels of complement regulatory proteins (CrP) on the surface of red blood cells (RBC) decrease during severe malarial anaemia and as part of cell ageing process. It remains unclear whether CrP changes seen during malaria contribute to the development of anaemia, or result from an altered RBC age distribution due to suppressive effects of malaria on erythropoiesis.\ud \ud METHODS\ud \ud A cross sectional study was conducted in the north-east coast of Tanzania to investigate whether the changes in glycosylphosphatidylinositol (GPI)-anchored complement regulatory proteins (CD55 and CD59) contributes to malaria anaemia. Blood samples were collected from a cohort of children under intensive surveillance for Plasmodium falciparum parasitaemia and illness. Levels of CD55 and CD59 were measured by flow cytometer and compared between anaemic (8.08 g/dl) and non- anaemic children (11.42 g/dl).\ud \ud RESULTS\ud \ud Levels of CD55 and CD59 decreased with increased RBC age. CD55 levels were lower in anaemic children and the difference was seen in RBC of all ages. Levels of CD59 were lower in anaemic children, but these differences were not significant. CD55, but not CD59, levels correlated positively with the level of haemoglobin in anaemic children.\ud \ud CONCLUSION\ud \ud The extent of CD55 loss from RBC of all ages early in the course of malarial anaemia and the correlation of CD55 with haemoglobin levels support the hypothesis that CD55 may play a causal role in this disorder

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin