ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning

We present ATOMIC, an atlas of everyday commonsense reasoning, organized through 877k textual descriptions of inferential knowledge. Compared to existing resources that center around taxonomic knowledge, ATOMIC focuses on inferential knowledge organized as typed if-then relations with variables (e.g., "if X pays Y a compliment, then Y will likely return the compliment"). We propose nine if-then relation types to distinguish causes vs. effects, agents vs. themes, voluntary vs. involuntary events, and actions vs. mental states. By generatively training on the rich inferential knowledge described in ATOMIC, we show that neural models can acquire simple commonsense capabilities and reason about previously unseen events. Experimental results demonstrate that multitask models that incorporate the hierarchical structure of if-then relation types lead to more accurate inference compared to models trained in isolation, as measured by both automatic and human evaluation.Comment: AAAI 2019 C

THE DENTISTS AND THE SERVICES THEY PROVIDED FOR TWO POPULATIONS; COMMENTS ON METHODOLOGY OF STUDY

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65469/1/j.1752-7325.1965.tb00460.x.pd

Integrative analysis identifies candidate tumor microenvironment and intracellular signaling pathways that define tumor heterogeneity in NF1

Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40-60% of patients develop plexiform neurofibromas (pNFs), which are deeply embedded in the peripheral nerves. Patients with pNFs have a ~10% lifetime chance of these tumors becoming malignant peripheral nerve sheath tumors (MPNSTs). These tumors have a severe prognosis and few treatment options other than surgery. Given the lack of therapeutic options available to patients with these tumors, identification of druggable pathways or other key molecular features could aid ongoing therapeutic discovery studies. In this work, we used statistical and machine learning methods to analyze 77 NF1 tumors with genomic data to characterize key signaling pathways that distinguish these tumors and identify candidates for drug development. We identified subsets of latent gene expression variables that may be important in the identification and etiology of cNFs, pNFs, other neurofibromas, and MPNSTs. Furthermore, we characterized the association between these latent variables and genetic variants, immune deconvolution predictions, and protein activity predictions

The effectiveness of therapies for dual language children with developmental language disorder: a systematic review of interventional studies

Purpose: This study aims to understand the effect of therapies on dual language children with developmental language disorder (DLD) on a range of bilingual language outcomes, compare with second-language-only therapy and determine whether there is any cross-linguistic transfer. Methods: A systematic review of English articles in 10 electronic databases was conducted. Screening, reviewing and appraising were performed independently by two reviewers. Quality was appraised and findings synthesised in accordance with the research questions. Results: Nine reports were identified. Five studies were found to be low in bias and therefore high in quality. Two were medium bias and two were high. Key findings were that instruction in the first language is required to support its continued acquisition and that bilingual instruction does not limit second language growth. Conclusions: There is no identified evidence to suggest that second-language-only is better than bilingual therapy for dual language children with DLD for the development of the second language. There is evidence to suggest that bilingual therapy is equally effective for second language development, and also supports development of the first language. Further work is required to understand the efficacious doses of both languages in order to develop cost effective therapies and achieve optimal outcomes

On a q-extension of Mehta's eigenvectors of the finite Fourier transform for q a root of unity

It is shown that the continuous q-Hermite polynomials for q a root of unity have simple transformation properties with respect to the classical Fourier transform. This result is then used to construct q-extended eigenvectors of the finite Fourier transform in terms of these polynomials.Comment: 12 pages, thoroughly rewritten, the q-extended eigenvectors now N-periodic with q an M-th root of

Genomic Characterization of Patient-Derived Xenograft Models Established from Fine Needle Aspirate Biopsies of a Primary Pancreatic Ductal Adenocarcinoma and from Patient-Matched Metastatic Sites

N-of-1 trials target actionable mutations, yet such approaches do not test genomically-informed therapies in patient tumor models prior to patient treatment. To address this, we developed patient-derived xenograft (PDX) models from fine needle aspiration (FNA) biopsies (FNA-PDX) obtained from primary pancreatic ductal adenocarcinoma (PDAC) at the time of diagnosis. Here, we characterize PDX models established from one primary and two metastatic sites of one patient. We identified an activating KRAS G12R mutation among other mutations in these models. In explant cells derived from these PDX tumor models with a KRAS G12R mutation, treatment with inhibitors of CDKs (including CDK9) reduced phosphorylation of a marker of CDK9 activity (phospho-RNAPII CTD Ser2/5) and reduced viability/growth of explant cells derived from PDAC PDX models. Similarly, a CDK inhibitor reduced phospho-RNAPII CTD Ser2/5, increased apoptosis, and inhibited tumor growth in FNA-PDX and patient-matched metastatic-PDX models. In summary, PDX models can be constructed from FNA biopsies of PDAC which in turn can enable genomic characterization and identification of potential therapies

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound–kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome

Blood transcriptomics identifies immune signatures indicative of infectious complications in childhood cancer patients with febrile neutropenia

Objectives: Febrile neutropenia (FN) is a major cause of treatment disruption and unplanned hospitalization in childhood cancer patients. This study investigated the transcriptome of peripheral blood mononuclear cells (PBMCs) in children with cancer and FN to identify potential predictors of serious infection. Methods: Whole-genome transcriptional profiling was conducted on PBMCs collected during episodes of FN in children with cancer at presentation to the hospital (Day 1; n  = 73) and within 8-24 h (Day 2; n  = 28) after admission. Differentially expressed genes as well as gene pathways that correlated with clinical outcomes were defined for different infectious outcomes. Results: Global differences in gene expression associated with specific immune responses in children with FN and documented infection, compared to episodes without documented infection, were identified at admission. These differences resolved over the subsequent 8-24 h. Distinct gene signatures specific for bacteraemia were identified both at admission and on Day 2. Differences in gene signatures between episodes with bacteraemia and episodes with bacterial infection, viral infection and clinically defined infection were also observed. Only subtle differences in gene expression profiles between non-bloodstream bacterial and viral infections were identified. Conclusion: Blood transcriptome immune profiling analysis during FN episodes may inform monitoring and aid in defining adequate treatment for different infectious aetiologies in children with cancer

Potent Activity of the HIV-1 Maturation Inhibitor Bevirimat in SCID-hu Thy/Liv Mice

The HIV-1 maturation inhibitor, 3-O-(3',3'-dimethylsuccinyl) betulinic acid (bevirimat, PA-457) is a promising drug candidate with 10 nM in vitro antiviral activity against multiple wild-type (WT) and drug-resistant HIV-1 isolates. Bevirimat has a novel mechanism of action, specifically inhibiting cleavage of spacer peptide 1 (SP1) from the C-terminus of capsid which results in defective core condensation.Oral administration of bevirimat to HIV-1-infected SCID-hu Thy/Liv mice reduced viral RNA by >2 log(10) and protected immature and mature T cells from virus-mediated depletion. This activity was observed at plasma concentrations that are achievable in humans after oral dosing, and bevirimat was active up to 3 days after inoculation with both WT HIV-1 and an AZT-resistant HIV-1 clinical isolate. Consistent with its mechanism of action, bevirimat caused a dose-dependent inhibition of capsid-SP1 cleavage in HIV-1-infected human thymocytes obtained from these mice. HIV-1 NL4-3 with an alanine-to-valine substitution at the N-terminus of SP1 (SP1/A1V), which is resistant to bevirimat in vitro, was also resistant to bevirimat treatment in the mice, and SP1/AIV had replication and thymocyte kinetics similar to that of WT NL4-3 with no evidence of fitness impairment in in vivo competition assays. Interestingly, protease inhibitor-resistant HIV-1 with impaired capsid-SP1 cleavage was hypersensitive to bevirimat in vitro with a 50% inhibitory concentration 140 times lower than for WT HIV-1.These results support further clinical development of this first-in-class maturation inhibitor and confirm the usefulness of the SCID-hu Thy/Liv model for evaluation of in vivo antiretroviral efficacy, drug resistance, and viral fitness