Smell and taste symptom-based predictive model for COVID-19 diagnosis.

BackgroundThe presentation of coronavirus 2019 (COVID-19) overlaps with common influenza symptoms. There is limited data on whether a specific symptom or collection of symptoms may be useful to predict test positivity.MethodsAn anonymous electronic survey was publicized through social media to query participants with COVID-19 testing. Respondents were questioned regarding 10 presenting symptoms, demographic information, comorbidities, and COVID-19 test results. Stepwise logistic regression was used to identify predictors for COVID-19 positivity. Selected classifiers were assessed for prediction performance using receiver operating characteristic (ROC) curve analysis.ResultsA total of 145 participants with positive COVID-19 testing and 157 with negative results were included. Participants had a mean age of 39 years, and 214 (72%) were female. Smell or taste change, fever, and body ache were associated with COVID-19 positivity, and shortness of breath and sore throat were associated with a negative test result (p < 0.05). A model using all 5 diagnostic symptoms had the highest accuracy with a predictive ability of 82% in discriminating between COVID-19 results. To maximize sensitivity and maintain fair diagnostic accuracy, a combination of 2 symptoms, change in sense of smell or taste and fever was found to have a sensitivity of 70% and overall discrimination accuracy of 75%.ConclusionSmell or taste change is a strong predictor for a COVID-19-positive test result. Using the presence of smell or taste change with fever, this parsimonious classifier correctly predicts 75% of COVID-19 test results. A larger cohort of respondents will be necessary to refine classifier performance

Transparent Synchronous Dataflow

Dataflow programming is a popular and convenient programming paradigm in systems modelling, optimisation, and machine learning. It has a number of advantages, for instance the lacks of control flow allows computation to be carried out in parallel as well as in distributed machines. More recently the idea of dataflow graphs has also been brought into the design of various deep learning frameworks. They facilitate an easy and efficient implementation of automatic differentiation, which is the heart of modern deep learning paradigm. [abstract abridged

Gas turbine combustor

A gas turbine engine has a combustor module including an annular combustor having a liner assembly that defines an annular combustion chamber having a length, L. The liner assembly includes a radially inner liner, a radially outer liner that circumscribes the inner liner, and a bulkhead, having a height, H1, which extends between the respective forward ends of the inner liner and the outer liner. The combustor has an exit height, H3, at the respective aft ends of the inner liner and the outer liner interior. The annular combustor has a ratio H1/H3 having a value less than or equal to 1.7. The annular combustor may also have a ration L/H3 having a value less than or equal to 6.0

Somatic Mutations of PIK3R1 Promote Gliomagenesis

The phosphoinositide 3-kinase (PI3K) pathway is targeted for frequent alteration in glioblastoma (GBM) and is one of the core GBM pathways defined by The Cancer Genome Atlas. Somatic mutations of PIK3R1 are observed in multiple tumor types, but the tumorigenic activity of these mutations has not been demonstrated in GBM. We show here that somatic mutations in the iSH2 domain of PIK3R1 act as oncogenic driver events. Specifically, introduction of a subset of the mutations identified in human GBM, in the nSH2 and iSH2 domains, increases signaling through the PI3K pathway and promotes tumorigenesis of primary normal human astrocytes in an orthotopic xenograft model. Furthermore, we show that cells that are dependent on mutant P85α-mediated PI3K signaling exhibit increased sensitivity to a small molecule inhibitor of AKT. Together, these results suggest that GBM patients whose tumors carry mutant PIK3R1 alleles may benefit from treatment with inhibitors of AKT

Direct Mediation and Metastable Supersymmetry Breaking for SO(10)

We examine a metastable $\mathcal{N}=1$ Macroscopic SO(N) SQCD model of Intriligator, Seiberg and Shih (ISS). We introduce various baryon and meson deformations, including multitrace operators and explore embedding an SO(10) parent of the standard model into two weakly gauged flavour sectors. Direct fundamental messengers and the symmetric pseudo-modulus messenger mediate SUSY breaking to the MSSM. Gaugino and sfermion masses are computed and compared for each deformation type. We also explore reducing the rank of the magnetic quark matrix of the ISS model and find an additional fundamental messenger.Comment: 43 pages, Latex. Version to appear in JHEP

What is new in uremic toxicity?

Uremic syndrome results from a malfunctioning of various organ systems due to the retention of compounds which, under normal conditions, would be excreted into the urine and/or metabolized by the kidneys. If these compounds are biologically active, they are called uremic toxins. One of the more important toxic effects of such compounds is cardio-vascular damage. A convenient classification based on the physico-chemical characteristics affecting the removal of such compounds by dialysis is: (1) small water-soluble compounds; (2) protein-bound compounds; (3) the larger “middle molecules”. Recent developments include the identification of several newly detected compounds linked to toxicity or the identification of as yet unidentified toxic effects of known compounds: the dinucleotide polyphosphates, structural variants of angiotensin II, interleukin-18, p-cresylsulfate and the guanidines. Toxic effects seem to be typically exerted by molecules which are “difficult to remove by dialysis”. Therefore, dialysis strategies have been adapted by applying membranes with larger pore size (high-flux membranes) and/or convection (on-line hemodiafiltration). The results of recent studies suggest that these strategies have better outcomes, thereby clinically corroborating the importance attributed in bench studies to these “difficult to remove” molecules

Sequence analysis of the Epstein-Barr virus (EBV) BRLF1 gene in nasopharyngeal and gastric carcinomas

<p>Abstract</p> <p>Background</p> <p>Epstein-Barr virus (EBV) has a biphasic infection cycle consisting of a latent and a lytic replicative phase. The product of immediate-early gene BRLF1, Rta, is able to disrupt the latency phase in epithelial cells and certain B-cell lines. The protein Rta is a frequent target of the EBV-induced cytotoxic T cell response. In spite of our good understanding of this protein, little is known for the gene polymorphism of BRLF1.</p> <p>Results</p> <p>BRLF1 gene was successfully amplified in 34 EBV-associated gastric carcinomas (EBVaGCs), 57 nasopharyngeal carcinomas (NPCs) and 28 throat washings (TWs) samples from healthy donors followed by PCR-direct sequencing. Fourteen loci were found to be affected by amino acid changes, 17 loci by silent nucleotide changes. According to the phylogenetic tree, 5 distinct subtypes of BRLF1 were identified, and 2 subtypes BR1-A and BR1-C were detected in 42.9% (51/119), 42.0% (50/119) of samples, respectively. The distribution of these 2 subtypes among 3 types of specimens was significantly different. The subtype BR1-A preferentially existed in healthy donors, while BR1-C was seen more in biopsies of NPC. A silent mutation A/G was detected in all the isolates. Among 3 functional domains, the dimerization domain of Rta showed a stably conserved sequence, while DNA binding and transactivation domains were detected to have multiple mutations. Three of 16 CTL epitopes, NAA, QKE and ERP, were affected by amino acid changes. Epitope ERP was relatively conserved; epitopes NAA and QKE harbored more mutations.</p> <p>Conclusions</p> <p>This first detailed investigation of sequence variations in BRLF1 gene has identified 5 distinct subtypes. Two subtypes BR1-A and BR1-C are the dominant genotypes of BRLF1. The subtype BR1-C is more frequent in NPCs, while BR1-A preferentially presents in healthy donors. BR1-C may be associated with the tumorigenesis of NPC.</p

Whole-exome sequencing combined with functional genomics reveals novel candidate driver cancer genes in endometrial cancer

Endometrial cancer is the most common gynecological malignancy, with more than 280,000 cases occurring annually worldwide. Although previous studies have identified important common somatic mutations in endometrial cancer, they have primarily focused on a small set of known cancer genes and have thus provided a limited view of the molecular basis underlying this disease. Here we have developed an integrated systems-biology approach to identifying novel cancer genes contributing to endometrial tumorigenesis. We first performed whole-exome sequencing on 13 endometrial cancers and matched normal samples, systematically identifying somatic alterations with high precision and sensitivity. We then combined bioinformatics prioritization with high-throughput screening (including both shRNA-mediated knockdown and expression of wild-type and mutant constructs) in a highly sensitive cell viability assay. Our results revealed 12 potential driver cancer genes including 10 tumor-suppressor candidates (ARID1A, INHBA, KMO, TTLL5, GRM8, IGFBP3, AKTIP, PHKA2, TRPS1, and WNT11) and two oncogene candidates (ERBB3 and RPS6KC1). The results in the ''sensor'' cell line were recapitulated by siRNA-mediated knockdown in endometrial cancer cell lines. Focusing on ARID1A, we integrated mutation profiles with functional proteomics in 222 endometrial cancer samples, demonstrating that ARID1A mutations frequently co-occur with mutations in the phosphatidylinositol 3-kinase (PI3K) pathway and are associated with PI3K pathway activation. siRNA knockdown in endometrial cancer cell lines increased AKT phosphorylation supporting ARID1A as a novel regulator of PI3K pathway activity. Our study presents the first unbiased view of somatic coding mutations in endometrial cancer and provides functional evidence for diverse driver genes and mutations in this disease. © 2012, Published by Cold Spring Harbor Laboratory Press.Link_to_subscribed_fulltex

Refinement of 1p36 Alterations Not Involving PRDM16 in Myeloid and Lymphoid Malignancies

Fluorescence in situ hybridization was performed to characterize 81 cases of myeloid and lymphoid malignancies with cytogenetic 1p36 alterations not affecting the PRDM16 locus. In total, three subgroups were identified: balanced translocations (N = 27) and telomeric rearrangements (N = 15), both mainly observed in myeloid disorders; and unbalanced non-telomeric rearrangements (N = 39), mainly observed in lymphoid proliferations and frequently associated with a highly complex karyotype. The 1p36 rearrangement was isolated in 12 cases, mainly myeloid disorders. The breakpoints on 1p36 were more widely distributed than previously reported, but with identifiable rare breakpoint cluster regions, such as the TP73 locus. We also found novel partner loci on 1p36 for the known multi-partner genes HMGA2 and RUNX1. We precised the common terminal 1p36 deletion, which has been suggested to have an adverse prognosis, in B-cell lymphomas [follicular lymphomas and diffuse large B-cell lymphomas with t(14;18)(q32;q21) as well as follicular lymphomas without t(14;18)]. Intrachromosomal telomeric repetitive sequences were detected in at least half the cases of telomeric rearrangements. It is unclear how the latter rearrangements occurred and whether they represent oncogenic events or result from chromosomal instability during oncogenesis