578 research outputs found
Measles Rash Identification Using Residual Deep Convolutional Neural Network
Measles is extremely contagious and is one of the leading causes of
vaccine-preventable illness and death in developing countries, claiming more
than 100,000 lives each year. Measles was declared eliminated in the US in 2000
due to decades of successful vaccination for the measles. As a result, an
increasing number of US healthcare professionals and the public have never seen
the disease. Unfortunately, the Measles resurged in the US in 2019 with 1,282
confirmed cases. To assist in diagnosing measles, we collected more than 1300
images of a variety of skin conditions, with which we employed residual deep
convolutional neural network to distinguish measles rash from other skin
conditions, in an aim to create a phone application in the future. On our image
dataset, our model reaches a classification accuracy of 95.2%, sensitivity of
81.7%, and specificity of 97.1%, indicating the model is effective in
facilitating an accurate detection of measles to help contain measles
outbreaks
Analysis of 17,576 Potentially Functional SNPs in Three Case–Control Studies of Myocardial Infarction
Myocardial infarction (MI) is a common complex disease with a genetic component. While several single nucleotide polymorphisms (SNPs) have been reported to be associated with risk of MI, they do not fully explain the observed genetic component of MI. We have been investigating the association between MI and SNPs that are located in genes and have the potential to affect gene function or expression. We have previously published studies that tested about 12,000 SNPs for association with risk of MI, early-onset MI, or coronary stenosis. In the current study we tested 17,576 SNPs that could affect gene function or expression. In order to use genotyping resources efficiently, we staged the testing of these SNPs in three case–control studies of MI. In the first study (762 cases, 857 controls) we tested 17,576 SNPs and found 1,949 SNPs that were associated with MI (P<0.05). We tested these 1,949 SNPs in a second study (579 cases and 1159 controls) and found that 24 SNPs were associated with MI (1-sided P<0.05) and had the same risk alleles in the first and second study. Finally, we tested these 24 SNPs in a third study (475 cases and 619 controls) and found that 5 SNPs in 4 genes (ENO1, FXN (2 SNPs), HLA-DPB2, and LPA) were associated with MI in the third study (1-sided P<0.05), and had the same risk alleles in all three studies. The false discovery rate for this group of 5 SNPs was 0.23. Thus, we have identified 5 SNPs that merit further examination for their potential association with MI. One of these SNPs (in LPA), has been previously shown to be associated with risk of cardiovascular disease in other studies
Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop.
Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting
Deregulation of the EGFR/PI3K/PTEN/Akt/mTORC1 pathway in breast cancer: possibilities for therapeutic intervention
The EGFR/PI3K/PTEN/Akt/mTORC1/GSK-3 pathway plays prominent roles in
malignant transformation, prevention of apoptosis, drug resistance and
metastasis. The expression of this pathway is frequently altered in
breast cancer due to mutations at or aberrant expression of: HER2,
ERalpha, BRCA1, BRCA2, EGFR1, PIK3CA, PTEN, TP53, RB as well as other
oncogenes and tumor suppressor genes. In some breast cancer cases,
mutations at certain components of this pathway (e.g., PIK3CA) are
associated with a better prognosis than breast cancers lacking these
mutations. The expression of this pathway and upstream HER2 has been
associated with breast cancer initiating cells (CICs) and in some cases
resistance to treatment. The anti-diabetes drug metformin can suppress
the growth of breast CICs and herceptin-resistant HER2+ cells. This
review will discuss the importance of the
EGFR/PI3K/PTEN/Akt/mTORC1/GSK-3 pathway primarily in breast cancer but
will also include relevant examples from other cancer types. The
targeting of this pathway will be discussed as well as clinical trials
with novel small molecule inhibitors. The targeting of the hormone
receptor, HER2 and EGFR1 in breast cancer will be reviewed in
association with suppression of the EGFR/PI3K/PTEN/Akt/mTORC1/GSK-3
pathway.USAMRMC {[}BC022276]; Intramural RECDA Award; Italian Association for
Cancer Research (AIRC); MIUR-PRIN; Italian MIUR-FIRB Accordi di
Programma; Italian ``Ministero dell'Istruzione, dell'Universita e della
Ricerca (Ministry for Education, Universities and Research) - FIRB-MERIT
{[}RBNE08YYBM]; Italian Ministry of Economy and Finance; Italian
Ministry of Health, Ricerca Finalizzata Stemness; MIUR FIRB
{[}RBAP11ZJFA\_001]; CRO; Italian Association for Cancer Research,
(AIRC) (RM PI); Italian Association for Cancer Research, (AIRC)
{[}MCO10016]; Italian Ministry of Health; Regione Friuli Venezia-Giuli
Reinterpretation of LHC Results for New Physics: Status and recommendations after Run 2
We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpretation Forum. We detail current experimental offerings in direct searches for new particles, measurements, technical implementations and Open Data, and provide a set of recommendations for further improving the presentation of LHC results in order to better enable reinterpretation in the future. We also provide a brief description of existing software reinterpretation frameworks and recent global analyses of new physics that make use of the current data
Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an
Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis
The trans-ancestral genomic architecture of glycemic traits
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe
Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks
A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV
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