Deep Neural Networks for Semiparametric Frailty Models via H-likelihood

For prediction of clustered time-to-event data, we propose a new deep neural network based gamma frailty model (DNN-FM). An advantage of the proposed model is that the joint maximization of the new h-likelihood provides maximum likelihood estimators for fixed parameters and best unbiased predictors for random frailties. Thus, the proposed DNN-FM is trained by using a negative profiled h-likelihood as a loss function, constructed by profiling out the non-parametric baseline hazard. Experimental studies show that the proposed method enhances the prediction performance of the existing methods. A real data analysis shows that the inclusion of subject-specific frailties helps to improve prediction of the DNN based Cox model (DNN-Cox)

frailtyHL: A Package for Fitting Frailty Models with H-likelihood

We present the frailtyHL package for fitting semi-parametric frailty models using h likelihood. This package allows lognormal or gamma frailties for random-effect distribution, and it fits shared or multilevel frailty models for correlated survival data. Functions are provided to format and summarize the frailtyHL results. The estimates of fixed effects and frailty parameters and their standard errors are calculated. We illustrate the use of our package with three well known data sets and compare our results with various alternative R-procedures

Subject-specific Deep Neural Networks for Count Data with High-cardinality Categorical Features

There is a growing interest in subject-specific predictions using deep neural networks (DNNs) because real-world data often exhibit correlations, which has been typically overlooked in traditional DNN frameworks. In this paper, we propose a novel hierarchical likelihood learning framework for introducing gamma random effects into the Poisson DNN, so as to improve the prediction performance by capturing both nonlinear effects of input variables and subject-specific cluster effects. The proposed method simultaneously yields maximum likelihood estimators for fixed parameters and best unbiased predictors for random effects by optimizing a single objective function. This approach enables a fast end-to-end algorithm for handling clustered count data, which often involve high-cardinality categorical features. Furthermore, state-of-the-art network architectures can be easily implemented into the proposed h-likelihood framework. As an example, we introduce multi-head attention layer and a sparsemax function, which allows feature selection in high-dimensional settings. To enhance practical performance and learning efficiency, we present an adjustment procedure for prediction of random parameters and a method-of-moments estimator for pretraining of variance component. Various experiential studies and real data analyses confirm the advantages of our proposed methods

Doxorubicin-incorporated polymeric micelles composed of dextran-b-poly(DL-lactide-co-glycolide) copolymer

Young-Il Jeong1,*, Do Hyung Kim1,2,*, Chung-Wook Chung1, Jin-Ju Yoo1, Kyung Ha Choi1, Cy Hyun Kim1,2, Seung Hee Ha1, Dae Hwan Kang1,2 1National Research and Development Center for Hepatobiliary Cancer, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea, Research Institute for Convergence of Biomedical Science and Technology, 2School of Medicine, Pusan National University, Yangsan, Republic of Korea*These authors contributed equally to this work.Background: Polymeric micelles using amphiphilic macromolecules are promising vehicles for antitumor targeting. In this study, we prepared anticancer agent-incorporated polymeric micelles using novel block copolymer.Methods: We synthesized a block copolymer composed of dextran and poly (DL-lactide-co-glycolide) (DexbLG) for antitumor drug delivery. Doxorubicin was selected as the anticancer drug, and was incorporated into polymeric micelles by dialysis. Polymeric micelles were observed by transmission electron microscopy to be spherical and smaller than 100 nm, with a narrow size distribution. The particle size of doxorubicin-incorporated polymeric micelles increased with increasing drug content. Higher initial drug feeding also increased the drug content. Results: During the drug-release study, an initial burst release of doxorubicin was observed for 10 hours, and doxorubicin was continuously released over 4 days. To investigate the in vitro anticancer effects of the polymeric micelles, doxorubicin-resistant HuCC-T1 cells were treated with a very high concentration of doxorubicin. In an antiproliferation study, the polymeric micelles showed higher cytotoxicity to doxorubicin-resistant HuCC-T1 cells than free doxorubicin, indicating that the polymeric micelles were effectively engulfed by tumor cells, while free doxorubicin hardly penetrated the tumor cell membrane. On confocal laser scanning microscopy, free doxorubicin expressed very weak fluorescence intensity, while the polymeric micelles expressed strong red fluorescence. Furthermore, in flow cytometric analysis, fluorescence intensity of polymeric micelles was almost twice as high than with free doxorubicin.Conclusion: DexbLG polymeric micelles incorporating doxorubicin are promising vehicles for antitumor drug targeting.Keywords: dextran, polymeric micelle, block copolymer, poly(DL-lactide-co-glycolide

Effect of 5-aminolevulinic acid-based photodynamic therapy via reactive oxygen species in human cholangiocarcinoma cells

Cancer cells have been reported to exhibit an enhanced capacity for protoporphyrin IX (PpIX) synthesis facilitated by the administration of 5-aminolevulinic acid (ALA). We investigated the effect of ALA-based photodynamic therapy (PDT) on human cholangiocarcinoma cells (HuCC-T1). Since protoporphyrin IX (PpIX), a metabolite of ALA, can produce reactive oxygen species (ROS) under irradiation and then induce phototoxicity, ALA-based PDT is a promising candidate for the treatment of cholangiocarcinoma. When various concentrations of ALA (0.05–2 mM) were used to treat HuCC-T1 cells for 6 or 24 hours, the intracellular PpIX level increased according to the ALA concentration and treatment time. Furthermore, an increased amount of PpIX in HuCC-T1 cells induced increased production of ROS by irradiation, resulting in increased phototoxicity

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT