Cutaneous squamous cell cancers (cSCCs) present an under-recognized health issue among non-Hispanic whites, one that is likely to increase as populations age. cSCC risks vary considerably among non-Hispanic whites, and this heterogeneity indicates the need for risk-stratified screening strategies that are guided by patients' personal characteristics and clinical histories. Here we describe cSCCscore, a prediction tool that uses patients' covariates and clinical histories to assign them personal probabilities of developing cSCCs within 3 years after risk assessment. cSCCscore uses a statistical model for the occurrence and timing of a patient's cSCCs, whose parameters we estimated using cohort data from 66,995 patients in the Kaiser Permanente Northern California healthcare system. We found that patients' covariates and histories explained approximately 75% of their interpersonal cSCC risk variation. Using cross-validated performance measures, we also found cSCCscore's predictions to be moderately well calibrated to the patients' observed cSCC incidence. Moreover, cSCCscore discriminated well between patients who subsequently did and did not develop a new primary cSCC within 3 years after risk assignment, with area under the receiver operating characteristic curve of approximately 85%. Thus, cSCCscore can facilitate more informed management of non-Hispanic white patients at cSCC risk. cSCCscore's predictions are available at https://researchapps.github.io/cSCCscore/.

Genome-wide association studies have identified genetic loci associated with cutaneous squamous cell carcinoma (cSCC) risk, but single-nucleotide polymorphism associations with cSCC invasiveness have not been investigated. We examined associations between cSCC invasiveness and 23 reported single-nucleotide polymorphisms among 67,833 non-Hispanic white subjects. Additionally, we performed a genome-wide scan and identified one SNP with significantly different frequencies in 5,724 subjects with at least one invasive tumor and 1,943 subjects with in situ tumors only. We then compared genotype frequencies among the invasive and in situ groups with those of 60,166 control subjects. The genome-wide scan identified that the T allele in single-nucleotide polymorphism rs41269979 in the class II human leukocyte antigen region was more frequent in the invasive than the in situ group (P = 4.93 x 10(-8)). Single-nucleotide polymorphisms in five of the 23 previously associated loci showed odds ratio heterogeneity between the in situ and invasive groups: rs447510 in HLA-DQA1 (P-het = 2.93 x 10(-3)), rs12203592 in IRF4 (P-het = 3.94 x 10(-4)), rs1805007 in MC1R (P-het = 7.71 x 10(-3)), and two SNPs in DEF8 (rs4268748, P-het x 1.09 x 10(-4) and rs8063761, P-het = 1.40 x 10(-4)). These findings may provide new insight into the genetic basis of cSCC invasiveness and may help identify individuals at higher risk for developing clinically aggressive cSCC.

Haze removal (or dehazing) is very important for many applications in computer vision. Because depth information and atmospheric light are usually unknown in practice, haze removal is a challenging problem, especially for single image dehazing. In this paper, we propose a new variational model for removing haze from a single input image. The proposed model combines Koschmieder's law with Retinex assumption that an image is the product of illumination and reflection. We assume that scene depth and surface radiance are spatially piecewise smooth, total variation is thus used for regularization in our model. The proposed model is defined as a constrained optimization problem, which is solved by an alternating minimization scheme and a fast gradient projection algorithm. Theoretical analyses are given for the proposed model and algorithm. Some numerical examples are presented, which have shown that our model has the best visual effect and the highest average PSNR (Peak Signal-to-Noise Ratio) compared to six relevant models in the literature. (C) 2018 Elsevier Ltd. All rights reserved.

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease. NAFLD begins with steatosis and advances to nonalcoholic steatohepatitis (NASH) and cirrhosis. The molecular mechanisms involved in NAFLD progression are not understood. Based on recent studies showing dysregulation of epidermal growth factor receptor (EGFR) in animal models of liver injury, we sought to determine if inhibition of EGFR mitigates liver fibrosis and HSC activation in NAFLD. We utilized the high fat diet (HFD)-induced murine model of liver injury to study the role of EGFR in NAFLD. The lipid accumulation, oxidative stress, hepatic stellate cell (HSC) activation and matrix deposition were examined in the liver tissues. We also evaluated the EGFR signaling pathway, ROS activation and pro-fibrogenic phenotype in oxidized low density lipoproteins (ox-LDL) challenged cultured HSCs. We demonstrate that EGFR was phosphorylated in liver tissues of HFD murine model of NAFLD. Inhibition of EGFR prevented diet -induced lipid accumulation, oxidative stress, and HSC activation and matrix deposition. In cultured HSCs, we show that ox-LDL caused rapid activation of the EGFR signaling pathway and induce the production of reactive oxygen species. EGFR also mediated HSC activation and promoted a pro-fibrogenic phenotype. In conclusion, our data demonstrate that EGFR plays an important role in NAFLD and is an attractive target for NAFLD therapy.

This paper designs two kinds of event-triggered control protocols for distributed optimal coordination of a group of agents with second order dynamics interacting according to given communication graph. First, a centralized event-triggered protocol is developed to accomplish the optimal coordination in the Pareto sense. The parameter is designed by constructing a new Lyapunov function. Second, it is shown that the event-triggered scheme is Zeno-free. Third, a distributed event-triggered protocol is devised by extending the proposed technique. Simulations are provided to demonstrate the effectiveness of the proposed design. (c) 2018 Elsevier B.V. All rights reserved.

In this paper, we consider the following Keller-Segel-Navier-Stokes system {n(t) = Delta n - del. (nS(x,n,c) . del c) - u . del n in Omega x (0, T), c(t) = Delta c - c + n . del c in Omega x (0, T), u(t) = Delta u - (u . del)u + del P + n del Phi, del . u = 0 in Omega x (0, T), subject to the boundary condition del c.v = (del n - nS(x,n, c) . del c).nu = 0, u = 0, and the initial data (n(0)(x), c(0)(x), u(0)(x)), where Omega subset of R-N is a smooth bounded domain with N is an element of {2, 3}, nu denotes the unit outer normal of partial derivative Omega, S is an element of C-2((Omega) over barx [0, infinity)(2))(NxN) and Phi is an element of C1+delta((Omega) over bar) with delta is an element of (0,1). We establish global' classical solutions decaying to the constant steady state ((n) over bar (0), (n) over bar (0), 0) exponentially with (n) over bar (0) := 1/vertical bar Omega vertical bar integral(Omega) n0(x)dx, whenever parallel to n(0)parallel to (L N/2 (Omega)), parallel to del c(0)parallel to)(LN (Omega)) and parallel to u(0)parallel to (LN (Omega)) small enough. (C) 2017 Elsevier Inc. All rights reserved.