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We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscle-infiltrating bladder cancer (NMIBC) in this work. A total of 147 patients from Xuzhou Central Hospital were enrolled as the training cohort, and 63 patients from Suqian Affiliated Hospital of Xuzhou Medical University were enrolled as the test cohort. Based on two consecutive phases of patch level prediction and WSI-level predictione, we built a pathomics model, with the initial model developed in the training cohort and subjected to transfer learning, and then the test cohort was validated for generalization. The features extracted from the visualization model were used for model interpretation. After migration learning, the area under the receiver operating characteristic curve for the deep learning-based pathomics model in the test cohort was 0.860 (95% CI 0.752–0.969), with good agreement between the migration training cohort and the test cohort in predicting recurrence, and the predicted values matched well with the observed values, with p values of 0.667766 and 0.140233 for the Hosmer–Lemeshow test, respectively. The good clinical application was observed using a decision curve analysis method. We developed a deep learning-based pathomics model showed promising performance in predicting recurrence within one year in NMIBC patients. Including 10 state prediction NMIBC recurrence group pathology features be visualized, which may be used to facilitate personalized management of NMIBC patients to avoid ineffective or unnecessary treatment for the benefit of patients. [ABSTRACT FROM AUTHOR]

At present, optimization of mechanical properties in quenching and partitioning (Q&P) steels relies primarily on the tailoring of microstructural characteristics by manipulating the alloying elements and the Q&P process. However, adjusting the final microstructure by taking advantage of the inheritance effect derived from the initial microstructure has received less attention. Based on a typical Fe–C–Mn–Si system, the present investigation explores the effect of microstructural inheritance in an ultrahigh strength hot-rolled Q&P steel. The typical hot rolling process is followed by three cooling rates, including quenching, air cooling, and coil cooling, to obtain different initial microstructures of full martensite, bainite–austenite, and ferrite–pearlite, respectively. The same Q&P treatment is then performed to elucidate the inheritance mechanism, and the final Q&P products consist of different fractions of tempered martensite, retained austenite, bainite and fresh martensite. With decreasing cooling rates after hot rolling, the ultimate tensile strengths of the steels after the Q&P treatment are identical at ~ 1.5 GPa, while the total elongations increase gradually from 10.9, 12.7 to 14.5 pct. The highest elongation of the coil-cooled Q&P steel can be attributed to the effect of microstructural inheritance on the Q&P process and retained austenite, leading to larger austenite grain sizes and more equiaxed morphologies. The combination of austenite chemistry and morphology results in the optimal mechanical stability for retained austenite to provide continuous and durable strain hardening. Compared to cold-rolled products, hot-rolled Q&P steel is very attractive to the industry as it can potentially eliminate the cold rolling step and reduce the production cost. Utilizing the microstructural inheritance effect provides a simple and feasible route to control the microstructures and mechanical properties of ultrahigh strength hot-rolled Q&P steel. [ABSTRACT FROM AUTHOR]

The top eigenpairs at the title mean the maximal, the submaximal, or a few of the subsequent eigenpairs of an Hermitizable matrix. Restricting on top ones is to handle with the matrices having large scale, for which only little is known up to now. This is different from some mature algorithms, that are clearly limited only to medium-sized matrix for calculating full spectrum. It is hoped that a combination of this paper with the earlier works, to be seen soon, may provide some effective algorithms for computing the spectrum in practice, especially for matrix mechanics. [ABSTRACT FROM AUTHOR]

The famous TV-Stokes models, which improve the restored images comfortable, have been very successful in image denoising. In this paper, we propose a new TV-Stokes model for image deblurring with a good geometry explanation. In the tangential field smoothing, the data fidelity term is chosen to measure the distance between the solution and the orthogonal projection of the tangential field of the observation image onto the range of the conjugate of the blurry operator, while the total variation of the solution is chosen as the regularization term. In the image reconstruction, we compute the smoothing part of the image from the smoothed tangential field for the first step, and use an anisotropic TV model to obtain the 'texture' part of the deblurred image. The solvability properties for the minimization problems in two steps are established, and fast algorithms are presented. Numerical experiments demonstrate that the new deblurring model can capture the details of images hidden in the blurry and noisy image, and the fast algorithms are efficient and robust. [ABSTRACT FROM AUTHOR]

Given a matrix A, n by n, and two subspaces K and L of dimension m, we consider how to determine a backward perturbation E whose norm is as small as possible, such that k and L are Krylov subspaces of A+ E and its adjoint, respectively. We first focus on determining a perturbation matrix for a given pair of biorthonormal bases, and then take into account how to choose an appropriate biorthonormal pair and express the Krylov residuals as a perturbation of the matrix A. Specifically, the perturbation matrix is globally optimal when A is Hermitian and K= L. The results show that the norm of the perturbation matrix can be assessed by using the norms of the Krylov residuals and those of the biorthonormal bases. Numerical experiments illustrate the efficiency of our strategy. [ABSTRACT FROM AUTHOR]

ABSTRACT Background/Objectives: Free radicals and reactive oxygen species (ROS), which are generated by UV irradiation, may induce an irreversible growth arrest similar to senescence. Tiron, 4,5-dihydroxy-1,3-benzene disulfonic acid, is a widely used antioxidant to rescue ROS-evoked cell death. The aim of the article was to explore the effects of tiron on skin photoaging and associated mechanisms. Methods: The effects of tiron on cell proliferation were determined using 3-(4,5-dimethylthiazol-2-Yl)-2,5-diphenyltetrazolium bromide. Senescent cells were determined by morphology and senescence-associated β-galactosidase activity analysis. Intracellular hydrogen peroxide, superoxide anion and glutathione concentration were analysed by a fluorescent probe. The concomitant changes of protein expression were analysed with Western blot. Results: Human dermal fibroblasts were induced to premature senescence by sub-cytotoxic doses of irradiated UVB. Strong senescence-associated β-galactosidase activity and increased intracellular superoxide anion were observed in human dermal fibroblasts irradiated by UVB. Tiron blocks UVB-induced glutathione depletion and increase of superoxide anion and protects against UVB-induced senescence-like characteristics in human dermal fibroblasts. Compared with normal fibroblasts, UVB-irradiated human dermal fibroblasts showed a higher ratio of active (hypophosphorylated) to inactive (phosphorylated) forms of Rb and p38, upregulation of p53 or p16 and c-Myc and insulin-like growth factor 1 (IGF-1) downregulation. After treatment with tiron, p53, p16 c-Myc and IGF-1 as well as phosphorylation Rb and p38 could partially recover. Conclusion: These results indicate that tiron protects against UVB-induced senescence-like characteristics in human dermal fibroblasts via the inhibition of production of superoxide anion and glutathione depletion, and modulation of related senescence proteins. [ABSTRACT FROM AUTHOR]