tissue of rat adjuvant-induced arthritis

Triptolide has been clinically used to treat patients with rheumatoid arthritis, in which chemokine receptors play an important role in immune and inflammatory responses. To investigate the effect of triptolide on CCR5, we used complete Freund’s adjuvant to produce adjuvant-induced arthritis (AIA) in rats. Our data show that both CCR5 mRNA and protein levels in synovial tissue of rats with AIA are significantly higher than those in normal rats. Triptolide can significantly inhibit rat AIA-induced overexpression of CCR5 at both mRNA and protein levels. These results may contribute to better understanding of the therapeutic effects of triptolide in rheumatoid arthritis. Key words: triptolide, CCR5, adjuvant induced arthritis, rheumatoid arthriti

An improved joint non-negative matrix factorization for identifying surgical treatment timing of neonatal necrotizing enterocolitis

Neonatal necrotizing enterocolitis is a severe neonatal intestinal disease. Timely identification of surgical indications is essential for newborns in order to seek the best time for treatment and improve prognosis. This paper attempts to establish an algorithm model based on multimodal clinical data to determine the features of surgical indications and construct an auxiliary diagnosis model. The proposed algorithm adds hypergraph constraints on the two modal data based on Joint Nonnegative Matrix Factorization (JNMF), aiming to mine the higher-order correlations of the two data features. In addition, the adjacency matrix of the two kinds of data is used as a network regularization constraint to prevent overfitting. Orthogonal and L1-norm regulations were introduced to avoid feature redundancy and perform feature selection, respectively, and confirmed 14 clinical features. Finally, we used three classifiers, random forest, support vector machine, and logistic regression, to perform binary classification of patients requiring surgery. The results show that when the features selected by the proposed algorithm model are classified by random forest, the area under the ROC curve is 0.8, which has high prediction accuracy

Effect of variable particle stiffness on force propagation and mechanical response of a composite granular material

The force propagation and mechanical response are important for understanding the elasticity and deformation of a composite granular packings. In this paper, a 2D composite granular layers composed of particles with variable stiffness is proposed, and the effect of stiffness ratio between component particles on mechanical response is mainly considered. The results show that the decrease of stiffness ratio broadens the linear range of mechanical response and enhances the elasticity of the response in a composite granular system, showing a role similar with the friction in a monodisperse granular packings. Furthermore, a phase diagram for the crossover between a single-peaked and a double-peaked response is proposed, in which the critical stiffness ratio corresponding to the occurrence of the crossover decreases with the magnitude of external loading and increases with the friction. Finally, the microscopic mechanism of the crossover of the response is further discussed based on changes in contact network and force network

A new construction of mutually unbiased maximally entangled bases in ℂq⊗ℂq

This paper is devoted to constructing mutually unbiased maximally entangled bases (MUMEBs) in [Formula: see text], where [Formula: see text] is a prime power. We prove that [Formula: see text] when [Formula: see text] is even, and [Formula: see text] when [Formula: see text] is odd, where [Formula: see text] is the maximal size of the sets of MUMEBs in [Formula: see text]. This highly raises the lower bounds of [Formula: see text] given in D. Xu, Quant. Inf. Process. 18(7) (2019) 213; D. Xu, Quant. Inf. Process. 19(6) (2020) 175. It should de noted that the method used in the paper is completely different from that in D. Xu, Quant. Inf. Process. 18(7) (2019) 213; D. Xu, Quant. Inf. Process. 19(6) (2020) 175. </jats:p

Hybrid Transmittance Fitting for Rendering Transparency on the GPU

In real-time rendering transparency is an important multi-fragment effect to visualize the structure of three-dimensional models. The per-pixel transmittance implicitly describes how the light is attenuated by traveling through several transparent fragments. We present a hybrid approach to fit the transmittance using the Heaviside step function and the trigonometric function. The k fragments with the largest contribution are exactly composited and the remaining ones are accurately compressed in an unified formulation. With a single geometry pass, fragments are sorted into a fixed-size array and overflowing ones are expanded by a truncated Fourier series. Then the transmittance is reconstructed on the fly to modulate the surface color in another geometry pass. Our approach favors high scene complexity but operates in bounded memory without losing noticeable high-frequency detail. We demonstrate that it is able to closely match the image quality at competitive frame rate, comparing to a realtime A-buffer implementation and other approximate transparency techniques. </jats:p