THE PREVENTION OF OBESITY-ASSOCIATED COLORECTAL CANCER VIA DIETARY SUPPRESSION OF INFLAMMATION-DRIVEN WNT-SIGNALING

Colorectal cancer (CRC) is the third leading cause of cancer deaths in the United States. A number of population studies have established that modifiable lifestyle factors such as obesity plays an important role in colorectal carcinogenesis. In the United States, more than one-third of adults are obese and obesity prevalence rates have no sign of decrease. Therefore, the development of effective strategies to prevent obesity-induced CRC is a public health priority. This study aimed to investigate whether genetic or dietary strategies can prevent obesity-induced CRC and determine the potential molecular mechanisms underlying the prevention effects of these strategies. We used Apc1638N mice, germline heterozygous mutation in the Apc gene, and Caco-2 cell line to study intestinal tumorigenesis. Hematoxylin and eosin stain and QuickPlex SQ 120, a chemiluminescence assay, were used to measure the inflammatory status. Real-time PCR, Western blot assay, and immunohistochemical analysis were used to further examine the signaling pathway status. We found that loss of Tumor necrosis factor alpha (TNF-α) decreased obesity associated intestinal tumorigenesis by decreasing the inflammation, and manipulating the β-catenin pathway and NF-kB signaling. In addition, IKK, a component of the NF-kB signaling, was involved in the regulation of β-catenin pathway. The administration of Vitamin D (VD), at 5000 IU level, exerted an anti-inflammatory property and led to suppressed intestinal Wnt-signaling and tumorigenesis in obese mice. The molecular function of sulforaphane (SFN) on a high dose of VD supplementation, although displayed on the inhibition of HDAC and the activation of autophagy, needs further investigation. Butyrate can increase the activity of Wnt/β-catenin pathway. Knocking down FFAR2 by siRNA decreased the expression of cleaved caspase 3 and the expression of phospho-GSK3β (Ser9) and active β-catenin in Caco-2 cells, subsequently mitigated the anticancer effect of butyrate

Factors Impacting University Majoring in Vocal Music Students’ Behavioral Intention to Chaoxing Learning Platform In Changsha, Hunan, China

Purpose: The purpose of this study was to determine students’ behavioral intention to Chaoxing learning platform. The study was conducted in public primary university in Changsha, Hunan Province, China, with majoring vocal students who had at least one year of experience using this technology. Research design, data and methodology: This is a quantitative study, which uses survey to collect sample data through a set of questionnaires to explore the factors influencing the Behavioral Intention of using Chaoxing learning platform for vocal music majors in university. The questionnaire is made by online questionnaire of Kingsoft Form with 500 sample size. The content validity method of Item Objective Congruence (IOC) Index was used, resulting all measuring items reserved by three experts. Pilot testing of 30 participants was approved under Cronbach’s Alpha reliability test at a score of 0.7 or over. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) were performed for data analysis, including goodness of model fits, validity, and reliability testing. Results: The results show Perceived Enjoyment, Self-Efficacy, Teacher Support, Perceived Ease, Perceived Usefulness, Perceived Ease of Use and Attitude all support the model. Conclusions: This study has a relevant role in promoting the service of Chaoxing platform and the improvement of related technologies

Scalable iterative data-adaptive RKHS regularization

We present iDARR, a scalable iterative Data-Adaptive RKHS Regularization method, for solving ill-posed linear inverse problems. The method searches for solutions in subspaces where the true solution can be identified, with the data-adaptive RKHS penalizing the spaces of small singular values. At the core of the method is a new generalized Golub-Kahan bidiagonalization procedure that recursively constructs orthonormal bases for a sequence of RKHS-restricted Krylov subspaces. The method is scalable with a complexity of $O(kmn)$ for $m$-by-$n$ matrices with $k$ denoting the iteration numbers. Numerical tests on the Fredholm integral equation and 2D image deblurring show that it outperforms the widely used $L^2$ and $l^2$ norms, producing stable accurate solutions consistently converging when the noise level decays

Fully discrete semi-Lagrangian methods for advection of differential forms

We study the discretization of linear transient transport problems for differential forms on bounded domains. The focus is on unconditionally stable semi-Lagrangian methods that employ finite element approximation on fixed meshes combined with tracking of the flow map. We derive these methods as finite element Galerkin approach to discrete material derivatives and discuss further approximations leading to fully discrete schemes. We establish comprehensive a priori error estimates, in particular a new asymptotic estimate of order $O(h^{r+1}\tau^{-\frac{1}{2}})$ for the L 2-error of semi-Lagrangian schemes with exact L 2-projection. Here, h is the spatial meshwidth, τ denotes the timestep, and r is the (full) polynomial degree of the piecewise polynomial discrete differential forms used as trial functions. Yet, numerical experiments hint that the estimates may still be sub-optimal for spatial discretization with lowest order discrete differential form