Collagen extract obtained from Nile tilapia (Oreochromis niloticus L.) skin accelerates wound healing in rat model via up regulating VEGF, bFGF, and α-SMA genes expression

Background Collagen is the most abundant structural protein in the mammalian connective tissue and represents approximately 30% of animal protein. The current study evaluated the potential capacity of collagen extract derived from Nile tilapia skin in improving the cutaneous wound healing in rats and investigated the underlying possible mechanisms. A rat model was used, and the experimental design included a control group (CG) and the tilapia collagen treated group (TCG). Full-thickness wounds were conducted on the back of all the rats under general anesthesia, then the tilapia collagen extract was applied topically on the wound area of TCG. Wound areas of the two experimental groups were measured on days 0, 3, 6, 9, 12, and 15 post-wounding. The stages of the wound granulation tissues were detected by histopathologic examination and the expression of vascular endothelial growth factor (VEGF), and transforming growth factor (TGF-ß1) were investigated using immunohistochemistry. Moreover, relative gene expression analysis of transforming growth factor-beta (TGF-ß1), basic fibroblast growth factor (bFGF), and alpha-smooth muscle actin (α-SMA) were quantified by real-time qPCR. Results The histopathological assessment showed noticeable signs of skin healing in TCG compared to CG. Immunohistochemistry results revealed remarkable enhancement in the expression levels of VEGF and TGF-β1 in TCG. Furthermore, TCG exhibited marked upregulation in the VEGF, bFGF, and α-SMA genes expression. These findings suggested that the topical application of Nile tilapia collagen extract can promote the cutaneous wound healing process in rats, which could be attributed to its stimulating effect on recruiting and activating macrophages to produce chemotactic growth factors, fibroblast proliferation, and angiogenesis. Conclusions The collagen extract could, therefore, be a potential biomaterial for cutaneous wound healing therapeutics. Backgroun

Spectral Theory and Numerical Approximation for Singular Fractional Sturm-Liouville eigen-Problems on Unbounded Domain

In this article, we first introduce a singular fractional Sturm-Liouville eigen-problems (SFSLP) on unbounded domain. The associated fractional differential operators in these problems are both Weyl and Caputo type . The properties of spectral data for fractional operators on unbounded domain has been investigated. Moreover, it has been shown that the eigenvalues of the singular problems are real-valued and the corresponding eigenfunctions are orthogonal. The analytical eigensolutions to SFSLP is obtained and defined as generalized Laguerre fractional-polynomials. The optimal approximation of such generalized Laguerre fractional-polynomials in suitably weighted Sobolev spaces involving fractional derivatives has been derived, which is also available for approximated fractional-polynomials growing fast at infinity. The obtained results demonstrate that the error analysis beneficial of fractional spectral methods for fractional differential equations on unbounded domains. As a numerical example, we employ the new fractional-polynomials bases to demonstrate the exponential convergence of the approximation in agreement with the theoretical results.Comment: This paper has been withdrawn by the author due to a crucial sign error in equation

Spline collocation methods for solving second-order intial value problems.

Abstract The aim of this paper is to solve the second order neutral delay differential equations (NDDEs) based on seventh C 3 -spline collocation methods with three parameters c 1 , c 2 , c 3 ∈ (0, 1). It is shown that the proposed methods for second order NDDEs possess a convergence rate of order seven if : Numerical results illustrating the behavior of the methods when faced with some difficult problems are presented and the numerical results are compared to those obtained by other methods

An Effective Method of Systems Requirement Optimization Based on Genetic Algorithms

Requirements engineering is the first step of software development process and it is one of the main concerns of software engineers. System requirements selection is the engineering process to select an optimal set of system requirements for implementation in the next system of the software from many requirements proposed by the customers on condition that budget and customer satisfaction are being balanced. This NP-hard problem is an important issue involving several conflicting objectives that have to be processed by software companies when developing new software systems. Software systems have to perform their function within resource constraints, but they also have to cover the largest number of customer requirements. Additionally, in real life problem, the requirements selection process suffers from complication due to interactions and other constrictions. In this paper, meta-heuristic techniques have been applied along with adapted/modified multi-objective function which has been successfully applied to several real cases of the problem. The system requirements selection problem has been formulated as a multiobjective optimization problem with two objectives that minimizes the total system’s development cost and maximizes customer’s satisfaction totality. Moreover, GA has been adapted to solve real cases of the problem and tested with case studies on two real datasets that have been carried out to demonstrate and prove the effectiveness of the multi-objective proposed approach and the obtained experimental results show that the updated GA can effectively generate high quality solutions and performs better than other pertinent algorithms previously published in the literature under a set of public datasets

Is childhood obesity a result of toxic exposure to cadmium or malathion? An observational pilot Egyptian study

AbstractNowadays, exposures to some environmental chemicals may contribute to obesity in children. The aim of the current work is to assess the association between the environmental pollutants cadmium, malaoxon and malathion dicarboxylic acid (MDCA) and obesity in children. Authors conducted a case-control study on 80 children. We recruited 40 obese children and 40 normal-weight children. For each child, we measured urinary concentrations of cadmium (by ICP), malaoxon (by LC/MS/MS), and MDCA (by LC/MS/MS). Results: Malaoxon concentrations were slightly higher among non-obese group B children (median = 0, IQR 0 to 10.29 mg/g) than in obese group A children (median = 0, IQR = 0 to 2.14). There were no significant differences in creatinine-adjusted MDCA or Cadmium

New Exact Solutions for New Model Nonlinear Partial Differential Equation

In this paper we propose a new form of Padé-II equation, namely, a combined Padé-II and modified Padé-II equation. The mapping method is a promising method to solve nonlinear evaluation equations. Therefore, we apply it, to solve the combined Padé-II and modified Padé-II equation. Exact travelling wave solutions are obtained and expressed in terms of hyperbolic functions, trigonometric functions, rational functions, and elliptic functions