On Fluorophore Imaging by Diffusion Equation Model:Decompositions and Optimizations

Fluorescence imaging is a target-specific molecular imaging technology using absorption coefficient of fluorophore.For this imaging model governed by an inverse problem for the coupled diffusion system,which describes the interaction of the excitation field from several boundary sources and the corresponding emission field,we reformulate it as an optimization problem.For solving this non-quadratic optimizing problem,we propose a decomposition scheme,which extracts the horizontal information of the target from the boundary measurement data directly.The realizability of this hybrid imaging scheme is rigorously proved mathematically for cubic and ellipsoid targets,by constructing an indicator function for the horizontal location of the target explicitly.Then based on this horizonal location as a good initial guess for the iteration process,the cost functional is optimized efficiently using the trust domain scheme.Numerical implementations are provided to show the validity of the proposed scheme.     

Regression Analysis for the Additive Hazards Model with General Biased Survival Data

Acta Mathematicae Applicatae Sinica, English Series - In survival analysis, data are frequently collected by some complex sampling schemes, e.g., length biased sampling, case-cohort sampling and so...     

A Novel Genetic Algorithm for Global Optimization

This paper presents a novel genetic algorithm for globally solving un-constraint optimization problem.In this algorithm,a new real coded crossover operator is proposed firstly.Furthermore,for improving the convergence speed and the searching ability of our algorithm,the good point set theory rather than random selection is used to generate the initial population,and the chaotic search operator is adopted in the best solution of the current iteration.The experimental results tested on numerical benchmark functions show that this algorithm has excellent solution quality and convergence characteristics,and performs better than some algorithms.     

Description of stability for linear time-invariant systems based on the first curvature

This paper focuses on using the first curvature κ(t) of trajectory to describe the stability of linear time-invariant system. We extend the results for two and three-dimensional systems (Wang, Sun, Song et al, arXiv:1808.00290) to n-dimensional systems. We prove that for a system $\text{◂=▸}\dot{r}(t)=\text{◂⋅▸}Ar(t)$, (a) if there exists a measurable set whose Lebesgue measure is greater than zero, such that $\text{◂≠▸}\underset{t\to +\infty }{\lim }\kappa (t)\ne 0$ or $\underset{t\to +\infty }{\lim }\kappa (t)$ does not exist for any initial value in this set, then the zero solution of the system is stable; (b) if the matrix A is invertible, and there exists a measurable set whose Lebesgue measure is greater than zero, such that $\text{◂=▸}\underset{t\to +\infty }{\lim }\kappa (t)=+\infty$ for any initial value in this set, then the zero solution of the system is asymptotically stable.     

Low Mach limit to one-dimensional nonisentropic planar compressible magnetohydrodynamic equations

This paper is concerned with a one-dimensional nonisentropic compressible planar magnetohydrodynamic flow with general initial data, whose behaviors at far fields x→±∞ are different. The low Mach limit for the system is rigorously justified. The limit relies on the uniform estimates including weighted time derivatives and an extended convergence lemma.     

Dynamical analysis of age-structured pertussis model with covert infection

An age-structured pertussis model with covert infection is proposed to understand the effect of covert infection on the recurrence of pertussis. It is found that vaccination only for young children does not have a decisive effect on whooping cough control. It is shown that although the vaccine coverage rate is relatively high, the model has a backward bifurcation for a larger covert infection rate. In addition, sufficient conditions for the disease-free steady state to be globally asymptotically stable are obtained.     

Preparing molecularly imprinted nanoparticles of saponins via cooperative imprinting strategy

Saponin is an important class of natural products with various pharmacological activities. The selective separation of saponins is an essential step before further analysis. Molecular imprinting has been an effective strategy for preparing antibody mimics. However, a facile and efficient imprinting strategy for saponins is still lacking owing to their amphiphilic nature. Herein, we have prepared the saponins imprinted nanoparticles via cooperative imprinting strategy. This new strategy relies on the combination of various non‐covalent interactions (hydrophobic and hydrogen bonding) and covalent boronate affinity interactions. The obtained imprinted nanoparticles could rebind specific saponins from complex matrices with good selectivity, superb tolerance to interference, and fast binding equilibrium. This method was verified to be versatile and facile. Thus, this strategy could greatly facilitate the preparation of imprinted nanoparticles for the specific recognition of saponins.     

Enzymatic Extraction of Bioactive and Self‐Assembling Wool Keratin for Biomedical Applications

Keratin is widely recognized as a high‐quality renewable protein resource for biomedical applications. Despite their extensive existence, keratin resources such as feathers, wool, and hair exhibit high stability and mechanical properties because of their high disulfide bond content. Consequently, keratin extraction is challenging and its application is greatly hindered. In this work, a biological extraction strategy is proposed for the preparation of bioactive keratin and the fabrication of self‐assembled keratin hydrogels (KHs). Based on moderate and controlled hydrolysis by keratinase, keratin with a high molecular weight of approximately 45 and 28 kDa that retain its intrinsic bioactivities is obtained. The keratin products show excellent ability to promote cell growth and migration and are conferred with significant antioxidant ability because of their intrinsically high cysteine content. In addition, without the presence of any cross‐linking agent, the extracted keratin can self‐assemble into injectable hydrogels. The KHs exhibit a porous network structure and 3D culture ability, showing potential in promoting wound healing. This enzyme‐driven keratin extraction strategy opens up a new approach for the preparation of keratin that can self‐assemble into injectable hydrogels for biomedical engineering.     

Affibody‐Conjugated RALA Polymers Delivering Oligomeric 5‐Fluorodeoxyuridine for Targeted Therapy of HER2 Overexpressing Gastric Cancer

Affibody‐conjugated RALA (affi‐RA) are designed for delivering oligomeric 5‐fluorodeoxyuridine (FUdR, metabolite of 5‐FU) strand to raise the selectivity of 5‐fluorouracil (5‐FU), decrease its toxicity and improve its suboptimal therapeutic efficacy. The nanodrugs, FUdR@affi‐RA, are spontaneously assembled by electrostatic interaction between positively charged affi‐RA and negatively charged FUdR₁₅‐strands (15 consecutive FUdR). FUdR@affi‐RA exhibits excellent stability under simulated physiological conditions. Compared with free FUdR, FUdR@affi‐RA shows excellent targeting and higher cytotoxicity in human epidermal growth factor receptor 2 (HER2) overexpressing gastric cancer N87 cells. Moreover, the anticancer mechanism studies reveal that FUdR@affi‐RA enhances the expression and activity of apoptosis‐associated proteins in the Bcl‐2/Bax‐caspase 8,9‐caspase 3 apoptotic pathway induced by FUdR. This study indicates that the fusion vector, affi‐RA, presents a promising delivery system platform for nucleoside analogue drugs and provides a new strategy for the development of therapeutics of cancer treatment.