Polyethylenimine‐Based Nanogels for Biomedical Applications

Nanogels (NGs) are 3‐dimensional (3D) networks composed of hydrophilic or amphiphilic polymer chains, allowing for effective and homogeneous encapsulation of drugs, genes, or imaging agents for biomedical applications. Polyethylenimine (PEI), possessing abundant positively charged amine groups, is an ideal platform for the development of NGs. A variety of effective PEI‐based NGs have been designed and much effort has been devoted to study the relationship between the structure and function of the NGs. In particular, PEI‐based NGs can be prepared either using PEI as the major NG component or using PEI as a crosslinker. This review reports the recent progresses in the design of PEI‐based NGs for gene and drug delivery and for bioimaging applications with a target focus to tackle the diagnosis and therapy of cancer.     

Importance sampling for non-Markovian tandem queues using subsolutions

Queueing Systems - In this paper, we use importance sampling simulation to estimate the probability that the number of customers in a d-node GI|GI|1 tandem queue reaches some high level N in a busy...     

Insight into shear‐induced modification for improving processability of polymers: Effect of shear rate on the evolution of entanglement state

Many experimental results have revealed that the re‐entanglement kinetics of disentangled polymers is much slower than that predicted by tube theory. This retarded recovery of fully entangled state is of practical significance that shear‐induced modification may offer a way to improve processability for a polymer by reducing viscosity. This work tried to figure out the shear‐rate dependence variation of viscosity in the view of evolution of entanglement state through disentanglement and re‐entanglement, aiming to provide fundamental insights into application prospect of shear‐induced modification in preparing “in‐pellet” disentangled polymers prior to final processing. High‐density polyethylene was sheared on a parallel‐plate rotational rheometer with a linearly increased shear rate. Results showed that higher shear rate could induce further disentanglement, resulting in a lower viscosity with a reduction rate up to 93.7%, larger molecular weight between entanglements M_e , and longer re‐entanglement time. Additionally, less entanglement would give a larger lamellar thickness of sheared samples after nonisothermal crystallization. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 598–606     

Data-Adaptive Estimation of Time-Varying Spectral Densities

This article introduces a data-adaptive nonparametric approach for the estimation of time-varying spectral densities from nonstationary time series. Time-varying spectral densities are commonly estimated by local kernel smoothing. The performance of these nonparametric estimators, however, depends crucially on the smoothing bandwidths that need to be specified in both time and frequency direction. As an alternative and extension to traditional bandwidth selection methods, we propose an iterative algorithm for constructing localized smoothing kernels data-adaptively. The main idea, inspired by the concept of propagation-separation, is to determine for a point in the time-frequency plane the largest local vicinity over which smoothing is justified by the data. By shaping the smoothing kernels nonparametrically, our method not only avoids the problem of bandwidth selection in the strict sense but also becomes more flexible. It not only adapts to changing curvature in smoothly varying spectra but also adjusts for structural breaks in the time-varying spectrum. Supplementary materials, including the R package tvspecAdapt containing an implementation of the routine, are available online.     

On partitions classified by smallest missing part

The Ramanujan Journal - In this paper, we study partitions classified by its smallest missing part. Our main theorem is an inequality related to the parity of the smallest missing part of...     

A rapid and sensitive UHPLC–MS/MS method for the determination of celosin A in rat plasma with application to pharmacokinetic study

Celosin A (CA), a natural compound isolated from Celosia argentea L., has been shown significant hepatoprotective effect on AHNP‐induced liver injury. This study described a rapid and sensitive ultra‐high‐pressure liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) assay for determination of CA in rat plasma. Methanol‐mediated precipitation was used for sample pretreatment. Chromatographic separation was achieved on a T3 column with gradient elution using water and acetonitrile as mobile phase. Determination was obtained using an electrospray ionization source in negative selected reaction monitoring mode at the transitions of m/z 793.3 → m/z 661.2 and m/z 955.6 → m/z 793.2 for CA and IS, respectively. The assay was linear over the concentration range 0.25–2500 ng/mL (r > 0.995) with a lowest limit of quantification (LLOQ) of 0.25 ng/mL. The intra‐ and inter‐day precisions (RSD) were 1.65–9.84 and 2.46–13.49%, respectively, while accuracy (RR) ranged from 96.21 to 99.45%, respectively. The recovery ranged from 95.09 to 102.22% and the matrix effect from 98.29 to 100.13%. The analyte was stable under the tested storage conditions. The method has been successfully applied to a preclinical pharmacokinetic study in rats after a single intravenous (2 mg/kg) or oral (50 mg/kg) administration. The oral bioavailability of CA was ~1.94%; in addition, there was no difference between male and female rats. This is the first time of the use of an UHPLC–MS/MS method for determination of CA concentration in rat plasma and for evaluation of its pharmacokinetic behavior.     

[2]Pseudorotaxane-Based Supramolecular Optical Indicator for the Visual Detection of Cellular Cyanide Excretion

Cyanide is extremely hazardous to living organisms and the environment. Owing to its wide range of applications and high toxicity, the development of functional materials for cyanide detection and sensing is highly desirable. Host–guest complexation between bis(p-phenylene)-34-crown-10 H and N-methylacridinium salt G remarkably decreases the detection limit for cyanide anions compared with that of the guest itself. The [2]pseudorotaxane selectively recognizes the cyanide anion with high optical sensitivity as a result of the nucleophilic addition of the cyanide anion at the 9-position of G . The host–guest complexation is further incorporated into supramolecular materials for the visual detection of cyanide anions, especially the detection of cellular cyanide excretion with a detection limit of 0.6 μm . This supramolecular method provides an extremely distinct strategy for the visual detection of cyanide anions.     

Revisiting radiative leptonic B decay

In this paper, we summarize the existing methods of solving the evolution equation of the leading-twist \begin{document}$B$\end{document}-meson LCDA. Then, in the Mellin space, we derive a factorization formula with next-to-leading-logarithmic (NLL) resummation for the form factors \begin{document}$F_{A,V}$\end{document} in the \begin{document}$B \to \gamma \ell\nu$\end{document} decay at leading power in \begin{document}$\Lambda/m_b$\end{document}. Furthermore, we investigate the power suppressed local contributions, factorizable non-local contributions (which are suppressed by \begin{document}$1/E_\gamma$\end{document} and \begin{document}$1/m_b$\end{document}), and soft contributions to the form factors. In the numerical analysis, which employs the two-loop-level hard function and the jet function, we find that both the resummation effect and the power corrections can sizably decrease the form factors. Finally, the integrated branching ratios are also calculated for comparison with future experimental data.     

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.