Hyaluronic acid-coated,prodrug-based nanostructured lipid carriers for enhanced pancreatic cancer therapy

Abstract

Context: Gemcitabine (GEM) and Baicalein (BCL) are reported to have anti-tumor effects including pancreatic cancer. Hyaluronic acid (HA) can bind to over-expressed receptors in various kinds of cancer cells.

Objective: The aim of this study is to develop prodrugs containing HA, BCL and GEM, and construct nanomedicine incorporate GEM and BCL in the core and HA on the surface. This system could target the cancer cells and co-deliver the drugs.

Methods: GEM-stearic acid lipid prodrug (GEM-SA) and hyaluronic acid-amino acid-baicalein prodrug (HA-AA-BCL) were synthesized. Then, GEM and BCL prodrug-based targeted nanostructured lipid carriers (HA-GEM-BCL NLCs) were prepared by the nanoprecipitation technique. The in vitro cytotoxicity studies of the NLCs were evaluated on AsPC1 pancreatic cancer cell line. In vivo anti-tumor effects were observed on the murine-bearing pancreatic cancer model.

Results: HA-GEM-BCL NLCs were effective in entering pancreatic cancer cells over-expressing HA receptors, and showed cytotoxicity of tumor cells in vitro. In vivo study revealed significant tumor growth inhibition ability of HA-GEM-BCL NLCs in murine pancreatic cancer model.

Conclusion: It could be concluded that HA-GEM-BCL NLCs could be featured as promising co-delivery, tumor-targeted nanomedicine for the treatment of cancers.     

Analysis of zonal shrinkage in alloy steels

Abstract

Thermal behaviour of the solidifying steel structure is important for understanding of the defects during ingot solidification. During solidification and cooling, most metals shrink. As a consequence in upper part of solid ingot, pores and pipes of typical shapes and size are formed. Forming of pipes is closely related to the casting and solidification processing parameters. In the present paper the influence of liquid temperature, chemical composition and temperature gradient on the shrinkage intensity are investigated. The ratio of the pipe depth to total ingot height as a criterion of the pipe size is used. The values of the temperature gradients on the base of the numerical model solidification are obtained. The experimental measurements of temperature change have been carried out on laboratory steel ingot. The results by numerical model are compared with the experimental ones and showed a good agreement.     

Anti prostate cancer using PEGylated bombesin containing,cabazitaxel loading nano-sized drug delivery system

Context: Prostate cancer (PCa) is the second most-frequently diagnosed cancer in men. Cabazitaxel was approved for the treatment of patients with hormone-refractory metastatic prostate cancer previously treated with a docetaxel-containing regimen.

Objective: In this study, bombesin (BN), a ligand reported to specifically target GRP overexpressing prostate tumor, was applied for the construction of lipid-polymer hybrid nanoparticles (LPNs), and used for the targeted delivery of cabazitaxel (CAB) to prostate cancer.

Methods: BN-polyethylene glycol-1,2-Distearoyl-sn-glycero-3-phosphoethanolamine (BN-PEG-DSPE) was synthesized. CAB loaded, BN-PEG-DSPE contained LPNs (BN-CAB-LPNs) were prepared. Their particle size, zeta potential and drug encapsulation efficiency (EE) were evaluated. In vitro cytotoxicity study of BN-CAB-LPNs was tested in LNCaP human prostatic cancer cell line (LNCaP cells). In vivo anti-tumor efficacy of the carriers was evaluated on mice bearing prostate cancer model.

Results: The optimum BN-CAB-LPNs formulations had a particle size of 184.9?nm and a 26.5?mV positive surface charge. The growth of LNCaP cells in vitro was obviously inhibited. BN-CAB-LPNs also displayed better anti-tumor activity than the other formulations in vivo.

Conclusion: The results demonstrated that BN-CAB-LPNs can sufficiently deliver CAB to the cancer cells and enhance the anti-tumor capacity. Thus, BN-CAB-LPNs can be proved to be a superior nanomedicine which can achieve better therapeutic efficacy of prostate tumor.     

One- and two-photon lasers with injected signal in a high-Q fabry-Pérot cavity

Abstract

Explicit models are derived for good cavity one- and two-photon lasers with an injected signal in a Fabry-Pérot cavity. The steady solutions and their stability properties are obtained analytically and compared with the corresponding ring cavity model ones. Only quantitative differences between both types of cavities are found. In particular we show that (i) the Fabry-Pérot cavity reduces significantly the domain of self-pulsing with respect to the ring cavity, and for the two-photon laser case (ii) larger output can be extracted from a Fabry-Pérot cavity than from a ring cavity under certain conditions, something impossible in free-running lasers. We conclude that ring cavity models are sensible models for describing qualitatively Fabry-Pérot experimental configurations.     

Simulating diffraction limiting in a pinhole camera

Abstract

Images synthesized by the simulation of light transport are typically generated with the premiss of rays passing through a theoretical or ideal pinhole, the implication being that an infinitely small hole will produce a perfectly sharp image. However, this is not the case. Ray and particle based models of light transport cannot reproduce the effect of diffraction limiting found of small aperture systems.

Here we consider a more appropriate wave based model. While computationally expensive, and practical for only very small apertures, it is capable of reproducing the results of a real pinhole camera. In simulating such a system, we observe that superposition of waves from multiple photons is unlikely to occur in real systems, and that Nyquist theory can be used to explain diffraction limiting as a sampling artefact.     

A review of methods for solubility determination in biopharmaceutical drug characterization

Abstract

The significance of thermodynamic solubility in biopharmaceutical compound or drug characterization as well as the importance of having methods that accurately establish it have been extensively addressed. Nonetheless, its precise determination continues to remain a challenging task to accomplish. Even more so when the number of compounds to evaluate is high and the available amount of each compound is low, both of which are inevitable for the compound characterization during the drug development process. Except for the shake-flask method which is still considered as the ‘gold standard’ in obtaining thermodynamic data, it is currently difficult to say that another satisfactory model which is routinely used to determine thermodynamic solubility is being applied. Therefore, this review summarizes the various experimental approaches which are based on the classical shake flask method but have yet attempted to speed up the experimental process of obtaining such data more conveniently. The most important experimental features of these approaches are provided to the reader. Some advantages and disadvantages associated with each approach are also highlighted, consequently offering a resource to those looking for the most appropriate of the approaches that have already fared well at determining the biopharmaceutically relevant drug solubility.     

Production and characterization of carbon-based adsorbents from waste lignocellulosic biomass: their effectiveness in heavy metal removal

Abstract

In this study, hazelnut shell and walnut shell which are the agricultural wastes existent abundantly in many countries were pyrolyzed at different temperatures in the temperature range of 400–700?°C in order to optimize the physicochemical properties of biochars. The biochars with large surface area were used to removal of lead (Pb²⁺) ions, one of the most important heavy metal pollutant, from aqueous solutions. The characterization of raw biomass and also biochars produced by pyrolysis were performed using FT-IR, BET, SEM, partial and elemental analysis techniques. In order to determine the adsorption characteristics of both biochars, batch adsorption experiments were carried out under different experimental conditions. The optimum conditions were determined by investigating the effect of adsorption parameters (initial heavy metal concentration, temperature, adsorbent amount, pH, contact time and mixing speed) for efficient removal of Pb²⁺ ions from aqueous solution. The experimental results were investigated in terms of Langmuir, Freundlich and Temkin isotherm models. Together with the calculated thermodynamic parameters, the adsorption mechanism was tried to be explained. In order to determine the kinetic model of the adsorption process, the experimental data were applied to pseudo first-order, pseudo second-order and intra-particle diffusion model, and the model constants were investigated.     

Bayesian State Space Modeling of Physical Processes in Industrial Hygiene

Abstract

Exposure assessment models are deterministic models derived from physical–chemical laws. In real workplace settings, chemical concentration measurements can be noisy and indirectly measured. In addition, inference on important parameters such as generation and ventilation rates are usually of interest since they are difficult to obtain. In this article, we outline a flexible Bayesian framework for parameter inference and exposure prediction. In particular, we devise Bayesian state space models by discretizing the differential equation models and incorporating information from observed measurements and expert prior knowledge. At each time point, a new measurement is available that contains some noise, so using the physical model and the available measurements, we try to obtain a more accurate state estimate, which can be called filtering. We consider Monte Carlo sampling methods for parameter estimation and inference under nonlinear and non-Gaussian assumptions. The performance of the different methods is studied on computer-simulated and controlled laboratory-generated data. We consider some commonly used exposure models representing different physical hypotheses. Supplementary materials for this article are available online.     

Multifunctional nanoassemblies of block copolymers for future cancer therapy

Abstract

Nanoassemblies from amphiphilic block copolymers are promising nanomedicine platforms for cancer diagnosis and therapy due to their relatively small size, high loading capacity of drugs, controlled drug release, in vivo stability and prolonged blood circulation. Recent clinical trials with self-assembled polymeric micelles incorporating anticancer drugs have shown improved antitumor activity and decreased side effects encouraging the further development of nanoassemblies for drug delivery. This review summarizes recent approaches considering stimuli-responsive, multifunctionality and more advanced architectures, such as vesicles or worm-like micelles, for tumor-specific drug and gene delivery.     

Ultrasonic Beam Models for Angle Beam Surface Wave Transducers

ABSTRACT

Explicit three-dimensional (3D) point source and multi-Gaussian beam models are obtained for the Rayleigh waves generated by a surface wave angle beam transducer using an angular plane wave spectrum approach. Simulations show that the multi-Gaussian surface wave beam model agrees well with the point source model while being computationally more efficient. The theoretical predictions obtained with the models are also compared to the experimental measurement results where good agreement with the models is found for both on-axis and off-axis field comparisons.     

Critical review of mechanism of superplastic deformation in fine grained metallic materials

Abstract

Superplastic deformation is arguably the most dramatic and direct illustration of the influence of grain boundaries on the mechanical properties of fine grained metals. Stable tensile elongations in excess of 1000%can be attained under suitable conditions, and microstructural observations show that most of this strain is a direct result of grain boundary sliding, with only transient accommodation strains taking place within the grains. The aim of this paper is to provide a critical review of some of the mechanisms that have been proposed to explain this behaviour. The attributes of superplasticity with which models must be consistent are first summarised, and superplasticity is compared with diffusion creep, this being an obvious starting point for understanding the process. Various models from the literature are then described and compared critically with the experimental evidence and the theory of grain boundary structure. Models based on the climb of dislocations from the head of a pileup are shown to have serious shortcomings on both theoretical and experimental grounds. A model developed by the author based on the basic geometrical theory of grain boundary structure is described, and is shown to lead quite naturally to explanations for many of the attributes of superplastic deformation. Finally, the paper identifies areas in which further progress is required.     

Spatial Signal Detection Using Continuous Shrinkage Priors

Abstract

Motivated by the problem of detecting changes in two-dimensional X-ray diffraction data, we propose a Bayesian spatial model for sparse signal detection in image data. Our model places considerable mass near zero and has heavy tails to reflect the prior belief that the image signal is zero for most pixels and large for an important subset. We show that the spatial prior places mass on nearby locations simultaneously being zero, and also allows for nearby locations to simultaneously be large signals. The form of the prior also facilitates efficient computing for large images. We conduct a simulation study to evaluate the properties of the proposed prior and show that it outperforms other spatial models. We apply our method in the analysis of X-ray diffraction data from a two-dimensional area detector to detect changes in the pattern when the material is exposed to an electric field.     

Simple model for austenite grain growth in microalloyed steels

Abstract

Previous models for grain growth are usually based on Beck's formula, which are inadequate for quantitative prediction of austenite grain growth during reheating of as cast microstructures in microalloyed steels. The applications of these empirical grain growth models are limited to some particular categories of steels, such as Nb, Nb–Ti and Ti–V microalloyed steels, etc. In this study, a metallurgically based model has been developed to predict the austenite grain growth kinetics in microalloyed steels. This model accounts for the pinning force of second phase particles on grain boundary migration, in which the mean particle size with time and temperature is calculated on the basis of the Lifshitz–Slyozov–Wagner (LSW) particle coarsening theory. The volume fraction of precipitates is obtained according to the thermodynamic model. The reliability of the model is validated by the agreement between theoretical predictions and experimental measurements in the literature.     

Simplifying biochemical models with intermediate species

Mathematical models are increasingly being used to understand complex biochemical systems, to analyse experimental data and make predictions about unobserved quantities. However, we rarely know how robust our conclusions are with respect to the choice and uncertainties of the model. Using algebraic techniques, we study systematically the effects of intermediate, or transient, species in biochemical systems and provide a simple, yet rigorous mathematical classification of all models obtained from a core model by including intermediates. Main examples include enzymatic and post-translational modification systems, where intermediates often are considered insignificant and neglected in a model, or they are not included because we are unaware of their existence. All possible models obtained from the core model are classified into a finite number of classes. Each class is defined by a mathematically simple canonical model that characterizes crucial dynamical properties, such as mono- and multistationarity and stability of steady states, of all models in the class. We show that if the core model does not have conservation laws, then the introduction of intermediates does not change the steady-state concentrations of the species in the core model, after suitable matching of parameters. Importantly, our results provide guidelines to the modeller in choosing between models and in distinguishing their properties. Further, our work provides a formal way of comparing models that share a common skeleton.     

Sonoluminescence: How bubbles glow

Abstract

We review recent attempts to elucidate the phenomenon of sonoluminescence in terms of fundamental principles. We focus mainly on the processes which generate the light, but other relevant facts, such as the bubble dynamics, must also be considered for the understanding of the physics involved. Our emphasis is on single bubble sonoluminescence which in recent years has received much attention, but we also look at some of the excellent work on multiple bubble sonoluminescence and its spectral characteristics for clues. The weakly ionized gas models were recently studied most thoroughly and are remarkably successful when combined with a hydrodynamic bubble model, in terms of reproducing observed spectral shapes, intensities, optical pulse widths and the dependencies of these observables on the experimental parameters. Other radiation models, such as proton tunnelling radiation and the confined electron model, were not combined with hydrodynamic models and/or have freely adjustable parameters so that their relevance to sonoluminescence studies is at present less critically tested.     

Quantifying the metallurgical response of a nuclear steel to welding thermal cycles

Solid-state phase transformations can drastically influence the evolution of stress in welds due to the strains associated with the transformations and related changes in mechanical properties. As such, finite-element predictions of welding residual stresses need reliable materials data including, where applicable, information on phase transformation kinetics and phase- and temperature-dependent material properties. Owing to a scarcity of such data, many authors have used uncalibrated empirical modelling approaches for the prediction of welding residual stresses. This paper addresses this critical shortage for an important nuclear pressure vessel (SA508) steel. Austenite formation, grain growth and decomposition data are presented and subsequently used to calibrate transformation models. These models are shown to accurately predict microstructure and residual stresses for experimental test cases.

This paper is part of a Themed Issue on Measurement, modelling and mitigation of residual stress.     

Validity of constitutive equations used for calculation of stresses in cooling castings

Abstract

The fundamentals of the constitutive equations used for modelling the mechanical behaviour of metallic materials over wide temperature ranges are briefly reviewed. Examples of stress-calculation problems in cooling castings are given. Four constitutive relationships used for practical calculation of the stresses are analysed. An experimental assessment of their validity, based on a comparison of stress values predicted by the models with those obtained for ring-shaped, aluminium alloy castings with metallic cores, as well as with some published data concerning beam-shaped, low-carbon steel castings, is presented. It is concluded that the essential simplifications assumed in deriving the models lead to significant disagreements with experimental results in most of the investigated cases.

MST/58     

Can we learn more from the data underlying the statistical α-β model with respect to the dynamical behavior of avalanches?

Hazard and risk assessment in avalanche-prone areas involves estimation of runout distances of potential avalanches. Methods for determination of the runout may be divided into two categories: 1) methods based on statistical approaches such as the well known α-β model or 2) methods based on numerical avalanche models such as the PCM-model or VS-type models (just to name the more traditional ones). Methods in the second group have the advantage that besides the runout distance, velocity and impact pressure distributions along the avalanche track can also be obtained, this being a requisite for meaningful risk assessments. However, the predictive power of dynamical models depends on the use of appropriate rheological models and their parameters.In the statistical α-β model, the maximum runout distance is solely a function of topography. The runout distance equations were found by regression analysis, correlating the longest registered runout distance of several hundred avalanche paths with a selection of topographic parameters.In this paper, we re-evaluate Norwegian and Austrian avalanche data, which served as basis for the α-β model in the respective countries, and additional avalanche data with respect to dynamical measures. As most of those avalanche data originate more or less from extreme events (i.e. avalanches with return periods of the order of 100 years), the dynamical measures may give hints about an appropriate rheology for dynamical models suitable for extreme avalanche events.The analysis raises reasonable doubt whether the classical ansatz for the retarding acceleration of snow avalanches with additive terms involving Coulomb-friction and a velocity-squared dependency, which is used in many avalanche models, is adequate for a physically-based model. Back-calculations of runout distances using a simple block model show a discrepancy between commonly proposed parameter values (and of the underlying rheological models) and the observations.     

Population trapping with quantized fields in two-channel models of atomic excitation

Abstract

In this paper, we study several models of two-channel atomic excitation involving quantized fields and search for field states that result in the trapping of the atomic population in a single bare state. This trapping is a result of quantum interference between the two channels. We study the following models: a two-level atom resonantly interacting with two quantized field modes, a two-level atom with competing one and three photon transitions, and a Raman coupled model containing both Stokes and anti-Stokes fields. We find a great variety of trapping states of the field, some of the states being highly non-classical. The effects of dissipation on the stability of the trapping states are discussed and a method for generating some of the states is presented.     

Testing models for superplastic bulge forming of domes

Abstract

The predictions of a new model for the superplastic bulge forming of domes developed by the authors, and of two earlier models, are examined in a study of the variation of dome height with time, the thickness distribution along the dome profile, and the factors influencing the thickness variation. The predictions of the models are compared with experimental measurements made on two aluminium alloys, AA 7475 and Supral 220, and an aluminium bronze, bulged under constant pressure conditions. The recent model shows improved agreement with experiment compared with the two earlier models. It has been shown that the strain rate sensitivity parameter m plays a large part in determining the thickness distribution, while the height of a dome is also important.

MST /1145