Novel, high throughput method to study in vitro protein release from polymer nanospheres

Controlled delivery of therapeutic protein drugs using biodegradable polymer carriers is a desired characteristic that enables effective, application-specific therapy and treatment. Previous studies have focused on protein delivery from polymers using conventional one-sample-at-a- time techniques, which are time-consuming and costly. In addition, many therapeutic proteins are in limited supply and are expensive, so it is desirable to reduce sample size for design and development of delivery devices. We have developed a rapid, high throughput technique based on a highly sensitive fluorescence-based assay to detect and quantify protein released from polyanhydrides while utilizing relatively small amounts of protein (∼40 μg). These studies focused on the release of a model protein, Texas Red conjugated bovine serum albumin, from polyanhydride copolymers based on sebacic acid (SA) and 1,6-bis(p-carboxyphenoxy)hexane (CPH). The protein release profiles were assessed simultaneously to investigate the effect of polymer device geometry (nanospheres vs films), polymer chemistry, and pH of the release medium. The results indicated that the nanosphere geometry, SA-rich chemistries, and neutral pH release medium led to a more rapid release of the protein compared to the film geometry, CPH-rich chemistries, and acidic pH release medium, respectively. This high throughput fluorescence-based method can be readily extended to study release kinetics for other proteins and polymer systems

PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network

We present PyCARL, a PyNN-based common Python programming interface for hardware-software co-simulation of spiking neural network (SNN). Through PyCARL, we make the following two key contributions. First, we provide an interface of PyNN to CARLsim, a computationally-efficient, GPU-accelerated and biophysically-detailed SNN simulator. PyCARL facilitates joint development of machine learning models and code sharing between CARLsim and PyNN users, promoting an integrated and larger neuromorphic community. Second, we integrate cycle-accurate models of state-of-the-art neuromorphic hardware such as TrueNorth, Loihi, and DynapSE in PyCARL, to accurately model hardware latencies that delay spikes between communicating neurons and degrade performance. PyCARL allows users to analyze and optimize the performance difference between software-only simulation and hardware-software co-simulation of their machine learning models. We show that system designers can also use PyCARL to perform design-space exploration early in the product development stage, facilitating faster time-to-deployment of neuromorphic products. We evaluate the memory usage and simulation time of PyCARL using functionality tests, synthetic SNNs, and realistic applications. Our results demonstrate that for large SNNs, PyCARL does not lead to any significant overhead compared to CARLsim. We also use PyCARL to analyze these SNNs for a state-of-the-art neuromorphic hardware and demonstrate a significant performance deviation from software-only simulations. PyCARL allows to evaluate and minimize such differences early during model development.Comment: 10 pages, 25 figures. Accepted for publication at International Joint Conference on Neural Networks (IJCNN) 202

One pion events by atmospheric neutrinos: A three flavor analysis

We study the one-pion events produced via neutral current (NC) and charged current (CC) interactions by the atmospheric neutrinos. We analyze the ratios of these events in the framework of oscillations between three neutrino flavors. The ratios of the CC events induced by $\nu_e$ to that of the NC events and a similar ratio defined with $\nu_\mu$ help us in distinguishing the different regions of the neutrino parameter space.Comment: 14 pages, 4 figures (separate postscript files

Moderate deviation principle for ergodic Markov chain. Lipschitz summands

For ${1/2}<\alpha<1$, we propose the MDP analysis for family $$S^\alpha_n=\frac{1}{n^\alpha}\sum_{i=1}^nH(X_{i-1}), n\ge 1,$$ where $(X_n)_{n\ge 0}$ be a homogeneous ergodic Markov chain, $X_n\in \mathbb{R}^d$, when the spectrum of operator $P_x$ is continuous. The vector-valued function $H$ is not assumed to be bounded but the Lipschitz continuity of $H$ is required. The main helpful tools in our approach are Poisson's equation and Stochastic Exponential; the first enables to replace the original family by $\frac{1}{n^\alpha}M_n$ with a martingale $M_n$ while the second to avoid the direct Laplace transform analysis

Amphiphilic polyanhydride nanoparticles stabilize bacillus anthracis protective antigen

Advancements toward an improved vaccine against Bacillus anthracis, the causative agent of anthrax, have focused on formulations composed of the protective antigen (PA) adsorbed to aluminum hydroxide. However, due to the labile nature of PA, antigen stability is a primary concern for vaccine development. Thus, there is a need for a delivery system capable of preserving the immunogenicity of PA through all the steps of vaccine fabrication, storage, and administration. In this work, we demonstrate that biodegradable amphiphilic polyanhydride nanoparticles, which have previously been shown to provide controlled antigen delivery, antigen stability, immune modulation, and protection in a single dose against a pathogenic challenge, can stabilize and release functional PA. These nanoparticles demonstrated polymer hydrophobicity-dependent preservation of the biological function of PA upon encapsulation, storage (over extended times and elevated temperatures), and release. Specifically, fabrication of amphiphilic polyanhydride nanoparticles composed of 1,6-bis(p-carboxyphenoxy)hexane and 1,8-bis(p-carboxyphenoxy)-3,6- dioxaoctane best preserved PA functionality. These studies demonstrate the versatility and superiority of amphiphilic nanoparticles as vaccine delivery vehicles suitable for long-term storage

Neutral forces acting on intragenomic variability shape the Escherichia coli regulatory network topology

Cis-regulatory networks (CRNs) play a central role in cellular decision making. Like every other biological system, CRNs undergo evolution, which shapes their properties by a combination of adaptive and nonadaptive evolutionary forces. Teasing apart these forces is an important step toward functional analyses of the different components of CRNs, designing regulatory perturbation experiments, and constructing synthetic networks. Although tests of neutrality and selection based on molecular sequence data exist, no such tests are currently available based on CRNs. In this work, we present a unique genotype model of CRNs that is grounded in a genomic context and demonstrate its use in identifying portions of the CRN with properties explainable by neutral evolutionary forces at the system, subsystem, and operon levels.We leverage our model against experimentally derived data from Escherichia coli. The results of this analysis show statistically significant and substantial neutral trends in properties previously identified as adaptive in originﾗdegree distribution, clustering coefficient, and motifsﾗ within the E. coli CRN. Our model captures the tightly coupled genomeﾖ interactome of an organism and enables analyses of how evolutionary events acting at the genome level, such as mutation, and at the population level, such as genetic drift, give rise to neutral patterns that we can quantify in CRNs

Symmetry realization of texture zeros

We show that it is possible to enforce texture zeros in arbitrary entries of the fermion mass matrices by means of Abelian symmetries; in this way, many popular mass-matrix textures find a symmetry justification. We propose two alternative methods which allow to place zeros in any number of elements of the mass matrices that one wants. They are applicable simultaneously in the quark and lepton sectors. They are also applicable in Grand Unified Theories. The number of scalar fields required by our methods may be large; still, in many interesting cases this number can be reduced considerably. The larger the desired number of texture zeros is, the simpler are the models which reproduce the texture.Comment: 13 pages, no figures, plain LaTeX; misprints corrected, a few sentences changed, one reference added, final version for Eur. Phys. J.

An instrumental puzzle: the modular integration of AOLI

The Adaptive Optics Lucky Imager, AOLI, is an instrument developed to deliver the highest spatial resolution ever obtained in the visible, 20 mas, from ground-based telescopes. In AOLI a new philosophy of instrumental prototyping has been applied, based on the modularization of the subsystems. This modular concept offers maximum flexibility regarding the instrument, telescope or the addition of future developments.Comment: 10 pages, 8 figures, Proc. SPIE 9908, Ground-based and Airborne Instrumentation for Astronomy VI, 99082Z (August 9, 2016

Possible test for CPT invariance with correlated neutral B decays

We study breakdown of $CPT$ symmetry which can occur in the decay process $B \bar B \to l^\pm X^\mp f$ with $f$ being a CP eigenstate. In this process, the standard model expectations for time ordered semi-leptonic and hadronic events, i.e. which of the two decays takes place first, can be altered in the case that there is a violation of the $CPT$ symmetry. To illustrate this possibility, we identify and study several time integrated observables. We find that an experiment with $10^{9}$ $B\bar B$ pairs, has the capability for improving the bound on $CPT$ violating parameter or perhaps observe $CPT$ violation.Comment: Revised version to be published in PR

PGB pair production at LHC and ILC as a probe of the topcolor-assisted technicolor models

The topcolor-assisted technicolor (TC2) model predicts some light pseudo goldstone bosons (PGBs), which may be accessible at the LHC or ILC. In this work we study the pair productions of the charged or neutral PGBs at the LHC and ILC. For the productions at the LHC we consider the processes proceeding through gluon-gluon fusion and quark-antiquark annihilation, while for the productions at the ILC we consider both the electron-positron collision and the photon-photon collision. We find that in a large part of parameter space the production cross sections at both colliders can be quite large compared with the low standard model backgrounds. Therefore, in future experiments these productions may be detectable and allow for probing TC2 model.Comment: 26 pages, 16 figures. slight changes in the text; notations for curves changed; references adde