Systematic Engineering of Uniform, Highly Efficient, Targeted and Shielded Viral-Mimetic Nanoparticles

In the past decades, numerous types of nanomedicines have been developed for the efficient and safe delivery of nucleic acid-based drugs for cancer therapy. Given that the destination sites for nucleic acid-based drugs are inside cancer cells, delivery systems need to be both targeted and shielded in order to overcome the extracellular and intracellular barriers. One of the major obstacles that has hindered the translation of nanotechnology-based gene-delivery systems into the clinic has been the complexity of the design and assembly processes, resulting in non-uniform nanocarriers with unpredictable surface properties and efficiencies. Consequently, no product has reached the clinic yet. In order to address this shortcoming, a multifunctional targeted biopolymer is genetically engineered in one step, eliminating the need for multiple chemical conjugations. Then, by systematic modulation of the ratios of the targeted recombinant vector to PEGylated peptides of different sizes, a library of targeted-shielded viral-mimetic nanoparticles (VMNs) with diverse surface properties are assembled. Through the use of physicochemical and biological assays, targeted-shielded VMNs with remarkably high transfection efficiencies (>95%) are screened. In addition, the batch-to-batch variability of the assembled targeted-shielded VMNs in terms of uniformity and efficiency is examined and, in both cases, the coefficient of variation is calculated to be below 20%, indicating a highly reproducible and uniform system. These results provide design parameters for engineering uniform, targeted-shielded VMNs with very high cell transfection rates that exhibit the important characteristics for in vivo translation. These design parameters and principles could be used to tailor-make and assemble targeted-shielded VMNs that could deliver any nucleic acid payload to any mammalian cell type.

Normal type Ia supernovae from violent mergers of white dwarf binaries

One of the most important questions regarding the progenitor systems of Type Ia supernovae (SNe Ia) is whether mergers of two white dwarfs can lead to explosions that reproduce observations of normal events. Here we present a fully three-dimensional simulation of a violent merger of two carbon-oxygen white dwarfs with masses of 0.9 M and 1.1 M combining very high resolution and exact initial conditions. A well-tested combination of codes is used to study the system. We start with the dynamical inspiral phase and follow the subsequent thermonuclear explosion under the plausible assumption that a detonation forms in the process of merging. We then perform detailed nucleosynthesis calculations and radiative transfer simulations to predict synthetic observables from the homologously expanding supernova ejecta. We find that synthetic color light curves of our merger, which produces about 0.62 M of Ni, show good agreement with those observed for normal SNe Ia in all wave bands from U to K. Line velocities in synthetic spectra around maximum light also agree well with observations. We conclude that violent mergers of massive white dwarfs can closely resemble normal SNe Ia. Therefore, depending on the number of such massive systems available these mergers may contribute at least a small fraction to the observed population of normal SNe Ia. © 2012 The American Astronomical Society. All rights reserved.

Synthetic X-ray spectra for simulations of the dynamics of an accretion flow irradiated by a quasar

Ultraviolet and X-ray observations show evidence of outflowing gas around many active galactic nuclei. It has been proposed that some of these outflows are driven off gas infalling towards the central supermassive black hole. We perform radiative transfer calculations to compute the gas ionization state and the emergent X-ray spectra for both two- and three-dimensional (3D) hydrodynamical simulations of this outflow-from-inflow scenario. By comparison with observations, our results can be used to test the theoretical models and guide future numerical simulations. We predict both absorption and emission features, most of which are formed in a polar funnel of relatively dense (10 -10 g cm ) outflowing gas. This outflow causes strong absorption for observer orientation angles of ?35°. Particularly in 3D, the strength of this absorption varies significantly for different lines of sight owing to the fragmentary structure of the gas flow. Although infalling material occupies a large fraction of the simulation volume, we do not find that it imprints strong absorption features in the X-ray spectra since the ionization state is predicted to be very high. Thus, an absence of observed inflow absorption features does not exclude the models. The main spectroscopic consequence of the infalling gas is a Compton-scattered continuum component that partially re-fills the absorption features caused by the outflowing polar funnel. Fluorescence and scattering in the outflow are predicted to give rise to several emission features including a multicomponent Fe Ka emission complex for all observer orientations. For the hydrodynamical simulations considered, we predict both ionization states and column densities for the outflowing gas that are too high to be quantitatively consistent with well-observed X-ray absorption systems. Nevertheless, our results are qualitatively encouraging and further exploration of the model parameter space is warranted. Higher resolution hydrodynamic simulations are needed to determine whether the outflows fragment on scales unresolved in our current study, which may yield the denser lower ionization material that could reconcile the models and the observations. © 2012 The Authors Monthly Notices of the Royal Astronomical Society © 2012 RAS.

Adsorption of metal ions on nitrogen surface functional groups in activated carbons

A commercially available coconut-shell-derived active carbon was oxidized with nitric acid, and both the original and oxidized active carbons were treated with ammonia at 1073 K to incorporate nitrogen functional groups into the carbon. An active carbon with very high nitrogen content (similar to9.4 wt % daf) was also prepared from a nitrogen-rich precursor, polyacrylonitrile (PAN). These nitrogen-rich carbons had points of zero charge (pH(pzc)) similar to H-type active carbons. X-ray absorption near-edge structure (XANES) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, and temperature-programmed desorption (TPD) were used to characterize the nitrogen functional groups in the carbons. The nitrogen functional groups present on the carbon surface were pyridinic, pyrrolic (or indolic), and pyridonic structures. The adsorption of transition metal cations Cd2+, Ni2+, and Cu2+ from aqueous solution on the suite of active carbons showed that adsorption was markedly higher for carbons with nitrogen functional groups present on the surface than for carbons with similar pH(pzc) values. In contrast, the adsorption characteristics of Ca2+ from aqueous solution were similar for all the carbons studied. Flow microcalorimetry (FMC) studies showed that the enthalpies of adsorption of Cd2+(aq) on the active carbons with high nitrogen contents were much higher than for nitric acid oxidized carbons studied previously, which also had enhanced adsorption characteristics for metal ion species. The enthalpies of adsorption of Cu2+ were similar to those obtained for Cd2+ for specific active carbons. The nitrogen functional groups in the carbons act as surface coordination sites for the adsorption of transition metal ions from aqueous solution. The adsorption characteristics of these carbons are compared with those of oxidized carbons.

PROSTATIC INTRAEPITHELIAL NEOPLASIA (PIN) - PERFORMANCE OF BAYESIAN BELIEF NETWORK FOR DIAGNOSIS AND GRADING

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PlN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.