Delayed hepatic uptake of multi-phosphonic acid poly(ethylene glycol) coated iron oxide measured by real-time Magnetic Resonance Imaging

We report on the synthesis, characterization, stability and pharmacokinetics of novel iron based contrast agents for magnetic resonance imaging (MRI). Statistical copolymers combining multiple phosphonic acid groups and poly(ethylene glycol) (PEG) were synthesized and used as coating agents for 10 nm iron oxide nanocrystals. In vitro, protein corona and stability assays show that phosphonic acid PEG copolymers outperform all other coating types examined, including low molecular weight anionic ligands and polymers. In vivo, the particle pharmacokinetics is investigated by monitoring the MRI signal intensity from mouse liver, spleen and arteries as a function of the time, between one minute and seven days after injection. Iron oxide particles coated with multi-phosphonic acid PEG polymers are shown to have a blood circulation lifetime of 250 minutes, i.e. 10 to 50 times greater than that of recently published PEGylated probes and benchmarks. The clearance from the liver takes in average 2 to 3 days and is independent of the core size, coating and particle stability. By comparing identical core particles with different coatings, we are able to determine the optimum conditions for stealth MRI probes.Comment: 19 pages 8 figures, RSC Advances, 201

Intraoperative Neurophysiological Monitoring for Endoscopic Endonasal Approaches to the Skull Base: A Technical Guide.

Intraoperative neurophysiological monitoring during endoscopic, endonasal approaches to the skull base is both feasible and safe. Numerous reports have recently emerged from the literature evaluating the efficacy of different neuromonitoring tests during endonasal procedures, making them relatively well-studied. The authors report on a comprehensive, multimodality approach to monitoring the functional integrity of at risk nervous system structures, including the cerebral cortex, brainstem, cranial nerves, corticospinal tract, corticobulbar tract, and the thalamocortical somatosensory system during endonasal surgery of the skull base. The modalities employed include electroencephalography, somatosensory evoked potentials, free-running and electrically triggered electromyography, transcranial electric motor evoked potentials, and auditory evoked potentials. Methodological considerations as well as benefits and limitations are discussed. The authors argue that, while individual modalities have their limitations, multimodality neuromonitoring provides a real-time, comprehensive assessment of nervous system function and allows for safer, more aggressive management of skull base tumors via the endonasal route

Assessment of Modeling Strategies for Lightly Reinforced Concrete Shear Walls

element detailing, which suggest they are susceptible to brittle, compression-controlled failure modes, and deemed deficient by industry practitioners. Researchers at the California Polytechnic State University [1], San Luis Obispo (Cal Poly), recently tested a slender RC wall with vertical and horizontal reinforcement ratios approaching ACI 318-14 [2] code minimum (ρl= ρh= 0.37%) and no boundary elements. Results from this wall test will be presented and contrasted with a set of lightly reinforced walls, specimens C1-C3 tested by Lu et al. [3] at the University of Auckland, New Zealand, with higher levels of reinforcement (ρl= 0.53%). This paper will examine the Cal Poly and Lu et al. walls by comparing experimental test results. It will also comment on the accuracy of current modelling strategies used by industry practitioners to estimate the strength, stiffness, and ductility of existing lightly reinforced walls. Finally, it will make recommendations for the necessary model calibrations to achieve accurate prediction of the response of the lightly reinforced walls using PERFORM-3D [4], as a refinement of Lowes et al. [5] modeling recommendations for this wall type. The overall goal with this study is to facilitate accurate modeling that will provide detailed understanding of the wall response, and to inform the industry practitioner about the need for retrofitting to meet modern standards

Impact of irreversibility and uncertainty on the timing of infrastructure projects

This paper argues that because of the irreversibility and uncertainty associated with Build - Operate - Transfer (BOT) infrastructure projects, their financial evaluation should also routinely include the determination of the value of the option to defer the construction start-up. This ensures that project viability is comprehensively assessed before any revenue or loan guarantees are considered by project sponsors to support the project. This paper shows that the framework can be used even in the context of the intuitive binomial lattice model. This requires estimating volatility directly from the evolution of the net operating income while accounting for the correlation between the revenue and costs functions. This approach ensures that the uncertainties usually associated with toll revenues, in particular, are thoroughly investigated and their impact on project viability is thoroughly assessed. This paper illustrates the usefulness of the framework with data from an actual (BOT) toll road project. The results show that by postponing the project for a couple of years the project turns out to be viable, whereas it was not without the deferral. The evaluation approach proposed therefore provides a better framework for determining when and the extent of government financial support, if any, that may be needed to support a BOT project on the basis of project economics. The analysis may also be applicable to private sector investment projects, which are characterized by irreversibility and a high rate of uncertainty

Autocorrelation analysis for the unbiased determination of power-law exponents in single-quantum-dot blinking

We present an unbiased and robust analysis method for power-law blinking statistics in the photoluminescence of single nano-emitters, allowing us to extract both the bright- and dark-state power-law exponents from the emitters' intensity autocorrelation functions. As opposed to the widely-used threshold method, our technique therefore does not require discriminating the emission levels of bright and dark states in the experimental intensity timetraces. We rely on the simultaneous recording of 450 emission timetraces of single CdSe/CdS core/shell quantum dots at a frame rate of 250 Hz with single photon sensitivity. Under these conditions, our approach can determine ON and OFF power-law exponents with a precision of 3% from a comparison to numerical simulations, even for shot-noise-dominated emission signals with an average intensity below 1 photon per frame and per quantum dot. These capabilities pave the way for the unbiased, threshold-free determination of blinking power-law exponents at the micro-second timescale

Achieving sub-diffraction imaging through bound surface states in negative-refracting photonic crystals at the near-infrared

We report the observation of imaging beyond the diffraction limit due to bound surface states in negative refraction photonic crystals. We achieve an effective negative index figure-of-merit [-Re(n)/Im(n)] of at least 380, ~125x improvement over recent efforts in the near-infrared, with a 0.4 THz bandwidth. Supported by numerical and theoretical analyses, the observed near-field resolution is 0.47 lambda, clearly smaller than the diffraction limit of 0.61 lambda. Importantly, we show this sub-diffraction imaging is due to the resonant excitation of surface slab modes, allowing refocusing of non-propagating evanescent waves

Electrochemical Characterization of Self-Assembled Monolayers on Gold Substrates Derived from Thermal Decomposition of Monolayer-Protected Cluster Films

Networked films of monolayer-protected clusters (MPCs), alkanethiolate-stabilized gold nanoparticles, can be thermally decomposed to form stable gold on glass substrates that are subsequently modified with self-assembled monolayers (SAMs) for use as modified electrodes. Electrochemical assessment of these SAM-modified gold substrates, including double-layer capacitance measurements, linear sweep desorption of the alkanethiolates, and diffusional redox probing, all show that SAMs formed on gold supports formed from thermolysis of MPC films possess substantially higher defect density compared to SAMs formed on traditional evaporated gold. The density of defects in the SAMs on thermolyzed gold is directly related to the strategies used to assemble the MPC film prior to thermolysis. Specifically, gold substrates formed from thermally decomposing MPC films formed with electrostatic bridges between carboxylic acid-modified MPCs and metal ion linkers are particularly sensitive to the degree of metal exposure during the assembly process. While specific metal dependence was observed, metal concentration within the MPC precursor film was determined to be a more significant factor. Specific MPC film linking strategies and pretreatment methods that emphasized lower metal exposure resulted in gold films that supported SAMs of lower defect density. The defect density of a SAM-modified electrode is shown to be critical in certain electrochemical experiments such as protein monolayer electrochemistry of adsorbed cytochrome c. While the thermal decomposition of nanoparticle film assemblies remains a viable and interesting technique for coating both flat and irregular shaped substrates, this study provides electrochemical assessment tools and tactics for determining and controlling SAM defect density on this type of gold structure, a property critical to their effective use in subsequent electrochemical applications

An introduction to crowdsourcing for language and multimedia technology research

Language and multimedia technology research often relies on large manually constructed datasets for training or evaluation of algorithms and systems. Constructing these datasets is often expensive with significant challenges in terms of recruitment of personnel to carry out the work. Crowdsourcing methods using scalable pools of workers available on-demand offers a flexible means of rapid low-cost construction of many of these datasets to support existing research requirements and potentially promote new research initiatives that would otherwise not be possible