Optimization of Pathogen Capture in Flowing Fluids with Magnetic Nanoparticles

Magnetic nanoparticles have been employed to capture pathogens for many biological applications; however, optimal particle sizes have been determined empirically in specific capturing protocols. Here, a theoretical model that simulates capture of bacteria is described and used to calculate bacterial collision frequencies and magnetophoretic properties for a range of particle sizes. The model predicts that particles with a diameter of 460 nm should produce optimal separation of bacteria in buffer flowing at 1 L h⁻¹. Validating the predictive power of the model, Staphylococcus aureus is separated from buffer and blood flowing through magnetic capture devices using six different sizes of magnetic particles. Experimental magnetic separation in buffer conditions confirms that particles with a diameter closest to the predicted optimal particle size provide the most effective capture. Modeling the capturing process in plasma and blood by introducing empirical constants (c_e), which integrate the interfering effects of biological components on the binding kinetics of magnetic beads to bacteria, smaller beads with 50 nm diameters are predicted that exhibit maximum magnetic separation of bacteria from blood and experimentally validated this trend. The predictive power of the model suggests its utility for the future design of magnetic separation for diagnostic and therapeutic applications.     

Annular‐ring slot antenna designs with circular polarization radiation

The design of a microstrip‐fed annular‐ring slot antenna (ARSA) with circular polarization (CP) radiation is initially studied. To obtain CP radiation with broad 3‐dB axial ratio (AR) bandwidth that can cover the WiMAX 2.3 GHz (2305–2320 MHz, 2345–2360 MHz) and WLAN 2.4 GHz (2400–2480 MHz) bands, a novel technique of extending an inverted L‐shaped slot from the bottom section of the annular‐ring is proposed. To suppress the harmonic modes induced by the CP ARSA, the technique of integrating a defected ground structure into the annular‐ring slot is further introduced. From the measured results, 10‐dB impedance bandwidth and 3‐dB AR bandwidth of 44.86 and 9.68% were achieved by the proposed harmonic suppressed CP ARSA. Furthermore, average gain and radiation efficiency of ～4.7 dBic and 71%, respectively, were also exhibited across the bands of interest. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:337–345, 2015.     

Preparation and physicochemical study of jute and glass composites of epoxy resin of (2E, 6E)-bis(4-hydroxybenzylidene)cyclohexanone

Polymer Bulletin - Jute and glass composites of epoxy resin of (2E, 6E)-bis(4-hydroxybenzylidene)cyclohexanone (EBHBC) were prepared by compressing molding technique using three different hardeners...     

The Critical Role of Passive Permeability in Designing Successful Drugs

Passive permeability is a key property in drug disposition and delivery. It is critical for gastrointestinal absorption, brain penetration, renal reabsorption, defining clearance mechanisms and drug-drug interactions. Passive diffusion rate is translatable across tissues and animal species, while the extent of absorption is dependent on drug properties, as well as in vivo physiology/pathophysiology. Design principles have been developed to guide medicinal chemistry to enhance absorption, which combine the balance of aqueous solubility, permeability and the sometimes unfavorable compound characteristic demanded by the target. Permeability assays have been implemented that enable rapid development of structure-permeability relationships for absorption improvement. Future advances in assay development to reduce nonspecific binding and improve mass balance will enable more accurately measurement of passive permeability. Design principles that integrate potency, selectivity, passive permeability and other ADMET properties facilitate rapid advancement of successful drug candidates to patients.     

Synthesis and Application of Novel Nano Fe-BTC/GO Composites as Highly Efficient Photocatalysts in the Dye Degradation

Topics in Catalysis - Nano Fe-BTC/graphene oxide (GO) composites were successfully synthesized by hydrothermal treatment with a microwave-assisted method. Samples were characterized by X-ray...     

CuInS2/SiNWs/Si composite material for application as potential photoelectrode for photoelectrochemical hydrogen generation

This work aims at developing a new composite material based on nanosized semiconducting CuInS₂ (CIS) particles combined with silicon nanowires grown on a silicon substrate (SiNWs/Si) for photoelectrochemical (PEC)-splitting of water. The CIS particles were prepared via a colloidal method using N-methylimidazole (NMI) as the solvent and an annealing treatment. The SiNWs were obtained by chemical etching of silicon (100) substrates assisted by a metal. The CIS/SiNWs/Si composite material was obtained by deposition of an aliquot of a suspension of CIS particles onto the SiNWs/Si substrate, using spin coating followed by a drying step. The XRD pattern demonstrated that CuInS₂ grows in the tetragonal/chalcopyrite phase, while SiNWs/Si presents a cubic structure. The SEM images show semi-spherical particles (～10 nm) distributed on the surface of silicon nanowires (～10 μm). The EIS measurements reveal n-type conductivity for CIS, SiNWs/Si and CIS/SiNWs/Si materials, which could favour the oxidation reaction of water molecules.     

Moderate lameness leads to marked behavioral changes in dairy cows

Lameness is one of the most prevalent diseases affecting the welfare of cows in modern dairy production. Lameness leads to behavioral changes in severely lame cows, which have been investigated in much detail. For early detection of lameness, knowledge of the effects of moderate lameness on cow behavior is crucial. Therefore, the behavior of nonlame and moderately lame cows was compared on 17 Swiss dairy farms. On each farm, 5 to 11 nonlame (locomotion score 1 of 5) and 2 to 7 moderately lame (locomotion score 3 of 5) cows were selected for data collection in two 48-h periods (A, B) separated by an interval of 6 to 10 wk. Based on visual locomotion scoring, 142 nonlame and 66 moderately lame cows were examined in period A and 128 nonlame and 53 moderately lame cows in period B. Between these 2 periods, the cows underwent corrective hoof trimming. Lying behavior, locomotor activity, and neck activity were recorded by accelerometers (MSR145 data logger, MSR Electronics GmbH, Seuzach, Switzerland), and feeding and rumination behaviors by noseband sensors (RumiWatch halter, ITIN + HOCH GmbH, Liestal, Switzerland). Furthermore, visits to the brush and the concentrate feeder, and the milking order position were recorded. In comparison with nonlame cows, moderately lame cows had a longer lying duration, a longer average lying bout duration, and a greater lateral asymmetry in lying duration. Average locomotor activity, locomotor activity during 1 h after feed delivery or push-ups, and average neck activity were lower in moderately lame cows. Eating time and the number of eating chews (jaw movements) were reduced in moderately lame compared with nonlame cows, whereas no effect of moderate lameness was evident for ruminating time, number of ruminating chews and boluses, and average number of ruminating chews per bolus. Moderately lame cows visited the concentrate feeder and the brush less frequently, and they were further back in the milking order compared with nonlame cows. In conclusion, nonlame and moderately lame cows differed in a biologically relevant way in many of the behavioral variables investigated in this study. Therefore, the use of these behavioral changes seems to be promising to develop a tool for early lameness detection.     

Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.