Chemical patterning for the highly specific and programmed assembly of nanostructures

We have developed a new chemical patterning technique based on standard lithography-based processes to assemble nanostructures on surfaces with extraordinarily high selectivity. This patterning process is used to create patterns of aminosilane molecular layers surrounded by highly inert poly (ethylene glycol) (PEG) molecules. While the aminosilane regions facilitate nanostructure assembly, the PEG coating prevents adsorption of molecules and nanostructures, thereby priming the semiconductor substrate for the highly localized and programmed assembly of nanostructures. We demonstrate the power and versatility of this manufacturing process by building multilayered structures of gold nanoparticles attached to molecules of DNA onto the aminosilane patterns, with zero nanocrystal adsorption onto the surrounding PEG regions. The highly specific surface chemistry developed here can be used in conjunction with standard microfabrication and emerging nanofabrication technology to seamlessly integrate various nanostructures with semiconductor electronics

Field-effect control of protein transport in a nanofluidic transistor circuit

Electrostatic interactions play an important role in nanofluidic channels when the channel size is comparable to the Debye screening length. Electrostatic fields have been used to control concentration and transport of ions in nanofluidic transistors. Here, we report a transistor-reservoir-transistor circuit that can be used to turn “on” or “off” protein transport using electrostatic fields with gate voltages of ±1 V. Our results suggest that global electrostatic interactions of the protein were dominant over other interactions in the nanofluidic transistor. The fabrication technique also demonstrates the feasibility of nanofluidic integrated circuits for the manipulation of biomolecules in picoliter volumes

Rectification of Ionic Current in a Nanofluidic Diode

We demonstrate rectification of ionic transport in a nanofluidic diode fabricated by introducing a surface charge discontinuity in a nanofluidic channel. Device current−voltage (I−V) characteristics agree qualitatively with a one-dimensional model at moderate to high ionic concentrations. This study illustrates ionic flow control using surface charge patterning in nanofluidic channels under high bias voltages

Intracellular Transport Dynamics of Endosomes Containing DNA Polyplexes along the Microtubule Network

We have explored the transport of DNA polyplexes enclosed in endosomes within the cellular environment by multiple particle tracking (MPT). The polyplex-loaded endosomes demonstrate enhanced diffusion at short timescales (t < 7 s) with their mean-square displacement (MSD) 〈Δx(t)(2)〉 scaling as t(1.25). For longer time intervals they exhibit subdiffusive transport and have an MSD scaling as t(0.7). This crossover from an enhanced diffusion to a subdiffusive regime can be explained by considering the action of motor proteins that actively transport these endosomes along the cellular microtubule network and the thermal bending modes of the microtubule network itself

Nanomechanical Sensor Array for Detection of Biomolecular Bindings: Toward a Label-Free Clinical Assay for Serum Tumor Markers

A label-free technique capable of rapidly screening human blood samples simultaneously for multiple serum tumor markers would enable accurate and cost-effective diagnosis of cancer before physiological symptoms appear. Recently, microfabricated, bimaterial cantilever sensors have been demonstrated to detect DNA hybridization and antigen-antibody binding at clinically relevant concentrations. Cantilever sensors deflect measurably under the surface stress resulting when biomolecules immobilized on one surface of the sensor interact with their binding partners [1]. We present an array of cantilever sensors (silicon nitride with a gold coated surface) capable of simultaneously interrogating 100 different biomolecular interactions

Association Between Genetic Variation in FOXO3 and Reductions in Inflammation and Disease Activity in Inflammatory Polyarthritis

This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/art.39760${\bf Background:}$ Genetic variation in FOXO3 (tagged by rs12212067) has been associated with a milder course of rheumatoid arthritis (RA) and shown to limit monocyte-driven inflammation through a TGFβ1-dependent pathway. This genetic association, however, has not been consistently observed in other RA cohorts. We sought to clarify the contribution of FOXO3 to prognosis in RA by combining detailed analysis of non-radiographic disease severity measures with an in vivo model of arthritis. ${\bf Methods:}$ Collagen-induced arthritis, the most commonly used mouse model of RA, was used to assess how Foxo3 contributes to arthritis severity. Using clinical, serological and biochemical methods, the arthritis that developed in mice carrying a loss-of-function mutation in Foxo3 was compared with that which occurred in littermate controls. The association of rs12212067 with non-radiographic measures of RA severity, including CRP, Swollen Joint Count, Tender Joint Count, DAS28 and the HAQ score were modelled longitudinally in a large prospective cohort of early RA patients. ${\bf Results:}$ Loss of Foxo3 function resulted in more severe arthritis in vivo (both clinically and histologically) and was associated with higher titres of anti-collagen antibodies and IL-6 in blood. Similarly, rs12212067 (a SNP that increases FOXO3 transcription) was associated with reduced inflammation – both biochemically and clinically – and with lower RA activity scores. ${\bf Conclusions:}$ Consistent with its known role in restraining inflammatory responses, FOXO3 limits the severity of in vivo arthritis and, through genetic variation that increases its transcription, is associated with reduced inflammation and disease activity in RA patients – effects that would lead to lesser radiographic damage.Arthritis Research UK (Grant ID: 20385)National Institute for Health ResearchWellcome Trust (Grant ID: 105920/Z/14/Z