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The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic.

We present a simple method to pattern capture antibodies (cAbs) on poly(dimethylsiloxane) (PDMS), with high accuracy and in a manner compatible with mass fabrication for use with capillary systems (CSs), using stencils microfabricated in Si. Capture antibodies are patterned as 60-270 [micro]m wide and 2 mm long lines on PDMS and used with CSs that have been optimized for convenient handling, pipetting of solutions, pumping of liquids, such as human blood serum, and visualization of signals for fluorescence immunoassays. With the use of this method, C-reactive protein (CRP) is detected with a sensitivity of 0.9 ng [mL.sup.-1] (7.8 pM) in 1 [micro]L of CRP-spiked human serum, within 11 min and using only four pipetting steps and a total volume of sample and reagents of 1.35 [micro]L. This exemplifies the high performances that can be achieved using this approach and an otherwise conventional surface sandwich fluorescence immunoassay. This method is simple and flexible and should therefore be applicable to a large number of demanding immunoassays.

We present a new computational method for reconstructing a vector velocity field from scattered, pulsed-wave ultrasound Doppler data. The main difficulty is that the Doppler measurements are incomplete, for they do only capture the velocity component along the beam direction. We thus propose to combine measurements from different beam directions. However, this is not yet sufficient to make the problem well posed because 1) the angle between the directions is typically small and 2) the data is noisy and nonuniformly sampled. We propose to solve this reconstruction problem in the continuous domain using regularization. The reconstruction is formulated as the minimizer of a cost that is a weighted sum of two terms: 1) the sum of squared difference between the Doppler data and the projected velocities 2) a quadratic regularization functional that imposes some smoothness on the velocity field. We express our solution for this minimization problem in a B-spline basis, obtaining a sparse system of equations that can be solved efficiently. Using synthetic phantom data, we demonstrate the significance of tuning the regularization according to the a priori knowledge about the physical property of the motion. Next, we validate our method using real phantom data for which the ground truth is known. We then present reconstruction results obtained from clinical data that originate from 1) blood flow in carotid bifurcation and 2) cardiac wall motion. Index Terms--Color Doppler imaging, color flow imaging, echocardiography, nonuniform sampling, projected sampling, pulsed wave Doppler, regularized reconstruction, shift-invariant spaces, tissue Doppler imaging, ultrasound Doppler, variational reconstruction, vector field reconstruction, velocity field reconstruction.

We propose a new spatio-temporal elastic registration algorithm for motion reconstruction from a series of images. The specific application is to estimate displacement fields from two-dimensional ultrasound sequences of the heart. The basic idea is to find a spatio-temporal deformation field that effectively compensates for the motion by minimizing a difference with respect to a reference frame. The key feature of our method is the use of a semi-local spatio-temporal parametric model for the deformation using splines, and the reformulation of the registration task as a global optimization problem. The scale of the spline model controls the smoothness of the displacement field. Our algorithm uses a multiresolution optimization strategy to obtain a higher speed and robustness. We evaluated the accuracy of our algorithm using a synthetic sequence generated with an ultrasound simulation package, together with a realistic cardiac motion model. We compared our new global multiframe approach with a previous method based on pairwise registration of consecutive frames to demonstrate the benefits of introducing temporal consistency. Finally, we applied the algorithm to the regional analysis of the left ventricle. Displacement and strain parameters were evaluated showing significant differences between the normal and pathological segments, thereby illustrating the clinical applicability of our method. Index Terms--Cardiac motion, elastic registration, parametric models, splines, temporal models.

A new optical flow-based method for estimating heart motion from two-dimensional echocardiographic sequences is presented. The radial component of the velocity with respect to a reference point is color coded and visualized inside a time-varying region of interest, in order to characterize myocardial contractility and to simplify the detection of myocardial dysfunction.

A novel method image reconstruction from nonuniform samples with no constraints on their locations is proposed. A variational approach where the reconstruction is formulated is adopted.