Jet injection of a monoclonal antibody: A preliminary study.

Monoclonal antibodies (mAbs) represent a major group of biotherapeutics. The high concentration and volume of drug administered together with a shift to administration via the subcutaneous route have generated interest in alternative delivery technologies. The feasibility of using a novel, highly controllable jet injection technology to deliver a mAb is presented. The effect of delivery parameters on protein structure were evaluated and compared with delivery using a conventional needle and syringe. Injection of mAb into a rat model showed that jet injection using the device resulted in more rapid absorption and longer duration of exposure.

A modular instrument for exploring the mechanics of cardiac myocytes.

The cardiac ventricular myocyte is a key experimental system for exploring the mechanical properties of the diseased and healthy heart. Millions of primary myocytes, which remain viable for 4-6 h, can be readily isolated from animal models. However, currently available instrumentation allows the mechanical properties of only a few physically loaded myocytes to be explored within 4-6 h. Here we describe a modular and inexpensive prototype instrument that could form the basis of an array of devices for probing the mechanical properties of single mammalian myocytes in parallel. This device would greatly increase the throughput of scientific experimentation and could be applied as a high-content screening instrument in the pharmaceutical industry. The instrument module consists of two independently controlled Lorentz force actuators-force transducers in the form of 0.025 x 1 x 5 mm stainless steel cantilevers with 0.5 m/N compliance and 360-Hz resonant frequency. Optical position sensors focused on each cantilever provide position and force resolution of <1 nm/ radicalHz and <2 nN/ radicalHz, respectively. The motor structure can produce peak displacements and forces of +/-200 mum and +/-400 microN, respectively. Custom Visual Basic.Net software provides data acquisition, signal processing, and digital control of cantilever position. The functionality of the instrument was demonstrated by implementation of novel methodologies for loading and attaching healthy mammalian ventricular myocytes to the force sensor and actuator and use of stochastic system identification techniques to measure their passive dynamic stiffness at various sarcomere lengths.

A stochastic method for generating signals with jointly specified probability mass, spectral, and correlation properties for the identification of physiological systems.

An efficient stochastic interchange method was developed that allows two discrete time sequences to be created with a specified cross-correlation function and individually defined amplitude and spectral characteristics. The technique is particularly useful for creating sequences for the stimulation of multi-input physiological systems. It is very general in that sequences of any signal type can be manipulated and are not limited to being white and/or uncorrelated. By temporally separating occurrences of common frequencies, the method can even be used to create sequences that share common power, but can be treated as uncorrelated. The method is made practical by an algorithm that updates efficiently the auto- and cross-correlation functions of the sequences as they are being created.

Parallel cascade identification and its application to protein family prediction.

Parallel cascade identification is a method for modeling dynamic systems with possibly high order nonlinearities and lengthy memory, given only input/output data for the system gathered in an experiment. While the method was originally proposed for nonlinear system identification, two recent papers have illustrated its utility for protein family prediction. One strength of this approach is the capability of training effective parallel cascade classifiers from very little training data. Indeed, when the amount of training exemplars is limited, and when distinctions between a small number of categories suffice, parallel cascade identification can outperform some state-of-the-art techniques. Moreover, the unusual approach taken by this method enables it to be effectively combined with other techniques to significantly improve accuracy. In this paper, parallel cascade identification is first reviewed, and its use in a variety of different fields is surveyed. Then protein family prediction via this method is considered in detail, and some particularly useful applications are pointed out.

Design and characterization of a laser-based instrument with spectroscopic feedback control for treatment of vascular lesions: the "Smart Scalpel".

To improve the effectiveness of microsurgical techniques, we are developing a semi-autonomous robotic surgical tool (called the "Smart Scalpel") as an alternate approach to treatment of vascular lesions. The device employs optical reflectance spectroscopy as part of a line scan imaging system to identify and selectively target blood vessels in a vascular lesion for thermal treatment with a focused laser beam. Our proof-of-concept reported here presents the design and construction of a prototype instrument, initial quantification of imaging system resolution and contrast, and preliminary verification of the imaging and targeting strategies with standard targets and live dermal tissue.

Automatic classification of protein sequences into structure/function groups via parallel cascade identification: a feasibility study.

A recent paper introduced the approach of using nonlinear system identification as a means for automatically classifying protein sequences into their structure/function families. The particular technique utilized, known as parallel cascade identification (PCI), could train classifiers on a very limited set of exemplars from the protein families to be distinguished and still achieve impressively good two-way classifications. For the nonlinear system classifiers to have numerical inputs, each amino acid in the protein was mapped into a corresponding hydrophobicity value, and the resulting hydrophobicity profile was used in place of the primary amino acid sequence. While the ensuing classification accuracy was gratifying, the use of (Rose scale) hydrophobicity values had some disadvantages. These included representing multiple amino acids by the same value, weighting some amino acids more heavily than others, and covering a narrow numerical range, resulting in a poor input for system identification. This paper introduces binary and multilevel sequence codes to represent amino acids, for use in protein classification. The new binary and multilevel sequences, which are still able to encode information such as hydrophobicity, polarity, and charge, avoid the above disadvantages and increase classification accuracy. Indeed, over a much larger test set than in the original study, parallel cascade models using numerical profiles constructed with the new codes achieved slightly higher two-way classification rates than did hidden Markov models (HMMs) using the primary amino acid sequences, and combining PCI and HMM approaches increased accuracy.

3D-1D threading methods for protein fold recognition.

The threading approach to protein fold recognition attempts to evaluate how well a query sequence fits into an already-solved fold. 3D-1D threaders rely on matching 1-dimensional strings of 3-dimensional information predicted from the query sequence with corresponding features of the target structure. In many cases this is combined with a sequence comparison. The combination of sequence and structure information has been shown to improve the accuracy of fold recognition, relative to the exclusive use of sequence or structure. In this paper, we review progress made since the introduction of threading methods a decade ago, highlighting recent advances. We focus on two emerging methods that are unconventional 3D-1D threaders: proximity correlation matrices and parallel cascade identification.

Are there critical bands in kinesthesia?

The effect of changing the bandwidth of noise on the ability of human subjects to detect a 10-Hz sinusoidal movement signal was measured in two experiments. The objective of these studies was to investigate whether critical bands exist for the kinesthetic system, as has been demonstrated for the auditory and tactile systems. It was found that subjects' ability to detect a 10-Hz sinusoidal movement stimulus embedded in noise was not influenced by the bandwidth of the noise over a range of 4-10 Hz. These findings suggest that, if a critical filter does exist for this system, it would have to be greater than 10 Hz.

Two methods for identifying Wiener cascades having noninvertible static nonlinearities.

Two methods are proposed for identifying the component elements of a Wiener cascade that is comprised of a dynamic linear element (L) followed by a static nonlinearity (N). Both methods avoid potential problems of instability in a procedure presented by Paulin [M. G. Paulin, Biol. Cybern. 69: 67-76, 1993], which itself is a modification of a method described earlier by Hunter and Korenberg [I. W. Hunter and M. J. Korenberg, Biol. Cybern. 55: 135-144, 1996]. The latter method is a rapidly convergent iterative procedure that produces accurate estimates of the L and N elements from short data records, provided that the static nonlinearity N is invertible. Subsequently, Paulin introduced a modification that removed this limitation and enabled identification of Wiener cascades with nonmonotonic static nonlinearities. However, Paulin presented his modification employing an autoregressive moving average (ARMA) model representation for the dynamic linear element. To remove the possibility that the estimated ARMA model could be unstable, we recast the procedure by utilizing instead a rapid method for finding an impulse response representation for the dynamic linear element. However, in this form the procedure did not have good convergence properties, so we introduced two key ideas, both of which provide effective alternatives for identifying Wiener cascades whether or not the static nonlinearities therein are invertible. The new procedures are illustrated on challenging examples involving high-degree polynomial static nonlinearities, of odd or even symmetry, a high-pass linear element, and output noise corruption of 50%.

Large deformation mechanical testing of biological membranes using speckle interferometry in transmission. I: Experimental apparatus.

This paper describes an apparatus designed to study large mechanical deformations in biological membranes. The task of mechanically characterizing biological membranes is challenging because of the anisotropic and nonlinear nature of their material properties. The apparatus described here is well suited to the task because it uses speckle interferometry to measure in-plane displacements in a distributed fashion and has multiple degrees of freedom in the applied stress mechanism. In this way few a priori assumptions or restrictions are imposed on the applied stress and strain fields. The interferometer operates in transmission mode to increase the light efficiency of the system since the sample biological membranes are translucent and reflect little light. The experimental results confirm that the strain fields in the biological membranes that are generated in the experiments are highly nonuniform and cannot be properly estimated from a small number of point measurements.

Large deformation mechanical testing of biological membranes using speckle interferometry in transmission. II: Finite element modeling.

In holography and speckle interferometry the measurement range is generally limited by the greatest number of fringes that can be resolved in a single image. As a result these techniques have been generally confined to small displacement measurement applications. In the case of out-of-plane measurements one can overcome this limitation by simply adding incremental measurements at individual detector pixels. In the case of in-plane measurements, however, summing incremental measurements is not a straightforward procedure since the interference pattern moves laterally across the detector as the material deforms. We describe a modeling technique based on finite elements which solves this problem. In combination with a full field method such as holography or speckle interferometry, it provides a very sensitive measurement technique with dense spatial sampling and large dynamic range. Experimental results of speckle interferometry operating in transmission to measure in-plane displacements of biological membranes are presented, where total material displacements are of the order of millimeters. The results also demonstrate how the finite strain tensor is calculated analytically from the data at any point on the material.

Prospects for telediagnosis using ultrasound.

Ultrasound imaging is currently used as a primary diagnostic tool in cardiology, abdominal disorders, pulmonary medicine, trauma, and obstetrics. Because of its relatively low capital and operating costs as well as its growth potential, it represents one of the major diagnostic modalities of future health care. However, the use of ultrasonography as a mobile and powerful modality is controlled by the availability of a highly skilled technician to acquire the images and an experienced physician to interpret them. This paper discusses the technology required to increase the availability of a diagnosing physician by employing telerobotics. With this technology, the physician can guide the motion of the transducer by the technician from a remote location. Thus, the physician controls the examination and renders the diagnosis. It is shown that communication lines at 1.5 Mbits/s (T-1 speed) can, with appropriate compression, support both real-time viewing of the ultrasound images and telerobotic manipulation of the transducer. The incremental costs of telediagnosis for an examination are estimated to be a small fraction of the base charges and significantly less than the expense of bringing a physician to a remote location or transporting a patient to a regional medical center. Telediagnosis can, in addition, provide benefits from immediate interpretation and consultation that cannot be duplicated using store-and-forward scenarios.

The identification of nonlinear biological systems: Volterra kernel approaches.

Representation, identification, and modeling are investigated for nonlinear biomedical systems. We begin by considering the conditions under which a nonlinear system can be represented or accurately approximated by a Volterra series (or functional expansion). Next, we examine system identification through estimating the kernels in a Volterra functional expansion approximation for the system. A recent kernel estimation technique that has proved to be effective in a number of biomedical applications is investigated as to running time and demonstrated on both clean and noisy data records, then it is used to illustrate identification of cascades of alternating dynamic linear and static nonlinear systems, both single-input single-output and multivariable cascades. During the presentation, we critically examine some interesting biological applications of kernel estimation techniques.

The identification of nonlinear biological systems: Volterra kernel approaches.

Representation, identification, and modeling are investigated for nonlinear biomedical systems. We begin by considering the conditions under which a nonlinear system can be represented or accurately approximated by a Volterra series (or functional expansion). Next, we examine system identification through estimating the kernels in a Volterra functional expansion approximation for the system. A recent kernel estimation technique that has proved to be effective in a number of biomedical applications is investigated as to running time and demonstrated on both clean and noisy data records, then it is used to illustrate identification of cascades of alternating dynamic linear and static nonlinear systems, both single-input single-output and multivariable cascades. During the presentation, we critically examine some interesting biological applications of kernel estimation techniques.

Robust phase-unwrapping method for phase images with high noise content.

We present a robust method of phase unwrapping that was designed for use on noisy phase images with arbitrary fringe patterns. The method proceeds by first identifying distinct regions between fringe boundaries in an image and then phase shifting the regions with respect to one another by multiples of 2π to unwrap the phase. Image pixels are segmented between interfringe and fringe boundary areas by fitting a plane model using least squares to overlapping domains centered on all pixels. The method is tolerant of fringe gradient degradation caused by noise, filtering artifacts, and finite instrumentation bandwidth.

Analysis of short-latency reflexes in human elbow flexor muscles.

1. A motor and digital controller have been developed to apply rapid stretches to the human elbow joint. The digital controller returns the forearm to the initial position before the reflex contraction. Thus short-latency reflex responses can be cleanly separated in time from the mechanical effects of the stretch under a wide variety of loading conditions. 2. The reflex force varies linearly with the velocity of stretch over nearly 2 orders of magnitude. The reflex force also varies linearly with the tonic level of force over the entire range of forces studied (0-100 N). This contrasts sharply with, for example, the human ankle joint, which shows a very limited linear range. 3. As the digital controller is made more compliant (less stiff), reflex shortening increases dramatically and becomes more prolonged, whereas the reflex force becomes somewhat smaller and shorter. With compliant loads and the brief stretches we applied, the reflex shortening is approximately equal to the stretch that generated it. 4. Simulations of the results confirm that the dependence of reflex shortening and force on the stiffness of the load is mainly determined by the mechanics of the limb and muscles. The simulations also indicate that 1) the gain of the reflex is as high as it can be without causing instability and 2) the presence of a rectification nonlinearity (e.g., lengthening the muscle produces a reflex, but shortening the muscle does not) is mainly responsible for preserving the stability of the elbow system.

Ophthalmic microsurgical robot and associated virtual environment.

An ophthalmic virtual environment has been developed as part of a teleoperated microsurgical robot built to perform surgery on the eye. The virtual environment is unique in that it incorporates a detailed continuum model of the anatomical structures of the eye, its mechanics and optical properties, together with a less detailed geometric-mechanical model of the face. In addition to providing a realistic visual display of the eye being operated on, the virtual environment simulates tissue properties during manipulation and cutting and the forces involved are determined by solving a mechanical finite element model of the tissue. These forces are then fed back to the operator via a force reflecting master and so the surgeon can experience both the visual and mechanical sensations associated with performing surgery. The virtual environment can be used to enhance the images produced by the camera on the microsurgical slave robot during surgery and as a surgical simulator in which it replaces these images with computer graphics generated from the eye model.

Chemical imaging with a confocal scanning Fourier-transform-Raman microscope.

Traditional approaches in confocal microscopy have focused on techniques to generate volumetric intensity or phase images of an object. In these different imaging modes the scattered optical-field properties depend on local refractive index and absorption, properties not unique to a given material. We report here on a confocal microscope that uses Raman scattered light to generate volumetric chemical images of a material. We designed and built a prototype instrument, called a confocal scanning laser Raman microscope, that combines a confocal scanning laser microscope with a Fourier-transform-Raman spectrometer. The high depth and lateral spatial resolution of the confocal optics design define a volume element from which the Raman scattered light is collected, and the spectrometer analyzes its spectral content. The sample is scanned through the microscope probe volume, and a chemical image isgenerated based on the content of the Raman spectrum extracted from each scan position in the sample. The results inclu e instrument characterization measurements and examples of confocal chemical imaging.

Quantitative analysis of four EMG amplifiers.

Four typical EMG amplifiers were tested quantitatively to observe the diversity and specificity of available equipment. Gain, phase, common mode rejection ratio (CMRR) and noise characteristics were measured for each device. Various gain and phase responses were observed, each best suited to specific application areas. For all amplifiers, the CMRR was shown to decrease dramatically in the presence of input impedance mismatches of more than 10 k omega between the two electrodes. Because such impedance mismatches are common on the skin surface, these results indicate that proper skin preparation is required to maximize the noise rejection capabilities of the tested amplifiers.

Nonparametric two-dimensional point spread function estimation for biomedical imaging.

The problem of identifying optical system point spread functions (PSFs) arises frequently in the area of image processing and restoration. The paper presents a method for determining two-dimensional PSFs from input/output image signals. The PSF of the system is determined from a set of linear equations involving elements of the input autocorrelation function and the input/output cross-correlation function. The resulting PSF is the one that minimises the sum of squares difference between the actual output image and the predicted one.