Spatiotemporal scaling changes in gait in a progressive model of Parkinson's disease.

Objective: Gait dysfunction is one of the most difficult motor signs to treat in patients with Parkinson's disease (PD). Understanding its pathophysiology and developing more effective therapies for parkinsonian gait dysfunction will require preclinical studies that can quantitatively and objectively assess the spatial and temporal features of gait.

Design: We developed a novel system for measuring volitional, naturalistic gait patterns in non-human primates, and then applied the approach to characterize the progression of parkinsonian gait dysfunction across a sequence of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatments that allowed for intrasubject comparisons across mild, moderate, and severe stages.

Parkinsonian daytime sleep-wake classification using deep brain stimulation lead recordings.

Excessive daytime sleepiness is a recognized non-motor symptom that adversely impacts the quality of life of people with Parkinson's disease (PD), yet effective treatment options remain limited. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for PD motor signs. Reliable daytime sleep-wake classification using local field potentials (LFPs) recorded from DBS leads implanted in STN can inform the development of closed-loop DBS approaches for prompt detection and disruption of sleep-related neural oscillations.

Intrathecal Opioid-Induced Hypothermia Following Subarachnoid Block With Morphine Injection for Elective Cesarean Delivery: A Case Report.

Opioids have been administered intrathecally with subarachnoid block for postoperative pain relief in parturients undergoing elective cesarean deliveries. This case report presents the uncommon occurrence of intrathecal opioid-induced hypothermia in the latent phase of recovery following elective cesarean delivery. There are few case reports on the occurrence of latent-phase postanesthesia care hypothermia in patients receiving subarachnoid block with morphine sulfate injection (Duramorph).

Enhancing the tensile properties of continuous millimeter-scale carbon nanotube fibers by densification.

This work presents a study of the tensile mechanical properties of millimeter-long fibers comprising carbon nanotubes (CNTs). These CNT fibers are made of aligned, loosely packed parallel networks of CNTs that are grown in and harvested from CNT forests without drawing or spinning. Unlike typical CNT yarn, the present fibers contain a large fraction of CNTs that span the fibers' entire gauge length.

Modeling mechanical energy storage in springs based on carbon nanotubes.

A modeling study of the potential for storing energy in the elastic deformation of springs comprised of carbon nanotubes (CNTs) is presented. Analytic models were generated to estimate the ideal achievable energy density in CNTs subject to axial tension, compression, bending and torsion, taking into account limiting mechanisms such as the strength of individual CNTs, the onset of buckling, and the packing density limitations of CNT groupings. The stored energy density in CNT springs is predicted to be highest under tensile loading, with maximum values more than three orders of magnitude greater than the energy density of steel springs, and approximately eight times greater than the energy density of lithium-ion batteries.

Principles of control for decoherence-free subsystems.

Decoherence-free subsystems (DFSs) are a powerful means of protecting quantum information against noise with known symmetry properties. Although Hamiltonians that can implement a universal set of logic gates on DFS encoded qubits without ever leaving the protected subsystem theoretically exist, the natural Hamiltonians that are available in specific implementations do not necessarily have this property. Here we describe some of the principles that can be used in such cases to operate on encoded qubits without losing the protection offered by the DFSs.

Benchmarking quantum control methods on a 12-qubit system.

In this Letter, we present an experimental benchmark of operational control methods in quantum information processors extended up to 12 qubits. We implement universal control of this large Hilbert space using two complementary approaches and discuss their accuracy and scalability. Despite decoherence, we were able to reach a 12-coherence state (or a 12-qubit pseudopure cat state) and decode it into an 11 qubit plus one qutrit pseudopure state using liquid state nuclear magnetic resonance quantum information processors.

Quantum process tomography of the quantum Fourier transform.

The results of quantum process tomography on a three-qubit nuclear magnetic resonance quantum information processor are presented and shown to be consistent with a detailed model of the system-plus-apparatus used for the experiments. The quantum operation studied was the quantum Fourier transform, which is important in several quantum algorithms and poses a rigorous test for the precision of our recently developed strongly modulating control fields. The results were analyzed in an attempt to decompose the implementation errors into coherent (overall systematic), incoherent (microscopically deterministic), and decoherent (microscopically random) components.

Incoherent noise and quantum information processing.

Incoherence in the controlled Hamiltonian is an important limitation on the precision of coherent control in quantum information processing. Incoherence can typically be modeled as a distribution of unitary processes arising from slowly varying experimental parameters. We show how it introduces artifacts in quantum process tomography and we explain how the resulting estimate of the superoperator may not be completely positive.

NMR analog of the quantum disentanglement eraser.

We report the implementation of a three-spin quantum disentanglement eraser on a liquid-state NMR quantum information processor. A key feature of this experiment was its use of pulsed magnetic field gradients to mimic projective measurements. This ability is an important step towards the development of an experimentally controllable system which can simulate any quantum dynamics, both coherent and decoherent.

Construction and implementation of NMR quantum logic gates for two spin systems.

The implementation of small prototype quantum computers has been studied through ensemble quantum computing via NMR measurements. In such laboratory studies it is convenient to have access to a wide array of logic gates. Here a systematic approach to reduce the logic gate to an NMR pulse sequence is introduced.

Ensemble quantum computing by NMR spectroscopy.

A quantum computer (QC) can operate in parallel on all its possible inputs at once, but the amount of information that can be extracted from the result is limited by the phenomenon of wave function collapse. We present a new computational model, which differs from a QC only in that the result of a measurement is the expectation value of the observable, rather than a random eigenvalue thereof. Such an expectation value QC can solve nondeterministic polynomial-time complete problems in polynomial time.

A robust method for estimating cross-relaxation rates from simultaneous fits to build-up and decay curves.

This paper introduces a novel computational method for estimating relaxation rates among pairs of spin orders. This method simultaneously estimates all the auto- and cross-relaxation rates from the same measurements, and avoids the ill-conditioning problems associated with multiexponential fits. The method models the relaxation dynamics by a system of linear differential equations, and assumes that measurements of the spin orders have been made at an equally spaced sequence of time points.

An evaluation of least-squares fits to COSY spectra as a means of estimating proton-proton coupling constants. II. Applications to polypeptides.

A new computational method for simultaneously estimating all the proton-proton coupling constants in a molecule from COSY spectra [Yang, J.-X. and Havel, T.

An evaluation of least-squares fits to COSY spectra as a means of estimating proton-proton coupling constants. I. Simulated test problems.

A computational method is described that takes an initial estimate of the chemical shifts, line widths and scalar coupling constants for the protons in a molecule, and refines this estimate so as to improve the least-squares fit between an experimental COSY spectrum and the spectrum simulated from these parameters in the weak-coupling approximation. In order to evaluate the potential of such refinements for estimating these parameters from COSY experiments, the method has been applied to a large number of sample problems which were themselves simulated from standard conformations of the amino acids, along with 25 near-native conformations of the protein bovine pancreatic trypsin inhibitor. The results of this evaluation show that: (i) if the chemical shifts are known to within ca.

Does compactness induce secondary structure in proteins? A study of poly-alanine chains computed by distance geometry.

A few years ago, lattice model studies indicated that compactness could induce polymer chains to develop protein-like secondary structures. Subsequent off-lattice studies have found the amounts of induced structure to be relatively small. Here we use distance geometry to generate random conformations of compact poly-alanine chains of various chain lengths.

Matrix decompositions of two-dimensional nuclear magnetic resonance spectra.

Two-dimensional NMR spectra are rectangular arrays of real numbers, which are commonly regarded as digitized images to be analyzed visually. If one treats them instead as mathematical matrices, linear algebra techniques can also be used to extract valuable information from them. This matrix approach is greatly facilitated by means of a physically significant decomposition of these spectra into a product of matrices--namely, S = PAPT.

SESAME: a least-squares approach to the evaluation of protein structures computed from NMR data.

A method is proposed for defining a probability distribution on an ensemble of protein conformations from a 2D NOE spectrum, while at the same time back-calculating the experimental spectrum from the ensemble. This enables one to assess the relative quality and significance of the conformations, and to test the consistency of the ensemble as a whole with the experimental spectrum. The method eliminates the need to integrate the cross-peak intensities and is surprisingly insensitive to random noise in the spectrum.

The solution structure of eglin c based on measurements of many NOEs and coupling constants and its comparison with X-ray structures.

A high-precision solution structure of the elastase inhibitor eglin c was determined by NMR and distance geometry calculations. A large set of 947 nuclear Overhauser (NOE) distance constraints was identified, 417 of which were quantified from two-dimensional NOE spectra at short mixing times. In addition, a large number of homonuclear 1H-1H and heteronuclear 1H-15N vicinal coupling constants were used, and constraints on 42 chi 1 and 38 phi angles were obtained.

Alternating zinc fingers in the human male associated protein ZFY: 2D NMR structure of an even finger and implications for "jumping-linker" DNA recognition.

ZFY, a sex-related Zn-finger protein encoded by the human Y chromosome, is distinguished from the general class of Zn-finger proteins by the presence of a two-finger repeat. Whereas odd-numbered domains and linkers fit a general consensus, even-numbered domains and linkers exhibit systematic differences. Because this alternation may have fundamental implications for the mechanism of protein-DNA recognition, we have undertaken biochemical and structural studies of fragments of ZFY.

A new method for building protein conformations from sequence alignments with homologues of known structure.

We describe a largely automatic procedure for building protein structures from sequence alignments with homologues of known structure. This procedure uses simple rules by which multiple sequence alignments can be translated into distance and chirality constraints, which are then used as input for distance geometry calculations. By this means one obtains an ensemble of conformations for the unknown structure that are compatible with the rules employed, and the differences among these conformations provide an indication of the reliability of the structure prediction.

The sampling properties of some distance geometry algorithms applied to unconstrained polypeptide chains: a study of 1830 independently computed conformations.

In this paper we study the statistical geometry of ensembles of poly (L-alanine) conformations computed by several different distance geometry algorithms. Since basic theory only permits us to predict the statistical properties of such ensembles a priori when the distance constraints have a very simple form, the only constraints used for these calculations are those necessary to obtain reasonable bond lengths and angles, together with a lack of short- and long-range atomic overlaps. The geometric properties studied include the squared end-to-end distance and radius of gyration of the computed conformations, in addition to the usual rms coordinate and phi/psi angle deviations among these conformations.