Diffusion-sensitive magnetic resonance spectroscopy and imaging in biomedical sciences

We present a mini-review of the development and contemporary applications of diffusion-sensitive nuclear magnetic resonance (NMR) techniques in biomedical sciences. Molecular diffusion is a fundamental physical phenomenon present in all biological systems. Due to the connection between experimentally measured diffusion metrics and the microscopic environment sensed by the diffusing molecules, diffusion measurements can be used for characterisation of molecular size, molecular binding and association, and the morphology of biological tissues. The emergence of magnetic resonance was instrumental to the development of biomedical applications of diffusion. We discuss the fundamental physical principles of diffusion NMR spectroscopy and diffusion MR imaging. The emphasis is placed on conceptual understanding, historical evolution and practical applications rather than complex technical details. Mathematical description of diffusion is presented to the extent that it is required for the basic understanding of the concepts. We present a wide range of spectroscopic and imaging applications of diffusion magnetic resonance, including colloidal drug delivery vehicles; protein association; characterisation of cell morphology; neural fibre tractography; cardiac imaging; and the imaging of load-bearing connective tissues. This paper is intended as an accessible introduction into the exciting and growing field of diffusion magnetic resonance.

Dynamic contrast-enhanced magnetic resonance imaging as a biomarker for the pharmacological response of PTK787/ZK 222584, an inhibitor of the vascular endothelial growth factor receptor tyrosine kinases, in patients with advanced colorectal cancer and liver metastases: Results from two phase I studies

Purpose: PTK787/ZK 222584 (PTK/ZK), an orally active inhibitor of vascular endothelial growth factor (VEGF) receptor tyrosine kinases, inhibits VEGF-mediated angiogenesis. The pharmacodynamic effects of PTK/ZK were evaluated by assessing changes in contrast-enhancement parameters of metastatic liver lesions using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with advanced colorectal cancer treated in two ongoing, dose-escalating phase I studies. Patients and Methods: Twenty-six patients had DCE-MRI performed at baseline, day 2, and at the end of each 28-day cycle. Doses of oral PTK/ZK ranged from 50 to 2000 mg once daily. Tumor permeability and vascularity were assessed by calculating the bidirectional transfer constant (Ki). The percentage of baseline Ki (% of baseline Ki) at each time point was compared with pharmacokinetic and clinical end points. Results: A significant negative correlation exists between the % of baseline Ki and increase in PTK/ZK oral dose and plasma levels (P = .01 for oral dose; P = .0001 for area under the plasma concentration curve at day 2). Patients with a best response of stable disease had a significantly greater reduction in Ki at both day 2 and at the end of cycle 1 compared with progressors (mean difference in % of baseline Ki, 47%, P = .004%; and 51%, P = .006; respectively). The difference in % of baseline Ki remained statistically significant after adjusting for baseline WHO performance status. Conclusion: These findings should help to define a biologically active dose of PTK/ZK. These results suggest that DCE-MRI may be a useful biomarker for defining the pharmacological response and dose of angiogenesis inhibitiors, such as PTK/ZK, for further clinical development. © 2003 by American Society of Clinical Oncology.

Tailoring the resonance of bilayer graphene sheets by interlayer sp3 bonds

Graphene-based resonators are envisioned to build the ultimate limit of two-dimensional nanoelectromechanical system due to their ultrasensitive detection of mass, force, pressure and charge. However, such application has been greatly impeded by their extremely low quality factor. In the present work, we explore, using the large-scale molecular dynamics simulation, the possibility of tailoring the resonance properties of a bilayer graphene sheet (GS) with interlayer sp3 bonds. For the bilayer GS resonator with interlayer sp3 bonds, we discovered that the sp3 bonds can either degrade or enhance the resonance properties of the resonator depending on their density and location. It is found that the distribution of sp3 bonds only along the edges of either pristine or hydrogenated bilayer GS, leads to a greatly enhanced quality factor. A quality factor of ~1.18×105 is observed for a 3.07×15.31 nm2 bilayer GS resonator with sp3 bonds, which is more than 30 times larger comparing with that of a pristine bilayer GS. The present study demonstrates that the resonance properties of a bilayer GS resonator can be tuned by introducing sp3 bonds. This finding provides a useful guideline for the synthesis of the bilayer GS for its application as a resonator component.

Nonlinear container ship model for the study of parametric roll resonance

Parametric roll is a critical phenomenon for ships, whose onset may cause roll oscillations up to +-40 degrees, leading to very dangerous situations and possibly capsizing. Container ships have been shown to be particularly prone to parametric roll resonance when they are sailing in moderate to heavy head seas. A Matlab/Simulink parametric roll benchmark model for a large container ship has been implemented and validated against a wide set of experimental data. The model is a part of a Matlab/Simulink Toolbox (MSS, 2007). The benchmark implements a 3rd-order nonlinear model where the dynamics of roll is strongly coupled with the heave and pitch dynamics. The implemented model has shown good accuracy in predicting the container ship motions, both in the vertical plane and in the transversal one. Parametric roll has been reproduced for all the data sets in which it happened, and the model provides realistic results which are in good agreement with the model tank experiments.

Simultaneous magnetic resonance imaging and consolidation measurement of articular cartilage

Magnetic resonance imaging (MRI) offers the opportunity to study biological tissues and processes in a non-disruptive manner. The technique shows promise for the study of the load-bearing performance (consolidation) of articular cartilage and changes in articular cartilage accompanying osteoarthritis. Consolidation of articular cartilage involves the recording of two transient characteristics: the change over time of strain and the hydrostatic excess pore pressure (HEPP). MRI study of cartilage consolidation under mechanical load is limited by difficulties in measuring the HEPP in the presence of the strong magnetic fields associated with the MRI technique. Here we describe the use of MRI to image and characterize bovine articular cartilage deforming under load in an MRI compatible consolidometer while monitoring pressure with a Fabry-Perot interferometer-based fiber-optic pressure transducer.

Stabilization of parametric roll resonance with active u-tanks via Lyapunov control design

Parametric ship roll resonance is a phenomenon where a ship can rapidly develop high roll motion while sailing in longitudinal waves. This effect can be described mathematically by periodic changes of the parameters of the equations of motion, which lead to a bifurcation. In this paper, the control design of an active u-tank stabilizer is carried out using Lyapunov theory. A nonlinear backstepping controller is developed to provide global exponential stability of roll. An extension of commonly used u-tank models is presented to account for large roll angles, and the control design is tested via simulation on a high-fidelity model of a vessel under parametric roll resonance.

Resonance of graphene nanoribbons doped with nitrogen and boron : a molecular dynamics study

Based on its enticing properties, graphene has been envisioned with applications in the area of electronics, photonics, sensors, bioapplications and others. To facilitate various applications, doping has been frequently used to manipulate the properties of graphene. Despite a number of studies conducted on doped graphene regarding its electrical and chemical properties, the impact of doping on the mechanical properties of graphene has been rarely discussed. A systematic study of the vibrational properties of graphene doped with nitrogen and boron is performed by means of a molecular dynamics simulation. The influence from different density or species of dopants has been assessed. It is found that the impacts on the quality factor, Q, resulting from different densities of dopants vary greatly, while the influence on the resonance frequency is insignificant. The reduction of the resonance frequency caused by doping with boron only is larger than the reduction caused by doping with both boron and nitrogen. This study gives a fundamental understanding of the resonance of graphene with different dopants, which may benefit their application as resonators.

Tuneable resonance properties of graphene by nitrogen-dopant

Doping as one of the popular methods to manipulate the properties of nanomaterials has received extensive application in deriving different types of graphene derivates, while the understanding of the resonance properties of dopant graphene is still lacking in literature. Based on the large-scale molecular dynamics simulation, reactive empirical bond order potential, as well as the tersoff potential, the resonance properties of N-doped graphene were studied. The studied samples were established according to previous experiments with the N atom’s percentage ranging from 0.43%-2.98%, including three types of N dopant locations, i.e., graphitic N, pyrrolic N and pyridinic N. It is found that different percentages of N-dopant exert different influence to the resonance properties of the graphene, while the amount of N-dopant is not the only factor that determines its impact. For all the considered cases, a relative large percentage of N-dopant (2.98% graphitic N-dopant) is observed to introduce significant influence to the profile of the external energy, and thus lead to an extremely low Q-factor comparing with that of the pristine graphene. The most striking finding is that, the natural frequency of the defective graphene with N-dopant appears uniformly larger than that of the pristine defective graphene. While for the perfect graphene, the N-dopant shows less influence to its natural frequency. This study will enrich the current understanding of the influence of dopants on graphene, which will eventually shed lights on the design of different molecules-doped graphene sheet.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

Frequency-motivated observer design for the prediction of parametric roll resonance control applications in marine systems

This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

Functional magnetic resonance brain imaging of executive cognitive performance in young first-episode schizophrenia patients and age-matched long-term cannabis users

Converging evidence from epidemiological, clinical and neuropsychological research suggests a link between cannabis use and increased risk of psychosis. Long-term cannabis use has also been related to deficit-like “negative” symptoms and cognitive impairment that resemble some of the clinical and cognitive features of schizophrenia. The current functional brain imaging study investigated the impact of a history of heavy cannabis use on impaired executive function in first-episode schizophrenia patients. Whilst performing the Tower of London task in a magnetic resonance imaging scanner, event-related blood oxygenation level-dependent (BOLD) brain activation was compared between four age and gender-matched groups: 12 first-episode schizophrenia patients; 17 long-term cannabis users; seven cannabis using first-episode schizophrenia patients; and 17 healthy control subjects. BOLD activation was assessed as a function of increasing task difficulty within and between groups as well as the main effects of cannabis use and the diagnosis of schizophrenia. Cannabis users and non-drug using first-episode schizophrenia patients exhibited equivalently reduced dorsolateral prefrontal activation in response to task difficulty. A trend towards additional prefrontal and left superior parietal cortical activation deficits was observed in cannabis-using first-episode schizophrenia patients while a history of cannabis use accounted for increased activation in the visual cortex. Cannabis users and schizophrenia patients fail to adequately activate the dorsolateral prefrontal cortex, thus pointing to a common working memory impairment which is particularly evident in cannabis-using first-episode schizophrenia patients. A history of heavy cannabis use, on the other hand, accounted for increased primary visual processing, suggesting compensatory imagery processing of the task.

Potential-dependent surface-enhanced resonance raman spectroscopy at nanostructured TiO2 : A case study on cytochrome b5

Abstract: Nanostructured titanium dioxide (TiO2) electrodes, prepared by anodization of titanium, are employed to probe the electron-transfer process of cytochrome b5 (cyt b5) by surface-enhanced resonance Raman (SERR) spectroscopy. Concomitant with the increased nanoscopic surface roughness of TiO2, achieved by raising the anodization voltage from 10 to 20 V, the enhancement factor increases from 2.4 to 8.6, which is rationalized by calculations of the electric field enhancement. Cyt b 5 is immobilized on TiO2 under preservation of its native structure but it displays a non-ideal redox behavior due to the limited conductivity of the electrode material. The electron-transfer efficiency which depends on the crystalline phase of TiO2 has to be improved by appropriate doping for applications in bioelectrochemistry. Nanostructured TiO2 electrodes are employed to probe the electron-transfer process of cytochrome b5 by surface-enhanced resonance Raman spectroscopy. Concomitant with the increased nanoscopic surface roughness of TiO2, the enhancement factor increases, which can be attributed to the electric field enhancement. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Complementary surface-enhanced resonance raman spectroscopic biodetection of mixed protein solutions by chitosan- and silica-coated plasmon-tuned silver nanoparticles

Silver nanoparticles with identical plasmonic properties but different surface functionalities are synthesized and tested as chemically selective surface-enhanced resonance Raman (SERR) amplifiers in a two-component protein solution. The surface plasmon resonances of the particles are tuned to 413 nm to match the molecular resonance of protein heme cofactors. Biocompatible functionalization of the nanoparticles with a thin film of chitosan yields selective SERR enhancement of the anionic protein cytochrome b5, whereas functionalization with SiO2 amplifies only the spectra of the cationic protein cytochrome c. As a result, subsequent addition of the two differently functionalized particles yields complementary information on the same mixed protein sample solution. Finally, the applicability of chitosan-coated Ag nanoparticles for protein separation was tested by in situ resonance Raman spectroscopy.