Parameterization of metabolite and macromolecule contributions in interrelated MR spectra of human brain using multidimensional modeling.

Macromolecular signals are crucial constituents of short echo-time H MR spectra with potential clinical implications in themselves as well as essential ramifications for the quantification of the usually targeted metabolites. Their parameterization, needed for general fitting models, is difficult because of their unknown composition. Here, a macromolecular signal parameterization together with metabolite signal quantification including relaxation properties is investigated by multidimensional modeling of interrelated 2DJ inversion-recovery (2DJ-IR) datasets.

Fitting interrelated datasets: metabolite diffusion and general lineshapes.

Objective: Simultaneous modeling of true 2-D spectroscopy data, or more generally, interrelated spectral datasets has been described previously and is useful for quantitative magnetic resonance spectroscopy applications. In this study, a combined method of reference-lineshape enhanced model fitting and two-dimensional prior-knowledge fitting for the case of diffusion weighted MR spectroscopy is presented.

Materials And Methods: Time-dependent field distortions determined from a water reference are applied to the spectral bases used in linear-combination modeling of interrelated spectra.

Influence of muscle fiber orientation on water and metabolite relaxation times, magnetization transfer, and visibility in human skeletal muscle.

Purpose: To gain a deeper understanding of the influence of skeletal muscle fiber orientation on metabolite visibility, magnetization transfer from water, and water proton relaxation rates in (1)H MR spectra.

Methods: Non-water-suppressed MR spectroscopy was performed in tibialis anterior muscle (TA) of 10 healthy adults, with the TA oriented either parallel or at the magic angle to the 3T field. Spectra were acquired with metabolite-cycled PRESS, and water inversion from 50 to 2510 ms before excitation.

Effects of beta-alanine supplementation and interval training on physiological determinants of severe exercise performance.

Introduction: We aimed to manipulate physiological determinants of severe exercise performance. We hypothesized that (1) beta-alanine supplementation would increase intramuscular carnosine and buffering capacity and dampen acidosis during severe cycling, (2) that high-intensity interval training (HIT) would enhance aerobic energy contribution during severe cycling, and (3) that HIT preceded by beta-alanine supplementation would have greater benefits.

Methods: Sixteen active men performed incremental cycling tests and 90-s severe (110 % peak power) cycling tests at three time points: before and after oral supplementation with either beta-alanine or placebo, and after an 11-days HIT block (9 sessions, 4 × 4 min), which followed supplementation.

On the use of Cramér-Rao minimum variance bounds for the design of magnetic resonance spectroscopy experiments.

Localized Magnetic Resonance Spectroscopy (MRS) is in widespread use for clinical brain research. Standard acquisition sequences to obtain one-dimensional spectra suffer from substantial overlap of spectral contributions from many metabolites. Therefore, specially tuned editing sequences or two-dimensional acquisition schemes are applied to extend the information content.

Two-dimensional linear-combination model fitting of magnetic resonance spectra to define the macromolecule baseline using FiTAID, a Fitting Tool for Arrays of Interrelated Datasets.

Object: To propose the determination of the macromolecular baseline (MMBL) in clinical 1H MR spectra based on T(1) and T(2) differentiation using 2D fitting in FiTAID, a general Fitting Tool for Arrays of Interrelated Datasets.

Materials And Methods: Series of localized inversion-recovery (IR) and 2DJ separation spectra of the brain were recorded at 3T. The MMBL was determined by three 2D evaluation methods based on (1) IR spectra only, (2) 2DJ spectra only, (3) both IR and 2DJ spectra (2DJ-IR).

Disulfide bond shuffling in bovine alpha-lactalbumin: MD simulation confirms experiment.

A simple and straightforward classical molecular dynamics simulation technique is proposed to predict possible disulfide bridge shuffling. Application to bovine alpha-lactalbumin shows that shuffling can be observed on short simulation time scales and yields results in agreement with experiment.