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Abstract: The balance between excitatory glutamatergic projection neurons and inhibitory GABAergic interneurons determines the function of cortical microcircuits. How these neurotransmitters relate to the functional status of an entire macro-scale network remains unknown. The posteromedial cortex (PMC) is the default mode network (DMN) node with the greatest functional connectivity; therefore, we hypothesized that PMC glutamate and GABA predict intrinsic functional connectivity (iFC) across the entire DMN. In 20 healthy men, we combined J-resolved magnetic resonance spectroscopy to measure glutamate and GABA in the PMC and resting fMRI followed by group Independent Components Analysis to extract the entire DMN. We showed that, controlling for age and partial GM volume in the MRS voxel, PMC glutamate and GABA explained about half of the variance of DMN iFC (represented by the network''s beta coefficient for rest). Glutamate correlated positively and GABA correlated negatively with DMN iFC; in an alternative statistical model which included the glutamate/GABA ratio, the ratio correlated positively with DMN iFC. Age had no independent association with DMN iFC. No other network was associated with PMC glutamate or GABA. We conclude that regional neurotransmitter concentrations in a network node strongly predict network but not global brain iFC. [Copyright &y& Elsevier]

Abstract: MRI analysis of cartilage matrix may play an important role in early detection and development of therapeutic protocols for degenerative joint disease. Correlations between MRI parameters and matrix integrity have been established in many studies, but the substantial overlap in values observed for normal and for degraded cartilage greatly limits the specificity of these analyses. We implemented established multiparametric analysis methods to define data clusters corresponding to control and degraded bovine nasal cartilage in two-, three-, and four-dimensional parameter spaces, and applied these results to discriminant analysis of a validation data set. Analyses were performed using the parameters (T 1, T 2, k m, ADC), where k m is the magnetization transfer rate and ADC is the apparent diffusion coefficient. Results were compared to univariate analyses. Multiparametric k-means clustering led to no improvement over univariate analyses, with a maximum sensitivity and specificity in the range of 60–70% for the detection of degradation using T 1, and in the range of 80% sensitivity but only 36% specificity using the parameter pair (T 1, k m). In contrast, model-based analysis using more general Gaussian clusters resulted in markedly improved classification, with sensitivity and specificity reaching levels of 80–90% using the pair (T 1, k m). Finally, a fuzzy clustering technique was implemented which may be still more appropriate to the continuum of degradation seen in degenerative cartilage disease. In view of its success in identifying mild cartilage degradation, the formal multiparametric approach implemented here may be applicable to the nondestructive evaluation of other biomaterials using MRI. [Copyright &y& Elsevier]

Abstract: The advancement of spectroscopy methods attained through increases in sensitivity, and often with the coupling of complementary techniques, has enabled real-time structure and function measurements of single cells. The purpose of this review is to illustrate, in light of advances, the strengths and the weaknesses of these methods. Included also is an assessment of the impact of the experimental setup and conditions of each method on cellular function and integrity. A particular emphasis is placed on noninvasive and nondestructive techniques for achieving single cell detection, including nuclear magnetic resonance, in addition to physical, optical, and vibrational methods. [Copyright &y& Elsevier]

Highlights: [•] We propose a method of stabilizing the inverse Laplace transform of 1D multiexponential NMR signals. [•] We examine simulated and experimental multiexponential NMR relaxation datasets. [•] Our method is based on conventional 2D relaxometry followed by 1D projection. [•] We compare these projections with 1D results on an equal experimental time basis. [•] We find markedly improved stability, accuracy, and insensitivity to regularization. [Copyright &y& Elsevier]

Vascular impairment is closely related to increased mortality in chronic kidney disease (CKD). The objective of this study was to assess impairments in the regulation of peripheral microvascular perfusion in patients with CKD based on time-frequency spectral analysis of resting near-infrared spectroscopy (NIRS) signals. Total hemoglobin (tHb) concentration and tissue saturation index (TSI) signals were collected using NIRS for a continuous 5 mins at 10 Hz from the forearm of 55 participants (34 CKD including 5 with end-stage renal disease, and 21 age-matched control). Continuous wavelet transform-based spectral analysis was used to quantify the spectral amplitude within five pre-defined frequency intervals (I, 0.0095–0.021 Hz; II, 0.021–0.052 Hz; III, 0.052–0.145 Hz; IV, 0.145–0.6 Hz and V, 0.6–2.0 Hz), representing endothelial, neurogenic, myogenic, respiratory and heartbeat activity, respectively. CKD patients showed lower tHb average spectral amplitude within the neurogenic frequency interval compared with controls (p = 0.014), consistent with an increased sympathetic outflow observed in CKD. CKD patients also showed lower TSI average spectral amplitude within the endothelial frequency interval compared with controls (p = 0.046), consistent with a reduced endothelial function in CKD. These findings demonstrate the potential of wavelet analysis of NIRS to provide complementary information on peripheral microvascular regulation in CKD. • Wavelet analysis of resting NIRS in skeletal muscle quantifies diminished peripheral microvascular regulation in CKD. • Reduced tHb neurogenic spectral amplitude reflects increased sympathetic outflow and reduced neurovascular control in CKD. • Reduced endothelial spectral amplitude of tissue saturation in CKD is suggestive of impaired endothelial function. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI) measures are commonly used as imaging markers to investigate individual differences in relation to behavioral and health-related characteristics. However, the ability to detect reliable associations in cross-sectional or longitudinal studies is limited by the reliability of the diffusion measures. Several studies have examined the reliability of diffusion measures within (i.e. intra-site) and across (i.e. inter-site) scanners with mixed results. Our study compares the test–retest reliability of diffusion measures within and across scanners and field strengths in cognitively normal older adults with a follow-up interval less than 2.25 years. Intra-class correlation (ICC) and coefficient of variation (CoV) of fractional anisotropy (FA) and mean diffusivity (MD) were evaluated in sixteen white matter and twenty-six gray matter bilateral regions. The ICC for intra-site reliability (0.32 to 0.96 for FA and 0.18 to 0.95 for MD in white matter regions; 0.27 to 0.89 for MD and 0.03 to 0.79 for FA in gray matter regions) and inter-site reliability (0.28 to 0.95 for FA in white matter regions, 0.02 to 0.86 for MD in gray matter regions) with longer follow-up intervals were similar to earlier studies using shorter follow-up intervals. The reliability of across field strengths comparisons was lower than intra- and inter-site reliabilities. Within and across scanner comparisons showed that diffusion measures were more stable in larger white matter regions (> 1500 mm 3 ). For gray matter regions, the MD measure showed stability in specific regions and was not dependent on region size. Linear correction factor estimated from cross-sectional or longitudinal data improved the reliability across field strengths. Our findings indicate that investigations relating diffusion measures to external variables must consider variable reliability across the distinct regions of interest and that correction factors can be used to improve consistency of measurement across field strengths. An important result of this work is that inter-scanner and field strength effects can be partially mitigated with linear correction factors specific to regions of interest. These data-driven linear correction techniques can be applied in cross-sectional or longitudinal studies. [ABSTRACT FROM AUTHOR]

Abstract: We present a fractional-order extension of the Bloch equations to describe anomalous NMR relaxation phenomena (T 1 and T 2). The model has solutions in the form of Mittag–Leffler and stretched exponential functions that generalize conventional exponential relaxation. Such functions have been shown by others to be useful for describing dielectric and viscoelastic relaxation in complex, heterogeneous materials. Here, we apply these fractional-order T 1 and T 2 relaxation models to experiments performed at 9.4 and 11.7 Tesla on type I collagen gels, chondroitin sulfate mixtures, and to bovine nasal cartilage (BNC), a largely isotropic and homogeneous form of cartilage. The results show that the fractional-order analysis captures important features of NMR relaxation that are typically described by multi-exponential decay models. We find that the T 2 relaxation of BNC can be described in a unique way by a single fractional-order parameter (α), in contrast to the lack of uniqueness of multi-exponential fits in the realistic setting of a finite signal-to-noise ratio. No anomalous behavior of T 1 was observed in BNC. In the single-component gels, for T 2 measurements, increasing the concentration of the largest components of cartilage matrix, collagen and chondroitin sulfate, results in a decrease in α, reflecting a more restricted aqueous environment. The quality of the curve fits obtained using Mittag–Leffler and stretched exponential functions are in some cases superior to those obtained using mono- and bi-exponential models. In both gels and BNC, α appears to account for micro-structural complexity in the setting of an altered distribution of relaxation times. This work suggests the utility of fractional-order models to describe T 2 NMR relaxation processes in biological tissues. [Copyright &y& Elsevier]