SEISMICgraph: a web-based tool for RNA structure data visualization.

In recent years, RNA has been increasingly recognized for its essential roles in biology, functioning not only as a carrier of genetic information but also as a dynamic regulator of gene expression through its interactions with other RNAs, proteins, and itself. Advances in chemical probing techniques have significantly enhanced our ability to identify RNA secondary structures and understand their regulatory roles. These developments, alongside improvements in experimental design and data processing, have greatly increased the resolution and throughput of structural analyses. Here, we introduce SEISMICgraph, a web-based tool designed to support RNA structure research by offering data visualization and analysis capabilities for a variety of chemical probing modalities. SEISMICgraph enables simultaneous comparison of data across different sequences and experimental conditions through a user-friendly interface that requires no programming expertise. We demonstrate its utility by investigating known and putative riboswitches and exploring how RNA modifications influence their structure and binding. SEISMICgraph's ability to rapidly visualize adenine-dependent structural changes and assess the impact of pseudouridylation on these transitions provides novel insights and establishes a roadmap for numerous future applications.

Frequency-dependent diffusion kurtosis imaging in the human brain using an oscillating gradient spin echo sequence and a high-performance head-only gradient.

Measuring the time/frequency dependence of diffusion MRI is a promising approach to distinguish between the effects of different tissue microenvironments, such as membrane restriction, tissue heterogeneity, and compartmental water exchange. In this study, we measure the frequency dependence of diffusivity (D) and kurtosis (K) with oscillating gradient diffusion encoding waveforms and a diffusion kurtosis imaging (DKI) model in human brains using a high-performance, head-only MAGNUS gradient system, with a combination of b-values, oscillating frequencies (f), and echo time that has not been achieved in human studies before. Frequency dependence of diffusivity and kurtosis are observed in both global and local white matter (WM) and gray matter (GM) regions and characterized with a power-law model ∼Λ*fθ. The frequency dependences of diffusivity and kurtosis (including changes between fmin and fmax, Λ, and θ) vary over different WM and GM regions, indicating potential microstructural differences between regions. A trend of decreasing kurtosis over frequency in the short-time limit is successfully captured for in vivo human brains. The effects of gradient nonlinearity (GNL) on frequency-dependent diffusivity and kurtosis measurements are investigated and corrected. Our results show that the GNL has prominent scaling effects on the measured diffusivity values (3.5∼5.5% difference in the global WM and 6∼8% difference in the global cortex) and subsequently affects the corresponding power-law parameters (Λ, θ) while having a marginal influence on the measured kurtosis values (<0.05% difference) and power-law parameters (Λ, θ). This study expands previous OGSE studies and further demonstrates the translatability of frequency-dependent diffusivity and kurtosis measurements to human brains, which may provide new opportunities to probe human brain microstructure in health and disease.

Multi-shot diffusion-weighted MRI reconstruction with magnitude-based spatial-angular locally low-rank regularization (SPA-LLR).

PURPOSE: To resolve the motion-induced phase variations in multi-shot multi-direction diffusion-weighted imaging (DWI) by applying regularization to magnitude images. THEORY AND METHODS: A nonlinear model was developed to estimate phase and magnitude images separately. A locally low-rank regularization (LLR) term was applied to the magnitude images from all diffusion-encoding directions to exploit the spatial and angular correlation. In vivo experiments with different resolutions and b-values were performed to validate the proposed method. RESULTS: The proposed method significantly reduces the noise level compared to the conventional reconstruction method and achieves submillimeter (0.8mm and 0.9mm isotropic resolutions) DWI with a b-value of 1,000  s/mm2 and 1-mm isotropic DWI with a b-value of 2,000  s/mm2 without modification of the sequence. CONCLUSIONS: A joint reconstruction method with spatial-angular LLR regularization on magnitude images substantially improves multi-direction DWI reconstruction, simultaneously removes motion-induced phase artifacts, and denoises images.

Multimodal characterization of the human nucleus accumbens.

Dysregulation of the nucleus accumbens (NAc) is implicated in numerous neuropsychiatric disorders. Treatments targeting this area directly (e.g. deep brain stimulation) demonstrate variable efficacy, perhaps owing to non-specific targeting of a functionally heterogeneous nucleus. Here we provide support for this notion, first observing disparate behavioral effects in response to direct simulation of different locations within the NAc in a human patient. These observations motivate a segmentation of the NAc into subregions, which we produce from a diffusion-tractography based analysis of 245 young, unrelated healthy subjects. We further explore the mechanism of these stimulation-induced behavioral responses by identifying the most probable subset of axons activated using a patient-specific computational model. We validate our diffusion-based segmentation using evidence from several modalities, including MRI-based measures of function and microstructure, human post-mortem immunohistochemical staining, and cross-species comparison of cortical-NAc projections that are known to be conserved. Finally, we visualize the passage of individual axon bundles through one NAc subregion in a post-mortem human sample using CLARITY 3D histology corroborated by 7T tractography. Collectively, these findings extensively characterize human NAc subregions and provide insight into their structural and functional distinctions with implications for stereotactic treatments targeting this region.

Generalized diffusion spectrum magnetic resonance imaging (GDSI) for model-free reconstruction of the ensemble average propagator.

Diffusion spectrum MRI (DSI) provides model-free estimation of the diffusion ensemble average propagator (EAP) and orientation distribution function (ODF) but requires the diffusion data to be acquired on a Cartesian q-space grid. Multi-shell diffusion acquisitions are more flexible and more commonly acquired but have, thus far, only been compatible with model-based analysis methods. Here, we propose a generalized DSI (GDSI) framework to recover the EAP from multi-shell diffusion MRI data. The proposed GDSI approach corrects for q-space sampling density non-uniformity using a fast geometrical approach. The EAP is directly calculated in a preferable coordinate system by multiplying the sampling density corrected q-space signals by a discrete Fourier transform matrix, without any need for gridding. The EAP is demonstrated as a way to map diffusion patterns in brain regions such as the thalamus, cortex and brainstem where the tissue microstructure is not as well characterized as in white matter. Scalar metrics such as the zero displacement probability and displacement distances at different fractions of the zero displacement probability were computed from the recovered EAP to characterize the diffusion pattern within each voxel. The probability averaged across directions at a specific displacement distance provides a diffusion property based image contrast that clearly differentiates tissue types. The displacement distance at the first zero crossing of the EAP averaged across directions orthogonal to the primary fiber orientation in the corpus callosum is found to be larger in the body (5.65 ±â€¯0.09 µm) than in the genu (5.55 ±â€¯0.15 µm) and splenium (5.4 ±â€¯0.15 µm) of the corpus callosum, which corresponds well to prior histological studies. The EAP also provides model-free representations of angular structure such as the diffusion ODF, which allows estimation and comparison of fiber orientations from both the model-free and model-based methods on the same multi-shell data. For the model-free methods, detection of crossing fibers is found to be strongly dependent on the maximum b-value and less sensitive compared to the model-based methods. In conclusion, our study provides a generalized DSI approach that allows flexible reconstruction of the diffusion EAP and ODF from multi-shell diffusion data and data acquired with other sampling patterns.

Eddy current nulled constrained optimization of isotropic diffusion encoding gradient waveforms.

PURPOSE: Isotropic diffusion encoding efficiently encodes additional microstructural information in combination with conventional linear diffusion encoding. However, the gradient-intensive isotropic diffusion waveforms generate significant eddy currents, which cause image distortions. The purpose of this study is to present a method for designing isotropic diffusion encoding waveforms with intrinsic eddy current nulling. METHODS: Eddy current nulled gradient waveforms were designed using a constrained optimization waveform for a 3T GE Premier MRI system. Encoding waveforms were designed for a variety of eddy current null times and sequence timings to evaluate the achievable b-value. Waveforms were also tested with both eddy current nulling and concomitant field compensation. Distortion reduction was tested in both phantoms and the in vivo human brain. RESULTS: The feasibility of isotropic diffusion encoding with intrinsic correction of eddy current distortion and signal bias from concomitant fields was demonstrated. The constrained optimization algorithm produced gradient waveforms with the specified eddy current null times. The reduction in the achievable diffusion weighting was dependent on the number of eddy current null times. A reduction in the eddy current-induced image distortions was observed in both phantoms and in vivo human subjects. CONCLUSION: The proposed framework allows the design of isotropic diffusion-encoding sequences with reduced image distortion.

Double diffusion encoding MRI for the clinic.

PURPOSE: The purpose of this study is to develop double diffusion encoding (DDE) MRI methods for clinical use. Microscopic diffusion anisotropy measurements from DDE promise greater specificity to changes in tissue microstructure compared with conventional diffusion tensor imaging, but implementation of DDE sequences on whole-body MRI scanners is challenging because of the limited gradient strengths and lengthy acquisition times. METHODS: A custom single-refocused DDE sequence was implemented on a 3T whole-body scanner. The DDE gradient orientation scheme and sequence parameters were optimized based on a Gaussian diffusion assumption. Using an optimized 5-min DDE acquisition, microscopic fractional anisotropy (µFA) maps were acquired for the first time in multiple sclerosis patients. RESULTS: Based on simulations and in vivo human measurements, six parallel and six orthogonal diffusion gradient pairs were found to be the minimum number of diffusion gradient pairs necessary to produce a rotationally invariant measurement of µFA. Simulations showed that optimal precision and accuracy of µFA measurements were obtained using b-values between 1500 and 3000 s/mm2 . The µFA maps showed improved delineation of multiple sclerosis lesions compared with conventional fractional anisotropy and distinct contrast from T2 -weighted fluid attenuated inversion recovery and T1 -weighted imaging. CONCLUSION: The µFA maps can be measured using DDE in a clinical setting and may provide new opportunities for characterizing multiple sclerosis lesions and other types of tissue degeneration. Magn Reson Med 80:507-520, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Iron is a sensitive biomarker for inflammation in multiple sclerosis lesions.

MRI phase imaging in multiple sclerosis (MS) patients and in autopsy tissue have demonstrated the presence of iron depositions in white matter lesions. The accumulation of iron in some but not all lesions suggests a specific, potentially disease-relevant process, however; its pathophysiological significance remains unknown. Here, we explore the role of lesional iron in multiple sclerosis using multiple approaches: immunohistochemical examination of autoptic MS tissue, an in vitro model of iron-uptake in human cultured macrophages and ultra-highfield phase imaging of highly active and of secondary progressive MS patients. Using Perls' stain and immunohistochemistry, iron was detected in MS tissue sections predominantly in non-phagocytosing macrophages/microglia at the edge of established, demyelinated lesions. Moreover, iron-containing macrophages but not myelin-laden macrophages expressed markers of proinflammatory (M1) polarization. Similarly, in human macrophage cultures, iron was preferentially taken up by non-phagocytosing, M1-polarized macrophages and induced M1 (super) polarization. Iron uptake was minimal in myelin-laden macrophages and active myelin phagocytosis led to depletion of intracellular iron. Finally, we demonstrated in MS patients using GRE phase imaging with ultra-highfield MRI that phase hypointense lesions were significantly more prevalent in patients with active relapsing than with secondary progressive MS. Taken together, our data provide a basis to interpret iron-sensitive GRE phase imaging in MS patients: iron is present in non-phagocytosing, M1-polarized microglia/macrophages at the rim of chronic active white matter demyelinating lesions. Phase imaging may therefore visualize specific, chronic proinflammatory activity in established MS lesions and thus provide important clinical information on disease status and treatment efficacy in MS patients.