In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω $$ \omega $$ , in addition to the diffusion tensor, D $$ \mathbf{D} $$ , and relaxation, R 1 $$ {R}_1 $$ , R 2 $$ {R}_2 $$ , correlations. A D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI.

OBJECTIVE: To assess the performance of hybrid multi-dimensional magnetic resonance imaging (HM-MRI) in quantifying hematoxylin and eosin (H&E) staining results, grading and predicting isocitrate dehydrogenase (IDH) mutation status of gliomas. MATERIALS AND METHODS: Included were 71 glioma patients (mean age, 50.17 ± 13.38 years; 35 men). HM-MRI images were collected at five different echo times (80-200 ms) with seven b-values (0-3000 s/mm2). A modified three-compartment model with very-slow, slow and fast diffusion components was applied to calculate HM-MRI metrics, including fractions, diffusion coefficients and T2 values of each component. Pearson correlation analysis was performed between HM-MRI derived fractions and H&E staining derived percentages. HM-MRI metrics were compared between high-grade and low-grade gliomas, and between IDH-wild and IDH-mutant gliomas. Using receiver operational characteristic (ROC) analysis, the diagnostic performance of HM-MRI in grading and genotyping was compared with mono-exponential models. RESULTS: HM-MRI metrics FDvery-slow and FDslow demonstrated a significant correlation with the H&E staining results (p < .05). Besides, FDvery-slow showed the highest area under ROC curve (AUC = 0.854) for grading, while Dslow showed the highest AUC (0.845) for genotyping. Furthermore, a combination of HM-MRI metrics FDvery-slow and T2Dslow improved the diagnostic performance for grading (AUC = 0.876). DISCUSSION: HM-MRI can aid in non-invasive diagnosis of gliomas.

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω, in addition to the diffusion tensor, D, and relaxation, R1, R2, correlations. A D(ω)-R1-R2 clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D(ω)-R1-R2 distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

Multidimensional encoding of restricted and anisotropic diffusion by double rotation of the q vector.

Diffusion NMR and MRI methods building on the classic pulsed gradient spin-echo sequence are sensitive to many aspects of translational motion, including time and frequency dependence ("restriction"), anisotropy, and flow, leading to ambiguities when interpreting experimental data from complex heterogeneous materials such as living biological tissues. While the oscillating gradient technique specifically targets frequency dependence and permits control of the sensitivity to flow, tensor-valued encoding enables investigations of anisotropy in orientationally disordered materials. Here, we propose a simple scheme derived from the "double-rotation" technique in solid-state NMR to generate a family of modulated gradient waveforms allowing for comprehensive exploration of the 2D frequency-anisotropy space and convenient investigation of both restricted and anisotropic diffusion with a single multidimensional acquisition protocol, thereby combining the desirable characteristics of the oscillating gradient and tensor-valued encoding techniques. The method is demonstrated by measuring multicomponent isotropic Gaussian diffusion in simple liquids, anisotropic Gaussian diffusion in a polydomain lyotropic liquid crystal, and restricted diffusion in a yeast cell sediment.

Molecular Mobility in Keratin-Rich Materials Monitored by Nuclear Magnetic Resonance: A Tool for the Evaluation of Structure-Giving Properties.

Keratins are structural proteins that are abundant in human skin, nails, and hair, where they provide mechanical strength. In the present study, we investigate the molecular mobilities and structures of three keratin-rich materials with clearly different mechanical properties: nails, stratum corneum (upper layer of epidermis), and keratinocytes (from lower layer of epidermis). We use solid-state NMR on natural-abundance 13C to characterize small changes in molecular dynamics in these biological materials with close to atomistic resolution. One strong advantage of this method is that it detects small fractions of mobile components in a molecularly complex material while it simultaneously gives information on the rigid components in the very same sample. The molecular mobility can be linked to mechanical material properties in different conditions, including hydration or exposure to osmolytes or organic solvents. Importantly, the study revealed that the response to both hydration and addition of urea is clearly different for the nail keratin compared to the stratum corneum keratin. The comparative examination of these materials may provide a better understanding of skin diseases originating from keratin malfunction and contributes to the design and development of new materials.

Solubility of Foreign Molecules in Stratum Corneum Brick and Mortar Structure.

The barrier function of the skin is mainly assured by its outermost layer, stratum corneum (SC). One key aspect in predicting dermal drug delivery and in safety assessment of skin exposure to chemicals is the need to determine the amount of chemical that is taken up into the SC. We here present a strategy that allows for direct measures of the amount of various solid chemicals that can be dissolved in the SC in any environmental relative humidity (RH). A main advantage of the presented method is that it distinguishes between molecules that are dissolved within the SC and molecules that are not dissolved but might be present at, for example, the skin surface. In addition, the method allows for studies of uptake of hydrophobic chemicals without the need to use organic solvents. The strategy relies on the differences in the molecular properties of the added molecules in the dissolved and the excess states, employing detection methods that act as a dynamic filter to spot only one of the fractions, either the dissolved molecules or the excess solid molecules. By measuring the solubility in SC and delipidized SC at the same RHs, the same method can be used to estimate the distribution of the added chemical between the extracellular lipids and corneocytes at different hydration conditions. The solubility in porcine SC is shown to vary with hydration, which has implications for the molecular uptake and transport across the skin. The findings highlight the importance of assessing the chemical uptake at hydration conditions relevant to the specific applications. The methodology presented in this study can also be generalized to study the solubility and partitioning of chemicals in other heterogeneous materials with complex composition and structure.

Ganglioside GM3 stimulates lipid-protein co-assembly in α-synuclein amyloid formation.

Parkinson's disease is characterized by the aggregation of the presynaptic protein α-synuclein (αSyn), and its co-assembly with lipids and other cellular matter in the brain. Here we investigated lipid-protein co-assembly in a system composed of αSyn and model membranes containing the glycolipid ganglioside GM3. We quantified the uptake of lipids into the co-assembled aggregates and investigated how lipid molecular dynamics is altered by being present in the co-assemblies using solution 1H- and solid-state 13C NMR spectroscopy. Aggregate morphology was studied using cryo-TEM. The overall lipid uptake in the co-assembled aggregates was found to increase with the molar ratio of GM3 in the vesicles. The lipids present in the co-assembled aggregates have reduced acyl chain and headgroup dynamics compared to the protein-free bilayer system. These findings may improve our understanding of how different types of lipids can influence the composition of αSyn aggregates, which may have consequences for amyloid formation in vivo.

Molecular dynamics simulations and solid-state nuclear magnetic resonance spectroscopy measurements of C-H bond order parameters and effective correlation times in a POPC-GM3 bilayer.

Glycolipids such as gangliosides affect the properties of lipid membranes and in extension the interactions between membranes and other biomolecules like proteins. To better understand how the properties of individual lipid molecules can contribute to shape the functional aspects of a membrane, the spatial restriction and dynamics of C-H bond segments can be measured using nuclear magnetic resonance (NMR) spectroscopy. We combine solid-state NMR spectroscopy with all-atom molecular dynamics (MD) simulations to investigate how ganglioside GM3 affects the bilayer structure and dynamics of C-H bond segments. These two methods yield reorientational correlation functions, molecular profiles of C-H bond order parameters |SCH| and effective correlation times τe, which we compare for lipids in POPC bilayers with and without 30 mol% GM3. Our results revealed that all C-H segments of POPC reorient slower in the presence of GM3 and that the defining features of the GM3-POPC bilayer lie in the GM3 headgroup; it gives the bilayer an extended headgroup layer with high order (|SCH| up to 0.3-0.4) and slow dynamics (τe up to 100 ns), a character that may be mechanistically important in ganglioside interactions with other biomolecules.

Nonparametric 5D D-R2 distribution imaging with single-shot EPI at 21.1 T: Initial results for in vivo rat brain.

In vivo human diffusion MRI is by default performed using single-shot EPI with greater than 50-ms echo times and associated signal loss from transverse relaxation. The individual benefits of the current trends of increasing B0 to boost SNR and employing more advanced signal preparation schemes to improve the specificity for selected microstructural properties eventually may be cancelled by increased relaxation rates at high B0 and echo times with advanced encoding. Here, initial attempts to translate state-of-the-art diffusion-relaxation correlation methods from 3 T to 21.1 T are made to identify hurdles that need to be overcome to fulfill the promises of both high SNR and readily interpretable microstructural information.

In situ 13 C solid-state polarization transfer NMR to follow starch transformations in food.

Convenience food products tend to alter their quality and texture while stored. Texture-giving food components are often starch-rich ingredients, such as pasta or rice. Starch transforms depending on time, temperature and water content, which alters the properties of products. Monitoring these transformations, which are associated with a change in mobility of the starch chain segments, could optimize the quality of food products containing multiple ingredients. In order to do so, we applied a simple and efficient in situ 13 C solid-state magic angle spinning (MAS) NMR approach, based on two different polarization transfer schemes, cross polarization (CP) and insensitive nuclei enhanced by polarization transfer (INEPT). The efficiency of the CP and INEPT transfer depends strongly on the mobility of chain segments-the time scale of reorientation of the CH-bond and the order parameter. Rigid crystalline or amorphous starch chains give rise to CP peaks, whereas mobile gelatinized starch chains appear as INEPT peaks. Comparing 13 C solid-state MAS NMR experiments based on CP and INEPT allows insight into the progress of gelatinization, and other starch transformations, by reporting on both rigid and mobile starch chains simultaneously with atomic resolution by the 13 C chemical shift. In conjunction with 1 H solid-state MAS NMR, complementary information about other food components present at low concentration, such as lipids and protein, can be obtained. We demonstrate our approach on starch-based products and commercial pasta as a function of temperature and storage.

Nonparametric D-R1-R2 distribution MRI of the living human brain.

Diffusion-relaxation correlation NMR can simultaneously characterize both the microstructure and the local chemical composition of complex samples that contain multiple populations of water. Recent developments on tensor-valued diffusion encoding and Monte Carlo inversion algorithms have made it possible to transfer diffusion-relaxation correlation NMR from small-bore scanners to clinical MRI systems. Initial studies on clinical MRI systems employed 5D D-R1 and D-R2 correlation to characterize healthy brain in vivo. However, these methods are subject to an inherent bias that originates from not including R2 or R1 in the analysis, respectively. This drawback can be remedied by extending the concept to 6D D-R1-R2 correlation. In this work, we present a sparse acquisition protocol that records all data necessary for in vivo 6D D-R1-R2 correlation MRI across 633 individual measurements within 25 min-a time frame comparable to previous lower-dimensional acquisition protocols. The data were processed with a Monte Carlo inversion algorithm to obtain nonparametric 6D D-R1-R2 distributions. We validated the reproducibility of the method in repeated measurements of healthy volunteers. For a post-therapy glioblastoma case featuring cysts, edema, and partially necrotic remains of tumor, we present representative single-voxel 6D distributions, parameter maps, and artificial contrasts over a wide range of diffusion-, R1-, and R2-weightings based on the rich information contained in the D-R1-R2 distributions.

Mucoadhesion: mucin-polymer molecular interactions.

Mucoadhesion, adhesion of a material to a mucous membrane or a mucus-covered surface, has been employed in drug delivery to prolong contact with adsorption sites and consequently a likely improvement of drug absorption. Mucoadhesion in the oral cavity also provides additional effects on tactile mouthfeel and extended flavor delivery, which impact consumer perception. The mechanisms behind mucoadhesion have not been well understood and there are contradictory literature results on the ranking of mucoadhesive properties of different polymers based on what in-vitro methods that are used. We herein examine the molecular interactions of different polymers with mucin from bovine submaxillary glands at pH 6.6 by using 1H NMR (Nuclear Magnetic Resonance) that provides atomically resolved information on conformational mobility of the mucin. Studying different types of polymers with different chemical structures and degrees of polymerization (DP), we can via the NMR linewidths and the signal intensities distinguish if the polymers interact with specific segments of the mucin or if they have a universal effect on the mobility of all the molecular segments of the mucin. The specific interaction sites on the mucin for positively charged polymer poly(ethyleneimine) are shown to be different from those for negatively and neutrally charged polymers. In addition, the interactions are also driven by the DP, the concentration of the polymers, and the dehydration. Deepened understanding of molecular effects of the different polymers on the mucin can therefore have strong impact on the development of mucoadhesive products in pharmaceutical and food applications. Finally, we raise awareness of the interpretation of rheological data in terms of mucoadhesion.

Molecular Assembly in Block Copolymer-Surfactant Nanoparticle Dispersions: Information on Molecular Exchange and Apparent Solubility from High-Resolution and PFG NMR.

Internally structured block copolymer-surfactant particles are formed when the complex salts of ionic-neutral block copolymers neutralized by surfactant counterions are dispersed in aqueous media. Here, we report the 1H NMR signal intensities and self-diffusion coefficients (D, from pulsed field gradient nuclear magnetic resonance, PFG NMR) of trimethyl alkylammonium surfactant ions and the poly(acrylamide)-block-poly(acrylate) (PAAm-b-PA) polyions forming such particles. The results reveal the presence of an "NMR-invisible" (slowly exchanging) fraction of aggregated surfactant ions in the particle core and an "NMR-visible" fraction consisting of surface surfactant ions in rapid exchange with the surfactant ions dissociated into the aqueous domain. They also confirm that the neutral PAAm blocks are exposed to water at the particle surface, while the PA blocks are buried in the particle core. The self-diffusion of the polyions closely agree with the self-diffusion of a hydrophobic probe molecule solubilized in the particles, showing that essentially all copolymer chains are incorporated in the aggregates. Through centrifugation, we prepared macroscopically phase-separated systems with a phase concentrated in particles separated from a clear dilute phase. D values for the surfactant and block copolymer indicated that the dilute phase contained small aggregates (ca. 5 nm) of surfactant ions and a few anionic-neutral block copolymer chains. Regardless of the overall concentration of the sample, the fraction of block copolymer found in the dilute phase was nearly constant. This indicates that the dilute fraction represented a tail of small particles created by the dispersion process rather than a true thermodynamic solubility of the complex salts.

Extraction of natural moisturizing factor from the stratum corneum and its implication on skin molecular mobility.

The natural moisturizing factor (NMF) is a mixture of small water-soluble compounds present in the upper layer of the skin, stratum corneum (SC). Soaking of SC in water leads to extraction of the NMF molecules, which may influence the SC molecular properties and lead to brittle and dry skin. In this study, we investigate how the molecular dynamics in SC lipid and protein components are affected by the removal of the NMF compounds. We then explore whether the changes in SC components caused by NMF removal can be reversed by a subsequent addition of one single NMF component: urea, pyrrolidone carboxylic acid (PCA) or potassium lactate. Samples of intact SC were investigated using NMR, X-ray diffraction, infrared spectroscopy and sorption microbalance. It is shown that the removal of NMF leads to reduced molecular mobility in keratin filaments and SC lipids compared to untreated SC. When the complex NMF mixture is replaced by one single NMF component, the molecular mobility in both keratin filaments and lipids is regained. From this we propose a general relation between the molecular mobility in SC and the amount of polar solutes which does not appear specific to the precise chemical identify of the NMF compounds.

Skin hydration as a tool to control the distribution and molecular effects of intermediate polarity compounds in intact stratum corneum.

The barrier function of the skin is mainly assured by its outermost layer, stratum corneum (SC), which consists of dead keratin-filled cells embedded in a lipid matrix. The skin is daily exposed to an environment with changing conditions in terms of hydration and different chemicals. Here we investigate how a molecule that has reasonable solubility in both hydrophobic and hydrophilic environments can be directed to certain regions in SC by changing the skin hydration. We use 1,2,3-trimethoxy propane (TMP) as a model substance and solid-state NMR on natural abundance 13C to obtain atomically resolved information on the molecular dynamics of TMP as well as SC lipid and protein components at varying hydration conditions. Upon dehydration, TMP redistributes from the hydrophilic corneocytes to the hydrophobic SC lipid regions. In this way, TMP can act to prevent the fluid-solid lipid transition in drying conditions and be present in the corneocytes in more humid conditions. Hydration can thereby be used as a switch to control the location and action of TMP or similar compounds in complex materials like SC. The general principles described here can also have impact on other applications including lipid-based formulations in food, drug delivery and cosmetics.

Glioma grading, molecular feature classification, and microstructural characterization using MR diffusional variance decomposition (DIVIDE) imaging.

OBJECTIVE: To evaluate the potential of diffusional variance decomposition (DIVIDE) for grading, molecular feature classification, and microstructural characterization of gliomas. MATERIALS AND METHODS: Participants with suspected gliomas underwent DIVIDE imaging, yielding parameter maps of fractional anisotropy (FA), mean diffusivity (MD), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), total mean kurtosis (MKT), MKA/MKT, and microscopic fractional anisotropy (µFA). Tumor type and grade, isocitrate dehydrogenase (IDH) 1/2 mutant status, and the Ki-67 labeling index (Ki-67 LI) were determined after surgery. Statistical analysis included 33 high-grade gliomas (HGG) and 17 low-grade gliomas (LGG). Tumor diffusion metrics were compared between HGG and LGG, among grades, and between wild and mutated IDH types using appropriate tests according to normality assessment results. Receiver operating characteristic and Spearman correlation analysis were also used for statistical evaluations. RESULTS: FA, MD, MKA, MKI, MKT, µFA, and MKA/MKT differed between HGG and LGG (FA: p = 0.047; MD: p = 0.037, others p < 0.001), and among glioma grade II, III, and IV (FA: p = 0.048; MD: p = 0.038, others p < 0.001). All diffusion metrics differed between wild-type and mutated IDH tumors (MKI: p = 0.003; others: p < 0.001). The metrics that best discriminated between HGG and LGGs and between wild-type and mutated IDH tumors were MKT and FA respectively (area under the curve 0.866 and 0.881). All diffusion metrics except FA showed significant correlation with Ki-67 LI, and MKI had the highest correlation coefficient (rs = 0.618). CONCLUSION: DIVIDE is a promising technique for glioma characterization and diagnosis. KEY POINTS: • DIVIDE metrics MKI is related to cell density heterogeneity while MKA and µFA are related to cell eccentricity. • DIVIDE metrics can effectively differentiate LGG from HGG and IDH mutation from wild-type tumor, and showed significant correlation with the Ki-67 labeling index. • MKI was larger than MKA which indicates predominant cell density heterogeneity in gliomas. • MKA and MKI increased with grade or degree of malignancy, however with a relatively larger increase in the cell eccentricity metric MKA in relation to the cell density heterogeneity metric MKI.

Multidimensional Diffusion Magnetic Resonance Imaging for Characterization of Tissue Microstructure in Breast Cancer Patients: A Prospective Pilot Study.

Diffusion-weighted imaging is a non-invasive functional imaging modality for breast tumor characterization through apparent diffusion coefficients. Yet, it has so far been unable to intuitively inform on tissue microstructure. In this IRB-approved prospective study, we applied novel multidimensional diffusion (MDD) encoding across 16 patients with suspected breast cancer to evaluate its potential for tissue characterization in the clinical setting. Data acquired via custom MDD sequences was processed using an algorithm estimating non-parametric diffusion tensor distributions. The statistical descriptors of these distributions allow us to quantify tissue composition in terms of metrics informing on cell densities, shapes, and orientations. Additionally, signal fractions from specific cell types, such as elongated cells (bin1), isotropic cells (bin2), and free water (bin3), were teased apart. Histogram analysis in cancers and healthy breast tissue showed that cancers exhibited lower mean values of "size" (1.43 ± 0.54 × 10-3 mm2/s) and higher mean values of "shape" (0.47 ± 0.15) corresponding to bin1, while FGT (fibroglandular breast tissue) presented higher mean values of "size" (2.33 ± 0.22 × 10-3 mm2/s) and lower mean values of "shape" (0.27 ± 0.11) corresponding to bin3 (p < 0.001). Invasive carcinomas showed significant differences in mean signal fractions from bin1 (0.64 ± 0.13 vs. 0.4 ± 0.25) and bin3 (0.18 ± 0.08 vs. 0.42 ± 0.21) compared to ductal carcinomas in situ (DCIS) and invasive carcinomas with associated DCIS (p = 0.03). MDD enabled qualitative and quantitative evaluation of the composition of breast cancers and healthy glands.

Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain.

Diffusion MRI techniques are used widely to study the characteristics of the human brain connectome in vivo. However, to resolve and characterise white matter (WM) fibres in heterogeneous MRI voxels remains a challenging problem typically approached with signal models that rely on prior information and constraints. We have recently introduced a 5D relaxation-diffusion correlation framework wherein multidimensional diffusion encoding strategies are used to acquire data at multiple echo-times to increase the amount of information encoded into the signal and ease the constraints needed for signal inversion. Nonparametric Monte Carlo inversion of the resulting datasets yields 5D relaxation-diffusion distributions where contributions from different sub-voxel tissue environments are separated with minimal assumptions on their microscopic properties. Here, we build on the 5D correlation approach to derive fibre-specific metrics that can be mapped throughout the imaged brain volume. Distribution components ascribed to fibrous tissues are resolved, and subsequently mapped to a dense mesh of overlapping orientation bins to define a smooth orientation distribution function (ODF). Moreover, relaxation and diffusion measures are correlated to each independent ODF coordinate, thereby allowing the estimation of orientation-specific relaxation rates and diffusivities. The proposed method is tested on a healthy volunteer, where the estimated ODFs were observed to capture major WM tracts, resolve fibre crossings, and, more importantly, inform on the relaxation and diffusion features along with distinct fibre bundles. If combined with fibre-tracking algorithms, the methodology presented in this work has potential for increasing the depth of characterisation of microstructural properties along individual WM pathways.

Toward nonparametric diffusion- T1 characterization of crossing fibers in the human brain.

PURPOSE: To estimate T1 for each distinct fiber population within voxels containing multiple brain tissue types. METHODS: A diffusion- T1 correlation experiment was carried out in an in vivo human brain using tensor-valued diffusion encoding and multiple repetition times. The acquired data were inverted using a Monte Carlo algorithm that retrieves nonparametric distributions P(D,R1) of diffusion tensors and longitudinal relaxation rates R1=1/T1 . Orientation distribution functions (ODFs) of the highly anisotropic components of P(D,R1) were defined to visualize orientation-specific diffusion-relaxation properties. Finally, Monte Carlo density-peak clustering (MC-DPC) was performed to quantify fiber-specific features and investigate microstructural differences between white matter fiber bundles. RESULTS: Parameter maps corresponding to P(D,R1) 's statistical descriptors were obtained, exhibiting the expected R1 contrast between brain tissue types. Our ODFs recovered local orientations consistent with the known anatomy and indicated differences in R1 between major crossing fiber bundles. These differences, confirmed by MC-DPC, were in qualitative agreement with previous model-based works but seem biased by the limitations of our current experimental setup. CONCLUSIONS: Our Monte Carlo framework enables the nonparametric estimation of fiber-specific diffusion- T1 features, thereby showing potential for characterizing developmental or pathological changes in T1 within a given fiber bundle, and for investigating interbundle T1 differences.

Revisiting the dissolution of cellulose in H3PO4(aq) through cryo-TEM, PTssNMR and DWS.

Cellulose can be dissolved in concentrated acidic aqueous solvents forming extremely viscous solutions, and, in some cases, liquid crystalline phases. In this work, the concentrated phosphoric acid aqueous solvent is revisited implementing a set of advanced techniques, such as cryo-transmission electronic microscopy (cryo-TEM), polarization transfer solid-state nuclear magnetic resonance (PTssNMR), and diffusing wave spectroscopy (DWS). Cryo-TEM images confirm that this solvent system is capable to efficiently dissolve cellulose. No cellulose particles, fibrils, or aggregates are visible. Conversely, PTssNMR revealed a dominant CP signal at 25 °C, characteristic of C-H bond reorientation with correlation time longer than 100 ns and/or order parameter above 0.5, which was ascribed to a transient gel-like network or an anisotropic liquid crystalline phase. Increasing the temperature leads to a gradual transition from CP to INEPT-dominant signal and a loss of birefringence in optical microscopy, suggesting an anisotropic-to-isotropic phase transition. Finally, an excellent agreement between optical microrheology and conventional mechanical rheometry was also obtained.