Transverse Relaxation Time Research Articles

Phase-based fast 3D high-resolution quantitative T2 MRI in 7 T human brain imaging

Magnetic resonance imaging (MRI) is a powerful and versatile technique that offers a range of physiological, diagnostic, structural, and functional measurements. One of the most widely used basic contrasts in MRI diagnostics is transverse relaxation time (T2)-weighted imaging, but it provides only qualitative information. Realizing quantitative high-resolution T2 mapping is imperative for the development of personalized medicine, as it can enable the characterization of diseases progression. While ultra-high-field (≥ 7 T) MRI offers the means to gain new insights by increasing the spatial resolution, implementing fast quantitative T2 mapping cannot be achieved without overcoming the increased power deposition and radio frequency (RF) field inhomogeneity at ultra-high-fields. A recent study has demonstrated a new phase-based T2 mapping approach based on fast steady-state acquisitions. We extend this new approach to ultra-high field MRI, achieving quantitative high-resolution 3D T2 mapping at 7 T while addressing RF field inhomogeneity and utilizing low flip angle pulses; overcoming two main ultra-high field challenges. The method is based on controlling the coherent transverse magnetization in a steady-state gradient echo acquisition; achieved by utilizing low flip angles, a specific phase increment for the RF pulses, and short repetition times. This approach simultaneously extracts both T2 and RF field maps from the phase of the signal. Prior to in vivo experiments, the method was assessed using a 3D head-shaped phantom that was designed to model the RF field distribution in the brain. Our approach delivers fast 3D whole brain images with submillimeter resolution without requiring special hardware, such as multi-channel transmit coil, thus promoting high usability of the ultra-high field MRI in clinical practice.

Mapping of magnetic resonance imaging's transverse relaxation time at low signal-to-noise ratio using Bloch simulations and principal component analysis image denoising.

High-resolution mapping of magnetic resonance imaging (MRI)'s transverse relaxation time (T2 ) can benefit many clinical applications by offering improved anatomic details, enhancing the ability to probe tissues' microarchitecture, and facilitating the identification of early pathology. Increasing spatial resolutions, however, decreases data's signal-to-noise ratio (SNR), particularly at clinical scan times. This impairs imaging quality, and the accuracy of subsequent radiological interpretation. Recently, principal component analysis (PCA) was employed for denoising diffusion-weighted MR images and was shown to be effective for improving parameter estimation in multiexponential relaxometry. This study combines the Marchenko-Pastur PCA (MP-PCA) signal model with the echo modulation curve (EMC) algorithm for denoising multiecho spin-echo (MESE) MRI data and improving the precision of EMC-generated single T2 relaxation maps. The denoising technique was validated on simulations, phantom scans, and in vivo brain and knee data. MESE scans were performed on a 3-T Siemens scanner. The acquired images were denoised using the MP-PCA algorithm and were then provided as input for the EMC T2 -fitting algorithm. Quantitative analysis of the denoising quality included comparing the standard deviation and coefficient of variation of T2 values, along with gold standard SNR estimation of the phantom scans. The presented denoising technique shows an increase in T2 maps' precision and SNR, while successfully preserving the morphological features of the tissue. Employing MP-PCA denoising as a preprocessing step decreases the noise-related variability of T2 maps produced by the EMC algorithm and thus increases their precision. The proposed method can be useful for a wide range of clinical applications by facilitating earlier detection of pathologies and improving the accuracy of patients' follow-up.

Time domain NMR: An alternative for study of the asphaltenes precipitated in petroleum.

During the oil production and processing stages, the asphaltene precipitation is one of the great operation problems of oil industry. It can precipitate in the formation, tubing, or surface, causing operating problems, such as reduction in oil recovery by changing the reservoir permeability and wettability, clogging of the pipelines, and difficulty in separations process. The quantification of asphaltenes in petroleum by ASTM D6560 standard method is very laborious and use of a larger solvent volume than necessary. The present work proposes the use of time domain nuclear magnetic resonance (TD-NMR) as new methodology to quantify the asphaltene precipitated in crude oil. Three (light, medium, and heavy) crude oils with asphaltenes content of 0.97, 1.88, and 7.00 wt% were mixed with n-heptane in different R (ml of solvent/g of oil) values and analyzed by means of transverse relaxation time (T2 ). According NMR results, the R values enough for complete asphaltene precipitation for the oils A, B, and C were, respectively, equal to 16.50, 23.00, and 39.50 ml g-1 . These outcomes represent a reduction of 58.75%, 42.50%, and 1.25% in the solvent volume per mass of oil for the oil A, B, and C, respectively, compared to the ASTM D6560 method, which imposes 40 ml g-1 . Therefore, it has been shown that TD-NMR can be applied to estimate the amount of asphaltene precipitated in petroleum and have potential to be applied in routine analysis with advantages of saving time and costs.

Impact of storage time and temperature of salad heads on the quality of fresh-cut Cichorium endivia

The impact of temperature and storage time of escarole salad heads on the quality of processed, fresh-cut salad was investigated. Based on temperatures recorded in a fresh-cut processing plant, salad heads were stored for four different storage times (0, 5, 9, and 12 d) at four temperatures (4, 7, 10, and 12 °C) before being processed. A range of quality criteria (technical yield, global visual aspect, pink cut surfaces, mechanical texture, aerobic microflora, respiration rate, atmosphere composition in fresh-cut salad pouches, nuclear magnetic resonance transverse relaxation time) were measured on processing day, after 7 d storage at 4 °C of the fresh-cut salad packaged in pouches, and 1 d after pouch opening. The results are presented for salads grown in southeast France and early-season harvest, validated by experimental repetitions with a late-season harvest and salads from another geographical origin. Storage of salad heads caused deterioration of all quality attributes except for total aerobic bacteria. The global visual aspect was the most sensitive to changes in storage conditions of salad heads (significant reduction in quality for 5 d over 7 °C). In contrast, mechanical texture (maximum load for the shear test) was only significantly different for the fresh-cut salad prepared from salad heads stored for 9 d at 12 °C. For all quality criteria, fresh-cut salads processed from salad heads stored for 5 d at 4 and 7 °C were not significantly different from those of non-stored salad heads. For storage time of 5 d or less, a temperature of 7 °C is likely as good as 4 °C for escarole salad-head storage intended for fresh-cut processing.

Optimization of two-dimensional T1*–T2* relaxation correlation measurements in shale

Shale reservoirs, composed of fine-grained and organic-rich sedimentary rock, are common unconventional oil and gas reservoirs. Magnetic resonance (MR) relaxometry, a non-destructive and non-invasive method, is a key technique for shale evaluation. The T1*–T2* relaxation correlation, a rapid two-dimensional MR measurement, is a newly emerging and powerful tool to study the structure of materials with short transverse relaxation times. T1* and T2* are the effective longitudinal and transverse relaxation times. T1*–T2* measurement is a promising laboratory method to analyze fluid and organic matter components in shale, but it is very sensitive to the acquisition parameters. In this paper, the effects of acquisition parameters, including flip angle α, initial interval τ1, α pulse interval τ, and scan number, on T1*–T2* relaxation correlation of shale were analyzed by numerical simulations and core plug experiments. The optimized T1*–T2* measurement can be two orders of magnitude faster than a simple T1–T2* measurement. This work provides a theoretical and practical guide for undertaking T1*–T2* measurements, which should be helpful for further laboratory study of shale.

Simultaneous Assessment of Wettability and Water Saturation Through Integration of 2D NMR and Electrical Resistivity Measurements

Summary Nuclear magnetic resonance (NMR) transverse relaxation (T2) measurements are sensitive to fluid saturations and wettability of the rocks. However, quantifying wettability index solely from NMR T2 models relies on accurate estimates of water saturation. It has been shown that integrating resistivity measurements and NMR T2 distributions enables simultaneous assessment of wettability and water saturation. Nevertheless, there still exist significant uncertainties in this approach in the presence of multiple types of fluids with overlapping transverse relaxation times or multimodal pore-size distribution. Thus, the objectives of this paper are (a) to introduce a new multiphysics workflow integrating 2D NMR with resistivity measurements to simultaneously quantify wettability index and water/hydrocarbon saturation and (b) to verify the reliability of the introduced workflow with core measurements in different rock types. The workflow starts by using 2D diffusivity-transverse relaxation (D-T2) or longitudinal-transverse relaxation (T1-T2) measurements to estimate fluid saturations. We use a nonlinear inversion algorithm to fit a multimodal Gaussian distribution to the 2D NMR measurements. We then calculate water and hydrocarbon saturations using the fluid volumes estimated from the multimodal Gaussian distribution. This estimate of water/hydrocarbon saturation is an input to our new physics-based resistivity model that explicitly incorporates the influence of wettability. The inputs to the resistivity model include water saturation, resistivity index, and pore-geometry-related parameters. In the core-scale verification step, we compare the results of wettability and fluid saturations obtained from the new workflow with gravimetrically assessed water saturation and Amott index measurements on core sample. We successfully verified the reliability of the new workflow with experimental measurements. Estimated water saturation using the introduced workflow resulted in an average relative error of less than 7% compared to the gravimetrically assessed water saturations. Wettability indices obtained from the workflow were in agreement with those estimated using Amott indices. The average absolute error between the estimated wettability indices and the Amott indices was 0.27. In conclusion, results demonstrated that integration of 2D NMR and electrical resistivity measurements enables reliable and simultaneous assessment of wettability and water saturation in different rock types. The method introduced in this paper is promising for reliable and real-time wettability assessment, both in the laboratory and in-situ condition. It provides a physics-based and robust method to accurately and simultaneously estimate water/hydrocarbon saturation and wettability in hydrocarbon-bearing rocks.

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions.

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acquired in a healthy population. This study focuses on multi-echo T2 relaxometry, a qMRI technique that probes the complex tissue microstructure by differentiating compartment-specific T2 relaxation times. However, estimation methods are still limited by their sensitivity to the underlying noise. Moreover, estimating the model's parameters is challenging because the resulting inverse problem is ill-posed, requiring advanced numerical regularization techniques. As a result, the estimates from distinct regularization strategies are different. In this work, we aimed to investigate the variability and reproducibility of different techniques for estimating the transverse relaxation time of the intra- and extra-cellular space () in gray (GM) and white matter (WM) tissue in a clinical setting, using a multi-site, multi-session, and multi-run T2 relaxometry dataset. To this end, we evaluated three different techniques for estimating the T2 spectra (two regularized non-negative least squares methods and a machine learning approach). Two independent analyses were performed to study the effect of using raw and denoised data. For both the GM and WM regions, and the raw and denoised data, our results suggest that the principal source of variance is the inter-subject variability, showing a higher coefficient of variation (CoV) than those estimated for the inter-site, inter-session, and inter-run, respectively. For all reconstruction methods studied, the CoV ranged between 0.32 and 1.64%. Interestingly, the inter-session variability was close to the inter-scanner variability with no statistical differences, suggesting that is a robust parameter that could be employed in multi-site neuroimaging studies. Furthermore, the three tested methods showed consistent results and similar intra-class correlation (ICC), with values superior to 0.7 for most regions. Results from raw data were slightly more reproducible than those from denoised data. The regularized non-negative least squares method based on the L-curve technique produced the best results, with ICC values ranging from 0.72 to 0.92.

Chitosan Effect on Hardening Dynamics of Calcium Phosphate Cement: Low-Field NMR Relaxometry Investigations.

Calcium phosphate cements are used in dentistry and orthopedics to repair and reconstruct bone defects. The properties of these bone cements can be improved by introducing additives into their composition. One favorable additive is chitosan, which can be beneficial but can also cause considerable damage if it has a high load, thus, limiting its clinical applicability and performance. That is why understanding chitosan’s role in cement composition is an important issue when developing new materials. The present work uses low-field nuclear magnetic resonance (NMR) relaxometry to investigate the effect introduced by the addition of chitosan on the hardening process of calcium phosphate cement. Two samples, prepared with and without chitosan, were comparatively investigated during the first six minutes of hardening. The liquid evolution inside these samples was monitored using transverse relaxation time distributions. It demonstrated an acceleration effect on the hardening dynamics introduced by the presence of chitosan. Furthermore, it was shown that even after one hour of hardening, there were still unreacted monomers inside the bone cement and their amount was reduced in the presence of chitosan.

Characterization of the Water Shortage Effects on Potato Tuber Tissues during Growth Using MRI Relaxometry and Biochemical Parameters.

The potato is one of the most cultivated crops worldwide, providing an important source of food. The quality of potato tubers relates to their size and dry matter composition and to the absence of physiological defects. It depends on the spatial and temporal coordination of growth and metabolic processes in the major tuber tissues: the cortex, flesh and pith. In the present study, variations in the biochemical traits of each of these tissues were investigated during tuber growth under optimal and water-deficit conditions. MRI relaxometry was used as a non-invasive and quantitative method to access information on cellular water status. The presence of slight but significant variations in organic compound contents quantified in the cortex and flesh revealed a tissue-dependent metabolic pattern. The T2 and relative I0 of the bi-exponential relaxation signal allowed a distinction to be made between the pith and the cortex, whereas the flesh could be differentiated from these tissues only through its relative I0. T2 values did not vary significantly during tuber development, in accordance with the typical growth pattern of tubers, but were shown to be sensitive to water stress. The interpretation of the multi-exponential transverse relaxation times is discussed and could be further developed via microscopic analysis.

Enhanced conversion efficiency of vacancy-related color centers in diamonds grown on a patterned metal surface by chemical vapor deposition

Vacancy-related color centers in diamonds, such as nitrogen-vacancy (NV) and silicon-vacancy (SiV) centers, have good application prospects in solid-state quantum technologies. In various applications, shot noise-limited sensitivity is determined by coherence time and photoluminescence (PL) intensity, which depends on the color center density. However, the conversion efficiencies of impurity atoms to color centers are low and usually increased by electron irradiation, which destroy the lattice structure and create defects leading to decoherence. In this study, we epitaxially grew diamond layers containing color centers on surfaces coated with metal stripes. The PL intensities of NV0, NV−, and SiV− centers located directly above the metal surface were 3.27, 3.47, and 11.15 times higher than those of the diamond epitaxial region. The [N]–[NV] and [Si]–[SiV] conversion efficiencies were 63.26% and 35.68%, respectively, which were comparable to or even better than those achieved by electron irradiation. Moreover, the region above the metal exhibited a high lattice quality, longer transverse relaxation time, higher magnetic field sensitivity, and larger NV−/NV0 ratio. The findings of this study can help advance the existing research on NV-based magnetometers, biofluorescent labeling, and interfacial spin quantum memory and be potentially applied to other vacancy-related color centers, such as germanium-vacancy.

Whey Protein Hydrolysates Improved the Oxidative Stability and Water-Holding Capacity of Pork Patties by Reducing Protein Aggregation during Repeated Freeze-Thaw Cycles.

The effects of whey protein hydrolysates (WPH) on myofibrillar protein (MP) oxidative stability and the aggregation behavior and the water-holding capacity of pork patties during freeze–thaw (F–T) cycles were investigated. During F–T cycles, the total sulfhydryl content and zeta potential of MP decreased, while peroxide value, surface hydrophobicity, particle size, pressure loss and transverse relaxation times increase. The oxidative stability and the water-holding capacity of pork patties were enhanced by the addition of WPH in a dose-dependent manner, whereas the MP aggregation decreased. The addition of 15% WPH had the most obvious effects on the pork patties, which was similar to that of the 0.02% BHA. After nine F–T cycles, the POV, surface hydrophobicity, particle size and pressure loss of the pork patties with 15% WPH were reduced by 17.20%, 30.56%, 34.67% and 13.96%, respectively, while total sulfhydryl content and absolute value of zeta potential increased by 69.62% and 146.14%, respectively. The results showed that adding 15% WPH to pork patties can be an effective method to inhibit lipid and protein oxidation, reducing protein aggregation and improving the water-holding capacity of pork patties during F–T cycles.

Quantification of Intra-Muscular Adipose Infiltration in Calf/Thigh MRI Using Fully and Weakly Supervised Semantic Segmentation.

Purpose: Infiltration of fat into lower limb muscles is one of the key markers for the severity of muscle pathologies. The level of fat infiltration varies in its severity across and within patients, and it is traditionally estimated using visual radiologic inspection. Precise quantification of the severity and spatial distribution of this pathological process requires accurate segmentation of lower limb anatomy into muscle and fat. Methods: Quantitative magnetic resonance imaging (qMRI) of the calf and thigh muscles is one of the most effective techniques for estimating pathological accumulation of intra-muscular adipose tissue (IMAT) in muscular dystrophies. In this work, we present a new deep learning (DL) network tool for automated and robust segmentation of lower limb anatomy that is based on the quantification of MRI’s transverse (T2) relaxation time. The network was used to segment calf and thigh anatomies into viable muscle areas and IMAT using a weakly supervised learning process. A new disease biomarker was calculated, reflecting the level of abnormal fat infiltration and disease state. A biomarker was then applied on two patient populations suffering from dysferlinopathy and Charcot–Marie–Tooth (CMT) diseases. Results: Comparison of manual vs. automated segmentation of muscle anatomy, viable muscle areas, and intermuscular adipose tissue (IMAT) produced high Dice similarity coefficients (DSCs) of 96.4%, 91.7%, and 93.3%, respectively. Linear regression between the biomarker value calculated based on the ground truth segmentation and based on automatic segmentation produced high correlation coefficients of 97.7% and 95.9% for the dysferlinopathy and CMT patients, respectively. Conclusions: Using a combination of qMRI and DL-based segmentation, we present a new quantitative biomarker of disease severity. This biomarker is automatically calculated and, most importantly, provides a spatially global indication for the state of the disease across the entire thigh or calf.

A new method for capillary pressure curve prediction based on NMR echo data using integral transform, the quantum genetic algorithm, and the artificial neural network in tight sandstone

The capillary pressure curve (CPC) is an important tool with which to investigate the petrophysical properties and pore structure of oil and gas reservoir rocks. However, the method of obtaining the CPC directly via laboratory measurements is usually time-consuming and costly, prone to the contamination or destruction of core samples, and can only be applied to limited cores. A new method adopting integral transform, the quantum genetic algorithm, and the artificial neural network (IT-QGA-ANN) based on nuclear magnetic resonance (NMR) echo data is proposed to improve CPC prediction accuracy in tight sandstone. First, 7 parameters that characterize rock properties are directly extracted from echo data using integral transform. This process does not require to obtain the transverse relaxation time (T2) distribution by inversion of echo data, thereby avoiding the influence of inversion uncertainty. These characteristic parameters are then used as the input of the ANN, and the QGA method is utilized to optimize the weights and thresholds of ANN. Numerical simulation results prove the validity of integral transform to extract characteristic parameters. A total of 18 tight sandstones are used for mercury injection and NMR tests. The results indicate that, compared with the traditional nonlinear regression and ANN methods, the proposed IT-QGA-ANN method can more accurately predict the CPC. The proposed method achieves the direct and accurate transformation from echo data to the CPC, and provides important guidance for solving complex nonlinear problems in oil and gas reservoir evaluation based on NMR.

Association of Superficial Cartilage Transverse Relaxation Time With Osteoarthritis Disease Progression: Data From the Foundation for the National Institutes of Health Biomarker Study of the Osteoarthritis Initiative.

To study whether layer-specific cartilage transverse relaxation time (T2) and/or longitudinal change is associated with clinically relevant knee osteoarthritis (OA) disease progression. The Foundation for the National Institutes of Health Biomarker Consortium was a nested case-control study on 600 knees from 600 Osteoarthritis Initiative participants. Progressor knees had both medial tibiofemoral radiographic joint space width (JSW) loss (≥0.7 mm) and a persistent increase in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score (≥9 on a 0-100 scale) at 24-48 months from baseline (n=194). Multiecho spin-echo (MESE) magnetic resonance images (MRIs) for cartilage T2 analysis had been acquired in the right knees only (97 progressor knees). These were compared to 104 control knees without JSW or pain progression. Fifty-three knees had JSW progression, and 57 pain progression only. Cartilage thickness segmentations obtained from double-echo steady-state MRI were matched to MESE MRI to extract superficial and deep femorotibial cartilage T2. Superficial medial femorotibial compartment (MFTC) T2 at baseline was the primary, and change in deep MFTC T2 between baseline and 12 months was the secondary analytic outcome of this post hoc exploratory study. Baseline superficial MFTC T2 was significantly elevated in progressor knees (adjusted mean 47.2 msec [95% confidence interval (95% CI) 46.5, 48.0]) and JSW progression only knees (adjusted mean 47.3 msec [95% CI 46.3, 48.3]), respectively, versus non-progressor knees (45.8 msec [95% CI 45.0, 46.5]) after adjustment for age, sex, body mass index, WOMAC pain score, and medial joint space narrowing grade (analysis of covariance). Change in T2 was not significantly associated with case status. Baseline superficial, but not deep, medial cartilage T2 is associated with clinically relevant disease progression in knee OA.

A comparative study of permeability prediction for Eocene sandstones — Part 2: Application and modification of the Schlumberger-Doll Research equation

Nuclear magnetic resonance (NMR) relaxometry provides insight into the pore radius distribution (PRD) of rocks. Several permeability (k) of prediction models are based on the knowledge of the PRD. The Schlumberger-Doll Research (SDR) equation relates the weighted geometric mean of the transverse relaxation time ([Formula: see text]) and porosity to k. In the common form of SDR equation, porosity is raised to the fourth power. This exponent is not in agreement with theoretical models of permeability prediction. Modified versions of the SDR equation have been tested with varying exponents for porosity and other characteristic relaxation times or pore radii determined from NMR relaxometry. We have evaluated the quality of various k-prediction models using a sample set of Eocene sandstones with known values of measured permeability. A porosity exponent of five provides the best quality permeability prediction using the weighted geometric mean of [Formula: see text]. The replacement of the weighted geometric mean of [Formula: see text] by the weighted arithmetic or harmonic mean in combination with a porosity exponent of six indicates a slightly lower predictive quality. The use of average pore radii instead of average [Formula: see text] enables a better permeability prediction. The porosity exponents become smaller in these equations. This finding is confirmed by multivariate regression that provides noninteger exponents for porosity, relaxation time, or characteristic pore radii.

The deuteron NMR Hahn echo decay in polyethylene oxide melts

The deuteron transverse relaxation properties of polyethylene oxide melts of four different molecular weights, covering the range from the onset of entanglements to the regime of fully entangled chains, are investigated using Hahn echo decays over an extensive time interval up to ten times the effective transverse spin relaxation time. The results are compared to predictions based on the Rouse and reptation formalisms, taking into account the dynamical heterogeneity of linear polymer chains produced by the end segments. The experimental results can be described qualitatively by a combination of both models, with the contribution of reptation dynamics increasing with growing chain length. The transition is continuous, rather than being characterized by sharp regime boundaries. Up to a molecular weight of 300.000 g/mol, the predicted limit of pure reptation dynamics is not yet reached. Quantitative deviations from the predicted decays as computed by numerical procedures become observable toward the long-time limit of the Hahn echo decays and are being discussed in terms of shortcomings of the available reptation theories.

Impact of Helium Ion Implantation Dose and Annealing on Dense Near-Surface Layers of NV Centers.

The implantation of diamonds with helium ions has become a common method to create hundreds-nanometers-thick near-surface layers of NV centers for high-sensitivity sensing and imaging applications; however, optimal implantation dose and annealing temperature are still a matter of discussion. In this study, we irradiated HPHT diamonds with an initial nitrogen concentration of 100 ppm using different implantation doses of helium ions to create 200-nm thick NV layers. We compare a previously considered optimal implantation dose of ∼ Hecm to double and triple doses by measuring fluorescence intensity, contrast, and linewidth of magnetic resonances, as well as longitudinal and transversal relaxation times and . From these direct measurements, we also estimate concentrations of P1 and NV centers. In addition, we compare the three diamond samples that underwent three consequent annealing steps to quantify the impact of processing at 1100 C, which follows initial annealing at 800 C. By tripling the implantation dose, we have increased the magnetic sensitivity of our sensors by %. By projecting our results to higher implantation doses, we demonstrate that it is possible to achieve a further improvement of up to 70%. At the same time, additional annealing steps at 1100 C improve the sensitivity only by 6.6 ± 2.7%.

Long single pulse NQR for broad resonance lines

This paper describes the experimental application of long single pulses to strongly inhomogeneously broadened NQR spectral lines, where the pulse length significantly exceeds the transverse relaxation time. A63Cu NQR resonance in the mineral covellite (CuS) was used as an exemplar for study in this specific regime, which was motivated by the requirement to obtain useful signals in very large volume applications having radiofrequency power limitations. In this study, signal transients that followed the application of the long single pulses were measured over a large range of radiofrequency field strength and pulse width. The results indicate effective generation of signal amplitudes. This is in contrast to previously reported studies involving long pulses applied to relatively narrow resonances. The results are found to be well described by simulations of the modified Bloch equations.

Determining the internal orientation, degree of ordering, and volume of elongated nanocavities by NMR: Application to studies of plant stem

This study investigates the fibril nanostructure of fresh celery samples by modeling the anisotropic behavior of the transverse relaxation time (T2) in nuclear magnetic resonance (NMR). Experimental results are interpreted within the framework of a previously developed theory, which was successfully used to model the nanostructures of several biological tissues as a set of water filled nanocavities, hence explaining the anisotropy the T2 relaxation time in vivo. An important feature of this theory is to determine the degree of orientational ordering of the nanocavities, their characteristic volume, and their average direction with respect to the macroscopic sample. Results exhibit good agreement between theory and experimental data, which are, moreover, supported by optical microscopic resolution. The quantitative NMR approach presented herein can be potentially used to determine the internal ordering of biological tissues noninvasively.

Effects of Commercial Polysaccharides Stabilizers with Different Charges on Textural, Rheological, and Microstructural Characteristics of Set Yoghurts.

The study investigated the preparation of set yoghurts by adding three common commercial polysaccharide stabilizers, namely sodium alginate (SA), gellan gum (GG), and konjac gum (KGM), in milk fermentation to evaluate their effects on the texture, rheology, and microstructure of set yoghurts. The physicochemical properties, water-holding capacity (WHC), texture, low-field nuclear magnetic resonance (LF-NMR), rheology, and microstructure of set yoghurts added with different kinds and quantities of polysaccharides were compared and analyzed. The results showed that the set yoghurts added with anionic polysaccharide GG had more obvious effects on improving WHC, firmness, and rheological properties compared with the set yoghurt added with KGM and SA. The firmness of set yoghurts with 0.02% (w/v) GG increased from 1.17 N to 1.32 N, which significantly improved the gel structure. The transverse relaxation time (T2) of set yoghurts added with GG was the closest to that of the control. Compared with the set yoghurts added with 0.02% SA and KGM, the free water area (A23) of the one added with 0.02% GG decreased most significantly. Moreover, all samples showed shear-thinning behavior, and the apparent elastic and viscous modulus (G′, G″) increased with the increase of GG concentration. The G′ and G″ of set yoghurts with 0.005% SA and KGM were higher than those in the control, decreased when adding 0.010%, and then increased with the increase of SA and KGM. Additionally, the microscopic observation demonstrated that the addition of GG in set yoghurts significantly promoted the formation of larger protein clusters and showed a tighter and more uniform protein network comparing with the other two polysaccharides (SA, KGM).