Diffusion Measurements Research Articles

Characterization of Mixing at the Edge of a Kuroshio Intrusion into the South China Sea: Analysis of Thermal Variance Diffusivity Measurements

Abstract The Kuroshio occasionally carries warm and salty North Pacific Water into fresher waters of the South China Sea, forming a front with a complex temperature–salinity (T–S) structure to the west of the Luzon Strait. In this study, we examine the T–S interleavings formed by alternating layers of North Pacific Water with South China Sea Water in a front formed during the winter monsoon season of 2014. Using observations from a glider array following a free-floating wave-powered vertical profiling float to calculate the fine-scale parameters Turner angle, Tu, and Richardson number, Ri, we identified areas favorable to double-diffusion convection and shear instability observed in a T–S interleaving. We evaluated the contribution of double-diffusion convection and shear instabilities to the thermal variance diffusivity, χ, using microstructure data and compared it with previous parameterization schemes based on fine-scale properties. We discover that turbulent mixing is not accurately parameterized when both Tu and Ri are within critical ranges (Tu > 60; Ri < ¼). In particular, χ associated with salt finger processes was an order of magnitude higher (6.7 × 10−7 K2 s−1) than in regions where only velocity shear was likely to drive mixing (8.7 × 10−8 K2 s−1).

Deep learning neural network approach to thermal-wave imaging of damage in solids with application to diffusivity measurements of a green (unsintered) metal powder compact slab

A method is proposed to measure the thermal diffusivity of a green (unsintered) metal powder compact slab by combining numerical solution and deep learning. The thermal diffusion and thermal-wave equation is first discretized in space and time domains. Square wave excitation signals at different frequencies are considered, and the corresponding thermal wave responses are obtained. The space and frequency dependencies of the thermal-wave amplitude and phase are obtained by using lock-in thermography. Then, deep learning candidate neural network sets composed of spatial coordinates, excitation frequency, amplitude, and phase values are quickly and massively obtained for training the deep learning network. The validity of the deep learning network is verified by predicting the known thermal diffusivity, and the parameters and robustness of the deep learning network are discussed. Experimentally, a square wave modulated laser beam is used to illuminate one side of a green metal powder compact slab and the spatial distribution of amplitude and phase at three excitation frequencies is obtained. The predicted slab thermal diffusivity is extracted through the formed deep learning network, and the validity of the predicted value is verified by comparing with independent measurements.

Superagers Resist Typical Age-Related White Matter Structural Changes.

Superagers are elderly individuals with the memory ability of people 30 years younger and provide evidence that age-related cognitive decline is not inevitable. In a sample of 64 superagers (mean age, 81.9; 59% women) and 55 typical older adults (mean age, 82.4; 64% women) from the Vallecas Project, we studied, cross-sectionally and longitudinally over 5 years with yearly follow-ups, the global cerebral white matter status as well as region-specific white matter microstructure assessment derived from diffusivity measures. Superagers and typical older adults showed no difference in global white matter health (total white matter volume, Fazekas score, and lesions volume) cross-sectionally or longitudinally. However, analyses of diffusion parameters revealed the better white matter microstructure in superagers than in typical older adults. Cross-sectional differences showed higher fractional anisotropy (FA) in superagers mostly in frontal fibers and lower mean diffusivity (MD) in most white matter tracts, expressed as an anteroposterior gradient with greater group differences in anterior tracts. FA decrease over time is slower in superagers than in typical older adults in all white matter tracts assessed, which is mirrored by MD increases over time being slower in superagers than in typical older adults in all white matter tracts except for the corticospinal tract, the uncinate fasciculus, and the forceps minor. The better preservation of white matter microstructure in superagers relative to typical older adults supports resistance to age-related brain structural changes as a mechanism underpinning the remarkable memory capacity of superagers, while their regional aging pattern is in line with the last-in-first-out hypothesis.

Ebola Virus Glycoprotein Strongly Binds to Membranes in the Absence of Receptor Engagement.

Ebola virus (EBOV) is an enveloped virus that must fuse with the host cell membrane in order to release its genome and initiate infection. This process requires the action of the EBOV envelope glycoprotein (GP), encoded by the virus, which resides in the viral envelope and consists of a receptor binding subunit, GP1, and a membrane fusion subunit, GP2. Despite extensive research, a mechanistic understanding of the viral fusion process is incomplete. To investigate GP-membrane association, a key step in the fusion process, we used two approaches: high-throughput measurements of single-particle diffusion and single-molecule measurements with optical tweezers. Using these methods, we show that the presence of the endosomal Niemann-Pick C1 (NPC1) receptor is not required for primed GP-membrane binding. In addition, we demonstrate this binding is very strong, likely attributed to the interaction between the GP fusion loop and the membrane's hydrophobic core. Our results also align with previously reported findings, emphasizing the significance of acidic pH in the protein-membrane interaction. Beyond Ebola virus research, our approach provides a powerful toolkit for studying other protein-membrane interactions, opening new avenues for a better understanding of protein-mediated membrane fusion events.

Model discovery approach enables noninvasive measurement of intra-tumoral fluid transport in dynamic MRI.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a routine method to noninvasively quantify perfusion dynamics in tissues. The standard practice for analyzing DCE-MRI data is to fit an ordinary differential equation to each voxel. Recent advances in data science provide an opportunity to move beyond existing methods to obtain more accurate measurements of fluid properties. Here, we developed a localized convolutional function regression that enables simultaneous measurement of interstitial fluid velocity, diffusion, and perfusion in 3D. We validated the method computationally and experimentally, demonstrating accurate measurement of fluid dynamics in situ and in vivo. Applying the method to human MRIs, we observed tissue-specific differences in fluid dynamics, with an increased fluid velocity in breast cancer as compared to brain cancer. Overall, our method represents an improved strategy for studying interstitial flows and interstitial transport in tumors and patients. We expect that our method will contribute to the better understanding of cancer progression and therapeutic response.

Perivascular space diffusivity and brain microstructural measures are associated with circadian time and sleep quality.

The glymphatic system is centred around brain cerebrospinal fluid flow and is enhanced during sleep, and the synaptic homeostasis hypothesis proposes that sleep acts on brain microstructure by selective synaptic downscaling. While so far primarily studied in animals, we here examine in humans if brain diffusivity and microstructure is related to time of day, sleep quality and cognitive performance. We use diffusion weighted images from 916 young healthy individuals, aged between 22 and 37 years, collected as part of the Human Connectome Project to assess diffusion tensor image analysis along the perivascular space index, white matter fractional anisotropy, intra-neurite volume fraction and extra-neurite mean diffusivity. Next, we examine if these measures are associated with circadian time of acquisition, the Pittsburgh Sleep Quality Index (high scores correspond to low sleep quality) and age-adjusted cognitive function total composite score. Consistent with expectations, we find that diffusion tensor image analysis along the perivascular space index and orbitofrontal grey matter extra-neurite mean diffusivity are negatively and white matter fractional anisotropy positively correlated with circadian time. Further, we find that grey matter intra-neurite volume fraction correlates positively with Pittsburgh Sleep Quality Index, and that this correlation is driven by sleep duration. Finally, we find positive correlations between grey matter intra-neurite volume fraction and cognitive function total composite score, as well as negative interaction effects between cognitive function total composite score and Pittsburgh Sleep Quality Index on grey matter intra-neurite volume fraction. Our findings propose that perivascular flow is under circadian control and that sleep downregulates the intra-neurite volume in healthy adults with positive impact on cognitive function.

Fabrication and evaluation of a spatially resolved fiber-optic probe for diffuse reflectance measurement for noninvasive diabetic foot ulcer diagnosis perspective

Fabrication and evaluation of a spatially resolved fiber-optic probe for diffuse reflectance measurement for noninvasive diabetic foot ulcer diagnosis perspective

A double-pass optical beam deflection instrument for the measurement of diffusion, thermodiffusion and Soret coefficients in liquid mixtures and its application to polymer analysis

Abstract We have developed a new double-pass optical beam deflection instrument for the measurement of diffusion, thermodiffusion and Soret coefficients in liquid mixtures. The increased sensitivity of the instrument results from a second passage of the readout laser beam through the Soret cell containing the sample. An elegant description of the total beam deflection is achieved by means of a transfer matrix formalism. The higher sensitivity allows for a reduction of the length of the detection arm and a compact and stiff design of the instrument. The performance of the new apparatus is demonstrated by its application to polymer analysis for the determination of the molar mass distribution of the polymer from the distribution of diffusion rates by means of the CONTIN algorithm.

In-Line Chemical Composition Monitoring for the Injection Molding Process of Biodegradable Polymer Blends Using Simultaneous Measurement of Near-Infrared Diffuse Reflectance and Transmission Spectra.

In the processing of polymer blends and composites, in-line near-infrared (NIR) spectroscopy enables monitoring of the composition and its composite uniformity and contributes to rapid process development and quality control. However, in the injection molding process, the study of the composition of polymer materials has been delayed due to high-pressure conditions. Our research group developed NIR probes for transmission and diffuse reflectance measurements that can withstand high-pressure and temperature conditions up to 130 MPa and 200 °C. In this research, transmission and diffuse reflectance spectra were measured inline during the injection molding process of polymer blends of poly(lactic acid) and polybutylene succinate adipate. The intensity of each polymer band in the second-derivative spectra exhibited a monotonic increase or decrease in response to changes in the blend ratio. Using transmission and diffuse reflectance spectra as explanatory variables of the partial least squares regression model simultaneously, the model showed high estimation accuracy for the entire region of the blend ratio. Finally, this model was applied to monitor the polymer changeover operation, and the change in the blend ratio in the molded product was successfully estimated in line.

Droplet size distribution of oil-in-water Pickering emulsions stabilized by cellulose nanofibers using restricted diffusion NMR

In this study, droplet size distributions (DSDs) of oil-in-water Pickering emulsions stabilized by cellulose nanofibers (CNFs) estimated from NMR diffusion measurements in conjunction with cogent mathematical modelling based on the Gaussian phase distribution (GPD) approximation for diffusion in a sphere. The effects of oil types and Pickering stabilizer loadings on DSDs were investigated by using different n-alkanes (octane to hexadecane) and CNF concentrations (0.5–1%). The NMR diffusion data of the dispersed oil were well-described by the GPD model with a monomodal log-normal distribution. Pickering emulsions composed of higher n-alkane carbon number and/or CNF concentration were found to have smaller median radii, RMedian, and these RMedian estimates were in good agreement with laser scattering data. The volume-based RMedian against the CNF concentrations or the number of hydrocarbon n-alkanes exhibited an approximate exponential relationship.

Investigation of the luminescence properties and temperature dependent luminescence properties of Sm3+ doped NaPbBi2(PO4)3 orthophosphate phosphor: A promising candidate for light and light sensing applications

The red phosphor for light application is in high demand. In this regard, a series of orange-red phosphors, NaPbBi2(PO4)3: Sm3+, with a single phase were obtained by the conventional solid state reaction method. The X-ray diffraction (XRD) confirms that the phosphor belongs to the cubic structure with a space group I-43d (220). The optical property of the phosphor was studied through the diffuse reflectance spectroscopy measurements and the characteristic peaks of the Sm3+ ions were identified. Exciting the phosphors at 404 nm, produced a strong orange-red emission at 601 nm. The optimum concentration of the phosphor was found to be 0.03 mol. In all emission transitions of the Sm3+ ions within the host lattice, the energy transfer (ET) occurs among the nearest neighbour ions. The lifetime values were in the order of milliseconds. The photometric parameters revealed that the emission lies in the orange-red region with color coordinates (0.5863, 0.4129) and a color purity of 99.4 %. The temperature dependent luminescence properties of the phosphor were also investigated and all these results showed that the phosphor could serve as a good candidate for light/light sensing applications.

Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder.

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

On Interactions of Sulfamerazine with Cyclodextrins from Coupled Diffusometry and Toxicity Tests.

This scientific study employs the Taylor dispersion technique for diffusion measurements to investigate the interaction between sulfamerazine (NaSMR) and macromolecular cyclodextrins (β-CD and HP-β-CD). The results reveal that the presence of β-CD influences the diffusion of the solution component, NaSMR, indicating a counterflow of this drug due to solute interaction. However, diffusion data indicate no inclusion of NaSMR within the sterically hindered HP-β-CD cavity. Additionally, toxicity tests were conducted, including pollen germination (Actinidia deliciosa) and growth curve assays in BY-2 cells. The pollen germination tests demonstrate a reduction in sulfamerazine toxicity, suggesting potential applications for this antimicrobial agent with diminished adverse effects. This comprehensive investigation contributes to a deeper understanding of sulfamerazine-cyclodextrin interactions and their implications for pharmaceutical and biological systems.

Estimating the prevalence of Non-Verbal Learning Disability (NVLD) from the ABCD sample.

Non-Verbal Learning Disability (NVLD) is a neurodevelopmental disorder characterized by deficits in processing visuospatial information but with age-appropriate verbal skills. This cognitive profile has been hypothesized to be associated with atypical white matter, but at the present there is a lack of evidence for this hypothesis. Currently, the condition is not characterized within the main diagnostic systems, in part because no clear set of criteria for characterizing the disorder exists. This report is the first attempt to estimate NVLD prevalence, using two sets of diagnostic criteria, in a large sample of over 11,000 children who were selected without regards to problems of specific nature, either psychological, neurological, physical and/or social. Furthermore, it examined the association between the profile of cognitive abilities and aspects of whole-brain white matter measures in children with and without symptoms associated with NVLD. Participants were drawn from the Adolescent Brain Cognitive Development (ABCD) study, a 10-year longitudinal study of 11,876 children in the U.S. The data used in the present study were drawn from the initial testing point at which the children were 9-10years old. Prevalence of NVLD based on two distinct sets of criteria, correlations between the measures used to create the criteria, correlations between criteria measures and measures of white matter integrity. The cognitive criteria included measures of visuospatial processing, reading, intelligence and social skills. By varying the cut-offs applied to social skills in conjunction with visuo-spatial difficulties, spared reading skills and intelligence scores, we calculated prevalence for two NVLD groups. White matter characteristics were measures of volume, fractional anisotropy and mean diffusivity. Based on the criteria used, the estimated prevalence of NVLD varied from 1 to 8%. Furthermore, children with NVLD showed a dissociation between measures of visuo-spatial processing not observed in non-NVLD children. At the neurological level, findings provide preliminary evidenceof associations between the cognitive profile of NVLD and abnormalities in white matters tracts. The present study documents that exists, within this large non-selected sample, a proportion of youth who show evidence of NVLD. Given those results, it appears essential to establish the best diagnostic criteria, to improve the treatment options and quality of life for children with this disorder.

Volcanic soil gas 4He/CO2 ratio: a useful geochemical tool for real-time eruption forecasting

At many dormant volcanoes, magmatic gases are not channeled through preferential degassing routes as fumaroles and only percolate through the flanks of the volcano in a diffuse way. This type of volcanic gas emission provides valuable information, even though the soil matrix contains an important atmospheric component. This study aimed to demonstrate that chemical ratios such as He/CO2 in soil gases provide excellent information on the evolution of volcanic unrest episodes and help forecast the volcanic eruption onset. Before and during the occurrence of the October 2011–March 2012 submarine of El Hierro, Canary Islands, more than 8500 soil He analyses and diffuse CO2 emission measurements were performed. The results show that the soil He/CO2 emission ratio began increasing drastically one month before eruption onset, reaching the maximum value 10 days before. During the eruptive period, this ratio also showed a maximum value several days before the period with the highest magma emission rate. The He/CO2 ratio was also helpful in forecasting the eruption onset. We demonstrate that this tool can be applied in real-time during volcanic emergencies. Our results also encourage a reevaluation of the global He emission from the subaerial volcanism.

Structural white matter properties and cognitive resilience to tau pathology.

We assessed whether macro- and/or micro-structural white matter properties are associated with cognitive resilience to Alzheimer's disease pathology years prior to clinical onset. We examined whether global efficiency, an indicator of communication efficiency in brain networks, and diffusion measurements within the limbic network and default mode network moderate the association between amyloid-β/tau pathology and cognitive decline. We also investigated whether demographic and health/risk factors are associated with white matter properties. Higher global efficiency of the limbic network, as well as free-water corrected diffusion measures within the tracts of both networks, attenuated the impact of tau pathology on memory decline. Education, age, sex, white matter hyperintensities, and vascular risk factors were associated with white matter properties of both networks. White matter can influence cognitive resilience against tau pathology, and promoting education and vascular health may enhance optimal white matter properties. Aβ and tau were associated with longitudinal memory change over ∼7.5 years. White matter properties attenuated the impact of tau pathology on memory change. Health/risk factors were associated with white matter properties.

Combined experimental and first principles look into (Ce, Mo) doped BiVO4

Here we investigated the effects of Ce and Mo doping on hydrothermally synthesized bismuth vanadate BiVO4 nanoparticles (NPs). The existence of monoclinic scheelite and tetragonal zircon phases of NPs was validated from Rietveld refinement of the powdered X-ray diffraction, room temperature Raman, and Fourier-transform infrared spectroscopy. The co-doping of Bi and V sites with respective Ce and Mo dopants in a mixed tetragonal zircon and monoclinic scheelite phases of BiVO4 lattice was corroborated from high-resolution transmission electron microscopy and X-ray photoelectron spectroscopy. The photoluminescence measurements revealed enhancement of photo-generated carrier recombination in (Ce, Mo) co-doped BiVO4 NPs which may have hampered its photocatalytic efficiency in degrading the methylene blue dye. The simulations based on Hubbard U corrected density functional theory (DFT+U) suggest that Mo and Ce co-doping introduced deep impurity states which may have facilitated the photo-generated carrier recombination detrimental to photocatalytic performance. The UV-vis diffuse reflectance measurements provided evidence for the presence of these defect states. In summary, this work may have presented a comprehensive experimental analysis of (Ce, Mo) doped BiVO4 supported by DFT simulations.

Antimicrobial Activities against Skin Flora from Tart-cherry Extracts (Prnus cerasus)

Purpose: In this study, antibacterial and anti-oxidant activities of Tart-cherry hydrothermal extracts (TCW) and ethanol extracts (TCE) against dermatological bacteria were measured, and the cell viability and anti-inflammatory effects were investigated in RAW264.7 macrophages to determine their characteristics for use as functional cosmetic materials. Methods: Anti-oxidant activity was determined using the DPPH method. The antibacterial activity against dermatophilosis was confirmed by the size of the clear zone formed by DISK diffusion and MIC measurement. The activity against an antibiotic-resistant MRSA strain was also measured. Anti-inflammatory response was identified by measuring cytotoxicity and NO activity in RAW264.7 macrophages, in which inflammatory reactions were induced with LPS. Results: Anti-oxidant activity of the TCE was 85.6%, and of TCW was 88.4% at 500 μg/mL. The size of the clear zone was confirmed using Cutibacterium acnes (18 mm), <i>Staphylococcus epidermis</i> (<i>S. epidermis</i> ) (4 mm), and <i>Staphylococcus aureus</i> (<i>S. aureus</i> ) (16 mm). No antifungal activity against <i>Candida albicans</i> was observed. RAW264.7 macrophages showed a survival rate of >90% at <250 μg/mL of extract. Additionally, a concentration-dependent inhibition of NO production was observed. Conclusion: Tart-cherry extracts possessed high anti-oxidant activity and anti-inflammatory efficacy. In addition to the antibacterial activity against the skin-residing bacteria, <i>S. aureus</i> and <i>S. epidermis</i>, high activity against the acne-causing strain <i>C. acnes</i> suggests a sufficient potential of Tart-cherry extracts as a raw material for the preparation of cosmetics and bioproducts.

Structural and functional correlates of disability, motor and cognitive performances in multiple sclerosis: Focus on the globus pallidus

ObjectivesTo explore structural and functional alterations of external (GPe) and internal (GPi) globus pallidus in people with multiple sclerosis (pwMS) compared to healthy controls (HC) and analyze their relationship with measures of clinical disability, motor and cognitive impairment. MethodsSixty pwMS and 30 HC comparable for age and sex underwent 3.0T MRI, including conventional, diffusion tensor MRI and resting state (RS) functional MRI. Expanded Disability Status Scale (EDSS) scores were rated and timed 25-foot walk (T25FW) test, nine-hole peg test (9HPT), and paced auditory serial addition test (PASAT) were administered. Two operators segmented the GP into GPe and GPi. Volumes, T1/T2 ratio, diffusivity indices and seed-based RS functional connectivity (FC) of the GP and its components were assessed. ResultsPwMS had no atrophy or altered diffusivity measures of the GP. Compared to HC, pwMS had higher T1/T2 ratio in both GP regions, which correlated with EDSS score (r = 0.26–0.39, p = 0.01–0.05). RS FC analysis highlighted component-specific functional alterations in pwMS: the GPe had decreased RS FC with fronto-parietal cortices, whereas the GPi had decreased intra-GP RS FC and increased RS FC with the thalamus. Worse EDSS, 9HPT, T25FW and PASAT scores were associated with GP RS FC modifications (r=-0.51‒0.51, p < 0.001). ConclusionsStructural GP involvement in MS was homogeneous across its portions. Increased T1/T2 ratio values, possibly representing iron accumulation, were related to more severe disability. RS FC alterations of the GPe and GPi were consistent with their roles within the basal ganglia network and correlated with worse functional status, suggesting less efficient communication between structures.

Atomic Diffusivities of Yttrium, Titanium and Oxygen Calculated by Ab Initio Molecular Dynamics in Molten 316L Oxide-Dispersion-Strengthened Steel Fabricated via Additive Manufacturing.

Oxide-dispersion-strengthened (ODS) steels have long been viewed as a prime solution for harsh environments. However, conventional manufacturing of ODS steels limits the final product geometry, is difficult to scale up to large components, and is expensive due to multiple highly involved, solid-state processing steps required. Additive manufacturing (AM) can directly incorporate dispersion elements (e.g., Y, Ti and O) during component fabrication, thus bypassing the need for an ODS steel supply chain, the scale-up challenges of powder processing routes, the buoyancy challenges associated with casting ODS steels, and the joining issues for net-shape component fabrication. In the AM process, the diffusion of the dispersion elements in the molten steel plays a key role in the precipitation of the oxide particles, thereby influencing the microstructure, thermal stability and high-temperature mechanical properties of the resulting ODS steels. In this work, the atomic diffusivities of Y, Ti, and O in molten 316L stainless steel (SS) as functions of temperature are determined by ab initio molecular dynamics simulations. The latest Vienna Ab initio Simulation Package (VASP) package that incorporates an on-the-fly machine learning force field for accelerated computation is used. At a constant temperature, the time-dependent coordinates of the target atoms in the molten 316L SS were analyzed in the form of mean square displacement in order to obtain diffusivity. The values of the diffusivity at multiple temperatures are then fitted to the Arrhenius form to determine the activation energy and the pre-exponential factor. Given the challenges in experimental measurement of atomic diffusivity at such high temperatures and correspondingly the lack of experimental data, this study provides important physical parameters for future modeling of the oxide precipitation kinetics during AM process.