Relative Diffusion Coefficient Research Articles

Ineffectiveness of 6,2',4'-trimethoxyflavone in mitigating cerebral ischemia/reperfusion injury after post-reperfusion administration in rats.

Pharmacological inhibition of aryl hydrocarbon receptor (AhR) activation after ischemia alleviates cerebral ischemia/reperfusion (IR) injury. To investigate whether AhR antagonist administration after reperfusion was also effective in attenuating cerebral IR injury. A total of 24 Sprague-Dawley rats were divided into the sham-operated group (no IR), control group (IR), and 6,2',4'-trimethoxyflavone (TMF) group (IR + TMF administration), with 10 rats assigned to each group. Cerebral IR injury was induced by 60 min of middle cerebral artery occlusion followed by reperfusion. TMF (5 mg/kg) was used as the AhR antagonist and was administered intraperitoneally immediately after reperfusion. Cerebral IR injury was observed using magnetic resonance imaging (MRI) and neurobehavioral assessments at baseline, immediately after ischemia, and at 3 days after ischemia. On MRI, the TMF group showed no significant differences in relative apparent diffusion coefficient (ADC), T2, and fractional anisotropy (FA) values; midline shift value; and infarct volume. In terms of neurobehavioral function, factors such as grip strength, contralateral forelimb use, time to touch, and time to remove adhesive tape from the forepaw, were also not significantly different between the control and TMF groups. This study demonstrated that AhR treatment after reperfusion had no noticeable effect on reducing cerebral IR injury in rats.

Role of diffusion-weighted imaging in the diagnosis of pituitary region tumors.

This study aimed to assess the role of Diffusion-Weighted Imaging (DWI) in routine pituitary Magnetic Resonance Imaging (MRI) protocols for distinguishing sellar and parasellar tumors, addressing the lack of clear guidelines in contemporary literature. A retrospective analysis of 242 pituitary MRI scans with DWI sequences was conducted in a single-center study using a 1.5T scanner and standard DWI sequence parameters. Measurements of both absolute and relative mean apparent diffusion coefficient (ADC) values, along with minimal ADC values within tumors, were performed. The adopted region of interest (ROI) based method used for these measurements was validated. Invasive pituitary adenomas exhibited significantly lower min ADC and min rADC than meningiomas, with optimal cut-off points of 0.64 (sensitivity 73%, specificity 82%) and 0.78 (sensitivity 73%, specificity 89%), respectively. Post-hemorrhagic pituitary adenomas demonstrated lower ADC values than adamantinomatous craniopharyngiomas, with an AUC of 0.893 for min rADC = 1.07, and Rathke's Cleft Cysts with mucous content, AUC 0.8 for min rADC = 1.01. Specific differentiation with high sensitivity and specificity based on diffusion parameters was observed for these tumor groups. Cystic pituitary non-functional adenomas obtained significantly lower ADC values compared to the adamantinomatous type of craniopharyngiomas and serous Rathke's Cleft Cysts (AUC up to 0.942). The study concludes that integrating DWI into routine pituitary MRI protocols enhances diagnostic accuracy in distinguishing sellar and parasellar tumors. The short scan time of one minute makes DWI a valuable and precise tool, supporting its recommendation as a standard component of pituitary MRI examinations.

Classification of Brain Infarction using Deep Learning techniques on Magnetic Resonance Imaging (MRI)

Background: This research concentrated on employing Convolutional Neural Networks (CNNs) to classify brain infarctions. A stroke occurs due to a blockage or hemorrhage in the blood vessels, which disrupts or diminishes the blood supply to the brain, leading to the death of brain cells. With the progress in machine learning techniques in medical imaging, early detection of stroke has become increasingly feasible, playing a crucial role in the diagnosis and treatment of this potentially fatal condition. Objective: Building an intelligent CNN model to classify types of brain infarction using up algorithms Median Filter preserving edges and efficient minimization of noise with durability against flowing noise, Fuzzy C – Mean to Image Segmentation and Recognition of Region of Interest for infarction location and size of the infarction for brain infarction Identification, GLCM, and FOSF. Methodology: The research was carried out in a private hospital; in Baghdad, Iraq, on 60 patients with brain infarction. Included were 9 hyperacute (>6 hours post brain infarction), 19 acute (7-72 hours), 12 subacute (4-7 days), and 20 chronic (< 15 days). We have introduced a Convolutional Neural Network (CNN) model as a solution to predict the likelihood of a patient experiencing a stroke at an early stage, aiming for maximize effectiveness and precision. Results: The ROC curve demonstrates that the average apparent diffusion coefficient (aveg (ADC) mm²/s) and relative apparent diffusion coefficient (rADC%) are two reliable and effective measures for monitoring brain infarction developments. High sensitivity indicates a strong ability to detect true positives (cases of infarction), while the shape and position of the curve suggest that average (ADC) mm²/s also maintains a reasonable specificity, minimizing false positives. This balance results in high overall diagnostic accuracy. Discussion: Both rACD (%) and aveg (ADC) mm²/s are robust indicators for the imaging monitoring of brain infarction developments. The inclusion of AI in the assessment process may result marginal improvements in specificity and accuracy.

Mechanistic Insight into Ion Transport in Layered Materials for Sodium-Ion Rechargeable Batteries

As a feasible alternative to Li-ion batteries (LIBs), Na-ion batteries (SIBs) are an emerging energy storage solution for electric vehicles, electronic devices, and large grid level energy storage systems. The TMD (transition metal dichalcogenides) component MoS2 and the NASICON structured-type NaxTi2(PO4)3 are two materials of interest as next-generation SIB materials. MoS2 is a 2D layered material with a graphene-like structure that can be used as a high-capacity anode or Na-ion host material as well as an electrocatalyst. Our experiments on the Al-doped 1T phase of MoS2 on reduced graphene oxide (rGO) nanosheets support demonstrated good electrochemical performance, such as 450, 400, etc. mAh/g at current densities of 0.05, 0.1 A/g. Experiments further revealed that Na-ion intercalation supports increased interlayer distance in 1T Al-MoS2@rGO, resulting in a stable phase structure. Density functional theory (DFT)-based simulations are utilized to study the intercalation properties of Na+ ions, in addition to GITT, EIS, and CV analysis. In this study, the Na-ion diffusion mechanism for 1T Al-MoS2@rGO interface and Al-MoS2-MoS2 interlayer host structure is explored. According to the experiments, the host structure is doped with 5% Al at a specific stable site, and Na-ions are introduced to the interface and interlayer (an interlayer distance of 9.3 Å is chosen, as estimated by the experiments). The Na-ion is hopped in both structures, and activation energies (Eact) are calculated to be 57.9 kJ/mol and 40.3 kJ/mol in the 1T Al-MoS2@rGO interface at migration distances of 0-2 Å and 2-4 Å, respectively. The related Na-ion diffusion coefficients are computed using an Arrhenius type fit to be in the order of 10-13 cm2/s and 10-10 cm2/s. Similarly, the Na-ion activation energy barriers in the 1T Al-MoS2-MoS2 interlayer are estimated to be between 49.8 and 59.6 kJ/mol, with related diffusivity ranging between 10-11 and 10-13 cm2/s. The outcomes of the DFT simulations are consistent with those of our experiments. The Na-ion transport properties in the NaTi2(PO4)3 bulk structure via the Na-ion vacancy assisted mechanism are investigated using MD simulations and DFT. The self-diffusion coefficients (DNa+) of bulk are examined, and then the lattice strain effect is proposed to alter its transport properties by introducing the lattice strain in uniaxial (x, y, z) and biaxial (xy, xz, yz) directions, and the changes are compared for strained and unstrained structure. In comparison to the unstrained structure at 323K, a significant improvement by 1-2 order change in DNa+ values (10-8 cm2/s - 10-10 cm2/s) is measured. DFT is also used to investigate the diffusion mechanisms along the various planes (line [001], [100], and [010]) of the bulk NaTi2(PO4)3 structure and Eact is determined along those directions, respectively. The values obtained are consistent with the experimental value ranges obtained for similar materials. In addition, a mixed ion-system is represented by inserting Li-ions at the surface of a NaTi2(PO4)3 structure, yielding the formula LixNay-xTi2(PO4)3. The sluggish kinetics of Li-ion in the NaTi2(PO4)3 structure were proposed by MD analysis. This corresponds well with experimental data that the NaTi2(PO4)3 framework exhibits preferred Na-ion insertion when cycling in mixed-ion electrolytes of varied concentrations, implying slow diffusion of Li-ions in the bulk Li+/Na+ mixed-ion crystal.

Multiparametric simultaneous hybrid 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) incorporating intratumoral and peritumoral regions for grading of glioma.

Preoperative grading gliomas is essential for therapeutic clinical decision-making. Current non-invasive imaging modality for glioma grading were primarily focused on magnetic resonance imaging (MRI) or positron emission tomography (PET) of the tumor region. However, these methods overlook the peritumoral region (PTR) of tumor and cannot take full advantage of the biological information derived from hybrid-imaging. Therefore, we aimed to combine multiparameter from hybrid 18F-fluorodeoxyglucose (18F-FDG) PET/MRI of the solid component and PTR were combined for differentiating high-grade glioma (HGG) from low-grade glioma (LGG). A total of 76 patients with pathologically confirmed glioma (41 HGG and 35 LGG) who underwent simultaneous 18F-FDG PET, arterial spin labelling (ASL), and diffusion-weighted imaging (DWI) with hybrid PET/MRI were retrospectively enrolled. The relative maximum standardized uptake value (rSUVmax), relative cerebral blood flow (rCBF), and relative minimum apparent diffusion coefficient (rADCmin) for the solid component and PTR at different distances outside tumoral border were compared. Receiver operating characteristic (ROC) curves were applied to assess the grading performance. A nomogram for HGG prediction was constructed. HGGs displayed higher rSUVmax and rCBF but lower rADCmin in the solid component and 5 mm-adjacent PTR, lower rADCmin in 10 mm-adjacent PTR, and higher rCBF in 15- and 20-mm-adjacent PTR. rSUVmax in solid component performed best [area under the curve (AUC) =0.865] as a single parameter for grading. Combination of rSUVmax in the solid component and adjacent 20 mm performed better (AUC =0.881). Integration of all 3 indicators in the solid component and adjacent 20 mm performed the best (AUC =0.928). The nomogram including rSUVmax, rCBF, and rADCmin in the solid component and 5-mm-adjacent PTR predicted HGG with a concordance index (C-index) of 0.906. Multiparametric 18F-FDG PET/MRI from the solid component and PTR performed excellently in differentiating HGGs from LGGs. It can be used as a non-invasive and effective tool for preoperative grade stratification of patients with glioma, and can be considered in clinical practice.

Comparative analysis of microdamage-affected chloride transport in concrete under static and dynamic hydraulic pressure

Concrete structures in marine environments frequently encounter the adverse impacts of hydraulic pressure, leading to a decrease in their durability. This study aims to conduct a comparative analysis of the internal microdamage in concrete when subjected to static and dynamic hydraulic pressure of equal intensity, and to examine the influence of such damage on chloride transport. By employing potentiometric titration, MIP, N2 adsorption, and AFM tests, the chloride concentration, pore structure parameters, and microscale elastic modulus of concrete under static and dynamic hydraulic pressure were analyzed. The results indicate that dynamic hydraulic pressure accelerates chloride transport in concrete. Compared with static hydraulic pressure, dynamic hydraulic pressure — sustained at the same intensity—results in an elevated threshold pore size along with an increased most probable pore size of the concrete. Furthermore, dynamic hydraulic pressure induces the expansion of microcracks, consequently decreasing the microscale elastic modulus of concrete. The use of mineral admixtures can effectively mitigate the damage evolution of concrete microstructure subjected to dynamic hydraulic pressure. Besides, a model is developed for relative chloride diffusion based on the principle of energy conservation and from the evolution law of the microscale elastic modulus gleaned from AFM tests. Through calculations, it can be found that the crack propagation rate and the decline rate of the relative chloride diffusion coefficient Df1Df2 increase markedly when dynamic hydraulic pressure intensity surpasses 40,000 Pa. The propagation of the crack length is moderated by a larger initial crack width.

Mechanisms of interface electrostatic potential induced asphalt-aggregate adhesion

The electrostatic potential at the interface of the asphalt molecular and aggregate oxides is the primary factor generating the adhesion between the asphalt-aggregate contact surfaces. However, the route of electrostatic potential affecting the asphalt-aggregate adhesion is yet to be determined at the molecular level. This study proposed that the electron accumulation at the interface of the asphalt molecular and aggregate oxides generates a significant electrostatic potential hence to induce the adhesion between the asphalt and aggregate in asphalt pavement. A microscopic molecular dynamics (MD) simulation incorporated with macroscopic adhesion work experiments is conducted to analyze the interface adhesive performance between the asphalt and aggregate. The adhesion work experiment demonstrated the effect of aggregate surface oxides on asphalt adhesion at the macro level and further verified the simulation results. The result demonstrated that a notable electron accumulation can be observed by MD at the interface of asphalt molecular and multiple oxides which generates the electrostatic potential. The strong electrostatic attractions and hydrogen bonds between alkaline oxides (MgO, CaO, CaCO3) and asphalt molecules enhance the relative concentration distribution, diffusion coefficient, and adhesion of asphalt on the aggregate surface. The significant electrostatic potential difference at the interface of the asphalt molecular and the oxide enables a strong adhesion between them due to the near-surface failure potential. Besides, the negative charge accumulation on both the benzene ring structure and oxygen atoms in the asphalt molecules results in poor adhesion at the interface of asphalt molecules and multiple oxides. It was found that a high correlation exists between the MD prediction and experimental testing results. Thus, this research provides a valuable tool for guiding the pairing and selection of asphalt with various minerals for pavement design, construction, and maintenance agencies.

Study of self-organization and structural phase transitions in water /AOT / isopropyl myristate biocompatible system

This work reports preparation and characterization of biocompatible sodium bis(2-ethylhexyl) sulfosuccinate (AOT) / water/ isopropyl myristate (IPM) systems. We studied their ability to form various self-organized structures such as microemulsions and liquid crystal templates for producing nanoparticles such as drug delivery vehicles, which play an important role in delivery of various substances. We determined concentration and temperature conditions that allow for forming various structures in this system and characterized the structural phase transition from the microemulsion to liquid crystalline phase, which is important for delivery of bioactive compounds. The parameters of the liquid crystalline phase of the water/AOT/isopropyl myristate system were calculated for the first time in this work. The sizes of microemulsion droplets were determined. To describe molecular motions in the studied microemulsion, self-diffusion coefficients of each component were measured. The values of relative diffusion coefficients demonstrated that reverse microemulsions were observed at AOT concentrations up to 60 % wt. Further increase in surfactant concentration slows down their molecular mobility and results in formation of aggregates with a bimodal size distribution and a subsequent formation of the hexagonal liquid crystalline phase. Geometry of the mesophase and its structure were investigated by X-ray diffraction. The respective phase diagram was plotted and analyzed using the data of polarized light microscopy, dynamic light scattering, and NMR self-diffusion. In this diagram, the areas corresponding to the microemulsion, the liquid crystal phase, and the structural phase transition were identified.The study of the structural phase transition from the microemulsion to liquid crystal will offer a predictive power for characterizing incorporation of drugs and controlling their delivery to target cells. A deeper understanding of the structural changes is necessary to clearly determine the conditions of drug delivery.

Noninvasive assessment of Ki-67 labeling index in glioma patients based on multi-parameters derived from advanced MR imaging.

To investigate the predictive value of multi-parameters derived from advanced MR imaging for Ki-67 labeling index (LI) in glioma patients. One hundred and nine patients with histologically confirmed gliomas were evaluated retrospectively. These patients underwent advanced MR imaging, including dynamic susceptibility-weighted contrast enhanced MR imaging (DSC), MR spectroscopy imaging (MRS), diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI), before treatment. Twenty-one parameters were extracted, including the maximum, minimum and mean values of relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), relative mean transit time (rMTT), relative apparent diffusion coefficient (rADC), relative fractional anisotropy (rFA) and relative mean diffusivity (rMD) respectively, and ration of choline (Cho)/creatine (Cr), Cho/N-acetylaspartate (NAA) and NAA/Cr. Stepwise multivariate regression was performed to build multivariate models to predict Ki-67 LI. Pearson correlation analysis was used to investigate the correlation between imaging parameters and the grade of glioma. One-way analysis of variance (ANOVA) was used to explore the differences of the imaging parameters among the gliomas of grade II, III, and IV. The multivariate regression showed that the model of five parameters, including rCBVmax (RC=0.282), rCBFmax (RC=0.151), rADCmin (RC= -0.14), rFAmax (RC=0.325) and Cho/Cr ratio (RC=0.157) predicted the Ki-67 LI with a root mean square (RMS) error of 0. 0679 (R2 = 0.8025).The regression check of this model showed that there were no multicollinearity problem (variance inflation factor: rCBVmax, 3.22; rCBFmax, 3.14; rADCmin, 1.96; rFAmax, 2.51; Cho/Cr ratio, 1.64), and the functional form of this model was appropriate (F test: p=0.682). The results of Pearson correlation analysis showed that the rCBVmax, rCBFmax, rFAmax, the ratio of Cho/Cr and Cho/NAA were positively correlated with Ki-67 LI and the grade of glioma, while the rADCmin and rMDmin were negatively correlated with Ki-67 LI and the grade of glioma. Combining multiple parameters derived from DSC, DTI, DWI and MRS can precisely predict the Ki-67 LI in glioma patients.

Predicting glioblastoma recurrence using multiparametric MR imaging of non-enhancing peritumoral regions at baseline

BackgroundTo assess the feasibility of multiparametric magnetic resonance imaging in predicting tumor recurrence in nonenhancing peritumoral regions in patients with glioblastoma at baseline. MethodsFifty-eight patients with recurrent glioblastoma underwent multiparametric magnetic resonance imaging, including T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging. Nonenhancing peritumoral regions with glioblastoma recurrence were identified by coregistering preoperative and post-recurrent magnetic resonance images. Regions of interest were placed in nonenhancing peritumoral regions with and without tumor recurrence to calculate the apparent diffusion coefficient value, and relative ratios of T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and cerebral blood volume values. ResultsSignificant lower relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative apparent diffusion coefficient but higher relative cerebral blood volume values were found in the nonenhancing peritumoral regions with tumor recurrence than without recurrence (all P < 0.05). The threshold values ≥ 0.89 for relative cerebral blood volume provide the optimal performance for predicting the nonenhancing peritumoral regions with future tumor recurrence, with the sensitivity, specificity, and accuracy of 84.7%, 83.6%, and 85.8%, respectively. The combination of relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative cerebral blood volume can provide better predictive performance than relative cerebral blood volume (P = 0.015). ConclusionThe combined use of T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging can effectively estimate the risk of future tumor recurrence at baseline.

Study on the Selection of Power Cable Rejuvenation Fluids Based on Relative Diffusion Coefficients

The present work presents and formulates a method for calculating the relative diffusion coefficient of rejuvenation fluid in injection cable rejuvenation technology, and the permeability characteristics of rejuvenation fluid in polyethylene insulation materials are calculated and compared. The main components of the rejuvenation fluid such as (Phenylmethyl-dimethoxysilane) PMDMS, (Diphenyldimethoxysilane) DPDMS and (Trimethylmethoxysilane) TMMS, and the catalysts such as (Tetra-isopropyl titanate) TIPT and (Tetra-isobutyl titanate) TIBT were analysed in depth. The article uses theoretical calculation method, combined with Helmroth and Limm-Hollifield models, to calculate the diffusion coefficients and relative diffusion coefficients of these compounds in polyethylene. Through comparative analysis of theoretical calculations, the optimal parameters for evaluating the permeability characteristics of rejuvenation fluids were determined. The research results show that TMMS has the best permeability characteristics in polyethylene, followed by PMDMS and DPDMS. In the catalyst, TIPT has better permeability characteristics than TIBT. And when selecting the composite formula for cable rejuvenation fluid, it is more convenient to use the relative diffusion coefficient as an index of diffusion characteristics. This research provides important theoretical basis and practical guidance for the formulation selection of cable rejuvenation fluids.

The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study.

Currently, there remains a scarcity of established preoperative tests to accurately predict the isocitrate dehydrogenase (IDH) mutation status in clinical scenarios, with limited research has explored the potential synergistic diagnostic performance among metabolite, perfusion, and diffusion parameters. To address this issue, we aimed to develop an imaging protocol that integrated 2-hydroxyglutarate (2HG) magnetic resonance spectroscopy (MRS) and intravoxel incoherent motion (IVIM) by comprehensively assessing metabolic, cellular, and angiogenic changes caused by IDH mutations, and explored the diagnostic efficiency of this imaging protocol for predicting IDH mutation status in clinical scenarios. Patients who met the inclusion criteria were categorized into two groups: IDH-wild type (IDH-WT) group and IDH-mutant (IDH-MT) group. Subsequently, we quantified the 2HG concentration, the relative apparent diffusion coefficient (rADC), the relative true diffusion coefficient value (rD), the relative pseudo-diffusion coefficient (rD*) and the relative perfusion fraction value (rf). Intergroup differences were estimated using t-test and Mann-Whitney U test. Finally, we performed receiver operating characteristic (ROC) curve and DeLong's test to evaluate and compare the diagnostic performance of individual parameters and their combinations. 64 patients (female, 21; male, 43; age, 47.0 ± 13.7years) were enrolled. Compared with IDH-WT gliomas, IDH-MT gliomas had higher 2HG concentration, rADC and rD (P < 0.001), and lower rD* (P = 0.013). The ROC curve demonstrated that 2HG + rD + rD* exhibited the highest areas under curve (AUC) value (0.967, 95%CI 0.889-0.996) for discriminating IDH mutation status. Compared with each individual parameter, the predictive efficiency of 2HG + rADC + rD* and 2HG + rD + rD* shows a statistically significant enhancement (DeLong's test: P < 0.05). The integration of 2HG MRS and IVIM significantly improves the diagnostic efficiency for predicting IDH mutation status in clinical scenarios.

Mechanisms and kinetic model for steel corrosion in unsaturated cementitious materials

Considering the complex coupling of steel corrosion in partially saturated concrete filled with water, the quantitative description of control mechanisms is still under debate. This work provides new experimental evidence supporting that diffusion control (relative diffusion coefficient) is the dominant mechanism in controlling corrosion rate by limiting the ferrous ion migration in unsaturated concrete. Furthermore, a new mechanism-based kinetic model is developed to predict the corrosion rate in different cementitious materials and corrosion conditions. In addition, the proposed kinetic model can quantify the variation of critical [Cl−]/[OH−] with degree of saturation, classify corrosive conditions, and predict the electrical resistivity and corrosion rate relationships.

The value of diffusion-weighted imaging in the natural history of meningiomas: a predictor of tumor growth.

The general trend in meningioma treatment is shifting from surgery to active surveillance. However, the natural history of meningioma still needs to be clarified, and a simple, practical method is needed to identify fast-growing tumors. The authors aimed to determine whether diffusion-weighted imaging (DWI) could be a valuable imaging modality for predicting meningioma growth. Consecutive asymptomatic patients with a meningioma diagnosed on MRI and followed up at the authors' institution between July 2011 and July 2019 were eligible for inclusion in this retrospective study. Univariable and multivariable Cox regression analyses were used to explore whether the relative apparent diffusion coefficient (rADC) was an independent predictor of meningioma growth. Correlations between tumor growth rate (TGR), tumor volume doubling time (VDT), Ki-67, and rADC were assessed using the Pearson correlation coefficient. The predictive ability of rADC was evaluated using receiver operating characteristic (ROC) curves and validated with internal validation data. Sixty-four patients (47 females, 17 males) with a mean age of 62.2 ± 1.4 years were included in this study. Univariable and multivariable analyses revealed that rADC was an independent predictor of meningioma growth (p < 0.05). ROC curve analysis showed that baseline rADC had good predictive power for growing meningiomas (AUC = 0.88, 95% CI 0.78-0.96), as well as slow- or fast-growing meningiomas (AUC = 0.83, 95% CI 0.59-0.98). Moreover, rADC still had a good ability to discriminate between growing and nongrowing meningiomas in the validation set (AUC = 0.85, 95% CI 0.64-1.00). In the 20 patients with tumor growth, baseline rADC was moderately negatively correlated with TGR (r = -0.50, p = 0.02) and strongly positively correlated with VDT (r = 0.63, p = 0.003). Moreover, Ki-67 was significantly associated with rADC in 8 patients who had undergone surgery (r = -0.75, p = 0.03). In asymptomatic meningiomas, the lower the rADC at baseline, the faster the TGR and the shorter the VDT. DWI could be a valuable tool in predicting meningioma growth in asymptomatic patients.

Separation of active chiral particles with different diffusion coefficients

In recent years, the study of active particles has become one of the important topics concerned by researchers in many fields, among which the phase separation of active chiral particles has important theoretical and practical significance. In this paper, the phase separation of binary mixed systems composed of active chiral particles with different diffusion coefficients is studied by Langevin dynamics. A smaller relative diffusion coefficient is conducive to the formation of large clusters and the separation of “cold” particles, while a larger relative diffusion coefficient will weaken the separation effect. Due to the influence of particle characteristics (self-driven velocity, self-rotational angular velocity) and relative diffusion coefficient on the collision between particles, if one wants the “cold” and “hot” particles to reach phase separation, increasing (or reducing) the self-driven velocity and self-rotational angular velocity cannot be synchronous, and the relative rate of change of self-driven velocity is smaller than that of the self-rotational angular velocity. By analyzing the changes of the effective diffusion coefficient of “cold” particles, the phenomenon of phase separation in the system can be better explained. A smaller effective diffusion coefficient means that the “cold” particles will aggregate into larger clusters, and the system may exhibit phase separation. However, when the effective diffusion coefficient is larger, the diffusion of “cold” particles is stronger and the “cold” particles will not form large clusters, which means that the system cannot aggregate into phase separation. In addition, with the filling rate of particle increasing, the proportion curve of the number of cold particles in maximum cold particle cluster undergoes a non-monotonic change, specifically, it first increases and then decreases. Each curve has an optimal filling rate but its width is different .With the increase of the relative diffusion coefficient and self-driven velocity, the width of the optimal filling rate of the proportion curve will become narrower and shift toward the right.

Pore‐Scale Modeling of Water and Ion Diffusion in Partially Saturated Clays

AbstractAn accurate mechanistic understanding of solute diffusion in partially saturated clays is critical for assessing the safety of deep geological repositories for radioactive waste. In this study, a pore‐scale numerical framework is developed to simulate water and ion diffusion in partially saturated clays. First, the two‐phase Shan‐Chen Lattice Boltzmann method is employed to establish the liquid‐gas distribution in a reconstructed three‐dimensional pore geometry of a clay. An equivalent solute method is also developed and validated to improve the numerical stability of the solution at the liquid/gas interface corresponding to steep variations of the concentration and diffusion coefficient of the water tracer. By using a mobility‐distance relationship from molecular simulations, Fick's law is numerically solved to simulate water diffusion in nanopores, while the coupled Poisson‐Boltzmann‐Nernst‐Planck equations are solved to simulate ion diffusion under the influence of the electrical double layer (EDL). Our model reveals that the decrease of relative effective diffusion coefficients during the desaturation is more pronounced for ions than for water, due to the additional transport pathway of water tracers in the gas phase. The obtained effective diffusion coefficients of tritiated water and ions agree well with reported data from compacted sedimentary rocks. By comparing the local electric potential and the distribution of ion concentrations in single pores, the simulation results suggest that the EDL in unsaturated clays has a more complex influence on ion distribution than under fully water‐saturated conditions. This study provides critical insights into the coupled transport processes of solutes in partially saturated clays.

(Invited) Ratchet Based Ion Pumps for Selective Ion Separations

Even though highly selective ion pumps are found in the membrane of every living cell, artificial ion selective separation is a longstanding unmet challenge in science and engineering. The development of a membrane-based ion separation technology can drive a dramatic progress in a wide range of applications such as: water treatment, bio-medical devices, extraction of precious metals from sea water, chemical sensors, solar fuels and more. In this contribution we report the experimental demonstration of ion pumps based on a electronic ratchet mechanism.Electronic ratchets are devices that utilize a temporal modulation of a spatially asymmetric electric field to drive steady state current. Like peristaltic pumps, where the pump mechanism is not in direct contact with the pumped fluid, electronic ratchets induce a net current with no direct charge transport between the power source and the pumped charge carriers. Thus, electronic ratchets can be used to pump ions in steady state with no electrochemical reactions between the power source and the pumped ions resulting in an 'all-electric' ion pump.Ratchet-based ion pumps (RBIPs) were fabricated by coating the two surfaces of nano-porous alumina wafers with gold, thus forming nano-porous capacitor-like devices. The electric field within the nano-pores is modulated by oscillating the capacitor voltage. Thus, when immersed in a solution, ions within the pores experience a modulating electric field resulting in ratchet-based ion pumping. The RBIPs performance was studied for various input signals, geometries, and solutions. RBIPs were shown to drive ionic current densities of several uA/cm^2 even when opposed by an electrostatic force. A significant ratchet action was observed with input signal amplitudes as low as 0.1V thus demonstrating that RBIPs can drive an ionic current with no associated redox reactions.An important hallmark of ratchets is the ability to invert the direction of particle flow with a change in the input signal frequency. The stopping frequency, which is the frequency at which the particle flux changes its direction, is determined by the potential distribution and particles transport properties. As a result, for a given ratchet, there can be a frequency at which particles with the same charge, but different diffusion coefficients, are transported in opposite directions. This concept, that was never applied to ion separations, can enable the extraction of ions with extremely low relative concentrations if their diffusion coefficient is even slightly different from the main ions in the solution. We show by simulation, that for the prevalent ions in water, ions with a relative diffusion coefficient difference as small as 1% can be driven to opposite directions with a velocity difference as high as 1.2 mm/s. Since the direction of ion transport is determined by the input signal frequency, the sorting properties can be tuned in real time providing a simple fit-to-purpose solution for a variety of ion separations applications. Figure 1

A novel lattice model to predict chloride diffusion coefficient of unsaturated cementitious materials based on multi-typed pore structure characteristics

This paper develops a novel lattice diffusive model to quantitatively study the chloride diffusion coefficient in unsaturated cementitious materials, in which the pore voxels are redistributed to make a better representation of a real microstructure of hardened cement paste. Considering the hierarchical microstructure and different drying-wetting cycles, water distributions in multiscale pore structures are modelled and the structure characteristics of water-filled pores, including water connectivity, water tortuosity and effective porosity, are computationally extracted based on that. A lattice diffusion network is established to predict relative chloride diffusion coefficient by combining the effect of both water saturation degree and pore structure characteristics. The predicted results are validated against experimental data, and a concise analytical equation is proposed to predict the relative chloride diffusion coefficient. The equation indicated that the relative chloride diffusion coefficient is proportional to water connectivity but inversely proportional to the square of water tortuosity. Besides, the lattice model's quantitative results reveal that the water connectivity and water tortuosity are highly related to pre-water loading processes, and influenced by the gel pore fraction, which in turn will affect the relative chloride diffusion coefficient. Compared with existing equations and non-redistributed models, the present model could improve the prediction accuracy significantly.

Magnetic Resonance Imaging Combined with Histological Techniques for Dynamic Assessment of Cytotoxic Edema after Cerebral Ischemia-Reperfusion Injury.

Reperfusion therapy after ischemic cerebral stroke may cause cerebral ischemia-reperfusion injury (CIRI), and cerebral edema is an important factor that may aggravate CIRI. Our study aimed to dynamically monitor the development of early cytotoxic edema after CIRI by magnetic resonance imaging (MRI) and to validate it using multiple histological imaging methods. Male Sprague Dawley rats were divided into sham and CIRI groups. T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI)-MRI scans were performed in the sham and CIRI groups after reperfusion. Relative apparent diffusion coefficient (rADC) values were calculated and the midline shift (MLS) was measured. A series of histological detection techniques were performed to observe changes in the cerebral cortex and striatum of CIRI rats. Correlation analysis of rADC values with aquaporin-4 (AQP4) and sodium-potassium-chloride cotransport protein 1 (Na+-K+-2Cl-- cotransporter 1; NKCC1) was performed. rADC values began to increase and reached a relatively low value in the cerebral cortex and striatum at 24 h after reperfusion, and the MLS reached relatively high values at 24 h after reperfusion (all p < 0.05). Hematoxylin-eosin (HE) staining showed that the nerve cells in the cortex and striatum of the sham group were regular in morphology and neatly arranged, and in the CIRI-24 h group were irregular, disorganized, and loosely structured. Using terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining, the number of TUNEL+ cells in the ischemic cortex and striatum in CIRI-24 h group was shown to increase significantly compared with the sham group (p < 0.05). Transmission electron microscopy showed that the perivascular astrocytic foot processes were swollen in the cortex and striatum of the CIRI-24 h group. Pearson correlation analysis demonstrated that rADC values were negatively correlated with the number of anti-glial fibrillary acidic protein (GFAP)+AQP4+ and GFAP+NKCC1+ cells of the CIRI rats. MRI combined with histological techniques can dynamically assess cytotoxic edema after CIRI, in a manner that is clear and intuitive for scientific researchers and clinicians, and provides a scientific basis for the application of MRI techniques for monitoring the dynamic progress of CIRI.

Effects of bulk viscosity, heat capacity ratio, and Prandtl number on the dispersion relationship of compressible flows

Here, we present the variation of the dispersion characteristics of the three-dimensional (3D) linearized compressible Navier–Stokes equation (NSE) to bulk viscosity ratio, specific heat ratio (γ), and Prandtl number (Pr). The 3D compressible NSE supports five types of waves, two vortical, one entropic, and two acoustic modes. While the vortical and entropic modes are non-dispersive, the acoustic modes are dispersive only up to a specific bifurcation wavenumber. We illustrate the characteristics and variation of relative (with respect to the vortical mode) diffusion coefficient for entropic and acoustic modes and a specially designed dispersion function for acoustic modes with depressed wavenumber η=KM/Re, the bulk viscosity ratio, γ, and Prandtl number Pr of the flow. Here, K, M, and Re denote the absolute wavenumber of disturbances, Mach number, and Reynolds number of the flow, respectively. At lower wavenumber components, the deviation of the dispersion function from the inviscid and adiabatic case is proportional to η2 at the leading order, and the relative diffusion coefficients increase linearly with bulk viscosity ratio and γ while varying inversely with Pr. With the increase in the bulk viscosity ratio, the shape and extent of the dispersion function alter significantly, and the change is more substantial for higher wavenumber components. The relative diffusion coefficient for entropic and acoustic modes shows contrasting variation with wavenumber depending upon bulk viscosity ratio, γ, and Pr. We also show by solving linearized compressible NSE that relatively significant evolution and radiation of acoustic and entropic disturbances occur when the bulk viscosity ratio is close to the corresponding critical value of maximum bifurcation wavenumber. Based on this criterion, we have presented an empirical relation for estimating bulk viscosity ratio depending upon γ and Pr, giving the corresponding range for obtaining relatively significant disturbance evolution.