Estimated Pore Size Research Articles

Applicability and safety of dual-frequency ultrasonic treatment for the transdermal delivery of drugs

Low-frequency ultrasound presents an attractive method for transdermal drug delivery. The controlled, yet non-specific nature of enhancement broadens the range of therapeutics that can be delivered, while minimizing necessary reformulation efforts for differing compounds. Long and inconsistent treatment times, however, have partially limited the attractiveness of this method. Building on recent advances made in this area, the simultaneous use of low- and high-frequency ultrasound is explored in a physiologically relevant experimental setup to enable the translation of this treatment to testing in vivo. Dual-frequency ultrasound, utilizing 20kHz and 1MHz wavelengths simultaneously, was found to significantly enhance the size of localized transport regions (LTRs) in both in vitro and in vivo models while decreasing the necessary treatment time compared to 20kHz alone. Additionally, LTRs generated by treatment with 20kHz+1MHz were found to be more permeable than those generated with 20kHz alone. This was further corroborated with pore-size estimates utilizing hindered-transport theory, in which the pores in skin treated with 20kHz+1MHz were calculated to be significantly larger than the pores in skin treated with 20kHz alone. This demonstrates for the first time that LTRs generated with 20kHz+1MHz are also more permeable than those generated with 20kHz alone, which could broaden the range of therapeutics and doses administered transdermally. With regard to safety, treatment with 20kHz+1MHz both in vitro and in vivo appeared to result in no greater skin disruption than that observed in skin treated with 20kHz alone, an FDA-approved modality. This study demonstrates that dual-frequency ultrasound is more efficient and effective than single-frequency ultrasound and is well-tolerated in vivo.

Model-Based Estimation of Microscopic Anisotropy in Macroscopically Isotropic Substrates Using Diffusion MRI.

Non-invasive estimation of cell size and shape is a key challenge in diffusion MRI. Changes in cell size and shape discriminate functional areas in the brain and can highlight different degrees of malignancy in cancer tumours. Consequently various methods have emerged recently that aim to measure the microscopic anisotropy of porous media such as biological tissue and aim to reflect pore eccentricity, the simplest shape feature. However, current methods assume a substrate of identical pores, and are strongly influenced by non-trivial size distribution. This paper presents a model-based approach that provides estimates of pore size and shape from diffusion MRI data. The technique uses a geometric model of randomly oriented finite cylinders with gamma distributed radii. We use Monte Carlo simulation to generate synthetic data in substrates consisting of randomly oriented cuboids with various size distributions and eccentricities. We compare the sensitivity of single and double pulsed field gradient (sPFG and dPFG) sequences to the size distribution and eccentricity and further compare different protocols of dPFG sequences with parallel and/or perpendicular pairs of gradients. The key result demonstrates that this model-based approach can provide features of pore shape (specifically eccentricity) that are independent of the size distribution unlike previous attempts to characterise microscopic anisotropy. We show further that explicitly accounting for size distribution is necessary for accurate estimates of average size and eccentricity, and a model that assumes a single size fails to recover the ground truth values. We find the most accurate parameter estimates for dPFG sequences with mixed parallel and perpendicular gradients, nevertheless all other sequences, including sPFG, show sensitivity as well.

Integration of lateral porous silicon membranes into planar microfluidics.

In this work, we present a novel fabrication process that enables the monolithic integration of lateral porous silicon membranes into single-layer planar microchannels. This fabrication technique relies on the patterning of local electrodes to guide pore formation horizontally within the membrane and on the use of silicon-on-insulator substrates to spatially localize porous silicon within the channel depth. The feasibility of our approach is studied by current flow analysis using the finite element method and supported by creating 10 μm long mesoporous membranes within 20 μm deep microchannels. The fabricated membranes are demonstrated to be potentially useful for dead-end microfiltration by adequately retaining 300 nm diameter beads while macromolecules such as single-stranded DNA and immunoglobulin G permeate the membrane. The experimentally determined fluidic resistance is in accordance with the theoretical value expected from the estimated pore size and porosity. The work presented here is expected to greatly simplify the integration of membranes capable of size exclusion based separation into fluidic devices and opens doors to the use of porous silicon in planar lab on a chip devices.

Antibiotic translocation through porins studied in planar lipid bilayers using parallel platforms.

In general, the method of choice to characterize the conductance properties of channel-forming bacterial porins is electrophysiology. Here, the classical method is to reconstitute single porins into planar lipid bilayers to derive functional information from the observed channel conductance. In addition to an estimated pore size, ion selectivity or transport properties in general are of importance. For the latter, measuring the ion current fluctuation can provide some information about the mode of transport of charged molecules penetrating the proteins. For instance, increasing the external voltage modifies the residence time in the channel: charged molecules with the ability to permeate through channels will travel faster whereas non-permeating molecules get pushed to the constriction zone with enhanced residence time. Here, we are interested in the ability of antibiotics to permeate channels and compare different techniques to reveal fast events.

New lights in light's criteria

Aims Nuclear magnetic resonance (NMR) spectroscopy-based metabolome-wide association studies (MWAS) has been increasingly used in advanced laboratory medicine and biomarker discovery. Here, we will apply NMR-based MWAS to develop new diagnostic test for exudative and transudative pleural effusions (PE) with improved accuracy. Methods PE will be classified into exudates and transudates according to the etiology and analyzed using 1 H-NMR spectroscopy (600 MHz). Biomarkers will be determined using MWAS using Receiver Operating Characteristic Curve Explorer and Tester (ROCCET) and filtered using a metabolome-wide significance level (MWSL) at p value −6 . Results There were 50 exudates and 17 transudates. Using MWAS, lipoprotein was determined to be the best biomarker that differentiated exudates from transudates ( p value: 1.01 × 10 −10 ) with an area-under-ROC curve of 0.96 (95% CI: 0.89–0.99), sensitivity of 98% and specificity of 88%. The diagnostic performance is superior to the current standard, Light's criteria, which showed a specificity of 65% despite the same sensitivity at 98%. Discussion The high level of lipoproteins in exudates is related to the larger capillary pore-size secondary to inflammation. In contrast, without inflammation, the capillary pore-size remains intact in transudates. We envisage NMR-based lipoprotein profiling will be a powerful tool for pleural capillary pore-size estimation and will become a new standard.

Simultaneous Gaussian and exponential inversion for improved analysis of shales by NMR relaxometry

Nuclear magnetic resonance (NMR) relaxometry is commonly used to provide lithology-independent porosity and pore-size estimates for petroleum resource evaluation based on fluid-phase signals. However in shales, substantial hydrogen content is associated with solid and fluid signals and both may be detected. Depending on the motional regime, the signal from the solids may be best described using either exponential or Gaussian decay functions. When the inverse Laplace transform, the standard method for analysis of NMR relaxometry results, is applied to data containing Gaussian decays, this can lead to physically unrealistic responses such as signal or porosity overcall and relaxation times that are too short to be determined using the applied instrument settings. We apply a new simultaneous Gaussian-Exponential (SGE) inversion method to simulated data and measured results obtained on a variety of oil shale samples. The SGE inversion produces more physically realistic results than the inverse Laplace transform and displays more consistent relaxation behavior at high magnetic field strengths. Residuals for the SGE inversion are consistently lower than for the inverse Laplace method and signal overcall at short T2 times is mitigated. Beyond geological samples, the method can also be applied in other fields where the sample relaxation consists of both Gaussian and exponential decays, for example in material, medical and food sciences.

Pleural effusion lipoproteins measured by NMR spectroscopy for diagnosis of exudative pleural effusions: a novel tool for pore-size estimation.

High-resolution proton nuclear magnetic resonance (NMR) spectrometry of biofluids has been increasingly used in laboratory diagnosis of various diseases. In this study, we extended the use of (1)H NMR spectroscopy for laboratory diagnosis of exudative pleural effusions using pleural fluids. We compared this new NMR-based test with Light's criteria, the current gold standard for laboratory diagnosis of exudative pleural effusions. We analyzed 67 samples of pleural effusions from patients with pulmonary malignancy (N = 32), pulmonary tuberculosis (N = 18), and congestive heart failure (N = 17). The metabolomes of pleural effusions were analyzed using (1)H NMR spectroscopy on a Bruker 600 MHz spectrometer. Through a metabolome-wide association approach with filtering of insignificant markers (p value <4 × 10(-6)) and multivariate analysis (principal component analysis and orthogonal partial least squares-discriminant analysis), lipoprotein was found to be the best biomarker that distinguished exudates from transudates. Using NMR-based lipoprotein profiling to classify exudative pleural effusions from transudates, the area-under-receiver operating characteristic (ROC) curve was 0.96 with sensitivity of 98%, specificity of 88%, and accuracy of 98%. In contrast, the current gold standard, Light's criteria, give a specificity of only 65% at the same sensitivity level of 98%. Using the principle of size exclusion, NMR-based lipoprotein profiling of pleural fluids has an unprecedented diagnostic performance superiority over the Light's criteria. The capillary leaks secondary to inflammation result in a larger pleural pore-size, which allows the large-sized lipoproteins to accumulate in exudative pleural effusions. In contrast, the pleural permeability is intact in transudates, which allow only small-sized lipoproteins to pass into the pleural effusions. The average capillary pore-size of the pleura can therefore be determined by using NMR-based lipoprotein profiling of pleural fluids. We believe this new test will change the current clinical practice for management of pleural effusions and will become a new standard for clinical practice.

Pore Size Estimation of Mesoporous Materials through Surfactant Self-Assembly Prediction

Abstract A theoretical model for pore size estimation of mesoporous materials was presented in this paper. It is based on the statistical thermodynamic model of micelle formation proposed by R. Nagarajan. The proposed model was applied to predict the pore size of MSU-X molecular sieve prepared in different synthetic systems. The estimation results were compared with reliable experimental measurements. The level of deviation is acceptable with the substantial simplifications included in the model. Hansen solubility parameter and Dimroth-Reichardt parameter were introduced to explain the discrepancies. The proposed model may help to screen suitable synthesis conditions and guide the controllable synthesis of molecular sieve to some extent.

Underwater Superoleophobicity Induced by the Thickness of the Thermally Grown Porous Oxide Layer on C84400 Copper Alloy

The underwater contact angle behavior on oxide layers of varying thicknesses was studied. These oxide layers were grown by thermally oxidizing C84400 copper alloys in N2-0.75 wt.% O2 and N2-5 wt.% O2 gas mixtures at 650 °C. Characterization of the oxidized specimens was effected using X-ray diffraction, scanning electron microscope (SEM) and contact angle goniometer. The results from the X-ray diffraction analyses confirmed the formation of CuO, ZnO and PbO. The average sizes of the oxide granules were in the range of 70 nm to 750 nm, with the average thickness of the oxide layer increasing with the increase in the weight percent of oxygen in the N2-O2 gas mixtures. The results showed that the oxide layer growth followed the parabolic law. The underwater oil contact angles increased, due to the change in the surface morphology and porosity of the oxide layer. The small sizes and irregular packing of the oxide granules cause hierarchical rough surface layers with pores. The estimated pore sizes, in the range of 88 ± 40 to 280 ± 76, were predominant on the oxide layers of the samples processed in the N2-5 wt.% O2 gas mixture. The presence of these pores caused an increase in the porosities as the thickness of the oxide layers increased. At oxide layer thickness above 25 microns, the measured contact angle exceeded 150° as underwater superoleophobicity was recorded.

A hydrogel-based tumor model for the evaluation of nanoparticle-based cancer therapeutics

Three-dimensional (3D) tissue-engineered tumor models have the potential to bridge the gap between monolayer cultures and patient-derived xenografts for the testing of nanoparticle (NP)-based cancer therapeutics. In this study, a hydrogel-derived prostate cancer (PCa) model was developed for the in vitro evaluation of doxorubicin (Dox)-loaded polymer NPs (Dox-NPs). The hydrogels were synthesized using chemically modified hyaluronic acid (HA) carrying acrylate groups (HA-AC) or reactive thiols (HA-SH). The crosslinked hydrogel networks exhibited an estimated pore size of 70–100 nm, similar to the spacing of the extracellular matrices (ECM) surrounding tumor tissues. LNCaP PCa cells entrapped in the HA matrices formed distinct tumor-like multicellular aggregates with an average diameter of 50 μm after 7 days of culture. Compared to cells grown on two-dimensional (2D) tissue culture plates, cells from the engineered tumoroids expressed significantly higher levels of multidrug resistance (MDR) proteins, including multidrug resistance protein 1 (MRP1) and lung resistance-related protein (LRP), both at the mRNA and the protein levels. Separately, Dox-NPs with an average diameter of 54 ± 1 nm were prepared from amphiphilic block copolymers based on poly(ethylene glycol) (PEG) and poly(ε-caprolactone) (PCL) bearing pendant cyclic ketals. Dox-NPs were able to diffuse through the hydrogel matrices, penetrate into the tumoroid and be internalized by LNCaP PCa cells through caveolae-mediated endocytosis and macropinocytosis pathways. Compared to 2D cultures, LNCaP PCa cells cultured as multicellular aggregates in HA hydrogel were more resistant to Dox and Dox-NPs treatments. Moreover, the NP-based Dox formulation could bypass the drug efflux function of MRP1, thereby partially reversing the resistance to free Dox in 3D cultures. Overall, the engineered tumor model has the potential to provide predictable results on the efficacy of NP-based cancer therapeutics.

Relating rejection of trace organic contaminants to membrane properties in forward osmosis: Measurements, modelling and implications

This study elucidates the relationship between membrane properties and the rejection of trace organic contaminants (TrOCs) in forward osmosis (FO). An asymmetric cellulose triacetate (CTA) and a thin-film composite (TFC) polyamide FO membrane were used for this investigation. The effective average pore radius (rp), selective barrier thickness over porosity parameter (l/ε), surface charge, support layer structural parameter (S), pure water permeability coefficient (A) and salt (NaCl) permeability coefficient (B) of the two membranes were systematically characterised. Results show that measured rejection of TrOCs as a function of permeate water flux can be well described by the pore hindrance transport model. This observation represents the first successful application of this model, which was developed for pressure-driven nanofiltration, to an osmotically-driven membrane process. The rejection of charged TrOCs by the CTA and TFC membranes was high and was governed by both electrostatic repulsion and steric hindrance. The TFC membrane exhibited higher rejection of neutral TrOCs with low molecular weight than the CTA membrane, although the estimated pore size of the TFC membrane (0.42 nm) was slightly larger than that of the CTA membrane (0.37 nm). This higher rejection of neutral TrOCs by the TFC membrane is likely attributed to its active layer properties, namely a more effective active layer structure, as indicated by a larger l/ε parameter, and pore hydration induced by the negative surface charge.

GCMC simulation of argon adsorption in wedge shaped mesopores of finite length

We have used Grand Canonical Monte Carlo simulation to study argon adsorption at 87 K in wedge shaped mesopores. The structural parameters, including mean pore size, wall length and wedge angle, were varied to investigate their effects on the size, shape and the position of the hysteresis loop. Although the effects of pore size have been studied previously, the wall length and wedge angle have received little attention. We find that the wedge angle can have a significant effect on the existence, position, size and shape of the hysteresis loop, while the wall length affects the adsorptive capacity associated with the loop and the behaviour of the isotherm beyond the loop. The results of this work have far-reaching consequences for the characterization of pore size distribution where it is commonly assumed, when constructing a kernel of local isotherms, that pore size is uniform, since even a small deviation from a constant pore width can shift the condensation and evaporation pressures significantly and thus lead to an incorrect estimation of pore size.

Axon radius estimation with Oscillating Gradient Spin Echo (OGSE) diffusion MRI

The estimation of axon radius provides insights into brain function [1] and could provide progression and classification biomarkers for a number of white matter diseases [2-4]. A recent in silico study [5] has shown that optimised gradient waveforms (GEN) and oscillating gradient waveform spin echo (OGSE) have increased sensitivity to small axon radius compared to pulsed gradient spin echo (PGSE) diffusion MR sequences. In a follow-up study [6], experiments with glass capillaries show the practical feasibility of GEN sequences and verify improved pore-size estimates. Here, we compare PGSE with sine, sine with arbitrary phase, and square wave OGSE (SNOGSE, SPOGSE, SWOGSE, respectively) for axon radius mapping in the corpus callosum of a rat, ex-vivo. Our results suggest improvements in pore size estimates from OGSE over PGSE, with greatest improvement from SWOGSE, supporting theoretical results from [5] and other studies [7-9].

Application of Artificial Neural Networks and Support Vector Machines for carbonate pores size estimation from 3D seismic data

This paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3D seismic data. To this end, an actual carbonate oil field in the south-western part of Iran was selected. Taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values. Seismic surveying was performed next on these models. From seismic response of the models, a large number of seismic attributes were identified as candidates for pore size estimation. Classes of attributes such as energy, instantaneous, and frequency attributes were included amongst others. Applying sensitivity analysis, we determined Instantaneous Amplitude and asymmetry as the two most significant attributes. These were subsequently used in our machine learning algorithms. In particular, we used feedforward artificial neural networks (FNN) and support vector regression machines (SVR) to develop relationships between the known attributes and pore size values in a given setting. The FNN consists of twenty one neurons in a single hidden layer and the SVR method uses a Gaussian radial basis function. Compared with real values from the well data, we observed that SVM performs better than FNN due to its better handling of noise and model complexity.

A simple shape-free model for pore-size estimation with positron annihilation lifetime spectroscopy

Positron annihilation lifetime spectroscopy is one of the methods for estimating pore size in insulating materials. We present a shape-free model to be used conveniently for such analysis. A basic model in classical picture is modified by introducing a parameter corresponding to an effective size of the positronium (Ps). This parameter is adjusted so that its Ps-lifetime to pore-size relation merges smoothly with that of the well-established Tao-Eldrup model (with modification involving the intrinsic Ps annihilation rate) applicable to very small pores. The combined model, i.e., modified Tao-Eldrup model for smaller pores and the modified classical model for larger pores, agrees surprisingly well with the quantum-mechanics based extended Tao-Eldrup model, which deals with Ps trapped in and thermally equilibrium with a rectangular pore.

Nanoparticle contrast agents to elucidate the structure of thin film composite nanofiltration membranes

The physical examination of pore size and nanostructure of nanofiltration (NF) membranes by imaging has proved elusive. In particular, until recently, no technique has been developed to image nanopores with dimensions in the 0.5–2nm range. These pores are crucial for the functional performance of NF membranes, and thus characterisation of their architecture might lead to tailored design of membranes for specific separation processes. This progress might be achieved via improvement in understanding the membrane structure described at the macromolecular level. Electron microscopy imaging of nanoporous polymers at sub-nanometre resolution is difficult due to insufficient electron contrast of polymers. One new approach to improving the characterisation methods is the use of high electron contrast osmium dioxide (OsO2) nanoparticles (NP), which are lodged in situ into the membrane pores. By mapping these nanoprobes using transmission electron microscopy (TEM), polymer nanostructures can be imaged at magnifications near the macromolecular level. In this paper, organic solvent nanofiltration (OSN) membranes with thin film composite (TFC) structures were characterised in terms of the permeation pathway (‘pore’) size and separation layer morphology. The estimated pore size correlates well with the solute rejection, implying that pore-flow models may be useful for describing the transport through the membranes.

Estimation of pore size distribution using concentric double pulsed-field gradient NMR

Estimation of pore size distribution of well calibrated phantoms using NMR is demonstrated here for the first time. Porous materials are a central constituent in fields as diverse as biology, geology, and oil drilling. Noninvasive characterization of monodisperse porous samples using conventional pulsed-field gradient (PFG) NMR is a well-established method. However, estimation of pore size distribution of heterogeneous polydisperse systems, which comprise most of the materials found in nature, remains extremely challenging. Concentric double pulsed-field gradient (CDPFG) is a 2-D technique where both q (the amplitude of the diffusion gradient) and φ (the relative angle between the gradient pairs) are varied. A recent prediction indicates this method should produce a more accurate and robust estimation of pore size distribution than its conventional 1-D versions. Five well defined size distribution phantoms, consisting of 1–5 different pore sizes in the range of 5–25μm were used. The estimated pore size distributions were all in good agreement with the known theoretical size distributions, and were obtained without any a priori assumption on the size distribution model. These findings support that in addition to its theoretical benefits, the CDPFG method is experimentally reliable. Furthermore, by adding the angle parameter, sensitivity to small compartment sizes is increased without the use of strong gradients, thus making CDPFG safe for biological applications.

Probing hysteresis during sorption of cyclohexane within mesoporous silica using NMR cryoporometry and relaxometry

The conventional data analysis methods for obtaining a pore size distribution (PSD) from gas sorption data make several critical assumptions that impact significantly on the accuracy of the PSD thereby obtained. In particular, assumptions must be made concerning the nature of the pore-filling or emptying process in adsorption, or desorption, respectively. The possibility of pore–pore interactions is also generally neglected. In this work, NMR cryoporometry and relaxometry have been used to study the adsorption and desorption of cyclohexane within a mesoporous, sol–gel silica catalyst support pellet with the aim of assessing the impact of the aforementioned problems for gas sorption PSDs and developing solutions. The advanced melting effect makes cryoporometry a particularly sensitive probe of adsorbate ganglia spatial distribution. It has been demonstrated that utilising gas sorption scanning curves provided insufficient additional information to alleviate the aforementioned problems with interpreting gas sorption data. The NMR data has shown how the nature of the sorption hysteresis changed with amount adsorbed, due to detectable variations in the mechanisms of pore-filling and emptying along the isotherm. Hence, relating a particular condensation or evaporation pressure to a specific characteristic pore size is not as straightforward as assumed in typical pore size analysis software. However, the NMR techniques reveal the additional information required to improve pore size estimates from gas sorption for disordered solids.

Microgels or microcapsules? Role of morphology on the release kinetics of thermoresponsive PNIPAm-co-PEGMa hydrogels

The effect of morphology of PNIPAm, PEGMa and PNIPAm-co-PEGMa hydrogels on the uptake and delivery (release kinetics) of a model drug (FITC–dextran) was investigated. Two types of hydrogel architectures: microgels and microcapsules, without and with core–shell morphology, were synthesized. The microcapsules had 30–50% greater uptake compared to the corresponding microgel architecture. The estimated pore size for the PNIPAm, PNIPAm-co-PEGMa and PEGMa hydrogels were 78, 92 and 130 A, respectively. The drug release was performed at 25, 37 (physiological temperature), and 45 °C (targeted stimulating temperature). Diffusion coefficients at temperatures below VPTT of the microgels showed close correlation with the pore size, but this was not the case for the microcapsules. The release kinetics is dominated by temperature responsiveness at T greater than the VPTT and by hydrogel morphology at T VPTT. More than 80% of the drug was released in the first 10 min using the temperature responsive microcapsule, compared to 1 h for the corresponding microgel. Unlike prior reports in the literature, the release of FITC–dextran is characteristic of a Super Case II Fickian diffusion and Anomalous release mechanism for the copolymer microgels when T > VPTT and for the PNIPAm and PEGMa microgels when T < VPTT. These results demonstrate the feasibility of modulating the release profile of encapsulated proteins (for tissue repair), chemotherapeutics (for drug delivery) and nucleic acids (for gene delivery) by tailoring the polymer morphology.

Micropore size estimation on gas separation membranes: A study in experimental and molecular dynamics

The effect of the gas molecular size and its affinity to the pore surface on gas permeation properties through the ceramic membranes was studied by both the gas permeation experiments and gas permeation simulations using a nonequilibrium molecular dynamics (MD) technique. A modified gas permeation model equation based on the gas translation (GT) mechanism was presented. MD simulation revealed that the effective diffusion length in a micropore depended on the gas molecular size, and the pre‐exponential coefficient of a modified GT model equation showed good correlation with the kinetic diameter of the gas molecules. Also presented is a simple method to estimate the mean pore size of microporous membranes. The estimated pore sizes were consistent with observed kinetic diameter dependencies of gas permeance for real silica membranes. The pore size of a Deca‐Dodecasil 3R (DDR) zeolite membrane was also reasonably estimated at ∼0.4 nm from the reported gas permeation data. © 2012 American Institute of Chemical Engineers AIChE J, 59: 2179–2194, 2013