Neuroanatomical Predictors of Transcranial Direct Current Stimulation (tDCS)-Induced Modifications in Neurocognitive Task Performance in Typically Developing Individuals.

Transcranial direct current stimulation (tDCS) is a noninvasive neuromodulation technique gaining more attention in neurodevelopmental disorders (NDDs). Due to the phenotypic heterogeneity of NDDs, tDCS is unlikely to be equally effective in all individuals. The present study aimed to establish neuroanatomical markers in typically developing (TD) individuals that may be used for the prediction of individual responses to tDCS. Fifty-seven male and female children received 2 mA anodal and sham tDCS, targeting the left dorsolateral prefrontal cortex (DLPFCleft), right inferior frontal gyrus, and bilateral temporoparietal junction. Response to tDCS was assessed based on task performance differences between anodal and sham tDCS in different neurocognitive tasks (N-back, flanker, Mooney faces detection, attentional emotional recognition task). Measures of cortical thickness (CT) and surface area (SA) were derived from 3 Tesla structural MRI scans. Associations between neuroanatomy and task performance were assessed using general linear models (GLM). Machine learning (ML) algorithms were employed to predict responses to tDCS. Vertex-wise estimates of SA were more closely linked to differences in task performance than measures of CT. Across ML algorithms, highest accuracies were observed for the prediction of N-back task performance differences following stimulation of the DLPFCleft, where 65% of behavioral variance was explained by variability in SA. Lower accuracies were observed for all other tasks and stimulated regions. This suggests that it may be possible to predict individual responses to tDCS for some behavioral measures and target regions. In the future, these models might be extended to predict treatment outcome in individuals with NDDs.

Asymmetrical cortical surface area decrease in epilepsy patients with postictal generalized electroencephalography suppression.

Postictal generalized electroencephalographic suppression is a possible electroencephalographic marker for sudden unexpected death in epilepsy. We aimed to investigate the cortical surface area abnormalities in epilepsy patients with postictal generalized electroencephalographic suppression. We retrospectively included 30 epilepsy patients with postictal generalized electroencephalographic suppression (PGES+), 21 epilepsy patients without postictal generalized electroencephalographic suppression (PGES-), and 30 healthy controls. Surface-based analysis on high-resolution T1-weighted images was conducted and cortical surface areas were compared among the three groups, alongside correlation analyses with seizure-related clinical variables. Compared with PGES- group, we identified reduced surface area in the bilateral insula with more extensive distribution in the right hemisphere in PGES+ group. The reduced right insular surface area was associated with younger seizure-onset age. When compared with healthy controls, PGES- group presented reduced surface area in the left caudal middle frontal gyrus; PGES+ group presented more widespread surface area reductions in the right posterior cingulate gyrus, left postcentral gyrus, middle frontal gyrus, and middle temporal gyrus. Our results suggested cortical microstructural impairment in patients with postictal generalized electroencephalographic suppression. The significant surface area reductions in the insular cortex supported the autonomic network involvement in the pathology of postictal generalized electroencephalographic suppression, and its right-sided predominance suggested the potential shared abnormal brain network for postictal generalized electroencephalographic suppression and sudden unexpected death in epilepsy.

Disentangling the size-dependent redox reactivity of iron oxides using thermodynamic relationships.

Nanoparticles often exhibit size-dependent redox reactivities, with smaller particles being more reactive in some cases, while less reactive in others. Predicting trends between redox reaction rates and particle sizes is often complicated because a particle's dimensions can simultaneously influence its aggregation state, reactive surface area, and thermodynamic properties. Here, we tested the hypothesis that interfacial redox reaction rates for nanoparticles with different sizes can be described with a single linear free-energy relationship (LFER) if size-dependent reactive surface areas and thermodynamic properties are properly considered. We tested this hypothesis using a well-known interfacial redox reaction: the reduction of nitrobenzene to aniline by iron-oxide-bound Fe2+. We measured the reduction potential (EH) values of nano-particulate hematite suspensions containing aqueous Fe2+ using mediated potentiometry and characterized the size and aggregation states of hematite samples at circumneutral pH values. We used the measured EH values to calculate surface energies and reactive surface areas using thermodynamic relationships. Nitrobenzene reduction rates were lower for smaller particles, despite their larger surface areas, due to their higher surface energies. When differences in surface areas and thermodynamic properties were considered, nitrobenzene reduction kinetics for all particle sizes was described with a LFER. Our results demonstrate that when Fe2+ serves as a reductant, an antagonistic effect exists, with smaller particles having larger reactive surface areas but also more positive reduction potentials. When Fe3+ serves as an oxidant, however, these two effects work in concert, which likely explains past discrepancies regarding how iron oxide particle sizes influence redox reaction rates.

Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age.

Surface area of the human cerebral cortex expands extremely dynamically and regionally heterogeneously from the third trimester of pregnancy to 2 y of age, reflecting the spatial heterogeneity of the underlying microstructural and functional development of the cerebral cortex. However, little is known about the developmental patterns and regionalization of cortical surface area during this critical stage, due to the lack of high-quality imaging data and accurate computational tools for pediatric brain MRI data. To fill this critical knowledge gap, by leveraging 1,037 high-quality MRI scans with the age between 29 post-menstrual weeks and 24 mo from 735 pediatric subjects in two complementary datasets, i.e., the Baby Connectome Project (BCP) and the developing Human Connectome Project (dHCP), and state-of-the-art dedicated image-processing tools, we unprecedentedly parcellate the cerebral cortex into a set of distinct subdivisions purely according to the developmental patterns of the cortical surface. Our discovered developmentally distinct subdivisions correspond well to structurally and functionally meaningful regions and reveal spatially contiguous, hierarchical, and bilaterally symmetric patterns of early cortical surface expansion. We also show that high-order association subdivisions, where cortical folds emerge later during prenatal stages, undergo more dramatic cortical surface expansion during infancy, compared with the central regions, especially the sensorimotor and insula cortices, thus forming a distinct central-pole division in early cortical surface expansion. These results provide an important reference for exploring and understanding dynamic early brain development in health and disease.

Mapping Genetic Topography of Cortical Thickness and Surface Area in Neonatal Brains.

Adult twin neuroimaging studies have revealed that cortical thickness (CT) and surface area (SA) are differentially influenced by genetic information, leading to their spatially distinct genetic patterning and topography. However, the postnatal origins of the genetic topography of CT and SA remain unclear, given the dramatic cortical development from neonates to adults. To fill this critical gap, this study unprecedentedly explored how genetic information differentially regulates the spatial topography of CT and SA in the neonatal brain by leveraging brain magnetic resonance (MR) images from 202 twin neonates with minimal influence by the complicated postnatal environmental factors. We capitalized on infant-dedicated computational tools and a data-driven spectral clustering method to parcellate the cerebral cortex into a set of distinct regions purely according to the genetic correlation of cortical vertices in terms of CT and SA, respectively, and accordingly created the first genetically informed cortical parcellation maps of neonatal brains. Both genetic parcellation maps exhibit bilaterally symmetric and hierarchical patterns, but distinct spatial layouts. For CT, regions with closer genetic relationships demonstrate an anterior-posterior (A-P) division, while for SA, regions with greater genetic proximity are typically within the same lobe. Certain genetically informed regions exhibit strong similarities between neonates and adults, with the most striking similarities in the medial surface in terms of SA, despite their overall substantial differences in genetic parcellation maps. These results greatly advance our understanding of the development of genetic influences on the spatial patterning of cortical morphology.SIGNIFICANCE STATEMENT Genetic influences on cortical thickness (CT) and surface area (SA) are complex and could evolve throughout the lifespan. However, studies revealing distinct genetic topography of CT and SA have been limited to adults. Using brain structural magnetic resonance (MR) images of twins, we unprecedentedly discovered the distinct genetically-informed parcellation maps of CT and SA in neonatal brains, respectively. Each genetic parcellation map comprises a distinct spatial layout of cortical regions, where vertices within the same region share high genetic correlation. These genetic parcellation maps of CT and SA of neonates largely differ from those of adults, despite their highly remarkable similarities in the medial cortex of SA. These discoveries provide important insights into the genetic organization of the early cerebral cortex development.

Interfacial residues in protein-protein complexes are in the eyes of the beholder.

Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.

Identification of potent BRD4-BD1 inhibitors using classical and steered molecular dynamics based free energy analysis.

In the present work a combination of traditional and steered molecular dynamics based techniques were employed to identify potential inhibitors against the human BRD4 protein (BRD4- BD1); an established drug target for multiple illnesses including various malignancies. Quinoline derivatives that were synthesized in-house were tested for their potential as new BRD4-BD1 inhibitors. Initially molecular docking experiments were performed to determine the binding poses of BRD4-BD1 inhibitors. To learn more about the thermodynamics of inhibitor binding to the BRD4-BD1 active site, the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) free energy calculations were conducted afterwards. The findings of the MM-PBSA analysis were further reinforced by performing steered umbrella sampling simulations which revealed crucial details about the binding/unbinding process of the most potent quinoline derivatives at the BRD4-BD1 active site. We report a novel quinoline derivative which can be developed into a fully functional BRD4-BD1 inhibitor after experimental validation. The identified compound (4 g) shows better properties than the standard BRD4-BD1 inhibitors considered in the study. The study also highlights the crucial role of Gln78, Phe79, Trp81, Pro82, Phe83, Gln84, Gln85, Val87, Leu92, Leu94, Tyr97, Met105, Cys136, Asn140, Ile146 and Met149 in inhibitor binding. The study provides a possible lead candidate and key amino acids involved in inhibitor recognition and binding at the active site of BRD4-BD1 protein. The findings might be of significance to medicinal chemists involved in the development of potent BRD4-BD1 inhibitors.

Neuroticism polygenic risk predicts conversion from mild cognitive impairment to Alzheimer's disease by impairing inferior parietal surface area.

The high prevalence of conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer's disease (AD) makes early prevention of AD extremely critical. Neuroticism, a heritable personality trait associated with mental health, has been considered a risk factor for conversion from aMCI to AD. However, whether the neuroticism genetic risk could predict the conversion of aMCI and its underlying neural mechanisms is unclear. Neuroticism polygenic risk score (N-PRS) was calculated in 278 aMCI patients with qualified genomic and neuroimaging data from ADNI. After 1-year follow-up, N-PRS in patients of aMCI-converted group was significantly greater than those in aMCI-stable group. Logistic and Cox survival regression revealed that N-PRS could significantly predict the early-stage conversion risk from aMCI to AD. These results were well replicated in an internal dataset and an independent external dataset of 933 aMCI patients from the UK Biobank. One sample Mendelian randomization analyses confirmed a potentially causal association from higher N-PRS to lower inferior parietal surface area to higher conversion risk of aMCI patients. These analyses indicated that neuroticism genetic risk may increase the conversion risk from aMCI to AD by impairing the inferior parietal structure.

Green iron oxide nanoparticles and magnetic nanobiochar: enhancing tomato performance, phytochemicals, and root-knot nematode resistance.

BACKGROUND: Green nanoparticles are considered to be an effective strategy for improving phytochemicals and raising productivity in soil infected by root-knot nematodes. This work aims to understand the characteristics of certain nanomaterials, including non-iron (nFe), green non-iron (GnFe), and green magnetic nanobiochar (GMnB), and the effect of adding them at 3 and 6 mg kg- 1 on phytochemicals and tomato (Solanum lycopersicum) plant growth in soils infected by root-knot nematodes. RESULTS: Spectroscopic characterization of nanomaterials showed that nFe, GnFe, and GMnB contained functional groups (e.g., Fe-O, S-H, C-H, OH, and C = C) and possessed a large surface area. Application of GMB at 6 mg kg- 1 was the most efficient treatment for increasing the phytochemicals of the tomato plant, with a rise of 123.2% in total phenolic, 194.7% in total flavonoids, 89.7% in total carbohydrate, 185.2% in total free amino acids, and 165.1% in total tannin compared to the untreated soil. Tomato plant growth and attributes increased with increasing levels of soil nano-amendment in this investigation. The addition of GnFe3 and GnFe6 increased the reduction of root galls of root-knot nematodes by 22.44% and 17.76% compared with nFe3 and nFe6, respectively. The inclusion of the examined soil nano-amendments increased phytochemicals and reduced the total number of root-knot nematodes on tomato plants at varying rates, which played a significant role in enhancing tomato growth. CONCLUSIONS: In conclusion, treating tomato plants with GnFe or GMnB can be used as a promising green nanomaterial to eliminate root-knot nematodes and increase tomato yield in sandy clay loam soil.

Assessment of breast cancer chemotherapy dose reduction in an integrated healthcare delivery system.

PURPOSE: Most cytotoxic drugs are dosed using body surface area (BSA), yet not all cancer patients receive the full BSA-determined dose. Prior work suggests that breast cancer patients who are obese are more likely to experience dose reduction than normal weight patients. However, the factors driving dose reduction remain unclear. METHODS: In 452 women diagnosed with stage I-IIIA primary breast cancer at Kaiser Permanente Northern California, we evaluated the association between obesity and dose reduction, and further explored other factors in relation to dose reduction, including various sociodemographic characteristics, tumor characteristics, and comorbidities. Study participants were a part of the Pathways Study, diagnosed between 2006 and 2013 and treated with cyclophosphamide + doxorubicin, followed by paclitaxel (ACT). Dose reduction was assessed using first cycle dose proportion (FCDP) and average relative dose intensity (ARDI), a metric of dose intensity over the course of chemotherapy. RESULTS: Overall, 8% of participants received a FCDP < 90% and 21.2% had an ARDI < 90%, with dose reduction increasing with body mass index. In adjusted logistic regression models, obese women had 4.1-fold higher odds of receiving an ARDI < 90% than normal weight women (95% CI: 1.9-8.9; p-trend = 0.0006). Increasing age was positively associated with an ADRI < 90%, as was the presence of comorbidity. Dose reduction was less common in later calendar years. CONCLUSION: Results offer insight on factors associated with chemotherapy dosing for a common breast cancer regimen. Larger studies are required to evaluate relevance to other regimens, and further work will be needed to determine whether dose reductions impact outcomes in obese women.

Porous Tellurium-Doped Ruthenium Dioxide Nanotubes for Enhanced Acidic Water Oxidation.

Electrocatalysts with high activity and durability for acidic oxygen evolution reaction (OER) play a crucial role in achieving cost-effective hydrogen production via proton exchange membrane water electrolysis. A novel electrocatalyst, Te-doped RuO2 (Te-RuO2) nanotubes, synthesized using a template-directed process, which significantly enhances the OER performance in acidic media is reported. The Te-RuO2 nanotubes exhibit remarkable OER activity in acidic media, requiring an overpotential of only 171 mV to achieve an anodic current density of 10 mA cm-2. Furthermore, they maintain stable chronopotentiometric performance under 10 mA cm-2 in acidic media for up to 50 h. Based on the experimental results and density functional calculations, this significant improvement in OER performance to the synergistic effect of large specific surface area and modulated electronic structure resulting from the doping of Te cations is attributed.

Surface Area-Enhanced Cerium and Sulfur-Modified Hierarchical Bismuth Oxide Nanosheets for Electrochemical Carbon Dioxide Reduction to Formate.

Electrochemical carbon dioxide reduction reaction (ECO2RR) is a promising approach to synthesize fuels and value-added chemical feedstocks while reducing atmospheric CO2 levels. Here, high surface area cerium and sulfur-doped hierarchical bismuth oxide nanosheets (Ce@S-Bi2O3) are develpoed by a solvothermal method. The resulting Ce@S-Bi2O3 electrocatalyst shows a maximum formate Faradaic efficiency (FE) of 92.5% and a current density of 42.09 mA cm-2 at -1.16 V versus RHE using a traditional H-cell system. Furthermore, using a three-chamber gas diffusion electrode (GDE) reactor, a maximum formate FE of 85% is achieved in a wide range of applied potentials (-0.86 to -1.36 V vs RHE) using Ce@S-Bi2O3. The density functional theory (DFT) results show that doping of Ce and S in Bi2O3 enhances formate production by weakening the OH* and H* species. Moreover, DFT calculations reveal that *OCHO is a dominant pathway on Ce@S-Bi2O3 that leads to efficient formate production. This study opens up new avenues for designing metal and element-doped electrocatalysts to improve the catalytic activity and selectivity for ECO2RR.

Ionic Porous Aromatic Frameworks Embedding Polyoxometalates for Heterogeneous Catalysis.

Porous aromatic frameworks (PAFs) are highly promising functional porous solids known for their feasible amenability and extraordinary stability. When the framework was modified by ionic functional groups, these ionic PAFs (iPAFs) exhibited charged channels for adsorption, separation, and catalysis. However, the surface areas of ionic porous frameworks are usually lower than that of neutral frameworks, and their synthesis is limited by specific strategies and complex modification processes. To address these challenges, an intuitive route to construct ionic porous framework with high specific surface area was proposed. Herein, a multivariate ionic porous aromatic framework (MTV-iPAFs, named PAF-270) was synthesized using readily available building units with ionic functional groups through a multivariable synthesis strategy. PAF-270 exhibited hierarchical structure with the highest specific surface area among reported imidazolium-functionalized PAFs. Utilizing its physical and chemical properties, the availability for polyoxometalate loading and heterogeneous catalysis of PAF-270 were explored. PAF-270 exhibited a high adsorption capacity up to 50 % for both H3O40PW12 (HPW) and (NH4)5H6PV8Mo4O40 (V8). HPW@PAF-270 and V8@PAF-270 exhibited excellent catalytic abilities for oleic acid esterification and extractive oxidative desulfurization, respectively. Due to the stability of PAFs, these materials also showed remarkable resistance to temperature and pH changes. Overall, these results underscore the potential application of MTV-iPAFs as versatile functional porous materials.

Shrinking Devices: Shape-Memory Polymer Fabrication of Micro-and Nanostructured Electrodes.

Since their discovery in the 1940s, shape memory polymers (SMPs) have been used in a broad spectrum of applications for research and industry.[1] SMPs can adopt a temporary shape and promptly return to their original form when submitted to an external stimulus. They have proven useful in fields such as wearable and stretchable electronics,[2] biomedicine,[3] and aerospace..[4] These materials are attractive and unique due to their ability to "remember" a shape after being submitted to elastic deformation. By combining the properties of SMPs with the advantages of electrochemistry, opportunities have emerged to develop structured sensing devices through simple and inexpensive fabrication approaches. The use of electrochemistry for signal transduction provides several advantages, including the translation into inexpensive sensing devices that are relatively easy to miniaturize, extremely low concentration requirements for detection, rapid sensing, and multiplexed detection. Thus, electrochemistry has been used in biosensing,[5] pollutant detection,[6] and pharmacological[7] applications, among others. To date, there is no review that summarizes the literature addressing the use of SMPs in the fabrication of structured electrodes for electrochemical sensing. This review aims to fill this gap by compiling the research that has been done on this topic over the last decade.

In Vitro Digestion-In Situ Absorption Setup Employing a Physiologically Relevant Value of the Membrane Surface Area/Volume Ratio for Evaluating Performance of Lipid-Based Formulations: A Comparative Study with an In Vitro Digestion-Permeation Model.

The aim of this study is to establish and test an in vitro digestion-in situ absorption model that can mimic in vivo drug flux by employing a physiologically relevant value of the membrane surface area (S)/volume (V) ratio for accurate prediction of oral drug absorption from lipid-based formulations (LBFs). Three different types of LBFs (Type IIIA-MC, Type IIIA-LC, and Type IV) loaded with cinnarizine (CNZ), a lipophilic weak base with borderline permeability, and a control suspension were prepared. Subsequently, a simultaneous in vitro digestion-permeation experiment was conducted using a side-by-side diffusion cell with a dialysis membrane having a low S/V value. During digestion, CNZ partially precipitated for Type IV, while it remained solubilized in the aqueous phase for Type IIIA-MC and Type IIIA-LC in the donor compartment. However, in vitro drug fluxes for Type IIIA-MC and Type IIIA-LC were lower than those for Type IV due to the reduced free fraction of CNZ in the donor compartment. In pharmacokinetic studies, a similar improvement in in vivo oral exposure relative to suspension was observed, regardless of the LBFs used. Consequently, a poor correlation was found between in vitro permeation and areas under the plasma concentration-time curve (AUCoral) (R2 = 0.087). A luminal concentration measurement study revealed that this discrepancy was attributed to the extremely high absorption rate of CNZ in the gastrointestinal tract compared to that across a dialysis membrane evaluated by the in vitro digestion-permeation model, i.e., the absorption of CNZ in vivo was completed regardless of the extent of the free fraction, owing to the rapid removal of CNZ from the intestine. Subsequently, we aimed to predict the oral absorption of CNZ from the same formulations using a model that demonstrated high drug flux by employing the physiologically relevant S/V value and rat jejunum segment as an absorption sink (for replicating in vivo intestinal permeability). Predigested formulations were injected into the rat intestinal loop, and AUCloop values were calculated from the plasma concentration-time profiles. A better correlation was found between AUCloop and AUCoral (R2 = 0.72), although AUCloop underestimated AUCoral for Type IV due to the precipitation of CNZ during the predigestion process. However, this result indicated the importance of mimicking the in vivo drug absorption rate in the predictive model. The method presented herein is valuable for the development of LBFs.

Mechanistic Insights into the Adsorption of Monoclonal Antibodies at the Water/Vapor Interface.

Monoclonal antibodies (mAbs) are active components of therapeutic formulations that interact with the water-vapor interface during manufacturing, storage, and administration. Surface adsorption has been demonstrated to mediate antibody aggregation, which leads to a loss of therapeutic efficacy. Controlling mAb adsorption at interfaces requires a deep understanding of the microscopic processes that lead to adsorption and identification of the protein regions that drive mAb surface activity. Here, we report all-atom molecular dynamics (MD) simulations of the adsorption behavior of a full IgG1-type antibody at the water/vapor interface. We demonstrate that small local changes in the protein structure play a crucial role in promoting adsorption. Also, interfacial adsorption triggers structural changes in the antibody, potentially contributing to the further enhancement of surface activity. Moreover, we identify key amino acid sequences that determine the adsorption of antibodies at the water-air interface and outline strategies to control the surface activity of these important therapeutic proteins.

Generality of Enhancing the Dissolution Rates of Free Acid Amorphous Solid Dispersions by the Incorporation of Sodium Hydroxide.

The incorporation of a counterion into an amorphous solid dispersion (ASD) has been proven to be an attractive strategy to improve the drug dissolution rate. In this work, the generality of enhancing the dissolution rates of free acid ASDs by incorporating sodium hydroxide (NaOH) was studied by surface-area-normalized dissolution. A set of diverse drug molecules, two common polymer carriers (copovidone or PVPVA and hydroxypropyl methylcellulose acetate succinate or HPMCAS), and two sample preparation methods (rotary evaporation and spray drying) were investigated. When PVPVA was used as the polymer carrier for the drugs in this study, enhancements of dissolution rates from 7 to 78 times were observed by the incorporation of NaOH into the ASDs at a 1:1 molar ratio with respect to the drug. The drugs having lower amorphous solubilities showed greater enhancement ratios, providing a promising path to improve the drug release performance from their ASDs. Samples generated by rotary evaporation and spray drying demonstrated comparable dissolution rates and enhancements when NaOH was added, establishing a theoretical foundation to bridge the ASD dissolution performance for samples prepared by different solvent-removal processes. In the comparison of polymer carriers, when HPMCAS was applied in the selected system (indomethacin ASD), a dissolution rate enhancement of 2.7 times by the incorporated NaOH was observed, significantly lower than the enhancement of 53 times from the PVPVA-based ASD. This was attributed to the combination of a lower dissolution rate of HPMCAS and the competition for NaOH between IMC and HPMCAS. By studying the generality of enhancing ASD dissolution rates by the incorporation of counterions, this study provides valuable insights into further improving drug release from ASD formulations of poorly water-soluble drugs.

A Refined Thin-Film Model for Drug Dissolution Considering Radial Diffusion - Simulating Powder Dissolution.

PURPOSE: We aim to present a refined thin-film model describing the drug particle dissolution considering radial diffusion in spherical boundary layer, and to demonstrate the ability of the model to describe the dissolution behavior of bulk drug powders. METHODS: The dissolution model introduced in this study was refined from a radial diffusion-based model previously published by our laboratory (So et al. in Pharm Res. 39:907-17, 2022). The refined model was created to simulate the dissolution of bulk powders, and to account for the evolution of particle size and diffusion layer thickness during dissolution. In vitro dissolution testing, using fractionated hydrochlorothiazide powders, was employed to assess the performance of the model. RESULTS: Overall, there was a good agreement between the experimental dissolution data and the predicted dissolution profiles using the proposed model across all size fractions of hydrochlorothiazide. The model over-predicted the dissolution rate when the particles became smaller. Notably, the classic Nernst-Brunner formalism led to an under-estimation of the dissolution rate. Additionally, calculation based on the equivalent particle size derived from the specific surface area substantially over-predicted the dissolution rate. CONCLUSION: The study demonstrated the potential of the radial diffusion-based model to describe dissolution of drug powders. In contrast, the classic Nernst-Brunner equation could under-estimate drug dissolution rate, largely due to the underlying assumption of translational diffusion. Moreover, the study indicated that not all surfaces on a drug particle contribute to dissolution. Therefore, relying on the experimentally-determined specific surface area for predicting drug dissolution is not advisable.

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States.

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the "black-box" nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having "no change" (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

2D-Like Catalyst with a Micro-nanolinked Functional Surface for Water Purification.

In water purification, the performance of heterogeneous advanced oxidation processes significantly relies upon the utilization of the catalyst's specific surface area (SSA). However, the presence of the structural "dead volume" and pore-size-induced diffusion-reaction trade-off limitation restricts the functioning of the SSA. Here, we reported an effective approach to make the best SSA by changing the traditional 3D spherule catalyst into a 2D-like form and creating an in situ micro-nanolinked structure. Thus, a 2D-like catalyst was obtained which was characterized by a mini "paddy field" surface, and it exhibited a sharply decreased dead volume, a highly available SSA and oriented flexibility. Given its paddy-field-like mass-transfer routine, the organic capture capability was 7.5-fold higher than that of the catalyst with mesopores only. Moreover, such a catalyst exhibited a record-high O3-to-·OH transition rate of 2.86 × 10-8 compared with reported millimetric catalysts (metal base), which contributed to a 6.12-fold higher total organic removal per catalyst mass than traditional 3D catalysts. The facile scale preparation, performance stability, and significant material savings with the 2D-like catalyst were also beneficial for practical applications. Our findings provide a unique and general approach for designing potential catalysts with excellent performance in water purification.