Confinement Effects on Proton Transfer in TiO2 Nanopores from Machine Learning Potential Molecular Dynamics Simulations.

Improved understanding of proton transfer in nanopores is critical for a wide range of emerging applications, yet experimentally probing mechanisms and energetics of this process remains a significant challenge. To help reveal details of this process, we developed and applied a machine learning potential derived from first-principles calculations to examine water reactivity and proton transfer in TiO2 slit-pores. We find that confinement of water within pores smaller than 0.5 nm imposes strong and complex effects on water reactivity and proton transfer. Although the proton transfer mechanism is similar to that at a TiO2 interface with bulk water, confinement reduces the activation energy of this process, leading to more frequent proton transfer events. This enhanced proton transfer stems from the contraction of oxygen-oxygen distances dictated by the interplay between confinement and hydrophilic interactions. Our simulations also highlight the importance of the surface topology, where faster proton transport is found in the direction where a unique arrangement of surface oxygens enables the formation of an ordered water chain. In a broader context, our study demonstrates that proton transfer in hydrophilic nanopores can be enhanced by controlling pore size, surface chemistry, and topology.

Fibrous Dysplasia of the Parietal Bone with Focal Motor Seizures: A Case Report.

BACKGROUND Monostotic fibrous dysplasia is a benign proliferation of fibrous and osseous tissues that expand medullary bone to cause symptoms due to compression of adjacent organs and anatomical structures. Focal seizures are rarely the first sign of this kind of lesion. This report describes a young female patient with left-sided focal motor seizures associated with fibrous dysplasia presenting as a mass in the right parietal bone. CASE REPORT An 18-year-old female student with left-sided focal motor seizures presented with a mass in the right parietal bone. Computed tomography revealed an expansile mixed-density lesion on the right parietal bone, a relatively homogeneous ground-glass appearance in the outer circumferential portion, and a lucent eccentric area with thinned but sclerotic borders. Magnetic resonance imaging revealed a homogeneously hypointense signal on T1WI, a small hyperintense signal on T2WI, and avid enhancement signal intensity on post-contrast T1. Electroencephalogram showed inter-ictal epileptiform activities derived from the right fronto-central lobe. Surgical en bloc resection with a margin of normal bone and cranioplasty were performed. Histopathology showed features indicative of fibrous dysplasia, including osteoid trabeculae arranged haphazardly in a dense fibroblastic stroma, irregular trabeculae lacking conspicuous osteoblastic rimming, and intervening fibrous stroma containing cytologically bland spindle cells. The patient achieved seizure control and has remained neurologically intact. CONCLUSIONS This report has highlighted the importance of early diagnosis of fibrous dysplasia of bone to exclude primary bone malignancy or bone metastasis, to ensure rapid management and symptom control.

Nuclear Quantum Effects on the Electronic Structure of Water and Ice.

The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of the hydrogen atoms. Despite numerous previous studies, a comprehensive understanding of the nuclear quantum effects (NQEs) on the electronic structure of water and ice at finite temperatures remains elusive. Here, we utilize molecular simulations that harness efficient machine-learning potentials and many-body perturbation theory to assess how NQEs impact the electronic bands of water and hexagonal ice. By comparing path-integral and classical simulations, we find that NQEs lead to a larger renormalization of the fundamental gap of ice, compared to that of water, ultimately yielding similar bandgaps in the two systems, consistent with experimental estimates. Our calculations suggest that the increased quantum mechanical delocalization of protons in ice, relative to water, is a key factor leading to the enhancement of NQEs on the electronic structure of ice.

Nonlinear Effects of Hydrophobic Confinement on the Electronic Structure and Dielectric Response of Water.

Fundamental studies of the dielectrics of confined water are critical to understand the ion transport across biological and synthetic nanochannels. The relevance of these fundamental studies, however, surmounts the difficulty of probing water's dielectric constant as a function of a fine variation in confinement. In this work, we explore the computational efficiency of machine learning potentials to derive the confinement effects on the dielectric constant, polarization, and dipole moment of water. Our simulations predict an enhancement of the axial dielectric constant of water under extreme confinement, arising from either the formation of ferroelectric structures of ordered water or larger dipole fluctuations facilitated by the disruption of water's H-bond network. Our study highlights the impact of hydrophobic nanoconfinement on the dielectric constant and on the ionic and electronic structure of water molecules, pointing to the importance of geometric flexibility and electronic polarizability to properly model confinement effects on water.

Mimosa pudica L. extract ameliorates pulmonary fibrosis via modulation of MAPK signaling pathways and FOXO3 stabilization.

ETHNOPHARMACOLOGICAL RELEVANCE: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing pulmonary disorder that has a poor prognosis and high mortality. Although there has been extensive effort to introduce several new anti-fibrotic agents in the past decade, IPF remains an incurable disease. Mimosa pudica L., an indigenous Vietnamese plant, has been empirically used to treat respiratory disorders. Nevertheless, the therapeutic effects of M. pudica (MP) on lung fibrosis and the mechanisms underlying those effects remain unclear. AIM OF THE STUDY: This study investigated the protective effect of a crude ethanol extract of the above-ground parts of MP against pulmonary fibrogenesis. MATERIALS AND METHODS: Inflammatory responses triggered by TNFα in structural lung cells were examined in normal human lung fibroblasts and A549 alveolar epithelial cells using Western blot analysis, reverse transcription-quantitative polymerase chain reaction assays, and immunocytochemistry. The epithelial-to-mesenchymal transition (EMT) was examined via cell morphology observations, F-actin fluorescent staining, gene and protein expression measurements, and a wound-healing assay. Anti-fibrotic assays including collagen release, differentiation, and measurements of fibrosis-related gene and protein expression levels were performed on TGFß-stimulated human lung fibroblasts and lung fibroblasts derived from mice with fibrotic lungs. Finally, in vitro anti-fibrotic activities were validated using a mouse model of bleomycin-induced pulmonary fibrosis. RESULTS: MP alleviated the inflammatory responses of A549 alveolar epithelial cells and lung fibroblasts, as revealed by inhibition of TNFα-induced chemotactic cytokine and chemokine expression, along with inactivation of the MAPK and NFκB signalling pathways. MP also partially reversed the TGFß-promoted EMT via downregulation of mesenchymal markers in A549 cells. Importantly, MP decreased the expression levels of fibrosis-related genes/proteins including collagen I, fibronectin, and αSMA; moreover, it suppressed collagen secretion and prevented myofibroblast differentiation in lung fibroblasts. These effects were mediated by FOXO3 stabilization through suppression of TGFß-induced ERK1/2 phosphorylation. MP consistently protected mice from the onset and progression of bleomycin-induced pulmonary fibrosis. CONCLUSION: This study explored the multifaceted roles of MP in counteracting the pathobiological processes of lung fibrosis. The results suggest that further evaluation of MP could yield candidate therapies for IPF.

Distance-Dependent Evolution of Electronic States in Kagome-Honeycomb Lateral Heterostructures in FeSn.

In this work, we demonstrate the formation and electronic influence of lateral heterointerfaces in FeSn containing Kagome and honeycomb layers. Lateral heterostructures offer spatially resolved property control, enabling the integration of dissimilar materials and promoting phenomena not typically observed in vertical heterostructures. Using the molecular beam epitaxy technique, we achieve a controllable synthesis of lateral heterostructures in the Kagome metal FeSn. With scanning tunneling microscopy/spectroscopy in conjunction with first-principles calculations, we provide a comprehensive understanding of the bonding motif connecting the Fe3Sn-terminated Kagome and Sn2-terminated honeycomb surfaces. More importantly, we reveal a distance-dependent evolution of the electronic states in the vicinity of the heterointerfaces. This evolution is significantly influenced by the orbital character of the flat bands. Our findings suggest an approach to modulate the electronic properties of the Kagome lattice, which should be beneficial for the development of future quantum devices.

Generation of induced pluripotent stem cell line (VRISGi004-A) from a healthy female donor by reprogramming erythroid progenitor cells.

We generated a human induced pluripotent stem cell (hiPSC) line from erythroid progenitor cells (EPCs) of a 20-year-old female healthy donor using Sendai virus vector encoding Yamanaka factors OCT3/4, SOX2, c-MYC, and KLF4. The established hiPSCs showed a standard morphology and expression of typical undifferentiated stem cell markers, a normal karyotype (46, XX), and demonstrated potential for differentiation in vitro. Furthermore, they were successfully differentiated into cardiomyocytes that expressed cardiomyocyte-specific markers. The iPSC line and iPSC-derived cardiomyocytes will provide new avenues for future drug testing/development and personalized cell therapy for cardiovascular diseases (CVDs).

Bioconversion of Shrimp Waste into Functional Lipid by a New Oleaginous Sakaguchia sp.

Chitin, the second most abundant biomolecule after cellulose in nature, is a significant aquaculture by-product, and is estimated at 6-8 million tons annually. Chitin is composed of monomeric N-acetylglucosamine (NAG) which can be seen as an alternative feedstock for biotechnology. Microbial functional lipids have gained attention due to their bioactivity and sustainable production. In this study, a new oleaginous yeast strain named Sakaguchia sp. HKC2 was found to be able to use NAG as the carbon source for growth and accumulate functional lipids such as PUFAs and carotenoids. When cultured on the NAG-containing medium, strain HKC2 exhibited slower growth and slower intracellular lipid accumulation compared to those on a glucose-containing medium. However, the lipids obtained from HKC2 grown on NAG medium were richer in PUFAs. Notably, torularhodin-a powerful bioactive carotenoid-was found in all HKC2 cultures on NAG, while torulene was abundant in glucose medium. These findings highlight a novel avenue for utilizing aquatic by-products and unlocking their potential.

Tumor-related epilepsy and post-surgical outcomes: tertiary hospital experience in Vietnam.

Seizures have a significant impact on the quality of life of those who suffer. This study aimed to evaluate the variables that influence the incidence of seizures during the perioperative period and effective measures to enhance epilepsy outcomes among individuals undergoing surgical resection of brain tumors. The authors carried out a prospective observational analysis of all patients who experienced seizures before their brain tumor surgery at UMC, HCMC between 2020 and 2022. 54 cases presented with seizures were enrolled for the study, generalized seizure was the most prevalent seizure type (61.1%), followed by focal seizure (29.6%). The majority of patients presented with seizures are those who were diagnosed with glioma. Low-grade gliomas and frontotemporal lobe tumors increase the postoperative risk of seizure. Other predictive factors are a prolonged history of seizure, especially resistant epilepsy and major peritumoral edema. In contrast, gross total resection reduces postoperative seizure incidence. There was correlation between Ki67 proliferation index and seizure incidence in both low-grade and high-grade gliomas. ECoG made insubstantial difference in enhancing the epilepsy surgery outcome. Overall, 88.9% of patients were seizure-free at 6 months of follow-up (Engel Class I), 7.4% were almost seizure-free (Class II), and 3.7% had significant improvement (Class III), figures for 12-month follow-up were 87.0%, 9.3%, and 3.7% respectively. A shorter history of seizure and gross-total resection appear to be associated with a favorable prognosis for seizure control.

Probing Confinement Effects on the Infrared Spectra of Water with Deep Potential Molecular Dynamics Simulations.

The hydrogen-bond network of confined water is expected to deviate from that of the bulk liquid, yet probing these deviations remains a significant challenge. In this work, we combine large-scale molecular dynamics simulations with machine learning potential derived from first-principles calculations to examine the hydrogen bonding of water confined in carbon nanotubes (CNTs). We computed and compared the infrared spectrum (IR) of confined water to existing experiments to elucidate confinement effects. For CNTs with diameters >1.2 nm, we find that confinement imposes a monotonic effect on the hydrogen-bond network and on the IR spectrum of water. In contrast, confinement below 1.2 nm CNT diameter affects the water structure in a complex fashion, leading to a strong directional dependence of hydrogen bonding that varies nonlinearly with the CNT diameter. When integrated with existing IR measurements, our simulations provide a new interpretation for the IR spectrum of water confined in CNTs, pointing to previously unreported aspects of hydrogen bonding in this system. This work also offers a general platform for simulating water in CNTs with quantum accuracy on time and length scales beyond the reach of conventional first-principles approaches.

Accuracy of Subthalamic Nucleus Electrode Implantation in Deep Brain Stimulation Surgery for Parkinson's Disease Treatment and Affecting Factors: Outcomes at Two Centers in Vietnam.

BACKGROUND: Deep brain stimulation (DBS) surgery for Parkinson's Disease (PD) has become more and more popular in Vietnam. However, the accuracy of implantation and affecting factors are under investigation. The objective of this study is to evaluate the accuracy of the subthalamic nucleus (STN)-DBS electrode implantation technique for treatment PD at Nguyen Tri Phuong Hospital and University Medical Center. To investigate factors related to accuracy. METHODS: We carried out a retrospective analysis of 58 patients with advanced PD who underwent STN-DBS surgery at Nguyen Tri Phuong Hospital and University Medical Center in Ho Chi Minh City, Viet Nam between June 2014 and July 2021 (115 leads total). All patients underwent the procedure with standard frame-based techniques under local anesthesia with microelectrode recording and macrostimuation test. RESULTS: Twenty-six female (44.8%) and thirty-two male (55.2%) patients with a mean age of 60.4 ± 8.3 years old (40-76 years) were included. Of total of 115 electrodes implanted, the mean target error (ΔT), radial error (ΔR), angle error (Δθ) were 1.94 ± 0.73 mm; 1.16 ± 0.69 mm; 2.22 ± 4.24 degrees, respectively. Vector error on each coordinate axis ΔX, ΔY, ΔZ were -0.35 ± 1.02 mm, +0.99 ± 0.82 mm, +0.73 ± 0.99 mm, respectively. There was a statistically significant correlation between subdural air volume, cortical shift, intracranial electrode bending, and accuracy. CONCLUSIONS: The current STN-DBS electrode implantation technique applied in our centers was quite accurate with acceptable error. More clinical trials are necessary to directly compare affecting factors to the accuracy of electrode implantation.

Mechanistic Insights on Permeation of Water over Iron Cations in Nanoporous Silicon Oxide Films for Selective H2 and O2 Evolution.

Electrocatalysts encapsulated by an ultrathin and semipermeable oxide layer offer a promising avenue for efficient, selective, and cost-effective production of hydrogen through photoelectrochemical water splitting. This architecture is especially attractive for Z-scheme water splitting, for which a nanoporous oxide film can be leveraged to mitigate undesired, yet kinetically facile, reactions involving redox shuttles, such as aqueous iron cations, by limiting transport of these species to catalytically active sites. In this work, molecular dynamics simulations were combined with electrochemical measurements to provide a mechanistic understanding of permeation of water and Fe(III)/Fe(II) redox shuttles through nanoporous SiO2 films. It is shown that even for SiO2 pores with a width as small as 0.8 nm, water does not experience any energy barrier for permeating into the pores due to a favorable interaction with hydrophilic silanol groups on the oxide surface. In contrast, permeation of Fe(III) and Fe(II) into microporous SiO2 pores is limited due to high energy barriers, which stem from a combination of distortion and dehydration of the second and third ion solvation shells. Our simulations and experimental results show that SiO2 coatings can effectively mitigate undesired Fe(III)/Fe(II) redox reactions at underlying electrodes by attenuating permeation of iron cations, while allowing water to permeate and thus participate in water splitting reactions. In a broader context, our study demonstrates that selectivity of solvated cations can be manipulated by controlling the pore size and surface chemistry of oxide films.

Fluids and Electrolytes under Confinement in Single-Digit Nanopores.

Confined fluids and electrolyte solutions in nanopores exhibit rich and surprising physics and chemistry that impact the mass transport and energy efficiency in many important natural systems and industrial applications. Existing theories often fail to predict the exotic effects observed in the narrowest of such pores, called single-digit nanopores (SDNs), which have diameters or conduit widths of less than 10 nm, and have only recently become accessible for experimental measurements. What SDNs reveal has been surprising, including a rapidly increasing number of examples such as extraordinarily fast water transport, distorted fluid-phase boundaries, strong ion-correlation and quantum effects, and dielectric anomalies that are not observed in larger pores. Exploiting these effects presents myriad opportunities in both basic and applied research that stand to impact a host of new technologies at the water-energy nexus, from new membranes for precise separations and water purification to new gas permeable materials for water electrolyzers and energy-storage devices. SDNs also present unique opportunities to achieve ultrasensitive and selective chemical sensing at the single-ion and single-molecule limit. In this review article, we summarize the progress on nanofluidics of SDNs, with a focus on the confinement effects that arise in these extremely narrow nanopores. The recent development of precision model systems, transformative experimental tools, and multiscale theories that have played enabling roles in advancing this frontier are reviewed. We also identify new knowledge gaps in our understanding of nanofluidic transport and provide an outlook for the future challenges and opportunities at this rapidly advancing frontier.

Coupling nitrate capture with ammonia production through bifunctional redox-electrodes.

Nitrate is a ubiquitous aqueous pollutant from agricultural and industrial activities. At the same time, conversion of nitrate to ammonia provides an attractive solution for the coupled environmental and energy challenge underlying the nitrogen cycle, by valorizing a pollutant to a carbon-free energy carrier and essential chemical feedstock. Mass transport limitations are a key obstacle to the efficient conversion of nitrate to ammonia from water streams, due to the dilute concentration of nitrate. Here, we develop bifunctional electrodes that couple a nitrate-selective redox-electrosorbent (polyaniline) with an electrocatalyst (cobalt oxide) for nitrate to ammonium conversion. We demonstrate the synergistic reactive separation of nitrate through solely electrochemical control. Electrochemically-reversible nitrate uptake greater than 70 mg/g can be achieved, with electronic structure calculations and spectroscopic measurements providing insight into the underlying role of hydrogen bonding for nitrate selectivity. Using agricultural tile drainage water containing dilute nitrate (0.27 mM), we demonstrate that the bifunctional electrode can achieve a 8-fold up-concentration of nitrate, a 24-fold enhancement of ammonium production rate (108.1 ug h-1 cm-2), and a >10-fold enhancement in energy efficiency when compared to direct electrocatalysis in the dilute stream. Our study provides a generalized strategy for a fully electrified reaction-separation pathway for modular nitrate remediation and ammonia production.

Tuning the many-body interactions in a helical Luttinger liquid.

In one-dimensional (1D) systems, electronic interactions lead to a breakdown of Fermi liquid theory and the formation of a Tomonaga-Luttinger Liquid (TLL). The strength of its many-body correlations can be quantified by a single dimensionless parameter, the Luttinger parameter K, characterising the competition between the electrons' kinetic and electrostatic energies. Recently, signatures of a TLL have been reported for the topological edge states of quantum spin Hall (QSH) insulators, strictly 1D electronic structures with linear (Dirac) dispersion and spin-momentum locking. Here we show that the many-body interactions in such helical Luttinger Liquid can be effectively controlled by the edge state's dielectric environment. This is reflected in a tunability of the Luttinger parameter K, distinct on different edges of the crystal, and extracted to high accuracy from the statistics of tunnelling spectra at tens of tunnelling points. The interplay of topology and many-body correlations in 1D helical systems has been suggested as a potential avenue towards realising non-Abelian parafermions.

Epilepsy surgery program in a resource-limited setting in Vietnam: A multicentered collaborative model.

OBJECTIVE: Although epilepsy surgery is more effective than medical therapy for drug-resistant patients, it is underutilized in both high-income and low- and middle-income countries. In light of our efforts to establish an epilepsy surgery program in a resource-limited setting, this study aimed to determine the outcome of the epilepsy surgery program in Ho Chi Minh City (HCMC), Vietnam. METHODS: In 2018, we developed the HCMC epilepsy core multidisciplinary team with members from various hospitals and centers. The team typically included neurologists, neurosurgeons, neuropsychologists, psychiatrists, and nursing specialists. Presurgical evaluations were performed for patients with drug-resistant epilepsy, fulfilling the ILAE criteria, with an epileptogenic lesion (mesial temporal sclerosis, low-grade gliomas, or focal cortical dysplasia). All epilepsy surgeries were performed in two epilepsy surgery centers in HCMC between 2018 and 2021. The patients were followed up for at least 12 months. RESULTS: Fifty-two patients with drug-resistant epilepsy underwent presurgical evaluation, of which 35 underwent surgery. Among the 52 patients, 20 (38.5%) underwent surgery after showing concordance among the results of standard presurgical assessments such as semiology, scalp interictal or ictal electroencephalography, and brain imaging. Among the 26 people with epilepsy who required more advanced evaluations, 15 underwent surgery with intraoperative electrocorticography to delineate the optimal resection borders. The outcomes of Engel Class I and Class II were achieved in 29/35 (82.8%) and 6/35 (17.2%) patients, respectively. SIGNIFICANCE: The epilepsy surgery program with a multicentered collaborative model in a resource-limited setting showed favorable outcomes in HCMC, Vietnam.

Ultra-high vacuum cleaver for the preparation of ionic crystal surfaces.

Cleaving single crystals in situ under ultra-high vacuum conditions provides a reliable and straightforward approach to prepare clean and atomically well-defined surfaces. Here, we present a versatile sample cleaver to efficiently prepare ionic crystal surfaces under ultra-high vacuum conditions, which is suitable for preparation of softer materials, such as alkali halides, and harder materials, such as metal oxides. One of the advantages of the presented cleaver design is that the cleaving blade and anvil to support the crystal are incorporated into the device. Therefore, no particularly strong mechanical manipulator is needed, and it is compatible with existing vacuum chambers equipped with an xyz-manipulator. We demonstrate atomically flat terraces and the atomic structure of NaCl(001), KBr(001), NiO(001), and MgO(001) cleavage planes prepared in situ under ultra-high vacuum conditions and imaged by low-temperature non-contact atomic force microscopy.

Rectified and Salt Concentration Dependent Wetting of Hydrophobic Nanopores.

Nanopores lined with hydrophobic groups function as switches for water and all dissolved species, such that transport is allowed only when applying a sufficiently high transmembrane pressure difference or voltage. Here we show a hydrophobic nanopore system whose wetting and ability to transport water and ions is rectified and can be controlled with salt concentration. The nanopore we study contains a junction between a hydrophobic zone and a positively charged hydrophilic zone. The nanopore is closed for transport at low salt concentrations and exhibits finite current only when the concentration reaches a threshold value that is dependent on the pore opening diameter, voltage polarity and magnitude, and type of electrolyte. The smallest nanopore studied here had a 4 nm diameter and did not open for transport in any concentration of KCl or KI examined. A 12 nm nanopore was closed for all KCl solutions but conducted current in KI at concentrations above 100 mM for negative voltages and opened for both voltage polarities at 500 mM KI. Nanopores with a hydrophobic/hydrophilic junction can thus function as diodes, such that one can identify a range of salt concentrations where the pores transport water and ions for only one voltage polarity. Molecular dynamics simulations together with continuum models provided a multiscale explanation of the observed phenomena and linked the salt concentration dependence of wetting with an electrowetting model. Results presented are crucial for designing next-generation chemical and ionic separation devices as well as understanding fundamental properties of hydrophobic interfaces under nanoconfinement.

Developing random forest hybridization models for estimating the axial bearing capacity of pile.

Accurate determination of the axial load capacity of the pile is of utmost importance when designing the pile foundation. However, the methods of determining the axial load capacity of the pile in the field are often costly and time-consuming. Therefore, the purpose of this study is to develop a hybrid machine-learning to predict the axial load capacity of the pile. In particular, two powerful optimization algorithms named Herd Optimization (PSO) and Genetic Algorithm (GA) were used to evolve the Random Forest (RF) model architecture. For the research, the data set including 472 results of pile load tests in Ha Nam province-Vietnam was used to build and test the machine-learning models. The data set was divided into training and testing parts with ratio of 80% and 20%, respectively. Various performance indicators, namely absolute mean error (MAE), mean square root error (RMSE), and coefficient of determination (R2) are used to evaluate the performance of RF models. The results showed that, between the two optimization algorithms, GA gave superior performance compared to PSO in finding the best RF model architecture. In addition, the RF-GA model is also compared with the default RF model, the results show that the RF-GA model gives the best performance, with the balance on training and testing set, meaning avoiding the phenomenon of overfitting. The results of the study suggest a potential direction in the development of machine learning models in engineering in general and geotechnical engineering in particular.