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A two‐step simulation approach combining large eddy simulation (LES) for turbulent flame and multidimensional/multivariate population balance Monte Carlo (PBMC) for nanoparticle dynamics is proposed to explore the detailed flame fields and particle dynamics of zirconia nanoparticles in a flame spray pyrolysis (FSP) reactor. The turbulent combustion of gas and spray are simulated by the nonlinear LES‐partially stirred reactor model. Thereafter, the differentially weighted PBMC is applied for the first time to describe the spatially resolved formation and growth of nanoparticles using the flame fields derived from LES as an input. An efficient submodel for particle spatial transport in multidimensional grids is adopted and tested to account for the effect of thermophoresis, convective and diffusion of the nanoparticles. This methodology is successfully applied to an FSP case, demonstrating a reliable level of fidelity when compared to experiments and other model. Simulation results are discussed, in particular the flame fields and the size, morphology, as well as polydisperse primary particle and aggregates size distribution. [ABSTRACT FROM AUTHOR]

As virtual reality display technologies advance, resolutions and refresh rates continue to approach human perceptual limits, presenting a challenge for real‐time rendering algorithms. Neural super‐resolution is promising in reducing the computation cost and boosting the visual experience by scaling up low‐resolution renderings. However, the added workload of running neural networks cannot be neglected. In this article, we try to alleviate the burden by exploiting the foveated nature of the human visual system, in a way that we upscale the coarse input in a heterogeneous manner instead of uniform super‐resolution according to the visual acuity decreasing rapidly from the focal point to the periphery. With the help of dynamic and geometric information (i.e., pixel‐wise motion vectors, depth, and camera transformation) available inherently in the real‐time rendering content, we propose a neural accumulator to effectively aggregate the amortizedly rendered low‐resolution visual information from frame to frame recurrently. By leveraging a partition‐assemble scheme, we use a neural super‐resolution module to upsample the low‐resolution image tiles to different qualities according to their perceptual importance and reconstruct the final output adaptively. Perceptually high‐fidelity foveated high‐resolution frames are generated in real‐time, surpassing the quality of other foveated super‐resolution methods. [ABSTRACT FROM AUTHOR]

Shifting from the typical 4e– pathway to H2O in electrochemical oxygen reduction to the 2e– pathway to H2O2 is increasingly recognized as an environmentally friendly approach for producing H2O2. However, the competitive 4e− pathway is a significant obstacle to the production of H2O2 since H2O is the thermodynamically favored product. Here, a series of Pt, Pd, and Rh active atoms diluted within inert‐Au matrices with precisely controlled atomic arrangements and coordination environments are synthesized via facet engineering for O2‐to‐H2O2 production. Surprisingly, individually dispersed Pt atoms within the Au surface enclosed by the square atomic arrangements exhibit superior H2O2 selectivity and achieve a maximum selectivity of 90% at 0.36 V versus the reversible hydrogen electrode. Operando synchrotron ambient pressure X‐ray photoelectron spectroscopy identifies the presence of *OOH key intermediates on these isolated Pt active sites. Grand canonical density‐functional theory also reveals that the kinetic energy barrier for the 2e− pathway (0.08 eV; OOH* + H+ + e− → H2O2) on the isolated Pt sites is significantly lower than the 4e− pathway (0.29 eV; OOH* + H+ + e− → O* + H2O). This work enables atomic‐scale control in dilute binary alloy surfaces with specific configurations of isolated active atoms and provides essential guidance for catalyst design to boost O2‐to‐H2O2 production. [ABSTRACT FROM AUTHOR]

Detecting CO2 in complex gas mixtures is challenging due to the presence of competitive gases in the ambient atmosphere. Photoelectrochemical (PEC) techniques offer a solution, but material selection and specificity remain limiting. Here, we constructed a hydrogen‐bonded organic framework material based on a porphyrin tecton decorated with diaminotriazine (DAT) moieties. The DAT moieties on the porphyrin molecules not only facilitate the formation of complementary hydrogen bonds between the tectons but also function as recognition sites in the resulting porous HOF materials for the selective adsorption of CO2. In addition, the in‐plane growth of FDU‐HOF‐2 into anisotropic molecular sheets with large areas of up to 23000 μm2 and controllable thickness between 0.298 and 2.407 μm were realized in yields of over 89 % by a simple solution‐processing method. The FDU‐HOF‐2 can be directly grown and deposited onto different substrates including silica, carbon, and metal oxides by self‐assembly in situ in formic acid. As a proof of concept, a screen‐printing electrode deposited with FDU‐HOF‐2 was fabricate as a label‐free photoelectrochemical (PEC) sensor for CO2 detection. Such a signal‐off PEC sensor exhibits low detection limit for CO2 (2.3 ppm), reusability (at least 30 cycles), and long‐term working stability (at least 30 days). [ABSTRACT FROM AUTHOR]

Describing spatiotemporal evolution and characteristics of dispersed systems using the population balance equation (PBE), examples including sectional and moment methods are fraught with numerous issues. Hence, this study develops an accurate method by combining computational fluid dynamics and population balance‐Monte Carlo method (CFD‐PBMC) with a moderate computational cost. An efficient sub‐model for particle migration was proposed to simulate the convection and diffusion processes of particulate flows. A graphics processing unit (GPU)‐based parallel computation was performed to accelerate the high‐dimensional CFD‐PBMC. Several classical cases with analytical or benchmark solutions were simulated, and a comprehensive comparison was made using the classical weighted random walk method. Good agreements were obtained, except in the case of radial migration, the reasons for which are explained in detail. The measured speedups on the GPU showed a factor of ~450 for pure migration and ~50 for the CFD‐PBMC method when compared with a standard high‐performance computer. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) is a high-risk pathogenic toxin for hepatic diseases. Excessive mitophagy is a hallmark in Cd-induced hepatotoxicity. However, the underlying mechanism remains obscure. Mitochondrial calcium uniporter (MCU) is a key regulator for mitochondrial and cellular homeostasis. Here, Cd exposure upregulated MCU expression and increased mitochondrial Ca2+ uptake are found. MCU inhibition through siRNA or by Ru360 significantly attenuates Cd-induced excessive mitophagy, thereby rescues mitochondrial dysfunction and increases hepatocyte viability. Heterozygous MCU knockout mice exhibit improved liver function, ameliorated pathological damage, less mitochondrial fragmentation, and mitophagy after Cd exposure. Mechanistically, Cd upregulates MCU expression through phosphorylation activation of cAMP-response element binding protein at Ser133(CREBS133) and subsequent binding of MCU promoter at the TGAGGTCT, ACGTCA, and CTCCGTGATGTA regions, leading to increased MCU gene transcription. The upregulated MCU intensively interacts with voltage-dependent anion-selective channel protein 1 (VDAC1), enhances its dimerization and ubiquitination, resulting in excessive mitophagy. This study reveals a novel mechanism, through which Cd upregulates MCU to enhance mitophagy and hepatotoxicity. [ABSTRACT FROM AUTHOR]

Facial recognition technology and related research have matured over time, but research in the field of individual animal recognition is still very limited. Therefore, this article focuses on the identification of cashmere goats with similar characteristics. First, the single shot multibox detector network was used to process the dataset. Next, transfer learning was applied to learn the characteristics of the goats, as well as the loss function is composed of Triplet Loss and Label Smoothing CrossEntropy Loss function. The result of Label Smoothing CrossEntropy Loss function is fused by multiple different branches, which is convenient for classification. We added a small number of images of 24 different breeds of sheep to each cashmere goat dataset with different ID to promote the distance between training individuals, and then used the trained model to find the number of goats with the lowest recognition accuracy. The Cycle‐Consistent Adversarial Network (Cycle‐GAN) learned the goat dataset with a high error rate in individual identification. Unlike previous studies using the Cycle‐GAN, we took the novel approach of using this network to learn and combine the features seen in photos of cashmere goats. Since the learned features were all observed in the same goats, this method achieved better results in learning the features of the goats. Finally, we found that recognition can be performed on this data with an accuracy of 93.75%. These results suggest that identification based on deep learning has a high accuracy rate, as well as great value in identifying individual cashmere goats. [ABSTRACT FROM AUTHOR]

Energy materials featuring the capability to store and release chemical energy reversibly involve generally complex geometrical structures with multiple elements. It has been a great challenge to establish the quantitative relationship between the structure of materials and their dynamic physicochemical properties. In recent years, machine learning (ML) technique has demonstrated its great power in accelerating the research on energy materials. This topical review introduces the key ingredients and typical applications of ML to energy materials. We mainly focus on the ML based atomic simulation via ML potentials in different architectures/implementations, including high dimensional neural networks (HDNN), Gaussian approximation potential (GAP), moment tensor potentials (MTP) and stochastic surface walking global optimization with global neural network potential (SSW‐NN) method. Three cases studies, namely, Si, LiC and LiTiO systems, are presented to demonstrate the ability of ML simulation in assessing the thermodynamics and kinetics of complex material systems. We highlight that the SSW‐NN method provides an automated solution for global potential energy surface data collection, ML potential construction and ML simulation, which boosts the current ability for large‐scale atomic simulation and thus holds the great promise for fast property evaluation and material discovery. [ABSTRACT FROM AUTHOR]

Energy materials featuring the capability to store and release chemical energy reversibly involve generally complex geometrical structures with multiple elements. It has been a great challenge to establish the quantitative relationship between the structure of materials and their dynamic physicochemical properties. In recent years, machine learning (ML) technique has demonstrated its great power in accelerating the research on energy materials. This topical review introduces the key ingredients and typical applications of ML to energy materials. We mainly focus on the ML based atomic simulation via ML potentials in different architectures/implementations, including high dimensional neural networks (HDNN), Gaussian approximation potential (GAP), moment tensor potentials (MTP) and stochastic surface walking global optimization with global neural network potential (SSW‐NN) method. Three cases studies, namely, Si, LiC and LiTiO systems, are presented to demonstrate the ability of ML simulation in assessing the thermodynamics and kinetics of complex material systems. We highlight that the SSW‐NN method provides an automated solution for global potential energy surface data collection, ML potential construction and ML simulation, which boosts the current ability for large‐scale atomic simulation and thus holds the great promise for fast property evaluation and material discovery. [ABSTRACT FROM AUTHOR]

Malignant pleural mesothelioma (MPM) is a type of cancer originating from the pleura with high aggressiveness and poor prognosis. A timely diagnosis is crucial to improve its prognosis. Laboratory biomarkers have significant advantages of reduced invasiveness, low cost, and are observer‐independent, and therefore represent a promising diagnostic tool for MPM. MicroRNA is a family of non‐coding RNA that regulates gene expression at the post‐transcriptional level. Accumulated studies showed that microRNA, either in tissue, circulating, and body fluid, has potential diagnostic value for various disorders. Here, we reviewed the diagnostic value of microRNA for MPM. [ABSTRACT FROM AUTHOR]

River wetted width (RWW) is an important variable in the study of river hydrological and biogeochemical processes. Presently, RWW is often measured from remotely sensed imagery, and the accuracy of RWW estimation is typically low when coarse spatial resolution imagery is used because river boundaries often run through pixels that represent a region that is a mixture of water and land. Thus, when conventional hard classification methods are used in the estimation of RWW, the mixed pixel problem can become a large source of error. To address this problem, this paper proposes a novel approach to measure RWW at the subpixel scale. Spectral unmixing is first applied to the imagery to obtain a water fraction image that indicates the proportional coverage of water in image pixels. A fine spatial resolution river map from which RWW may be estimated is then produced from the water fraction image by superresolution mapping (SRM). In the SRM analysis, a deep convolutional neural network is used to eliminate the negative effects of water fraction errors and reconstruct the geographical distribution of water. The proposed approach is assessed in two experiments, with the results demonstrating that the convolutional neural network‐based SRM model can effectively estimate subpixel scale details of rivers and that the accuracy of RWW estimation is substantially higher than that obtained from the use of a conventional hard image classification. The improvement shows that the proposed method has great potential to derive more accurate RWW values from remotely sensed imagery. Key Points: The accuracy of river wetted width measured with remotely sensed imagery is mainly affected by mixed pixels along river boundariesThe deep convolutional neural network effectively eliminates fraction errors and models the geographical distribution of water accuratelyThe super‐resolution mapping analysis can substantially increase the accuracy of river wetted width estimation [ABSTRACT FROM AUTHOR]

The potential energy surface (PES) calculation is the bottleneck for modern material simulation. The high‐dimensional neural network (HDNN) technique emerged recently appears to be a problem solver for fast and accurate PES computation. The major cost of the HDNN lies at the computation of the structural descriptors that capture the geometrical environment of atoms. Here, we introduce a massive parallelization strategy optimized for our recently developed power‐type structural descriptor. The method involves three‐levels: from the top to the bottom the parallelization is over atoms first, then, over structural descriptors and finally over the n‐body functions. We illustrate the parallelization method in a boron crystal system and show that the parallelization efficiency is maximally 100%, 58%, and 34% at each level. © 2018 Wiley Periodicals, Inc. A massive parallelization strategy is designed to speed up the computation of high‐dimensional neural network based on the power‐type structural descriptors. The parallelization framework is designed to be hierarchical with three‐levels to make the best use of computational resources. Using this framework, the authors achieved a speed‐up of 411 on 560 cores for the neural network computation of a 560‐atom Boron solid. [ABSTRACT FROM AUTHOR]

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Heparin-binding hemagglutinin (HBHA) is a 199 amino acid virulence factor at the envelope of Mycobacterium tuberculosis that contributes to latent tuberculosis. The binding of HBHA to respiratory epithelial cells, which leads to extrapulmonary dissemination of the pathogen, is mediated by cell-surface heparan sulfate (HS). We report the structural characterization of the HBHA/HS complex by NMR spectroscopy. To develop a model for the molecular recognition, the first chemically synthesized uniformly 13C- and 15N-labeled HS octasaccharide and a uniformly 13C- and 15N-labeled form of HBHA were prepared. Residues 180-195 at the C-terminal region of HBHA show large chemical shift perturbation upon association with the octasaccharide. Molecular dynamics simulations conforming to the multidimensional NMR data revealed key electrostatic and even hydrophobic interactions between the binding partners that may aid in the development of agents targeting the binding event. [ABSTRACT FROM AUTHOR]

New Findings What is the central question of this study? Our previous study demonstrates that elevated orexin 2 receptor (OX2R) activity within the rostral ventrolateral medulla (RVLM) contributes to hypertension in spontaneously hypertensive rats (SHRs), and a lower OX2R protein level was detected in their RVLM. The present study aims to explore the mechanisms underlying elevated orexinergic activity in the RVLM of SHRs, compared with their normotensive counterparts, Wistar-Kyoto rats., What is the main finding and its importance? Increased orexinergic input into the RVLM and enhanced OX2R responsiveness in the RVLM, which was mainly mediated by augmented OX2R-neuronal nitric oxide synthase signalling, may underlie the elevated OX2R activity within the RVLM of SHRs., Our previous study showed that elevated orexin 2 receptor (OX2R) activity within the rostral ventrolateral medulla (RVLM) contributes to hypertension in spontaneously hypertensive rats (SHRs). Herein, we investigated the mechanism(s) underlying the elevated OX2R activity. The following results were found. (i) More hypothalamic orexin A-immunoreactive (OXA-IR) cells existed in SHRs than in Wistar-Kyoto (WKY) rats at either 4 (2217 ± 43 versus 1809 ± 69) or 16 weeks of age (1829 ± 59 versus 1230 ± 84). The number of OXA-IR cells that project to the RVLM was higher in 16-week-old SHRs than in WKY rats (91 ± 11 versus 52 ± 11). (ii) Higher numbers of OXA-IR and RVLM-projecting OXA-IR cells were found in the dorsomedial and perifornical hypothalamus of 16-week-old SHRs. (iii) Spontaneously hypertensive rats had higher levels of orexin A and B in the hypothalamus and higher levels of orexin A in the RVLM than did WKY rats. (iv) Unilateral intra-RVLM application of OX2R agonist, orexin A or [Ala11, d-Leu15]-orexin B (50 pmol) induced a larger pressor response in SHRs than in WKY rats. (v) Intra-RVLM pretreatment with a neuronal nitric oxide synthase (NOS) inhibitor, 7-nitro-indazole (2.5 pmol), or a soluble guanylate cyclase inhibitor, methylene blue (250 pmol), reducedthe intra-RVLM [Ala11, d-Leu15]-orexin B-induced pressor response in both WKY rats and SHRs. In contrast, an inducible NOS inhibitor, aminoguanidine (100 pmol), was ineffective. (vi) Neuronal NOS was co-expressed with OX2R in RVLM neurons. In conclusion, increased orexinergic input and enhanced OX2R-neuronal NOS signalling may underlie elevated OX2R activity in the RVLM and contribute to the pathophysiology of hypertension in SHRs. [ABSTRACT FROM AUTHOR]

The relationship between microstructure and mechanical properties was studied in a Nb-bearing high-speed railway wheel steel and compared with a traditional low-alloyed medium carbon steel. The microstructure of medium carbon steel comprised of ferrite and pearlite and the percentage of ferrite was increased from 4 to 24% on the addition of 0.06 wt% Nb and the grain size was refined. The addition of Nb inhibited mixed microstructure and delayed the coarsening temperature of austenite grains from 880 to 960 °C. The yield strength of Nb-bearing steel was increased from 385 to 455 MPa and the Charpy v-notch energy at -20 °C was increased from 7.0 to 19.0 J with no apparent reduction in tensile strength. Niobium formulates grain refinement and transformation of austenite to ferrite and pearlite over a wide region of cooling rate (<10 °Cs-1) and temperature range (530-690 °C) in the medium carbon steel. With the calculation of Thermal-Calc software and solid solubility formula, Nb exists in the form of precipitates. The grain refining and precipitation strengthening are roles of niobium in promoting ferrite-pearlite transformation and improve toughness in the medium carbon steel. [ABSTRACT FROM AUTHOR]

In recent years, there has been rapid expansion of glycan synthesis, fueled by the recognition that the structural complexity of sugars translates to a myriad of biological functions. Such chemical syntheses involve many challenges, mostly due to the regio- and stereochemical aspects of glycosidic bond formation. One-pot strategies were developed to assist in attaining faster and more economical access to the glycan constructs. In this front, achievements in protecting group manipulation, glycosylation, and combinations of these have been reported. Protecting group manipulations in one pot take advantage of the reaction compatibility of commonly used transformations, many of which occur in high regioselectivity. Sequential glycosylations, on the other hand, rely on leaving group orthogonalities and reactivity tuning, as well as the preactivation technique. Altogether, these approaches offer attractive means to the much needed glycan structures and, consequently, help usher in advances in glycoscience. [ABSTRACT FROM AUTHOR]

Fondaparinux, a synthetic pentasaccharide based on the heparin antithrombin-binding domain, is an approved clinical anticoagulant. Although it is a better and safer alternative to pharmaceutical heparins in many cases, its high cost, which results from the difficult and tedious synthesis, is a deterrent for its widespread use. The chemical synthesis of fondaparinux was achieved in an efficient and concise manner from commercially available D-glucosamine, diacetone α- D-glucose, and penta-O-acetyl- D-glucose. The method involves suitably functionalized building blocks that are readily accessible and employs shared intermediates and a series of one-pot reactions that considerably reduce the synthetic effort and improve the yield. [ABSTRACT FROM AUTHOR]

Human lung epithelial cells natively offer terminal N-acetylneuraminic acid (Neu5Ac) α(2→6)-linked to galactose (Gal) as binding sites for influenza virus hemagglutinin. N-Glycolylneuraminic acid (Neu5Gc) in place of Neu5Ac is known to affect hemagglutinin binding in other species. Not normally generated by humans, Neu5Gc may find its way to human cells from dietary sources. To compare their influence in influenza virus infection, six trisaccharides with Neu5Ac or Neu5Gc α(2→6) linked to Gal and with different reducing end sugar units were prepared using one-pot assembly and divergent transformation. The sugar assembly made use of an N-phthaloyl-protected sialyl imidate for chemoselective activation and α-stereoselective coupling with a thiogalactoside. Assessment of cytopathic effect showed that the Neu5Gc-capped trisaccharides inhibited the viral infection better than their Neu5Ac counterparts. [ABSTRACT FROM AUTHOR]

The unique, plate-like morphology of hydroxyapatite (HAP) nanocrystals in bone lends to the hierarchical structure and functions of bone. Proteins enriched in phosphoserine (Ser-OPO3) and glutamic acid (Glu) residues have been proposed to regulate crystal morphology; however, the atomic-level mechanisms remain unclear. Previous molecular dynamics studies addressing biomineralization have used force fields with limited benchmarking, especially at the water/mineral interface, and often limited sampling for the binding free energy profile. Here, we use the umbrella sampling/weighted histogram analysis method to obtain the adsorption free energy of Ser-OPO3 and Glu on HAP (100) and (001) surfaces to understand organic-mediated crystal growth. The calculated organic-water-mineral interfacial energies are carefully benchmarked to density functional theory calculations, with explicit inclusion of solvating water molecules around the adsorbate plus the Poisson-Boltzmann continuum model for long-range solvation effects. Both amino acids adsorb more strongly on the HAP (100) face than the (001) face. Growth rate along the [100] direction should then be slower than in the [001] direction, resulting in plate-like crystal morphology with greater surface area for the (100) than the (001) face, consistent with bone HAP crystal morphology. Thus, even small molecules are capable of regulating bone crystal growth by preferential adsorption in specific directions. Furthermore, Ser-OPO3 is a more effective growth modifier by adsorbing more strongly than Glu on the (100) face, providing one possible explanation for the energetically expensive process of phosphorylation of some proteins involved in bone biomineralization. The current results have broader implications for designing routes for biomimetic crystal synthesis. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The cell envelope of mycobacterial species, which include the deadly Mycobacterium tuberculosis, carries unique glycan structures that are crucial for infection and bacterial survival. Notable among these glycans are the structurally-related phosphatidylinositol mannosides (PIMs), lipomannan, and lipoarabinomannan. The immunoactivities of these structures attracted considerable attention from synthetic chemists and biologists alike, who are keen on evaluating vaccine or adjuvant properties. Moreover, PIMs are interesting synthetic targets because of the regio- and stereoselective considerations in generating the inositol and mannosyl cores. In this paper, we summarize the recent efforts in the chemical synthesis of PIMs as well as their analogues. Particular emphasis is given on the challenges associated with the preparation of the chiral myo-inositol derivatives, the regioselective installation of mannosyl residues, and phosphatidylation strategies. The results of the bioevaluation of selected compounds are also briefly described. [ABSTRACT FROM AUTHOR]

New Findings What is the central question of this study? Central orexinergic activity is involved in tonic and phasic control of cardiovascular homeostasis. A potential role for elevated central orexinergic activity in the maintenance of hypertension in spontaneously hypertensive rats (SHRs) has not previously been explored., What is the main finding and what is its importance? We show that central or intra-rostral ventrolateral medulla blockade of orexin 2 receptors produces a significant reduction of arterial pressure in SHRs, but not Wistar-Kyoto rats. This study demonstrates a previously unrecognized role of orexin 2 receptors in maintaining hypertension in SHRs., Orexins can raise arterial pressure and sympathetic activity and are involved in tonic and phasic control of cardiovascular homeostasis. We hypothesized that elevated central orexinergic activity contributes to the maintenance of hypertension in spontaneously hypertensive rats (SHRs). We examined this hypothesis by suppressing central orexinergic activity in SHRs and Wistar-Kyoto rats (WKYs) with specific antagonists or antibodies against orexin 1 (OX1R) and 2 receptors (OX2R). Intracerebroventricular administration of an OX1R antagonist, SB-334867 (30 and 100 nmol), induced no significant change in mean arterial pressure (MAP) and heart rate (HR) in SHRs and WKYs except that at 100 nmol it reduced HR in WKYs. In contrast, an OX2R antagonist, TCS-OX2-29 (3-30 nmol) induced long-lasting reductions of MAP and HR in SHRs (21 ± 3 mmHg and 22 ± 2 beats min−1 at 30 nmol), but not in WKYs. Intracerebroventricular anti-OX2R IgG, but not anti-OX1R IgG or non-immune goat IgG, significantly lowered MAP and HR in SHRs. None of the three IgGs affected MAP or HR in WKYs. The OX2R protein level in the rostral ventrolateral medulla (RVLM) was lower in SHRs than in WKYs, whereas no differences were found between SHRs and WKYs in the paraventricular hypothalamic nucleus, dorsomedial-perifornical hypothalamic area or caudal nucleus tractus solitarii. The OX1R protein levels in these four regions did not differ between SHRs and WKYs. Injection of TCS-OX2-29 (50 pmol) into the RVLM produced a larger reduction of MAP in SHRs than in WKYs. We conclude that elevated OX2R-mediated activity in the brain, especially in the RVLM, may contribute to hypertension in SHRs. [ABSTRACT FROM AUTHOR]

Recent studies suggest that oxidative stress and mitochondrial dysfunction play important roles in the neurotoxicity of nickel. Because mitochondrial DNA (mtDNA) is highly vulnerable to oxidative stress and melatonin can efficiently protect mtDNA against oxidative damage in various pathological conditions, the aims of this study were to determine whether mtDNA oxidative damage was involved in the neurotoxicity of nickel and to assay the neuroprotective effects of melatonin in mtDNA. In this study, we exposed mouse neuroblastoma cell lines (Neuro2a) to different concentrations of nickel chloride (NiCl2, 0.125, 0.25, and 0.5 m m) for 24 hr. We found that nickel significantly increased reactive oxygen species (ROS) production and mitochondrial superoxide levels. In addition, nickel exposure increased mitochondrial 8-hydroxyguanine (8-OHdG) content and reduced mtDNA content and mtDNA transcript levels. Consistent with this finding, nickel was found to destroy mtDNA nucleoid structure and decrease protein levels of Tfam, a key protein component for nucleoid organization. However, all the oxidative damage to mtDNA induced by nickel was efficiently attenuated by melatonin pretreatment. Our results suggest that oxidative damage to mtDNA may account for the neurotoxicity of nickel. Melatonin has great pharmacological potential in protecting mtDNA against the adverse effects of nickel in the nervous system. [ABSTRACT FROM AUTHOR]

Nickel is a potential neurotoxic pollutant. Oxidative stress is supposed to be involved in the mechanism underlying nickel-induced neurotoxicity. Melatonin has efficient protective effects against various oxidative damages in nervous system. The purpose of this study was to investigate whether melatonin could efficiently protect against neurotoxicity induced by nickel. Here, we exposed primary cultured cortical neurons and mouse neuroblastoma cell lines (neuro2a) to different concentrations of nickel chloride (NiCl2) (0.125, 0.25, 0.5, and 1 mm) for 12 hr or 0.5 mm NiCl2 for various periods (0, 3, 6, 12, and 24 hr). We found that nickel significantly increased reactive oxygen species production and caused the loss of cell viability both in cortical neurons and neuro2a cells. In addition, nickel exposure obviously inhibited the mitochondrial function, disrupted the mitochondrial membrane potential (ΔΨm), reduced ATP production, and decreased mitochondrial DNA (mtDNA) content. However, each of these oxidative damages was efficiently attenuated by melatonin pretreatment. These protective effects of melatonin may be attributable to its roles in reducing oxidative stress and improving mitochondrial function in nickel-treated nerve cells. Our results suggested that melatonin may have great pharmacological potential in protecting against the adverse effects of nickel in the nervous system. [ABSTRACT FROM AUTHOR]

Here we introduce the LASP code, which is designed for large‐scale atomistic simulation of complex materials with neural network (NN) potential. The software architecture and functionalities of LASP will be overviewed. LASP features with the global neural network (G‐NN) potential that is generated by learning the first principles dataset of global PES from stochastic surface walking (SSW) global optimization. The combination of the SSW method with global NN potential facilitates greatly the PES exploration for a wide range of complex materials. Not limited to SSW‐NN global optimization, the software implements standard interfaces to dock with other energy/force evaluation packages and can also perform common tasks for computing PES properties, such as single‐ended and double‐ended transition state search, the molecular dynamics simulation with and without restraints. A few examples are given to illustrate the efficiency and capabilities of LASP code. Our ongoing efforts for code developing and G‐NN potential library building are also presented. This article is categorized under: Software > Simulation Methods [ABSTRACT FROM AUTHOR]

The cover picture shows the one‐pot methods enabling the protection of sugar building blocks and glycosylation to assemble oligosaccharides inspired by their natural counterparts. These synthetic sugars could help to understand and take advantage of the character of sugar functions in nature. Read more in the Review from the group of S.‐C. Hung on page 347. [ABSTRACT FROM AUTHOR]