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Due to the low activity and poor selectivity of current artificial nitrogen fixation catalysts, there is an urgent need to develop efficient and environmentally friendly Electrochemical ammonia synthesis (EAS) electrocatalysts. Electrochemical ammonia synthesis is considered an environmentally friendly and sustainable method for artificial nitrogen fixation. Herein, Fe2O3 nanoparticles assembled on MoSe2 (Fe2O3/MoSe2) were first developed and regarded as an efficient electrocatalytic nitrogen fixation catalyst with high electroactive. The Fe2O3/MoSe2 composites exhibited excellent NRR activity with an NH3 yield of 55.52 µg∙h− 1∙mg− 1 at -0.5 V and Faradaic efficiency of 9.6% at -0.6 V vs. RHE. Notably, the Fe2O3/MoSe2 composites exhibited excellent stability and durability in recycling tests. Density functional theory (DFT) calculations revealed that the interfacial charge transport from Fe2O3 to MoSe2 could significantly enhance the Electrochemical nitrogen reduction reaction (NRR) activity of Fe2O3/MoSe2 by promoting the conductivity of Fe2O3/MoSe2 and reducing the free energy barrier for the rate-determining of *N2 to *N2H formation step. This work provides a promising avenue for the green synthesis of NH3.

Although substantial evidence shows the link of local anesthesia and decreased tumor recurrence, the role of amide-linked local anesthetics, particularly bupivacaine, on angiogenesis (a hallmark of tumor progression and metastasis) has not been revealed. In this work, we demonstrate the anti-angiogenic activity of bupivacaine and its underlying mechanism in endothelial cells. We show that bupivacaine inhibits early stage of capillary network formation via suppressing endothelial cell migration without affecting adhesion to matrix. Bupivacaine also inhibits endothelial cell growth and survival. Mechanism analysis indicates that bupivacaine inhibits mitochondrial respiration via decreasing mitochondrial respiratory activity of complex I and II but not IV or V, resulting in energy depletion, oxidative stress, inhibition of Akt/mTOR, and activation of AMPK pathway. The rescue of an antioxidant NAC on the effects of bupivacaine confirms that bupivacaine inhibits angiogenesis through oxidative stress-dependent inhibition of Akt/mTOR and activation of AMPK. Our work clearly demonstrates the inhibitory effects of bupivacaine on angiogenesis via targeting mitochondria. Our findings are in line with the previous work providing the preclinical evidence on how local anesthetics could influence the outcome of cancer patients.

Background Dexmedetomidine (Dex) is a highly selective agonist of the α2 adrenergic receptor and a common sedative; however, its anti-inflammatory effect has been studied. In this study, the inhibitory effect of Dex on inflammation in dental pulp cells was assessed. For this, the effect of Dex on inflammation induced by carrageenan (Car) in human dental pulp cells (hDPCs) was evaluated. Car incubation induced a robust inflammatory response in hDPCs as well as activation of PKA–STAT3 and PKC–nuclear factor kappa B (NF-κB) signaling pathways. Results Dex reduced the expression of inflammatory cytokines in a dose-dependent manner. Meanwhile, the phosphorylation of PKA, PKC, STAT3, and NF-κB as well as the nuclear accumulation of STAT3 and NF-κB were significantly increased in Dex-treated Car-induced hDPCs. Western blotting results also showed that the phosphorylation level of transient receptor potential cation channel subfamily V member 1 (TRPV1) was downregulated as a result of Dex treatment. Furthermore, we found that administration of the TRPV1 agonist capsaicin (Cap) reversed the effects of Dex on proinflammatory cytokines; however, the expression and activation of PKA–STAT3 and PKC–NF-κB signals were not altered owing to Cap administration. Conclusions These results indicate that Dex plays a defensive role in dental pulp inflammation by regulating the TRPV1 channel and can be used as a potential target for human dental pulp inflammation intervention.

Constant alterations of oasis landscape pattern, triggered by specific natural and human driving forces, have aroused some heated discussions in the field of regional environmental change research especially in arid areas. In this study, the Normalized Difference Vegetation Index and the Soil Brightness Index have been selected to successfully identify discrete land cover classes derived from a series of Landsat satellite images of Manas River watershed in 1989, 1998, and 2014. FRAGSTATS and principal components analysis were used to recognize independent components of landscape structure. Nine land cover classes combined with ten landscape metrics indicated variations in the composition and configuration of landscape pattern. Results related to historical data were analyzed to identify driving forces, mainly including population growth, agricultural modernization, urbanization, and water resource provision. The results revealed a trend toward less landscape fragmentation, as indicated by a steady decrease in the number of patches as well as an increase in mean patch size and contagion. To be more specific, we found substantial increases in cropland (72.3%) as well as built-up land (43.7%) with larger and more compact patches, while water (64.1%), snow cover (52.0%), and saline–alkali soil (48.5%) dropped sharply. Our findings suggested that population influx and reclamation of saline–alkali soil were two major driving forces critical to those landscape pattern changes.

Structure characterization of intrinsically disordered proteins (IDPs) remains a key obstacle in understanding their functional mechanisms. Due to the highly dynamic feature of IDPs, structure ensembles instead of static unique structures are often derived from experimental data. Several state-of-the-art computational methods have been developed to select an optimal ensemble from a pregenerated structure pool, but they suffer from low efficiency for large IDPs. Here we present a matching pursuit genetic algorithm (MPGA) for structure ensemble determination, which takes advantages from both matching pursuit (MP) to reduce the search space and genetic algorithm (GA) to reduce the restriction on constraint types. The MPGA method is validated using a reference ensemble with predefined structures. In comparison with the conventional GA, MPGA takes much less computational time for large IDPs. The utility of the method is demonstrated by application to structure ensemble determination of a mechanosensing protein domain with 306 amino acids. The structure ensemble determined reveals that the N-terminal region 1-240 is more compact than the C-terminal region 240-306. The unique structural feature explains why only a small portion of YXXP tyrosine residues can be phosphorylated easily by kinases in the absence of extension force and why the phosphorylation is force-dependent.

Additional file 1: Fig. S1. Ropivacaine and bupivacaine arrest cell cycle via increasing G2/M percentage in esophageal carcinoma cells. After 24-h drug treatment, the cell cycle was assessed by staining cells with Propidium iodide (PI) and followed by flow cytometry. *P

Background : Dexmedetomidine (Dex) is a highly selective agonist of the α2 adrenergic receptor and a common sedative; however, its anti-inflammatory effect has been studied. In this study, the inhibitory effect of Dex on inflammation in dental pulp cells was assessed. To solve this problem, the effect of Dex on inflammation induced by carrageenan (Car) in human dental pulp cells (hDPCs) was studied. Car incubation induced a robust inflammatory response in the hDPCs as well as activation of PKA–STAT3 and PKC–nuclear factor kappa B (NFκB) signaling pathways. Results : Dex could reduce the expression of inflammatory cytokines in a dose-dependent manner. Meanwhile, the phosphorylation of PKA, PKC, STAT3, and NFκB as well as the nuclear accumulation of STAT3 and NFκB were significantly increased in Dex-treated Car-induced hDPCs. Western blotting results also showed that the phosphorylation level of transient receptor potential cation channel subfamily V member 1 (TRPV1) was downregulated owing to Dex treatment. Further, we found that the administration of the TRPV1 agonist capsaicin (Cap) reversed the effects of Dex on proinflammatory cytokines; however, the expression and activation of PKA–STAT3 and PKC–NFκB signals were not altered owing to Cap administration. Conclusions : These results indicate that Dex exerts a defensive role in dental pulp inflammation by regulating the TRPV1 channel and can be used as a potential target for human dental pulp inflammation intervention.

Our understanding of mutations in noncoding DNA is still nascent across most cancer types. Similarly, the potential clinical utility of noncoding DNA in cancer liquid biopsy assays remains mostly unexplored. Here, we identify high-frequency noncoding mutation hotspots in whole genomes from hundreds of gastrointestinal tumors and show that these mutations can be detected in liquid biopsy samples from cancer patients. We demonstrate how profiling of noncoding mutation hotspots can significantly increase the accuracy of ctDNA burden estimation, with minimal impact on sequencing cost, when paired with existing targeted cfDNA assays. Our results suggest that targeted NGS liquid biopsy assays should target both protein-coding and noncoding mutations when estimation and monitoring of ctDNA burden is a key clinical endpoint. Citation Format: Guo Yu, Zhong Wee Poh, Guanhua Zhu, Iain Tan, Sarah Ng, Patrick Tan, Anders Skanderup. Monitoring of ctDNA burden from noncoding DNA [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr 44.

A novel copper(II) complex [Cu2(BIT)4(DMF)2]•2DMF (BIT = 1,2-benzisothiazolin-3-one, DMF = N,N-dimethylformamide) was synthesized via standing diffusion method. The structure of crystal was characterized by elemental analysis, IR spectroscopy and single-crystal X-ray diffraction. The complex crystallizes in monoclinic C2/c space group and a = 30.850 (3) A, b = 8.5534 (8) A, c = 21.6491 (18) A, β= 128.487 (2)°, V = 4.4716 (7) nm3, Z = 4. The fluorescent properties of the complex was studied. Theoretical study of the complex was carried out by density functional theory B3LYP method using Gaussian 03 program. CCDC: 911350.

Zika virus (ZIKV) has become a great public health emergency. Its non-structural protein 3 (NS3) is a key enzyme in viral replication and has been considered as a potential therapeutic target. A conformational characterization of ZIKV NS3 is critical for a comprehensive understanding of its molecular interactions and functions. However, the high conformational flexibility of solution NS3 obstacles the structural characterization of NS3 solely from the experimental observable that averages over its heterogeneous conformations. Here, we employed replica exchange with solute tempering (REST) method to simulate the di-domain protein ZIKV NS3. Three independent MD simulations identified a conserved conformational ensemble of NS3, consisting of a major conformational state and several minor states from compact to loose conformations. The major state agrees well with the scattering profile from small-angle X-ray scattering (SAXS) experiments. Moreover, the simulated ensemble is supported by a direct data-fitting result that requires both short- and long-range structural contacts to recover the experimental data. We discussed the interplay between simulation and experiment in ensemble construction of flexible biomolecules and shed light on the physically derived conformational ensembles. Ministry of Education (MOE) This research is supported by the Tier 3 grant (MOE2012-T3-1- 008) from the Ministry of Education, Singapore.

The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure‐based and physics‐based atomistic force field with an efficient sampling strategy is adopted to simulate a model di‐domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low‐energy structures and the minimum‐size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small‐angle X‐ray scattering data. It is illustrated that the regularizations of energy and ensemble‐size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high‐energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure‐ensemble optimizations with a topology‐based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates. MOE (Min. of Education, S’pore) Accepted version

A novel complex, [(Cu2L4(CH3OH)(H2O)]·1/2CH3OH·H2O (HL = 2-furoic acid), was synthesized and characterized by elemental analysis, IR spectroscopy, and X-ray single-crystal diffraction. The title complex crystallizes in monoclinic, space group P2(1)/c with a = 10.2035 (12) A, b = 13.1875 (17) A, c = 20.069 (3) A, a = 90°, b = 90.1460 (10)°, g = 90°, V = 2700.4 (6) nm3, Z = 2, F(000) = 1332, S = 1.053, Dc = 1.612 g·cm−3, R 1 = 0.0664 ((I > 2σ(I)), wR 2 = 0.1772, μ = 1.648 mm−1. Theoretical study of the title complex was carried out by Density Functional Theory B3LYP method. CCDC: 921325.

An ensemble-modeling scheme incorporating coarse-grained simulations with experimental small-angle X-ray scattering (SAXS) data is applied to dengue virus 2 (DENV2) nonstructural protein 5 (NS5). NS5 serves a key role in viral replication through its two domains that are connected by a 10-residue polypeptide segment. A set of representative structures is generated from a simulated structure pool using SAXS data fitting by the non-negativity least squares (NNLS) or standard ensemble optimization method (EOM) based on a genetic algorithm (GA). It is found that a proper low-energy threshold of the structure pool is necessary to produce a conformational ensemble of two representative structures by both NNLS and GA that agrees well with the experimental SAXS profile. The stability of the constructed ensemble is validated also by molecular dynamics simulations with an all-atom force field. The constructed ensemble successfully revealed the domain–domain orientation and domain-contacting interface of DENV2 NS5. Using experimental data fitting and additional investigations with synthesized data, it is found that energy restraint on the conformational pool is necessary to avoid overinterpretation of experimental data by spurious conformational representations. MOE (Min. of Education, S’pore) Accepted version

The structural variation of multi-domain proteins with flexible components mediates many biological processes. Their structure determination is crucial for understanding the mechanism of their interactions and functions, but it remains a challenge to derive the structure ensemble of flexible biomolecules solely from experimental data. Computational methods assist in the interpretation of the time- and spatial-averaged experimental data for a correct structural characterization. A conformational ensemble can be determined by selecting a weighted combination of representative structures from a given structure pool, yielding the best fit to experimental measurements. However, a raw numerical data fitting causes the over-interpretation of the experimental data, which would recover the structure ensemble of wrong conformations. In our study, we have employed the idea of hybrid models to simulate multi-domain proteins. The intra-domain structures are modeled with the structure-based potential and the inter-domain interactions are characterized with the physics-based energies. For ensemble construction with experimental data, structure energy is proposed as a physics-based regularization to minimize the problem of data over-fitting. The absence of energy regularization exposes ensemble construction to the noise from high-energy structures. We have demonstrated the importance of the physics-based regularization to interpret experimental data to avoid arbitrary and spurious conformational representations. We have implemented our computational model and ensemble optimization to two systems of multi-domain proteins on the coarse-grained and atomistic levels respectively. Firstly, we simulate the dengue virus 2 (DENV2) non-structural protein 5 (NS5) at the coarse-grained level and construct its conformational ensemble with experimental small-angle X-ray scattering (SAXS) data. The energy regularization assists to recover a conformational ensemble from the SAXS profile, which successfully reveals the domain-domain orientation and domain contacting interface of NS5. Moreover, we applied the computational modeling scheme to a di-domain complex of a poly(U)-binding protein (Pub1), followed by ensemble construction with its experimental paramagnetic relaxation enhancement (PRE) data that correspond to inter-atomic distance restraints. A conformational ensemble of Pub1 has been recovered from the low-energy structures and with the ensemble-size restraint. This ensemble is in good agreement with experimental PRE rates and also supported by the experimental data of chemical shift perturbations. ​Doctor of Philosophy (SBS)

The activated carbon-filled cellulose acetate (CA) hollow-fiber membranes were prepared by using phase-inverse technique and subsequently characterized by scanning electronic microscopy (SEM), atomic force microscopy (AFM), dynamic mechanical analysis (DMA), thermal mechanical analysis (TMA), and tensile analysis. The SEM observation demonstrated that the activated carbon-filled CA hollow-fiber membranes possess four-layer structure, which consists of an external skin dense layer, an external void layer, a central sponge layer, and an internal skin dense layer, whereas the pure CA hollow-fiber membranes lack the macrovoid layer. As the measurement of AFM, the roughness of both internal and external surface of activated carbon-filled fibers is much higher than that of pure CA fiber, respectively. Higher Young's modulus and storage modulus of filled membranes indicate that the activated carbon particles were homogeneously dispersed in the polymeric matrix. To investigate the feasibility of the newly developed hollow-fiber membranes for cell immobilization cells and to evaluate the inhibitory effect of phenol on immobilized cells, Pseudomonas putida ATCC 17484 was chosen to be immobilized on both pure CA and activated carbon-filled hollow-fiber membranes. Batch experiments for phenol biodegradation were carried out for both free suspension and immobilized cells at the initial concentration of 1500 mg/L phenol. In the case of free suspension, neither cell growth nor phenol degradation occurred to any measurable extent up to 35 h. We found that both pure CA fiber and activated carbon-filled fiber immobilization systems can completely degrade the phenol. However, the biodegradation rate of activated carbon-filled fiber system was higher than that of pure CA fiber system. © 2000 John Wiley & Sons, Inc. J Appl Polym Sci 76: 695–707, 2000

It is an important way for segmentations of CT images to extract contours of objects slice-by-slice. For such a way, an important idea is analogy. That is to say, correct the contour in current slice (current contour) according to the contour in previous slice (previous contour). The key to properly correct the current contour is the ability to recognize occlusions (or say leaking parts) in the current contour. We present a curve-based curve parameterization method to recognize occlusions. The previous contour is evolved to the current contour using line projections. In the process of evolution, the parameterization is realized, which includes two types of information for every point in the evolved contour: the arc length parameter on the previous contour, and distance moved from the initial position to the present position. Using these two parameters, we are able to recognize occlusions in the current contour. Many experiments indicate that the method can recognize all of the occlusions in a given contour. Consequently, the method is robust and can be used as a part of an algorithm to automatically extract contours for CT images.