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Effects of Salvia miltiorrhiza Bunge extract and its single components on monosodium urate-induced pain in vivo and lipopolysaccharide-induced inflammation in vitro

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Journal of Traditional Chinese Medicine 2021年第2期41卷 219-226页

作者： FENG Jinghui Set Byeol Kim Hee Jung Lee su min sim Soon sung Lim Hong Won suh Department of Pharmacology College of MedicineHallym UniversityChuncheon 200-702South Korea Department of Food Sciences and Nutrition College of NaturalHealthand Life SciencesHallym UniversityChuncheon 200-702Republic of

OBJECTIVE:To investigate the possible antinociceptive effects of Salvia(S.)miltiorrhiza Bunge and its single components in monosodium urate(Msu)-induced pain model in mice and lipopolysaccharide(LPS)-induced inflammation model in RAW264.7 ***:Pretreatment of *** Bunge extract(from 1 to 50μg/mL)concentration-dependently attenuated LPS-induced nitric oxide(NO)*** extract of *** Bunge(50 or 100 mg/kg)also caused reversals of decreased threshold for pain in the Msu-treated group as measured by Von-Frey ***,we assessed the antinociceptive and anti-inflammatory properties of the active single components from *** Bunge such as 15,16-dihydrotanshinoneⅠ,tanshinoneⅠ,cryptotanshinone,miltirone,tanshinoneⅡA,and salvianolic acid *** of them showed an anti-inflammatory effect in LPS-induced NO release model and an antinociceptive effect in Msu-treated pain ***:Our results suggest that *** Bunge extract may exert anti-inflammatory effect by reducing LPS-induced NO release and an antinociceptive property in Msu-treated pain ***,tanshinoneⅡA,miltirone,cryptotanshinone,and 15,16-dihydrotanshinoneⅠ,not only appear to be responsible for LPS-induced NO release induced by *** Bunge,but also in the production of *** Bunge extract-induced antinociception in Msu-treated pain ***:Therefore,the analgesic and anti-inflammatory property of *** Bunge indicate it as a therapeutic potential candidate for the treatment of pain and inflammation.

关键词： Salvia miltiorrhiza lipopolysaccharides nitric oxide inflammation analgesics

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Study on viscosity mechanism of caffeine crystallization solutions Author links open overlay panel

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Particuology 2024年第8期91卷 341-350页

作者： Linjing Yu min su School of Chemical Engineering Hebei University of TechnologyTianjin300130China

The solid-liquid viscous system formed by high viscosity crystallization solution impacts the flow and separation ***,it is very important to study the viscosity mechanism to improve viscosity and regulate crystallization,ensuring a seamless production ***,the viscosity of crystallization solution was taken as the measurement parameter of caffeine as a model *** investigated the viscosity mechanism of caffeine crystallization solutions by combining experiment and *** results indicated that the weak interactions between caffeine and water result in increased viscosity of the caffeine crystallization ***,caffeine crystals possess elongated needle-like shapes,featuring a substantial specific surface ***,there isπ-πstacking occurring between the(200)crystal face and(110)crystal face,effectively fostering coalescence of the crystals towards the radial side of the crystal along its elongated axis,resulting in a more viscous crystallization *** results contribute to comprehending the viscosity mechanism of crystal systems and provide theoretical foundation to enhance engineering efficiency in crystallization.

关键词： Crystallization Caffeine Viscosity mechanism Molecular simulation

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Synergistic precipitant powered self-assembly of papain for cross-linked enzyme crystals preparation

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Particuology 2024年第2期85卷 102-112页

作者： Qi Hao Pan Guo Honghai Wang min su Chunli Li Yuqi Hu Weiyi su School of Chemical Engineering and Technology Hebei University of TechnologyTianjin300130China National-Local Joint Engineering Laboratory for Energy Conservation of Chemical Process Integration and Resources Utilization Tianjin300130China

In this study,we prepared cross-linked enzyme crystals(CLECs)of papain to further broaden the application of the enzyme with high activity in extreme ***,papain crystals were successfully obtained based on the micro-batch,batch,and expanded batch crystallization ***,ammonium sulfate and polyethylene glycol 6000(PEG6000)were synergistically used as the precipitants,while L-cysteine was applied to enhance the activity of ***,the interaction between L-cysteine and papain was modeled by molecular docking *** was found that L-cysteine could form a hydrogen bond with aspartic acid residue(Asp)at site 158,and the electrostatic attraction with lysine residue(Lys)at site 156 was also quite *** the enzyme crystals were cross-linked by glutaraldehyde at optimized *** papain CLECs were identified by various methods,and it was found that the thermal stability and enzymatic activity both increased compared to the raw *** importantly,it could be applied at more rigorous conditions,for example,pH of 4.

关键词： Papain Cross-linked enzyme crystals L-cysteine Molecular docking Crystallization

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Reconstructing historical forest fire risk in the non-satellite era using the improved forest fire danger index and long short-term memory deep learning-a case study in Sichuan Province,southwestern China

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Forest Ecosystems 2024年第1期11卷 87-99页

作者： Yuwen Peng Huiyi su min sun mingshi Li Co-Innovation Center for sustainable Forestry in Southern China Nanjing Forestry UniversityNanjing 210037China College of Forestry Nanjing Forestry UniversityNanjing 210037China

Historical forest fire risk databases are vital for evaluating the effectiveness of past forest management approaches,enhancing forest fire warnings and emergency response capabilities,and accurately budgeting potential carbon emissions resulting from ***,due to the unavailability of spatial information technology,such databases are extremely difficult to build reliably and completely in the non-satellite *** study presented an improved forest fire risk reconstruction framework that integrates a deep learning-based time series prediction model and spatial interpolation to address the challenge in Sichuan Province,southwestern ***,the forest fire danger index(FFDI)was improved by supplementing slope and aspect *** compared the performances of three time series models,namely,the autoregressive integrated moving average(ARIMA),Prophet and long short-term memory(LSTM)in predicting the modified forest fire danger index(MFFDI).The bestperforming model was used to retrace the MFFDI of individual stations from 1941 to *** this,the Anusplin spatial interpolation method was used to map the distributions of the MFFDI at five-year intervals,which were then subjected to weighted overlay with the distance-to-river layer to generate forest fire risk maps for reconstructing the forest fire danger *** results revealed LSTM as the most accurate in fitting and predicting the historical MFFDI,with a fitting determination coefficient(R^2)of 0.709,mean square error(MSE)of0.047,and validation R^2 and MSE of 0.508 and 0.11,*** validation of the predicted forest fire risk maps indicated that 5 out of 7 historical forest fire events were located in forest fire-prone areas,which is higher than the results determined from the original FFDI(2 out of 7).This proves the effectiveness of the improved MFFDI and indicates a high level of reliability of the historical forest fire risk reconstruction method proposed in this stu

关键词： Forest fire risk reconstruction MFFDI Time series models LSTM ARIMA Prophet Anusplin

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Strain Gradient Finite Element Formulation of Flexoelectricity in Ferroelectric Material Based on Phase-Field Method

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Acta Mechanica Solida Sinica 2024年第4期37卷 570-579页

作者： Shuai Wang Hengchang su min Yi Li-Hua Shao National Key Laboratory of Strength and Structural Integrity Institute of Solid MechanicsSchool of Aeronautic Science and EngineeringBeihang UniversityBeijing100191People’s Republic of China State Key Laboratory of Mechanics and Control for Aerospace Structures and Institute for Frontier Science and Key Laboratory for Intelligent Nano Materials and Devices of ministry of Education and College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing210016People’s Republic of China

Flexoelectricity is a two-way coupling effect between the strain gradient and electric field that exists in all dielectrics,regardless of point group ***,the high-order derivatives of displacements involved in the strain gradient pose challenges in solving electromechanical coupling problems incorporating the flexoelectric *** this study,we formulate a phase-field model for ferroelectric materials considering the flexoelectric effect.A four-node quadrilateral element with 20 degrees of freedom is constructed without introducing high-order shape *** microstructure evolution of domains is described by an independent order parameter,namely the spontaneous polarization governed by the time-dependent Ginzburg–Landau *** model is developed based on a thermodynamic framework,in which a set of microforces is introduced to construct the constitutive relation and evolution *** the flexoelectric part of electric enthalpy,the strain gradient is determined by interpolating the mechanical strain at the node via the values of Gaussian integration points in the isoparametric *** model is shown to be capable of reproducing the classic analytical solution of dielectric materials incorporating the flexoelectric *** model is verified by duplicating some typical phenomena in flexoelectricity in cylindrical tubes and truncated pyramids.A comparison is made between the polarization distribution in dielectrics and *** model can reproduce the solution to the boundary value problem of the cylindrical flexoelectric tube,and demonstrate domain twisting at domain walls in ferroelectrics considering the flexoelectric effect.

关键词： Flexoelectricity Phase-field method Ferroelectrics Domain configuration

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Optimization on crystallization process of the magnetic core lysozyme

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Particuology 2024年第4期87卷 106-113页

作者： Lixia Hou Chunxiao Qu min su Zhihan Liang Qi Hao School of Chemical Engineering Hebei University of TechnologyTianjin300130China

The continuous growth of the biomedical market highlights the significance of improvement in the ef-ficiency of batch production for protein drug ***,we investigated the effect of polymer-modified Fe_(3)O_(4) nanoparticles on lysozyme(Lys)crystallization at different conditions,using function-alized Fe_(3)O_(4) magnetic nanoparticles(Polymer C@Fe_(3)O_(4))as nucleation *** study revealed that the surface charge density of Polymer C@Fe_(3)O_(4) was highest at a modification mass ratio of Fe_(3)O_(4) to Polymer C is 8∶*** ratio facilitates the augmentation of electrostatic interaction and the promotion of *** adding 15%of the PolymerC@Fe_(3)O_(4) prepared from Fe_(3)O_(4) with an average particle size of 150 nm,the magnetic core lysozyme(M-Lys)crystals with an average particle size of 11.08μm,narrow size distribution,and regular morphology were obtained in a yield of 82.42%within 60 min.

关键词： Protein Crystallization Magnetic particle Lysozyme

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surfactant-assisted crystallization of lysozyme and its mechanism

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Particuology 2024年第7期90卷 199-208页

作者： Yujie Song Rongfei Ren min su Zhihan Liang Qi Hao School of Chemical Engineering Hebei University of TechnologyTianjin 300130China

surfactants were used to assist in the crystallization of *** types of surfactants with different structures(sodium dodecyl sulfate,cetyltrimethylammonium bromide,or betaine hydrochloride[BH])were *** study indicated that three surfactants were all capable of shortening the crystallization induction time of lysozyme,with BH inducing the shortest crystallization induction time(t=1 min)and the largest crystal size(37μm).The molecular interactions among each of the three surfactants aforementioned and lysozyme were also investigated by *** was found that hydrogen bonding dominantly acted between the carboxyl structure of the surfactant BH and the lysozyme,which produced the most favorable conformation for the self-assembly of lysozyme(promote lysozyme orderly aggregation and shorten the crystallization induction time).On this basis,the mechanism of surfactant-promoted lysozyme crystallization was proposed.

关键词： Protein Crystallization surfactant Lysozyme Molecular interaction Mechanism

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The study of intelligent algorithm in particle identification of heavy-ion collisions at low and intermediate energies

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Nuclear Science and Techniques 2024年第2期35卷 170-182页

作者： Gao-Yi Cheng Qian-min su Xi-Guang Cao Guo-Qiang Zhang School of Electronic and Electrical Engineering Shanghai University of Engineering ScienceShanghai 201620China Shanghai Advanced Research Institute Chinese Academy of SciencesShanghai 201210China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China

Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate *** urgently need solutions to the dilemma of traditional particle identification *** study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate *** intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 ***-based machine learning algorithms and deep learning algorithms *** show excellent performance and generalization *** additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is *** learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.

关键词： Heavy-ion collisions at low and intermediate energies Machine learning Ensemble learning algorithm Particle identification Data imbalance

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Identification of key genes regulating the synthesis of quercetin derivatives in Rosa roxburghii through integrated transcriptomics and metabolomics

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Journal of Integrative Agriculture 2024年第3期23卷 876-887页

作者： Liyao su min Wu Tian Zhang Yan Zhong Zongming(Max) Cheng State Key Laboratory of Crop Genetics and Germplasm Enhancement College of HorticultureNanjing Agricultural UniversityNanjing210095China

Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five different stages of R. roxburghii fruit development. Flavonoids and the genes related to their biosynthesis were found to undergo significant changes in abundance across different developmental stages, and numerous quercetin derivatives were identified. We found three gene expression modules that were significantly associated with the abundances of the different flavonoids in R. roxburghii and identified three structural UDP-glycosyltransferase genes directly involved in the synthesis of quercetin derivatives within these modules. In addition, we found that RrBEH4, RrLBD1 and RrPIF8could significantly increase the expression of downstream quercetin derivative biosynthesis genes. Taken together,these results provide new insights into the metabolism of flavonoids and the accumulation of quercetin derivatives in R. roxburghii.

关键词： Rosa roxburghii quercetin derivatives weighted gene co-expression network analysis transcription factor transcriptome metabolome

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Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding

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Light(Science & Applications) 2024年第3期13卷 466-477页

作者： Xinyuan Fang Xiaonan Hu Baoli Li Hang su Ke Cheng Haitao Luan min Gu Institute of Photonic Chips University of Shanghai for Science and TechnologyShanghai 200093China Centre for Artificial-Intelligence Nanophotonics School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China

Machine learning with optical neural networks has featured unique advantages of the information processing including high speed,ultrawide bandwidths and low energy consumption because the optical dimensions(time,space,wavelength,and polarization)could be utilized to increase the degree of ***,due to the lack of the capability to extract the information features in the orbital angular momentum(OAM)domain,the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network ***,we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network(CNN)based on Laguerre-Gaussian(LG)beam modes with diverse diffraction *** proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction,and deep-learning diffractive layers as a *** resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding,leading to an accuracy as high as 97.2%for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes,as well as a resistance to eavesdropping in point-to-point free-space ***,through extending the target encoded modes into multiplexed OAM states,we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%.Our work provides a deep insight to the mechanism of machine learning with spatial modes basis,which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

关键词： polarization mode momentum

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