Compound 3k治疗骨关节炎:调控氧化应激通路改善软骨细胞糖酵解的作用机制

背景:骨关节炎现已被认为是一种代谢性疾病,既往研究表明糖酵解在骨关节炎的发生发展中起重要作用。Compound 3k作为一种新型糖酵解小分子抑制剂,具有抗炎及抗肿瘤等功效,因此可靶向糖酵解,有望为骨关节炎治疗提供新的思路。目的:基于缺氧诱导因子1α/活性氧的氧化应激通路探究Compound 3k在糖酵解过度活跃所导致的骨关节炎中的作用机制。方法:取对数生长期的ATDC5成软骨细胞,用10 ng/mL白细胞介素1β作用24 h诱导骨关节炎体外细胞模型,以CCK-8法检测不同浓度(0.25,0.5,1,2.5,5,10,15μmol/L)Compound 3k的细胞毒性,选出合适浓度进行后续实验。将软骨细胞随机分为对照组、模型组、治疗组,模型组以10 ng/mL的白细胞介素1β诱导,治疗组以Compound 3k预刺激2 h后与白细胞介素1β共培养,用CCK-8法检测各组细胞增殖情况;用ELISA试剂盒检测各组细胞炎症水平;用试剂盒检测各组细胞活性氧、细胞外乳酸脱氢酶及葡萄糖含量;qRT-PCR及Western blot检测相关炎症因子白细胞介素6、肿瘤坏死因子α及糖酵解相关基因葡萄糖转运蛋白1、甘油醛3-磷酸脱氢酶、单羧酸转运蛋白1和缺氧诱导因子1α的表达水平。结果与结论:①与对照组相比,模型组细胞增殖活性下降、糖酵解水平活跃,表现为细胞外乳酸脱氢酶含量增加(P<0.001),葡萄糖含量减少(P<0.001),相关炎症因子白细胞介素6(P<0.0001)及肿瘤坏死因子α(P<0.001),糖酵解相关基因葡萄糖转运蛋白1(P<0.001)、甘油醛3-磷酸脱氢酶(P<0.001)、单羧酸转运蛋白1(P<0.001)及缺氧诱导因子1α(P<0.001)的表达水平均上调,并伴随氧化应激,活性氧过量产生。②与模型组相比,Compound 3k的治疗有效提高细胞增殖活性,抑制过度活跃的糖酵解水平的同时,抑制了骨关节炎软骨细胞炎症(P<0.001)及糖酵解相关基因的表达(P<0.001),且抑制氧化应激,缺氧诱导因子1α的表达水平下调(P<0.0001),活性氧水平下降。③上述结果证实,Compound 3k抑制了白细胞介素1β诱导的软骨细胞炎症,其机制可能与糖酵解及缺氧诱导因子1α/活性氧介导的氧化应激有关。

基于Multi-Agent的无人机集群体系自主作战系统设计

针对无人集群自主作战体系设计中的关键问题,提出基于Multi-Agent的无人集群自主作战系统设计方法。建立无人集群各节点的Agent模型及其推演规则;对于仿真系统模块化和通用化的需求,设计系统互操作式接口和无人集群自主作战的交互关系;开展无人集群系统仿真推演验证。仿真结果表明,所提设计方案不仅能够有效开展并完成自主作战网络生成-集群演化-效能评估的全过程动态演示验证,而且能够通过重复随机试验进一步评估无人集群的协同作战效能,最后总结了集群协同作战的策略和经验。

联合物理层与MAC层的multi-TRP上行重叠传输处理机制

针对非理想回程下现有协议难以有效处理多传输接收节点(multi-TRP)场景中多定时提前(multi-TA)导致的严重上行链路(UL)重叠传输问题,联合改进物理层复用技术和介质访问控制(MAC)令牌桶技术,提出了一种新型的UL重叠传输处理机制。该新型机制通过改进物理层重叠信道识别流程、复用要求及复用规则,将物理层复用信息与重叠信息反馈至MAC层,并对MAC层令牌桶技术进行优化。通过仿真实验对所提机制与现有协议机制进行对比,结果表明,在逻辑时隙不可重叠和可重叠2种情形下,物理上行控制信道(PUCCH)实际复用数量性能平均提升了57.58%和49.40%,物理上行共享信道(PUSCH)实际可用资源数量性能平均提升了12.09%和26.03%;优先级最高逻辑信道实际占用资源数量性能平均提升了33.33%和45.48%。

基于Multi-Agent的水电站变压器故障诊断系统

为了精准、快速完成水电站变压器的故障诊断,设计基于Multi-Agent的水电站变压器故障诊断系统。变压器状态监控agent将检测到的变压器故障信息发送给系统管理agent,系统管理agent通过通信agent将变压器故障信息发送给变压器故障诊断agent,变压器故障诊断agent利用小波变换方法提取变压器故障特征,并将其作为IFOA-SVM模型输入,完成变压器故障分类后,获取变压器故障诊断结果,该结果通过通信agent显示给用户。实验表明,该系统可有效诊断变压器故障诊断,诊断成功率受系统故障信息丢失率的影响较小,诊断耗时、耗能小,并具有较高故障诊断成功率。

Comparative evaluation of commercial Douchi by different molds:biogenic amines,non-volatile and volatile compounds

To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

Effect of different drying methods on the amino acids,α-dicarbonyls and volatile compounds of rape bee pollen

The significant demand for high quality food has motivated us to adopt appropriate processing methods to improve the food nutritional quality and flavors.In this study,the effects of five drying methods,namely,pulsed vacuum drying(PVD),freeze drying(FD),infrared drying(IRD),hot-air drying(HAD)and sun drying(SD)on free amino acids(FAAs),α-dicarbonyl compounds(α-DCs)and volatile compounds(VOCs)in rape bee pollen(RBP)were determined.The results showed that FD significantly released the essential amino acids(EAAs)compared with fresh samples while SD caused the highest loss.Glucosone was the dominantα-DCs in RBP and the highest loss was observed after PVD.Aldehydes were the dominant volatiles of RBP and SD samples contained more new volatile substances(especially aldehydes)than the other four drying methods.Comprehensively,FD and PVD would be potential methods to effectively reduce the quality deterioration of RBP in the drying process.

Numerical modeling of fracture propagation of supercritical CO_(2)compound fracturing

The exploitation of shale gas is promising due to depletion of the conventional energy and intensification of the greenhouse effect.In this paper,we proposed a heat-fluid-solid coupling damage model of supercritical CO_(2)(SC-CO_(2))compound fracturing which is expected to be an efficient and environmentally friendly way to develop shale gas.The coupling model is solved by the finite element method,and the results are in good agreement with the analytical solutions and fracturing experiments.Based on this model,the fracture propagation characteristics at the two stages of compound fracturing are studied and the influence of pressurization rate,in situ stress,bedding angle,and other factors are considered.The results show that at the SC-CO_(2)fracturing stage,a lower pressurization rate is conducive to formation of the branches around main fractures,while a higher pressurization rate inhibits formation of the branches around main fractures and promotes formation of the main fractures.Both bedding and in situ stress play a dominant role in the fracture propagation.When the in situ stress ratio(δ_(x)/δ_(y))is 1,the presence of bedding can reduce the initiation pressure and failure pressure.Nevertheless,it will cause the fracture to propagate along the bedding direction,reducing the fracture complexity.In rocks without bedding,hydraulic fracturing has the lengthening and widening effects for SC-CO_(2)induced fracture.In shale,fractures induced at the hydraulic fracturing stage are more likely to be dominated by in situ stresses and have a shorter reorientation radius.Therefore,fracture branches propagating along the maximum principal stress direction may be generated around the main fractures induced by SC-CO_(2)at the hydraulic fracturing stage.When the branches converge with the main fractures,fracture zones are easily formed,and thus the fracture complexity and damage area can be significantly increased.The results are instructive for the design and application of SC-CO_(2)compound fracturing.

Role of methoxy and C_(α)-based substituents in electrochemical oxidation mechanisms and bond cleavage selectivity of β-O-4 lignin model compounds

In order to better understand the specific substituent effects on the electrochemical oxidation process of β-O-4 bond, a series of methoxyphenyl type β-O-4 dimer model compounds with different localized methoxyl groups, including 2-(2-methoxyphenoxy)-1-phenylethanone, 2-(2-methoxyphenoxy)-1-phenylethanol, 2-(2-methoxyphenoxy)-1-(4-methoxyphenyl)ethanone, 2-(2-methoxyphenoxy)-1-(4-methoxyphenyl)ethanol, 2-(2,6-dimethoxyphenoxy)-1-(4-methoxyphenyl)ethanone, 2-(2,6-dimethoxyphenoxy)-1-(4-methoxyphenyl)ethanol have been selected and their electrochemical properties have been studied experimentally by cyclic voltammetry, and FT-IR spectroelectrochemistry. Combining with electrolysis products distribution analysis and density functional theory calculations, oxidation mechanisms of all six model dimers have been explored. In particular, a total effect from substituents of both para-methoxy(on the aryl ring closing to Cα) and Cα-OH on the oxidation mechanisms has been clearly observed, showing a significant selectivity on the Cα-Cβbond cleavage induced by electrochemical oxidations.

Preparation of lactic acid bacteria compound starter cultures based on pasting properties and its improvement of glutinous rice flour and dough

The effects of 5 lactic acid bacteria(LAB)fermentation on the pasting properties of glutinous rice flour were compared,and suitable fermentation strains were selected based on the changes of viscosity,setback value,and breakdown value to prepare LAB compound starter cultures.The results revealed that Latilactobacillus sakei HSD004 and Lacticaseibacillus rhamnosus HSD005 had apparent advantages in increasing the viscosity and reducing the setback and breakdown values of glutinous rice flour.In particular,the compound starter created using the two abovementioned LAB in the ratio of 3:1 had better performance than that using a single LAB in improving the pasting properties and increasing the water and oil absorption capacity of glutinous rice flour.Moreover,the gelatinization enthalpy of the fermented samples increased significantly.For frozen glutinous rice dough stored for 28 days,the viscoelasticity of frozen dough prepared by compound starter was better than that of control dough,and the freezable water content was lower than that of control dough.These results indicate that compound LAB fermentation is a promising technology in the glutinous rice-based food processing industry,which has significance for its application.

The Flipping-Free Full-Parallax Tabletop Integral Imaging with Enhanced Viewing Angle Based on Space-Multiplexed Voxel Screen and Compound Lens Array

Tabletop integral imaging display with a more realistic and immersive experience has always been a hot spot in three-dimensional imaging technology,widely used in biomedical imaging and visualization to enhance medical diagnosis.However,the traditional structural characteristics of integral imaging display inevitably introduce the flipping effect outside the effective viewing angle.Here,a full-parallax tabletop integral imaging display without the flipping effect based on space-multiplexed voxel screen and compound lens array is demonstrated,and two holographic functional screens with different parameters are optically designed and fabricated.To eliminate the flipping effect in the reconstruction process,the space-multiplexed voxel screen consisting of a projector array and the holographic functional screen is presented to constrain light beams passing through the corresponding lens.To greatly promote imaging quality within the viewing area,the aspherical structure of the compound lens is optimized to balance the aberrations.It cooperates with the holographic functional screen to modulate the light field spatial distribution.Compared with the simulation results,the distortion rate of the imaging display is reduced to less than 9%from more than 30%.In the experiment,the floating high-quality reconstructed three-dimensional image without the flipping effect can be observed with the correct 3D perception at 96°×96°viewing angle,where 44,100 viewpoints are employed.

Modern approaches for detection of volatile organic compounds in metabolic studies focusing on pathogenic bacteria:Current state of the art

Pathogenic microorganisms produce numerous metabolites,including volatile organic compounds(VOCs).Monitoring these metabolites in biological matrices(e.g.,urine,blood,or breath)can reveal the presence of specific microorganisms,enabling the early diagnosis of infections and the timely implementation of tar-geted therapy.However,complex matrices only contain trace levels of VOCs,and their constituent com-ponents can hinder determination of these compounds.Therefore,modern analytical techniques enabling the non-invasive identification and precise quantification of microbial VOCs are needed.In this paper,we discuss bacterial VOC analysis under in vitro conditions,in animal models and disease diagnosis in humans,including techniques for offline and online analysis in clinical settings.We also consider the advantages and limitations of novel microextraction techniques used to prepare biological samples for VOC analysis,in addition to reviewing current clinical studies on bacterial volatilomes that address inter-species in-teractions,the kinetics of VOC metabolism,and species-and drug-resistance specificity.

Analysis on the formation principle and present situation of nano phase state of multi-component self-assembly of traditional Chinese compound medicine decoction

Traditional Chinese medicine decoction is a complex polydispersed phase system containing real solution,colloid solution,emulsion and suspension.The compound decoction of traditional Chinese medicine has complex components,including saponins,alkaloids,polysaccharides,flavonoids,amino acids and so on,which can be self-assembled to form gels,fibers,micelles,vesicles and so on.The self-assembled nano-phase not only neutralizes the single drug and reduces the toxicity and side effects,but also has its own pharmacological effects,which complement each other to achieve synergistic effect,so as to achieve the role of drug supplement,which is of research significance.The formation principle,solubilization and synergism principle and characterization method of multi-component self-assembly of traditional Chinese medicine compound decoction are discussed in this paper.

Multi Location Field Evaluation of BC1F2 Sorghum Populations for Striga Resistance in Niger

In Niger, a landlocked country, sorghum is the second staple food cultivated over the country by smallholder farmer. The crop is important for human and animal consumption. Despite its importance, the crop is affected by biotic and abiotic constraints. Among those constraints, striga has a high impact on yield. In fact, to survive, farmers are growing their local preferred sorghum varieties wish is highly sensible to the weed. Striga management is a challenge that requires a permanent solution. In addition, the development of high-yielding Striga resistant genotypes will be appreciated by farmers. The development of striga resistance will be based on the breeding population performances under farmer’s diverse environmental conditions adaptation. The main objective of this study is to evaluate two breeding populations for striga resistance in two different environments at Boulke and Dibissou in Tahoua region, to identify the early and high-yielding striga tolerant genotypes under natural infestation.

A Robust Approach for Multi Classification-Based Intrusion Detection through Stacking Deep Learning Models

Intrusion detection is a predominant task that monitors and protects the network infrastructure.Therefore,many datasets have been published and investigated by researchers to analyze and understand the problem of intrusion prediction and detection.In particular,the Network Security Laboratory-Knowledge Discovery in Databases(NSL-KDD)is an extensively used benchmark dataset for evaluating intrusion detection systems(IDSs)as it incorporates various network traffic attacks.It is worth mentioning that a large number of studies have tackled the problem of intrusion detection using machine learning models,but the performance of these models often decreases when evaluated on new attacks.This has led to the utilization of deep learning techniques,which have showcased significant potential for processing large datasets and therefore improving detection accuracy.For that reason,this paper focuses on the role of stacking deep learning models,including convolution neural network(CNN)and deep neural network(DNN)for improving the intrusion detection rate of the NSL-KDD dataset.Each base model is trained on the NSL-KDD dataset to extract significant features.Once the base models have been trained,the stacking process proceeds to the second stage,where a simple meta-model has been trained on the predictions generated from the proposed base models.The combination of the predictions allows the meta-model to distinguish different classes of attacks and increase the detection rate.Our experimental evaluations using the NSL-KDD dataset have shown the efficacy of stacking deep learning models for intrusion detection.The performance of the ensemble of base models,combined with the meta-model,exceeds the performance of individual models.Our stacking model has attained an accuracy of 99%and an average F1-score of 93%for the multi-classification scenario.Besides,the training time of the proposed ensemble model is lower than the training time of benchmark techniques,demonstrating its efficiency and robustness.

Assessment of electrostatic discharge sensitivity of nitrogen-rich heterocyclic energetic compounds and their salts as high energy-density dangerous compounds:A study of structural variables

Nitrogen-rich heterocyclic energetic compounds(NRHECs)and their salts have witnessed widespread synthesis in recent years.The substantial energy-density content within these compounds can lead to potentially dangerous explosive reactions when subjected to external stimuli such as electrical discharge.Therefore,developing a reliable model for predicting their electrostatic discharge sensitivity(ESD)becomes imperative.This study proposes a novel and straightforward model based on the presence of specific groups(-NH_(2) or-NH-,-N=N^(+)-O^(-)and-NNO_(2),-ONO_(2) or-NO_(2))under certain conditions to assess the ESD of NRHECs and their salts,employing interpretable structural parameters.Utilizing a comprehensive dataset comprising 54 ESD measurements of NRHECs and their salts,divided into 49/5 training/test sets,the model achieves promising results.The Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and Maximum Error for the training set are reported as 0.16 J,0.12 J,and 0.5 J,respectively.Notably,the ratios RMSE(training)/RMSE(test),MAE(training)/MAE(test),and Max Error(training)/Max Error(test)are all greater than 1.0,indicating the robust predictive capabilities of the model.The presented model demonstrates its efficacy in providing a reliable assessment of ESD for the targeted NRHECs and their salts,without the need for intricate computer codes or expert involvement.

Organic Compounds Possessing the Plastic Crystalline Phase: Calculation of Their Fusion Enthalpies

For the first time, for different organic and inorganic compounds possessing the plastic crystalline phase, a new semiempirical equation describing dependence of their fusion enthalpies on such physico-chemical quantities as normal melting temperature, surface tension, molar volume and critical molar volume is received on the base of the principle of corresponding states and the energy equipartition theorem. Moreover, the proposed equation allows one to take into account the particularities of one-particle molecular rotation in the plastic crystalline phase.

Lightweight Res-Connection Multi-Branch Network for Highly Accurate Crowd Counting and Localization

Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.

Mutual information oriented deep skill chaining for multi‐agent reinforcement learning

Multi‐agent reinforcement learning relies on reward signals to guide the policy networks of individual agents.However,in high‐dimensional continuous spaces,the non‐stationary environment can provide outdated experiences that hinder convergence,resulting in ineffective training performance for multi‐agent systems.To tackle this issue,a novel reinforcement learning scheme,Mutual Information Oriented Deep Skill Chaining(MioDSC),is proposed that generates an optimised cooperative policy by incorporating intrinsic rewards based on mutual information to improve exploration efficiency.These rewards encourage agents to diversify their learning process by engaging in actions that increase the mutual information between their actions and the environment state.In addition,MioDSC can generate cooperative policies using the options framework,allowing agents to learn and reuse complex action sequences and accelerating the convergence speed of multi‐agent learning.MioDSC was evaluated in the multi‐agent particle environment and the StarCraft multi‐agent challenge at varying difficulty levels.The experimental results demonstrate that MioDSC outperforms state‐of‐the‐art methods and is robust across various multi‐agent system tasks with high stability.

Nutritional values,bioactive compounds and health benefits of purslane(Portulaca oleracea L.):a comprehensive review

Portulaca oleracea L.,commonly known as purslane,is a worldwide weed species belonging to the family Portulacaceae and has been known as“Global Panacea”.As one of the most widely consumed green vegetables and medicinal plants around the world,it has recently been re-evaluated as a potential“new crop”due to the properties that differentiate it as one of the best vegetable sources of omega-3 fatty acid(α-linolenic acid),as well as a variety of nutrients and phytochemicals.Accordingly,emerging research has found that purslane exhibits health-promoting properties like anti-inflammatory,anti-hyperglycemic,antioxidant,neuroprotective,and immunomodulatory.These findings suggest that this species possesses a potential using as a dietary supplement beyond potherb and traditional medicine.This review systematically summarizes the up-to-date research carried out on purslane,including the nutritional compositions,bioactive compounds,and health benefits it exerts as well as limitations,challenges,and future directions of research.Finally,we hope that this review would provide purslane with a comprehensive reference and future scope as functional and health-promoting food for disease prevention and treatment.

Bioactive compounds in Hericium erinaceus and their biological properties:a review

Hericium erinaceus is a nutritious edible and medicinal fungi,rich in a variety of functional active ingredients,with various physiological functions such as antioxidation,anticancer,and enhancing immunity.It is also effective in protecting the digestive system and preventing neurodegenerative diseases.In this review paper,we summarize the sources,structures and efficacies of the main active components in H.erinaceus fruiting body,mycelium,and culture media,and update the latest research progress on their biological activities and the related molecular mechanisms.Based on this information,we provide detailed challenges in current research,industrialization and information on the active ingredients of H.erinaceus.Perspectives for future studies and new applications of H.erinaceus are proposed.