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Gut microbial-host-isozymes are new targets for diseases

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Science China(life Sciences) 2024年第7期67卷 1525-1527页

作者： Zhiwei Zhang kai Wang Changtao jiang Department of Physiology and Pathophysiology School of Basic Medical SciencesState Key Laboratory of Female Fertility PromotionCenter for Reproductive MedicinePeking UniversityBeijing 100191China Center for Obesity and Metabolic Disease Research School of Basic Medical SciencesState Key Laboratory of Vascular Homeostasis and RemodelingPeking UniversityBeijing 100191China

Gut microbiota can interact with the host through lots of media including small molecular metabolites and proteins(Cani,2019;Fan and Pedersen,2021;Krautkramer et al.,2021).Recently,a new interaction pattern was identified,i.e.,gut microbiota can mimic the function of the host by producing a variety of enzymes with functions homologous to host enzymes.

关键词： al. diseases pattern

The efficiency and safety evaluation of hemoglobin hydrolysate as a non-heme iron fortifier

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Food Science and Human Wellness 2024年第2期13卷 999-1010页

作者： Dejiang Xue Shuai jiang Miao Zhang kai Shan RenéLametsch Chunbao li Key Laboratory of Meat Processing and Quality Control Ministry of EducationKey Laboratory of Meat ProcessingMinistry of Agriculture and Rural AffairsJiangsu Collaborative Innovation Center of Meat ProductionProcessing and Quality ControlCollege of Food Science and TechnologyNanjing Agricultural UniversityNanjing 210095China Department of Food Science University of CopenhagenFrederiksberg C DK-1958Denmark

Hemoglobin hydrolysate is derived from the enzymatic degradation of hemoglobin.This work aimed to evaluate whether hemoglobin hydrolysate promotes the absorption of non-heme iron and the safety of absorbed iron in mice by analyzing the iron binding content,iron circulation,and liver homeostasis.We found that hemoglobin hydrolysate promoted the absorption of non-heme iron with high efficiency in duodenum by spontaneously binding non-heme iron during digestion,and increased hepatic iron content by up-regulating divalent metal transporter 1,zinc transporter 14,but hepatic iron content only increased at 3 weeks.Duodenal iron entered the blood through ferroportin without restriction at 3 weeks,and excessive iron entered the liver and then affected the hepatocyte membranes permeability and lipid synthesis through oxidative stress.With the prolongation of dietary intervention,the up-regulated hepcidin acted on the ferroportin to restrict excess iron from entering the blood,and then the hepatic homeostasis recovered.In addition,hemoglobin hydrolysate enhanced the hepatic antioxidant capacity.Taken together,hemoglobin hydrolysate has a strong ability to promote the absorption of non-heme iron in vivo,and the absorbed iron is relatively safe due to the regulation of hepcidin.

关键词： Hemoglo bin hydrolysate Non-heme iron Absorption liver homeostasis Hepcidin

On the Strong Approximation for a Simple Reentrant line in light Traffic Under First-buffer First-served Service Discipline

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Acta Mathematicae Applicatae Sinica 2024年第3期40卷 823-839页

作者： kai-ming YANG Yong-jiang GUO School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China

For a 2-station and 3-class reentrant line under first-buffer first-served(FBFS)service discipline in light traffic,we firstly construct the strong approximations for performance measures including the queue length,workload,busy time and idle time processes.Based on the obtained strong approximations,we use a strong approximation method to find all the law of the iterated logarithms(liLs)for the above four performance measures,which are expressed as some functions of system parameters:means and variances of interarrival and service times,and characterize the fluctuations around their fluid approximations.

关键词： reentrant line queueing network FBFS service discipline strong approximation liL Brownian motion

Emerging role of exosomes in ulcerative colitis: Targeting NOD-like receptor family pyrin domain containing 3 inflammasome

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World Journal of Gastroenterology 2024年第6期30卷 527-541页

作者： Xin li li-jiang Ji kai-Di Feng Hua Huang Mei-Rou liang Shi-Jin Cheng Xiu-Dong Meng School of Basic Medicine Guizhou University of Traditional Chinese MedicineGuiyang 550025Guizhou ProvinceChina Department of Anorectal Surgery Changshu Hospital Affiliated to Nanjing University of Chinese MedicineChangshu 215500Jiangsu ProvinceChina College of Traditional Chinese Medicine Tianjin University of Traditional Chinese MedicineTianjin 301617China

Ulcerative colitis(UC)is a chronic recurrent inflammatory bowel disease.Despite ongoing advances in our understanding of UC,its pathogenesis is yet unelu-cidated,underscoring the urgent need for novel treatment strategies for patients with UC.Exosomes are nanoscale membrane particles that mediate intercellular communication by carrying various bioactive molecules,such as proteins,RNAs,DNA,and metabolites.The NOD-like receptor family pyrin domain containing 3(NLRP3)inflammasome is a cytosolic tripartite protein complex whose activation induces the maturation and secretion of proinflammatory cytokines interleukin-1β(IL-1β)and IL-18,triggering the inflammatory response to a pathogenic agent or injury.Growing evidence suggests that exosomes are new modulators of the NLRP3 inflammasome,with vital roles in the pathological process of UC.Here,recent evidence is reviewed on the role of exosomes and NLRP3 inflammasome in UC.First,the dual role of exosomes on NLRP3 inflammasome and the effect of NLRP3 inflammasome on exosome secretion are summarized.Finally,an outlook on the directions of exosome-NLRP3 inflammasome crosstalk research in the context of UC is proposed and areas of further research on this topic are high-lighted.

关键词： Ulcerative colitis Exosomes Inflammasome Evidence Therapeutics

A Robust Framework for Multimodal Sentiment Analysis with Noisy Labels Generated from Distributed Data Annotation

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2965-2984页

作者： kai jiang Bin Cao Jing Fan School of Computer Science and Technology Zhejiang University of TechnologyHangzhou310023China

Multimodal sentiment analysis utilizes multimodal data such as text,facial expressions and voice to detect people’s attitudes.With the advent of distributed data collection and annotation,we can easily obtain and share such multimodal data.However,due to professional discrepancies among annotators and lax quality control,noisy labels might be introduced.Recent research suggests that deep neural networks(DNNs)will overfit noisy labels,leading to the poor performance of the DNNs.To address this challenging problem,we present a Multimodal Robust Meta Learning framework(MRML)for multimodal sentiment analysis to resist noisy labels and correlate distinct modalities simultaneously.Specifically,we propose a two-layer fusion net to deeply fuse different modalities and improve the quality of the multimodal data features for label correction and network training.Besides,a multiple meta-learner(label corrector)strategy is proposed to enhance the label correction approach and prevent models from overfitting to noisy labels.We conducted experiments on three popular multimodal datasets to verify the superiority of ourmethod by comparing it with four baselines.

关键词： Distributed data collection multimodal sentiment analysis meta learning learn with noisy labels

Rheum palmatum L. and Salvia miltiorrhiza Bge. Alleviates Acute Pancreatitis by Regulating Th17 Cell Differentiation: An Integrated Network Pharmacology Analysis, Molecular Dynamics Simulation and Experimental Validation

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Chinese Journal of Integrative Medicine 2024年第5期30卷 408-420页

作者： FENG Min-chao LUO Fang HUANG liang-jiang li kai CHEN Zu-min li Hui YAO Chun QIN Bai-jun CHEN Guo-zhong The First Clinical Medical College Guangxi University of Traditional Chinese MedicineNanning 530000China Guangxi Key Laboratory of Molecular Biology of Traditional Chinese Medicine and Preventive Medicine Nanning 530000China Graduate School Guangxi University of Traditional Chinese MedicineNanning 530000China Department of Gastroenterology the First Affiliated Hospital of Guangxi University of Traditional Chinese MedicineNanning 530023China

Objective: To identify the core targets of Rheum palmatum L. and Salvia miltiorrhiza Bge.,(Dahuang-Danshen, DH-DS) and the mechanism underlying its therapeutic efficacy in acute pancreatitis(AP)using a network pharmacology approach and validate the findings in animal experiments. Methods: Network pharmacology analysis was used to elucidate the mechanisms underlying the therapeutic effects of DH-DS in AP. The reliability of the results was verified by molecular docking simulation and molecular dynamics simulation.Finally, the results of network pharmacology enrichment analysis were verified by immunohistochemistry,Western blot analysis and real-time quantitative PCR, respectively. Results: Sixty-seven common targets of DH-DS in AP were identified and mitogen-activated protein kinase 3(MAPK3), Janus kinase 2(JAK2), signal transducer and activator of transcription 3(STAT3), protein c-Fos(FOS) were identified as core targets in the protein interaction(PPI) network analysis. Gene ontology analysis showed that cellular response to organic substance was the main functions of DH-DS in AP, and Kyoto Encyclopedia of Genes and Genomes analysis showed that the main pathway included Th17 cell differentiation. Molecular docking simulation confirmed that DH-DS binds with strong affinity to MAPK3, STAT3 and FOS. Molecular dynamics simulation revealed that FOS-isotanshinone Ⅱ and STAT3-dan-shexinkum d had good binding capacity. Animal experiments indicated that compared with the AP model group, DH-DS treatment effectively alleviated AP by inhibiting the expression of interleukin-1β, interleukin-6 and tumor necrosis factor-α, and blocking the activation of Th17 cell differentiation(P<0.01). Conclusion: DH-DS could inhibit the expression of inflammatory factors and protect pancreatic tissues,which would be functioned by regulating Th17 cell differentiation-related m RNA and protein expressions.

关键词： Rheum palmatum L. Salvia miltiorrhiza Bge. molecular docking simulation network pharmacology acute pancreatitis Th17 cell differentiation

Variability Analysis for a Two-station Queueing Network in Heavy Traffic with Arrival Processes Driven by Queues

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Acta Mathematicae Applicatae Sinica 2024年第2期40卷 445-466页

作者： Jian CAO Yong-jiang GUO kai-ming YANG School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China

The law of the iterated logarithm(liL)for the performance measures of a two-station queueing network with arrivals modulated by independent queues is developed by a strong approximation method.For convenience,two arrival processes modulated by queues comprise the external system,all others are belong to the internal system.It is well known that the exogenous arrival has a great influence on the asymptotic variability of performance measures in queues.For the considered queueing network in heavy traffic,we get all the liLs for the queue length,workload,busy time,idle time and departure processes,and present them by some simple functions of the primitive data.The liLs tell us some interesting insights,such as,the liLs of busy and idle times are zero and they reflect a small variability around their fluid approximations,the liL of departure has nothing to do with the arrival process,both of the two phenomena well explain the service station’s situation of being busy all the time.The external system shows us a distinguishing effect on the performance measures:an underloaded(overloaded,critically loaded)external system affects the internal system through its arrival(departure,arrival and departure together).In addition,we also get the strong approximation of the network as an auxiliary result.

关键词： two-station queueing network the law of the iterated logarithm(liL) strong approximation fluid approximation

Jellyfish bio-inspired Fe@CNT@CuNC derived from ZIF-8 for cathodic oxygen reduction

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Nano Research 2024年第4期17卷 2352-2359页

作者： kai Cheng Zequan liu Demin jiang Min Song Yuqiao Wang Research Center for Nano Photoelectrochemistry and Devices School of Chemistry and Chemical EngineeringSoutheast UniversityNanjing 211189China Yangtze River Delta Carbon Neutrality Strategy Development Institute Southeast UniversityNanjing 210096China School of Energy and Environment Southeast UniversityNanjing 210096China

Biomimetics provides guidance to design and synthesize advanced catalysts for oxygen reduction reaction in microbial fuel cells(MFCs).Herein,jellyfish-inspired Fe clusters on carbon nanotubes connected with CuNC(Fe@CNT@CuNC)were designed and prepared by using zeolitic imidazolate framework(ZIF)-8 precursors to imitate the organic texture and function of jellyfish.The antibacterial effect of Cu^(+)ions depressed the growth of cathode biofilm to ensure rapid mass transport.Fe clusters and CuNC connected by CNTs accelerated the electron transfer from Fe to CuNC.The optimization of oxygen adsorption was caused by electron redistribution between sites of Fe and Cu.Jellyfish-like catalysts achieved a half-wave potential of 0.86 V and onset potential of 0.95 V vs.reversible hydrogen electrode(RHE).MFCs gained the maximum power density of 1600 mW·m^(-2) after 500 h measurement.This work provides insights into the special design of advanced catalysts based on bio-inspiration and biomimetics.

关键词： bio-inspiration oxygen reduction reaction antibacterial ability microbial fuel cells density functional theory(DFT)rational design

Probabilistic modeling of multifunction radars with autoregressive kernel mixture network

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Defence Technology（防务技术） 2024年第5期35卷 275-288页

作者： Hancong Feng kaili.jiang Zhixing Zhou Yuxin Zhao kailun Tian Haixin Yan Bin Tang School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

The task of modeling and analyzing intercepted multifunction radars(MFRs)pulse trains is vital for cognitive electronic reconnaissance.Existing methodologies predominantly rely on prior information or heavily constrained models,posing challenges for non-cooperative applications.This paper introduces a novel approach to model MFRs using a Bayesian network,where the conditional probability density function is approximated by an autoregressive kernel mixture network(ARKMN).Utilizing the estimated probability density function,a dynamic programming algorithm is proposed for denoising and detecting change points in the intercepted MFRs pulse trains.Simulation results affirm the proposed method's efficacy in modeling MFRs,outperforming the state-of-the-art in pulse train denoising and change point detection.

关键词： Probabilistic forecasting Multifunction radar Unsupervised learning Change point detection Outlier detection

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