The automatic stealth task of military time-sensitive targets plays a crucial role in maintaining national military security and mastering battlefield dynamics in military applications.We propose a novel Military Time...The automatic stealth task of military time-sensitive targets plays a crucial role in maintaining national military security and mastering battlefield dynamics in military applications.We propose a novel Military Time-sensitive Targets Stealth Network via Real-time Mask Generation(MTTSNet).According to our knowledge,this is the first technology to automatically remove military targets in real-time from videos.The critical steps of MTTSNet are as follows:First,we designed a real-time mask generation network based on the encoder-decoder framework,combined with the domain expansion structure,to effectively extract mask images.Specifically,the ASPP structure in the encoder could achieve advanced semantic feature fusion.The decoder stacked high-dimensional information with low-dimensional information to obtain an effective mask layer.Subsequently,the domain expansion module guided the adaptive expansion of mask images.Second,a context adversarial generation network based on gated convolution was constructed to achieve background restoration of mask positions in the original image.In addition,our method worked in an end-to-end manner.A particular semantic segmentation dataset for military time-sensitive targets has been constructed,called the Military Time-sensitive Target Masking Dataset(MTMD).The MTMD dataset experiment successfully demonstrated that this method could create a mask that completely occludes the target and that the target could be hidden in real time using this mask.We demonstrated the concealment performance of our proposed method by comparing it to a number of well-known and highly optimized baselines.展开更多
Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single ...Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.展开更多
Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases.The holistic view of TCM coincides with the new generation of medical...Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases.The holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and system.TCM gave birth to a new method featuring holistic and systematic"network target",a core theory and method of network pharmacology.TCM is also an important research object of network pharmacology.TCM network pharmacology,which aims to understand the network-based biological basis of complex diseases,TCM syndromes and herb treatments,plays a critical role in the origin and development process of network pharmacology.This review introduces new progresses of TCM network pharmacology in recent years,including predicting herb targets,understanding biological foundation of diseases and syndromes,network regulation mechanisms of herbal formulae,and identifying disease and syndrome biomarkers based on biological network.These studies show a trend of combining computational,experimental and clinical approaches,which is a promising direction of TCM network pharmacology research in the future.Considering that TCM network pharmacology is still a young research field,it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.展开更多
Objective To predict the main active ingredients,potential targets and molecular mechanisms of Yuan Zhi powder in treatment of dementia by using network pharmacology.Methods A database of chemical constituents of Yuan...Objective To predict the main active ingredients,potential targets and molecular mechanisms of Yuan Zhi powder in treatment of dementia by using network pharmacology.Methods A database of chemical constituents of Yuan Zhi powder was constructed by using databases and literatures.Potential targets were predicted by reverse molecular docking,and then a component-target network was constructed.The target network of Alzheimer's disease(AD)was mapped and analyzed to obtain the“active ingredient-AD target”network.The key targets were screened through network analysis.Finally,the rationality of the prediction was analyzed by comparing with the target reported in the literatures.Results There were180chemical constituents acting on the AD target,and the targets included three key targets(cyclooxygenase-2,muscarinic acetylcholine receptor M1,and muscarinic acetylcholine receptor M2)and an important target(acetylcholine esterase).Alzheimer's disease may be treated by regulating the activity of acetylcholine receptors and the binding toβ-amyloid protein,and its biological process may be concentrated in the acetylcholine receptor signal pathway,negative regulation of synaptic transmission and so on.Conclusion The fact that Yuan Zhi powder can treat AD is consistent with the characteristics of multi-components-multitargets-multiple pathways of traditional Chinese medicine.The important targets obtained from network analysis have a large proportion in literature research,so network analysis have some rationality.展开更多
Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of r...Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of researches, such as small target detection in complex environments is susceptible to background interference and poor detection results. To solve these issues, this study proposes a method which introduces the attention mechanism into the you only look once(YOLO) network. In addition, the amateur-produced mask dataset was created and experiments were conducted. The results showed that the detection effect of the proposed mothed is much better.展开更多
Parkinson’s disease（PD）is the second most common neurodegenerative disease affecting 1%of the population over 60 years of age.The progressive degeneration of dopaminergic neurons at the substantia nigra pars compa...Parkinson’s disease（PD）is the second most common neurodegenerative disease affecting 1%of the population over 60 years of age.The progressive degeneration of dopaminergic neurons at the substantia nigra pars compacta（SNpc）results in a severe and gradual depletion of dopamine content in the striatum,a phenomena that is responsible for the characteristic motor symptoms of this disease.展开更多
We study the target inactivation and recovery in two-layer networks. Five kinds of strategies are chosen to attack the two-layer networks and to recover the activity of the networks by increasing the inter-layer coupl...We study the target inactivation and recovery in two-layer networks. Five kinds of strategies are chosen to attack the two-layer networks and to recover the activity of the networks by increasing the inter-layer coupling strength. The results show that we can easily control the dying state effectively by a randomly attacked situation. We then investigate the recovery activity of the networks by increasing the inter-layer coupled strength. The optimal values of the inter-layer coupled strengths are found, which could provide a more effective range to recovery activity of complex networks. As the multilayer systems composed of active and inactive elements raise important and interesting problems, our results on the target inactivation and recovery in two-layer networks would be extended to different studies.展开更多
Radiation-induced lung injury(RILI)is a common complication of cancer radiotherapy,yet effective treatments remain elusive.Compound Kushen injection(CKI),a traditional Chinese medicine(TCM)formula,is widely used in cl...Radiation-induced lung injury(RILI)is a common complication of cancer radiotherapy,yet effective treatments remain elusive.Compound Kushen injection(CKI),a traditional Chinese medicine(TCM)formula,is widely used in clinical practice for treating radiation-related diseases and as an adjunct therapy for cancer and has demonstrated some effectiveness.However,the mechanisms underlying CKI intervention in RILI and its role in cancer adjunctive therapy remain unclear.In this study,we refined previous statistical approaches and successfully integrated quantitative data on the compounds in CKI.We constructed a network-based holistic target model and developed modular biological networks to explore the modular regulatory effects of CKI in RILI.Through this network-based analysis,we identified specific alkaloid components of CKI that contribute to its therapeutic effect in alleviating RILI.Furthermore,through transcriptomic analysis,we confirmed that oxidative stress plays a central role in the treatment of RILI by CKI.The modular regulatory effects of CKI have been validated in animal models of irradiation,demonstrating the ability of CKI to alleviate oxidative stress,reduce inflammation,regulate immune responses,and inhibit apoptosis.In addition,we demonstrated that nuclear factor erythroid 2-related factor 2(NRF2)serves as a key mediator of the antioxidant effects of CKI.Matrine and sophoridine,representative alkaloids in CKI,exhibit binding interactions with NRF2.CKI promotes the nuclear translocation of NRF2,and NRF2 activates its downstream targets,such as heme oxygenase-1(HO-1)and NAD(P)H quinone dehydrogenase 1(NQO1),to suppress oxidative stress in RILI.This,in turn,inhibits the expression of inflammatory molecules,including interleukin(IL)-6,tumor necrosis factor(TNF)-α,and inducible nitric oxide synthase(iNOS),while promoting the activity of antioxidants such as superoxide dismutase(SOD)and glutathione peroxidase-4(GPX-4),thereby exerting therapeutic effects on RILI.展开更多
Network pharmacology provides a transformative framework for decoding multi-target,system-level mechanisms of the foodmedicine homology(FMH)substances,overcoming the limitations of reductionist approaches by integrati...Network pharmacology provides a transformative framework for decoding multi-target,system-level mechanisms of the foodmedicine homology(FMH)substances,overcoming the limitations of reductionist approaches by integrating multi-omics data,computational modeling,and network analysis.Central to this paradigm is the“Network Targets”theory,which conceptualizes therapeutic intervention as the reconfiguration of disease-associated biological networks rather than the modulation of isolated single targets.Artificial intelligence accelerates this process by enabling high-dimensional data integration,predictive modeling of synergistic combinations,and the identification of active constituents.This review outlines the key databases and computational tools that operationalize network pharmacology in FMH research and systematically categorizes their applications,including material screening,ingredient identification,synergy analysis,quality standard establishment,safety assessment,formula optimization,functional food discovery,and personalized recommendation,supported by experimental validation across numerous FMH items.Despite the challenges in data standardization and dynamic modeling,the integration of multi-omics,dynamic networks,and centralized repositories will further advance the field.Ultimately,network pharmacology will bridge traditional FMH wisdom with contemporary mechanistic rigor,positioning FMH as the cornerstone of precision nutrition and preventive medicine.展开更多
Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobil...Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.展开更多
A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filte...A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.展开更多
Traditional Chinese Medicine（TCM）, a crucial component of the current medical system, has been extensively used in clinical practice due to its valuable therapeutic efficacy, and its potentials as an important sourc...Traditional Chinese Medicine（TCM）, a crucial component of the current medical system, has been extensively used in clinical practice due to its valuable therapeutic efficacy, and its potentials as an important source of new pharmacophores. TCM is characterized by holistic theory, which emphasizes maintaining the balance of the patient＇s whole body using herbal formulae（fangji in Chinese） composed of mixtures of herbs with multiple bioactive ingredients. Because of the complex nature of these formulae, it is necessary to develop systematic methods to identify their bioactive ingredients and to clarify their mechanisms of action. With the rapid progress in bioinformatics, systems biology, and polypharmacology, ＂network pharmacology＂, which shifts the ＂one target, one drug＂ paradigm to the ＂network target, multi-component＂ strategy, has attracted the attention because it can not only reveal the underlying complex interactions between a herbal formula and cellular proteins but detect the influence of their interactions on the function and behavior of the system. Growing evidence shows that the network pharmacology strategy can be a powerful approach to modern research on TCM. The present paper focuses on the basis of network pharmacology and the recent progress in its methodology, illustrates its utility in screening bioactive ingredients and elucidating the mechanisms of action of TCM herbal formulae, analyzes its limitations and problems, and discusses its development direction and application prospects.展开更多
Traditional Chinese medicine（TCM） holds a holistic theory, and specializes in balancing disordered human body using numerous natural products, particularly Chinese herbal formulae. TCM has certain treatment advantag...Traditional Chinese medicine（TCM） holds a holistic theory, and specializes in balancing disordered human body using numerous natural products, particularly Chinese herbal formulae. TCM has certain treatment advantages for patients suffering from various complex diseases. However, due to the complex nature of TCM, it remains difficult to unveil such holistic medicine by the current reductionism research strategies, which treat both herbal ingredients and targets in isolation. Recently, an emerging network pharmacology approach has been introduced to tackle this bottleneck problem. A TCM-derived novel therapeutic concept, ＂network target＂, which is different from the Western medicine＇s ＂onetarget＂ concept, has been proposed from China. The network target strategy is able to illustrate the complex interactions among the biological systems, drugs, and complex diseases from a network perspective, and thus provides an innovative approach to access ancient remedies in a precision manner and at a systematic level, which also highlights TCM＇s potential in current medical systems.展开更多
Objective To investigate the mechanism of benzyl isothiocyanate(BITC)in the treatment of anaplastic thyroid cancer(ATC).Methods Using network pharmacological analysis,key targets of BITC and ATC were screened,followed...Objective To investigate the mechanism of benzyl isothiocyanate(BITC)in the treatment of anaplastic thyroid cancer(ATC).Methods Using network pharmacological analysis,key targets of BITC and ATC were screened,followed by CO and KEGG enrichment analysis.In order to validate the findings,AutoDock software was used to dock BITC and ATC key targets.BITC was applied to two ATC cell lines(8505C and CAL-62).Flow cytometry was used to analyze cell apoptosis.Autophagy inhibitors hydroxychloroquine sulfate(HCQ)and 3-methyladenine(3MA)were used in combination with BITC.Real-time quantitative PCR was conducted to detect the gene level of LC3B,while Western blotting was utilized to examine the expression of NF-kB,LC3B I,Beclin-1,and Bcl-2.In animal experiments,a mouse tumor model was constructed using CAL-62 cells,treated with intraperitoneal injections of BITC(100 mg/kg)and normal saline respectively,administered every other day for a total of 21 days.Immunoblotting of tumor tissue was performed to detect the expression of LC3B II,Bcl-2,Beclin-1,and NFkB.Results A total of 10 key targets with binding energies≤-4.0 kcal/mol were identified.KECG analysis showed that these genes are mainly involved in NF-kB signaling pathway and apoptosis.BITC inhibited ATC cells with IC50 values of 27.56μmol/L for 8505C and 28.30μmol/L for CAL-62.The expression levels of NF-kB,Beclin-1,and Bcl-2 decreased,while LC3B I and LC3B gene expression increased.Combining 3MA with BITC enhanced cell inhibition LC3B II expression.HCQ increased LC3B II expression without enhancing cell and viability inhibition.In the mouse tumor model,compared to the control group,the treatment group had higher LC3B II and lower Bcl-2,Beclin-1,and NF-kB levels.Conclusion BITC could inhibit the growth of ATC cells in vitro and in vivo,disrupt the autophagy degradation,and inhibit the NF-kB pathway.展开更多
The comparison between traditional Chinese medicine Jinzhen oral liquid(JZOL)and West-ern medicine in treating children with acute bronchitis(AB)showed encouraging outcomes.This trial eval-uated the efficacy and safet...The comparison between traditional Chinese medicine Jinzhen oral liquid(JZOL)and West-ern medicine in treating children with acute bronchitis(AB)showed encouraging outcomes.This trial eval-uated the efficacy and safety of the JZOL for improving cough and expectoration in children with AB.480 children were randomly assigned to take JZOL or ambroxol hydrochloride and clenbuterol hydrochloride oral solution for 7 days.The primary outcome was time-to-cough resolution.The median time-to-cough resolution in both groups was 5.0 days and the antitussive onset median time was only 1 day.This random-ized controlled trial showed that JZOL was not inferior to cough suppressant and phlegm resolving western medicine in treating cough and sputum and could comprehensively treat respiratory and systemic discom-fort symptoms.Combined with clinical trials,the mechanism of JZOL against AB was uncovered by network target analysis,it was found that the pathways in TRP channels like IL-1b/IL1R/TRPV1/TRPA1,NGF/TrkA/TRPV1/TRPA1,and PGE2/EP/PKA/TRPV1/TRPA1 might play important roles.Animal ex-periments further confirmed that inflammation and the immune regulatory effect of JZOL in the treatment of AB were of vital importance and TRP channels were the key mechanism of action.展开更多
Cold and Hot syndrome, also known as “ZHENG” in Mandarin, is a fundamental theory in traditional Chinese medicine(TCM) and plays a pivotal role in the differentiation of diseases in TCM. Diseases are treated with va...Cold and Hot syndrome, also known as “ZHENG” in Mandarin, is a fundamental theory in traditional Chinese medicine(TCM) and plays a pivotal role in the differentiation of diseases in TCM. Diseases are treated with varying formulas according to the specific syndrome differentiations in TCM. A way of the principles followed in TCM medical strategy is “cold herbs for hot syndrome, and hot herbs for cold syndrome.”Therefore, from the perspective of cold/hot syndrome, we summarizes the present research regarding the characteristics and mechanisms of cold/hot herbs(including herbs with cool and warm properties) in digestive system diseases, respiratory diseases, and autoimmune diseases,among others. As novel technologies have advanced, various methods, such as those based on network target, machine learning, and deep learning, have emerged to reveal the mechanisms underlying cold/hot syndrome and cold/hot herbs. With the help of these technologies, it has been found that cold and hot herbs, as well as formulae with cold or hot intentions, have similarities and differences in the treatment of these diseases. In conclusion, cold and cool may have stronger antibacterial, antiviral, and anti-infiammatory effects, whereas hot and warm herbs may specifically enhance immune regulation. With the assistance of advancing data algorithms, uncovering the mechanisms of cold/hot herbs may accelerate and provide a new research paradigm for further achieving precision in TCM.展开更多
基金supported in part by the National Natural Science Foundation of China(Grant No.62276274)Shaanxi Natural Science Foundation(Grant No.2023-JC-YB-528)Chinese aeronautical establishment(Grant No.201851U8012)。
文摘The automatic stealth task of military time-sensitive targets plays a crucial role in maintaining national military security and mastering battlefield dynamics in military applications.We propose a novel Military Time-sensitive Targets Stealth Network via Real-time Mask Generation(MTTSNet).According to our knowledge,this is the first technology to automatically remove military targets in real-time from videos.The critical steps of MTTSNet are as follows:First,we designed a real-time mask generation network based on the encoder-decoder framework,combined with the domain expansion structure,to effectively extract mask images.Specifically,the ASPP structure in the encoder could achieve advanced semantic feature fusion.The decoder stacked high-dimensional information with low-dimensional information to obtain an effective mask layer.Subsequently,the domain expansion module guided the adaptive expansion of mask images.Second,a context adversarial generation network based on gated convolution was constructed to achieve background restoration of mask positions in the original image.In addition,our method worked in an end-to-end manner.A particular semantic segmentation dataset for military time-sensitive targets has been constructed,called the Military Time-sensitive Target Masking Dataset(MTMD).The MTMD dataset experiment successfully demonstrated that this method could create a mask that completely occludes the target and that the target could be hidden in real time using this mask.We demonstrated the concealment performance of our proposed method by comparing it to a number of well-known and highly optimized baselines.
文摘Traditional Chinese medicine(TCM)demonstrates distinctive advantages in disease prevention and treatment.However,analyzing its biological mechanisms through the modern medical research paradigm of“single drug,single target”presents significant challenges due to its holistic approach.Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks,overcoming the limitations of reductionist research models and showing considerable value in TCM research.Recent integration of network target computational and experimental methods with artificial intelligence(AI)and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology.The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles.This review,centered on network targets,examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships,alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae,syndromes,and toxicity.Looking forward,network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics,potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.
基金supported by the National Natural Science Foundation of China(Nos.6201101081,81630103 and 81225025)Tsinghua University Spring Breeze Fund(No.2020-Z99CFY040)Beijing National Research Center for Information Science and Technology(Nos.BNR2019TD01020 and BNR2019-RC01012)。
文摘Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases.The holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and system.TCM gave birth to a new method featuring holistic and systematic"network target",a core theory and method of network pharmacology.TCM is also an important research object of network pharmacology.TCM network pharmacology,which aims to understand the network-based biological basis of complex diseases,TCM syndromes and herb treatments,plays a critical role in the origin and development process of network pharmacology.This review introduces new progresses of TCM network pharmacology in recent years,including predicting herb targets,understanding biological foundation of diseases and syndromes,network regulation mechanisms of herbal formulae,and identifying disease and syndrome biomarkers based on biological network.These studies show a trend of combining computational,experimental and clinical approaches,which is a promising direction of TCM network pharmacology research in the future.Considering that TCM network pharmacology is still a young research field,it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.
基金funding support from the Major new drug creation project (2017ZX09101002-002-008)National Natural Science Foundation of China (81403171)Autonomous Program of China Academy of Chinese Medical Sciences (QZPT001 and 2014065)
文摘Objective To predict the main active ingredients,potential targets and molecular mechanisms of Yuan Zhi powder in treatment of dementia by using network pharmacology.Methods A database of chemical constituents of Yuan Zhi powder was constructed by using databases and literatures.Potential targets were predicted by reverse molecular docking,and then a component-target network was constructed.The target network of Alzheimer's disease(AD)was mapped and analyzed to obtain the“active ingredient-AD target”network.The key targets were screened through network analysis.Finally,the rationality of the prediction was analyzed by comparing with the target reported in the literatures.Results There were180chemical constituents acting on the AD target,and the targets included three key targets(cyclooxygenase-2,muscarinic acetylcholine receptor M1,and muscarinic acetylcholine receptor M2)and an important target(acetylcholine esterase).Alzheimer's disease may be treated by regulating the activity of acetylcholine receptors and the binding toβ-amyloid protein,and its biological process may be concentrated in the acetylcholine receptor signal pathway,negative regulation of synaptic transmission and so on.Conclusion The fact that Yuan Zhi powder can treat AD is consistent with the characteristics of multi-components-multitargets-multiple pathways of traditional Chinese medicine.The important targets obtained from network analysis have a large proportion in literature research,so network analysis have some rationality.
基金supported by the National Key Research and Development Program of China (No.2022YFE0196000)the National Natural Science Foundation of China (No.61502429)。
文摘Target detection is an important task in computer vision research, and such an anomaly detection and the topic of small target detection task is more concerned. However, there are still some problems in this kind of researches, such as small target detection in complex environments is susceptible to background interference and poor detection results. To solve these issues, this study proposes a method which introduces the attention mechanism into the you only look once(YOLO) network. In addition, the amateur-produced mask dataset was created and experiments were conducted. The results showed that the detection effect of the proposed mothed is much better.
基金supported by FONDECYT-11140738 (G.M.).Michael J. Fox Foundation for Parkinson Research, Ring Initiative ACT1109+1 种基金FONDEF D11I1007 (C.H.). We also thank, FONDECYT-1140549Millennium Institute P09-015-F, COPEC-UC, and Frick Foundation (C.H.). V.C. is supported by CONICYT fellowship
文摘Parkinson’s disease（PD）is the second most common neurodegenerative disease affecting 1%of the population over 60 years of age.The progressive degeneration of dopaminergic neurons at the substantia nigra pars compacta（SNpc）results in a severe and gradual depletion of dopamine content in the striatum,a phenomena that is responsible for the characteristic motor symptoms of this disease.
基金Supported by the National Basic Research Program of China under Grant Nos 2013CBA01502,2011CB921503 and 2013CB834100the National Natural Science Foundation of China under Grant Nos 11374040 and 11274051
文摘We study the target inactivation and recovery in two-layer networks. Five kinds of strategies are chosen to attack the two-layer networks and to recover the activity of the networks by increasing the inter-layer coupling strength. The results show that we can easily control the dying state effectively by a randomly attacked situation. We then investigate the recovery activity of the networks by increasing the inter-layer coupled strength. The optimal values of the inter-layer coupled strengths are found, which could provide a more effective range to recovery activity of complex networks. As the multilayer systems composed of active and inactive elements raise important and interesting problems, our results on the target inactivation and recovery in two-layer networks would be extended to different studies.
基金supported by the Innovation Team and Talent Support Program Project of Traditional Chinese Medicine(ZYYCXTD-D-202405)from National Administration of Traditional Chinese Medicine,the National Natural Science Foundation of China(T2341008)the Pilot Project for Disciplinary Breakthroughs of Ministry of Education(Prevention and Treatment of Multi-System Comorbid Diseases with Traditional Chinese Medicine).
文摘Radiation-induced lung injury(RILI)is a common complication of cancer radiotherapy,yet effective treatments remain elusive.Compound Kushen injection(CKI),a traditional Chinese medicine(TCM)formula,is widely used in clinical practice for treating radiation-related diseases and as an adjunct therapy for cancer and has demonstrated some effectiveness.However,the mechanisms underlying CKI intervention in RILI and its role in cancer adjunctive therapy remain unclear.In this study,we refined previous statistical approaches and successfully integrated quantitative data on the compounds in CKI.We constructed a network-based holistic target model and developed modular biological networks to explore the modular regulatory effects of CKI in RILI.Through this network-based analysis,we identified specific alkaloid components of CKI that contribute to its therapeutic effect in alleviating RILI.Furthermore,through transcriptomic analysis,we confirmed that oxidative stress plays a central role in the treatment of RILI by CKI.The modular regulatory effects of CKI have been validated in animal models of irradiation,demonstrating the ability of CKI to alleviate oxidative stress,reduce inflammation,regulate immune responses,and inhibit apoptosis.In addition,we demonstrated that nuclear factor erythroid 2-related factor 2(NRF2)serves as a key mediator of the antioxidant effects of CKI.Matrine and sophoridine,representative alkaloids in CKI,exhibit binding interactions with NRF2.CKI promotes the nuclear translocation of NRF2,and NRF2 activates its downstream targets,such as heme oxygenase-1(HO-1)and NAD(P)H quinone dehydrogenase 1(NQO1),to suppress oxidative stress in RILI.This,in turn,inhibits the expression of inflammatory molecules,including interleukin(IL)-6,tumor necrosis factor(TNF)-α,and inducible nitric oxide synthase(iNOS),while promoting the activity of antioxidants such as superoxide dismutase(SOD)and glutathione peroxidase-4(GPX-4),thereby exerting therapeutic effects on RILI.
基金supported by the project of Henan-Zhongjing Pharmaceutical Big Data Repository and Large Model Algorithm Development Research(252028037).
文摘Network pharmacology provides a transformative framework for decoding multi-target,system-level mechanisms of the foodmedicine homology(FMH)substances,overcoming the limitations of reductionist approaches by integrating multi-omics data,computational modeling,and network analysis.Central to this paradigm is the“Network Targets”theory,which conceptualizes therapeutic intervention as the reconfiguration of disease-associated biological networks rather than the modulation of isolated single targets.Artificial intelligence accelerates this process by enabling high-dimensional data integration,predictive modeling of synergistic combinations,and the identification of active constituents.This review outlines the key databases and computational tools that operationalize network pharmacology in FMH research and systematically categorizes their applications,including material screening,ingredient identification,synergy analysis,quality standard establishment,safety assessment,formula optimization,functional food discovery,and personalized recommendation,supported by experimental validation across numerous FMH items.Despite the challenges in data standardization and dynamic modeling,the integration of multi-omics,dynamic networks,and centralized repositories will further advance the field.Ultimately,network pharmacology will bridge traditional FMH wisdom with contemporary mechanistic rigor,positioning FMH as the cornerstone of precision nutrition and preventive medicine.
基金Project(2013AA06A411)supported by the National High Technology Research and Development Program of ChinaProject(CXZZ14_1374)supported by the Graduate Education Innovation Program of Jiangsu Province,ChinaProject supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China
文摘Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.
基金supported by National Natural Science Foundation of China (Nos.62265010,62061024)Gansu Province Science and Technology Plan (No.23YFGA0062)Gansu Province Innovation Fund (No.2022A-215)。
文摘A wireless sensor network mobile target tracking algorithm(ISO-EKF)based on improved snake optimization algorithm(ISO)is proposed to address the difficulty of estimating initial values when using extended Kalman filtering to solve the state of nonlinear mobile target tracking.First,the steps of extended Kalman filtering(EKF)are introduced.Second,the ISO is used to adjust the parameters of the EKF in real time to adapt to the current motion state of the mobile target.Finally,the effectiveness of the algorithm is demonstrated through filtering and tracking using the constant velocity circular motion model(CM).Under the specified conditions,the position and velocity mean square error curves are compared among the snake optimizer(SO)-EKF algorithm,EKF algorithm,and the proposed algorithm.The comparison shows that the proposed algorithm reduces the root mean square error of position by 52%and 41%compared to the SOEKF algorithm and EKF algorithm,respectively.
基金National Natural Science Foundation of China(81225025)Beijing Nova Program(Z1511000003150126)
文摘Traditional Chinese Medicine（TCM）, a crucial component of the current medical system, has been extensively used in clinical practice due to its valuable therapeutic efficacy, and its potentials as an important source of new pharmacophores. TCM is characterized by holistic theory, which emphasizes maintaining the balance of the patient＇s whole body using herbal formulae（fangji in Chinese） composed of mixtures of herbs with multiple bioactive ingredients. Because of the complex nature of these formulae, it is necessary to develop systematic methods to identify their bioactive ingredients and to clarify their mechanisms of action. With the rapid progress in bioinformatics, systems biology, and polypharmacology, ＂network pharmacology＂, which shifts the ＂one target, one drug＂ paradigm to the ＂network target, multi-component＂ strategy, has attracted the attention because it can not only reveal the underlying complex interactions between a herbal formula and cellular proteins but detect the influence of their interactions on the function and behavior of the system. Growing evidence shows that the network pharmacology strategy can be a powerful approach to modern research on TCM. The present paper focuses on the basis of network pharmacology and the recent progress in its methodology, illustrates its utility in screening bioactive ingredients and elucidating the mechanisms of action of TCM herbal formulae, analyzes its limitations and problems, and discusses its development direction and application prospects.
基金Supported by the National Natural Science Foundation of China(No.81225025 and 91229201)
文摘Traditional Chinese medicine（TCM） holds a holistic theory, and specializes in balancing disordered human body using numerous natural products, particularly Chinese herbal formulae. TCM has certain treatment advantages for patients suffering from various complex diseases. However, due to the complex nature of TCM, it remains difficult to unveil such holistic medicine by the current reductionism research strategies, which treat both herbal ingredients and targets in isolation. Recently, an emerging network pharmacology approach has been introduced to tackle this bottleneck problem. A TCM-derived novel therapeutic concept, ＂network target＂, which is different from the Western medicine＇s ＂onetarget＂ concept, has been proposed from China. The network target strategy is able to illustrate the complex interactions among the biological systems, drugs, and complex diseases from a network perspective, and thus provides an innovative approach to access ancient remedies in a precision manner and at a systematic level, which also highlights TCM＇s potential in current medical systems.
文摘Objective To investigate the mechanism of benzyl isothiocyanate(BITC)in the treatment of anaplastic thyroid cancer(ATC).Methods Using network pharmacological analysis,key targets of BITC and ATC were screened,followed by CO and KEGG enrichment analysis.In order to validate the findings,AutoDock software was used to dock BITC and ATC key targets.BITC was applied to two ATC cell lines(8505C and CAL-62).Flow cytometry was used to analyze cell apoptosis.Autophagy inhibitors hydroxychloroquine sulfate(HCQ)and 3-methyladenine(3MA)were used in combination with BITC.Real-time quantitative PCR was conducted to detect the gene level of LC3B,while Western blotting was utilized to examine the expression of NF-kB,LC3B I,Beclin-1,and Bcl-2.In animal experiments,a mouse tumor model was constructed using CAL-62 cells,treated with intraperitoneal injections of BITC(100 mg/kg)and normal saline respectively,administered every other day for a total of 21 days.Immunoblotting of tumor tissue was performed to detect the expression of LC3B II,Bcl-2,Beclin-1,and NFkB.Results A total of 10 key targets with binding energies≤-4.0 kcal/mol were identified.KECG analysis showed that these genes are mainly involved in NF-kB signaling pathway and apoptosis.BITC inhibited ATC cells with IC50 values of 27.56μmol/L for 8505C and 28.30μmol/L for CAL-62.The expression levels of NF-kB,Beclin-1,and Bcl-2 decreased,while LC3B I and LC3B gene expression increased.Combining 3MA with BITC enhanced cell inhibition LC3B II expression.HCQ increased LC3B II expression without enhancing cell and viability inhibition.In the mouse tumor model,compared to the control group,the treatment group had higher LC3B II and lower Bcl-2,Beclin-1,and NF-kB levels.Conclusion BITC could inhibit the growth of ATC cells in vitro and in vivo,disrupt the autophagy degradation,and inhibit the NF-kB pathway.
基金the National Key Research and Development Program of the Ministry of Science and Technology of China in 2018,“Research on Modernization of TCM”project,“Demonstration Study on Evidence-based Evaluation and Effect Mechanism of Ten Chinese Patent Medicines and Classic Famous Prescriptions in the Treatment of Major Diseases after marketed”(2018YFC1707400 and 2018YFC17074101,China)National Administration of Traditional Chinese Medicine(GZY-KJS-2024-03,China).
文摘The comparison between traditional Chinese medicine Jinzhen oral liquid(JZOL)and West-ern medicine in treating children with acute bronchitis(AB)showed encouraging outcomes.This trial eval-uated the efficacy and safety of the JZOL for improving cough and expectoration in children with AB.480 children were randomly assigned to take JZOL or ambroxol hydrochloride and clenbuterol hydrochloride oral solution for 7 days.The primary outcome was time-to-cough resolution.The median time-to-cough resolution in both groups was 5.0 days and the antitussive onset median time was only 1 day.This random-ized controlled trial showed that JZOL was not inferior to cough suppressant and phlegm resolving western medicine in treating cough and sputum and could comprehensively treat respiratory and systemic discom-fort symptoms.Combined with clinical trials,the mechanism of JZOL against AB was uncovered by network target analysis,it was found that the pathways in TRP channels like IL-1b/IL1R/TRPV1/TRPA1,NGF/TrkA/TRPV1/TRPA1,and PGE2/EP/PKA/TRPV1/TRPA1 might play important roles.Animal ex-periments further confirmed that inflammation and the immune regulatory effect of JZOL in the treatment of AB were of vital importance and TRP channels were the key mechanism of action.
基金supported by the Anhui Province Traditional Chinese Medicine Science and Technology Research Project (202303a07020001)grants from the National Natural Science Foundation of China (T2341008 and 62061160369)
文摘Cold and Hot syndrome, also known as “ZHENG” in Mandarin, is a fundamental theory in traditional Chinese medicine(TCM) and plays a pivotal role in the differentiation of diseases in TCM. Diseases are treated with varying formulas according to the specific syndrome differentiations in TCM. A way of the principles followed in TCM medical strategy is “cold herbs for hot syndrome, and hot herbs for cold syndrome.”Therefore, from the perspective of cold/hot syndrome, we summarizes the present research regarding the characteristics and mechanisms of cold/hot herbs(including herbs with cool and warm properties) in digestive system diseases, respiratory diseases, and autoimmune diseases,among others. As novel technologies have advanced, various methods, such as those based on network target, machine learning, and deep learning, have emerged to reveal the mechanisms underlying cold/hot syndrome and cold/hot herbs. With the help of these technologies, it has been found that cold and hot herbs, as well as formulae with cold or hot intentions, have similarities and differences in the treatment of these diseases. In conclusion, cold and cool may have stronger antibacterial, antiviral, and anti-infiammatory effects, whereas hot and warm herbs may specifically enhance immune regulation. With the assistance of advancing data algorithms, uncovering the mechanisms of cold/hot herbs may accelerate and provide a new research paradigm for further achieving precision in TCM.
