Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network lev...Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.展开更多
Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indice...Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.展开更多
To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartogra...To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartography of heterogeneous combat networks based on the operational chain”(FCBOC).In this framework,a functional module detection algorithm named operational chain-based label propagation algorithm(OCLPA),which considers the cooperation and interactions among combat entities and can thus naturally tackle network heterogeneity,is proposed to identify the functional modules of the network.Then,the nodes and their modules are classified into different roles according to their properties.A case study shows that FCBOC can provide a simplified description of disorderly information of combat networks and enable us to identify their functional and structural network characteristics.The results provide useful information to help commanders make precise and accurate decisions regarding the protection,disintegration or optimization of combat networks.Three algorithms are also compared with OCLPA to show that FCBOC can most effectively find functional modules with practical meaning.展开更多
BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological s...BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological substrates underlying depression,the intricate patterns of disrupted brain network connectivity in adolescents warrant further exploration.AIM To elucidate the neural correlates of adolescent depression by examining brain network connectivity using resting-state functional magnetic resonance imaging(rs-fMRI).METHODS The study cohort comprised 74 depressed adolescents and 59 healthy controls aged 12 to 17 years.Participants underwent rs-fMRI to evaluate functional connectivity within and across critical brain networks,including the visual,default mode network(DMN),dorsal attention,salience,somatomotor,and frontoparietal control networks.RESULTS Analyses revealed pronounced functional disparities within key neural circuits among adolescents with depression.The results demonstrated existence of hemispheric asymmetries characterized by enhanced activity in the left visual network,which contrasted the diminished activity in the right hemisphere.The DMN facilitated increased activity within the left prefrontal cortex and reduced engagement in the right hemisphere,implicating disrupted self-referential and emotional processing mechanisms.Additionally,an overactive right dorsal attention network and a hypoactive salience network were identified,underscoring significant abnormalities in attentional and emotional regulation in adolescent depression.CONCLUSION The findings from this study underscore distinct neural connectivity disruptions in adolescent depression,underscoring the critical role of specific neurobiological markers for precise early diagnosis of adolescent depression.The observed functional asymmetries and network-specific deviations elucidate the complex neurobiological architecture of adolescent depression,supporting the development of targeted therapeutic strategies.展开更多
Background:This study investigated the impacts and mechanisms of yunweiling in the management of Functional Constipation(FC)using network pharmacology and experimental research.Methods:Using the Traditional Chinese Me...Background:This study investigated the impacts and mechanisms of yunweiling in the management of Functional Constipation(FC)using network pharmacology and experimental research.Methods:Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),Genecard,and Online Mendelian Inheritance in Man(OMIM)databases,a potential gene target for yunweiling in treating FC was found.A pharmacological network was built and viewed in Cytoscape.A protein interac-tion map was created with STRING and Cytoscape.‘clusterProfiler’helped uncover its mechanism.Molecular docking was done with AutoDock Vina.In a constipation mouse model,Western blot was used to assess yunweiling's effectiveness.Results:To investigate yunweiling's therapeutic effects on FC,we employed a loperamide-induced constipation model.Successful model establishment was con-firmed by first black stool time,reduced stool output,and impaired gastrointestinal motility.Yunweiling treatment,especially at high and medium doses,significantly al-leviated constipation symptoms by reducing first black stool time,increasing stool output,and enhancing gastrointestinal motility.HE staining revealed yunweiling's ability to restore colon tissue structure.Yunweiling modulated the expression of key proteins TP53,P-AKT,P-PI3K,RET,and Rai,implicating its involvement in the PI3K-Akt signaling pathway.Comparative analysis showed yunweiling to be more effective than its individual components(shionone,β-sitosterol,and daucosterol)in improving constipation.The combination of yunweiling with TP53 and PI3K-Akt inhibitors fur-ther enhanced its therapeutic effects,suggesting a synergistic mechanism.Conclusions:The integration of network pharmacology and experimental investiga-tions indicated the effectiveness of yunweiling in managing FC,offering essential theoretical support for clinical application.展开更多
As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly ess...As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel integrated topological-functional(ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm under different conditions is validated.The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in the overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insight into urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience.展开更多
Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.P...Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.展开更多
BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explo...BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explore the potential characteristics of the brain network and functional connectivity(FC)of SA.METHODS Twenty-six SA individuals and 47 usual aging individuals were recruited from community-dwelling elderly,which were taken the magnetic resonance imaging scan and the global cognitive function assessment by Mini Mental State Examination(MMSE).The resting state-functional magnetic resonance imaging data were preprocessed by DPABISurf,and the brain functional network was conducted by DPABINet.The support vector machine model was constructed with altered functional connectivities to evaluate the identification value of SA.RESULTS The results found that the 6 inter-network FCs of 5 brain networks were significantly altered and related to MMSE performance.The FC of the right orbital part of the middle frontal gyrus and right angular gyrus was mostly increased and positively related to MMSE score,and the FC of the right supramarginal gyrus and right temporal pole:Middle temporal gyrus was the only one decreased and negatively related to MMSE score.All 17 significantly altered FCs of SA were taken into the support vector machine model,and the area under the curve was 0.895.CONCLUSION The identification of key brain networks and FC of SA could help us better understand the brain mechanism and further explore neuroimaging biomarkers of SA.展开更多
OBJECTIVE:To evaluate the effectiveness of the combined use of 7 commonly used Traditional Chinese Medicine external treatment methods and rehabilitation training in improving limb function in patients with cerebral h...OBJECTIVE:To evaluate the effectiveness of the combined use of 7 commonly used Traditional Chinese Medicine external treatment methods and rehabilitation training in improving limb function in patients with cerebral hemorrhage through a network Meta-analysis.METHODS:A computer-based search was conducted in 8 databases,including China National Knowledge Infrastructure Database,Wanfang Database,China Science and Technology Journal Database,Pub Med,Cochrane Library,Web of Science,Scopus,and Embase,from their inception until February 19,2023.Randomized controlled trials(RCTs)investigating the effectiveness of the combined use of 7 commonly used Traditional Chinese Medicine external treatment methods and rehabilitation training in improving limb function in patients with cerebral hemorrhage were included.Two researchers independently screened the literature,extracted data from the included studies,and performed quality assessment using the Cochrane Collaboration's standards.The software Stata 17.0 was used to create a network evidence graph for each combination of Traditional Chinese Medicine external treatment methods and rehabilitation training,and to generate a publication bias funnel plot.Network Meta-analysis was conducted using Rev Man 5.3 to assess the risk of bias in the included studies,with mean difference(MD)used for continuous variables and odds ratio(OR)used for dichotomous variables.If there was good consistency among the included studies(P>0.05),a consistency model was applied for data analysis.If there was poor consistency among the included studies(P<0.05),an inconsistency model was used.RESULTS:A total of 27 studies involving 2113 patients with limb dysfunction caused by cerebral hemorrhage were included.The results of the network Meta-analysis indicated that the combined use of 7 Traditional Chinese Medicine external treatment methods and rehabilitation training was more effective in improving limb function in patients with cerebral hemorrhage compared to rehabilitation training alone.In terms of improving simplified Fugl-Meyer Assessment(FMA)scores,the effectiveness ranking was as follows:acupuncture+rehabilitation training>Acupoint sticking therapy+rehabilitation training>massage+rehabilitation training>electroacupuncture+rehabilitation training>moxibustion+rehabilitation training>Traditional Chinese Medicine therapy+rehabilitation training>Chinese herbal fumigation+rehabilitation training.In terms of improving Barthel Index(BI)scores,the effectiveness ranking was as follows:electroacupuncture+rehabilitation training>Acupoint sticking therapy+rehabilitation training>acupuncture+rehabilitation training>massage+rehabilitation training>moxibustion+rehabilitation training>Traditional Chinese Medicine fumigation+rehabilitation training>Traditional Chinese Medicine therapy+rehabilitation training.CONCLUSION:Based on existing literature evidence,our findings suggest the following:(a)The combination of the seven commonly used external treatment methods with rehabilitation training is superior to using rehabilitation training alone for the treatment of hemiplegia resulting from cerebral hemorrhage.(b)In terms of improving FMA scores,the combination of acupuncture and rehabilitation training shows the most significant effectiveness.(c)In terms of improving BI scores,the combination of electro-acupuncture and rehabilitation training demonstrates the most significant effectiveness.Therefore,we still need more multicenter,large-sample,high-quality randomized controlled trials to further validate the findings of this study.展开更多
A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predicti...A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller （OGPC） and the functional link network （FLN） direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking.展开更多
The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is...The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is proposed,which generalizes the standard PFC algorithm to networked control systems with random delays.The algorithm uses the time-stamp method to estimate the control delay,predicts the future outputs based on a discrete time delay state space model,and drives the control law that applies to an NCS from the idea of a PFC algorithm.A networked control system was constructed based on TrueTime simulator,with which the time-stamped PFC algorithm was compared with the standard PFC algorithm.The response curves show that the proposed algorithm has better control performance.展开更多
Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore func...Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.展开更多
Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the...Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.展开更多
Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of s...Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of stability of slopes or landslides. This effect is more pronounced in sensitive clays which show large changes in shear strength from peak to residual states. This study analyses the prediction of the residual strength of clay based on a new prediction model, functional networks（FN） using data available in the literature. The performance of FN was compared with support vector machine（SVM） and artificial neural network（ANN） based on statistical parameters like correlation coefficient（R）, Nash–Sutcliff coefficient of efficiency（E）, absolute average error（AAE）, maximum average error（MAE） and root mean square error（RMSE）. Based on R and E parameters, FN is found to be a better prediction tool than ANN for the given data. However, the R and E values for FN are less than SVM. A prediction equation is presented that can be used by practicing geotechnical engineers. A sensitivity analysis is carried out to ascertain the importance of various inputs in the prediction of the output.展开更多
Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain f...Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. Objective： To offer an overview of the different influences of acupuncture on the brain functional connec- tivity network from studies using resting-state fMRI. Search strategy： The authors performed a systematic search according to PRISMA guidelines, The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Inclusion criteria： Electronic searches were conducted in PubMed using the keywords ＂acupuncture＂ and ＂neuroimaging＂ or ＂resting-state fMRI＂ or ＂functional connectivity＂, Data extraction and analysis： Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Results： Forty-four resting-state fMRI studies were included in this systematic review according to inclu- sion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro- acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connec- tivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupunc- ture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. Conclusion： It can be presumed that the functional connectivity network is closely related to the mech- anism of acupuncture, and central integration plays a critical role in the acupuncture mechanism.展开更多
An unidirectional and bidirectional hybrid connective star network model with coupling time-delay is constructed in this paper. According to synchronization error systems, adaptive controllers for each node are struct...An unidirectional and bidirectional hybrid connective star network model with coupling time-delay is constructed in this paper. According to synchronization error systems, adaptive controllers for each node are structured by using the linear system stability method and the Lyapunov stability method. These adaptive controllers can realize the modified functional projective synchronization between each node of star network and an isolated node by argument and analysis. Finally, the corrective and effective of the adaptive controllers are illustrated by some numerical examples.展开更多
Research on brain function after brachial plexus injury focuses on local cortical functional reorganization,and few studies have focused on brain networks after brachial plexus injury.Changes in brain networks may hel...Research on brain function after brachial plexus injury focuses on local cortical functional reorganization,and few studies have focused on brain networks after brachial plexus injury.Changes in brain networks may help understanding of brain plasticity at the global level.We hypothesized that topology of the global cerebral resting-state functional network changes after unilateral brachial plexus injury.Thus,in this cross-sectional study,we recruited eight male patients with unilateral brachial plexus injury（right handedness,mean age of 27.9±5.4years old）and eight male healthy controls（right handedness,mean age of 28.6±3.2）.After acquiring and preprocessing resting-state magnetic resonance imaging data,the cerebrum was divided into 90 regions and Pearson’s correlation coefficient calculated between regions.These correlation matrices were then converted into a binary matrix with affixed sparsity values of 0.1–0.46.Under sparsity conditions,both groups satisfied this small-world property.The clustering coefficient was markedly lower,while average shortest path remarkably higher in patients compared with healthy controls.These findings confirm that cerebral functional networks in patients still show smallworld characteristics,which are highly effective in information transmission in the brain,as well as normal controls.Alternatively,varied small-worldness suggests that capacity of information transmission and integration in different brain regions in brachial plexus injury patients is damaged.展开更多
Chloroplast is a typical plant cell organelle where photosynthesis takes place. In this study, a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of pr...Chloroplast is a typical plant cell organelle where photosynthesis takes place. In this study, a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions. We then constructed a chloroplast protein interaction network primarily based on these core protein interactions. The network had 22 925 protein interaction pairs which involved 2 214 proteins. A total of 160 previously uncharacterized proteins were annotated in this network. The subunits of the photosynthetic complexes were modularized, and the functional relationships among photosystem Ⅰ （PSI）, photosystem Ⅱ （PSII）, light harvesting complex of photosystem Ⅰ （LHC Ⅰ） and light harvesting complex of photosystem Ⅰ （LHC Ⅱ） could be deduced from the predicted protein interactions in this network. We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis. Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.展开更多
Background:We aimed to reveal the mechanism of functional constipation in the treatment of Atractylodes macrocephala Koidz.(AMK)and Paeonia lactiflora Pall.(PLP).Methods:The main active ingredients of AMK and PLP were...Background:We aimed to reveal the mechanism of functional constipation in the treatment of Atractylodes macrocephala Koidz.(AMK)and Paeonia lactiflora Pall.(PLP).Methods:The main active ingredients of AMK and PLP were screened by the Traditional Chinese Medicine Systems Pharmacology(TCMSP)platform.A database of functional constipation targets was established by GeneCard and OMIM.An“ingredient-target”network map was constructed with Cytoscape software(version 3.7.1),and molecular docking analysis was performed on the components and genes with the highest scores.The rats in the normal group were given saline,and those in the other groups were given 10 mg/kg diphenoxylate once a day for 14 days.The serum and intestinal tissue levels of adenosine monophosphate(cAMP),protein kinase A(PKA),and adenylyl cyclase(AC)of the rats and aquaporin(AQP)1,AQP3,and AQP8 were measured.Results:AMK and PLP had a significant role in the regulation of targets in the treatment of functional constipation.After treatment with AMK,PLP,or mosapride,the serum and intestinal tissue levels of AC,cAMP,and PKA were significantly downregulated.Groups receiving AMK and PLP or mosapride exhibited a reduction in the level of AQP1,AQP3,and AQP8 to varying degrees.Conclusion:Molecular docking analysis revealed that AMK and PLP had a significant role in the regulation of targets in the treatment of functional constipation.Studies have confirmed that AMK and PLP can also affect AC,cAMP,and PKA.AC,cAMP,and PKA in model rats were significantly downregulated.AQP expression is closely related to AC,cAMP,and PKA.AMK and PLP can reduce the expression of AQP1,AQP3,and AQP9 in the colon of constipated rats.展开更多
Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this ...Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this paper develops a new method of constructing functional network based on phase synchronization. Electroencephalogram （EEG） data were collected while subjects looking at a green cross in two states, performing an attention task and relaxing with eyes-open. The EEG from these two states was filtered by three band-pass filters to obtain signals of theta （4-7 Hz）, alpha （8-13 Hz） and beta （14-30 Hz） bands. Mean resultant length was used to estimate strength of phase synchronization in three bands to construct networks of both states, and mean degree K and cluster coefficient C of networks were calculated as a function of threshold. The result shows higher cluster coetticient in the attention state than in the eyes-open state in all three bands, suggesting that cluster coefficient reflects brain state. In addition, an obvious fronto-parietal network is found in the attention state, which is a well-known attention network. These results indicate that attention modulates the fronto-parietal connectivity in different modes as compared with the eyes-open state. Taken together this method is an objective and important tool to study the properties of neural networks of brain rhythm,展开更多
基金supported by the National Natural Science Foundation of China,Nos.81871836(to MZ),82172554(to XH),and 81802249(to XH),81902301(to JW)the National Key R&D Program of China,Nos.2018YFC2001600(to JX)and 2018YFC2001604(to JX)+3 种基金Shanghai Rising Star Program,No.19QA1409000(to MZ)Shanghai Municipal Commission of Health and Family Planning,No.2018YQ02(to MZ)Shanghai Youth Top Talent Development PlanShanghai“Rising Stars of Medical Talent”Youth Development Program,No.RY411.19.01.10(to XH)。
文摘Distinct brain remodeling has been found after different nerve reconstruction strategies,including motor representation of the affected limb.However,differences among reconstruction strategies at the brain network level have not been elucidated.This study aimed to explore intranetwork changes related to altered peripheral neural pathways after different nerve reconstruction surgeries,including nerve repair,endto-end nerve transfer,and end-to-side nerve transfer.Sprague–Dawley rats underwent complete left brachial plexus transection and were divided into four equal groups of eight:no nerve repair,grafted nerve repair,phrenic nerve end-to-end transfer,and end-to-side transfer with a graft sutured to the anterior upper trunk.Resting-state brain functional magnetic resonance imaging was obtained 7 months after surgery.The independent component analysis algorithm was utilized to identify group-level network components of interest and extract resting-state functional connectivity values of each voxel within the component.Alterations in intra-network resting-state functional connectivity were compared among the groups.Target muscle reinnervation was assessed by behavioral observation(elbow flexion)and electromyography.The results showed that alterations in the sensorimotor and interoception networks were mostly related to changes in the peripheral neural pathway.Nerve repair was related to enhanced connectivity within the sensorimotor network,while end-to-side nerve transfer might be more beneficial for restoring control over the affected limb by the original motor representation.The thalamic-cortical pathway was enhanced within the interoception network after nerve repair and end-to-end nerve transfer.Brain areas related to cognition and emotion were enhanced after end-to-side nerve transfer.Our study revealed important brain networks related to different nerve reconstructions.These networks may be potential targets for enhancing motor recovery.
基金supported by the National Natural Science Foundation of China,No.82071909(to GF)the Natural Science Foundation of Liaoning Province,No.2023-MS-07(to HL)。
文摘Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.
文摘To extract and display the significant information of combat systems,this paper introduces the methodology of functional cartography into combat networks and proposes an integrated framework named“functional cartography of heterogeneous combat networks based on the operational chain”(FCBOC).In this framework,a functional module detection algorithm named operational chain-based label propagation algorithm(OCLPA),which considers the cooperation and interactions among combat entities and can thus naturally tackle network heterogeneity,is proposed to identify the functional modules of the network.Then,the nodes and their modules are classified into different roles according to their properties.A case study shows that FCBOC can provide a simplified description of disorderly information of combat networks and enable us to identify their functional and structural network characteristics.The results provide useful information to help commanders make precise and accurate decisions regarding the protection,disintegration or optimization of combat networks.Three algorithms are also compared with OCLPA to show that FCBOC can most effectively find functional modules with practical meaning.
基金Supported by the Medical Research Project of the Chongqing Municipal Health Commission,No.2024WSJK110.
文摘BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological substrates underlying depression,the intricate patterns of disrupted brain network connectivity in adolescents warrant further exploration.AIM To elucidate the neural correlates of adolescent depression by examining brain network connectivity using resting-state functional magnetic resonance imaging(rs-fMRI).METHODS The study cohort comprised 74 depressed adolescents and 59 healthy controls aged 12 to 17 years.Participants underwent rs-fMRI to evaluate functional connectivity within and across critical brain networks,including the visual,default mode network(DMN),dorsal attention,salience,somatomotor,and frontoparietal control networks.RESULTS Analyses revealed pronounced functional disparities within key neural circuits among adolescents with depression.The results demonstrated existence of hemispheric asymmetries characterized by enhanced activity in the left visual network,which contrasted the diminished activity in the right hemisphere.The DMN facilitated increased activity within the left prefrontal cortex and reduced engagement in the right hemisphere,implicating disrupted self-referential and emotional processing mechanisms.Additionally,an overactive right dorsal attention network and a hypoactive salience network were identified,underscoring significant abnormalities in attentional and emotional regulation in adolescent depression.CONCLUSION The findings from this study underscore distinct neural connectivity disruptions in adolescent depression,underscoring the critical role of specific neurobiological markers for precise early diagnosis of adolescent depression.The observed functional asymmetries and network-specific deviations elucidate the complex neurobiological architecture of adolescent depression,supporting the development of targeted therapeutic strategies.
基金funded by the TCM Spleen and Stomach Discipline Leader Project of High-level Talents in Yunnan Province (no grant number)TCM Joint Project of Yunnan Provincial Science and Technology Department (grant number 202101AZ070001-209).
文摘Background:This study investigated the impacts and mechanisms of yunweiling in the management of Functional Constipation(FC)using network pharmacology and experimental research.Methods:Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),Genecard,and Online Mendelian Inheritance in Man(OMIM)databases,a potential gene target for yunweiling in treating FC was found.A pharmacological network was built and viewed in Cytoscape.A protein interac-tion map was created with STRING and Cytoscape.‘clusterProfiler’helped uncover its mechanism.Molecular docking was done with AutoDock Vina.In a constipation mouse model,Western blot was used to assess yunweiling's effectiveness.Results:To investigate yunweiling's therapeutic effects on FC,we employed a loperamide-induced constipation model.Successful model establishment was con-firmed by first black stool time,reduced stool output,and impaired gastrointestinal motility.Yunweiling treatment,especially at high and medium doses,significantly al-leviated constipation symptoms by reducing first black stool time,increasing stool output,and enhancing gastrointestinal motility.HE staining revealed yunweiling's ability to restore colon tissue structure.Yunweiling modulated the expression of key proteins TP53,P-AKT,P-PI3K,RET,and Rai,implicating its involvement in the PI3K-Akt signaling pathway.Comparative analysis showed yunweiling to be more effective than its individual components(shionone,β-sitosterol,and daucosterol)in improving constipation.The combination of yunweiling with TP53 and PI3K-Akt inhibitors fur-ther enhanced its therapeutic effects,suggesting a synergistic mechanism.Conclusions:The integration of network pharmacology and experimental investiga-tions indicated the effectiveness of yunweiling in managing FC,offering essential theoretical support for clinical application.
基金Project supported by the National Natural Science Foundation of China (Grant No. 71971150)the Project of Research Center for System Sciences and Enterprise Development (Grant No. Xq16B05)the Fundamental Research Funds for the Central Universities of China (Grant No. SXYPY202313)。
文摘As a key mode of transportation, urban metro networks have significantly enhanced urban traffic environments and travel efficiency, making the identification of critical stations within these networks increasingly essential. This study presents a novel integrated topological-functional(ITF) algorithm for identifying critical nodes, combining topological metrics such as K-shell decomposition, node information entropy, and neighbor overlapping interaction with the functional attributes of passenger flow operations, while also considering the coupling effects between metro and bus networks. Using the Chengdu metro network as a case study, the effectiveness of the algorithm under different conditions is validated.The results indicate significant differences in passenger flow patterns between working and non-working days, leading to varying sets of critical nodes across these scenarios. Moreover, the ITF algorithm demonstrates a marked improvement in the accuracy of critical node identification compared to existing methods. This conclusion is supported by the analysis of changes in the overall network structure and relative global operational efficiency following targeted attacks on the identified critical nodes. The findings provide valuable insight into urban transportation planning, offering theoretical and practical guidance for improving metro network safety and resilience.
基金supported by Natural Science Foundation of China(Nos.62303126,62362008,author Z.Z,https://www.nsfc.gov.cn/,accessed on 20 December 2024)Major Scientific and Technological Special Project of Guizhou Province([2024]014)+2 种基金Guizhou Provincial Science and Technology Projects(No.ZK[2022]General149) ,author Z.Z,https://kjt.guizhou.gov.cn/,accessed on 20 December 2024)The Open Project of the Key Laboratory of Computing Power Network and Information Security,Ministry of Education under Grant 2023ZD037,author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024)Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT2024B25),author Z.Z,https://www.gzu.edu.cn/,accessed on 20 December 2024).
文摘Due to the development of cloud computing and machine learning,users can upload their data to the cloud for machine learning model training.However,dishonest clouds may infer user data,resulting in user data leakage.Previous schemes have achieved secure outsourced computing,but they suffer from low computational accuracy,difficult-to-handle heterogeneous distribution of data from multiple sources,and high computational cost,which result in extremely poor user experience and expensive cloud computing costs.To address the above problems,we propose amulti-precision,multi-sourced,andmulti-key outsourcing neural network training scheme.Firstly,we design a multi-precision functional encryption computation based on Euclidean division.Second,we design the outsourcing model training algorithm based on a multi-precision functional encryption with multi-sourced heterogeneity.Finally,we conduct experiments on three datasets.The results indicate that our framework achieves an accuracy improvement of 6%to 30%.Additionally,it offers a memory space optimization of 1.0×2^(24) times compared to the previous best approach.
基金Supported by the Wuxi Municipal Health Commission Major Project,No.Z202107。
文摘BACKGROUND Successful aging(SA)refers to the ability to maintain high levels of physical,cognitive,psychological,and social engagement in old age,with high cognitive function being the key to achieving SA.AIM To explore the potential characteristics of the brain network and functional connectivity(FC)of SA.METHODS Twenty-six SA individuals and 47 usual aging individuals were recruited from community-dwelling elderly,which were taken the magnetic resonance imaging scan and the global cognitive function assessment by Mini Mental State Examination(MMSE).The resting state-functional magnetic resonance imaging data were preprocessed by DPABISurf,and the brain functional network was conducted by DPABINet.The support vector machine model was constructed with altered functional connectivities to evaluate the identification value of SA.RESULTS The results found that the 6 inter-network FCs of 5 brain networks were significantly altered and related to MMSE performance.The FC of the right orbital part of the middle frontal gyrus and right angular gyrus was mostly increased and positively related to MMSE score,and the FC of the right supramarginal gyrus and right temporal pole:Middle temporal gyrus was the only one decreased and negatively related to MMSE score.All 17 significantly altered FCs of SA were taken into the support vector machine model,and the area under the curve was 0.895.CONCLUSION The identification of key brain networks and FC of SA could help us better understand the brain mechanism and further explore neuroimaging biomarkers of SA.
基金Supported by the Key Research and Development Plan Project of Shaanxi Province:Standardized Diagnosis and Treatment Protocol for Cerebral Hemorrhage with Integrated Traditional Chinese and Western Medicine and Research on its Therapeutic Mechanisms(No.2019ZDLSF04-06-01)the National Key Research and Development Plan Project:Development and Implementation of a Clinical Research Information Sharing System for Traditional Chinese Medicine(No.2017YFC1703500,No.2017YFC1703502)the Discipline Innovation Team Building Project of Shaanxi University of Chinese Medicine:Innovative Research Team for the Construction of Integrated Traditional Chinese and Western Medicine Cerebrovascular Disease Diagnosis and Treatment System and Its Clinical Application(No.2019-YL15)。
文摘OBJECTIVE:To evaluate the effectiveness of the combined use of 7 commonly used Traditional Chinese Medicine external treatment methods and rehabilitation training in improving limb function in patients with cerebral hemorrhage through a network Meta-analysis.METHODS:A computer-based search was conducted in 8 databases,including China National Knowledge Infrastructure Database,Wanfang Database,China Science and Technology Journal Database,Pub Med,Cochrane Library,Web of Science,Scopus,and Embase,from their inception until February 19,2023.Randomized controlled trials(RCTs)investigating the effectiveness of the combined use of 7 commonly used Traditional Chinese Medicine external treatment methods and rehabilitation training in improving limb function in patients with cerebral hemorrhage were included.Two researchers independently screened the literature,extracted data from the included studies,and performed quality assessment using the Cochrane Collaboration's standards.The software Stata 17.0 was used to create a network evidence graph for each combination of Traditional Chinese Medicine external treatment methods and rehabilitation training,and to generate a publication bias funnel plot.Network Meta-analysis was conducted using Rev Man 5.3 to assess the risk of bias in the included studies,with mean difference(MD)used for continuous variables and odds ratio(OR)used for dichotomous variables.If there was good consistency among the included studies(P>0.05),a consistency model was applied for data analysis.If there was poor consistency among the included studies(P<0.05),an inconsistency model was used.RESULTS:A total of 27 studies involving 2113 patients with limb dysfunction caused by cerebral hemorrhage were included.The results of the network Meta-analysis indicated that the combined use of 7 Traditional Chinese Medicine external treatment methods and rehabilitation training was more effective in improving limb function in patients with cerebral hemorrhage compared to rehabilitation training alone.In terms of improving simplified Fugl-Meyer Assessment(FMA)scores,the effectiveness ranking was as follows:acupuncture+rehabilitation training>Acupoint sticking therapy+rehabilitation training>massage+rehabilitation training>electroacupuncture+rehabilitation training>moxibustion+rehabilitation training>Traditional Chinese Medicine therapy+rehabilitation training>Chinese herbal fumigation+rehabilitation training.In terms of improving Barthel Index(BI)scores,the effectiveness ranking was as follows:electroacupuncture+rehabilitation training>Acupoint sticking therapy+rehabilitation training>acupuncture+rehabilitation training>massage+rehabilitation training>moxibustion+rehabilitation training>Traditional Chinese Medicine fumigation+rehabilitation training>Traditional Chinese Medicine therapy+rehabilitation training.CONCLUSION:Based on existing literature evidence,our findings suggest the following:(a)The combination of the seven commonly used external treatment methods with rehabilitation training is superior to using rehabilitation training alone for the treatment of hemiplegia resulting from cerebral hemorrhage.(b)In terms of improving FMA scores,the combination of acupuncture and rehabilitation training shows the most significant effectiveness.(c)In terms of improving BI scores,the combination of electro-acupuncture and rehabilitation training demonstrates the most significant effectiveness.Therefore,we still need more multicenter,large-sample,high-quality randomized controlled trials to further validate the findings of this study.
基金Supported by the National Nature Science Foundation of China (90716028)~~
文摘A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller （OGPC） and the functional link network （FLN） direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking.
文摘The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is proposed,which generalizes the standard PFC algorithm to networked control systems with random delays.The algorithm uses the time-stamp method to estimate the control delay,predicts the future outputs based on a discrete time delay state space model,and drives the control law that applies to an NCS from the idea of a PFC algorithm.A networked control system was constructed based on TrueTime simulator,with which the time-stamped PFC algorithm was compared with the standard PFC algorithm.The response curves show that the proposed algorithm has better control performance.
基金supported by the National Natural Science Foundation of China,No.60905024
文摘Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.
基金supported by the Natural Science Foundation of Guangdong Province,No.2016A030313180(to FCJ)
文摘Previous studies on brain functional connectivity networks in children have mainly focused on changes in function in specific brain regions, as opposed to whole brain connectivity in healthy children. By analyzing the independent components of activation and network connectivity between brain regions, we examined brain activity status and development trends in children aged 3 and 5 years. These data could provide a reference for brain function rehabilitation in children with illness or abnormal function. We acquired functional magnetic resonance images from 15 3-year-old children and 15 5-year-old children under natural sleep cond让ions. The participants were recruited from five kindergartens in the Nanshan District of Shenzhen City, China. The parents of the participants signed an informed consent form with the premise that they had been fully informed regarding the experimental protocol. We used masked independent component analysis and BrainNet Viewer software to explore the independent components of the brain and correlation connections between brain regions. We identified seven independent components in the two groups of children, including the executive control network, the dorsal attention network, the default mode network, the left frontoparietal network, the right frontoparietal network, the salience network, and the motor network. In the default mode network, the posterior cingulate cortex, medial frontal gyrus, and inferior parietal lobule were activated in both 3- and 5-year-old children, supporting the "three-brain region theory” of the default mode network. In the frontoparietal network, the frontal and parietal gyri were activated in the two groups of children, and functional connectivity was strengthened in 5-year-olds compared with 3-year-olds, although the nodes and network connections were not yet mature. The high-correlation network connections in the default mode networks and dorsal attention networks had been significantly strengthened in 5-year-olds vs. 3-year-olds. Further, the salience network in the 3-year-old children included an activated insula/inferior frontal gyrus-anterior cingulate cortex network circu让 and an activated thalamus-parahippocampal-posterior cingulate cortex-subcortical regions network circuit. By the age of 5 years, no des and high-correlation network connections (edges) were reduced in the salience network. Overall, activation of the dorsal attention network, default mode network, left frontoparietal network, and right frontoparietal network increased (the volume of activation increased, the signals strengthened, and the high-correlation connections increased and strengthened) in 5-year-olds compared with 3-year-olds, but activation in some brain nodes weakened or disappeared in the salience network, and the network connections (edges) were reduced. Between the ages of 3 and 5 years, we observed a tendency for function in some brain regions to be strengthened and for the generalization of activation to be reduced, indicating that specialization begins to develop at this time. The study protocol was approved by the local ethics committee of the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences in China with approval No. SIAT-IRB- 131115-H0075 on November 15, 2013.
文摘Landslides are common natural hazards occurring in most parts of the world and have considerable adverse economic effects. Residual shear strength of clay is one of the most important factors in the determination of stability of slopes or landslides. This effect is more pronounced in sensitive clays which show large changes in shear strength from peak to residual states. This study analyses the prediction of the residual strength of clay based on a new prediction model, functional networks（FN） using data available in the literature. The performance of FN was compared with support vector machine（SVM） and artificial neural network（ANN） based on statistical parameters like correlation coefficient（R）, Nash–Sutcliff coefficient of efficiency（E）, absolute average error（AAE）, maximum average error（MAE） and root mean square error（RMSE）. Based on R and E parameters, FN is found to be a better prediction tool than ANN for the given data. However, the R and E values for FN are less than SVM. A prediction equation is presented that can be used by practicing geotechnical engineers. A sensitivity analysis is carried out to ascertain the importance of various inputs in the prediction of the output.
基金supported by the National Natural Science Foundation of China(No.81473784)University Science Research Project of Anhui Province of China(No.KJ2017A298)+1 种基金the Key Project of the Youth Elite Support Plan in Universities of Anhui Province of China(No.gxyq ZD2016134)Construction Project of Scientific Research Innovation Platform of Anhui Province of China(No.2015TD033)
文摘Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. Objective： To offer an overview of the different influences of acupuncture on the brain functional connec- tivity network from studies using resting-state fMRI. Search strategy： The authors performed a systematic search according to PRISMA guidelines, The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Inclusion criteria： Electronic searches were conducted in PubMed using the keywords ＂acupuncture＂ and ＂neuroimaging＂ or ＂resting-state fMRI＂ or ＂functional connectivity＂, Data extraction and analysis： Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Results： Forty-four resting-state fMRI studies were included in this systematic review according to inclu- sion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro- acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connec- tivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupunc- ture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. Conclusion： It can be presumed that the functional connectivity network is closely related to the mech- anism of acupuncture, and central integration plays a critical role in the acupuncture mechanism.
基金Supported by the National Natural Science Foundation of China(11161027)Natural Science Foundation of Gansu Province(1610RJZA080)the Foundation of Gansu Education Bureau(2017A-155)
文摘An unidirectional and bidirectional hybrid connective star network model with coupling time-delay is constructed in this paper. According to synchronization error systems, adaptive controllers for each node are structured by using the linear system stability method and the Lyapunov stability method. These adaptive controllers can realize the modified functional projective synchronization between each node of star network and an isolated node by argument and analysis. Finally, the corrective and effective of the adaptive controllers are illustrated by some numerical examples.
文摘Research on brain function after brachial plexus injury focuses on local cortical functional reorganization,and few studies have focused on brain networks after brachial plexus injury.Changes in brain networks may help understanding of brain plasticity at the global level.We hypothesized that topology of the global cerebral resting-state functional network changes after unilateral brachial plexus injury.Thus,in this cross-sectional study,we recruited eight male patients with unilateral brachial plexus injury（right handedness,mean age of 27.9±5.4years old）and eight male healthy controls（right handedness,mean age of 28.6±3.2）.After acquiring and preprocessing resting-state magnetic resonance imaging data,the cerebrum was divided into 90 regions and Pearson’s correlation coefficient calculated between regions.These correlation matrices were then converted into a binary matrix with affixed sparsity values of 0.1–0.46.Under sparsity conditions,both groups satisfied this small-world property.The clustering coefficient was markedly lower,while average shortest path remarkably higher in patients compared with healthy controls.These findings confirm that cerebral functional networks in patients still show smallworld characteristics,which are highly effective in information transmission in the brain,as well as normal controls.Alternatively,varied small-worldness suggests that capacity of information transmission and integration in different brain regions in brachial plexus injury patients is damaged.
基金Acknowledgements We thank the RIKEN BRC in Japan for provision of all full-length cDNA in this study. National Natural Science Foundation of China （grants numbers 30530100 and 90408010）, the State Key Program of Basic Research of China （grant numbers 2007CB947600 and 2007CB108800）, and Hi-Tech Research and Development Program of China （grant number 2006AA02Z313） supported this project.
文摘Chloroplast is a typical plant cell organelle where photosynthesis takes place. In this study, a total of 1 808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions. We then constructed a chloroplast protein interaction network primarily based on these core protein interactions. The network had 22 925 protein interaction pairs which involved 2 214 proteins. A total of 160 previously uncharacterized proteins were annotated in this network. The subunits of the photosynthetic complexes were modularized, and the functional relationships among photosystem Ⅰ （PSI）, photosystem Ⅱ （PSII）, light harvesting complex of photosystem Ⅰ （LHC Ⅰ） and light harvesting complex of photosystem Ⅰ （LHC Ⅱ） could be deduced from the predicted protein interactions in this network. We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis. Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.
基金supported by the Project of Zhejiang Natural Science Foundation(LY19H280004)the Exploration Project of Zhejiang Natural Science Foundation(LQ21H270002)。
文摘Background:We aimed to reveal the mechanism of functional constipation in the treatment of Atractylodes macrocephala Koidz.(AMK)and Paeonia lactiflora Pall.(PLP).Methods:The main active ingredients of AMK and PLP were screened by the Traditional Chinese Medicine Systems Pharmacology(TCMSP)platform.A database of functional constipation targets was established by GeneCard and OMIM.An“ingredient-target”network map was constructed with Cytoscape software(version 3.7.1),and molecular docking analysis was performed on the components and genes with the highest scores.The rats in the normal group were given saline,and those in the other groups were given 10 mg/kg diphenoxylate once a day for 14 days.The serum and intestinal tissue levels of adenosine monophosphate(cAMP),protein kinase A(PKA),and adenylyl cyclase(AC)of the rats and aquaporin(AQP)1,AQP3,and AQP8 were measured.Results:AMK and PLP had a significant role in the regulation of targets in the treatment of functional constipation.After treatment with AMK,PLP,or mosapride,the serum and intestinal tissue levels of AC,cAMP,and PKA were significantly downregulated.Groups receiving AMK and PLP or mosapride exhibited a reduction in the level of AQP1,AQP3,and AQP8 to varying degrees.Conclusion:Molecular docking analysis revealed that AMK and PLP had a significant role in the regulation of targets in the treatment of functional constipation.Studies have confirmed that AMK and PLP can also affect AC,cAMP,and PKA.AC,cAMP,and PKA in model rats were significantly downregulated.AQP expression is closely related to AC,cAMP,and PKA.AMK and PLP can reduce the expression of AQP1,AQP3,and AQP9 in the colon of constipated rats.
基金supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 30800242)
文摘Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this paper develops a new method of constructing functional network based on phase synchronization. Electroencephalogram （EEG） data were collected while subjects looking at a green cross in two states, performing an attention task and relaxing with eyes-open. The EEG from these two states was filtered by three band-pass filters to obtain signals of theta （4-7 Hz）, alpha （8-13 Hz） and beta （14-30 Hz） bands. Mean resultant length was used to estimate strength of phase synchronization in three bands to construct networks of both states, and mean degree K and cluster coefficient C of networks were calculated as a function of threshold. The result shows higher cluster coetticient in the attention state than in the eyes-open state in all three bands, suggesting that cluster coefficient reflects brain state. In addition, an obvious fronto-parietal network is found in the attention state, which is a well-known attention network. These results indicate that attention modulates the fronto-parietal connectivity in different modes as compared with the eyes-open state. Taken together this method is an objective and important tool to study the properties of neural networks of brain rhythm,
