The numerical simulation of the fluid flow and the flexible rod(s)interaction is more complicated and has lower efficiency due to the high computational cost.In this paper,a semi-resolved model coupling the computatio...The numerical simulation of the fluid flow and the flexible rod(s)interaction is more complicated and has lower efficiency due to the high computational cost.In this paper,a semi-resolved model coupling the computational fluid dynamics and the flexible rod dynamics is proposed using a two-way domain expansion method.The gov-erning equations of the flexible rod dynamics are discretized and solved by the finite element method,and the fluid flow is simulated by the finite volume method.The interaction between fluids and solid rods is modeled by introducing body force terms into the momentum equations.Referred to the traditional semi-resolved numerical model,an anisotropic Gaussian kernel function method is proposed to specify the interactive forces between flu-ids and solid bodies for non-circle rod cross-sections.A benchmark of the flow passing around a single flexible plate with a rectangular cross-section is used to validate the algorithm.Focused on the engineering applications,a test case of a finite patch of cylinders is implemented to validate the accuracy and efficiency of the coupled model.展开更多
Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in s...Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.展开更多
Spinal cord injury(SCI) often results in permanent dysfunction of locomotion,sensation,and autonomic regulation,imposing a substantial burden on both individuals and society(Anjum et al.,2020).SCI has a complex pathop...Spinal cord injury(SCI) often results in permanent dysfunction of locomotion,sensation,and autonomic regulation,imposing a substantial burden on both individuals and society(Anjum et al.,2020).SCI has a complex pathophysiology:an initial primary injury(mechanical trauma,axonal disruption,and hemorrhage) is followed by a progressive secondary injury cascade that involves ischemia,neuronal loss,and inflammation.Given the challenges in achieving regeneration of the injured spinal cord,neuroprotection has been at the forefront of clinical research.展开更多
Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after inju...Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after injury,which limits the ability to observe long-term behavioral recovery.Here,we used a severe stroke rat model with 150 minutes of ischemia,which produced severe behavioral deficiencies that persisted at 12 weeks,to study the therapeutic effect of neural stem cells on neural restoration in chronic stroke.Our study showed that stroke model rats treated with human neural stem cells had long-term sustained recovery of motor function,reduced infarction volume,long-term human neural stem cell survival,and improved local inflammatory environment and angiogenesis.We also demonstrated that transplanted human neural stem cells differentiated into mature neurons in vivo,formed stable functional synaptic connections with host neurons,and exhibited the electrophysiological properties of functional mature neurons,indicating that they replaced the damaged host neurons.The findings showed that human fetal-derived neural stem cells had long-term effects for neurological recovery in a model of severe stroke,which suggests that human neural stem cells-based therapy may be effective for repairing damaged neural circuits in stroke patients.展开更多
The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they ...The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they exhibit dense interconnectivity(Braitenburg and Schüz,1998;Campagnola et al.,2022).The strength and probability of connectivity depend on cell type,inter-neuronal distance,and species.Still,every cortical neuron receives input from thousands of other neurons while transmitting output to a similar number of neurons.Second,communication between neurons occurs primarily via chemical or electrical synapses.展开更多
Invasive as well as non-invasive neurotechnologies conceptualized to interface the central and peripheral nervous system have been probed for the past decades,which refer to electroencephalography,electrocorticography...Invasive as well as non-invasive neurotechnologies conceptualized to interface the central and peripheral nervous system have been probed for the past decades,which refer to electroencephalography,electrocorticography and microelectrode arrays.The challenges of these mentioned approaches are characterized by the bandwidth of the spatiotemporal resolution,which in turn is essential for large-area neuron recordings(Abiri et al.,2019).展开更多
In the words of the late Sir Colin Blakemore,neurologists have historically sought to infer brain functions in a manner akin to to king a hammer to a computeranalyzing localized anatomical lesions caused by trauma,tum...In the words of the late Sir Colin Blakemore,neurologists have historically sought to infer brain functions in a manner akin to to king a hammer to a computeranalyzing localized anatomical lesions caused by trauma,tumors,or strokes,noting deficits,and inferring what functions certain brain regions may be responsible for.This approach exemplifies a deletion heuristic,where the absence of a specific function reveals insights about the underlying structures or mechanisms responsible for it.By observing what is lost when a particular brain region is damaged,throughout the history of the field,neurologists have pieced together the intricate relationship between anatomy and function.展开更多
The mature central nervous system(CNS,composed of the brain,spinal cord,olfactory and optic nerves)is unable to regenerate spontaneously after an insult,both in the cases of neurodegenerative diseases(for example Alzh...The mature central nervous system(CNS,composed of the brain,spinal cord,olfactory and optic nerves)is unable to regenerate spontaneously after an insult,both in the cases of neurodegenerative diseases(for example Alzheimer's or Parkinson's disease)or traumatic injuries(such as spinal cord lesions).In the last 20 years,the field has made significant progress in unlocking axon regrowth.展开更多
Microglia,the resident immune cells of the central nervous system,exhibit a wide array of functional states,even in their so-called“homeostatic”condition,when they are not actively responding to overt pathological s...Microglia,the resident immune cells of the central nervous system,exhibit a wide array of functional states,even in their so-called“homeostatic”condition,when they are not actively responding to overt pathological stimuli.These functional states can be visualized using a combination of multi-omics techniques(e.g.,gene and protein expression,posttranslational modifications,mRNA profiling,and metabolomics),and,in the case of homeostatic microglia,are largely defined by the global(e.g.,genetic variations,organism’s age,sex,circadian rhythms,and gut microbiota)as well as local(specific area of the brain,immediate microglial surrounding,neuron-glia interactions and synaptic density/activity)signals(Paolicelli et al.,2022).While phenomics(i.e.,ultrastructural microglial morphology and motility)is also one of the key microglial state-defining parameters,it is known that cells with similar morphology can belong to different functional states.展开更多
Spontaneous recovery frequently proves maladaptive or insufficient because the plasticity of the injured adult mammalian central nervous system is limited.This limited plasticity serves as a primary barrier to functio...Spontaneous recovery frequently proves maladaptive or insufficient because the plasticity of the injured adult mammalian central nervous system is limited.This limited plasticity serves as a primary barrier to functional recovery after brain injury.Neuromodulation technologies represent one of the fastest-growing fields in medicine.These techniques utilize electricity,magnetism,sound,and light to restore or optimize brain functions by promoting reorganization or long-term changes that support functional recovery in patients with brain injury.Therefore,this review aims to provide a comprehensive overview of the effects and underlying mechanisms of neuromodulation technologies in supporting motor function recovery after brain injury.Many of these technologies are widely used in clinical practice and show significant improvements in motor function across various types of brain injury.However,studies report negative findings,potentially due to variations in stimulation protocols,differences in observation periods,and the severity of functional impairments among participants across different clinical trials.Additionally,we observed that different neuromodulation techniques share remarkably similar mechanisms,including promoting neuroplasticity,enhancing neurotrophic factor release,improving cerebral blood flow,suppressing neuroinflammation,and providing neuroprotection.Finally,considering the advantages and disadvantages of various neuromodulation techniques,we propose that future development should focus on closed-loop neural circuit stimulation,personalized treatment,interdisciplinary collaboration,and precision stimulation.展开更多
Diabetic retinopathy is a prominent cause of blindness in adults,with early retinal ganglion cell loss contributing to visual dysfunction or blindness.In the brain,defects inγ-aminobutyric acid synaptic transmission ...Diabetic retinopathy is a prominent cause of blindness in adults,with early retinal ganglion cell loss contributing to visual dysfunction or blindness.In the brain,defects inγ-aminobutyric acid synaptic transmission are associated with pathophysiological and neurodegenerative disorders,whereas glucagon-like peptide-1 has demonstrated neuroprotective effects.However,it is not yet clear whether diabetes causes alterations in inhibitory input to retinal ganglion cells and whether and how glucagon-like peptide-1 protects against neurodegeneration in the diabetic retina through regulating inhibitory synaptic transmission to retinal ganglion cells.In the present study,we used the patch-clamp technique to recordγ-aminobutyric acid subtype A receptor-mediated miniature inhibitory postsynaptic currents in retinal ganglion cells from streptozotocin-induced diabetes model rats.We found that early diabetes(4 weeks of hyperglycemia)decreased the frequency of GABAergic miniature inhibitory postsynaptic currents in retinal ganglion cells without altering their amplitude,suggesting a reduction in the spontaneous release ofγ-aminobutyric acid to retinal ganglion cells.Topical administration of glucagon-like peptide-1 eyedrops over a period of 2 weeks effectively countered the hyperglycemia-induced downregulation of GABAergic mIPSC frequency,subsequently enhancing the survival of retinal ganglion cells.Concurrently,the protective effects of glucagon-like peptide-1 on retinal ganglion cells in diabetic rats were eliminated by topical administration of exendin-9-39,a specific glucagon-like peptide-1 receptor antagonist,or SR95531,a specific antagonist of theγ-aminobutyric acid subtype A receptor.Furthermore,extracellular perfusion of glucagon-like peptide-1 was found to elevate the frequencies of GABAergic miniature inhibitory postsynaptic currents in both ON-and OFF-type retinal ganglion cells.This elevation was shown to be mediated by activation of the phosphatidylinositol-phospholipase C/inositol 1,4,5-trisphosphate receptor/Ca2+/protein kinase C signaling pathway downstream of glucagon-like peptide-1 receptor activation.Moreover,multielectrode array recordings revealed that glucagon-like peptide-1 functionally augmented the photoresponses of ON-type retinal ganglion cells.Optomotor response tests demonstrated that diabetic rats exhibited reductions in visual acuity and contrast sensitivity that were significantly ameliorated by topical administration of glucagon-like peptide-1.These results suggest that glucagon-like peptide-1 facilitates the release ofγ-aminobutyric acid onto retinal ganglion cells through the activation of glucagon-like peptide-1 receptor,leading to the de-excitation of retinal ganglion cell circuits and the inhibition of excitotoxic processes associated with diabetic retinopathy.Collectively,our findings indicate that theγ-aminobutyric acid system has potential as a therapeutic target for mitigating early-stage diabetic retinopathy.Furthermore,the topical administration of glucagon-like peptide-1 eyedrops represents a non-invasive and effective treatment approach for managing early-stage diabetic retinopathy.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
A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identifica...A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identification method. By solving a cubic equation in the feature space, an explicit predictive control law is obtained through the predictive control mechanism. The effect of controller is demonstrated on a recognized benchmark problem and on the control of continuous-stirred tank reactor (CSTR). Simulation results show that SVM with quadratic polynomial kernel function based predictive controller can be well applied to nonlinear systems, with good performance in following reference trajectory as well as in disturbance-rejection.展开更多
Landslide probability prediction plays an important role in understanding landslide information in advance and taking preventive measures.Many factors can influence the occurrence of landslides,which is easy to have a...Landslide probability prediction plays an important role in understanding landslide information in advance and taking preventive measures.Many factors can influence the occurrence of landslides,which is easy to have a curse of dimensionality and thus lead to reduce prediction accuracy.Then the generalization ability of the model will also decline sharply when there are only small samples.To reduce the dimension of calculation and balance the model’s generalization and learning ability,this study proposed a landslide prediction method based on improved principal component analysis(PCA)and mixed kernel function least squares support vector regression(LSSVR)model.First,the traditional PCA was introduced with the idea of linear discrimination,and the dimensions of initial influencing factors were reduced from 8 to 3.The improved PCA can not only weight variables but also extract the original feature.Furthermore,combined with global and local kernel function,the mixed kernel function LSSVR model was framed to improve the generalization ability.Whale optimization algorithm(WOA)was used to optimize the parameters.Moreover,Root Mean Square Error(RMSE),the sum of squared errors(SSE),Mean Absolute Error(MAE),Mean Absolute Precentage Error(MAPE),and reliability were employed to verify the performance of the model.Compared with radial basis function(RBF)LSSVR model,Elman neural network model,and fuzzy decision model,the proposed method has a smaller deviation.Finally,the landslide warning level obtained from the landslide probability can also provide references for relevant decision-making departments in emergency response.展开更多
This paper is concerned with certain multilinear commutators of BMO functions and multilinear singular integral operators with non-smooth kernels. By the sharp maximal functions estimates, the weighted norm inequaliti...This paper is concerned with certain multilinear commutators of BMO functions and multilinear singular integral operators with non-smooth kernels. By the sharp maximal functions estimates, the weighted norm inequalities for this kind of commutators are established.展开更多
In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barr...In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barrier term. Iteration bounds both for large-and small-update methods are derived, namely, O（nlog（n/c）） and O（√nlog（n/ε））. This new kernel function has simple algebraic expression and the proximity function has not been used before. Analogous to the classical logarithmic kernel function, our complexity analysis is easier than the other pri- mal-dual interior-point methods based on logarithmic barrier functions and recent kernel functions.展开更多
In this paper,we propose and analyze a full-Newton step feasible interior-point algorithm for semidefinite optimization based on a kernel function with linear growth term.The kernel function is used both for determini...In this paper,we propose and analyze a full-Newton step feasible interior-point algorithm for semidefinite optimization based on a kernel function with linear growth term.The kernel function is used both for determining the search directions and for measuring the distance between the given iterate and theμ-center for the algorithm.By developing a new norm-based proximity measure and some technical results,we derive the iteration bound that coincides with the currently best known iteration bound for the algorithm with small-update method.In our knowledge,this result is the first instance of full-Newton step feasible interior-point method for SDO which involving the kernel function.展开更多
In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear ...In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear growth term to derive the search direction,and by introducing new technical results and selecting suitable parameters,we prove that the iteration bound of the algorithm is as good as best-known polynomial complexity of interior-point methods.Furthermore,numerical results illustrate the efficiency of the proposed method.展开更多
This paper is devoted to studying the commutators of the multilinear singular integral operators with the non-smooth kernels and the weighted Lipschitz functions. Some mapping properties for two types of commutators o...This paper is devoted to studying the commutators of the multilinear singular integral operators with the non-smooth kernels and the weighted Lipschitz functions. Some mapping properties for two types of commutators on the weighted Lebesgue spaces, which extend and generalize some previous results, are obtained.展开更多
基金supported by Shanghai 2021“Science and Technology Innovation Action Plan”:Social Development Science and Technology Research Project(Grant No.21DZ1202703).
文摘The numerical simulation of the fluid flow and the flexible rod(s)interaction is more complicated and has lower efficiency due to the high computational cost.In this paper,a semi-resolved model coupling the computational fluid dynamics and the flexible rod dynamics is proposed using a two-way domain expansion method.The gov-erning equations of the flexible rod dynamics are discretized and solved by the finite element method,and the fluid flow is simulated by the finite volume method.The interaction between fluids and solid rods is modeled by introducing body force terms into the momentum equations.Referred to the traditional semi-resolved numerical model,an anisotropic Gaussian kernel function method is proposed to specify the interactive forces between flu-ids and solid bodies for non-circle rod cross-sections.A benchmark of the flow passing around a single flexible plate with a rectangular cross-section is used to validate the algorithm.Focused on the engineering applications,a test case of a finite patch of cylinders is implemented to validate the accuracy and efficiency of the coupled model.
基金supported by the National Natural Science Foundation of China,Nos.82072165 and 82272256(both to XM)the Key Project of Xiangyang Central Hospital,No.2023YZ03(to RM)。
文摘Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.
文摘Spinal cord injury(SCI) often results in permanent dysfunction of locomotion,sensation,and autonomic regulation,imposing a substantial burden on both individuals and society(Anjum et al.,2020).SCI has a complex pathophysiology:an initial primary injury(mechanical trauma,axonal disruption,and hemorrhage) is followed by a progressive secondary injury cascade that involves ischemia,neuronal loss,and inflammation.Given the challenges in achieving regeneration of the injured spinal cord,neuroprotection has been at the forefront of clinical research.
文摘Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after injury,which limits the ability to observe long-term behavioral recovery.Here,we used a severe stroke rat model with 150 minutes of ischemia,which produced severe behavioral deficiencies that persisted at 12 weeks,to study the therapeutic effect of neural stem cells on neural restoration in chronic stroke.Our study showed that stroke model rats treated with human neural stem cells had long-term sustained recovery of motor function,reduced infarction volume,long-term human neural stem cell survival,and improved local inflammatory environment and angiogenesis.We also demonstrated that transplanted human neural stem cells differentiated into mature neurons in vivo,formed stable functional synaptic connections with host neurons,and exhibited the electrophysiological properties of functional mature neurons,indicating that they replaced the damaged host neurons.The findings showed that human fetal-derived neural stem cells had long-term effects for neurological recovery in a model of severe stroke,which suggests that human neural stem cells-based therapy may be effective for repairing damaged neural circuits in stroke patients.
基金supported in part by the Rosetrees Trust(#CF-2023-I-2_113)by the Israel Ministry of Innovation,Science,and Technology(#7393)(to ES).
文摘The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they exhibit dense interconnectivity(Braitenburg and Schüz,1998;Campagnola et al.,2022).The strength and probability of connectivity depend on cell type,inter-neuronal distance,and species.Still,every cortical neuron receives input from thousands of other neurons while transmitting output to a similar number of neurons.Second,communication between neurons occurs primarily via chemical or electrical synapses.
文摘Invasive as well as non-invasive neurotechnologies conceptualized to interface the central and peripheral nervous system have been probed for the past decades,which refer to electroencephalography,electrocorticography and microelectrode arrays.The challenges of these mentioned approaches are characterized by the bandwidth of the spatiotemporal resolution,which in turn is essential for large-area neuron recordings(Abiri et al.,2019).
文摘In the words of the late Sir Colin Blakemore,neurologists have historically sought to infer brain functions in a manner akin to to king a hammer to a computeranalyzing localized anatomical lesions caused by trauma,tumors,or strokes,noting deficits,and inferring what functions certain brain regions may be responsible for.This approach exemplifies a deletion heuristic,where the absence of a specific function reveals insights about the underlying structures or mechanisms responsible for it.By observing what is lost when a particular brain region is damaged,throughout the history of the field,neurologists have pieced together the intricate relationship between anatomy and function.
基金supported by ANR(ANR-21CE16-0008-01)ANR(ANR-21-CE16-0008-02 and ANR-23CE52-0007)+1 种基金UNADEV(A22018CS)(to HN)UNADEV(A22020CS)(to SB)。
文摘The mature central nervous system(CNS,composed of the brain,spinal cord,olfactory and optic nerves)is unable to regenerate spontaneously after an insult,both in the cases of neurodegenerative diseases(for example Alzheimer's or Parkinson's disease)or traumatic injuries(such as spinal cord lesions).In the last 20 years,the field has made significant progress in unlocking axon regrowth.
基金supported by Deutsche Forschungsgemeinschaft,German Research Foundation grant GA 654/13-2 to OG.
文摘Microglia,the resident immune cells of the central nervous system,exhibit a wide array of functional states,even in their so-called“homeostatic”condition,when they are not actively responding to overt pathological stimuli.These functional states can be visualized using a combination of multi-omics techniques(e.g.,gene and protein expression,posttranslational modifications,mRNA profiling,and metabolomics),and,in the case of homeostatic microglia,are largely defined by the global(e.g.,genetic variations,organism’s age,sex,circadian rhythms,and gut microbiota)as well as local(specific area of the brain,immediate microglial surrounding,neuron-glia interactions and synaptic density/activity)signals(Paolicelli et al.,2022).While phenomics(i.e.,ultrastructural microglial morphology and motility)is also one of the key microglial state-defining parameters,it is known that cells with similar morphology can belong to different functional states.
基金supported by the National Natural Science Foundation of China,No.82371399(to YY)the Natural Science Foundation of Jiangsu Province,No.BK20221206(to YY)+1 种基金the Young Elite Scientists Sponsorship Program of Jiangsu Province,No.TJ-2022-028(to YY)the Scientific Research Program of Wuxi Health Commission,No.Z202302(to LY)。
文摘Spontaneous recovery frequently proves maladaptive or insufficient because the plasticity of the injured adult mammalian central nervous system is limited.This limited plasticity serves as a primary barrier to functional recovery after brain injury.Neuromodulation technologies represent one of the fastest-growing fields in medicine.These techniques utilize electricity,magnetism,sound,and light to restore or optimize brain functions by promoting reorganization or long-term changes that support functional recovery in patients with brain injury.Therefore,this review aims to provide a comprehensive overview of the effects and underlying mechanisms of neuromodulation technologies in supporting motor function recovery after brain injury.Many of these technologies are widely used in clinical practice and show significant improvements in motor function across various types of brain injury.However,studies report negative findings,potentially due to variations in stimulation protocols,differences in observation periods,and the severity of functional impairments among participants across different clinical trials.Additionally,we observed that different neuromodulation techniques share remarkably similar mechanisms,including promoting neuroplasticity,enhancing neurotrophic factor release,improving cerebral blood flow,suppressing neuroinflammation,and providing neuroprotection.Finally,considering the advantages and disadvantages of various neuromodulation techniques,we propose that future development should focus on closed-loop neural circuit stimulation,personalized treatment,interdisciplinary collaboration,and precision stimulation.
基金supported by the National Natural Science Foundation of China,Nos.32070989(to YMZ),31872766(to YMZ),81790640(to XLY),and 82070993(to SJW)the grant from Sanming Project of Medicine in Shenzhen,No.SZSM202011015(to XLY)。
文摘Diabetic retinopathy is a prominent cause of blindness in adults,with early retinal ganglion cell loss contributing to visual dysfunction or blindness.In the brain,defects inγ-aminobutyric acid synaptic transmission are associated with pathophysiological and neurodegenerative disorders,whereas glucagon-like peptide-1 has demonstrated neuroprotective effects.However,it is not yet clear whether diabetes causes alterations in inhibitory input to retinal ganglion cells and whether and how glucagon-like peptide-1 protects against neurodegeneration in the diabetic retina through regulating inhibitory synaptic transmission to retinal ganglion cells.In the present study,we used the patch-clamp technique to recordγ-aminobutyric acid subtype A receptor-mediated miniature inhibitory postsynaptic currents in retinal ganglion cells from streptozotocin-induced diabetes model rats.We found that early diabetes(4 weeks of hyperglycemia)decreased the frequency of GABAergic miniature inhibitory postsynaptic currents in retinal ganglion cells without altering their amplitude,suggesting a reduction in the spontaneous release ofγ-aminobutyric acid to retinal ganglion cells.Topical administration of glucagon-like peptide-1 eyedrops over a period of 2 weeks effectively countered the hyperglycemia-induced downregulation of GABAergic mIPSC frequency,subsequently enhancing the survival of retinal ganglion cells.Concurrently,the protective effects of glucagon-like peptide-1 on retinal ganglion cells in diabetic rats were eliminated by topical administration of exendin-9-39,a specific glucagon-like peptide-1 receptor antagonist,or SR95531,a specific antagonist of theγ-aminobutyric acid subtype A receptor.Furthermore,extracellular perfusion of glucagon-like peptide-1 was found to elevate the frequencies of GABAergic miniature inhibitory postsynaptic currents in both ON-and OFF-type retinal ganglion cells.This elevation was shown to be mediated by activation of the phosphatidylinositol-phospholipase C/inositol 1,4,5-trisphosphate receptor/Ca2+/protein kinase C signaling pathway downstream of glucagon-like peptide-1 receptor activation.Moreover,multielectrode array recordings revealed that glucagon-like peptide-1 functionally augmented the photoresponses of ON-type retinal ganglion cells.Optomotor response tests demonstrated that diabetic rats exhibited reductions in visual acuity and contrast sensitivity that were significantly ameliorated by topical administration of glucagon-like peptide-1.These results suggest that glucagon-like peptide-1 facilitates the release ofγ-aminobutyric acid onto retinal ganglion cells through the activation of glucagon-like peptide-1 receptor,leading to the de-excitation of retinal ganglion cell circuits and the inhibition of excitotoxic processes associated with diabetic retinopathy.Collectively,our findings indicate that theγ-aminobutyric acid system has potential as a therapeutic target for mitigating early-stage diabetic retinopathy.Furthermore,the topical administration of glucagon-like peptide-1 eyedrops represents a non-invasive and effective treatment approach for managing early-stage diabetic retinopathy.
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.
基金Support by China 973 Project (No. 2002CB312200).
文摘A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identification method. By solving a cubic equation in the feature space, an explicit predictive control law is obtained through the predictive control mechanism. The effect of controller is demonstrated on a recognized benchmark problem and on the control of continuous-stirred tank reactor (CSTR). Simulation results show that SVM with quadratic polynomial kernel function based predictive controller can be well applied to nonlinear systems, with good performance in following reference trajectory as well as in disturbance-rejection.
基金supported by the Natural Science Foundation of Shaanxi Province(Grant No.2019JQ206)in part by the Science and Technology Department of Shaanxi Province(Grant No.2020CGXNG-009)in part by the Education Department of Shaanxi Province under Grant 17JK0346.
文摘Landslide probability prediction plays an important role in understanding landslide information in advance and taking preventive measures.Many factors can influence the occurrence of landslides,which is easy to have a curse of dimensionality and thus lead to reduce prediction accuracy.Then the generalization ability of the model will also decline sharply when there are only small samples.To reduce the dimension of calculation and balance the model’s generalization and learning ability,this study proposed a landslide prediction method based on improved principal component analysis(PCA)and mixed kernel function least squares support vector regression(LSSVR)model.First,the traditional PCA was introduced with the idea of linear discrimination,and the dimensions of initial influencing factors were reduced from 8 to 3.The improved PCA can not only weight variables but also extract the original feature.Furthermore,combined with global and local kernel function,the mixed kernel function LSSVR model was framed to improve the generalization ability.Whale optimization algorithm(WOA)was used to optimize the parameters.Moreover,Root Mean Square Error(RMSE),the sum of squared errors(SSE),Mean Absolute Error(MAE),Mean Absolute Precentage Error(MAPE),and reliability were employed to verify the performance of the model.Compared with radial basis function(RBF)LSSVR model,Elman neural network model,and fuzzy decision model,the proposed method has a smaller deviation.Finally,the landslide warning level obtained from the landslide probability can also provide references for relevant decision-making departments in emergency response.
基金Supported by the National Natural Science Foundation of China (10771054, 10771221, 11071200)the Youth Foundation of Wuyi University (No. xq0930)
文摘This paper is concerned with certain multilinear commutators of BMO functions and multilinear singular integral operators with non-smooth kernels. By the sharp maximal functions estimates, the weighted norm inequalities for this kind of commutators are established.
基金Supported by the Natural Science Foundation of Hubei Province (2008CDZD47)
文摘In this paper, we design a primal-dual interior-point algorithm for linear optimization. Search directions and proximity function are proposed based on a new kernel function which includes neither growth term nor barrier term. Iteration bounds both for large-and small-update methods are derived, namely, O（nlog（n/c）） and O（√nlog（n/ε））. This new kernel function has simple algebraic expression and the proximity function has not been used before. Analogous to the classical logarithmic kernel function, our complexity analysis is easier than the other pri- mal-dual interior-point methods based on logarithmic barrier functions and recent kernel functions.
基金Supported by University Science Research Project of Anhui Province(KJ2019A1297)University Teaching Research Project of Anhui Province(2019jxtd144)。
文摘In this paper,we propose and analyze a full-Newton step feasible interior-point algorithm for semidefinite optimization based on a kernel function with linear growth term.The kernel function is used both for determining the search directions and for measuring the distance between the given iterate and theμ-center for the algorithm.By developing a new norm-based proximity measure and some technical results,we derive the iteration bound that coincides with the currently best known iteration bound for the algorithm with small-update method.In our knowledge,this result is the first instance of full-Newton step feasible interior-point method for SDO which involving the kernel function.
基金Supported by University Science Research Project of Anhui Province(2023AH052921)Outstanding Youth Talent Project of Anhui Province(gxyq2021254)。
文摘In this paper,a new full-Newton step primal-dual interior-point algorithm for solving the special weighted linear complementarity problem is designed and analyzed.The algorithm employs a kernel function with a linear growth term to derive the search direction,and by introducing new technical results and selecting suitable parameters,we prove that the iteration bound of the algorithm is as good as best-known polynomial complexity of interior-point methods.Furthermore,numerical results illustrate the efficiency of the proposed method.
基金Supported by the National Natural Science Foundation of China (10771054,11071200)the NFS of Fujian Province of China (No. 2010J01013)
文摘This paper is devoted to studying the commutators of the multilinear singular integral operators with the non-smooth kernels and the weighted Lipschitz functions. Some mapping properties for two types of commutators on the weighted Lebesgue spaces, which extend and generalize some previous results, are obtained.
