Human functional MRI studies in acute and various chronic pain conditions have revolutionized how we view pain, and have led to a new theory that complex multi-dimensional pain experience （sensory-discriminative, aff...Human functional MRI studies in acute and various chronic pain conditions have revolutionized how we view pain, and have led to a new theory that complex multi-dimensional pain experience （sensory-discriminative, affective/motivational, and cognitive） is represented by concurrent activity in widely-distributed brain regions （termed a network or pain matrix）. Despite these break- through discoveries, the specific functions proposed for these regions remain elusive, because detailed electrophys- iological characterizations of these regions in the primate brain are lacking. To fill in this knowledge gap, we have studied the cortical areas around the central and lateral sulci of the non-human primate brain with combined submillimeter resolution functional imaging （optical imaging and fMRI） and intracranial electrophysiological recording. In this mini-review, I summarize and present data showing that the cortical circuitry engaged in nociceptive processing is much more complex than previously recognized. Electrophysiological evidence supports the engage- ment of a distinct nociceptive-processing network within SI （i.e., areas 3a, 3b, 1 and 2）, SII, and other areas along the lateral sulcus. Deafferentation caused by spinal cord injury profoundly alters the relationships between fMRI and electrophysiological signals. This finding has significant implications for using fMRI to study chronic pain conditions involving deafferentation in humans.展开更多
An ultrasonic nomogram was developed for preoperative prediction of Castleman disease(CD)pathological type(hyaline vascular(HV)or plasma cell(PC)variant)to improve the understanding and diagnostic accuracy of ultrasou...An ultrasonic nomogram was developed for preoperative prediction of Castleman disease(CD)pathological type(hyaline vascular(HV)or plasma cell(PC)variant)to improve the understanding and diagnostic accuracy of ultrasound for this disease.Fifty cases of CD confirmed by pathology were gathered from January 2012 to October 2018 from three hospitals.A grayscale ultrasound image of each patient was collected and processed.First,the region of interest of each gray ultrasound image was manually segmented using a process that was guided and calibrated by radiologists who have been engaged in imaging diagnosis for more than 5 years.In addition,the clinical characteristics and other ultrasonic features extracted from the color Doppler and spectral Doppler ultrasound images were also selected.Second,the chi-square test was used to select and reduce features.Third,a naïve Bayesian model was used as a classifier.Last,clinical cases with gray ultrasound image datasets from the hospital were used to test the performance of our proposed method.Among these patients,31 patients(18 patients with HV and 13 patients with PC)were used to build a training set for the predictive model and 19(11 patients with HV and 8 patients with PC)were used for the test set.From the set,584 high-throughput and quantitative image features,such as mass shape size,intensity,texture characteristics,and wavelet characteristics,were extracted,and then 152 images features were selected.Comparing the radiomics classification results with the pathological results,the accuracy rate,sensitivity,and specificity were 84.2%,90.1%,and 87.5%,respectively.The experimental results show that radiomics was valuable for the differentiation of CD pathological type.展开更多
The management of traumatic peripheral nerve injury remains a considerable concern for clinicians.With minimal innovations in surgical technique and a limited number of specialists trained to treat peripheral nerve in...The management of traumatic peripheral nerve injury remains a considerable concern for clinicians.With minimal innovations in surgical technique and a limited number of specialists trained to treat peripheral nerve injury,outcomes of surgical intervention have been unpredictable.The inability to manipulate the pathophysiology of nerve injury（i.e.,Wallerian degeneration） has left scientists and clinicians depending on the slow and lengthy process of axonal regeneration（-1 mm/day）.When axons are severed,the endings undergo calcium-mediated plasmalemmal sealing,which limits the ability of the axon to be primarily repaired.Polythethylene glycol（PEG） in combination with a bioengineered process overcomes the inability to fuse axons.The mechanism for PEG axonal fusion is not clearly understood,but multiple studies have shown that a providing a calcium-free environment is essential to the process known as PEG fusion.The proposed mechanism is PEG-induced lipid bilayer fusion by removing the hydration barrier surrounding the axolemma and reducing the activation energy required for membrane fusion to occur.This review highlights PEG fusion,its past and current studies,and future directions in PEG fusion.展开更多
White matter(WM)comprises approximately half of the human brain volume and is primarily composed of bundles of axons and glia.The axons conduct nerve impulses between gray matter(GM)to support information transmission...White matter(WM)comprises approximately half of the human brain volume and is primarily composed of bundles of axons and glia.The axons conduct nerve impulses between gray matter(GM)to support information transmission and coordination within brain networks or circuits.Despite the overwhelming emphasis of human brain imaging on GM,few would deny the importance of the functional contributions of WM to human cognition and behavior.For in vivo brain studies,diffusion magnetic resonance imaging(MRI)has been widely used to delineate WM fibers and measure their microstructural properties,but diffusion MRI reveals little about functional activity.For a long time,we have lacked an in vivo way to quantify functional metrics of wM.In contrast to the widespread application of functional MRI(fMRI)based on blood oxygenation-level-dependent(BOLD)signals to assess GM functions[1],BOLD effects in WM have been regarded as noise or nuisance variables in most neuroimaging studies.展开更多
Background Resting-state functional magnetic resonance imaging(RS-fMRI)has been proved to be a useful tool to study the brain mechanism in the quest to probe the distinct pattern of inter-region interactions in the br...Background Resting-state functional magnetic resonance imaging(RS-fMRI)has been proved to be a useful tool to study the brain mechanism in the quest to probe the distinct pattern of inter-region interactions in the brain.As an important application of RSfMRI,the graph-based approach characterizes the brain as a complex network.However,the network is susceptible to its scale that determines the trade-off between sensitivity and anatomical variability.Objective To balance sensitivity and anatomical variability,a pyramid representation of the functional network is proposed,which is composed of five individual networks reconstructed at multiple scales.Methods The pyramid representation of the functional network was applied to two groups of participants,including patients with Alzheimer’s disease(AD)and normal elderly(NC)individuals,as a demonstration.Features were extracted from the multi-scale networks andwere evaluated with their inter-group differences between AD andNC,aswell as the discriminative power in recognizing AD.Moreover,the proposed method was also validated by another dataset from people with autism.Results The different features reflect the highest sensitivity to distinguish AD at different scales.In addition,the combined features have higher accuracy than any single scale-based feature.These findings highlight the potential use ofmulti-scale features asmarkers of the disrupted topological organization in AD networks.Conclusion We believe that multi-scale metrics could provide a more comprehensive characterization of the functional network and thus provide a promising solution for representing the underlying functional mechanism in the human brain on a multi-scale basis.展开更多
基金supported by NIH Grant R01 NS069909an imaging track Grant from the Dana Foundation
文摘Human functional MRI studies in acute and various chronic pain conditions have revolutionized how we view pain, and have led to a new theory that complex multi-dimensional pain experience （sensory-discriminative, affective/motivational, and cognitive） is represented by concurrent activity in widely-distributed brain regions （termed a network or pain matrix）. Despite these break- through discoveries, the specific functions proposed for these regions remain elusive, because detailed electrophys- iological characterizations of these regions in the primate brain are lacking. To fill in this knowledge gap, we have studied the cortical areas around the central and lateral sulci of the non-human primate brain with combined submillimeter resolution functional imaging （optical imaging and fMRI） and intracranial electrophysiological recording. In this mini-review, I summarize and present data showing that the cortical circuitry engaged in nociceptive processing is much more complex than previously recognized. Electrophysiological evidence supports the engage- ment of a distinct nociceptive-processing network within SI （i.e., areas 3a, 3b, 1 and 2）, SII, and other areas along the lateral sulcus. Deafferentation caused by spinal cord injury profoundly alters the relationships between fMRI and electrophysiological signals. This finding has significant implications for using fMRI to study chronic pain conditions involving deafferentation in humans.
基金This work was supported by the National Natural Science Foundation[grant number 61806029]the Chengdu University of Information Engineering Research Fund[grant number KYTZ201719]+1 种基金Youth Technology Fund of Sichuan Provincial Education Hall[grant number 17QNJJ0004]the Project of Sichuan Provincial Education Hall[grant numbers 18ZA0089,2017GZ0333 and 2018Z065].
文摘An ultrasonic nomogram was developed for preoperative prediction of Castleman disease(CD)pathological type(hyaline vascular(HV)or plasma cell(PC)variant)to improve the understanding and diagnostic accuracy of ultrasound for this disease.Fifty cases of CD confirmed by pathology were gathered from January 2012 to October 2018 from three hospitals.A grayscale ultrasound image of each patient was collected and processed.First,the region of interest of each gray ultrasound image was manually segmented using a process that was guided and calibrated by radiologists who have been engaged in imaging diagnosis for more than 5 years.In addition,the clinical characteristics and other ultrasonic features extracted from the color Doppler and spectral Doppler ultrasound images were also selected.Second,the chi-square test was used to select and reduce features.Third,a naïve Bayesian model was used as a classifier.Last,clinical cases with gray ultrasound image datasets from the hospital were used to test the performance of our proposed method.Among these patients,31 patients(18 patients with HV and 13 patients with PC)were used to build a training set for the predictive model and 19(11 patients with HV and 8 patients with PC)were used for the test set.From the set,584 high-throughput and quantitative image features,such as mass shape size,intensity,texture characteristics,and wavelet characteristics,were extracted,and then 152 images features were selected.Comparing the radiomics classification results with the pathological results,the accuracy rate,sensitivity,and specificity were 84.2%,90.1%,and 87.5%,respectively.The experimental results show that radiomics was valuable for the differentiation of CD pathological type.
基金supported by the Department of Defense:Grant Number OR120216--Development of Class Ⅱ Medical Device for Clinical Translation of a Novel PEG Fusion Method for Immediate Physiological Recovery after Peripheral Nerve Injury
文摘The management of traumatic peripheral nerve injury remains a considerable concern for clinicians.With minimal innovations in surgical technique and a limited number of specialists trained to treat peripheral nerve injury,outcomes of surgical intervention have been unpredictable.The inability to manipulate the pathophysiology of nerve injury（i.e.,Wallerian degeneration） has left scientists and clinicians depending on the slow and lengthy process of axonal regeneration（-1 mm/day）.When axons are severed,the endings undergo calcium-mediated plasmalemmal sealing,which limits the ability of the axon to be primarily repaired.Polythethylene glycol（PEG） in combination with a bioengineered process overcomes the inability to fuse axons.The mechanism for PEG axonal fusion is not clearly understood,but multiple studies have shown that a providing a calcium-free environment is essential to the process known as PEG fusion.The proposed mechanism is PEG-induced lipid bilayer fusion by removing the hydration barrier surrounding the axolemma and reducing the activation energy required for membrane fusion to occur.This review highlights PEG fusion,its past and current studies,and future directions in PEG fusion.
基金supported by the National Natural Science Foundation of China(82371507 and 82090034)Outstanding Youth Fund for Universities in Anhui Province(2024AH020004)+5 种基金the collaborative innovation project between universities and Hefei Comprehensive National Science Center(GXXT-2022-028)the Hefei Comprehensive National Science Center Hefei Brain Project,the 2021 Anhui Province Key R&D Project:Population Health Special Project(202104j07020033)major project of Research Fund of Anhui Institute of Translational Medicine in 2020(2020zhyx A04)the Anhui Province Clinical Medical Research Transformation Special Project(202204295107020006 and 202204295107020028)National Institutes of Health grant(R01 NS113832 and R01 NS129855)National Research and Engineering Council Canada,Discovery Grant。
文摘White matter(WM)comprises approximately half of the human brain volume and is primarily composed of bundles of axons and glia.The axons conduct nerve impulses between gray matter(GM)to support information transmission and coordination within brain networks or circuits.Despite the overwhelming emphasis of human brain imaging on GM,few would deny the importance of the functional contributions of WM to human cognition and behavior.For in vivo brain studies,diffusion magnetic resonance imaging(MRI)has been widely used to delineate WM fibers and measure their microstructural properties,but diffusion MRI reveals little about functional activity.For a long time,we have lacked an in vivo way to quantify functional metrics of wM.In contrast to the widespread application of functional MRI(fMRI)based on blood oxygenation-level-dependent(BOLD)signals to assess GM functions[1],BOLD effects in WM have been regarded as noise or nuisance variables in most neuroimaging studies.
基金This work was funded by National Natural Science Foundation of China(grant numbers 81901828,81873890)。
文摘Background Resting-state functional magnetic resonance imaging(RS-fMRI)has been proved to be a useful tool to study the brain mechanism in the quest to probe the distinct pattern of inter-region interactions in the brain.As an important application of RSfMRI,the graph-based approach characterizes the brain as a complex network.However,the network is susceptible to its scale that determines the trade-off between sensitivity and anatomical variability.Objective To balance sensitivity and anatomical variability,a pyramid representation of the functional network is proposed,which is composed of five individual networks reconstructed at multiple scales.Methods The pyramid representation of the functional network was applied to two groups of participants,including patients with Alzheimer’s disease(AD)and normal elderly(NC)individuals,as a demonstration.Features were extracted from the multi-scale networks andwere evaluated with their inter-group differences between AD andNC,aswell as the discriminative power in recognizing AD.Moreover,the proposed method was also validated by another dataset from people with autism.Results The different features reflect the highest sensitivity to distinguish AD at different scales.In addition,the combined features have higher accuracy than any single scale-based feature.These findings highlight the potential use ofmulti-scale features asmarkers of the disrupted topological organization in AD networks.Conclusion We believe that multi-scale metrics could provide a more comprehensive characterization of the functional network and thus provide a promising solution for representing the underlying functional mechanism in the human brain on a multi-scale basis.
