Brain tumors are considered as most fatal cancers.To reduce the risk of death,early identification of the disease is required.One of the best available methods to evaluate brain tumors is Magnetic resonance Images(MRI...Brain tumors are considered as most fatal cancers.To reduce the risk of death,early identification of the disease is required.One of the best available methods to evaluate brain tumors is Magnetic resonance Images(MRI).Brain tumor detection and segmentation are tough as brain tumors may vary in size,shape,and location.That makes manual detection of brain tumors by exploring MRI a tedious job for radiologists and doctors’.So an automated brain tumor detection and segmentation is required.This work suggests a Region-based Convolution Neural Network(RCNN)approach for automated brain tumor identification and segmentation using MR images,which helps solve the difficulties of brain tumor identification efficiently and accurately.Our methodology is based on the accurate and efficient selection of tumorous areas.That reduces computational complexity and time.We have validated the designed experimental setup on a standard dataset,BraTS 2020.We used binary evaluation matrices based on Dice Similarity Coefficient(DSC)and Mean Average Precision(mAP).The segmentation results are compared with state-of-the-art methodologies to demonstrate the effectiveness of the proposed method.The suggested approach attained an averageDSC of 0.92 andmAP 0.92 for 10 patients,while on the whole dataset,the scores are DSC 0.89 and mAP 0.90.The following results clearly show the performance efficiency of the proposed methodology.展开更多
Objective The resting-state functional magnetic resonance imaging(rs-f MRI)method was used to observe brain activity and its functional connection upon electroacupuncture stimulation at bilateral uterine acupoints(EX-...Objective The resting-state functional magnetic resonance imaging(rs-f MRI)method was used to observe brain activity and its functional connection upon electroacupuncture stimulation at bilateral uterine acupoints(EX-CA1),as well as to investigate the mechanism of acupuncture in the treatment of gynecological diseases.Methods Twenty-two healthy female subjects were stimulated by electroacupuncture at bilateral uterine acupoints;rs-f MRI data of the brain were acquired and standardized.Degree centrality(DC),amplitude of low-frequency fluctuation(ALFF),and regional homogeneity(ReHo)were used to analyze local spontaneous brain activity via acupuncture.An independent component analysis was used to evaluate the functional connectivity of the resting brain networks after acupuncture.Results Analytical results showed that the neural activity intensity of the precuneus lobe,orbitofrontal cortex,lingual gyrus,amygdala,and posterior central gyrus decreased after acupuncture(voxel P<0.001,cluster P<0.05).Functional connectivity analysis revealed weakened auditory and right frontal-parietal networks(voxel P<0.001,cluster P<0.05),enhanced visual network(voxel P<0.001,cluster P<0.05),and synergistic auditory network and hypothalamic-pituitary system.Conclusion Significant differences in neural activity and functional connectivity in specific brain regions were observed after acupuncture intervention at uterine acupoints;the hypothalamic-pituitary system also showed various active states in different brain regions.It is speculated that the effective mechanism of acupuncture at uterine acupoints is related to the regulation of reproductive hormones,emotional changes,and somatic sensations.Therefore,the methods used in this study could clarify the neural mechanism of uterine-point acupuncture in the treatment of gynecological diseases and may serve as a reference for other studies pertaining to acupuncture.展开更多
Objective To investigate gene expression of transforming growth factor-β(TGF-β)in local bony callus in tracumatic brain in jury combined with extremity long bone fracture in rats.Methods Eighty male SD rats were ran...Objective To investigate gene expression of transforming growth factor-β(TGF-β)in local bony callus in tracumatic brain in jury combined with extremity long bone fracture in rats.Methods Eighty male SD rats were randomized into 2 even展开更多
Alzheimer’s disease（AD）is broadly defined by dementia and the presence of specific neuropathological features in the brain（amyloid plaques,neurofibrillary tangles（NFTs）and congophilic amyloid angiopathy）.Howeve...Alzheimer’s disease（AD）is broadly defined by dementia and the presence of specific neuropathological features in the brain（amyloid plaques,neurofibrillary tangles（NFTs）and congophilic amyloid angiopathy）.However,the rate of disease progression,type of cognitive impairment,and extent of neuropathology vary widely in patients with AD（Murray et al.,2011）.展开更多
Intense abdominal pain is the most common symptom in chronic pancreatitis, but the underlying mechanisms are not completely understood and pain management remains a significant clinical challenge.The focus of pain ori...Intense abdominal pain is the most common symptom in chronic pancreatitis, but the underlying mechanisms are not completely understood and pain management remains a significant clinical challenge.The focus of pain origin in chronic pancreatitis traditionally has been on the pancreatic gland, assuming pain to originate in the pancreas or its surrounding organs. However, research in the last decade points to abnormal central nervous system pain processing.For this reason, electroencephalography has been receiving increasing attention. In contrast to imaging methods such as functional magnetic resonance and positron emission tomography, electroencephalogram has excellent temporal resolution making it possible to investigate central processing of pain on a millisecond time scale. Moreover, continuously advancing methodology made it possible to explore brain sources responsible for generation of evoked potentialsand hence to study brain reorganization due to pain in chronic pancreatitis. The aim of this review is to give an overview of the current methods and findings in electroencephalography as a tool to unravel the origin of pancreatic pain.展开更多
Background:The pathogenesis of neck pain in the brain,which is the fourth most common cause of disability,remains unclear.Furthermore,little is known about the characteristics of dynamic local functional brain activit...Background:The pathogenesis of neck pain in the brain,which is the fourth most common cause of disability,remains unclear.Furthermore,little is known about the characteristics of dynamic local functional brain activity in cervical pain.Objective:The present study aimed to investigate the changes of local brain activity caused by chronic neck pain and the factors leading to neck pain.Methods:Using the amplitude of low-frequency fluctuations(ALFF)method combined with sliding window approach,we compared local brain activity that was measured by the functional magnetic resonance imaging(fMRI)of 107 patients with chronic neck pain(CNP)with that of 57 healthy control participants.Five pathogenic factors were selected for correlation analysis.Results:The group comparison results of dynamic amplitude of low-frequency fluctuation(dALFF)variability showed that patients with CNP exhibited decreased dALFF variability in the left inferior temporal gyrus,the middle temporal gyrus,the angular gyrus,the inferior parietal marginal angular gyrus,and the middle occipital gyrus.The abnormal dALFF variability of the left inferior temporal gyrus was negatively correlated with the average daily working hours of patients with neck pain.Conclusions:The findings indicated that the brain regions of patients with CNP responsible for audition,vision,memory,and emotion were subjected to temporal variability of abnormal regional brain activity.Moreover,the dALFF variability in the left inferior temporal gyrus might be a risk factor for neck pain.This study revealed the brain dysfunction of patients with CNP from the perspective of dynamic local brain activity,and highlighted the important role of dALFF variability in understanding the neural mechanism of CNP.展开更多
基金This work was funded by the Ministry of Education under Grant NRF-2019R1A2C1006159Grant NRF-2021R1A6A1A03039493。
文摘Brain tumors are considered as most fatal cancers.To reduce the risk of death,early identification of the disease is required.One of the best available methods to evaluate brain tumors is Magnetic resonance Images(MRI).Brain tumor detection and segmentation are tough as brain tumors may vary in size,shape,and location.That makes manual detection of brain tumors by exploring MRI a tedious job for radiologists and doctors’.So an automated brain tumor detection and segmentation is required.This work suggests a Region-based Convolution Neural Network(RCNN)approach for automated brain tumor identification and segmentation using MR images,which helps solve the difficulties of brain tumor identification efficiently and accurately.Our methodology is based on the accurate and efficient selection of tumorous areas.That reduces computational complexity and time.We have validated the designed experimental setup on a standard dataset,BraTS 2020.We used binary evaluation matrices based on Dice Similarity Coefficient(DSC)and Mean Average Precision(mAP).The segmentation results are compared with state-of-the-art methodologies to demonstrate the effectiveness of the proposed method.The suggested approach attained an averageDSC of 0.92 andmAP 0.92 for 10 patients,while on the whole dataset,the scores are DSC 0.89 and mAP 0.90.The following results clearly show the performance efficiency of the proposed methodology.
基金National Nature Science Foundation of China(61872225)Natural Science Foundation of Shandong Province(ZR2020KF013,ZR2020ZD44,ZR2019ZD04,and ZR2020QF043)+1 种基金Introduction and Cultivation Program for Young Creative Talents in Colleges and Universities of Shandong Province(2019-173)Special Fund of Qilu Health and Health Leading Talents Training Project。
文摘Objective The resting-state functional magnetic resonance imaging(rs-f MRI)method was used to observe brain activity and its functional connection upon electroacupuncture stimulation at bilateral uterine acupoints(EX-CA1),as well as to investigate the mechanism of acupuncture in the treatment of gynecological diseases.Methods Twenty-two healthy female subjects were stimulated by electroacupuncture at bilateral uterine acupoints;rs-f MRI data of the brain were acquired and standardized.Degree centrality(DC),amplitude of low-frequency fluctuation(ALFF),and regional homogeneity(ReHo)were used to analyze local spontaneous brain activity via acupuncture.An independent component analysis was used to evaluate the functional connectivity of the resting brain networks after acupuncture.Results Analytical results showed that the neural activity intensity of the precuneus lobe,orbitofrontal cortex,lingual gyrus,amygdala,and posterior central gyrus decreased after acupuncture(voxel P<0.001,cluster P<0.05).Functional connectivity analysis revealed weakened auditory and right frontal-parietal networks(voxel P<0.001,cluster P<0.05),enhanced visual network(voxel P<0.001,cluster P<0.05),and synergistic auditory network and hypothalamic-pituitary system.Conclusion Significant differences in neural activity and functional connectivity in specific brain regions were observed after acupuncture intervention at uterine acupoints;the hypothalamic-pituitary system also showed various active states in different brain regions.It is speculated that the effective mechanism of acupuncture at uterine acupoints is related to the regulation of reproductive hormones,emotional changes,and somatic sensations.Therefore,the methods used in this study could clarify the neural mechanism of uterine-point acupuncture in the treatment of gynecological diseases and may serve as a reference for other studies pertaining to acupuncture.
文摘Objective To investigate gene expression of transforming growth factor-β(TGF-β)in local bony callus in tracumatic brain in jury combined with extremity long bone fracture in rats.Methods Eighty male SD rats were randomized into 2 even
文摘Alzheimer’s disease（AD）is broadly defined by dementia and the presence of specific neuropathological features in the brain（amyloid plaques,neurofibrillary tangles（NFTs）and congophilic amyloid angiopathy）.However,the rate of disease progression,type of cognitive impairment,and extent of neuropathology vary widely in patients with AD（Murray et al.,2011）.
文摘Intense abdominal pain is the most common symptom in chronic pancreatitis, but the underlying mechanisms are not completely understood and pain management remains a significant clinical challenge.The focus of pain origin in chronic pancreatitis traditionally has been on the pancreatic gland, assuming pain to originate in the pancreas or its surrounding organs. However, research in the last decade points to abnormal central nervous system pain processing.For this reason, electroencephalography has been receiving increasing attention. In contrast to imaging methods such as functional magnetic resonance and positron emission tomography, electroencephalogram has excellent temporal resolution making it possible to investigate central processing of pain on a millisecond time scale. Moreover, continuously advancing methodology made it possible to explore brain sources responsible for generation of evoked potentialsand hence to study brain reorganization due to pain in chronic pancreatitis. The aim of this review is to give an overview of the current methods and findings in electroencephalography as a tool to unravel the origin of pancreatic pain.
基金supported by the Science and Technology Support Program of Sichuan Province(2018JY0562)the National Natural Science Foundation of China(81722050,81973962 and U1808204)the Key Project of Research and Development of Ministry of Science and Technology(2018AAA0100705).
文摘Background:The pathogenesis of neck pain in the brain,which is the fourth most common cause of disability,remains unclear.Furthermore,little is known about the characteristics of dynamic local functional brain activity in cervical pain.Objective:The present study aimed to investigate the changes of local brain activity caused by chronic neck pain and the factors leading to neck pain.Methods:Using the amplitude of low-frequency fluctuations(ALFF)method combined with sliding window approach,we compared local brain activity that was measured by the functional magnetic resonance imaging(fMRI)of 107 patients with chronic neck pain(CNP)with that of 57 healthy control participants.Five pathogenic factors were selected for correlation analysis.Results:The group comparison results of dynamic amplitude of low-frequency fluctuation(dALFF)variability showed that patients with CNP exhibited decreased dALFF variability in the left inferior temporal gyrus,the middle temporal gyrus,the angular gyrus,the inferior parietal marginal angular gyrus,and the middle occipital gyrus.The abnormal dALFF variability of the left inferior temporal gyrus was negatively correlated with the average daily working hours of patients with neck pain.Conclusions:The findings indicated that the brain regions of patients with CNP responsible for audition,vision,memory,and emotion were subjected to temporal variability of abnormal regional brain activity.Moreover,the dALFF variability in the left inferior temporal gyrus might be a risk factor for neck pain.This study revealed the brain dysfunction of patients with CNP from the perspective of dynamic local brain activity,and highlighted the important role of dALFF variability in understanding the neural mechanism of CNP.
