The effect of Astragaloside IV on ethanol-induced gastric mucosal injury in rats: Involvement of inflammation.

The present study aimed to investigate the potential protective effects of Astragaloside IV (AS-IV) against ethanol-induced gastric mucosal injury in rats. The animals were divided into 7 groups and pretreated with vehicle, various doses of AS-IV (1,2 and 4mg/kg, i.p.) or omeprazole (40mg/kg), 75min later, the gastric mucosal injury was induced by oral administration of ethanol. One hour after ethanol ingestion, the rats were euthanized and gastric tissues were collected to biochemical analyze. Myeloperoxidase (MPO), tumor necrosis factor α (TNF-α), interleukin 1ß (IL-1ß), interleukin 10 (IL-10), nuclear factor kappa B (NF-κB) p65 protein, TNF receptor-associated factor 2 (TRAF2) and nuclear NF-κB (nNF-κB) proteins were estimated by enzyme-linked immunosorbent assay or western blot analysis. The gastric mucosal lesions were assessed by macroscopic and histopathological examinations. The results showed pretreatment with AS-IV attenuated the severity of ethanol gastric mucosal damage as evidenced by lowering of injury scores, histopathologic aberrations and leukocyte invasion. These actions were analogous to the reference omeprazole. AS-IV suppressed gastric inflammation by curbing of MPO, TNF-α levels along with NF-κB p65 and TRAF2 expression. It also augmented the anti-inflammatory IL-10 levels. Meanwhile, AS-IV could inhibit NF-κB transcription by inhibiting the expression of NF-κB p65 and increasing the expression of nNF-κB. It seems that AS-IV as an anti-inflammatory agent may have a protective effect against ethanol-induced mucosal injury by inhibition of neutrophil infiltration and reducing the expression of NF-κB p65, TRAF2 and inflammatory cytokines via regulating TNF-α/NF-κB signal pathway in gastric tissue.

Enhanced Autophagy Contributes to Protective Effects of GM1 Ganglioside Against Aß1-42-Induced Neurotoxicity and Cognitive Deficits.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. The aggregation of Aß peptides, Aß1-42 in particular, is thought to be a fundamental pathogenic mechanism leading to the neuronal damage in AD. Recently, monosialoganglioside GM1 is reported to possess pivotal neuroprotection in neurodegenerative diseases. Previous studies have focused on the conformational dynamics and the biochemical interaction of the amyloid-peptide with the GM1 ganglioside, as well as the protective effect of GM1 on cognition. However, the phenomenon of autophagy with regard to neuronal dysfunction in AD is less investigated. In the present study, GM1 treatment were investigated in an AD mouse model and cultured PC12 dells to examine cognition-protective and neuroprotective effects of GM1. Furthermore, GM1 was found to induce autophagy via testing light chain 3 (LC3), Beclin1, neighbor of BRCA1 gene 1 protein and p62 (a substrate of LC3). Chloroquine, an inhibitor of lysosomal, was used to exclude the interference of lysosome, which could fuse with autophagosome and then clear it. In the presence of the inhibitor of autophagy (3-methyladenine; 3-MA), the protective effect of GM1 on PC12 cells in Aß (1-42) induced toxic conditions was diminished. Interestingly, the expression of histone deacetylase 1 was increased in PC12 cells when treated with GM1, indicating that autophagy might be activated by GM1 through a pathway integrates protein acetylation. This study provides a novel insight into the protective role of GM1 against Aß (1-42)-induced neurotoxicity via enhancing autophagy.

Staging of cervical cancer based on tumor heterogeneity characterized by texture features on (18)F-FDG PET images.

The aim of the study is to assess the staging value of the tumor heterogeneity characterized by texture features and other commonly used semi-quantitative indices extracted from (18)F-FDG PET images of cervical cancer (CC) patients. Forty-two patients suffering CC at different stages were enrolled in this study. Firstly, we proposed a new tumor segmentation method by combining the intensity and gradient field information in a level set framework. Secondly, fifty-four 3D texture features were studied besides of SUVs (SUVmax, SUVmean, SUVpeak) and metabolic tumor volume (MTV). Through correlation analysis, receiver-operating-characteristic (ROC) curves analysis, some independent indices showed statistically significant differences between the early stage (ES, stages I and II) and the advanced stage (AS, stages III and IV). Then the tumors represented by those independent indices could be automatically classified into ES and AS, and the most discriminative feature could be chosen. Finally, the robustness of the optimal index with respect to sampling schemes and the quality of the PET images were validated. Using the proposed segmentation method, the dice similarity coefficient and Hausdorff distance were 91.78 ± 1.66% and 7.94 ± 1.99 mm, respectively. According to the correlation analysis, all the fifty-eight indices could be divided into 20 groups. Six independent indices were selected for their highest areas under the ROC curves (AUROC), and showed significant differences between ES and AS (P < 0.05). Through automatic classification with the support vector machine (SVM) Classifier, run percentage (RP) was the most discriminative index with the higher accuracy (88.10%) and larger AUROC (0.88). The Pearson correlation of RP under different sampling schemes is 0.9991 ± 0.0011. RP is a highly stable feature and well correlated with tumor stage in CC, which suggests it could differentiate ES and AS with high accuracy.

A Segmentation Algorithm for Quantitative Analysis of Heterogeneous Tumors of the Cervix With ¹8F-FDG PET/CT.

As positron-emission tomography (PET) images have low spatial resolution and much noise, accurate image segmentation is one of the most challenging issues in tumor quantification. Tumors of the uterine cervix present a particular challenge because of urine activity in the adjacent bladder. Here, we propose and validate an automatic segmentation method adapted to cervical tumors. Our proposed methodology combined the gradient field information of both the filtered PET image and the level set function into a level set framework by constructing a new evolution equation. Furthermore, we also constructed a new hyperimage to recognize a rough tumor region using the fuzzy c-means algorithm according to the tissue specificity as defined by both PET (uptake) and computed tomography (attenuation) to provide the initial zero level set, which could make the segmentation process fully automatic. The proposed method was verified based on simulation and clinical studies. For simulation studies, seven different phantoms, representing tumors with homogenous/heterogeneous-low/high uptake patterns and different volumes, were simulated with five different noise levels. Twenty-seven cervical cancer patients at different stages were enrolled for clinical evaluation of the method. Dice similarity coefficients (DSC) and Hausdorff distance (HD) were used to evaluate the accuracy of the segmentation method, while a Bland-Altman analysis of the mean standardized uptake value (SUVmean) and metabolic tumor volume (MTV) was used to evaluate the accuracy of the quantification. Using this method, the DSCs and HDs of the homogenous and heterogeneous phantoms under clinical noise level were 93.39 ±1.09% and 6.02 ±1.09 mm, 93.59 ±1.63% and 8.92 ±2.57 mm, respectively. The DSCs and HDs in patients measured 91.80 ±2.46% and 7.79 ±2.18 mm. Through Bland-Altman analysis, the SUVmean and the MTV using our method showed high correlation with the clinical gold standard. The results of both simulation and clinical studies demonstrated the accuracy, effectiveness, and robustness of the proposed method. Further assessment of the quantitative indices indicates the feasibility of this algorithm in accurate quantitative analysis of cervical tumors in clinical practice.

Exploring the patterns of acupuncture on mild cognitive impairment patients using regional homogeneity.

PURPOSE: To investigate the different responses to acupuncture in MCI patients and age-matched healthy subjects reflected by the Regional Homogeneity (ReHo) indices. METHODS: The experiment was performed at the acupoint KI3 in 12 MCI patients and 12 healthy controls, respectively. A novel non-repeated event-related (NRER) fMRI design paradigm was applied to separately detect neural activities related to different stages of acupuncture (pre-acupuncture resting state, needling manipulation and post-acupuncture resting state). ReHo values were calculated for MCI patients and healthy controls in pre- and post-acupuncture resting state. Then, a two-way ANCOVA with repeated measures with post-hoc two sample t-tests was performed to explore the different responses to acupuncture in the two groups. RESULTS: The ANCOVA revealed a significant main effect of group, but no significant main effect of acupuncture and interactions between group and acupuncture. During the pre-acupuncture resting state, ReHo values increased in the precentral gyrus (PCG), superior frontal gyrus (SFG), and insula (INS) and decreased mainly in middle temporal gyrus (MTG), parahippocampal (PHIP) and cingulate cortex in MCI patients compared with healthy controls. Furthermore, we found that the regions including precuneus (PCUN), and cingulate cortex showed increased ReHo values for MCI patients following acupuncture. For healthy controls, the medial frontal gyrus, PCG, anterior cingulate cortex (ACC) and INS showed enhanced ReHo values following acupuncture. During the post-acupuncture resting state, MCI patients showed increased ReHo values mainly in the MTG, superior parietal lobule (SPL), middle frontal gyrus (MFG), supramarginal (SMG), and PCG, and decreased ReHo values mainly in the frontal regions, PHIP, and posterior cingulated cortex (PCC) compared to healthy controls. CONCLUSION: Though we found some ReHo changes between MCI patients and healthy controls, the two-way ANCOVA results showed no significant effects after multiple corrections. Further study is needed to reveal the real acupuncture effects on MCI patients.

A longitudinal study of hand motor recovery after sub-acute stroke: a study combined FMRI with diffusion tensor imaging.

Previous studies have shown that motor recovery of stroke can be assessed by the cortical activity and the structural integrity of the corticospinal tract (CST), but little is known about the relation between the cortical activity and the structural integrity during motor recovery. In the present study, we investigated the changes in brain activities evoked by twenty days' functional electrical stimulation (FES) training in twelve sub-acute stroke patients with unilateral upper-limb disability. We compared cortex activity evoked by wrist movement of eleven stroke patients to that of eleven age-matched healthy subjects to figure out how cortex activity changed after stroke. We also measured the structural integrity represented by the fractional anisotropy (FA) asymmetry of the posterior limb of the internal capsule (PLIC) to find the relationship between the brain activity and the structure integrity. In our study, we found that patients with sub-acute stroke have shown greater activity in the contralesional primary motor cortex (M1) during the affected hand's movement compared with healthy group, while the activity in ipsilesional M1 was decreased after the therapy compared to that before therapy, and the contralesional non-primary motor cortex showed greater activity after therapy. At the baseline we found that the positive correlation between the FA asymmetry of PLIC and the contralesional non-primary motor cortex activity showed that the greater damaged CST, the greater contralesional non-primary motor cortex recruited. While the negative correlation between them after the FES training indicates that after recovery the non-primary motor cortex plays different role in different stroke phases. Our study demonstrates that functional organization of a residual distributed motor system is related to the degree of disruption to the CST, and the non-primary motor areas plays an important role in motor recovery.

Altered hub configurations within default mode network following acupuncture at ST36: a multimodal investigation combining fMRI and MEG.

Acupuncture, an externally somatosensory stimulation in the Traditional Chinese Medicine, has been proposed about its modulations on the brain's default mode network (DMN). However, it is still unknown on how the internal brain resting networks are modulated and what inferences can be made about the physiological processes underlying these changes. Combining high spatial resolution of functional magnetic resonance imaging (fMRI) with high temporal resolution of magnetoencephalography (MEG), in the current multimodal study, we sought to explore spatiotemporally whether or not band-specific DMN hub configurations would be induced by verum acupuncture, compared with sham control. Spatial independent component analysis was applied to fMRI data, followed by the discrete regional sources seeded into MEG data. Partial correlation analysis was further adopted to estimate the intrinsic functional connectivity and network hub configurations. One of the most striking findings is that the posterior cingulate cortex is not only validated as a robust DMN hub, but served as a hub only within the delta and gamma bands following the verum acupuncture, compared with its consistently being a DMN hub in sham control group. Our preliminary results may provide a new perspective to lend support for the specificity of neural mechanism underlying acupuncture.

Acupuncture induces divergent alterations of functional connectivity within conventional frequency bands: evidence from MEG recordings.

As an ancient Chinese healing modality which has gained increasing popularity in modern society, acupuncture involves stimulation with fine needles inserted into acupoints. Both traditional literature and clinical data indicated that modulation effects largely depend on specific designated acupoints. However, scientific representations of acupoint specificity remain controversial. In the present study, considering the new findings on the sustained effects of acupuncture and its time-varied temporal characteristics, we employed an electrophysiological imaging modality namely magnetoencephalography with a temporal resolution on the order of milliseconds. Taken into account the differential band-limited signal modulations induced by acupuncture, we sought to explore whether or not stimulation at Stomach Meridian 36 (ST36) and a nearby non-meridian point (NAP) would evoke divergent functional connectivity alterations within delta, theta, alpha, beta and gamma bands. Whole-head scanning was performed on 28 healthy participants during an eyes-closed no-task condition both preceding and following acupuncture. Data analysis involved calculation of band-limited power (BLP) followed by pair-wise BLP correlations. Further averaging was conducted to obtain local and remote connectivity. Statistical analyses revealed the increased connection degree of the left temporal cortex within delta (0.5-4 Hz), beta (13-30 Hz) and gamma (30-48 Hz) bands following verum acupuncture. Moreover, we not only validated the closer linkage of the left temporal cortex with the prefrontal and frontal cortices, but further pinpointed that such patterns were more extensively distributed in the ST36 group in the delta and beta bands compared to the restriction only to the delta band for NAP. Psychophysical results for significant pain threshold elevation further confirmed the analgesic effect of acupuncture at ST36. In conclusion, our findings may provide a new perspective to lend support for the specificity of neural expression underlying acupuncture.

Altered topological patterns of brain networks in mild cognitive impairment and Alzheimer's disease: a resting-state fMRI study.

Recent studies have shown that cognitive and memory decline in patients with Alzheimer's disease (AD) is coupled with losses of small-world attributes. However, few studies have investigated the characteristics of the whole brain networks in individuals with mild cognitive impairment (MCI). In this functional magnetic resonance imaging (fMRI) study, we investigated the topological properties of the whole brain networks in 18 AD patients, 16 MCI patients, and 18 age-matched healthy subjects. Among the three groups, AD patients showed the longest characteristic path lengths and the largest clustering coefficients, while the small-world measures of MCI networks exhibited intermediate values. The finding was not surprising, given that MCI is considered to be the prodromal stage of AD. Compared with normal controls, MCI patients showed decreased nodal centrality mainly in the medial temporal lobe as well as increased nodal centrality in the occipital regions. In addition, we detected increased nodal centrality in the medial temporal lobe and frontal gyrus, and decreased nodal centrality mainly in the amygdala in MCI patients compared with AD patients. The results suggested a widespread rewiring in AD and MCI patients. These findings concerning AD and MCI may be an integrated reflection of reorganization of the brain networks accompanied with the cognitive decline that may lead to AD.

Investigation of the effective connectivity of resting state networks in Alzheimer's disease: a functional MRI study combining independent components analysis and multivariate Granger causality analysis.

Recent neuroimaging studies have shown that the cognitive and memory decline in patients with Alzheimer's disease (AD) is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses in small-world attributes. However, the causal interactions among the spatially isolated, but functionally related, resting state networks (RSNs) are still largely unexplored. In this study, we first identified eight RSNs by independent components analysis from resting state functional MRI data of 18 patients with AD and 18 age-matched healthy subjects. We then performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that patients with AD exhibited decreased causal interactions among the RSNs in both intensity and quantity relative to normal controls. Results from mGCA indicated that the causal interactions involving the default mode network and auditory network were weaker in patients with AD, whereas stronger causal connectivity emerged in relation to the memory network and executive control network. Our findings suggest that the default mode network plays a less important role in patients with AD. Increased causal connectivity of the memory network and self-referential network may elucidate the dysfunctional and compensatory processes in the brain networks of patients with AD. These preliminary findings may provide a new pathway towards the determination of the neurophysiological mechanisms of AD.

Exploring the effective connectivity of resting state networks in mild cognitive impairment: an fMRI study combining ICA and multivariate Granger causality analysis.

Mild cognitive impairment (MCI) was recognized as the prodromal stage of Alzheimer's disease (AD). Recent neuroimaging studies have shown that the cognitive and memory decline in AD and MCI patients is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses of small-world attributes. However, the causal interactions among the spatially isolated but function-related resting state networks (RSNs) are still largely unexplored in MCI patients. In this study, we first identified eight RSNs by independent components analysis (ICA) from resting state functional MRI data of 16 MCI patients and 18 age-matched healthy subjects respectively. Then, we performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that MCI patients exhibited decreased causal interactions among the RSNs in both intensity and quantity compared with normal controls. Results from mGCA indicated that the causal interactions involving the default mode network (DMN) became weaker in MCI patients, while stronger causal connectivity emerged related to the memory network and executive control network. Our findings suggested that the DMN played a less important role in MCI patients. Increased causal connectivity of the memory network and executive control network may elucidate the dysfunctional and compensatory processes in the brain networks of MCI patients. These preliminary findings may be helpful for further understanding the pathological mechanisms of MCI and provide a new clue to explore the neurophysiological mechanisms of MCI.

Modulatory effects of acupuncture on resting-state networks: a functional MRI study combining independent component analysis and multivariate Granger causality analysis.

PURPOSE: To investigate acupuncture specificity by exploring causal relationships of brain networks following acupuncture at GB40 (Qiuxu), with the acupoint KI3 (Taixi) as a control (belonging to the same nerve segment but different meridians). MATERIALS AND METHODS: Needling at acupoints GB40 and KI3 was performed in 12 subjects separately. The specific coherent patterns, resting-state networks (RSNs), were retrieved by independent component analysis (ICA) from functional magnetic resonance imaging (fMRI) data of resting state and post-acupuncture resting states, respectively. Then multivariate Granger causality analysis (mGCA) was applied to evaluate the effective connectivity within and among the detected RSNs-default model, memory, executive, auditory, and motor brain networks. RESULTS: Following acupuncture at GB40, the strength of causal connectivity between the superior temporal gyrus (STG) and anterior insula was enhanced, while the connection strength between the STG and postcentral gyrus increased following acupuncture at KI3. Additionally, the causal influences within the auditory network increased following acupuncture at GB40, in comparison with the executive network following acupuncture at KI3. CONCLUSION: The current study demonstrates that acupuncture at different acupoints could exert different modulatory effects on RSNs. Our findings may help to understand the neurophysiological mechanisms underlying acupuncture specificity.

Differential neural responses to acupuncture revealed by MEG using wavelet-based time-frequency analysis: a pilot study.

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, still faces many controversies. As previous neuroimaging studies on acupuncture mainly adopted relatively low time-resolution functional magnetic resonance imaging (fMRI) technology and inappropriate block-designed experimental paradigm due to sustained effect, in the current study, we employed a single block-designed paradigm together with high temporal-resolution magnetoencephalography (MEG) technology. We applied time-frequency analysis based upon Morlet wavelet transforming approach to detect differential oscillatory brain dynamics induced by acupuncture at Stomach Meridian 36 (ST36) using a nearby nonacupoint (NAP) as control condition. We observed that frequency power changes were mainly restricted to delta band for both ST36 group and NAP group. Consistently increased delta band power in contralateral temporal regions and decreased power in the counterparts of ipsilateral hemisphere were detected following stimulation at ST36 on the right leg. Compared with ST36, no significant delta ranges were found in temporal regions in NAP group, illustrating different oscillatory brain patterns. Our results may provide additional evidence to support the specificity of acupuncture modulation effects.

Exploring the evolution of post-acupuncture resting-state networks combining ICA and multivariate Granger causality.

The sustained effects of acupuncture have been widely applied to clinical treatment, thus it can be assumed that the relatively functional specificity of acupoints may evolve as the function of time. In this study, we originally combined ICA and multivariate Granger causality analysis to explore the causal interactions within and among the post-acupuncture resting-state networks (RSNs) at a hearing-related acupoint GB40, with the cognition-related acupoint KI3 as a control. Following acupuncture at GB40, the superior temporal gyrus (STG) and anterior insula (AI) within auditory network appeared persistent bidirectional connection with maximal strength, and the interactions between the auditory network and others became more complex as time passed. For KI3, both the superior parietal lobule (SPL) and dorsolateral prefrontal cortex (DLPFC), as vital nuclei of cognitive function, emerged increased causal outflows and inflows as time went on. We concluded that acupuncture at different acupoints may exert different evolutive effects on causal interactions within and across the RSNs during segmented post-stimulus resting states.

[Study on complex system of Chinese materia medica GAP fulfilling].

OBJECTIVE: To provide new model of thinking and management for Chinese Meteria Medica GAP fulfilling. METHOD: After analyzing the problems of GAP fulfilling, and considering GAP a complex system, we had some initial discussions about the systematic structure, characteristics and the methods for fulfilling it. RESULT: The GAP was a complex system which consisted of biological system, environment system and management system with its own characteristics and methods. CONCLUSION: The GAP fulfilling still has some problems and needs the direction of systematic opinion of complex system.