Regulation of RAGE splicing by hnRNP A1 and Tra2ß-1 and its potential role in AD pathogenesis.

The receptor for advanced glycation end products (RAGE) gene expresses two major alternative splicing isoforms, full-length membrane-bound RAGE (mRAGE) and secretory RAGE (esRAGE). Both isoforms play important roles in Alzheimer's disease (AD) pathogenesis, either via interaction of mRAGE with ß-amyloid peptide (Aß) or inhibition of the mRAGE-activated signaling pathway. In the present study, we showed that heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) and Transformer2ß-1 (Tra2ß-1) were involved in the alternative splicing of mRAGE and esRAGE. Functionally, two factors had an antagonistic effect on the regulation. Glucose deprivation induced an increased ratio of mRAGE/esRAGE via up-regulation of hnRNP A1 and down-regulation of Tra2ß-1. Moreover, the ratios of mRAGE/esRAGE and hnRNP A1/Tra2ß-1 were increased in peripheral blood mononuclear cells from AD patients. The results provide a molecular basis for altered splicing of mRAGE and esRAGE in AD pathogenesis. The receptor for advanced glycation end products (RAGE) gene expresses two major alternative splicing isoforms, membrane-bound RAGE (mRAGE) and secretory RAGE (esRAGE). Both isoforms play important roles in Alzheimer's disease (AD) pathogenesis. Mechanism for imbalanced expression of these two isoforms in AD brain remains elusive. We proposed here a hypothetic model to illustrate that impaired glucose metabolism in AD brain may increase the expression of splicing protein hnRNP A1 and reduce Tra2ß-1, which cause the imbalanced expression of mRAGE and esRAGE.

Recognition of moyamoya disease and its hemorrhagic risk using deep learning algorithms: sourced from retrospective studies.

Although intracranial hemorrhage in moyamoya disease can occur repeatedly, predicting the disease is difficult. Deep learning algorithms developed in recent years provide a new angle for identifying hidden risk factors, evaluating the weight of different factors, and quantitatively evaluating the risk of intracranial hemorrhage in moyamoya disease. To investigate whether convolutional neural network algorithms can be used to recognize moyamoya disease and predict hemorrhagic episodes, we retrospectively selected 460 adult unilateral hemispheres with moyamoya vasculopathy as positive samples for diagnosis modeling, including 418 hemispheres with moyamoya disease and 42 hemispheres with moyamoya syndromes. Another 500 hemispheres with normal vessel appearance were selected as negative samples. We used deep residual neural network (ResNet-152) algorithms to extract features from raw data obtained from digital subtraction angiography of the internal carotid artery, then trained and validated the model. The accuracy, sensitivity, and specificity of the model in identifying unilateral moyamoya vasculopathy were 97.64 ± 0.87%, 96.55 ± 3.44%, and 98.29 ± 0.98%, respectively. The area under the receiver operating characteristic curve was 0.990. We used a combined multi-view conventional neural network algorithm to integrate age, sex, and hemorrhagic factors with features of the digital subtraction angiography. The accuracy of the model in predicting unilateral hemorrhagic risk was 90.69 ± 1.58% and the sensitivity and specificity were 94.12 ± 2.75% and 89.86 ± 3.64%, respectively. The deep learning algorithms we proposed were valuable and might assist in the automatic diagnosis of moyamoya disease and timely recognition of the risk for re-hemorrhage. This study was approved by the Institutional Review Board of Huashan Hospital, Fudan University, China (approved No. 2014-278) on January 12, 2015.

Recognition of Cognitive Impairment in Adult Moyamoya Disease: A Classifier Based on High-Order Resting-State Functional Connectivity Network.

Objective: Vascular cognitive impairment (VCI) is a common complication in adult patients with moyamoya disease (MMD), and is reversible by surgical revascularization in its early stage of mild VCI. However, accurate diagnosis of mild VCI is difficult based on neuropsychological examination alone. This study proposed a method of dynamic resting-state functional connectivity (FC) network to recognize global cognitive impairment in MMD. Methods: For MMD, 36 patients with VCI and 43 patients with intact cognition (Non-VCI) were included, as well as 26 normal controls (NCs). Using resting-state fMRI, dynamic low-order FC networks were first constructed with multiple brain regions which were generated through a sliding window approach and correlated in temporal dimension. In order to obtain more information of network interactions along the time, high-order FC networks were established by calculating correlations among each pair of brain regions. Afterwards, a sparse representation-based classifier was constructed to recognize MMD (experiment 1) and its cognitive impairment (experiment 2) with features extracted from both low- and high-order FC networks. Finally, the ten-fold cross-validation strategy was proposed to train and validate the performance of the classifier. Results: The three groups did not differ significantly in demographic features (p > 0.05), while the VCI group exhibited the lowest MMSE scores (p = 0.001). The Non-VCI and NCs groups did not differ significantly in MMSE scores (p = 0.054). As for the classification between MMD and NCs, the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the classifier reached 90.70, 88.57, 93.67, and 73.08%, respectively. While for the classification between VCI and Non-VCI, the AUC, accuracy, sensitivity, and specificity of the classifier reached 91.02, 84.81, 80.56, and 88.37%, respectively. Conclusion: This study not only develops a promising classifier to recognize VCI in adult MMD in its early stage, but also implies the significance of time-varying properties in dynamic FC networks.

Minocycline reduces intracerebral hemorrhage-induced white matter injury in piglets.

AIMS: White matter (WM) injury after intracerebral hemorrhage (ICH) results in poor or even fatal outcomes. As an anti-inflammatory drug, minocycline has been considered a promising choice to treat brain injury after ICH. However, whether minocycline can reduce WM injury after ICH is still controversial. In the present study, we investigate the effect and underlying mechanism of minocycline on WM injury after ICH. METHODS: An ICH model was induced by an injection of autologous blood into the right frontal lobe of piglets. First, transcriptional analysis was performed at day 1 or 3 to investigate the dynamic changes in neuroinflammatory gene expression in WM after ICH. Second, ICH piglets were treated either with minocycline or with vehicle alone. All piglets then underwent magnetic resonance imaging to measure brain swelling. Brain tissue was used for real-time polymerase chain reaction (RT-PCR), immunohistochemistry, Western blot, and electron microscopy. RESULTS: Transcriptional analysis demonstrated that transforming growth factor-ß (TGF-ß)/mitogen-activated protein kinase (MAPK) signaling is associated with microglia/macrophage-mediated inflammation activation after ICH and is then involved in WM injury after ICH in piglets. Minocycline treatment results in less ICH-induced brain swelling, fewer neurological deficits, and less WM injury in comparison with the vehicle alone. In addition, minocycline reduces microglial activation and alleviates demyelination in white matter after ICH. Finally, we found that minocycline attenuates WM injury by increasing the expression of TGF-ß and suppressing MAPK activation after ICH. CONCLUSION: These results indicate that TGF-ß-mediated MAPK signaling contributes to WM injury after ICH, which can be altered by minocycline treatment.

Microstructural damage pattern of vascular cognitive impairment: a comparison between moyamoya disease and cerebrovascular atherosclerotic disease.

Moyamoya disease and cerebrovascular atherosclerotic disease are both chronic ischemic diseases with similar presentations of vascular cognitive impairment. The aim of the present study was to investigate the patterns of microstructural damage associated with vascular cognitive impairment in the two diseases. The study recruited 34 patients with moyamoya disease (age 43.9 ± 9.2 years; 20 men and 14 women, 27 patients with cerebrovascular atherosclerotic disease (age: 44.6 ± 7.6 years; 17 men and 10 women), and 31 normal controls (age 43.6 ± 7.3 years; 18 men and 13 women) from Huashan Hospital of Fudan University in China. Cognitive function was assessed using the Mini-Mental State Examination, long-term delayed recall of Auditory Verbal Learning Test, Trail Making Test Part B, and the Symbol Digit Modalities Test. Single-photon emission-computed tomography was used to examine cerebral perfusion. Voxel-based morphometry and tract-based spatial statistics were performed to identify regions of gray matter atrophy and white matter deterioration in patients and normal controls. The results demonstrated that the severity of cognitive impairment was similar between the two diseases in all tested domains. Patients with moyamoya disease and those with cerebrovascular atherosclerotic disease suffered from disturbed supratentorial hemodynamics. Gray matter atrophy in bilateral middle cingulate cortex and parts of the frontal gyrus was prominent in both diseases, but in general, was more severe and more diffuse in those with moyamoya disease. White matter deterioration was significant for both diseases in the genu and body of corpus callosum, in the anterior and superior corona radiation, and in the posterior thalamic radiation, but in moyamoya disease, it was more diffuse and more severe. Vascular cognitive impairment was associated with regional microstructural damage, with a potential link between, gray and white matter damage. Overall, these results provide insight into the pathophysiological nature of vascular cognitive impairment. This study was approved by the Institutional Review Board in Huashan Hospital, China (approval No. 2014-278). This study was registered with ClinicalTrials.gov on December 2, 2014 with the identifier NCT02305407.

Postoperative executive function in adult moyamoya disease: a preliminary study of its functional anatomy and behavioral correlates.

OBJECTIVE Chronic frontal hemodynamic disturbances are associated with executive dysfunction in adult patients with moyamoya disease (MMD). However, the impact of surgical revascularization on executive dysfunction and its underlying mechanism remains unclear. The aim of the present study was to examine the postoperative radiological correlates of cognitive improvement and thereby explore its underlying mechanism. METHODS Fourteen patients who met the inclusion criteria were identified at Huashan Hospital, were operated on, and were successfully followed up for 6 months. Postoperative changes in cortical perfusion and regional amplitude of low-frequency fluctuations (ALFF) were examined by SPECT and resting-state functional MRI, respectively. Executive function was evaluated by 2 tests (Trail Making Test Part B and the summation of executive subtests of Memory and Executive Screening [MES-EX]). Follow-up neuropsychological outcomes were then correlated with radiological changes to identify nodes functioning as leading contributors to postoperative executive outcomes. RESULTS All patients underwent successful unilateral bypass procedures, with some operations performed on the left side and some on the right side. At the 6-month follow-up, the baseline and follow-up test scores for the different sides did not differ significantly. The group with good collaterals (Matsushima Grade A, 9 patients) exhibited significantly increased postoperative perfusion (change in [△] hemodynamics) in bilateral frontal (left, p = 0.009; right, p = 0.003) and left parietal lobe (p = 0.014). The Spearman's correlation test suggested that only the right frontal lobe exhibited significant positive postoperative radiological correlates with cognitive performance (△MES-EX vs △hemodynamics, r = 0.620, p = 0.018; △MES-EX vs △ALFF, r = 0.676, p = 0.008; △hemodynamics vs △ALFF, r = 0.547, p = 0.043). Subsequent regional ALFF analysis revealed that the right dorsolateral prefrontal cortex (DLPFC) was the only node in the responsible hemisphere to exhibit significant postoperative changes. CONCLUSIONS The results not only advance our understanding of pathological interactions of postoperative executive performance in adult MMD, but also indicate that the right DLPFC amplitude might be a quantitative predictor of postoperative executive control improvement.