Increased number and domain of interlaminar astrocytes in layer I of the temporal cortex in epilepsy.

AIM: The functions of the interlaminar astrocytes in layer I of the human cortex are currently unknown. Here, we aimed to explore whether there is any morphological remodelling of interlaminar astrocytes in layer I of the temporal cortex in epilepsy. METHODS: Tissues were obtained from 17 epilepsy surgery patients and 17 post-mortem age-matched controls. In addition, 10 Alzheimer's disease (AD) patients and 10 age-matched controls were used as the disease control group. Paraffin sections (6 µm) and frozen sections (35 or 150 µm) of inferior temporal gyrus tissue were used for immunohistochemistry. With the use of tissue transparency, 3D reconstruction and hierarchical clustering, we performed a quantitative morphological analysis of astrocytes. RESULTS: Upper and lower zones were identified in layer I of the human cortex. Compared with the astrocytes in layers IV-V, layer I interlaminar astrocytes occupied a significantly smaller volume and exhibited shorter and fewer process intersections. Increased Chaslin's gliosis (consisting of types I and II subpial interlaminar astrocytes) and number of glial fibrillary acidic protein (GFAP)-immunoreactive interlaminar astrocytes in layer I of the temporal cortex were confirmed in patients with epilepsy. There was no difference in the number of interlaminar astrocytes in layer I between AD and age-matched control groups. Using tissue transparency and 3D reconstruction technology, the astrocyte domain in the human temporal cortex was classified into four clusters, among which the interlaminar astrocytes in cluster II were more abundant in epilepsy, showing specific topological structures in patients with epilepsy. Furthermore, there was a significant increase in the astrocyte domain of interlaminar cells in layer I of the temporal cortex in patients with epilepsy. CONCLUSION: The observed significant astrocytic structural remodelling in the temporal cortex of epilepsy patients showed that the astrocyte domain in layer I may play an important role in temporal lobe epilepsy.

Neuroprotective effect of a Keap1-Nrf2 Protein-Protein Inter-action inhibitor on cerebral Ischemia/Reperfusion injury.

Oxidative stress has been confirmed to be closely related to the occurrence and development of cerebral ischemic/reperfusion (I/R). The Keap1-Nrf2 pathway is widely recognized as a defensive system to maintain cellular redox homeostasis. Targeting Keap1-Nrf2 interaction by small molecules to release Nrf2 should be a promising strategy to treat cerebral I/R injury. The piperazinyl-naphthalenesulfonamide 6 K was reported to be a Keap1-Nrf2 protein-protein interaction inhibitor, showing promising antioxidative effect. Herein, this study is to investigate whether 6 K could prevent brain from I/R injury. The related mechanism of oxidative stress was also elucidated using in vivo mice middle cerebral artery occlusion (MCAO) model and in vitro SH-SY5Y oxygen-glucose deprivation/reperfusion (OGD/R) model. The results indicated that treatment of 6 K markedly decreased infarct volume, apoptotic neurons and oxidative damage and promoted neurologic recovery in vivo. The cell model revealed that the reactive oxygen species (ROS) was decreased, and cell viability was increased. Western blots and immunofluorescence staining demonstrated that compound treatment promoted Nrf2 release and nuclear translocation. The downstream protective enzymes were significantly enhanced at both in vivo and in vitro levels. Collectively, 6 K is a promising protective agent against cerebral I/R injury through activation of Nrf2 to suppress oxidative stress.

Deep learning and radiomics based automatic diagnosis of hippocampal sclerosis.

Accurate and rapid segmentation of the hippocampus can help doctors perform intractable temporal lobe epilepsy (TLE) preoperative evaluations to identify good surgical candidates. This study aims to establish a radiomics system for the automatic diagnosis of hippocampal sclerosis with the help of machine learning. A total of 240 cases were analysed to develop a diagnostic model. First, an automatic hippocampal segmentation process was established that exploits a priori knowledge of the relatively fixed location of the hippocampus in brain partitions, as well as a deep-learning segmentation network based on an Attention U-net. Then, we extracted 527 radiomics features from each side of the segmented hippocampus. The iterative sparse representation based on feature selection and a support vector machine classifier were finally used to establish the diagnostic model of hippocampal sclerosis. The diagnostic model consists of two consecutive steps: distinguish hippocampal sclerosis (HS) from normal control (NC) and detect whether the HS is located on the left or right side. When the automatic diagnosis model identified HS and NC, the sensitivity and specificity reached 0.941 and 0.917 in the 10-fold cross-validation set and 0.920 and 0.909 in the independent testing set. When the diagnostic model detected HS lateralization, the sensitivity and specificity reached 0.923 and 0.920 in cross-validation and 0.909 and 0.929 in independent testing. Our results show that the developed radiomics model can help detect TLE patients with hippocampal sclerosis and has the potential to simplify preoperative evaluations and select surgical candidates.

Noninvasive molecular diagnosis of craniopharyngioma with MRI-based radiomics approach.

BACKGROUND: Frequent somatic mutations of BRAF and CTNNB1 were identified in both histological subtypes of craniopharyngioma (adamantinomatous and papillary) which shed light on target therapy to cure this oncogenic disease. The aim of this study was to investigate the noninvasive MRI-based radiomics diagnosis to detect BRAF and CTNNB1 mutations in craniopharyngioma patients. METHODS: Forty-four patients pathologically diagnosed as adamantinomatous craniopharyngioma (ACP) or papillary craniopharyngioma (PCP) were retrospectively studied. High-throughput features were extracted from manually segmented tumors in MR images of each case. The modifications-robustness in region of interests and Random Forest-based feature selection methods were adopted to select the most significant features. Random forest classifier with 10-fold cross-validation was applied to build our radiomics model. RESULTS: Four features were selected to make pathological diagnosis between ACP and PCP with area under the receiver operating characteristic curve (AUC) of 0.89, accurancy (ACC) of 0.86, sensitivity (SENS) of 0.89 and specificity (SPEC) of 0.85. The other two features were applied to estimate BRAF V600E mutation with AUC of 0.91, ACC of 0.93, SENS of 0.83 and SPEC of 0.97. Accurate predication of CTNNB1 mutation by three selected features was realized with AUC of 0.93, ACC of 0.86, SENS of 0.86 and SPEC of 0.86. CONCLUSIONS: We developed a reliable MRI-based radiomics approach to perform pathological and molecular diagnosis in craniopharyngioma patients with considerably accurate prediction, which could offer potential guidance for clinical decision-making.

Identification of FXYD6 as the novel biomarker for glioma based on differential expression and DNA methylation.

OBJECTIVE: As a single-transmembrane protein of the FXYD family, FXYD6 plays different roles under physiological and pathological status, especially in the nervous system. This study aims to identify FXYD6 as a biomarker for glioma, by analyzing its expression and methylation patterns. METHODS: Using TCGA and GTEx datasets, we analyzed FXYD6 expression in various tissues, confirming its levels in normal brain and different glioma grades via immunoblotting and immunostaining. FXYD6 biological functions were explored through enrichment analysis, and tumor immune infiltration was assessed using ESTIMATE and TIMER algorithms. Pearson correlation analysis probed FXYD6 associations with biological function-related genes. A glioma detection model was developed using FXYD6 methylation data from TCGA and GEO. Consistently, a FXYD6 methylation-based prognostic model was constructed for glioma via LASSO Cox regression. RESULTS: FXYD6 was observed to be downregulated in GBM and implicated in a range of cellular functions, including synapse formation, cell junctions, immune checkpoint, ferroptosis, EMT, and pyroptosis. Hypermethylation of specific FXYD6 CpG sites in gliomas was identified, which could be used to build a diagnostic model. Additionally, FXYD6 methylation-based prognostic model could serve as an independent factor as well. CONCLUSIONS: FXYD6 is a promising biomarker for the diagnosis and prognosis of glioma, with its methylation-based prognostic model serving as an independent factor. This highlights its potential in clinical application for glioma management.

Guiding Epilepsy Surgery with an LRP1-Targeted SPECT/SERRS Dual-Mode Imaging Probe.

Accurate identification of the resectable epileptic lesion is a precondition of operative intervention to drug-resistant epilepsy (DRE) patients. However, even when multiple diagnostic modalities are combined, epileptic foci cannot be accurately identified in ∼30% of DRE patients. Inflammation-associated low-density lipoprotein receptor-related protein-1 (LRP1) has been validated to be a surrogate target for imaging epileptic foci. Here, we reported an LRP1-targeted dual-mode probe that is capable of providing comprehensive epilepsy information preoperatively with SPECT imaging while intraoperatively delineating epileptic margins in a sensitive high-contrast manner with surface-enhanced resonance Raman scattering (SERRS) imaging. Notably, a novel and universal strategy for constructing self-assembled monolayer (SAM)-based Raman reporters was proposed for boosting the sensitivity, stability, reproducibility, and quantifiability of the SERRS signal. The probe showed high efficacy to penetrate the blood-brain barrier. SPECT imaging showed the probe could delineate the epileptic foci clearly with a high target-to-background ratio (4.11 ± 0.71, 2 h). Further, with the assistance of the probe, attenuated seizure frequency in the epileptic mouse models was achieved by using SPECT together with Raman images before and during operation, respectively. Overall, this work highlights a new strategy to develop a SPECT/SERRS dual-mode probe for comprehensive epilepsy surgery that can overcome the brain shift by the co-registration of preoperative SPECT and SERRS intraoperative images.

Automated intraoperative central sulcus localization and somatotopic mapping using median nerve stimulation.

Objective. Accurate identification of functional cortical regions is essential in neurological resection. The central sulcus (CS) is an important landmark that delineates functional cortical regions. Median nerve stimulation (MNS) is a standard procedure to identify the position of the CS intraoperatively. In this paper, we introduce an automated procedure that uses MNS to rapidly localize the CS and create functional somatotopic maps.Approach. We recorded electrocorticographic signals from 13 patients who underwent MNS in the course of an awake craniotomy. We analyzed these signals to develop an automated procedure that determines the location of the CS and that also produces functional somatotopic maps.Main results. The comparison between our automated method and visual inspection performed by the neurosurgeon shows that our procedure has a high sensitivity (89%) in identifying the CS. Further, we found substantial concordance between the functional somatotopic maps generated by our method and passive functional mapping (92% sensitivity).Significance. Our automated MNS-based method can rapidly localize the CS and create functional somatotopic maps without imposing additional burden on the clinical procedure. With additional development and validation, our method may lead to a diagnostic tool that guides neurosurgeons and reduces postoperative morbidity in patients undergoing resective brain surgery.

Neural excitatory rebound induced by valproic acid may predict its inadequate control of seizures.

BACKGROUND: Valproic acid (VPA) represents one of the most efficient antiseizure medications (ASMs) for both general and focal seizures, but some patients may have inadequate control by VPA monotherapy. In this study, we aimed to verify the hypothesis that excitatory dynamic rebound induced by inhibitory power may contribute to the ineffectiveness of VPA therapy and become a predictor of post-operative inadequate control of seizures. METHODS: Awake craniotomy surgeries were performed in 16 patients with intro-operative high-density electrocorticogram (ECoG) recording. The relationship between seizure control and the excitatory rebound was further determined by diagnostic test and univariate analysis. Thereafter, kanic acid (KA)-induced epileptic mouse model was used to confirm that its behavior and neural activity would be controlled by VPA. Finally, a computational simulation model was established to verify the hypothesis. FINDINGS: Inadequate control of seizures by VPA monotherapy and post-operative status epilepticus are closely related to a significant excitatory rebound after VPA injection (rebound electrodes≧5/64, p = 0.008), together with increased synchronization of the local field potential (LFP). In addition, the neural activity in the model mice showed a significant rebound on spike firing (53/77 units, 68.83%). The LFP increased the power spectral density in multiple wavebands after VPA injection in animal experiments (p < 0.001). Computational simulation experiments revealed that inhibitory power-induced excitatory rebound is an intrinsic feature in the neural network. INTERPRETATION: Despite the limitations, we provide evidence that inadequate control of seizures by VPA monotherapy could be associated with neural excitatory rebounds, which were predicted by intraoperative ECoG analysis. Combined with the evidence from computational models and animal experiments, our findings suggested that ineffective ASMs may be because of the excitatory rebound, which is mediated by increased inhibitory power. FUNDING: This work was supported by National Natural Science Foundation of China (62127810, 81970418), Shanghai Municipal Science and Technology Major Project (2018SHZDZX03) and ZJLab; Science and Technology Commission of Shanghai Municipality (18JC1410403, 19411969000, 19ZR1477700, 20Z11900100); MOE Frontiers Center for Brain Science; Shanghai Key Laboratory of Health Identification and Assessment (21DZ2271000); Shanghai Shenkang (SHDC2020CR3073B).

A functional assembly framework based on implementable neurobionic material.

Neurobionic material is an emerging field in material and translational science. For material design, much focus has already been transferred from von Neumann architecture to the neuromorphic framework. As it is impractical to reconstruct the real neural tissue solely from materials, it is necessary to develop a feasible neurobionics framework to realize advanced brain function. In this study, we proposed a mathematical neurobionic material model, and attempted to explore advanced function only by simple and feasible structures. Here an equivalent simplified framework was used to describe the dynamics expressed in an equation set, while in vivo study was performed to verify simulation results. In neural tissue, the output of neurobionic material was characterized by spike frequency, and the stability is based on the excitatory/inhibitory proportion. Spike frequency in mathematical neurobionic material model can spontaneously meet the solution of a nonlinear equation set. Assembly can also evolve into a certain distribution under different stimulations, closely related to decision making. Short-term memory can be formed by coupling neurobionic material assemblies. In vivo experiments further confirmed predictions in our mathematical neurobionic material model. The property of this neural biomimetic material model demonstrates its intrinsic neuromorphic computational ability, which should offer promises for implementable neurobionic device design.

Reorganization of auditory-visual network interactions in long-term unilateral postlingual hearing loss.

Long-term unilateral hearing loss could reorganize the functional network association between the bilateral auditory cortices, while alterations of other functional networks need to be further explored. We attempted to investigate the pattern of the reorganization of functional network associations between the auditory and visual cortex caused by long-term postlingual unilateral hearing loss (UHI) and its relationship with clinical characteristics. Therefore, 48 patients with hearing loss caused by unilateral acoustic tumors and 52 matched healthy controls were enrolled, and their high-resolution structural MRI and resting-state functional MRI data were also collected to depict the brain network. Degree centrality (DC) was employed to evaluate the functional network association of the auditory-visual network interaction. Group comparisons were performed to investigate the network reorganization, and its correlations with clinical data were calculated. Compared with the healthy control group, patients with UHI showed significantly increased DC between the auditory network (superior temporal gyrus and the medial geniculate body) and the visual network. Meanwhile, this difference was positively correlated with the extent of hearing impairment, and the correlation was more significant with the ipsilateral superior temporal gyrus in cases of acoustic neuroma. These results suggest that long-term unilateral hearing impairment may lead to enhancement of the visual-auditory network interactions and that the degree of reorganization is positively correlated with the pure tone average (PTA) and is more significant for the ipsilateral superior temporal gyrus, which provides clinical evidence regarding cross-modal plasticity in the UHI and its lateralization.