Role of the globus pallidus in motor and non-motor symptoms of Parkinson's disease.

The globus pallidus plays a pivotal role in the basal ganglia circuit. Parkinson's disease is characterized by degeneration of dopamine-producing cells in the substantia nigra, which leads to dopamine deficiency in the brain that subsequently manifests as various motor and non-motor symptoms. This review aims to summarize the involvement of the globus pallidus in both motor and non-motor manifestations of Parkinson's disease. The firing activities of parvalbumin neurons in the medial globus pallidus, including both the firing rate and pattern, exhibit strong correlations with the bradykinesia and rigidity associated with Parkinson's disease. Increased beta oscillations, which are highly correlated with bradykinesia and rigidity, are regulated by the lateral globus pallidus. Furthermore, bradykinesia and rigidity are strongly linked to the loss of dopaminergic projections within the cortical-basal ganglia-thalamocortical loop. Resting tremors are attributed to the transmission of pathological signals from the basal ganglia through the motor cortex to the cerebellum-ventral intermediate nucleus circuit. The cortico-striato-pallidal loop is responsible for mediating pallidi-associated sleep disorders. Medication and deep brain stimulation are the primary therapeutic strategies addressing the globus pallidus in Parkinson's disease. Medication is the primary treatment for motor symptoms in the early stages of Parkinson's disease, while deep brain stimulation has been clinically proven to be effective in alleviating symptoms in patients with advanced Parkinson's disease, particularly for the movement disorders caused by levodopa. Deep brain stimulation targeting the globus pallidus internus can improve motor function in patients with tremor-dominant and non-tremor-dominant Parkinson's disease, while deep brain stimulation targeting the globus pallidus externus can alter the temporal pattern of neural activity throughout the basal ganglia-thalamus network. Therefore, the composition of the globus pallidus neurons, the neurotransmitters that act on them, their electrical activity, and the neural circuits they form can guide the search for new multi-target drugs to treat Parkinson's disease in clinical practice. Examining the potential intra-nuclear and neural circuit mechanisms of deep brain stimulation associated with the globus pallidus can facilitate the management of both motor and non-motor symptoms while minimizing the side effects caused by deep brain stimulation.

Classifying disorders of consciousness using a novel dual-level and dual-modal graph learning model.

BACKGROUND: Disorders of consciousness (DoC) are a group of conditions that affect the level of awareness and communication in patients. While neuroimaging techniques can provide useful information about the brain structure and function in these patients, most existing methods rely on a single modality for analysis and rarely account for brain injury. To address these limitations, we propose a novel method that integrates two neuroimaging modalities, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), to enhance the classification of subjects into different states of consciousness. METHOD AND RESULTS: The main contributions of our work are threefold: first, after constructing a dual-model individual graph using functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), we introduce a brain injury mask mechanism that consolidates damaged brain regions into a single graph node, enhancing the modeling of brain injuries and reducing deformation effects. Second, to address over-smoothing, we construct a dual-level graph that dynamically construct a population-level graph with node features from individual graphs, to promote the clustering of similar subjects while distinguishing dissimilar ones. Finally, we employ a subgraph exploration model with task-fMRI data to validate the interpretability of our model, confirming that the selected brain regions are task-relevant in cognition. Our experimental results on data from 89 healthy participants and 204 patients with DoC from Huashan Hospital, Fudan University, demonstrate that our method achieves high accuracy in classifying patients into unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), or normal conscious state, outperforming current state-of-the-art methods. The explainability results of our method identified a subset of brain regions that are important for consciousness, such as the default mode network, the salience network, the dorsal attention network, and the visual network. Our method also revealed the relationship between brain networks and language processing in consciousness, and showed that language-related subgraphs can distinguish MCS from UWS patients. CONCLUSION: We proposed a novel graph learning method for classifying DoC based on fMRI and DTI data, introducing a brain injury mask mechanism to effectively handle damaged brains. The classification results demonstrate the effectiveness of our method in distinguishing subjects across different states of consciousness, while the explainability results identify key brain regions relevant to this classification. Our study provides new evidence for the role of brain networks and language processing in consciousness, with potential implications for improving the diagnosis and prognosis of patients with DoC.

Plasma alpha B crystallin as potential biomarker for predicting pre-operative seizures in glioma.

PURPOSE: Glioma-associated epilepsy affects a significant proportion of glioma patients, contributing to disease progression and diminished survival rates. However, the lack of a reliable preoperative seizure predictor hampers effective surgical planning. This study investigates the potential of Alpha B crystallin protein (CRYAB) plasma levels as a predictive biomarker for epilepsy seizures in glioma patients. METHODS: Plasma samples were obtained from 75 participants, including 21 glioma patients with pre-operative epilepsy, 14 glioma patients without pre-operative epilepsy, and 21 age- and sex-matched control subjects. Additionally, 11 idiopathic epilepsy patients and 8 intractable epilepsy patients served as positive disease control groups. The study utilized ELISA to accurately quantify the circulating levels of CRYAB in the plasma samples of all participants. RESULTS: The analysis revealed a significant reduction in plasma CRYAB levels in glioma patients with pre-operative epilepsy and idiopathic epilepsy. The receiver operating characteristic (ROC) curve analysis displayed an impressive performance, indicating an AUC of 0.863 (95% CI, 0.810-0.916) across the entire patient cohort. Furthermore, plasma CRYAB levels exhibited a robust diagnostic capability, with an AUC of 0.9135, a sensitivity of 100.0%, and a specificity of 73.68%, effectively distinguishing glioma patients with preoperative epilepsy from those without epilepsy. The Decision Curve Analysis (DCA) underscored the clinical relevance of plasma CRYAB levels in predicting pre-operative epilepsy in glioma. CONCLUSION: The findings imply that the reduced levels of CRYAB may assist in prediction of seizure occurrence in glioma patients, although future large-scale prospective studies are warranted.

Comprehensive analysis reveals that LTBR is a immune-related biomarker for glioma.

Glioma is a common malignant brain tumor with great heterogeneity and huge difference in clinical outcomes. Although lymphotoxin (LT) beta receptor (LTBR) has been linked to immune system and response development for decades, the expression and function in glioma have not been investigated. To confirm the expression profile of LTBR, integrated RNA-seq data from glioma and normal brain tissues were analyzed. Functional enrichment analysis, TMEscore analysis, immune infiltration, the correlation of LTBR with immune checkpoints and ferroptosis, and scRNAseq data analysis in gliomas were in turn performed, which pointed out that LTBR was pertinent to immune functions of macrophages in gliomas. In addition, after being trained and validated in the tissue samples of the integrated dataset, an LTBR DNA methylation-based prediction model succeeded to distinguish gliomas from non-gliomas, as well as the grades of glioma. Moreover, by virtue of the candidate LTBR CpG sites, a prognostic risk-score model was finally constructed to guide the chemotherapy, radiotherapy, and immunotherapy for glioma patients. Taken together, LTBR is closely correlated with immune functions in gliomas, and LTBR DNA methylation could serve as a biomarker for diagnosis and prognosis of gliomas.

Role of HCN channels in the functions of basal ganglia and Parkinson's disease.

Parkinson's disease (PD) is a motor disorder resulting from dopaminergic neuron degeneration in the substantia nigra caused by age, genetics, and environment. The disease severely impacts a patient's quality of life and can even be life-threatening. The hyperpolarization-activated cyclic nucleotide-gated (HCN) channel is a member of the HCN1-4 gene family and is widely expressed in basal ganglia nuclei. The hyperpolarization-activated current mediated by the HCN channel has a distinct impact on neuronal excitability and rhythmic activity associated with PD pathogenesis, as it affects the firing activity, including both firing rate and firing pattern, of neurons in the basal ganglia nuclei. This review aims to comprehensively understand the characteristics of HCN channels by summarizing their regulatory role in neuronal firing activity of the basal ganglia nuclei. Furthermore, the distribution and characteristics of HCN channels in each nucleus of the basal ganglia group and their effect on PD symptoms through modulating neuronal electrical activity are discussed. Since the roles of the substantia nigra pars compacta and reticulata, as well as globus pallidus externus and internus, are distinct in the basal ganglia circuit, they are individually described. Lastly, this investigation briefly highlights that the HCN channel expressed on microglia plays a role in the pathological process of PD by affecting the neuroinflammatory response.

sTBI-GAN: An adversarial learning approach for data synthesis on traumatic brain segmentation.

Automatic brain segmentation of magnetic resonance images (MRIs) from severe traumatic brain injury (sTBI) patients is critical for brain abnormality assessments and brain network analysis. Construction of sTBI brain segmentation model requires manually annotated MR scans of sTBI patients, which becomes a challenging problem as it is quite impractical to implement sufficient annotations for sTBI images with large deformations and lesion erosion. Data augmentation techniques can be applied to alleviate the issue of limited training samples. However, conventional data augmentation strategies such as spatial and intensity transformation are unable to synthesize the deformation and lesions in traumatic brains, which limits the performance of the subsequent segmentation task. To address these issues, we propose a novel medical image inpainting model named sTBI-GAN to synthesize labeled sTBI MR scans by adversarial inpainting. The main strength of our sTBI-GAN method is that it can generate sTBI images and corresponding labels simultaneously, which has not been achieved in previous inpainting methods for medical images. We first generate the inpainted image under the guidance of edge information following a coarse-to-fine manner, and then the synthesized MR image is used as the prior for label inpainting. Furthermore, we introduce a registration-based template augmentation pipeline to increase the diversity of the synthesized image pairs and enhance the capacity of data augmentation. Experimental results show that the proposed sTBI-GAN method can synthesize high-quality labeled sTBI images, which greatly improves the 2D and 3D traumatic brain segmentation performance compared with the alternatives. Code is available at .

Shared and malignancy-specific functional plasticity of dynamic brain properties for patients with left frontal glioma.

The time-varying brain activity may parallel the disease progression of cerebral glioma. Assessment of brain dynamics would better characterize the pathological profile of glioma and the relevant functional remodeling. This study aims to investigate the dynamic properties of functional networks based on sliding-window approach for patients with left frontal glioma. The generalized functional plasticity due to glioma was characterized by reduced dynamic amplitude of low-frequency fluctuation of somatosensory networks, reduced dynamic functional connectivity between homotopic regions mainly involving dorsal attention network and subcortical nuclei, and enhanced subcortical dynamic functional connectivity. Malignancy-specific functional remodeling featured a chaotic modification of dynamic amplitude of low-frequency fluctuation and dynamic functional connectivity for low-grade gliomas, and attenuated dynamic functional connectivity of the intrahemispheric cortico-subcortical connections and reduced dynamic amplitude of low-frequency fluctuation of the bilateral caudate for high-grade gliomas. Network dynamic activity was clustered into four distinct configuration states. The occurrence and dwell time of the weakly connected state were reduced in patients' brains. Support vector machine model combined with predictive dynamic features achieved an averaged accuracy of 87.9% in distinguishing low- and high-grade gliomas. In conclusion, dynamic network properties are highly predictive of the malignant grade of gliomas, thus could serve as new biomarkers for disease characterization.

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.

Rapid intraoperative multi-molecular diagnosis of glioma with ultrasound radio frequency signals and deep learning.

BACKGROUND: Molecular diagnosis is crucial for biomarker-assisted glioma resection and management. However, some limitations of current molecular diagnostic techniques prevent their widespread use intraoperatively. With the unique advantages of ultrasound, this study developed a rapid intraoperative molecular diagnostic method based on ultrasound radio-frequency signals. METHODS: We built a brain tumor ultrasound bank with 169 cases enrolled since July 2020, of which 43483 RF signal patches from 67 cases with a pathological diagnosis of glioma were a retrospective cohort for model training and validation. IDH1 and TERT promoter (TERTp) mutations and 1p/19q co-deletion were detected by next-generation sequencing. We designed a spatial-temporal integration model (STIM) to diagnose the three molecular biomarkers, thus establishing a rapid intraoperative molecular diagnostic system for glioma, and further analysed its consistency with the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5). We tested STIM in 16-case prospective cohorts, which contained a total of 10384 RF signal patches. Two other RF-based classical models were used for comparison. Further, we included 20 cases additional prospective data for robustness test (ClinicalTrials.govNCT05656053). FINDINGS: In the retrospective cohort, STIM achieved a mean accuracy and AUC of 0.9190 and 0.9650 (95% CI, 0.94-0.99) respectively for the three molecular biomarkers, with a total time of 3 s and a 96% match to WHO CNS5. In the prospective cohort, the diagnostic accuracy of STIM is 0.85 ± 0.04 (mean ± SD) for IDH1, 0.84 ± 0.05 for TERTp, and 0.88 ± 0.04 for 1p/19q. The AUC is 0.89 ± 0.02 (95% CI, 0.84-0.94) for IDH1, 0.80 ± 0.04 (95% CI, 0.71-0.89) for TERTp, and 0.85 ± 0.06 (95% CI, 0.73-0.98) for 1p/19q. Compared to the second best available method based on RF signal, the diagnostic accuracy of STIM is improved by 16.70% and the AUC is improved by 19.23% on average. INTERPRETATION: STIM is a rapid, cost-effective, and easy-to-manipulate AI method to perform real-time intraoperative molecular diagnosis. In the future, it may help neurosurgeons designate personalized surgical plans and predict survival outcomes. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Clinical application of neuromodulation therapy in patients with disorder of consciousness: A pooled analysis of 544 participants.

BACKGROUND: The number of patients with disorders of consciousness (DoC) has increased dramatically with the advancement of intensive care and emergency medicine, which brings tremendous economic burdens and even ethical issues to families and society. OBJECTIVE: To evaluate the effectiveness of neuromodulation therapy for patients with DoC. METHODS: First, we conducted a literature review of individual patient data (IPD) on PubMed, EMBASE, and Cochrane-controlled trials following PRISMA guidelines. Then, we collected neuromodulation cases from our institution. Finally, we conducted a pooled analysis using the participants from the medical literature (n = 522) and our local institutions (n = 22). RESULTS: In this pooled analysis of 544 patients with DoC with a mean age of 46.33 years, our results revealed that patients have improved CRS-R scores [1.0 points (95% CI, 0.57-1.42)] after neuromodulation. Among them, patients have better effectiveness in traumatic than non-traumatic etiology (P < 0.05). The effectiveness of consciousness improvement could be affected by the age, baseline consciousness state, and duration of stimulation. Compared with non-invasive intervention, an invasive intervention can bring more behavioral improvement (P < 0.0001) to MCS rather than UWS/VS patients. Importantly, neuromodulation is a valuable therapy even years after the onset of DoC. CONCLUSION: This pooled analysis spotlights that the application of neuromodulation can improve the behavioral performance of patients with DoC. A preliminary trend is that age, etiology, baseline consciousness state, and stimulation duration could impact its effectiveness.

RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation.

Medical image segmentation methods are generally designed as fully-supervised to guarantee model performance, which requires a significant amount of expert annotated samples that are high-cost and laborious. Semi-supervised image segmentation can alleviate the problem by utilizing a large number of unlabeled images along with limited labeled images. However, learning a robust representation from numerous unlabeled images remains challenging due to potential noise in pseudo labels and insufficient class separability in feature space, which undermines the performance of current semi-supervised segmentation approaches. To address the issues above, we propose a novel semi-supervised segmentation method named as Rectified Contrastive Pseudo Supervision (RCPS), which combines a rectified pseudo supervision and voxel-level contrastive learning to improve the effectiveness of semi-supervised segmentation. Particularly, we design a novel rectification strategy for the pseudo supervision method based on uncertainty estimation and consistency regularization to reduce the noise influence in pseudo labels. Furthermore, we introduce a bidirectional voxel contrastive loss in the network to ensure intra-class consistency and inter-class contrast in feature space, which increases class separability in the segmentation. The proposed RCPS segmentation method has been validated on two public datasets and an in-house clinical dataset. Experimental results reveal that the proposed method yields better segmentation performance compared with the state-of-the-art methods in semi-supervised medical image segmentation. The source code is available at https://github.com/hsiangyuzhao/RCPS.

Quantitative analysis using intraoperative contrast-enhanced ultrasound in adult-type diffuse gliomas with isocitrate dehydrogenase mutations: association between hemodynamics and molecular features.

PURPOSE: The relationship between contrast-enhanced ultrasound (CEUS) hemodynamics and the molecular biomarkers of adult-type diffuse gliomas, particularly isocitrate dehydrogenase (IDH), remains unclear. This study was conducted to provide a comprehensive description of the vascularization of adult-type diffuse gliomas using quantitative indicators. Additionally, it was designed to identify any variables with the potential to intraoperatively predict IDH mutation status. METHODS: This prospective study enrolled patients with adult-type diffuse gliomas between November 2021 and September 2022. Intraoperative CEUS was performed, and CEUS videos were recorded for 90-second periods. Hemodynamic parameters, including the peak enhancement (PE) difference, were calculated based on the time-intensity curve of the region of interest. A differential analysis was performed on the CEUS parameters with respect to molecular biomarkers and grades. Receiver operating characteristic curves for various parameters were analyzed to evaluate the ability of those parameters to predict IDH mutation status. RESULTS: Sixty patients with adult-type diffuse gliomas were evaluated. All hemodynamic parameters, apart from rising time, demonstrated significant differences between IDH-mutant and IDH-wildtype adult-type diffuse gliomas. The PE difference emerged as the optimal indicator for differentiating between IDH-wildtype and IDH-mutant gliomas, with an area under the curve of 0.958 (95% confidence interval, 0.406 to 0.785). Additionally, the hemodynamic parameters revealed significant differences across both grades and types of adult-type diffuse gliomas. CONCLUSION: Hemodynamic parameters can be used intraoperatively to effectively distinguish between IDHwildtype and IDH-mutant adult-type diffuse gliomas. Additionally, quantitative CEUS equips neurosurgeons with dynamic perfusion information for various types and grades of adult-type diffuse gliomas.

Probing Intrinsic Neural Timescales in EEG with an Information-Theory Inspired Approach: Permutation Entropy Time Delay Estimation (PE-TD).

Time delays are a signature of many physical systems, including the brain, and considerably shape their dynamics; moreover, they play a key role in consciousness, as postulated by the temporo-spatial theory of consciousness (TTC). However, they are often not known a priori and need to be estimated from time series. In this study, we propose the use of permutation entropy (PE) to estimate time delays from neural time series as a more robust alternative to the widely used autocorrelation window (ACW). In the first part, we demonstrate the validity of this approach on synthetic neural data, and we show its resistance to regimes of nonstationarity in time series. Mirroring yet another example of comparable behavior between different nonlinear systems, permutation entropy-time delay estimation (PE-TD) is also able to measure intrinsic neural timescales (INTs) (temporal windows of neural activity at rest) from hd-EEG human data; additionally, this replication extends to the abnormal prolongation of INT values in disorders of consciousness (DoCs). Surprisingly, the correlation between ACW-0 and PE-TD decreases in a state-dependent manner when consciousness is lost, hinting at potential different regimes of nonstationarity and nonlinearity in conscious/unconscious states, consistent with many current theoretical frameworks on consciousness. In summary, we demonstrate the validity of PE-TD as a tool to extract relevant time scales from neural data; furthermore, given the divergence between ACW and PE-TD specific to DoC subjects, we hint at its potential use for the characterization of conscious states.

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.

Ameliorating parkinsonian motor dysfunction by targeting histamine receptors in entopeduncular nucleus-thalamus circuitry.

In Parkinson's disease (PD), reduced dopamine levels in the basal ganglia have been associated with altered neuronal firing and motor dysfunction. It remains unclear whether the altered firing rate or pattern of basal ganglia neurons leads to parkinsonism-associated motor dysfunction. In the present study, we show that increased histaminergic innervation of the entopeduncular nucleus (EPN) in the mouse model of PD leads to activation of EPN parvalbumin (PV) neurons projecting to the thalamic motor nucleus via hyperpolarization-activated cyclic nucleotide-gated (HCN) channels coupled to postsynaptic H2R. Simultaneously, this effect is negatively regulated by presynaptic H3R activation in subthalamic nucleus (STN) glutamatergic neurons projecting to the EPN. Notably, the activation of both types of receptors ameliorates parkinsonism-associated motor dysfunction. Pharmacological activation of H2R or genetic upregulation of HCN2 in EPNPV neurons, which reduce neuronal burst firing, ameliorates parkinsonism-associated motor dysfunction independent of changes in the neuronal firing rate. In addition, optogenetic inhibition of EPNPV neurons and pharmacological activation or genetic upregulation of H3R in EPN-projecting STNGlu neurons ameliorate parkinsonism-associated motor dysfunction by reducing the firing rate rather than altering the firing pattern of EPNPV neurons. Thus, although a reduced firing rate and more regular firing pattern of EPNPV neurons correlate with amelioration in parkinsonism-associated motor dysfunction, the firing pattern appears to be more critical in this context. These results also confirm that targeting H2R and its downstream HCN2 channel in EPNPV neurons and H3R in EPN-projecting STNGlu neurons may represent potential therapeutic strategies for the clinical treatment of parkinsonism-associated motor dysfunction.

Clinical Characteristics of and Treatment Strategy for Hydrocephalus in Patients With Severe Disorders of Consciousness.

Abstract Making an appropriate diagnosis and administering effective treatment for hydrocephalus in patients with severe disorders of consciousness (DOC) remains controversial and difficult. Given that the typical symptoms are usually concealed by the limited behavioral responsiveness of patients with severe DOC, hydrocephalus diagnosis is likely to be missed in the clinic. Even if not, the presence of hydrocephalus may reduce the likelihood of DOC recovery, posing a conundrum for clinicians. From December 2013 to January 2023, the clinical data and therapeutic schedule of hydrocephalus in patients with severe DOC at Huashan Hospital's Neurosurgical Emergency Center were studied retrospectively. Sixty-eight patients (mean age [± SD] 52.53 ± 17.03 years, 35 males and 33 females) with severe DOC were included. The hydrocephalus was discovered after computed tomography (CT) or magnetic resonance imaging (MRI) revealed enlarged ventricles in the patients. During hospitalization, patients underwent a surgical treatment that included a ventriculoperitoneal (V-P) shunt and/or cranioplasty (CP) implantation. Following the surgery, an individualized V-P pressure was established based on the patient's ventricle size and neurological function variation. To account for the improvement in consciousness in patients with severe DOC, Glasgow Coma Scale (GCS) and Coma Recovery Scale-Revised (CRS-R) assessments were performed before and after hydrocephalus treatment. All patients with severe DOC had varying degrees of ventricular enlargement, deformation, and poor brain compliance. Approximately 60.3% (41/68) of them had low- or negative-pressure hydrocephalus (LPH or NegPH). Of the patients, 45.5% (31/68) had a one-stage V-P shunt and CP operation performed concurrently, whereas the remaining 37 patients had a single V-P shunt operation performed independently. Besides two patients with DOC who developed surgical complications, 92.4% (61/66) of the survivors showed an improvement in consciousness after hydrocephalus treatment. In patients with severe DOC, LPH or NegPH was common. Secondary hydrocephalus in patients with DOC had been largely ignored, hampering their neurological rehabilitation. Even months or years after the onset of severe DOC, active treatment of hydrocephalus can significantly improve patients' consciousness and neurological function. This study summarized several evidence-based treatment experiences of hydrocephalus in patients with DOC.

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.

Enhanced brain parcellation via abnormality inpainting for neuroimage-based consciousness evaluation of hydrocephalus patients by lumbar drainage.

Brain network analysis based on structural and functional magnetic resonance imaging (MRI) is considered as an effective method for consciousness evaluation of hydrocephalus patients, which can also be applied to facilitate the ameliorative effect of lumbar cerebrospinal fluid drainage (LCFD). Automatic brain parcellation is a prerequisite for brain network construction. However, hydrocephalus images usually have large deformations and lesion erosions, which becomes challenging for ensuring effective brain parcellation works. In this paper, we develop a novel and robust method for segmenting brain regions of hydrocephalus images. Our main contribution is to design an innovative inpainting method that can amend the large deformations and lesion erosions in hydrocephalus images, and synthesize the normal brain version without injury. The synthesized images can effectively support brain parcellation tasks and lay the foundation for the subsequent brain network construction work. Specifically, the novelty of the inpainting method is that it can utilize the symmetric properties of the brain structure to ensure the quality of the synthesized results. Experiments show that the proposed brain abnormality inpainting method can effectively aid the brain network construction, and improve the CRS-R score estimation which represents the patient's consciousness states. Furthermore, the brain network analysis based on our enhanced brain parcellation method has demonstrated potential imaging biomarkers for better interpreting and understanding the recovery of consciousness in patients with secondary hydrocephalus.

Histamine bidirectionally regulates the intrinsic excitability of parvalbumin-positive neurons in the lateral globus pallidus and promotes motor behaviour.

BACKGROUND AND PURPOSE: Parvalbumin (PV)-positive neurons are a type of neuron in the lateral globus pallidus (LGP) which plays an important role in motor control. The present study investigated the effect of histamine on LGPPV neurons and motor behaviour. EXPERIMENTAL APPROACH: Histamine levels in LGP as well as its histaminergic innervation were determined through brain stimulation, microdialysis, anterograde tracing and immunostaining. Mechanisms of histamine action were detected by immunostaining, single-cell qPCR, whole-cell patch-clamp recording, optogenetic stimulation and CRISPR/Cas9 gene-editing techniques. The effect of histamine on motor behaviour was detected by animal behavioural tests. KEY RESULTS: A direct histaminergic innervation in LGP from the tuberomammillary nucleus (TMN) and a histamine-induced increase in the intrinsic excitability of LGPPV neurons were determined by pharmacological blockade or by genetic knockout of the histamine H1 receptor (H1 R)-coupled TWIK-related potassium channel-1 (TREK-1) and the small-conductance calcium-activated potassium channel (SK3), as well as by activation or overexpression of the histamine H2 receptor (H2 R)-coupled hyperpolarization-activated cyclic nucleotide-gated channel (HCN2). Histamine negatively regulated the STN → LGPGlu transmission in LGPPV neurons via the histamine H3 receptor (H3 R), whereas blockage or knockout of H3 R increased the intrinsic excitability of LGPPV neurons. CONCLUSIONS AND IMPLICATIONS: Our results indicated that the endogenous histaminergic innervation in the LGP can bidirectionally promote motor control by increasing the intrinsic excitability of LGPPV neurons through postsynaptic H1 R and H2 R, albeit its action was negatively regulated by the presynaptic H3 R, thereby suggesting possible role of histamine in motor deficits manifested in Parkinson's disease (PD).