Myasthenia gravis (MG) is an autoimmune disorder characterized by immune dysregulation at the neuromuscular junction. Monocyte-derived dendritic cells (moDCs) are increasingly recognized as key drivers of MG pathogenesis; however, the mechanisms that govern their dysfunction remain incompletely understood. This study integrated human genetics, patient immunophenotyping, and therapeutic evaluation in the experimental autoimmune myasthenia gravis (EAMG) model. Monocytes were isolated and differentiated into moDCs to assess the effects of HMGB1 and its inhibitor, 18α-glycyrrhetinic acid (18α-GA), on the expression profiles, phenotypes, and functions of moDCs. Therapeutic efficacy was further assessed in EAMG using 18α-GA, HMGB1 neutralizing antibody, and adoptive transfer of 18α-GA-induced tolerogenic moDCs. Mendelian randomization (MR) analyses revealed bidirectional causality between MG and moDCs. MG patients exhibited elevated plasma HMGB1 levels and mature phenotypes of moDCs. Mechanistically, HMGB1 activated the IRE1α/XBP1 and NF-κB pathways in moDCs through the engagement of TLR4, thereby inducing endoplasmic reticulum (ER) stress, promoting the activation of moDCs, and driving an imbalance in CD4+ T cell immune responses. Through a multitargeted mechanism of action, 18α-GA effectively inhibited both the IRE1α/XBP1 and NF-κB pathways in moDCs, thereby blunting ER stress and driving the differentiation of moDCs toward tolerogenic phenotypes. The minimal effective dose of 18α-GA alleviated EAMG by counteracting HMGB1-driven, moDC-mediated CD4+ T cell dysfunction, and showed better therapeutic performance compared with HMGB1 neutralizing antibody. Moreover, the adoptive transfer of 18α-GA-induced tolerogenic moDCs was effective in treating EAMG. HMGB1-mediated ER stress reprogrammed moDCs via the IRE1α/XBP1 and NF-κB pathways to promote pathogenic CD4+ T cell responses in MG. Targeting the HMGB1-ER stress axis in moDCs could restore immune balance and represent a promising therapeutic strategy for MG.

Gamma-frequency (40 Hz) flicker stimulation has emerged as a noninvasive approach for modulating Alzheimer's disease (AD)-related pathology, yet the influence of stimulation intensity remains unclear. We examined whether visual 40 Hz stimulation at different light intensities elicits distinct neurobiological effects in 19-24-week-old 3xTg-AD mice. High-intensity stimulation (1100-1500 lux) improved cognitive performance, modulated AMPK/mTOR signaling and autophagy-related markers, reduced neuronal Aβ burden, and preserved synaptic and neuronal integrity in both the primary visual cortex and hippocampus. In contrast, low-intensity stimulation (100-500 lux) primarily induced molecular changes in the primary visual cortex, with limited effects on hippocampal pathology or cognition. Pharmacological inhibition of autophagy with 3-methyladenine attenuated these effects. Together, these findings suggest graded responses to visual 40 Hz stimulation within the tested intensity range and implicate stimulation intensity as a contributing factor to region-specific and cognitive outcomes in early-stage AD models.

At present, the diagnosis of cerebral artery dissection (CeAD) worldwide still relies on imaging findings, making rapid clinical differentiation in the early stages challenging. Our purpose is to explore the distribution characteristics of the cholesterol, high-density lipoprotein, and glucose (CHG) index, triglycerides-glucose (TyG) index, and non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) in patients with CeAD at admission through case–control design, so as to evaluate the potential value of the three indicators in the early identification of acute phase and provide guidance for early clinical identification and timely intervention. We collected data on CeAD patients admitted to Tongji Hospital, Wuhan, China, from March 2015 to September 2025, with non-CeAD intracerebral hemorrhage (ICH) patients as the control group. After 1:1 propensity score matching, 128 samples were retained in each group. Logistic regression analysis was used to analyze the correlation between the three indicators and the presence of CeAD. The identification efficacy and dose–response relationship of each indicator were evaluated by receiver operating characteristic (ROC) curve and restricted cubic spline (RCS) curve, and the net benefit of clinical application of each index was evaluated by decision curve analysis (DCA). The results were expressed as odds ratio (OR) and 95

AIM:This study aimed to assess the associations between particulate matter (PM) exposures and depressive symptom trajectories, as well as the potential contributing role of loneliness in these associations. METHODS:The analysis included 11,758 participants (≥45 years), with depressive symptoms and covariate data from the China Health and Retirement Longitudinal Study (2011-2020) and PM data from the ChinaHighAirPollutants dataset. Depressive symptom trajectories were identified using group-based trajectory modeling. Individual and combined effects of PM on depressive symptom trajectories were assessed using multivariable logistic regression and weighted quantile sum (WQS) regression, with results reported as odds ratio (OR) and 95% confidence interval (CI). A serial multiple mediator model was used to evaluate the contributing role of loneliness. RESULTS:Five depressive symptom trajectories were identified: stable-low, stable-moderate, stable-high, decreasing, and increasing. PM exposures were positively associated with more severe depressive symptom trajectory groups (stable-high [PM10: OR = 1.10, 95% CI 1.04-1.16; WQS: OR = 1.41, 95% CI 1.09-1.82] and increasing [PM1.0: OR = 1.44, 95% CI 1.06-1.98; PM2.5: OR = 1.10, 95% CI 1.02-1.19; PM10: OR = 1.10, 95% CI 1.06-1.13; WQS: OR = 1.21, 95% CI 1.01-1.45]) compared to the stable-low symptoms trajectory. Loneliness contributed to 26.73%-29.73% of the associations between PM exposure and depressive symptom trajectories. CONCLUSION:Exposures to individual and mixed PM pollutants increase the risk of severe depressive symptom trajectory groups, and reducing loneliness alleviates these effects. The findings underscore the need for further coordinated control of PM pollutants and alleviating loneliness to prevent depressive symptoms.

Purpose: There remains a lack of epidemiological data and evidence regarding risk factors for intracranial arterial dissection (IAD) worldwide, making it difficult to make a more timely and accurate clinical diagnosis. We aimed to identify risk factors, clinical and imaging features of spontaneous IAD (sIAD) using a case-control design. Methods: We collected data on sIAD patients admitted to Tongji Hospital in Wuhan, China from June 2017 to June 2024. Non-IAD ischemic stroke (IS) and non-IAD intracerebral hemorrhage (ICH) patients served as control groups. Logistic regression models analyzed the three data sets, with results expressed as odds ratio (OR) and 95% confidence interval (CI). Results: After screening, 71 patients with sIAD, 84 patients with non-IAD IS and 102 patients with non-IAD ICH were included in this study. The findings showed that the participants with diabetes had a lower likelihood of sIAD than non-IAD IS (OR = 0.145, 95%CI = 0.030-0.702). Compared with non-IAD ICH patients, individuals with sIAD had lower systolic blood pressure on admission (OR = 0.941, 95%CI = 0.900-0.983) and less likely to be young (OR = 0.911, 95%CI = 0.855-0.970). Serological data showed that compared with non-IAD ICH patients, elevated triglyceride (OR = 0.326, 95%CI = 0.179-0.594) were associated with the reduced likelihood of sIAD, whereas the opposite was true for uric acid levels (OR = 1.007, 95%CI = 1.000-1.014). In imaging, sIAD patients showed the largest number of arterial lumen dilatation, followed by stenosis with dilatation. Conclusions: Diabetes may be associated with a reduced likelihood of sIAD. Differences in serologic markers may help in the differential diagnosis of sIAD from other cerebrovascular events.

Objective: Conventional brain stimulators primarily rely on implantable batteries, necessitating repeated replacement surgeries. Ultrasound-driven stimulators offer a promising wireless alternative, yet existing systems are predominantly extracranial and face limitations in stability and efficiency. Here, we fabricated a miniaturized, implantable ultrasound-driven intracranial brain stimulator (UIBS), achieving stable and efficient neuromodulation. Methods: The UIBS was developed by integrating a flexible composite structure consisting of PVDF-TrFE and a flexible acoustic matching layer with a rectifier circuit embedded in a PEEK structure. Additionally, transcranial ultrasound transmission was optimized through numerical simulations and experimental validation. Electrical output performance, the electrolysis-defined safety window, and neuromodulation efficacy as well as biocompatibility following UIBS implantation into the rat primary somatosensory cortex were systematically assessed. Results: The optimal transcranial ultrasound frequency was determined to be 1.5 MHz. Driven by transcranial ultrasound at 2 MPa, the UIBS generated a rectified output voltage exceeding 1.3 V, with a safe electrolysis duration exceeding 10 seconds at 100 Hz. Furthermore, in vivo experiments demonstrated that under ultrasound driving, the device can be stably implanted and reliably evoke neural activity in the primary somatosensory cortex, while maintaining good biosafety. Conclusion: This work presents a novel and miniaturized UIBS, enabling effective intracranial energy harvesting and precise neuromodulation, addressing key constraints of battery-dependent and extracranial devices.

Oxidative stress, neuroinflammation, and cellular senescence interact to drive Alzheimer’s disease (AD) progression. SRS11-92 is a redox-active small molecule with reported cytoprotective effects. This study sought to determine whether SRS11-92 mitigates Aβ-evoked oxidative stress and cellular senescence, and to delineate the underlying mechanism. SH-SY5Y cells were challenged with Aβ25-35 and pretreated with SRS11-92. Oxidative stress (ROS, MDA, SOD activity, and GSH), inflammatory mediators (TNF-α, IL-1β, and IL-6), senescence markers (SA-β-gal, p53, p16, and p21), and Nrf2/HO-1/NF-κB proteins were quantified. Pathway dependence was assessed using the selective Nrf2 inhibitor ML385. 3xTg-AD mice received SRS11-92 for 6 weeks; cognitive function was assessed by novel object recognition, cortical neuronal integrity was assessed by Nissl staining, and cellular senescence in the hippocampus was evaluated by SA-β-gal. SRS11-92 attenuated Aβ25-35-induced cytotoxicity in a dose-dependent manner in SH-SY5Y cells, reduced ROS and MDA, and restored SOD activity and GSH. It suppressed TNF-α, IL-1β, and IL-6, decreased the percentage of SA-β-gal-positive cells, and downregulated p53, p16, and p21. Mechanistically, SRS11-92 increased total and nuclear Nrf2 and upregulated HO-1, while restricting NF-κB p65 nuclear translocation. ML385 abrogated these molecular and phenotypic benefits, confirming that SRS11-92 acts via the Nrf2 pathway in vitro. In 3xTg-AD mice, SRS11-92 improved cognitive function, partially rescued cortical Nissl-positive neurons, and reduced the hippocampal SA-β-gal-positive burden. SRS11-92 exerts significant neuroprotective effects, attributable to reducing stress-induced senescence via activating Nrf2/HO-1 and constraining NF-κB signalling.

Carotid ultrasound image segmentation and classification are crucial in assessing the severity of carotid plaques which serve as a major cause of ischemic stroke. Although many methods are employed for carotid plaque segmentation and classification, treating these tasks separately neglects their interrelatedness. Currently, there is limited research exploring the key information of both plaque and background regions, and collecting and annotating extensive segmentation data is a costly and time-intensive task. To address these two issues, we propose an end-to-end semi-supervised multi-task learning network(SML-Net), which can classify plaques while performing segmentation. SML-Net identifies regions by extracting image features and fuses multi-scale features to improve semi-supervised segmentation. SML-Net effectively utilizes plaque and background regions from the segmentation results and extracts features from various dimensions, thereby facilitating the classification task. Our experimental results indicate that SML-Net achieves a plaque classification accuracy of 86.59% and a Dice Similarity Coefficient (DSC) of 82.36%. Compared to the leading single-task network, SML-Net improves DSC by 1.2% and accuracy by 1.84%. Similarly, when compared to the best-performing multi-task network, our method achieves a 1.05% increase in DSC and a 2.15% improvement in classification accuracy.

Iron metabolism plays a vital role in maintaining physiological homeostasis, and its dysregulation is implicated in a range of pathological consequences and illnesses, including Alzheimeru2019s disease (AD). Prior studies have demonstrated that Tau protein and amyloid precursor protein are involved in iron homeostasis disorder. Ferroptosis, an iron-dependent form of regulated cell death, has emerged as a key contributor to AD pathogenesis and a promising therapeutic target. Acyl-CoA synthetase long-chain family 4 (ACSL4) is a lipid metabolizing enzyme that enhances ferroptosis sensitivity by promoting the incorporation of oxidizable polyunsaturated fatty acids into membrane phospholipids. Beyond ferroptosis, ACSL4 also plays crucial roles in neuroinflammation and oxidative stress, which are implicated in AD progression. Therefore, targeting ACSL4 is fantastic and has a lot of promise for treating AD. Nevertheless, the precise mechanisms through which ACSL4 contributes to AD pathology have yet to be fully elucidated. This review reveals a potentially vital role of ACSL4 in AD, focusing on its involvement in ferroptosis, oxidative stress, and neuroinflammation. Additionally, we describe some natural and synthetic compounds targeting ACSL4 with therapeutic potential in AD. Building on the theoretical findings of earlier studies about focused interventions of the ACSL4 path, our evaluation provided a broad basis for the clinical transformation in the treatment of AD strategies.

OBJECTIVES:To estimate the impact of China's volume-based procurement (VBP) policy on the expenditure of both policy-covered and uncovered drugs, and to identify the elements that contribute to drug expenditure changes under VBP policy. METHODS:Using national drug procurement data of public medical institutions, this study included 25 policy-covered VBP drugs and 99 policy-uncovered alternative drugs as samples, seven "4+7" pilot cities and eight "4+7" expansion provinces as observation regions. Time-varying difference-in-difference (DID) model was applied to quantify policy impact on drug expenditures. The drug expenditure index decomposition method was employed to analyze the determinants of drug expenditure changes following VBP policy. RESULTS:The expenditure of VBP drugs significantly decreased by 42.19% after VBP policy (β = -0.55, p < 0.001), while alternative drugs increased by 11.52% (β = -0.11, p < 0.001), with a significant reduction in the overall expenditure of observed drugs (β = -0.05, p < 0.001). The decrease of VBP drug expenditures showed a trend of tertiary hospital (β = -0.64, p < 0.001) > secondary hospital (β = -0.57, p < 0.001) > primary healthcare centers (β = -0.39, p < 0.001). The index decomposition showed that manufacturer structure index (IM) decline was the primary driver for expenditure reduction of policy-covered drugs, with the IM decrease of 54.17% in pilot cities and 40.86% in expansion regions. The secondary driver was the price index (IP), with a decline of 31.68% in pilot cities and 36.08% in expansion regions. The restraining factor was the quantity index (IQ), increasing by 92.54% in pilot cities and 52.04% in expansion regions. IQ also drove the increase in alternative drug expenditures, increasing by 95.56% in pilot cities and 32.76% in expansion regions. CONCLUSION:VBP policy effectively promoted the decline of total drug expenditures, primarily through manufacturer-level market displacement and the absolute price reduction. However, the "spillover effect" of alternative drugs weakened the overall effect on cost control. Strengthening holistic governance and improving the quality and intensiveness of drug use are important directions for future policy perfection.

Iron metabolism plays a vital role in maintaining physiological homeostasis, and its dysregulation is implicated in a range of pathological consequences and illnesses, including Alzheimer's disease (AD). Prior studies have demonstrated that Tau protein and amyloid precursor protein are involved in iron homeostasis disorder. Ferroptosis, an iron-dependent form of regulated cell death, has emerged as a key contributor to AD pathogenesis and a promising therapeutic target. Acyl-CoA synthetase long-chain family 4 (ACSL4) is a lipid metabolizing enzyme that enhances ferroptosis sensitivity by promoting the incorporation of oxidizable polyunsaturated fatty acids into membrane phospholipids. Beyond ferroptosis, ACSL4 also plays crucial roles in neuroinflammation and oxidative stress, which are implicated in AD progression. Therefore, targeting ACSL4 is fantastic and has a lot of promise for treating AD. Nevertheless, the precise mechanisms through which ACSL4 contributes to AD pathology have yet to be fully elucidated. This review reveals a potentially vital role of ACSL4 in AD, focusing on its involvement in ferroptosis, oxidative stress, and neuroinflammation. Additionally, we describe some natural and synthetic compounds targeting ACSL4 with therapeutic potential in AD. Building on the theoretical findings of earlier studies about focused interventions of the ACSL4 path, our evaluation provided a broad basis for the clinical transformation in the treatment of AD strategies.

In recent years, the incidence of neurodegenerative diseases (NDs) has gradually increased over the past decades due to the rapid aging of the global population. Traditional research has had difficulty explaining the relationship between its etiology and unhealthy lifestyle and diets. Emerging evidence had proved that the pathogenesis of neurodegenerative diseases may be related to changes of the gut microbiota’s composition. Metabolism of gut microbiota has insidious and far-reaching effects on neurodegenerative diseases and provides new directions for disease intervention. Here, we delineated the basic relationship between gut microbiota and neurodegenerative diseases, highlighting the metabolism of gut microbiota in neurodegenerative diseases and also focusing on treatments for NDs based on gut microbiota. Our review may provide novel insights for neurodegeneration and approach a broadly applicable basis for the clinical therapies for neurodegenerative diseases.

The phenomenon of growth in drug consumption within the framework of national volume-based procurement (VBP) policy raises speculations about demand release and policy inducing. This study aims to explore the reasons and mechanisms of drug consumption increases following VBP policy from two perspectives. We collected data from the China Drug Supply Information Platform, National Bureau of Statistics and the Joint Procurement Office. Twenty cardiovascular international non-proprietary names (INNs) in the first three VBP batches and 28 observation regions were included, constructing 418 valid INN-region combinations as the unit for analysis. The average monthly consumption volume of VBP cardiovascular drug was assigned as the explained variable. The generalized difference-in-difference method was conducted using the price reduction level and the size of policy assessment task as the policy intensity indicator. Moderating effect model was employed to examine the role of resident’s income level. Increased cardiovascular drug consumption was observed in 285 (68.18

BACKGROUND:Intracerebral hemorrhage (ICH) is a stroke subtype characterized by high mortality and complex post-event complications. Research has extensively covered the acute phase of ICH; however, ICU readmission determinants remain less explored. Utilizing the MIMIC-III and MIMIC-IV databases, this investigation develops machine learning (ML) models to anticipate ICU readmissions in ICH patients. METHODS:Retrospective data from 2242 ICH patients were evaluated using ICD-9 codes. Recursive feature elimination with cross-validation (RFECV) discerned significant predictors of ICU readmissions. Four ML models-AdaBoost, RandomForest, LightGBM, and XGBoost-underwent development and rigorous validation. SHapley Additive exPlanations (SHAP) elucidated the effect of distinct features on model outcomes. RESULTS:ICU readmission rates were 9.6% for MIMIC-III and 10.6% for MIMIC-IV. The LightGBM model, with an AUC of 0.736 (95% CI: 0.668-0.801), surpassed other models in validation datasets. SHAP analysis revealed hydrocephalus, sex, neutrophils, Glasgow Coma Scale (GCS), specific oxygen saturation (SpO2) levels, and creatinine as significant predictors of readmission. CONCLUSION:The LightGBM model demonstrates considerable potential in predicting ICU readmissions for ICH patients, highlighting the importance of certain clinical predictors. This research contributes to optimizing patient care and ICU resource management. Further prospective studies are warranted to corroborate and enhance these predictive insights for clinical utilization.

Background and Objectives: Total Plaque Area (TPA) measurement is critical for early diagnosis and intervention of carotid atherosclerosis in individuals with high risk for stroke. The delineation of the carotid plaques is necessary for TPA measurement, and deep learning methods can automatically segment the plaque and measure TPA from carotid ultrasound images. A large number of labeled images is essential for training a good deep learning model, but it is very difficult to collect such large labeled datasets for carotid image segmentation in clinical practice. Self-supervised learning can provide a possible solution to improve the deep-learning models on small labeled training datasets by designing a pretext task to pre-train the models without using the segmentation masks. However, the existing self-supervised learning methods do not consider the feature presentations of object contours.Methods: In this paper, we propose an image registration-based self-supervised learning method and a stacked U-Net (SSL-SU-Net) for carotid plaque ultrasound image segmentation, which can better exploit the semantic features of carotid plaque contours in self-supervised task training.Results: Our network was trained on different numbers of labeled images (n = 10, 33, 50 and 100 subjects) and tested on 44 subjects from the SPARC dataset (n = 144, London, Canada). The network trained on the entire SPARC dataset was then directly applied to an independent dataset collected in Zhongnan hospital (n = 497, Wuhan, China). For the 44 subjects tested on the SPARC dataset, our method yielded a DSC of 80.25-89.18% and the produced TPA measurements, which were strongly correlated with manual segmentation (r = 0.965-0.995, rho < 0.0001). For the Zhongnan dataset, the DSC was 90.3% and algorithm TPAs were strongly correlated with manual TPAs (r = 0.985, rho < 0.0001).Conclusions: The results demonstrate that our proposed method yielded excellent performance and good generalization ability when trained on a small labeled dataset, facilitating the use of deep learning in carotid ultrasound image analysis and clinical practice. The code of our algorithm is available https://github .com / a610lab /Registration-SSL.

Depression is a prominent contributor to global disability. A growing body of data suggests that depression is associated with the pathophysiology of the medial prefrontal cortex (mPFC), but the underlying mechanisms remain poorly understood. Mice were subjected to chronic restraint stress (CRS) for 3 weeks to create depression models during this investigation. Protein tandem mass tag (TMT) quantification and LC-MS/MS analysis were conducted to examine proteome patterns. Afterwards, to further explore the enrichment of differential proteins and the signaling pathways involved, we annotated these differentially expressed proteins. We confirmed that CRS mice developed depression-like and anxiety-like behaviors. Among the 8081 measured proteins, a total of 15 proteins were found to be differentially expressed. These proteins exhibited functional enrichment in a variety of biological functions, and among these pathways, alterations in synaptic function and autophagy are noteworthy. In addition, we identified a differentially expressed protein called Wnt2b and found that CRS may disrupt synaptic plasticity by affecting the activation of the Wnt2b/β-catenin pathway. Our findings showed depression-like behaviors in the CRS mouse model and molecular alterations in the mPFC, which may help explain the pathogenesis of depression and identify novel antidepressant medication targets. Significance Depression is a prevalent and frequent chronic mental illness and is now a significant contributor to global disability. In this study, we used chronic restraint stress to establish a mouse model of depression, and differentially expressed proteins in the medial prefrontal cortex of depressed model mice were detected by TMT proteomics. Our study verified the presence of altered synaptic function and excessive autophagy in the mPFC of CRS-induced mice from a proteomic perspective. Furthermore, we demonstrated that CRS may disrupt synaptic plasticity by affecting the activation of the Wnt2b/β-catenin pathway, which may be a key link in the pathogenesis of depression and may provide new insights for identifying new antidepressant drug targets.

PURPOSE:Through three neurocritical care unit (NCCU) surveys in China, we tried to understand the development status of neurocritical care and clarify its future development. METHODS:Using a cross-sectional survey method and self-report questionnaires, the number and quality of NCCUs were investigated through three steps: administering the questionnaire, sorting the survey data, and analyzing the survey data. RESULTS:At the second and third surveys, the number of NCCUs (76/112/206) increased by 47% and 84%, respectively. The NCCUs were located in tertiary grade A hospitals or teaching hospitals (65/100/181) in most provinces (24/28/29). The numbers of full-time doctors (359/668/1337) and full-time nurses (904/1623/207) in the NCCUs increased, but the doctor-bed ratio and nurse-bed ratio were still insufficient (0.4:1 and 1.3:1). CONCLUSION:In the past 20 years, the growth rate of NCCUs in China has accelerated, while the allocation of medical staff has been insufficient. Although most NCCU hospital bed facilities and instruments and equipment tend to be adequate, there are obvious defects in some aspects of NCCUs.

Abstract Purpose Spontaneous intracerebral haemorrhage (ICH) is the main presentation in adults with moyamoya disease (MMD), an unusual clinical entity with a poor prognosis. However, optimal management in the acute stage of ICH in patients with MMD remains a challenge. Since minimally invasive surgery (MIS) plus local thrombolysis has emerged as a promising strategy for ICH, we aimed to describe our experience of performing this procedure in this special population in the acute phase, while focusing on its efficacy and safety. Materials and methods The medical data of patients with ICH treated with MIS and local thrombolysis between November 2013 and December 2017 were retrospectively reviewed at our institution. MMD was identified based on the angiographic images. The primary outcome was postoperative intracranial rebleeding. The secondary outcomes were 30-day mortality and 6-month outcome graded using the modified Rankin scale (mRS). Logistic regression was applied to explore independent risk factors for the above outcomes. Results A cohort of consecutive 337 ICH patients was analysed, of whom 14 (4.15%) were diagnosed with MMD. In total, 36 (11.46%) patients experienced postoperative intracranial rehaemorrhage, of which one patient had MMD. No significant difference was found between the patients with and without MMD regarding postoperative rebleeding (9.09% vs. 11.55%, p = 1.000). Additionally, the 30-day mortality of patients with MMD was 21.42% (3/14), which was not significantly different from that of non-MMD patients (10.83%; p = 0.201). Moreover, 53.8% of patients had poor outcomes at the 6-month follow-up among MMD patients, similar to 43.9% of patients without MMD (p = 0.573). The coexistence of MMD failed to show a significant association with postoperative intracranial rebleeding (p = 0.348), 30-day mortality (p = 0.211), or poor outcome at the 6-month follow-up (p = 0.450). Conclusion Our findings suggest that coexistent MMD is not associated with an increased risk of postoperative rebleeding or poor outcome after local thrombolysis for ICH.

Coronavirus disease-2019 (COVID-19) first emerged in late 2019 and has since spread worldwide. More than 600 million people have been diagnosed with COVID-19, and over 6 million have died. Vaccination against COVID-19 is one of the best ways to protect humans. Epilepsy is a common disease, and there are approximately 10 million patients with epilepsy (PWE) in China. However, China has listed "uncontrolled epilepsy" as a contraindication for COVID-19 vaccination, which makes many PWE reluctant to get COVID-19 vaccination, greatly affecting the health of these patients in the COVID-19 epidemic. However, recent clinical practice has shown that although a small percentage of PWE may experience an increased frequency of seizures after COVID-19 vaccination, the benefits of COVID-19 vaccination for PWE far outweigh the risks, suggesting that COVID-19 vaccination is safe and recommended for PWE. Nonetheless, vaccination strategies vary for different PWE, and this consensus provides specific recommendations for PWE to be vaccinated against COVID-19.