BackgroundSome intracranial aneurysms (IAs) still develop in-stent stenosis (ISS) even after successful pipeline embolization device (PED) implantation. ISS increases the risk of retreatment and ischemic complications, thereby affecting the long-term prognosis of IA patients. This study aims to identify predictors for ISS after PED treatment of IAs, and develop a nomogram for assessing individual risk.Materials and MethodsThis analysis included unruptured IA patients treated with PEDs between April 2016 and October 2023 at three institutions. The patients were grouped into the training cohort and validation cohort according to the admission institution. Predictors were identified via least absolute shrinkage and selection operator analysis and multivariable regression analysis. A nomogram was then developed to predict ISS after PED implantation in the training cohort. The area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate the predictive accuracy and clinical value of the nomograms.ResultsA total of 1335 IA patients were included in this study (1049 in the training cohort and 286 in the validation cohort). A total of 139 (13.3%) and 41 (14.3%) patients developed ISS in the training cohort and validation cohort, respectively. A nomogram with five predictors (difference between the proximal and distal parent artery diameters, distal stent-to-vessel diameter ratio, overlapping devices, balloon angioplasty, and dissecting aneurysms) was developed via multivariate logistic regression analysis. AUCs of the nomogram in the training cohort and validation cohort were 0.836 (95%CI, 0.801-0.870) and 0.829 (95%CI, 0.770-0.888), respectively. Calibration curve and DCA analysis confirmed the utility and clinical applicability of this nomogram.ConclusionThis nomogram showed high accuracy and clinical utility in predicting ISS after PED treatment, indicating that the nomogram can guide the identification of high-risk patients and the development of improved treatment strategies.

Cognitive impairment (CI) after aneurysmal subarachnoid hemorrhage (aSAH) is common, but its temporal course and prediction using multimodal data remain unclear. This prospective cohort study assessed time to first-detected CI among survivors eligible for follow-up cognitive testing. CI was defined as an education-adjusted Montreal Cognitive Assessment score <26 at 7 to 24 months after admission. A sensitivity endpoint using MoCA <23 was also examined. First-detected CI-free survival was compared between patients with aSAH and those with unruptured intracranial aneurysms (UIAs). Within the aSAH cohort, six prediction schemes were tested, including core clinical variables alone and clinical variables plus baseline cognition, plasma biomarkers, event-related potentials (ERPs), MRI, or CSF markers. Patients with aSAH had lower 24-month first-detected CI-free survival than patients with UIA, 43.7% vs. 71.4%, with an 8.1-month loss in restricted mean survival time, 95% CI 6.2 to 9.6. They also had a higher hazard of first-detected CI, HR 7.21, 95% CI 3.59 to 14.49. Among the six prediction schemes, only the ERP CP2 pair model met all prespecified performance criteria. In temporal internal validation, this model achieved an AUROC of 0.928 and a Brier score of 0.103. Incremental value was greatest in patients aged ≥60 years and those with Fisher grade 3 to 4. aSAH was associated with earlier CI and substantial loss of CI-free time compared with UIA. An ERP-based model showed the most stable internally validated performance, especially in older patients and those with greater hemorrhagic burden. External multicenter validation is needed before clinical use.

BackgroundArtificial intelligence can help to identify irregular shapes and sizes, crucial for managing unruptured intracranial aneurysms (UIAs). However, existing artificial intelligence tools lack reliable classification of UIA shape irregularity and validation against gold-standard three-dimensional rotational angiography (3DRA). This study aimed to develop and validate a deep-learning model using computed tomography angiography (CTA) for classifying irregular shapes and measuring UIA size.MethodsCTA and 3DRA of UIA patients from a referral hospital were included as a derivation set, with images from multiple medical centers as an external test set. Senior investigators manually measured irregular shape and aneurysm size on 3DRA as the ground truth. Convolutional neural network (CNN) models were employed to develop the CTA-based model for irregular shape classification and size measurement. Model performance for UIA size and irregular shape classification was evaluated by intraclass correlation coefficient (ICC) and area under the curve (AUC), respectively. Junior clinicians’ performance in irregular shape classification was compared before and after using the model.ResultsThe derivation set included CTA images from 307 patients with 365 UIAs. The test set included 305 patients with 350 UIAs. The AUC for irregular shape classification of this model in the test set was 0.87, and the ICC of aneurysm size measurement was 0.92, compared with 3DRA. With the model’s help, junior clinicians’ performance for irregular shape classification was significantly improved (AUC 0.86 before vs 0.97 after, P<0.001).ConclusionThis study provided a deep-learning model based on CTA for irregular shape classification and size measurement of UIAs with high accuracy and external validity. The model can be used to improve reader performance.

Background:Routine health care increasingly requires digital access for appointment scheduling, medication refills, test-result review, clinician messaging, remote monitoring, and telehealth. For older adults with cardiovascular-risk conditions, complete internet disconnection may indicate accumulated geriatric vulnerability and barriers to continuous care. We examined whether complete digital disconnection was associated with mortality or residential-care transition and whether the risk gradient was driven by connectivity rather than telehealth use. Methods:We constructed staggered-entry prospective cohorts using rounds 11-14 of the National Health and Aging Trends Study (2021-2025). Community-dwelling Medicare beneficiaries aged ≥65 years with hypertension, heart disease, or diabetes entered the cohort in round 11, 12, or 13 and were followed through round 14. Digital integration was categorized as telehealth use, connected non-use, or complete disconnection. Outcomes were all-cause mortality and a composite of death or transition to nursing-home or residential care. The primary analysis used survey-weighted discrete-time survival models with entry-cohort fixed effects and participant-level cluster-robust variance estimation. Models were sequentially adjusted for demographic, socioeconomic, health, frailty-related, and geriatric-vulnerability factors. Robustness was assessed using multiple imputation, competing-risks models, E-values, and sensitivity analyses addressing reverse causation. Results:Among 12,139 person-baseline observations from 6,530 adults, the survey-weighted prevalence of complete disconnection was 29.7%. Compared with non-disconnected participants, completely disconnected adults had a higher unadjusted risk of the composite outcome; after adjustment for health and frailty-related factors, the association attenuated but persisted (composite hazard ratio [HR], 1.39; 95% CI, 1.12-1.73; mortality HR, 1.50; 95% CI, 1.16-1.94). The survey-weighted 3-year absolute risk difference was 12.1 percentage points. Telehealth users and connected non-users had similar adjusted risks (composite HR, 0.99; 95% CI, 0.79-1.24). Associations weakened after adjustment for functional status and exclusion of first-interval events. Conclusions:Complete digital disconnection was a reproducible and readily measured prognostic marker of mortality or residential-care transition among older adults with cardiovascular-risk conditions. These findings support a prognostic rather than causal interpretation. Age-friendly digital care should preserve offline-accessible pathways for older adults who remain completely disconnected.

Sudden Cardiac Death (SCD) remains a leading cause of mortality worldwide, with outcomes critically dependent on the effective implementation of the "Chain of Survival" - early recognition, early CPR, early defibrillation, and post-resuscitation care. In regional and pre-hospital settings, systemic fragmentation between emergency dispatch, ambulance services, and hospitals undermines this chain. This study presents the development, implementation, and impact evaluation of an integrated, AI-enabled multi-modal emergency care system designed to strengthen the entire Chain of Survival for SCD in a regional context.: We designed and deployed a system integrating a unified information platform, IoT-enabled devices, point-of-care testing (POCT), and AI-driven clinical decision support. The system was implemented phased across three counties in Anyang, China (population ≈ 2.1 million) from January 2022 to December 2023. We conducted a quasi-experimental before-and-after study using routinely collected emergency medical services (EMS) data. Primary outcomes were median response time (call receipt to scene arrival), pre-hospital STEMI identification rate, and return of spontaneous circulation (ROSC) for out-of-hospital cardiac arrest (OHCA) of cardiac origin. Data from 1,208 emergency cases (pre-implementation: n = 587; post-implementation: n = 621) were analyzed. Interrupted time series (ITS) analysis was performed to control for secular trends. The median emergency response time decreased from 9.8 min (IQR: 7.2-13.1) to 6.7 min (IQR: 5.1-9.0) (P < 0.001). The pre-hospital STEMI identification rate improved from 65% to 90% (p < 0.01). For OHCA of cardiac origin, the ROSC rate increased from 18% to 31% (p < 0.05), representing a 72% relative improvement. ITS analysis confirmed a significant level change for response time (β = -2.8 min, 95% CI: -3.7 to -1.9, P < 0.001) and for ROSC (β = +12% points, 95% CI: +5 to + 19, P = 0.01) immediately following implementation, with no significant pre-existing trends. The AI models demonstrated robust performance during validation (deterioration prediction AUC 0.89; STEMI detection AUC 0.92). The Anyang Model provides evidence that a systematically integrated, AI-driven platform is feasible and temporally associated with substantial improvements in regional emergency care for SCD. While causal attribution requires further validation, this systems-level approach offers a replicable framework that can be adapted to diverse resource settings.

BACKGROUND:Delayed intraparenchymal hemorrhage (DIPH) is a severe complication after pipeline embolization device (PED) deployment for intracranial aneurysms (IAs). However, predictive models are lacking. This study aims to develop and validate a new nomogram to predict DIPH risk in IA patients. METHODS:This retrospective study included 959 IA patients treated with PEDs at three institutions between October 2018 and June 2024. Patients were categorized into a training cohort (n=685) and a validation cohort (n=274). Predictors were identified using the least absolute shrinkage and selection operator and multivariable regression analyses. A nomogram was developed based on these predictors. The area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were utilized to assess the predictive accuracy and clinical value of the nomograms. RESULTS:The incidence of DIPH was 2.3% in the training cohort. Multivariate logistic regression analysis demonstrated that age (odds ratio [OR] per 10 years, 2.063, P=0.005), maximum diameter (OR, 1.099, P=0.004), adenosine diphosphate-induced maximal platelet aggregation (OR, 0.896, P<0.001), and overlapping devices (OR, 7.226, P=0.007) were independent risk factors for DIPH. A nomogram was developed based on these four predictors. The AUCs of the nomogram in the training and validation cohorts were 0.875 (95% CI, 0.762 to 0.988) and 0.886 (95% CI, 0.757 to 1.000), respectively. The calibration curve and DCA analyses confirmed the utility and clinical applicability of the nomogram. CONCLUSION:A simple to use nomogram for the individualized prediction of DIPH after PED treatment in patients with IAs was constructed, which may facilitate early identification of high-risk patients and the development of advanced treatment strategies.

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by a unique combination of mechanical obstruction resulting from organized thrombi and a variable degree of secondary small-vessel remodeling, both of which contribute to increased pulmonary vascular resistance. In this process, pulmonary artery smooth muscle cell (SMC) phenotypic switching plays a critical role in the progression of microvascular disease. However, the underlying molecular mechanisms remain incompletely elucidated. Single-cell RNA sequencing (scRNA-seq) data from CTEPH patients and normal pulmonary artery tissues (GSE224143, GSE228644) were integrated. After data preprocessing, unsupervised clustering, and cell type annotation using Seurat, we focused on SMC subtype analysis and constructed functional landscapes via pseudobulk DESeq2, Gene Ontology (GO) enrichment analysis, Monocle3 pseudotime trajectory analysis, and high-dimensional weighted gene co-expression network analysis (hdWGCNA). Core findings were validated using bulk RNA-seq datasets (GSE84538) and experimental approaches, including Western blotting, immunofluorescence, EdU proliferation assay, and Transwell/scratch wound healing migration assay. scRNA-seq analysis identified 18 distinct cell clusters in pulmonary vascular tissues. Compared with controls, CTEPH tissues showed reduced fibroblasts and increased immune cells (T cells, monocytes/macrophages) and SMCs. Four SMC phenotypes were identified, with a marked expansion of fibroblast-like SMCs in CTEPH and a dynamic transition from contractile to fibroblast-like phenotype confirmed by pseudotime analysis. Upregulated genes in CTEPH SMCs were enriched in extracellular matrix organization and TGF-β signaling pathways (significantly activated). Cross-validation via hdWGCNA, pseudotime trajectory, and bulk RNA-seq data identified NDRG1 (a hypoxia-inducible gene) as a core gene. NDRG1 was significantly overexpressed in CTEPH SMCs and tissues, positively correlating with pulmonary vascular resistance (PVR). Functional experiments showed that NDRG1 knockdown inhibited hypoxia-induced migration/proliferation of human pulmonary artery smooth muscle cells (HPASMCs), suppressed TGF-β/SMAD pathway activation, and reduced fibroblast-like phenotype marker (Vimentin, COL1A1) expression. NDRG1 is associated with SMC phenotypic switching toward the fibroblast-like phenotype and promotes pulmonary vascular remodeling in CTEPH via the TGF-β/SMAD pathway. NDRG1 and related key gene axes may serve as potential therapeutic targets for CTEPH.

Objective:Our study aimed to establish a predictive model based on non-enhanced CT imaging features of epicardial adipose tissue (EAT) to differentiate patients with coronary heart disease (CHD) from those without. Methods:In this radiomics study, we collected clinical and radiomic data from a total of 281 patients diagnosed with CHD at the China-Japan Friendship Hospital, along with 188 healthy individuals who underwent physical examinations at our hospital. The participants were allocated to either a training or validation group at random, following a 7:3 ratio. We performed multivariate logistic regression analysis to create a clinical model, using a significance threshold of p < 0.05. Additionally, we employed the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm to highlight important radiomic features for constructing a radiomics model. Lastly, we integrated the clinical and radiomics models to establish a combined model. To assess the model's effectiveness, we used the area under the curve (AUC), DeLong's test, and decision curve analysis (DCA). Results:In this radiomics study, the AUC of the clinical model were 0.883 (95% CI: 0.848-0.918) for the training cohort and 0.872 (95% CI: 0.812-0.932) for the validation cohort. In the radiomics model, the AUC for the training cohort was 0.853 (95% CI: 0.814-0.892) and for the validation cohort, it was 0.822 (95% CI: 0.751-0.893). DeLong's test revealed no significant difference in AUC between the clinical and radiomics models in both the training cohort (p = 0.218) and the validation cohort (p = 0.24). The combined model exhibited good discriminative ability, and the AUC were 0.930 (95% CI: 0.905-0.956) for the training cohort and 0.914 (95% CI: 0.863 -0.965) for the validation cohort. In the DeLong's test, we found that the AUC of the combined model was significantly higher in both cohorts compared to the other models (p < 0.05). Furthermore, the DCA curve revealed that using the combined model to identify patients with CHD provided greater advantages compared to using the two separate models. Conclusions:Our findings indicate that the combined model, which incorporated clinical features and the radiomics signature of EAT, can serve as a valuable tool for distinguishing patients with and without CHD.

PURPOSE:COVID-19 is an acute respiratory illness that has been shown to impair speech and voice, yet its effects on the neural dynamics of speech production remain largely unknown. This longitudinal study investigated the short-term neurobehavioral impact of COVID-19 on sensorimotor control of speech production. METHOD:Before and after COVID-19 infection, participants in the experimental group produced sustained vowels while hearing their voice unexpectedly pitch-shifted in auditory feedback. An age- and sex-matched control group without intervening COVID-19 infection underwent identical testing across a comparable interval. Vocal compensations and event-related potentials (ERPs), together with source localization and Granger causality analyses, were used to characterize the neurobehavioral effects of COVID-19 on vocal feedback control. RESULTS:Compared to pre-infection state, the experimental group exhibited reduced vocal compensations, decreased N1 amplitudes, and increased P2 amplitudes with shortened latencies at post-infection state. Enhanced P2 responses were significantly correlated with suppressed vocal compensations and received contributions from the superior, middle, and inferior temporal gyri; the premotor cortex; and the inferior frontal gyrus. Directed causal connectivity was identified from temporal to frontal regions. In contrast, the control group showed no significant changes in vocal or ERP responses between the two sessions. CONCLUSIONS:These findings provide the first evidence for short-term neurobehavioral effects of COVID-19 on auditory feedback control of vocal production. Reduced vocal compensation, together with decreased N1 responses, enhanced P2 responses, and strengthened frontotemporal connectivity, suggests a functional reorganization of auditory-vocal integration following recent COVID-19 infection.

ObjectiveTo describe the short-term safety, procedural characteristics, and clinical outcomes of ovarian vein embolization with adjunctive local sclerotherapy in a selected subgroup of women with pelvic venous disorder presenting with vulvar/external genital varicosities.MethodsThis retrospective single-center experience included 16 women with pelvic venous disorder presenting with concomitant vulvar/external genital varicosities who were treated between 2019 and 2023. The treatment strategy was primarily directed at pelvic venous reflux with ovarian vein embolization, followed by adjunctive local sclerotherapy for symptomatic vulvar/external genital varicosities during the same interventional session. Clinical assessment included symptom evaluation, visual analog scale (VAS), pelvic venous clinical severity score (PVCSS), and follow-up imaging.ResultsThe median follow-up duration was 7.0 months (IQR, 6.0–8.5 months). Technical success was achieved in all patients. Mean VAS decreased from 5.8 ± 1.8 before treatment to 0.9 ± 0.9 at follow-up, and mean PVCSS decreased from 10.7 ± 2.3 to 4.0 ± 1.6. Complete symptom relief was observed in 9 patients (56%) and partial relief in 7 patients (44%). No patient required reintervention during follow-up, and no major procedure-related adverse events were observed.ConclusionsOvarian vein embolization with adjunctive local sclerotherapy was technically feasible and was associated with short-term symptom improvement in women with pelvic venous disorder presenting with vulvar/external genital varicosities.

Natural antioxidant enzymes play a central role in regulating oxidative stress within living organisms. During tissue repair following injury, these enzymes act synergistically to scavenge excess reactive oxygen species and maintain cellular redox homeostasis, thereby supporting cell proliferation and differentiation, resolving inflammation, and facilitating extracellular matrix remodeling. Inspired by the catalytic properties and regulatory mechanisms of natural antioxidant enzyme systems, antioxidant nanozymes are artificial catalytic nanomaterials that mimic the activity of natural antioxidant enzymes and have emerged as a promising platform to overcome the limitations of natural enzymes and promote tissue regeneration. This review systematically summarizes the classification and catalytic mechanisms of antioxidant nanozymes, along with mechanism-guided design strategies. We further highlight recent advances in their application in regenerative medicine, including skin wound healing, cardiovascular repair, cartilage regeneration, neural tissue repair, bone tissue regeneration, and ocular repair. Finally, the challenges and future prospects of antioxidant nanozymes in regenerative medicine are discussed.

BackgroundArteriovenous malformations (AVMs) are rare congenital vascular anomalies involving high-flow shunting between arteries and veins. Intraosseous AVMs of the mandible are particularly uncommon and present substantial diagnostic and therapeutic challenges. Because even minor trauma or dental procedures may trigger severe hemorrhage, early recognition and appropriate management are essential.Case presentationWe describe a 33-year-old woman with a long-standing vascular lesion of the right mandible who developed uncontrolled oral bleeding after tooth extraction. Imaging confirmed a diffuse intraosseous AVM. After multiple unsuccessful treatments elsewhere, she underwent endovascular therapy consisting of super-selective arterial and venous access, coil embolization, and sclerotherapy with absolute ethanol and polidocanol foam. The procedure resulted in complete occlusion of the lesion without complications. Follow-up at 4 days, 6 months, and 1 year showed no recurrence.ConclusionMandibular AVMs are complex lesions that carry a significant risk of life-threatening hemorrhage. This case demonstrates that combined endovascular embolization and sclerotherapy can provide effective and durable control. Accurate diagnosis, timely intervention, and continued follow-up are essential to achieving favorable outcomes for this rare condition.

BACKGROUND:Hyperthermia (including thermal ablation and whole-body hyperthermia) is one of the methods to treat lung tumor. The primary mechanism underlying this method involves causing tumor cell necrosis, apoptosis, and pyroptosis. Pyroptosis can trigger a series of inflammatory reactions and serves as a contributing factor to lung injury. The objective of this study was to investigate whether hyperthermia can induce pyroptosis of normal lung epithelial cells, while concurrently triggering pyroptosis of lung tumor cells. MATERIALS AND METHODS:The cell lines PC-9 and BEAS-2B used in this study represent lung tumor cells and normal lung epithelial cells, respectively. PC-9 and BEAS-2B cells was simulated with a 45°C thermostatic water bath in vitro . Cell morphological characteristics were observed using microscopy. Gene expressions were evaluated by quantitative real-time PCR and protein expressions were assessed using Western blotting. RESULTS:Heat stress induced morphological features of pyroptosis in BEAS-2B and PC-9 cells and upregulated pyroptosis-related gene expressions ( GSDMD, GSDME, caspase-1, caspase-3, IL-1β , and IL-18 ) in both cells. Also, heat stress resulted in an upregulation of cleaved GSDME but not cleaved GSDMD in BEAS-2B and PC-9 cells and increased cleaved GSDME can be efficiently abrogated by inhibition of caspase-3. CONCLUSION:Heat induces pyroptosis in BEAS-2B and PC-9 cells, and the mechanism of pyroptosis induction is realized through the GSDME/caspase-3 pathway. The results showed hyperthermia can induce pyroptosis of lung cancer cells as well as normal lung epithelial cells at the same time. This might provide a potential target for prevention and treatment of lung injury after hyperthermia.

Patients with cerebral venous thrombosis (CVT) may experience poor response to anticoagulant therapy and delayed surgical treatment may lead to clinical deterioration. However, the factors contributing to clinical deterioration remain poorly understood. Patients with CVT from three centers between January 2017 and October 2023 were included and grouped as the development cohort and validation cohort. The danger triangle was defined as the posterior two-thirds of the superior sagittal sinus, confluence of sinuses, straight sinus, and deep venous system. The primary endpoint was clinical deterioration, characterized by new or progressive bleeding or infarctions or worsened neurological conditions post-admission. Using the results of multivariable logistic analysis, the Cerebral venOus thrombosis DEterioration (CODE) score was developed within the development cohort and validated within the validation cohort. The score’ performance in predicting clinical deterioration was evaluated using the area under the receiver operating characteristic curve (AUC). The development cohort included 194 CVT patients (101 males, and the median age was 38 years). clinical deterioration occurred in 45 (23.2 https://classic.clinicaltrials.gov/ct2/show/NCT06266585 )

BACKGROUND:Intracranial aneurysms (IAs) represent a significant and potentially fatal category of cerebrovascular disorders that pose serious health risks. Observational studies have indicated a potential link between brain imaging-derived phenotypes (IDPs) and various IAs. Nonetheless, the nature of these relationships remains ambiguous. METHODS:Two-sample bidirectional Mendelian randomization (MR) analyses were performed to examine the causal links between IDPs and IAs. We utilized summary statistics from a population comprising 587 brain IDPs (UK Biobank). Additionally, we incorporated data of IAs from the HUNT study. RESULTS:We identified a total of 13 IDPs that demonstrated a significant causal influence on the risk of developing IA, subarachnoid hemorrhage, and unruptured IA by forward MR. Specifically, an increase in mean diffusivity in the right external capsule is associated with the risk of IA (odds ratio [OR] = 1.830, 95% confidence interval [CI]: 1.134-2.553, P = 1.04 × 10-7). The results from the reverse MR analysis revealed that there is an association between genetically predicted IA and isotropic or free water volume fraction in body of corpus callosum (OR = 0.323, 95% CI: 0.232-0.461, P = 7.22 × 10-5), and an association between subarachnoid hemorrhage and mean diffusivity in the body of corpus callosum (OR = 0.360, 95% CI: 0.236-0.540, P = 2.50 × 10-4). CONCLUSIONS:The findings indicate that these IDPs play a crucial role in the etiology of these IAs and highlight the importance of understanding the mechanisms through which they exert their effects.

PurposeThis study aimed to evaluate the effectiveness and outcomes of embolo/sclerotherapy in treating Schobinger Stage IV peripheral arteriovenous malformations (pAVMs) associated with high-output cardiac failure (HOCF).MethodsBetween January 2017 and December 2024, 12 patients with Schobinger Stage IV pAVMs and associated HOCF were treated with embolization using coils and sclerosing agents, including bleomycin polidocanol foam (BPF) and anhydrous ethanol. Procedural outcomes, complications, devascularization and improvements in cardiac function were evaluated during follow-up.ResultsA total of 24 embolo/sclerotherapy sessions were performed on the 12 patients. Complete or over 80% devascularization of the vascular malformations was achieved in 9 patients. Echocardiographic follow-up revealed significant improvements in cardiac ejection fraction and ventricular dilatation. Additionally, 8 patients showed improvement in heart valve regurgitation. For all patients, the symptom of dyspnea disappeared after embolization and no serious complications occurred. LVEF improvement showed a significant positive correlation with a decrease in venous drainage pressure of the nidus after surgery (P < 0.001) in 11 patients, while one patient was excluded due to an increase in venous drainage post-surgery.ConclusionThis study provides evidence that embolo/sclerotherapy effectively treats pAVMs with associated HOCF by reducing abnormal blood flow and significantly improving symptoms. The results also reveal a linear relationship between the decrease in venous drainage pressure and improvement in LVEF in patients with HOCF caused by pAVMs after embolo/sclerotherapy.

To elucidate the effects of cerebral venous sinus thrombosis (CVST) on mice and the effects of sarpogrelate (S) on CVST, mice were randomly divided into the sham-operated group, CVST group, and CVST + S group (sarpogrelate). Neurological function was evaluated using the rotarod test, balance beam test, and open-field test. Moreover, laser speckle contrast imaging was employed to observe the blood flow in the cerebral cortex of mice, and immunofluorescence was used to quantify the neurons. In the neurofunctional assessment tests (i.e., rotarod test, balance beam test, and open-field test), the CVST group exhibited poorer performance compared to the sham-operated group. However, mice treated with sarpogrelate showed significantly better performance than the CVST group (P < 0.05). Moreover, a significant decrease in cerebral blood flow was observed in the CVST group compared to the sham-operated group (P < 0.01). In contrast, a significant increase in blood flow was observed in the CVST + S group compared to the CVST group (P < 0.05). Furthermore, the number of neurons in the hippocampus and prefrontal cortex of mice in the CVST group was lower than that in the sham group (P < 0.05), and the number of neurons in the hippocampus and prefrontal cortex of the CVST + S group was higher than that of the CVST group (P < 0.05). Sarpogrelate can increase blood flow in the cerebral cortex of mice with CVST, leading to decreased neuronal cell damage and improved neurological function.

BACKGROUND:Risk factors and mechanisms of cognitive impairment (CI) after aneurysmal subarachnoid hemorrhage (aSAH) are unclear. This study used a neuropsychological battery, MRI, ERP and CSF and plasma biomarkers to predict long-term cognitive impairment after aSAH. MATERIALS AND METHODS:214 patients hospitalized with aSAH (n = 125) or unruptured intracranial aneurysms (UIA) (n = 89) were included in this prospective cohort study. Neuropsychological tests were administered 7 to 24 months post-discharge. MRI, ERP, and CSF and plasma biomarkers were used to predict long-term CI, and area under ROC curves were calculated. RESULTS:Patients with aSAH CI showed significant impairment across composite scores and cognitive domains on the neuropsychological battery vs. patients with aSAH No CI. On ALFF (MRI), the right medial orbitofrontal cortex (AUC = 0.78), right inferior frontal gyrus (AUC = 0.848), and right inferior parietal lobule (AUC = 0.868) distinguished aSAH CI from aSAH No CI. For ERP, consistent changes were found across specific EEG electrodes (FP1, F3, CP1, FP2, F4, CP2), including increased PA, prolonged PL and decreased ITPC. ITPC showed the highest sensitivity for distinguishing aSAH CI from aSAH No CI, followed by PA. Channel F4 (ITPC, AUC = 0.912, PA, AUC = 0.846), corresponding to the right inferior frontal gyrus, was the most sensitive for detecting CI, followed by channel CP2 (ITPC, AUC = 0.903, PA, AUC = 0.806), corresponding to the right inferior parietal lobule. CSF (Aβ42, Aβ40, p-tau181/Aβ42, p-tau181/total-tau, total-tau) and plasma biomarkers (Aβ-40, p-tau181) were significantly associated with long-term CI. CONCLUSION:ALFF, ERP, and CSF and plasma Aβ and tau levels and ratios have clinical utility for evaluating and predicting long-term cognitive impairment following aSAH. MRI may reveal the pathogenesis of cognitive impairment following aSAH. ERP can be administered at the bedside offering sensitive, non-invasive, repeatable, and sustainable monitoring, which is particularly suitable for immobile coma patients. ERP may represent a promising method to monitor neural function and its outcomes.

BACKGROUND:Neonatal brain injury due to bilirubin toxicity presents critical need for effective healing treatments. Docosahexaenoic acid (DHA), having neuroprotective properties, offers potential therapeutic benefits in promoting brain repair and recovery. OBJECTIVES:This study focused on evaluating the healing capabilities of DHA in neonatal brains damaged by bilirubin-induced injury, with particular attention to its role in enhancing brain tissue repair mechanisms. METHODS:Employing the bilirubin encephalopathy model in neonatal Sprague-Dawley rats and neuronal cell cultures, we investigated the therapeutic impact of DHA. RESULTS:The study measured improvements in brain tissue integrity, assessed bilirubin levels, analyzed gene and protein expressions pertinent to the brain's recovery process. DHA administration resulted in significant repair in neonatal brains, evidenced by reduction in bilirubin levels and restoration of normal brain tissue architecture. CONCLUSION:Molecular analysis indicated the distinct modulation of the CTBP1/miR-155-5p/KDM5A pathway, critical for cellular repair processes and marked decrease in markers of cellular damage and stress.