CT angiography (CTA) is a key investigation in cerebrovascular disease. However, CTA is not always available and it also requires intravenous injection of iodinated contrast agents. It is increasingly possible to derive additional information from standard imaging sequences using Artificial Intelligence techniques. We investigated whether CTA maps could be derived from non-contrast CT (NCCT). We conducted a retrospective, multicenter study across five Chinese hospitals, enrolling 3,709 patients who underwent head NCCT paired with CTA. The dataset encompassed three cerebrovascular conditions: intracranial aneurysms (IA), intracranial atherosclerotic stenosis (IAS), and normal intracranial arteries. We developed the Cerebrovascular CTA Generative Artificial Intelligence Model (CTA-GAI) to synthesize CTA images directly from NCCT head scans. Synthetic outputs were evaluated against five typical models using quantitative metrics and visual assessment by clinicians. We also assessed the potential clinical utility of synthetic CTA for preliminary screening and triage by evaluating its ability to distinguish diseased from normal intracranial arteries and to classify common cerebrovascular subtypes. CTA-GAI demonstrated consistent and robust performance across both the validation and test sets. In internal validation, synthetic CTA images achieved a mean absolute error (MAE) of 0.0416, mean squared error (MSE) of 0.0178, peak signal-to-noise ratio (PSNR) of 25.59 dB, and structural similarity index measure (SSIM) of 85.41%. Clinicians assigned an average visual quality score of 4.45 out of 5. These metrics reflect close approximation to real CTA images. Performance remained consistent across four external validation sets. In a test set of 110 patients, clinicians achieved an overall accuracy, precision, sensitivity, specificity, and F1 score of 92.7%, 97.7%, 86.0%, 98.3%, and 91.5%, in distinguishing diseased intracranial arteries. Differentiation between IA and IAS within diseased arteries reached 90.7% accuracy. CTA-GAI can synthesize CTA-like images from NCCT that show promising utility for preliminary assessment in clinical practice. These results support its potential role as a rapid, low-cost, and non-invasive tool for large-scale screening or triage of cerebrovascular diseases.
Plasma glial fibrillary acidic protein (GFAP), a marker of astrocyte reactivity, is elevated across multiple neurodegenerative conditions, including Alzheimer disease. However, its role in neurodegeneration and cognitive decline driven by cerebrovascular pathology, independent of β-amyloid (Aβ) copathology, remains poorly characterized. We investigated whether plasma GFAP is associated with medial temporal atrophy and cognition across a spectrum of cerebrovascular burden in Aβ-negative cognitively impaired individuals. In this cross-sectional multicenter study, Aβ PET-negative cognitively impaired participants were recruited from South Korean memory clinics. Plasma GFAP was measured using ultrasensitive Simoa assays. White matter hyperintensity burden was graded using the Fazekas scale and stratified into low (LVP: Fazekas 1) and high (HVP: Fazekas 2-3) cerebrovascular burden groups. Medial temporal gray matter density was assessed using voxel-based morphometry, and hippocampal and amygdalar volumes were derived from T1-weighted MRI adjusted for intracranial volume. Linear regression, interaction, and bootstrap mediation models were used to assess associations among GFAP, brain structure, and cognition. A total of 324 participants were included (LVP n = 203; HVP n = 121; median age 73 years [interquartile range 66-78]; 67.9% female). Compared with LVP, HVP participants were older (75 vs 71 years; p < 0.0001), had lower Mini-Mental State Examination (MMSE) scores (22.7 vs 24.5; p = 0.005), and higher plasma GFAP (136.7 vs 112.1 pg/mL; p = 0.001). Higher GFAP was associated with lower medial temporal gray matter density in HVP (β = -0.311; p = 0.001) but not LVP (β = -0.012; p = 0.858), with a significant GFAP-vascular burden interaction (β = -0.309; p = 0.008). In HVP, higher GFAP was associated with smaller hippocampal (β = -0.179; p = 0.044) and amygdalar volumes (β = -0.169; p = 0.049) and lower MMSE (β = -0.194; p = 0.039). Medial temporal atrophy statistically explained the GFAP-MMSE association (indirect β = -0.071, 95% CI -0.140 to -0.010; p = 0.016). Vascular comorbidities (diabetes, dyslipidemia, hypertension) did not modify the GFAP-cognition association. In Aβ-negative cognitively impaired individuals with high cerebrovascular burden, elevated plasma GFAP is associated with medial temporal atrophy and cognitive decline, suggesting GFAP may capture astrocyte-reactivity relevant to vascular cognitive impairment beyond amyloid pathology. These cross-sectional findings require confirmation in longitudinal and ethnically diverse cohorts.
Prolonged glucocorticoid elevation is strongly associated with brain dysfunction and the pathogenesis of stress-related disorders, including several psychiatric disorders. Elevated lactate levels have been reported in the brains of patients with psychiatric disorders and animal models of chronic stress and psychiatric disorders. Prolonged glucocorticoid elevation may disrupt brain lactate homeostasis, but the mechanisms through which this occurs and the pathological significance of the disruption are incompletely understood. Here, we show that chronic corticosterone (CORT) treatment increases lactate in the hippocampus and reduces monocarboxylate transporter 1 (MCT1) expression in hippocampal cerebrovascular endothelial cells. Cerebrovascular-specific overexpression of MCT1 reduced hippocampal lactate accumulation and ameliorated impaired hippocampal neurogenesis, depression-like behavior, and cognitive impairment in chronically CORT-treated mice. Conversely, knockdown of cerebrovascular MCT1 expression increased lactate accumulation in the hippocampus and caused impaired hippocampal neurogenesis and cognitive impairment. These findings suggest that chronic glucocorticoid elevation induces lactate accumulation via dysregulation of cerebrovascular lactate transport, thereby impairing neurogenesis and inducing behavioral abnormalities. This mechanism may contribute to stress-related brain dysfunction and the pathogenesis of psychiatric disorders.
Treatment for grade I and II blunt cerebrovascular injuries (BCVIs) involves 3 mo of antiplatelet or anticoagulation therapy with repeat imaging within 7-10 d. We hypothesized that patients at safety-net hospitals often do not complete this regimen, leaving them at risk for cerebrovascular events. We performed a retrospective review of patients with grade I-II BCVI at a level 1 trauma center (January 2016-July 2024). Data included timing of initial and repeat computed tomography angiography, initiation, duration, and adherence to medical treatment. Outcomes were completion of repeat imaging and 3-mo medical treatment. Univariate and multivariable analyses were conducted to identify factors associated with treatment completion. Of 286 patients screened, 38 (30 grade I, 8 grade II) were diagnosed with BCVI. Median age was 44 y, 61% were male, and motor vehicle collision was the most common mechanism (39.5%). Repeat imaging was obtained in 23 patients (60.5%) at a median of 6 d (interquartile range 3-13). Medical treatment was initiated in 32 (84.2%), with 27 (71.1%) discharged on treatment; 12 (44%) completed the 3-mo regimen. No patients obtained 7- to 10-d outpatient imaging, and fewer than half had BCVI addressed in follow-up. On univariate analysis, Hispanic ethnicity (Odds Ratio [OR] 15.6, P = 0.02) and BCVI-specific follow-up (OR 15.0, P = 0.01) were associated with treatment completion. In multivariable analysis, BCVI-specific follow-up remained associated (OR 15.8, P = 0.03). Adherence to guideline-recommended BCVI therapy and follow-up imaging was poor. Structured discharge pathways and linkage to BCVI-specific follow-up may improve treatment completion.
The pan-immune-inflammation value (PIV) is a novel biomarker reflecting systemic inflammation. Its role in predicting adverse cardiovascular and cerebrovascular events in diabetic patients after percutaneous coronary intervention (PCI) is unclear. This study evaluated PIV's prognostic value for major adverse cardiovascular and cerebrovascular events (MACCE) post-PCI in diabetics with coronary heart disease (CHD), and compared it to other inflammation-based markers like systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR). Retrospective analysis of diabetic CHD patients undergoing PCI. PIV was calculated as (neutrophil × platelet × monocyte)/lymphocyte counts from pre-procedural blood. Optimal cutoff determined via ROC curve. Patients stratified into high/low PIV groups. Follow-up for MACCE (e.g., MI, stroke, revascularization). Kaplan-Meier (KM) survival, Cox regression, and ROC comparisons assessed outcomes. Over 24-month median follow-up, 52 MACCE occurred (24.8%). High-PIV group had higher incidence (37.7% vs. 11.5%, p < 0.001) and worse MACCE-free survival (log-rank p < 0.001). Multivariate Cox confirmed high PIV as independent predictor (adjusted HR = 2.87, 95% CI: 1.55-5.32, p = 0.001). PIV AUC = 0.74 (95% CI: 0.68-0.80), outperforming SII (0.69), NLR (0.66), and PLR (0.64; DeLong's test p < 0.05 vs. NLR/PLR). PIV is a robust, independent predictor of MACCE post-PCI in diabetics, with superior accuracy over other markers. It offers cost-effective risk stratification. Limitations: retrospective design; prospective validation needed.
Infertility is increasingly recognized as a marker for heightened cardiovascular risk in women due to shared pathophysiological pathways such as chronic inflammation, endothelial dysfunction, and adverse metabolic profiles. The aim of the present study was to examine the association between infertility and the long-term risk of major cardiovascular outcomes, including cerebrovascular disease (CeVD), heart failure (HF), and ischemic heart disease (IHD), in a large, nationwide population-based cohort. This study used Taiwan's National Health Insurance Research Database (2000-2021) to identify women aged 18-50 years with infertility and compare them with non-infertility controls using 1:4 age matching and 1:1 propensity score matching (PSM) to balance baseline characteristics. The primary outcome was a composite of CeVD, HF, and IHD. Risks were assessed using Cox proportional hazards models and reported as hazard ratios (HRs) with 95% confidence intervals (CIs), with subgroup analyses stratified by age (18-34 and 35-50 years). A total of 39 337 women with infertility and 157 348 controls were included after 1:4 age matching; 20 974 matched pairs remained after 1:1 PSM. The infertility group had a significantly higher risk of the composite outcome, which persisted after adjustment and PSM (adjusted HR = 1.15, 95% CI: 1.08-1.21; PS-matched HR = 1.18, 95% CI: 1.10-1.26). Similar patterns were observed for CeVD and IHD, with consistent trends across age subgroups, particularly among those aged 35-50 years. In this nationwide cohort study, infertility was associated with modestly increased long-term risks of CeVD and IHD, with age-specific patterns observed for CeVD. These findings highlight the importance of cerebrovascular and heart disease awareness in the long-term follow-up of women with infertility, pending confirmation in prospective studies.
Diabetes is a significant worldwide health concern. Cerebrovascular disease (CVD) appears as a serious complication associated with diabetic patients, increasing the risk of mortality. Our study analyzes trends in mortality due to diabetes mellitus (DM) and CVD from 1999 to 2023 in the United States (U.S.) and explores the population and geographics at high risk, stressing the need for targeted public health strategies. A retrospective analysis of death records was done that have both DM and CVD on them using the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) database. Crude and age-adjusted mortality rates (AAMR)s per 100,000 population and annual percent changes (APC)s in age-adjusted mortality rate were determined and measured across different demographics and geographics in the U.S. A total of 818,742 deaths were registered caused by DM and CVD. The overall AAMR declined, decreasing sharply from 1999 to 2011 (APC -4.11*). AAMR remained stable till 2018 and surged significantly up to 2021 (APC 12.39*), then continued to decline sharply up till 2023 (APC 5.91*). Males had higher AAMRs than females throughout the study (Overall AAMR: Male: 31.1 vs Female: 24.9). The top AAMR of 53.3 was observed in NH African Americans among races/ethnicities. CMR in Older Adults (65-85+ years) was 14 times greater than that of those aged 45-64 years. The observed AAMR was higher in non-metropolitan (32.3) areas, while the south represented the highest AAMR among the four regions. To address the observed disparities in different demographics and geographies, a proper distribution of resources and more targeted interventions are needed.
Cerebrovascular reactivity (CVR), a promising marker of neurovascular responsiveness, is commonly measured using blood-oxygenation-level-dependent magnetic resonance imaging (BOLD-MRI) during a vasoactive gas challenge. While CVR magnitude (vascular response strength) has been widely studied, CVR delay (response time) is comparatively underexplored yet may provide valuable insight into vascular dysfunction across several neurological conditions. We systematically reviewed publications assessing delay using gas-challenge BOLD-MRI up to October 2025, identifying 200 relevant papers. Only 44 (22%) papers investigated delay in detail; the remainder only applied delay correction to improve CVR magnitude accuracy. Findings in disease were mixed and often limited by small sample sizes and methodological differences. Hypercapnic stimuli, typically delivered via fixed-inspired or fixed-expired methods, were most commonly used. While cross-correlation was the most popular delay estimation method, several alternatives, including haemodynamic response function fitting and Fourier analysis, have been proposed, but systematic comparisons against standard delay estimation methods remain limited, especially in clinical populations. Our review highlights inconsistencies in delay measurement and interpretation, with delay mostly treated as a confounder rather than a meaningful physiological parameter. Greater methodological validation and harmonisation are needed to realise the potential of CVR delay as a novel biomarker of brain health and disease.
This study aimed to establish individualized metabolic networks for patients with ischemic cerebrovascular disease (ICVD) using cerebral glucose metabolism data and to analyze topological alterations before and after surgical intervention. We enrolled 31 surgically treated ICVD patients with unilateral cerebral infarction (21 with complete postoperative follow-up) and 17 normal controls (NC). We constructed individualized brain metabolic networks from [18F]-fluoro-2-deoxy-D-glucose positron emission tomography ([18F]FDG PET) scans using Kullback-Leibler divergence. In the NC group, subnetworks were defined as the left intrahemispheric, right intrahemispheric and interhemispheric networks. In the ICVD group, after hemispheric alignment based on the surgical side, subnetworks were redefined as the surgical intrahemispheric, non-surgical intrahemispheric, and interhemispheric networks. Then, graph-theoretical parameters were calculated to derive the metabolic connectivity expression score (MCES). Finally, we used Kruskal-Wallis tests, paired t-tests, and Spearman correlation analysis to assess topological differences and their relationship with National Institutes of Health Stroke Scale (NIHSS) scores. The preoperative ICVD group showed significantly altered metabolic connectivity compared with controls, with higher global MCES values (0.83 vs. 0.32, p < 0.0001). Ipsilesional subnetworks exhibited reduced connectivity, whereas contralesional subnetworks showed increased connectivity. Subnetwork analysis showed that the interhemispheric network in the ICVD group had a mean MCES of 0.91, which was significantly higher than that of the interhemispheric network in the NC group (0.17, p < 0.0001). Postoperatively, network connectivity showed partial recovery, particularly within the interhemispheric network. MCES was significantly correlated with NIHSS scores in the global, non-surgical intrahemispheric, and interhemispheric networks (|r|=0.58 ~ 0.65, p < 0.05), but not in the surgical intrahemispheric network. ICVD is associated with disrupted metabolic connectivity that exhibits early postoperative remodeling following surgical revascularization. Changes in interhemispheric network topology may provide insight into early postoperative metabolic network reorganization.
Sepsis is one of the common causes of death in the neurological intensive care unit (NICU) stroke patients, the aim of this study was to evaluate the diagnostic performance of blood biomarkers studied for the early diagnosis of sepsis in ICU hospitalized patients with acute moderate to severe stroke, and to establish a that is specifically used to predict the occurrence of sepsis or not after stroke. A prediction model was built including 157 patients with severe cerebrovascular disease [including acute ischemic stroke (AIS) or cerebral hemorrhage (ICH)] who had National Institute of Health stroke scale (NIHSS) >14 or Glasgow coma scale (GCS) <8 from January 2020 to November 2022 in NICU. Laboratory parameters and clinical characteristics of the patients were collected as well as Enzyme-Linked Immunosorbent Assay (ELISA) to detect blood biomarkers IL-10, MIP-1β, TNF-α, nNOS, iNOS, MMP-9, S-100β, and ET-1 within 48 h after symptom onset. Multi-factorial logistic regression was used to construct for predicting sepsis in patients with acute moderate-to-severe stroke, and internal validation was evaluated using bootstrap validation. The performance of the graph was assessed based on its calibration, discrimination, and clinical utility. The prevalence of sepsis in acute moderate-to-severe stroke patients was 12.1%. The GCS scores of patients with comorbidity sepsis were all lower than those of patients without sepsis, and the NIHSS scores were higher than those of patients without sepsis. Logistic stepwise regression was performed to identify 4 variables Hyperlipidaemia (P < 0.001), IL-10 (P < 0.001), NIHSS (P = 0.015), and Blood creatinine (P < 0.001), and to establish a prediction model for sepsis in acute moderate-to-severe stroke patients. The area under the curve (AUC) of the prediction model was 0.816 (95% CI: 0.721 ~ 0.911), and the calibration curve was well fitted, which has good clinical application value.
Exposure to intermediate and high altitude induces hypobaric hypoxia, which may alter cerebral hemodynamics through complex interactions involving hypoxia-driven vasodilation, hypocapnia, hematological changes, and vascular remodeling; however, cerebrovascular responses vary substantially between native high-altitude populations and lowlander individuals. We conducted a systematic review and meta-analysis to quantify altitude-related changes in cerebral blood flow (CBF) and related hemodynamic parameters and to explore sources of heterogeneity. Major databases were searched through inception to November 2025 for observational studies evaluating cerebral hemodynamics at ≥1,500 m above sea level. Outcomes included mean velocity (MV), volumetric blood flow, arterial diameter, cerebrovascular conductance, cerebral oxygen saturation, autoregulation index, and global CBF. Random-effects models (Paule-Mandel) were used to pool mean differences, with subgroup and meta-regression analyses performed; certainty of evidence was assessed using GRADE. Fifty-five studies including 1,935 participants were analyzed. Altitude exposure was associated with a reduction in mean cerebral artery velocity (MD -5.79 cm/s; 95% CI -9.37 to -2.21; I² = 96%), reduced volumetric blood flow (MD -32.99 ml/min; 95% CI -45.24 to -20.73; I² = 98%), decreased arterial diameter (MD -0.27 mm; 95% CI -0.45 to -0.08; I² = 91%), lower cerebrovascular conductance (MD -0.43 ml/min/mmHg; 95% CI -0.65 to -0.21; I² = 24%), reduced cerebral oxygen saturation (MD -4.45%; 95% CI -6.77 to -2.14; I² = 74%), and lower global cerebral blood flow (MD -155.00 ml/min; 95% CI -350.11 to 40.11; I² = 95%), although heterogeneity was substantial across outcomes. Subgroup analyses suggested that native high-altitude populations and lowlander individuals exhibit distinct cerebrovascular responses, with population status, age, and altitude level explaining part of the observed variability. Overall certainty of evidence was very low. These findings indicate that exposure to altitude is associated with heterogeneous but consistent alterations in cerebral hemodynamic parameters, with marked differences between native and non-native populations, underscoring the importance of population-specific physiological adaptation when interpreting cerebrovascular responses to hypoxia.
To develop and validate the performance and prognostic value of a deep-learning (DL) model for carotid plaque component quantification on CTA. A multicenter retrospective study was conducted in three stages: Stage 1: Model development and concordance analysis: A DL model was developed for plaque detection and segmentation using 2164 CTA scans (Cohort 1). DL-radiologist measurement agreement was assessed using ICC and Spearman's test (Cohort 2). Stage 2: Diagnostic validation: Performance was validated against 1) 118 co-registered CTA-OCT image pairs (Cohort 3) and 2) 146 patients with paired HR-MRI and CTA (Cohort 4). Stage 3: Prognosis validation: In 610 symptomatic patients (Cohort 5), multivariable Cox regression assessed the association between lipid core burden (LCB) and recurrent cerebrovascular events, and the incremental predictive value of LCB was quantified by ΔAUC and NRI. The DL model achieved a detection sensitivity of 0.85 with an average of 1.08 false positives per case. It demonstrated good-to-excellent agreement with radiologist assessments. In Stage 2, DL-driven lipid core component is associated with high-risk plaques identified by OCT and HR-MRI. In Stage 3, in a median 2-year follow-up, LCB independently predicted recurrent cerebrovascular events (HR: 1.08, 95% Cl: 1.03-1.13, P<0.001). The incorporation of LCB provided incremental risk stratification beyond clinical and CTA-driven anatomical factors (ΔAUC +0.09, NRI: 0.22, P=0.001). The DL model accurately quantifies carotid plaque components on CTA, with LCB adding prognostic value for recurrent cerebrovascular events in patients with symptomatic carotid stenosis.
We investigated the contribution of antecedent gestational diabetes mellitus (GDM) or gestational hypertensive disorder (GHTD) to the risk of cardiovascular disease (CVD) among women with Type 2 diabetes mellitus (T2DM). In a population-based cohort using the Ministry of Health of Ontario (Canada) healthcare administrative data, women without prior CVD with T2DM and a history of GDM or GHTD as of 1 January 2018 (n = 11 525, mean age: 43 years) were age-matched to three comparator cohorts (women with T2DM and no history of GDM or GHTD [n = 11 525], women without T2DM and without GDM or GHTD [n = 11 525] and men with T2DM [n = 11 525]). Incident CVD (coronary artery disease [CAD] and cerebrovascular disease) and heart failure (HF) were assessed until 31 December 2023. There were 1231 CVD events over a median follow-up of 6 years. Compared to women with T2DM but no history of GDM or GHTD, women with T2DM and a history of GDM or GHTD exhibited higher incident CVD (adjusted hazard ratio [aHR]: 1.19, 95% CI: 1.01, 1.41) and CAD (aHR: 1.35, 95% CI: 1.10, 1.66) risks. They also had higher CVD (aHR: 3.70, 95% CI: 2.79, 4.91), CAD (aHR: 4.96, 95% CI: 3.43, 7.19), cerebrovascular disease (aHR: 2.41, 95% CI: 1.54, 3.76) and HF (aHR: 4.95, 95% CI: 2.05, 11.94) risks versus women without T2DM and no history of GDM or GHTD. However, they had lower CVD, CAD, cerebrovascular disease and HF risks, compared to men with T2DM. Among women with T2DM, prior GDM or GHTD conferred a higher CVD risk.
Cerebral small vessel diseases (CSVDs) are a group of disorders affecting the small arteries, veins, and capillaries supplying the white matter and deep grey matter structures. They are the most common form of cerebrovascular disease, accounting for approximately half of vascular dementia cases and 20% of stroke incidence. Whilst genetic testing is a routine diagnostic tool for monogenic CSVDs, less than 20% of patients have a causal variant in known CSVD genes. We performed whole exome sequencing on 117 patients suspected of monogenic CSVD who previously tested negative for pathogenic variants in seven well-characterised CSVD genes (NOTCH3, HTRA1, COL4A1, COL4A2, TREX1, GLA, and FOXC1). Targeted analysis was conducted on known and associated CSVD genes, as well as candidate genes which cause conditions with overlapping symptomology to CSVD. Burden analysis focussing on rare, functional variants was used to identify novel associations when compared against a cohort of 1035 non-neurological controls. We identified 18 suspected disease-causing variants across nine CSVD-associated genes and a significant burden of both rare and rare, likely disease-causing heterozygous variants in ABCC6. Two genes from stroke and neurodegenerative disease gene panels also possessed a significant burden of rare, likely disease-causing variants, MYH11 (adjusted P = 1 × 10-2) and NOTCH1 (adjusted P = 1 × 10-2). We further identified novel associations for seven genes (COL7A1, HMCN1, LAMA1, MMP9, TENM4, TNC, TTN) with monogenic CSVD in this cohort. Our findings implicate several genes as potentially causal of monogenic CSVD, highlighting the need for more extensive genetic screening in suspected CSVD cases, and functional characterisation of implicated variants to determine their mechanistic role in CSVD pathogenesis.
SARS-CoV-2 infection and BNT162b2 mRNA vaccination carry distinct cardiovascular risk profiles, yet direct comparative evidence across all immunological exposure groups and both sexes remains limited. Using the TriNetX Research Network (December 2020-December 2024), we stratified 30.3 million individuals into four mutually exclusive cohorts: uninfected/unvaccinated controls (G1), infected/unvaccinated (G2), vaccinated-only (G3), and hybrid immunity (G4). Fifty prespecified cardiovascular, cerebrovascular, and mortality outcomes were evaluated across four temporal windows (0-3, 3-6, 6-9, and >9 months) with analyses stratified by biological sex. SARS-CoV-2 infection was associated with 3- to 5-fold increases in cardiovascular events during the acute phase, including myocarditis (males: RR 4.44; females: RR 5.59) and all-cause mortality (males: RR 4.53), with risks persisting beyond nine months. BNT162b2 vaccination conferred 65-76% reductions in major adverse cardiovascular events (0-3 months). Post-infection vaccination (hybrid immunity) provided an additional 36-38% MACE reduction; males exhibited late pericarditis elevation beyond nine months. Completing the two-dose primary series maximally reduced mortality (by 77%) and myocarditis (by 62%) versus single dosing. In this US cohort, SARS-CoV-2 infection confers substantially greater and more sustained cardiovascular risk than BNT162b2 vaccination across all comparisons and both sexes, consistent with a favorable cardiovascular risk-benefit profile for vaccination.
To investigate the prevalence and distribution characteristics of unexpected antibodies through a retrospective analysis of 115 positive cases and explore transfusion strategies for patients with unexpected antibodies. Clinical data of 33,013 patients who underwent unexpected antibody testing in a hospital from May 2023 to October 2025 were collected, and 115 positive cases were retrospectively analyzed. The overall positivity rate of unexpected antibodies and their distribution across different sexes and ABO blood types were statistically analyzed. The effects of transfusion history, pregnancy history, disease types, and treatment history on the production of unexpected antibodies were examined. Among 33,013 tested individuals, 115 were positive for unexpected antibodies, yielding an overall positivity rate of 0.35%. The positive rate was 0.28% (44/15,932) in men and 0.42% (71/17,081) in women, with a statistically significant difference (P < 0.05). Among the 115 patients with positive, result, 44 were men (38.3%) and 71 were women (61.7%), showing a significant difference in gender distribution (P < 0.05). The positivity rate of unexpected antibodies differed significantly among ABO blood types (P = 0.006). Sixty patients (52.2%) had a history of transfusion, while 55 (47.8%) had no transfusion history, with no significant difference (P > 0.05). Regarding antibody specificity, 39 cases (33.9%) involved Rh blood group system antibodies, 34 cases (29.6%) involved MNS blood group system antibodies, 26 cases (22.6%) had undetermined specificity, and the remaining cases involved Duffy, Lewis, and other blood group system antibodies. In terms of disease distribution, positive patients were predominantly concentrated in four categories: digestive system diseases, hematological diseases, cardiovascular and cerebrovascular diseases, and obstetrics and gynecology diseases. Transfusion history and pregnancy history are the major contributing factors to the development of unexpected antibodies. The positive rate of unexpected antibodies varies among individuals with different ABO blood groups, with the highest rate observed in those with blood type A. Antibodies from different blood group systems exhibit distinct characteristics. Blood transfusion departments should develop individualized transfusion strategies based on antibody specificity and patients' clinical features to maximize the safety of clinical transfusion.
TMEM16A forms a Ca²⁺-activated Cl⁻ channel in vascular mural cells (smooth muscle cells and pericytes) that generates depolarizing Cl⁻ efflux upon intracellular Ca²⁺ elevation, thereby amplifying agonist-induced vasoconstriction. TMEM16A has been implicated in excessive capillary pericyte constriction following cerebral ischemia, suggesting that its inhibition may improve post-stroke recovery. However, the impact of systemic vascular TMEM16A inhibition on focal reperfusion efficiency and cerebrovascular autoregulation remains unknown. To address this question, mice with inducible mural cell-specific (Myosin Heavy Chain 11 promoter controlled) deletion of TMEM16A were subjected to transient middle cerebral artery occlusion. Reperfusion dynamics and stroke-reperfusion outcome were assessed using laser speckle contrast imaging, cylinder test for motor function, and infarct quantification by 2,3,5-triphenyltetrazolium chloride staining. Systemic cardiovascular parameters were monitored with radiotelemetry. Middle cerebral artery myogenic tone was assessed with pressure myography. Mice lacking TMEM16A in mural cells exhibited impaired reperfusion and worsened stroke outcome compared with wild-type controls, despite unchanged systemic cardiovascular parameters. In wild-type mice, capillary pericytes maintained basal contractile tone in both hemispheres, and this was further enhanced in peri-infarct cortex. In contrast, TMEM16A-deficient capillary pericytes lacked basal tone in both the ipsilateral and contralateral hemispheres. TMEM16A-deficient middle cerebral arteries failed to develop pressure-induced myogenic tone. These findings demonstrate that TMEM16A is required for effective cerebral autoregulation and that its deficiency significantly impairs post-ischemic reperfusion. The results caution against systemic TMEM16A inhibition as a therapeutic strategy for stroke and highlight the need for spatially restricted approaches to modulate cerebral perfusion via the Ca²⁺-activated Cl⁻ channels.
Alzheimer's Disease (AD) core pathology involves amyloidβ and ptau, leading to neurodegeneration (ATN model), yet individuals with comparable core pathology show considerable biological and clinical heterogeneity, motivating new models that consider non-specific processes and co-pathology. MRI and peripheral proteomics offer complementary, non-invasive approaches for capturing biological variation beyond core pathology, and many researchers have begun integrating them. However, no systematic overview of this literature exists. This scoping review evaluated studies combining MRI and peripheral plasma proteomics in AD within revised diagnostic frameworks, summarizing strengths and gaps. Following PRISMA 2020 guidelines, PubMed, Embase, and Scopus were searched through June 14, 2023, yielding 3,185 records; 63 studies met the inclusion criteria. For each study, study design, participant characteristics, proteomic platforms, imaging modalities, statistical approaches, and significant associations between non-core-pathological proteins and MRIderived measures were extracted. Across studies, methodological variability was high. Grey matter volume was the most commonly examined imaging metric, followed by cerebrovascular dysfunction, cortical thickness, white-matter and whole-brain volume, and connectivity measures. Overall, 127 non-core-pathology proteins, mostly related to inflammation/immune function, were associated with MRI metrics, though only three appeared in five or more studies. Roughly half of the studies incorporated core AD biomarkers. This scoping review of 63 studies demonstrates that integrating peripheral proteomics with MRI is an increasingly common approach in AD research, with GFAP, CRP, and IL-6 as the most frequently reported proteins, and grey matter volume and vascular dysfunction as the most commonly examined imaging phenotypes. However, effect sizes are generally modest, findings are heterogeneous, and many studies lack core AD biomarkers, highlighting the need for greater methodological consensus and more mechanistic, multimodal, and longitudinal research. Integrating MRI and peripheral proteomics is increasingly common in AD research, but consensus on analytic and imaging approaches is limited. Heterogeneity in proteomic platforms and statistical methods constrains comparability; most associations are modest, and observational designs limit causal inference. Future work should emphasize methodological harmonization, reproducibility, multivariate and machine-learning approaches, and randomized trials to test mechanistic pathways.
To evaluate the impact of Bentall-de Bono (BD) versus modified Bentall-de Bono (MBD) procedures on patient survival and long-term clinical outcomes. We reviewed 1,478 patients who underwent Bentall procedures between 2003 and 2022. Patients were initially stratified into two groups based on surgical technique: the BD group (n = 1,274), and the MBD group (n = 204). To mitigate baseline imbalances and selection bias, a 1:1 propensity score matching analysis was performed, yielding 202 matched pairs. Long-term survival was assessed using Kaplan-Meier analysis. Stroke was analyzed as an exploratory secondary cerebrovascular outcome. Predictors of mortality were identified via multivariable Cox proportional hazards regression. In the matched cohort, the median follow-up was 5.98 (interquartile range: 3.53-9.84) years. Kaplan-Meier analysis demonstrated comparable 10-year survival rates between the BD and MBD groups (90.9% vs. 88.4%, P = 0.42). Freedom from stroke was evaluated exploratorily and did not differ significantly between groups. (80.0% vs. 80.2%, P = 0.63). Multivariable Cox regression confirmed that the surgical technique (BD vs. MBD) was not an independent predictor of long-term mortality (hazard ratio [HR], 0.84; 95% confidence interval [CI], 0.40-1.74; P = 0.634). Independent predictors of late mortality included advanced age and prolonged aortic cross-clamp time. There is no difference in long-term survival following BD versus MBD.
Vascular cognitive impairment (VCI), including vascular dementia (VaD), encompasses a spectrum of cognitive deficits resulting from cerebrovascular pathology, ranging from mild impairment to dementia. As the second leading cause of dementia worldwide, VCI remains a major therapeutic challenge. A comprehensive search of ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) identified randomized controlled trials (RCTs) conducted or completed between 2012 and 2025. Trials enrolling participants diagnosed with VCI or VaD across all disease stages and all trial phases were included. Forty-one RCTs met the inclusion criteria encompassing diverse therapeutic mechanisms. Investigated agents included neuroprotective and vascular-targeted compounds, neurotransmitter modulators, symptom-focused drugs for behavioral and psychological symptoms of dementia (BPSD), traditional Chinese medicine (TCM) formulations, and agents acting on novel pathways. Recent trials in VCI and VaD show increasing methodological rigor and therapeutic diversity, signaling growing research momentum in the field. Nonetheless, progress is constrained by regional concentration of studies, limited publication of completed results, and inconsistent disease classification across stages. Strengthening global collaboration, ensuring transparent reporting, and standardizing disease staging will be critical to advancing pharmacological development for vascular cognitive disorders.