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Stretchable semiconducting polymers have been developed as a key component to enable skin-like wearable electronics, but their electrical performance must be improved to enable more advanced functionalities. Here, we report a solution processing approach that can achieve multi-scale ordering and alignment of conjugated polymers in stretchable semiconductors to substantially improve their charge carrier mobility. Using solution shearing with a patterned microtrench coating blade, macroscale alignment of conjugated-polymer nanostructures was achieved along the charge transport direction. In conjunction, the nanoscale spatial confinement aligns chain conformation and promotes short-range π–π ordering, substantially reducing the energetic barrier for charge carrier transport. As a result, the mobilities of stretchable conjugated-polymer films have been enhanced up to threefold and maintained under a strain up to 100%. This method may also serve as the basis for large-area manufacturing of stretchable semiconducting films, as demonstrated by the roll-to-roll coating of metre-scale films.Solution shearing of semiconducting polymers with a patterned blade induces improved alignment of the polymeric chains at the nano- and macroscale. This leads to increased charge transport in stretchable, roll-to-roll deposited organic transistors.

ObjectiveIntracranial atherosclerosis is a major cause of ischaemic stroke worldwide. A number of studies have shown the effects of statin treatment on coronary and carotid artery plaques, but there is little evidence on the effects of statin treatment on intracranial atherosclerotic plaques.MethodsThe Intensive Statin Treatment in Acute Ischaemic Stroke Patients with Intracranial Atherosclerosis - High-Resolution Magnetic Resonance Imaging (STAMINA-MRI) Trial is a single-arm, prospective, observational study monitoring imaging and clinical outcomes of high-dose statin treatment among statin-naive patients with acute ischaemic stroke caused by symptomatic intracranial atherosclerosis. The primary outcome was the change in vascular remodelling and plaque characteristics before and after 6 months (median: 179 days, IQR 163–189 days) of statin treatment measured by high-resolution MRI (HR-MRI).ResultsA total of 77 patients (mean age: 62.6±13.7 years, 61.0% women) were included in this study. Low-density lipoprotein cholesterol (LDL-C) levels (mg/dL) at initial and follow-up assessments were 125.81±35.69 and 60.95±19.28, respectively. Overall, statin treatment significantly decreased enhancement of plaque volume (mm3, 32.07±39.15 vs 17.06±34.53, p=0.013), the wall area index (7.50±4.28 vs 5.86±4.05, p=0.016) and stenosis degree (%, 76.47±20.23 vs 64.05±21.29, p<0.001), but not the remodelling index (p=0.195). However, 35% patients showed no change or increased enhancement volume and stenosis degree after statin treatment. Higher reduction of LDL-C and longer duration of statin treatment were associated with decreased enhancement volume after statin treatment.ConclusionsHigh-dose statin treatment effectively stabilised symptomatic intracranial atherosclerotic plaques as documented by HR-MRI. Further study is needed to determine laboratory and genetic factors associated with poor response to statins and alternative therapeutic options, such as proprotein convertase subtilisin-kexin type 9 inhibitors, for these patients.Trial registration numberClinicalTrials.gov NCT02458755.

We aimed to develop a novel prediction model for early neurological deterioration (END) based on an interpretable machine learning (ML) algorithm for atrial fibrillation (AF)-related stroke and to evaluate the prediction accuracy and feature importance of ML models. Data from multicenter prospective stroke registries in South Korea were collected. After stepwise data preprocessing, we utilized logistic regression, support vector machine, extreme gradient boosting, light gradient boosting machine (LightGBM), and multilayer perceptron models. We used the Shapley additive explanation (SHAP) method to evaluate feature importance. Of the 3,213 stroke patients, the 2,363 who had arrived at the hospital within 24 h of symptom onset and had available information regarding END were included. Of these, 318 (13.5%) had END. The LightGBM model showed the highest area under the receiver operating characteristic curve (0.772; 95% confidence interval, 0.715–0.829). The feature importance analysis revealed that fasting glucose level and the National Institute of Health Stroke Scale score were the most influential factors. Among ML algorithms, the LightGBM model was particularly useful for predicting END, as it revealed new and diverse predictors. Additionally, the effects of the features on the predictive power of the model were individualized using the SHAP method.

Both intracranial atherosclerotic stenosis (ICAS) and moyamoya disease (MMD) are prevalent in Asians. We hypothesized that the Ring Finger protein 213 gene polymorphism (RNF213), a susceptibility locus for MMD in East Asians, is also a susceptibility gene for ICAS in patients whose diagnosis had been confirmed by conventional angiography (absence of basal collaterals) and high-resolution MRI (HR-MRI, presence of plaque). We analyzed 532 consecutive patients with ischemic events in the middle cerebral artery (MCA) distribution and relevant stenotic lesion on the distal internal carotid artery or proximal MCA, but no demonstrable carotid or cardiac embolism sources. Additional angiography was performed on 370 (69.5%) patients and HR-MRI on 283 (53.2%) patients. Based on angiographic and HR-MRI findings, 234 patients were diagnosed with ICAS and 288 with MMD. The RNF213 variant was observed in 50 (21.4%) ICAS patients and in 119 (69.1%) MMD patients. The variant was observed in 25.2% of patients with HR-MRI-confirmed ICAS. Similarly, 15.8% of ICAS patients in whom MMD was excluded by angiography had this variant. Among the ICAS patients, RNF213 variant carriers were younger and more likely to have a family history of MMD than non-carriers were. Multivariate testing showed that only the age of ICAS onset was independently associated with the RNF213 variant (odds ratio, 0.97; 95% CI, 0.944-0.99). RNF213 is a susceptibility gene not only for MMD but also for ICAS in East Asians. Further studies are needed on RNF213 variants in ICAS patients outside East Asian populations.

Cancer and stroke, which are known to be associated with one another, are the most common causes of death in the elderly. However, the pathomechanisms that lead to stroke in cancer patients are not well known. Circulating extracellular vesicles (EVs) play a role in cancer-associated thrombosis and tumor progression. Therefore, we hypothesized that cancer cell-derived EVs cause cancer-related coagulopathy resulting in ischemic stroke. Serum levels of D-dimer and EVs expressing markers for cancer cells (epithelial cell adhesion molecule [CD326]), tissue factor (TF [CD142]), endothelial cells (CD31+CD42b-), and platelets (CD62P) were measured using flow cytometry in (a) 155 patients with ischemic stroke and active cancer (116 - cancer-related, 39 - conventional stroke mechanisms), (b) 25 patients with ischemic stroke without cancer, (c) 32 cancer patients without stroke, and (d) 101 healthy subjects. The levels of cancer cell-derived EVs correlated with the levels of D-dimer and TF+ EVs. The levels of cancer cell-derived EVs (CD326+ and CD326+CD142+) were higher in cancer-related stroke than in other groups (P<0.05 in all the cases). Path analysis showed that cancer cell-derived EVs are related to stroke via coagulopathy as measured by D-dimer levels. Poor correlation was observed between TF+ EV and D-dimer, and path analysis demonstrated that cancer cell-derived EVs may cause cancer-related coagulopathy independent of the levels of TF+ EVs. Our findings suggest that cancer cell-derived EVs mediate coagulopathy resulting in ischemic stroke via TF-independent mechanisms.

Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by progressive stenosis of large intracranial arteries and a hazy network of basal collaterals called moyamoya vessels. A polymorphism (R4810K) in the Ring Finger Protein 213 ( RNF213 ) gene, at chromosome 17q25.3, is the strongest genetic susceptibility factor for MMD in East Asian populations. MMD was regarded prevalent in childhood and in East Asian populations. However, the so-called MMD could represent only the tip of the iceberg. MMD is increasingly reported in adult patients and in Western populations. Moreover, the RNF213 variant was recently reported to be associated with non-MMD disorders, such as intracranial atherosclerosis and systemic vasculopathy (e.g., peripheral pulmonary artery stenosis and renal artery stenosis). In this review, we summarize the spectrums of RNF213 vasculopathy in terms of clinical and genetic phenotypes. Continuous efforts are required for pathophysiology-based diagnoses and treatment, which will benefit from collaboration between clinicians and researchers, and between stroke and vascular physicians.

In animal models of stroke, behavioral assessments could be complemented by a variety of neuroimaging studies to correlate them with recovery and better understand mechanisms of improvement after stem cell therapy. We evaluated morphological and connectivity changes after treatment with human mesenchymal stem cells (hMSCs) in a rat stroke model, through quantitative measurement of T 2 -weighted images and diffusion tensor imaging (DTI). Transient middle cerebral artery occlusion rats randomly received PBS (PBS-only), FBS cultured hMSCs (FBS-hMSCs), or stroke patients’ serum cultured hMSCs (SS-hMSCs). Functional improvement was assessed using a modified neurological severity score (mNSS). Quantitative analyses of T 2 -weighted ischemic lesion and ventricular volume changes were performed. Brain microstructure/connectivity changes were evaluated in the ischemic recovery area by DTI-derived microstructural indices such as relative fractional anisotropy (rFA), relative axial diffusivity (rAD), and relative radial diffusivity (rRD), and relative fiber density (rFD) analyses. According to mNSS results, the SS-hMSCs group showed the most prominent functional improvement. Infarct lesion volume of the SS-hMSCs group was significantly decreased at 2 weeks when compared to the PBS-only groups, but there were no differences between the FBS-hMSCs and SS-hMSCs groups. Brain atrophy was significantly decreased in the SS-hMSCs group compared to the other groups. In DTI, rFA and rFD values were significantly higher and rRD value was significant lower in the SS-hMSCs group and these microstructure/connectivity changes were correlated with T 2 -weighted morphological changes. T 2 -weighted volume alterations (ischemic lesion and brain atrophy), and DTI microstructural indices and rFD changes, were well matched with the results of behavioral assessment. These quantitative MRI measurements could be potential outcome predictors of functional recovery after treatment with stem cells for stroke.

Ischemic stroke is a major cause of mortality worldwide. Proper etiological subtyping of ischemic stroke is crucial for tailoring treatment strategies. This study explored the utility of circulating microRNAs encapsulated in extracellular vesicles (EV-miRNAs) to distinguish the following ischemic stroke subtypes: large artery atherosclerosis (LAA), cardioembolic stroke (CES), and small artery occlusion (SAO). Using next-generation sequencing (NGS) and machine-learning techniques, we identified differentially expressed miRNAs (DEMs) associated with each subtype. Through patient selection and diagnostic evaluation, a cohort of 70 patients with acute ischemic stroke was classified: 24 in the LAA group, 24 in the SAO group, and 22 in the CES group. Our findings revealed distinct EV-miRNA profiles among the groups, suggesting their potential as diagnostic markers. Machine-learning models, particularly logistic regression models, exhibited a high diagnostic accuracy of 92% for subtype discrimination. The collective influence of multiple miRNAs was more crucial than that of individual miRNAs. Additionally, bioinformatics analyses have elucidated the functional implications of DEMs in stroke pathophysiology, offering insights into the underlying mechanisms. Despite limitations like sample size constraints and retrospective design, our study underscores the promise of EV-miRNAs coupled with machine learning for ischemic stroke subtype classification. Further investigations are warranted to validate the clinical utility of the identified EV-miRNA biomarkers in stroke patients.

Moyamoya disease (MMD) is a rare cerebrovascular disorder characterized by stenosis of the internal carotid arteries with compensatory development of collateral vessels. Although a founder variant of RNF213, p.Arg4810Lys (c.14429G>A, rs112735431), is a major genetic risk factor for MMD in East Asians, the frequency and disease susceptibility of other variants in this gene remain largely unknown. In the present study, we investigated the association of RNF213 variants with MMD in Korean patients and population controls. For all RNF213 variants listed in the Human Gene Mutation Database (HGMD) as disease-causing or likely disease-causing mutations for MMD, genotyping was performed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Genetic data from 264 adult patients with MMD were analyzed and compared with two control populations comprised of 622 and 1,100 Korean individuals, respectively. Among the 30 RNF213 variants that were listed in the HGMD, p.Arg4810Lys was identified in 67.4% (178/264) of patients with MMD and showed a significantly higher allele frequency than in the controls, giving an odds ratio of 63.29 (95% confidence interval, 33.11-120.98) for the 622 controls and 48.55 (95% confidence interval, 31.00-76.03) for the 1100 controls. One additional variant, p.Ala5021Val (c.15062C>T, rs138130613), was identified in 0.8% (2/264) of patients; however, the allele frequencies were not significantly different from those in the controls. These results suggest that, in our cohort of Korean patients, the p.Arg4810Lys is the only variant that is strongly associated with MMD among the 30 RNF213 variants listed in the HGMD.

Purpose To validate JLK-LVO, a software detecting large vessel occlusion (LVO) on computed tomography angiography (CTA), within a multicenter dataset. Methods From 2021 to 2023, we enrolled patients with ischemic stroke who underwent CTA within 24-hour of onset at six university hospitals for validation and calibration datasets and at another university hospital for an independent dataset for testing model calibration. The diagnostic performance was evaluated using area under the curve (AUC), sensitivity, and specificity across the entire study population and specifically in patients with isolated middle cerebral artery (MCA)-M2 occlusion. We calibrated LVO probabilities using logistic regression and by grouping LVO probabilities based on observed frequency. Results After excluding 168 patients, 796 remained; the mean (SD) age was 68.9 (13.7) years, and 57.7% were men. LVO was present in 193 (24.3%) of patients, and the median interval from last-known-well to CTA was 5.7 h (IQR 2.5–12.1 h). The software achieved an AUC of 0.944 (95% CI 0.926–0.960), with a sensitivity of 89.6% (84.5–93.6%) and a specificity of 90.4% (87.7–92.6%). In isolated MCA-M2 occlusion, the AUROC was 0.880 (95% CI 0.824–0.921). Due to sparse data between 20 and 60% of LVO probabilities, recategorization into unlikely (0–20% LVO scores), less likely (20–60%), possible (60–90%), and suggestive (90–100%) provided a reliable estimation of LVO compared with mathematical calibration. The category of LVO probabilities was associated with follow-up infarct volumes and functional outcome. Conclusion In this multicenter study, we proved the clinical efficacy of the software in detecting LVO on CTA.