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Simultaneously achieving both a high efficiency and long lifetime in deep-blue organic light-emitting diodes is challenging. Here we report thermally activated delayed fluorescence (TADF) organic light-emitting diodes that aim to meet this goal by combining a new design of blue TADF materials with a triplet-exciton recycling protocol. Two TADF materials, one distributing and one emitting, were doped into a host to form triplet-exciton-distributed TADF devices. The singlet excitons were transferred from the host to the emitter via the distributing TADF material by cascade energy transfer, whereas the triplet excitons were transferred to the emitter as singlet excitons by a triplet-exciton recycling process between the low-triplet-energy host and the distributing TADF material. The resulting triplet-exciton-distributed TADF devices achieved a high external quantum efficiency of 33.5 ± 0.1, a colour coordinate corrected current efficiency over 400 cd A–1, a lifetime of >5,000 h and a y colour coordinate below 0.10.Exciton energy cascade transfer and recycling bring improvements in the efficiency and lifetime of deep-blue organic light-emitting diodes.

A novel deep-learning algorithm for artificial neural networks (ANNs), completely different from the back-propagation method, was developed in a previous study. The purpose of this study was to assess the feasibility of using the algorithm for the detection of intracranial haemorrhage (ICH) and the classification of its subtypes, without employing the convolutional neural network (CNN). For the detection of ICH with the summation of all the computed tomography (CT) images for each case, the area under the ROC curve (AUC) was 0.859, and the sensitivity and the specificity were 78.0% and 80.0%, respectively. Regarding ICH localisation, CT images were divided into 10 subdivisions based on the intracranial height. With the subdivision of 41–50%, the best diagnostic performance for detecting ICH was obtained with AUC of 0.903, the sensitivity of 82.5%, and the specificity of 84.1%. For the classification of the ICH to subtypes, the accuracy rate for subarachnoid haemorrhage (SAH) was considerably excellent at 91.7%. This study revealed that our approach can greatly reduce the ICH diagnosis time in an actual emergency situation with a fairly good diagnostic performance.

A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300, 000 pMSSM model sets – each tested against 200 signal regions by ATLAS – have been used to train and validate SUSY-AI. The code is currently able to reproduce the ATLAS exclusion regions in 19 dimensions with an accuracy of at least 93 % . It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/ . An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/ .

Purpose Here, we presented our early experience with flow diversion procedures using the Surpass Evolve flow diverter (SE, Stryker) and reported the feasibility and safety profile compared to those of a control group treated with other types of flow diverters. Methods We included 31 and 53 consecutive flow diversion procedures performed using the SE and other commercial flow diverters, respectively, to treat intracranial aneurysms at our institution. We used two commercial flow diversion systems in the comparison group: the pipeline embolization device and Surpass Streamline. Results In the SE group, technical failures occurred in three (9.7%) cases, due to either incomplete wall apposition ( n  = 1, 3.2%) or stent migration ( n  = 2, 6.5%). Major complications occurred in four (12.9%) cases: delayed rupture of the target aneurysm ( n  = 1, 3.2%), major ischemic stroke ( n  = 1, 3.2%), sudden death from an unidentified cause ( n  = 1, 3.2%), and parent artery occlusion with stent thrombosis ( n  = 1, 3.2%). Balloon angioplasty was performed in eight (25.8%) cases. On post-procedure MRI, a DWI-positive lesion was detected in three (9.7%) cases. After multivariate adjustment, the SE group was independently associated with less procedural time of ≥ 90 min (adjusted OR, 0.09; 95% CI, 0.03–0.29; p  < 0.001), balloon angioplasty (adjusted OR, 0.22; 95% CI, 0.07–0.75; p  = 0.015), and DWI-positive lesions (adjusted OR, 0.04; 95% CI, 0.01–0.19; p  < 0.001). Conclusion The SE is safe and easy to deploy.

Background The standard Centiloid (CL) method was proposed to harmonize and quantify global 18 F-labeled amyloid beta (Aβ) PET ligands using MRI as an anatomical reference. However, there is need for harmonizing and quantifying regional Aβ uptakes between ligands using CT as an anatomical reference. In the present study, we developed and validated a CT-based regional direct comparison of 18 F-florbetaben (FBB) and 18 F-flutemetamol (FMM) Centiloid (rdcCL). Methods For development of MRI-based or CT-based rdcCLs, the cohort consisted of 63 subjects (20 young controls (YC) and 18 old controls (OC), and 25 participants with Alzheimer’s disease dementia (ADD)). We performed a direct comparison of the FMM-FBB rdcCL method using MRI and CT images to define a common target region and the six regional VOIs of frontal, temporal, parietal, posterior cingulate, occipital, and striatal regions. Global and regional rdcCL scales were compared between MRI-based and CT-based methods. For clinical validation, the cohort consisted of 2245 subjects (627 CN, 933 MCI, and 685 ADD). Results Both MRI-based and CT-based rdcCL scales showed that FMM and FBB were highly correlated with each other, globally and regionally ( R 2 = 0.96~0.99). Both FMM and FBB showed that CT-based rdcCL scales were highly correlated with MRI-based rdcCL scales ( R 2 = 0.97~0.99). Regarding the absolute difference of rdcCLs between FMM and FBB, the CT-based method was not different from the MRI-based method, globally or regionally ( p value = 0.07~0.95). In our clinical validation study, the global negative group showed that the regional positive subgroup had worse neuropsychological performance than the regional negative subgroup ( p < 0.05). The global positive group also showed that the striatal positive subgroup had worse neuropsychological performance than the striatal negative subgroup ( p < 0.05). Conclusions Our findings suggest that it is feasible to convert regional FMM or FBB rdcSUVR values into rdcCL scales without additional MRI scans. This allows a more easily accessible method for researchers that can be applicable to a variety of different conditions.

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.

Both Moyamoya disease (MMD) and intracranial atherosclerotic stenosis (ICAS) are more prevalent in Asians than in Westerners. We hypothesized that a substantial proportion of patients with adult-onset MMD were misclassified as having ICAS, which may in part explain the high prevalence of intracranial atherosclerotic stroke in Asians. We analyzed 352 consecutive patients with ischemic events within the MCA distribution and relevant intracranial arterial stenosis, but no demonstrable carotid or cardiac embolism sources. Conventional angiography was performed in 249 (70.7%) patients, and the remains underwent MRA. The occurrence of the c.14429G>A (p.Arg4810Lys) variant in ring finger protein 213 (RNF213) was analyzed. This gene was recently identified as a susceptibility gene for MMD in East Asians. The p.Arg4810Lys variant was observed in half of patients with intracranial stenosis (176 of 352, 50.0%), in no healthy control subjects (n = 51), and in 3.2% of stroke control subjects (4 of 124 patients with other etiologies). The presence of basal collaterals, bilateral involvement on angiography, and absence of diabetes were independently associated with the presence of the RNF213 variant. Among 131 patients who met all three diagnostic criteria and were diagnosed with MMD, three-fourths (75.6%) had this variant. However, a significant proportion of patients who met two criteria (57.7%), one criterion (28.6%), or no criteria (20.0%) also had this variant. Some of them developed typical angiographic findings of MMD on follow-up angiography. Careful consideration of MMD is needed when diagnosing ICAS because differential therapeutic strategies are required for these diseases and due to the limitations of the current diagnostic criteria for MMD.

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.

Background Cholesterol plays important roles in β-amyloid (Aβ) metabolism and atherosclerosis. However, the relationships of plasma cholesterol levels with Aβ and cerebral small vessel disease (CSVD) burdens are not fully understood in Asians. Herein, we investigated the relationships between plasma cholesterol profile components and Aβ and CSVD burdens in a large, non-demented Korean cohort. Methods We enrolled 1,175 non-demented participants (456 with unimpaired cognition [CU] and 719 with mild cognitive impairment [MCI]) aged ≥ 45 years who underwent Aβ PET at the Samsung Medical Center in Korea. We performed linear regression analyses with each cholesterol (low-density lipoprotein cholesterol [LDL-c], high-density lipoprotein cholesterol [HDL-c], and triglyceride) level as a predictor and each image marker (Aβ uptake on PET, white matter hyperintensity [WMH] volume, and hippocampal volume) as an outcome after controlling for potential confounders. Results Increased LDL-c levels (β = 0.014 to 0.115, p  = 0.013) were associated with greater Aβ uptake, independent of the APOE e4 allele genotype and lipid-lowering medication. Decreased HDL-c levels (β =  − 0.133 to − 0.006, p  = 0.032) were predictive of higher WMH volumes. Increased LDL-c levels were also associated with decreased hippocampal volume (direct effect β =  − 0.053, p  = 0.040), which was partially mediated by Aβ uptake (indirect effect β =  − 0.018, p  = 0.006). Conclusions Our findings highlight that increased LDL-c and decreased HDL-c levels are important risk factors for Aβ and CSVD burdens, respectively. Furthermore, considering that plasma cholesterol profile components are potentially modified by diet, exercise, and pharmacological agents, our results provide evidence that regulating LDL-c and HDL-c levels is a potential strategy to prevent dementia.

PurposeAlthough most deep learning (DL) studies have reported excellent classification accuracy, these studies usually target typical Alzheimer’s disease (AD) and normal cognition (NC) for which conventional visual assessment performs well. A clinically relevant issue is the selection of high-risk subjects who need active surveillance among equivocal cases. We validated the clinical feasibility of DL compared with visual rating or quantitative measurement for assessing the diagnosis and prognosis of subjects with equivocal amyloid scans.Methods18F-florbetaben scans of 430 cases (85 NC, 233 mild cognitive impairment, and 112 AD) were assessed through visual rating-based, quantification-based, and DL-based methods. DL was trained using 280 two-dimensional PET images (80%) and tested by randomly assigning the remaining (70 cases, 20%) cases and a clinical validation set of 54 equivocal cases. In the equivocal cases, we assessed the agreement among the visual rating, quantification, and DL and compared the clinical outcome according to each modality-based amyloid status.ResultsThe visual reading was positive in 175 cases, equivocal in 54 cases, and negative in 201 cases. The composite SUVR cutoff value was 1.32 (AUC 0.99). The subject-level performance of DL using the test set was 100%. Among the 54 equivocal cases, 37 cases were classified as positive (Eq(deep+)) by DL, 40 cases were classified by a second-round visual assessment, and 40 cases were classified by quantification. The DL- and quantification-based classifications showed good agreement (83%, κ = 0.59). The composite SUVRs differed between Eq(deep+) (1.47 [0.13]) and Eq(deep−) (1.29 [0.10]; P < 0.001). DL, but not the visual rating, showed a significant difference in the Mini-Mental Status Examination score change during the follow-up between Eq(deep+) (− 4.21 [0.57]) and Eq(deep−) (− 1.74 [0.76]; P = 0.023) (mean duration, 1.76 years).ConclusionsIn visually equivocal scans, DL was more related to quantification than to visual assessment, and the negative cases selected by DL showed no decline in cognitive outcome. DL is useful for clinical diagnosis and prognosis assessment in subjects with visually equivocal amyloid scans.