Extracranial Artery Stenosis Is Associated With Total MRI Burden of Cerebral Small Vessel Disease in Ischemic Stroke Patients of Suspected Small or Large Artery Origins

Background and Purpose: Extracranial artery stenosis (ECAS) is related to individual imaging markers of cerebral small vessel disease (cSVD). However, little has been reported on the association between ECAS and the total burden of cSVD as assessed by magnetic resonance imaging (MRI). The purpose of this study was to investigate the relationship between ECAS and cSVD burden in patients with ischemic stroke of suspected small or large artery origin.Methods: We reviewed consecutive patients with ischemic stroke of suspected small or large artery origin who underwent color Doppler ultrasonography and brain MRI. Bilateral extracranial cerebral arteries including common carotid artery, internal carotid artery (ICA), and proximal vertebral artery (VA, ostium, V2–3 segments) were assessed using color Doppler ultrasonography. ECAS severity was classified as no/mild stenosis, moderate stenosis, severe stenosis, or occlusion. The total cSVD score was assessed by awarding one point according to the load of each of these cSVD markers as determined using MRI; lacunar infarction, white matter hyperintensities, cerebral microbleeds, and enlarged perivascular spaces. The relationship between ECAS severity and cSVD burden according to MRI was examined.Results: Two hundred and twenty one patients were included in this study (mean age 61 ± 12 years, 75.6% male). Hypertension, current smoking, hyperlipidaemia, and diabetic mellitus were frequent among the patients (67.4, 45.7, 43.9, and 36.7%, respectively), while the other vascular risk factors including previous stroke or TIA and alcohol excess were less frequent (19.0 and 15.4%, respectively). Patients with higher total cSVD burden was significantly older and had severer ECAS. The frequency of hypertension was significantly higher in patients with higher total cSVD burden. This analysis indicated that that increasing ECAS severity (from no stenosis through to 100%) was independently associated with increasing total cSVD score after adjusting for other vascular risk factors (odds ratio 1.76, 95% CI [1.16–2.69]).Conclusions: In this study, high levels of ECAS from ultrasound evidence were associated with coexisting advanced cerebral cSVD in ischemic stroke patients of suspected small or large artery origin. Further studies are required to determine if and how extracranial arterial imaging helps reduce cSVD burden or improves cognitive function

Genome-wide characterization of the biggest grass, bamboo, based on 10,608 putative full-length cDNA sequences

<p>Abstract</p> <p>Background</p> <p>With the availability of rice and sorghum genome sequences and ongoing efforts to sequence genomes of other cereal and energy crops, the grass family (Poaceae) has become a model system for comparative genomics and for better understanding gene and genome evolution that underlies phenotypic and ecological divergence of plants. While the genomic resources have accumulated rapidly for almost all major lineages of grasses, bamboo remains the only large subfamily of Poaceae with little genomic information available in databases, which seriously hampers our ability to take a full advantage of the wealth of grass genomic data for effective comparative studies.</p> <p>Results</p> <p>Here we report the cloning and sequencing of 10,608 putative full length cDNAs (FL-cDNAs) primarily from Moso bamboo, <it>Phyllostachys heterocycla </it>cv. <it>pubescens</it>, a large woody bamboo with the highest ecological and economic values of all bamboos. This represents the third largest FL-cDNA collection to date of all plant species, and provides the first insight into the gene and genome structures of bamboos. We developed a Moso bamboo genomic resource database that so far contained the sequences of 10,608 putative FL-cDNAs and nearly 38,000 expressed sequence tags (ESTs) generated in this study.</p> <p>Conclusion</p> <p>Analysis of FL-cDNA sequences show that bamboo diverged from its close relatives such as rice, wheat, and barley through an adaptive radiation. A comparative analysis of the lignin biosynthesis pathway between bamboo and rice suggested that genes encoding caffeoyl-CoA O-methyltransferase may serve as targets for genetic manipulation of lignin content to reduce pollutants generated from bamboo pulping.</p

Regulating Top-Surface Multilayer/Single-Crystal Graphene Growth by “Gettering” Carbon Diffusion at Backside of the Copper Foil

A unique strategy is reported to constrain the nucleation centers for multilayer graphene (MLG) and, later, single-crystal graphene domains by gettering carbon source on backside of the flat Cu foil, during chemical vapor deposition. Hitherto, for a flat Cu foil, the top-surface-based growth mechanism is emphasized, while overlooking the graphene on the backside. However, the systematic experimental findings indicate a strong correlation between the backside graphene and the nucleation centers on the top-surface, governed by the carbon diffusion through the bulk Cu. This understanding steers to devise a strategy to mitigate the carbon diffusion to the top-surface by using a carbon “getter” substrate, such as nickel, on the backside of the Cu foil. Depth profiling of the nickel substrate, along with the density functional theory calculations, verifies the gettering role of the nickel support. The implementation of the backside carbon gettering approach on single-crystal graphene growth results in lowering the nucleation density by two orders of magnitude. This enables the single-crystal domains to grow by 6 mm laterally on the untreated Cu foil. Finally, the growth of large-area polycrystalline single layer graphene, free of unwanted MLG domains, with significantly improved field-effect mobility of ≈6800 cm^2 V^(−1) s^(−1) is demonstrated

Acceleration of on-axis and ring-shaped electron beams in wakefields driven by Laguerre-Gaussian pulses

The acceleration of electron beams with multiple transverse structures in wakefields driven by Laguerre-Gaussian pulses has been studied through three-dimensional (3D) particle-in-cell simulations. Under different laser-plasma conditions, the wakefield shows different transverse structures. In general cases, the wakefield shows a donut-like structure and it accelerates the ring-shaped hollow electron beam. When a lower plasma density or a smaller laser spot size is used, besides the donut-like wakefield, a central bell-like wakefield can also be excited. The wake sets in the center of the donut-like wake. In this case, both a central on-axis electron beam and a ring-shaped electron beam are simultaneously accelerated. Further, reducing the plasma density or laser spot size leads to an on-axis electron beam acceleration only. The research is beneficial for some potential applications requiring special pulse beam structures, such as positron acceleration and collimation

Privacy reinforcement learning for faults detection in the smart grid

Recent anticipated advancements in ad hoc Wireless Mesh Networks (WMN) have made them strong natural candidates for Smart Grid’s Neighborhood Area Network (NAN) and the ongoing work on Advanced Metering Infrastructure (AMI). Fault detection in these types of energy systems has recently shown lots of interest in the data science community, where anomalous behavior from energy platforms is identified. This paper develops a new framework based on privacy reinforcement learning to accurately identify anomalous patterns in a distributed and heterogeneous energy environment. The local outlier factor is first performed to derive the local simple anomalous patterns in each site of the distributed energy platform. A reinforcement privacy learning is then established using blockchain technology to merge the local anomalous patterns into global complex anomalous patterns. Besides, different optimization strategies are suggested to improve the whole outlier detection process. To demonstrate the applicability of the proposed framework, intensive experiments have been carried out on well-known CASAS (Center of Advanced Studies in Adaptive Systems) platform. Our results show that our proposed framework outperforms the baseline fault detection solutions.publishedVersio