Enhanced overall efficiency of GaInN-based light-emitting diodes with reduced efficiency droop by Al-composition-graded AlGaN/GaN superlattice electron blocking layer

AlxGa1-xN/GaN superlattice electron blocking layers (EBLs) with gradually decreasing Al composition toward the p-type GaN layer are introduced to GaInN-based high-power light-emitting diodes (LEDs). GaInN/GaN multiple quantum well LEDs with 5- and 9-period Al-composition-graded AlxGa1-xN/GaN EBL show comparable operating voltage, higher efficiency as well as less efficiency droop than LEDs having conventional bulk AlGaN EBL, which is attributed to the superlattice doping effect, enhanced hole injection into the active region, and reduced potential drop in the EBL by grading Al compositions. Simulation results reveal a reduction in electron leakage for the superlattice EBL, in agreement with experimental results. (C) 2013 AIP Publishing LLC.open1133sciescopu

Application and evaluation of the MLVA typing assay for the Brucella abortus strains isolated in Korea

<p>Abstract</p> <p>Background</p> <p>A Brucella eradication program has been executed in Korea. To effectively prevent and control brucellosis, a molecular method for genetic identification and epidemiological trace-back must be established. As part of that, the MLVA typing assay was evaluated and applied to <it>B. abortus </it>isolates for analyzing the characteristics of the regional distribution and relationships of foreign isolates.</p> <p>Results</p> <p>A total of 177 isolates originating from 105 cattle farms for the period 1996 to 2008 were selected as representatives for the nine provinces of South Korea. A dendrogram of strain relatedness was constructed in accordance with the number of tandem repeat units for 17 loci so that it was possible to trace back in the restricted areas. Even in a farm contaminated by one source, however, the <it>Brucella </it>isolates showed an increase or decrease in one TRs copy number at some loci with high DI values. Moreover, those 17 loci was confirmed in stability via <it>in-vitro </it>and <it>in-vivo </it>passage, and found to be sufficiently stable markers that can readily identify the inoculated strain even if minor changes were detected. In the parsimony analysis with foreign <it>Brucella </it>isolates, domestic isolates were clustered distinctively, and located near the Central and Southern American isolates.</p> <p>Conclusion</p> <p>The MLVA assay has enough discrimination power in the <it>Brucella </it>species level and can be utilized as a tool for the epidemiological trace-back of the <it>B. abortus </it>isolates. But it is important to consider that <it>Brucella </it>isolates may be capable of undergoing minor changes at some loci in the course of infection or in accordance with the changes of the host.</p

Expression of Keratin 10 in Rat Organ Surface Primo-vascular Tissues

AbstractThe primo-vascular system is described as the anatomical structure corresponding to acupuncture meridians and has been identified in several tissues in the body, but its detailed anatomy and physiology are not well understood. Recently, the presence of keratin 10 (Krt10) in primo-vascular tissue was reported, but this finding has not yet been confirmed. In this study, we compared Krt10 expression in primo-vascular tissues located on the surface of rat abdominal organs with Krt10 expression on blood and lymphatic vessels. Krt10 protein (approximately 56.5 kDa) was evaluated by western blot analysis and immunohistochemistry. Krt10 (IR) in the primo-node was visualized as patchy spots around each cell or as a follicle-like structure containing a group of cells. Krt10 IR was also identified in vascular and lymphatic tissues, but its distribution was diffuse over the extracellular matrix of the vessels. Thus Krt10 protein was expressed in all three tissues tested, but the expression pattern of Krt10 in primo-vascular tissue differed from those of blood and lymphatic vascular tissues, suggesting that structural and the regulatory roles of Krt10 in primo-vascular system are different from those in blood and lymphatic vessels

Gene-based copy number variation study reveals a microdeletion at 12q24 that influences height in the Korean population

AbstractHeight is a classic polygenic trait with high heritability (h2=0.8). Recent genome-wide association studies have revealed many independent loci associated with human height. In addition, although many studies have reported an association between copy number variation (CNV) and complex diseases, few have explored the relationship between CNV and height. Recent studies reported that single nucleotide polymorphisms (SNPs) are highly correlated with common CNVs, suggesting that it is warranted to survey CNVs to identify additional genetic factors affecting heritable traits such as height.This study tested the hypothesis that there would be CNV regions (CNVRs) associated with height nearby genes from the GWASs known to affect height. We identified regions containing >1% copy number deletion frequency from 3667 population-based cohort samples using the Illumina HumanOmni1-Quad BeadChip. Among the identified CNVRs, we selected 15 candidate regions that were located within 1Mb of 283 previously reported genes. To assess the effect of these CNVRs on height, statistical analyses were conducted with samples from a case group of 370 taller (upper 10%) individuals and a control group of 1828 individuals (lower 50%).We found that a newly identified 17.7kb deletion at chromosomal position 12q24.33, approximately 171.6kb downstream of GPR133, significantly correlated with height; this finding was validated using quantitative PCR. These results suggest that CNVs are potentially important in determining height and may contribute to height variation in human populations

Safety and optimal neuroprotection of neu2000 in acute ischemic stroke with reCanalization: study protocol for a randomized, double-blinded, placebo-controlled, phase-II trial

BACKGROUND: The potential of neuroprotective agents should be revisited in the era of endovascular thrombectomy (EVT) for acute large-artery occlusion because their preclinical effects have been optimized for ischemia and reperfusion injury. Neu2000, a derivative of sulfasalazine, is a multi-target neuroprotectant. It selectively blocks N-methyl-D-aspartate receptors and scavenges for free radicals. This trial aimed to determine whether neuroprotectant administration before EVT is safe and leads to a more favorable outcome. METHODS: This trial is a phase-II, multicenter, three-arm, randomized, double-blinded, placebo-controlled, blinded-endpoint drug trial that enrolled participants aged ≥ 19 years undergoing an EVT attempt less than 8 h from symptom onset, with baseline National Institutes of Health Stroke Scale (NIHSS) score ≥ 8, Alberta Stroke Program Early CT score ≥ 6, evidence of large-artery occlusion, and at least moderate collaterals on computed tomography angiography. EVT-attempted patients are randomized into control, low-dose (2.75 g), and high-dose (5.25 g) Neu2000KWL over 5 days. Seventy participants per group are enrolled for 90% power, assuming that the treatment group has a 28.4% higher proportion of participants with functional independence than the placebo group. The primary outcome, based on intention-to-treat criteria is the improvement of modified Rankin Scale (mRS) scores at 3 months using a dichotomized model. Safety outcomes include symptomatic intracranial hemorrhage within 5 days. Secondary outcomes are distributional change of mRS, mean differences in NIHSS score, proportion of NIHSS score 0-2, and Barthel Index > 90 at 1 and 4 weeks, and 3 months. DISCUSSION: The trial results may provide information on new therapeutic options as multi-target neuroprotection might mitigate reperfusion injury in patients with acute ischemic stroke before EVT

Polarization-engineered high efficiency GaInN light-emitting diodes optimized by genetic algorithm

A genetic algorithm is employed to find an optimum epitaxial structure of multiple quantum wells (MQWs) and electron-blocking layer (EBL) for a GaInN-based light-emitting diode (LED). The optimized LED is composed of locally Si-doped quantum barriers (QBs) in the MQWs and a quaternary heterostructured AlGaInN EBL having a polarization-induced electric field directed oppositely to that of a conventional AlGaN EBL. The optimized LED shows 15.6% higher internal quantum efficiency, 24.6% smaller efficiency droop, and 0.21 V lower forward voltage at 200 A/cm(2) comparing to the reference LED, which has fully Si-doped QB and 20-nm-thick Al0.19Ga0.81N EBL. We find that local Si doping near the QB/QW interface compensates the negative polarization-induced sheet charge at the interface and reduces electric field in the QWs, thereby enhancing electron-hole wave function overlap. In addition, the inverted polarization field in the quaternary EBL provides a high barrier for electrons but a low barrier for holes, resulting in enhanced electron-blocking and hole-injection characteristics.open1113sciescopu

Densely Convolutional Spatial Attention Network for nuclei segmentation of histological images for computational pathology

IntroductionAutomatic nuclear segmentation in digital microscopic tissue images can aid pathologists to extract high-quality features for nuclear morphometrics and other analyses. However, image segmentation is a challenging task in medical image processing and analysis. This study aimed to develop a deep learning-based method for nuclei segmentation of histological images for computational pathology.MethodsThe original U-Net model sometime has a caveat in exploring significant features. Herein, we present the Densely Convolutional Spatial Attention Network (DCSA-Net) model based on U-Net to perform the segmentation task. Furthermore, the developed model was tested on external multi-tissue dataset – MoNuSeg. To develop deep learning algorithms for well-segmenting nuclei, a large quantity of data are mandatory, which is expensive and less feasible. We collected hematoxylin and eosin–stained image data sets from two hospitals to train the model with a variety of nuclear appearances. Because of the limited number of annotated pathology images, we introduced a small publicly accessible data set of prostate cancer (PCa) with more than 16,000 labeled nuclei. Nevertheless, to construct our proposed model, we developed the DCSA module, an attention mechanism for capturing useful information from raw images. We also used several other artificial intelligence-based segmentation methods and tools to compare their results to our proposed technique.ResultsTo prioritize the performance of nuclei segmentation, we evaluated the model’s outputs based on the Accuracy, Dice coefficient (DC), and Jaccard coefficient (JC) scores. The proposed technique outperformed the other methods and achieved superior nuclei segmentation with accuracy, DC, and JC of 96.4% (95% confidence interval [CI]: 96.2 – 96.6), 81.8 (95% CI: 80.8 – 83.0), and 69.3 (95% CI: 68.2 – 70.0), respectively, on the internal test data set.ConclusionOur proposed method demonstrates superior performance in segmenting cell nuclei of histological images from internal and external datasets, and outperforms many standard segmentation algorithms used for comparative analysis