Notes

Health proteins oligomer construction prediction making use of GALAXY within CASP14.
Optical opacity reduces quality of biometry images, making it potentially difficult to find the correct location for irradiation during femtosecond laser-assisted cataract surgery (FLACS). After experiencing a case of posterior capsule (PC) rupture because of optical opacity, we started lens thickness (LT) inspection, which indicates comparison of between intra- and pre-operatively measured LT. We retrospectively investigated the effectiveness of the LT inspection. One observer reviewed all FLACS treatment summaries for 3 years by CATALYS in the Jikei University Hospital, Tokyo. Based on the lines defining the PC on intraoperative OCT images, all cases were classified into three groups undescribed, appropriate and inappropriate PC. Among the 1070 cases, 1047 cases had appropriate PC. In 19 cases, the PC line was undescribed because of dense cataract. Among 474 cases with no inspection, 4 cases had an inappropriate PC. Whereas, in 596 cases with the LT inspection, there was no case of an inappropriate PC. LT inspection significantly reduced the cases with inappropriate PC. The safety margins normally work to prevent severe complications. However, rare outlier cases had a high risk of severe complications. We propose LT inspection could be the most practical and convenient way for safety surgery.We demonstrated high-quality single crystalline a-plane undoped-gallium nitride grown on a nonpatterned r-plane sapphire substrate via metal-organic chemical vapor deposition. Pilaralisib in vivo The effect of four different numbers of sandwiched strain-periodic AlN/GaN multilayers on the strain state, crystal quality, optical and electrical properties was investigated. Field emission scanning electron microscopy and atomic force microscopy showed that the surface morphology was improved upon insertion of 120 pairs of AlN/GaN thin layers with a root-mean-square roughness of 2.15 nm. On-axis X-ray ω-scan rocking curves showed enhanced crystalline quality the full width at half maximum decreased from 1224 to 756 arcsec along the [0001] direction and from 2628 to 1360 arcsec along the [1-100] direction for a-GaN grown with 120 pairs of AlN/GaN compared to a-GaN without AlN/GaN pairs. Reciprocal space mapping showed that a-plane GaN with a high number of AlN/GaN pairs exhibits near-relaxation strain states. Room-temperature photoluminescence spectra showed that the sample with the highest number of AlN/GaN pairs exhibited the lowest-intensity yellow and blue luminescence bands, indicating a reduction in defects and dislocations. The a-plane InGaN/GaN LEDs with 120 pairs of SSPM-L AlN/GaN exhibited a significant increase (~ 250%) in light output power compared to that of LEDs without SSPM-L AlN/GaN pairs.Sensory genes play a key role in the host location of parasitoids. To date, the sensory genes that regulate parasitoids to locate gall-inducing insects have not been uncovered. An obligate ectoparasitoid, Quadrastichus mendeli Kim & La Salle (Hymenoptera Eulophidae Tetrastichinae), is one of the most important parasitoids of Leptocybe invasa, which is a global gall-making pest in eucalyptus plantations. Interestingly, Q. mendeli can precisely locate the larva of L. invasa, which induces tumor-like growth on the eucalyptus leaves and stems. Therefore, Q. mendeli-L. invasa provides an ideal system to study the way that parasitoids use sensory genes in gall-making pests. In this study, we present the transcriptome of Q. mendeli using high-throughput sequencing. In total, 31,820 transcripts were obtained and assembled into 26,925 unigenes in Q. mendeli. Then, the major sensory genes were identified, and phylogenetic analyses were performed with these genes from Q. mendeli and other model insect species. Three chemosensory proteins (CSPs), 10 gustatory receptors (GRs), 21 ionotropic receptors (IRs), 58 odorant binding proteins (OBPs), 30 odorant receptors (ORs) and 2 sensory neuron membrane proteins (SNMPs) were identified in Q. mendeli by bioinformatics analysis. Our report is the first to obtain abundant biological information on the transcriptome of Q. mendeli that provided valuable information regarding the molecular basis of Q. mendeli perception, and it may help to understand the host location of parasitoids of gall-making pests.Au nanoparticles synthesized from colloidal techniques have the capability in many applications such as catalysis and sensing. Au nanoparticles function as both catalyst and highly sensitive SERS probe can be employed for sustainable and green catalytic process. However, capping ligands that are necessary to stabilize nanoparticles during synthesis are negative for catalytic activity. In this work, a simple effective mild thermal treatment to remove capping ligands meanwhile preserving the high SERS sensitivity of Au nanoparticles is reported. We show that under the optimal treatment conditions (250 °C for 2 h), 50 nm Au nanoparticles surfaces are free from any capping molecules. The catalytic activity of treated Au nanoparticles is studied through H2O2 decomposition, which proves that the treatment is favorable for catalytic performance improvement. A reaction intermediate during H2O2 decomposition is observed and identified.Diabetic retinopathy (DR) is a leading cause of blindness and affects millions of people throughout the world. Early detection and timely checkups are key to reduce the risk of blindness. Automated grading of DR is a cost-effective way to ensure early detection and timely checkups. Deep learning or more specifically convolutional neural network (CNN)-based methods produce state-of-the-art performance in DR detection. Whilst CNN based methods have been proposed, no comparisons have been done between the extracted image features and their clinical relevance. Here we first adopt a CNN visualization strategy to discover the inherent image features involved in the CNN's decision-making process. Then, we critically analyze those features with respect to commonly known pathologies namely microaneurysms, hemorrhages and exudates, and other ocular components. We also critically analyze different CNNs by considering what image features they pick up during learning to predict and justify their clinical relevance. The experiments are executed on publicly available fundus datasets (EyePACS and DIARETDB1) achieving an accuracy of 89 ~ 95% with AUC, sensitivity and specificity of respectively 95 ~ 98%, 74 ~ 86%, and 93 ~ 97%, for disease level grading of DR.
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