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Bjerkandera adusta degrades polycyclic aromatic compound. However, its effect on preventing plant disease is unknown. We carried out both the confrontation culture and greenhouse pot experiments to address effects of B. adusta M1 strain on the growth of pathogenic Fusarium oxysporum f. sp. conglutinans (FOC) and incidence of Fusarium wilt in Brassica napus L. The results showed the hyphal growth rate of B. adusta M1 was significantly greater than that of FOC. The B. adusta M1 fermentation broth also significantly inhibited the growth of FOC hyphae by 62.79 ± 1.80%, which was greater than an inhibition rate of 40.63 ± 1.68% by the fungicide, carbendazim. The electron microscopic image showed the FOC hyphae was directly penetrated by the B. adusta M1 hyphae, indicating a strong mycoparasitism by B. adusta M1. Both the B. adusta M1 and its fermentation broth reduced the incidence and disease index of the Fusarium wilt in Br. napus, and the control effects of B. adusta M1 and its fermentation broth on Fusarium wilt were comparable or better than carbendazim. Furthermore, both the B. adusta M1 and its fermentation broth increased the activity of the defense enzymes including superoxide dismutase (25.92% and 22.38%), catalase (78.80% and 82.28%), peroxidase (46.64% and 6.83%) and phenylalanine ammonia-lyase (44.23% and 5.77%). Similarly, both the B. adusta M1 and its fermentation broth decreased the cell membrane permeability (48.68% and 33.71%) and malondialdehyde concentration (71.04% and 17.51%) of plant leaf. Therefore, B. adusta M1 can be applied as a potential biocontrol fungus to against Fusarium wilt.

Autonomous Underwater Helicopter (AUH) is a novel dish-shaped multi-functional submersible vehicle in the autonomous underwater vehicle (AUV) family. Numerical study of launch and recovery system for AUVs from a research vessel is significant in the overall design. Single-arm crane and air-launch way are the important ways of launching AUVs with the high expertise and security. However, AUVs are still easily subject to a huge impact load which can cause the body damage, malfunction of electronic components, and other serious accidents when AUVs are launching into water. In this paper, unsteady, incompressible, two-phase flow with identified boundary conditions was modeled in the computational domain using Volume of Fluid (VOF) technology, and different overset-grid sizes were set and analyzed to ascertain the accuracy of computational fluid dynamics (CFD) simulation first due to the setting of the grid which will directly affect the accuracy of the calculation results, especially the overset-grid convergence validation. Then, the change of water-entry impact force and velocity of AUH with different water-entry velocities and angles were calculated by CFD analysis software STAR-CCM + solver. The proper immersion angle of the AUH should be 75° under comprehensive analysis and comparison. Besides, the variations of pressure distribution of the AUH in the whole water-entry process were also obtained, which provides reference for the shape optimization in the future work.

Rare monogenic disorders often share molecular etiologies involved in the pathogenesis of common diseases. Congenital disorders of glycosylation (CDG) and deglycosylation (CDDG) are rare pediatric disorders with symptoms that range from mild to life threatening. A biological mechanism shared among CDG and CDDG as well as more common neurodegenerative diseases such as Alzheimer’s disease and amyotrophic lateral sclerosis, is endoplasmic reticulum (ER) stress. We developed isogenic human cellular models of two types of CDG and the only known CDDG to discover drugs that can alleviate ER stress. Systematic phenotyping confirmed ER stress and identified elevated autophagy among other phenotypes in each model. We screened 1049 compounds and scored their ability to correct aberrant morphology in each model using an agnostic cell-painting assay based on >300 cellular features. This primary screen identified multiple compounds able to correct morphological phenotypes. Independent validation shows they also correct cellular phenotypes and alleviate each of the ER stress markers identified in each model. Many of the active compounds are associated with microtubule dynamics, which points to new therapeutic opportunities for both rare and more common disorders presenting with ER stress, such as Alzheimer’s disease and amyotrophic lateral sclerosis.

Detecting small objects is a challenging task. We focus on a special case: the detection and classification of traffic signals in street views. We present a novel framework that utilizes a visual attention model to make detection more efficient, without loss of accuracy, and which generalizes. The attention model is designed to generate a small set of candidate regions at a suitable scale so that small targets can be better located and classified. In order to evaluate our method in the context of traffic signal detection, we have built a traffic light benchmark with over 15,000 traffic light instances, based on Tencent street view panoramas. We have tested our method both on the dataset we have built and the Tsinghua–Tencent 100K (TT100K) traffic sign benchmark. Experiments show that our method has superior detection performance and is quicker than the general faster RCNN object detection framework on both datasets. It is competitive with state-of-the-art specialist traffic sign detectors on TT100K, but is an order of magnitude faster. To show generality, we tested it on the LISA dataset without tuning, and obtained an average precision in excess of 90%.

In this paper, we proposed a multi-task system that can identify dish types, food ingredients, and cooking methods from food images with deep convolutional neural networks. We built up a dataset of 360 classes of different foods with at least 500 images for each class. To reduce the noises of the data, which was collected from the Internet, outlier images were detected and eliminated through a one-class SVM trained with deep convolutional features. We simultaneously trained a dish identifier, a cooking method recognizer, and a multi-label ingredient detector. They share a few low-level layers in the deep network architecture. The proposed framework shows higher accuracy than traditional method with handcrafted features, and the cooking method recognizer and ingredient detector can be applied to dishes which are not included in the training dataset to provide reference information for users.

The receptor for advanced glycation end products (RAGE) and its proinflammatory S100/calgranulin ligands are enriched in joints of subjects with rheumatoid arthritis (RA) and amplify the immune/inflammatory response. In a model of inflammatory arthritis, blockade of RAGE in mice immunized and challenged with bovine type II collagen suppressed clinical and histologic evidence of arthritis, in parallel with diminished levels of TNF-alpha, IL-6, and matrix metalloproteinases (MMP) 3, 9 and 13 in affected tissues. Allelic variation within key domains of RAGE may influence these proinflammatory mechanisms, thereby predisposing individuals to heightened inflammatory responses. A polymorphism of the RAGE gene within the ligand-binding domain of the receptor has been identified, consisting of a glycine to serine change at position 82. Cells bearing the RAGE 82S allele displayed enhanced binding and cytokine/MMP generation following ligation by a prototypic S100/calgranulin compared with cells expressing the RAGE 82G allele. In human subjects, a case-control study demonstrated an increased prevalence of the 82S allele in patients with RA compared with control subjects. These data suggest that RAGE 82S upregulates the inflammatory response upon engagement of S100/calgranulins, and, thereby, may contribute to enhanced proinflammatory mechanisms in immune/inflammatory diseases.

The receptor for advanced glycation end products (RAGE), a multi-ligand member of the immunoglobulin superfamily of cell surface molecules, interacts with distinct molecules implicated in homeostasis, development and inflammation, and certain diseases such as diabetes and Alzheimer's disease. Engagement of RAGE by a ligand triggers activation of key cell signalling pathways, such as p21ras, MAP kinases, NF-kappaB and cdc42/rac, thereby reprogramming cellular properties. RAGE is a central cell surface receptor for amphoterin, a polypeptide linked to outgrowth of cultured cortical neurons derived from developing brain. Indeed, the co-localization of RAGE and amphoterin at the leading edge of advancing neurites indicated their potential contribution to cellular migration, and in pathologies such as tumour invasion. Here we demonstrate that blockade of RAGE-amphoterin decreased growth and metastases of both implanted tumours and tumours developing spontaneously in susceptible mice. Inhibition of the RAGE-amphoterin interaction suppressed activation of p44/p42, p38 and SAP/JNK MAP kinases; molecular effector mechanisms importantly linked to tumour proliferation, invasion and expression of matrix metalloproteinases.

Gene mapping of a mouse coat mutation has been investigated. First, 100 10-bp random primers were used to amplify DNA, but the mutation could not be located by this method because there were no correlation between the amplified products and coat phenotypes. Second, by usingIdh1, Car2, Mup1, Pgb1, Hbb, Es10, Es1, Mod1, Gdc1, Ce2, Es3 as genetic markers, linkage test crosses (two-point test) consisting of intercrossing uncovered BALB/c mice (homozygotes) to CBA/N and C57BV6 mice with normal hair and backcrossing the heterozygotes of the F1 to the uncovered BALB/c mice were made. It was soon evident that the mutation was linked toEs3 on chromosome 11. Furthermore, three-point test was made by usingEs3 and D11Mit8 (a microsatellite DNA) as genetic markers. The result showed that the mutation was linked toEs3 with the percentage recombination of (7.89 ± 2.19)%, and linked to Dl1Mit8 with the percentage recombination of (26.30± 3.57)%. The percentage recombination betweenEs3 and D11Mit8 was (32.90±3.81)%. The mutation was named Uncovered, with the symbolUncv. According to the recombinations, the loci order was D11Mit8-26.30±3.57-Uncv- 7.89 -2.19-Es3. From the location on the chromosome, it was concluded that the mutation was a new mutation which affected the skin and hair structure of mouse. TheUncv has entered MGD (Mouse Genome Database).