Rice (Oryza sativa L.) is a chilling-sensitive staple crop that originated in subtropical regions of Asia. Introduction of the chilling tolerance trait enables the expansion of rice cultivation to temperate regions. Here we report the cloning and characterization of HAN1, a quantitative trait locus (QTL) that confers chilling tolerance on temperate japonica rice. HAN1 encodes an oxidase that catalyzes the conversion of biologically active jasmonoyl-L-isoleucine (JA-Ile) to the inactive form 12-hydroxy-JA-Ile (12OH-JA-Ile) and fine-tunes the JA-mediated chilling response. Natural variants in HAN1 diverged between indica and japonica rice during domestication. A specific allele from temperate japonica rice, which gained a putative MYB cis-element in the promoter of HAN1 during the divergence of the two japonica ecotypes, enhances the chilling tolerance of temperate japonica rice and allows it to adapt to a temperate climate. The results of this study extend our understanding of the northward expansion of rice cultivation and provide a target gene for the improvement of chilling tolerance in rice.

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Cyadox (CYX), (2-formylquinoxaline)-N(1),N(4)-dioxide cyanoacetylhydrazone, is a growth promoter, which is more efficient and less toxic to animals. Few studies have been performed to reveal the metabolism of CYX in animals till now. In this study, the metabolic fate of CYX in the liver microsomes of animal was investigated firstly using high-performance liquid chromatography combined with hybrid ion trap/time-of-flight mass spectrometry. CYX was incubated with rat, chicken and pig liver microsomes in the presence of a NADPH-generating system. Multiple scans of metabolites in MS and MS(2) modes and accurate mass measurements were performed simultaneously through data-dependent acquisition. Most measured mass errors were less than 10 ppm for both protonated molecules and fragment ions using external mass calibration. The structures of metabolites and their fragment ions were easily and reliably characterized based on the accurate MS(2) spectra and known structure of CYX. The relative biotransformation of CYX into characterized metabolites was estimated based on the UV absorption and the assumption that all metabolites had the same extinction coefficient as the parent compound at 305 nm. Totally, seven metabolites were identified as three reduced metabolites (cyadox 1-monoxide (Cy1), cyadox 4-monoxide (Cy2) and bisdesoxycyadox (Cy4)), three hydrolysis metabolites of the amide bond (N-decyanoacetyl cyadox (Cy5), N-decyanoacetyl cyadox 1-monoxide (Cy6) and N-decyanoacetyl bisdesoxycyadox (Cy7)) and a hydroxylation metabolite of Cy1 (Cy3). Cy1-Cy6 could be detected in rat, chicken and pig liver microsomes while metabolite Cy7 could only be observed in pig. The amounts of the metabolites in three species are different. For the formations of Cy1 and Cy3, the rank order was rat approximately chicken > pig. For Cy4 and Cy5, the order was pig > rat > chicken. Cy1 and Cy4 have been previously reported, whereas the other five metabolites were novel. The N-->O group reduction and hydroxylation were the main metabolic pathways for CYX in the three species.

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During image segmentation tasks in computer vision, achieving high accuracy performance while requiring fewer computations and faster inference is a big challenge. This is especially important in medical imaging tasks but one metric is usually compromised for the other. To address this problem, this paper presents an extremely fast, small and computationally effective deep neural network called Stripped-Down UNet (SD-UNet), designed for the segmentation of biomedical data on devices with limited computational resources. By making use of depthwise separable convolutions in the entire network, we design a lightweight deep convolutional neural network architecture inspired by the widely adapted U-Net model. In order to recover the expected performance degradation in the process, we introduce a weight standardization algorithm with the group normalization method. We demonstrate that SD-UNet has three major advantages including: (i) smaller model size (23x smaller than U-Net); (ii) 8x fewer parameters; and (iii) faster inference time with a computational complexity lower than 8M floating point operations (FLOPs). Experiments on the benchmark dataset of the Internatioanl Symposium on Biomedical Imaging (ISBI) challenge for segmentation of neuronal structures in electron microscopic (EM) stacks and the Medical Segmentation Decathlon (MSD) challenge brain tumor segmentation (BRATs) dataset show that the proposed model achieves comparable and sometimes better results compared to the current state-of-the-art.

T-2 toxin, a highly toxic member of the type-A trichothecenes, is produced by various Fusarium moulds that can potentially affect human health. It is strongly cytotoxic for human hematopoietic progenitors. Alimentary toxic aleukia (ATA), a disease typically associated with human, is primarily induced by T-2 toxin. A comparison of the metabolism of T-2 toxin incubated with hepatocytes of rats, piglets, chickens, and the hepatic subcellular fractions (microsomes and cytosol) of piglets, chickens, rats, and carp (common carp and grass carp) was carried out. The activities of the recombinant pig CYP3A29 on the transformation of T-2 and HT-2 toxins were preliminary studied. Metabolites were identified by novel LC/MS-IT-TOF. Qualitative similarities and differences across the species were observed. In liver microsomes, HT-2 toxin, neosolaniol (NEO), 3'-OH-T-2, and 3'-OH-HT-2 were detected in rats, chickens, and pigs. 3'-OH-HT-2 and HT-2 toxin was not detectable in common carp and grass crap, respectively. Moreover, in liver microsomes, the hydroxyl metabolites accounted for the largest percentage in carp, whereas the hydrolysis product, HT-2 toxin, was the major one for the land animals. Only hydrolysis products such as NEO and HT-2 toxin were detected in hepatocytes. Recombinant pig CYP3A29 was able to convert T-2 and HT-2 toxins to high rates of 3'-OH-T-2 and 3'-OH-HT-2, respectively. Both CYP450 and carboxylesterase enzymes have been found to play a role in the metabolism of T-2 toxin. Metabolism of T-2 toxin across species produces a similar spectrum of metabolites. Preliminary metabolic studies of carp reveal that ester hydrolysis of T-2 toxin in carp may not play as important a role as is the case with land animals.

Segmentation of infrared (IR) ship images is always a challenging task, because of the intensity inhomogeneity and noise. The fuzzy C-means (FCM) clustering is a classical method widely used in image segmentation. However, it has some shortcomings, like not considering the spatial information or being sensitive to noise. In this paper, an improved FCM method based on the spatial information is proposed for IR ship target segmentation. The improvements include two parts: 1) adding the nonlocal spatial information based on the ship target and 2) using the spatial shape information of the contour of the ship target to refine the local spatial constraint by Markov random field. In addition, the results of K -means are used to initialize the improved FCM method. Experimental results show that the improved method is effective and performs better than the existing methods, including the existing FCM methods, for segmentation of the IR ship images.