The B-box transcription factor IbBBX29 regulates leaf development and flavonoid biosynthesis in sweet potato.

Plant flavonoids are valuable natural antioxidants. Sweet potato (Ipomoea batatas) leaves are rich in flavonoids, regenerate rapidly, and can adapt to harsh environments, making them an ideal material for flavonoid biofortification. Here, we demonstrate that the B-box (BBX) family transcription factor IbBBX29 regulates the flavonoid contents and development of sweet potato leaves. IbBBX29 was highly expressed in sweet potato leaves and significantly induced by auxin (IAA). Overexpression of IbBBX29 contributed to a 21.37%-70.94% increase in leaf biomass, a 12.08%-21.85% increase in IAA levels, and a 31.33%-63.03% increase in flavonoid accumulation in sweet potato, whereas silencing this gene produced opposite effects. Heterologous expression of IbBBX29 in Arabidopsis (Arabidopsis thaliana) led to a dwarfed phenotype, along with enhanced IAA and flavonoid accumulation. RNA-seq analysis revealed that IbBBX29 modulates the expression of genes involved in the IAA signaling and flavonoid biosynthesis pathways. Chromatin immunoprecipitation-quantitative polymerase chain reaction and electrophoretic mobility shift assay indicated that IbBBX29 targets key genes of IAA signaling and flavonoid biosynthesis to activate their expression by binding to specific T/G-boxes in their promoters, especially those adjacent to the transcription start site. Moreover, IbBBX29 physically interacted with developmental and phenylpropanoid biosynthesis-related proteins, such as AGAMOUS-LIKE 21 protein IbAGL21 and MYB308-like protein IbMYB308L. Finally, overexpressing IbBBX29 also increased flavonoid contents in sweet potato storage roots. These findings indicate that IbBBX29 plays a pivotal role in regulating IAA-mediated leaf development and flavonoid biosynthesis in sweet potato and Arabidopsis, providing a candidate gene for flavonoid biofortification in plants.

Identification and transcriptome data analysis of ARF family genes in five Orchidaceae species.

The Orchidaceae is a large family of perennial herbs especially noted for the exceptional diversity of specialized flowers. Elucidating the genetic regulation of flowering and seed development of orchids is an important research goal with potential utility in orchid breeding programs. Auxin Response Factor (ARF) genes encode auxin-responsive transcription factors, which are involved in the regulation of diverse morphogenetic processes, including flowering and seed development. However, limited information on the ARF gene family in the Orchidaceae is available. In this study, 112 ARF genes were identified in the genomes of 5 orchid species (Apostasia shenzhenica, Dendrobium catenatum, Phalaenopsis aphrodite, Phalaenopsis equestris and Vanilla planifolia,). These genes were grouped into 7 subfamilies based on their phylogenetic relationships. Compared with the ARF family in model plants, such as Arabidopsis thaliana and Oryza sativa, one group of ARF genes involved in pollen wall synthesis has been lost during evolution of the Orchidaceae. This loss corresponds with absence of the exine in the pollinia. Through mining of the published genomic and transcriptomic data for the 5 orchid species: the ARF genes of subfamily 4 may play an important role in flower formation and plant growth, whereas those of subfamily 3 are potentially involved in pollen wall development. the study results provide novel insights into the genetic regulation of unique morphogenetic phenomena of orchids, which lay a foundation for further analysis of the regulatory mechanisms and functions of sexual reproduction-related genes in orchids.

Cypermethrin and/or sulfamethoxazole exposure effect on apoptosis and endoplasmic reticulum of grass carp cardiomyocyte.

With the soar use range of pesticides and antibiotics in agricultural production, the pollution of surrounding runoff has become more severe; thus, the health and safety of non-target species such as fish are at risk. Excessive amounts of cypermethrin (CMN, 0.651 mg/l) and sulfamethoxazole (SMZ, 0.3 mg/l) are known to trigger oxidative stress and endoplasmic reticulum stress, resulting in toxic effects on cells. The damage degree of poisons on grass carp and the effect of the corresponding axis pathway PERK/eif2α/CHOP are still unknown. Therefore, our study set up two single poison groups (CMN/SMZ) and a combined poison group (CMN&SMZ) to detect this pathway and related indicators. After detection, the content of MDA both in CMN and SMZ group myocardium tissue was increased, while the SOD, CAT activity and GSH levels were decreased. Apoptosis-related genes (Bax, PUMA, P53 and Caspase-3/9), inflammation-related genes (TNF-α, iNOS and IL-1ß/6/8), ER stress pathway PERK/eif2α/CHOP and related genes (ATF6, IRE1a and GRP78) were all increased; in contrast, the anti-apoptotic gene Bcl-2 was down-regulated. From the overall trend observation, the apoptosis proportion of cardiomyocytes in the combined poison group was higher than that of the single poison. In summary, this study shows that CMZ and SMZ can induce oxidative stress and subsequent ER stress in grass carp cardiomyocytes by regulating the PERK/eif2α/CHOP signaling axle, thereby inducing apoptosis, and followed by inflammatory responses. The combined effect of the CMZ and SMZ mixture was severer than that of a single poison (CMZ or SMZ), so it can be inferred that the damage degree of grass carp myocardium tissue would be aggravated with the appearance of CMZ or/and SMZ. The experimental results of this study have suggestions and warnings for the toxicological research of CMZ and SMZ and the management of industrial and ecological balance.

Chip-scale humidity sensor based on a silicon nanobeam cavity.

In this Letter, a novel humidity sensor based on a chip-scale silicon nanobeam cavity with polymethyl methacrylate (PMMA) cladding is demonstrated. This sensor is easy to fabricate and compatible with CMOS technology. It shows a humidity sensing with a linear wavelength dependence of 22.9 pm/% relative humidity (RH) in a wide range of RH from 10% to 85%, an ultra-fast response time of 540 ms, and high stability. After annealing, the sensor exhibits high reversibility, repeatability, and temperature insensitivity at the range of 25°C-40°C. To the best of our knowledge, this is the first application of integrated photonics in high performance humidity detection. It provides a new way for the chip-scale sensor to integrate with photonic devices and optical systems.

Effects of X-ray on the metacestodes of Echinococcus granulosus in vitro.

BACKGROUND: Radiotherapy may represent an alternative treatment modality for cystic echinococcosis (CE), but there is no adequate evidence for it up to now. In this study, we aim to investigate the parasiticidal effects of X-ray on the metacestodes of Echinococcus granulosus in vitro. METHODS: Protoscoleces obtained from sheep naturally infected with CE were cultivated in RPMI 1640 medium containing 10% fetal bovine serum (FBS) at 37 °C in 5% CO2. Upon encystation on day 14, the metacestodes were subjected to various intensities of X-ray. Metacestode structures were observed using light microscope and transmission electron microscopy (TEM), and Real-Time PCR was carried out to determine the expression of EgTPX, EgHSP70, EgEPC1 and Caspase-3. RESULTS: On day 14, encystation was noticed in the majority of protoscoleces in the control group. In the X-ray groups, the encystation rate showed significant decrease compared with that of the control group (P < 0.05), especially the groups subjected to a dose of ≥40 Gy (P < 0.01). Light microscope findings indicated the hooklets on the rostellum were deranged in the irradiation group, and malformation was noticed in the suckers in a dose dependent manner. For the TEM findings, the cellular structure of the germinal layer of the cysts was completely interrupted by X-ray on day 7. The expression of EgTPX, EgHSP70, EgEPC1 and Caspase-3 was up-regulated after irradiation, especially at a dose of ≥45Gy (P < 0.05). CONCLUSIONS: X-ray showed parasiticidal effects on the metacestodes of E. granulosus. Irradiation triggered increased expression of EgTPX, EgHSP70, EgEPC1 and Caspase-3.

Color components determination and full-length comparative transcriptomic analyses reveal the potential mechanism of carotenoid synthesis during Paphiopedilum armeniacum flowering.

Background: Paphiopedilum armeniacum (P. armeniacum), an ornamental plant native to China, is known for its distinctive yellow blossoms. However, the mechanisms underlying P. armeniacum flower coloration remain unclear. Methods: We selected P. armeniacum samples from different flowering stages and conducted rigorous physicochemical analyses. The specimens were differentiated based on their chemical properties, specifically their solubilities in polar solvents. This key step enabled us to identify the main metabolite of flower color development of P. armeniacum, and to complete the identification by High-performance liquid chromatography (HPLC) based on the results. Additionally, we employed a combined approach, integrating both third-generation full-length transcriptome sequencing and second-generation high-throughput transcriptome sequencing, to comprehensively explore the molecular components involved. Results: We combined physical and chemical analysis with transcriptome sequencing to reveal that carotenoid is the main pigment of P. armeniacum flower color. Extraction colorimetric method and HPLC were used to explore the characteristics of carotenoid accumulation during flowering. We identified 28 differentially expressed carotenoid biosynthesis genes throughout the flowering process, validated their expression through fluorescence quantification, and discovered 19 potential positive regulators involved in carotenoid synthesis. Among these candidates, three RCP2 genes showed a strong potential for governing the PDS and ZDS gene families. In summary, our study elucidates the fundamental mechanisms governing carotenoid synthesis during P. armeniacum flowering, enhancing our understanding of this process and providing a foundation for future research on the molecular mechanisms driving P. armeniacum flowering.

Deep learning with citizen science data enables estimation of species diversity and composition at continental extents.

Effective solutions to conserve biodiversity require accurate community- and species-level information at relevant, actionable scales and across entire species' distributions. However, data and methodological constraints have limited our ability to provide such information in robust ways. Herein we employ a Deep-Reasoning Network implementation of the Deep Multivariate Probit Model (DMVP-DRNets), an end-to-end deep neural network framework, to exploit large observational and environmental data sets together and estimate landscape-scale species diversity and composition at continental extents. We present results from a novel year-round analysis of North American avifauna using data from over nine million eBird checklists and 72 environmental covariates. We highlight the utility of our information by identifying critical areas of high species diversity for a single group of conservation concern, the North American wood warblers, while capturing spatiotemporal variation in species' environmental associations and interspecific interactions. In so doing, we demonstrate the type of accurate, high-resolution information on biodiversity that deep learning approaches such as DMVP-DRNets can provide and that is needed to inform ecological research and conservation decision-making at multiple scales.

Identification of Potential Gene Regulatory Pathways Affecting the Ratio of Four-Seed Pod in Soybean.

The number of four-seed pods is one of the most important agronomic traits affected by gene and environment that can potentially improve soybean (Glycine max) yield. However, the gene regulatory network that affects the ratio of four-seed pod (the ratio of the number of four-seed pods to the total number of pods in each individual plant) is yet unclear. Here, we performed bulked segregant RNA sequencing (BSR-seq) on a series of recombinant inbred lines (RILs) derived from hybrid progenies between Heinong 48 (HN48), a cultivar with a high ratio of four-seed pod, and Henong 64 (HN64), a cultivar with a low ratio of four-seed pod. Two tissues, flower bud and young pod, at two different growth stages, R1 and R3, were analyzed under the ratios of four-seed pod at less than 10% and greater than 30%, respectively. To identify the potential gene regulation pathways associated with the ratio of soybean four-seed pod, we performed differentially expressed analysis on the four bulked groups. A differentially expressed gene (DEG) encoding a photosystem II 5-kDa protein had the function of participating in the energy conversion of photosynthesis. In addition, 79 common DEGs were identified at different developmental stages and under different ratios of four-seed pod. Among them, four genes encoding calcium-binding proteins and a WRKY transcription factor were enriched in the plant-pathogen interaction pathway, and they showed a high level of expression in roots. Moreover, 10 DEGs were identified in the reported quantitative trait locus (QTL) interval of four-seed pod, and two of them were significantly enriched in the pentose and glucuronate interconversion pathway. These findings provide basic insights into the understanding of the underlying gene regulatory network affected by specific environment and lay the foundation for identifying the targets that affect the ratio of four-seed pod in soybean.

VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.