室内植物表型平台及性状鉴定研究进展和展望

Plant phenomics is under rapid development in recent years, a research field that is progressing towards integration, scalability, multi-perceptivity and high-throughput analysis. Through combining remote sensing, Internet of Things (IoT), robotics, computer vision, and artificial intelligence techniques such as machine learning and deep learning, relevant research methodologies, biological applications and theoretical foundation of this research domain have been advancing speedily in recent years. This article first introduces the current trends of plant phenomics and its related progress in China and worldwide. Then, it focuses on discussing the characteristics of indoor phenotyping and phenotypic traits that are suitable for indoor experiments, including yield, quality, and stress related traits such as drought, cold and heat resistance, salt stress, heavy metals, and pests. By connecting key phenotypic traits with important biological questions in yield production, crop quality and Stress-related tolerance, we associated indoor phenotyping hardware with relevant biological applications and their plant model systems, for which a range of indoor phenotyping devices and platforms are listed and categorised according to their throughput, sensor integration, platform size, and applications. Additionally, this article introduces existing data management solutions and analysis software packages that are representative for phenotypic analysis. For example, ISA-Tab and MIAPPE ontology standards for capturing metadata in plant phenotyping experiments, PHIS and CropSight for managing complicated datasets, and Python or MATLAB programming languages for automated image analysis based on libraries such as OpenCV, Scikit-Image, MATLAB Image Processing Toolbox. Finally, due to the importance of extracting meaningful information from big phenotyping datasets, this article pays extra attention to the future development of plant phenomics in China, with suggestions and recommendations for the integration of multi-scale phenotyping data to increase confidence in research outcomes, the cultivation of cross-disciplinary researchers to lead the next-generation plant research, as well as the collaboration between academia and industry to enable world-leading research activities in the near future

Research of influence and mechanism of combining exercise with diet control on a model of lipid metabolism rat induced by high fat diet

OBJECTIVE: To investigate the influence and mechanism of combining exercise with diet control on a model of lipid metabolism rat induced by high fat diet. METHODS: Twenty-four male Wistar rats were randomly divided into 3 groups of 8: normal, model and intervention. The model group and intervention group were fed with high fat diet, while the normal group received basal feed. From day 1, the intervention group was randomly given interventions such as swimming exercise and dietary restriction. The interventions duration were 28 days. At the end of the experiment, the levels of rats’ body weight and liver weight were detected, the serum levels of total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and hepatic triglyceride content (TG) were detected by using biochemical assay, serum level of gastrin (GAS), motilin (MTL) were assayed by the enzyme linked immunosorbent assay (ELISA). RESULTS: Compared with the level of body weight and liver weight in the normal rats, body weight and liver weight in the rat of the model group were significantly increase (P<0.05 or P<0.01). Plasma concentrations of TC, LDL-C and hepatic TG in the model group were significantly increased compared with those in the normal group (P<0.05 or P<0.01). The contents of GAS, MTL, HDL-C in the model rats’plasma were significantly reduced compared with those of the normal group (P<0.05 or P<0.01). Compared with those in the model group, rats’ body weight, liver weight, serum TC, LDL-C, and TG content of liver in the intervention group decreased significantly (P<0.05 or P<0.01). Meanwhile, serum content of GAS, MTL, HDL-C were significantly improved in the intervention rats compared to the model group. CONCLUSION: The action of combining exercise with diet control for lipid metabolism disorder might be related to regulation of GAS, MTL and other gastrointestinal hormones

Protein contact order prediction from primary sequences

© 2008 Shi et al; licensee BioMed Central Ltd

Simulations of summertime fossil fuel CO2 in the Guanzhong basin, China

Recent studies on fossil fuel CO2 simulation associated with Delta(CO2)-C-14 measurements is quite limited, particularly in China. In this study, the fossil fuel CO2 recently added to the atmosphere (delta CO(2)ff) over the Guanzhong basin, central China, during summer 2012 is simulated using a modified WRF-CHEM model constrained by measured CO2 mixing ratio and Delta(CO2)-C-14. The model well captures the temporal variation of observed CO2 mixing ratio and Delta(CO2)-C-14, and reasonably reproduces the distribution of observed Delta(CO2)-C-14. The simulation shows a significant variation of delta CO(2)ff during summertime, ranging from &lt;5 ppmv to similar to 100 ppmv and no remarkable trend of delta CO(2)ff is found for June, July, and August. The delta CO(2)ff level is closely associated with atmospheric diffusion conditions. The diurnal cycle of delta CO(2)ff presents a double-peak pattern, a nocturnal one and a rush-hour one, related to the development of planetary boundary layer and CO2 emission from vehicles. The spatial distributions of summertime delta CO(2)ff within the basin is clearly higher than the outside, reaching up to 40 ppmv in urban Xi&#39;an and 15 ppmv in its surrounding areas, indicative of large local fossil fuel emissions. Furthermore, we find that neglecting the influence of summer heterotrophic respiration in terrestrial biosphere would slightly underestimate the calculated delta CO(2)ff by about 0.38 ppmv in the basin. (C) 2017 Elsevier B.V. All rights reserved

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

Visual aesthetic assessment has been an active research field for decades. Although latest methods have achieved promising performance on benchmark datasets, they typically rely on a large number of manual annotations including both aesthetic labels and related image attributes. In this paper, we revisit the problem of image aesthetic assessment from the self-supervised feature learning perspective. Our motivation is that a suitable feature representation for image aesthetic assessment should be able to distinguish different expert-designed image manipulations, which have close relationships with negative aesthetic effects. To this end, we design two novel pretext tasks to identify the types and parameters of editing operations applied to synthetic instances. The features from our pretext tasks are then adapted for a one-layer linear classifier to evaluate the performance in terms of binary aesthetic classification. We conduct extensive quantitative experiments on three benchmark datasets and demonstrate that our approach can faithfully extract aesthetics-aware features and outperform alternative pretext schemes. Moreover, we achieve comparable results to state-of-the-art supervised methods that use 10 million labels from ImageNet.Comment: AAAI Conference on Artificial Intelligence, 2020, accepte

Overexpression of GATA2 Enhances Development and Maintenance of Human Embryonic Stem Cell-Derived Hematopoietic Stem Cell-like Progenitors

GATA2 is essential for the endothelial-to-hematopoietic transition (EHT) and generation of hematopoietic stem cells (HSCs). It is poorly understood how GATA2 controls the development of human pluripotent stem cell (hPSC)-derived HS-like cells. Here, using human embryonic stem cells (hESCs) in which GATA2 overexpression was induced by doxycycline (Dox), we elucidated the dual functions of GATA2 in definitive hematopoiesis before and after the emergence of CD34+CD45+CD90+CD38– HS-like cells. Specifically, GATA2 promoted expansion of hemogenic precursors via the EHT and then helped to maintain HS-like cells in a quiescent state by regulating cell cycle. RNA sequencing showed that hPSC-derived HS-like cells were very similar to human fetal liver-derived HSCs. Our findings will help to elucidate the mechanism that controls the early stages of human definitive hematopoiesis and may help to develop a strategy to generate hPSC-derived HSCs

Overexpression of GATA2 Enhances Development and Maintenance of Human Embryonic Stem Cell-Derived Hematopoietic Stem Cell-like Progenitors

GATA2 is essential for the endothelial-to-hematopoietic transition (EHT) and generation of hematopoietic stem cells (HSCs). It is poorly understood how GATA2 controls the development of human pluripotent stem cell (hPSC)-derived HS-like cells. Here, using human embryonic stem cells (hESCs) in which GATA2 overexpression was induced by doxycycline (Dox), we elucidated the dual functions of GATA2 in definitive hematopoiesis before and after the emergence of CD34⁺CD45⁺CD90⁺CD38⁻ HS-like cells. Specifically, GATA2 promoted expansion of hemogenic precursors via the EHT and then helped to maintain HS-like cells in a quiescent state by regulating cell cycle. RNA sequencing showed that hPSC-derived HS-like cells were very similar to human fetal liver-derived HSCs. Our findings will help to elucidate the mechanism that controls the early stages of human definitive hematopoiesis and may help to develop a strategy to generate hPSC-derived HSCs

Geographic Distribution and Genetic Diversity of Rice Stripe Mosaic Virus in Southern China

Rice stripe mosaic virus (RSMV) transmitted by the leafhopper Recilia dorsalis is a tentative new species in the genus Cytorhabdovirus identified recently in South China. To explore its geographic distribution and genetic diversity, field investigation and viral whole-genome sequencing were conducted in this study. The results indicated that RSMV was present in the rice samples collected across southern China. Twelve representative samples from different geographical regions were selected for viral whole-genome sequencing and the viral genome variation was analyzed in combination with a previously reported RSMV isolate. Identity analysis showed that the genome sequences of 13 RSMV isolates were highly conserved with nucleotide identities over 99.4%. There was a strong negative selection pressure during the evolution of RSMV with more transitions (72.08%) than transversions (27.92%) found between the RSMV isolates. Among the seven genes encoded by RSMV, the P gene was the most variable, followed by N, M, L, and G; the P3 and P6 amino acid sequences were not found to be mutated and no mutations were found in the non-coding region. A phylogenetic tree based on the RSMV whole-genome nucleotide sequences revealed that all RSMV isolates clustered in two groups based on geographical origin. Notably, the L proteins of the Guangxi and Hainan isolates had five and one specific amino acid sites, respectively, suggesting that the L gene has undergone environmental adaptive variation during the dispersal of RSMV