Plant Methods最新文献

{"title":"An efficient multiplex approach to CRISPR/Cas9 gene editing in citrus.","authors":"Cintia H D Sagawa, Geoffrey Thomson, Benoit Mermaz, Corina Vernon, Siqi Liu, Yannick Jacob, Vivian F Irish","doi":"10.1186/s13007-024-01274-4","DOIUrl":"https://doi.org/10.1186/s13007-024-01274-4","url":null,"abstract":"<p><p>CRISPR/Cas9-mediated gene editing requires high efficiency to be routinely implemented, especially in species which are laborious and slow to transform. This requirement intensifies further when targeting multiple genes simultaneously, which is required for genetic screening or more complex genome engineering. Species in the Citrus genus fall into this category. Here we describe a series of experiments with the collective aim of improving multiplex gene editing in the Carrizo citrange cultivar using tRNA-based sgRNA arrays. We evaluate a range of promoters for their efficacy in such experiments and achieve significant improvements by optimizing the expression of both the Cas9 endonuclease and the sgRNA array. In the case of the former we find the UBQ10 or RPS5a promoters from Arabidopsis driving the zCas9i endonuclease variant useful for achieving high levels of editing. The choice of promoter expressing the sgRNA array also had a large impact on gene editing efficiency across multiple targets. In this respect Pol III promoters perform especially well, but we also demonstrate that the UBQ10 and ES8Z promoters from Arabidopsis are robust alternatives. Ultimately, this study provides a quantitative insight into CRISPR/Cas9 vector design that has practical application in the simultaneous editing of multiple genes in Citrus, and potentially other eudicot plant species.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"148"},"PeriodicalIF":4.7,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local mapping of root orientation traits by X-ray micro-CT and 3d image analysis: A study case on carrot seedlings grown in simulated vs real weightlessness.","authors":"L Gargiulo, G Mele, L G Izzo, L E Romano, G Aronne","doi":"10.1186/s13007-024-01276-2","DOIUrl":"https://doi.org/10.1186/s13007-024-01276-2","url":null,"abstract":"<p><strong>Background: </strong>Root phenotyping is particularly challenging because of complexity and inaccessibility of root apparatus. Orientation is one of the most important architectural traits of roots and its characterization is generally addressed using multiple approaches often based on overall measurements which are difficult to correlate to plant specific physiological aspects and its genetic features. Hence, a 3D image analysis approach, based on the recent method of Straumit, is proposed in this study to obtain a local mapping of root angles.</p><p><strong>Results: </strong>Proposed method was applied here on radicles of carrot seedlings grown in real weightlessness on the International Space Station (ISS) and on Earth simulated weightlessness by clinorotation. A reference experiment in 1 g static condition on Earth was also performed. Radicles were imaged by X-ray micro-CT and two novel root orientation traits were defined: the \"root angle to sowing plane\" (RASP) providing accurate angle distributions for each analysed radicle and the \"root orientation changes\" (ROC) number. The parameters of the RASP distributions and the ROC values did not exhibit any significant difference in orientation between radicles grown under clinorotation and on the ISS. Only a slight thickening in root corners was found in simulated vs real weightlessness. Such results showed that a simple uniaxial clinostat can be an affordable analog in experimental studies reckoning on weightless radicles growth.</p><p><strong>Conclusions: </strong>The proposed local orientation mapping approach can be extended also to different root systems providing a contribution in the challenging task of phenotyping complex and important plant structures such as roots.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"150"},"PeriodicalIF":4.7,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11439289/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel application of laser speckle imaging technique for prediction of hypoxic stress of apples.","authors":"Piotr Mariusz Pieczywek, Artur Nosalewicz, Artur Zdunek","doi":"10.1186/s13007-024-01271-7","DOIUrl":"https://doi.org/10.1186/s13007-024-01271-7","url":null,"abstract":"<p><strong>Background: </strong>Fruit storage methods such as dynamic controlled atmosphere (DCA) technology enable adjusting the level of oxygen in the storage room, according to the physiological state of the product to slow down the ripening process. However, the successful application of DCA requires precise and reliable sensors of the oxidative stress of the fruit. In this study, respiration rate and chlorophyll fluorescence (CF) signals were evaluated after introducing a novel predictors of apples' hypoxic stress based on laser speckle imaging technique (LSI).</p><p><strong>Results: </strong>Both chlorophyll fluorescence and LSI signals were equally good for stress detection in principle. However, in an application with automatic detection based on machine learning models, the LSI signal proved to be superior, due to its stability and measurement repeatability. Moreover, the shortcomings of the CF signal appear to be its inability to indicate oxygen stress in tissues with low chlorophyll content but this does not apply to LSI. A comparison of different LSI signal processing methods showed that method based on the dynamics of changes in image content was better indicators of stress than methods based on measurements of changes in pixel brightness (inertia moment or laser speckle contrast analysis). Data obtained using the near-infrared laser provided better prediction capabilities, compared to the laser with red light.</p><p><strong>Conclusions: </strong>The study showed that the signal from the scattered laser light phenomenon is a good predictor for the oxidative stress of apples. Results showed that effective prediction using LSI was possible and did not require additional signals. The proposed method has great potential as an alternative indicator of fruit oxidative stress, which can be applied in modern storage systems with a dynamically controlled atmosphere.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"147"},"PeriodicalIF":4.7,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11437772/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating waterlogging stress response and recovery in barley (Hordeum vulgare L.): an image-based phenotyping approach.","authors":"Patrick Langan, Emilie Cavel, Joey Henchy, Villő Bernád, Paul Ruel, Katie O'Dea, Keshawa Yatagampitiya, Hervé Demailly, Laurent Gutierrez, Sónia Negrão","doi":"10.1186/s13007-024-01256-6","DOIUrl":"https://doi.org/10.1186/s13007-024-01256-6","url":null,"abstract":"<p><p>Waterlogging is expected to become a more prominent yield restricting stress for barley as rainfall frequency is increasing in many regions due to climate change. The duration of waterlogging events in the field is highly variable throughout the season, and this variation is also observed in experimental waterlogging studies. Such variety of protocols make intricate physiological responses challenging to assess and quantify. To assess barley waterlogging tolerance in controlled conditions, we present an optimal duration and setup of simulated waterlogging stress using image-based phenotyping. Six protocols durations, 5, 10, and 14 days of stress with and without seven days of recovery, were tested. To quantify the physiological effects of waterlogging on growth and greenness, we used top down and side view RGB (Red-Green-Blue) images. These images were taken daily throughout each of the protocols using the PSI PlantScreen™ imaging platform. Two genotypes of two-row spring barley, grown in glasshouse conditions, were subjected to each of the six protocols, with stress being imposed at the three-leaf stage. Shoot biomass and root imaging data were analysed to determine the optimal stress protocol duration, as well as to quantify the growth and morphometric changes of barley in response to waterlogging stress. Our time-series results show a significant growth reduction and alteration of greenness, allowing us to determine an optimal protocol duration of 14 days of stress and seven days of recovery for controlled conditions. Moreover, to confirm the reproducibility of this protocol, we conducted the same experiment in a different facility equipped with RGB and chlorophyll fluorescence imaging sensors. Our results demonstrate that the selected protocol enables the assessment of genotypic differences, which allow us to further determine tolerance responses in a glasshouse environment. Altogether, this work presents a new and reproducible image-based protocol to assess early stage waterlogging tolerance, empowering a precise quantification of waterlogging stress relevant markers such as greenness, Fv/Fm and growth rates.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"146"},"PeriodicalIF":4.7,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438059/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pyramid-YOLOv8: a detection algorithm for precise detection of rice leaf blast.","authors":"Qiang Cao, Dongxue Zhao, Jinpeng Li, JinXuan Li, Guangming Li, Shuai Feng, Tongyu Xu","doi":"10.1186/s13007-024-01275-3","DOIUrl":"https://doi.org/10.1186/s13007-024-01275-3","url":null,"abstract":"<p><p>Rice blast is the primary disease affecting rice yield and quality, and its effective detection is essential to ensure rice yield and promote sustainable agricultural production. To address traditional disease detection methods' time-consuming and inefficient nature, we proposed a method called Pyramid-YOLOv8 for rapid and accurate rice leaf blast disease detection in this study. The algorithm is built on the YOLOv8x network framework and features a multi-attention feature fusion network structure. This structure enhances the original feature pyramid structure and works with an additional detection head for improved performance. Additionally, this study designs a lightweight C2F-Pyramid module to enhance the model's computational efficiency. In the comparison experiments, Pyramid-YOLOv8 shows excellent performance with a mean Average Precision (mAP) of 84.3%, which is an improvement of 9.9%, 4.3%, 7.4%, 6.1%, 1.5%, 3.7%, and 8.2% compared to the models Faster-RCNN, RT-DETR, YOLOv3-SPP, YOLOv5x, YOLOv9e, and YOLOv10x, respectively. Additionally, it reaches a detection speed of 62.5 FPS; the model comprises only 42.0 M parameters. Meanwhile, the model size and Floating Point Operations (FLOPs) are reduced by 41.7% and 23.8%, respectively. These results demonstrate the high efficiency of Pyramid-YOLOv8 in detecting rice leaf blast. In summary, the Pyramid-YOLOv8 algorithm developed in this study offers a robust theoretical foundation for rice disease detection and introduces a new perspective on disease management and prevention strategies in agricultural production.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"149"},"PeriodicalIF":4.7,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11437801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142352020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing UAVs and deep learning for accurate grass weed detection in wheat fields: a study on biomass and yield implications","authors":"Tao Liu, Yuanyuan Zhao, Hui Wang, Wei Wu, Tianle Yang, Weijun Zhang, Shaolong Zhu, Chengming Sun, Zhaosheng Yao","doi":"10.1186/s13007-024-01272-6","DOIUrl":"https://doi.org/10.1186/s13007-024-01272-6","url":null,"abstract":"Weeds are undesired plants competing with crops for light, nutrients, and water, negatively impacting crop growth. Identifying weeds in wheat fields accurately is important for precise pesticide spraying and targeted weed control. Grass weeds in their early growth stages look very similar to wheat seedlings, making them difficult to identify. In this study, we focused on wheat fields with varying levels of grass weed infestation and used unmanned aerial vehicles (UAVs) to obtain images. By utilizing deep learning algorithms and spectral analysis technology, the weeds were identified and extracted accurately from wheat fields. Our results showed that the precision of weed detection in scattered wheat fields was 91.27% and 87.51% in drilled wheat fields. Compared to areas without weeds, the increase in weed density led to a decrease in wheat biomass, with the maximum biomass decreasing by 71%. The effect of weed density on yield was similar, with the maximum yield decreasing by 4320 kg·ha− 1, a drop of 60%. In this study, a method for monitoring weed occurrence in wheat fields was established, and the effects of weeds on wheat growth in different growth periods and weed densities were studied by accurately extracting weeds from wheat fields. The results can provide a reference for weed control and hazard assessment research.","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"4 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Production of genetically stable and Odontoglossum ringspot virus-free Cymbidium orchid ‘New True’ plants via meristem-derived protocorm-like body (PLB) subcultures","authors":"Jova Riza Campol, Aung Htay Naing, Hay Mon Aung, Su Bin Cho, Hyunhee Kang, Mi Young Chung, Chang Kil Kim","doi":"10.1186/s13007-024-01269-1","DOIUrl":"https://doi.org/10.1186/s13007-024-01269-1","url":null,"abstract":"This study aimed to produce Odontoglossum ringspot virus (ORSV)-free Cymbidium orchid ‘New True’ plants from ORSV-infected mother plants by culturing their meristems and successively repeating subcultures of protocorm-like bodies (PLBs) derived from the meristems. Initially, ORSV was confirmed as the causative agent of viral symptoms in orchid leaves via reverse transcription-polymerase chain reaction (RT-PCR) analysis. Meristems from infected plants were cultured to generate PLBs, which in sequence were repeatedly subcultured up to four times. RT-PCR and quantitative RT-PCR analyses revealed that while ORSV was undetectable in shoots derived from the first subculture, complete elimination of the virus required at least a second subculture. Genetic analysis using inter-simple sequence repeat markers indicated no somaclonal variation between regenerated plants and the mother plant, suggesting that genetic consistency was maintained. Overall, our findings demonstrate that subculturing PLBs for a second time is ideal for producing genetically stable, ORSV-free Cymbidium orchids, thus offering a practical means of generating genetically stable, virus-free plants and enhancing plant health and quality in the orchid industry.","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"83 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of ribosome profiling in plants including structural analysis of rRNA fragments","authors":"Michael K. Y. Ting, Yang Gao, Rouhollah Barahimipour, Rabea Ghandour, Jinghan Liu, Federico Martinez-Seidel, Julia Smirnova, Vincent Leon Gotsmann, Axel Fischer, Michael J. Haydon, Felix Willmund, Reimo Zoschke","doi":"10.1186/s13007-024-01267-3","DOIUrl":"https://doi.org/10.1186/s13007-024-01267-3","url":null,"abstract":"Ribosome profiling (or Ribo-seq) is a technique that provides genome-wide information on the translational landscape (translatome). Across different plant studies, variable methodological setups have been described which raises questions about the general comparability of data that were generated from diverging methodologies. Furthermore, a common problem when performing Ribo-seq are abundant rRNA fragments that are wastefully incorporated into the libraries and dramatically reduce sequencing depth. To remove these rRNA contaminants, it is common to perform preliminary trials to identify these fragments because they are thought to vary depending on nuclease treatment, tissue source, and plant species. Here, we compile valuable insights gathered over years of generating Ribo-seq datasets from different species and experimental setups. We highlight which technical steps are important for maintaining cross experiment comparability and describe a highly efficient approach for rRNA removal. Furthermore, we provide evidence that many rRNA fragments are structurally preserved over diverse nuclease regimes, as well as across plant species. Using a recently published cryo-electron microscopy (cryo-EM) structure of the tobacco 80S ribosome, we show that the most abundant rRNA fragments are spatially derived from the solvent-exposed surface of the ribosome. The guidelines presented here shall aid newcomers in establishing ribosome profiling in new plant species and provide insights that will help in customizing the methodology for individual research goals.","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"50 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Micro computed tomography analysis of barley during the first 24 hours of germination","authors":"Olivia Doolan, Mathew G. Lewsey, Marta Peirats-Llobet, Neil Bricklebank, Nicola Aberdein","doi":"10.1186/s13007-024-01266-4","DOIUrl":"https://doi.org/10.1186/s13007-024-01266-4","url":null,"abstract":"Grains make up a large proportion of both human and animal diets. With threats to food production, such as climate change, growing sustainable and successful crops is essential to food security in the future. Germination is one of the most important stages in a plant’s lifecycle and is key to the success of the resulting plant as the grain undergoes morphological changes and the development of specific organs. Micro-computed tomography is a non-destructive imaging technique based on the differing x-ray attenuations of materials which we have applied for the accurate analysis of grain morphology during the germination phase. Micro Computed Tomography conditions and parameters were tested to establish an optimal protocol for the 3-dimensional analysis of barley grains. When comparing optimal scanning conditions, it was established that no filter, 0.4 degrees rotation step, 5 average frames, and 2016 × 1344 camera binning is optimal for imaging germinating grains. It was determined that the optimal protocol for scanning during the germination timeline was to scan individual grains at 0 h after imbibition (HAI) and then the same grain again at set time points (1, 3, 6, 24 HAI) to avoid any negative effects from X-ray radiation or disruption to growing conditions. Here we sought to develop a method for the accurate analysis of grain morphology without the negative effects of possible radiation exposure. Several factors have been considered, such as the scanning conditions, reconstruction, and possible effects of X-ray radiation on the growth rate of the grains. The parameters chosen in this study give effective and reliable results for the 3-dimensional analysis of macro structures within barley grains while causing minimal disruption to grain development.","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"19 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing cannabis cultivation: an efficient in vitro system for flowering induction","authors":"Orly Lavie, Kobi Buxdorf, Leor Eshed Williams","doi":"10.1186/s13007-024-01265-5","DOIUrl":"https://doi.org/10.1186/s13007-024-01265-5","url":null,"abstract":"Cannabis sativa L. is a versatile medicinal plant known for its therapeutic properties, derived from its diverse array of secondary metabolites synthesized primarily in female flower organs. Breeding cannabis is challenging due to its dioecious nature, strict regulatory requirements, and the need for photoperiod control to trigger flowering, coupled with highly dispersible pollen that can easily contaminate nearby female flowers. This study aimed to develop a protocol for in vitro flowering in cannabis, investigate factors affecting in vitro flower production, and generate viable in vitro seeds, potentially offering a method for producing sterile cannabinoids or advancing breeding techniques. We show that the life cycle of cannabis can be fully completed in tissue culture; plantlets readily produce inflorescences and viable seeds in vitro. Our findings highlight the superior performance of DKW medium with 2% sucrose in a filtered vessel and emphasize the need for low light intensity during flower induction to optimize production. The improved performance in filtered vessels suggests that plants conduct photosynthesis in vitro, highlighting the need for future investigations into the effects of forced ventilation to refine this system. All tested lines readily developed inflorescences upon induction, with a 100% occurrence rate, including male flowering. We revealed the non-dehiscent trait of in vitro anthers, which is advantageous as it allows for multiple crosses to be conducted in vitro without concerns about cross-contamination. The current work developed and optimized an effective protocol for in vitro flowering and seed production in cannabis, potentially providing a platform for sterile cannabinoid production and an efficient tool for breeding programs. This system allows for the full and consistent control of plant growth conditions year-round, potentially offering the reliable production of sterile molecules suitable for pharmacological use. As a breeding strategy, this method overcomes the complex challenges of breeding cannabis, such as the need for large facilities, by enabling the production of hundreds of lines in a small facility. By offering precise control over factors such as plant growth regulators, light intensity, photoperiod, and temperature, this system also serves as a valuable tool for studying flowering aspects in cannabis.","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"58 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142208858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}