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Kane CN, McAdam SAM. Spatial and Temporal Freezing Dynamics of Leaves Revealed by Time-Lapse Imaging. PLANT, CELL & ENVIRONMENT 2025; 48:164-175. [PMID: 39253967 PMCID: PMC11615429 DOI: 10.1111/pce.15118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 07/01/2024] [Accepted: 08/14/2024] [Indexed: 09/11/2024]
Abstract
Freezing air temperatures kill most leaves, yet the leaves of some species can survive these events. Tracking the temporal and spatial dynamics of freezing remains an impediment to characterizing frost tolerance. Here we deploye time-lapse imaging and image subtraction analysis, coupled with fine wire thermocouples, to discern the in situ spatial dynamics of freezing and thawing. Our method of analysis of pixel brightness reveals that ice formation in leaves exposed to natural frosts initiates in mesophyll before spreading to veins, and that while ex situ xylem sap freezes near 0°C, in situ xylem sap has a freezing point of -2°C in our model freezing-resistant species of Lonicera. Photosynthetic rates in leaves that have been exposed to a rapid freeze or thaw do not recover, but leaves exposed to a slow, natural freezing and thawing to -10°C do recover. Using this method, we are able to quantify the spatial formation and timing of freezing events in leaves, and suggest that in situ and ex situ freezing points for xylem sap can differ by more than 4°C depending on the rate of temperature decline.
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Affiliation(s)
- Cade N. Kane
- Department of Botany and Plant PathologyPurdue UniversityWest LafayetteIndianaUSA
- Department of Organismic and Evolutionary BiologyHarvard UniversityCambridgeMassachusettsUSA
| | - Scott A. M. McAdam
- Department of Botany and Plant PathologyPurdue UniversityWest LafayetteIndianaUSA
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Ma L, Hu Z, Shen W, Zhang Y, Wang G, Chang B, Lu J, Cui Y, Xu H, Feng Y, Jin B, Zhang X, Wang L, Lin J. Three-dimensional reconstruction and multiomics analysis reveal a unique pattern of embryogenesis in Ginkgo biloba. PLANT PHYSIOLOGY 2024; 196:95-111. [PMID: 38630866 DOI: 10.1093/plphys/kiae219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/23/2024] [Accepted: 03/11/2024] [Indexed: 04/19/2024]
Abstract
Ginkgo (Ginkgo biloba L.) is one of the earliest extant species in seed plant phylogeny. Embryo development patterns can provide fundamental evidence for the origin, evolution, and adaptation of seeds. However, the architectural and morphological dynamics during embryogenesis in G. biloba remain elusive. Herein, we obtained over 2,200 visual slices from 3 stages of embryo development using micro-computed tomography imaging with improved staining methods. Based on 3-dimensional (3D) spatiotemporal pattern analysis, we found that a shoot apical meristem with 7 highly differentiated leaf primordia, including apical and axillary leaf buds, is present in mature Ginkgo embryos. 3D rendering from the front, top, and side views showed 2 separate transport systems of tracheids located in the hypocotyl and cotyledon, representing a unique pattern of embryogenesis. Furthermore, the morphological dynamic analysis of secretory cavities indicated their strong association with cotyledons during development. In addition, we identified genes GbLBD25a (lateral organ boundaries domain 25a), GbCESA2a (cellulose synthase 2a), GbMYB74c (myeloblastosis 74c), GbPIN2 (PIN-FORMED 2) associated with vascular development regulation, and GbWRKY1 (WRKYGOK 1), GbbHLH12a (basic helix-loop-helix 12a), and GbJAZ4 (jasmonate zim-domain 4) potentially involved in the formation of secretory cavities. Moreover, we found that flavonoid accumulation in mature embryos could enhance postgerminative growth and seedling establishment in harsh environments. Our 3D spatial reconstruction technique combined with multiomics analysis opens avenues for investigating developmental architecture and molecular mechanisms during embryogenesis and lays the foundation for evolutionary studies of embryo development and maturation.
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Affiliation(s)
- Lingyu Ma
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
- Research Institute of Wood Industry, Chinese Academy of Sciences, Beijing 100091, China
| | - Zijian Hu
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
| | - Weiwei Shen
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
| | - Yingying Zhang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
| | - Guangchao Wang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
| | - Bang Chang
- College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou 225009, China
| | - Jinkai Lu
- College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou 225009, China
| | - Yaning Cui
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
| | - Huimin Xu
- College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Yun Feng
- Center for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Biao Jin
- College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou 225009, China
| | - Xi Zhang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
| | - Li Wang
- College of Horticulture and Landscape Architecture, Yangzhou University, Yangzhou 225009, China
| | - Jinxing Lin
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China
- Institute of Tree and Genome Editing, Beijing Forestry University, Beijing 100083, China
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Liu J, Zheng Y, Lin L, Guo J, Lv Y, Yuan J, Zhai H, Chen X, Shen L, Li L, Bai S, Han H. A robust transformer-based pipeline of 3D cell alignment, denoise and instance segmentation on electron microscopy sequence images. JOURNAL OF PLANT PHYSIOLOGY 2024; 297:154236. [PMID: 38621330 DOI: 10.1016/j.jplph.2024.154236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 03/15/2024] [Accepted: 03/20/2024] [Indexed: 04/17/2024]
Abstract
Germline cells are critical for transmitting genetic information to subsequent generations in biological organisms. While their differentiation from somatic cells during embryonic development is well-documented in most animals, the regulatory mechanisms initiating plant germline cells are not well understood. To thoroughly investigate the complex morphological transformations of their ultrastructure over developmental time, nanoscale 3D reconstruction of entire plant tissues is necessary, achievable exclusively through electron microscopy imaging. This paper presents a full-process framework designed for reconstructing large-volume plant tissue from serial electron microscopy images. The framework ensures end-to-end direct output of reconstruction results, including topological networks and morphological analysis. The proposed 3D cell alignment, denoise, and instance segmentation pipeline (3DCADS) leverages deep learning to provide a cell instance segmentation workflow for electron microscopy image series, ensuring accurate and robust 3D cell reconstructions with high computational efficiency. The pipeline involves five stages: the registration of electron microscopy serial images; image enhancement and denoising; semantic segmentation using a Transformer-based neural network; instance segmentation through a supervoxel-based clustering algorithm; and an automated analysis and statistical assessment of the reconstruction results, with the mapping of topological connections. The 3DCADS model's precision was validated on a plant tissue ground-truth dataset, outperforming traditional baseline models and deep learning baselines in overall accuracy. The framework was applied to the reconstruction of early meiosis stages in the anthers of Arabidopsis thaliana, resulting in a topological connectivity network and analysis of morphological parameters and characteristics of cell distribution. The experiment underscores the 3DCADS model's potential for biological tissue identification and its significance in quantitative analysis of plant cell development, crucial for examining samples across different genetic phenotypes and mutations in plant development. Additionally, the paper discusses the regulatory mechanisms of Arabidopsis thaliana's germline cells and the development of stamen cells before meiosis, offering new insights into the transition from somatic to germline cell fate in plants.
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Affiliation(s)
- Jiazheng Liu
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - Yafeng Zheng
- College of Life Sciences, Peking University, Beijing 100871, China; State Key Laboratory of Protein and Plant Gene Research, Beijing 100871, China
| | - Limei Lin
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - Jingyue Guo
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - Yanan Lv
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - Jingbin Yuan
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - Hao Zhai
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - Xi Chen
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - Lijun Shen
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China
| | - LinLin Li
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China.
| | - Shunong Bai
- College of Life Sciences, Peking University, Beijing 100871, China; State Key Laboratory of Protein and Plant Gene Research, Beijing 100871, China.
| | - Hua Han
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China; Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Team of Microscale Reconstruction and Intelligent Analysis, Laboratory of Brain-AI, Institute of Automation, Chinese Academy of Sciences, Beijing 101499, China.
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Shen L. Effects of Pelvic Floor Muscle Massage on the Pregnancy Outcome of Frozen Embryo Transfer in Patients with Thin Endometrium. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:2803363. [PMID: 35813410 PMCID: PMC9259337 DOI: 10.1155/2022/2803363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 06/02/2022] [Accepted: 06/03/2022] [Indexed: 11/18/2022]
Abstract
Objective To observe the effects of pelvic floor muscle mass on the priority outcome of frozen embryo transfer in patients with thin endometrium. Methods The patients who were prepared for freeze-thaw embryo transfer were randomly divided into the study group and control group. Both groups of patients began to take estradiol valerate tablets 3 mg on the third day of menstrual cycle and added progesterone for luteal support after 14 days. Both groups selected high-quality embryos for embryo transfer on the day of embryo transfer. The basic information, embryo transfer, intimal thickness, intimal type, clinical pregnancy rate, and early abortion rate of the two groups were compared. Results The intimal thickness of patients in the control group and the study group on the second day of menstruation was (0.49 ± 0.03) and (0.45 ± 0.02) and that before progesterone was (1.17 ± 0.03) and (1.20 ± 0.04), respectively (P < 0.05). At the same time, the number of excellent embryos in the study group was significantly higher than that in the control group (P < 0.05), but there was no significant difference in the number of transplants between the two groups (P > 0.05). The proportion of intimal blood flow of type III + II in the study group was significantly higher than that in the control group (P < 0.05). The main adverse pregnancy outcomes of the whole group included biochemical pregnancy, early abortion, and ectopic pregnancy. The incidence of biochemical pregnancy in the control group and the study group was 63.3% (38/60) and 40.0% (24/60), respectively. The incidence of biochemical pregnancy in the control group was significantly higher than that in the study group, but there was no significant difference in the incidence of early abortion and ectopic pregnancy between the two groups (P > 0.05). Conclusion Pelvic floor muscle massage can improve endometrial thickness and subendometrial blood flow, so as to improve the pregnancy rate of frozen thawed embryo transfer patients.
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Affiliation(s)
- Longying Shen
- Kuishan Health Center of Rizhao Economic and Technological Development Zone, China
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