Rapid germination of non-dormant seeds is one adaptation plants have evolved to counter seed predation by rodents. Some rodent species have evolved behaviors that prevent or slow the seed germination process through seed embryo removal or seed pruning; however, no plant species is known to have successfully escaped embryo removal or seed pruning by rodents. Here, we report that the non-dormant seeds of Pittosporopsis kerrii Craib in tropical rain forests in China have a high regeneration capacity to counter seed pruning by rodents. We found seed pruning, instead of embryo removal, was commonly used by rodents to increase food storage time by slowing down the seed germination process, but that P. kerrii seeds have a high regeneration capacity to escape seed predation by rodents: all pruned seeds, pruned roots and embryo-removed seeds by rodents or people retain the ability to develop into seedlings. Seeds of P. kerrii also have other capacities (i.e. rapid seed decomposition and indigestible dormant taproots) to escape predation by reducing the plant's attractiveness to rodents. The association between seed pruning behavior in rodents and high regeneration capacity of pruned seeds or roots in P. kerrii seeds are likely novel adaptation strategies adopted by seeds and rodents, respectively.
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http://dx.doi.org/10.1007/s00442-011-1908-1 | DOI Listing |
Plant Cell Physiol
December 2024
Key Laboratory of Specialty Agri-Product Quality and Hazard Controlling Technology of Zhejiang, College of Life Sciences, China Jiliang University, Hangzhou 310018, P.R. China.
Rocketing labor cost is a major challenge threatening agricultural sustainability and food security worldwide. The replacement of manual pruning of horticultural plants with chemical pruning has long been a goal for saving cost and reducing virus spreading. Here, guided by the structure-function relationship of allelochemical benzoic acid derivatives, we have identified 4-(2-phenylethynyl)-benzoicacid (PEBA) as a highly bioactive compound.
View Article and Find Full Text PDFJ Extracell Vesicles
November 2024
Institute of Neuropathology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
Extracellular vesicles (EVs) have gained significant attention as pathology mediators and potential diagnostic tools for neurodegenerative diseases. However, isolation of brain-derived EVs (BDEVs) from tissue remains challenging, often involving enzymatic digestion steps that may compromise the integrity of EV proteins and overall functionality. Here, we describe that collagenase digestion, commonly used for BDEV isolation, produces undesired protein cleavage of EV-associated proteins in brain tissue homogenates and cell-derived EVs.
View Article and Find Full Text PDFSensors (Basel)
August 2024
School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China.
Real-time seed detection on resource-constrained embedded devices is essential for the agriculture industry and crop yield. However, traditional seed variety detection methods either suffer from low accuracy or cannot directly run on embedded devices with desirable real-time performance. In this paper, we focus on the detection of rapeseed varieties and design a dual-dimensional (spatial and channel) pruning method to lighten the YOLOv7 (a popular object detection model based on deep learning).
View Article and Find Full Text PDFInt J Mol Sci
September 2024
Fisheries Science Institute, Beijing Academy of Agriculture and Forestry Sciences & Beijing Key Laboratory of Fisheries Biotechnology, Beijing 100068, China.
J Bioinform Comput Biol
August 2024
School of Computer Science, University of Science and Technology of China, Heifei, Anhui 230027, P. R. China.
The graph of sequences represents the genetic variations of pan-genome concisely and space-efficiently than multiple linear reference genome. In order to accelerate aligning reads to the graph, an index of graph-based reference genomes is used to obtain candidate locations. However, the potential combinatorial explosion of nodes on the sequence graph leads to increasing the index space and maximum memory usage of alignment process considerably, especially for large-scale datasets.
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