Abstract This study presents a methodology for a high-throughput digitization and quantification process of plant cell walls characterization, including the automated development of two-dimensional finite element models. Custom algorithms based on machine learning can also analyze the cellular microstructure for phenotypes such as cell size, cell wall curvature, and cell wall orientation. To demonstrate the utility of these models, a series of compound microscope images of both herbaceous and woody representatives were observed and processed. In addition, parametric analyses were performed on the resulting finite element models. Sensitivity analyses of the structural stiffness of the resulting tissue based on the cell wall elastic modulus and the cell wall thickness; demonstrated that the cell wall thickness has a three-fold larger impact of tissue stiffness than cell wall elastic modulus.
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Chemical inhibition of cell surface modification sensitizes bacteria to phage infection
Chemical inhibitor of cell wall alanylation sensitizes bacteria to diverse bacteriophages, revealing the widespread immunity conferred by cell wall modification.
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- Award ID(s):
- 2143636
- PAR ID:
- 10554880
- Publisher / Repository:
- Royal Society of Chemistry
- Date Published:
- Journal Name:
- RSC Chemical Biology
- Volume:
- 5
- Issue:
- 11
- ISSN:
- 2633-0679
- Page Range / eLocation ID:
- 1132 to 1139
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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