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Dendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and tortuosity. We have previously demonstrated that microtubules and actin filaments are associated with arbor elongation and branching, fully constraining dendrogram topology. Here we relate the local distribution of these two primary cytoskeletal components with dendritic spatial embedding. We first reconstruct and analyze 167 sensory neurons from the larva encompassing multiple cell classes and genotypes. We observe that branches with higher microtubule concentration are overall straighter and tend to deviate less from the direction of their parent branch. F-actin displays a similar effect on the angular deviation from the parent branch direction, but its influence on branch tortuosity varies by class and genotype. We then create a computational model of dendritic morphology purely constrained by the cytoskeletal composition imaged from real neurons. The model quantitatively captures both spatial embedding and dendrogram topology across all tested neuron groups. These results suggest a common developmental mechanism regulating diverse morphologies, where the local cytoskeletal distribution can fully specify the overall emergent geometry of dendritic arbors.
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http://dx.doi.org/10.1101/2023.02.24.529978 | DOI Listing |
Microsc Res Tech
September 2024
Department of Earth and Environmental Sciences, Palaeontology and Geobiology, Ludwig-Maximilians-Universität München, Munich, Germany.
To evaluate scale morphological variability (shape, size, topological macro- and microstructures, ornamentation patterns) of cyprinid fishes, nine species of the genus Garra were selected and their scales from five different body regions were studied by using light and scanning electron microscopy. The scales of the examined species were thin with a central or antero-centrally positioned focus, with no cteni in the posterior part. In addition to these typical characteristics, some morphological variation was observed in the overall shape (irregular round, true oval, round-triangular, irregular pentagonal, hexagonal, irregular hexagonal, pentagonal, ovoid), and the focus shape.
View Article and Find Full Text PDFViruses
March 2023
College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China.
Lumpy skin disease virus (LSDV) is capable of causing transboundary diseases characterized by fever, nodules on the skin, mucous membranes, and inner organs. The disease may cause emaciation with the enlargement of lymph nodes and sometimes death. It has had endemic importance in various parts of Asia in recent years, causing substantial economic losses to the cattle industry.
View Article and Find Full Text PDFInt J Mol Sci
April 2023
Center for Neural Informatics, Structures, and Plasticity and Neuroscience Program, Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA 22030, USA.
Dendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and straightness.
View Article and Find Full Text PDFDendritic morphology underlies the source and processing of neuronal signal inputs. Morphology can be broadly described by two types of geometric characteristics. The first is dendrogram topology, defined by the length and frequency of the arbor branches; the second is spatial embedding, mainly determined by branch angles and tortuosity.
View Article and Find Full Text PDFPLoS One
February 2023
Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan.
Environmental factors affect the growth of microorganisms and therefore alter the composition of microbiota. Correlative analysis of the relationship between metagenomic composition and the environmental gradient can help elucidate key environmental factors and establishment principles for microbial communities. However, a reasonable method to quantitatively compare whole metagenomic data and identify the primary environmental factors for the establishment of microbiota has not been reported so far.
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