Stellate Morphology
Stellate Morphology - Related Videos
06:40
Seven Steps to Stellate Cells
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Cited by 67 •
2011
Here we describe a method for the isolation of hepatic stellate cells from mouse liver. For stellate cell purification, mouse livers are digested in situ and in vitro by pronase-collagenase treatment prior to density gradient centrifugation. This technique yields highly pure hepatic stellate cells.
07:50
Location, Dissection, and Analysis of the Murine Stellate Ganglion
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Cited by 15 •
2020
Pathophysiological changes in the cardiac autonomic nervous system, especially in its sympathetic branch, contribute to the onset and maintenance of ventricular arrhythmias. In the present protocol, we show how to characterize murine stellate ganglia to improve the understanding of the underlying molecular and cellular processes.
01:29
Microbial Morphologies
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2025
Bacterial and archaeal cells exhibit remarkable diversity in shape and structure, critical in their adaptability and functionality. Among bacteria, the most commonly observed shapes include cocci and bacilli. Cocci are spherical and may exist singly or in groupings such as pairs (diplococci), chains (streptococci), clusters (staphylococci), or tetrads. Bacilli, in contrast, are rod-shaped and can also occur as single cells, in pairs, or chains, depending on their environmental and genetic...
10:24
Electrophysiological and Morphological Characterization of Neuronal Microcircuits in Acute Brain Slices Using Paired Patch-Clamp Recordings
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Cited by 28 •
2015
Patch-clamp recordings and simultaneous intracellular biocytin filling of synaptically coupled neurons in acute brain slices allow a correlated analysis of their structural and functional properties. The aim of this protocol is to describe the essential technical steps of electrophysiological recording from neuronal microcircuits and their subsequent morphological analysis.
02:52
Two-Photon Microscopy for Imaging Neuronal Morphology in a Mouse Pup
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2025
Source: Mizuno, H., et al. In Vivo Two-photon Imaging of Cortical Neurons in Neonatal Mice. J. Vis. Exp. (2018)This video showcases two-photon microscopy being used to image neurons in the brain of an anesthetized transgenic mouse pup. The two-photon laser allows for deeper imaging with high spatial resolution and minimal light scattering, enabling the detailed capture of neuronal morphology, including dendritic projections.
FAQs
The key variables are dendrite number, branching pattern, and orientation. More numerous or extensively branched processes can provide greater membrane area for synaptic contacts, while their orientation determines which spatially distributed inputs are accessible. Together, these features influence how a neuron collects and integrates signals, making morphology relevant to circuit-level information processing.
Radiating dendrites can support input integration from different directions rather than concentrating contacts along a single orientation. The functional consequence depends not only on total process count but also on how branches are arranged around the soma. Thus, two neurons with a similar number of dendrites may still differ in the inputs they sample and the way they participate in a circuit.
Linking shape to electrophysiology means asking whether structural differences coincide with differences in neuronal signal processing. Researchers can classify cells by morphology, then relate dendritic number, branching, or orientation to electrophysiological observations. This comparison helps interpret how cellular structure contributes to function without treating a star-shaped appearance alone as a complete description of neuronal activity.
Quantitative morphometry turns descriptive impressions into measurements that can be compared across neurons, regions, or experimental conditions. Researchers can examine dendrite number, branching pattern, and orientation to identify structural differences and relate them to connectivity or electrophysiological function. This approach strengthens neuronal classification and makes studies of circuit organization more systematic.
A practical workflow begins by visualizing neurons with microscopy, preserving or revealing their processes through an appropriate labeling approach, and then examining the resulting images quantitatively. Measurements focus on dendritic number, branching, and orientation. The data can then be compared with electrophysiological observations or connectivity patterns to connect cellular structure with circuit organization.
When comparing cells, record more than whether they appear star shaped. Count or characterize the number of dendrites, describe how extensively they branch, and document their orientation relative to the cell body or surrounding circuit. These measurements provide a structured basis for distinguishing neuronal classes and testing whether morphological variation corresponds to different roles in signal integration.
In the cerebral cortex and cerebellum, stellate morphology can help researchers interpret how neurons are arranged and connected within local circuits. Morphological classification provides a cellular framework for relating individual neurons to broader circuit organization. When combined with labeling and microscopy, the approach helps investigate how structural patterns contribute to the organization of these regions.
The same analysis is useful beyond static cell classification. Researchers can apply it to developmental studies and neurological disease research, using dendritic number, branching, and orientation as measurable structural features. Comparing these characteristics across cells or conditions can connect cellular anatomy with circuit organization and help interpret how structural patterns relate to disease-focused neuroscience.