Stromal Feature Detection
Stromal Feature Detection - Related Videos
07:51
Full-Field Optical Coherence Microscopy for Histology-Like Analysis of Stromal Features in Corneal Grafts
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Cited by 3 •
2022
We describe use of full-field optical coherence microscopy as a method for high quality assessment of corneal donor stroma. This protocol can be used to identify features indicative of health or disease, and is aimed at improving the screening and selection of donor tissues, and hence the results of keratoplasty.
12:42
Heterotypic Three-dimensional In Vitro Modeling of Stromal-Epithelial Interactions During Ovarian Cancer Initiation and Progression
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Cited by 20 •
2012
We describe methodologies for establishing in vitro heterotypic three-dimensional models comprising ovarian fibroblasts and normal ovarian surface or ovarian cancer epithelial cells. We discuss the use of these models to study stromal-epithelial interactions that occur during ovarian cancer development.
07:27
Recurrent Herpetic Stromal Keratitis in Mice, a Model for Studying Human HSK
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Cited by 17 •
2012
Most studies of herpetic corneal disease use a primary infection model. However, primary infection with HSV-1 does not typically lead to human disease. Here we describe a recurrent model of herpetic corneal disease, which more closely mimics human disease.
08:40
Optimization of the Wound Scratch Assay to Detect Changes in Murine Mesenchymal Stromal Cell Migration After Damage by Soluble Cigarette Smoke Extract
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Cited by 44 •
2015
The capacity to migrate is a key function of many different cell types, including mesenchymal stromal cells (MSCs). However, quantifying alterations in migratory capacity after damage is challenging. This protocol describes an easily adaptable migration assay that uses rigorous statistics to quantify changes in MSC migratory capacity after damage.
05:42
Visual Search for Features and Conjunctions
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University How do people find objects in cluttered visual scenes? Think, for example, of looking for keys on a messy desk, finding the ripest-looking fruit at the grocery store, locating your car when you can’t quite remember where you parked it, or finding an old friend at an airport exit gate. Clearly, an understanding of visual perception is going to play a role in any answers, and more specifically, an understanding of visual attention...
FAQs
Reliable classification comes from combining several evidence types rather than relying on one visual cue. Imaging shows tissue structure, cellular morphology distinguishes cell appearances, spatial organization reveals how features are arranged, and marker expression helps characterize compartments. Together, these signals support more specific interpretation of stromal regions and their relationships with neighboring immune or infected cells.
Spatial organization is important because location can indicate how stromal compartments shape local immune environments. Examining where features occur relative to immune or infected cells can reveal inflammatory niches, altered tissue architecture, or changes associated with cellular recruitment. This context helps connect a detected feature with tissue-level behavior instead of treating it as an isolated cellular or molecular signal.
Unlike an analysis limited to immune-cell identity or pathogen-associated signals, stromal feature detection preserves the tissue context in which those signals occur. It considers structural features, morphology, spatial relationships, and marker expression together. That distinction matters when disease-related changes involve barriers, supportive compartments, or local interactions that cannot be interpreted fully from neighboring cell measurements alone.
An analysis typically begins with tissue imaging, followed by examination of stromal morphology and spatial arrangement. Marker expression is then considered to help distinguish stromal compartments, and the findings are compared with the positions of neighboring immune or infected cells. The final interpretation links these observations to changes in architecture, inflammatory niches, barrier function, or recruitment.
The method can produce a tissue-level description of altered architecture, inflammatory niches, barrier function, and cellular recruitment. These outcomes help investigators assess whether disease or experimental treatment is associated with changes in the microenvironment. Because the analysis connects features with their locations and neighboring cells, it can also contribute to tissue-based biomarker development and interpretation of local immune responses.
In immunology and infection studies, the approach is useful for examining how host tissues respond to infection and how pathogens relate to stromal environments. It can clarify host-pathogen interactions by showing changes in supportive tissue compartments and surrounding immune organization. The same information supports evaluation of therapies designed to influence the tissue microenvironment, not only individual cells.