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A method for preserving and visualizing the three-dimensional structure of the mouse zonule.

ABSTRACT: Mechanical failure of the ciliary zonule characterizes several ocular and systemic diseases. The mouse has emerged as a useful model system to investigate the composition and structure/function relationships of the zonule. However, visualizing the organization of the diaphanous fibers that comprise the zonule is technically challenging because the fibers do not take up conventional histological stains and are disrupted easily during processing. Here, we describe a simple method for maintaining physiological pressure within the mouse eye during fixation, and a gel-embedding technique for stabilizing the zonular fibers during subsequent tissue processing and imaging steps. This approach facilitates quantitative measurements of fiber number and cross-sectional dimensions and will allow the effects of targeted disruption of zonule components to be assessed systematically.

SUBMITTER: Bassnett S

PROVIDER: S-EPMC6698427 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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A method for preserving and visualizing the three-dimensional structure of the mouse zonule.

Bassnett Steven S

Experimental eye research 20190531

Mechanical failure of the ciliary zonule characterizes several ocular and systemic diseases. The mouse has emerged as a useful model system to investigate the composition and structure/function relationships of the zonule. However, visualizing the organization of the diaphanous fibers that comprise the zonule is technically challenging because the fibers do not take up conventional histological stains and are disrupted easily during processing. Here, we describe a simple method for maintaining p ...[more]

PMID: 31158380

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Project description:BACKGROUND:The words 'infection' and 'inflammation' lack specific definitions. Here, such words are not defined. Instead, the ability to visualize host-microbial interactions was explored. METHODS:Leukocyte differential counts and four bacterial species (Staphylococcus aureus, Streptococcus dysgalactiae, Staphylococcus chromogenes, and Escherichia coli) were determined or isolated in a cross-sectional and randomized study conducted with 611 bovine milk samples. Two paradigms were evaluated: (i) the classic one, which measures non-structured (count or percent) data; and (ii) a method that, using complex data structures, detects and differentiates three-dimensional (3D) interactions among lymphocytes (L), macrophages (M), and neutrophils (N). RESULTS:Classic analyses failed to differentiate bacterial-positive (B+) from -negative (B-) observations: B- and B+ data overlapped, even when statistical significance was achieved. In contrast, the alternative approach showed distinct patterns, such as perpendicular data inflections, which discriminated microbial-negative/mononuclear cell-predominating (MCP) from microbial-positive/phagocyte-predominating (PP) subsets. Two PP subcategories were distinguished, as well as PP/culture-negative (false-negative) and MCP/culture-positive (false-positive) observations. In 3D space, MCP and PP subsets were perpendicular to one another, displaying ? 91% specificity or sensitivity. Findings supported five inferences: (i) disease is not always ruled out by negative bacterial tests; (ii) low total cell counts can coexist with high phagocyte percents; (iii) neither positive bacterial isolation nor high cell counts always coincide with PP profiles; (iv) statistical significance is not synonymous with discrimination; and (v) hidden relationships cannot be detected when simple (non-structured) data formats are used and statistical analyses are performed before data subsets are identified, but can be uncovered when complexity is investigated. CONCLUSIONS:Pattern recognition-based assessments can detect host-microbial interactions usually unobserved. Such cutoff-free, confidence interval-free, gold standard-free approaches provide interpretable information on complex entities, such as 'infection' and 'inflammation', even without definitions. To investigate disease dynamics, combinations of observational and experimental longitudinal studies, on human and non-human infections, are recommended.

Dataset Information

A method for preserving and visualizing the three-dimensional structure of the mouse zonule.

Publications

A method for preserving and visualizing the three-dimensional structure of the mouse zonule.

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