The mouse laser-induced choroidal neovascularization (CNV) model has been a crucial mainstay model for neovascular age-related macular degeneration (AMD) research. By administering targeted laser injury to the RPE and Bruch's membrane, the procedure induces angiogenesis, modeling the hallmark pathology observed in neovascular AMD. First developed in non-human primates, the laser-induced CNV model has come to be implemented into many other species, the most recent of which being the mouse. Mouse experiments are advantageously more cost-effective, experiments can be executed on a much faster timeline, and they allow the use of various transgenic models. The miniature size of the mouse eye, however, poses a particular challenge when performing the procedure. Manipulation of the eye to visualize the retina requires practice of fine dexterity skills as well as simultaneous hand-eye-foot coordination to operate the laser. However, once mastered, the model can be applied to study many aspects of neovascular AMD such as molecular mechanisms, the effect of genetic manipulations, and drug treatment effects. The laser-induced CNV model, though useful, is not a perfect model of the disease. The wild-type mouse eye is otherwise healthy, and the chorio-retinal environment does not mimic the pathologic changes in human AMD. Furthermore, injury-induced angiogenesis does not reflect the same pathways as angiogenesis occurring in an age-related and chronic disease state as in AMD. Despite its shortcomings, the laser-induced CNV model is one of the best methods currently available to study the debilitating pathology of neovascular AMD. Its implementation has led to a deeper understanding of the pathogenesis of AMD, as well as contributing to the development of many of the AMD therapies currently available.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4780856PMC
http://dx.doi.org/10.3791/53502DOI Listing

Publication Analysis

Top Keywords

cnv model
16
neovascular amd
12
laser-induced cnv
12
laser-induced choroidal
8
choroidal neovascularization
8
amd
8
mouse eye
8
model
7
mouse
6
laser-induced
5

Similar Publications

Copy number variation (CNV) is an important part of human genetic variations, which is associated with various kinds of diseases. To tackle the limitations of traditional CNV detection methods, such as restricted detection types, high error rates, and challenges in precisely identifying the location of variant breakpoints, a new method called MSCNV (copy number variations detection method for multi-strategies integration based on a one-class support vector machine model) is proposed. MSCNV establishes a multi-signal channel that integrates three strategies: read depth, split read, and read pair.

View Article and Find Full Text PDF

Copy Number Variant Does Not Influence Stroke Severity in 2 C57BL/6J Mouse Models nor in Humans: An Exploratory Study.

Stroke

January 2025

Department of Experimental Neurology, Center for Stroke Research Berlin (CSB), Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany (M.F., S.B., S.M., K.W., M.E., A.M., U.D., C.S.).

Background: Contrary to the common belief, the most commonly used laboratory C57BL/6J mouse inbred strain presents a distinctive genetic and phenotypic variability, and for several traits, the genotype-phenotype link remains still unknown. Recently, we characterized the most important stroke survival factor such as brain collateral plasticity in 2 brain ischemia C57BL/6J mouse models (bilateral common carotid artery stenosis and middle cerebral artery occlusion) and observed a Mendelian-like fashion of inheritance of the posterior communicating artery (PcomA) patency. Interestingly, a copy number variant (CNV) spanning locus was reported to segregate in an analogous Mendelian-like pattern in the C57BL/6J colonies of the Jackson Laboratory.

View Article and Find Full Text PDF

Integrating mitochondrial and lysosomal gene analysis for breast cancer prognosis using machine learning.

Sci Rep

January 2025

Departments of Breast Surgery, First Affiliated Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, People's Republic of China.

The impact of mitochondrial and lysosomal co-dysfunction on breast cancer patient outcomes is unclear. The objective of this study is to develop a predictive machine learning (ML) model utilizing mitochondrial and lysosomal co-regulators in order to provide a foundation for future studies focused on breast cancer (BC) patients' stratification and personalized interventions. Firstly, Differences and correlations of mitochondrial and lysosome related genes were screened and validated by differential analysis, copy number variation (CNV), single nucleotide polymorphism (SNPs) and correlation analysis.

View Article and Find Full Text PDF

Background: Patients suffer from esophageal squamous cell carcinoma (ESCC), which is the ninth highly aggressive malignancy. Tumor-infiltrating immune cells (TIIC) exert as major component of the tumor microenvironment (TME), showing possible prognostic value in ESCC.

Methods: Transcriptome data and scRNA-seq data of ESCC samples were extracted from the GEO and TCGA databases.

View Article and Find Full Text PDF

Background: The role of pyroptosis in lung squamous cell carcinoma (LUSC) remains unclear. This study aimed to screen pyroptosis-related genes (PRGs) and construct a model to investigate the immune infiltration, gene mutations, and immune response of patients of LUSC.

Methods: We conducted a comprehensive evaluation of pyroptosis patterns in patients with LUSC with 51 PRGs.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!