SecNIa Protease Study: Amyloid-β Pathology and Cognitive Data in 5xFAD Mice
by Euy Jun Park·Updated 2mo ago
872.5 KB1files
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Description
872.5 KB PDF from figshare details a study where a secretory viral protease, SecNIa, was delivered via AAV to 5xFAD mice, a model of Alzheimer's disease. Author Euy Jun Park published the work on April 22, 2026, reporting that SecNIa expression reduced soluble and insoluble Aβ, decreased plaques, and improved cognition. The findings suggest a direct therapeutic strategy for targeting extracellular amyloid-β pathology.
Use Cases
Analyzing the efficacy of Aβ-cleaving proteases based on reported reductions in soluble and insoluble amyloid-β levels.
Studying cognitive improvement in mouse models based on normalized recognition memory and enhanced spatial learning metrics.
Evaluating adeno-associated virus (AAV) delivery methods for therapeutic proteins based on robust hippocampal expression and CSF secretion data.
Comparing immunotherapy approaches for Alzheimer's disease based on the direct extracellular Aβ degradation mechanism described.
Strengths
Study reports specific, quantified outcomes: reduced Aβ, decreased plaques, and improved cognition.
Data is openly shared under a CC-BY-4.0 license, permitting reuse with attribution.
The methodology is clearly described, involving AAV delivery and analysis in the 5xFAD mouse model.
Limitations
The dataset is a single 872.5 KB PDF document; underlying raw numerical or image data is not directly accessible.
Column-level documentation is absent; field semantics must be inferred from the published article.
Row count is unknown, which may limit suitability assessment for quantitative analysis.
Provenance
Source
Euy Jun Park via figshare
Collection Method
Experimental study using AAV-mediated delivery of SecNIa protease in 5xFAD transgenic mice.
Time Range
Study period not specified; publication date is 2026.
Freshness
Last updated 2026-04-22 05:45:15; freshness should be verified.
Geography
Laboratory study; geographic location not specified.
The primary data is embedded within a scientific PDF; extraction for computational analysis may require manual effort.