DOI: 10.5061/dryad.wh70rxx2j
title: Data from: Longitudinal three-photon imaging for tracking amyloid plaques and vascular degeneration in a mouse model of Alzheimer’s disease

description: Vascular abnormalities may contribute to amyloid-beta accumulation and
 neurotoxicity in Alzheimer’s disease (AD). Monitoring vascular
 degeneration as AD progresses is essential. Three-photon fluorescence
 microscopy (3PM) enables high-resolution deep tissue imaging with minimal
 invasiveness and photodamage. We demonstrated the potential of
 three-photon imaging to track vascular and amyloid-related changes in deep
 cortical structures. It offers a tool for studying the interplay between
 vascular and amyloid pathologies in AD, supporting future research into
 disease mechanisms and therapeutic strategies. This dataset contains all
 three-photon imaging data used in the manuscript, including plaques and
 vascular structures across multiple mice, fields of view (FOVs), and two
 longitudinal imaging sessions. GFP labeled neurons with vessels as well as
 neonatal lung imaging for power calibration can also be found in the
 folder.
description: # Data from: Longitudinal three-photon imaging for tracking amyloid
 plaques and vascular degeneration in a mouse model of Alzheimer’s disease
 Dataset DOI: 10.5061/dryad.wh70rxx2j ## Description of the data and file
 structure The data were collected for a study using longitudinal
 three-photon microscopy to monitor changes in blood vessels and amyloid
 plaques in APP NL-G-F mice. Mice were imaged twice, four weeks apart.
 Texas Red labeled the vasculature, and methoxy-XO4 labeled amyloid
 plaques. Three-photon imaging enabled deep cortical imaging, and the
 resulting stacks were processed to segment vessels and plaques and to
 quantify structural changes over time. This dataset
 (wetransfer_data-3p_2025-11-21_1143.zip) also includes one stack of
 GFP-labeled neurons with vessels, two additional plaque–vessel stacks, and
 six neonatal lung images used for power calibration. ### Files and
 variables All files are TIFF image stacks (16-bit grayscale). **1. Fig 3**
 XY pixel size 0.98 µm; Z-step 5 µm (plaques/vessels), 10 µm (neurons);
 channels: Texas Red, methoxy-XO4, GFP, THG. * 3a Plaques.tif – Methoxy-XO4
 plaques * 3a Vessels.tif – Texas Red vessels * 3b GFP neurons.tif –
 GFP-labeled neurons with vessels **2. Longitudinal Imaging** Each mouse
 was imaged twice, 4 weeks apart (Session 1 and Session 2).\ XY pixel size
 0.98 µm; Z-step 5 µm; depth ~0–900 µm; excitation 1340 nm. Texas Red
 (vessels), methoxy-XO4 (plaques) **Mouse 1 FOV I** * Plaques S1, Plaques
 S2 * Vessels S1, Vessels S2 **Mouse 1 FOV II** * Plaques S1, Plaques S2 *
 Vessels S1, Vessels S2 **Mouse 2 FOV I** * Plaques S1, Plaques S2 *
 Vessels S1, Vessels S2 **Mouse 2 FOV II** * Plaques S1, Plaques S2 *
 Vessels S1, Vessels S2 **Mouse 3 FOV I** * Plaques S1 (if present),
 Plaques S2 * Vessels S1, Vessels S2 **3. Calibration Data** XY pixel size
 0.98 µm; Z-step 5 µm; used for power-stability checks. *
 neonatal_lung_sampleA1–A3.tif * neonatal_lung_sampleB1–B3.tif **4.
 High-plaque load test images** XY pixel size 0.98 µm; Z-step 5 µm; depth
 ~0–900 µm; excitation 1340 nm. Texas Red (vessels), methoxy-XO4 (plaques)
 * Vessels plus plaques.tif * Vessels plus plaques 2.tif ## Code/software
 All data can be viewed and processed using the codes accessible on: 
 [https://github.com/estassss/Longitudinal-three-photon-imaging](https://github.com/estassss/Longitudinal-three-photon-imaging)