Data and code from: Multi-modal label-free imaging of cellular metabolism and oxidative stress in 3D brain tissue models

Zhang, Yang 1 2 ; Georgakoudi, Irene 1 3

Published May 12, 2026 on Dryad. https://doi.org/10.5061/dryad.w3r228149

Data files

May 12, 2026 version files 8.11 GB

Abstract

This dataset contains multi-modal label-free imaging data generated from 3D engineered human brain tissue models composed of human induced neural stem cell-derived neurons, astrocytes, and microglia cultured under multiple experimental conditions and longitudinal timepoints. The repository includes raw and processed two-photon fluorescence intensity imaging, fluorescence lifetime imaging microscopy (FLIM), and spectral imaging datasets, together with spectral reference profiles, extracted metabolic measurements, image analysis outputs, and associated metadata tables. Endogenous fluorescence signals from key fluorophores, including NAD(P)H, flavin adenine dinucleotide (FAD), lipoamide dehydrogenase, and lipofuscin, were used to quantify optical redox ratio, mitochondrial fragmentation, fluorescence lifetime parameters, oxidative stress-related signals, and NAD(P)H bound-state dynamics at single-cell resolution. Spectral characterization and multi-wavelength imaging data are included to support fluorophore separation and correction for spectral overlap and lipofuscin interference. All data were generated from in vitro human cell culture models and do not contain personally identifiable human participant information or clinical data.

Dataset DOI: 10.5061/dryad.w3r228149

Description of the data and file structure

This repository contains raw and processed multi-modal label-free imaging datasets generated from 3D engineered human brain tissue models composed of neurons, astrocytes, and microglia derived from human induced neural stem cells. The dataset includes two-photon fluorescence intensity imaging, fluorescence lifetime imaging microscopy (FLIM), spectral imaging data, cell annotation files, ROI-based quantification tables, and helper scripts used for downstream analysis.

The data were collected longitudinally across multiple culture timepoints and experimental conditions, including monoculture and triculture systems.

Files and variables

File: Triculture_Annoations.zip

Description: Contains annotation files corresponding to triculture datasets containing neurons, astrocytes, and microglia. Annotation files include ROI labels, segmented cellular regions, and cell-type-associated annotations used for image analysis and downstream quantification.

File: Monoculture_Annotations.zip

Description: Contains annotation files corresponding to monoculture datasets containing neurons and scaffold/background regions used for image analysis and ROI identification.

File: HelperFunctions.zip

Description: Contains MATLAB and Python helper scripts used for image processing, ROI extraction, fluorescence quantification, spectral analysis, and downstream analysis workflows.

File: Raw_Images.zip

Description: Contains raw microscopic imaging datasets acquired using multi-photon fluorescence imaging systems, including two-photon fluorescence intensity imaging, spectral imaging, and fluorescence lifetime imaging microscopy (FLIM) datasets.

File: Data_records.zip

Description: Contains tabular data records, ROI-based file name information, processed measurement outputs, and associated metadata generated from the imaging datasets across multiple experimental conditions and timepoints.

Missing values and empty cells

Some tabular files contain intentionally preserved empty cells. These empty cells do not necessarily represent missing data. Instead, they commonly indicate that a specific ROI, image, imaging modality, processing output, or analysis category did not contain or require the corresponding data type.

For example:
- Certain ROIs may contain fluorescence intensity measurements but no associated spectral or FLIM data
- Some imaging outputs may only apply to specific experimental conditions or processing workflows
- Some analysis fields are only populated when corresponding image features or modalities are present

Empty cells were intentionally preserved to maintain the original table structure and compatibility with downstream analysis scripts and numeric data formatting.

Code/software

Raw image files can be viewed using standard image analysis software capable of opening TIFF (.tif) image formats, including Fiji/ImageJ and MATLAB 2024b (MathWorks). MATLAB (.mat) files can be opened using MATLAB 2024b or compatible MATLAB versions. CSV tabular files can be opened using spreadsheet software or data analysis tools such as Microsoft Excel, Python, or R.Data processing and analysis workflows were performed using MATLAB 2024b and Python 3.7. Helper scripts used for image processing, ROI extraction, fluorescence quantification, spectral analysis, and downstream analysis workflows are included in HelperFunctions.zip.

Associated analysis code is also available at:https://doi.org/10.5281/zenodo.17228894

Access information

Other publicly accessible locations of the data:

Associated analysis code and helper scripts are publicly available at Zenodo:
https://doi.org/10.5281/zenodo.17228894

Data was derived from the following sources:

Data were generated from in vitro human induced neural stem cell-derived brain tissue models developed in this study and were not derived from external public datasets.