A microneedle device for rapid dermal interstitial fluid sampling
Data files
Sep 05, 2025 version files 58.03 MB
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3Dmodels.zip
11 MB
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Figure2.zip
41.60 MB
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Figure3.zip
3.33 MB
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Figure4.zip
953 B
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Figure5.zip
478.38 KB
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Figure6.zip
1.20 MB
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README.md
3.61 KB
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Supplementary.zip
418.32 KB
Abstract
Dermal interstitial fluid (ISF) offers a promising alternative to invasive blood tests and opportunities for novel skin diagnostics. Progress in both the understanding and adoption of ISF tests is hindered by sampling challenges, including lengthy collection times, non-negligible failure rates, variable collection volumes, and inconsistent bioanalyte levels. The causes of many of these issues are not well understood. We demonstrate a microneedle device that is several times faster than state-of-the-art, collecting an average of 15.5 mg of ISF in 5 minutes in humans with a near-zero failure rate. This improvement was achieved by designing the spatial pressure gradient driving ISF flow. The influence of penetration depth, collection time, pressure, and age on ISF collection was elucidated, with Darcy's law explaining multiple observations. A data-driven acceptance criterion of <1% blood contamination for ISF is proposed. The device and findings presented will empower researchers to better conduct robust studies in the development of ISF diagnostics.
Dataset DOI: 10.5061/dryad.c2fqz61p1
Description of the data and file structure
This dataset contains all 3D models, data, simulations, and code from the associated publication, organized by figure. It includes device design and simulation files, proteomics data for ISF, plasma, and RBC, contaminant protein lists for RBC and plasma, and code for removing blood contamination. Raw mass spectrometry proteomics data are on ProteomeXchange.
Files and variables
Additional details regarding individual files can be found in the README included in each zip file. Definitions of variables are found in the README files for CSV data and in the Variables sheet for XLSX files.
File: 3Dmodels.zip
Description: 3D model files of all versions of the POP device and experimental accessories. Both STL and Autodesk Fusion F3D files are included.
File: Figure2.zip
Description: Raw data for Figure 2, including Autodesk Fusion F3D files of the simulation setups and VTU files of the simulation results.
File: Figure3.zip
Description: Raw data for Figure 3, including proteomics data and R code for generating volcano plots in the figure. Documentation for the input, output, and purpose of each R file is included.
File: Figure4.zip
Description: Raw data for Figure 4.
File: Figure5.zip
Description: R code and files for 1) generating ranked lists of RBC and plasma contaminant proteins, 2) estimating proteomic quantification error at any blood contamination level, and 3) processing proteomics data to remove proteins affected by blood contamination. Documentation for the input, output, and purpose of each R file is included.
File: Figure6.zip
Description: Raw data for Figure 6, including R code for decontaminating proteomics data in Figure 6A to show the fraction of the most abundant ISF and plasma proteins by iBAQ. Documentation for the input, output, and purpose of each R file is included.
File: Supplementary.zip
Description: R code and input file for generating a histogram of the coefficient of variation to estimate MS quantification error. List of Early Detection Research Network proteins found in ISF and plasma.
Code/software
Autodesk Fusion is needed to view the F3D design and simulation setup files. Alternatively, STL and VTU files are included and are viewable in open-source software such as ParaView. RStudio is used to run R scripts. Required R packages are shown in the R files. Documentation of the input, output, and purpose of each R file is included in the individual zip files.
Missing Data
Where applicable, an explanation for missing data is found in the README associated with each figure. For proteomic data, 0 or an empty cell indicates that the protein is below the threshold of detection. Alternatively, a peptide-spectrum match can yield slightly different results between technical replicates, resulting in empty cells. For tabular data derived from proteomic data, an empty cell indicates insufficient sample size for performing the calculations.
Access information
Associated mass spectrometry proteomics data on ProteomeXchange: Accession PXD064496
Human subjects data
Human participants in the study consented to the publication of de-identified data in the public domain. A unique sample number was generated for each de-identified specimen collected from the participant. No link was maintained between the sample numbers and the participants.
