The ability to resolve subcellular features can greatly enhance biological discovery, identification of disease targets, and the development of targeted therapeutics. Super-resolution microscopy methods such as structured illumination microscopy (SIM), stochastic optical reconstruction microscopy (STORM), and stimulated emission depletion microscopy (STED) enable nanoscale imaging of specimens (Gustafsson, 2000; Hell and Wichmann, 1994; Rust et al., 2006). However, these approaches require specialized expertise, costly reagents and microscopes. ExM is an inexpensive and accessible method that similarly resolves fluorescently labeled structures at subcellular resolution by isotropically enlarging specimens within a swellable polyelectrolyte hydrogel (Chen et al., 2015). Images of expanded cells show a higher effective resolution due to an increase in the distance between the fluorescent molecules. Super-resolution imaging and ExM are critical tools that are widely used in biological research; however, sample processing and imaging require time-consuming manual manipulation, limiting throughput. Although there has been success in increasing the throughput of certain super-resolution microscopy techniques, these methods require highly specialized equipment and expertise which limits the accessibility of these tools (Holden et al., 2014; Gunkel et al., 2014; Mahecic et al., 2020; Xie et al., 2023). To circumvent these limitations, we developed HiExM that combines parallel sample processing and automated high-content confocal imaging in a standard 96-well cell culture plate.

Adapting standard ExM to a 96-well plate requires the reproducible delivery of a small volume of gel solution to each well (<1 µL compared to ~200 µL/sample for slide-based ExM). This small volume is necessary to allow complete gel expansion within the size constraints of wells in a 96-well plate. To achieve this goal, we engineered a device that retains small liquid droplets when dipped into a reservoir of monomeric expansion gel solution. These droplets can then be deposited into the centers of wells across the cell culture plate (Figure 1a and b). The retention of the gel solution is mediated by a series of reticulated grooves at the end of a cylindrical post which allows for the formation of a pendant droplet (Figure 1c). We estimate that each post retains ~230 nL of gel solution as measured by the mass of liquid accumulated on all post tips of a single device after dipping (Supplementary methods).

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The small volume of gel solution delivered to each well by the device forms a toroidal droplet where the inner surface is molded by the conical surface of the post-tip and the outer surface is constrained by surface tension (Figure 1c and d). The post-tip dimensions allow delivery of a volume of gel solution that expands relative to the diameter of the well (Figure 1d). The toroidal gel enables isotropic gel expansion within the well constraints while allowing for easy device removal because the inner surface of the gel expands outward away from the conical post-tip, effectively detaching the gel from the device. To achieve this toroidal geometry, our device design incorporates three key features to ensure each post of the device contacts the midpoint at the bottom of each well (Figure 1—figure supplement 1). First, two sets of three cantilevers (‘pressure struts’) are located at each end of the device and flank two rows of six posts (12 posts per device). These pressure struts apply outward force to the inside of the outer four wells ensuring that the device remains in contact with the well surface throughout the expansion process. Second, the spine of the device incorporates several notches extending through the long side of the device allowing it to bend to accommodate plate inconsistencies between the depths of individual wells. Finally, the post lengths are offset from the center four posts to allow for sequential deformation that ensures each post contacts the well surface. Together, these design features allow for reproducible deposition and expansion of gels in a 96-well plate.

To test our device for high-throughput gel expansion, we first performed ProExM using ammonium persulfate (APS) and tetramethylethylenediamine (TEMED) to initiate gel polymerization (Figure 1—figure supplement 2; Tillberg et al., 2016). Since APS rapidly accelerates the polymerization of polyacrylamide hydrogels, TEMED-containing expansion gel solution is first delivered by the device and removed leaving a ≤1 µl droplet in each well of the plate on ice. Another device is then used to deliver APS-containing expansion gel solution at the same volume and the polymerization reaction is initiated by placing the plate on a 50 °C surface. Given the large air-liquid-interface of the gel, droplet delivery and polymerization are performed in a nitrogen-filled glove bag to minimize oxygen inhibition of the reaction. Although we observed gel formation across wells, polymerization and expansion were inconsistent, likely due to inconsistent radical formation and rapid evaporation of the small volume relative to the rate of polymerization (Figure 1—animation 1). To overcome this limitation, we tested photochemical initiators including Lithium phenyl(2,4,6-trimethylbenzoyl)phosphinate (LAP), diphenyl(2,4,6-trimethylbenzoyl)phosphine oxide (TPO), and 1-[4-(2-Hydroxyethoxy)-phenyl]–2-hydroxy-2-methyl-1-propane-1-one (Irgacure 2959) which control polymerization of polyacrylamide gels when exposed to UV light (Li et al., 2022; Pawar et al., 2016). LAP has shown success in slide-based ExM using PEG-based hydrogels (Blatchley et al., 2022; Günay et al., 2023). We found that Irgacure 2959 allowed reproducible gel formation and expansion when compared to either APS/TEMED or other photoinitiators (Figure 1—animation 2).

We next tested the ability of the HiExM platform to achieve nanoscale image resolution of biological specimens. Briefly, A549 cells were cultured, fixed, permeabilized, and immunostained with alpha-tubulin antibodies to visualize microtubules as a reference structure before and after expansion. Stained samples were then incubated with Acryloyl-X (AcX) overnight at 4 °C to allow anchoring of native proteins to the polymer matrix during gel formation. Device posts were immersed in the expansion gel solution containing 0.1% Irgacure 2959. Devices were inserted into the well plate followed by exposure to UV light (365 nm) in an anoxic environment at room temperature to initiate the polymerization reaction. Cells embedded in the resulting gels were digested with Proteinase K then expanded in deionized water overnight (Figure 1—figure supplements 2 and 3). Visual inspection using an epifluorescence microscope showed both robust gel formation and fluorescence signal retention across wells. Although we observed bleaching of AlexaFluor dyes in our Irgacure 2959 photopolymerized gels, Cyanine-based Fluorescent (CF) dyes are robust against bleaching in HiExM and result in reproducible signal retention (Figure 1—figure supplement 4; Jiang et al., 2021). We also titrated AcX and ProteinaseK to optimize signal retention in HiExM and found the 50 µg/mL AcX and 1 U/mL ProteinaseK were most consistent for A549 cells (Figure 1—figure supplement 5). This optimization step is likely critical for different cell types. In some cases, we observed residual Hoechst signal underneath expanded cells due to digested cells that were incompletely removed during wash steps during the expansion process (Figure 1—figure supplement 6). This signal does not impact the interpretation of results.

A major workflow bottleneck associated with super-resolution imaging, including current ExM protocols, is the significant time and expertise required for image acquisition. For example, the vertical component of expansion increases the depth of the sample, necessitating more optical z-slices to image the full depth of the sample. Moreover, expansion effectively decreases the field-of-view due to increasing sample size, necessitating the acquisition of more images to analyze the same number of cells at lower resolution. To enable rapid 3D image capture of expanded cells in 96-well plates, we used a high-content confocal microscope (Opera Phenix system, Perkin Elmer) (Figure 2a). This approach allowed autonomous capture of images across the entire plate at a resolution of ~115 nm compared to ~463 nm for unexpanded samples using the same microscope, objective (63 X, 1.15NA water immersion), and imaging wavelength (Figure 2—figure supplement 1). Image resolution was calculated using a decorrelation analysis (Descloux et al., 2019). We used the PreciScan plug-in in the Harmony analysis software to first accurately target regions of interest based on Hoechst staining to reduce acquisition times at higher magnification. Briefly, we imaged plates at 5 x across entire wells and stored the coordinates of nuclei for each well. These coordinates were then used to direct the 63 x magnification objective to the relevant fields of view.

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We next benchmarked the performance of our platform relative to slide-based proExM (Tillberg et al., 2016). Image distortion due to expansion was measured using a non-rigid registration (NRR) algorithm (Chen et al., 2015) Prior to the application of HiExM, images of microtubule stained A549 cells were acquired using the Opera Phenix from 61 fields around the center of each well (Figure 2a). Cells were then expanded as above and 12 fields were imaged per well. Images from pre- and post-expansion were stitched together and the images for each well were then compared side-by-side to identify matched cells. Although we observed that gels did not maintain a fixed position pre- and post- expansion, close inspection of the images allowed us to align their orientations. Distortion was calculated using the root mean squared error (RMSE) of a two-dimensional deformation vector field by comparing microtubule morphology in the same cell before and after expansion in six to ten fields in each well across six arbitrarily selected wells (Figure 2c and d). The average percent error (up to 40 μm measurement length post-expansion) was plotted against the distance from the center of the gel (Figure 2e). Our analysis found no correlation (R²=0.003) between expansion error and distance from the gel center. In fact, we observed only a small number of outliers (>3 s.d.) in any given well (<2 instances per gel across six gels). These outliers are not expected to affect biological interpretation. The outliers, which are closer to the center of the gel, likely occur when the device post is not in full contact with the well surface, resulting in a higher volume of gel at the center that resists gel swelling under the device (Figure 2—figure supplement 2). Expansion error was also highly consistent when comparing wells across multiple plates (average = 3.68%), comparable to slide-based ExM (Figure 2f; Chen et al., 2015; Tillberg et al., 2016). We observed only a small number of image fields (7 of 58) with an average percent error above 6% (maximum 6.78%). Moreover, the calculated error showed that photoinitiation resulted in markedly lower spatial errors compared to APS and TEMED polymerization chemistry (Figure 2—figure supplement 3). Analyzing cell seeding densities also showed that cell confluency did not affect image distortion as measured by NRR (Figure 2—figure supplement 4).

We next measured expansion factors within individual gels, between gels, and across plates by manually measuring the distance between matched pairs of cell landmarks in FIJI before and after expansion. We found that the expansion factor was highly reproducible across different regions of the gel confirming robust expansion using our method (Figure 2g). The average expansion factor of gels sampled across three plates was 4.16+/-0.394 (Figure 2h), consistent with proExM (Tillberg et al., 2016). We next compared the distributions of expansion factors across three well plates by ANOVA and found statistically significant differences between expansion factor distributions. Thus, while uniform within gels, the expansion factor is somewhat variable between gels and plates. We attribute these differences primarily to the small size of the gels, making them vulnerable to the effects of evaporation. This variability should be taken into consideration for studies where absolute length measurements between plates are important for biological interpretation. Collectively, these data show that the HiExM method results in reproducible nanoscale and isotropic expansion of cells within gels, across wells, and plates.

The ability to image cells at increased resolution using HiExM provides an opportunity to analyze nanoscale cellular features for a range of applications including cell phenotyping as well as drug and toxicology studies. As proof of concept, we analyzed the effects of the cardiotoxic chemotherapy agent doxorubicin (dox) on human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) cultured in 96-well plates (Figure 3a; Johnson-Brbor and Dubey, 2023). Commonly used dox concentrations in in vitro cardiotoxicity studies range between 0.1 to 10 μM, depending on experimental goals (Maillet et al., 2016; Yu et al., 2020; Zhao and Zhang, 2017; Stefanova et al., 2023). Although studies largely focus on electrophysiology, structural changes at the cellular level also provide critical information for assessing cardiotoxicity. For example, changes in nuclear morphology as well as DNA damage are associated with cellular stress and apoptosis, which are commonly observed at high dox concentrations (>200 nM) in in vitro studies using conventional microscopy (Maillet et al., 2016; Yu et al., 2020; Zhao and Zhang, 2017; Stefanova et al., 2023; Gewirtz, 1999). In contrast, heart tissue is potentially exposed to lower dox concentrations in clinical treatments (Johnson-Brbor and Dubey, 2023; Chao et al., 2023; Greene et al., 1983) Because HiExM has the sensitivity to detect nanoscale cellular features, we compared nuclei using Hoechst signal intensity in CMs treated with 1 nM, 10 nM, 100 nM, and 1 µM dox after 24 hr compared with DMSO (Figure 3b). Although we did not observe a significant change in overall nuclear morphology (Figure 3—figure supplement 1), images showed increasing Hoechst density at the nuclear periphery in a dox concentration-dependent manner.

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To quantify this effect, we measured the gradient slope of Hoechst intensity around the nuclear periphery. To this end, we masked 529 nuclei from the background in dox-treated and control samples (Figure 3c). We selected a single optical slice that intersected the nucleus perpendicularly along the z-axis for our analysis to avoid an out-of-focus signal at the nuclear edge (Figure 3—figure supplement 2). To account for irregular nuclear shapes, we iteratively grouped pixels into rings for each nucleus starting with the edge of the mask (Figure 3d). The mask is dilated outward from the edge of the nucleus to include a background reading as a reference. The average pixel intensity value for each ring represents the average Hoechst intensity as a function of the relative distance from the edge of the nucleus to its center (Figure 3e, Figure 3—animation 1). Notably, HiExM revealed a peak of Hoechst intensity at the edge of the nucleus that is not resolved in pre-expansion images (Figure 3f). A line-scan-based analysis showed the same trend (Figure 3—figure supplement 3). To further evaluate these differences, we next calculated the first derivative of each curve and found the maximum and minimum values, which correspond to the gradient slopes on either side of the peak (Figure 3g, Figure 3—figure supplement 4). In this case, a higher magnitude of gradient slope reflects a ‘sharper’ transition from the nuclear edge to the background (outside) or from the nuclear edge to the nucleoplasm (inside). Post-expansion, the gradient slopes on both sides of the peak showed a significant increase at dox concentrations as low as 10 nM compared to DMSO, whereas no trend is observed in pre-expansion images (Figure 3g).

In addition to gradient slopes at the nuclear edge, we also quantified the pattern of Hoechst signal at the nuclear edge by calculating the curvature of the peak using the second derivative (Figure 3h). These data also showed a significant increase in Hoechst intensity at 10 nM dox compared to DMSO, whereas no significant difference is observed using conventional confocal microscopy (Figure 3i). We note that, for both the outer gradient slope and peak curvature, values decrease from 100 nM to 1 µM dox, consistent with increased chromatin condensation associated with apoptosis typically observed at higher dox concentrations (Zhao and Zhang, 2017; Toné et al., 2007). In contrast, CMs treated with increasing concentrations of H₂O₂, another cellular stressor, did not show similar differences in Hoechst patterns (Figure 3—figure supplement 5). Although direct evidence specifically linking dox to increased DNA condensation at the nuclear periphery is limited, the known pro-apoptotic effects of dox strongly suggest that our observations correlate with these changes (Maillet et al., 2016; Zhao and Zhang, 2017; Mobaraki et al., 2017). Thus, we suggest that HiExM can detect early alterations in response to dox treatment using the Hoechst signal, setting the stage for further investigation to understand the consequences across a range of drugs and conditions. Overall, our analysis demonstrates the ability of HiExM to detect subtle cellular changes compared to standard confocal microscopy that could improve the resolution of drug screening approaches.

Our work demonstrates that HiExM is a simple and inexpensive method that can increase the throughput of expansion microscopy. Another recent method also reports a scalable ExM-based method with comparable throughput, albeit this approach requires the use of a custom cell culture microplate and manual imaging (Xie et al., 2023) Our device is fabricated with CNC milling, a common fabrication technique available in most academic settings, making our method widely accessible. The HiExM device can also be produced by injection molding which can further extend its accessibility and distribution in research settings. We have also adapted our device to fit cell culture plates of varying dimensions including a 24-well plate which can accommodate greater expansion and significantly higher resolution (Figure 1—figure supplement 7; Damstra et al., 2022). Moreover, the use of a photo-active gel solution enabled consistent expansion in our HiExM workflow. In this work, we found that the use of photoinitiation with irgacure caused signal loss for to varying degrees depending on the fluorophore; coupled with the signal dilution inherent to the expansion process, signal intensity is an important consideration when using HiExM. Our platform is amenable to other photo-active expansion chemistries such as the Photo-ExM chemistry which does not require CF dyes or an anoxic environment (Figure 3—figure supplement 6; Blatchley et al., 2022; Günay et al., 2023).

Another advantage of HiExM is that it is fully compatible with autonomous imaging, allowing data acquisition of thousands of cells within a day. HiExM achieved a resolution of ~115 nm in a 96-well culture plate using a 63 x water immersion objective with a 1.15 numerical aperture. By employing microscopes with a higher numerical aperture, we expect our platform can achieve significantly greater resolution. We also show that HiExM error measurements are similar to proExM and suggest that expansion distortions should be considered for robust data interpretation. Recent innovative work that developed a microplate-based ExM protocol maintains hydrogel geometry and orientation improves coordinate-based imaging to accurately assess distortions with ease (Seehra et al., 2023). Another recent work used micropatterning to apply expandable protein grids to coverslips for local expansion factor measurement. This method could be adapted to HiExM to enable expansion measurements in large datasets where non-rigid registration is impractical (Damstra et al., 2023) Taken together, HiExM is an accessible nanoscale imaging platform designed for scalable sample preparation and autonomous imaging, broadening the use of ExM in biological research and pharmaceutical applications.

Solidworks files for our devices as well as code for our analysis are available at the following link: https://github.com/lboyerlab/hiExM_Supplementary_Files (copy archived at lboyerlab, 2024). Raw data produced from this work are accessible through Dryad (https://doi.org/10.5061/dryad.fbg79cp57).

1. 1. John D

   (2024) Dryad Digital Repository

   Data for: High-throughput expansion microscopy enables scalable super-resolution imaging.

   https://doi.org/10.5061/dryad.fbg79cp57

1. 1. Asano SM
   2. Gao R
   3. Wassie AT
   4. Tillberg PW
   5. Chen F
   6. Boyden ES

   (2018) Expansion microscopy: Protocols for imaging proteins and RNA in cells and tissues

   Current Protocols in Cell Biology 80:e56.

   https://doi.org/10.1002/cpcb.56

   • PubMed
   • Google Scholar
2. 1. Blatchley MR
   2. Günay KA
   3. Yavitt FM
   4. Hawat EM
   5. Dempsey PJ
   6. Anseth KS

   (2022) In situ super-resolution imaging of organoids and extracellular matrix interactions via phototransfer by allyl sulfide exchange-expansion microscopy (PhASE-ExM)

   Advanced Materials 34:e2109252.

   https://doi.org/10.1002/adma.202109252

   • PubMed
   • Google Scholar
3. 1. Chao FC
   2. Manaia EB
   3. Ponchel G
   4. Hsieh CM

   (2023) A physiologically-based pharmacokinetic model for predicting doxorubicin disposition in multiple tissue levels and quantitative toxicity assessment

   Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie 168:115636.

   https://doi.org/10.1016/j.biopha.2023.115636

   • PubMed
   • Google Scholar
4. 1. Chen F
   2. Tillberg PW
   3. Boyden ES

   (2015) Expansion microscopy

   Science 347:543–548.

   https://doi.org/10.1126/science.1260088

   • Google Scholar
5. 1. Damstra HGJ
   2. Mohar B
   3. Eddison M
   4. Akhmanova A
   5. Kapitein LC
   6. Tillberg PW

   (2022) Visualizing cellular and tissue ultrastructure using ten-fold robust expansion microscopy (TREx)

   eLife 11:e73775.

   https://doi.org/10.7554/eLife.73775

   • PubMed
   • Google Scholar
6. 1. Damstra HGJ
   2. Passmore JB
   3. Serweta AK
   4. Koutlas I
   5. Burute M
   6. Meye FJ
   7. Akhmanova A
   8. Kapitein LC

   (2023) GelMap: intrinsic calibration and deformation mapping for expansion microscopy

   Nature Methods 20:1573–1580.

   https://doi.org/10.1038/s41592-023-02001-y

   • PubMed
   • Google Scholar
7. 1. Descloux A
   2. Grußmayer KS
   3. Radenovic A

   (2019) Parameter-free image resolution estimation based on decorrelation analysis

   Nature Methods 16:918–924.

   https://doi.org/10.1038/s41592-019-0515-7

   • PubMed
   • Google Scholar
8. 1. Gewirtz DA

   (1999) A critical evaluation of the mechanisms of action proposed for the antitumor effects of the anthracycline antibiotics adriamycin and daunorubicin

   Biochemical Pharmacology 57:727–741.

   https://doi.org/10.1016/s0006-2952(98)00307-4

   • PubMed
   • Google Scholar
9. 1. Greene RF
   2. Collins JM
   3. Jenkins JF
   4. Speyer JL
   5. Myers CE

   (1983)

   Plasma pharmacokinetics of adriamycin and adriamycinol: implications for the design of in vitro experiments and treatment protocols

   Cancer Research 43:3417–3421.

   • PubMed
   • Google Scholar
10. 1. Günay KA
    2. Chang T-L
    3. Skillin NP
    4. Rao VV
    5. Macdougall LJ
    6. Cutler AA
    7. Silver JS
    8. Brown TE
    9. Zhang C
    10. Yu C-CJ
    11. Olwin BB
    12. Boyden ES
    13. Anseth KS

    (2023) Photo-expansion microscopy enables super-resolution imaging of cells embedded in 3D hydrogels

    Nature Materials 22:777–785.

    https://doi.org/10.1038/s41563-023-01558-5

    • PubMed
    • Google Scholar
11. 1. Gunkel M
    2. Flottmann B
    3. Heilemann M
    4. Reymann J
    5. Erfle H

    (2014) Integrated and correlative high-throughput and super-resolution microscopy

    Histochemistry and Cell Biology 141:597–603.

    https://doi.org/10.1007/s00418-014-1209-y

    • PubMed
    • Google Scholar
12. 1. Gustafsson MGL

    (2000) Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy

    Journal of Microscopy 198:82–87.

    https://doi.org/10.1046/j.1365-2818.2000.00710.x

    • PubMed
    • Google Scholar
13. 1. Hell SW
    2. Wichmann J

    (1994) Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy

    Optics Letters 19:780–782.

    https://doi.org/10.1364/ol.19.000780

    • PubMed
    • Google Scholar
14. 1. Holden SJ
    2. Pengo T
    3. Meibom KL
    4. Fernandez Fernandez C
    5. Collier J
    6. Manley S

    (2014) High throughput 3D super-resolution microscopy reveals Caulobacter crescentus in vivo Z-ring organization

    PNAS 111:4566–4571.

    https://doi.org/10.1073/pnas.1313368111

    • PubMed
    • Google Scholar
15. 1. Jiang J
    2. Li X
    3. Mao F
    4. Wu X
    5. Chen Y

    (2021) Small molecular fluorescence dyes for immuno cell analysis

    Analytical Biochemistry 614:114063.

    https://doi.org/10.1016/j.ab.2020.114063

    • PubMed
    • Google Scholar
16. Book

    1. Johnson-Brbor K
    2. Dubey R

    (2023)

    Doxorubicin

    StatPearls Publishing.

    • Google Scholar
17. Software

    1. lboyerlab

    (2024) hiExM_Supplementary_Data, version swh:1:rev:6c982971c095704ca32dcb37c87659603c9a70e0

    Software Heritage.

    https://archive.softwareheritage.org/swh:1:dir:996b638e5868c4370bb2220df6bf1f84c24f181e;origin=https://github.com/lboyerlab/hiExM_Supplementary_Files;visit=swh:1:snp:86ead59bb994687b82aa81de2ebc9de0603133ee;anchor=swh:1:rev:6c982971c095704ca32dcb37c87659603c9a70e0
18. 1. Li N
    2. Xiang Z
    3. Rong Y
    4. Zhu L
    5. Huang X

    (2022) 3D Printing tannic acid-based gels via digital light processing

    Macromolecular Bioscience 22:2100455.

    https://doi.org/10.1002/mabi.202100455

    • PubMed
    • Google Scholar
19. 1. Mahecic D
    2. Gambarotto D
    3. Douglass KM
    4. Fortun D
    5. Banterle N
    6. Ibrahim KA
    7. Le Guennec M
    8. Gönczy P
    9. Hamel V
    10. Guichard P
    11. Manley S

    (2020) Homogeneous multifocal excitation for high-throughput super-resolution imaging

    Nature Methods 17:726–733.

    https://doi.org/10.1038/s41592-020-0859-z

    • PubMed
    • Google Scholar
20. 1. Maillet A
    2. Tan K
    3. Chai X
    4. Sadananda SN
    5. Mehta A
    6. Ooi J
    7. Hayden MR
    8. Pouladi MA
    9. Ghosh S
    10. Shim W
    11. Brunham LR

    (2016) Modeling doxorubicin-induced cardiotoxicity in human pluripotent stem cell derived-cardiomyocytes

    Scientific Reports 6:25333.

    https://doi.org/10.1038/srep25333

    • PubMed
    • Google Scholar
21. 1. Mobaraki M
    2. Faraji A
    3. Zare M
    4. Manshadi HRD

    (2017) Molecular mechanisms of cardiotoxicity: A review on major side-effect of doxorubicin

    Indian Journal of Pharmaceutical Sciences 79:1000235.

    https://doi.org/10.4172/pharmaceutical-sciences.1000235

    • Google Scholar
22. 1. Pawar AA
    2. Saada G
    3. Cooperstein I
    4. Larush L
    5. Jackman JA
    6. Tabaei SR
    7. Cho N-J
    8. Magdassi S

    (2016) High-performance 3D printing of hydrogels by water-dispersible photoinitiator nanoparticles

    Science Advances 2:e1501381.

    https://doi.org/10.1126/sciadv.1501381

    • PubMed
    • Google Scholar
23. 1. Rust MJ
    2. Bates M
    3. Zhuang X

    (2006) Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)

    Nature Methods 3:793–795.

    https://doi.org/10.1038/nmeth929

    • PubMed
    • Google Scholar
24. 1. Seehra RS
    2. Warrington SJ
    3. Allouis BHK
    4. Sheard TMD
    5. Spencer ME
    6. Shakespeare T
    7. Cadby A
    8. Bose D
    9. Strutt D
    10. Jayasinghe I

    (2023) Geometry-preserving expansion microscopy microplates enable high-fidelity nanoscale distortion mapping

    Cell Reports Physical Science 4:101719.

    https://doi.org/10.1016/j.xcrp.2023.101719

    • Google Scholar
25. 1. Stefanova ME
    2. Ing-Simmons E
    3. Stefanov S
    4. Flyamer I
    5. Dorado Garcia H
    6. Schöpflin R
    7. Henssen AG
    8. Vaquerizas JM
    9. Mundlos S

    (2023) Doxorubicin changes the spatial organization of the genome around active promoters

    Cells 12:2001.

    https://doi.org/10.3390/cells12152001

    • PubMed
    • Google Scholar
26. 1. Tillberg PW
    2. Chen F
    3. Piatkevich KD
    4. Zhao Y
    5. Yu C-CJ
    6. English BP
    7. Gao L
    8. Martorell A
    9. Suk H-J
    10. Yoshida F
    11. DeGennaro EM
    12. Roossien DH
    13. Gong G
    14. Seneviratne U
    15. Tannenbaum SR
    16. Desimone R
    17. Cai D
    18. Boyden ES

    (2016) Protein-retention expansion microscopy of cells and tissues labeled using standard fluorescent proteins and antibodies

    Nature Biotechnology 34:987–992.

    https://doi.org/10.1038/nbt.3625

    • PubMed
    • Google Scholar
27. 1. Toné S
    2. Sugimoto K
    3. Tanda K
    4. Suda T
    5. Uehira K
    6. Kanouchi H
    7. Samejima K
    8. Minatogawa Y
    9. Earnshaw WC

    (2007) Three distinct stages of apoptotic nuclear condensation revealed by time-lapse imaging, biochemical and electron microscopy analysis of cell-free apoptosis

    Experimental Cell Research 313:3635–3644.

    https://doi.org/10.1016/j.yexcr.2007.06.018

    • PubMed
    • Google Scholar
28. 1. Xie J
    2. Han D
    3. Xu S
    4. Zhang H
    5. Li Y
    6. Zhang M
    7. Deng Z
    8. Tian J
    9. Ye Q

    (2023) An image-based high-throughput and high-content drug screening method based on microarray and expansion microscopy

    ACS Nano 17:15516–15528.

    https://doi.org/10.1021/acsnano.3c01865

    • PubMed
    • Google Scholar
29. 1. Yu X
    2. Ruan Y
    3. Shen T
    4. Qiu Q
    5. Yan M
    6. Sun S
    7. Dou L
    8. Huang X
    9. Wang Q
    10. Zhang X
    11. Man Y
    12. Tang W
    13. Jin Z
    14. Li J

    (2020) Dexrazoxane protects cardiomyocyte from doxorubicin-induced apoptosis by modulating miR-17-5p

    BioMed Research International 2020:5107193.

    https://doi.org/10.1155/2020/5107193

    • PubMed
    • Google Scholar
30. 1. Zhao L
    2. Zhang B

    (2017) Doxorubicin induces cardiotoxicity through upregulation of death receptors mediated apoptosis in cardiomyocytes

    Scientific Reports 7:44735.

    https://doi.org/10.1038/srep44735

    • PubMed
    • Google Scholar

Author details

1. John H Day

   Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   John H Day is an inventor on a provisional patent filed for the HiExM device (MIT-064US(02))

   "This ORCID iD identifies the author of this article:" 0000-0002-5515-6606

2. Catherine M Della Santina

   Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Software, Formal analysis, Visualization, Writing – original draft

   Contributed equally with

   Pema Maretich and Alexander L Auld

   Competing interests

   Catherine M Della Santina is an inventor on a provisional patent filed for the HiExM device. (MIT-064US(02))

3. Pema Maretich

   Department of Biology, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Conceptualization

   Contributed equally with

   Catherine M Della Santina and Alexander L Auld

   Competing interests

   Pema Maretich is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))

4. Alexander L Auld

   Department of Biology, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Conceptualization

   Contributed equally with

   Catherine M Della Santina and Pema Maretich

   Competing interests

   Alex L Auld is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))

5. Kirsten K Schnieder

   Department of Biology, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Investigation, Methodology

   Competing interests

   No competing interests declared

6. Tay Shin

   Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Resources, Software

   Competing interests

   No competing interests declared

7. Edward S Boyden

   1. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States
   2. Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, United States
   3. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
   4. McGovern Institut, Massachusetts Institute of Technology, Cambridge, United States
   5. Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, United States
   6. K Lisa Yang Center for Bionics, Massachusetts Institute of Technology, Cambridge, United States
   7. Center for Neurobiological Engineering, Massachusetts Institute of Technology, Cambridge, United States
   8. Koch Institute, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Resources, Supervision, Funding acquisition

   Competing interests

   Edward S Boyden is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))

8. Laurie A Boyer

   1. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, United States
   2. Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
   3. Koch Institute, Massachusetts Institute of Technology, Cambridge, United States

   Contribution

   Supervision, Funding acquisition, Project administration

   For correspondence

   lboyer@mit.edu

   Competing interests

   Laurie A Boyer is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))

   "This ORCID iD identifies the author of this article:" 0000-0003-3491-4962

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