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Heart-on-a-Chip Model with Integrated Extra- and Intracellular Bioelectronics for Monitoring Cardiac Electrophysiology under Acute Hypoxia
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Heart-on-a-Chip Model with Integrated Extra- and Intracellular Bioelectronics for Monitoring Cardiac Electrophysiology under Acute Hypoxia
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  • Haitao Liu
    Haitao Liu
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    School of Materials Science and Technology, Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid Wastes, National Laboratory of Mineral Materials, China University of Geosciences, Beijing 100083, PR China
    More by Haitao Liu
  • Olurotimi A. Bolonduro
    Olurotimi A. Bolonduro
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
  • Ning Hu
    Ning Hu
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Guangdong Province Key Laboratory of Display Material and Technology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou 510275, PR China
    More by Ning Hu
  • Jie Ju
    Jie Ju
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    More by Jie Ju
  • Akshita A. Rao
    Akshita A. Rao
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
  • Breanna M. Duffy
    Breanna M. Duffy
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
  • Zhaohui Huang
    Zhaohui Huang
    School of Materials Science and Technology, Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid Wastes, National Laboratory of Mineral Materials, China University of Geosciences, Beijing 100083, PR China
  • Lauren D. Black
    Lauren D. Black
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    Department of Cell, Molecular & Developmental Biology, School of Graduate Biomedical Sciences, Tufts University, Boston, Massachusetts 02111, United States
  • Brian P. Timko*
    Brian P. Timko
    Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    *E-mail: [email protected]
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Nano Letters

Cite this: Nano Lett. 2020, 20, 4, 2585–2593
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https://doi.org/10.1021/acs.nanolett.0c00076
Published February 24, 2020

Copyright © 2020 American Chemical Society. This publication is licensed under these Terms of Use.

Abstract

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We demonstrated a bioelectronic heart-on-a-chip model for studying the effects of acute hypoxia on cardiac function. A microfluidic channel enabled rapid modulation of medium oxygenation, which mimicked the regimes induced by a temporary coronary occlusion and reversibly activated hypoxia-related transduction pathways in HL-1 cardiac model cells. Extracellular bioelectronics provided continuous readouts demonstrating that hypoxic cells experienced an initial period of tachycardia followed by a reduction in beat rate and eventually arrhythmia. Intracellular bioelectronics consisting of Pt nanopillars temporarily entered the cytosol following electroporation, yielding action potential (AP)-like readouts. We found that APs narrowed during hypoxia, consistent with proposed mechanisms by which oxygen deficits activate ATP-dependent K+ channels that promote membrane repolarization. Significantly, both extra- and intracellular devices could be multiplexed, enabling mapping capabilities unachievable by other electrophysiological tools. Our platform represents a significant advance toward understanding electrophysiological responses to hypoxia and could be applicable to disease modeling and drug development.

Copyright © 2020 American Chemical Society

Cardiovascular disease (CVD) is the leading cause of death worldwide, with CVD due to ischemic disease accounting for a large proportion of the patient population. (1,2) Cardiac ischemia occurs when an artery supplying blood to the heart muscle is partially or fully blocked. This blockage reduces blood flow to downstream muscle, creating a region of hypoxia. If severe or for an extended time, the ischemia can cause myocardial infarction (MI), leading to tissue death, abnormal cardiac electrophysiology, and functional decline. Despite decades of research, deaths due to ischemic heart disease have increased between 1990 and 2013 by 41.7%. (1) Therefore, there is a clear need for improved preclinical models to develop novel therapeutics.

Bioelectrical activity is a critical component of healthy myocardial function, as it is this organized electrical propagation that induces synchronized pumping. It is known that changes in oxygen level in the microcellular environment induce a number of functional responses among cardiomyocytes (CMs), including changes in resting membrane potential, release of neurotransmitters, shifts in gene expression, altered metabolic functions, and activated ion channels. (3−7) Electrical measurement, such as the shape and duration of action potentials (AP), provides key information on the metabolic state, type, and density of various ion channels within a given cell. (8,9) Many of these changes occur rapidly upon induction of hypoxia, requiring continuous and multiplexed measurement strategies that can record cellular electrophysiology in real time. (7) Furthermore, study of AP changes prior to, during, and after a hypoxic event require stable intracellular probing methods. Current preclinical models for cardiovascular disease, including in vitro cell assays and in vivo animal models, allow for limited to no potential to monitor acute intracellular electrical responses to hypoxic stress. Recent heart-on-a-chip models have effectively recapitulated the structure and function of native myocardium (10) including under hypoxia. (11) However, current models for hypoxia do not provide readouts of electrophysiological activity, which changes rapidly during both hypoxia and recovery. Further studies could better inform future therapeutic development through disease modeling and drug screening applications.

The ideal electrophysiological platform should provide stable, multiplexed bioelectronic readouts while exerting minimal disturbances to cellular function. (12) Patch clamp electrophysiology is considered a gold standard for short-term measurements, but patch pipettes are generally difficult to multiplex and moreover present mechanical mismatches with cell membranes that preclude long-term study. Optical imaging using exogenous or genetically encoded dyes offers spatial mapping of AP propagation, but these techniques require instrumentation that precludes continuous, long-term monitoring, and they may be limited in temporal resolution. Bioelectronic devices such as multielectrode arrays (MEAs) (13−15) or field-effect transistors (FETs) (16−18) offer a compelling alternative, providing electrophysiological readouts with high temporal resolution and at multiple length scales, ranging from subcellular to tissue level. In extracellular configurations, these devices record spikes that only approximate the AP. Nevertheless, they are powerful, because they can be readily multiplexed up to a level of thousands of devices (19) and moreover support long-term cultures. For these reasons, extracellular bioelectronics have enabled fundamental insights into cardiac signaling, disease modeling, and pharmacology. More recently, 3D bioprobes including freestanding nanowire-FETs, (20−22) nanopillars, (23,24) nanomushrooms, (25) and nanovolcanoes (26) have been achieved. These structures could stably enter the cytosol following mechanical, electrical, or chemical perturbations, allowing bioelectronic readouts that were similar or identical to the AP.

In this report, we demonstrate a heart-on-a-chip model consisting of a microfluidic channel and cell culture area with integrated extra- or intracellular bioelectronic devices (Figure 1a). The microfluidic channel enabled temporal modulation of medium oxygenation that we could switch between normoxic (21% O2), hypoxic (1–4% O2), and recovery/reperfusion (21% O2) conditions that mimicked coronary occlusion followed by unblocking. (27) As a cell model, we chose immortalized mouse atrial HL-1 cells, which have been used to study cardiac signaling, electrical coupling, and transcriptional regulation. (28) Moreover, HL-1 cells demonstrated similar responses to ischemia and reperfusion as primary cardiomyocytes. (29) The central innovation of our work relates to the bioelectronic interfaces, which provided continuous readouts of cardiac signaling. The multiplexed signals from extracellular devices enabled us to monitor beat rates, rhythmicity, and wavefront propagation velocities, which changed rapidly during hypoxia and recovery. Our intracellular probes consisted of Pt nanopillar arrays that entered the cytosol following localized membrane poration. (23) These devices provided accurate readouts of the cardiac AP, which contained details about ion channel functions that were not available from extracellular measurements but were crucial to understanding adaptive responses to hypoxia. Significantly, these intracellular probes provided both single-cell resolution and multiplexing capabilities, thereby enabling us to observe spatial heterogeneities in cellular function that are innate in biological systems but could not have been readily recorded using other electrophysiological techniques.

Figure 1

Figure 1. Overview of the heart-on-a-chip platform. (a) (top) Optical image and (bottom) scheme representing fully assembled chip with integrated recording elements, reference electrode, and PDMS channel for media delivery. (b) Representative optical image of an extracellular recording element coated with Pt black (red arrow). (c) Representative optical image of an intracellular recording element comprised of an underlying Au pad with five vertical Pt nanopillars (blue arrow). (d) (top) SEM detail of five vertical nanopillars corresponding to the location marked by the blue arrow in panel c. (inset) Schematic representation of a single nanopillar cross section. (bottom) Cross section of a single nanopillar after etching with FIB. Note that the Pt nanopillar fully penetrated the SiO2 layer to form a junction with the underlying Au layer. (e) Immunostaining of the HL-1 cell monolayer cultured in a PDMS channel at 4 DIV showing α-actinin cytoskeleton (green), Cx-43 gap junction proteins (red), and nuclei (blue, DAPI). (f) Stitched immunofluorescence image showing continuous HL-1 monolayer across the lateral direction of the microfluidic channel. Yellow dotted lines denote edges of the PDMS boundary.

We fabricated extra- or intracellular bioelectronic devices using top-down photolithography and nanofabrication techniques. All devices were fabricated as 2 × 8 element arrays, with 600 or 1000 μm spacing between devices (Figure S1). For extracellular measurements, we fabricated planar electrodes consisting of 30 μm diameter Au pads and interconnects passivated by a 2 μm thick layer of SU-8. We subsequently coated these electrodes with Pt black, which increased the surface area (30) to yield devices with an impedance of ∼20 kΩ (1 kHz) and filtered baseline noise of <20 μVpp (Figure 1b). For intracellular measurements, we fabricated Pt nanopillar arrays, where each nanopillar was 150–200 nm in diameter and 1.5–2.0 μm in height. These nanopillars were fabricated in groups of 5, e.g., 5 nanopillars on each of 16 underlying Au pads, enabling 16 independently addressable intracellular probes. Each underlying Au pad was passivated with a 200 nm insulating SiO2 layer; we then used focused ion beam (FIB) to mill holes through the passivation followed by Pt deposition. (23) We chose that strategy to ensure that only the nanopillar portion of the device—that is, the portion that could access the intercellular space—would form a bioelectronic interface. A cross section view achieved by FIB/SEM confirmed that the nanopillars fully penetrated the SiO2 layer to make electrical contact with the underlying Au layer (Figure 1d). We also performed electrical impedance measurements to verify the electrical integrity of our SiO2 layer; our nanopillar arrays had impedances of ∼300 kΩ (1 kHz), which was much larger than we recorded for planar devices and consistent with our expectation of a much smaller unpassivated surface area: 4–6 μm2 compared to ∼700 μm2 for planar devices (Figure S2).

We next fabricated fluidic device assemblies by permanently bonding a poly(dimethylsiloxane) (PDMS) channel layer onto the surface of our bioelectronic device chips (Figure 1a). These channels were coated with fibronectin and then seeded with HL-1 cells. After seeding, we flowed medium at a rate of 40 μL/h, which provided sufficient nutrient and oxygen delivery to support a healthy cell culture. (30,31) HL-1 cells demonstrate pacemaker activity; (32) we found that by 3–4 days in vitro (DIV), our cells formed confluent monolayers that beat spontaneously (Movie S1). Immunohistochemistry demonstrated well-defined actinin filaments and significant connexin-43 protein expression, which are associated with cytoskeletal mechanics and electrical coupling, respectively (Figure 1e,f). Generally, connexin-43 proteins were distributed uniformly across cell membranes, which is consistent with other works involving HL-1 cells (33) and attributed to the relatively early stage in culture; we however did note several locations where these proteins were localized at cell–cell junctions as is typical of primary CMs (Figure S3). Our platform maintained healthy cultures for at least 7 DIV.

Cells undergo an adaptive response when exposed to acute hypoxic stress where hypoxia-inducible factor-1-alpha (HIF-1α), a transcriptional regulator, activates in order to increase oxygen delivery and facilitate metabolic adaptation to hypoxia. (34) At the onset of mild hypoxia, HIF-1α translocates into the nucleus, where it binds the HIF-1β subunit and upregulates the relevant genes. (35,36) To assess the ability of our platform activate these signaling pathways, we exposed HL-1 cells at 4 DIV to hypoxic medium (1% O2) for up to 5 h. Immunostaining revealed that by 2.5 h, HIF-1α was strongly expressed and had localized in the nucleus (Figure S4a). This expression was constant throughout the remainder of the hypoxic episode. However, upon applying a normoxic recovery medium for 90 min, HIF-1α returned to basal levels (Figure S4b); HIF-1α degrades with a <5 min half-life posthypoxia. (37) These results demonstrate the ability of our platform to model normoxia, hypoxia, and early stages of recovery.

To validate the ability of our platform to achieve bioelectronic readouts, we first monitored electrophysiology using extracellular electrodes, which yielded ≥85% functional bioelectronic interfaces and enabled continuous recording over the course of the experiment. Prior to inducing hypoxic stress, HL-1 cells beat with a frequency of 3.0 ± 0.5 Hz across N = 8 distinct cultures, consistent with previously reported results for HL-1 cultures in static conditions. (32) To induce a period of acute hypoxia, we switched normoxic media with hypoxic (1% O2) media for 5 h, according to the protocol depicted schematically in Figure 2a. These conditions induced an initial period of tachycardia, with beating frequency increasing from 3.2 to 4.2 Hz, followed by a gradual reduction in frequency until arrhythmia with much longer firing intervals, 4.9 ± 1.5 s. In a separate culture (Figure S5), we induced ischemia gradually by first perfusing 4% O2 medium for 20 min before further reducing O2 to 1%. In that case, we also observed tachycardia, albeit at a slower rate of increase before cresting and then returning to basal. Similar electrophysiological patterns—that is, hypoxia-induced tachycardia followed by a decrease in beat rate to below basal—were also observed in primary murine CMs that were exposed to hypoxic media in static conditions. (38) Arrhythmia is also a symptom of ischemia. (39) We maintained hypoxia for either 5.5 h (Figure 2a) or 20 h (Figure S5); in both cases, rhythmic beating recovered within 30 min after reintroducing normoxic media. The tachycardia present at that time is consistent with reperfusion injury, which is common following ischemia. (40)

Figure 2

Figure 2. Extracellular bioelectronic readouts before, during, and after hypoxia. (a) (top) Scheme of media delivery protocol with distinct regions of normoxia, hypoxia, and recovery and (bottom) HL-1 firing rate. The red dotted box highlights the transition from rhythmic beating to arrhythmia. (b) Representative signals from a single device recorded during (I) normoxia, (II) hypoxia, upon onset of arrhythmia, and (III) recovery. These traces correspond to the points noted in panel a. (inset) Single peak expansions of (black) overlaid individual traces and (red) average of individual traces. (c) Scheme of electrode layout (black dots) and representative multiplexed readouts from a chip with 14 out of 16 functional bioelectronic interfaces. (d,e) Isochronal maps representing signal propagation at two time points each during (d) normoxia and (e) hypoxia for ∼1 h. Black arrow overlays represent the gradient of the isochrones. The area of each map is 1000 μm wide × 4200 μm tall.

The high yield of multiplexed readouts enabled us to further assess cell–cell communication. Figure 2c shows typical signals from a chip with 14 out of 16 functioning bioelectronic interfaces. Cross-correlation analysis enabled us to construct isochronal maps that provided information about wavefront propagation velocities. We found that under normoxia, wavefronts propagated uniformly with an average speed of 18.9 ± 5.0 mm/s, which is typical for HL-1 cells. (41) These characteristics were stable: another data set collected 10 min later showed a nearly identical propagation pattern and speed, 19.3 ± 5.0 mm/s (Figure 2d). In contrast, 1% O2 hypoxia for 1 h resulted in turbid propagation patterns that changed significantly between successive analyses performed 10 min apart (Figure 2e). We also found that the average propagation speeds were reduced to 11.9 ± 11.0 and 13.3 ± 8.5 mm/s at the two time points shown. While these data represent snapshots at just four time points, we emphasize that they are representative of 6 time points analyzed during normoxia and 14 during a 5 h hypoxic episode. We found that propagation speeds became progressively slower over the course of hypoxia, and normoxic and hypoxic data sets were significantly different (p < 0.001, Welch’s t test) (Figure S6). Collectively, these characteristics—tachycardia, arrhythmia, and reduced propagation velocities—are consistent with cardiac responses to hypoxia, whereby excitation thresholds are decreased and Cx-43 gap junction expression is diminished, leading to reentrant arrhythmias and an increase in tissue impedance. (39) Our results demonstrate the ability of our platform to achieve ischemia-like conditions and moreover establish a time frame for hypoxic responses.

We next sought to achieve intracellular readouts from our microfluidic platform using Pt nanopillar electrodes as shown in Figures 1c,d and S1b. Prior to electroporation, nanopillars recorded extracellular signals with an average magnitude of ∼60 μV and baseline noise of 20 μVpp (Figure 3a). Immediately following electroporation (3 Vpp, 200 μs biphasic square pulses for 2–3 s), we found that nanopillar electrodes recorded intracellular signals with an initial magnitude of 2.3 mV (Figure 3b). The signal shape resembled that of a slow AP, with well-defined rising (phase 0) and falling (phase 3) edges consistent with inward Ca2+ and outward K+ currents, respectively, followed by a refractory period and resting phase (phase 4). These characteristics are consistent with previous reports (8,23) and moreover expected given that HL-1 cells are derived from atrial cardiomyocytes. (42,43) We observed intracellular signals for at least 10 min following electroporation, and we found that their amplitude decreased to ∼7% of the initial value during that time, consistent with sealing of the transient pores. (23) However, both the AP duration at 50% repolarization (APD50) as well as signal shape remained constant during that period (Figure 3c–e).

Figure 3

Figure 3. Electrophysiology using nanopillar electrodes in normoxic media. (a) Representative extracellular signal recorded prior to electroporation. Inset shows expansion of single representative peak. (b) Intracellular signals recorded immediately after electroporation. (c) (blue square) Normalized action potential amplitude and (red circle) APD50 as a function of time after electroporation. Within 2 min, the amplitude of the action potentials decreased to around 24% of the maximum, while APD50 was unchanged. (d) Expansions of peaks shown in panel b at locations noted by red, blue, and yellow arrows, plotted on (left) absolute and (right) normalized scales. Note that the baseline of these peaks is offset for clarity.

To analyze the intracellular electrophysiology of HL-1 cells under hypoxia, we investigated the APD50, AP duration at 90% repolarization (APD90), and depolarization time (Figure 4a). We chose to study these parameters under normoxia (0 h) and at three time points under 1% O2 hypoxia (2, 4, and 6 h) given the time course of responses observed with extracellular readouts. By the 6 h time point, our intracellular probes recorded arrhythmia with long firing intervals (Figure 4b) similar to those shown in Figure 2b,II. We observed a substantial reduction in mean APD50 (−46%), APD90 (−34%), and depolarization time (−44%) by the 2 h time point, which persisted through 4 and 6 h (Figure 4d–g). These changes are expected given that we also observed HIF-1α activation by 2 h as shown in Figure S4. AP shortening is also expected given that hypoxia lowers intracellular ATP and activates ATP-dependent potassium channels, which promote membrane repolarization. (44)

Figure 4

Figure 4. Intracellular electrophysiology of HL-1 cells during 1% O2 hypoxic stress. (a) Schematic representation of typical HL-1 AP highlighting key parameters. (b) Intracellular recording showing arrhythmic beating after 6 h of hypoxic stress. (c) Representative examples of AP recordings following 0, 2, 4, or 6 h of hypoxic stress. Note that the 0 h time point represents normoxia. (d–f) Summary statistics representing (d) APD50, (e) APD90, and (f) depolarization time corresponding to each time point represented in panel c. (g) Percentage change for APD50, APD90, and depolarization time throughout hypoxia. Statistics are from N = 14 different cells in 4 different cultures. *P < 0.05, **P < 0.01, ***P < 0.0005, ****P < 0.0001 in Welch’s t test. All error bars denote s.d.

A distinct advantage of our nanopillar approach is that it not only enables accurate AP measurements but also does so at the single-cell level. This functionality opens avenues to spatially map intracellular features within the same sample, thereby providing insights into heterogeneities that would not be revealed by lower-resolution or ensemble techniques. To explore this possibility, we recorded intracellular signals from five devices simultaneously, under normoxia or after 2 h of exposure to hypoxia (1% O2), as shown in Figure 5a. Propagation maps of signals along these linear device arrays showed qualitative characteristics similar to those presented in Figure 2, with uniform propagation in the normoxic sample compared to nonuniform propagation in the hypoxic sample. The corresponding propagation speeds are 22.7 ± 0.6 and 27.3 ± 5.2 mm/s, respectively (Figure 5b). (45) Heat maps representing the electrophysiological properties of each trace demonstrate that APD50, APD90, and depolarization time generally decrease with hypoxia (Figure 5c), consistent with the statistical analysis presented in Figure 4. Interestingly, however, each group includes one clear outlier: an abnormally short AP in the normoxia group and an abnormally long AP in the hypoxia group. These outliers represent the innate variabilities in biological systems: for example, HL-1 cells exhibit substantial phenotypic/electrophysiological variability, (46,47) while nuclear HIF-1α is activated nonuniformly, particularly at early stages of hypoxia. (48) Similar variability gradients have been observed among and within clusters of human embryonic stem-cell-derived cardiac cell clusters, using optical dyes. (49)

Figure 5

Figure 5. Multiplexed intracellular recordings. (a) Representative APs simultaneously recorded under (left) normoxia and (right) hypoxia after 2 h. The color-coded legend represents the corresponding device arrangement; spacing between devices is 600 μm. (b) Propagation maps correlating to each trace and spatial location shown in panels a and b. Each map is 3600 μm tall and represents propagation along the direction of the linear device array. (c) Heat maps representing APD50, APD90, and depolarization time corresponding to each trace and spatial location shown in panels a and b.

We have demonstrated an ischemia-on-a-chip model with integrated extra- or intracellular bioelectronic devices. These devices provided electrophysiological readouts with complementary attributes: extracellular devices recorded stable signals with high device yield, which enabled us to continuously monitor beat frequency and wavefront propagation, while intracellular devices provided accurate recordings of the AP. While this work focused solely on the effects of hypoxia, other factors that are relevant to ischemia including acidosis, hyperkalemia, nutrient deprivation, and waste accumulation (27) could be incorporated into the model by modulating the composition or flow of the medium. Our proof-of-concept multiplexing capabilities—limited to 16 devices here—could also be extended to much larger or denser arrays. For example, >1000-element nanoelectrode arrays capable of parallel, network-level intracellular recording from CMs (50) and connected neurons (51) have been demonstrated. Improvements upon our nanofabrication techniques to achieve probes with nanoscale concavities, (25) smaller diameters, (20−22) and/or biochemical (26,52) surface ligands could promote membrane integration and yield more stable and long-term intracellular recordings. We could also adapt our platform to include 3D cardiac tissue constructs with embedded bioelectronic devices, (14,18,53) which would more adequately recapitulate endogenous tissues. The distinct advantages of our platform could be applicable to a wide variety of conditions relevant to hypoxia or ischemia. For example, multiplexed outputs are relevant to assessing responses to oxygen concentration gradients and borderzone infarcts, while continuous, real-time readouts are relevant to understanding the rapid changes that occur during reperfusion injuries. Further studies could yield fundamental insights into cardiac signaling pathways or provide a high-throughput platform for assessing therapeutics.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.nanolett.0c00076.

  • Movie S1. Spontaneous beating of cells that formed confluent monolayers (MP4)

  • Materials and Methods; Scheme S1. Illustration of microfluidic chip with integrated nanopillar microelectrode arrays; Scheme S2. Strategy to generate hypoxic medium flow; Figure S1. Design of MEA devices; Figure S2. Representative electrical impedance spectra of planar and nanopillar bioelectronic devices; Figure S3. Gap junction localization; Figure S4. HIF-1α validation of heart-on-a-chip; Figure S5. Extracellular bioelectronic readouts before, during, and after hypoxia; Figure S6. Summary of wavefront propagation speeds derived from isochronal map (PDF)

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Author Information

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  • Corresponding Author
  • Authors
    • Haitao Liu - Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United StatesSchool of Materials Science and Technology, Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid Wastes, National Laboratory of Mineral Materials, China University of Geosciences, Beijing 100083, PR ChinaOrcidhttp://orcid.org/0000-0003-1824-0304
    • Olurotimi A. Bolonduro - Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    • Ning Hu - Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United StatesState Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Guangdong Province Key Laboratory of Display Material and Technology, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou 510275, PR ChinaOrcidhttp://orcid.org/0000-0001-7178-3952
    • Jie Ju - Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    • Akshita A. Rao - Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    • Breanna M. Duffy - Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United States
    • Zhaohui Huang - School of Materials Science and Technology, Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid Wastes, National Laboratory of Mineral Materials, China University of Geosciences, Beijing 100083, PR ChinaOrcidhttp://orcid.org/0000-0001-7188-0875
    • Lauren D. Black - Department of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, United StatesDepartment of Cell, Molecular & Developmental Biology, School of Graduate Biomedical Sciences, Tufts University, Boston, Massachusetts 02111, United StatesOrcidhttp://orcid.org/0000-0002-7486-5811
  • Author Contributions

    H.L., O.A.B., N.H., and B.P.T. designed the experiments; N.H. designed the electronic interface; H.L., O.A.B., J.J, B.M.D., and A.A.R. performed the experiments and analyzed the data; Z.H. provided guidance relating to nanopillar fabrication; L.D.B. provided guidance relating to data analysis and interpretation; H.L., O.A.B., B.M.D., and B.P.T. wrote the manuscript; and B.P.T. provided overall guidance of the project. All authors read and approved the manuscript.

    H.L., O.A.B., and N.H. contributed equally.

    Author Contributions

    H.L., O.A.B., N.H., and B.P.T. designed the experiments; N.H. designed the electronic interface; H.L., O.A.B., J.J, B.M.D., and A.A.R. performed the experiments and analyzed the data; Z.H. provided guidance relating to nanopillar fabrication; L.D.B. provided guidance relating to data analysis and interpretation; H.L., O.A.B., B.M.D., and B.P.T. wrote the manuscript; and B.P.T. provided overall guidance of the project. All authors read and approved the manuscript.

    H.L., O.A.B., and N.H. contributed equally.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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This work was supported by a Tufts Collaborates grant (to B.P.T.), a Tufts Research Advancement Fund award (to B.P.T.), a Department of Defense Grant W81XWH-16-1-0304 (to L.D.B.), an American Heart Association Grant-in-Aid Award 16GRNT27760100 (to L.D.B.), a Student National Scholarship (to H.L.), and a China National Scholarship (to N.H). This work was performed in part at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Coordinated Infrastructure Network (NNCI), which is supported by the National Science Foundation under NSF award no. 1541959. CNS is part of Harvard University.

Abbreviations

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AP

action potential

APD50

action potential duration, 50% repolarization

APD90

action potential duration, 90% repolarization

CM

cardiomyocyte

DIV

days in vitro

FIB

focused ion beam

HIF-1α

hypoxia-inducible factor-1α

MEA

mutielectrode array

References

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This article references 53 other publications.

  1. 1
    Benjamin, E. J.; Muntner, P.; Alonso, A.; Bittencourt, M. S.; Callaway, C. W.; Carson, A. P.; Chamberlain, A. M.; Chang, A. R.; Cheng, S.; Das, S. R.; Delling, F. N.; Djousse, L.; Elkind, M. S. V.; Ferguson, J. F.; Fornage, M.; Jordan, L. C.; Khan, S. S.; Kissela, B. M.; Knutson, K. L.; Kwan, T. W.; Lackland, D. T.; Lewis, T. T.; Lichtman, J. H.; Longenecker, C. T.; Loop, M. S.; Lutsey, P. L.; Martin, S. S.; Matsushita, K.; Moran, A. E.; Mussolino, M. E.; O’Flaherty, M.; Pandey, A.; Perak, A. M.; Rosamond, W. D.; Roth, G. A.; Sampson, U. K. A.; Satou, G. M.; Schroeder, E. B.; Shah, S. H.; Spartano, N. L.; Stokes, A.; Tirschwell, D. L.; Tsao, C. W.; Turakhia, M. P.; VanWagner, L. B.; Wilkins, J. T.; Wong, S. S.; Virani, S. S. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation 2019, 139 (10), e56e528,  DOI: 10.1161/CIR.0000000000000659
  2. 2
    World Health Organization. Noncommunicable diseases country profiles 2018; World Health Organization: Geneva, 2018.
  3. 3
    Duranteau, J.; Chandel, N. S.; Kulisz, A.; Shao, Z.; Schumacker, P. T. Intracellular signaling by reactive oxygen species during hypoxia in cardiomyocytes. J. Biol. Chem. 1998, 273 (19), 1161911624,  DOI: 10.1074/jbc.273.19.11619
  4. 4
    Dutta, S.; Minchole, A.; Quinn, T. A.; Rodriguez, B. Electrophysiological properties of computational human ventricular cell action potential models under acute ischemic conditions. Prog. Biophys. Mol. Biol. 2017, 129, 4052,  DOI: 10.1016/j.pbiomolbio.2017.02.007
  5. 5
    Nakada, Y.; Canseco, D. C.; Thet, S.; Abdisalaam, S.; Asaithamby, A.; Santos, C. X.; Shah, A. M.; Zhang, H.; Faber, J. E.; Kinter, M. T.; Szweda, L. I.; Xing, C.; Hu, Z.; Deberardinis, R. J.; Schiattarella, G.; Hill, J. A.; Oz, O.; Lu, Z.; Zhang, C. C.; Kimura, W.; Sadek, H. A. Hypoxia induces heart regeneration in adult mice. Nature 2017, 541 (7636), 222227,  DOI: 10.1038/nature20173
  6. 6
    Kubasiak, L. A.; Hernandez, O. M.; Bishopric, N. H.; Webster, K. A. Hypoxia and acidosis activate cardiac myocyte death through the Bcl-2 family protein BNIP3. Proc. Natl. Acad. Sci. U. S. A. 2002, 99 (20), 1282512830,  DOI: 10.1073/pnas.202474099
  7. 7
    Martewicz, S.; Michielin, F.; Serena, E.; Zambon, A.; Mongillo, M.; Elvassore, N. Reversible alteration of calcium dynamics in cardiomyocytes during acute hypoxia transient in a microfluidic platform. Integrative Biology 2012, 4 (2), 153164,  DOI: 10.1039/C1IB00087J
  8. 8
    Lin, Z. C.; Xie, C.; Osakada, Y.; Cui, Y.; Cui, B. Iridium oxide nanotube electrodes for sensitive and prolonged intracellular measurement of action potentials. Nat. Commun. 2014, 5, 3206,  DOI: 10.1038/ncomms4206
  9. 9
    Zhu, Z.; Burnett, C. M.; Maksymov, G.; Stepniak, E.; Sierra, A.; Subbotina, E.; Anderson, M. E.; Coetzee, W. A.; Hodgson-Zingman, D. M.; Zingman, L. V. Reduction in number of sarcolemmal KATP channels slows cardiac action potential duration shortening under hypoxia. Biochem. Biophys. Res. Commun. 2011, 415 (4), 637641,  DOI: 10.1016/j.bbrc.2011.10.125
  10. 10
    Ribas, J.; Sadeghi, H.; Manbachi, A.; Leijten, J.; Brinegar, K.; Zhang, Y. S.; Ferreira, L.; Khademhosseini, A. Cardiovascular Organ-on-a-Chip Platforms for Drug Discovery and Development. Appl. In Vitro Toxicol 2016, 2 (2), 8296,  DOI: 10.1089/aivt.2016.0002
  11. 11
    Kang, Y. B. A.; Eo, J.; Bulutoglu, B.; Yarmush, M. L.; Usta, O. B. Progressive hypoxia-on-a-chip: An in vitro oxygen gradient model for capturing the effects of hypoxia on primary hepatocytes in health and disease. Biotechnol. Bioeng. 2020, 117, 763,  DOI: 10.1002/bit.27225
  12. 12
    Bolonduro, O. A.; Duffy, B. M.; Rao, A. A.; Black, L. D.; Timko, B. P. From Biomimicry to Bioelectronics: Smart Materials for Cardiac Tissue Engineering. Nano Res. 2020  DOI: 10.1007/s12274-020-2682-3 .
  13. 13
    Spira, M. E.; Hai, A. Multi-electrode array technologies for neuroscience and cardiology. Nat. Nanotechnol. 2013, 8 (2), 8394,  DOI: 10.1038/nnano.2012.265
  14. 14
    Feiner, R.; Engel, L.; Fleischer, S.; Malki, M.; Gal, I.; Shapira, A.; Shacham-Diamand, Y.; Dvir, T. Engineered hybrid cardiac patches with multifunctional electronics for online monitoring and regulation of tissue function. Nat. Mater. 2016, 15 (6), 67985,  DOI: 10.1038/nmat4590
  15. 15
    Xu, L.; Gutbrod, S. R.; Bonifas, A. P.; Su, Y.; Sulkin, M. S.; Lu, N.; Chung, H. J.; Jang, K. I.; Liu, Z.; Ying, M.; Lu, C.; Webb, R. C.; Kim, J. S.; Laughner, J. I.; Cheng, H.; Liu, Y.; Ameen, A.; Jeong, J. W.; Kim, G. T.; Huang, Y.; Efimov, I. R.; Rogers, J. A. 3D multifunctional integumentary membranes for spatiotemporal cardiac measurements and stimulation across the entire epicardium. Nat. Commun. 2014, 5, 3329,  DOI: 10.1038/ncomms4329
  16. 16
    Timko, B. P.; Cohen-Karni, T.; Yu, G.; Qing, Q.; Tian, B.; Lieber, C. M. Electrical recording from hearts with flexible nanowire device arrays. Nano Lett. 2009, 9 (2), 9148,  DOI: 10.1021/nl900096z
  17. 17
    Cohen-Karni, T.; Timko, B. P.; Weiss, L. E.; Lieber, C. M. Flexible electrical recording from cells using nanowire transistor arrays. Proc. Natl. Acad. Sci. U. S. A. 2009, 106 (18), 730913,  DOI: 10.1073/pnas.0902752106
  18. 18
    Dai, X.; Zhou, W.; Gao, T.; Liu, J.; Lieber, C. M. Three-dimensional mapping and regulation of action potential propagation in nanoelectronics-innervated tissues. Nat. Nanotechnol. 2016, 11 (9), 77682,  DOI: 10.1038/nnano.2016.96
  19. 19
    Tsai, D.; Sawyer, D.; Bradd, A.; Yuste, R.; Shepard, K. L. A very large-scale microelectrode array for cellular-resolution electrophysiology. Nat. Commun. 2017, 8, 1802,  DOI: 10.1038/s41467-017-02009-x
  20. 20
    Tian, B.; Lieber, C. M. Nanowired Bioelectric Interfaces. Chem. Rev. 2019, 119 (15), 91369152,  DOI: 10.1021/acs.chemrev.8b00795
  21. 21
    Zhao, Y.; You, S. S.; Zhang, A.; Lee, J. H.; Huang, J.; Lieber, C. M. Scalable ultrasmall three-dimensional nanowire transistor probes for intracellular recording. Nat. Nanotechnol. 2019, 14 (8), 783790,  DOI: 10.1038/s41565-019-0478-y
  22. 22
    Eschermann, J. F.; Stockmann, R.; Hueske, M.; Vu, X. T.; Ingebrandt, S.; Offenhäusser, A. Action potentials of HL-1 cells recorded with silicon nanowire transistors. Appl. Phys. Lett. 2009, 95 (8), 083703  DOI: 10.1063/1.3194138
  23. 23
    Xie, C.; Lin, Z.; Hanson, L.; Cui, Y.; Cui, B. Intracellular recording of action potentials by nanopillar electroporation. Nat. Nanotechnol. 2012, 7 (3), 18590,  DOI: 10.1038/nnano.2012.8
  24. 24
    Dipalo, M.; Amin, H.; Lovato, L.; Moia, F.; Caprettini, V.; Messina, G. C.; Tantussi, F.; Berdondini, L.; De Angelis, F. Intracellular and Extracellular Recording of Spontaneous Action Potentials in Mammalian Neurons and Cardiac Cells with 3D Plasmonic Nanoelectrodes. Nano Lett. 2017, 17 (6), 39323939,  DOI: 10.1021/acs.nanolett.7b01523
  25. 25
    Fendyur, A.; Spira, M. E. Toward on-chip, in-cell recordings from cultured cardiomyocytes by arrays of gold mushroom-shaped microelectrodes. Front. Neuroeng. 2012, 5, 21,  DOI: 10.3389/fneng.2012.00021
  26. 26
    Desbiolles, B. X. E.; de Coulon, E.; Bertsch, A.; Rohr, S.; Renaud, P. Intracellular Recording of Cardiomyocyte Action Potentials with Nanopatterned Volcano-Shaped Microelectrode Arrays. Nano Lett. 2019, 19 (9), 61736181,  DOI: 10.1021/acs.nanolett.9b02209
  27. 27
    Chen, T.; Vunjak-Novakovic, G. In vitro Models of Ischemia-Reperfusion Injury. Regen Eng. Transl Med. 2018, 4 (3), 142153,  DOI: 10.1007/s40883-018-0056-0
  28. 28
    White, S. M.; Constantin, P. E.; Claycomb, W. C. Cardiac physiology at the cellular level: use of cultured HL-1 cardiomyocytes for studies of cardiac muscle cell structure and function. Am. J. Physiol-Heart C 2004, 286 (3), H823H829,  DOI: 10.1152/ajpheart.00986.2003
  29. 29
    Teixeira, G.; Abrial, M.; Portier, K.; Chiari, P.; Couture-Lepetit, E.; Tourneur, Y.; Ovize, M.; Gharib, A. Synergistic protective effect of cyclosporin A and rotenone against hypoxia-reoxygenation in cardiomyocytes. J. Mol. Cell. Cardiol. 2013, 56, 5562,  DOI: 10.1016/j.yjmcc.2012.11.023
  30. 30
    Maoz, B. M.; Herland, A.; Henry, O. Y. F.; Leineweber, W. D.; Yadid, M.; Doyle, J.; Mannix, R.; Kujala, V. J.; FitzGerald, E. A.; Parker, K. K.; Ingber, D. E. Organs-on-Chips with combined multi-electrode array and transepithelial electrical resistance measurement capabilities. Lab Chip 2017, 17 (13), 22942302,  DOI: 10.1039/C7LC00412E
  31. 31
    Yang, M.; Lim, C. C.; Liao, R.; Zhang, X. A novel microfluidic impedance assay for monitoring endothelin-induced cardiomyocyte hypertrophy. Biosens. Bioelectron. 2007, 22 (8), 168893,  DOI: 10.1016/j.bios.2006.07.032
  32. 32
    Yang, Z.; Murray, K. T. Ionic mechanisms of pacemaker activity in spontaneously contracting atrial HL-1 cells. J. Cardiovasc. Pharmacol. 2011, 57 (1), 2836,  DOI: 10.1097/FJC.0b013e3181fda7c4
  33. 33
    Martins-Marques, T.; Anjo, S. I.; Pereira, P.; Manadas, B.; Girao, H. Interacting Network of the Gap Junction (GJ) Protein Connexin43 (Cx43) is Modulated by Ischemia and Reperfusion in the Heart. Mol. Cell. Proteomics 2015, 14 (11), 304055,  DOI: 10.1074/mcp.M115.052894
  34. 34
    Semenza, G. L. Hypoxia-inducible factor 1 and cardiovascular disease. Annu. Rev. Physiol. 2014, 76, 3956,  DOI: 10.1146/annurev-physiol-021113-170322
  35. 35
    Chu, W.; Wan, L.; Zhao, D.; Qu, X.; Cai, F.; Huo, R.; Wang, N.; Zhu, J.; Zhang, C.; Zheng, F.; Cai, R.; Dong, D.; Lu, Y.; Yang, B. Mild hypoxia-induced cardiomyocyte hypertrophy via up-regulation of HIF-1alpha-mediated TRPC signalling. J. Cell Mol. Med. 2012, 16 (9), 202234,  DOI: 10.1111/j.1582-4934.2011.01497.x
  36. 36
    Lee, J. W.; Ko, J.; Ju, C.; Eltzschig, H. K. Hypoxia signaling in human diseases and therapeutic targets. Exp. Mol. Med. 2019, 51 (6), 68,  DOI: 10.1038/s12276-019-0235-1
  37. 37
    Semenza, G.; Hydroxylation, L. of HIF-1: Oxygen Sensing at the Molecular Level. Physiology 2004, 19 (4), 176182,  DOI: 10.1152/physiol.00001.2004
  38. 38
    Yeung, C. K.; Sommerhage, F.; Wrobel, G.; Law, J. K.; Offenhausser, A.; Rudd, J. A.; Ingebrandt, S.; Chan, M. To establish a pharmacological experimental platform for the study of cardiac hypoxia using the microelectrode array. J. Pharmacol. Toxicol. Methods 2009, 59 (3), 14652,  DOI: 10.1016/j.vascn.2009.02.005
  39. 39
    Cascio, W. E.; Yang, H.; Muller-Borer, B. J.; Johnson, T. A. Ischemia-induced arrhythmia: the role of connexins, gap junctions, and attendant changes in impulse propagation. J. Electrocardiol 2005, 38 (4 Suppl), 5559,  DOI: 10.1016/j.jelectrocard.2005.06.019
  40. 40
    Lujan, H. L.; DiCarlo, S. E. Reperfusion-induced sustained ventricular tachycardia, leading to ventricular fibrillation, in chronically instrumented, intact, conscious mice. Physiol. Rep. 2014, 2 (6), e12057,  DOI: 10.14814/phy2.12057
  41. 41
    Dang, K. M.; Rinklin, P.; Afanasenkau, D.; Westmeyer, G.; Schurholz, T.; Wiegand, S.; Wolfrum, B. Chip-Based Heat Stimulation for Modulating Signal Propagation in HL-1 Cell Networks. Adv. Biosyst 2018, 2 (12), 1800138,  DOI: 10.1002/adbi.201800138
  42. 42
    Claycomb, W. C.; Lanson, N. A.; Stallworth, B. S.; Egeland, D. B.; Delcarpio, J. B.; Bahinski, A.; Izzo, N. J. HL-1 cells: a cardiac muscle cell line that contracts and retains phenotypic characteristics of the adult cardiomyocyte. Proc. Natl. Acad. Sci. U. S. A. 1998, 95 (6), 29792984,  DOI: 10.1073/pnas.95.6.2979
  43. 43
    Lin, Z. C.; McGuire, A. F.; Burridge, P. W.; Matsa, E.; Lou, H.-Y.; Wu, J. C.; Cui, B. Accurate nanoelectrode recording of human pluripotent stem cell-derived cardiomyocytes for assaying drugs and modeling disease. Microsystems & Nanoengineering 2017, 3, 16080,  DOI: 10.1038/micronano.2016.80
  44. 44
    Shaw, R. M.; Rudy, Y. Electrophysiologic effects of acute myocardial ischemia: a theoretical study of altered cell excitability and action potential duration. Cardiovasc. Res. 1997, 35 (2), 25672,  DOI: 10.1016/S0008-6363(97)00093-X
  45. 45

    These speeds are on the same order as those derived from extracellular electrodes. We note however that they do not represent the true wavefront velocity but rather a projection along the direction of the linear electrode array.

  46. 46
    Sartiani, L.; Bochet, P.; Cerbai, E.; Mugelli, A.; Fischmeister, R. Functional expression of the hyperpolarization-activated, non-selective cation current I(f) in immortalized HL-1 cardiomyocytes. J. Physiol. 2002, 545 (1), 8192,  DOI: 10.1113/jphysiol.2002.021535
  47. 47
    Dias, P.; Desplantez, T.; El-Harasis, M. A.; Chowdhury, R. A.; Ullrich, N. D.; Cabestrero de Diego, A.; Peters, N. S.; Severs, N. J.; MacLeod, K. T.; Dupont, E. Characterisation of connexin expression and electrophysiological properties in stable clones of the HL-1 myocyte cell line. PLoS One 2014, 9 (2), e90266  DOI: 10.1371/journal.pone.0090266
  48. 48
    Hafez, P.; Chowdhury, S. R.; Jose, S.; Law, J. X.; Ruszymah, B. H. I.; Ramzisham, A. R. M.; Ng, M. H. Development of an In Vitro Cardiac Ischemic Model Using Primary Human Cardiomyocytes. Cardiovasc Eng. Techn 2018, 9 (3), 529538,  DOI: 10.1007/s13239-018-0368-8
  49. 49
    Zhu, R. J.; Millrod, M. A.; Zambidis, E. T.; Tung, L. Variability of Action Potentials Within and Among Cardiac Cell Clusters Derived from Human Embryonic Stem Cells. Sci. Rep. 2016, 6, 18544,  DOI: 10.1038/srep18544
  50. 50
    Abbott, J.; Ye, T.; Qin, L.; Jorgolli, M.; Gertner, R. S.; Ham, D.; Park, H. CMOS nanoelectrode array for all-electrical intracellular electrophysiological imaging. Nat. Nanotechnol. 2017, 12 (5), 460466,  DOI: 10.1038/nnano.2017.3
  51. 51
    Abbott, J.; Ye, T.; Krenek, K.; Gertner, R. S.; Ban, S.; Kim, Y.; Qin, L.; Wu, W.; Park, H.; Ham, D. A nanoelectrode array for obtaining intracellular recordings from thousands of connected neurons. Nat. Biomed Eng. 2020, 4, 232,  DOI: 10.1038/s41551-019-0455-7
  52. 52
    Lee, J. H.; Zhang, A.; You, S. S.; Lieber, C. M. Spontaneous Internalization of Cell Penetrating Peptide-Modified Nanowires into Primary Neurons. Nano Lett. 2016, 16 (2), 150913,  DOI: 10.1021/acs.nanolett.6b00020
  53. 53
    Liu, H. T.; Haider, B.; Fried, H. R.; Ju, J.; Bolonduro, O.; Raghuram, V.; Timko, B. P. Nanobiotechnology: 1D nanomaterial building blocks for cellular interfaces and hybrid tissues. Nano Res. 2018, 11 (10), 53725399,  DOI: 10.1007/s12274-018-2189-3

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  23. Nitin Verma, Neha Kanojia, Komal Thapa, Prarit Chandel, Kamal Dua. Organ-on-a-chip in the diagnosis and treatment of chronic respiratory disorders and its application to advanced drug delivery systems. 2025, 267-285. https://doi.org/10.1016/B978-0-443-27345-2.00008-4
  24. Samuel P. Moss, Ezgi Bakirci, Adam W. Feinberg. Engineering the 3D structure of organoids. Stem Cell Reports 2025, 20 (1) , 102379. https://doi.org/10.1016/j.stemcr.2024.11.009
  25. Frøydis Sved Skottvoll, Enrique Escobedo‐Cousin, Michal Marek Mielnik. The Role of Silicon Technology in Organ‐On‐Chip: Current Status and Future Perspective. Advanced Materials Technologies 2024, 39 https://doi.org/10.1002/admt.202401254
  26. Yunqi Man, Yanfei Liu, Qiwen Chen, Zhirou Zhang, Mingfeng Li, Lishang Xu, Yifu Tan, Zhenbao Liu. Organoids‐On‐a‐Chip for Personalized Precision Medicine. Advanced Healthcare Materials 2024, 13 (30) https://doi.org/10.1002/adhm.202401843
  27. Sang Jin Lee, Wonwoo Jeong, Anthony Atala. 3D Bioprinting for Engineered Tissue Constructs and Patient‐Specific Models: Current Progress and Prospects in Clinical Applications. Advanced Materials 2024, 36 (49) https://doi.org/10.1002/adma.202408032
  28. Madison Stiefbold, Haokang Zhang, Leo Q. Wan. Engineered platforms for mimicking cardiac development and drug screening. Cellular and Molecular Life Sciences 2024, 81 (1) https://doi.org/10.1007/s00018-024-05231-1
  29. Feng Xu, Hang Jin, Lingling Liu, Yuanyuan Yang, Jianzheng Cen, Yaobin Wu, Songyue Chen, Daoheng Sun. Architecture design and advanced manufacturing of heart-on-a-chip: scaffolds, stimulation and sensors. Microsystems & Nanoengineering 2024, 10 (1) https://doi.org/10.1038/s41378-024-00692-7
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  31. Zuzanna Iwoń, Ewelina Krogulec, Aleksandra Kierlańczyk, Michał Wojasiński, Elżbieta Jastrzębska. Hypoxia and re-oxygenation effects on human cardiomyocytes cultured on polycaprolactone and polyurethane nanofibrous mats. Journal of Biological Engineering 2024, 18 (1) https://doi.org/10.1186/s13036-024-00432-5
  32. Jiande Zhang, Min-Hyeok Kim, Seulgi Lee, Sungsu Park. Integration of nanobiosensors into organ-on-chip systems for monitoring viral infections. Nano Convergence 2024, 11 (1) https://doi.org/10.1186/s40580-024-00455-0
  33. Riya Kar, Debabrata Mukhopadhyay, Ramcharan Singh Angom. Progress in Disease Modeling for Myocardial Infarction and Coronary Artery Disease: Bridging In Vivo and In Vitro Approaches. Hearts 2024, 5 (4) , 429-447. https://doi.org/10.3390/hearts5040031
  34. Merel Peletier, Xiaohan Zhang, Scarlett Klein, Jeffrey Kroon. Multicellular 3D models to study myocardial ischemia–reperfusion injury. Frontiers in Cell and Developmental Biology 2024, 12 https://doi.org/10.3389/fcell.2024.1494911
  35. Natalie N. Khalil, Megan L. Rexius‐Hall, Divya Gupta, Liam McCarthy, Riya Verma, Austin C. Kellogg, Kaelyn Takamoto, Maryann Xu, Tiana Nejatpoor, Sarah J. Parker, Megan L. McCain. Hypoxic–Normoxic Crosstalk Activates Pro‐Inflammatory Signaling in Human Cardiac Fibroblasts and Myocytes in a Post‐Infarct Myocardium on a Chip. Advanced Healthcare Materials 2024, 13 (28) https://doi.org/10.1002/adhm.202401478
  36. Xinmei Xu, Suet Cheung, Xiaomeng Jia, Gang Fan, Yongjian Ai, Yi Zhang, Qionglin Liang. Trends in organ-on-a-chip for pharmacological analysis. TrAC Trends in Analytical Chemistry 2024, 180 , 117905. https://doi.org/10.1016/j.trac.2024.117905
  37. Rustem Salmenov, Christine Mummery, Menno ter Huurne. Cell cycle visualization tools to study cardiomyocyte proliferation in real-time. Open Biology 2024, 14 (10) https://doi.org/10.1098/rsob.240167
  38. Balu Mahendran Gunasekaran, Soorya Srinivasan, Madeshwari Ezhilan, Venkatachalam Rajagopal, Noel Nesakumar. Advancements in Organ‐on‐a‐Chip Systems: Materials, Characterization, and Applications. ChemistrySelect 2024, 9 (40) https://doi.org/10.1002/slct.202403611
  39. Cansu İlke Kuru, Fulden Ulucan-Karnak. Lab-on-a-chip: A Stepping Stone for Personalized Healthcare Management. 2024, 221-243. https://doi.org/10.1039/9781837673476-00221
  40. Olurotimi A. Bolonduro, Zijing Chen, Corey P. Fucetola, Yan‐Ru Lai, Megan Cote, Rofiat O. Kajola, Akshita A. Rao, Haitao Liu, Emmanuel S. Tzanakakis, Brian P. Timko. An Integrated Optogenetic and Bioelectronic Platform for Regulating Cardiomyocyte Function. Advanced Science 2024, 21 https://doi.org/10.1002/advs.202402236
  41. Dhiraj Kumar, Rahul Nadda, Ramjee Repaka. Advances and challenges in organ-on-chip technology: toward mimicking human physiology and disease in vitro. Medical & Biological Engineering & Computing 2024, 62 (7) , 1925-1957. https://doi.org/10.1007/s11517-024-03062-7
  42. Jihoon Ko, Dohyun Park, Jungseub Lee, Sangmin Jung, Kyusuk Baek, Kyung E. Sung, Jeeyun Lee, Noo Li Jeon. Microfluidic high-throughput 3D cell culture. Nature Reviews Bioengineering 2024, 2 (6) , 453-469. https://doi.org/10.1038/s44222-024-00163-8
  43. Kamil Elkhoury, Sacha Kodeih, Eduardo Enciso‐Martínez, Ali Maziz, Christian Bergaud. Advancing Cardiomyocyte Maturation: Current Strategies and Promising Conductive Polymer‐Based Approaches. Advanced Healthcare Materials 2024, 13 (13) https://doi.org/10.1002/adhm.202303288
  44. Xiao Li, Hui Zhu, Bingsong Gu, Cong Yao, Yuyang Gu, Wangkai Xu, Jia Zhang, Jiankang He, Xinyu Liu, Dichen Li. Advancing Intelligent Organ‐on‐a‐Chip Systems with Comprehensive In Situ Bioanalysis. Advanced Materials 2024, 36 (18) https://doi.org/10.1002/adma.202305268
  45. Negar Farhang Doost, Soumya K. Srivastava. A Comprehensive Review of Organ-on-a-Chip Technology and Its Applications. Biosensors 2024, 14 (5) , 225. https://doi.org/10.3390/bios14050225
  46. Jennifer Kieda, Amid Shakeri, Shira Landau, Erika Yan Wang, Yimu Zhao, Benjamin Fook Lai, Sargol Okhovatian, Ying Wang, Richard Jiang, Milica Radisic. Advances in cardiac tissue engineering and heart‐on‐a‐chip. Journal of Biomedical Materials Research Part A 2024, 112 (4) , 492-511. https://doi.org/10.1002/jbm.a.37633
  47. Derrick Butler, Darwin R. Reyes. Heart-on-a-chip systems: disease modeling and drug screening applications. Lab on a Chip 2024, 24 (5) , 1494-1528. https://doi.org/10.1039/D3LC00829K
  48. Yuan Yang, Hao Yang, Fedir N. Kiskin, Joe Z. Zhang. The new era of cardiovascular research: revolutionizing cardiovascular research with 3D models in a dish. Medical Review 2024, 4 (1) , 68-85. https://doi.org/10.1515/mr-2023-0059
  49. Ranjit Barua, Nirmalendu Biswas, Deepanjan Das. Emergent Applications of Organ-on-a-Chip (OOAC) Technologies With Artificial Vascular Networks in the 21st Century. 2024, 198-219. https://doi.org/10.4018/979-8-3693-1214-8.ch010
  50. Bingsong Gu, Kang Han, Hanbo Cao, Xinxin Huang, Xiao Li, Mao Mao, Hui Zhu, Hu Cai, Dichen Li, Jiankang He. Heart-on-a-chip systems with tissue-specific functionalities for physiological, pathological, and pharmacological studies. Materials Today Bio 2024, 24 , 100914. https://doi.org/10.1016/j.mtbio.2023.100914
  51. Mohammad Irfan Hajam, Mohammad Mohsin Khan. Microfluidics: a concise review of the history, principles, design, applications, and future outlook. Biomaterials Science 2024, 12 (2) , 218-251. https://doi.org/10.1039/D3BM01463K
  52. Xinyi Chen, Sitian Liu, Mingying Han, Meng Long, Ting Li, Lanlan Hu, Ling Wang, Wenhua Huang, Yaobin Wu. Engineering Cardiac Tissue for Advanced Heart‐On‐A‐Chip Platforms. Advanced Healthcare Materials 2024, 13 (1) https://doi.org/10.1002/adhm.202301338
  53. Shuyu Zhang, Guoshi Xu, Juan Wu, Xiao Liu, Yong Fan, Jun Chen, Gordon Wallace, Qi Gu. Microphysiological Constructs and Systems: Biofabrication Tactics, Biomimetic Evaluation Approaches, and Biomedical Applications. Small Methods 2024, 8 (1) https://doi.org/10.1002/smtd.202300685
  54. Guven Akcay, Cagla Celik, Nilay Ildız, Ismail Ocsoy. Functional Biosensors in Cell and Tissue Fabrication for Smart Life-Sciences Applications. 2024, 235-253. https://doi.org/10.1007/978-981-99-5787-3_13
  55. Anirban Goutam Mukherjee, Uddesh Ramesh Wanjari, Pragya Bradu, Antara Biswas, Megha Patil, Kaviyarasi Renu, Balachandar Vellingiri, Abilash Valsala Gopalakrishnan. Recent breakthrough in organ-on-a-chip. 2024, 391-409. https://doi.org/10.1016/B978-0-443-13782-2.00007-3
  56. Dominik Grochala, Anna Paleczek, Gerardo Lopez-Muñoz, Artur Rydosz. Measurement and analytical techniques. 2024, 137-185. https://doi.org/10.1016/B978-0-443-15384-6.00003-3
  57. Patrycja Baranowska, Magdalena Flont, Agnieszka Żuchowska, Zbigniew Brzózka, Elżbieta Jastrzębska. Organ-on-a-chip systems. 2024https://doi.org/10.1016/B978-0-443-15978-7.00048-5
  58. Sara Deir, Yasaman Mozhdehbakhsh Mofrad, Shohreh Mashayekhan, Amir Shamloo, Amirreza Mansoori-Kermani. Step-by-step fabrication of heart-on-chip systems as models for cardiac disease modeling and drug screening. Talanta 2024, 266 , 124901. https://doi.org/10.1016/j.talanta.2023.124901
  59. George Ronan, Gokhan Bahcecioglu, Nihat Aliyev, Pinar Zorlutuna. Engineering the cardiac tissue microenvironment. Progress in Biomedical Engineering 2024, 6 (1) , 012002. https://doi.org/10.1088/2516-1091/ad0ea7
  60. Monique Bax, Jordan Thorpe, Valentin Romanov. The future of personalized cardiovascular medicine demands 3D and 4D printing, stem cells, and artificial intelligence. Frontiers in Sensors 2023, 4 https://doi.org/10.3389/fsens.2023.1294721
  61. Xingxing Liu, Dongxin Xu, Jiaru Fang, Yuheng Liao, Mingyue Zhang, Hongbo Li, Wenjian Yang, Yue Wu, Zhongyuan Xu, Ning Hu, Diming Zhang. Sensitive and prolonged intracellular electrophysiological recording by three‐dimensional nanodensity regulation. VIEW 2023, 4 (6) https://doi.org/10.1002/VIW.20230031
  62. Jing Liu, Ying Wang. Advances in organ‐on‐a‐chip for the treatment of cardiovascular diseases. MedComm – Biomaterials and Applications 2023, 2 (4) https://doi.org/10.1002/mba2.63
  63. Martin Kulke, Dayna M. Olson, Jingcheng Huang, David M. Kramer, Josh V. Vermaas. Long‐Range Electron Transport Rates Depend on Wire Dimensions in Cytochrome Nanowires. Small 2023, 19 (52) https://doi.org/10.1002/smll.202304013
  64. Silin Liu, Chongkai Fang, Chong Zhong, Jing Li, Qingzhong Xiao. Recent advances in pluripotent stem cell-derived cardiac organoids and heart-on-chip applications for studying anti-cancer drug-induced cardiotoxicity. Cell Biology and Toxicology 2023, 39 (6) , 2527-2549. https://doi.org/10.1007/s10565-023-09835-4
  65. Jinyoung Kim, Junghoon Kim, Yoonhee Jin, Seung-Woo Cho. In situ biosensing technologies for an organ-on-a-chip. Biofabrication 2023, 15 (4) , 042002. https://doi.org/10.1088/1758-5090/aceaae
  66. Viviana Roman, Mirela Mihaila, Nicoleta Radu, Stefania Marineata, Carmen Cristina Diaconu, Marinela Bostan. Cell Culture Model Evolution and Its Impact on Improving Therapy Efficiency in Lung Cancer. Cancers 2023, 15 (20) , 4996. https://doi.org/10.3390/cancers15204996
  67. Sitian Liu, Zihan Wang, Xinyi Chen, Mingying Han, Jie Xu, Ting Li, Liu Yu, Maoyu Qin, Meng Long, Mingchuan Li, Hongwu Zhang, Yanbing Li, Ling Wang, Wenhua Huang, Yaobin Wu. Multiscale Anisotropic Scaffold Integrating 3D Printing and Electrospinning Techniques as a Heart‐on‐a‐Chip Platform for Evaluating Drug‐Induced Cardiotoxicity. Advanced Healthcare Materials 2023, 12 (24) https://doi.org/10.1002/adhm.202300719
  68. Karina Cuanalo-Contreras, Andreas M.R. Hogrebe, Karoline Teichmann, Dennis Benkmann. Track‐Etched Membranes for Drug Pharmaceutical Research. Chemie Ingenieur Technik 2023, 95 (9) , 1372-1380. https://doi.org/10.1002/cite.202300089
  69. Kiran Raj M, Jyotsana Priyadarshani, Pratyaksh Karan, Saumyadwip Bandyopadhyay, Soumya Bhattacharya, Suman Chakraborty. Bio-inspired microfluidics: A review. Biomicrofluidics 2023, 17 (5) https://doi.org/10.1063/5.0161809
  70. Laura A. Milton, Matthew S. Viglione, Louis Jun Ye Ong, Gregory P. Nordin, Yi-Chin Toh. Vat photopolymerization 3D printed microfluidic devices for organ-on-a-chip applications. Lab on a Chip 2023, 23 (16) , 3537-3560. https://doi.org/10.1039/D3LC00094J
  71. Suhyeon Kim, Seungho Baek, Ronald Sluyter, Konstantin Konstantinov, Jung Ho Kim, Sunkook Kim, Yong Ho Kim. Wearable and implantable bioelectronics as eco‐friendly and patient‐friendly integrated nanoarchitectonics for next‐generation smart healthcare technology. EcoMat 2023, 5 (8) https://doi.org/10.1002/eom2.12356
  72. Ornella Urzì, Roberta Gasparro, Elisa Costanzo, Angela De Luca, Gianluca Giavaresi, Simona Fontana, Riccardo Alessandro. Three-Dimensional Cell Cultures: The Bridge between In Vitro and In Vivo Models. International Journal of Molecular Sciences 2023, 24 (15) , 12046. https://doi.org/10.3390/ijms241512046
  73. Hanna Vuorenpää, Miina Björninen, Hannu Välimäki, Antti Ahola, Mart Kroon, Laura Honkamäki, Jussi T. Koivumäki, Mari Pekkanen-Mattila. Building blocks of microphysiological system to model physiology and pathophysiology of human heart. Frontiers in Physiology 2023, 14 https://doi.org/10.3389/fphys.2023.1213959
  74. Yanjun Liu, Ling Lin, Liang Qiao. Recent developments in organ-on-a-chip technology for cardiovascular disease research. Analytical and Bioanalytical Chemistry 2023, 415 (18) , 3911-3925. https://doi.org/10.1007/s00216-023-04596-9
  75. Bingsong Gu, Xiao Li, Cong Yao, Xiaoli Qu, Mao Mao, Dichen Li, Jiankang He. Integration of microelectrodes and highly-aligned cardiac constructs for in situ electrophysiological recording. Microchemical Journal 2023, 190 , 108587. https://doi.org/10.1016/j.microc.2023.108587
  76. Vasant Iyer, David A. Issadore, Firooz Aflatouni. The next generation of hybrid microfluidic/integrated circuit chips: recent and upcoming advances in high-speed, high-throughput, and multifunctional lab-on-IC systems. Lab on a Chip 2023, 23 (11) , 2553-2576. https://doi.org/10.1039/D2LC01163H
  77. Guocheng Fang, Yu‐Cheng Chen, Hongxu Lu, Dayong Jin. Advances in Spheroids and Organoids on a Chip. Advanced Functional Materials 2023, 33 (19) https://doi.org/10.1002/adfm.202215043
  78. Naina Sunildutt, Pratibha Parihar, Abdul Rahim Chethikkattuveli Salih, Sang Ho Lee, Kyung Hyun Choi. Revolutionizing drug development: harnessing the potential of organ-on-chip technology for disease modeling and drug discovery. Frontiers in Pharmacology 2023, 14 https://doi.org/10.3389/fphar.2023.1139229
  79. Omar Mourad, Ryan Yee, Mengyuan Li, Sara S. Nunes. Modeling Heart Diseases on a Chip: Advantages and Future Opportunities. Circulation Research 2023, 132 (4) , 483-497. https://doi.org/10.1161/CIRCRESAHA.122.321670
  80. Laura Paz-Artigas, Pilar Montero-Calle, Olalla Iglesias-García, Manuel M. Mazo, Ignacio Ochoa, Jesús Ciriza. Current approaches for the recreation of cardiac ischaemic environment in vitro. International Journal of Pharmaceutics 2023, 632 , 122589. https://doi.org/10.1016/j.ijpharm.2023.122589
  81. Eline Simons, Bart Loeys, Maaike Alaerts. iPSC-Derived Cardiomyocytes in Inherited Cardiac Arrhythmias: Pathomechanistic Discovery and Drug Development. Biomedicines 2023, 11 (2) , 334. https://doi.org/10.3390/biomedicines11020334
  82. Uyen M. N. Cao, Yuli Zhang, Julie Chen, Darren Sayson, Sangeeth Pillai, Simon D. Tran. Microfluidic Organ-on-A-chip: A Guide to Biomaterial Choice and Fabrication. International Journal of Molecular Sciences 2023, 24 (4) , 3232. https://doi.org/10.3390/ijms24043232
  83. Yonggeng Ma, Chenbin Liu, Siyu Cao, Tianshu Chen, Guifang Chen. Microfluidics for diagnosis and treatment of cardiovascular disease. Journal of Materials Chemistry B 2023, 11 (3) , 546-559. https://doi.org/10.1039/D2TB02287G
  84. Fatih Kocabaş. Therapeutic Targeting of Epicardial and Cardiac Progenitors in the Heart Regeneration. 2023, 279-305. https://doi.org/10.1007/978-981-99-0722-9_11
  85. Sridhar Chandrasekaran, Arunkumar Jayakumar, Rajkumar Velu, S. Stella Mary. Design and Manufacturing of 3D Printed Sensors for Biomedical Applications. 2023, 63-76. https://doi.org/10.1007/978-981-99-7100-8_3
  86. Friederike Adams, Christoph M. Zimmermann, Paola Luciani, Olivia M. Merkel. Microfluidics for nanopharmaceutical and medical applications. 2023, 343-408. https://doi.org/10.1016/B978-0-12-822482-3.00010-5
  87. Hayriye Öztatlı, Zeynep Altintas, Bora Garipcan. Biosensors for organs-on-a-chip and organoids. 2023, 471-514. https://doi.org/10.1016/B978-0-323-90222-9.00007-8
  88. Arnab Pal, Kuldeep Kaswan, Snigdha Roy Barman, Yu-Zih Lin, Jun-Hsuan Chung, Manish Kumar Sharma, Kuei-Lin Liu, Bo-Huan Chen, Chih-Cheng Wu, Sangmin Lee, Dongwhi Choi, Zong-Hong Lin. Microfluidic nanodevices for drug sensing and screening applications. Biosensors and Bioelectronics 2023, 219 , 114783. https://doi.org/10.1016/j.bios.2022.114783
  89. Joseph Criscione, Zahra Rezaei, Carol M. Hernandez Cantu, Sean Murphy, Su Ryon Shin, Deok-Ho Kim. Heart-on-a-chip platforms and biosensor integration for disease modeling and phenotypic drug screening. Biosensors and Bioelectronics 2023, 220 , 114840. https://doi.org/10.1016/j.bios.2022.114840
  90. Martta Häkli, Joose Kreutzer, Antti-Juhana Mäki, Hannu Välimäki, Reeja Maria Cherian, Pasi Kallio, Katriina Aalto-Setälä, Mari Pekkanen-Mattila, . Electrophysiological Changes of Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes during Acute Hypoxia and Reoxygenation. Stem Cells International 2022, 2022 , 1-15. https://doi.org/10.1155/2022/9438281
  91. Megan L. Rexius-Hall, Natalie N. Khalil, Sean S. Escopete, Xin Li, Jiayi Hu, Hongyan Yuan, Sarah J. Parker, Megan L. McCain. A myocardial infarct border-zone-on-a-chip demonstrates distinct regulation of cardiac tissue function by an oxygen gradient. Science Advances 2022, 8 (49) https://doi.org/10.1126/sciadv.abn7097
  92. Abolfazl Salehi Moghaddam, Zahra Salehi Moghaddam, Seyed Mohammad Davachi, Einolah Sarikhani, Saba Nemati Mahand, Hossein Ali Khonakdar, Zohreh Bagher, Nureddin Ashammakhi. Recent advances and future prospects of functional organ-on-a-chip systems. Materials Chemistry Frontiers 2022, 6 (24) , 3633-3661. https://doi.org/10.1039/D2QM00072E
  93. Yuting Xiang, Haitao Liu, Wenjian Yang, Zhongyuan Xu, Yue Wu, Zhaojian Tang, Zhijing Zhu, Zhiyong Zeng, Depeng Wang, Tianxing Wang, Ning Hu, Diming Zhang. A biosensing system employing nanowell microelectrode arrays to record the intracellular potential of a single cardiomyocyte. Microsystems & Nanoengineering 2022, 8 (1) https://doi.org/10.1038/s41378-022-00408-9
  94. Rebecca B. Riddle, Karin Jennbacken, Kenny M. Hansson, Matthew T. Harper. Endothelial inflammation and neutrophil transmigration are modulated by extracellular matrix composition in an inflammation-on-a-chip model. Scientific Reports 2022, 12 (1) https://doi.org/10.1038/s41598-022-10849-x
  95. Korakot Boonyaphon, Zhenglin Li, Sung-Jin Kim. Gravity-driven preprogrammed microfluidic recirculation system for parallel biosensing of cell behaviors. Analytica Chimica Acta 2022, 1233 , 340456. https://doi.org/10.1016/j.aca.2022.340456
  96. Milan Finn Wesseler, Mathias Nørbæk Johansen, Aysel Kızıltay, Kim I. Mortensen, Niels B. Larsen. Optical 4D oxygen mapping of microperfused tissue models with tunable in vivo -like 3D oxygen microenvironments. Lab on a Chip 2022, 22 (21) , 4167-4179. https://doi.org/10.1039/D2LC00063F
  97. Shoshana L. Das, Bryan P. Sutherland, Emma Lejeune, Jeroen Eyckmans, Christopher S. Chen. Mechanical response of cardiac microtissues to acute localized injury. American Journal of Physiology-Heart and Circulatory Physiology 2022, 323 (4) , H738-H748. https://doi.org/10.1152/ajpheart.00305.2022
  98. Isabella Francis, Jesus Shrestha, Keshav Raj Paudel, Philip M. Hansbro, Majid Ebrahimi Warkiani, Suvash C. Saha. Recent advances in lung-on-a-chip models. Drug Discovery Today 2022, 27 (9) , 2593-2602. https://doi.org/10.1016/j.drudis.2022.06.004
  99. Gozde Basara, Gokhan Bahcecioglu, S. Gulberk Ozcebe, Bradley W Ellis, George Ronan, Pinar Zorlutuna. Myocardial infarction from a tissue engineering and regenerative medicine point of view: A comprehensive review on models and treatments. Biophysics Reviews 2022, 3 (3) https://doi.org/10.1063/5.0093399
  100. Bradley W. Ellis, George Ronan, Xiang Ren, Gokhan Bahcecioglu, Satyajyoti Senapati, David Anderson, Eileen Handberg, Keith L. March, Hsueh‐Chia Chang, Pinar Zorlutuna. Human Heart Anoxia and Reperfusion Tissue (HEART) Model for the Rapid Study of Exosome Bound miRNA Expression As Biomarkers for Myocardial Infarction. Small 2022, 18 (28) https://doi.org/10.1002/smll.202201330
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Nano Letters

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Published February 24, 2020

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  • Abstract

    Figure 1

    Figure 1. Overview of the heart-on-a-chip platform. (a) (top) Optical image and (bottom) scheme representing fully assembled chip with integrated recording elements, reference electrode, and PDMS channel for media delivery. (b) Representative optical image of an extracellular recording element coated with Pt black (red arrow). (c) Representative optical image of an intracellular recording element comprised of an underlying Au pad with five vertical Pt nanopillars (blue arrow). (d) (top) SEM detail of five vertical nanopillars corresponding to the location marked by the blue arrow in panel c. (inset) Schematic representation of a single nanopillar cross section. (bottom) Cross section of a single nanopillar after etching with FIB. Note that the Pt nanopillar fully penetrated the SiO2 layer to form a junction with the underlying Au layer. (e) Immunostaining of the HL-1 cell monolayer cultured in a PDMS channel at 4 DIV showing α-actinin cytoskeleton (green), Cx-43 gap junction proteins (red), and nuclei (blue, DAPI). (f) Stitched immunofluorescence image showing continuous HL-1 monolayer across the lateral direction of the microfluidic channel. Yellow dotted lines denote edges of the PDMS boundary.

    Figure 2

    Figure 2. Extracellular bioelectronic readouts before, during, and after hypoxia. (a) (top) Scheme of media delivery protocol with distinct regions of normoxia, hypoxia, and recovery and (bottom) HL-1 firing rate. The red dotted box highlights the transition from rhythmic beating to arrhythmia. (b) Representative signals from a single device recorded during (I) normoxia, (II) hypoxia, upon onset of arrhythmia, and (III) recovery. These traces correspond to the points noted in panel a. (inset) Single peak expansions of (black) overlaid individual traces and (red) average of individual traces. (c) Scheme of electrode layout (black dots) and representative multiplexed readouts from a chip with 14 out of 16 functional bioelectronic interfaces. (d,e) Isochronal maps representing signal propagation at two time points each during (d) normoxia and (e) hypoxia for ∼1 h. Black arrow overlays represent the gradient of the isochrones. The area of each map is 1000 μm wide × 4200 μm tall.

    Figure 3

    Figure 3. Electrophysiology using nanopillar electrodes in normoxic media. (a) Representative extracellular signal recorded prior to electroporation. Inset shows expansion of single representative peak. (b) Intracellular signals recorded immediately after electroporation. (c) (blue square) Normalized action potential amplitude and (red circle) APD50 as a function of time after electroporation. Within 2 min, the amplitude of the action potentials decreased to around 24% of the maximum, while APD50 was unchanged. (d) Expansions of peaks shown in panel b at locations noted by red, blue, and yellow arrows, plotted on (left) absolute and (right) normalized scales. Note that the baseline of these peaks is offset for clarity.

    Figure 4

    Figure 4. Intracellular electrophysiology of HL-1 cells during 1% O2 hypoxic stress. (a) Schematic representation of typical HL-1 AP highlighting key parameters. (b) Intracellular recording showing arrhythmic beating after 6 h of hypoxic stress. (c) Representative examples of AP recordings following 0, 2, 4, or 6 h of hypoxic stress. Note that the 0 h time point represents normoxia. (d–f) Summary statistics representing (d) APD50, (e) APD90, and (f) depolarization time corresponding to each time point represented in panel c. (g) Percentage change for APD50, APD90, and depolarization time throughout hypoxia. Statistics are from N = 14 different cells in 4 different cultures. *P < 0.05, **P < 0.01, ***P < 0.0005, ****P < 0.0001 in Welch’s t test. All error bars denote s.d.

    Figure 5

    Figure 5. Multiplexed intracellular recordings. (a) Representative APs simultaneously recorded under (left) normoxia and (right) hypoxia after 2 h. The color-coded legend represents the corresponding device arrangement; spacing between devices is 600 μm. (b) Propagation maps correlating to each trace and spatial location shown in panels a and b. Each map is 3600 μm tall and represents propagation along the direction of the linear device array. (c) Heat maps representing APD50, APD90, and depolarization time corresponding to each trace and spatial location shown in panels a and b.

  • References


    This article references 53 other publications.

    1. 1
      Benjamin, E. J.; Muntner, P.; Alonso, A.; Bittencourt, M. S.; Callaway, C. W.; Carson, A. P.; Chamberlain, A. M.; Chang, A. R.; Cheng, S.; Das, S. R.; Delling, F. N.; Djousse, L.; Elkind, M. S. V.; Ferguson, J. F.; Fornage, M.; Jordan, L. C.; Khan, S. S.; Kissela, B. M.; Knutson, K. L.; Kwan, T. W.; Lackland, D. T.; Lewis, T. T.; Lichtman, J. H.; Longenecker, C. T.; Loop, M. S.; Lutsey, P. L.; Martin, S. S.; Matsushita, K.; Moran, A. E.; Mussolino, M. E.; O’Flaherty, M.; Pandey, A.; Perak, A. M.; Rosamond, W. D.; Roth, G. A.; Sampson, U. K. A.; Satou, G. M.; Schroeder, E. B.; Shah, S. H.; Spartano, N. L.; Stokes, A.; Tirschwell, D. L.; Tsao, C. W.; Turakhia, M. P.; VanWagner, L. B.; Wilkins, J. T.; Wong, S. S.; Virani, S. S. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation 2019, 139 (10), e56e528,  DOI: 10.1161/CIR.0000000000000659
    2. 2
      World Health Organization. Noncommunicable diseases country profiles 2018; World Health Organization: Geneva, 2018.
    3. 3
      Duranteau, J.; Chandel, N. S.; Kulisz, A.; Shao, Z.; Schumacker, P. T. Intracellular signaling by reactive oxygen species during hypoxia in cardiomyocytes. J. Biol. Chem. 1998, 273 (19), 1161911624,  DOI: 10.1074/jbc.273.19.11619
    4. 4
      Dutta, S.; Minchole, A.; Quinn, T. A.; Rodriguez, B. Electrophysiological properties of computational human ventricular cell action potential models under acute ischemic conditions. Prog. Biophys. Mol. Biol. 2017, 129, 4052,  DOI: 10.1016/j.pbiomolbio.2017.02.007
    5. 5
      Nakada, Y.; Canseco, D. C.; Thet, S.; Abdisalaam, S.; Asaithamby, A.; Santos, C. X.; Shah, A. M.; Zhang, H.; Faber, J. E.; Kinter, M. T.; Szweda, L. I.; Xing, C.; Hu, Z.; Deberardinis, R. J.; Schiattarella, G.; Hill, J. A.; Oz, O.; Lu, Z.; Zhang, C. C.; Kimura, W.; Sadek, H. A. Hypoxia induces heart regeneration in adult mice. Nature 2017, 541 (7636), 222227,  DOI: 10.1038/nature20173
    6. 6
      Kubasiak, L. A.; Hernandez, O. M.; Bishopric, N. H.; Webster, K. A. Hypoxia and acidosis activate cardiac myocyte death through the Bcl-2 family protein BNIP3. Proc. Natl. Acad. Sci. U. S. A. 2002, 99 (20), 1282512830,  DOI: 10.1073/pnas.202474099
    7. 7
      Martewicz, S.; Michielin, F.; Serena, E.; Zambon, A.; Mongillo, M.; Elvassore, N. Reversible alteration of calcium dynamics in cardiomyocytes during acute hypoxia transient in a microfluidic platform. Integrative Biology 2012, 4 (2), 153164,  DOI: 10.1039/C1IB00087J
    8. 8
      Lin, Z. C.; Xie, C.; Osakada, Y.; Cui, Y.; Cui, B. Iridium oxide nanotube electrodes for sensitive and prolonged intracellular measurement of action potentials. Nat. Commun. 2014, 5, 3206,  DOI: 10.1038/ncomms4206
    9. 9
      Zhu, Z.; Burnett, C. M.; Maksymov, G.; Stepniak, E.; Sierra, A.; Subbotina, E.; Anderson, M. E.; Coetzee, W. A.; Hodgson-Zingman, D. M.; Zingman, L. V. Reduction in number of sarcolemmal KATP channels slows cardiac action potential duration shortening under hypoxia. Biochem. Biophys. Res. Commun. 2011, 415 (4), 637641,  DOI: 10.1016/j.bbrc.2011.10.125
    10. 10
      Ribas, J.; Sadeghi, H.; Manbachi, A.; Leijten, J.; Brinegar, K.; Zhang, Y. S.; Ferreira, L.; Khademhosseini, A. Cardiovascular Organ-on-a-Chip Platforms for Drug Discovery and Development. Appl. In Vitro Toxicol 2016, 2 (2), 8296,  DOI: 10.1089/aivt.2016.0002
    11. 11
      Kang, Y. B. A.; Eo, J.; Bulutoglu, B.; Yarmush, M. L.; Usta, O. B. Progressive hypoxia-on-a-chip: An in vitro oxygen gradient model for capturing the effects of hypoxia on primary hepatocytes in health and disease. Biotechnol. Bioeng. 2020, 117, 763,  DOI: 10.1002/bit.27225
    12. 12
      Bolonduro, O. A.; Duffy, B. M.; Rao, A. A.; Black, L. D.; Timko, B. P. From Biomimicry to Bioelectronics: Smart Materials for Cardiac Tissue Engineering. Nano Res. 2020  DOI: 10.1007/s12274-020-2682-3 .
    13. 13
      Spira, M. E.; Hai, A. Multi-electrode array technologies for neuroscience and cardiology. Nat. Nanotechnol. 2013, 8 (2), 8394,  DOI: 10.1038/nnano.2012.265
    14. 14
      Feiner, R.; Engel, L.; Fleischer, S.; Malki, M.; Gal, I.; Shapira, A.; Shacham-Diamand, Y.; Dvir, T. Engineered hybrid cardiac patches with multifunctional electronics for online monitoring and regulation of tissue function. Nat. Mater. 2016, 15 (6), 67985,  DOI: 10.1038/nmat4590
    15. 15
      Xu, L.; Gutbrod, S. R.; Bonifas, A. P.; Su, Y.; Sulkin, M. S.; Lu, N.; Chung, H. J.; Jang, K. I.; Liu, Z.; Ying, M.; Lu, C.; Webb, R. C.; Kim, J. S.; Laughner, J. I.; Cheng, H.; Liu, Y.; Ameen, A.; Jeong, J. W.; Kim, G. T.; Huang, Y.; Efimov, I. R.; Rogers, J. A. 3D multifunctional integumentary membranes for spatiotemporal cardiac measurements and stimulation across the entire epicardium. Nat. Commun. 2014, 5, 3329,  DOI: 10.1038/ncomms4329
    16. 16
      Timko, B. P.; Cohen-Karni, T.; Yu, G.; Qing, Q.; Tian, B.; Lieber, C. M. Electrical recording from hearts with flexible nanowire device arrays. Nano Lett. 2009, 9 (2), 9148,  DOI: 10.1021/nl900096z
    17. 17
      Cohen-Karni, T.; Timko, B. P.; Weiss, L. E.; Lieber, C. M. Flexible electrical recording from cells using nanowire transistor arrays. Proc. Natl. Acad. Sci. U. S. A. 2009, 106 (18), 730913,  DOI: 10.1073/pnas.0902752106
    18. 18
      Dai, X.; Zhou, W.; Gao, T.; Liu, J.; Lieber, C. M. Three-dimensional mapping and regulation of action potential propagation in nanoelectronics-innervated tissues. Nat. Nanotechnol. 2016, 11 (9), 77682,  DOI: 10.1038/nnano.2016.96
    19. 19
      Tsai, D.; Sawyer, D.; Bradd, A.; Yuste, R.; Shepard, K. L. A very large-scale microelectrode array for cellular-resolution electrophysiology. Nat. Commun. 2017, 8, 1802,  DOI: 10.1038/s41467-017-02009-x
    20. 20
      Tian, B.; Lieber, C. M. Nanowired Bioelectric Interfaces. Chem. Rev. 2019, 119 (15), 91369152,  DOI: 10.1021/acs.chemrev.8b00795
    21. 21
      Zhao, Y.; You, S. S.; Zhang, A.; Lee, J. H.; Huang, J.; Lieber, C. M. Scalable ultrasmall three-dimensional nanowire transistor probes for intracellular recording. Nat. Nanotechnol. 2019, 14 (8), 783790,  DOI: 10.1038/s41565-019-0478-y
    22. 22
      Eschermann, J. F.; Stockmann, R.; Hueske, M.; Vu, X. T.; Ingebrandt, S.; Offenhäusser, A. Action potentials of HL-1 cells recorded with silicon nanowire transistors. Appl. Phys. Lett. 2009, 95 (8), 083703  DOI: 10.1063/1.3194138
    23. 23
      Xie, C.; Lin, Z.; Hanson, L.; Cui, Y.; Cui, B. Intracellular recording of action potentials by nanopillar electroporation. Nat. Nanotechnol. 2012, 7 (3), 18590,  DOI: 10.1038/nnano.2012.8
    24. 24
      Dipalo, M.; Amin, H.; Lovato, L.; Moia, F.; Caprettini, V.; Messina, G. C.; Tantussi, F.; Berdondini, L.; De Angelis, F. Intracellular and Extracellular Recording of Spontaneous Action Potentials in Mammalian Neurons and Cardiac Cells with 3D Plasmonic Nanoelectrodes. Nano Lett. 2017, 17 (6), 39323939,  DOI: 10.1021/acs.nanolett.7b01523
    25. 25
      Fendyur, A.; Spira, M. E. Toward on-chip, in-cell recordings from cultured cardiomyocytes by arrays of gold mushroom-shaped microelectrodes. Front. Neuroeng. 2012, 5, 21,  DOI: 10.3389/fneng.2012.00021
    26. 26
      Desbiolles, B. X. E.; de Coulon, E.; Bertsch, A.; Rohr, S.; Renaud, P. Intracellular Recording of Cardiomyocyte Action Potentials with Nanopatterned Volcano-Shaped Microelectrode Arrays. Nano Lett. 2019, 19 (9), 61736181,  DOI: 10.1021/acs.nanolett.9b02209
    27. 27
      Chen, T.; Vunjak-Novakovic, G. In vitro Models of Ischemia-Reperfusion Injury. Regen Eng. Transl Med. 2018, 4 (3), 142153,  DOI: 10.1007/s40883-018-0056-0
    28. 28
      White, S. M.; Constantin, P. E.; Claycomb, W. C. Cardiac physiology at the cellular level: use of cultured HL-1 cardiomyocytes for studies of cardiac muscle cell structure and function. Am. J. Physiol-Heart C 2004, 286 (3), H823H829,  DOI: 10.1152/ajpheart.00986.2003
    29. 29
      Teixeira, G.; Abrial, M.; Portier, K.; Chiari, P.; Couture-Lepetit, E.; Tourneur, Y.; Ovize, M.; Gharib, A. Synergistic protective effect of cyclosporin A and rotenone against hypoxia-reoxygenation in cardiomyocytes. J. Mol. Cell. Cardiol. 2013, 56, 5562,  DOI: 10.1016/j.yjmcc.2012.11.023
    30. 30
      Maoz, B. M.; Herland, A.; Henry, O. Y. F.; Leineweber, W. D.; Yadid, M.; Doyle, J.; Mannix, R.; Kujala, V. J.; FitzGerald, E. A.; Parker, K. K.; Ingber, D. E. Organs-on-Chips with combined multi-electrode array and transepithelial electrical resistance measurement capabilities. Lab Chip 2017, 17 (13), 22942302,  DOI: 10.1039/C7LC00412E
    31. 31
      Yang, M.; Lim, C. C.; Liao, R.; Zhang, X. A novel microfluidic impedance assay for monitoring endothelin-induced cardiomyocyte hypertrophy. Biosens. Bioelectron. 2007, 22 (8), 168893,  DOI: 10.1016/j.bios.2006.07.032
    32. 32
      Yang, Z.; Murray, K. T. Ionic mechanisms of pacemaker activity in spontaneously contracting atrial HL-1 cells. J. Cardiovasc. Pharmacol. 2011, 57 (1), 2836,  DOI: 10.1097/FJC.0b013e3181fda7c4
    33. 33
      Martins-Marques, T.; Anjo, S. I.; Pereira, P.; Manadas, B.; Girao, H. Interacting Network of the Gap Junction (GJ) Protein Connexin43 (Cx43) is Modulated by Ischemia and Reperfusion in the Heart. Mol. Cell. Proteomics 2015, 14 (11), 304055,  DOI: 10.1074/mcp.M115.052894
    34. 34
      Semenza, G. L. Hypoxia-inducible factor 1 and cardiovascular disease. Annu. Rev. Physiol. 2014, 76, 3956,  DOI: 10.1146/annurev-physiol-021113-170322
    35. 35
      Chu, W.; Wan, L.; Zhao, D.; Qu, X.; Cai, F.; Huo, R.; Wang, N.; Zhu, J.; Zhang, C.; Zheng, F.; Cai, R.; Dong, D.; Lu, Y.; Yang, B. Mild hypoxia-induced cardiomyocyte hypertrophy via up-regulation of HIF-1alpha-mediated TRPC signalling. J. Cell Mol. Med. 2012, 16 (9), 202234,  DOI: 10.1111/j.1582-4934.2011.01497.x
    36. 36
      Lee, J. W.; Ko, J.; Ju, C.; Eltzschig, H. K. Hypoxia signaling in human diseases and therapeutic targets. Exp. Mol. Med. 2019, 51 (6), 68,  DOI: 10.1038/s12276-019-0235-1
    37. 37
      Semenza, G.; Hydroxylation, L. of HIF-1: Oxygen Sensing at the Molecular Level. Physiology 2004, 19 (4), 176182,  DOI: 10.1152/physiol.00001.2004
    38. 38
      Yeung, C. K.; Sommerhage, F.; Wrobel, G.; Law, J. K.; Offenhausser, A.; Rudd, J. A.; Ingebrandt, S.; Chan, M. To establish a pharmacological experimental platform for the study of cardiac hypoxia using the microelectrode array. J. Pharmacol. Toxicol. Methods 2009, 59 (3), 14652,  DOI: 10.1016/j.vascn.2009.02.005
    39. 39
      Cascio, W. E.; Yang, H.; Muller-Borer, B. J.; Johnson, T. A. Ischemia-induced arrhythmia: the role of connexins, gap junctions, and attendant changes in impulse propagation. J. Electrocardiol 2005, 38 (4 Suppl), 5559,  DOI: 10.1016/j.jelectrocard.2005.06.019
    40. 40
      Lujan, H. L.; DiCarlo, S. E. Reperfusion-induced sustained ventricular tachycardia, leading to ventricular fibrillation, in chronically instrumented, intact, conscious mice. Physiol. Rep. 2014, 2 (6), e12057,  DOI: 10.14814/phy2.12057
    41. 41
      Dang, K. M.; Rinklin, P.; Afanasenkau, D.; Westmeyer, G.; Schurholz, T.; Wiegand, S.; Wolfrum, B. Chip-Based Heat Stimulation for Modulating Signal Propagation in HL-1 Cell Networks. Adv. Biosyst 2018, 2 (12), 1800138,  DOI: 10.1002/adbi.201800138
    42. 42
      Claycomb, W. C.; Lanson, N. A.; Stallworth, B. S.; Egeland, D. B.; Delcarpio, J. B.; Bahinski, A.; Izzo, N. J. HL-1 cells: a cardiac muscle cell line that contracts and retains phenotypic characteristics of the adult cardiomyocyte. Proc. Natl. Acad. Sci. U. S. A. 1998, 95 (6), 29792984,  DOI: 10.1073/pnas.95.6.2979
    43. 43
      Lin, Z. C.; McGuire, A. F.; Burridge, P. W.; Matsa, E.; Lou, H.-Y.; Wu, J. C.; Cui, B. Accurate nanoelectrode recording of human pluripotent stem cell-derived cardiomyocytes for assaying drugs and modeling disease. Microsystems & Nanoengineering 2017, 3, 16080,  DOI: 10.1038/micronano.2016.80
    44. 44
      Shaw, R. M.; Rudy, Y. Electrophysiologic effects of acute myocardial ischemia: a theoretical study of altered cell excitability and action potential duration. Cardiovasc. Res. 1997, 35 (2), 25672,  DOI: 10.1016/S0008-6363(97)00093-X
    45. 45

      These speeds are on the same order as those derived from extracellular electrodes. We note however that they do not represent the true wavefront velocity but rather a projection along the direction of the linear electrode array.

    46. 46
      Sartiani, L.; Bochet, P.; Cerbai, E.; Mugelli, A.; Fischmeister, R. Functional expression of the hyperpolarization-activated, non-selective cation current I(f) in immortalized HL-1 cardiomyocytes. J. Physiol. 2002, 545 (1), 8192,  DOI: 10.1113/jphysiol.2002.021535
    47. 47
      Dias, P.; Desplantez, T.; El-Harasis, M. A.; Chowdhury, R. A.; Ullrich, N. D.; Cabestrero de Diego, A.; Peters, N. S.; Severs, N. J.; MacLeod, K. T.; Dupont, E. Characterisation of connexin expression and electrophysiological properties in stable clones of the HL-1 myocyte cell line. PLoS One 2014, 9 (2), e90266  DOI: 10.1371/journal.pone.0090266
    48. 48
      Hafez, P.; Chowdhury, S. R.; Jose, S.; Law, J. X.; Ruszymah, B. H. I.; Ramzisham, A. R. M.; Ng, M. H. Development of an In Vitro Cardiac Ischemic Model Using Primary Human Cardiomyocytes. Cardiovasc Eng. Techn 2018, 9 (3), 529538,  DOI: 10.1007/s13239-018-0368-8
    49. 49
      Zhu, R. J.; Millrod, M. A.; Zambidis, E. T.; Tung, L. Variability of Action Potentials Within and Among Cardiac Cell Clusters Derived from Human Embryonic Stem Cells. Sci. Rep. 2016, 6, 18544,  DOI: 10.1038/srep18544
    50. 50
      Abbott, J.; Ye, T.; Qin, L.; Jorgolli, M.; Gertner, R. S.; Ham, D.; Park, H. CMOS nanoelectrode array for all-electrical intracellular electrophysiological imaging. Nat. Nanotechnol. 2017, 12 (5), 460466,  DOI: 10.1038/nnano.2017.3
    51. 51
      Abbott, J.; Ye, T.; Krenek, K.; Gertner, R. S.; Ban, S.; Kim, Y.; Qin, L.; Wu, W.; Park, H.; Ham, D. A nanoelectrode array for obtaining intracellular recordings from thousands of connected neurons. Nat. Biomed Eng. 2020, 4, 232,  DOI: 10.1038/s41551-019-0455-7
    52. 52
      Lee, J. H.; Zhang, A.; You, S. S.; Lieber, C. M. Spontaneous Internalization of Cell Penetrating Peptide-Modified Nanowires into Primary Neurons. Nano Lett. 2016, 16 (2), 150913,  DOI: 10.1021/acs.nanolett.6b00020
    53. 53
      Liu, H. T.; Haider, B.; Fried, H. R.; Ju, J.; Bolonduro, O.; Raghuram, V.; Timko, B. P. Nanobiotechnology: 1D nanomaterial building blocks for cellular interfaces and hybrid tissues. Nano Res. 2018, 11 (10), 53725399,  DOI: 10.1007/s12274-018-2189-3
  • Supporting Information

    Supporting Information


    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.nanolett.0c00076.

    • Movie S1. Spontaneous beating of cells that formed confluent monolayers (MP4)

    • Materials and Methods; Scheme S1. Illustration of microfluidic chip with integrated nanopillar microelectrode arrays; Scheme S2. Strategy to generate hypoxic medium flow; Figure S1. Design of MEA devices; Figure S2. Representative electrical impedance spectra of planar and nanopillar bioelectronic devices; Figure S3. Gap junction localization; Figure S4. HIF-1α validation of heart-on-a-chip; Figure S5. Extracellular bioelectronic readouts before, during, and after hypoxia; Figure S6. Summary of wavefront propagation speeds derived from isochronal map (PDF)


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