Correction to: Communications Engineeringhttps://doi.org/10.1038/s44172-026-00594-8, published online 11 February 2026 In the version of the article initially published, Or Perlman was missing from the author list and has now been added. Additionally, Alessandro Rizzo was originally listed with two affiliations, but this has now been corrected to a single affiliation. These corrections have been made to the HTML and PDF versions of the article.

In vitro modelling of cardiac microtissues via human pluripotent stem cell-derived cardiomyocytes (hiPSCs-CMs) holds great promise in experimental pharmacology, especially to improve drug safety and efficacy evaluation. However, the predictive capability of these models is currently hampered by a series of heterogeneity sources mainly related, but not limited to, their immature phenotype. While increased levels of complexity in human-derived models can favor maturation, differences in experimental approaches introduce variability in electrophysiological responses, which is difficult to mitigate. To tackle these aspects, this work proposes a novel measurement strategy in the dynamic frequency regime to induce and analyze multiple operation modes in hiPSC-CMs contraction during drug evaluation. We designed and validated a system for fully automated analysis of cardiac models in a dynamic regime via optical time-lapse microscopy. We show that repeated video-based measurements of the same biological samples in the presence of physical conditioning allow, with appropriate normalization and adjustment operations, accurate estimates of the responses of interest. The analyzed operation modes provided increased representativeness of video-based contractile parameters and reliable trend estimates of concentration-response curves without requiring a high number of biological replicates. In particular, the findings obtained with four benchmark experimental models, including two-dimensional (2D), two-dimensional aligned (2DA), tridimensional microtissues (3D-MTs), and engineered heart tissues (EHTs) in triple cell-type co-culturing, indicate that the proposed approach is effective in drug-response evaluation of four pharmacological compounds with known expected effects and a reference solvent, and offers a promising foundation for the development of high-throughput and robust tools for pharmacological screening.

Deep learning has proven to be one of the most effective methods in analyzing biological images to extract parameters fundamental for studying physiological functions and pathological conditions. In particular, when coupled with time-lapse microscopy (TLM), deep learning proves particularly effective in studying behaviors involving temporal dynamics. However, TLM videos are often affected by experimental noise and setup limitations, which can lead to inaccurate and poorly reproducible results. Taking advantage of the variational and generative capabilities of Variational Autoencoders (VAEs), we propose VAE-MOTION, a deep learning-based model for the analysis of cardiac contractile dynamics. By incorporating a temporal encoder into its architecture, our model allows the restoration of video quality by removing noise or increasing resolution, while simultaneously extracting accurate contraction-related signals from the latent space. The generation of synthetic videos allowed extensive training of VAE-MOTION, which subsequently validated on real videos from two different cardiac tissue models: 2D monolayers and 3D microtissues. VAE-MOTION was compared to two gold-standard methods in extracting contraction parameters relevant to drug efficacy or toxicity studies, demonstrating its potential for analyzing temporal dynamics in a given phenomenon or process.

Organ-on-Chip (OoC) devices enable controlled replication of physiological microenvironments and are increasingly used in biomedical engineering and drug discovery. This study presents a comprehensive 3D simulation-based characterization of mass transport and mechanical properties of a silicon-based Barrier-on-Chip (BoC) device comprising two stacked microfluidic channels separated by a porous Si3N4 membrane. Steady-state laminar flow simulations are performed to obtain the velocity field, after which transient convection-diffusion simulations are conducted to evaluate species transport toward and across the membrane. The mechanical performance of the membrane is analyzed using coupled Fluid-Structure Interaction (FSI) simulations with effective material properties accounting for porosity. Three flow configurations namely coflow, counter-flow, and single-channel flow are investigated across four volumetric flow rates. The results show that both flow configuration and flow rate strongly influence concentration distributions along the membrane. Counter-flow produces the strongest axial concentration gradient, which becomes more spatially uniform at higher flow rates as convection-dominated transport increasingly governs the system. Higher flow rates also result in larger membrane deflections, with counter-flow producing deflections approximately two orders of magnitude greater than co-flow at low flow rates for both configurations. Wall shear stress increases linearly with flow rate, spanning the physiologically relevant ranges for intestinal epithelial and blood-brain barrier endothelial cells. These findings provide quantitative design guidelines for selecting flow configurations and rates based on target concentration gradients, shear stress levels, and mechanical constraints in BoC applications.

We present partially-transparent ionic polymer–metal composite (IPMC) actuators and their seamless integration into microphysiological systems, to enable dynamic mechanical stimulation of cell monolayers with direct optical access. The proposed IPMC platform employs a layered microfabrication strategy that allows precise tailoring of electrode geometry while preserving optical transparency across selected regions of the actuator. This design overcomes a key limitation of conventional IPMCs, namely their inherent opacity and resulting lack of (bio-)opto-mechatronics compatibility, thereby facilitating in vitro applications and real-time optical and fluorescent microscopy. The actuators are integrated into standard 12-well culture plates through customized mechanical and electrical interfaces and are driven by a compact, programmable electronic control system, enabling flexible modulation of actuation dynamics within biologically-relevant regimes. We confirm the biocompatibility of the platform by culturing Human Embryonic Kidney (HEK) cells and contractile cardiomyocytes from human-induced pluripotent stem cells (hiPSC-CMs). Together, these advances establish a scalable, low-voltage, and optically-compatible actuation platform for organ-on-chip and mechanobiology applications.

Monitoring of organ health and tissue damage through real-time sensing of chemical parameters such as pH and oxygen concentration could provide helpful information in the field of solid organ transplantation. Several sensors have been developed to detect oxygen concentrations and pH levels in tissues separately; however, there is no report to date on a single device in such context that can detect both pH and oxygen alterations simultaneously and in real time. This paper reports the development of a single, bi-functional optical sensor device that can simultaneously and reversibly respond to changes in both pH and oxygen concentration. The proposed optical sensor integrates both pH- and oxygen-sensitive probes, and is optimized to achieve minimal cross-sensitivity during simultaneous measurements. The sensor is excited with light of 405 nm wavelength to detect pH and oxygen changes respectively at emission wavelengths of 520 nm and 600 nm. The sensor detects pH and oxygen alterations with a response time of about 12.5 s and less than 1.5 s, respectively. The sensor exhibits a sensitivity of 75.75% for pH variations and 20.4% per mg/ml for changes in oxygen concentration. The sensor was tested on a human liver declined for transplantation to analyse the initial sensor behaviour on human tissue. Including the sensor in an organ perfusion setup to monitor pH and oxygen levels could potentially provide insight into the microcirculation of an organ before transplantation.

Dielectric spectroscopy is a label-free, non-contact, real-time, multi-layer sensing technology, and has been used for identification and quantification of many biological materials. A combination of such sensing features is in demand for monitoring of organ-on-chip systems; however available sensing technologies have yet to address this need. In this work, we explore the possibility of leveraging the inherent features of dielectric spectroscopy for the application in organ-on-chip systems, by investigating three key technological developments using open-ended coaxial probes. Firstly, biocompatible non-contact sensing capabilities are proved by showing similar sensing performance of Parylene C-coated probes and uncoated probes. Secondly, a setup and methodology are developed for highly accurate and non-destructive height positioning of the probe to allow for precise extraction of intermediate sample layers. Finally, non-contact multi-layer sensing performance of the presented technology is successfully demonstrated by means of a biological phantom in a three-layered system. With further integration, dielectric spectroscopy can potentially become a cornerstone sensing technique for organ-on-chip by enabling real-time non-contact tracking of various tissue contents and properties.

The mechanisms governing the onset and eventual progression of several neurodegenerative disorders remain poorly understood or even undiscovered. This lack of pathophysiological insight can be partly attributed to reliance on inaccurate in vitro models. Notwithstanding research efforts towards recapitulating brain functions on flat devices, mimicking the brain's three-dimensional (3D) architecture in vitro remains a prime target, as 3D models more closely resemble the functional behavior and dynamic responses of in vivo organs. In this work, we present a novel, wafer-scale approach for microfabrication of soft and transparent 3D microelectrode arrays (MEAs) for in vitro electrical recording and optical inspection of electrogenic cell cultures. The proposed 3D MEAs entail 90μ m -high polydimethylsiloxane-based micro-pyramids featuring multiple, electrically-distinct and vertically-stacked titanium nitride electrodes on their slanted facets. Our innovative 3D MEAs will facilitate the development of physiologically-accurate brain-on-a-chip models capable of monitoring 3D electrical communication in neuronal networks while allowing their simultaneous optical characterization.

Real-time pH and oxygen concentration sensing is critical for monitoring tissue damage and organ health; however, there is no report to date in such context of a single device that can simultaneously detect both pH and oxygen changes. This paper presents the development of a single optical sensor device that can simultaneously and reversibly respond to changes in both pH and oxygen concentration. The proposed optical sensor integrates both pH- and oxygen-sensitive probes, and is optimized to achieve minimal cross-sensitivity during simultaneous measurements. This approach enables high accuracy in early detection of chemical correlates of tissue or organ damage, improving screening and efficacy in organ transplants.

We present a novel silicon-based organ-on-chip (OoC) device featuring integrated microelectrodes to assess barrier function in biological tissue co-cultures. The microfluidic device consists of two vertically-stacked microchannels separated by a submicron-thin, microporous silicon nitride membrane, enabling in vivo-like proximity for co-cultured tissues. The integrated four-probe electrode geometry on slanted microchannel sidewalls ensures unobstructed optical access to the membrane and consistent measurement repeatability. Experimental validation through electrical impedance spectroscopy supported the device's sensitivity to sodium chloride concentration. Fabricated through a scalable, wafer-scale batch process, the device additionally demonstrated biocompatibility and optical transparency, representing a significant advancement for in situ tissue barrier assessments.

Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart in vitro. Currently, multiple EHT platforms are used by both industry and academia for different applications, such as drug discovery, disease modelling, and fundamental research. The tissues’ contractile force, one of the main hallmarks of tissue function and maturation level of cardiomyocytes, can be read out from EHT platforms by optically tracking the movement of elastic pillars induced by the contractile tissues. However, existing optical tracking algorithms which focus on calculating the contractile force are customized and platform-specific, often not available to the broad research community, and thus hamper head-to-head comparison of the model output. Therefore, there is the need for robust, standardized and platform-independent software for tissues’ force assessment. To meet this need, we developed ForceTracker: a standalone and computationally efficient software for analyzing contractile properties of tissues in different EHT platforms. The software uses a shape-detection algorithm to single out and track the movement of pillars’ tips for the most common shapes of EHT platforms. In this way, we can obtain information about tissues’ contractile performance. ForceTracker is coded in Python and uses a multi-threading approach for time-efficient analysis of large data sets in multiple formats. The software efficiency to analyze circular and rectangular pillar shapes is successfully tested by analyzing different format videos from two EHT platforms, developed by different research groups. We demonstrate robust and reproducible performance of the software in the analysis of tissues over time and in various conditions. ForceTracker’s detection and tracking shows low sensitivity to common incidental defects, such as alteration of tissue shape or air bubbles. Detection accuracy is determined via comparison with manual measurements using the software ImageJ. We developed ForceTracker as a tool for standardized analysis of contractile performance in EHT platforms to facilitate research on disease modeling and drug discovery in academia and industry.

It is estimated that 99 % of the world population is exposed to air pollution above air quality guidelines and this is responsible for 6.7 million premature deaths annually. Lung and skin are the first organs exposed to air pollution, and this is associated with carcinogenesis, inflammation and atopic disease. Proposed mechanisms of adverse health effects in lung and skin include oxidative stress, inflammation, and loss of epithelial barrier integrity. Most knowledge has been gained using simple 2D or more complex culture models, however these cultures have important limitations, such as a lack of perfusion and stretching and lack of cell-cell crosstalk. Organ-on-chip (OoC) technology may be used to overcome limitations of the in vitro models currently used in air pollution research and opens possibilities for studying the pathways underlying adverse health effects of air pollution on immune-mediated diseases of the lung and skin using more physiologically relevant exposure experiments. In this review we discuss currently used in vitro models to study the effect of air pollution on epithelial barrier integrity and development of immune-mediated diseases and identify gaps in current knowledge on adverse health effects of air pollution. We then focus on how OoC technology can enhance mechanistic studies of the skin and lung's response to air pollution.

In this work, we present a numerical testbench, realized in a circuit simulation environment, enabling a priori uncertainty evaluation of dielectric spectroscopy in the application field of organs-on-chip. This testbench evaluates the impact of noise, ambient temperature variation and impurity of liquid standards on the uncertainty of dielectric spectroscopy measurements. Moreover, the proposed approach allows to account for the impact on measurement sensitivity of system parameters such as probe dimensions and probe coatings. The estimated uncertainty contributions for the considered effects are compared and benchmarked experimentally. Finally, the testbench is employed to project the dielectric spectroscopy accuracy on a relevant biological application, namely monitoring the growth of a 7 μm-thick kidney cell monolayer.

We present the fluidic and electrical packaging of a novel silicon-based trans-epithelial electrical resistance (TEER) sensor chip designed for a modular and standardized organ-on-chip (OoC) platform. The package comprises three key components: the housing of the TEER chip, microfluidic routing for seamless integration with the platform, and electrical connections to a platform-integrated potentiostat. This modular solution enables continuous impedance measurements while maintaining unobstructed optical access to the tissue culture region. Experiments confirmed leak-free fluid flow across the stacked microfluidic channels and stable sensitivity of TiN electrodes to PBS. The TEER module retains optical transparency, bi-ocompatibility, and industrial scalability, supporting advanced in situ tissue barrier assessments in standardized OoC systems.