Lab on a Chip

Sensitive and low-cost protein biomarker detection is critical for disease diagnosis. Advanced microfluidic systems can generate miniature reaction compartments for a high-sensitivity assay. However, these platforms often require external instruments, skilled operators, and complex setups. Here, we develop a Lab on a Capillary (LabCap) platform that integrates photopatterned hydrogel rings within a glass capillary using a reconfigurable stop-flow lithography system. During sample loading and unloading steps, nanoliter-scale aqueous droplets (torodrops) are spontaneously formed around the hydrogel rings, creating isolated reaction compartments without the need for external instruments or an immiscible oil phase. The LabCap platform enables quantitative detection of clinically relevant biomarkers, including C-reactive protein (CRP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP). By adjusting the incubation protocol, assay speed and sensitivity can be tuned to meet different analytical requirements. A periodic medium exchange protocol enables biomarker detection at concentrations as low as 1 ng/mL, whereas prolonged static incubation extends detection to 0.1 ng/mL. In addition, LabCap offers practical advantages, including low fabrication cost (< EUR 1 per device), low reagent consumption (<100 microlitres per assay step), and minimal wash-buffer usage (1 mL). These results demonstrate that LabCap is a simple, cost-effective, and versatile platform for biomarker detection.

We demonstrate a new sample-loading strategy ('spot-loading') for Spores-on-a-Chip microfluidic sensors that enables multiplexed experimentation. The previous limitation of one biological sample per device is overcome through controlled sample loading at an intermediate step of the chip fabrication process. As a proof-of-concept, we use dual spore chips to compare the germination behaviours of two spore strains in two distinct microenvironments.

Isothermal nucleic acid amplification tests enable rapid and decentralized molecular diagnostics but often lack robust quantitative readouts compared to quantitative PCR. Here, we present a semi-quantitative nucleic acid measurement approach using machine learning to extract spatiotemporal features from real-time fluorescence imaging of rapid isothermal amplification reactions in microfluidic chips. A convolutional neural network was trained on multiple images sampled throughout a chip-based recombinase polymerase amplification reaction to classify samples into clinically relevant or logarithmically spaced concentration ranges spanning five orders of magnitude. The clinical classification model achieved 94.6% accuracy, and the logarithmic model achieved 92.7% accuracy, with most errors occurring between adjacent concentration categories. By learning spatiotemporal patterns of fluorescence development rather than relying on explicit feature extraction, the model remained accurate at both high and low nucleic acid concentration regimes where other quantitative isothermal molecular tests struggle. This approach enables automated interpretation of amplification reactions and extends the usable dynamic range of the assay. These results demonstrate that integrating machine learning with image-based amplification methods can support rapid semi-quantitative molecular testing and may facilitate broader deployment of nucleic acid diagnostics outside centralized laboratory settings. Author summaryMany rapid nucleic acid testing methods for infectious diseases are simple to run but struggle to measure how much genetic material is present, which limits their usefulness in clinical decision-making. In our work, we study a technique that produces visible fluorescent patterns during nucleic acid amplification reactions. Traditionally, the amount of nucleic acids present are measured by counting individual bright spots, but this becomes difficult when the target nucleic acid concentration is high and the spots merge together. We developed a machine learning approach that models how the fluorescence pattern changes over time. By analyzing a sequence of images from each reaction, our model can assign samples to concentration ranges across a wide span. This allows us to extract meaningful information even when traditional analysis methods break down. Because this approach works with simple imaging systems and does not require complex equipment, it could help support more informative and accessible diagnostic testing in point-of-care and low-resource settings.

Intestinal organoids are powerful in vitro models, but their use in large-scale analyses remains constrained by the low throughput, labor-intensive handling, and high reagent consumption of conventional Matrigel dome culture. Here, we present Organoid-in-Bead (OrB), a vortex-based compartmentalization workflow that partitions organoid fragments into thousands of discrete Matrigel microbeads, enabling scalable, high-density culture from a single batch preparation. OrB maintains dome-comparable organoid growth and epithelial polarity, supports passaging-based culture expansion, yields more than 5,000 organoids in the final 10 cm dish format, and reduces Matrigel and medium consumption by approximately 70% on a per-organoid basis. OrB therefore provides a practical and scalable upstream workflow for generating screening-scale intestinal organoids. HighlightsO_LIOrB generates Matrigel microcompartments by vortexing without microfluidics C_LIO_LIOrB enables scalable, high-density intestinal organoid culture in one batch C_LIO_LIOrB maintains dome-comparable growth and epithelial polarity and supports passaging C_LIO_LIOrB yields >5,000 organoids per batch with [~]70% less Matrigel/medium per organoid C_LI

Adoptive T-cell therapies rely on the identification and expansion of rare tumor-reactive T cells, yet current enrichment strategies are limited by the low abundance of these cells and complexity of their functional enrichment. Here, we present a microfluidic platform that exploits hydrodynamic shear as a controllable parameter for enriching antigen-specific T cells through peptide-major histocompatibility complex (pMHC)-mediated capture. An eight-channel microfluidic device was engineered to simultaneously interrogate a range of wall shear stresses while maintaining uniform cell delivery, enabling systematic identification of shear conditions that maximize antigen-specific enrichment. Using engineered MART-1-specific Jurkat cells, we demonstrate that T-cell capture is jointly regulated by wall shear stress and pMHC density, with intermediate shear preferentially enriching antigen-specific cells over nonspecific binders. Translation of the optimal operating condition to a high-throughput single-shear device enabled approximately 35-fold enrichment of antigen-specific T cells from peripheral blood mononuclear cells containing only 0.05% target cells. We further show that peptide-MHC complexes isolated directly from melanoma whole-cell lysates support shear-dependent enrichment comparable to recombinant pMHCs. Finally, primary MART-1-specific CD8 T cells enriched using tumor-derived pMHCs retained the ability to recognize melanoma cells and upregulated the activation marker CD137 following antigen-specific stimulation. Together, these findings establish hydrodynamic shear as an orthogonal parameter for antigen-specific T-cell enrichment and provide a framework for integrating force-based selection with tumor-derived pMHCs to isolate functional antigen-specific T cells using tumor-derived pMHCs.

Chronic infections persist in large part thanks to protection that biofilms afford their bacterial creators. The extracellular polymeric substance of biofilms is a hydrated matrix of DNA, polysaccharides, and structural proteins, amongst other components, through which nutrients, signalling molecules, and antimicrobial agents must diffuse to reach the bacteria within. Quantitative measurement of transport on the nanoscale within in vivo biofilms remains challenging due to optical heterogeneity, autofluorescence, active remodelling of biofilms and the ambiguity in trajectory reconstruction during single-particle tracking (SPT). Here, we present a methodological framework for measuring molecular transport in defined minimal extracellular matrix models using quantum dots as fluorescent nanoscale probes imaged with high-speed SlimVar microscopy. To establish conditions in which high-diffusivity particle trajectories can be reliably reconstructed, upper limits to quantum dot concentrations were estimated from Brownian motion. The 99th-percentile inter-frame jump distance was estimated from the three-dimensional Brownian jump distance distribution and used to define a target average nearest neighbour distance, and therefore a per-particle volume, used for calculating a concentration which minimises the probability of trajectory collision during data acquisition. Quantum dot movement was imaged at sub-millisecond frame rates and diffusion coefficients were calculated in a 20% glycerol control and in DNA nanostar hydrogels modelling minimal extracellular matrix scaffolds assembled at 250 M and 500 M. Median diffusion coefficients decreased from 94.9 m2*s-1 in glycerol to 15.9 m2*s-1 and 8.3 m2*s-1 in the 250 M and 500 M hydrogels, respectively. More broadly, this work establishes a workflow for quantitative SPT in minimal biofilm models. Rather than attempting to reproduce the full biological complexity of native biofilms, this approach provides the basis of a modular experimental framework in which individual extracellular matrix components can be incorporated sequentially and their effects on molecular transport quantified.

Control of fluids is a hallmark of microfluidic systems and fundamental for the successful application of microfluidic devices. Trigger valves use geometric features to autonomously control the release of fluids in microfluidic devices. Our previous work has adapted geometries used in closed trigger valve systems to enable use in open systems, allowing for open microfluidic devices with up to three trigger valves. Here, we focus on the parallel co-flows produced by sequential release of trigger valves and present a model that predicts their layer widths as a function of the geometric characteristics of the different side channels of each trigger valve. We show layered co-flows with widths as low as 50 microns. Additionally, we expand the use of trigger valves in open microfluidic devices by incorporating 1) varied step heights, 2) devices with up to seven trigger valves, and 3) use of varied fluids and plastics. To validate the implementation and use of these trigger valves in open systems, we have developed a theoretical framework to compare predicted outcomes (i.e., fluid travel distance, velocity, and layering width) with our experimental values. This theoretical work offers applications in various fields, including hydrogel patterning for 3D cell culture, organ-on-a-chip models, at-home sample preparation, and autonomous microfluidic systems for biosensing.

Neurological disorders are a major cause of death and disability worldwide. The brain's energy metabolism is essential to its proper function, yet the mechanisms driving neuroenergetic dysfunction remain poorly understood. A key challenge is the limited availability of human-relevant models that can reproduce the complexity of brain physiology. An Organ-on-Chip (OoC) system was developed to mimic the neurovascular unit metabolic coupling by incorporating human isogenic iPSC-derived endothelial-like cells, pericyte-like cells, astrocytes, and a cerebral organoid, representing the main cellular components of the NVU. The novel, customized microfluidic platform enables research on neurovascular coupling by interconnecting a blood-brain barrier-on-a-chip model with a 3D brain parenchymal compartment to mimic physiological conditions.

Despite major improvements in molecular characterization of breast cancer, current biomarkers still fall short in accurate treatment prediction. Interrogating tumor tissue ex-vivo in its native conformation is a direct strategy for guiding treatment of individual patients but presents a challenge. In this study, we developed a microfluidic tissue array (FTA) using small biopsy samples (< 1mm3) mimicking physiological flow for consistent exchange of nutrients and waste, retaining the tumor native stroma. Cell/patient-derived breast cancer xenograft tissues were maintained over 2 weeks in the array and their response to therapeutic agents, doxorubicin or neratinib, were interrogated. Drug response in the uFTA showed >2-fold reduction in tumor cell viability which corroborated tumor size shrinkage in mice bearing the same tumor load. EdU/Ki67 assays indicated selective retention of cells with higher proliferative capacity after drug treatment, underscoring in vivo clinical relevance . We have also developed a valved-FTA to increase throughput and variety of treatment conditions on the same chip. Together, this FTA can be staged as a powerful, low-cost benchtop theranostic tool for personalized cancer therapeutics compatible with FDA New Approach Methods.

The increasing prevalence of neurological disorders highlights the need for human in vitro systems that recapitulate key mechanisms of neurodegeneration and neuroinflammation. Although induced pluripotent stem cell (iPSC)-derived organoids and spheroids have advanced structural modelling of the human brain, platforms capable of robustly capturing neuronal electrophysiology in 3D remain limited. Here, we present a neuro-microphysiological system (NeuroMPS) that combines iPSC-derived neurospheres with tailored microelectrode arrays to enable non-invasive, high-resolution monitoring of neuronal network dynamics and functional maturation in vitro. Human iPSC-derived neurospheres, comprising neurons and glial cells, developed synchronous network activity after six weeks of differentiation. The NeuroMPS integrates two key components: a custom microelectrode array with capped electrodes optimized for neurite-level signal detection, and a glass microwell module providing structural confinement and optical compatibility for imaging. This configuration supports stable, longitudinal electrophysiological recordings from three-dimensional neural constructs and enables multimodal analyses. We evaluated platform performance using pharmacological modulators (PTX, TTX, bicuculline, CNQX and 4-AP) and the neurotoxin rotenone through electrophysiological recordings, morphological assessment and metabolic activity profiling. Alterations in network activity were detected within minutes, including at the lowest concentrations tested, whereas corresponding morphological and metabolic changes emerged only at higher doses and later time points. These findings demonstrate the greater sensitivity of electrophysiological readouts in 3D neuronal cultures and their potential for early prediction of compound-induced effects. Collectively, our results establish NeuroMPS as a physiologically relevant, scalable and non-invasive platform for functional interrogation of human iPSC-derived neural networks, with applications in neuropharmacology, neurotoxicology and disease modelling.

High-risk neuroblastoma patients face poor survival despite intensive treatment. Drug testing using patient-derived models can support therapy prioritization for precision medicine and drug development. Models incorporating tumour microenvironmental components, such as co-cultures and short-term cultured patient samples containing substantial non-malignant cell fractions, could better recapitulate microenvironment-dependent drug responses. However, conventional viability assays measure the combined signal from all viable cells in a well and therefore cannot determine tumour-specific drug responses. Here, we establish a microscopy-based readout to quantify cell-type-specific viability in two complementary settings: neuroblastoma-PBMC co-cultures and freshly dissociated patient tumour samples. In the co-cultures, PBMCs were pre-labelled with a cell-tracking dye, and Calcein staining was used to independently quantify the viability of tumour cells and PBMCs in the same well. The Calcein-based viability readout correlated strongly with conventional CellTiter-Glo measurements and was compatible with automated high-throughput drug screening. The imaging workflow enabled identification of compounds with differential efficacy in co-culture versus monoculture and distinguished tumour-specific effects from PBMC toxicity. The microscopy-based viability readout was further adapted to short-term cultured patient samples. Neuroblastoma tumour cells were distinguished from the non-malignant cells using a combination of tumour-specific surface markers NCAM, L1CAM and B7H3. This enabled determination of tumour fractions and measurement of tumour-specific drug responses. Tumour fractions varied substantially between patient samples, highlighting the importance of tumour-specific viability measurements. Together, the microscopy-based viability readout for co-cultures and patient samples enables scalable assessment of tumour-specific drug responses.

High content imaging is being applied to achieve quantitative fluorescence readouts in increasingly complex 3-dimensional (3D) cell culture models such as spheroids and organoids. Compared to conventional 2D assays, 3D assays better represent biological heterogeneity but require more complex sample preparation, 3D imaging and 3D image analysis that can affect the accuracy and precision of such assays. We used spheroids formed from the NRAS-activated melanoma cell line 19161 modified to express an ERK kinase translocation reporter (KTR) as an exemplar 3D phenotypic assay carried out in 96-well plates. The spheroids were treated with the ERK activator TPA and a range of concentrations of the MEK inhibitor Binimetinib. 3D live-cell imaging with sub-cellular spatial resolution was performed using a dual-view oblique plane microscope (dOPM) - a form of single-objective light-sheet microscope - and the experiment was performed separately at 4 different institutes. The results were analysed using an identical 3D analysis pipeline and parameters. We assessed the variation in assay readout using a linear mixed effects model. Random variance at the well level was negligible (SD = 0.0048 relative to range of KTR biosensor readout at reference site of 0.17), indicating low technical noise. Treatment effects were dose-dependent and highly statistically significant compared to DMSO control across all sites (Dunnett-corrected p < 0.001). The range in KTR readout between the minimum (3.5 M Binimetinib) and maximum (100 nM TPA) treatments varied between 59 to 96% relative to the reference site. Measured bias in KTR readout between sites was between 6 and 12% of the range of the reference site. This study quantifies the reproducibility of a 3D live spheroid-based assay employing a fluorescence biosensor requiring readout out at the per-cell level using the dOPM platform and discusses areas where experimental protocol could be improved in the future to further improve reproducibility.

Rapidly detecting infectious diseases such as Covid-19 is essential to control outbreaks and treat patients early. However, no available screening method combines low cost, portability, speed (<20 min, ideally <5 min), and ultrasensitivity (e.g., <1 virus/L): lateral flow assays are fast, portable, and inexpensive but insensitive, whereas ultrasensitive assays require centralized labs with long turnaround times. We recently developed an ultrasensitive immunoassay that captures, separates, and counts saliva biomarker molecules using buoyant microbubbles and magnetic microspheres, but the original assay took 55 minutes and was not readily deployable. Here, we redesigned the assay protocol and reader for emergency medicine and mobile care by streamlining the workflow, collecting saliva with larger swabs, filtering it through a 10 m cap, and using larger microbubbles to accelerate flotation. A paramedic successfully ran the assay on the back of a parked medical van in 3.5 minutes (spit-to-results) while achieving a 1.3 fg/mL analytical detection limit for SARS-CoV-2 nucleocapsid protein (~0.04 virus1/L). The assay remained positive across 9 orders of magnitude. We describe the challenges and opportunities ahead for point-of-care deployment.

Optogenetic control enables light-actuated regulation of gene expression and provides a programmable interface between living cells and electronic systems. However, routine prototyping of optogenetic constructs remains limited by infrastructure. Existing closed-loop platforms often require chemostats, microfluidics, robotic handling, or custom optical sensors, which can increase cost, reduce accessibility, or constrain measurement performance. Here, we present LEMOS 2.0, an updated LED-Embedded Microplate for Optogenetic Studies, a low-cost device for optogenetic stimulation and gene-circuit characterization inside standard off-the-shelf microplate readers. LEMOS 2.0 builds on the original LEMOS platform by increasing throughput from 16 to 32 microwells and reducing light leakage between adjacent microwells, allowing dark conditions to be used as an additional illumination state. The device consists of a 3D-printed frame, individually addressable LEDs positioned next to each microwell, a rechargeable battery, and an onboard microcontroller for Bluetooth-based wireless communication. Biocompatible polydimethylsiloxane microwells are cast directly into the device by replica molding, allowing bacterial cultures to be stimulated while optical density and fluorescence are measured by the microplate reader. This protocol describes the full LEMOS 2.0 workflow, including device fabrication, circuit assembly, Arduino programming, PDMS microwell casting, plate-reader setup, strain and culture preparation, automated experiment execution, device cleanup, and fluorescence/OD600 data analysis. As a demonstration, the protocol uses the CcaSR optogenetic system, in which sfGFP expression is activated by green light and repressed by red light. LEMOS 2.0 is intended to make optogenetic perturbation and gene-expression characterization more accessible to wet-lab users, enabling faster design-build-test-learn cycles without requiring specialized bioreactor or microfluidic infrastructure.

Accurate and decentralized quantification of serotonin, also known as 5-hydroxytryptamine (5-HT), in biological fluids is critically important for the diagnosis, prognosis, and therapeutic monitoring of neurological and psychiatric disorders. However, conventional analytical methods generally rely on centralized laboratory infrastructure, skilled personnel, and labor-intensive sample processing, which restrict their applicability in rapid near-patient and point-of-care settings. Herein, we report a portable molecularly imprinted polymer (MIP)-based electrochemical sensing platform for selective and on-site detection of serotonin using screen-printed carbon electrodes (SPCEs). The biomimetic recognition interface was fabricated through direct electropolymerization of a polydopamine recognition layer in the presence of serotonin as the template molecule, followed by template extraction to generate complementary recognition cavities for selective rebinding. The sensor fabrication parameters, including monomer concentration, electropolymerization cycles, template-to-monomer stoichiometry, and electrolyte pH, were systematically optimized to achieve improved sensitivity, selectivity, and signal stability. Under optimized conditions, the MIP/SPCE sensor exhibited a broad linear response from 10 pM -10 uM in phosphate buffer, with a correlation coefficient of R2 = 0.974 and an ultralow limit of detection of 0.16 pM. The analytical applicability of the platform was further validated in spiked artificial serum, where the sensor achieved an LOD of 0.12 pM, satisfactory recovery values of 88.66-96.02%, and acceptable precision with RSD values [&le;] 8.43% (n=3), confirming its reliability in a complex biological matrix. The developed sensor demonstrated excellent selectivity toward serotonin against physiologically relevant interferents, maintaining signal retention between 99% and 101%. In addition, the platform showed high operational repeatability with an RSD of 0.45%, good inter-electrode reproducibility with an RSD of 6.3%, and long-term storage stability, retaining 90-110% of its initial response over 28 days. Importantly, cross-platform validation using a smartphone-coupled potentiostat demonstrated strong analytical agreement with laboratory-grade instrumentation, as evidenced by R2 = 0.9967 and a slope of 1.023. These findings establish the proposed MIP/SPCE platform as a simple, low-cost, portable, and smartphone-compatible electrochemical device for field-deployable serotonin monitoring in clinically relevant samples.

Automated platforms such as Chi.Bio enable simultaneous monitoring of optical density and fluorescent reporter expression in 20 ml reactor cultures with controllable pump systems. As such, they provide an appealing option for contemporary gene expression quantification, quantitative physiology, and laboratory evolution and ecology experiments. While optical density calibration for this device is well established, no equivalent calibration framework exists for fluorescence, making quantitative comparison with reference instruments unreliable. Here, we characterize Chi.Bio fluorescence capabilities using fluorescent calibration microspheres and fixed GFP-expressing S. cerevisiae and E. coli cells, compared with orthogonal plate-reader measurements. We show that microsphere fluorescence is detectable and scales linearly with concentration, whereas the GFP signal from both species falls below the device detection limit. Comparison of background-correction strategies indicates that direct subtraction of a non-fluorescent control measured within the same device yields more reliable fluorescence estimates than the commonly used on-line normalization method. Knowledge of these sensitivity boundaries of the device provides practical guidelines for experimental design of future studies.

Modelling human cortical microcircuitry in vitro requires platforms that recapitulate both the compositional complexity and spatial architecture of developing neural tissue. Current organoid and assembloid models often rely on the bulk fusion of pre-differentiated, region-specific cells, lacking the capacity for emergent spatial co-differentiation and microenvironment-driven multiscale organisation. There is also a lack of neural and neuronal-glial models with photo-architectured network geometries. To address these limitations, we present a volumetric in situ differentiation system using a triculture of precision reprogrammed human iPSC-derived glutamatergic neurons, GABAergic neurons and astrocytes embedded throughout ultra-soft photocrosslinkable hydrogel microenvironments. The deterministic and spatially controlled method allows us to engineer macro-scale, interconnected human neural networks directly onto functional microelectrode array interfaces using projection photopatterning for high-throughput screening. Unlike fusion-based organoids and assembloids, our platform enables simultaneous, spatially distributed lineage differentiation and maturation, and extensive topography-guided neurite outgrowth bridging localised cellular hubs to recapitulate various aspects of neurodevelopmental patterning and synaptic integration in 3D. The model enables topographic patterning of neuronal-glial networks as well as 3D cell-embedded bioprinting with the developed triculture system. Both modes of cellular growth are studied and demonstrated here. Longitudinal electrophysiological tracking over a month of culture reveals a transition from immature, quiescent states to asynchronous, information-dense microcircuits characterised by an expanded state-space manifold and physiological excitatory-inhibitory balance. By replicating the mechanics of native brain parenchyma, the model presents a highly reproducible, scalable and flexible platform for the study of cortical microcircuitry development, neurodegenerative decline, and inter-regional network assembly.

Engineered epithelial models require three-dimensional extracellular matrix environments that support organized cell growth and allow independent access to luminal and basal compartments. However, many organ-on-chip (OoC) fabrication strategies rely on planar geometries, non-native materials, or multi-step assembly workflows that limit architectural complexity and experimental control. Here, we report a direct in-chip volumetric printing strategy for fabricating stretchable and perfusable collagen-I scaffolds inside custom OoC devices. A vitamin C-regulated ruthenium/sodium persulfate photocrosslinking system enabled high-fidelity printing of collagen-I into open-lumen architectures with ductal- and alveolar-inspired features. By generating scaffolds directly within the final culture device, this workflow eliminates post-print transfer and integrates defined collagen architectures with compartmentalized fluidic access and a mechanically actuable chip format. To support chip-based culture, printed collagen constructs were stabilized after fabrication using EDC/NHS chemistry, which limited thermally induced collagen densification, improved shape retention, and maintained scaffold anchorage during perfusion. The chip design provided separate access to the printed lumen and surrounding basal compartment, which enabled compartment-specific fluid handling while preserving scaffold integrity during inflation, stretching, and perfusion of the printed construct. On the collagen-I scaffolds, human milk-derived mammary epithelial cells formed epithelial layers with tight junctions and lactation associated markers. The platform further supported perfusion culture, in situ staining, and whole-chip volumetric imaging. Together, this work establishes direct in-chip collagen-I volumetric printing as a biofabrication strategy for creating perfusable epithelial tissue chips with native matrix architecture and compartmentalized fluidic control.

Mechanical forces have a major effect on cell behavior. Most cells in vitro are grown under static conditions on hard tissue culture plastic, conditions that do not accurately reflect living tissues. The ability of cells to sense and respond to mechanical forces is essential for key biological processes, including development, proliferation, and migration. Disruption of the ability to respond to mechanical forces are known to be a critical factor in many diseases, including cardiovascular disease, progeria, and cancer. Here, we present the design, fabrication, and biological testing of a custom-built cell-stretching device that applies controlled biaxial strain to cells cultured on a polydimethylsiloxane (PDMS) membrane. We then used this device to examine how cells respond to strain. In response to biaxial strain, MCF-7 cells activated the mechanosensitive immediate early gene (IEX-1), with its expression increasing significantly after 1 and 3 hours of stretching. Cells exposed to mechanical strain also remodeled their cytoskeleton in a direction-dependent manner. Under uniaxial strain, actin filaments reoriented perpendicular to the stretch direction, whereas biaxially stretched cells do not promote directional reorientation, but instead appear to reinforce actin at the cell periphery. Similarly, cells under uniaxial strain exhibited changes in nuclear orientation and shape that were not observed under biaxial strain. Nuclear area remained unchanged in either strain condition. These results highlight that the biaxial stretcher can be used to apply strain to cells, and that cells respond differently to biaxial strain compared to what has been reported for uniaxial strain.

Flow imaging microscopy (FIM) is an important technology for high-throughput characterization of microscopic particles and microorganisms. However, conventional FIM relies on single-plane imaging (SPI), resulting in out-of-focus particles, reduced measurement precision, and incomplete characterization of irregularly shaped objects extending along the z-axis. To address these limitations, a volumetric flow imaging (VFI) framework was developed and implemented on the portable ARTiMiS platform. This approach captures multiple frames along the z-axis and extracts the highest fidelity image for each particle, which can also be used for single image generation with all particles in focus (i.e., all in focus image) and for three-dimensional reconstruction of irregularly shaped objects. Benchmarking VFI with microspheres, live cells (Chlorella vulgaris), and filamentous cyanobacteria demonstrated increased fraction of particles in focus, reduced variability in particle size measurement, and increased resolvability of elongated particles in comparison to conventional SPI on commercially available FIM technologies. For C. vulgaris, VFI-derived size distributions closely matched curated FlowCam measurements without requiring post-processing to exclude out-of-focus particles. All-in-focus image reconstruction enabled simultaneous visualization of particles distributed across multiple depths and consistently resolved a greater proportion of filamentous structures as compared to SPI. For Aphanizomenon sp., Dolichospermum sp., and Planktothrix agardhii, the SPI approach captured only 84%, 61%, and 58%, respectively, of the total filament length resolved by AIF reconstruction. Beyond image-based characterization, VFI enabled estimation of dynamic particle properties such as sinking velocity and mass density. Application of this framework to C. vulgaris cultures revealed distinct mass-density trajectories under nitrogen-replete and nitrogen-deplete conditions, with cell mass density increasing over time under nitrogen-replete conditions and decreasing under nitrogen deprivation. Collectively, these results establish VFI as a next-generation framework for FIM that expands its analytical capabilities beyond conventional morphometric characterization and provides new opportunities for single-cell-enabled environmental monitoring and biomanufacturing.