Lab on a Chip

Organ-on-chip (OoC) systems are increasingly used to generate human-relevant evidence in drug discovery and preclinical development, yet interpretation can be limited by the interaction of biological variability, device-to-device variability, and technical assay noise. Here, we describe the UstarFlowAI barrier-confidence framework, an in silico assay-readiness approach that quantifies whether a predefined permeability-related effect is resolvable under specified uncertainty. The proposed context of use is decision support for laminar, low-Reynolds-number airway epithelial monolayer barrier OoC assays in which device fabrication, pump performance, flow, wall shear stress, and biological fluctuation may affect permeability-related readouts. Monte Carlo simulations propagate defined manufacturing, biological, systemic, and well-level uncertainty and estimate the minimum detectable shift (MDS) under a prespecified decision rule. In the present proof-of-concept design, the reference workflow was parameterized at 9.4% technical coefficient of variation (CV), whereas the standardized workflow was parameterized at 5.0% CV, corresponding to an approximately 46.8% reduction in the modeled technical-noise component. At n = 48 replicate wells per group and a nominal total assay-noise operating point of 17% CV, a predefined 10% permeability shift exceeded the upper MDS uncertainty bound for the standardized workflow in both best- and worst-case scenarios, whereas it overlapped the 95% MDS interval for the reference workflow and therefore did not meet the prespecified PASS criterion. These findings demonstrate the behavior of the computational framework under the stated assumptions; they do not constitute experimental validation, regulatory qualification, or evidence that a 10% shift is universally meaningful across barrier OoC systems. We therefore propose a prospective wet-lab validation strategy in which model predictions are tested against airway barrier measurements generated under controlled sources of technical and biological variability. The framework is intended to complement, rather than replace, the underlying biological model by making assay uncertainty and decision thresholds explicit and auditable.

Fermentation is a process through which microorganisms are used to transform basic molecules into high value substances in various applications such as biopharma, food production, and biofuel generation. In such processes, monitoring the health of microbial cells is essential, as it is a key factor in the final product yield. Traditional methods of assessing the health of fermenter populations have involved manually extracting samples from the fermenter for benchtop testing, which lacked the accuracy and efficacy of real-time continuous measurements. This has opened the door for inline sensors to be integrated into fermenters for continuous measurement; including microfluidic based Electrochemical Impedance Spectroscopy (EIS). EIS utilizes a range of frequencies to gain insight into the characteristics of microbial populations, such as cell size and membrane capacitance. EIS cytometry, in particular, has emerged as a relevant tool, as it enables single-cell level detection in real-time. However, current EIS cytometry devices cannot be deployed directly within fermenters due to the high cell density conditions. This has limited EIS analysis in fermenters to bulk measurements averaged across a population. Here, we present a microfluidic chip that uses passive cell-flux-partitioning geometry to direct cells from high-density culture through a single-cell-constrained flow path containing integrated impedance-sensing electrodes. The proposed chip combines geometric channel design and embedded electrodes to enable continuous impedance measurements from cell-containing flow while operating at input cell densities on the scale of 10^9 CFU/mL. This work demonstrates a first step toward integrating single-cell-constrained microfluidic handling with impedance sensing for inline monitoring in industrial biomanufacturing.

Lymphatic endothelial cell (LEC) function is strongly tied to transitions between button- and zipper-like junctions that control fluid flow into vessels. Published methods quantifying junction morphology are limited to single cell analysis or use few quantitative metrics to describe junctions across LEC monolayers. Therefore, a novel 3-step image analysis pipeline was developed to identify new metrics that quantify differences in button- and zipper-like junctions in LECs. The pipeline used Cellpose, CellProfiler, and Fiji to analyze VE-cadherin expression across lymphatic vessels within a 3D microfluidic chip and quantify VE-cadherin radial intensity, number of objects, object size, branchpoints, end-points, and junction thickness. Tumor necrosis factor (TNF)- exposure produced but-ton-like junctions, and unexposed cells were zippered. Radial intensity was heightened at the cell membrane in zipper-like junctions while perinuclear intensity increased for but-ton-like junctions. Increased branchpoints, endpoints, objects per cell, and junction thick-ness were associated with junction buttoning, while increased object size was associated with junction zippering. Principle component analysis results reinforced these trends and identified metric combinations that represented each junctional state. Overall, this semi-automated pipeline quantified differences in VE-cadherin junction morphology across LEC monolayers and generated new quantitative metrics to expand the tools available for studying junction morphology in lymphatic vasculature.

Cell fusion enables cell-based applications, yet systematic optimization remains constrained by low throughput (microfluidic devices) and manual operation (bulk protocols). Here, an automated microfluidic platform is presented for cell pairing and chemical fusion at a statistically relevant scale. High throughput is achieved by arranging ~350,000 deformability-based cell traps as concentric circular arrays in a radial chip. Using tumor and dendritic cells as a model for cancer vaccine, the device reproducibly co-occupies ~75% of traps (~250,000) of which ~140,000 hold exactly one cell of each type. This exceeds the yield of previously reported in hydrodynamic pairing arrays by more than an order of magnitude. A concentration step-up-and-down PEG profile yielded a fusion efficiency of ~20% (range 17.7-23.4%, n =3) at viability above 90% that results in producing at least ~50,000 hybrids per chip. This efficiency is comparable to that reported for PEG-based fusion in small-scale microfluidic devices but obtained at higher throughput and approximately four-fold higher than the conventional benchtop protocol. Fusion efficiencies were quantified by image analysis and validated by flow cytometry. By combining automation, large-area circular trap arrays and reagent control, the platform is useful for data-rich optimization of cell engineering processes previously constrained by limited microfluidic throughput.

The human pancreas secretes digestive fluid that flows through an extensive ductal network before emptying into the duodenum. However, little is known about how hydrodynamic forces influence pancreatic function and development. We hypothesized that pancreatic cells respond to physiological levels of fluid shear stress. In this study, we developed a microfluidic system featuring reversible sealing between the device layer and the cell culture substrate, enabling (1) conventional open-well cell culture prior to fluid shear stress application and (2) selective patterning of proteins and cells for migration studies. Channel dimensions were chosen to support 24-hour perfusion using standard syringe pumps. Using this platform, we investigated effects of physiological shear stress levels representing basal and activated pancreatic function (2, 8 and 33 mPa) on human iPSC-derived pancreatic progenitor cells. Pancreatic progenitor cells exhibit graded sensitivity to shear stress at the transcriptomic level. Specifically, shear stress upregulated expression of cell cycle-related gene sets; endocrine-associated genes including NEUROG3; and Notch receptor ligands (DLL1, DLL3) in a magnitude-dependent manner. The exposure to unidirectional fluid flow also resulted in a reduction in YAP1 protein content, decreased WWTR1 gene expression, and downregulation of YAP/TAZ target genes. Furthermore, barrier-based migration assays under shear stress revealed that cell patches expanded their boundaries both along and against the flow, with greater distance in the direction of flow. Our system and findings may help lay the foundation for understanding biophysical regulation of developmental processes in a physiologically important, yet hard-to-access, epithelial model system.

Point-of-care (POC) molecular detection has enabled rapid and accessible testing at or near the site of need, facilitating timely decision-making in clinical, field, and industrial settings. Despite these advancements, molecular detection platforms remain limited in their ability to prepare DNA from complex tissue matrices, restricting their applicability to a narrow range of sample types. To address sample preparation inefficiencies, focused ultrasound extraction (FUSE) has been developed for the rapid release of DNA from robust tissue matrices. FUSE disintegrates target tissue and releases DNA by delivering high pressure ultrasound pulses that generate a cavitation bubble cloud. In prior work, FUSE was performed using large, laboratory-based equipment. Here, a miniaturized FUSE device was designed and tested to enable POC DNA sample preparation. Design constraints were defined based on prior FUSE experiments, and based on these metrics, a 750 kHz cylindrical transducer was fabricated. The pressure output was measured, and high-speed optical imaging demonstrated that the transducer generated sustained cavitation within the defined focal region. The feasibility of DNA extraction from piscine and timber tissues was evaluated, and results show that the device can release DNA with quality suitable for PCR-based detection from both tissue types. These results demonstrate the potential of this device to rapidly extract DNA from complex samples and expand the applicability of molecular detection platforms.

Hormone dynamics are central to a multitude of conditions in women's health; however, limitations in the cost, convenience, and multiplexing capacity of current hormone assays preclude routine longitudinal hormone testing. This limitation severely restricts our understanding in this historically neglected field, presenting a need for improved bioanalytical tools to support hormone-informed care. Silicon photonic resonator sensors have excellent multiplexing capacity and scalable fabrication, and offer strong potential to meet this important need. Here we demonstrate, for the first time, multiplexed silicon photonic detection of two urinary hormone biomarkers, follicle-stimulating hormone (FSH) and pregnanediol-3-glucuronide (PdG), using sub-wavelength grating ring resonators and a polydopamine-based, regenerable surface chemistry. We combine a sandwich immunoassay for FSH and an antigen-down competitive immunoassay for PdG on the same chip, both amplified using a commercially available quantum-dot-streptavidin conjugate and with on-chip regeneration over multiple measurement cycles. In artificial urine, this proof-of-principle multiplexed assay achieves limits of detection of 0.594 ng/mL for FSH and 19.1 ng/mL for PdG. This architecture is inherently scalable to tens of hormone targets on a millimetre-scale chip (a >10x multiplexing improvement over typical lateral-flow immunoassays) enabling future low-cost, quantitative at-home hormone panels that could transform research, diagnostics, and treatment in women's health.

Extracellular vesicles (EVs) are nanosized, lipid bilayer-enclosed particles that mediate intercellular communication and hold considerable promise as biomarkers and therapeutic agents. However, their functional heterogeneity remains incompletely understood, largely due to the absence of reliable methods for isolating specific EV subpopulations. Here, we established a Nanoscale Flow sorting (NanoFACS) workflow and evaluated its potential for EV detection, sorting, and molecular characterization. We assessed critical parameters, including fluorescent staining and labeling approaches, background signal discrimination, dilution and flow-rate effects, and scatter triggering. We achieved high-purity sorting of CFSE-stained and antibody-labeled EVs, preserving vesicle integrity and sufficient RNA yields for small RNA sequencing of sorted populations. We identified EV subtype-specific small RNAs despite partial cargo overlap in single-marker sorted populations. Our results establish a reproducible antibody-based NanoFACS workflow that defines key operational parameters for reliable EV detection and sorting, with potential adaptability across conventional and spectral flow cytometry platforms. By reducing background and non-EV-associated events, the workflow enables the isolation of phenotypically defined EV subpopulations suitable for downstream molecular analysis, providing a practical approach to investigate EV heterogeneity.

Extracellular vesicles (EV) are cell-secreted, nanosized biological particles that are involved in most physiological and pathophysiological processes. Their composition and properties reflect the pathophysiological state of the producing cell, tissue, and organ. Released into biological fluids, they may be used as a potential source of non-invasive biomarkers for diagnosis, prognosis or therapeutic follow-up in several diseases such as cancer. However, despite the development of single-EV analysis technologies, the sorting of EV subpopulations for downstream analysis remains a major challenge. Here, we describe a novel instrument that combines a highly sensitive optical detection system with an advanced lab-on-a-chip device. Using engineered fluorescent small extracellular vesicles (sEV), we demonstrate that the Hekat NanoSorter enables sensitive, scalable, and reproducible detection and sorting of individual sEVs for downstream analysis by cryo-EM. Furthermore, detailed characterization of the sorted EV populations, together with the detection of sEVs labeled with an in vitro pathophysiological marker, demonstrates the ability of the NanoSorter to monitor and enrich clinically relevant EV-associated biomarkers. These findings highlight the clinical potential of extracellular vesicle sorting for their use as biomarkers for therapeutic monitoring and treatment outcome assessment.

At-home sampling can address obstacles to participation in transcriptomics research. We previously developed the homeRNA and homeRNAmax platforms; these custom-designed tubes containing RNA stabilizer interface with a blood tube compatible with upper-arm blood collection devices, allowing for blood collection and RNA stabilization to occur from a participant's home. In this work we introduce homeRNAdrop, an insert for a commercially available blood tube (BD Microtainer) that divides the tube into two compartments: the top compartment holds 200 L blood and the bottom compartment holds ~590 L liquid stabilizer (RNAlater). By combining blood collection and RNA stabilization into the same tube, homeRNAdrop streamlines sample preparation for participants and allows for more compact sample storage for the lab. In a remote pilot study, n=25 participants from across the United States tested the homeRNAdrop kit. The n=23 samples successfully received by the lab show that samples collected using homeRNAdrop are of sufficient RNA quality (all RINs > 6, a common cutoff for analysis) and yield (mean yield=1.44 g) for downstream gene expression analysis. Almost all participants who successfully collected blood using the Tasso Mini device found the homeRNAdrop device easy to use (n=23/24). Overall, this work adds a simplified, user-friendly platform to the growing suite of tools for remote blood RNA stabilization.

Microfluidics-assisted encapsulation of cells in hydrogel microbeads has found diverse applications in tissue engineering, disease modelling, and drug testing. However, upscaled production of submillimeter-sized microbeads, each encapsulating optimally tens to hundreds of living cells, remains a challenge. Excessive viscous stresses or non-homogeneous crosslinking reactions hamper droplet monodispersity, hydrogel integrity, and/or cell viability. Herein, we present a device consisting of (i) tens of parallel step-emulsifiers arranged radially around the hydrogel inlet and (ii) an in-flow UV crosslinking system capable of continuous generation and crosslinking of up to around 45000 microbeads/min, each encapsulating N~50 cells, at cell viability exceeding 80%. We use gelatin methacryloyl (GelMA) as the biomaterial of choice and establish a unique sweet spot in terms of UV wavelength, irradiance, and exposure time- the latter controlled via the net applied flow rate and the length of the UV-exposed microchannel- at which we achieve an optimal balance between long-term microbead stability and cell viability. In particular, we observe a strong correlation between reduced cell viability and poor crosslinking efficiency, the latter attributed to the presence of a spontaneous core-shell structure. We further study the impact of added methacrylated hyaluronic acid (HAMA) and extracellular matrix (ECM) on cell proliferation and microtissue formation in the case of triple-negative breast cancer (TNBC) cells for future application in drug testing. The upscaled production of the encapsulated microtissues demonstrated here provides new perspectives for both drug testing and cell therapies where the precision in microenvironment formulation as well as production throughput remain of primary importance.

In breast cancer, collagen fiber alignment and the second harmonic generation forward-to-backward ratio (F/B), an optical measurement sensitive to fibril-scale organization within collagen fibers, have each been associated with metastatic outcome. Although both are measured at the tumor-stromal interface, in vitro studies have largely examined them separately, because experimental systems have not allowed the two to be varied independently. To address this technical gap, we used a microfluidic biofabrication approach to generate paired aligned and unaligned regions within 3D collagen hydrogels via extensional strain and varied measured F/B across gels by changing the pre-gel pH. The resulting library covered alignment values reported in breast tumors and F/B values associated with poorer metastatic outcome in invasive ductal carcinoma at matched matrix stiffness, pore diameter, and fiber fraction. In MDA-MB-231 cells, alignment biased migration along the fiber axis without changing migration speed, as expected, but the magnitude of the contact guidance response varied with measured F/B. In contrast, MCF-7 cells showed little overall contact guidance, yet migrated ~30% faster in high F/B than low F/B gels in both aligned and unaligned regions. Together, these results show that cells migrated differently in matrices with similar fiber alignment. Thus, including measured F/B may provide additional information to help anticipate how cells migrate in collagen environments that appear similar based on alignment alone.

Antibiotic resistance is an increasingly serious problem worldwide. Identifying the bacterial species can help guide antibiotic selection and improve patient outcomes. In sepsis, where every minute counts, rapid identification is particularly important, and new approaches are needed. In this study, deep learning models were trained to identify bacterial species from phase-contrast time-lapse images of cells growing in microfluidic traps, without fluorescent labels. We demonstrated this approach in two previous studies using laboratory strains. Here, the previous work is extended to clinical bacterial isolates, evaluating performance on isolates not seen during training. Furthermore, it was tested whether autofluorescence could aid species identification. Two validation sets were acquired in separate experiments from the training data, the first containing clinical-isolate traps with five species (Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae, Staphylococcus aureus and Enterobacter cloacae), imaged every two minutes, and the second containing clinical isolates of two species (E. coli and K. pneumoniae) recovered from spiked donor blood, imaged every minute. Training with the best previous CNN method achieved unsatisfactory results. Therefore, vision transformers were explored, and a self-supervised adaptation procedure was developed for pretrained DINOv3 using a frozen teacher, followed by supervised classification using time-lapse montages. Mean macro-F1 was 93.6 {+/-} 1.3% for isolates precultured in Mueller-Hinton medium using 60 frames (118 minutes) and 87.2 {+/-} 2.7% for isolates precultured in blood using 55 frames (54 minutes) (mean {+/-} sample standard deviation across training seeds). Performance was evaluated over time by increasing the number of frames available to the model during testing, and Fourier-domain filtering approximated reduced numerical aperture. The results are promising and suggest that the aperture can be decreased while retaining good results. However, further evaluation on independent isolates, experiments and patient samples is needed to establish generalization. Together with previous findings, these results bring us closer to rapid image-based diagnostics that could transform the initial treatment of acute bacterial infections by enabling better-informed antibiotic selection.

Oxygen (O2) transport is a major limitation in high-density cell culture, particularly as three-dimensional (3D) spheroids are increasingly used to better mimic in vivo tissue environments. Here, we developed a poly(4-methyl-1-pentene) (PMP)-based microwell platform, leveraging its lower molecular absorption and greater mechanical stability than the commonly used O2-permeable polydimethylsiloxane (PDMS), while retaining high O2 permeability. We measured O2 permeability in 50-m-thick PMP membranes and found approximately 200-fold greater O2 permeability than the conventional 1-mm polystyrene culture-plate material. PMP membrane-based microwell plates with 350-m-diameter wells maintained spatial separation of pre-formed hepatocyte spheroids while supplying O2 from the plate bottom, synergistically enhancing spheroid oxygenation. Compared with non-O2-permeable plates, the platform reduced localized hypoxia and hypoxia-associated cell injury while improving spheroid viability and growth. Collectively, PMP-based O2-permeable microwell plates provide a promising, scalable, high-throughput platform for spheroid culture with multiple applications in tissue engineering, drug screening and beyond.

Engineered cardiac and skeletal muscle tissues suspended between flexible posts support disease modeling and pharmacology, yet their stimulation, longitudinal imaging and quantitative analysis often remain fragmented and labor-intensive. Here we present Stimulatrix, an open-source platform integrating automated video acquisition within a cell culture incubator, synchronized electrical stimulation and deep learning for longitudinal assessment of contractile tissues in multiwell plates. The platform quantifies tissue compaction, force generation and contraction kinetics with optional cloud processing reducing dependence on local GPU hardware. We demonstrate the workflow in cardiac tissues comprising human induced pluripotent stem cell-derived cardiomyocytes and cardiac fibroblasts, and in primary human skeletal muscle constructs. Force and kinetic measurements were benchmarked against manual annotations. Longitudinal profiling resolved responses to matrix composition and pacing regimens and tracked doxorubicin-associated loss of cardiac contractile force. Stimulatrix provides an accessible workflow for automated functional phenotyping of engineered muscle tissues.

Continuous biomarker monitoring with affinity biosensors remains limited by probe saturation, slow dissociation, signal carryover, and regeneration methods that require chemical washing, harsh buffers, or external reset modules. Here, we report a flow-programmed, self-regenerative electrochemical aptamer-based biosensor for continuous 17{beta}-estradiol monitoring. The platform restores the sensing interface by tuning buffer flow through the device, enabling repeated sensing-regeneration cycles without chemical stripping or active-reset hardware. The biosensor achieves a 1.46 pM limit of detection, and a log-linear dynamic range from 100 pM to 1 M in real human sweat, covering physiologically relevant estradiol concentrations. It exhibits high selectivity, with responses to potential molecularly similar interferents remaining below 10% of the 17{beta}-estradiol signal. Under dynamic flow operation, the device shows reversible signal recovery and stable electrochemical performance, with higher buffer-wash flow reducing baseline carryover between measurements. A coupled binding-transport simulation captures the flow-dependent regeneration trends and maps how wash-flow rate, wash duration, and apparent aptamer affinity affect regeneration efficiency. Ex vivo testing in real human sweat, including samples from pregnant women, supports translational relevance. This work establishes buffer-flow programming as a reagent-free route to regenerable electrochemical aptamer sensing for automated, wearable-compatible estradiol monitoring.

Biofilm mechanics depend strongly on growth history, hydration, nutrient availability, and interfacial attachment, yet conventional rheology requires harvesting and transfer that can perturb the as-grown structure. Here, we introduce bioRheoFlow, a 3D-printed rheometer-mounted platform for cultivation and mechanical characterization without sample transfer. The platform combines evaporation compensation with static or axial nutrient flow, and benchmark measurements validate its rheometric performance. Applied to Pseudomonas putida and Pantoea sp., bioRheoFlow reveals that biofilms cultivated in situ under axial flow exhibit substantially higher elastic moduli than conventionally grown and scraped samples. Despite similar linear-viscoelastic stress ranges, the species show distinct nonlinear responses: P. putida exhibits a lower crossover stress and more abrupt failure, whereas Pantoea sp. sustains larger stresses and deformations. Creep suggests contributions from bulk deformation and biofilm-substrate interactions. bioRheoFlow provides a controlled framework for probing growth-conditioned mechanics in living biofilms.

Emerging efforts to engineer multicellular kidney tissues for drug discovery, disease modeling, and therapeutic repair require scalable generation of kidney organoids derived from human induced pluripotent stem cells (hiPSCs). Here, we report a method for generating kidney ureteric bud and collecting duct epithelial organoids in stirred tank bioreactors. We demonstrate that extracellular matrix microcarriers facilitate organoid expansion and are compatible with suspension bioreactor methods. The combination of cell-coated matrix microcarriers with stirred bioreactors promotes maturation marker expression compared to static controls comprising matrix-embedded organoids. Our method offers promise for generating epithelial organoids that serve as multicellular models and organ building blocks for scalable biofabrication.

Advanced in vitro models that better recapitulate human intestinal physiology are needed to improve translational relevance and reduce reliance on animal experimentation. Microfluidic gut-on-chip systems provide controlled architectural and mechanical microenvironments that more closely resemble native tissue than conventional static cultures. However, how these features influence epithelial responses to microbial stimuli remains incompletely understood. In this study, we compared conventional two-dimensional (2D) Caco-2 monolayers with a perfused three-dimensional (3D) gut-on-chip model exhibiting crypt-like epithelial organization. Microbial challenge was employed as a biologically relevant perturbation to investigate barrier-associated responses under distinct culture conditions. Following exposure to the probiotic Escherichia coli Nissle 1917 (EcN), epithelial morphology, barrier-associated gene expression, inflammatory signaling, and temporal response patterns were assessed over time. In a complementary approach, susceptibility to bacterial stress was examined using increasing doses of Citrobacter rodentium (C. rodentium). Both culture systems responded dynamically to microbial exposure; however, differences in response patterns were observed between static and perfused cultures. EcN induced transient alterations in epithelial organization followed by recovery-associated responses, while C. rodentium caused dose-dependent structural and transcriptional changes. Notably, epithelial damage became apparent at lower bacterial loads in conventional 2D cultures, whereas the chip-based model maintained tissue integrity under comparable conditions. Together, these findings indicate that epithelial architecture and the surrounding culture environment influence barrier-associated responses to microbial challenge. The study highlights the utility of gut-on-chip systems for investigating host-microbe interactions and provides a framework for functional comparison of advanced intestinal in vitro models.

Digital micromirror device (DMD)-based bioprinting enables high-resolution fabrication of hydrogel-based tissue constructs, but print fidelity and hydrogel mechanics are typically coupled through polymer concentration, light exposure, and crosslinking density. This creates a materials constraint for vascular bioprinting, where constructs must preserve microscale architecture during fabrication while supporting multicellular remodeling, lumen formation, and long-term tissue organization. To meet these requirements, we developed a 4D GelMA-Cad/gelatin hydrogel with time-dependent mechanics that maintains print fidelity while providing a soft, cell-permissive matrix. GelMA-Cad provides a covalently photocrosslinked, bioactive network containing an N-cadherin-mimetic peptide, while uncrosslinked gelatin serves as a transient matrix-modifying component that diffuses from the hydrogel after fabrication, producing further softening without bulk degradation of the GelMA-Cad network. We characterized hydrogel chemistry with NMR, quantified time-dependent changes in stiffness, visualized pore morphology with cryo-SEM, and evaluated the platform in retinal and pulmonary constructs. The 4D hydrogel supports 3D-patterned accuracy, cell viability, inner blood-retinal barrier vasculature, and vascularized lung-alveolar tissue models. Single-cell RNA-sequencing of the pulmonary vascular-alveolar model demonstrated compartment-specific transcriptional responses, including enrichment of lung capillary-associated endothelial features and AT1-like epithelial states. Overall, this platform decouples DMD print fidelity from post-print matrix mechanics for vascularized soft tissue bioprinting and tissue modeling.