APL Bioengineering

Cell mechanics can serve as an important biomarker for cell state and phenotype, such as metastatic ability. While some molecular mechanisms underlying cell mechanical properties have been investigated through targeted analyses, a genome-wide study of human genes and gene networks that modulate cell biophysical properties has not been attempted. In this work, we combined a microfluidic stiffness-based sorting device with a genome-scale CRISPR knockout (GeCKO) screen in order to investigate the effect of individual gene knockouts on cell stiffening and cell softening across the entire protein-coding genome. We processed approximately 150 million Cas9-expressing ovarian cancer cells that had been transduced with a library of 76,000 single guide RNAs (sgRNAs) against the 19,000 protein-coding genes in the genome. The cells were sorted into 5 mechanical subsets. We identified 7 gene knockouts that were significantly depleted in the softer subsets and over 700 gene knockouts that were significantly enriched in the stiffer subsets. Of these significant genes of interest, we selected 3 genes that were highly expressed in our ovarian cancer cell line with greater than 100-fold enrichment in the stiff outlet and resulted in significant changes in ovarian cancer patient survival. These genes, PIK3R4, CCDC88A, and GSK3B, when knocked out result in a significant and predicted increase in cell stiffness. This study is the first to explore the relation between human gene expression and cell mechanics at the genome-scale to generate datasets at the intersection between cell genotype, mechanotype, and phenotype for metastatic cancer cells. The method could also be applied to study the effect of genes on other biophysical cell processes as well as for identifying pathways for the control of cellular mechanics across many cell types.

Colorectal cancer (CRC) is the second most common cause of cancer-related mortality. At the molecular level, CRC is associated with genetic mutations and epigenetic modifications that dysregulate various signaling networks. From the biophysical viewpoint, invasive and metastatic cell migration need to be empowered by mechanical forces. In this study, we analyze the dynamic deformation of patient-derived CRC organoids in Fourier space and demonstrate how organoids with protooncogene BRAF mutation exhibit deformation phenotypes at an early stage. The organoids with BRAFmut have significantly lower elasticity and higher viscosity than those with BRAFWT, which mathematically indicated as the weakening of cell-cell adhesion. Immunohistochemical images, qRT-PCR, and TCGA data analysis confirm the downregulation of E-cadherin (CDH1) in BRAFmut organoids as well as in BRAFmut CRC, suggesting that the decrease in cell-cell adhesion in BRAFmut CRC facilitates invasive and metastatic migration. Notably, the recovery of CDH1 expression by pharmacological inhibition of DNA methylation can quantitatively be detected as the change in mechanical properties, suggesting that the complementary combination of dynamic phenotyping, mathematical modelling, and molecular-level analyses has a potential to unravel the mechanistic causality of the critical gene mutation and CRCs prognosis and the response to therapeutic interventions.

Mechanical homeostasis indicates the remarkable ability displayed by cells in tissues to maintain their mechanical properties near a stable homeostatic set-point. Experimental investigations and theoretical studies indicate that mechanical stress represents a key homeostatic target that stromal cells, such as fibroblasts, seek to maintain by tuning the intracellular structure and by remodeling the extracellular matrix. Much of what is known about mechanical homeostasis of tissues under tension, or tensional homeostasis, is based on experiments on tissue equivalents, that is fibroblast-populated collagen gels. However, existing platforms used to investigate tensional homeostasis cannot infer mechanical stress dynamically. Here we developed an integrated biomechanical bioreactor combining force sensing with confocal microscopy to dissect the mechanobiological mechanisms of tensional homeostasis. We used our novel platform to test the hypothesis that fibroblasts maintain a constant state of stress across varying collagen concentrations. Contrary to this assumption, synchronized force and imaging measurements revealed that stress is not constant but rather elevated at low collagen concentrations, where fibroblast contraction drives earlier collagen fiber alignment and greater tissue compaction. Conversely, force generation and -SMA expression increase with increasing collagen concentration, accompanied by modest transcriptional changes. However, at the highest collagen concentration, this homeostatic balance is disrupted, with lower force generation and -SMA expression, as gene expression shifts toward VEGFC-mediated autocrine survival signaling. These findings demonstrate that tensional homeostasis emerges from a dynamic balance between cellular contractility and extracellular matrix densification rather than stress maintenance, and reveal that excessive matrix density disrupts this balance by triggering a pro-survival response.

Understanding how cells migrate in response to external cues has important implications for biology, medicine, and bioengineering. Chemical, mechanical, and electrical signals are the primary drivers of directed cell migration, and each has been extensively studied over the past decades. Among them, chemical cues were the first to be investigated and remain the most widely studied due to their undeniable role in in vivo guidance. Mechanical signals--particularly substrate stiffness gradients--have gained prominence for their ubiquity across cell types and their potential to direct migration. More recently, growing evidence suggests that electrotaxis offers a highly precise and programmable means to guide cell movement. Despite this, these cues are often studied in isolation, whereas in vivo they typically coexist and interact. Using wellestablished biophysical models, we investigate how mechanical and electrical signals cooperate and how they can be engineered to compete for control over cell migration. We demonstrate that an electric field can override and even reverse durotaxis, with outcomes that depend strongly on the specific cell type. To address this large variability in controlling cell migration, we propose particular steps toward further exploration. To support such future research, we provide a freely available platform for predicting electro-mechanical interactions in cell migration, based on a given cells sensing and signaling characteristics, which could tailor the mechanical and electrical signals that arise naturally during organ development, cancer invasion, or tissue regeneration.

Recent research has emphasized the critical role of cell state transitions in tissue homeostasis. In lung biology, transitional cells are recognized as a feature of tissue-scale processes during both normal physiology and disease. The precise way that transitional cell states emerge and are regulated remains to be determined. Engineered tissues, built in a laboratory through bioengineering approaches, allow detailed study of cellular states that are not commonly found in native biology, and allow opportunities to directly induce and manipulate cellular transitions. The following study explores and characterizes epithelial cell states that emerge via cellular reprogramming in a tissue engineering context. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/701406v1_ufig1.gif" ALT="Figure 1"> View larger version (68K): org.highwire.dtl.DTLVardef@1d456f3org.highwire.dtl.DTLVardef@1989ba5org.highwire.dtl.DTLVardef@127dd7org.highwire.dtl.DTLVardef@3dd7a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Scaling up microvessel culture systems is essential for producing vascularized clinically relevant tissues, yet current platforms offer little guidance on how to preserve flow conditions during scale-up. Here, we present a computational-experimental framework using computational fluid dynamics (CFD) to guide the design and scaling of microvessel bioreactors. Interstitial flow distributions were pre-dicted in two perfusion-based platforms-a permeable insert and a rhomboidal microfluidic chamber-across multiple scaling factors and hydrostatic pressures. CFD identified IF ranges conducive to vascu-logenesis and quantified how geometry and pressure modulate flow uniformity. Scaled-up bioreactors generated microvessel networks with consistent morphology and connectivity over a 30-fold increase in culture volume, confirming that maintaining equivalent IF ensures reproducible outcomes. The permeable insert platform maintained uniform IF across scales, while the rhomboidal chamber produced spatially varying IF resulting in heterogeneous but physiologically relevant networks. These findings establish CFD as a predictive tool for rationally scaling perfusion bioreactors, enabling microvessel production at clinically relevant scales with controllable morphology. Significance StatementScaling up microvessel bioreactors is critical for engineering large pre-vascularized tissues. However, larger scales may disrupt flow conditions that drive vessel formation. This study demonstrates that computational fluid dynamics (CFD) can predict interstitial flow and guide the rational scale-up while preserving the vasculogenic microenvironment. Experiments across 30+-fold size increase confirmed that matching inter-stitial flow results in morphologically identical microvessel networks. By linking simulation-based design with experimental validation, this work establishes CFD as design tool for scalable perfusion bioreactors for production of microvessel networks at clinically relevant scales.

The extracellular matrix (ECM) plays a pivotal role in lymphatic vasculature physiology, yet the specific contribution of individual ECM components to lymphatic endothelial permeability remains poorly understood, limiting the development of physiologically relevant in vitro models for lymphatic disease research and therapeutic development. Here, we used an in vitro transwell platform to systematically investigate how four clinically relevant ECM proteins, collagen I, fibronectin, fibrin, and laminin, regulate human lymphatic endothelial cell (LEC) barrier function and junctional integrity. Fibrin and collagen I substrates enhanced barrier integrity, demonstrating 80% and 67% increases in transendothelial electrical resistance (TEER), respectively, compared to uncoated controls. FITC-dextran transport assays confirmed these findings, with fibrin and collagen I reducing permeability by 20% and 10%, respectively. Immunofluorescence analysis revealed elevated ZO-1 expression on fibrin, fibronectin, and laminin matrices, while VE-cadherin levels remained unchanged across conditions. Quantitative junctional analysis demonstrated that fibrin increased ZO-1 junction continuity by [~]35%, while collagen I and fibronectin enhanced continuity by [~]22%, with all ECM coatings reducing discontinuous junctions by 60-80%. Mechanistically, RhoA expression was reduced in LECs cultured on fibrin, suggesting decreased stress fiber formation contributes to enhanced barrier function, though overall actin cytoskeletal anisotropy remained unchanged. These findings demonstrate that ECM composition modulates LEC junctional organization and barrier integrity, with fibrin and collagen I exerting the most pronounced barrier-enhancing effects. This engineered platform provides a foundation for developing next-generation in vitro models of lymphatic vasculature that more accurately recapitulate physiological conditions, with applications in lymphedema research, cancer metastasis studies, and immune cell trafficking investigations.

It has been broadly recognized that the crosstalk between cells and their extracellular matrix (ECM) is crucial for the proper function of biological tissues. Relatively recently the role of ECM came in focus in the context of neuronal development and regeneration, where the effects of the ECM mechanics on the migration of neurons and neurite growth are still incompletely understood. Here we present an in silico twin framework for neurite growth focusing on its biophysical interactions with the ECM. This coarsegrained model accounts for viscoelastic liquid- and solid-like ECMs and neurite growth by ECM-mediated traction forces. Resulting growth trajectories can be rationalized based on the theory of random walks and polymer physics. To critically assess models predictive power, we performed experiments on neurites of hippocampal rat neurons growing in 3D collagen gels and observed a more persistent axon outgrowth in denser matricies. The model fully recapitulated the effect, thereby underpinning the central role of mechanical interactions with ECM as guiding principle of axonal growth. We argue that a combination our model with optical microscopy may provide an is silico twin helping to disentangle the contributions of "passive" physics from more complex effects of chemical queues or an apparent mechanosensing.

As cell imaging grows in scale, precision, and complexity, data integration and harmonization become increasingly important for studying cell-material interactions. Quantitative understanding of how cells respond to mechanical cues, such as substrate stiffness and topography, is often limited by differences in experimental conditions and imaging formats. This study presents a framework that combines compact, interpretable cell shape models with generative artificial intelligence to harmonize 2D and 3D immunofluorescent datasets within defined experimental contexts. By efficiently capturing morphology and associated biological features, the approach enables generation of realistic synthetic cells, including rare or intermediate phenotypes, to augment machine-learning analyses and support scalable in silico studies. This work advances data-driven investigation of cellular responses to biomaterial-derived mechanical cues.

Most cellular therapies, like CAR T cells, remain ineffective in solid tumors. This is primarily due to a complex tumor microenvironment (TME), which creates biochemically hostile and often immunosuppressive conditions that limit efficacy of immunotherapies. Besides, cellular therapy efficacy is still often established in traditional 2D cultures that fail to simulate relevant aspects of solid tumor biology. Recent advances in three-dimensional (3D) and organ-on-chip culture systems have provided more physiologically relevant models for immunotherapy testing. These microphysiological systems (MPS) not only offer a 3D environment that alters tumor cell sensitivity to therapy but also enable inclusion of TME components and assessment of processes such as extravasation and infiltration, key steps in CAR T cell activity in vivo. This study focuses on applying an advanced culture technique and further building on the use of a scalable on-chip platform, the OrganoPlate, to grow EpCAM-positive and EpCAM-negative tumor cells in co-culture with an endothelial vessel to study EpCAM-targeting CAR T cell migration and killing kinetics. The CAR T cells specifically targeted and killed EpCAM-positive HT-29 tumor cells while EpCAM-negative A375 tumor cells were not affected. In addition, target cell killing was dependent on the ratio between CAR T and tumor cells (E:T ratio) and was enhanced by addition of IL-2. Inflammatory cytokines like INF-{gamma}, TNF and IL-6 increased overtime in cultures containing CAR T cells. Morphometric analyses of the endothelial compartment showed E:T ratio dependent disruption of endothelial vessels. Additionally, this system was able to distinguish EpCAM ScFv-CD28-CD3z and EpCAM ScFv-TM-4-1BB-CD3z CAR T cells killing abilities and was used for studying the effect of immune checkpoint inhibitors and Temozolomide, a DNA targeting drug, on CAR T cell performance. Altogether, this work adds to the available advanced culture techniques for immunotherapy developers by describing a model that is modular, scalable, and suitable for phenotypic and functional characterization of CAR T cells.

Maintaining a confluent, antithrombotic endothelium on cardiovascular biomaterial surfaces remains a major barrier to long-term hemocompatibility, as endothelial cells (ECs) rapidly denude under supraphysiological shear in prosthetic devices. Here, we hypothesized that mesoscale surface geometry ([~]100-200 {micro}m) could reorganize near-wall hemodynamics, preserving endothelial coverage and function under extreme shear. Engineered microtrenches were introduced onto an implant biomaterial to generate spatially defined shear environments. Under supraphysiological near-wall shear ([~]250 dyn/cm{superscript 2}), microtrenched geometries created attenuated shear and vorticity gradients. Endothelial monolayers were sustained in these flow domains for 120 hours, whereas flat controls rapidly denuded. Endothelial retention in 22.5{degrees} angled trenches increased dramatically, from an EC of 33 to 101 dyn/cm{superscript 2}. 45{degrees} angled trenches further increased endothelial shear resistance to an EC of 207 dyn/cm{superscript 2}. Endothelial monolayers demonstrated collective mechano-adaptation to ultra-high shear through VE-cadherin junction thickening and coordinated cytoskeletal and nuclear alignment. Mechanoadapted monolayers exhibited increased eNOS expression correlated with local shear and elevated nitrite production (45{degrees}: 50.4 {+/-} 6.1 {micro}M; 22.5{degrees}: 35.7 {+/-} 3.3 {micro}M; 0{degrees}: 28.4 {+/-} 6.8 {micro}M). In contrast, interfaces with abrupt shear transitions or elevated rotational flow exhibited reduced coverage, junctional thinning, and re-emergence of VCAM-1 and PAI-1, indicating inflammatory and pro-thrombotic activation. Structural, functional, and inflammatory readouts exhibited peak responses within a shared shear-vorticity regime. Multivariate regression identified shear-vorticity coupling as the dominant predictor of endothelial persistence, with optima clustering within a mechanical range ({approx}0.8-2.9 x 10 dyn{middle dot}cm-{superscript 2}{middle dot}s-{superscript 1}). These findings establish geometry-driven modulation of near-wall flow as a predictive, material-agnostic strategy for endothelialization and vasoprotection of high-shear cardiovascular implants.

Currently in vitro models of microvascular biology rely on self-assembly of vascular cells in compatible gels. However, the stochastic nature of this process results in large variations in lumen sizes, perfusion continuity, and shear stresses making systematic and reproducible analysis challenging. Here, we report a new technology to generate artificial capillaries on a chip with custom control over lumen sizes and architectures using a combination of femtosecond laser cavitation and collagen casting within multi-chambered microfluidic chips. The design allows seeding of endothelial cells within capillary-sized microchannels and seeding of stromal cells within top-open silos, with independent control over seeding sequence and media compositions. Results show that endothelialized microchannels, coined as artificial capillaries, exhibit excellent barrier function with reproducible control over lumen sizes ({phi}=8-35{micro}m) and their architectures (straight, curvatures, tapered, branched). The physical flow parameters measured across the lumen (namely, flow shear) and at the channel outlets (flow velocities) have been validated against high-fidelity numerical assessments from the Large Eddy Simulation scheme within the digitized versions of the microchannels. The experiment-computation compatibility enabled us to predict changes in regional velocity and wall shear stresses within artificial capillaries, for various capillary architectures. We also show that in situ editing of artificial capillaries in the form of adding new branches or adding occlusions is possible. Lastly, we developed a co-culture model which enables the study of stromal cells with artificial capillaries using conventional imaging methods. We envision that acellular chips with two seeding ports can be readily shipped worldwide and could potentially be adopted as a new technology to study microvascular biology in a reproducible manner.

Neurons in the brain are organized and connected into complex networks in which electrochemical signaling forms the basis for all brain function. Cortical neuronal net-works are arranged in distinct modular, layered, and hierarchical structures, underlying its diverse functions such as learning, memory, or vision. Modern biotechnology has enabled an array of techniques to culture human neural cells, ranging from discreet co-cultures to complex developmental organoids, but all of which almost exclusively form unstructured and hypersynchronous networks. Overcoming this and capturing the functional and anatomical properties of the brain in vitro has proven to be a great challenge. Current techniques for guiding neuronal connectivity in vitro is often limited to a small fraction of the total population of neural cells, leaving most of the culture effectively unguided. To provide large-scale guidance of neurons in culture, we developed a microtunnel device which allows large-scale cell entry through an array of perforations, and guides neuronal network formation through a series of tunnels. Human neural stem cells capable of forming extensive neuronal projections were used to investigate several different microtunnel designs. One particularity noteworthy design which produced predominantly unidirectional growth was used to successfully validate its effect on propagation of neural activity on microelectrode arrays. Serendipitously, we found that our microtunnels had an extraordinary effect on signal-to-noise ratio and the quality of electrophysiological recordings with regards to number of active channels and detected spikes. Since we often found the neuronal growth surprising, we developed a simple computer model which could reproduce neuronal growth in the various tunnels, allowing computer aided design (CAD) of future projects.

Caveolae, flask-shaped membrane invaginations highly enriched in endothelial cells, play a central role in buffering membrane tension, yet the principles governing their spatial organization remain elusive. This investigation sought to generate the most comprehensive and systematic analysis of blood vessel caveolar spatial organization. To do so, our group leveraged micropatterning technologies to impose precise biophysical constraints on endothelial cell geometry to probe how caveolae are organized under defined tensional and polarity environments. These experiments were integrated with a high-throughput spatial cell mapping computational pipeline for analyzing thousands of caveolae, providing an extremely high-fidelity analysis. Our results provide a governing framework of how total cellular caveolae are spatially organized during random and directional migration, non-motile polarized, nascent and stable monolayers with differing confinement levels as well as in angiogenic vasculature in vivo. Broadly, our results demonstrated caveolae preferentially organized in the rear of migrating and polarized endothelial cells. In differing monolayer configurations, caveolae default to a peri-junctional spatial organization. Lastly, in mouse retinal blood vessels caveolae are most prominent in the vascular front due to their responsiveness to vascular endothelial growth factor signaling. Overall, these results strongly suggest that caveolae cellular arrangement and number are highly predictive of vascular stability and remodeling states.

Elastic and viscoelastic properties of extracellular matrices (ECM) are known to regulate cellular behavior and mechanosensation differently, with implications for morphogenesis, wound healing, and pathophysiology. Most in vitro cellular processes, including cell migration, are studied on linear-elastic substrates to mimic extracellular matrices. However, most tissues are viscoelastic and display a loss modulus (G) that may be 10-20% of their storage modulus (G) under biophysically relevant conditions. Recent research has shown that cells can distinguish between elastic and viscoelastic ECM, leading to alterations in their cellular morphology, migration rates, and contractility. Here, we present a protocol for creating PAH-based model ECMs that enables the fabrication of viscoelastic substrates with storage moduli similar to those of their elastic counterparts. To explore how G influences epithelial cell mechanobiology, we fabricated tunable viscoelastic model ECMs with G of 3 kPa, 8 kPa, and 12 kPa, and for each, independently tuned G values to approximately 300 Pa, 500 Pa, and 700 Pa, respectively. We found that A549 cells cultured on stiff elastic model ECMs migrated [~]30% slower and formed larger focal adhesions compared to their viscoelastic counterparts. Conversely, A549 cells on intermediate viscoelastic model ECMs exhibited a [~]54% reduction in migration speed, with no significant difference in focal adhesion size relative to their elastic counterparts. These findings highlight the complex interplay between substrate (ECM) elastic and viscoelastic properties in regulating epithelial cell mechanobiology and emphasize the importance of time-dependent matrix mechanics in governing epithelial responses.

Precision-cut lung slices (PCLS) retain the native cells and extracellular matrix that contribute to the structural and functional integrity of lung tissue. This technique enables the study of cell-matrix interactions and is particularly useful for pre-clinical pharmacological studies. More specifically, PCLS are widely used to model the complex pathophysiology of pulmonary fibrosis, an uncurable and progressive interstitial lung disease. Current ex vivo pulmonary fibrosis models expose PCLS to pro-fibrotic biochemical cues over a short timeframe (hours to days) and quickly collect samples for analysis due to viability concerns. This condensed timeline is a limitation to understanding chronic disease mechanisms. To extend the utility of ex vivo pulmonary fibrosis models, PCLS were embedded in engineered hydrogels and exposed to pro-fibrotic biochemical and biophysical cues. Hydrogel-embedded PCLS maintained greater than 80% total cell viability over 3 weeks in culture. Gene expression patterns in samples exposed to pro-fibrotic cues matched trends measured in human fibrotic lung tissue. Finally, treatment with Nintedanib, a Food and Drug Administration approved pulmonary fibrosis drug, moderately reduced fibroblast activation and influenced epithelial cell differentiation. Collectively, these results show that hydrogel-embedded PCLS models of pulmonary fibrosis extend our ability to study fibrotic processes ex vivo and, when applied to human tissues, present a new approach methodology for studying lung disease and treatment.

Glioblastoma (GBM) lethality arises from aggressive invasion and diffuse infiltration of brain tissue. Conventional GBM preclinical models often fail to predict clinical therapeutic efficacy because they do not recapitulate the pathological extracellular matrix (ECM) cues that drive tumor invasion. Here, we present an ECM mimetic 3D platform using a fibrin scaffold to recapitulate the hemorrhagic, pro-thrombotic tumor microenvironment characteristic of high-grade gliomas. This fibrin scaffold induces a pro-invasive phenotype in GBM spheroids by upregulating proliferation/cell cycle- (MYC, FOXOM1, CCND1) and invasion-associated-(CTSS, FOXM1, CCND1) genes. Traditional cell morphology quantification methods (e.g., circularity) distil complex shapes into singular metrics and cannot capture the nuances of invasion. To address this limitation, we have applied a deep-learning segmentation pipeline (MARS-Net) and high-content morphodynamic descriptors. By using the Preserving Heterogeneity (PHet) algorithm, the 3D platform accurately classifies invasiveness levels and captures the invasion-inhibitory effects of potential repurposable drug candidates. We demonstrate that our model can predict a spheroids long-term invasive fate with high accuracy using only partial image sets from early time-points, rather than the complete time-course images. Our work presents an in vivo-like, scalable 3D platform integrated with a quantitative high-throughput pipeline to elucidate GBM invasion mechanisms and to evaluate anti-invasive compounds.

We present an automated framework to generate 1 demographically stratified virtual populations of abdominal aortic aneurysms (AAAs) and to quantify anatomy-flow relationships via an in silico observational study. Using 258 CTA-derived cases, we generated 182 validated AAA geometries and ran 364 simulations, extracting 11 geometric descriptors and six haemodynamic biomarkers. The automated constraint-aware framework blends statistically grounded sampling, anatomical plausibility and regional morphing to provide a scalable route for reproducible CFD to uncover geometry-biomarker relations at cohort scale. The proximal neck diameter was the strongest determinant of shear, increasing mean WSS (r {approx} 0.77) and peak WSS0.95(r {approx} 0.58) while reducing low-TAWSS area (r {approx} -0.36). Maximum diameter minimally affected peak shear (r {approx} -0.03) but led to moderate increase of low-TAWSS regions (r {approx} +0.20). Compactness indices suppressed oscillatory shear; sphericity and convexity, largely under-explored AAA shape descriptors, showed strong inverse correlation with OSI (r {approx} -0.68, -0.65) and mean WSS (r {approx} -0.47, -0.59). The framework reveals neck calibre and shape compactness, not maximum diameter alone, as dominant modulators of AAA haemodynamics. Subject Areasfluid mechanics, biomechanics, biomedical engineering

Hematogenous metastasis is initiated when tumor cells (TCs) intravasate into the vasculature, yet intravasation remains poorly understood because it is difficult to observe in vivo and intravasated TCs are challenging to isolate. To address these challenges, we developed IntravChip, a continuously perfused microfluidic platform containing a vascularized primary tumor microenvironment (TME) enabling the observation of TC intravasation, and a downstream chamber to collect intravasated TCs. The IntravChip can support a high TC concentration in the TME while maintaining complete vascular perfusion, which we found was necessary to collect intravasated cells. Using MDA-MB-231 breast TCs, we identified an optimal initial TC seeding density that, by day 9, yields a densely populated TME and 100-440 collected intravasated TCs. We validated the IntravChip across several TC types, showing that MDA-MB-231 and MV3 TCs have the highest intravasation rates while MCF-7 TCs have low intravasation efficiency. We also show that the IntravChip is compatible with super-resolution nano-imaging. Our devices enabled high-quality STORM imaging, which revealed that H3K9me3 nanodomains are significantly differentially distributed in intravasated MDA-MB-231 tumor cells compared to those residing in the TME. Finally, the IntravChip was validated as a platform to test the effects of anti-cancer drugs on tumor cells and on the vasculature. We showed that a 5 M concentration of sorafenib reduced intravasation events by 69% without impacting the morphology of the microvascular networks (MVNs), while a 10 M concentration led to a significant decrease in vessel diameter. This platform enables quantitative analysis of TC intravasation, collection of intravasated TCs for characterization, and screening of anti-metastatic therapies.

It is increasingly necessary to both study biology in 3D and obtain quantitative measurements. Not all 3D-reconstructions are created equal, particularly when using the anatomical model as a basis for force calculations, i.e. computational modeling. Here, we compare 3D anatomical reconstructions from two emerging imaging modalities: 4D ultrasound (4DUS) and light sheet fluorescent microscopy (LSFM) against our previous nano-computed tomography (nanoCT) cohort data, using the tortuous highly intricate pharyngeal arch artery system of the chick embryo as a test bed. We highlight modality-specific morphological image acquisition discrepancies and their influence on subsequent computational fluid dynamics results. Overall, LSFM accurately captured quantitative volumetric measurements of small rapidly-changing vascular morphologies while 4DUS systematically inflated small tortuous vessels. Differences in image-based morphology changes led to significant changes in computationally-obtained force magnitudes and flow patterns linked to vessel angle and tortuosity. This validates LSFM as a comparative preclinical vascular quantitative imaging tool and suggests that 4DUS needs extensive 3D anatomical validation for non cardiac chamber vessels.