Small Methods

Capturing fast hemodynamics in deep organs is essential for understanding microvascular regulation of organ responses to physiological demands and pathological stress. However, non-invasive three-dimensional (3D) imaging of these microscale processes remains challenging due to trade-offs between spatial resolution, imaging speed, and penetration depth. Here, we present fluctuation-based high-order super-resolution acoustic microscope (FLAME), a tracking-free 3D ultrasound imaging technology capable of fast microvascular angiography and flow measurement. Using as few as 30 volumes, FLAME improves 3D ultrasound resolution by 8-fold (~50 m) and shortens data acquisition time by over two orders of magnitude, from tens of seconds to tens of milliseconds, compared with conventional tracking-based super-resolution approaches1-6. This high-throughput capability supports high-fidelity imaging of tissue functions under flexible experimental settings. FLAME achieves an unprecedented 3D super-resolution frame rate of ~40 Hz, capturing transient hemodynamic responses to various physiological and pathological stimuli in different mouse organs, from the microvascular level to the whole-body scale. With open-sourced implementation, FLAME provides an accessible platform for real-time, in-depth hemodynamic monitoring across diverse biomedical applications and clinical translation.

Fluorescence microscopy is routinely used in the quantitative analysis of Giant Unilamellar Vesicles (GUVs) because it makes GUVs visible and easy to detect. Nonetheless, it requires fluorescence-equipped microscopes and, especially, the addition of tagged molecules that may introduce undesired and unaccounted variations compared to the pristine formulation. Alternatively, phase-contrast microscopy can be used to observe GUVs without labelling, yet the automatic detection of GUVs in phase-contrast images by standard image processing techniques is difficult. To overcome this limitation, we developed a framework for the automated detection and size characterization of label-free GUVs based on YOLOv11 model, a state-of-art lightweight Convolutional Neural Network (CNN) for object detection. Trained on 164 phase-contrast microscope images containing 4666 manually annotated vesicles, the model enables robust detection under low contrast-to-noise ratio and heterogeneous illumination. The trained model is implemented in a stand-alone desktop application supporting multiple analysis in a single run, pixel-to-micrometer calibration, and automated size distribution analysis. This approach achieves high detection accuracy and competitive cross-microscope generalization using YOLOv11 nano on greyscale image. Retraining scripts compatible with standard hardware are also provided to enhance adaptability. This tool enables fast and reliable analysis of GUVs without altering their composition, supporting experimental reproducibility.

Adoptive cellular therapies can be effective against solid tumors but rely on the identification and expansion of rare tumor-reactive T cells (TRTs). Here, we utilize antigen-presenting cell-mimetic scaffolds (APC-ms), a modular biomaterial platform that presents defined peptide-HLA and co-stimulatory ligands on a fluid lipid bilayer to selectively recover rare antigen-specific T cells from peripheral blood. Independent variation of peptide-HLA, co-stimulatory ligands, and cytokine support defined a formulation that enriched MART-1-specific T cells to above 2% of CD8+ T cells in 35 of 50 HLA-A*02:01+ healthy donors from low or undetectable baseline frequencies. Compared with mo-DCs, APC-ms achieved greater fold expansion of MART-1-specific T cells with increased functional avidity and preservation of an early differentiation phenotype, and generated a higher number of MART-1-specific clonotypes. In five of eight patients with treatment-naive melanoma, APC-ms could enrich MART-1-specific T cells to a median of 13.7% of CD8+ cells (range 0.30 - 57.2%) Moreover, APC-ms could expand T cells specific for an HLA-A*24:01-restricted personal neoantigen that were previously undetectable in peripheral blood of a patient with melanoma. These findings establish APC-ms as a tunable platform for the recovery of rare TRTs from peripheral blood, supporting its further development for therapeutic TCR discovery and personalized adoptive cell therapy.

Extracellular microRNAs (miRNAs) contribute to metastasis through communication between tumour cells and their microenvironment, yet their sustained, sequence-selective depletion remains challenging. Here we report Programmable RNA-Intercepting Molecular Eraser (PRIME), a membrane-anchored DNA nanomachine that organizes miRNA recognition and catalytic degradation at the cell surface. A double-tetrahedral DNA scaffold positions a programmable recognition hairpin beside RNase H. Target binding generates an RNA/DNA hybrid for RNase H-mediated cleavage, and product release resets the hairpin for subsequent degradation cycles. Membrane-anchored PRIME depleted matched extracellular miRNAs by 70.6-89.4% across lung, breast and cervical cancer cell models. Multi-target PRIME (M-PRIME) inhibited migration by 71.3-96.0% in Transwell assays across these models. To evaluate its therapeutic potential, we established an orthotopic lung-tumour model and an early-intervention breast-cancer lung-colonization model in mice. Aptamer-directed M-PRIME combined with gemcitabine reduced pulmonary tumour burden by 74.5% in established lung tumours and 93.2% in the lung-colonization model. These effects were consistent with PRIME-mediated extracellular miRNA degradation, with circulating target miRNA levels reduced by 77.5-98.7% relative to gemcitabine alone. Together, these findings establish a programmable material strategy for sustained extracellular RNA depletion and support its potential to enhance chemotherapy in preclinical tumour models.

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.

Microlasers based on whispering-gallery modes (WGMs) provide bright, spectrally narrow emission, making them ideal optical probes for high-resolution cellular tagging, single-cell tracking, and biosensing. To reproducibly apply WGM microlasers in biomedical or tissue-engineering contexts, control over the number of lasers in a cell population is highly desirable. Here we use a commercial instrument for flow cytometry-based cell sorting to obtain HEK293T cell populations with a controlled number of polystyrene laser particles (LPs). By modifying the particle surface with poly(ethyleneimine) (PEI) or lipofectamine, we enhance LP-association to cells. We demonstrate that our sorting procedure yields viable cells showing unchanged proliferation rates. Manufacturer-dependent differences in particle-cell interactions were observed and investigated by scanning and transmission electron microscopy (SEM/TEM) and flow cytometry. Finally, we show that the same sorting approach enables the generation of multi-cellular spheroids with a defined ratio of LP-containing and LP-free cells. This work lays the foundation for larger tissue engineering studies with defined LP populations and control over LP-placement with respect to the cell.

Gas-bubble-enhanced focused ultrasound (FUSGB) is advancing clinically across a myriad of applications, including targeted drug delivery through transient blood-brain barrier opening (BBBO). Its broader translation requires a better understanding of the bioeffects that enable reproducible enhancement of barrier permeability while avoiding vascular injury, underscoring the need to clarify the relationship between acoustic exposure, bubble activity, and the biological response central to treatment optimization. These interactions are difficult to isolate in vivo, and acoustic reflections, geometry, and field distortion in conventional cultureware hinder quantitative in vitro studies. Herein, we present a theoretically and experimentally characterized ultrasound-transparent organ-on-chip device with >99.9% US transparency that enables quantitative in vitro modeling of the FUSGB procedure and study of BBBO. Furthermore, submicron bubbles (sMB, ~800nm) were fabricated and characterized. Acoustic dose-dependent subharmonic and broadband cavitation dose curves (SCD and BCD), as well as temporal responses, were studied. A 3-day accelerated Caco--2 surrogate barrier with a high TEER (~1200xcm2) was used to demonstrate US dose-dependent targeted barrier opening, visualized using an in vitro Evans Blue assay. Together, this study and its findings establish a foundation for quantitative in vitro modeling of FUS BBBO, as well as other US interactions in microphysiological systems, supporting systematic evaluation of procedural regimens, large-parameter-space optimization, acoustic safety window, and exposure conditions for brain drug delivery, and additionally enabling mechanistic insight into FUSGB BBBO.

Macromolecular release from synthetic cells often relies on membrane pores or channels. We explored whether internally generated osmotic stress could increase membrane permeability and promote release. Using double-emulsion microfluidics, we encapsulated an Escherichia coli cell-free expression system in Pluronic L121 polymersomes to co-express the fluorescent protein mScarlet3 and the dextranase PsDex1711 in the presence of dextran. PsDex1711-mediated dextran hydrolysis produced a greater increase in bulk osmolality than reactions without PsDex1711 DNA. Tracking hundreds of individual polymersomes showed that PsDex1711-containing populations expanded, whereas control populations contracted. The distribution of normalized fluorescence revealed a subset with lower residual fluorescence than the main population. In selected expanded polymersomes, integrated internal mScarlet3 fluorescence declined to 18-22% of peak levels, without visible membrane disruption, consistent with protein release. These findings support a proof of concept for using internal gene expression to promote macromolecular release through osmotic actuation without introducing dedicated membrane pores.

Nanobubbles (NBs) have been widely investigated as ultrasound contrast and therapeutic agents, yet whether submicron gas bubbles can directly generate measurable ultrasound signals remains controversial. Because acoustic scattering scales with bubble size, several studies have recently attributed nanobubble echogenicity primarily to larger bubbles. A recent Science Advances publication, attributed the loss of ultrasound signal after filtration to the removal of residual larger bubbles [1]. This interpretation assumes that filtration acts solely as a size-selection process. Here, we show that filtration also alters the shell properties and stability of lipid-coated NBs, independent of size. Filtered NBs (F-NBs) show significant lipid loss and accumulation on the filters themselves, resulting in decreased bubble stability and greater susceptibility to destruction under acoustic excitation. To decouple size from processing effects, we generated NB populations size-matched to filtered samples using increased centrifugation (IC-NBs), a comparatively gentler separation method. Despite comparable size distributions, IC-NBs retained sustained ultrasound scattering, whereas filtered NBs showed significantly reduced acoustic persistence. Filtration through 5 m pores, ~5-fold larger than the largest bubbles, preserved acoustic persistence but still reduced bubble concentration by ~30%, suggesting that membrane contact may contribute to bubble loss beyond size exclusion. Complementary lipid and gas-content assays provided further evidence of filtration-induced changes. The 0.45 m filtration removed substantially more total lipid than could be attributed to free-lipid removal alone, while the lipid associated with the larger bubbles removed during filtration accounted for only ~5% of the additional lipid loss. Encapsulated gas content remained comparable to that of size-matched centrifuged controls, suggesting that the reduced acoustic stability of filtered NBs is more closely associated with changes in lipid content than with loss of the gas core. These results indicate that membrane filtration is not a purely size-selective process: it removes substantially more lipid than size exclusion predicts and yields bubbles that are less stable under ultrasound, most likely through changes in shell lipid content or in the surrounding lipid reservoir, underscoring the importance of processing-induced effects in interpreting nanobubble echogenicity.

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.

Circulating microRNAs (miRNAs) have emerged as promising liquid biopsy markers; however, their clinical translation is restricted by low abundance, biological heterogeneity, and the complexity of multiplex profiling. Herein, we develop a targeted cycling-mediated duplex-specific nuclease (DSN)-nanozyme signal amplification platform (TC-DSN-Nano) that establishes a compartmentalized catalytic transduction strategy for multiplexed miRNA analysis. By encapsulating gold nanozymes within liposomal nanoreactors, this platform spatially separates molecular recognition from catalytic signal generation, preserving nanozyme activity during sensor construction. Upon target miRNA recognition, DSN-mediated recycling induces regenerative release of nanozyme-loaded liposomes from magnetic substrates, converting individual miRNA molecules into amplified catalytic outputs without conventional nucleic acid amplification. The platform enables programmable profiling of six prostate cancer (PCa) associated miRNAs in serum samples. Furthermore, machine learning-assisted integration of multiplexed miRNA signatures enables accurate discrimination among healthy donors, nonmetastatic PCa patients, and metastatic PCa patients, achieving an overall classification accuracy of 90.5%. This work establishes a general compartmentalized nanozyme transduction framework that integrates molecular recycling, catalytic amplification, and computational analysis for liquid biopsy-based cancer stratification.

In this paper, we introduce Nagini3D, a 3D biological image segmentation method that hybridizes two high-performing yet highly complementary segmentation paradigms: deep learning-based approaches and snake-based methods. Our approach leverages both the high efficiency of data-driven techniques and the convenient shape representation provided by active surfaces, which proves highly practical for incorporating a priori knowledge as well as for the post-analysis of segmented objects. By considering a complete 3D volume, our method ensures segmentation consistency across all three dimensions, unlike many approaches that handle volumes in a slice-by-slice manner. Additionally, it theoretically enables the representation of any object with spherical topology, overcoming the limitations of common 3D methods that rely on object convexity assumptions. Furthermore, the continuous representation of objects allows for a resolution-independent description, facilitating the extraction of various geometric features of interest (e.g., local curvature, principal deformations). We demonstrate both the quality of the segmentation produced by our method and the richness of the accessible geometric features through an extensive set of experiments conducted on multiple real and simulated datasets, including objects with challenging geometries.

High-speed atomic force microscopy (HS-AFM) experiments provide unique insights into nanoscale biological processes by directly visualizing the surface topography dynamics of biomolecules, such as proteins, over extended periods of time and generating large imaging data sets. However, the lack of computational methods for automated data analysis has thus far limited the full utilization of these data for the quantitative understanding of single-molecule dynamic. Here, we present the AFM Analysis Arena (A3) within BioAFMviewer as a software platform for automated, high-throughput quantitative analysis of AFM topographic imaging data within a user-friendly interactive graphical interface, implementing a convenient workflow from raw HS-AFM (AFM) imaging to statistical analysis. In several applications to HS-AFM imaging data, we demonstrate methods of automatized molecule detection and dynamic tracking to highlight the available capacities, aiming to transform HS-AFM measurements from observations towards an analytical tool in nanoscale biology.

Cell membrane-coated nanoparticles (CNPs) are a potentially transformative biomimetic targeted-delivery platform, which can engage therapeutic targets through source-cell membrane protein functions or homotypic interactions. However, their therapeutic development is limited by the current inability to accurately resolve membrane coating completeness, and CNP particle-to-particle variation. Here, we introduce a STochastic Optical Reconstruction Microscopy (STORM)-based approach that resolves population composition and quantifies membrane coating coverage at the single-particle level. Applying it to dendritic cell membrane- and HeLa cell membrane-coated nanoparticles (DCmPs and HeLamPs), we revealed substantial heterogeneity within both particle types and a cell-type dependence of coating outcomes, corroborated by confocal imaging and flow cytometry. We also quantified membrane protein composition, including peptide major histocompatibility complex class I (pMHC-I) among DCmPs, and confirmed that DCmPs preferentially engaged antigen-specific T cells in coculture. This single-particle framework establishes a quantitative standard for CNP characterization, providing a foundation for quality control and rational design.

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.

Cell-level analysis of high-resolution spatial transcriptomics depends on accurate segmentation and transcript assignment, yet current workflows often trade transcript capture for boundary purity and can require substantial image-analysis expertise. We developed MCseg, a downloadable no-code platform whose fixed segmentation engine was derived by an AI-agent-guided search in which an AI agent iteratively proposed and evaluated combinations of image-processing and segmentation operations against Xenium-derived cell boundaries. In a lung adenocarcinoma development set, fixed-parameter MCseg increased mean panoptic quality from 0.432 to 0.472 relative to an Optuna-tuned two-diameter Cellpose baseline, while a reference-guided calibration analysis reached 0.554. In an independent expert-annotated colorectal cancer region, MCseg showed higher lineage recall and micro-F1 than the StarDist-based ENACT workflow among cells covered by both methods. Across 15 colorectal cancer regions, MCseg increased neighborhood expression discordance and reduced lineage-exclusive co-expression relative to Space Ranger at similar UMI density. The fixed workflow also transferred to fresh-frozen breast cancer without tissue-specific architecture search, illustrating an agent-guided route to reproducible, locally deployable cell-level spatial transcriptomic analysis.

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.

Tumor necrosis factor-alpha (TNF-) represents a major pro-inflammatory cytokine associated with chronic inflammation. Enhanced understanding of intracellular trafficking of TNF- enables the identification of drug targets that modulate TNF- secretion at the cellular source. However, conventional cytokine assays provide only bulk measurements of secreted TNF- or static measurements in fixed cells and therefore cannot provide mechanistic information. Here, we report a fluorescence imaging platform to visualize and quantify intracellular TNF- trafficking in human T cells. Using a Jurkat T cell line stably expressing TNF- fused to mStayGold as a model system, we revealed through single-particle tracking (SPT) that T cell activation increased the motility of TNF- vesicles and that microtubule perturbation disrupted this increased motility. 3D structured illumination microscopy uncovered spatial associations between TNF- vesicles and lysosomes, and SPT further demonstrated their coordinated transport. Using total internal reflection fluorescence microscopy, we captured the sub-second splitting of single TNF- vesicles into multiple puncta that subsequently separated, suggesting delivery of TNF- from the vesicle to the plasma membrane. Confocal-based super-resolution microscopy further resolved TNF- vesicles fusing with the plasma membrane and transmembrane TNF-. Together, these imaging capabilities for tracking and super-resolving the intracellular transport and membrane delivery of TNF- in live T cells enable mechanistic studies of TNF- trafficking and release.

Solid tumors are known to be refractory to treatment due to a poorly perfused microenvironment that blocks immune cell infiltration and effective drug delivery. Histotripsy is a non-invasive focused ultrasound modality that generates cavitation microbubbles to mechanically disrupt solid tumors, resulting in decreased hypoxia and stimulation of tumor-targeted adaptive immune responses. In this study, we aim to investigate whether post-histotripsy hypoxia reduction and cytotoxic immune cell infiltration are associated with normalization of tumor vasculature and enhanced perfusion. Structural analysis of both treated and contralateral off-target tumors following partial histotripsy revealed significant vascular remodeling, enhanced vascular integrity, and decreased vascular leakage indicative of vascular normalization in multiple in vivo models of melanoma, hepatocellular carcinoma, and pancreatic adenocarcinoma. These effects appeared antigen-specific, as no remodeling was observed in contralateral off-target tumors of discordant pathology. Mechanistically, CXCR3+CD8+ T cells played a role in mediating these vascular changes, as genetic knockout of CD8 and pharmacological antagonism of CXCR3 impaired both remodeling and normalization. Additionally, significant changes in endothelial CXCR4 and Angiopoietin-1 and -2 expressions were observed following histotripsy, indicating their potential involvement in promoting vascular normalization and remodeling. Significant vascular remodeling was accompanied by enhanced tumor perfusion and intratumoral delivery of chemotherapeutic agents and therapeutic monoclonal antibodies. These findings suggest that histotripsy not only creates a more favorable microenvironment for immunotherapy, but also optimizes drug delivery into solid tumors. Combinatorial approaches using histotripsy with chemotherapy or immunotherapy may be a novel therapeutic strategy to overcome current limitations of conventional solid tumor therapies.

Membrane tension, defined as the energy cost to expand the membrane surface area, is a fundamental mechanical property of the lipid bilayer and an important modulator of various cellular processes. Liposomes provide model systems to study protein-mediated membrane dynamics, where membrane tension can be controlled by osmotic pressure and micropipette aspiration. However, it is challenging to individually control membrane tension of nanometer-sized liposomes, such as small unilamellar vesicles (SUVs), that are widely used for modeling subcellular membrane structures and drug delivery. To bridge this technological gap, we present reconfigurable DNA origami rings for dynamically controlling membrane tension of sub-100 nm liposomes. The DNA nanorings template the formation of uniformly sized SUVs and undergo trigger-responsive dilation and contraction, thus applying controlled and reversible mechanical stress to the SUV membranes. Electron microscopy analyses show deformed liposomes with ~2.5% expanded membrane area following ring dilation. The corresponding increase in membrane tension opens a mechanosensitive ion channel MscL with gating tension of ~10 mN/m. Selectively manipulating a mixture of SUV populations enables timed release of their distinct molecular cargos, either concurrently or one at a time. Furthermore, vesicles with expanded membranes are more conducive to SNARE-mediated fusion. The nanomechanical device thus provides a programmable platform for engineering the mechanics of synthetic nano-vesicles and studying membrane tension modulated processes at the molecular level.