ACS Sensors最新文献

Microbially induced calcium carbonate precipitation (MICP) in microfluidic systems produces spatially and temporally heterogeneous precipitates whose polymorph composition governs material outcomes but is difficult to monitor non-destructively in situ. We present a Raman-grounded deep learning framework that decouples spectroscopic labeling from optical inference: each Raman spectrum is matched to an individually segmented crystal instance, and a five-channel EfficientNet-B0 classifier trained on these per-instance labels assigns polymorph identity to the remaining crystals from brightfield and polarized light alone. Trained on 550 Raman-labeled instances and applied across 5123 segmented crystals spanning five experimental datasets, the framework achieved 97.3% test accuracy across three polymorph classes-calcite, early-stage vaterite, and late-stage vaterite-at individual-crystal resolution. Late-stage vaterite emerged as a third optically distinct class, identified from 48 h imaging and confirmed by Raman to retain vaterite phase identity despite its altered optical signature. The framework resolved systematic effects of solution composition, bacterial density, pH, and time on polymorph composition and captured the dissolution of vaterite toward a calcite-dominated state within a single device. Operating at individual-crystal resolution across heterogeneous crystal populations without requiring droplet confinement, the approach provides a practical route to non-destructive polymorph monitoring in MICP and living building materials applications.

Developing advanced instrumentation systems for the automated, precise isolation of target circulating tumor cells (CTCs) from blood, followed by molecular marker analysis, stands as a pivotal trend in the field of liquid biopsy. However, current isolation technologies typically rely on subsequent centrifugation steps to enrich CTC samples for downstream assays, such as single-cell western blotting (scWB), creating challenges for developing integrated systems. Here, we present an integrated viscoelastic microfluidic system (IVEM) that leverages viscoelastic fluids to automatically separate and concentrate CTCs. The IVEM includes a CTC separation module (CSM) for high-purity isolation and a CTC concentration module (CCM) to remove excess cell suspension. To clarify the working mechanism, particle migration behavior is systematically analyzed through theoretical modeling and numerical simulations and validated by polystyrene (PS) particle experiments. The performance of the IVEM is evaluated through separation experiments using blood samples spiked with MCF-7 cells. The processing throughput, purity, recovery rate, and concentration factor of MCF-7 cells reach 1.82 mL·h-1, 82.13 ± 2.87, 81.30 ± 4.72, and 4.26 ± 0.92%, respectively. The IVEM enables label-free, continuous on-chip enrichment of separated CTCs without additional off-chip processing. This integration facilitates future incorporation of other functional modules, such as high performance single-cell capture, into liquid biopsy systems, thereby further enhancing the clinical applicability of technologies such as scWB.

The risk of hydrogen explosions in industrial and hydrogen energy facilities presents serious safety threats. An inherent trade-off between response magnitude and response/recovery kinetics plagues chemiresistive H2 sensors: monocomponent materials are incapable of concurrently realizing high-efficiency H2 activation and ultrafast gas-solid interfacial charge transfer/desorption. Herein, we synthesized SnO2@WO3 hexagonal nanosheets via hydrothermal cluster-nucleus coassembly and decorated them with Pd nanoparticles by wet-chemical reduction. The Pd/SnO2@WO3 sensor exhibits a response (Rair/Rgas) of 22.4 toward 1000 ppm H2 at 220 °C, along with response/recovery times as short as 1.4/3.2 s, and a detection limit as low as 200 ppb. The enhanced sensing performance originates from the coupling of preferential H2 dissociation on Pd with efficient migration and conversion of active hydrogen at the defect-rich SnO2@WO3 heterointerface, which accelerates interfacial oxygen consumption and electron reinjection. A backpropagation artificial neural network (BP-ANN) regression model enables high-precision quantification of single-channel H2 signals; the sensor is integrated into a wearable printed circuit board (PCB) module for H2 leakage warning. These results show this material platform is suitable for wearable hydrogen safety monitoring in real-world environments.

Although chimeric antigen receptor T-cell (CAR-T) therapy has substantially improved outcomes in diffuse large B-cell lymphoma (DLBCL), disease relapse remains a major clinical challenge. Because treatment-associated immune remodeling evolves dynamically over time, complementary biomarkers capable of longitudinally monitoring immune-cell state changes are needed to evaluate therapeutic response and relapse following CAR-T therapy. In this study, we developed a label-free, high-throughput image cytometry platform for longitudinal, multiparametric profiling of peripheral blood mononuclear cells (PBMCs) collected from a cohort of 17 DLBCL patients undergoing CAR-T therapy. Using bright-field single-cell imaging, we quantified four representative biophysical parameters, including cell size, eccentricity, refractive index, and mean pixel intensity, from PBMC populations at base and post-treatment time points. These parameters were analyzed at both population and patient levels to characterize treatment-associated remodeling trajectories and biophysical heterogeneity. Static comparisons revealed population-level biophysical differences between the 10 relapsed (R) and 7 nonrelapsed (NR) patients. Longitudinal and patient-level analyses, performed by tracking serial PBMC samples collected from the same patients across treatment time points, demonstrated that treatment outcome was associated with coordinated remodeling trajectories in NR patients and greater patient-specific heterogeneity in R patients. Patient-level effect size and heterogeneity analyses further demonstrated that relapse was associated with altered remodeling dynamics that were not apparent from population-averaged measurements alone. These findings demonstrate that longitudinal biophysical profiling of PBMCs enables quantitative monitoring of treatment-associated immune remodeling and provides a complementary biomarker for assessing therapeutic response following CAR-T therapy.

Genetically encoded bioluminescent calcium indicators enable excitation-free imaging of Ca2+ dynamics with low background and without excitation-associated photobleaching. However, many exhibit lower dynamic ranges than their fluorescent counterparts, motivating the development of new sensor configurations, particularly for imaging in the red optical window, where tissue absorption and scattering are reduced. Here, we developed HyBRIC and HyBRIC2, two hybrid indicators that integrate Ca2+-dependent luciferase activation and bioluminescence resonance energy transfer (BRET) within a single molecular architecture. When paired with pyCTZ luciferin, they exhibited an approximately 55-fold Ca2+-dependent signal increase in red-window emission in vitro. Compared with HyBRIC, HyBRIC2 showed improved brightness and responsiveness in mammalian cells. It robustly resolved induced Ca2+ dynamics in HEK293T and HeLa cells, with particularly strong red-window responses. Together, these findings expand the limited repertoire of responsive red-window bioluminescent calcium indicators and establish hybrid sensing as a modular strategy for improving biosensor contrast.

Current treatments for inflammatory bowel disease (IBD) lack real-time inflammatory monitoring and lesion-specific drug delivery, resulting in poor efficacy and systemic toxicity. To address this, we present a smart oral capsule that operates a closed-loop "sense-decide-act" strategy entirely autonomously-sensing and drug release are driven by changes in the digestive tract environment without any external intervention. The capsule features a dual-layer shell sequentially responsive to pH and matrix metalloproteinases (MMPs), enabling colon-targeted delivery and inflammation-specific activation. An integrated multimodal sensor wirelessly tracks colonic TNF-α (>5 ng mL-1), pH (>7.0), and Na+ (>100 mM). The encapsulated budesonide nanoparticles (Bud@PEG-SS-NPs) release the drug specifically in reactive oxygen species (ROS)-rich microenvironments and show superior anti-inflammatory efficacy in both lipopolysaccharide (LPS)-induced cellular models and dextran sulfate sodium (DSS)-induced mouse colitis. In live rats, the capsule achieved on-demand drug release in response to elevated local TNF-α levels, and a single intervention significantly alleviated inflammation. This work establishes a new paradigm for personalized, adaptive IBD therapy and provides a versatile platform for closed-loop management of other gastrointestinal diseases.

Aptamer-based molecular monitors enable continuous, real-time tracking of analytes in complex environments, including in vivo, but their practical deployment is limited by short operational lifetimes of only hours. This instability arises in part from the electrochemical interrogation of the aptamer-bound redox reporter methylene blue, whose standard potential overlaps with oxygen reduction on gold electrodes, leading to peroxide generation and, concomitantly, accelerated sensor degradation. We previously demonstrated that peroxide accumulates to tens-to-hundreds of micromolar on the sensor surface under typical operating conditions. Here, we address this limitation by rationally designing redox reporters with more positive standard potentials, beyond the range of oxygen electroreduction. Using electron-withdrawing substituents and extended conjugation strategies, we developed a new reporter, Netz Lab Blue, exhibiting a standard potential 160 mV more positive than methylene blue. Aptamer-based monitors incorporating Netz Lab Blue withstand ≥10,000 interrogation cycles in buffered saline without measurable signal loss, whereas methylene blue-based sensors lose >20% signal under identical conditions. In oxygen-saturated solutions, Netz Lab Blue-based sensors retain full stability over the same duty cycle while methylene blue-based devices fail completely. Additionally, Netz Lab Blue delivers 40% higher signal gain for the same aptamer sequence and under identical packing density relative to methylene blue. These improvements translate directly to biological environments, where Netz Lab Blue‑based sensors exhibit stable performance in rat blood and support continuous, real‑time in vivo drug monitoring in the brain of rodents using two distinct aptamer sensors. By eliminating peroxide generation during electrochemical interrogation, this new redox reporter markedly extends sensor lifetime and performance, potentially enabling continuous molecular monitoring over days to weeks in biomedical applications that seek to interrogate human physiology.

Most existing VOC sensors rely on battery power and only single-parameter outputs, limiting long-term deployment, maintenance efficiency, and chemical discrimination. Here, we report a self-powered multivariable photovoltaic sensor (MPVS) that repurposes an organic photovoltaic junction as an information-rich VOC sensing platform. By integrating a gas-permeable silver nanowire electrode with a donor-acceptor bulk-heterojunction active layer, the MPVS enables efficient analyte access while maintaining stable photovoltaic operation under illumination. Exposure to VOCs induces coupled and reversible changes in open-circuit voltage (VOC) and short-circuit current density (JSC), providing two orthogonal sensing features without external power input. Using a single PM6:Y6 junction, we demonstrate concentration-dependent responses and reliable discrimination of representative VOCs. Extending the concept to a five-element MPVS array incorporating different Y-series acceptors generates high-dimensional photovoltaic fingerprints that enable accurate identification of eight chemically distinct VOCs. Density functional theory (DFT) calculations and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) reveal that analyte-dependent noncovalent interactions, particularly strong hydrogen bonding in the case of formic acid, underlie the observed selectivity. By integrating energy harvesting and multivariate sensing within a single organic photovoltaic platform, this work establishes a scalable, battery-free approach to artificial olfaction, offering a promising pathway for distributed and long-term VOC monitoring systems.

Antigen-specific T cells constitute a low percentage of peripheral blood mononuclear cells (PBMCs) and require antigen presentation by autologous antigen-presenting cells for activation and cytokine secretion. Conventional interferon-γ release assay (IGRA) averages rare activation events beyond cellular resolution, while single-cell compartmentalization disrupts the intracellular synapses for T cell immunity. Here, we developed mSTAR (matrix-based Specific T-cell Activation Reporter), an active-matrix digital microfluidic platform that partitions microliters of PBMCs into a nanoliter-scale matrix of 16 cell microcommunities (CMCs), each retaining tens to hundreds of PBMCs in their native heterotypic composition to preserve the natural physiological immune response. In a proof of concept, mSTAR executes parallel IGRA for a tuberculosis disease model, including CMC stimulation and magnetic-bead-based immunofluorescence assay. The IGRA of the mSTAR system achieves a limit of detection of 3.70 pg/mL, yielding 16 interferon-γ quantification readouts and ratios between CMCs incubated with different stimulants (negative, positive, or specific antigen). This enables the mapping and reporting of activated antigen-specific T cells in the matrix, thereby achieving functional phenotyping of each CMC. Poisson-based modeling of the droplet matrix converts rare T-cell activation events into a nearly digital estimation, and the positive CMCs encapsulating target cells can be retrieved for further characterization without loss. By bridging functional phenotyping and molecular features without prior cell sorting or engineering, mSTAR provides a programmable immunoanalytical infrastructure for broad downstream applications such as antigen-specific immunotherapy development or T-cell receptor discovery.

Early and sensitive detection of human immunodeficiency virus 1 (HIV-1) p24 antigen is crucial for identifying acute infection before seroconversion and monitoring low-level viremia. Here, we report a magnetic bead (MB)-based electrochemical immunoassay using stencil-printed carbon electrodes, systematically comparing streptavidin-, tosyl-, and N-hydroxysuccinimide-MBs for p24 detection. Tosyl-MBs achieved superior analytical performance with limits of detection of 19.4 pg/mL in tris-buffered saline with Tween 20, 24.3 pg/mL in media containing viral lysis buffer, and 8.8 pg/mL in human serum, demonstrating excellent matrix tolerance and reproducibility across the clinically relevant concentration range. The sandwich immunoassay employed optimized capture and horseradish peroxidase-conjugated detection antibodies with chronoamperometric readout using 3,3',5,5'-tetramethylbenzidine substrate at 0.0 V vs a silver pseudoreference electrode, enabling rapid immunocomplex quantification on magnet-retained beads with minimal sample handling. Tosyl-MBs provided the strongest concentration-dependent response across all matrices tested, with surface chemistry influencing antibody immobilization efficiency, nonspecific background signal, and p24 capture capacity. The platform demonstrated stability for at least 28 days under storage conditions and successfully distinguished inactivated HIV-1 samples from negative controls, thereby establishing tosyl-MB electrochemical immunoassays that are compatible with serum and other complex biological matrices. Further validation with clinical specimens, integration of simplified sample-processing steps, and implementation in portable instrumentation will be required to assess their potential for future point-of-care HIV diagnostics.