ACS Sensors最新文献

Genetically encoded biosensors enable the monitoring of metabolite dynamics in living organisms. We present CoBiSe, a computational biosensor design approach using Constraint Network Analysis to identify optimal insertion sites for reporter modules in molecular recognition elements (MREs). Applied to the iron-binding protein DtxR from Corynebacterium glutamicum, CoBiSe identified a flexible connective loop (residues 138–150) for inserting the reporter module, resulting in IronSenseR, a novel ratiometric biosensor for ferrous iron (Fe²⁺). IronSenseR demonstrates high specificity for Fe²⁺ with dissociation constants of 1.78 ± 0.03 (FeSO₄) and 2.90 ± 0.12 μM (FeCl₂), while showing no binding to Fe³⁺ and other divalent cations. In vivo assessment in Escherichia coli, Pseudomonas putida, and Corynebacterium glutamicum confirmed IronSenseR’s capability to detect changes in the intracellular iron pool. The creation of IronSenseR underlines that by reducing search space and eliminating labor-intensive screening, CoBiSe streamlines biosensor development and enables precise creation of next-generation biosensors for diverse metabolites.

The advent of normothermic machine perfusion (NMP) has substantially enhanced liver transplantation outcomes by enabling physiologic preservation and functional assessment of donor grafts. However, despite the well-established role of donor-derived inflammation influencing graft viability and post-transplant outcomes, current viability assessment metrics, such as lactate clearance, are insufficiently sensitive or specific to capture the underlying immunological status of the organ. Conventional immunoassays, while analytically robust, are limited by prolonged processing times that preclude rapid clinical decision-making and fail to reflect the multifactorial nature of immune-mediated graft injury. To address this critical gap, we developed a paper-based, multiplexed cytokine vertical flow assay (xcVFA) capable of detecting interleukin-6, tumor necrosis factor-α, and interleukin-8 directly from NMP perfusate within 30 min, enabling rapid and actionable inflammatory profiling during organ preservation. The xcVFA miniaturizes conventional sandwich ELISAs and integrates a hand-held smartphone reader for image capture, where signal readouts feed into three independent neural network classifiers, each trained to categorize respective cytokine levels. Lastly, an integrated decision tree translates cytokine profiles into overall inflammation status. The xcVFA achieved limits of detection of ∼2 ng/mL, with each classifier achieving macro-averaged F₁ scores of >0.9 and one-vs-rest AUCs ≥ 0.9. In a blinded validation test, the integrated decision tree inflammation classifier achieved 90.9% overall accuracy, correctly distinguishing noninflamed grafts from a graft discarded due to inflammation. In summary, these results show that the xcVFA enables rapid, decentralized inflammatory profiling during NMP and may augment current viability criteria by incorporating inflammatory biomarkers into clinical decision-making. This point-of-care device has the potential to improve liver graft selection, optimize organ utilization, and reduce post-transplant complications.

Early detection of breast cancer can significantly increase survival rates, and annual screening increases the chance of early detection. However, anatomical imaging methods, such as mammography, underperform in women with dense breast tissue, and alternatives such as ultrasound and magnetic resonance imaging can be more time- and cost-intensive. Molecular imaging methods have the potential to provide both spatial and molecular information, yielding advantages over traditional imaging. However, molecular imaging has previously been impractical for annual screening due to its high cost, risk of ionizing radiation, long acquisition time, and IV injection of contrast agents. Therefore, a cost-effective and lower-risk method is needed. This study reports the design of a bivalent near-infrared fluorophore sulfo-Cy5.5 carbonic anhydrase 9 (CAIX/CA9) targeting molecule (biAAZ-Cy5.5) for oral administration and fluorescent breast cancer screening. A challenge in developing orally delivered contrast agents is balancing sufficient oral bioavailability with efficient targeting and background clearance. Previous work from our group developed an integrin-targeting agent for oral delivery (α_Vβ₃-IRdye800CW) that binds α_Vβ₃ integrin with sufficient oral absorption to successfully detect breast tumors in a mouse model. However, similar to current screening methods, the potential for false positives caused by benign tumors limits its application. To increase the diagnostic potential of this approach, we developed a second molecular targeting agent for dual-channel imaging. By selecting the malignant tumor-associated marker CA9 and using acetazolamide (AAZ) as the targeting molecule, the bivalent biAAZ-Cy5.5 shows high specificity, high affinity, and low off-target binding. With ∼7.6% oral bioavailability in mice, biAAZ-Cy5.5 uptake was sufficient for in vivo imaging. Oral coadministration of α_Vβ₃-IRdye800CW and biAAZ-Cy5.5 in HT29 (CA9⁺, α_Vβ₃⁺) and HCT116 (CA9^–, α_Vβ₃⁺) tumor-bearing mice demonstrated that biAAZ-Cy5.5 selectively targets the CA9-expressing tumors. The combination of an 800 nm integrin-targeting agent for high sensitivity with the 680 nm CA9-targeting agent for improved specificity highlights the utility of dual-channel imaging.

Flexible wearable sensors have been developed for real-time noninvasive detection in various emerging fields, such as electronic skin, human–machine interfaces, and micro/nanorobots, which are expected to provide new impetus for intelligent clinical diagnosis, smart city monitoring, and industrial safety production. Herein, ultrasensitive flexible sensors based on a series of ionic polymer organogels were developed via a facile one-step photopolymerization strategy, and the component of ionic gels was readily tuned by varying the organic anions and cations. Particularly, the sensor based on 1-butyl-1-methylpiperidine bis(trifluoromethanesulfonyl)imide ([BMPip][TFSI]) exhibited good sensing performance toward styrene vapor, featuring fast response, a low theoretical detection limit (ca. 193 ppb), and excellent long-term stability. In addition, it can be integrated with a Bluetooth module for real-time and rapid detection of styrene vapor via a smartphone application, implying its great potential for portable microdevice applications. Density functional theory (DFT) calculations confirmed that [BMPip][TFSI] exhibits high adsorption energy toward styrene and chlorobenzene, elucidating the gas sensing mechanism based on the ionic conduction and surface adsorption. Leveraging their highly transparent and flexible features, multifunctional ionic gels show great application potential in device integration and wearable sensing for styrene and chlorobenzene monitoring.

The utilization of hydrogen as an energy source is becoming more and more widespread. Since hydrogen is a highly explosive gas, its use requires the development of inexpensive and simple sensors capable of measuring hydrogen concentrations under a variety of conditions. These sensors must meet several parameters, such as small size, light weight, corrosion resistance, and remote operation capability. The ideal hydrogen sensors should also be insensitive to the presence of various interfering gases and humidity or temperature variation and be protected against potential poisoning. In this work, we present a simple optical hydrogen sensor that satisfies most of the above criteria. The sensor is based on a plasmon-active multimode optical fiber coated with Pd and PDM layers in a stepwise manner. The Pd layer, deposited on the plasmon active area, ensures sensitivity toward hydrogen through hydrogenation of Pd, leading to a significant shift in the plasmon absorption band wavelength position. An additional PDMS layer ensures sensor protection against various interfering gases (NO₂, CH₄, CO₂, CO, and NH₃), including the moisture of sulfur-containing compounds. The sensor response is measured within tens of seconds, while its regeneration takes approximately 2 min. The operating temperature range is from RT to 80 °C, with a slight decrease in sensor functionality at an elevated temperature. The proposed structure is simple, allows the removal of hydrogen detection, and can be used under various operation conditions.

Conventional conductive gels for wearable strain sensors have been fundamentally limited by their dependence on external power sources, interfacial issues with electrodes and the inherent trade-off between conductivity and mechanical properties. To overcome these critical challenges, we developed an innovative ion-electron dual-conduction mechanism combined with an impregnation strategy, leading to the successful fabrication of an integrated “electrode–electrolyte–electrode” structured conductive gel (PAML-EG/LiCl-PANI). The combination of the ternary deep eutectic solvent PDES (choline chloride/acrylic acid/acrylamide) with LiCl established efficient ion pathways, while in situ polymerization of polyaniline formed a continuous electronic network. Furthermore, the introduction of lauryl methacrylate (LMA) and cetyltrimethylammonium bromide (CTAB) micelles generated hydrophobic microdomains, combining with the dynamic hydrogen bonding and electrostatic interactions of PDES to form a multiscale energy dissipation network. The resulting gel exhibits outstanding electrical conductivity (21.84 mS/cm) and ultrahigh fracture elongation of 4425 ± 187%. When employed as a strain sensor, the gel displays rapid 440 ms response times and high sensitivity with gauge factors up to 19.71. As all-in-one supercapacitor, it achieves remarkable areal capacitance of 131.23 mF/cm² while maintaining excellent pressure tolerance and self-healing capability during operation. The self-powered sensing platform constructed from this multifunctional gel successfully achieves real-time monitoring of human motion states without external power requirements. These findings establish a new material-device codesign paradigm that simultaneously optimizes mechanical robustness, electrochemical performance and sensing capability, representing a significant advancement in the field of autonomous wearable electronics.

Biophotonics─and more recently, biointegrated photonics─offer transformative tools for probing cellular processes with unprecedented precision. Among these, whispering-gallery-mode (WGM) resonators (optical microcavities formed in spherical structures) have emerged as powerful biosensors and intracellular barcodes. Lipid droplets (LDs), with their high refractive index and intrinsic spherical geometry, are ideal candidates for supporting intracellular lasing. Although lasing in LDs has been previously demonstrated, it has not yet been harnessed to study live-cell biology. Here, we report the first use of WGM resonances in LDs of live primary adipocytes, employing a continuous-wave (CW) laser at powers below the biological damage threshold. By measuring these resonances, we achieved nanometer-scale precision in size estimation, enabling real-time observation of rapid LD dynamics and deformations on the minute scale─far beyond the spatiotemporal resolution of conventional microscopy. We systematically characterized this photonic sensing approach, demonstrating its ability to resolve adipocyte heterogeneity, monitor lipolytic responses to forskolin and isoproterenol, and detect early signs of cell viability loss─well before conventional assays. This proof-of-concept establishes intracellular LD WGM resonances as a robust platform for investigating live single-cell metabolism. The technique enables rapid, cost-effective assessment of adipocyte function, reveals cell-to-cell variability obscured by bulk assays, and lays the foundation for high-throughput analysis of metabolism- and obesity-related diseases at both the cellular and tissue levels.

A 3D-printed electrochemical microfluidic device (3D-EMD) was developed to assess the transferrin saturation (TSAT) biomarker in ischemic stroke patients. The all-in-one 3D-EMD integrates a strategically engineered immunoassay module for the direct and selective isolation of transferrin (Tf) from unpretreated clinical samples, unaffected by sample coloration, with an interchangeable electrochemical sensor for the simultaneous detection of Tf and Tf-bound iron. Both modules are interconnected through microfluidic channels whose flow is regulated by a cylindrical rotary valve. The analytical workflow enables magnetic bead-based direct Tf immunocapture and simultaneous electrochemical detection of Tf and Tf-bound iron via square wave voltammetry, allowing TSAT assessment within 60 min using only 50 μL of sample. Validation with certified reference materials demonstrated excellent accuracy (E_r ≤ 5%) and precision (RSD ≤ 4%). Application to human serum from ischemic stroke patients showed strong correlation (r = 0.87) and agreement (slope 0.9 ± 0.3; intercept 6 ± 10; p < 0.05) with the urea-PAGE reference method, which typically requires up to 18 h. Overall, the 3D-EMD constitutes an elegant, fully integrated dual-functionality platform that seamlessly combines customizable sample preparation with online electrochemical detection in a single device. This configuration enables direct serum analysis and supports clinical decision-making in time-critical conditions. The device shows strong potential as a rapid point-of-care testing candidate for ischemic stroke and as a next-generation platform for broader clinical diagnostics.

Human motion recognition holds significant value in clinical rehabilitation, human–machine interaction (HMI), and sports science. Self-powered triboelectric sensors (TESs) based on triboelectric effect and electrostatic induction offer promising solutions for applications such as precision medicine, sign language translation, and robotics. However, challenges such as signal stability, complex motion decoupling, and long-term durability remain. This Perspective systematically explores these challenges by focusing on the critical role of material design and structural innovation in enhancing TESs performance. First, we analyze the core triboelectric sensing mechanism and compare traditional polymers with novel high-performance materials that overcome limitations in dielectric properties, mechanical strength, and environmental stability. We then explore structural innovations such as biomimetic design, multimodal integration, and textile integration to enhance sensitivity, comfort, and large-area deployment. In addition, we systematically analyzed the motion recognition mechanisms of the lower limbs, upper limbs, trunk, and head/neck from the perspective of physiological partitioning and summarized the progress of TESs in various application scenarios. Finally, we identify existing technical challenges and general strategies and envision future developments through the integration of artificial intelligence to achieve real-time, precise biomechanical feedback and auxiliary diagnosis of diseases, aiming to provide a technical roadmap for self-powered sensing systems and promote their implementation in smart healthcare and immersive interaction applications.