Macrophages are highly plastic immune cells that adopt diverse functional states to modulate inflammation. Capturing this dynamic heterogeneity requires single-cell resolution. However, conventional fluorescence flow cytometry relies on multistep antibody labeling and lacks a direct quantitative read-out of cell-intrinsic properties. In this study, we identify specific membrane capacitance (Csm), an intrinsic electrical property of individual cells, as a sensitive and quantitative marker of macrophage polarization. Measured at single-cell resolution using high-throughput, label-free microfluidic impedance cytometry, Csm increases in pro-inflammatory states and decreases in anti-inflammatory conditions, offering a direct readout of functional macrophage states. Leveraging this metric, we establish a rapid drug screening platform targeting macrophage polarization. Notably, screening the histone deacetylase (HDAC) family reveals that the inhibition of Class IIa HDACs or the activation of Class III HDACs effectively suppresses pro-inflammatory polarization. These effects are validated using blood samples from stroke patients and further supported by improvement of ischemic outcomes in mouse cerebral ischemic models. Collectively, our results highlight Csm as a robust, label-free marker for real-time single-cell analysis of macrophage polarization, offering a valuable tool for both basic research and therapeutic development in neuroinflammation.

Label-free and effective sorting of red and white blood cells based on their physical properties is crucial for subsequent single-cell analysis or immune cell engineering applications. However, cell sorting relying on the physical effects of one single physical property remains highly challenging. This paper proposes a cell sorting method based on a focused traveling surface acoustic wave (FTSAW)-based acoustofluidic chip, which leverages the ability of FTSAW acoustofluidics to comprehensively respond to multiple physical characteristics of cells (e.g., size, density, morphology, and deformability), and furthermore allows for precise setting of the action area range and adjustment of the action intensity. In experiments, a pair of focused interdigital transducers (FIDTs, characteristic frequency: 128.6 MHz) on the substrate of lithium niobate and a typical microchannel structure (single-side sheath flow focusing followed by bifurcated sorting, i.e., "two streams merging into one and then splitting into two") were designed and fabricated. Parameter optimization experiments for separation and sorting were conducted on 3 μm and 5 μm polystyrene (PS) beads, as well as red and white blood cell samples after sheath flow focusing. The results indicate that the FTSAW-based acoustofluidic chip enabled white blood cell sorting with high purity (∼90%) and high biological viability (∼98%). This study demonstrates the potential of the FTSAW-based acoustofluidic chip for cell sorting. Owing to its easy integration and advantages (non-contact operation, no sieve pore clogging, broad compatibility with cell culture media), it is expected to serve as a key pre-processing technology in microfluidic systems for single-cell analysis or cell engineering.

INTRODUCTION:The dynamic monitoring of microglial polarization remains constrained by the static M1/M2 dichotomy and a lack of robust biomarkers, limiting therapeutic development for neurological disorders. Recent advances in bioelectrical characterization, however, have revealed that cellular processes correlate with distinct dielectric properties, suggesting a potential new approach for label-free cellular analysis. OBJECTIVES:This study aimed to establish specific membrane capacitance (Csm) as a label-free, continuous metric for microglial polarization states and to elucidate the underlying biophysical mechanisms. METHODS:We employed high-throughput single-cell dielectric phenotyping via a microfluidic impedance cytometry platform (54 cells/s) to characterize the ability of Csm to capture the continuous spectrum between M1/M2 phenotypes. Complementary lipidomic and proteomic analyses, alongside pharmacological interventions, were used to investigate the molecular basis of dielectric changes. RESULTS:We demonstrate that M1-polarized microglia exhibit a significantly elevated Csm compared to M2 or resting (M0) states. This shift of Csm was continuous and dose-dependent to polarizing stimuli and was mechanistically linked to membrane lipid remodeling, specifically an increased lysophosphatidylcholine/phosphatidylcholine ratio (LPC/PC) regulated by Pla2g4a/Lpcat1. Furthermore, PPARγ/SIRT1 activators reversibly modulated these continuous changes of dielectric signatures. Pharmacological validation confirmed Csm's sensitivity to membrane reorganization. CONCLUSION:Our results establish Csm as a real-time, single-cell functional metric for the continuum of microglial polarization, directly linking biophysical measurements to subcellular biochemistry. This work identifies Csm as a promising screening tool for neuroimmunomodulators and a predictive biomarker for therapeutic response, providing a scalable platform for neuroinflammation research.

Brain-on-a-chip (BOC) refers to a miniaturized in vitro platform that integrates living neuronal networks on a micro-engineered chip, enabling the simulation of brain functions, neural activities and physiological responses. BOC technology is an advanced evolution of microphysiological systems (MPS) and Lab-on-a-Chip platforms, providing novel paradigms for in vitro modeling and exploring early-stage biocomputing by interfacing living neural networks with engineered electronics. Microelectrode arrays (MEAs) serve as the critical physical interface for bidirectional communication in these systems. In this review, we systematically examine the technological landscape and engineering requirements of MEAs tailored for BOC applications, evaluating them across electrical characteristics, structural properties, and biocompatibility. Two primary classes of current MEA technologies, including planar arrays for 2D neural cultures and 3D flexible arrays for brain organoids, are discussed in detail. We highlight the transition from passive planar electrodes to high-density active CMOS and TFT-based arrays, and detail how 3D flexible MEAs utilize endogenous integration and exogenous wrapping strategies to overcome tissue-mechanics mismatches. Furthermore, the integration of MEAs with microfluidics, optoelectronics, and electrochemical sensors to enable multimodal monitoring is explored. With the advantages of the various MEAs, the application of MEAs for BOC, particularly in biological computing and network plasticity research, is discussed. Finally, future technological developments in scalability bottlenecks, chronic stability, and the incorporation of artificial intelligence for MEAs of BOC are prospected.

Extracellular vesicles (EVs) and EV-derived microRNAs (EV-miRNAs) are emerging as valuable nanoscale circulating biomarkers for tumor progression and immune responses. Conventional detection methods, such as quantitative reverse transcription polymerase chain reaction (qRT-PCR), require large sample volumes and labor-intensive purification, limiting the analysis of EV-miRNAs from scarce samples. In this work, we present an integrated DropFET device that combines a high-density active-matrix digital microfluidic (AM-DMF) chip with a silicon nanowire array field-effect transistor (SiNW array FET) sensor for fully integrated EV-miRNA detection. Based on a bio-cascade strategy, EVs are efficiently captured with dual-antibody-functionalized magnetic beads, lysed in situ on-chip, and the released miRNAs are directionally delivered to the SiNW sensor for electrical sensing. With a detection limit of 10-17 M, the device discriminates single-base mismatches and reliably distinguishes EV-miRNA expression differences between normal and M1 disease states. This integrated approach enables low-volume EV enrichment and ultrasensitive EV-miRNA detection, offering a promising platform for clinical analysis of rare samples.

Transepithelial electrical resistance (TEER) measurement is a label free, rapid and real-time technique, which is commonly used to evaluate the integrity of cell barriers. TEER characterization is important for applications, such as tissue (brain, intestines, lungs) barrier modeling, drug screening, and cell growth monitoring. Traditional TEER methods usually only show the average impedance of the whole cell layer, and lack accuracy and the characterization of internal spatial differences within cell layer regions. Here, we introduce a new spatial TEER strategy that utilizes microelectrode arrays (MEA) integrated in a Transwell to dynamically monitor TEER. A new electrical model which could reveal spatial impedance non-uniformity was proposed to extract accurate resistance from the measured data. Based on our method, the TEER signals from 16 different regions were successfully monitored in real time. The mapped impedance hotspots in different regions closely correlate with both fluorescence cell staining signals and calculated cell coverage, indicating the effectiveness of the developed spatial TEER system in monitoring local cell growth in vitro. The real-time spatial TEER responses to ethylene glycol-bis(β-aminoethylether)-N,N,N',N'-tetraacetic acid (EGTA) and cisplatin were studied, which could either reduce barrier integrity or inhibit cellular growth. The obtained results demonstrated the spatial TEER's applicability for cell barrier function and cell growth monitoring. Our approach provides accurate spatial electrical information of cell barriers and holds potential applications in drug development and screening.

Metal nanoparticles are commonly found in our daily lives and pose great risks to people's health. Therefore, it is crucial to establish a research model for the toxic effects of metal nanoparticles. In recent decades, three-dimensional (3D) cell models have attracted increasing interest in the fields of cell barriers, nanotoxicology, and drug screening, as they have significant advantages over two-dimensional (2D) cell models in accurately simulating in vivo behavior of human cells. The accurate spatiotemporal reaction characteristics achieved through the diffusion effect of metal nanoparticles in Matrigel scaffolds are of great importance in nanotoxicology. However, traditional impedance sensors face challenges in performing spatiotemporal dynamic impedance monitoring and evaluating the toxic impact of metal nanoparticles on 3D cells. Here, we propose an impedance sensor that integrates a plug-in vertical electrode array (PVEA) chip with a multi-channel detection system. This sensor can dynamically record 3D cell impedance in the vertical direction, which is consistent with the temporal and spatial progression of metal nanoparticle penetration, and also closely related to the spatiotemporal activity of cells influenced by metal nanoparticles. This method can detect subtle changes in impedance signals at different positions caused by the diffusion of metal nanoparticles, and has high application value in Nanotoxicology evaluation. This universal, high-throughput 3D cell impedance sensor has great potential in toxicity detection and drug screening.

This paper presents the first co-designed 64-channel broadband PMUT array and multi-level CMOS transmitter (TxCMOS) in 0.18 mu m BCD platform, achieving a record 70% bandwidth at 5MHz with only +/- 5V drive voltage. Our innovative integration of multi-PMUT channel architecture and novel multi-level pulser enables high transceiving efficiency for wearables, including 8.4 kPa/V/mm(2) for transmission and 1.2 mV/V for self-reception sensitivity. Integration with a CMOS low-noise amplifier (LNA) boosts received signals to 60mVpp signals (6x voltage gain). Critically, we demonstrate-for the first time-human deep artery imaging via TxCMOS-PMUT, capturing M-mode ultrasound imaging of the brachial artery (5 mm diameter at 15 mm depth). The system achieves 19 mu m resolution in simultaneous upper and lower arterial wall tracking, enabling cardiac-cycle-correlated blood pressure calculation. This breakthrough establishes the broadband TxCMOS-PMUT as a transformative technology for wearable, non-invasive cardiovascular monitoring and high-resolution deep-tissue imaging.

This work proposes a CMOS-compatible label-free epidermal growth factor receptor (EGFR) biosensor based on 13 nm wide silicon nanowire (SiNW) arrays formed by a spaced image transfer (SIT) process. We overcome the Debye screening effect using a smaller molecule aptamer as the capture probe in order to reduce the thickness of the sensing layer and improve the interaction between the target molecule and the probe after capture through the optimization of the sensing interface. We demonstrate that the biosensor shows good stability, specificity, and a wide dynamic range (more than five orders of magnitude), and compared with traditional sensing technologies, our proposed Si nanowire field effect transistor (FET) biosensor provides a noninvasive, ultrasensitive, and stable method for fg/mL-level protein molecule detection. This will help us further understand cellular heterogeneity through single-cell protein analysis, which is expected to be used in molecular diagnostics.

Thermal emitters applied in non-dispersive infrared (NDIR) gas sensors can provide high-quality infrared emission, ensuring accurate gas detection. This review summarizes the development of thermal emitters based on the Micro-Electro-Mechanical Systems (MEMS) technology, highlighting the optimization methods from three perspectives: structural design, microheater design and radiation layer design. These strategies aim to achieve low power consumption, fast response, large modulation depth and high homogeneity of thermal emitters. The review also discusses radiation materials with broadband or narrowband high emissivity, outlining their respective advantages and disadvantages. The performance of different MEMS thermal emitters is analyzed to identify optimal approaches for structural and material designs.

This paper developed a label-free electrical sandwich method based on a novel silicon nanowire field-effect transistor biosensor (SiNW BioFET) for analyzing multiple membrane proteins of small extracellular vesicles (sEVs), enabling subpopulations detection. The detection antibody's negative charge was further increased by coupling negatively charged single-stranded DNA, amplifying the electrical response upon binding to sEVs membrane proteins, thus facilitating the analysis of sEV subpopulations.

Wide-field inspection, nano detection, and real-time observation are essential for investigating biomolecular interaction processes. Surface plasmon resonance microscopy (SPRM) is a label-free, real-time, and nano-imaging method that is widely employed for the dynamic detection of nanoscale biomolecules. The field of view (FOV) of SPRM is limited by the usage of high NA objectives, and a scanning SPRM is required to obtain a large FOV. However, during the scanning, the focus drift introduced by the mechanical vibrations blurs the imaging quality of SPRM, making the detection deviate from the true status. To this end, this paper presents the development of autofocus scanning SPRM (AFS-SPRM) that is capable of performing automated real-time focus drift correction during auto-scanning, thereby enabling high-quality SPRM imaging with large FOV. Only 80 ms is taken to process each defocusing event, and the ability to maintain focus has been improved by 30 times by comparison with SPRM. The AFS-SPRM was successfully employed to distinguish nanoparticles of different sizes and to observe the changes of macrophages in a culture medium containing nanoparticles. This investigation illustrates the superior imaging capabilities of AFS-SPRM and demonstrates its potential for observing interactions between biomolecules at the nanoscale.

Flexible humidity sensors, as pivotal sensing components in the Internet of Things and intelligent era, have achieved significant progress in material innovation, fabrication engineering, and application diversification in recent years. This review systematically presents the current research status of flexible humidity sensors, focusing on the influence of novel humidity-sensitive materials(including polymers, metal oxides, carbon-based materials, and two-dimensional materials) on key performance metrics such as sensitivity, response time, and stability. The optimization effects of fabrication technologies such as screen printing, spraying, and deposition on device performance are also analyzed. Furthermore, the innovative applications of flexible humidity sensors in fields including healthcare, smart agriculture, smart homes, and human-machine interaction are elaborated in detail. These applications highlight the sensors’ adaptability to diverse environmental requirements and their potential to enable intelligent monitoring and interactive systems. Finally, future technological directions for flexible humidity sensors are proposed from the perspectives of material system innovation, improvement of multi-parameter collaborative sensing performance, and optimization of adaptability to complex environments. The proposed development directions are targeted at achieving higher precision, multifunctionality, and self-powered operation, providing insights and guidance for the research and development of next-generation flexible intelligent sensing devices. By bridging material science, manufacturing engineering, and application engineering, this comprehensive review provides a forward-looking perspective on advancing flexible humidity sensing technologies for emerging intelligent systems.

An intelligent humidity sensing system has been developed for real-time monitoring of human behaviors through respiration detection. The key component of this system is a humidity sensor that integrates a thermistor and a micro-heater. This sensor employs porous nanoforests as its sensing material, achieving a sensitivity of 0.56 pF/%RH within a range of 60–90% RH, along with excellent long-term stability and superior gas selectivity. The micro-heater in the device provides a high operating temperature, enhancing sensitivity by 5.8 times. This significant improvement enables the capture of weak humidity variations in exhaled gases, while the thermistor continuously monitors the sensor’s temperature during use and provides crucial temperature information related to respiration. With the assistance of a machine learning algorithm, a behavior recognition system based on the humidity sensor has been constructed, enabling behavior states to be classified and identified with an accuracy of up to 96.2%. This simple yet intelligent method holds great potential for widespread applications in medical assistance analysis and daily health monitoring.

Surface plasmon resonance microscopy (SPRM) is an emerging tool for nanoscale observation. However, while employing the SPRM to observe long-term dynamic processes on the nanoscale, the micrometer-scale optomechanical drift-induced defocus is the main obstacle. This paper proposes a focus drift correction (FDC) enhanced SPRM that calculates the positional deviations of inherent reflection spots to correct defocus displacement without relying on an extra optical system or special imaging pattern, enabling universally applicable nanoscale continuous observation. With the FDC relationships we first revealed, we developed a close-looped SPRM system with focus accuracy reaching 15nm/pixel and applied the proposed approach to statically and dynamically observe single nanoparticles. The results showed that the SPRM combined with our FDC approach can not only visually distinguish two types of nanoparticles with the sizes of 50 and 100nm but also distinguish the two types of 100nm nanoparticles with different materials. These findings indicate that the FDC approach by reflection-based positional detection would provide fundamental support for improving the accuracy and consistency of the SPRM and expand its application for long-term nanoscale monitoring.

Pirani sensors are critical to precision industries such as semiconductor manufacturing. To achieve higher sensitivity, a wider measurement range, and faster response in Pirani sensors, this work presents a MEMS Pirani sensor consisting of a thermoelectric conversion structure and an Al winding structure. The Al winding structure plays dual functionality as both a Joule-heating element and a temperature-sensitive resistor, enabling synergistic operation. Such a multifunctional design eliminates the necessity for external radiation sources in the traditional thermoelectric conversion structure, while simultaneously enabling real-time temperature monitoring. Furthermore, the built-in radiation source allows the sensor to achieve a short thermal response time of 6.9 ms, which is 42 % faster than the conventional sensors that rely on external heating sources. Overall, the sensor exhibits a high sensitivity of 0.873 V/decade at 5 V supply voltage, with a pressure detection range from 0.03 Pa to 105 Pa. Based on such a sensor, a Pirani vacuum detection module has been developed and successfully used in semiconductor equipment. Given the CMOS compatibility of the materials and processes used, the Pirani sensor and the module presented in this work are expected to find broad applications in industrial equipment such as dry etching, vacuum coating, freeze drying, and in inspection of vacuum conditions within packaged MEMS devices.

Directional surface plasmon polaritons (SPPs) are expected to promote the energy efficiency of plasmonic devices, via limiting the energy in a given spatial domain. The directional scattering of dielectric nanoparticles induced by the interference between electric and magnetic responses presents a potential candidate for directional SPPs. Magnetic nanoparticles can introduce permeability as an extra manipulation, whose directional scattered SPPs have not been investigated yet. In this work, we demonstrated the directional scattered SPPs by using single magnetic nanoparticles via simulation and experiment. By increasing the permeability and particle size, the high-order TEM modes are excited inside the particle and induce more forward directional SPPs. It indicated that the particle size manifests larger tuning range compared with the permeability. Experimentally, the maximum forward-to-backward (F-to-B) SPP scattering intensity ratio of 118.52:1 is visualized by using a single 1 mu m Fe 3 O 4 magnetic nanoparticle. The directional scattered SPPs of magnetic nanoparticles are hopeful to improve the efficiency of plasmonic devices and pave the way for plasmonic circuits on-chip. (c) 2024 Optica Publishing Group

Wearable ultrasound imaging technology has become an emerging modality for the continuous monitoring of deep-tissue physiology, providing crucial health and disease information. Fast volumetric imaging that can provide a full spatiotemporal view of intrinsic 3D targets is desirable for interpreting internal organ dynamics. However, existing 1D ultrasound transducer arrays provide 2D images, making it challenging to overcome the trade-off between the temporal resolution and volumetric coverage. In addition, the high driving voltage limits their implementation in wearable settings. With the use of microelectromechanical system (MEMS) technology, we report an ultrasonic phased-array transducer, i.e., a 2D piezoelectric micromachined ultrasound transducer (pMUT) array, which is driven by a low voltage and is chip-compatible for fast 3D volumetric imaging. By grouping multiple pMUT cells into one single drive channel/element, we propose an innovative cell–element–array design and operation of a pMUT array that can be used to quantitatively characterize the key coupling effects between each pMUT cell, allowing 3D imaging with 5-V actuation. The pMUT array demonstrates fast volumetric imaging covering a range of 40 mm × 40 mm × 70 mm in wire phantom and vascular phantom experiments, achieving a high temporal frame rate of 11 kHz. The proposed solution offers a full volumetric view of deep-tissue disorders in a fast manner, paving the way for long-term wearable imaging technology for various organs in deep tissues.