Microsystems & Nanoengineering最新文献

Establishing robust pharmacokinetics-pharmacodynamics (PK-PD) correlations remains a major challenge owing to high selectivity and low permeability of the blood-brain barrier (BBB), which limits the predictive power of conventional plasma pharmacokinetics on specific brain tissue. Here, we present a highly biomimetic microfluidic BBB-brain organ-on-a-chip combined with liquid chromatography-mass spectrometry (LC-MS) and electrochemical sensing technology for micro PK-PD monitoring with target cells. The platform incorporates human cerebral microvascular endothelial cells and neuron-like cells cultured on opposite sides of a collagen/fibronectin-modified porous membrane under physiological shear stress. This configuration reinforces the physical, metabolic and physiological barrier functions of BBB, as evidenced by the high expression of tight junction proteins, low apparent permeability, expression of efflux transporters, and reversible response to hypertonic stimuli. A neurodegenerative disease model is induced using 1-methyl-4-phenylpyridinium iodide (MPP⁺) to recapitulate key pathological features of early-stage Parkinson's disease. The pharmacokinetic profile of pramipexole (PPX) is monitored using both LC-MS and an integrated, regenerable electrochemical sensor. The sensor enables in situ, real-time and online detection of PPX with high sensitivity and specificity, showing strong concordance with LC-MS. Furthermore, neurotransmitter (norepinephrine) exocytosis level is quantified as a pharmacodynamic indicator, enabling micro PK-PD correlation within the disease-on-a-chip model. Collectively, the proposed new method for micro PK-PD study is expected to provide great prospects for the preclinical screening and action mechanism research of novel anti-Parkinson's disease drugs.

Surface acoustic wave radio frequency identification (SAW RFID) has gained widespread adoption in remote sensing and identification. However, conventional SAW RFID tags suffer from significant energy loss due to the inherently low reflectance of standard reflectors, fundamentally limiting their wireless interrogation range. To address this limitation, this paper proposes a novel SAW RFID architecture employing reflective multistrip couplers (RMSCs), which exploit the velocity difference between symmetric and antisymmetric wave modes to achieve coherent reflection, thereby circumventing conventional electrical or mechanical reflection mechanisms. Numerical simulations were conducted to analyze performance deterioration induced by parasitic resistances and capacitance and to identify the optimal strip number for peak reflectance. The fabricated RMSC reflector achieves a low loss of 1 dB, with a reflectance difference of merely 0.33 dB compared to the simulation results. A 433 MHz SAW RFID prototype implementing RMSC reflectors on a 128°YX-LiNbO₃ single-crystal substrate demonstrated a -10.63 dB peak time-domain amplitude at room temperature, representing a substantial improvement over conventional designs. Temperature characterization from -20 °C to 90 °C revealed linear functions in time delay and phase responses, with coefficients of determination (R²) exceeding 0.9999. These results validate the RMSC reflector as a high-reflectance solution for enhancing SAW RFID performance, suggesting significant potential for long-range wireless sensing applications.

The reliability of through-glass via (TGV) interconnects is critical for advanced semiconductor packaging. This work investigates microstructural and mechanical evolution in electroplated TGV-Cu subjected to long-term aging at 250 °C. TGV samples were fabricated via laser-induced etching and double-sided copper electroplating, then aged for up to 1008 h. Nanoindentation revealed region-dependent reductions in hardness (from 2.0-2.5 GPa to below 0.5 GPa) and modulus (from 110-130 GPa to 40-90 GPa), with surface-near regions most affected. The glass substrate maintained stable mechanical properties until microcracks formed after 1008 h. EBSD quantification showed grain-size enlargement from 0.46 µm to 1.86 µm and a concurrent decrease in dislocation density. Molecular dynamics simulations of 3, 4, 5 nm grains corroborated the inverse relationship between grain size and micro-mechanical properties. A hybrid Potts-phase field model further linked grain coarsening to stress relaxation and elastic-energy minimization, revealing that as grains grow, the overall von Mises stress in the structure decreases; high-modulus grains retain relatively higher local stresses, while low-modulus, low-stress grains exhibit faster growth rates. Electrical I-V measurements confirmed stable ohmic behavior, despite a drop in insulation resistance. These integrated experimental and computational insights provide theoretical guidance for optimizing TGV interposer design and ensuring long-term operational reliability in heterogeneous integration technologies.

Surface plasmon resonance (SPR) biosensoris a new type of high sensitivity, real-time, label-free detection technology, which plays an increasingly important role in the biomedicine field. Considering the urgent requirement of trace detection, especially for diagnosing early-stage diseases, the demand for high detection sensitivity of sensors is increasing. In recent years, various nanostructures have been proposed to design SPR biosensors. By constructing composite nanostructures, the detection sensitivity has been significantly enhanced, which has become a promising solution to expand the application of SPR biosensors. This review systematically summarized the basic principle, fabrication and illustrative application of SPR biosensors based on versatile nanostructures. Firstly, the mechanisms of various nanostructures to enhance the detection sensitivity of SPR biosensors were clarified. Then, the preparation strategies of various nanostructures were comprehensively illustrated. In addition, this review also summarized the latest applications of SPR biosensors with different structures. Finally, this review carefully highlighted the current challenges and possible development directions in future.

Recent innovations in skin microphysiological systems (MPSs) have gained momentum following regulatory advances such as the FDA Modernization Act 2.0 and the global shift toward alternatives to animal testing. This review highlights the development of three major technologies-3D bioprinting, skin organoids, and skin-on-a-chip-and their roles in replicating human skin physiology for research and preclinical applications. We examine how these platforms model complex skin functions, including epidermal barrier formation, vascular and immune interactions, and disease phenotypes such as psoriasis, atopic dermatitis, melanoma, and viral infections. In addition to summarizing their utility in toxicological screening and therapeutic evaluation, we explore how current OECD test guidelines may guide future validation efforts. Finally, we discuss emerging strategies for integrating automation and machine learning-based image analysis to enable scalable, high-content screening of skin MPS models across diverse applications.

State-of-the-art high-density multielectrode arrays enable the recording of simultaneous spiking activity from hundreds of neurons. Although significant efforts have been dedicated to enhancing neural recording devices and developing more efficient sorting algorithms, there has been relatively less focus on the allocation of microelectrodes-a factor that undeniably affects spike sorting effectiveness and ultimately the total number of detected neurons. Here, we systematically examined the relationship between optimal electrode spacing and spike sorting efficiency by creating virtual sparser layouts from high-density recordings through spatial downsampling. We assessed spike sorting performance by comparing the quantity of well-isolated single units per electrode in sparse configurations across various brain regions (neocortex and thalamus), species (rat, mouse, and human) and various spike-sorting algorithms. Enabling the theoretical estimation of optimal electrode arrangements, we complement experimental results with a geometrical modeling framework. Contrary to the general assumption that higher electrode density inherently leads to more efficient sorting, both our theoretical and experimental results reveal a clear optimum for electrode spacing specific to species and regions. We demonstrate that carefully choosing optimal electrode distances could yield a total of 1.7-3.75 times increase in spike sorting efficiency. These findings emphasize the necessity of species- and region-specific microelectrode design optimization.

Capsule endoscopy has revolutionized gastrointestinal (GI) diagnosis but is limited to imaging, often requiring invasive procedures for subsequent therapy. This work presents a magnetically actuated robotic capsule endoscope (MARCE) that integrates controllable magnetic navigation, real-time visualization, and targeted drug delivery via microneedle patches to bridge the gap between diagnosis and therapy. The MARCE features a retractable micro-camera for continuous monitoring of the GI tract, dual-layer hyaluronic acid microneedle patches enabling multi-point drug administration, and an electrothermally triggered protective cover to prevent premature dissolution in GI fluids. Sized similarly to conventional clinical capsules (11.8 mm in diameter and 21.5 mm in length), the MARCE demonstrates controlled epinephrine release from its microneedle patches (up to 0.4 mg) and provides sufficient magnetic actuation force (~0.58 N) and torque (~18.4 N mm) for intestine locomotion and penetration. Driven by a custom-developed electromagnetic actuation system, the MARCE achieves precise 3D locomotion with an average positional error <1.5 mm controlled microneedles penetration (with a peak force of 0.15 N), and successful drug delivery across multiple lesions in ex-vivo porcine intestinal tissue. This integrated platform streamlines diagnostic-therapeutic workflows, offering a minimally invasive solution for GI disorders such as bleeding, with potential to enhance patient comfort and treatment precision.

Cell therapy products are rapidly transforming clinical practice, but their short shelf-lives and inability to undergo terminal sterilization create major challenges for sterility testing. Conventional rapid microbiological methods (RMMs) are hindered by the dense cellular background of therapeutic samples, which masks rare microbial contaminants and necessitates pre-analytical processing. Efficient separation of microorganisms from high-density cell suspensions is therefore a critical prerequisite for enabling real-time, in-process sterility assurance. Here, we systematically elucidate the Dean flow-dominated migration mechanism and determine its effective range for continuous, label-free separation of non-typical contaminants ≤ 5 μm in microchannels exceeding 40 μm in height. We demonstrate that particles with ap/h < 0.05 undergo exclusive Dean-induced lateral migration, while those near the inertial focusing threshold (ap/h ≈ 0.07) exhibit a Reynolds number-dependent transition between unfocused and centerline-focused streams. Leveraging these principles, we designed optimized channel geometries that achieved > 95% separation efficiency and > 96% purity of T cells versus three morphologically distinct bacteria at 10⁵ bacteria/mL. At ultra-low loads (< 10 CFU/mL), culture-based assays confirmed 100% detection for inocula > 1 CFU/mL. Our findings validate Dean migration as a governing mechanism for submicron particle separation and provide a path toward integrating microfluidic modules into closed CAR-T manufacturing platforms, advancing real-time microbial quality control in cell therapy production.

Continuous glucose monitoring (CGM) is vital for diabetes care, but current invasive electrochemical sensors of blood glucose often cause potential infection and skin irritation. Non-invasive sensors in sweat glucose are promising alternatives but limited by low sensitivity and poor compatibility with complex sweat environments, because the sweat glucose has concentrations of 20 - 600 μmol/L and are 100-fold more dilute than the blood glucose. Here, we report a portable optical sensing system that integrates an optical watch prototype with functionalized plasmonic silver-coated silicon nanopillars substrate for non-invasive and label-free glucose detection in sweat. The nanopillar sensor with wide-range plasmonic hot spots is functionalized with 4-mercaptophenylboronic acid for selective glucose capture and optical signal transduction through both Raman scattering and plasmonic detection. The optical watch system has a compact LED illumination at 623-660 nm and wireless transmission of data to a smartphone application. Significantly, the whole system demonstrated excellent sensitivity down to 22 μmol/L and high selectivity in detecting glucose in artificial sweat, which were validated by human sweat samples to confirm its applicability in real-life scenarios. Our study offers a promising portable and non-invasive alternative to traditional CGM and highlights the potential of integrating nanophotonic sensors with wearable platforms for continuous health monitoring and personalized medicine.

Human exhaled gas is rich in biomarker information that could be used for early diagnosis of disease. With the development of nanotechnology and the Internet of Medical Things (IoMT), AI-assisted nano gas sensor arrays as a non-invasive exhaled gas detection platform brings fascinating technological solutions to the field of breath detection. Herein, we designed a new heterojunction sensing array by anchoring n-GaN nanoparticles on MOF-derived p-MO_x porous nanosheets. The gas sensor arrays demonstrated remarkable response speed (10 s), excellent repeatability, and extreme anti-humidity with a lower detection limit of 1 ppb at room temperature. Energy band structure combined with density functional theory (DFT) calculations were used to analyze the entire gas sensing process. Furthermore, we developed a new breath detection device and successfully performed clinical patient exhaled gas detection. With the assistance of ensemble learning, the recognition accuracy of lung cancer patients and healthy volunteers can reach 95.8%. This work provides an innovative technology for the construction of heterojunction sensor arrays and exhaled gas detection device, which has a promising application prospect in the field of early disease diagnosis and IoMT.