Biosensors and Bioelectronics最新文献

Oxidative stress is widely recognized as a pivotal factor contributing to numerous Central Nervous System (CNS) ailments. The concentrations of hydrogen peroxide (H₂O₂) and phosphorylated proteins within the human body serve as crucial indicators of oxidative stress. As such, the real-time monitoring of H₂O₂ and phosphorylated proteins in sweat is vital for the early identification, diagnosis, and management of diseases linked to oxidative stress. In this context, we present a novel microfluidic wearable electrochemical sensor by modifying the electrode with Prussian blue (PB) and loading sulfur-rich vacancy-containing molybdenum disulfide (MoS_2-X) onto Multi-walled carbon nanotube (CNTs) to form coaxially layered CNTs/MoS_2-X, which was then synthesized with highly dispersed titanium dioxide nanoparticles (TiO₂) to synthesize CNTs/MoS_2-X/TiO₂ composites for the detection of human sweat H₂O₂ and phosphorylated proteins, respectively. This structure, with its sulfur vacancies and coaxial layering, significantly improved sensitivity of electrochemical sensors, allowing it to detect H₂O₂ in a range of 0.01–1 mM with a detection limit of 4.80 μM, and phosphoproteins in a range of 0.01–1 mg/mL with a threshold of 0.917 μg/mL. Furthermore, the miniature sensor demonstrates outstanding performance in detecting analytes in both simulated and real sweat. Comprehensive biosafety assessments have validated the compatibility of the electrode material, underscoring the potential of sensor as a reliable and non-invasive method for tracking biomarkers linked to CNS disorders. This microfluidic wearable electrochemical biosensor with high performance and biosafety features shows great promise for the development of cutting-edge wearable technology devices for tracking CNS disease indicators.

Automation of liquid handling is indispensable to improve throughput and reproducibility in biochemical assays. However, the incorporation of automated systems into laboratory workflows is often hindered by the high cost and complexity associated with building robotic liquid handlers. Here, we report a 3D-printed liquid handler based on a fluidic manifold, thereby obviating the need for complex robotic mechanisms. The fluidic manifold, termed a dispensing and aspirating (DA) device, comprises parallelized multi-pipette structures connected by distribution and aspiration channels, enabling the precise supply and removal of reagents, respectively. Leveraging the versatility of 3D printing, the DA device can be custom-designed and printed to fit specific applications. As a proof-of-principle, we engineered a 3D-printed liquid handler dedicated for 3D digital rolling circle amplification (4DRCA), an advanced biochemical assay involving multiple sample preparation steps such as antibody incubation, cell fixation, nucleic acid amplification, probe hybridization, and extensive washing. We demonstrate the efficacy of the 3D-printed liquid handler to automate the preparation of clinical samples for the simultaneous, in situ analysis of oncogenic protein and transcript markers in B-cell acute lymphoblastic leukemia cells using 4DRCA. This approach provides an effective and accessible solution for liquid handling automation, offering high throughput and reproducibility in biochemical assays.

In recent years, in vitro three-dimensional (3D) neuronal network models utilizing extracellular matrices have been advancing. To understand the network activity from these models, attempts have been made to measure activity in multiple regions simultaneously using a microelectrode array (MEA). Although there hve been many attempts to measure the activity of 3D networks using 2-dimensional (2D) MEAs, the physical coupling between the 3D network and the microelectrodes was not stable and needed to be improved. In this study, we proposed a neuronal cluster interface that improves the active channel ratio of commercial 2D MEAs, enabling reliable measurement of 3D network activity. To achieve this, neuronal clusters, which consist of a small number of neurons, were patterned on microelectrodes and used as mediators to transmit the signal between the 3D network and the microelectrodes. We confirmed that the patterned neuronal clusters enhanced the active channel ratio and SNR(signal-to-noise-ratio) about 3D network recording and stimulation for a month. Our interface was able to functionally connect with 3D networks and measure the 3D network activity without significant alternation of activity characteristics. Finally, we demonstrated that our interface can be used to analyze the differences in the dynamics of 3D and 2D networks and to construct the 3D clustered network. This method is expected to be useful for studying the functional activity of various 3D neuronal network models, offering broad applications for the use of these models.

Surface enhanced Raman spectroscopy (SERS) utilizes the fingerprint features of molecular vibrations to identify and detect substances. However, in traditional single focus excitation scenarios, its signal collection efficiency of the objective is restricted. Furthermore, the uneven distribution of samples on the SERS substrate would result in poor signal stability, while the excitation power is limited to avoid sample damage. SERS detection system always requires precise adjustment of focal length and spot size, making it difficult for point-of-care testing applications. Here, we proposed a SERS microfluidic chip with barium titanate microspheres array (BTMA) embedded using vacuum self-assembled hot-pressing method for SERS detection with simultaneous enhancement of sensitivity and stability. Due to photonic nano-jets and directional antenna effects, high index microspheres are perfect micro-lens for effective light focusing and signal collecting. The BTMA can not only disperse excitation beam into an array of focal points covering the target uniformly with very low signal fluctuation, but enlarge the power threshold for higher signal intensity. We conducted a proof-of-principle experiment on chip for the detection of bacteria with immuno-magnetic tags and immuno-SERS tags. Together with magnetic and ultrasonic operations, the target bacteria in the flow were evenly congregated on the focal plane of BTMA. It demonstrated a limit of detection of 5 cells/mL, excellent signal reproducibility (error∼4.84%), and excellent position tolerance of 500 μm in X–Y plane (error∼5.375%). It can be seen that BTMA-SERS microfluidic chip can effectively solve the contradiction between sensitivity and stability in SERS detection.

The integration between RNA-sequencing and micro-spectroscopic techniques has recently profiled the advanced transcriptomic discoveries on the cellular level. In the current study, by combining the sensation approach (including bio-molecules structural evaluation, high throughput next-generation sequencing (HT-NGS), and confocal Raman microscopy) the functionality on the single live cancer cells’ ferroptosis and apoptosis signaling pathways is visualized. Our study reveals a hydrophobic tunnel by phycocyanin-isoprene molecule (PC-SIM) electrostatic charge within hepatoma cells (HepG2) that activates the ferritin light chain (FTL) and caspase-8 associate protein (CASP8AP2) ferroptosis responsible genes. Moreover, this research proves that PC-vanillin (VAN) stimulation induces the actin-binding factor profilin-1 (PFN1), subsequently in situ tracking its expression at 1139.75 cm⁻¹ microRaman wavenumber. While PC-thymol (THY) induces the lysophospholipase-2 (LYPLA2) (p-value = 0.009) and acetylneuraminate-9-O-acetyltransferase (CASD1) (p-value = 0.022) at 1143.19 cm⁻¹. our findings establish a new concept to promote the cross-disciplinary use of instant cellular-based detection technology for intermediary evaluating the signaling cellular transcriptome.

As one class of molecular imprinted polymers (MIPs), surface imprinted polymer (SIP)-based biosensors show great potential in direct whole-bacteria detection. Micro-contact imprinting, that involves stamping the template bacteria immobilized on a substrate into a pre-polymerized polymer matrix, is the most straightforward and prominent method to obtain SIP-based biosensors. However, the major drawbacks of the method arise from the requirement for fresh template bacteria and often non-reproducible bacteria distribution on the stamp substrate. Herein, we developed a positive master stamp containing photolithographic mimics of the template bacteria (E. coli) enabling reproducible fabrication of biomimetic SIP-based biosensors without the need for the “real” bacteria cells. By using atomic force and scanning electron microscopy imaging techniques, respectively, the E. coli-capturing ability of the SIP samples was tested, and compared with non-imprinted polymer (NIP)-based samples and control SIP samples, in which the cavity geometry does not match with E. coli cells. It was revealed that the presence of the biomimetic E. coli imprints with a specifically designed geometry increases the sensor E. coli-capturing ability by an “imprinting factor” of about 3. These findings show the importance of geometry-guided physical recognition in bacterial detection using SIP-based biosensors. In addition, this imprinting strategy was employed to interdigitated electrodes and QCM (quartz crystal microbalance) chips. E. coli detection performance of the sensors was demonstrated with electrochemical impedance spectroscopy (EIS) and QCM measurements with dissipation monitoring technique (QCM-D).

In this work, we present an electrochemical sensor for fast, low-cost, and easy detection of the SARS-CoV-2 spike protein in infected patients. The sensor is based on a selected combination of nanomaterials with a specific purpose. A bioconjugate formed by Few-layer bismuthene nanosheets (FLB) and tetrahedral DNA nanostructures (TDNs) is immobilized on Carbon Screen-Printed Electrodes (CSPE). The TDNs contain on the top vertex an aptamer that specifically binds to the SARS-CoV-2 spike protein, and a thiol group at the three basal vertices to anchor to the FLB. The TDNs are also marked with a redox indicator, Azure A (AA), which allows the direct detection of SARS-CoV-2 spike protein through changes in the current intensity of its electrolysis before and after the biorecognition reaction. The developed sensor can detect SARS-CoV-2 spike protein with a detection limit of 1.74 fg mL⁻¹ directly in nasopharyngeal swab human samples. Therefore, this study offers a new strategy for rapid virus detection since it is versatile enough for different viruses and pathogens.

The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat quality because, athletes might have positive test for CLN even after consuming very low quantity of CLN contaminated meat. Numerous materials applied for CLN monitoring faced potential challenges like sluggish ion transport, non-uniform ion/molecule movement, and inadequate electrode surface binding. To overcome these shortcomings, herein we engineered bimetallic zeolitic imidazole framework (BM-ZIF) derived N-doped porous carbon embedded Co nanoparticles (CN-CoNPs), dispersed on conductive cellulose acetate-polyaniline (CP) electrospun nanofibers for sensitive electrochemical monitoring of CLN. Interestingly, the smartly designed CN-CoNPs wrapped CP (CN-CoNPs-CP) electrospun nanofibers offers rapid diffusion of CLN molecules to the sensing interface through amine and imine groups of CP, thus minimizing the inhomogeneous ion transportation and inadequate electrode surface binding. Additionally, to synchronize experiments, machine learning (ML) algorithms were applied to optimize, predict, and validate voltametric current responses. The ML-trained sensor demonstrated high selectivity, even amidst interfering substances, with notable sensitivity (4.7527 μA/μM/cm²), a broad linear range (0.002–8 μM), and a low limit of detection (1.14 nM). Furthermore, the electrode exhibited robust stability, retaining 98.07% of its initial current over a 12-h period. This ML-powered sensing approach was successfully employed to evaluate meat quality in terms of CLN level. To the best of our knowledge, this is the first study of using ML powered system for electrochemical sensing of CLN.

Functional nucleic acids (FNAs) have attracted increasing attention in recent years due to their diverse physiological functions. The understanding of their conformational recognition mechanisms has advanced through nucleic acid tailoring strategies and sequence optimization. With the development of the FNA tailoring techniques, they have become a methodological guide for nucleic acid repurposing. Therefore, it is necessary to systematize the relationship between FNA tailoring strategies and the development of nucleic acid multifunctionality. This review systematically categorizes eight types of FNA multifunctionality, and introduces the traditional FNA tailoring strategy from five aspects, including deletion, substitution, splitting, fusion and elongation. Based on the current state of FNA modification, a new generation of FNA tailoring strategy, called the high-content tailoring strategy, was unprecedentedly proposed to improve FNA multifunctionality. In addition, the multiple applications of rational tailoring-driven FNA performance enhancement in various fields were comprehensively summarized. The limitations and potential of FNA tailoring and repurposing in the future are also explored in this review. In summary, this review introduces a novel tailoring theory, systematically summarizes eight FNA performance enhancements, and provides a systematic overview of tailoring applications across all categories of FNAs. The high-content tailoring strategy is expected to expand the application scenarios of FNAs in biosensing, biomedicine and materials science, thus promoting the synergistic development of various fields.

A drop-casting method for the scalable construction of a solar cell-type light-addressable photoelectrochemical (PEC) sensor on commercial phenol resin (PR) plates is reported. The sensor was fabricated by laser writing of addressable laser-induced graphene (LIG) electrode arrays on PR plates with ring-disc dual-electrode cell configurations using a 405 nm laser machine. Beneficial from the good hydrophilicity of PR-based LIG and the excellent film formation of bismuth sulfide nanorods (Bi₂S₃ NRs), uniform Bi₂S₃ photovoltaic films can be reproducibly deposited onto the LIG disc photoanode array via drop casting modification, which show a sensitive photocurrent response toward thiocholine (TCl) when the ring cathode array was coated with Ag/AgCl. An acetylcholinesterase (AChE)-based PEC biosensor was therefore constructed by a similar drop-casting modification method. The resulting biosensor exhibits good sensitivity toward an AChE inhibitor, i.e., galantamine hydrobromide (GH), with a calibration range of 10–300 μM and a detection limit of 7.33 μM (S/N = 3). Moreover, the biosensor possesses good storage stability, which can achieve the high-throughput screening of AChE inhibitor drugs from traditional Chinese medicines (TCMs). The present work thus demonstrates the promising application of LIG technology in constructing light-addressable PEC sensing devices with high performance and low cost.