Search

Abstract: We report a micromachined H2 sensor that is composed of a Pt micro-heater, low-stress insulating layer (SiO2/SiNx/SiO2), Pt-interdigitated electrodes, and gas sensing materials. Three types of Pt micro-heater are designed as function of electrode width, and their thermal properties are systematically analyzed by finite element modeling FEM with infrared camera. The power consumptions when the surface temperature reached 150, 200, 250, and 300 °C are calculated to approximately 33, 48, 67 and 85 mW, respectively. The response of the PdO nanoparticles-decorated TiO2 thin films to H2 is much higher than those of other gases such as CH4 and CO at 200 °C (48 mW). Further, the response time is reduced to approximately 3 s. The enhancement of gas sensing properties is related to well-designed micro-heater and catalytic effects of PdO nanoparticles such as electronic and chemical sensitization. These results suggest that the PdO nanoparticles-decorated TiO2 thin film, namely MEMS-based H2 sensors are very promising for use in IoT application to improve the quality of human’s life.Graphical Abstract: [ABSTRACT FROM AUTHOR]

We report a sputtered PdO decorated TiO2 sensing layer by radiofrequency (RF) sputtering methods and demonstrated gas sensing performance for H2 gas. We prepared sputtered anatase TiO2 sensing films with 200 nm thickness and deposited a Pd layer on top of the TiO2 films with a thickness ranging from 3 nm to 13 nm. Using an in situ TiO2/Pd multilayer annealing process at 550°C for 1 hour, we observed that Pd turns into PdO by Auger electron spectroscopy (AES) depth profile and confirmed decorated PdO on TiO2 sensing layer from scanning electron microscope (SEM) and atomic-force microscope (AFM). We also observed a positive sensing signal for 3, 4.5, and 6.5 nm PdO decorated TiO2 sensor while we observed negative output signal for a 13.5 nm PdO decorated one. Using a microheater platform, we acquired fast response time as ~11 sec and sensitivity as 6 μV/ppm for 3 nm PdO under 33 mW power. [ABSTRACT FROM AUTHOR]

Targeting exosome for liquid biopsy has gained significant attention for its diagnostic and therapeutic potential. For detecting neuronal disease diagnosis such as Alzheimer's disease (AD), the main technique for identifying AD still relies on positron-emission tomography (PET) imaging to detect the presence of amyloid-β (Aβ). While the detection of Aβ in cerebrospinal fluid has also been suggested as a marker for AD, the lack of quantitative measurements has compromised existing assays. In cerebrospinal fluid, in addition to Aβ, T-Tau, and P-Tau, alpha-synuclein has been considered a biomarker of neurodegeneration. This review suggests that and explains how the exosome can be used as a neuronal diagnostic component. To this end, we summarize current progress in exosome preparation/isolation and quantification techniques and comment on the outlooks for neuronal exosome-based diagnostic techniques. [ABSTRACT FROM AUTHOR]

Lateral flow assays (LFAs) have emerged as indispensable tools for point-of-care testing during the pandemic era. However, the interpretation of results through unassisted visual inspection by untrained individuals poses inherent limitations. In our study, we propose a novel approach that combines computer vision (CV) and lightweight machine learning (ML) to overcome these limitations and significantly enhance the performance of LFAs. By incorporating CV-assisted analysis into the LFA assay, we achieved a remarkable three-fold improvement in analytical sensitivity for detecting Influenza A and for SARS-CoV-2 detection. The obtained R 2 values reached approximately 0.95, respectively, demonstrating the effectiveness of our approach. Moreover, the integration of CV techniques with LFAs resulted in a substantial amplification of the colorimetric signal specifically for COVID-19 positive patient samples. Our proposed approach, which incorporates a simple machine learning algorithm, provides substantial enhancements in assay sensitivity, improving diagnostic efficacy and accessibility of point-of-care testing without requiring significant additional resources. Moreover, the simplicity of the machine learning algorithm enables its standalone use on a mobile phone, further enhancing its practicality for point-of-care testing.

EVs/exosomes are considered as the next generation of biomarkers, including for liquid biopsies. Consequently, the quantification of EVs/exosomes is crucial for facilitating EV/exosome research and applications. Paper-based enzyme-linked immunosorbent assay (p-ELISA) is a portable diagnostic system with low cost that is simple and easy to use; however, it shows low sensitivity and linearity. In this study, we develop p-ELISA for targeting EVs/exosomes by using streptavidin agarose resin-based immobilization (SARBI). This method reduces assay preparation times, provides strong binding, and retains good sensitivity and linearity. The time required for the total assay, including preparation steps and surface immobilization, was shortened to ∼2 h. We evaluated SARBI p-ELISA systems with/without CD63 capture Ab and then with fetal bovine serum (FBS) and EVs/exosome-depleted fetal bovine serum (dFBS). The results provide evidence supporting the selective capture ability of SARBI p-ELISA. We obtain semiquantitative p-ELISA results using an exosome standard (ES) and human serum (HS), with R2 values of 0.95 and 0.92, respectively.

A microsized slit-embedded cantilever sensor (slit cantilever) was fabricated and evaluated as a biosensing platform in a liquid environment. In order to minimize the degradation caused by viscous damping, a 300 × 100 µm² (length × width) sized cantilever was released by a 5 µm gap-surrounding and vibrated by an internal piezoelectric-driven self-actuator. Owing to the structure, when the single side of the slit cantilever was exposed to liquid a significant quality factor (Q = 35) could be achieved. To assess the sensing performance, the slit cantilever was exploited to study the biophysical kinetics related to Aβ peptide. First, the quantification of Aβ peptide with a concentration of 10 pg/mL to 1 μg/mL was performed. The resonant responses exhibited a dynamic range from 100 pg/mL to 100 ng/mL (-56.5 to -774 ΔHz) and a dissociation constant (K D ) of binding affinity was calculated as 1.75 nM. Finally, the Aβ self-aggregation associated with AD pathogenesis was monitored by adding monomeric Aβ peptides. As the concentration of added analyte increased from 100 ng/mL to 10 µg/mL, both the frequency shift values (-813 to -1804 ΔHz) and associate time constant increased. These results showed the excellent sensing performance of the slit cantilever overcoming a major drawback in liquid environments to become a promising diagnostic tool candidate., Competing Interests: The authors declare no conflict of interest.

Preventing unexpected explosive attacks and tracing explosion-related molecules require the development of highly sensitive gas-vapor detection systems. For that purpose, a micromechanical cantilever-based olfactory sensing system including a sample preconcentrator was developed to detect 2,4-dinitrotoluene (2,4-DNT), which is a well-known by-product of the explosive molecule trinitrotoluene (TNT) and exists in concentrations on the order of parts per billion in the atmosphere at room temperature. A peptide receptor (His-Pro-Asn-Phe-Ser-Lys-Tyr-Ile-Leu-His-Gln-Arg) that has high binding affinity for 2,4-DNT was immobilized on the surface of the cantilever sensors to detect 2,4-DNT vapor for highly selective detection. A micro-preconcentrator (µPC) was developed using Tenax-TA adsorbent to produce higher concentrations of 2,4-DNT molecules. The preconcentration was achieved via adsorption and thermal desorption phenomena occurring between target molecules and the adsorbent. The µPC directly integrated with a cantilever sensor and enhanced the sensitivity of the cantilever sensor as a pretreatment tool for the target vapor. The response was rapidly saturated within 5 min and sustained for more than 10 min when the concentrated vapor was introduced. By calculating preconcentration factor values, we verified that the cantilever sensor provides up to an eightfold improvement in sensing performance.

The ability to measure pressure and force is essential in biomedical applications such as minimally invasive surgery (MIS) and palpation for detecting cancer cysts. Here, we report a force sensor for measuring a shear and normal force by combining an arrayed piezoelectric sensors layer with a precut glass top plate connected by four stress concentrating legs. We designed and fabricated a thin film piezoelectric force sensor and proposed an enhanced sensing tool to be used for analyzing gentle touches without the external voltage source used in FET sensors. Both the linear sensor response from 3 kPa to 30 kPa and the exact signal responses from the moving direction illustrate the strong feasibility of the described thin film miniaturized piezoelectric force sensor.