Boosting the performance of an iontophoretic biosensing system with a graphene aerogel and Prussian blue for highly sensitive and noninvasive glucose monitoring.

Diabetes and impaired glucose regulation (IGR) threaten the lives and health of numerous patients. Interstitial fluid (ISF) glucose, displaying an excellent correlation with blood glucose, is highly desired to address the limitations of invasive and minimally invasive glucose detection. Herein, we present a screen-printed iontophoretic biosensing system to extract ISF noninvasively and perform in situ instant glucose detection. A three-dimensional graphene aerogel combined with Prussian blue (GA@PB) was introduced as an electron mediator, providing suitable support for glucose oxidase (GOx) immobilization, highly boosting the detection sensitivity. Additionally, a self-made diffuse cell and an ex vivo model were developed to demonstrate the efficacy of ISF extraction based on reverse iontophoresis technology. Highly sensitive and accurate detection of ISF glucose could be achieved with an LOD of 0.26 mM over a 0-15 mM range. Finally, tests on healthy volunteers were conducted to further validate the feasibility of this as-proposed system. Combined with its well flexible and biocompatible features, it holds considerable prospects in the development of wireless wearable biosensors for continuous blood glucose monitoring.

Estimation of soil organic carbon in LUCAS soil database using Vis-NIR spectroscopy based on hybrid kernel Gaussian process regression.

Soil Organic Carbon (SOC) is crucial for determining soil fertility and environmental quality. The problem with traditional SOC chemical analysis methods is that they are time-consuming and resource-intensive. In recent years, visible-near infrared (Vis-NIR) spectroscopy has been employed as an alternative method for SOC determination. However, when applied on a larger scale, the prediction accuracy of soil properties decreases due to the heterogeneity of samples. Therefore, this study compared and analyzed the performance of partial least squares regression (PLSR), support vector regression (SVR), random forest (RF), and gaussian process regression (GPR) in predicting SOC. On this basis, a GPR model based on a hybrid kernel function (HKF-GPR) was proposed for SOC prediction. This hybrid kernel function was designed according to the properties of single kernel functions and the characteristics of soil spectral data. Results indicate that in large soil spectral databases, the GPR model outperforms other models in estimating SOC. The HKF-GPR model achieved the best SOC estimation accuracy, with an R2 of 0.7671, RMSE of 5.2934 g/kg, RPD of 2.0721, and RPIQ of 2.5789. Compared to other regression models, the HKF-GPR model proposed in this paper offers broader applicability and superior performance, enabling SOC estimation in large soil spectral libraries.

A stochastic resonance etection algorithm based on orthonormalized basis function for magnetic anomaly detection.

To address the problem that the performance of the detector in airborne magnetic anomaly detection (MAD) is terrible, a stochastic resonance (SR) detection algorithm based on orthonormalized basis function (OBF-SR) is proposed for MAD under low signal-to-noise ratio conditions. The signal contaminated by noise is first preprocessed by the OBF method, where the sum of the three components in the OBF space is selected as the SR system input. Then, a parallel SR system with different initial states is designed to detect the signal. Finally, the simulation analysis of MAD methods is performed to draw a comparison between the OBF-SR method, the typical SR method, and the OBF method. The results show that the OBF-SR method outperforms the SR and OBF methods in the detection probability and detection range under the same conditions.

ROCK inhibitor Y­27632 protects rats against cerebral ischemia/reperfusion­induced behavioral deficits and hippocampal damage.

Cerebral ischemic injury is a major cause of death and long­term disability worldwide that leads to neurological and behavioral deficits, and for which successful treatments are still lacking. Ras homolog family member A (RhoA) and Rho­associated coiled­coil containing protein kinase (ROCK) are associated with the growth of neurons and the movement of neuronal growth cones. RhoA/ROCK inhibitors have been demonstrated to promote the recovery of motor function following nerve injury, but the underlying mechanism requires further investigation. The present study aimed to investigate the effects of the ROCK inhibitor Y­27632 on middle cerebral artery occlusion (MCAO)­induced cerebral ischemic injury. Rats were randomly assigned to the Control, Y­27632, MCAO + Vehicle or MCAO + Y­27632 group. Firstly, infarct volume, cognitive ability and cerebral injury were assessed. Secondly, indicators of cerebral inflammation, oxidative stress and apoptosis were evaluated. Finally, the expression of recombinant glial fibrillary acidic protein (GFAP) and allograft inflammatory factor 1 (AIF1) in the brain were measured to assess the activation of astrocytes and microglia, respectively. The results showed that Y­27632 effectively increased the survival rate and behavioral performance of rats, and attenuated the cerebral injury, oxidative stress and cerebral inflammation levels following MCAO. The disturbance in hippocampal neurons caused by MCAO was also alleviated following treatment with Y­27632. Neuronal apoptosis was also decreased following Y­27632 treatment, as demonstrated by the TUNEL assay and the expression levels of Caspases­3, 8 and 9 and Bax/Bcl­2 ratio. The levels of GFAP and AIF1 were increased by MCAO and further promoted by Y­27632, indicating the activation of astrocytes and microglia. In conclusion, the present study offered evidence of a protective effect of Y­27632 administration on cerebral ischemia/reperfusion induced behavioral and hippocampal damage by activating astrocytes and microglia.