Application of the Electrospinning Technique in Electrochemical Biosensors: An Overview.

Electrospinning is a cost-effective and flexible technology for producing nanofibers with large specific surface areas, functionalized surfaces, and stable structures. In recent years, electrospun nanofibers have attracted more and more attention in electrochemical biosensors due to their excellent morphological and structural properties. This review outlines the principle of electrospinning technology. The strategies of producing nanofibers with different diameters, morphologies, and structures are discussed to understand the regulation rules of nanofiber morphology and structure. The application of electrospun nanofibers in electrochemical biosensors is reviewed in detail. In addition, we look towards the future prospects of electrospinning technology and the challenge of scale production.

Static and Dynamic Plantar Pressure Distribution in 94 Patients with Different Stages of Unilateral Knee Osteoarthritis Using the Footscan® Platform System: An Observational Study.

BACKGROUND Plantar pressure analysis is widely used in the study of knee osteoarthritis (KOA). The present study aimed to investigate the static and dynamic plantar pressure distribution in patients with different stages of unilateral KOA using the Footscan® platform system. MATERIAL AND METHODS We recruited 94 patients aged 61.75±7.23 years old with different stages of unilateral KOA for static and dynamic analysis using the Footscan® platform system. The static pressure (%) of the left, right, anterior, posterior, and the pelvic rotation (°) was assessed. The peak pressure (PP, kPa) was investigated in 10 areas of the foot: medial heel (MH), lateral heel (LH), midfoot (MF), first to fifth metatarsals (M1-M5), hallux (T1), and toes 2-5 (T2-5). The correlation between KOA stages and plantar pressure distributions was investigated. RESULTS The results revealed that static pressure on the unaffected side and pelvic rotation were positively correlated with KOA stages. In addition, there was a positive correlation between KOA stages and PP of M5, MF, and LH zones on the affected side and PP of M2, M3, and M4 zones on the unaffected side, and a negative correlation between KOA stages and PP of T1 and T2-5 zones on the affected side. CONCLUSIONS With the progression of KOA, static plantar pressure tends to distributed on the unaffected side, and the dynamic plantar pressure tends to be distributed laterally on both feet. The plantar pressure distributions in unilateral KOA patients are abnormal and are closely related to the severity of KOA.

Coaxial electrospinning synthesis of size-tunable CuO/NiO hollow heterostructured nanofibers: Towards detection of glucose level in human serum.

Nanofibers (NFs) have found wide applications by virtue of their particular morphology and high specific surface area. In this study, size-tunable hollow CuO/NiO NFs were synthesized by coaxial electrospinning and subsequent calcination. The synthesized hollow CuO/NiO NFs owned large specific surface area for catalytic active sites. In addition, the formation of heterostructure interface between CuO and NiO was beneficial to improve the electrocatalytic performance. As non-enzymatic electrode material, the synthesized CuO/NiO NFs exhibited superior electrocatalytic capability for glucose oxidation. When the molar ratio of CuO to NiO is 0.4, the composite NFs achieved the optimal electrocatalytic ability for glucose oxidation, performing high sensitivity of 1324.17 µA mM-1 cm-2 and wide liner range from 1 to 10,000 µM. The constructed electrode has been utilized to detect glucose concentration in real serum with excellent recovery, indicating that CuO/NiO hollow heterostructured NFs are promising materials for biomedical applications.

Controlled synthesis of Cu-Sn alloy nanosheet arrays on carbon fiber paper for self-supported nonenzymatic glucose sensing.

Nanoalloy shows significant advantages and broad application prospects in chemical catalysis, due to the possessed high specific surface energy and abundant active sites can greatly promote their catalytic performance. In this work, morphology-controlled Cu-Sn alloy nanosheet arrays supported on carbon fiber paper (CP) substrate (Cu-Sn/CP) have been developed by a facile one-step electrodeposition technique at room temperature for the first time. Benefiting from the large active surface area, considerable ion transport channels and strong synergistic catalytic effect between Cu and Sn, the as-prepared Cu-Sn/CP served as a self-supported electrode for efficient nonenzymatic glucose sensing. Under optimized conditions, Cu-Sn/CP electrode offers wide linear ranges of 0.0005-2.0 mM and 2.0-10.0 mM, respectively. The detection limit is as low as 0.061 µM (S/N = 3). Cu-Sn/CP electrode also exhibited excellent selectivity and stability. Additionally, the proposed sensor is proven to be suitable for the detection of glucose in human serum samples.

Clinical and genetic analysis of a Chinese pedigree affected with benign familial neonatal convulsion / 中华医学遗传学杂志

OBJECTIVE@#To analyze the clinical phenotype and genetic variant in a Chinese pedigree affected with benign familial neonatal convulsion (BFNC).@*METHODS@#Clinical data and peripheral blood samples of the pedigree were obtained with informed consent. Whole exome sequencing (WES) was carried out for the proband. Candidate variants were verified by Sanger sequencing.@*RESULTS@#The pedigree comprised 9 individuals, among whom 4 were affected, including 3 males and 1 female. All patients had developed seizures during the neonatal period, which had ceased in 4 to 6 months. One patient had recurrence in between 1 and 2 years old. Genetic testing has identified a novel nonsense c.810G>A (p.W270X) variant in exon 5 of the KCNQ2 gene, which has co-separated with the BFNC phenotype in the pedigree.@*CONCLUSION@#The patients from this pedigree have conformed to the diagnosis of BFNC with good prognosis, which was in keeping with previously reported cases. The heterozygous c.810G>A (p.W270X) nonsense variant of the KCNQ2 gene probably underlay the pathogenesis of BFNC in this pedigree, which has expanded the mutational spectrum of the disease.

Glucose sensor based on Pd nanosheets deposited on Cu/Cu2O nanocomposites by galvanic replacement.

A novel non-enzymatic glucose sensor was established by galvanic replacement synthesis of Pd nanosheets (PdNS) on Cu/Cu2O nanocomposites using fluorine-doped tin oxide (FTO) substrates. To prepare PdNS-Cu/Cu2O/FTO electrode, Cu/Cu2O nanocomposites were firstly deposited on FTO electrode through potential oscillating, and then Pd nanosheets were synthesized on Cu/Cu2O nanocomposites by galvanic replacement reduction. X-ray diffraction, scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy were applied to investigate the morphology and composition of PdNS-Cu/Cu2O nanohybrids. The synthesized PdNS-Cu/Cu2O exhibited great electrochemical activity toward glucose oxidation. Under optimized conditions, the proposed glucose sensor displayed a wide linear range from 0.5 µM to 2600 µM with detection limit of 0.1 µM. In addition, the proposed electrode was used to determine glucose in true blood specimen, indicating potential application for routine glucose analysis.

Facile Synthesis of ZnMn2O4@rGO Microspheres for Ultrasensitive Electrochemical Detection of Hydrogen Peroxide from Human Breast Cancer Cells.

Mixed transition-metal oxides have witnessed increasing attention in catalysts and electrocatalysts. Herein, reduced graphene oxide-wrapped ZnMn2O4 microspheres (ZnMn2O4@rGO) were facilely synthesized through the solvothermal technique. The microstructure and morphology of ZnMn2O4@rGO microspheres were analyzed under Raman, X-ray photoelectron, X-ray diffraction, and energy-dispersive spectroscopies and scanning electron microscopy. The synthesized ZnMn2O4@rGO was employed as an excellent electrocatalyst for the reduction of hydrogen peroxide (H2O2). The ZnMn2O4@rGO-modified glassy carbon electrode (ZnMn2O4@rGO/GCE) exhibited a linear detection to H2O2 in a wide concentration range of 0.03-6000 µM with a detection limit of 0.012 µM. The biosensor was evaluated to determine H2O2 secreted by human breast cancer cells (MCF-7), indicating its promising applications in physiology and diagnosis.

[Study on Outliers Influence in NIR Quantitative Analysis Model].

As a secondary analysis method, reproducibility and reliability of near-infrared spectroscopy (NIRS) quantitative analysis are quite dependent on modelling process. In this paper, it is focused on outlier analysis for protein quantitative model of wheat based on NIRS. The purpose is to discuss the outlier effect in modelling process of complex sample set. The indicator of outliers is the deviation between two interpretative percentage curves in partial least squares regression (PLSR) modelling, when two percentage curves have significant deviation or departure point, the sample set should include the outliers. The innovative research work is the analysis and treatment of outliers. On the basis of sub-model ergodic calculation method, outliers can be gradually identified and picked-up. The standard deviation of model's prediction residual is used as the reference graduation to distinguish the degree of deviation. According to the degree of deviation from sample population, outliers can also be divided into significant outliers, relative outliers and potential outliers. In this paper, the significant outliers of the sample set are about 7.8%, and the relative outliers are about 15.6%. The outliers will pull normal samples apart from the ideal fitting line and make the dispersity increase. No matter modelling with removed outliers or weighted samples, the purpose is to make the fitting results of quantitative analysis modelling more inclined to majority samples, while reducing or eliminating the impact of outliers.

[VMTBB-Based Spectral Radiometric Calibration of NIR Fiber Coupled Spectrometer].

The medium temperature black body (MTBB) is conventional high precision equipment used as spectral radiometric scale in infrared spectral region. However, in near-infrared (NIR) spectral region, there are few papers about spectral radiometric calibration by using MTBB, that is because NIR spectral region is the borderland of its effective spectral region. The main research of this paper is spectral radiometric calibration method by using MTBB in NIR spectral region. Accordingly, this paper is devoted mostly to a discussion of how the calibration precision could be affected by selecting different structural parameters of calibration model. The purpose of this paper is to present the results of research and provide technical reference for improving the traceability in NIR spectral radiometric calibration. In this paper, a NIR fiber coupled spectrometer, whose wavelength range covers from 950 to 1700 nm, has been calibrated by a MTBB with adjustable temperature range from 50 to 1050 °C. Concentrating on calibration process, two key points have been discussed. For one thing, the geometric factors of radiation transfer model of the calibration systems have been compared between traditional structure and fiber direct-coupled structure. Because the fiber direct-coupled model is simple and effective, it has been selected instead of traditional model based on the radiation transfer between two coaxial discs. So, it is an advantaged radiation transfer model for radiometric calibration of fiber coupled spectrometer. For another thing, the relation between calibration accuracy and structural parameters of calibration model has been analyzed intensively. The root cause is scale feature of attribute of calibration data itself, which is the nonlinear structure in scales of spectral data. So, the high precision calibration needs nonlinear calibration model, and the uniform sampling for scale feature is also very important. Selecting sample is an inevitable problem when the nonlinear model is explained by small sample dataset. As the analytic results, there are obviously influences for the calibration precision among different strategies of selecting model's structural parameters. The calibration precision, which is mathematical described by standard deviation of spectral data for calibration, could be from ±0.1% to ±1%.

[Research on variable selection of wheat near-infrared spectroscopy based on latent projective graph].

To simplify the model and improve the precision of prediction model, latent projective graph (LPG) was used for variable selection. The original spectrum was processed by continuous wavelet transform (CWT), LPG was obtained by principal component analysis (PCA), and based on the assumption that collinear wavelengths might have the same contribution to the modeling, a few latent spectral variables were selected for establishing prediction model. The root mean square error of prediction (RMSEP) model was 0. 3454, better than other modeling methods. This work proved that variable selection with LPG could simplify the near-infrared spectral model effectively, and improve the precision of prediction model.