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Mechanochemical functionality of ternary heterojunctions TiO2(The)/TiO2(R)/ZnO and TiO2(A)/TiO2(Ur)/SnO2 regarding successful demand separating inside semiconductor photocatalysis: Any relative examine.
Here we study the analytical performance of label-free optical biosensors with respect to analyte-induced refractive index changes that can be measured by a biosensor (refractive index resolution). We present an analytical model that interrelates the refractive index resolution and the parameters of the optical platform of a biosensor. We demonstrate that the figure of merit (FOM), which has been widely used to design optical platforms of label-free optical biosensors, is not an appropriate metric to guide the design or predict the performance of label-free optical biosensors. Therefore, we propose an extended definition of FOM that addresses its limitations. We confirm the validity of the proposed approach by both numerical simulations and experiments. Finally, we show that the analytical model of the refractive index resolution not only makes it possible to predict the performance of a biosensor but also provides strategies for achieving optimal performance.Progressive aggregation and protein misfolding are the initial fundamental indicators of neurodegenerative disorders such as Alzheimer's disease (AD). In this study, a highly sensitive and novel method to detect amyloid beta (Aβ) biomarkers, which are a hallmark of AD, using an immunoassay platform-based interdigitated capacitive biosensor, has been explored. For several decades, aptamers have classified as a novel class of molecular recognition probes comprising single-stranded complementary DNA sequences that bind to their identified targets with high specificity and affinity by an in vitro technique called SELEX (systematic evolution of exponential and enrichment). Aptamers, often referred to as "chemical antibodies", possess several highly obvious features for clinical use. The proposed sensing bio-device was fabricated and glazed with oligomeric Aβ (oAβ) aptamer and anti-oAβ antibody, functionalized onto a Pt/Ti-featured SiO2 substrate. Subsequently, analytical studies were conducted to confirm that the specificity, sensitivity, and selective detection of the oAβ-based bioengineered surfaces facilitate a label-free approach. The bionic capacitive sensor achieved real-time detection within 5 s (faster response than ELISA) under the femto-molar range concentrations of oAβ peptide in plasma using anti-oAβ antibody and oAβ aptamer with ultra-high affinity. Furthermore, the prepared capacitive biochip was selective against plasma-borne antigens and standby for 100 days at 4 °C. The developed biosensor is suitable for point-of-care (POC) diagnostic applications owing to its portability and scalability. Furthermore, the superior efficacy of oAβ in identifying AD has huge potential for biomedical applications.MicroRNAs (miRNAs) are a class of small, single-stranded, and non-coding RNA molecules that act as post-transcriptional regulators of gene expression, participating in the regulation of a variety of important biological activities. Accumulating evidence suggests that miRNAs are closely related to many major human diseases, especially cancer, and they are considered to be highly promising diagnostic biomarkers and therapeutic targets for disease diagnosis and treatment. To this end, the development of highly accurate, selective, and sensitive strategies for miRNA detection is essential for realizing the early diagnosis of diseases and improving the success rate of treatment. Over the past decade, functional nucleic acid nanostructures have emerged as powerful tools for detecting disease-related miRNAs because of their unique advantages, e.g., high stability, specificity, and activity. Particularly, thanks to the rapid advancement of systematic evolution of ligands by exponential enrichment (SELEX) technology, it is now feasible to strictly select and reasonably design functional nucleic acids with high specificity and activity toward targets of interest, and thereby enhance the performance of miRNA detection. In this article, we present a comprehensive review of the application of functional nucleic acids including RNA aptamers and DNAzymes selected by SELEX in the construction of biosensors for miRNA detection in recent years. We also provide insights into the impact of the advantages of RNA aptamers and DNAzymes on the enhancement of the performance of miRNA biosensors. We hope this review will serve as a valuable foundation to inspire more exciting research in this emerging field in near future.Surface-enhanced Raman scattering (SERS) technique has enlarged the application of Raman spectroscopy, and the most crucial problem is the exploration of SERS-active materials. In the paper, a SERS substrate made of helical gold nanoparticles by the directed synthesis of L-glutathione (L-GSH) was proposed. Because of the large surface specific area and the uneven conduction electrons distribution for sharp tips resulted from the complex concave surface and the symmetry breaking structure, The nanostructure has shown an impressive average enhancement factor (EF) of 2.95 × 105 under off-resonant condition. This phenomenon was explained by the experimental results and finite difference time domain (FDTD) method. Finally, the SERS substrates were used to detect thiram on pear with a limit of detection (LOD) of 0.62 mg/kg and R2 of 0.9772. The proposed SERS substrates suggest the potential application of chiral molecules such as amino acids, peptides et al. in the SERS-active materials fabrication.Multiple biomarkers to diagnose the combined manifestations of a patient's disease are an indispensable guide in point-of-care testing (POCT) and clinical applications. Currently, multiplex determination of molecules at different concentrations usually requires assays with adjustable detection ranges. Here, for the first time, commercially available 3M tapes, Tape 610, Tape 810, Tape 600, are integrated into a self-designed key valve microfluidic chip (KVMC) to construct a Tape-based KVMC. Interestingly, 3M tapes with different absorption tunability for the encapsulated antibodies have been used in KVMC as substrate to enable detection of diseases biomarkers in serum ranging from pg mL-1 to μg mL-1. The Tapes antibody layer in the chip has been successfully developed without sophisticated modifications, and the detection probe can be used for a wide range of detection of three biomarkers without multiple modifications and amplification. Automated, multiplexed, simultaneous bioassays of clinically relevant inflammatory biomarkers are performed in the Tape-based KVMC POCT system, with a limit of detection (LOD) of 0.23 μg mL-1 for C-reactive protein (CRP), 0.14 ng mL-1 for procalcitonin (PCT), and 12.53 pg mL-1 for interleukin-6 (IL-6), respectively, which offers a desirable strategy for the early clinical diagnosis of sepsis. The developed Tape-based KVMC possesses high sensitivity and excellent selectivity for three biomarkers in undiluted human serum samples, providing the foundation for the application of chip POCT in clinical and field precision diagnostics.Conventional in vitro study often involves the destruction of the cells followed by purification and dilution steps before applying enzymatic assay or metabolomic analysis. It is a costly and laborious process, and it cannot monitor changes as a function of time. Recently, we have developed a new label-free live-cell FTIR approach that can directly measure biochemical compositional changes within living cells in situ and the spectral changes are shown to be highly specific to the drug applied. In this work, we have demonstrated for the first time the effect of two anti-diabetic drugs, metformin and Resveratrol, on insulin-resistant liver cells (HepG2). Using live-cell FTIR with principal component analysis, we have shown the differences in the biochemical profiles between normal and insulin-resistant cells (p 0.05) and the restoration of the biochemical profile and sensitivity to insulin from the insulin-resistant cells after the drug treatment (p less then 0.05). Particularly, a rise in the glycogen level, marked by three distinctive peaks at 1150, 1080 and 1020 cm-1, within the living cells after the anti-diabetic drug treatments is observed. The live-cell FTIR results are confirmed by a parallel gold-standard biochemical assay, demonstrating the restoration of insulin sensitivity of the insulin-resistance cells. Live-cell FTIR can be a complementary tool for drug efficacy screening, especially for insulin sensitizers.The food-borne pathogen Campylobacter jejuni produces autoinducer-2 (AI-2) as an interspecies signalling molecule. AI-2 can trigger enhanced colonisation and biofilm formation, and this poses a serious risk to public health. To date, this communication system of C. jejuni is only partially understood, as detection and quantification of such autoinducer signalling molecules in complex media is hard to achieve. We have developed a whole-cell Vibrioharveyi-based biosensor assay to accurately quantify and follow production of AI-2 by C. jejuni 81-176 in a defined growth medium and in a model food system. Several V. harveyi strains were tested, but the most sensitive bioluminescent response to C. jejuni AI-2 was achieved with V. harveyi MM30, likely due to its ability to self-amplify the response to AI-2. The AI-2 concentrations measured by this biosensor were confirmed using an independent analytical method, HPLC-FLD, which we introduced for Campylobacter analytics for the first time. The AI-2 concentration produced by C. jejuni 81-176 in the model food system was ∼5-fold that in the defined growth medium, at the same cell density. Together with the linear increments in AI-2 concentrations with cell density, this suggests that in C. jejuni, AI-2 represents a metabolic by-product rather than a true quorum-sensing molecule. This biosensor method is highly sensitive, as shown by the reduction in the limit of detection (by a factor of 100) compared to HPLC-FLD, and it enables quantification of AI-2 in complex matrices, such as food, which will help to improve the quality and safety of food production.Electrohydrodynamic-jet (E-jet) printing technique enables the high-resolution printing of complex soft electronic devices. As such, it has an unmatched potential for becoming the conventional technique for printing soft electronic devices. In this study, the electrical conductivity of the E-jet printed circuits was studied as a function of key printing parameters (nozzle speed, ink flow rate, and voltage). The collected experimental dataset was then used to train a machine learning algorithm to establish models capable of predicting the characteristics of the printed circuits in real-time. A decision tree was applied to the data set and resulted in an accuracy of 0.72, and further evaluations showed that pruning the tree increased the accuracy while sensitivity decreased in the highly pruned trees. The k-fold cross-validation (CV) method was used in model selection to test the ability of the model to get trained on data. The accuracy of CV method was the highest for random forest at 0.83 and K-NN model (k = 10) at 0.82. Precision parameters were compared to evaluate the supervised classification models. According to F-measure values, the K-NN model (k = 10) and random forest are the best methods to classify the conductivity of electrodes.
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