Analytical biochemistry最新文献

Nanotechnology is an important science that finds a wide range of applications from energy production to industrial production processes and biomedical applications. Nanoparti-cles, which are the most frequently preferred nanomaterials that form the basis of nanotechnolo-gy, are prepared with different composition, size, shape and surface chemistry to provide new techniques in applications in many different fields. The use of nanoparticles in the preparation of plasmonic sensors has increased the interest in plasmonic sensors such as surface plasmon resonance, electrochemical sensors, surface enhanced raman scattering and colorimetric sensors due to their increased sensing capacity on sensor surfaces. Plasmonic sensors are an important option in many different fields, such as medicine, environmental agriculture and food safety, thanks to their ability to solve a multitude of challenges. Because, plasmonic sensors are defined as sensing devices with important features such as sensitive and fast detection, no need for labels, real-time analysis, portability. In this review, the information about nanoparticles and their types and working principles of plasmonic sensors is given. Then, examples in clinical applications using different plasmonic sensors prepared with plasmonic nanoparticles are discussed in detail.

Organophosphate pesticides (OPs) are causing non-selective inhibition in enzymatic bioreceptors, thus the enzymatic-inhibition-based traditional assays are not suitable for their specific detection in food and environmental samples. Accordingly, a selective nanostructured electrochemical biosensing system was designed using six mutants of the esterase-2 (EST2 protein) enzymes from A. acidocaldarius to be exploited as targeting bio-receptors for the specific detection of OPs. Each of the EST2 mutant enzymes was immobilized on disposable screen-printed electrodes modified with Aluminum oxide (Al₂O₃)/Copper (Cu) nanocomposite. Consequently, chronoamperometric assay was fully optimized, and cross-reactivity study was carried out using paraoxon, malathion and chlorpyrifos. The comparative cross-reactivity study was performed on the six mutant proteins in terms of inhibitory percentage over a wide range of pesticide concentrations. Eventually, a wide dynamic inhibition range was achieved while the limit of detection for the paraoxon toxicity was 0.01 nM and the limit of quantification was 0.05 nM. Finally, paraoxon was selectively determined using the newly developed EST-based biosensor in different spiked food samples.

Seventy-two intentionally sequence-diverse antibody variable regions were selected, expressed as IgG1 antibodies, and evaluated by chemical unfolding to survey the complexities of denaturant induced unfolding behavior. A two-transition fit well described the curves and uncovered a wide range of sensitivities to denaturant. Four general types of unfolding curves were observed: balanced traces (each transition responsible for half of the total unfolding curve), low-unfolding traces (first transition is a majority of the unfolding curve), high-unfolding traces (the second transition is the majority of the unfolding curve), and coincident traces (the two transitions are found close to each other, approximating a single transition). The complexity of the data from this survey indicates that focusing on the first inflection point or fitting a single transition model is likely an over-simplistic method for measuring stability by the chemical unfolding assay. Additionally, other conformational assays, such as thermal and low pH unfolding, showed no correlation with the chemical unfolding results, indicating that each of these assays provide alternate information on the different pathways of antibody conformational stability. These results provide a basis for beginning to better connect unfolding behavior to other physical phenotypic behaviors and production process behaviors.

In the present work, a convenient, efficient and disposable electrochemical sensor has been developed by electropolymerizing methylene blue (PMB) on the surface of a pencil graphite electrode (PGE), which facilitates the electrochemical analysis of an antioxidant l-Ascorbic Acid (AA). The structural characteristics of both the methylene blue modified pencil graphite electrode (PMB/PGE) and the bare pencil graphite electrode (BPGE) have been examined using scanning electron microscopy (SEM) in conjunction with energy-dispersive X-ray analysis (EDX). Additionally, the charge transfer behavior has been evaluated using the electron impedance spectroscopy (EIS). The voltammetric response of AA has been examined using different methods, such as differential pulse voltammetry (DPV) and linear sweep voltammetry (LSV). This exploration has been carried out in 0.1 M phosphate buffer solution (PBS) of physiological pH 7.0. The electrochemical sensor PMB/PGE proposed in this study exhibited an improved peak current and a slight negative shift in peak potential for AA compared to bare electrode. The enhancement in peak current at the modified electrode has been attributed to the electrocatalytic characteristics of the modifiers. The limit of detection (LOD) for AA has been determined using the differential pulse voltammetry (DPV), with concentrations ranging from 1.0 μM to 12.0 μM. The calculated LOD value has been found to be 0.15 μM. The selectivity and practicality of the modified electrode has been assessed through the real sample analysis and demonstrating its capability to detect AA in the presence of paracetamol (PA) resulting in satisfactory recovery results. Hence the proposed sensor could be successfully validated for the determination of AA in pharmaceutical sample.

Immunoassays could provide valuable insights into disease biomarkers and gut health by measuring fecal proteins. However, reliably isolating intact proteins from feces is challenging due to its heterogeneous and variable composition. This paper aims to review and compare different methods for extracting proteins from fecal samples to make them suitable for immunoassay analysis. Mechanical homogenization helps release proteins by disrupting solids, while protease inhibitors preserve protein integrity. Detergents like SDS solubilize proteins by disrupting hydrophobic interactions. Organic solvents such as acetone precipitate proteins and remove contaminants. Thermal treatment denatures proteases. Immunocapture uses antibodies to purify target proteins away from interference selectively. Commercial kits contain optimized buffers but may be cost-prohibitive. Combining mechanical, chemical, and immunological techniques synergistically integrates their advantages, improving the recovery of native proteins with reduced matrix effects. While all methods have merits, tailored protocols integrating multiple mechanisms appear most promising for extracting immunoassay-suitable fecal proteins. Further optimization and standardization of such combination approaches matched to proteins and assays of interest helps expand noninvasive fecal proteome analysis.

Gamboge exhibits anti-colorectal cancer (CRC) activity, however, its active compounds and the underlying mechanisms remain unclear. Herein, a liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method for determining gambogellic acid, β-morellic acid, isogambogenic acid, gambogenic acid, R-gambogic acid, S-gambogic acid, and hydroxygambogic acid in gamboge was established. The key parameters including ion transitions, voltages, LOD, and LOQ were determined, with LOD ranging from 0.8 to 2.0 ng mL^-1 and LOQ from 2.7 to 6.7 ng mL^-1. The recovery rates were found to be between 95.6 % and 103.5 %. Furthermore, the active compounds were successfully determined, and molecular mechanisms of gamboge in treating CRC were explored. Network pharmacology revealed a "compound-target-pathway" network where the seven compounds could target key proteins, modulate PI3K-Akt and JAK-STAT pathways, and inhibit CRC development. Molecular docking validated SRC, SATA3, PIK3CA, among others, as potential targets for the active compounds in CRC intervention. In conclusion, this method significantly reduces analysis time and improves efficiency relative to existing approaches, making it highly suitable for the effective determination of multiple compounds in the quality control of gamboge materials.

Dopamine, one of the most important neurotransmitters, plays a crucial role in the functions of human metabolism, as well as the cardiovascular, central nervous and hormonal systems. This study focuses on the synthesis of nanostructured silver chromate and their application in dopamine sensing. The nanoparticles were synthesized using a complexation-mediated route using aminosalicylic acid as a stabilizer, resulting in uniform particles ranging from 3 to 15 nm in size. The synthesized silver chromate was characterized using X-ray diffraction, transmission electron microscopy and X-ray photoelectron spectroscopy techniques. Electrochemical studies revealed that the silver chromate exhibit excellent catalytic activity for the detection of dopamine. The electroanalysis provided the selective recognition of dopamine with the limit of detection of 1.05 μM and sensitivity of 2.68 μA μM^-1 cm^-2 in a linear range of 5-45 μM. Additionally, a portable, IoT (internet of things)-integrated sensor based on the synthesized silver chromate was developed using Arduino Uno R4 Wi-Fi module, enabling real-time monitoring of dopamine with data transmission to a cloud platform.

Sphingolipids (SL), a class of membrane lipids, play important roles in numerous biological processes. Their significant structural diversity poses challenges for accurate quantification. To address this, liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has emerged as a powerful tool for sphingolipidomics, capable of profiling these lipids comprehensively. In this study, we utilized LC-MS/MS with high-resolution mass spectrometry (MRM^HR) to develop a targeted method for the identification and quantification of various SL species. This method, based on validated parameters such as precursor/fragment ions (m/z) and retention time, demonstrated high sensitivity and accuracy, successfully identifying SL species across 12 distinct classes. Its open-panel design also facilitates the analysis of new SL-species targets. Notably, using this approach, we identified 40 SL species in plasma samples from COVID-19 patients, and we determined the influence of matrix metalloproteinase-3 (MMP-3) expression on the positive downstream of SL metabolism. Beyond plasma analysis, this method has potential applications in other biomedical contexts, such as extracellular vesicles (EVs), describing the cargo of sphingosine-1-phosphate (S1P) on macrophage-derived EVs. The establishment of this targeted workflow enabling precise quantification of a wide range of SL species, holds promise for identifying novel biomarkers and therapeutic targets.

The norovirus (NoV), known for its high contagion rate, is the leading cause of acute gastroenteritis. The development of a NoV vaccine is hindered by significant antigenic variation, lack of suitable models, unknown vaccine protection duration, limited human challenge studies, complex performance patterns, and the absence of a reliable in vitro cultivation system, making prevention, early detection, and control the only effective measures to mitigate outbreaks. This review aims to discuss about several norovirus biosensor for point-of-care analysis. Several innovative biosensors have been developed, including techniques such as electrochemical NoV biosensors, colorimetric NoV biosensors, fluorescence NoV biosensors, CRISPR-based NoV biosensors, and other NoV biosensors. These approaches have detected norovirus in biological samples with high sensitivity and specificity. This biosensing technique holds significant promise, not only in improving the speed and accuracy of diagnostic processes but also in strengthening the global response to norovirus infections, thereby underscoring its pivotal role in public health and disease prevention.

In recent years, mounting investigations have highlighted the pivotal role of centrosomes in cancer progression. In this study, we employed bioinformatics and statistics to establish a 13-centrosome-associated gene prognostic model for lung adenocarcinoma (LUAD) utilizing transcriptomic data from TCGA. Based on the Riskscore, patients were stratified into high- and low-risk groups. Through survival analysis and receiver operating characteristic curve analysis, our model demonstrated a consistent and robust prognostic capacity, which was further validated using the GEO database. Univariate/multivariate Cox regression analyses identified our model as an independent prognostic factor for LUAD patients. Subsequently, immunoinfiltration analysis showed that immune cell infiltration levels of aDCs, iDCs, Mast cells, and Neutrophils, as well as immune functionalities such as HLA, Type I IFN Response and Type II IFN Response, were markedly reduced in the high-risk group compared to the low-risk group. Finally, we conducted a drug screening to identify potential treatments for patients with different prognoses. We utilized the GDSC database and molecular docking techniques to identify small molecule compounds targeting the prognostic genes. In conclusion, our prognostic model exhibits robust and reliable predictive capability, and it may have important clinical implications in guiding treatment decisions for LUAD patients.