Detection of Traces of Ovalbumin and Casein in White and Red Wines by Quantitative Western Blotting

A novel and ultrasensitive electrochemical immunosensor based on nanocellulose-Ti3C2Tx@ZrO2 nano framework for the detection of ovalbumin

A versatile and highly sensitive sensing platform based on nanocellulose/MXene/ZrO2 nano framework has been developed at the surface of a glassy carbon electrode (GCE) for detecting ovalbumin (Ova). To create this innovative nano framework, dialdehyde groups were introduced onto the surface of cellulose nanofibers (CNFs), which were then decorated with MXene nanosheets and nanostructured zirconia. Nanocellulose/MXene/ZrO2 nano framework was used as electrochemical mediator and immobilization environment that provided the large surface area and 197 % increment in the electrochemical signal which allowed the Ova detection in the femtomolar range. Ovalbumin antibody was immobilized on the surface of dialdehyde cellulose nanofiber through covalent bonding between amino groups of Ova and dialdehyde groups of CNFs. The assembly process of nano framework, anti-Ova, and Ova antigen were characterized using electrochemical approaches (CV and DPV). The fabricated immunosensor is further applied to DPV detection of Ova and it demonstrated a linear response to Ova antigen in the linear range of 0.01-1000 pg/mL. With optimal experimental conditions, the detection limit, quantification limit and sensitivity of Ova were found to be 1.1 fg/mL, 0.01 pg/mL and 0.1497 μA pg/mL cm-2, respectively. The fabricated immunosensor exhibited high selectivity, reproducibility, and interference resistance and achieved excellent recoveries in real food samples spiked with Ova, indicating its potential applicability in food safety monitoring.

Molecular imprinted electrochemical sensor for ovalbumin detection based on boronate affinity and signal amplification approach

Ovalbumin (OVA), a class of glycoproteins, is the main allergen in hen egg white that often causes allergies in humans, especially in babies. Therefore, it is pivotal to be able to detect and separate OVA. This work presents an ingenious sandwich-structured magnetic molecular imprinted electrochemical sensor for OVA detection by utilizing boronate affinity and signal amplification strategy. With anti-OVA antibody-modified gold nanoparticles (AuNPs) as amplifiers, the imprinted cavities in the probe could capture protein to form a sandwich structure. Due to its specific recognition of antibody and molecular imprinted polymers and the signal amplification of AuNPs, the sensor had good selectivity and sensitivity toward OVA and a low detection limit of 3.0 fg/mL. The sensor also had excellent stability and could satisfactorily detect OVA in real red wine samples.

Imprinted proteins for determination of ovalbumin

A strategy to design imprinted proteins (IPs) able to detect a glycoprotein (ovalbumin, OVA) was proposed. Glucose oxidase (GOx) was used as a matrix for obtaining the binding cavities with high specificity towards the template protein. The effective method to purify the obtained IPs from the template molecules was developed based on a combination of dialysis and gel filtration. HRP was chosen as a model template to discover the optimal production conditions, and the optimal template concentration (100 µg⋅L^-1) was chosen. The obtained imprinted proteins were characterized by the high adsorption selectivity towards the target protein (the imprinting factor towards OVA and HRP is 4.7). The developed method was transferred to the synthesis of the anti-OVA IPs. The binding properties of these IPs were estimated using the OVA conjugates with low- (FITC) and high- (HRP) molecular weight label molecules. The ability of the synthesized anti-OVA IPs as recognition elements in immunoassay was studied. Under the optimized experimental conditions, the proposed imprinted proteins exhibited a good linear response to OVA in the concentration range of 10-2000 ng⋅mL^-1 with a detection limit of 6 ng⋅mL^-1. The obtained recognition elements were tested for OVA determination in real samples of chicken egg white, and a sample of OVA-free cake spiked by OVA.

Adverse Reactions to Illicit Drugs (Marijuana, Opioids, Cocaine) and Alcohol

Drug allergy has been a research topic within the allergy field for decades. However, many drug reactions presumed to be of allergic nature are not and originate from different mechanisms. Drug-induced reactions can affect numerous organ systems, present with various symptoms, and have more than 1 mechanism of action. In this rostrum article, we want to give an overview of the different allergic and nonallergic reactions that can be expected with the (illicit) use of cannabis, cocaine, opioids, and alcohol. In addition, this article focuses on the different methods available to diagnose allergy related to these 4 drug types and highlight the pitfalls of nonallergic reactions or allergy "mimickers" complicating the diagnosis of true drug allergy. Finally, the impact on current medical practices and future research in support of the allergist in diagnosis and treatment of these medical problems is addressed.

Epitope-imprinted polydopamine electrochemical sensor for ovalbumin detection

A novel, sensitive and selective electrochemical sensor based on epitope-imprinted polydopamine (PDA) was developed for ovalbumin (OVA) detection. Molecularly imprinted polydopamine was synthesized on an AuNP-coated screen-printed carbon electrode (SPCE) via electropolymerization in the presence of OVA IgE-binding epitope as the template. Key process parameters including template concentration, electropolymerization cycle, pH, time required for template removal and rebinding were optimized. Electrochemical detection of OVA was performed by differential pulse voltammetry (DPV) in 5 mM K₃Fe(CN)₆ and 0.1 M KCl as the supporting electrolyte. Under optimized conditions, the sensor demonstrated excellent sensitivity toward OVA with linear range from 23.25 to 232.50 nM (1 to 10 ppm), limit of detection (LOD) of 10.76 nM (0.46 ppm), and limit of quantification (LOQ) of 35.87 nM (1.54 ppm). The sensor also exhibited good selectivity against other proteins such as human serum albumin (HSA), bovine serum albumin (BSA), and lysozyme (LYZ). OVA in wine samples was detected with RSD of 5.63-10.82%, and recovery percentage of 104.74-105.96%. The developed method can be easily adapted to detect other allergic proteins in the food supply chain.

Implementation of an Enzyme Linked Immunosorbent Assay for the Quantification of Allergenic Egg Residues in Red Wines Using Commercially Available Antibodies

Since the early 2000s, labeling of potentially allergenic food components to protect people who suffer from food allergies is compulsory in numerous industrialized countries. In Europe, milk and egg components used during the winemaking process must be indicated on the label since July 1, 2012. Several ELISA procedures have been developed to detect allergenic residues in wines. However, the complexity of the wine matrix can inhibit the immunoenzymatic reaction. The aim of this study was to implement an ELISA assay for the detection of ovalbumin in red wines using commercially available antibodies. The specificity of the acquired antibodies and the absence of cross reactivity were assessed by immunoblotting and ELISA. An ELISA assay with a LOD of 14.2 μg/L and a LOQ of 56.4 μg/L of ovalbumin in aqueous solution was obtained. Differences in ELISA signals were observed when analyzing various fining agents, although reproducible conformation of the antigen could be reached for the comparison of ovalbumin and Ovicolle. The differences between samples in terms of pH could be leveled but the inhibition of the ELISA signal, positively correlated to the tannin content of the wines, could not be suppressed. Thus, standard curves of ovalbumin in several wines were obtained by relative quantification. The control steps and the difficulties encountered presented in this study should be considered by anybody working toward the development of ELISA assays for the detection of allergenic residues in complex food matrices.