Decoding food reactions: a detailed exploration of food allergies vs. intolerances and sensitivities.

The food matrix is a complex system encompassing all constituent elements in food production. It influences the digestibility of these elements through direct interactions and affects the digestive environment. Furthermore, the gastrointestinal system possesses precise mechanisms that efficiently process dietary components into essential nutrients, effectively preventing the onset of abnormal immune responses or dysfunctional host reactions in most instances. However, the incidence of adverse food reactions is constantly increasing, and evidence indicates that this process is environmental. Adverse reactions can be categorized as toxic or nontoxic. Toxic reactions are dose-dependent and can result from natural compounds, processing-induced substances, or contaminants. Nontoxic reactions like food intolerance and hypersensitivity depend on individual susceptibility and evoke specific pathological and physiological responses. This review aims to elucidate the mechanisms underlying the occurrence of immune- (food allergies and sensitivities) and non-immune-mediated (food intolerance) reactions, emphasizing the fundamental distinctions between these two categories. Enhanced comprehension and distinction of these mechanisms will significantly contribute to advancing preventive and therapeutic approaches and establishing guidelines for food labeling concerning immune-mediated reactions.

ALLERDET: A novel web app for prediction of protein allergenicity.

Allergic diseases are increasing around the world with unprecedented complexity and severity. One of the reasons is that genetically modified crops produce new potentially allergenic proteins. From this starting point, many researchers have paid attention to the development of tools to predict the allergenicity of new proteins. In this study, a novel approach is introduced for the prediction of food allergens based on Artificial Intelligence techniques: a pairwise sequence alignment with the FASTA program for feature extraction and the use of the Deep Learning technique known as Restricted Boltzmann Machines in combination with the Decision Tree method for the prediction process. The developed tool, called ALLERDET (publicly available at http://allerdet.frangam.com), overcomes the state-of-the-art methods. The performance of our method is: 98.46% sensitivity, 94.37% specificity and 97.26% accuracy), on a data set built from several publicly available sources.

FcεR1-expressing nociceptors trigger allergic airway inflammation.

BACKGROUND: Lung nociceptor neurons amplify immune cell activity and mucus metaplasia in response to an inhaled allergen challenge in sensitized mice. OBJECTIVE: We sought to identify the cellular mechanisms by which these sensory neurons are activated subsequent to allergen exposure. METHODS: We used calcium microscopy and electrophysiologic recording to assess whether vagal neurons directly respond to the model allergen ovalbumin (OVA). Next, we generated the first nociceptor-specific FcεR1γ knockdown (TRPV1Cre::FcεR1γfl/fl) mice to assess whether this targeted invalidation would affect the severity of allergic inflammation in response to allergen challenges. RESULTS: Lung-innervating jugular nodose complex ganglion neurons express the high-affinity IgE receptor FcεR1, the levels of which increase in OVA-sensitized mice. FcεR1γ-expressing vagal nociceptor neurons respond directly to OVA complexed with IgE with depolarization, action potential firing, calcium influx, and neuropeptide release. Activation of vagal neurons by IgE-allergen immune complexes, through the release of substance P from their peripheral terminals, directly amplifies TH2 cell influx and polarization in the airways. Allergic airway inflammation is decreased in TRPV1Cre::FcεR1γfl/fl mice and in FcεR1α-/- mice into which bone marrow has been transplanted. Finally, increased in vivo circulating levels of IgE following allergen sensitization enhances the responsiveness of FcεR1 to immune complexes in both mouse jugular nodose complex ganglion neurons and human induced pluripotent stem cell-derived nociceptors. CONCLUSIONS: Allergen sensitization triggers a feedforward inflammatory loop between IgE-producing plasma cells, FcεR1-expressing vagal sensory neurons, and TH2 cells, which helps to both initiate and amplify allergic airway inflammation. These data highlight a novel target for reducing allergy, namely, FcεR1γ expressed by nociceptors.

Effect of thermal processing on the antigenicity of allergenic milk, egg and soy proteins.

The detection of allergenic proteins and the influence of processing on the structure and antigenicity of these proteins are relevant topics. Using commercial enzyme-linked immunosorbent assay kits, this study aimed to evaluate the degradation profiles of milk, egg and soy proteins during the processing of semisweet biscuits. The formulations were baked under different conditions according to a complete factorial experiment that included a three-level temperature factor and a six-level time factor. ß-lactoglobulin and egg white proteins were severely degraded, the degradation of casein was intermediate, and soy proteins were the most stable. Complete allergen protein degradation was found under only the extreme baking conditions, which resulted in products that were not sensorily acceptable. Residual levels of the proteins were detected after baking, indicating that this thermal processing reduced but did not eliminate the antigenicity of these proteins; thus, baking cannot be considered a strategy to protect allergic consumers.

New technologies in molecular allergodiagnostics.

The article presents the characteristics of the ALEX2 (MacroArrayDX, Wien, Austria). It is designed for simultaneous detection of IgE total and specific IgE-aB to 120 extracts and 180 molecules by solid-phase enzyme immunoassay. Extracts and allergen molecules combined with nano-particles are sorbed on a solid-phase substrate, forming a macroscopic multiplex matrix - the immune allergy chip. The Institute of Clinical and Laboratory Standards (CLSI) conducted research on the verification and validation of the ALEX2 in relation to the ImmunoCAP macroarray test system (ThermoFisher Scientific, Uppsala, Sweden), which is often used in allergodiagnostics. The results obtained on the two test systems were comparable. One of the most important features of the ALEX2 test system is that unique allergen molecules and allergenic extracts are included in its composition, and a method has been found to inhibit cross-reactive hydrocarbon determinants (CCDs), which cause frequent non-specific binding of IgE-aT. The use of this test system makes it possible to carry out component allergy diagnostics with the determine of the dominant sensitizing factor in cases of mono- and polyvalent sensitization. The test results affect the determination of indications and the effectiveness of ASIT, allow assessing the risk of anaphylaxis and predicting further treatment tactics for the patient.

Parallel Reaction Monitoring Mass Spectrometry Method for Detection of Both Casein and Whey Milk Allergens from a Baked Food Matrix.

Milk allergy is among the most common food allergies present in early childhood, which in some cases may persist into adulthood as well. Proteins belonging to both casein and whey fractions of milk can trigger an allergic response in susceptible individuals. Milk is present as an ingredient in many foods, and it can also be present as casein- or whey-enriched milk-derived ingredients. As whey proteins are more susceptible to thermal processing than caseins, conventional methods often posed a challenge in accurate detection of whey allergens, particularly from a processed complex food matrix. In this study, a targeted mass spectrometry method has been developed to detect the presence of both casein and whey allergens from thermally processed foods. A pool of 19 candidate peptides representing four casein proteins and two whey proteins was identified using a discovery-driven target selection approach from various milk-derived ingredients. These target peptides were evaluated by parallel reaction monitoring of baked cookie samples containing known amounts of nonfat dry milk (NFDM). The presence of milk could be detected from baked cookies incurred with NFDM at levels as low as 1 ppm using seven peptides representing α-, ß-, and κ-casein proteins and three peptides representing a whey protein, ß-lactoglobulin, by this consensus PRM method.

Application of real-time PCR for tree nut allergen detection in processed foods.

Currently, food allergies are an important health concern worldwide. The presence of undeclared allergenic ingredients or the presence of traces of allergens due to accidental contamination during food processing poses a great health risk to sensitized individuals. Therefore, reliable analytical methods are required to detect and identify allergenic ingredients in food products. Real-time PCR allowed a specific and accurate amplification of allergen sequences. Some processing methods could induce the fragmentation and/or degradation of genomic DNA and some studies have been performed to analyze the effect of processing on the detection of different targets, as thermal treatment, with and without applying pressure. In this review, we give an updated overview of the applications of real-time PCR for the detection of allergens of tree nut in processed food products. The different variables that contribute to the performance of PCR methodology for allergen detection are also review and discussed.

A reference method for determining the total allergenic protein content in a processed food: the case of milk in cookies as proof of concept.

The establishment of a reference method for the determination of the allergen protein content in a processed food material has been explored. An analytical approach was developed to enable the comparability of food allergen measurement results expressed in a decision-relevant manner. A proof of concept is here presented, resulting in quantity values for the common measurand, namely 'mass of total allergen protein per mass of food'. The quantities are determined with SI traceability to enable the comparability of reported results. A method for the quantification of total milk protein content in an incurred baked food at a concentration level clinically relevant is presented. The strategy on how to obtain the final analytical result is outlined. Challenges associated with this method are discussed, in particular the optimal extraction of the marker proteins, the complete digestion and release of the peptides in an equimolar fashion, the use of conversion factors to translate the amount of measured proteins into total milk protein and the estimation of the uncertainty contributions as well as of the combined uncertainty of the final result. The implementation of such a reference method for the determination of the total allergen content in a processed food is an important step, which will provide comparable measurement data of relevance to risk assessors. Graphical abstract.

The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods when using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods.

: Food allergens present a significant health risk to the human population, so their presence must be monitored and controlled within food production environments. This is especially important for powdered food, which can contain nearly all known food allergens. Manufacturing is experiencing the fourth industrial revolution (Industry 4.0), which is the use of digital technologies, such as sensors, Internet of Things (IoT), artificial intelligence, and cloud computing, to improve the productivity, efficiency, and safety of manufacturing processes. This work studied the potential of small low-cost sensors and machine learning to identify different powdered foods which naturally contain allergens. The research utilised a near-infrared (NIR) sensor and measurements were performed on over 50 different powdered food materials. This work focussed on several measurement and data processing parameters, which must be determined when using these sensors. These included sensor light intensity, height between sensor and food sample, and the most suitable spectra pre-processing method. It was found that the K-nearest neighbour and linear discriminant analysis machine learning methods had the highest classification prediction accuracy for identifying samples containing allergens of all methods studied. The height between the sensor and the sample had a greater effect than the sensor light intensity and the classification models performed much better when the sensor was positioned closer to the sample with the highest light intensity. The spectra pre-processing methods, which had the largest positive impact on the classification prediction accuracy, were the standard normal variate (SNV) and multiplicative scattering correction (MSC) methods. It was found that with the optimal combination of sensor height, light intensity, and spectra pre-processing, a classification prediction accuracy of 100% could be achieved, making the technique suitable for use within production environments.

In house validation of a high resolution mass spectrometry Orbitrap-based method for multiple allergen detection in a processed model food.

In recent years, mass spectrometry (MS) has been establishing its role in the development of analytical methods for multiple allergen detection, but most analyses are being carried out on low-resolution mass spectrometers such as triple quadrupole or ion traps. In this investigation, performance provided by a high resolution (HR) hybrid quadrupole-Orbitrap™ MS platform for the multiple allergens detection in processed food matrix is presented. In particular, three different acquisition modes were compared: full-MS, targeted-selected ion monitoring with data-dependent fragmentation (t-SIM/dd2), and parallel reaction monitoring. In order to challenge the HR-MS platform, the sample preparation was kept as simple as possible, limited to a 30-min ultrasound-aided protein extraction followed by clean-up with disposable size exclusion cartridges. Selected peptide markers tracing for five allergenic ingredients namely skim milk, whole egg, soy flour, ground hazelnut, and ground peanut were monitored in home-made cookies chosen as model processed matrix. Timed t-SIM/dd2 was found the best choice as a good compromise between sensitivity and accuracy, accomplishing the detection of 17 peptides originating from the five allergens in the same run. The optimized method was validated in-house through the evaluation of matrix and processing effects, recoveries, and precision. The selected quantitative markers for each allergenic ingredient provided quantification of 60-100 µgingred/g allergenic ingredient/matrix in incurred cookies.

Advanced DNA- and Protein-based Methods for the Detection and Investigation of Food Allergens.

Currently, food allergies are an important health concern worldwide. The presence of undeclared allergenic ingredients or the presence of traces of allergens due to contamination during food processing poses a great health risk to sensitized individuals. Therefore, reliable analytical methods are required to detect and identify allergenic ingredients in food products. The present review addresses the recent developments regarding the application of DNA- and protein-based methods for the detection of allergenic ingredients in foods. The fitness-for-purpose of reviewed methodology will be discussed, and future trends will be highlighted. Special attention will be given to the evaluation of the potential of newly developed and promising technologies that can improve the detection and identification of allergenic ingredients in foods, such as the use of biosensors and/or nanomaterials to improve detection limits, specificity, ease of use, or to reduce the time of analysis. Such rapid food allergen test methods are required to facilitate the reliable detection of allergenic ingredients by control laboratories, to give the food industry the means to easily determine whether its product has been subjected to cross-contamination and, simultaneously, to identify how and when this cross-contamination occurred.

[Allergen analysis]. / Allergenanalytik.

The fundamental requirement when testing for and ensuring compliance with legally required labelling regulations is the reliable analysis of food allergens. This can be carried out by means of either DNA (deoxyribonucleic acid) or protein detection. Protein detection has the advantage of directly detecting the allergenic component and can currently be carried out using immunological (enzyme-linked immunosorbent assay [ELISA])/lateral flow devices [LFD]) or mass spectrometry-based techniques. DNA detection is indirect, but allows the presence of food allergens to be validated through the use of another marker. Each method has its pros and cons, which have to be considered on a case-by-case basis. ELISA is quantitative, quick and easy to carry out and has high sensitivity. LFD testing is ideal for industrial applications, as the tests can be carried out on-site. Both antibody-based tests may have problems with processed foods and false positive results. Mass-spectrometric techniques show a lot of promise, but are currently still time-consuming and complex to carry out. They also run into problems with processed foods and their degree of sensitivity is matrix and parameter dependent. For these reasons, this technique is only occasionally used. Polymerase chain reaction (PCR) provides the highest specificity and, depending on the target sequence, a very good to good level of sensitivity. Despite the high stability of DNA, PCR is still subject to the influence of processing and matrix related factors. Due to natural variation and production-related changes in the structures relevant in the process of detection, all methods exhibit a relatively high level of uncertainty of measurement. At present, there is no method which provides the absolute correct quantification. However, by means of laboratory-based analyses it is possible to calibrate for the allergen in question and thus be able to make reliable measurements using methods that are already available.

Lipid matrix-specific pretreatment method for enhancing the extractability and allergenicity maintenance of bovine milk allergens in ELISA detection.

The presence of various components in the food matrix makes allergen detection difficult and inaccurate, and pretreatment is an innovative breakthrough point. Food matrices were categorised based on their composition. Subsequently, a pretreatment method was established using a combination of ultrasound-assisted n-hexane degreasing and weakly alkaline extraction systems to enhance the detection accuracy of bovine milk allergens. Results showed that more allergens were obtained with less structural destruction, as demonstrated using immunological quantification and spectral analysis. Concurrently, allergenicity preservation was confirmed through liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, a KU812 cell degranulation model, and western blotting. The method exhibited good accuracy (bias, 8.47%), repeatability (RSDr, 1.52%), and stability (RSDR, 5.65%). In foods with high lipid content, such as chocolate, the allergen content was 2.29-fold higher than that of commercial kits. Laser confocal scanning microscopy (LCSM) and scanning electron microscopy (SEM) analyses revealed a significant decrease in fat content after post-pretreatment using our method. In addition, colloidal stability surpassed that achieved using commercial kits, as indicated through the PSA and zeta potential results. The results demonstrated the superiority of the extractability and allergenicity maintenance of lipid matrix-specific pretreatment methods for improving the accuracy of ELISA based allergen detection in real food.

Standardization of a Mass Spectrometry-Based Workflow for Food Allergen Quantification.

In this chapter, the analytical workflow typically used for the development and validation of an analytical method tailored to food allergen detection and quantification is presented. The main steps defining the workflow are herein described and commented with specific notes about the critical issues that can be faced and common solutions to be adopted. References to guidelines and/or recommendation available from official bodies, as well as main papers from international consortia operating on the specific research field, are also reported, whenever possible. As such, this chapter may represent a practical guide to drive method development in the standardization of analytical methods for food allergen detection.

3D bio-printing-based vascular-microtissue electrochemical biosensor for fish parvalbumin detection.

A novel 3D bio-printing vascular microtissue biosensor was developed to detect fish parvalbumin quickly. The graphite rod electrode was modified with gold and copper organic framework (Cu-MOF) to improve the sensor properties. Polydopamine-modified multi-wall carbon nanotubes (PDA-MWCNT) were mixed with gelatin methacryloyl (GelMA) to prepare a conductive hydrogel. The conductive hydrogel was mixed with mast cells and endothelial cells to produce a bio-ink for 3D bioprinting. High throughput and standardized preparation of vascular microtissue was performed by stereolithography 3D bioprinting. The vascular microtissue was immobilized on the modified electrode to construct the microtissue sensor. The biosensor's peak current was positively correlated with the fish parvalbumin concentration, and the detection linear concentration range was 0.1 ∼ 2.5 µg/mL. The standard curve equation was IDPV(µA) = 31.30 + 5.46 CPV(µg/mL), the correlation coefficient R2 was 0.990 (n = 5), and the detection limit was 0.065 µg/mL. These indicated a biomimetic microtissue sensor detecting fish parvalbumin has been successfully constructed.

Detection of the peripheral blood antigens and clinical value in recurrent aphthous ulcer: A cross-section study.

Abstract Background/purpose: Recurrent aphthous ulcer (RAU) is one of the most common diseases of oral mucosa, which is generally believed to be related to immunity, though the etiology is still unclear. It is suspected that allergies are directly related to RAU. So we sought to explore the relationship between hypersensitivity and RAU. Materials and methods: 40 RAU patients who were in ulceration period and 40 people who were in good health were selected from Jan 2016 to Feb 2017, matched in age and sex. The peripheral blood antigens of 40 RAU patients and 40 healthy people was tested, and serum specific IgE (sIgE) with 6 groups of antigens and total IgE (tIgE) analysis was performed to identify IgE-mediated allergic reaction possibly affecting RAU. We then investigated the food intolerance and IgG levels to discover the correlation between non-IgE mediated allergic reaction and RAU. Results: The positive cases and rate of sIgE in RAU group was higher than that of control, but the difference was not statistically significant (P＞0.05). Positive grade of animal fur scraps (EX1), house dust mixed (HX2) and the serum tIgE concentration of the RAU group were significantly higher than the control group (P＜0.05).The number of food intolerance in RAU group was significantly higher than that in control group (P＜0.05). Conclusion: Our findings suggested certain correlation between RAU and anaphylaxis. Daily contact allergens and food intolerance may be one of the causes of RAU. Moreover, this provides reference value for clinical diagnosis and treatment.

[Distribution characteristics and results of allergens in patients with allergic rhinitis in Ningxia area].

Objective:To investigate the distribution of allergens in patients with allergic rhinitis （AR） in Ningxia, and provide theoretical data for the prevention and treatment of AR in this region. Methods:A total of 1664 patients diagnosed with AR in the Otorhinolaryngology Head and Neck Surgery Department of Yinchuan First People's Hospital Outpatient Clinic from January 2018 to December 2021 were retrospectively collected. Use the allergen sIgE antibody detection kit （immunoblotting method） to detect inhalation and ingestion allergens in patients.Results: ①Among all AR patients, 1 158 cases were detected positive, resulting in the detection rate was 69.59%; ②The detection rate of inhalation allergen was 65.87%, and the detection rate of ingestion allergen was 19.83%; ③Mugwort was the most sensitive allergen, and 76.32% of the patients having a positive grade ≥3; ④Out of the patients, 294 cases （25.39%） were allergic to only one allergen, 244 cases （21.07%） were allergic to two allergens, and 620 cases （53.54%） were allergic to three or more allergens; ⑤During different seasons, the highest number of positive allergens detected was in the summer, with 968 cases （83.59%）. Mugwort was the main allergen during this season （69.01%）. After the COVID-19 epidemic, the total positive rate of sIgE tests in AR patients decreased compared to before, and the difference was statistically significant （P<0.001）; ⑥Mugwort, dog epithelium, mold combination, egg, peanut, soybean, Marine fish combination and fruit combination all showed statistically significant differences between different gender groups （P<0.05）; ⑦Common ragweed, mugwort, dust mite combination, cockroach, egg, milk, Marine fish combination, shrimp, fruit combination and nut combination all showed statistically significant differences among different age groups （P<0.05）; ⑧There were statistically significant differences in hay dust among different ethnic groups （P<0.05）. Conclusion:Artemisia argyi is the main allergen in Ningxia, and the distribution characteristics of different allergens are influenced by treatment season, the COVID-19 epidemic, gender, age, ethnicity, and other factors, showing certain distribution patterns and rules.

Multifold improvement in allergen detection capability of dipstick-type immunosensors via macromolecular crowding.

Dipstick-type lateral flow immunosensors are used widely for on-site detection of food allergens. The weakness of the immunosensors of this type, however, is their low sensitivity. Contrary to current methods, that focus on improving detection capability through the introduction of novel labels or multistep protocols, this work exploits macromolecular crowding to modify and regulate the microenvironment of the immunoassay, thus promoting the interactions that are responsible for allergen recognition and signal generation. The effect of 14 macromolecular crowding agents was explored using, as a model, commercially available and widely applied dipstick immunosensors, which are already optimized in terms of reagents and conditions for peanut allergen detection. An about 10-fold improvement in detection capability was achieved by using polyvinylpyrrolidone, Mr 29,000, as a macromolecular crowder without compromising simplicity and practicality. The proposed approach is complementary to other methods of improving the sensitivity by using novel labels. Because biomacromolecular interactions have a fundamental role in all types of biosensors, we foresee that the proposed strategy will also find applications in other biosensors and analytical devices.

In vitro selection and optimization of high-affinity aptamer for milk allergen α-lactalbumin and its application in dual-mode detection.

Milk is one of the most common sources of protein in people's daily lives, and it is also recognized by the World Health Organization (WHO) as one of the eight categories of food allergies to human beings. α-lactalbumin (α-La) is the main cause of milk allergy. In this study, a single-stranded DNA aptamer with high binding affinity to α-La were selected using systematic evolution of ligands by exponential enrichment (SELEX) method. Compared with the full-length sequence, the binding affinity of the truncated aptamer LA-1t for α-La was increased six times using fluorescence analysis. Circular dichroism (CD) indicated that the secondary structure of LA-1t contained a typical hairpin structure. Through the docking simulation of LA-1t and α-La, these experimental results were further explained theoretically, and the recognition mechanism was explained. Finally, the colorimetric and fluorescence signal of boron nitride quantum dots anchored to porous CeO2 nanorods (BNQDs/CeO2) were modulated by FAM-labeled LA-1t to achieve highly selective and sensitive determination of α-La. This dual-mode sensing strategy displayed sensitive recognition for α-La in a linear range of 5-4,000 ng/ml with the LOD was 3.32 ng/ml (colorimetry) and 0.71 ng/ml (fluorescence), respectively. Simultaneously, the colorimetry/fluorescence dual-mode sensing strategy was applied for detecting α-La in spiked real samples and demonstrated good stability and reliability.

Predisposition of hypersensitivity in patients with exfoliative cheilitis.

BACKGROUND/PURPOSE: Exfoliative cheilitis (EC) is a chronic and reversible inflammatory disease of the lips without definite etiology. Clinically, different types of allergens can be found in exfoliative cheilitis patients, however, few studies have focused on the relationship between exfoliative cheilitis and hypersensitivity. This research aimed to investigate the prevalence of hypersensitivity in EC patients. MATERIALS AND METHODS: A prospective study was conducted in 30 patients with exfoliative cheilitis and 30 healthy controls, matched in age and sex. Laboratory tests included serum total IgE, allergen-specific IgE, and food-specific IgG. RESULTS: Increased serum total IgE level, positive food-specific IgG were seen more frequently in exfoliative cheilitis patients than in healthy control (P < 0.05). Special IgE level to FX5 and the degree of food-specific IgG to wheat were seen higher in exfoliative cheilitis patients than in healthy control (P < 0.05). CONCLUSION: This study suggests that patients with exfoliative cheilitis may have predisposition of hypersensitivity. The detection of allergens should be strengthened in the future clinical work.