Research Progress in Food Allergen Labeling Management and Its Enlightenment to China

In recent years, the incidence of food allergy has continued to rise globally. Food allergy has become a global food safety and public health problem. Currently, avoiding allergens is the best way to deal with food allergy, and food allergen labeling plays an important role in protecting allergic consumers. This paper reviews recent progress in food allergen risk assessment from the perspectives of the establishment of the food allergens list, the soring-out and utilization of national nutrition and diet survey results, and the population threshold for food allergens. Furthermore, the problems existing in China’s food allergen management are discussed. It is expected that this review will provide information for scientific research and a theoretical reference to strengthen the management of food allergens

Ad hoc Joint FAO/WHO Expert Consultation on Risk Assessment of Food Allergens Part 1: Review and validation of Codex priority allergen list through risk assessment

The objectives of the meeting is to see whether the published criteria (FAO/WHO, 2000) for assessing additions and exclusions to the list is still current and appropriate. The Expert Committee determined that only foods or ingredients that cause immune-mediated hypersensitivities such as IgE-mediated food allergies and coeliac disease should be included on the list of foods and ingredients included in section 4.2.1.4 of the GSLPF. Thus, it was recommended that foods or ingredients such as lactose, sulphite, and food additives which cause food intolerances rather than immune-mediated responses, should be excluded from this list. The Committee identified prevalence of the immune-mediated hypersensitivity to a specific food, severity (i.e. proportion of severe objective reactions to a food/ingredient such as anaphylaxis), and the potency of food/ingredient (i.e. the amount of the food/ingredient required to cause objective symptoms) as the three key criteria that should be used to establish the priority allergen list. Subgroups of the Expert Committee were established to review the literature on the prevalence, severity and potency of immune-mediated hypersensitivity of each food currently on the GSLPF list (cereals containing gluten and products of these; crustacea and products of these; eggs and egg products; fish and fish products; peanuts, soybeans and products of these; milk and milk products; tree nuts and nut products; ), as well as other foods found on priority allergen lists established in individual countries or regions (e.g. mollusks, mustard, celery, sesame, buckwheat, lupin, and others).Los objetivos de la reunión son ver si los criterios publicados (FAO / OMS, 2000) para evaluar las adiciones y exclusiones a la lista siguen vigentes y son apropiados. El Comité de Expertos determinó que solo los alimentos o ingredientes que causan hipersensibilidades inmunomediadas, como las alergias alimentarias mediadas por IgE y la enfermedad celíaca, deben incluirse en la lista de alimentos e ingredientes incluidos en la sección 4.2.1.4 de la GSLPF. Por lo tanto, se recomendó que se excluyeran de esta lista alimentos o ingredientes como lactosa, sulfito y aditivos alimentarios que causan intolerancias alimentarias en lugar de respuestas inmunomediadas. El Comité identificó la prevalencia de la hipersensibilidad inmunomediada a un alimento específico, la gravedad (es decir, la proporción de reacciones objetivas graves a un alimento / ingrediente como la anafilaxia) y la potencia del alimento / ingrediente (es decir, la cantidad de alimento / ingrediente requerida causar síntomas objetivos) como los tres criterios clave que deben utilizarse para establecer la lista de alérgenos prioritarios. Se establecieron subgrupos del Comité de Expertos para revisar la literatura sobre la prevalencia, severidad y potencia de la hipersensibilidad inmunomediada de cada alimento actualmente en la lista GSLPF (cereales que contienen gluten y productos de estos; crustáceos y productos de estos; huevos y productos de huevo ; pescado y productos de pescado; cacahuetes, soja y productos de estos; leche y productos lácteos; frutos secos y productos de frutos secos;), así como otros alimentos que se encuentran en las listas de alérgenos prioritarios establecidas en países o regiones individuales (por ejemplo, moluscos, mostaza, apio , sésamo, alforfón, altramuz y otros).Instituto de Investigación de Tecnología de AlimentosFil: Baumert, Joseph. Universidad de Nebraska-Lincoln. Departamento de Ciencia y Tecnología de Alimentos; Estados UnidosFil: Brooke-Taylor, Simon. Imperial College London. Instituto Nacional del Corazón y los Pulmones; Reino Unido.Fil: Chen, Hongbing. Nanchang Universidad. Instituto Conjunto de Investigación Chino-Alemán; China.Fil: Crevel, René W.R. René Crevel Consulting Limited; Reino Unido.Fil: Geert Houben. Organización para la Investigación Científica Aplicada TNO; Países Bajos.Fil: Jackson, Lauren. División de Ciencia y Tecnología del Procesamiento de Alimentos. Ingeniería de Procesos de la Administración de Alimentos y Medicamentos de los EE. UU. (FDA); Estados Unidos de América.Fil: Kyriakidis, Symeon. Laboratorio Estatal de Química General (GCSL). Autoridad Independiente de Ingresos Públicos (IAPR); Grecia.Fil: La Vieille, Sébastien. Universidad Laval. Departamento de Ciencias de los Alimentos; Canadá.Fil: Lee, N Alice. Universidad de Nueva Gales del Sur . Escuela de Química e Ingeniería. Ciencia e ingeniería de los alimentos; Australia.Fil: López, María Cristina. Universidad Nacional de San Martín. Ingeniería de Alimentos; Argentina.Fil: Luccioli, Stefano. Administración de Alimentos y Medicamentos de los Estados Unidos. Centro de Seguridad Alimentaria y Nutrición Aplicada; Estados UnidosFil: O’Mahony, Patrick. Universidad College Dublin; Irlanda.Fil: O’Mahony, Patrick. Autoridad de Seguridad Alimentaria de Irlanda; Irlanda.Fil: Polenta, Gustavo Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Tecnología de Alimentos; Argentina.Fil: Polenta, Gustavo Alberto. Instituto de Ciencia y Tecnología de los Sistemas Alimentarios Sustentables (ICyTeSAS) UEDD INTA-CONICET; Argentina.Fil: Pöpping, Bert. Food Consulting Strategically (FOCO); Alemania.Fil: Pöpping, Bert. Comités de Normalización ISO - CEN. Grupo de trabajo CEN Alérgenos Alimentarios (CEN TC 275 WG 12).); Alemania.Fil: Remington, Benjamin C. Remington Consulting Group B.V.; Holanda.Fil: Remington, Benjamin C. Universidad de Nebraska–Lincoln. Programa de Recursos e Investigación de Alergias Alimentarias. Estados UnidosFil: Södergren, Eva. ThermoFisher Scientific; Suecia.Fil: Srikulnath, Sirinrat. Universidad de Kasetsart (UKaset). Instituto de Investigación y Desarrollo de Productos Alimentarios. Centro de Servicio de Aseguramiento de la Calidad de los Alimentos. Unidad de Alérgenos Alimentarios; Tailandia.Fil: Taylor, Stephen L. Universidad de Nebraska-Lincoln. Departamento de Ciencia y Tecnología de Alimentos; Estados UnidosFil: Turner, Paul J. Universidad de Sídney; Australia.Fil: Turner, Paul J. Colegio Imperial de Ciencia, Tecnología y Medicina. Alergia e Inmunología Pediátricas; Inglaterra

Risk Assessment of Food Allergens. Part 1: Review and Validation of Codex Alimetarius Priority Allergen list Through Risk Assessment

The labelling of food allergens in pre-packaged foods plays a key role in protecting food allergic individuals, as no preventative clinical treatment is currently available. The list of major foods and ingredients known to cause hypersensitivity was included into the Codex General Standard for the Labelling of Packaged Foods (GSLPF) in 1999. There have been many scientific developments in the understanding of food allergens and their management since the original drafting of the GSLPF. Thus, in response to the request from Codex for scientific advice, including current evidence of consumer understanding of allergens, FAO and WHO convened a series of three expert meetings to provide scientific advice on this subject. The purpose of the first meeting of the Ad hoc Joint FAO/WHO Expert Consultation on Risk Assessment of Food Allergens was to review and validate the Codex priority allergen list through risk assessment. This report focuses on the deliberations and conclusions of this meeting. Resumen: El etiquetado de los alérgenos alimentarios en los alimentos preenvasados ​​juega un papel clave en la protección personas alérgicas a los alimentos, ya que actualmente no se dispone de un tratamiento clínico preventivo. Se incluyó la lista de los principales alimentos e ingredientes que causan hipersensibilidad en la Norma General del Codex para el Etiquetado de Alimentos Envasados ​​(GSLPF) en 1999. Ha habido muchos avances científicos en la comprensión de alérgenos alimentarios y su gestión desde la redacción original de la GSLPF. Por lo tanto, en respuesta a la solicitud del Codex de asesoramiento científico, incluida la actual evidencia de la comprensión del consumidor de los alérgenos, la FAO y la OMS convocaron una serie de tres reuniones de expertos para proporcionar asesoramiento científico sobre este tema. El propósito de la primera reunión de la Consulta Conjunta Especial de Expertos FAO/OMS sobre evaluación de riesgos de los alérgenos alimentarios fue revisar y validar la prioridad del Codex lista de alérgenos a través de la evaluación de riesgos. Este informe se centra en las deliberaciones y conclusiones de esta reunión.Instituto de Investigación de Tecnología de Alimentos (ITA)Fil: Baumert, Joseph. Universidad de Nebraska-Lincoln. Departamento de Ciencia y Tecnología de Alimentos; Estados UnidosFil: Brooke-Taylor, Simon. Imperial College London. Instituto Nacional del Corazón y los Pulmones; Reino Unido.Fil: Che, Huilian. Universidad de Agricultura de China. Facultad de Ciencias de la Alimentación e Ingeniería Nutricional; China.Fil: Chen, Hongbing. Nanchang Universidad. Instituto Conjunto de Investigación Chino-Alemán; China.Fil: Crevel, René W.R. René Crevel Consulting Limited; Reino Unido.Fil: Houben, Geert F. Alergia alimentaria e inmunotoxicología. Científico principal de TNO; Países Bajos.Fil: Jackson, Lauren. Administración de Alimentos y Medicamentos. División de Ciencia y Tecnología del Procesamiento de Alimentos. Ingeniería de Procesos; Estados UnidosFil: Kyriakidis, Symeon. Autoridad Independiente de Ingresos Públicos. Laboratorio Estatal de Química General; Grecia.Fil: La Vieille, Sébastien. Salud Canadá. Dirección de Alimentos; Canadá.Fil: Lee, N Alice. Universidad de Nueva Gales del Sur. Escuela de Química e Ingeniería. Ciencia e ingeniería de los alimentos; Australia.Fil: López, María Cristina. Universidad Nacional de San Martín. Ingeniería de Alimentos; Argentina.Fil: Luccioli, Stefano. Administración de Alimentos y Medicamentos. Centro de Seguridad Alimentaria y Nutrición Aplicada; Estados UnidosFil: O’Mahony, Patrick. Autoridad de Seguridad Alimentaria de Irlanda . Ciencia y Tecnología de los Alimentos; Irlanda.Fil: Polenta, Gustavo Alberto. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Investigación Tecnología de Alimentos; Argentina.Fil: Pöpping, Bert. Food Consulting Strategically (FOCO); Alemania.Fil: Remington, Benjamin C. Grupo BV. Consultoría Remington; Holanda.Fil: Södergren, Eva. Agencia Sueca de Alimentos. Equipo de Encuestas Dietéticas y Departamento de Nutrición para Beneficio de Riesgo Evaluación; Suecia.Fil: Srikulnath, Sirinrat. Universidad de Kasetsart (UKaset). Instituto de Investigación y Desarrollo de Productos Alimentarios. Centro de Servicio de Aseguramiento de la Calidad de los Alimentos. Unidad de Alérgenos Alimentarios; Tailandia.Fil: Taylor, Stephen L. Universidad de Nebraska-Lincoln. Departamento de Ciencia y Tecnología de Alimentos; Estados UnidosFil: Turner, Paul J. Colegio Imperial de Ciencia, Tecnología y Medicina. Alergia e Inmunología Pediátricas; Inglaterra

Antioxidant Properties of the Mung Bean Flavonoids on Alleviating Heat Stress

Background: It is a widespread belief in Asian countries that mung bean soup (MBS) may afford a protective effect against heat stress. Lack of evidence supports MBS conferring a benefit in addition to water. Results: Here we show that vitexin and isovitexin are the major antioxidant components in mungbean (more than 96 % of them existing in the bean seed coat), and both of them could be absorbed via gavage into rat plasma. In the plasma of rats fed with mungbean coat extract before or after exposure to heat stress, the levels of malonaldehyde and activities of lactate dehydrogenase and nitric oxide synthase were remarkably reduced; the levels of total antioxidant capacity and glutathione (a quantitative assessment of oxidative stress) were significantly enhanced. Conclusions: Our results demonstrate that MBS can play additional roles to prevent heat stress injury. Characterization of the mechanisms underlying mungbean beneficial effects should help in the design of diet therapy strategies to alleviate heat stress, as well as provide reference for searching natural medicines against oxidative stress induced diseases

Identification of Allergens in White- and Red-Fleshed Pitaya (<i>Selenicereus undatus</i> and <i>Selenicereus costaricensis</i>) Seeds Using Bottom-Up Proteomics Coupled with Immunoinformatics

White-fleshed pitaya (Selenicereus undatus) and red-fleshed pitaya (Selenicereus costaricensis) are becoming increasingly popular because of their nutritional and medicinal benefits. However, in addition to their beneficial properties, allergy to pitaya fruits has occurred in daily life. In this study, we investigated the protein profile of pitaya fruit seeds and focused on the most reactive proteins against immunoglobulin E (IgE) in sera from allergic patients by immunoblotting. A protein band of approximately 20 kDa displayed a clear reaction with the serum IgE. The protein bands of interest were excised, in-gel digested, and analyzed using liquid chromatography–tandem mass spectrometry (LC–MS/MS), followed by data searching against a restricted database (Caryophyllales in UniProtKB) for protein identification. Immunoinformatic tools were used to predict protein allergenicity. The potential allergens included cupin_1 and heat shock protein 70 (HSP70) in white-fleshed pitaya seeds, and cupin_1, heat shock protein 70, and heat shock protein sti1-like in red-fleshed pitaya seeds are potential allergens. The expression of potential allergens was further verified at the transcriptional level in the species of S. undatus and S. costaricensis.</i

The Interaction of Food Allergy and Diabetes: Food Allergy Effects on Diabetic Mice by Intestinal Barrier Destruction and Glucagon-like Peptide 1 Reduction in Jejunum

The increase in food allergies and diabetes leads to the assumption that they are related. This study aimed to (1) verify the interaction between food allergy and diabetes and (2) explore the potential mechanisms by which food allergy promotes diabetes. Female BALB/c mice were grouped into a control group (CK), an ovalbumin-sensitized group (OVA), a diabetes group (STZ), and a diabetic allergic group (STZ + OVA) (Mice were modeled diabetes with STZ first, then were given OVA to model food allergies), and an allergic diabetic group (OVA + STZ) (Mice were modeled food allergies with OVA first, then were given STZ to model diabetes). The results showed that OVA + STZ mice exhibited a more serious Th2 humoral response, and they were more susceptible to diabetes. Furthermore, when the OVA + STZ mice were in the sensitized state, the intestinal barrier function was severely impaired, and mast cell activation was promoted. Moreover, we found that the effect of food allergy on diabetes is related to the inhibition of GLP-1 secretion and the up-regulation of the PI3K/Akt/mTOR/NF-κB P65 signaling pathway in the jejunum. Overall, our results suggest that food allergies have interactions with diabetes, which sheds new light on the importance of food allergies in diabetes

Molecular Basis of IgE-Mediated Shrimp Allergy and Heat Desensitization

Crustacean allergy, especially to shrimp, is the most predominant cause of seafood allergy. However, due to the high flexibility of immunoglobulin E (IgE), its three-dimensional structure remains unsolved, and the molecular mechanism of shrimp allergen recognition is unknown. Here a chimeric IgE was built in silico, and its variable region in the light chain was replaced with sequences derived from shrimp tropomyosin (TM)-allergic patients. A variety of allergenic peptides from the Chinese shrimp TM were built, treated with heating, and subjected to IgE binding in silico. Amino acid analysis shows that the amino acid residue conservation in shrimp TM contributes to eliciting an IgE-mediated immune response. In the shrimp-allergic IgE, Glu98 in the light chain and other critical residues that recognize allergens from shrimp are implicated in the molecular basis of IgE-mediated shrimp allergy. Heat treatment could alter the conformations of TM allergenic peptides, impact their intramolecular hydrogen bonding, and subsequently decrease the binding between these peptides and IgE. We found Glu98 as the characteristic amino acid residue in the light chain of IgE to recognize general shrimp-allergic sequences, and heat-induced conformational change generally desensitizes shrimp allergens

Investigation on the allergen claims of pre-packaged food in China

Objective To investigate the current status of allergen claims in the label of prepackaged foods in China, and to provide suggestions for the revision of the General Rules for the Labelling of Prepackaged Foods. Methods Sampling or photographing was performed in large and medium-sized supermarkets across the country, allergen claims information on pre-packaged food were collected, various food allergen claims were analyzed. Results A total of 8 694 samples were included. The overall identification rate of allergen claims was 21.58% (1 876/8 694). The percentage of foods containing allergens claims in bakery foods was the highest (65.73%, 468/712). Among the allergens, the highest rate of claims was milk and dairy (17.09%, 1 486/8 694). The most frequent claims were "may contain", "this streamline also produces", "this processing equipment also produces", and "this plant also processes" which indicated the presence of cross-contaminations, and those claims were mainly in bakery foods, puffed foods, grains and their products. Conclusion There were many types of food allergens in pre-packaged foods in China. The use of allergen claim was not standardized, and their were too many cross-contamination claims. In general, allergen claims were widely used in food products and should become the focus of allergens management in China

IGRNet: A Deep Learning Model for Non-Invasive, Real-Time Diagnosis of Prediabetes through Electrocardiograms

The clinical symptoms of prediabetes are mild and easy to overlook, but prediabetes may develop into diabetes if early intervention is not performed. In this study, a deep learning model&mdash;referred to as IGRNet&mdash;is developed to effectively detect and diagnose prediabetes in a non-invasive, real-time manner using a 12-lead electrocardiogram (ECG) lasting 5 s. After searching for an appropriate activation function, we compared two mainstream deep neural networks (AlexNet and GoogLeNet) and three traditional machine learning algorithms to verify the superiority of our method. The diagnostic accuracy of IGRNet is 0.781, and the area under the receiver operating characteristic curve (AUC) is 0.777 after testing on the independent test set including mixed group. Furthermore, the accuracy and AUC are 0.856 and 0.825, respectively, in the normal-weight-range test set. The experimental results indicate that IGRNet diagnoses prediabetes with high accuracy using ECGs, outperforming existing other machine learning methods; this suggests its potential for application in clinical practice as a non-invasive, prediabetes diagnosis technology

Prediction of Type 2 Diabetes Risk and Its Effect Evaluation Based on the XGBoost Model

In view of the harm of diabetes to the population, we have introduced an ensemble learning algorithm&mdash;EXtreme Gradient Boosting (XGBoost) to predict the risk of type 2 diabetes and compared it with Support Vector Machines (SVM), the Random Forest (RF) and K-Nearest Neighbor (K-NN) algorithm in order to improve the prediction effect of existing models. The combination of convenient sampling and snowball sampling in Xicheng District, Beijing was used to conduct a questionnaire survey on the personal data, eating habits, exercise status and family medical history of 380 middle-aged and elderly people. Then, we trained the models and obtained the disease risk index for each sample with 10-fold cross-validation. Experiments were made to compare the commonly used machine learning algorithms mentioned above and we found that XGBoost had the best prediction effect, with an average accuracy of 0.8909 and the area under the receiver&rsquo;s working characteristic curve (AUC) was 0.9182. Therefore, due to the superiority of its architecture, XGBoost has more outstanding prediction accuracy and generalization ability than existing algorithms in predicting the risk of type 2 diabetes, which is conducive to the intelligent prevention and control of diabetes in the future