Food allergy across the globe

A spotlight on analytical prospects in food allergens: From emerging allergens and novel foods to bioplastics and plant-based sustainable food contact materials

The present review throws a spotlight on new and emerging food safety concerns in view of a well-established food allergen risk arising from global socio-economic changes, international trade, circular economy, environmental sustainability, and upcycling. Food culture globalization needs harmonization of regulations, technical specifications, and reference materials towards mutually recognised results. In parallel, routine laboratories require high-throughput reliable analytical strategies, even in-situ testing devices, to test both food products and food contact surfaces for residual allergens. Finally, the currently neglected safety issues associated to possible allergen exposure due to the newly proposed bio- and plant-based sustainable food contact materials require an in-depth investigation.

Managing the allergy and asthma epidemic in 2020s-Lessons from the Finnish experience

In Finland, a systematic public health programme was implemented from 2008 to 2018 to mitigate the burden of allergic disorders by revisiting the prevention strategy. Allergy health and contacts with natural environment were emphasized to promote immunological and psychological resilience instead of poorly justified avoidance. Allergy management practices were improved and low‐valued recommendations for care, for example for food allergy, were revised. Patients and families were empowered to use guided self‐management to proactively stop symptom exacerbations. A professional non‐governmental organization implemented the nationwide education for healthcare and patient NGOs for patients, families and lay public. In healthcare, the work supporting allergic patients and families was organized towards common goals and integrated into everyday work without extra costs. Reaching the predefined goals was followed by employing the national healthcare registers and questionnaire surveys. Governmental bodies contributed with kick‐off funding, which was supplemented by private funding. International collaboration, for example with the European patient organization (EFA), increased awareness of the Finnish action and predisposed it for peer review. The 10‐year results are favourable, patients are less disabled, practices and attitudes in healthcare have changed, and major cost savings have been obtained. Views of the lay public and patients are slow to move, however. Local multidisciplinary allergy teams were set up to continue the activities also after the Programme. Changes in environment and lifestyle in the last 50 years are the main reasons for the allergy rise. The Finnish experience may help to manage allergic diseases, improve nature relatedness in the fast‐urbanizing world, combat nature loss and reduce the disease burden.

Immunologic and pathologic characterization of a novel swine biomedical research model for eosinophilic esophagitis

Eosinophilic esophagitis (EoE) is a chronic allergy-mediated condition with an increasing incidence in both children and adults. Despite EoE's strong impact on human health and welfare, there is a large unmet need for treatments with only one recently FDA-approved medication for EoE. The goal of this study was to establish swine as a relevant large animal model for translational biomedical research in EoE with the potential to facilitate development of therapeutics. We recently showed that after intraperitoneal sensitization and oral challenge with the food allergen hen egg white protein (HEWP), swine develop esophageal eosinophilia-a hallmark of human EoE. Herein, we used a similar sensitization and challenge treatment and evaluated immunological and pathological markers associated with human EoE. Our data demonstrate that the incorporated sensitization and challenge treatment induces (i) a systemic T-helper 2 and IgE response, (ii) a local expression of eotaxin-1 and other allergy-related immune markers, (iii) esophageal eosinophilia (>15 eosinophils/0.24 mm²), and (iv) esophageal endoscopic findings including linear furrows and white exudates. Thereby, we demonstrate that our sensitization and oral challenge protocol not only induces the underlying immune markers but also the micro- and macro-pathological hallmarks of human EoE. This swine model for EoE represents a novel relevant large animal model that can drive translational biomedical research to develop urgently needed treatment strategies for EoE.

Factors Associated With Lower Respiratory Tract Infection Among Chinese Students Aged 6-14 Years

AIMS

We employed machine-learning methods to explore data from a large survey on students, with the goal of identifying and validating a thrifty panel of important factors associated with lower respiratory tract infection (LRTI).

METHODS

Cross-sectional cluster sampling was performed for a survey of students aged 6-14 years who attended primary or junior high school in Beijing within January, 2022. Data were collected via electronic questionnaires. Statistical analyses were completed using the PyCharm (Edition 2018.1 x64) and Python (Version 3.7.6).

RESULTS

Data from 11,308 students (5,527 girls and 5,781 boys) were analyzed, and 909 of them had LRTI with the prevalence of 8.01%. After a comprehensive evaluation, the Gaussian naive Bayes (gNB) algorithm outperformed the other machine-learning algorithms. The gNB algorithm had accuracy of 0.856, precision of 0.140, recall of 0.165, F1 score of 0.151, and area under the receiver operating characteristic curve (AUROC) of 0.652. Using the optimal gNB algorithm, top five important factors, including age, rhinitis, sitting time, dental caries, and food or drug allergy, had decent prediction performance. In addition, the top five factors had prediction performance comparable to all factors modeled. For example, under the sequential deep-learning model, the accuracy and loss were separately gauged at 92.26 and 25.62% when incorporating the top five factors, and 92.22 and 25.52% when incorporating all factors.

CONCLUSIONS

Our findings showed the top five important factors modeled by gNB algorithm can sufficiently represent all involved factors in predicting LRTI risk among Chinese students aged 6-14 years.