28 results
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D2.480 - Features of the molecular sensitization profile in children with autism spectrum disorder

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D2.485 - Comprehensive Understanding of the Characteristics of Pediatric Pollen Allergy Patients

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D2.486 - Levels of house dust mite in dust settlements are associated with risk for allergic rhinitis in children

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D2.489 - B-Cell Subset Reconstitution After Rituximab-Containing Chemotherapy in Children and Adolescents With Non-Hodgkin Lymphoma: A Single-Center Experience

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D2.478 - HEREDITORY ANGIOEDEMA - A case report

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D2.477 - Nationwide Survey of Healthcare Transition from Paediatric to Adult Services for Allergic Diseases in Japan

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D2.479 - The bullous pemphigoid in a baby

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D2.481 - Severe obstructive syndrome in children with bronchopulmonary malformations

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D2.482 - Neuroendocrine Cell Hyperplasia of Infancy (NEHI): Report of 7 Cases

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D2.483 - Outdoor Activity and Screen Time at Age 3 years and Allergic Symptoms at Age 6 years: A Nationwide Birth Cohort Study (JECS)

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D2.487 - Avoiding Unnecessary Food Avoidance: Outcomes of Infants with Localised Reactions During Weaning

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D2.488 - Functional confirmation of exercise-induced bronchoconstriction in children: A three-year retrospective study

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D3.484 - Non-Invasive Detection of Airborne Fungal Exposure Using Machine Learning–Assisted Volatile Biomarker Sensing

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D3.485 - Prevalence of Ambrosia artemisiifolia in Italy: Bioinformatics and Botanical Aerobiology Analysis

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D3.477 - IgE Sialylation as a Potential Biomarker of Allergy: Evidence from Patients with Diverse Allergic Conditions

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D3.478 - Microsplenia: Spleen Size Reduction as a Comprehensive Biomarker for Immune-Related Diseases, Disease Monitoring, and Treatment Response

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D3.479 - Association between Mitochondrial DNA Copy Number and Lung Function in Schoolchildren

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D3.480 - Protamine Hypersensitivity Risk in an Elderly Patient with Recurrent Food Anaphylaxis and High Cardiovascular Risk- Case Report

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D3.481 - Machine Learning–Based Plasma Proteomic Signatures for Prediction of Chronic Rhinosinusitis

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D3.482 - Harnessing the Baseline Nasal Microbiome to Predict Pollen Related Symptom Expression