Optimization of the allergen classification of the International Classification Of Diseases, 11th Revision (ICD-11).

Background: Accurate diagnosis of triggers or causative allergens is essential for appropriate risk assessment, providing correct advice to patients with allergy and their caregivers and personalized treatment. However, allergens have never been represented in the World Health Organization International Classification of Diseases (ICD).

Objective: In this article, we present the process of selection of allergens to better fit the ICD, 11th Revision (ICD-11) structure and the outcomes of this process.

Metapopulation ecology links antibiotic resistance, consumption, and patient transfers in a network of hospital wards.

Antimicrobial resistance (AMR) is a global threat. A better understanding of how antibiotic use and between-ward patient transfers (or connectivity) impact population-level AMR in hospital networks can help optimize antibiotic stewardship and infection control strategies. Here, we used a metapopulation framework to explain variations in the incidence of infections caused by seven major bacterial species and their drug-resistant variants in a network of 357 hospital wards.

Semantic data interoperability, digital medicine, and e-health in infectious disease management: a review.

Disease management requires the use of mixed languages when discussing etiology, diagnosis, treatment, and follow-up. All phases require data management, and, in the optimal case, such data are interdisciplinary and uniform and clear to all those involved. Such semantic data interoperability is one of the technical building blocks that support emerging digital medicine, e-health, and P4-medicine (predictive, preventive, personalized, and participatory).

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays.

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens.