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Background Juvenile-onset recurrent respiratory papillomatosis (JORRP) is a rare and serious disease caused by human papillomavirus (HPV) presumably acquired during vaginal delivery. HPV vaccination of females through age 26 years, recommended in the United States since 2006, can prevent HPV transmission. We assessed trends in JORRP cases before and after HPV vaccine introduction in the United States. Methods Case-patients were identified from 26 pediatric otolaryngology centers in 23 U.S. states. Demographics and clinical history were abstracted from medical records. Case-patients were grouped by year of birth, and birth-cohort incidences were calculated using number of births from either national or state-level natality data from the 23 states. We calculated incidence rate ratios (IRR) and 95% confidence intervals (CI) in 2-year intervals. Results We identified 576 U.S. JORRP case-patients born in 2004–2013. Median age at diagnosis was 3.4 years (interquartile range: 1.9, 5.5). Number of identified JORRP case-patients declined from a baseline of 165 born in 2004–2005 to 36 born in 2012–2013. Incidence of JORRP per 100 000 births using national data declined from 2.0 cases in 2004–2005 to 0.5 cases in 2012–2013 (IRR = 0.2, 95% CI =.1–.4); incidence using state-level data declined from 2.9 cases in 2004–2005 to 0.7 cases in 2012–2013 (IRR = 0.2, 95% CI =.1–.4). Conclusions Over a decade, numbers of JORRP case-patients and incidences declined significantly. Incidences calculated using national denominator data are likely underestimates; those calculated using state-level denominator data could be overestimates. These declines are most likely due to HPV vaccination. Increasing vaccination uptake could lead to elimination of this HPV-related disease. [ABSTRACT FROM AUTHOR]

Background Juvenile-onset recurrent respiratory papillomatosis (JORRP) is a rare disease characterized by the growth of papillomas in the respiratory tract. In the United States, JORRP is not a nationally notifiable condition and current data are limited. Methods Children with JORRP aged <18 years were enrolled from 26 pediatric otolaryngology centers in 23 US states from January 2015 through August 2020. Demographic, birth information, and maternal vaccination history were collected from a parent/guardian. Clinical history was abstracted from medical records. Papilloma biopsies were tested for 28 human papillomavirus (HPV) types. Mothers who delivered in 2006 or later were considered age-eligible for HPV vaccination if aged ≤26 years in 2006. We described characteristics of enrolled children and their birth mothers and analyzed disease severity by diagnosis age and HPV type using multiple logistic regression. Results Among 215 children with JORRP, 88.8% were delivered vaginally; 64.2% were firstborn. Among 190 mothers, the median delivery age was 22 years. Among 114 (60.0%) age-eligible for HPV vaccination, 16 (14.0%) were vaccinated, 1 (0.9%) before delivery. Among 162 specimens tested, 157 (96.9%) had detectable HPV; all 157 had a vaccine-preventable type. Disease severity was associated with younger diagnosis age and HPV 11; adjusted analyses found only younger diagnosis age significant (adjusted odds ratio: 6.1; 95% confidence interval: 2.9, 12.8). Conclusions Children with JORRP were commonly firstborn and delivered vaginally to young mothers; most of the mothers reported no HPV vaccination before delivery. Vaccine-preventable HPV was identified in all specimens with detectable HPV. Increasing preexposure HPV vaccination could substantially reduce or eliminate JORRP in the United States. [ABSTRACT FROM AUTHOR]

Motivation Molecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behaviour of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner. Results We developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML- qual), that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability. Availability and implementation The present tool is available online: https://lifeware.inria.fr/∼soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) is a progressive, inflammatory autoimmune disease of unknown aetiology. The complex mechanism of aetiopathogenesis, progress and chronicity of the disease involves genetic, epigenetic and environmental factors. To understand the molecular mechanisms underlying disease phenotypes, one has to place implicated factors in their functional context. However, integration and organization of such data in a systematic manner remains a challenging task. Molecular maps are widely used in biology to provide a useful and intuitive way of depicting a variety of biological processes and disease mechanisms. Recent large-scale collaborative efforts such as the Disease Maps Project demonstrate the utility of such maps as versatile tools to organize and formalize disease-specific knowledge in a comprehensive way, both human and machine-readable. We present a systematic effort to construct a fully annotated, expert validated, state-of-the-art knowledge base for RA in the form of a molecular map. The RA map illustrates molecular and signalling pathways implicated in the disease. Signal transduction is depicted from receptors to the nucleus using the Systems Biology Graphical Notation (SBGN) standard representation. High-quality manual curation, use of only human-specific studies and focus on small-scale experiments aim to limit false positives in the map. The state-of-the-art molecular map for RA, using information from 353 peer-reviewed scientific publications, comprises 506 species, 446 reactions and 8 phenotypes. The species in the map are classified to 303 proteins, 61 complexes, 106 genes, 106 RNA entities, 2 ions and 7 simple molecules. The RA map is available online at ramap.elixir-luxembourg.org as an open-access knowledge base allowing for easy navigation and search of molecular pathways implicated in the disease. Furthermore, the RA map can serve as a template for omics data visualization. [ABSTRACT FROM AUTHOR]