124 research outputs found
Long term (5 Year) safety of bronchial thermoplasty: Asthma Intervention Research (AIR) trial
<b>Background:</b>
Bronchial thermoplasty (BT) is a bronchoscopic procedure that improves asthma control by reducing excess airway smooth muscle. Treated patients have been followed out to 5 years to evaluate long-term safety of this procedure.
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<b>Methods:</b>
Patients enrolled in the Asthma Intervention Research Trial were on inhaled corticosteroids ≥200 μg beclomethasone or equivalent + long-acting-beta2-agonists and demonstrated worsening of asthma on long-acting-β2-agonist withdrawal. Following initial evaluation at 1 year, subjects were invited to participate in a 4 year safety study. Adverse events (AEs) and spirometry data were used to assess long-term safety out to 5 years post-BT.
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<b>Results:</b>
45 of 52 treated and 24 of 49 control group subjects participated in long-term follow-up of 5 years and 3 years respectively. The rate of respiratory adverse events (AEs/subject) was stable in years 2 to 5 following BT (1.2, 1.3, 1.2, and 1.1, respectively,). There was no increase in hospitalizations or emergency room visits for respiratory symptoms in Years 2, 3, 4, and 5 compared to Year 1. The FVC and FEV1 values showed no deterioration over the 5 year period in the BT group. Similar results were obtained for the Control group.
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<b>Conclusions:</b>
The absence of clinical complications (based on AE reporting) and the maintenance of stable lung function (no deterioration of FVC and FEV1) over a 5-year period post-BT in this group of patients with moderate to severe asthma support the long-term safety of the procedure out to 5 years
Genome sequence and rapid evolution of the rice pathogen Xanthomonas oryzae pv. oryzae PXO99A
Background: Xanthomonas oryzae pv. oryzae causes bacterial blight of rice (Oryza sativa L.), a major disease that constrains production of this staple crop in many parts of the world. We report here on the complete genome sequence of strain PXO99A and its comparison to two previously sequenced strains, KACC10331 and MAFF311018, which are highly similar to one another. Results: The PXO99 A genome is a single circular chromosome of 5,240,075 bp, considerably longer than the genomes of the other strains (4,941,439 bp and 4,940,217 bp, respectively), and it contains 5083 protein-coding genes, including 87 not found in KACC10331 or MAFF311018. PXO99A contains a greater number of virulence-associated transcription activator-like effector genes and has at least ten major chromosomal rearrangements relative to KACC10331 and MAFF311018. PXO99 A contains numerous copies of diverse insertion sequence elements, members of which are associated with 7 out of 10 of the major rearrangements. A rapidly-evolving CRISPR (clustered regularly interspersed short palindromic repeats) region contains evidence of dozens of phage infections unique to the PXO99A lineage. PXO99A also contains a unique, near-perfect tandem repeat of 212 kilobases close to the replication terminus. Conclusion: Our results provide striking evidence of genome plasticity and rapid evolution within Xanthomonas oryzae pv. oryzae. The comparisons point to sources of genomic variation and candidates for strain-specific adaptations of this pathogen that help to explain the extraordinary diversity of Xanthomonas oryzae pv. oryzae genotypes and races that have been isolated from around the world. © 2008 Salzberg et al; licensee BioMed Central Ltd
Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals
Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details
Insight into the evolution of the Solanaceae from the parental genomes of Petunia hybrida
Petunia hybrida is a popular bedding plant that has a long history as a genetic model system. We report the whole-genome sequencing and assembly of inbred derivatives of its two wild parents, P. axillaris N and P. inflata S6. The current assemblies include 91.3% and 90.2% coverage of their diploid genomes (1.4 Gb; 2n=14) containing 32,928 and 36,697 protein-coding genes, respectively. The Petunia lineage has experienced at least two rounds of paleohexaploidization, the older gamma hexaploidy event, which is shared with other Eudicots, and the more recent Solanaceae paleohexaploidy event that is shared with tomato and other Solanaceae species. Transcription factors that were targets of selection during the shift from bee- to moth pollination reside in particularly dynamic regions of the genome, which may have been key to the remarkable diversity of floral color patterns and pollination systems. The high quality genome sequences will enhance the value of Petunia as a model system for basic and applied research on a variety of unique biological phenomena
Nordic consensus report on asthma management
AbstractThe work with the Nordic consensus report on asthma management started some years ago. The Nordic countries have common socioeconomic conditions. We acknowledge the international as well as other European guidelines providing valuable recommendations. Nevertheless, we felt the need to combine the common Nordic experiences in order to have a local statement of asthma and asthma care, based upon Nordic clinical science and tradition. The work has been rewarding and we acknowledge many valuable contributions from paediatricians, allergologists and lung physicians in all Nordic countries. The response has so far been positive and we feel that the present material reflects the main opinion of Nordic physicians taking care of asthma patients of all ages. However, the asthma and allergy research field is rapidly developing. Thus, this document should merely be regarded as a time-limited contribution to the continuing scientific discussion of this fascinating field
A Genome-Wide Survey of Switchgrass Genome Structure and Organization
The perennial grass, switchgrass (Panicum virgatum L.), is a promising bioenergy crop and the target of whole genome sequencing. We constructed two bacterial artificial chromosome (BAC) libraries from the AP13 clone of switchgrass to gain insight into the genome structure and organization, initiate functional and comparative genomic studies, and assist with genome assembly. Together representing 16 haploid genome equivalents of switchgrass, each library comprises 101,376 clones with average insert sizes of 144 (HindIII-generated) and 110 kb (BstYI-generated). A total of 330,297 high quality BAC-end sequences (BES) were generated, accounting for 263.2 Mbp (16.4%) of the switchgrass genome. Analysis of the BES identified 279,099 known repetitive elements, >50,000 SSRs, and 2,528 novel repeat elements, named switchgrass repetitive elements (SREs). Comparative mapping of 47 full-length BAC sequences and 330K BES revealed high levels of synteny with the grass genomes sorghum, rice, maize, and Brachypodium. Our data indicate that the sorghum genome has retained larger microsyntenous regions with switchgrass besides high gene order conservation with rice. The resources generated in this effort will be useful for a broad range of applications
Monogenic variants in dystonia: an exome-wide sequencing study
Background Dystonia is a clinically and genetically heterogeneous condition that occurs in isolation (isolated dystonia), in combination with other movement disorders (combined dystonia), or in the context of multisymptomatic phenotypes (isolated or combined dystonia with other neurological involvement). However, our understanding of its aetiology is still incomplete. We aimed to elucidate the monogenic causes for the major clinical categories of dystonia. Methods For this exome-wide sequencing study, study participants were identified at 33 movement-disorder and neuropaediatric specialty centres in Austria, Czech Republic, France, Germany, Poland, Slovakia, and Switzerland. Each individual with dystonia was diagnosed in accordance with the dystonia consensus definition. Index cases were eligible for this study if they had no previous genetic diagnosis and no indication of an acquired cause of their illness. The second criterion was not applied to a subset of participants with a working clinical diagnosis of dystonic cerebral palsy. Genomic DNA was extracted from blood of participants and whole-exome sequenced. To find causative variants in known disorder-associated genes, all variants were filtered, and unreported variants were classified according to American College of Medical Genetics and Genomics guidelines. All considered variants were reviewed in expert round-table sessions to validate their clinical significance. Variants that survived filtering and interpretation procedures were defined as diagnostic variants. In the cases that went undiagnosed, candidate dystonia-causing genes were prioritised in a stepwise workflow. Findings We sequenced the exomes of 764 individuals with dystonia and 346 healthy parents who were recruited between June 1, 2015, and July 31, 2019. We identified causative or probable causative variants in 135 (19%) of 728 families, involving 78 distinct monogenic disorders. We observed a larger proportion of individuals with diagnostic variants in those with dystonia (either isolated or combined) with coexisting non-movement disorder-related neurological symptoms (100 [45%] of 222;excepting cases with evidence of perinatal brain injury) than in those with combined (19 [19%] of 98) or isolated (16 [4%] of 388) dystonia. Across all categories of dystonia, 104 (65%) of the 160 detected variants affected genes which are associated with neurodevelopmental disorders. We found diagnostic variants in 11 genes not previously linked to dystonia, and propose a predictive clinical score that could guide the implementation of exome sequencing in routine diagnostics. In cases without perinatal sentinel events, genomic alterations contributed substantively to the diagnosis of dystonic cerebral palsy. In 15 families, we delineated 12 candidate genes. These include IMPDH2, encoding a key purine biosynthetic enzyme, for which robust evidence existed for its involvement in a neurodevelopmental disorder with dystonia. We identified six variants in IMPDH2, collected from four independent cohorts, that were predicted to be deleterious de-novo variants and expected to result in deregulation of purine metabolism. Interpretation In this study, we have determined the role of monogenic variants across the range of dystonic disorders, providing guidance for the introduction of personalised care strategies and fostering follow-up pathophysiological explorations
Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering
This publication is the Proceedings of the 29th EG-ICE International Workshop on Intelligent Computing in Engineering from July 6-8, 2022. The EG-ICE International Workshop on Intelligent Computing in Engineering brings together international experts working on the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolution of challenges such as supporting multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways.
 
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