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Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.
Background. Data on potential variations in delivery of appropriate stroke care over time are scarce. We investigated temporal changes in the quality of acute hospital stroke care across five national audits in Europe over a period of six years. Methods. Data were derived from national stroke audits in Germany, Poland, Scotland, Sweden, and England/Wales/Northern Ireland participating within the European Implementation Score (EIS) collaboration. Temporal changes in predefined quality indicators with comparable information between the audits were investigated. Multivariable logistic regression analyses were performed to estimate adherence to quality indicators over time. Results. Between 2004 and 2009, individual data from 542,112 patients treated in 538 centers participating continuously over the study period were included. In most audits, the proportions of patients who were treated on a SU, were screened for dysphagia, and received thrombolytic treatment increased over time and ranged from 2-fold to almost 4-fold increase in patients receiving thrombolytic therapy in 2009 compared to 2004. Conclusions. A general trend towards a better quality of stroke care defined by standardized quality indicators was observed over time. The association between introducing a specific measure and higher adherence over time might indicate that monitoring of stroke care performance contributes to improving quality of care.
Introduction: Chronic nonbacterial osteomyelitis (CNO) is an inflammatory disorder of unknown etiology. In children and adolescents CNO predominantly affects the metaphyses of the long bones, but lesions can occur at any site of the skeleton. Prospectively followed cohorts using a standardized protocol in diagnosis and treatment have rarely been reported. Methods: Thirty-seven children diagnosed with CNO were treated with naproxen continuously for the first 6 months. If assessment at that time revealed progressive disease or no further improvement, sulfasalazine and short-term corticosteroids were added. The aims of our short-term follow-up study were to describe treatment response in detail and to identify potential risk factors for an unfavorable outcome. Results: Naproxen treatment was highly effective in general, inducing a symptom-free status in 43% of our patients after 6 months. However, four nonsteroidal anti-inflammatory drug (NSAID) partial-responders were additionally treated with sulfasalazine and short-term corticosteroids. The total number of clinical detectable lesions was significantly reduced. Mean disease activity estimated by the patient/physician and the physical aspect of health-related quality of life including functional ability (global assessment/childhood health assessment questionnaire and childhood health assessment questionnaire) and pain improved significantly. Forty-one percent of our patients showed radiological relapses, but 67% of them were clinically silent. Conclusions: Most children show a favorable clinical course in the first year of anti-inflammatory treatment with NSAIDs. Relapses and new radiological lesions can occur at any time and at any site in the skeleton but may not be clinically symptomatic. Whole-body magnetic resonance imaging proved to be very sensitive for initial and follow-up diagnostics.
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
(2016)
Background
A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.
Results
We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.
Conclusions
The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.
Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.
Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics and metabarcoding to measure forest recovery post-agriculture in a global biodiversity hotspot in Ecuador. We show that the community composition, and not species richness, of vocalizing vertebrates identified by experts reflects the restoration gradient. Two automated measures – an acoustic index model and a bird community composition derived from an independently developed Convolutional Neural Network - correlated well with restoration (adj-R² = 0.62 and 0.69, respectively). Importantly, both measures reflected composition of non-vocalizing nocturnal insects identified via metabarcoding. We show that such automated monitoring tools, based on new technologies, can effectively monitor the success of forest recovery, using robust and reproducible data.
Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) can present with different histopathological growth patterns. The impact of these histopathological growth patterns on relapse characteristics is unknown. We therefore analyzed paired biopsies obtained at initial diagnosis and relapse from 33 NLPHL patients who had received first‐line treatment within German Hodgkin Study Group (GHSG) trial protocols, and from a second cohort of 41 relapsed NLPHL patients who had been treated outside GHSG studies. Among the 33 GHSG patients, 21 patients presented with a typical growth pattern at initial diagnosis, whereas 12 patients had a variant histology. The histopathological growth patterns at initial diagnosis and at relapse were consistent in 67% of cases. A variant histology at initial diagnosis was associated with a shorter median time to lymphoma recurrence (2.8 vs 5.2 years; P = .0219). A similar tendency towards a shorter median time to lymphoma recurrence was observed for patients presenting with a variant histology at relapse, irrespective of the growth pattern at initial diagnosis. Results obtained from the 41 NLPHL patients who had been treated outside GHSG studies were comparable (median time to lymphoma recurrence for variant histology vs typical growth pattern at initial diagnosis: 1.5 vs 7.0 years). In conclusion, the histopathological growth pattern remains consistent at relapse in the majority of NLPHL cases, and has major impact on the time of relapse.
(1) Background: Refractory acute graft-versus-host disease (R-aGvHD) remains a leading cause of death after allogeneic stem cell transplantation. Survival rates of 15% after four years are currently achieved; deaths are only in part due to aGvHD itself, but mostly due to adverse effects of R-aGvHD treatment with immunosuppressive agents as these predispose patients to opportunistic infections and loss of graft-versus-leukemia surveillance resulting in relapse. Mesenchymal stromal cells (MSC) from different tissues and those generated by various protocols have been proposed as a remedy for R-aGvHD but the enthusiasm raised by initial reports has not been ubiquitously reproduced. (2) Methods: We previously reported on a unique MSC product, which was generated from pooled bone marrow mononuclear cells of multiple third-party donors. The products showed dose-to-dose equipotency and greater immunosuppressive capacity than individually expanded MSCs from the same donors. This product, MSC-FFM, has entered clinical routine in Germany where it is licensed with a national hospital exemption authorization. We previously reported satisfying initial clinical outcomes, which we are now updating. The data were collected in our post-approval pharmacovigilance program, i.e., this is not a clinical study and the data is high-level and non-monitored. (3) Results: Follow-up for 92 recipients of MSC-FFM was reported, 88 with GvHD ≥°III, one-third only steroid-refractory and two-thirds therapy resistant (refractory to steroids plus ≥2 additional lines of treatment). A median of three doses of MSC-FFM was administered without apparent toxicity. Overall response rates were 82% and 81% at the first and last evaluation, respectively. At six months, the estimated overall survival was 64%, while the cumulative incidence of death from underlying disease was 3%. (4) Conclusions: MSC-FFM promises to be a safe and efficient treatment for severe R-aGvHD.