751 research outputs found
Is aortic wall degeneration related to bicuspid aortic valve anatomy in patients with valvular disease?
ObjectivePatients with bicuspid aortic valve are at increased risk for aortic complications.MethodsA total of 115 consecutive patients with bicuspid aortic valve disease underwent surgery of the ascending aorta. We classified the cusp configuration by 3 types: fusion of left coronary and right coronary cusps (type A), fusion of right coronary and noncoronary cusps (type B), and fusion of left coronary and noncoronary cusps (type C). Histopathologic changes in the ascending aortic wall were graded (aortic wall score).ResultsWe observed type A fusion in 85 patients (73.9%), type B fusion in 28 patients (24.3%), and type C fusion in 2 patients (1.8%). Patients with type A fusion were younger at operation than patients with type B fusion (51.3 ± 15.5 years vs 58.7 ± 7.6 years, respectively; P = .034). The mean ascending aorta diameter was 48.9 ± 5.0 mm and 48.7 ± 5.7 mm in type A and type B fusion groups, respectively (P = .34). The mean aortic root diameter was significantly larger in type A fusion (4.9 ± 6.7 mm vs 32.7 ± 2.8 mm; P < .0001). The aortic wall score was significantly higher in type A fusion than in type B fusion (P = .02). The prevalence of aortic wall histopathologic changes was significantly higher in type A fusion. Moreover, there were no statistically significant differences between type A and type B fusion in terms of prevalence of bicuspid aortic valve stenosis, regurgitation, or mixed disease.ConclusionIn diseased bicuspid aortic valves, there was a statistically significant association between type A valve anatomy and a more severe degree of wall degeneration in the ascending aorta and dilatation of the aortic root at younger age compared with type B valve anatomy
Pilot study with oral rapamycin in patients undergoing stenting in coronary arteries: Buenos Aires experience (ORAR trial)
Predictive Criteria to Study the Pathogenesis of Malaria-Associated ALI/ARDS in Mice
Malaria-associated acute lung injury/acute respiratory distress syndrome (ALI/ARDS) often results in morbidity and mortality. Murine models to study malaria-associated ALI/ARDS have been described; we still lack a method of distinguishing which mice will develop ALI/ARDS before death. This work aimed to characterize malaria-associated ALI/ARDS in a murine model and to demonstrate the first method to predict whether mice are suffering from ALI/ARDS before death. DBA/2 mice infected with Plasmodium berghei ANKA developing ALI/ARDS or hyperparasitemia (HP) were compared using histopathology, PaO2 measurement, pulmonary X-ray, breathing capacity, lung permeability, and serum vascular endothelial growth factor (VEGF) levels according to either the day of death or the suggested predictive criteria. We proposed a model to predict malaria-associated ALI/ARDS using breathing patterns (enhanced pause and frequency respiration) and parasitemia as predictive criteria from mice whose cause of death was known to retrospectively diagnose the sacrificed mice as likely to die of ALI/ARDS as early as 7 days after infection. Using this method, we showed increased VEGF levels and increased lung permeability in mice predicted to die of ALI/ARDS. This proposed method for accurately identifying mice suffering from ALI/ARDS before death will enable the use of this model to study the pathogenesis of this disease.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento CientÃfico e Tecnológico (CNPq)Univ São Paulo, Inst Ciencias Biomed, Dept Imunol, BR-05508900 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Ciencias Biol, BR-09972270 Diadema, SP, BrazilUniv São Paulo, Inst Med Trop São Paulo, BR-05403000 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Ciencias Exatas & Terra, BR-09972270 Diadema, SP, BrazilUniv São Paulo, Inst Ciencias Biomed, Dept Parasitol, BR-05508000 São Paulo, BrazilUniv São Paulo, Fac Med Vet & Zootecn, Dept Cirurgia, BR-05508270 São Paulo, BrazilUniv São Paulo, Fac Med Vet & Zootecn, Dept Med Vet Prevent & Saude Anim, BR-05508270 São Paulo, BrazilUniv São Paulo, Fac Ciencias Farmaceut, Dept Anal Clin & Toxicol, BR-05508000 São Paulo, BrazilUniversidade Federal de São Paulo, Dept Ciencias Biol, BR-09972270 Diadema, SP, BrazilUniversidade Federal de São Paulo, Dept Ciencias Exatas & Terra, BR-09972270 Diadema, SP, BrazilFAPESP: 2009/53256-7FAPESP: 2009/53889-0CNPq: 306668/2012-2CNPq: 470590/2009-2Web of Scienc
Fabular: regression formulas as probabilistic programming
Regression formulas are a domain-specific language adopted by several R packages for describing an important and useful class of statistical models: hierarchical linear regressions. Formulas are succinct, expressive, and clearly popular, so are they a useful addition to probabilistic programming languages? And what do they mean? We propose a core calculus of hierarchical linear regression, in which regression coefficients are themselves defined by nested regressions (unlike in R). We explain how our calculus captures the essence of the formula DSL found in R. We describe the design and implementation of Fabular, a version of the Tabular schema-driven probabilistic programming language, enriched with formulas based on our regression calculus. To the best of our knowledge, this is the first formal description of the core ideas of R's formula notation, the first development of a calculus of regression formulas, and the first demonstration of the benefits of composing regression formulas and latent variables in a probabilistic programming language.Adam Åšcibior received travel support from the DARPA PPAML programme. Marcin Szymczak was supported by Microsoft Research through its PhD Scholarship Programme.This is the author accepted manuscript. The final version is available from the Association of Computer Machinery via http://dx.doi.org/10.1145/2837614.283765
West Nile virus transmission. results from the integrated surveillance system in Italy, 2008 to 2015
IIn Italy a national Plan for the surveillance of imported and autochthonous human vector-borne diseases (chikungunya, dengue, Zika virus disease and West Nile virus (WNV) disease) that integrates human and veterinary (animals and vectors) surveillance, is issued and revised annually according with the observed epidemiological changes. Here we describe results of the WNV integrated veterinary and human surveillance systems in Italy from 2008 to 2015. A real time data exchange protocol is in place between the surveillance systems to rapidly identify occurrence of human and animal cases and to define and update the map of affected areas i.e. provinces during the vector activity period from June to October. WNV continues to cause severe illnesses in Italy during every transmission season, albeit cases are sporadic and the epidemiology varies by virus lineage and geographic area. The integration of surveillance activities and a multidisciplinary approach made it possible and have been fundamental in supporting implementation of and/or strengthening preventive measures aimed at reducing the risk of transmission of WNV trough blood, tissues and organ donation and to implementing further measures for vector control
Mortality and Advanced Support Requirement for Patients With Cancer With COVID-19 : A Mathematical Dynamic Model for Latin America
PURPOSE: In the midst of a global pandemic, evidence suggests that similar to other severe respiratory viral infections, patients with cancer are at higher risk of becoming infected by COVID-19 and have a poorer prognosis. METHODS: We have modeled the mortality and the intensive care unit (ICU) requirement for the care of patients with cancer infected with COVID-19 in Latin America. A dynamic multistate Markov model was constructed. Transition probabilities were estimated on the basis of published reports for cumulative probability of complications. Basic reproductive number (R0) values were modeled with R using the EpiEstim package. Estimations of days of ICU requirement and absolute mortality were calculated by imputing number of cumulative cases in the Markov model. RESULTS: Estimated median time of ICU requirement was 12.7 days, median time to mortality was 16.3 days after infection, and median time to severe event was 8.1 days. Peak ICU occupancy for patients with cancer was calculated at 16 days after infection. Deterministic sensitivity analysis revealed an interval for mortality between 18.5% and 30.4%. With the actual incidence tendency, Latin America would be expected to lose approximately 111,725 patients with cancer to SARS-CoV-2 (range, 87,116-143,154 patients) by the 60th day since the start of the outbreak. Losses calculated vary between < 1% to 17.6% of all patients with cancer in the region. CONCLUSION: Cancer-related cases and deaths attributable to SARS-CoV-2 will put a great strain on health care systems in Latin America. Early implementation of interventions on the basis of data given by disease modeling could mitigate both infections and deaths among patients with cancer
Software design and code generation for the engineering graphical user interface of the ASTRI SST-2M prototype for the Cherenkov Telescope Array
ASTRI is an on-going project developed in the framework of the Cherenkov Telescope Array (CTA). An end- to-end prototype of a dual-mirror small-size telescope (SST-2M) has been installed at the INAF observing station on Mt. Etna, Italy. The next step is the development of the ASTRI mini-array composed of nine ASTRI SST-2M telescopes proposed to be installed at the CTA southern site. The ASTRI mini-array is a collaborative and international effort carried on by Italy, Brazil and South-Africa and led by the Italian National Institute of Astrophysics, INAF. To control the ASTRI telescopes, a specific ASTRI Mini-Array Software System (MASS) was designed using a scalable and distributed architecture to monitor all the hardware devices for the telescopes. Using code generation we built automatically from the ASTRI Interface Control Documents a set of communication libraries and extensive Graphical User Interfaces that provide full access to the capabilities offered by the telescope hardware subsystems for testing and maintenance. Leveraging these generated libraries and components we then implemented a human designed, integrated, Engineering GUI for MASS to perform the verification of the whole prototype and test shared services such as the alarms, configurations, control systems, and scientific on-line outcomes. In our experience the use of code generation dramatically reduced the amount of effort in development, integration and testing of the more basic software components and resulted in a fast software release life cycle. This approach could be valuable for the whole CTA project, characterized by a large diversity of hardware components
Genetic architecture distinguishes systemic juvenile idiopathic arthritis from other forms of juvenile idiopathic arthritis: Clinical and therapeutic implications
Objectives Juvenile idiopathic arthritis (JIA) is a heterogeneous group of conditions unified by the presence of chronic childhood arthritis without an identifiable cause. Systemic JIA (sJIA) is a rare form of JIA characterised by systemic inflammation. sJIA is distinguished from other forms of JIA by unique clinical features and treatment responses that are similar to autoinflammatory diseases. However, approximately half of children with sJIA develop destructive, long-standing arthritis that appears similar to other forms of JIA. Using genomic approaches, we sought to gain novel insights into the pathophysiology of sJIA and its relationship with other forms of JIA. Methods We performed a genome-wide association study of 770 children with sJIA collected in nine countries by the International Childhood Arthritis Genetics Consortium. Single nucleotide polymorphisms were tested for association with sJIA. Weighted genetic risk scores were used to compare the genetic architecture of sJIA with other JIA subtypes. Results The major histocompatibility complex locus and a locus on chromosome 1 each showed association with sJIA exceeding the threshold for genome-wide significance, while 23 other novel loci were suggestive of association with sJIA. Using a combination of genetic and statistical approaches, we found no evidence of shared genetic architecture between sJIA and other common JIA subtypes. Conclusions The lack of shared genetic risk factors between sJIA and other JIA subtypes supports the hypothesis that sJIA is a unique disease process and argues for a different classification framework. Research to improve sJIA therapy should target its unique genetics and specific pathophysiological pathways
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