Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment

Radio emission from Supernova Remnants

The explosion of a supernova releases almost instantaneously about 10^51 ergs of mechanic energy, changing irreversibly the physical and chemical properties of large regions in the galaxies. The stellar ejecta, the nebula resulting from the powerful shock waves, and sometimes a compact stellar remnant, constitute a supernova remnant (SNR). They can radiate their energy across the whole electromagnetic spectrum, but the great majority are radio sources. Almost 70 years after the first detection of radio emission coming from a SNR, great progress has been achieved in the comprehension of their physical characteristics and evolution. We review the present knowledge of different aspects of radio remnants, focusing on sources of the Milky Way and the Magellanic Clouds, where the SNRs can be spatially resolved. We present a brief overview of theoretical background, analyze morphology and polarization properties, and review and critical discuss different methods applied to determine the radio spectrum and distances. The consequences of the interaction between the SNR shocks and the surrounding medium are examined, including the question of whether SNRs can trigger the formation of new stars. Cases of multispectral comparison are presented. A section is devoted to reviewing recent results of radio SNRs in the Magellanic Clouds, with particular emphasis on the radio properties of SN 1987A, an ideal laboratory to investigate dynamical evolution of an SNR in near real time. The review concludes with a summary of issues on radio SNRs that deserve further study, and analyzing the prospects for future research with the latest generation radio telescopes.Comment: Revised version. 48 pages, 15 figure

Impaired Spleen Formation Perturbs Morphogenesis of the Gastric Lobe of the Pancreas

Despite the extensive use of the mouse as a model for studies of pancreas development and disease, the development of the gastric pancreatic lobe has been largely overlooked. In this study we use optical projection tomography to provide a detailed three-dimensional and quantitative description of pancreatic growth dynamics in the mouse. Hereby, we describe the epithelial and mesenchymal events leading to the formation of the gastric lobe of the pancreas. We show that this structure forms by perpendicular growth from the dorsal pancreatic epithelium into a distinct lateral domain of the dorsal pancreatic mesenchyme. Our data support a role for spleen organogenesis in the establishment of this mesenchymal domain and in mice displaying perturbed spleen development, including Dh +/−, Bapx1−/− and Sox11−/−, gastric lobe development is disturbed. We further show that the expression profile of markers for multipotent progenitors is delayed in the gastric lobe as compared to the splenic and duodenal pancreatic lobes. Altogether, this study provides new information regarding the developmental dynamics underlying the formation of the gastric lobe of the pancreas and recognizes lobular heterogeneities regarding the time course of pancreatic cellular differentiation. Collectively, these data are likely to constitute important elements in future interpretations of the developing and/or diseased pancreas

Integrating real-world data from Brazil and Pakistan into the OMOP common data model and standardized health analytics framework to characterize COVID-19 in the Global South

Objectives: The aim of this work is to demonstrate the use of a standardized health informatics framework to generate reliable and reproducible real-world evidence from Latin America and South Asia towardsand characterizinge coronavirus disease 2019 (COVID-19) in the Global South. Materials and Methods: Patient-level COVID-19 records collected in a patient self-reported notification system, hospital in-patient and out-patient records, and off-sitecommunity diagnostic labs were harmonized to the Observational Medical Outcomes Partnership common data model and analyzed using a federated network analytics design framework. Clinical characteristics of individuals tested for, diagnosed with or tested positive for, hospitalized with, admitted to intensive care unit with, or dying with COVID-19 were estimated. Results: Two COVID-19 databases covering 8.3 million people from Pakistan and 2.6 million people from Bahia, Brazil were analyzed. In total, 109 504 (Pakistan) and 921 (Brazil) medical concepts were harmonized to Observational Medical Outcomes Partnership common data model. In total, 341 505 (4.1%) people in the Pakistan dataset and 1 312 832 (49.2%) people in the Brazilian dataset were tested for COVID-19 between January 1, 2020 and April 20, 2022, aged with a median [IQR] age of 36 [25, 76] and 38 (27, 50); 45.540.3% and 56.55% were female in Pakistan and Brazil, respectively. Five1.2% percent Pakistan individuals in the Pakistan dataset had Afghan ethnicity. In Brazil, 52.3% had mixed ethnicity. In agreement with international findings, COVID-19 outcomes were more severe in men, elderly, and those with underlying health conditions. Conclusions: COVID-19 data from 2 large countries in the Global South were harmonized and analyzed using a standardized health informatics framework developed by an international community of health informaticians. This proof-of-concept study demonstrates a potential open scienceframework for global knowledge mobilization and clinical translation for timely response to health-care needs in pandemics and beyond.</p

Integrating real-world data from Brazil and Pakistan into the OMOP common data model and standardized health analytics framework to characterize COVID-19 in the Global South

Objectives: The aim of this work is to demonstrate the use of a standardized health informatics framework to generate reliable and reproducible real-world evidence from Latin America and South Asia towardsand characterizinge coronavirus disease 2019 (COVID-19) in the Global South. Materials and Methods: Patient-level COVID-19 records collected in a patient self-reported notification system, hospital in-patient and out-patient records, and off-sitecommunity diagnostic labs were harmonized to the Observational Medical Outcomes Partnership common data model and analyzed using a federated network analytics design framework. Clinical characteristics of individuals tested for, diagnosed with or tested positive for, hospitalized with, admitted to intensive care unit with, or dying with COVID-19 were estimated. Results: Two COVID-19 databases covering 8.3 million people from Pakistan and 2.6 million people from Bahia, Brazil were analyzed. In total, 109 504 (Pakistan) and 921 (Brazil) medical concepts were harmonized to Observational Medical Outcomes Partnership common data model. In total, 341 505 (4.1%) people in the Pakistan dataset and 1 312 832 (49.2%) people in the Brazilian dataset were tested for COVID-19 between January 1, 2020 and April 20, 2022, aged with a median [IQR] age of 36 [25, 76] and 38 (27, 50); 45.540.3% and 56.55% were female in Pakistan and Brazil, respectively. Five1.2% percent Pakistan individuals in the Pakistan dataset had Afghan ethnicity. In Brazil, 52.3% had mixed ethnicity. In agreement with international findings, COVID-19 outcomes were more severe in men, elderly, and those with underlying health conditions. Conclusions: COVID-19 data from 2 large countries in the Global South were harmonized and analyzed using a standardized health informatics framework developed by an international community of health informaticians. This proof-of-concept study demonstrates a potential open scienceframework for global knowledge mobilization and clinical translation for timely response to health-care needs in pandemics and beyond