Outcomes and care practices for preterm infants born at less than 33 weeks’ gestation: A quality-improvement study

BACKGROUND: Preterm birth is the leading cause of morbidity and mortality in children younger than 5 years. We report the changes in neonatal outcomes and care practices among very preterm infants in Canada over 14 years within a national, collaborative, continuous quality-improvement program. METHODS: We retrospectively studied infants born at 23–32 weeks’ gestation who were admitted to tertiary neonatal intensive care units that participated in the Evidence-based Practice for Improving Quality program in the Canadian Neonatal Network from 2004 to 2017. The primary outcome was survival without major morbidity during the initial hospital admission. We quantified changes using process-control charts in 6-month intervals to identify special-cause variations, adjusted regression models for yearly changes, and interrupted time series analyses. RESULTS: The final study population included 50 831 infants. As a result of practice changes, survival without major morbidity increased significantly (56.6% [669/1183] to 70.9% [1424/2009]; adjusted odds ratio [OR] 1.08, 95% confidence interval [CI] 1.06–1.10, per year) across all gestational ages. Survival of infants born at 23–25 weeks’ gestation increased (70.8% [97/137] to 74.5% [219/294]; adjusted OR 1.03, 95% CI 1.02–1.05, per year). Changes in care practices included increased use of antenatal steroids (83.6% [904/1081] to 88.1% [1747/1983]), increased rates of normothermia at admission (44.8% [520/1160] to 67.5% [1316/1951]) and reduced use of pulmonary surfactant (52.8% [625/1183] to 42.7% [857/2009]). INTERPRETATION: Network-wide quality-improvement activities that include better implementation of optimal care practices can yield sustained improvement in survival without morbidity in very preterm infants

The Ocean Sampling Day Consortium

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

The ocean sampling day consortium

Kopf, Anna ... et. al.-- 5 pages, 1 figure.-- This manuscript is NOAA-GLERL contribution number 1763Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world’s oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traitsThis work was supported by the Micro B3 project, which is funded from the European Union’s Seventh Framework Programme (FP7; Joint Call OCEAN.2011‐2: Marine microbial diversity – new insights into marine ecosystems functioning and its biotechnological potential) under the grant agreement no 287589Peer Reviewe

Synthetic seismic data generation for automated AI-based procedures with an example application to high-resolution interpretation

This paper discusses the generation of synthetic 3D seismic data for training neural networks to solve a variety of seismic processing, interpretation, and inversion tasks. Using synthetic data is a way to address the shortage of seismic data, which are required for solving problems with machine learning techniques. Synthetic data are built via a simulation process that is based on a mathematical representation of the physics of the problem. In other words, using synthetic data is an indirect way to teach neural networks about the physics of the problem. An important incentive for using synthetic data to solve problems with artificial intelligence methods is that with real seismic data the ground truth is always unknown. When generating synthetic seismic data, we first build the model and then calculate the data, so the answer (model) is always known and always exact. We describe a methodology for generating on-the-fly simulated postmigration (1D modeling) synthetic data in 3D, which are high resolution and look similar to real data. A wide range of models is covered by generating an unlimited number of data examples. The synthetic data are built from impedance models that are constructed through geostatistical simulation of real well logs. With geostatistical simulation, we can describe various geologic variance models in 3D and obtain realistic images. To cover a broad range of scenarios, we need to generalize the seismic data story by randomly perturbing many parameters including structures, conformity styles, dip-strike directions, variograms, measured input logs, frequencies, phase spectra, etc. </jats:p