Doing synthetic biology with photosynthetic microorganisms

The use of photosynthetic microbes as synthetic biology hosts for the sustainable production of commodity chemicals and even fuels has received increasing attention over the last decade. The number of studies published, tools implemented, and resources made available for microalgae have increased beyond expectations during the last few years. However, the tools available for genetic engineering in these organisms still lag those available for the more commonly used heterotrophic host organisms. In this mini-review, we provide an overview of the photosynthetic microbes most commonly used in synthetic biology studies, namely cyanobacteria, chlorophytes, eustigmatophytes and diatoms. We provide basic information on the techniques and tools available for each model group of organisms, we outline the state-of-the-art, and we list the synthetic biology tools that have been successfully used. We specifically focus on the latest CRISPR developments, as we believe that precision editing and advanced genetic engineering tools will be pivotal to the advancement of the field. Finally, we discuss the relative strengths and weaknesses of each group of organisms and examine the challenges that need to be overcome to achieve their synthetic biology potential.Peer reviewe

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Evaluation of silicon nitride and silicon carbide as efficient polysilicon grain-growth inhibitors

10.1023/A:1006679625601Journal of Materials Science Letters18171427-1431JMSL

Robust atlas-based segmentation of highly variable anatomy: left atrium segmentation

Automatic segmentation of the heart’s left atrium offers great benefits for planning and outcome evaluation of atrial ablation procedures. However, the high anatomical variability of the left atrium presents significant challenges for atlas-guided segmentation. In this paper, we demonstrate an automatic method for left atrium segmentation using weighted voting label fusion and a variant of the demons registration algorithm adapted to handle images with different intensity distributions. We achieve accurate automatic segmentation that is robust to the high anatomical variations in the shape of the left atrium in a clinical dataset of MRA images.National Alliance for Medical Image Computing (U.S.) (NIH NIBIB NAMIC U54-EB005149)Neuroimaging Analysis Center (U.S.) (NIH NCRR NAC P41-RR13218)National Institute of Neurological Disorders and Stroke (U.S.) (NIH NINDS R01-NS051826)National Institutes of Health (U.S.) (Grant R01EB008743-01A2)National Science Foundation (U.S.) (CAREER grant 0642971)Irwin Mark Jacobs and Joan Klein Jacobs Presidential FellowshipJulie Payette-NSERC Research Scholarshi