Electron microscopic and biochemical characterization of Fraction 1 protein

High resolution electron microscopy of Fraction I protein from plant leave

Reassociation of hemocyanins from subunit mixtures

Reactions of hemocyanin from different biological origins studied by electron microscop

Macromolecular organization of hemocyanins and apohemocyanins as revealed by electron microscopy

Comparative high resolution electron microscopic studies of structural organization of hemocyanins and apohemocyanins from mollusca and arthropod

The evaluation of an integrated network approach of preventive care for children with overweight and obesity:Study protocol for an implementation and effectiveness study

Background: Children with overweight often do not receive appropriate integrated care. An innovative integrated network approach of preventive care for overweight children aged 4-12 years old has been developed and implemented in four neighbourhoods of 's-Hertogenbosch, The Netherlands. This new approach focusses on self-management of the family and is based on the principles of stepped and matched care. Youth health care (YHC) nurses support the families in their new role as central care providers. The aim of this study is to evaluate the implementation and effectiveness of this network approach. Methods: The implementation of the new approach (reach, functioning of the central care provider, network functioning and patient satisfaction) is assessed by interviews and checklists with professionals and parents of 4-12 year old overweight or obese children. To evaluate effectiveness, we aim to compare 120 overweight or obese children in 's-Hertogenbosch with 60 overweight or obese children outside 's-Hertogenbosch during one year of YHC involvement. Quality of life, psychosocial problems of the child and parental empowerment are the main outcomes of the effectiveness study. Outcomes are measured with digital questionnaires at inclusion, at three months and one year after inclusion. BMI measurements and referrals are distracted from medical files. Discussion: Integrated care for overweight and obese children is high on the agenda of many municipalities in The Netherlands. The new approach is expected to have beneficial effects for overweight children, their parents and professionals. With the results of this study, we can optimize the support for overweight and obese children and their parents. The first results are expected to be available in 2019

ELECTRON-MICROSCOPIC ANALYSIS AND BIOCHEMICAL-CHARACTERIZATION OF A NOVEL METHANOL DEHYDROGENASE FROM THE THERMOTOLERANT BACILLUS-SP C1

Methanol dehydrogenase from the thermotolerant Bacillus sp. C1 was studied by electron microscopy and image processing. Two main projections can be distinguished: one exhibits 5-fold symmetry and has a diameter of 15 nm, the other is rectangular with sides of 15 and 9 nm. Subsequent image processing showed that the 5-fold view possesses mirror symmetry. The rectangular views can be divided into two separate classes, one of which has 2-fold rotational symmetry. It is concluded that methanol dehydrogenase is a decameric molecule, and a tentative model is presented. The estimated molecular weight is 430,000, based on a subunit molecular weight of 43,000. The enzyme contains one zinc and one to two magnesium ions per subunit. N-terminal amino acid sequence analysis revealed substantial similarity with alcohol dehydrogenases from Saccharomyces cerevisiae, Zymomonas mobilis, Clostridium acetobutylicum, and Escherichia coli, which contain iron or zinc but no magnesium. In view of the aberrant structural and kinetic properties, it is proposed to distinguish the enzyme from common alcohol dehydrogenases (EC 1.1.1.1) by using the name NAD-dependent methanol dehydrogenase

Complex diffuse radio emission in the merging PLANCK ESZ cluster Abell 3411

We present VLA radio and Chandra X-ray observations of the merging galaxy cluster Abell 3411. For the cluster, we find an overall temperature of 6.4 keV and an X-ray luminosity of 2.8 x 10^{44} erg s^{-1} between 0.5 and 2.0 keV. The Chandra observation reveals the cluster to be undergoing a merger event. The VLA observations show the presence of large-scale diffuse emission in the central region of the cluster, which we classify as a 0.9 Mpc size radio halo. In addition, a complex region of diffuse, polarized emission is found in the southeastern outskirts of the cluster, along the projected merger axis of the system. We classify this region of diffuse emission as a radio relic. The total extent of this radio relic is 1.9 Mpc. For the combined emission in the cluster region, we find a radio spectral index of -1.0 \pm 0.1 between 74 MHz and 1.4 GHz. The morphology of the radio relic is peculiar, as the relic is broken up into five fragments. This suggests that the shock responsible for the relic has been broken up due to interaction with a large-scale galaxy filament connected to the cluster or other substructures in the ICM. Alternatively, the complex morphology reflects the presence of electrons in fossil radio bubbles that are re-accelerated by a shock.Comment: Accepted for publication in ApJ, 8 pages, 5 figure

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning.

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions. Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy. Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status. We show that these traits have a substantial heritable component (8-44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported. Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits