Arginase from kiwifruit: properties and seasonal variation

The in vitro activity of arginase (EC 3.5.3.1) was investigated in youngest-mature leaves and roots (1-3 mm diameter) of kiwifruit vines (Actinidia deliciosa var. deliciosa) during an annual growth cycle, and enzyme from root material partially purified. No seasonal trend in the specific activity of arginase was observed in roots. Measurements in leaves, however, rose gradually during early growth and plateaued c. 17 weeks after budbreak. Changes in arginase activity were not correlated with changes in the concentration of arginine (substrate) or glutamine (likely end-product of arginine catabolism) in either tissue during the growth cycle. Purification was by (NH4)2SO4 precipitation and DEAE-cellulose chromatography. The kinetic properties of the enzyme, purified 60-fold over that in crude extracts, indicated a pH optimum of 8.8, and a Km (L-arginine) of 7.85 mM. Partially-purified enzyme was deactivated by dialysis against EDTA, and reactivated in the presence of Mn²⁺, Co²⁺, and Ni²⁺

A hybrid discrete–continuum approach for modelling microcirculatory blood flow

In recent years, biological imaging techniques have advanced significantly and it is now possible to digitally reconstruct microvascular network structures in detail, identifying the smallest capillaries at sub-micron resolution and generating large 3D structural data sets of size >106 vessel segments. However, this relies on ex vivo imaging; corresponding in vivo measures of microvascular structure and flow are limited to larger branching vessels and are not achievable in three dimensions for the smallest vessels. This suggests the use of computational modelling to combine in vivo measures of branching vessel architecture and flows with ex vivo data on complete microvascular structures to predict effective flow and pressures distributions. In this paper, a hybrid discrete–continuum model to predict microcirculatory blood flow based on structural information is developed and compared with existing models for flow and pressure in individual vessels. A continuum-based Darcy model for transport in the capillary bed is coupled via point sources of flux to flows in individual arteriolar vessels, which are described explicitly using Poiseuille’s law. The venular drainage is represented as a spatially uniform flow sink. The resulting discrete–continuum framework is parameterized using structural data from the capillary network and compared with a fully discrete flow and pressure solution in three networks derived from observations of the rat mesentery. The discrete–continuum approach is feasible and effective, providing a promising tool for extracting functional transport properties in situations where vascular branching structures are well defined

Improved prediction accuracy for disease risk mapping using Gaussian process stacked generalization.

Maps of infectious disease-charting spatial variations in the force of infection, degree of endemicity and the burden on human health-provide an essential evidence base to support planning towards global health targets. Contemporary disease mapping efforts have embraced statistical modelling approaches to properly acknowledge uncertainties in both the available measurements and their spatial interpolation. The most common such approach is Gaussian process regression, a mathematical framework composed of two components: a mean function harnessing the predictive power of multiple independent variables, and a covariance function yielding spatio-temporal shrinkage against residual variation from the mean. Though many techniques have been developed to improve the flexibility and fitting of the covariance function, models for the mean function have typically been restricted to simple linear terms. For infectious diseases, known to be driven by complex interactions between environmental and socio-economic factors, improved modelling of the mean function can greatly boost predictive power. Here, we present an ensemble approach based on stacked generalization that allows for multiple nonlinear algorithmic mean functions to be jointly embedded within the Gaussian process framework. We apply this method to mapping Plasmodium falciparum prevalence data in sub-Saharan Africa and show that the generalized ensemble approach markedly outperforms any individual method

Cryopreservation of Human Adipose Tissues and Adipose-Derived Stem Cells with DMSO and/or Trehalose: A Systematic Review.

Adipose tissue senescence is implicated as a major player in obesity- and ageing-related disorders. There is a growing body of research studying relevant mechanisms in age-related diseases, as well as the use of adipose-derived stem cells in regenerative medicine. The cell banking of tissue by utilising cryopreservation would allow for much greater flexibility of use. Dimethyl sulfoxide (DMSO) is the most commonly used cryopreservative agent but is toxic to cells. Trehalose is a sugar synthesised by lower organisms to withstand extreme cold and drought that has been trialled as a cryopreservative agent. To examine the efficacy of trehalose in the cryopreservation of human adipose tissue, we conducted a systematic review of studies that used trehalose for the cryopreservation of human adipose tissues and adipose-derived stem cells. Thirteen articles, including fourteen studies, were included in the final review. All seven studies that examined DMSO and trehalose showed that they could be combined effectively to cryopreserve adipocytes. Although studies that compared nonpermeable trehalose with DMSO found trehalose to be inferior, studies that devised methods to deliver nonpermeable trehalose into the cell found it comparable to DMSO. Trehalose is only comparable to DMSO when methods are devised to introduce it into the cell. There is some evidence to support using trehalose instead of using no cryopreservative agent

Gaussian bosonic synergy: quantum communication via realistic channels of zero quantum capacity

As with classical information, error-correcting codes enable reliable transmission of quantum information through noisy or lossy channels. In contrast to the classical theory, imperfect quantum channels exhibit a strong kind of synergy: there exist pairs of discrete memoryless quantum channels, each of zero quantum capacity, which acquire positive quantum capacity when used together. Here we show that this "superactivation" phenomenon also occurs in the more realistic setting of optical channels with attenuation and Gaussian noise. This paves the way for its experimental realization and application in real-world communications systems.Comment: 5 pages, 4 figures, one appendi

Investigation of Non-Stable Processes in Close Binary Ry Scuti

We present results of reanalysis of old electrophotometric data of early type close binary system RY Scuti obtained at the Abastumani Astrophysical Observatory, Georgia, during 1972-1990 years and at the Maidanak Observatory, Uzbekistan, during 1979-1991 years. It is revealed non-stable processes in RY Sct from period to period, from month to month and from year to year. This variation consists from the hundredths up to the tenths of a magnitude. Furthermore, periodical changes in the system's light are displayed near the first maximum on timescales of a few years. That is of great interest with regard to some similar variations seen in luminous blue variable (LBV) stars. This also could be closely related to the question of why RY Sct ejected its nebula.Comment: 11 pages, 6 figures, 2 table

Spatial modelling of soil-transmitted helminth infections in Kenya: a disease control planning tool

Background Implementation of control of parasitic diseases requires accurate, contemporary maps that provide intervention recommendations at policy-relevant spatial scales. To guide control of soil transmitted helminths (STHs), maps are required of the combined prevalence of infection, indicating where this prevalence exceeds an intervention threshold of 20%. Here we present a new approach for mapping the observed prevalence of STHs, using the example of Kenya in 2009. Methods and Findings Observed prevalence data for hookworm, Ascaris lumbricoides and Trichuris trichiura were assembled for 106,370 individuals from 945 cross-sectional surveys undertaken between 1974 and 2009. Ecological and climatic covariates were extracted from high-resolution satellite data and matched to survey locations. Bayesian space-time geostatistical models were developed for each species, and were used to interpolate the probability that infection prevalence exceeded the 20% threshold across the country for both 1989 and 2009. Maps for each species were integrated to estimate combined STH prevalence using the law of total probability and incorporating a correction factor to adjust for associations between species. Population census data were combined with risk models and projected to estimate the population at risk and requiring treatment in 2009. In most areas for 2009, there was high certainty that endemicity was below the 20% threshold, with areas of endemicity ≥20% located around the shores of Lake Victoria and on the coast. Comparison of the predicted distributions for 1989 and 2009 show how observed STH prevalence has gradually decreased over time. The model estimated that a total of 2.8 million school-age children live in districts which warrant mass treatment. Conclusions Bayesian space-time geostatistical models can be used to reliably estimate the combined observed prevalence of STH and suggest that a quarter of Kenya's school-aged children live in areas of high prevalence and warrant mass treatment. As control is successful in reducing infection levels, updated models can be used to refine decision making in helminth control

A guided self-help intervention supporting mental health professionals’ decisions regarding sharing of lived experience

Mental health professionals with lived experience often experience heightened stigma and fear that their competency may be questioned. We present a new intervention (HOP-MHP) designed to support them in decisions about sharing their lived experience and preliminary results regarding the intervention’s acceptability and feasibility

Synthesis and pre-clinical evaluation of a [18F] fluoromethyl-tanaproget derivative for imaging of progesterone receptor expression

The estrogen receptor (ER) and progesterone receptor (PR) are over-expressed in ∼50% of breast cancer lesions, and used as biomarkers to stratify patients for endocrine therapy. Currently, immunohistochemical (IHC) assessment of these lesions from a core-needle biopsy in deep-sited metastases has limitations associated with sampling error and lack of standardization. An alternative solution is positron emission tomography (PET)-based probes, which are inherently quantitative and capable of imaging the entire tumor, including metastases. This work features the synthesis and biological evaluation of a novel fluorinated derivative of tanaproget, a high affinity non-steroidal PR ligand, as a candidate for imaging PR expression in vivo. Radiolabeling of the candidate was achieved in a 15% ± 4 radiochemical yield (non-decay corrected) in one step from [18F]fluoromethyltosylate in 30 min. Cell uptake studies showed a significant difference between the radioligand uptake in PR+ and PR- cell lines; however, in vivo imaging was confounded by defluorination hypothesized to occur via iminium salt formation. Investigation into high affinity, metabolically stable non-steroidal PR ligands is currently ongoing