Occurrence and Severity of the Viruses of Strawberry in Minnesota

Approximately 900 plants of commercially grown strawberries of 45 varieties and experimental seedling selections were collected from various parts of the state of Minnesota and indexed for the presence of viruses. Their presence in these plants was demonstrated by the appearance of symptoms in the indicator plant, Fragaria vesca L., after they were inarch-grafted. 93 % of the plants indexed were virus-infected. Based on symptoms, the viruses have been classified into 14 symptomtypes. It was found that mottle and mild yellow-edge were the two dominant viruses, whereas crinkle and vein chlorosis were of rare occurrence. There was no indication that certain symptom-types are associated with particular commercial varieties of strawberries or experimental seedling selections

Biomarkers for Diagnosis and Prognosis of Sinusoidal Obstruction Syndrome after Hematopoietic Cell Transplantation.

Reliable, non-invasive methods for diagnosing and prognosing sinusoidal obstruction syndrome (SOS) early after hematopoietic cell transplantation (HCT) are needed. We used a quantitative mass spectrometry-based proteomics approach to identify candidate biomarkers of SOS by comparing plasma pooled from 20 patients with and 20 patients without SOS. Of 494 proteins quantified, we selected six proteins [L-Ficolin, vascular-cell-adhesion-molecule-1 (VCAM1), tissue-inhibitor of metalloproteinase-1, von Willebrand factor, intercellular-adhesion-molecule-1, and CD97] based on a differential heavy/light isotope ratio of at least 2 fold, information from the literature, and immunoassay availability. Next, we evaluated the diagnostic potential of these six proteins and five selected from the literature [suppression of tumorigenicity-2 (ST2), angiopoietin-2 (ANG2), hyaluronic acid (HA), thrombomodulin, and plasminogen activator inhibitor-1] in samples from 80 patients. The results demonstrate that together ST2, ANG2

Global snow mass measurements and the effect of stratigraphic detail on inversion of microwave brightness temperatures

Snow provides large seasonal storage of freshwater, and information about the distribution of snow mass as Snow Water Equivalent (SWE) is important for hydrological planning and detecting climate change impacts. Large regional disagreements remain between estimates from reanalyses, remote sensing and modelling. Assimilating passive microwave information improves SWE estimates in many regions but the assimilation must account for how microwave scattering depends on snow stratigraphy. Physical snow models can estimate snow stratigraphy, but users must consider the computational expense of model complexity versus acceptable errors. Using data from the National Aeronautics and Space Administration Cold Land Processes Experiment (NASA CLPX) and the Helsinki University of Technology (HUT) microwave emission model of layered snowpacks, it is shown that simulations of the brightness temperature difference between 19 GHz and 37 GHz vertically polarised microwaves are consistent with Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and Special Sensor Microwave Imager (SSM/I) retrievals once known stratigraphic information is used. Simulated brightness temperature differences for an individual snow profile depend on the provided stratigraphic detail. Relative to a profile defined at the 10 cm resolution of density and temperature measurements, the error introduced by simplification to a single layer of average properties increases approximately linearly with snow mass. If this brightness temperature error is converted into SWE using a traditional retrieval method then it is equivalent to ±13 mm SWE (7% of total) at a depth of 100 cm. This error is reduced to ±5.6 mm SWE (3 % of total) for a two-layer model

A local glucose-and oxygen concentration-based insulin secretion model for pancreatic islets

<p>Abstract</p> <p>Background</p> <p>Because insulin is the main regulator of glucose homeostasis, quantitative models describing the dynamics of glucose-induced insulin secretion are of obvious interest. Here, a computational model is introduced that focuses not on organism-level concentrations, but on the quantitative modeling of local, cellular-level glucose-insulin dynamics by incorporating the detailed spatial distribution of the concentrations of interest within isolated avascular pancreatic islets.</p> <p>Methods</p> <p>All nutrient consumption and hormone release rates were assumed to follow Hill-type sigmoid dependences on local concentrations. Insulin secretion rates depend on both the glucose concentration and its time-gradient, resulting in second-and first-phase responses, respectively. Since hypoxia may also be an important limiting factor in avascular islets, oxygen and cell viability considerations were also built in by incorporating and extending our previous islet cell oxygen consumption model. A finite element method (FEM) framework is used to combine reactive rates with mass transport by convection and diffusion as well as fluid-mechanics.</p> <p>Results</p> <p>The model was calibrated using experimental results from dynamic glucose-stimulated insulin release (GSIR) perifusion studies with isolated islets. Further optimization is still needed, but calculated insulin responses to stepwise increments in the incoming glucose concentration are in good agreement with existing experimental insulin release data characterizing glucose and oxygen dependence. The model makes possible the detailed description of the intraislet spatial distributions of insulin, glucose, and oxygen levels. In agreement with recent observations, modeling also suggests that smaller islets perform better when transplanted and/or encapsulated.</p> <p>Conclusions</p> <p>An insulin secretion model was implemented by coupling local consumption and release rates to calculations of the spatial distributions of all species of interest. The resulting glucose-insulin control system fits in the general framework of a sigmoid proportional-integral-derivative controller, a generalized PID controller, more suitable for biological systems, which are always nonlinear due to the maximum response being limited. Because of the general framework of the implementation, simulations can be carried out for arbitrary geometries including cultured, perifused, transplanted, and encapsulated islets.</p

A View from the Past Into our Collective Future: The Oncofertility Consortium Vision Statement

Today, male and female adult and pediatric cancer patients, individuals transitioning between gender identities, and other individuals facing health extending but fertility limiting treatments can look forward to a fertile future. This is, in part, due to the work of members associated with the Oncofertility Consortium. The Oncofertility Consortium is an international, interdisciplinary initiative originally designed to explore the urgent unmet need associated with the reproductive future of cancer survivors. As the strategies for fertility management were invented, developed or applied, the individuals for who the program offered hope, similarly expanded. As a community of practice, Consortium participants share information in an open and rapid manner to addresses the complex health care and quality-of-life issues of cancer, transgender and other patients. To ensure that the organization remains contemporary to the needs of the community, the field designed a fully inclusive mechanism for strategic planning and here present the findings of this process. This interprofessional network of medical specialists, scientists, and scholars in the law, medical ethics, religious studies and other disciplines associated with human interventions, explore the relationships between health, disease, survivorship, treatment, gender and reproductive longevity. The goals are to continually integrate the best science in the service of the needs of patients and build a community of care that is ready for the challenges of the field in the future

Type 1 diabetes mellitus induces structural changes and molecular remodelling in the rat kidney

There is much evidence that diabetes mellitus (DM) –induced hyperglycemia (HG) is responsible for kidney failure or nephropathy leading to cardiovascular complications. Cellular and molecular mechanism(s) whereby DM can damage the kidney is still not fully understood. This study investigated the effect of streptozotocin (STZ)-induced diabetes (T1DM) on the structure and associated molecular alterations of the isolated rat left kidney following 2 and 4 months of the disorder compared to the respective age-matched controls. The results revealed hypertrophy and general disorganized architecture of the kidney characterized by expansion in glomerular borders, tubular atrophy and increased vacuolization of renal tubular epithelial cells in the diabetic groups compared to controls. Electron microscopic analysis revealed ultrastructural alterations in the left kidney highlighted by an increase in glomerular basement membrane width. In addition, increased caspase-3 immuno-reactivity was observed in the kidney of T1DM animals compared to age-matched controls. These structural changes were associated with elevated extracellular matrix (ECM) deposition and consequently, altered gene expression profile of ECM key components, together with elevated levels of key mediators (MMP9, integrin 5α, TIMP4, CTGF, vimentin) and reduced expressions of Cx43 and MMP2 of the ECM. Marked hypertrophy of the kidney was highlighted by increased atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) gene expression. These changes also correlated with increased TGFβ1 activity, gene expression in the left kidney and elevated active TGFβ1 in plasma of T1DM rats compared to control. The results clearly demonstrated that TIDM could elicit severe structural changes and alteration in biochemical markers (remodeling) in the kidney leading to diabetic nephropathy (DN)