Modeling physical and chemical climate of the northeastern United States for a geographic information system

A model of physical and chemical climate was developed for New York and New England that can be used in a GIs for integration with ecosystem models. The variables included are monthly average maximum and minimum daily temperatures, precipitation, humidity, and solar radiation, as well as annual atmospheric deposition of sulfur and nitrogen. Equations generated from regional data bases were combined with a digital elevation model of the region to generate digital coverages of each variable

Differences in Spectral Sensitivity Within and Among Species of Darters (genus Etheostoma)

We examined variation in the visual system both within and among seven species of darters, colorful freshwater fishes of the genus Etheostoma. Using microspectrophotometry, we found that darters possess rod photoreceptor cells, single cone photoreceptor cells containing middle wavelength sensitive (MWS) visual pigments, and twin photoreceptor cells containing (LWS) visual pigments. No variation in peak sensitivity was detected among species or individuals in the rod class. In the MWS class, significant variation was detected among species and a strong statistical trend suggests differences among individuals. By contrast, all differences in the LWS class could be attributed to variation among individuals. Patterns of variation detected among species, among individuals, and among cone classes suggest that complex patterns of selection may be shaping the visual system of these fishes. Further, differences among individuals may have important consequences for visually based behaviors

Competing risks of cancer mortality and cardiovascular events in individuals with multimorbidity

Background: Cancer patients with cardiovascular and other comorbidities are at concurrent risk of multiple adverse outcomes. However, most treatment decisions are guided by evidence from single-outcome models, which may be misleading for multimorbid patients. Objective: We assessed the interacting effects of cancer, cardiovascular, and other morbidity burdens on the competing outcomes of cancer mortality, serious cardiovascular events, and other-cause mortality. Design: We analyzed a cohort of 6,500 adults with initial cancer diagnosis between 2001 and 2008, SEER 5-year survival ≥26%, and a range of cardiovascular risk factors. We estimated the cumulative incidence of cancer mortality, a serious cardiovascular event (myocardial infarction, coronary revascularization, or cardiovascular mortality), and other-cause mortality over 5 years, and identified factors associated with the competing risks of each outcome using cause-specific Cox proportional hazard models. Results: Following cancer diagnosis, there were 996 (15.3%) cancer deaths, 328 (5.1%) serious cardiovascular events, and 542 (8.3%) deaths from other causes. In all, 4,634 (71.3%) cohort members had none of these outcomes. Although cancer prognosis had the greatest effect, cardiovascular and other morbidity also independently increased the hazard of each outcome. The effect of cancer prognosis on outcome was greatest in year 1, and the effect of other morbidity was greater in individuals with better cancer prognoses. Conclusion: In multimorbid oncology populations, comorbidities interact to affect the competing risk of different outcomes. Quantifying these risks may provide persons with cancer plus cardiovascular and other comorbidities more accurate information for shared decision-making than risks calculated from single-outcome models. Journal of Comorbidity 2014:4(1):29–3

Retrospective evaluation of the seasonality of canine tetanus in England (2006-2017):49 dogs

Objective To evaluate the seasonality of canine tetanus in England.Methods Medical records of a single referral hospital in England were reviewed. Dogs diagnosed with localized or generalized tetanus between January 2006 and June 2017 were studied.Results Forty-nine cases were included. The prevalence of tetanus in England was significantly higher in the winter when compared with the summer (P = 0.002) and autumn (P = 0.024), with the highest number of cases recorded in February.Conclusions The prevalence of canine tetanus in England was significantly higher in winter months, especially in February

Pericellular activation of hepatocyte growth factor by the transmembrane serine proteases matriptase and hepsin, but not by the membrane-associated protease uPA

HGF (hepatocyte growth factor) is a pleiotropic cytokine homologous to the serine protease zymogen plasminogen that requires canonical proteolytic cleavage to gain functional activity. The activating proteases are key components of its regulation, but controversy surrounds their identity. Using quantitative analysis we found no evidence for activation by uPA (urokinase plasminogen activator), despite reports that this is a principal activator of pro-HGF. This was unaffected by a wide range of experimental conditions, including the use of various molecular forms of both HGF and uPA, and the presence of uPAR (uPA receptor) or heparin. In contrast the catalytic domains of the TTSPs (type-II transmembrane serine proteases) matriptase and hepsin were highly efficient activators (50% activation at 0.1 and 3.4 nM respectively), at least four orders of magnitude more efficient than uPA. PS-SCL (positional-scanning synthetic combinatorial peptide libraries) were used to identify consensus sequences for the TTSPs, which in the case of hepsin corresponded to the pro-HGF activation sequence, demonstrating a high specificity for this reaction. Both TTSPs were also found to be efficient activators at the cell surface. Activation of pro-HGF by PC3 prostate carcinoma cells was abolished by both protease inhibition and matriptase-targeting siRNA (small interfering RNA), and scattering of MDCK (Madin–Darby canine kidney) cells in the presence of pro-HGF was abolished by inhibition of matriptase. Hepsin-transfected HEK (human embryonic kidney)-293 cells also activated pro-HGF. These observations demonstrate that, in contrast with the uPA/uPAR system, the TTSPs matriptase and hepsin are direct pericellular activators of pro-HGF, and that together these proteins may form a pathway contributing to their involvement in pathological situations, including cancer

The effectiveness of beach mega-nourishment, assessed over three management epochs

Resilient coastal protection requires adaptive management strategies that build with nature to maintain long-term sustainability. With increasing pressures on shorelines from urbanisation, industrial growth, sea-level rise and changing storm climates soft approaches to coastal management are implemented to support natural habitats and maintain healthy coastal ecosystems. The impact of a beach mega-nourishment along a frontage of interactive natural and engineered systems that incorporate soft and hard defences is explored. A coastal evolution model is applied to simulate the impact of different hypothetical mega-nourishment interventions to assess their impacts’ over 3 shoreline management planning epochs: present-day (0–20 years), medium-term (20–50 years) and long-term (50–100 years). The impacts of the smaller interventions when appropriately positioned are found to be as effective as larger schemes, thus making them more cost-effective for present-day management. Over time the benefit from larger interventions becomes more noticeable, with multi-location schemes requiring a smaller initial nourishment to achieve at least the same benefit as that of a single-location scheme. While the longer-term impact of larger schemes reduces erosion across a frontage the short-term impact down drift of the scheme can lead to an increase in erosion as the natural sediment drift becomes interrupted. This research presents a transferable modelling tool to assess the impact of nourishment schemes for a variety of sedimentary shorelines and highlights both the positive and negative impact of beach mega-nourishment

Optimizing hatchery practices for genetic improvement of marine bivalves

This is the final version. Available from Wiley via the DOI in this record. Aquaculture currently accounts for approximately half of all seafood produced and is the fastest growing farmed food sector globally. Marine bivalve aquaculture, the farming of oysters, mussels and clams, represents a highly sustainable component of this industry and has major potential for global expansion via increased efficiency, and numbers of, production systems. Artificial spat propagation (i.e. settled juveniles) in hatcheries and selective breeding have the potential to offer rapid and widespread gains for molluscan aquaculture industry. However, bivalves have unique life-histories, genetic and genomic characteristics, which present significant challenges to achieving such genetic improvement. Selection pressures experienced by bivalve larvae and spat in the wild contribute to drive population structure and animal fitness. Similarly, domestication selection is likely to act on hatchery-produced spat, the full implications of which have not been fully explored. In this review, we outline the key features of these taxa and production practices applied in bivalve aquaculture, which have the potential to affect the genetic and phenotypic variability of hatchery-propagated stock. Alongside, we compare artificial and natural processes experienced by bivalves to investigate the possible consequences of hatchery propagation on stock production. In addition, we identify key areas of investigation that need to be prioritized to continue to the advancement of bivalve genetic improvement via selective breeding. The growing accessibility of next-generation sequencing technology and high-powered computational capabilities facilitate the implementation of novel genomic tools in breeding programmes of aquatic species. These emerging techniques represent an exciting opportunity for sustainably expanding the bivalve aquaculture sector.Biotechnology & Biological Sciences Research Council (BBSRC)Natural Environment Research CouncilBiotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research Counci

Evaluating Patient Interest in an Adherence-Focused Smartphone App to Improve HIV Care

Objective: Evaluate patient interest in a smartphone mobile application (app) to assist in medication adherence. Methods: In January 2014, a 19-question, anonymous, paper survey was distributed to a convenience sample of patients in the reception area of a nonprofit HIV primary care clinic and pharmacy. Results: Of the 101 patients surveyed, 72.3% had a smartphone and 70.3% were interested in downloading and using an adherence app if one was available. If an app was customizable, patients desired appointment reminders (87%), notifications to schedule appointments (85%), refill notifications (83%), medication reminders (79%), and adherence tracked by pharmacy (59%). Conclusions: Results share insights on the potential use of technology to assist an HIV patient population with medication adherence. Conflict of Interest Dr. Jennifer Rodis is the creator and director of the Partner For Promotion (PFP) program otherwise she has no additional conflicts of interest or financial interests that the authors or members of their immediate families have in any product or service discussed in the manuscript, including grants (pending or received), employment, gifts, stock holdings or options, honoraria, consultancies, expert testimony, patents and royalties. All other authors declare no conflicts of interest or financial interests that the authors or members of their immediate families have in any product or service discussed in the manuscript, including grants (pending or received), employment, gifts, stock holdings or options, honoraria, consultancies, expert testimony, patents and royalties   Type: Student Projec

py4DSTEM: a software package for multimodal analysis of four-dimensional scanning transmission electron microscopy datasets

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full 2D image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields and other sample-dependent properties. However, extracting this information requires complex analysis pipelines, from data wrangling to calibration to analysis to visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail, and present results from several experimental datasets. We have also implemented a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open source HDF5 standard. We hope this tool will benefit the research community, helps to move the developing standards for data and computational methods in electron microscopy, and invite the community to contribute to this ongoing, fully open-source project