Bone mineral density measurement and osteoporosis treatment after a fragility fracture in older adults: regional variation and determinants of use in Quebec

BACKGROUND: Osteoporosis (OP) is a skeletal disorder characterized by reduced bone strength and predisposition to increased risk of fracture, with consequent increased risk of morbidity and mortality. It is therefore an important public health problem. International and Canadian associations have issued clinical guidelines for the diagnosis and treatment of OP. In this study, we identified potential predictors of bone mineral density (BMD) testing and OP treatment, which include place of residence. METHODS: Our study was a retrospective population-based cohort study using data from the Quebec Health Insurance Board. The studied population consisted of all individuals 65 years and older for whom a physician claimed a consultation for a low velocity vertebral, hip, wrist, or humerus fracture in 1999 and 2000. Individuals were considered to have undergone BMD testing if there was a claim for such a procedure within two years following a fracture. They were considered to have received an OP treatment if there was at least one claim to Quebec's health insurance plan (RAMQ) for OP treatment within one year following a fracture. We performed descriptive analyses and logistic regressions by gender. Predictors included age, site of fracture, social status, comorbidity index, prior BMD testing, prior OP treatment, long-term glucocorticoid use, and physical distance to BMD device. RESULTS: The cohort, 77% of which was female, consisted of 25,852 individuals with fragility fractures. BMD testing and OP treatment rates were low and gender dependent (BMD: men 4.6%; women 13.1%; OP treatment: men 9.9%; women 29.7%). There was an obvious regional variation, particularly in BMD testing, ranging from 0 to 16%. Logistic regressions demonstrate that individuals living in long term care facilities received less BMD testing. Patients who had suffered from vertebral fractures, or who had received prior OP treatment or BMD testing, regardless of gender, subsequently received more BMD testing and OP treatments. Furthermore, increasing the distance between a patient's residence and BMD facility precluded likelihood of BMD testing. CONCLUSION: BMD testing rate was extremely low but not completely explained by reduced physical access; gender, age, social status, prior BMD testing and OP treatment were all important predictors for future BMD testing and OP treatment

The processing and impact of dissolved riverine nitrogen in the Arctic Ocean

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Estuaries and Coasts 35 (2012): 401-415, doi:10.1007/s12237-011-9417-3.Although the Arctic Ocean is the most riverine-influenced of all of the world’s oceans, the importance of terrigenous nutrients in this environment is poorly understood. This study couples estimates of circumpolar riverine nutrient fluxes from the PARTNERS (Pan-Arctic River Transport of Nutrients, Organic Matter, and Suspended Sediments) Project with a regionally configured version of the MIT general circulation model to develop estimates of the distribution and availability of dissolved riverine N in the Arctic Ocean, assess its importance for primary production, and compare these estimates to potential bacterial production fueled by riverine C. Because riverine dissolved organic nitrogen is remineralized slowly, riverine N is available for uptake well into the open ocean. Despite this, we estimate that even when recycling is considered, riverine N may support 0.5–1.5 Tmol C year−1 of primary production, a small proportion of total Arctic Ocean photosynthesis. Rapid uptake of dissolved inorganic nitrogen coupled with relatively high rates of dissolved organic nitrogen regeneration in N-limited nearshore regions, however, leads to potential localized rates of riverine-supported photosynthesis that represent a substantial proportion of nearshore production.Funding for this work was provided through NSFOPP- 0229302 and NSF-OPP-0732985.Support to SET was additionally provided by an NSERC Postdoctoral Fellowship

Family physicians\u27 professional identity formation: a study protocol to explore impression management processes in institutional academic contexts.

BACKGROUND: Despite significant differences in terms of medical training and health care context, the phenomenon of medical students\u27 declining interest in family medicine has been well documented in North America and in many other developed countries as well. As part of a research program on family physicians\u27 professional identity formation initiated in 2007, the purpose of the present investigation is to examine in-depth how family physicians construct their professional image in academic contexts; in other words, this study will allow us to identify and understand the processes whereby family physicians with an academic appointment seek to control the ideas others form about them as a professional group, i.e. impression management. METHODS/DESIGN: The methodology consists of a multiple case study embedded in the perspective of institutional theory. Four international cases from Canada, France, Ireland and Spain will be conducted; the \u22case\u22 is the medical school. Four levels of analysis will be considered: individual family physicians, interpersonal relationships, family physician professional group, and organization (medical school). Individual interviews and focus groups with academic family physicians will constitute the main technique for data generation, which will be complemented with a variety of documentary sources. Discourse techniques, more particularly rhetorical analysis, will be used to analyze the data gathered. Within- and cross-case analysis will then be performed. DISCUSSION: This empirical study is strongly grounded in theory and will contribute to the scant body of literature on family physicians\u27 professional identity formation processes in medical schools. Findings will potentially have important implications for the practice of family medicine, medical education and health and educational policies

Application of the bacteriophage Mu-driven system for the integration/amplification of target genes in the chromosomes of engineered Gram-negative bacteria—mini review

The advantages of phage Mu transposition-based systems for the chromosomal editing of plasmid-less strains are reviewed. The cis and trans requirements for Mu phage-mediated transposition, which include the L/R ends of the Mu DNA, the transposition factors MuA and MuB, and the cis/trans functioning of the E element as an enhancer, are presented. Mini-Mu(LR)/(LER) units are Mu derivatives that lack most of the Mu genes but contain the L/R ends or a properly arranged E element in cis to the L/R ends. The dual-component system, which consists of an integrative plasmid with a mini-Mu and an easily eliminated helper plasmid encoding inducible transposition factors, is described in detail as a tool for the integration/amplification of recombinant DNAs. This chromosomal editing method is based on replicative transposition through the formation of a cointegrate that can be resolved in a recombination-dependent manner. (E-plus)- or (E-minus)-helpers that differ in the presence of the trans-acting E element are used to achieve the proper mini-Mu transposition intensity. The systems that have been developed for the construction of stably maintained mini-Mu multi-integrant strains of Escherichia coli and Methylophilus methylotrophus are described. A novel integration/amplification/fixation strategy is proposed for consecutive independent replicative transpositions of different mini-Mu(LER) units with “excisable” E elements in methylotrophic cells

Singlet extensions of the standard model at LHC Run 2: benchmarks and comparison with the NMSSM

The Complex singlet extension of the Standard Model (CxSM) is the simplest extension that provides scenarios for Higgs pair production with different masses. The model has two interesting phases: the dark matter phase, with a Standard Model-like Higgs boson, a new scalar and a dark matter candidate; and the broken phase, with all three neutral scalars mixing. In the latter phase Higgs decays into a pair of two different Higgs bosons are possible. In this study we analyse Higgs-to-Higgs decays in the framework of singlet extensions of the Standard Model (SM), with focus on the CxSM. After demonstrating that scenarios with large rates for such chain decays are possible we perform a comparison between the NMSSM and the CxSM. We find that, based on Higgs-to-Higgs decays, the only possibility to distinguish the two models at the LHC run 2 is through final states with two different scalars. This conclusion builds a strong case for searches for final states with two different scalars at the LHC run 2. Finally, we propose a set of benchmark points for the real and complex singlet extensions to be tested at the LHC run 2. They have been chosen such that the discovery prospects of the involved scalars are maximised and they fulfil the dark matter constraints. Furthermore, for some of the points the theory is stable up to high energy scales. For the computation of the decay widths and branching ratios we developed the Fortran code sHDECAY, which is based on the implementation of the real and complex singlet extensions of the SM in HDECAY

Using machine learning to identify important predictors of COVID-19 infection prevention behaviors during the early phase of the pandemic

Before vaccines for coronavirus disease 2019 (COVID-19) became available, a set of infection-prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine-learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection-prevention behavior in 56,072 participants across 28 countries, administered in March to May 2020. The machine-learning model predicted 52% of the variance in infection-prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual-level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically derived predictors were relatively unimportant