Metformin and cardiorenal outcomes in diabetes : a reappraisal

The guidance issued to the pharmaceutical industry by the US Food and Drug Administration in 2008 has led to the publication of a series of randomised, controlled cardiovascular outcomes trials with newer therapeutic classes of glucose‐lowering medications. Several of these trials, which evaluated the newer therapeutic classes of SGLT2 inhibitors and GLP‐1 receptor agonists have reported a reduced incidence of major adverse cardiovascular and/or renal outcomes, usually relative to placebo and standard of care. Metformin was the first glucose‐lowering agent reported to improve cardiovascular outcomes in the UK Prospective diabetes Study (UKPDS) and thus became the foundation of standard care. However, as this clinical trial reported more than 20 years ago, differences from current standards of trial design and evaluation complicate comparison of the cardiovascular profiles of older and newer agents. Our article revisits the evidence for cardiovascular protection with metformin and reviews its effects on the kidney.Publisher PDFPeer reviewe

Bed-load effects on hydrodynamics of rough-bed open-channel flows

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Stretched exponential behavior and random walks on diluted hypercubic lattices

Diffusion on a diluted hypercube has been proposed as a model for glassy relaxation and is an example of the more general class of stochastic processes on graphs. In this article we determine numerically through large scale simulations the eigenvalue spectra for this stochastic process and calculate explicitly the time evolution for the autocorrelation function and for the return probability, all at criticality, with hypercube dimensions $N$ up to N=28. We show that at long times both relaxation functions can be described by stretched exponentials with exponent 1/3 and a characteristic relaxation time which grows exponentially with dimension $N$. The numerical eigenvalue spectra are consistent with analytic predictions for a generic sparse network model.Comment: 16 pages, 7 figure

Evaluating implicit feedback models using searcher simulations

In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simulations. Since these algorithms select additional terms for query modification based on inferences made from searcher interaction, not on relevance information searchers explicitly provide (as in traditional RF), we refer to them as implicit feedback models. We introduce six different models that base their decisions on the interactions of searchers and use different approaches to rank query modification terms. The aim of this article is to determine which of these models should be used to assist searchers in the systems we develop. To evaluate these models we used searcher simulations that afforded us more control over the experimental conditions than experiments with human subjects and allowed complex interaction to be modeled without the need for costly human experimentation. The simulation-based evaluation methodology measures how well the models learn the distribution of terms across relevant documents (i.e., learn what information is relevant) and how well they improve search effectiveness (i.e., create effective search queries). Our findings show that an implicit feedback model based on Jeffrey's rule of conditioning outperformed other models under investigation

Using mobile phones in pub talk

We present the findings from a study of how people interleave mobile phone use with conversation in pubs. Our findings, informed by ethnomethodology and conversation analysis, unpack the interactional methods through which groups of people in pubs occasioned, sustained, and disengaged from mobile device use during conversation with friends. Fundamentally, the work that is done consists of various methods of accounting for mobile device use, and displaying involvement in social interaction while the device is used. We highlight multiple examples of the nuanced ways in which interleaving is problematic in interaction, and relate our findings to the CSCW and HCI literature on collocated interaction. We conclude by considering avenues for future research, and discuss how we may support or disrupt interleaving practices through design to overcome the highlighted interactional troubles

Localization and Functional Characterization of the Alternative Oxidase in Naegleria

The Alternative oxidase (AOX) is a protein involved in maintaining the Krebs cycle in instances where the respiratory chain has been inhibited, while allowing for the maintenance of cell growth and necessary metabolic processes for survival. Among eukaryotes, alternative oxidases have disperse distribution and are found in plants, fungi and a few protists, including Naegleria ssp. Naegleria species are free-living unicellular amoeboflagellates, and include the pathogenic species of N. fowleri, the so-called brain eating amoeba. Using a multidisciplinary approach, we aimed to understand the evolution, localization and function of AOX and the role that plays in Naegleria’s biology. Our analyses suggest that the protein was present in last common ancestor of the genus and structure prediction showed that all functional residues are also present in Naegleria species. Using a combination of cellular and biochemical techniques, we also functionally characterize N. gruberi’s AOX in its mitochondria and we demonstrate that its inactivation affects its proliferation. Consequently, we discuss the benefits of the presence of this protein in Naegleria species, along with its potential pathogenicity role in N. fowleri. We predict that our findings will spearhead new explorations to understand the cell biology, metabolism and evolution of Naegleria and other free-living relatives

Risk algorithm using serial biomarker measurements doubles the number of screen-detected cancers compared with a single-threshold rule in the United Kingdom collaborative trial of ovarian cancer screening

PURPOSE: Cancer screening strategies have commonly adopted single-biomarker thresholds to identify abnormality. We investigated the impact of serial biomarker change interpreted through a risk algorithm on cancer detection rates. PATIENTS AND METHODS: In the United Kingdom Collaborative Trial of Ovarian Cancer Screening, 46,237 women, age 50 years or older underwent incidence screening by using the multimodal strategy (MMS) in which annual serum cancer antigen 125 (CA-125) was interpreted with the risk of ovarian cancer algorithm (ROCA). Women were triaged by the ROCA: normal risk, returned to annual screening; intermediate risk, repeat CA-125; and elevated risk, repeat CA-125 and transvaginal ultrasound. Women with persistently increased risk were clinically evaluated. All participants were followed through national cancer and/or death registries. Performance characteristics of a single-threshold rule and the ROCA were compared by using receiver operating characteristic curves. RESULTS: After 296,911 women-years of annual incidence screening, 640 women underwent surgery. Of those, 133 had primary invasive epithelial ovarian or tubal cancers (iEOCs). In all, 22 interval iEOCs occurred within 1 year of screening, of which one was detected by ROCA but was managed conservatively after clinical assessment. The sensitivity and specificity of MMS for detection of iEOCs were 85.8% (95% CI, 79.3% to 90.9%) and 99.8% (95% CI, 99.8% to 99.8%), respectively, with 4.8 surgeries per iEOC. ROCA alone detected 87.1% (135 of 155) of the iEOCs. Using fixed CA-125 cutoffs at the last annual screen of more than 35, more than 30, and more than 22 U/mL would have identified 41.3% (64 of 155), 48.4% (75 of 155), and 66.5% (103 of 155), respectively. The area under the curve for ROCA (0.915) was significantly (P = .0027) higher than that for a single-threshold rule (0.869). CONCLUSION: Screening by using ROCA doubled the number of screen-detected iEOCs compared with a fixed cutoff. In the context of cancer screening, reliance on predefined single-threshold rules may result in biomarkers of value being discarded

Assessing a New Clue to How Much Carbon Plants Take Up

Current climate models disagree on how much carbon dioxide land ecosystems take up for photosynthesis. Tracking the stronger carbonyl sulfide signal could help