Tissue plasminogen activator dose and pulmonary artery pressure reduction in catheter directed thrombolysis of submassive pulmonary embolism.

PURPOSE:The purpose of this study is to assess the incremental effect of tissue plasminogen activator (t-PA) dose on pulmonary artery pressure (PAP) and bleeding during catheter directed thrombolysis (CDT) of submassive pulmonary embolism (PE). MATERIALS AND METHODS:Records of 46 consecutive patients (25 men, 21 women, mean age 55±14 y) who underwent CDT for submassive PE between September 2009 and February 2017 were retrospectively reviewed. Mean t-PA rate was 0.7±0.3 mg/h. PAP was measured at baseline and daily until CDT termination. Mixed-effects regression modeling was performed of repeated PAP measures in individual patients. Bleeding events were classified by Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries (GUSTO) and t-PA dose at onset. RESULTS:Mean t-PA dose was 43.0±30.0 mg over 61.9± 28.8 h. Mean systolic PAP decreased from 51.7±15.5 mmHg at baseline to 35.6±12.7 mmHg at CDT termination (p<0.001). Mixed-effects regression revealed a linear decrease in systolic PAP over time (β = -0.37 (SE = 0.05), p<0.001) with reduction in mean systolic PAP to 44.8±1.9 mmHg at 12 mg t-PA/20 h, 39.5±2.0 mmHg at 24 mg t-PA/40 h, and 34.9±2.1 mmHg at 36 mg/60 h. No severe, one moderate, and 8 mild bleeding events occurred; bleeding onset was more frequent at ≤24 mg t-PA (p <0.001). One patient expired from cardiopulmonary arrest after 16 h of CDT (15.4 mg t-PA); no additional intra-procedural fatalities occurred. CONCLUSION:Increased total t-PA dose and CDT duration were associated with greater PAP reduction without increased bleeding events

Wind-Modulated Western Maine Coastal Current and Its Connectivity With the Eastern Maine Coastal Current

Using a high-resolution circulation model and an offline particle tracking model, we investigated variations of the Western Maine Coastal Current (WMCC) and its connectivity with the Eastern Maine Coastal Current (EMCC). The models showed that the weak, broad, and sinuous WMCC is generally southwestward with an offshore and a nearshore core, fed by the extension of the EMCC and runoff from the Penobscot and Kennebec–Androscoggin Rivers, respectively. A sea-level dome can form offshore of Casco Bay in late fall and early winter as the northeastward alongshore wind sets up a seaward sea-level gradient from the coast to meet the shoreward sea-level gradient from Wilkinson Basin. Consequently, northeastward flows (i.e., the counter-WMCC) emerge on the inshore side of the dome. Both the circulation and particle tracking models suggested that the connectivity generally peaks twice annually, highest in winter and then secondarily in late spring or early summer. The former is concurrent with the most southwest offshore veering of the EMCC, while the latter is concurrent with the strongest EMCC. Moreover, the counter-WMCC can reduce the connectivity and result in year-to-year variations

Limits on the Optical Brightness of the Epsilon Eridani Dust Ring

The STIS/CCD camera on the {\em Hubble Space Telescope (HST)} was used to take deep optical images near the K2V main-sequence star $\epsilon$ Eridani in an attempt to find an optical counterpart of the dust ring previously imaged by sub-mm observations. Upper limits for the optical brightness of the dust ring are determined and discussed in the context of the scattered starlight expected from plausible dust models. We find that, even if the dust is smoothly distributed in symmetrical rings, the optical surface brightness of the dust, as measured with the {\em HST}/STIS CCD clear aperture at 55 AU from the star, cannot be brighter than about 25 STMAG/"$^2$. This upper limit excludes some solid grain models for the dust ring that can fit the IR and sub-mm data. Magnitudes and positions for $\approx$59 discrete objects between 12.5" to 58" from $\epsilon$ Eri are reported. Most if not all of these objects are likely to be background stars and galaxies.Comment: Revision corrects author lis

Impact of EMA regulatory label changes on systemic diclofenac initiation, discontinuation, and switching to other pain medicines in Scotland, England, Denmark, and The Netherlands

Purpose: In June 2013 a European Medicines Agency referral procedure concluded that diclofenac was associated with an elevated risk of acute cardiovascular events and contraindications, warnings, and changes to the product information were implemented across the European Union. This study measured the impact of the regulatory action on the prescribing of systemic diclofenac in Denmark, The Netherlands, England, and Scotland. Methods: Quarterly time series analyses measuring diclofenac prescription initiation, discontinuation and switching to other systemic nonsteroidal anti-inflammatory (NSAIDs), topical NSAIDs, paracetamol, opioids, and other chronic pain medication in those who discontinued diclofenac. Absolute effects were estimated using interrupted time series regression. Results: Overall, diclofenac prescription initiations fell during the observation periods of all countries. Compared with Denmark where there appeared to be amore limited effect, the regulatory action was associated with significant immediate reductions in diclofenac initiation in The Netherlands (−0.42%, 95% CI, −0.66% to −0.18%), England (−0.09%, 95% CI, −0.11% to −0.08%), and Scotland (−0.67%, 95% CI, −0.79% to −0.55%); and falling trends in diclofenac initiation in the Netherlands (−0.03%, 95% CI, −0.06% to −0.01% per quarter) and Scotland (−0.04%, 95% CI, −0.05% to −0.02% per quarter). There was no significant impact on diclofenac discontinuation in any country. The regulatory action was associated with modest differences in switching to other pain medicines following diclofenac discontinuation. Conclusions: The regulatory action was associated with significant reductions in overall diclofenac initiation which varied by country and type of exposure. There was no impact on discontinuation and variable impact on switching

MGMR: leveraging RNA-Seq population data to optimize expression estimation

<p>Abstract</p> <p>Background</p> <p>RNA-Seq is a technique that uses Next Generation Sequencing to identify transcripts and estimate transcription levels. When applying this technique for quantification, one must contend with reads that align to multiple positions in the genome (multireads). Previous efforts to resolve multireads have shown that RNA-Seq expression estimation can be improved using probabilistic allocation of reads to genes. These methods use a probabilistic generative model for data generation and resolve ambiguity using likelihood-based approaches. In many instances, RNA-seq experiments are performed in the context of a population. The generative models of current methods do not take into account such population information, and it is an open question whether this information can improve quantification of the individual samples</p> <p>Results</p> <p>In order to explore the contribution of population level information in RNA-seq quantification, we apply a hierarchical probabilistic generative model, which assumes that expression levels of different individuals are sampled from a Dirichlet distribution with parameters specific to the population, and reads are sampled from the distribution of expression levels. We introduce an optimization procedure for the estimation of the model parameters, and use HapMap data and simulated data to demonstrate that the model yields a significant improvement in the accuracy of expression levels of paralogous genes.</p> <p>Conclusions</p> <p>We provide a proof of principal of the benefit of drawing on population commonalities to estimate expression. The results of our experiments demonstrate this approach can be beneficial, primarily for estimation at the gene level.</p

Updated resonance photo-decay amplitudes to 2 GeV

We present the results of an energy-dependent and set of single-energy partial-wave analyses of single-pion photoproduction data. These analyses extend from threshold to 2 GeV in the laboratory photon energy, and update our previous analyses to 1.8 GeV. Photo-decay amplitudes are extracted for the baryon resonances within this energy range. We consider two photoproduction sum rules and the contributions of two additional resonance candidates found in our most recent analysis of $\pi N$ elastic scattering data. Comparisons are made with previous analyses.Comment: Revtex, 26 pages, 3 figures. Postscript figures available from ftp://clsaid.phys.vt.edu/pub/pr or indirectly from http://clsaid.phys.vt.edu/~CAPS

The Genome Sequence of the Rumen Methanogen Methanobrevibacter ruminantium Reveals New Possibilities for Controlling Ruminant Methane Emissions

BACKGROUND: Methane (CH(4)) is a potent greenhouse gas (GHG), having a global warming potential 21 times that of carbon dioxide (CO(2)). Methane emissions from agriculture represent around 40% of the emissions produced by human-related activities, the single largest source being enteric fermentation, mainly in ruminant livestock. Technologies to reduce these emissions are lacking. Ruminant methane is formed by the action of methanogenic archaea typified by Methanobrevibacter ruminantium, which is present in ruminants fed a wide variety of diets worldwide. To gain more insight into the lifestyle of a rumen methanogen, and to identify genes and proteins that can be targeted to reduce methane production, we have sequenced the 2.93 Mb genome of M. ruminantium M1, the first rumen methanogen genome to be completed. METHODOLOGY/PRINCIPAL FINDINGS: The M1 genome was sequenced, annotated and subjected to comparative genomic and metabolic pathway analyses. Conserved and methanogen-specific gene sets suitable as targets for vaccine development or chemogenomic-based inhibition of rumen methanogens were identified. The feasibility of using a synthetic peptide-directed vaccinology approach to target epitopes of methanogen surface proteins was demonstrated. A prophage genome was described and its lytic enzyme, endoisopeptidase PeiR, was shown to lyse M1 cells in pure culture. A predicted stimulation of M1 growth by alcohols was demonstrated and microarray analyses indicated up-regulation of methanogenesis genes during co-culture with a hydrogen (H(2)) producing rumen bacterium. We also report the discovery of non-ribosomal peptide synthetases in M. ruminantium M1, the first reported in archaeal species. CONCLUSIONS/SIGNIFICANCE: The M1 genome sequence provides new insights into the lifestyle and cellular processes of this important rumen methanogen. It also defines vaccine and chemogenomic targets for broad inhibition of rumen methanogens and represents a significant contribution to worldwide efforts to mitigate ruminant methane emissions and reduce production of anthropogenic greenhouse gases

Instability in clinical risk stratification models using deep learning

While it has been well known in the ML community that deep learning models suffer from instability, the consequences for healthcare deployments are under characterised. We study the stability of different model architectures trained on electronic health records, using a set of outpatient prediction tasks as a case study. We show that repeated training runs of the same deep learning model on the same training data can result in significantly different outcomes at a patient level even though global performance metrics remain stable. We propose two stability metrics for measuring the effect of randomness of model training, as well as mitigation strategies for improving model stability.Comment: Accepted for publication in Machine Learning for Health (ML4H) 202

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity