What are the most practical primary care screens for post-traumatic stress disorder?

The 4-item Primary Care Post-Traumatic Stress Disorder screen (PC-PTSD) is a simple and effective tool to identify symptoms of post-traumatic stress disorder (PTSD) in primary care patients (strength of recommendation [SOR ]: B, 1 good-quality prospective cohort study and 1 good-quality retrospective cohort study). The 7-item Breslau screen also predictably identifies patients with PTSD symptoms (SOR : B, 1 good-quality prospective cohort study)

Determining anion-quadrupole interactions among protein, DNA, and ligand molecules

Background An extensive search through the Protein Databank (about 4500 nonredundant structures) was previously completed within our lab to analyze the energetic and geometric characteristics of an understudied molecular interaction known as an anion-quadrupole (AQ) interaction. Such an interaction occurs when the positively charged edge of an aromatic ring, resulting from a quadruple moment (i.e., a dual dipole moment), renders the aromatic molecule noncovalently bound to a nearby anionic molecule. The study considered a very limited scenario of molecules that can participate in AQ interactions, consisting of the phenyl group of a phenylalanine (phe) amino acid as the aromatic participant and the carboxylate group of an aspartate (asp) or glutamate (glu) amino acid as the anionic participant. The results revealed anion-quadrupole pairs to be prevalent within most of the protein structures. It was also observed that the interaction energy for AQ pairs was heavily dependent on the angle between the anion and plane of the aromatic ring, favoring a more planar interaction. In light of these critical observations being made from such a limited scenario, only phe-glu and phe-asp pairs and in a reduced sample set of the PDB, we are now continuing this work of identifying AQ interactions using a greatly expanded strategy. We are following these four aims: 1. Optimizing the AQ-search program to run in a semi-parallel fashion and on a large cluster of processors in order to handle larger analyses, 2. Adding to our search additional anionic participants which will include non-protein structures such as DNA and small ligands, 3. Studying a subset of the AQ pairs with molecular dynamics simulations in buried and solvent exposed environments to observe non-static behavioral traits as well as the reproducibility of AQ interactions by force field parameters. 4. Building an online database for public access to our data and search program. Acknowledgments We would like to acknowledge the NSF-IGERT traineeship, Scalable Computing and Leading Edge Innovative Technologies (SCALE-IT), for providing the resources for this project

Persistence and clearance of Ebola virus RNA from seminal fluid of Ebola virus disease survivors: a longitudinal analysis and modelling study

Background By January, 2016, all known transmission chains of the Ebola virus disease (EVD) outbreak in west Africa had been stopped. However, there is concern about persistence of Ebola virus in the reproductive tract of men who have survived EVD. We aimed to use biostatistical modelling to describe the dynamics of Ebola virus RNA load in seminal fl uid, including clearance parameters. Methods In this longitudinal study, we recruited men who had been discharged from three Ebola treatment units in Guinea between January and July, 2015. Participants provided samples of seminal fl uid at follow-up every 3–6 weeks, which we tested for Ebola virus RNA using quantitative real-time RT-PCR. Representative specimens from eight participants were then inoculated into immunodefi cient mice to test for infectivity. We used a linear mixed-eff ect model to analyse the dynamics of virus persistence in seminal fl uid over time. Findings We enrolled 26 participants and tested 130 seminal fl uid specimens; median follow up was 197 days (IQR 187–209 days) after enrolment, which corresponded to 255 days (228–287) after disease onset. Ebola virus RNA was detected in 86 semen specimens from 19 (73%) participants. Median duration of Ebola virus RNA detection was 158 days after onset (73–181; maximum 407 days at end of follow-up). Mathematical modelling of the quantitative time-series data showed a mean clearance rate of Ebola virus RNA from seminal fl uid of –0·58 log units per month, although the clearance kinetic varied greatly between participants. Using our biostatistical model, we predict that 50% and 90% of male survivors clear Ebola virus RNA from seminal fl uid at 115 days (90% prediction interval 72–160) and 294 days (212–399) after disease onset, respectively. We also predicted that the number of men positive for Ebola virus RNA in aff ected countries would decrease from about 50 in January 2016, to fewer than 1 person by July, 2016. Infectious virus was detected in 15 of 26 (58%) specimens tested in mice. Interpretation Time to clearance of Ebola virus RNA from seminal fl uid varies greatly between individuals and could be more than 13 months. Our predictions will assist in decision-making about surveillance and preventive measures in EVD outbreaks

Persistence and clearance of Ebola virus RNA from seminal fluid of Ebola virus disease survivors: a longitudinal analysis and modelling study.

BACKGROUND: By January, 2016, all known transmission chains of the Ebola virus disease (EVD) outbreak in west Africa had been stopped. However, there is concern about persistence of Ebola virus in the reproductive tract of men who have survived EVD. We aimed to use biostatistical modelling to describe the dynamics of Ebola virus RNA load in seminal fluid, including clearance parameters. METHODS: In this longitudinal study, we recruited men who had been discharged from three Ebola treatment units in Guinea between January and July, 2015. Participants provided samples of seminal fluid at follow-up every 3-6 weeks, which we tested for Ebola virus RNA using quantitative real-time RT-PCR. Representative specimens from eight participants were then inoculated into immunodeficient mice to test for infectivity. We used a linear mixed-effect model to analyse the dynamics of virus persistence in seminal fluid over time. FINDINGS: We enrolled 26 participants and tested 130 seminal fluid specimens; median follow up was 197 days (IQR 187-209 days) after enrolment, which corresponded to 255 days (228-287) after disease onset. Ebola virus RNA was detected in 86 semen specimens from 19 (73%) participants. Median duration of Ebola virus RNA detection was 158 days after onset (73-181; maximum 407 days at end of follow-up). Mathematical modelling of the quantitative time-series data showed a mean clearance rate of Ebola virus RNA from seminal fluid of -0·58 log units per month, although the clearance kinetic varied greatly between participants. Using our biostatistical model, we predict that 50% and 90% of male survivors clear Ebola virus RNA from seminal fluid at 115 days (90% prediction interval 72-160) and 294 days (212-399) after disease onset, respectively. We also predicted that the number of men positive for Ebola virus RNA in affected countries would decrease from about 50 in January 2016, to fewer than 1 person by July, 2016. Infectious virus was detected in 15 of 26 (58%) specimens tested in mice. INTERPRETATION: Time to clearance of Ebola virus RNA from seminal fluid varies greatly between individuals and could be more than 13 months. Our predictions will assist in decision-making about surveillance and preventive measures in EVD outbreaks. FUNDING: This study was funded by European Union's Horizon 2020 research and innovation programme, Directorate-General for International Cooperation and Development of the European Commission, Institut national de la santé et de la recherche médicale (INSERM), German Research Foundation (DFG), and Innovative Medicines Initiative 2 Joint Undertaking

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA

Purpose: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. Methods: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Results: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0–1.00) and 85.9% (75.4–92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20–2.92) or receiving a written TLD (HR 2.32, CI 1.11–4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Conclusion: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Total Domination Dot-Stable Graphs

A set S of vertices in a graph G is a total dominating set if every vertex of G is adjacent to some vertex in S. The minimum cardinality of a total dominating set of G is the total domination number of G. Two vertices of G are said to be dotted (identified) if they are combined to form one vertex whose open neighborhood is the union of their neighborhoods minus themselves. We note that dotting any pair of vertices cannot increase the total domination number. Further we show it can decrease the total domination number by at most 2. A graph is total domination dot-stable if dotting any pair of adjacent vertices leaves the total domination number unchanged. We characterize the total domination dot-stable graphs and give a sharp upper bound on their total domination number. We also characterize the graphs attaining this bound

Human corneal keratocyte response to micro-and nano-gratings on chitosan and PDMS

10.1007/s12195-011-0186-7Cellular and Molecular Bioengineering43399-41

Persistence and clearance of Ebola virus RNA from seminal fluid of Ebola virus disease survivors: a longitudinal analysis and modelling study

Summary: Background: By January, 2016, all known transmission chains of the Ebola virus disease (EVD) outbreak in west Africa had been stopped. However, there is concern about persistence of Ebola virus in the reproductive tract of men who have survived EVD. We aimed to use biostatistical modelling to describe the dynamics of Ebola virus RNA load in seminal fluid, including clearance parameters. Methods: In this longitudinal study, we recruited men who had been discharged from three Ebola treatment units in Guinea between January and July, 2015. Participants provided samples of seminal fluid at follow-up every 3–6 weeks, which we tested for Ebola virus RNA using quantitative real-time RT-PCR. Representative specimens from eight participants were then inoculated into immunodeficient mice to test for infectivity. We used a linear mixed-effect model to analyse the dynamics of virus persistence in seminal fluid over time. Findings: We enrolled 26 participants and tested 130 seminal fluid specimens; median follow up was 197 days (IQR 187–209 days) after enrolment, which corresponded to 255 days (228–287) after disease onset. Ebola virus RNA was detected in 86 semen specimens from 19 (73%) participants. Median duration of Ebola virus RNA detection was 158 days after onset (73–181; maximum 407 days at end of follow-up). Mathematical modelling of the quantitative time-series data showed a mean clearance rate of Ebola virus RNA from seminal fluid of −0·58 log units per month, although the clearance kinetic varied greatly between participants. Using our biostatistical model, we predict that 50% and 90% of male survivors clear Ebola virus RNA from seminal fluid at 115 days (90% prediction interval 72–160) and 294 days (212–399) after disease onset, respectively. We also predicted that the number of men positive for Ebola virus RNA in affected countries would decrease from about 50 in January 2016, to fewer than 1 person by July, 2016. Infectious virus was detected in 15 of 26 (58%) specimens tested in mice. Interpretation: Time to clearance of Ebola virus RNA from seminal fluid varies greatly between individuals and could be more than 13 months. Our predictions will assist in decision-making about surveillance and preventive measures in EVD outbreaks. Funding: This study was funded by European Union's Horizon 2020 research and innovation programme, Directorate-General for International Cooperation and Development of the European Commission, Institut national de la santé et de la recherche médicale (INSERM), German Research Foundation (DFG), and Innovative Medicines Initiative 2 Joint Undertaking