No information was available for contacts of the remaining 18 students. Those who were reported by students to have developed influenza-like symptoms a few days after the students arrived home were asked to provide diagnostic samples. Four contacts of three confirmed cases reported ILI and all were tested. Only one of these contacts tested positive

for influenza A(H1N1). Thus, the secondary attack rate was 0.5% (1/188) for confirmed influenza and 2.1% (4/188) for probable influenza. Of the 188 contacts, 137 were contacts of students with symptoms, and 4 (2.9%) of these reported illness. The 39 students with www.selleckchem.com/products/dinaciclib-sch727965.html confirmed influenza had 98 contacts so, for this group, the secondary attack rate for confirmed influenza was 1% (1/98), and the secondary attack rate for probable influenza was 4% (4/98). All patients seen were advised about preventive measures to avoid further transmission: the use of masks, home isolation, and hand washing. No student received prophylaxis or antiviral find more treatment with oseltamivir, as all had mild illness

and none had underlying diseases or risk factors for severe illness. The symptoms resolved without specific treatment after a mean of 4–5 days. All confirmed and probable cases recovered satisfactorily and none required hospitalization. Only seven students had been vaccinated with the seasonal influenza vaccine before the

trip, of whom four developed laboratory-confirmed A(H1N1) 2009 pandemic influenza. Figure 3 shows the aircraft seats occupied by ID-8 the 113 students on the return flight from the Dominican Republic. Students who became ill were seated throughout the aircraft with no apparent clustering. We were not able to obtain information on illness among other passengers who shared the return flight. The viral nucleotide sequences obtained from infected students were indistinguishable from sequences of viruses in GenBank from the Dominican Republic. However, the sequences were also indistinguishable from other viral sequences identified in Spain. We describe here a high primary attack rate of pandemic A(H1N1) influenza among a group of medical students who traveled to the Dominican Republic during a period of epidemic influenza transmission, followed by a low secondary attack rate among household contacts after the students’ return to Spain. The relatively mild clinical presentation of pandemic A(H1N1) influenza in this group of students is consistent with previously described outbreaks.6 However, we found a higher frequency of gastrointestinal symptoms than reported in previous studies in cases of influenza,6,13 but the high percentage of gastrointestinal symptoms in students with (64%) and without (43.2%) ILI suggests the possible coexistence of travelers’ diarrhea in this group.

SdrF, a surface protein, appears to play a critical role in the initial colonization step by adhering to type I collagen and Dacron™. The role of ionic interactions in S. epidermidis adherence to prosthetic material was examined. SdrF was cloned and expressed in Lactococcus lactis. The effect of pH, cation concentration, and detergents on adherence to different types RGFP966 clinical trial of plastic surfaces was assessed by crystal

violet staining and bacterial cell counting. SdrF, in contrast with controls and other S. epidermidis surface proteins, bound to hydrophobic materials such as polystyrene. Binding was an ionic interaction and was affected by surface charge of the plastic, pH, and cation concentration. Adherence of the SdrF construct was increased to positively charged plastics and

was reduced by increasing concentrations of Ca2+ and Na+. Binding was optimal at pH 7.4. Kinetic studies demonstrated that the SdrF B domain as well as one of the B subdomains was sufficient to mediate binding. The SdrF construct also bound more avidly to Goretex™ than the lacotococcal control. SdrF is a multifunctional protein that contributes to prosthetic devices infections by ionic, as well as specific receptor–ligand interactions. Infections are among the most common complications of prosthetic device implantation (Baddour et al., 2003; Gandelman et al., 2007; Wang et al., 2007). The capacity of bacteria to adhere to these devices through both specific and nonspecific interactions is a critical first step in the initiation of these infections (Broekhuizen mTOR inhibitor et al., 2006; Tsapikouni et al., 2008; Otto, 2009). This problem is enhanced when the infection involves devices such as ventricular assist devices that are critical to patient survival (Rose et al., 2001). Infections L-gulonolactone oxidase involving these devices occur in 15–30% of patients and generally

require either device removal or transplantation to affect a cure (Herrmann et al., 1997; Holman et al., 1997; Gordon et al., 2006) [INTERMACS (http://www.intermacs.org)]. Staphylococcus epidermidis remains the most common cause of prosthetic device-related infections (Simon et al., 2005; Gordon et al., 2006). As part of the commensal skin flora, staphylococci are uniquely situated to contaminate wounds when cutaneous barriers are breached. Surface proteins known as microbial surface components recognizing adhesive matrix molecules facilitate the initial colonization step (Patti et al., 1994; MacKintosh et al., 2006; Otto, 2009). SdrF, a S. epidermidis surface protein, appears to contribute to the initiation of prosthetic device infections. Previous studies showed that SdrF, a member of the serine–aspartate (SD) family of surface proteins, binds type I collagen and mediates adhesion of S. epidermidis to the ventricular assisted device (VAD) driveline (Bowden et al., 2005; Arrecubieta et al., 2007, 2009).

SdrF, a surface protein, appears to play a critical role in the initial colonization step by adhering to type I collagen and Dacron™. The role of ionic interactions in S. epidermidis adherence to prosthetic material was examined. SdrF was cloned and expressed in Lactococcus lactis. The effect of pH, cation concentration, and detergents on adherence to different types PF-02341066 manufacturer of plastic surfaces was assessed by crystal

violet staining and bacterial cell counting. SdrF, in contrast with controls and other S. epidermidis surface proteins, bound to hydrophobic materials such as polystyrene. Binding was an ionic interaction and was affected by surface charge of the plastic, pH, and cation concentration. Adherence of the SdrF construct was increased to positively charged plastics and

was reduced by increasing concentrations of Ca2+ and Na+. Binding was optimal at pH 7.4. Kinetic studies demonstrated that the SdrF B domain as well as one of the B subdomains was sufficient to mediate binding. The SdrF construct also bound more avidly to Goretex™ than the lacotococcal control. SdrF is a multifunctional protein that contributes to prosthetic devices infections by ionic, as well as specific receptor–ligand interactions. Infections are among the most common complications of prosthetic device implantation (Baddour et al., 2003; Gandelman et al., 2007; Wang et al., 2007). The capacity of bacteria to adhere to these devices through both specific and nonspecific interactions is a critical first step in the initiation of these infections (Broekhuizen Quizartinib in vitro et al., 2006; Tsapikouni et al., 2008; Otto, 2009). This problem is enhanced when the infection involves devices such as ventricular assist devices that are critical to patient survival (Rose et al., 2001). Infections Immune system involving these devices occur in 15–30% of patients and generally

require either device removal or transplantation to affect a cure (Herrmann et al., 1997; Holman et al., 1997; Gordon et al., 2006) [INTERMACS (http://www.intermacs.org)]. Staphylococcus epidermidis remains the most common cause of prosthetic device-related infections (Simon et al., 2005; Gordon et al., 2006). As part of the commensal skin flora, staphylococci are uniquely situated to contaminate wounds when cutaneous barriers are breached. Surface proteins known as microbial surface components recognizing adhesive matrix molecules facilitate the initial colonization step (Patti et al., 1994; MacKintosh et al., 2006; Otto, 2009). SdrF, a S. epidermidis surface protein, appears to contribute to the initiation of prosthetic device infections. Previous studies showed that SdrF, a member of the serine–aspartate (SD) family of surface proteins, binds type I collagen and mediates adhesion of S. epidermidis to the ventricular assisted device (VAD) driveline (Bowden et al., 2005; Arrecubieta et al., 2007, 2009).

The different capsular polymers in Escherichia coli are divided in four groups (1–4) according to serological, genetic and biochemical criteria (Whitfield, 2006). A few E. coli strains express CPSs belonging to group 2 that contain

polysialic acid (PA). These PAs have been shown to be bacterial pathogenic determinants (Reglero et al., 1993; Rick & Silver, 1996). Other polysaccharides have been described in E. coli that are involved in cellular attachment and biofilm formation. These include colanic acid (CA) (Prigent-Combaret et al., 2000; Whitfield, 2006), which is not usually produced in significant amounts at physiological temperatures (up GS-1101 molecular weight to 30 °C), and provides protection against extreme environmental conditions (Whitfield, 2006). Escherichia coli K92 produces PA as a capsular polymer (Gotschlich et al., 1981; González-Clemente et al., 1990). We have recently observed that it is also able to synthesize CA (Navasa et al., 2009). Moreover, this bacterium reciprocally thermoregulates the formation of both PA and CA. Thus, when E. coli K92 is grown in defined media at 37 °C it produces predominantly PA but at lower temperatures

(below 20 °C) it is not detectable selleck (González-Clemente et al., 1990), whereas synthesis of CA is maximal (Navasa et al., 2009). The chromosomal locus for PA synthesis Telomerase (designated kps) has a conserved structure comprising three regions (Fig. 1a) (Whitfield, 2006). Transcription of the kps locus is driven by two convergent temperature-regulated promoters located upstream of regions 1 (PR1) and 3 (PR3) (Cieslewicz & Vimr, 1996; Stevens et al., 1997). This thermoregulation is a defining feature of group 2 capsules, and although a detailed understanding of the process is not yet available, current information points to a complex and multifactorial system (Rowe et al., 2000). Escherichia coli K92 is

also capable of degrading sialic acid and, similar to E. coli K1 (Rodríguez-aparicio et al., 1987; Vimr et al., 2004), the catabolism genes are included in the chromosomal locus, the nan system (Fig. 1b). The genes encoding the enzymes responsible for the production and transport of CA are clustered in large operons that are largely identical to the group 1 capsule locus (Whitfield & Paiment, 2003). In E. coli, the CPS synthesis gene cluster is termed the wca/cps operon (Fig. 1c). The regulatory system that controls transcription of the CA biosynthesis locus can be activated by growth at lower temperatures (below 30 °C) or under stress conditions (Sledjeski & Gottesman, 1996) and its expression is regulated by a complex signal transduction pathway called the Rcs system (Majdalani & Gottesman, 2005). As yet, E.

“
“The objective of this study was to evaluate the use of an audience response

system (i.e. clickers) as an engaging tool for learning and examine its potential for enhancing continuing education (CE) activities. Attendees at a symposium were invited to utilise and evaluate the use of clickers. Electronic data relating to participant demographics and feedback were collected using clickers during the symposium. The 60 attendees who used the clickers were mostly pharmacists (76%) who worked in hospital pharmacy practice (86%). Attendees strongly agreed or agreed that clickers were easy to use (94%), enhanced interaction (98%), allowed comparison of knowledge with PF-562271 clinical trial that of their peers (78%), brought to attention their knowledge deficits (64%) and should be used again (94%). The innovative use of clickers at the symposium was

very well received by all attendees and offered a number of benefits, including the ability to provide a more engaging and interactive CE activity. “
“To establish a consensual and coherent ranking of healthcare programmes that involve the presence of ward-based and clinic-based clinical pharmacists, based on health outcome, health costs and safe delivery of care. This descriptive study was derived from a structured dialogue (Delphi technique) among directors of pharmacy department. We established a quantitative profile of healthcare programmes Masitinib (AB1010) at five sites that involved the provision of ward-based and clinic-based pharmaceutical care. A summary table of evidence established a unique

Daporinad quality rating per inpatient (clinic-based) or outpatient (ward-based) healthcare programme. Each director rated the perceived impact of pharmaceutical care per inpatient or outpatient healthcare programme on three fields: health outcome, health costs and safe delivery of care. They agreed by consensus on the final ranking of healthcare programmes. A ranking was assigned for each of the 18 healthcare programmes for outpatient care and the 17 healthcare programmes for inpatient care involving the presence of pharmacists, based on health outcome, health costs and safe delivery of care. There was a good correlation between ranking based on data from a 2007–2008 Canadian report on hospital pharmacy practice and the ranking proposed by directors of pharmacy department. Given the often limited human and financial resources, managers should consider the best evidence available on a profession’s impact to plan healthcare services within an organization. Data are few on ranking healthcare programmes in order to prioritize which healthcare programme would mostly benefit from the delivery of pharmaceutical care by ward-based and clinic-based pharmacists.

Pharmacy practice research can benefit from research that uses both ‘numbers’ (quantitative) and ‘words’ (qualitative) to develop a strong evidence base to support pharmacy-led services. In the first article of the pair we introduced the basic concepts of mixed-methods R428 clinical trial research including its definition, advantages and typologies. In this second article the rationale, applications, limitations and challenges of conducting a mixed-methods study are discussed. A framework to improve quality of reporting mixed-methods studies is also proposed for researchers and

reviewers. Not all research problems require mixed-methods enquiry and therefore the rationale for choosing a mixed-methods approach should always be presented. A literature review by MK-1775 manufacturer Greene et al. in 1989 identified five reasons for conducting mixed-methods research including triangulation, complementarity, development, initiation and expansion

(explained below).[1] In 2006, in a review of social science literature, Bryman expanded the list and identified 16 reasons for conducting mixed-methods research.[2] To date the use of mixed-methods research in pharmacy practice is relatively limited. To illustrate this point, a quick Medline and EMBASE search combining the keywords ‘mixed-methods’ or ‘multi-methods’ with ‘pharmacy’ or ‘Pharmacist’ resulted only in 33 hits (after deduplication; date of search 2 April 2012). However, it should be noted here that it was not a comprehensive search to locate all mixed-methods studies but rather it aimed to identify examples and highlight the limited use of mixed-methods research in the field of pharmacy practice. In this section we will explore some examples of how pharmacy practice researchers have used mixed methods together with a discussion of the strengths and weaknesses of the reporting within each study. We have purposively selected these examples to illustrate the five reasons

identified by Greene et al.[1] for using a mixed-methods approach. Triangulation Fenbendazole seeks convergence, corroboration and correspondence of results from different methods’.[1] Guirguis used a mixed-methods approach (concurrent triangulation) to study pharmacists’ experiences and beliefs about an interactive communication approach, the three prime questions (3PQs) model.[3] Developed in the USA, 3PQs is a patient-centred model designed to assess the patient’s knowledge and recognize information deficits before providing education. The quantitative methods included pharmacist self-report forms to record their experiences using the 3PQs and a 19-item questionnaire survey (16 closed and three open-ended questions) for evaluating pharmacist self-efficacy and role beliefs towards 3PQs. The qualitative method included a focus-group interview to elaborate on the pharmacists’ experience using 3PQs.

Based

on duplicate screening of titles and abstracts from the various literature searches, we retrieved 163 full-text articles. Twenty-one articles were included in the review (see Figure 2). The excluded articles were primarily reviews or descriptions of a CDSS without formal evaluation, interventions that did not target pharmacists or interventions that did Rucaparib order not reach methodological adequacy (i.e. they did not have a comparison group) The key features of the 21 studies (setting, participants, interventions and study outcomes) are shown in Table 3.[16–36] Ten studies focused on guidelines and other treatment recommendations (QUM interventions) and 11 targeted drug safety (critical drug interactions, drugs in pregnancy and the elderly, monitoring treatment or dose adjustments). All but one study was conducted in North America; 13 were conducted in ambulatory care, and eight in institutional care (hospital inpatients). Sixteen interventions focused on pharmacists exclusively and five

also included physicians and/or other health care professionals such as nurses or nurse practitioners (see Table 4[16–36]). Eight studies utilised Small molecule library cost system-initiated decision support, four utilised user-initiated decision support, six used a mixture of system and user-initiated support (‘mixed’); and in three studies the method of invoking the CDSS was unclear. Prescribing outcomes were reported in the majority of studies (n= 16), clinical outcomes in nine studies, and patient outcomes in five studies. Two studies reported outcomes in all three domains. Three studies reported pharmacist activity measures as outcomes. The interventions in eight of the studies consisted of CDSS only, while the 13 remaining studies were classified as multi-faceted, with pharmacists receiving additional training, lectures, written guidelines and/or support materials

in addition to the 17-DMAG (Alvespimycin) HCl decision support itself. Cardiovascular disease management was the most common clinical focus (n= 6). Other clinical areas included anticoagulant therapy (n= 3), antibiotic prescribing (n= 2) and respiratory conditions such as asthma and chronic obstructive pulmonary disease (COPD; n= 2). Sixteen of the 21 trials were RCTs, four were non-randomised studies with concurrent or historical control groups and one used an interrupted time-series design. Of the 16 RCTs, seven were randomised by cluster (ward, team, unit, pharmacy), three by pharmacist, four by physician and 12 by patient (randomisation occurred at several levels in some studies). Fourteen studies reported no baseline differences between study groups or made the appropriate statistical adjustments to account for baseline differences. With the exception of one of the pharmacist activity measures, all other outcomes reported were based on objective measures (e.g. derived from prescribing or dispensing database), subjective measures but with assessment blind to the intervention group allocation (e.g.

Similarly, SC glucose sensors which have become part of some integrated CSII systems rely on the difference between SC glucose and BG being proportional to the rate of change taking

place in BG;9 this time lag limits the sensitivity of continuous glucose monitors to detect hypoglycaemia; algorithms can be produced to mitigate this where there are sufficient data from sequential readings to give the BG/time gradient. Intraperitoneal insulin infusion offers a more physiological route for insulin delivery Panobinostat cost devices, producing greater porto-systemic and hepatic insulin gradients, and controls hepatic glucose metabolism more efficiently. Recent research10,11 in our laboratory has focused on producing an implantable insulin delivery device (INSmart) which would deliver insulin to the peritoneum in an automated fashion linked to changing glucose levels (Figures 1a and b). INSmart delivers insulin via a glucose-sensitive gel which acts as

both a sensor see more and controller of the amount of insulin released (Figure 1c). The glucose-sensitive gel comprises polymerised derivatives of dextran and a glucose-sensitive lectin, concanavalin A. The highly viscous gel that forms due to the equilibrium binding between the dextran and the lectin binding sites impedes insulin release. This changes in the presence of glucose as the binding sites are disrupted resulting in a reduction in the viscosity of the gel that facilitates insulin very release. This process is both reversible and repeatable, being sensitive to the changes in glucose levels that occur in the peritoneal cavity. The gel layer is therefore both the sensor and the delivery port in this design and contains no electronics or moving parts. The benefits of an INSmart device for the treatment of diabetes are that it could provide automated control preventing hypoglycaemia and also the long-term harm from hyperglycaemia. However,

the associated risks from an implantable device could arise from surgery, leakage of the insulin reservoir and infection. A prototype design was used to demonstrate the feasibility of this novel approach by restoring normoglycaemia in diabetic rats12 and pigs13 for up to five weeks but would require some redesign to provide it with biocompatibility, reliability and security to be optimal for clinical use. In designing a clinically-testable prototype it is important to understand the needs of the market, i.e. potential users, and to assess their reaction to it. To gain these insights it was decided to conduct a survey of current users of CSII. We surveyed CSII users to determine their current approach to glucose management and their appreciation of its importance, and to understand the practical difficulties of achieving desired control with their current pump therapy.

Previous diagnoses of cancer, surgery (including trauma and fracture) and pregnancy were included only in the analysis for overall VTE (the latter two as time-dependent variables). Diagnoses of cancer, diabetes mellitus, myocardial infarction, heart failure, stroke, psychiatric diseases (as a surrogate for the use of neuroleptic drugs) and obesity,

as well Cell Cycle inhibitor as surgery and pregnancy, were extracted from the DNHR. We first assessed the impact of HIV infection on the risk of being diagnosed with VTE, both overall and separately for unprovoked and provoked thrombotic episodes. Because both HIV infection and VTE may be strongly associated with IDU, all analyses were stratified by IDU. Time was computed from index date until date of VTE, death, emigration, loss to follow-up or 1 January 2008, whichever came first. We used a cumulative incidence function to illustrate time to first VTE, recognizing death as a competing risk.

We calculated the incidence rates (IRs) and 95% confidence intervals (CIs) for VTE. We used time-updated Cox regression Fludarabine solubility dmso analysis to compute incidence rate ratios (IRRs) as estimates of the relative risk for VTE in the non-IDU and the IDU groups compared with the general population cohort. To examine the combined impact of immunodeficiency (CD4 count<200 cells/μL) and HAART on the risk of VTE in the HIV-infected group, we used time-dependent Cox regression analysis to compute IRRs. In the latter analysis the IRR was compared with an observed time when the HIV-infected patients were not on HAART and had a CD4 count>200 cells/μL. In all models, we controlled for gender, age at index date (categorized in five age intervals: 0–15, 16–30, 31–45, 46–60, and Montelukast Sodium 60+years) and calendar year (categorized in four time intervals: 1995–1997, 1998–2000, 2001–2003, and 2004–2007) as well as diabetes, myocardial infarction, heart failure, stroke, psychiatric diagnoses and obesity. Statistical analyses were performed using sas version 9.1 (SAS

Institute, Cary, NC, USA). The study was approved by the Danish Data Protection Agency. We identified 4333 HIV-infected patients and 43 330 individuals in the general population cohort. The median age on the index date was 36.6 years and 76.6% were male. IDU was reported as the mode of infection in 482 HIV-infected patients (11.1%). Additional characteristics of IDU and non-IDU HIV-infected patients and population cohort individuals are provided in Table 1. During the study period we observed 148 (3.4%) first episodes of VTE in the HIV-infected group, of which 56 (37.8%) occurred in the IDU group (83.9% unprovoked) and 92 (62.2%) occurred in the non-IDU group (73.9% unprovoked). In comparison, 371 (0.9%) episodes of VTE occurred in the population control cohort (79.2% unprovoked). The median age at diagnosis of VTE in the non-IDU group [46.4 years; interquartile range (IQR) 36.5–55.

These microorganisms were isolated and identified as fungal endophytes and tested for their performance to compete against R. solani using in vitro dual culture assays. We tested the ability of antagonistic fungal isolates to excrete volatile substances and evaluated the effect of filtrates of liquid cultures of all fungal isolates on the mycelial growth of R. solani. Finally, we evaluated the antagonism under greenhouse conditions. Rhizoctonia solani R14 and Phomopsis sp. R24 strains were isolated from infected potato plants from a field in August 2007 in Montreal region (Canada). Fungal endophytes (E1, E2 E8, E13, and E18) were

isolated from the leaves ALK inhibitor of Norway maples in October 2007 in Montreal based on the methods described by Berg et al. (2005). These endophytes were evaluated for antagonism against R. solani. Fungal strains were identified by PCR and sequencing of internal transcribed spacer (ITS) regions of rDNA. Mycelia, grown in liquid potato dextrose broth at 25 °C, were harvested by filtration and used to extract DNA using the plant DNA extraction kit (Qiagen, Canada). PCR was performed using primers ITS1 and ITS4 to amplify ITS regions of seven isolates (R14, R44, E1, E2, E8, E13, and E18)

(Tables 1 and 2). Amplification reactions were carried out in a volume of 50 μL using the Dream Taq kit (Fermentas, Ulixertinib concentration Canada) according to the manufacture’s recommendations. PCR was performed using a Mastercycler (Eppendorf, Canada) following the programme: 5 min at 94 °C, followed by 29 cycles of 30 s at 94 °C, 30 s at 59 °C HSP90 and 1 min at 72 °C, and 7 min at 72 °C. PCR amplicons were sequenced at the Genome Quebec Innovation Center (Montreal, Canada). Sequences were blasted using the nucleotide blast search at NCBI. Sequences were deposited in EMBL under

accession numbers FN646616–FN646622. Morphological observations such as colony growth, colour, type of mycelia, size, and form arrangement of conidia were used to confirm molecular data (Alexopoulos et al., 1996). Fungal isolates were screened for their ability to suppress the mycelial growth of R. solani strain R14 by in vitro dual culture assays on potato dextrose agar (PDA) (Lahlali et al., 2007). Each combination of pathogen/antagonist was replicated 10 times and plates were randomly placed in the dark and incubated at 25 °C until the PDA medium was completely covered with pathogen mycelia. As negative controls, 10 Petri dishes were inoculated only with an R. solani agar disc and a water agar disc. The radial mycelial growth of R. solani towards the antagonistic fungus (Ri) and that on a control plate (Rc) were measured and the mycelial growth inhibition was calculated according to the formula: (Rc−Ri)/Rc × 100. Statistical analyses were performed with anova using the sas statistical package (SAS Institute, Cary, NC). When the effect was found to be significant, the LSD was performed for mean separation at P≤0.05.