, 2010). For instance, while the deletion of Pil1 leads to

clustering of the remaining eisosome components, aberrant plasma membrane invaginations and the reduction of the endocytic rate in yeast (Walther et al., 2006), the deletion of Pil1 homologue in A. oryzea, and A. nidulans had no effect on endocytosis (Higuchi et al., 2009; Vangelatos et al., 2010). In view of the important role of Nce102 in eisosome assembly in yeast and the possible involvement in nonclassical export of PD0332991 nmr some virulence factors to the cell surface (Nombela et al., 2006), we carried out a gene knock out study to understand the role of Nce102 homologue in the growth and pathogenesis of A. fumigatus. We first identified the gene in fungal genome data base, cloned it, and generated a deletion mutant. The intracellular localization of AfuNce102 was also examined using EGFP-tagged AfuNce102. AfuNce102 deletion mutant showed a clear delay in conidiophore formation at 37 °C and severely affected sporulation at 25 °C. Asexual sporulation is a complex process that requires highly coordinated activity of upstream and central developmental pathways. For instance, FluG pathway contains several upstream developmental activators that can activate an overlapping regulatory pathway containing key

conidiation regulators like brlA and wetA (Etxebeste et al., 2010). In examination of brlA expression levels as the central regulator of conidiation, we did not detect any difference between the parental strain and the AfuNce102 deletion mutant indicating that AfuNce102

may not see more influence brlA expression in A. fumigatus. AfuNce102 does not seem to be related to an extracellular sporulation activating factor (s), which is thought to be a product of fluG gene (D’Souza et al., 2001). This was concluded as the conidiation defect of AfuNce102 deletant was not suppressed when the mutant was grown in the vicinity of the wild type. In addition to the main regulatory pathways, several reports have introduced other key players in sporulation process. For example, Soid-Raggi et al. (2006) have identified a transmembrane flavoprotein, Tmpa, which is necessary for conidiophore formation in A. nidulans, and Li et al. (2007) demonstrated the role of normal sphingolipid metabolism in asexual sporulation. Although the deletion of eisosomal Dolutegravir concentration proteins, Pil A, PilB, or SurG, in A. nidulans has not changed the growth phenotype, sporulation, or spore survival (Vangelatos et al., 2010), the deletion of Nce102 homologue in A. fumigatus caused abnormal sporulation. The most severe defect in conidiation was observed at 25 °C. This may indicate an additional function for AfuNCE102 in fungal development. It has been proposed that Nce102 can modulate plasma membrane organization through sphingolipid signaling in yeast. The overexpression of Nce102 in yeast can block the inhibitory effect of a sphingolipid synthesis blocker, myriocin, on eisosomes (Frohlich et al., 2009).

, 2010). For instance, while the deletion of Pil1 leads to

clustering of the remaining eisosome components, aberrant plasma membrane invaginations and the reduction of the endocytic rate in yeast (Walther et al., 2006), the deletion of Pil1 homologue in A. oryzea, and A. nidulans had no effect on endocytosis (Higuchi et al., 2009; Vangelatos et al., 2010). In view of the important role of Nce102 in eisosome assembly in yeast and the possible involvement in nonclassical export of LEE011 supplier some virulence factors to the cell surface (Nombela et al., 2006), we carried out a gene knock out study to understand the role of Nce102 homologue in the growth and pathogenesis of A. fumigatus. We first identified the gene in fungal genome data base, cloned it, and generated a deletion mutant. The intracellular localization of AfuNce102 was also examined using EGFP-tagged AfuNce102. AfuNce102 deletion mutant showed a clear delay in conidiophore formation at 37 °C and severely affected sporulation at 25 °C. Asexual sporulation is a complex process that requires highly coordinated activity of upstream and central developmental pathways. For instance, FluG pathway contains several upstream developmental activators that can activate an overlapping regulatory pathway containing key

conidiation regulators like brlA and wetA (Etxebeste et al., 2010). In examination of brlA expression levels as the central regulator of conidiation, we did not detect any difference between the parental strain and the AfuNce102 deletion mutant indicating that AfuNce102

may not selleck kinase inhibitor influence brlA expression in A. fumigatus. AfuNce102 does not seem to be related to an extracellular sporulation activating factor (s), which is thought to be a product of fluG gene (D’Souza et al., 2001). This was concluded as the conidiation defect of AfuNce102 deletant was not suppressed when the mutant was grown in the vicinity of the wild type. In addition to the main regulatory pathways, several reports have introduced other key players in sporulation process. For example, Soid-Raggi et al. (2006) have identified a transmembrane flavoprotein, Tmpa, which is necessary for conidiophore formation in A. nidulans, and Li et al. (2007) demonstrated the role of normal sphingolipid metabolism in asexual sporulation. Although the deletion of eisosomal MycoClean Mycoplasma Removal Kit proteins, Pil A, PilB, or SurG, in A. nidulans has not changed the growth phenotype, sporulation, or spore survival (Vangelatos et al., 2010), the deletion of Nce102 homologue in A. fumigatus caused abnormal sporulation. The most severe defect in conidiation was observed at 25 °C. This may indicate an additional function for AfuNCE102 in fungal development. It has been proposed that Nce102 can modulate plasma membrane organization through sphingolipid signaling in yeast. The overexpression of Nce102 in yeast can block the inhibitory effect of a sphingolipid synthesis blocker, myriocin, on eisosomes (Frohlich et al., 2009).

, 2010). For instance, while the deletion of Pil1 leads to

clustering of the remaining eisosome components, aberrant plasma membrane invaginations and the reduction of the endocytic rate in yeast (Walther et al., 2006), the deletion of Pil1 homologue in A. oryzea, and A. nidulans had no effect on endocytosis (Higuchi et al., 2009; Vangelatos et al., 2010). In view of the important role of Nce102 in eisosome assembly in yeast and the possible involvement in nonclassical export of Linsitinib manufacturer some virulence factors to the cell surface (Nombela et al., 2006), we carried out a gene knock out study to understand the role of Nce102 homologue in the growth and pathogenesis of A. fumigatus. We first identified the gene in fungal genome data base, cloned it, and generated a deletion mutant. The intracellular localization of AfuNce102 was also examined using EGFP-tagged AfuNce102. AfuNce102 deletion mutant showed a clear delay in conidiophore formation at 37 °C and severely affected sporulation at 25 °C. Asexual sporulation is a complex process that requires highly coordinated activity of upstream and central developmental pathways. For instance, FluG pathway contains several upstream developmental activators that can activate an overlapping regulatory pathway containing key

conidiation regulators like brlA and wetA (Etxebeste et al., 2010). In examination of brlA expression levels as the central regulator of conidiation, we did not detect any difference between the parental strain and the AfuNce102 deletion mutant indicating that AfuNce102

may not CH5424802 manufacturer influence brlA expression in A. fumigatus. AfuNce102 does not seem to be related to an extracellular sporulation activating factor (s), which is thought to be a product of fluG gene (D’Souza et al., 2001). This was concluded as the conidiation defect of AfuNce102 deletant was not suppressed when the mutant was grown in the vicinity of the wild type. In addition to the main regulatory pathways, several reports have introduced other key players in sporulation process. For example, Soid-Raggi et al. (2006) have identified a transmembrane flavoprotein, Tmpa, which is necessary for conidiophore formation in A. nidulans, and Li et al. (2007) demonstrated the role of normal sphingolipid metabolism in asexual sporulation. Although the deletion of eisosomal PDK4 proteins, Pil A, PilB, or SurG, in A. nidulans has not changed the growth phenotype, sporulation, or spore survival (Vangelatos et al., 2010), the deletion of Nce102 homologue in A. fumigatus caused abnormal sporulation. The most severe defect in conidiation was observed at 25 °C. This may indicate an additional function for AfuNCE102 in fungal development. It has been proposed that Nce102 can modulate plasma membrane organization through sphingolipid signaling in yeast. The overexpression of Nce102 in yeast can block the inhibitory effect of a sphingolipid synthesis blocker, myriocin, on eisosomes (Frohlich et al., 2009).

For each AHL, one flask was incubated under standard aerobic conditions. Another flask was incubated with an anaerobic atmosphere by injecting argon for 3 min and adding 10 μM 3-(3,4dichlorophenyl)-1,1-dimethylurea

(DCMU) to inhibit photosynthesis and therefore oxygen (O2) production (Rippka & Stanier, 1978) to avoid a possible inhibition of nitrogenase activity derived from the formation of abnormal heterocyst cell walls during maturation or the damage from other mechanisms responsible for maintaining low O2 concentration within the heterocysts. After 1-h incubation at 30 °C, 2 mL of acetylene was injected. Samples of 1 mL from the air in the sealed flask were taken at different times during 20 h starting 15 min after acetylene injection to determine the concentration of the ethylene produced PLX4032 chemical structure using a GC-MS (HP 5890 series II) equipped with injector, column (Porapak Q) and flame

ionization detector (kept at 100, 80 and 150 °C, respectively). The detected signals were processed with the computing integrator PYE Unicam DP88. The equipment was calibrated with known concentrations of ethylene. To determine the nitrogenase activity of the cultures per unit Chl a, the following formula was used: nitrogenase activity=nmol ethylene in sample × 14 mL/2 ×μg Chl check details a mL−1; where 14 was the atmosphere volume in 17-mL flasks and 2 the volume of culture in the flask. C10-HSL was also added to BG110C cultures of Anabaena sp. PCC7120 with mature heterocysts (24 h after nitrogen step-down) and the nitrogenase

activity then measured as described before. To assess a possible effect of AHLs on the expression of genes involved in nitrogen fixation, Northern hybridization was carried out with probes for the nifH and fdxH genes. Samples of 50 mL were taken at 0, 3, 6, 20 and 24 h after nitrogen step-down. Cells were filtered, washed and resuspended in 1 mL of Tris 50 mM/EDTA 100 mM, centrifuged and the pellet was frozen in liquid nitrogen before RNA extraction. RNA from whole filaments was extracted in Selleckchem Paclitaxel the presence of ribonucleoside–vanadyl complex as described previously (Muro-Pastor et al., 2002). For Northern analysis, 30 μg of RNA was loaded per lane and electrophoresed in 1% agarose denaturing formaldehyde gels. Transfer and fixation to Hybond-N+ membranes (Amersham Biosciences) were carried out using 0.1 M NaOH. Hybridization was performed at 65 °C according to the recommendations of the manufacturer of the membranes. The nifH and fdxH probes were fragments of these genes amplified by PCR. The nifH probe was amplified using plasmid pCSAV60 (containing the nifH gene cloned in pGEM-T vector) as a template and oligonucleotides NH-1 (corresponding to positions −334 to −314 with respect to the translation start of nifH) and NH-4 (complementary to nucleotides +884 to +863 with respect to the translation start of nifH) (Valladares et al., 2007).

, 1993). After ingestion of the crystal toxins by the susceptible larvae, crystalline inclusions are dissolved due to

the alkaline pH of the larval midgut. Then the 51- and 42-kDa protoxins are activated by midgut proteases to form the active proteins, of approximately 43 and 39 kDa, respectively (Broadwell & Baumann, 1987; Nicolas et al., 1990). This is then followed by the binding of the activated binary toxin to a specific receptor presented on the surface of midgut epithelium cells of susceptible larvae (Davidson, 1988; Silva-Filha et al., 1997). The binary toxin receptor has been identified as a 60-kDa α-glucosidase (Cpm1), which is attached to the cell membrane by a glycosyl-phosphatidyl inositol anchor (Silva-Filha et al., 1999; Darboux et learn more al., 2001). Using N- and C-terminal deletion

constructs of both BinA and BinB in in vivo gut binding studies, it has been proposed that the C-terminus of BinA is important for larvicidal toxicity, whereas both N- and C-terminal fragments of BinA are required for interaction with BinB. In addition, it has been proposed that the N-terminus of BinB is crucial for binding to the receptor in gut epithelial cells (Oei et al., 1992). Even though BinB has been shown to play a role in receptor recognition, its binding mechanism is still unknown. Because of the lack of structural information for the binary toxin, selleck compound functional studies have been based mainly on its primary amino acid sequence and Farnesyltransferase secondary structure prediction (Broadwell et al., 1990; Berry et al., 1993; Shanmugavelu et al., 1998; Elangovan et al., 2000; Yuan et al., 2001; Promdonkoy et al., 2008; Sanitt et al., 2008). Interestingly, the amino acid sequences of BinA or BinB are not similar to other bacterial toxins. They

are, however, homologous to each other, with a 25% amino acid identity and a 40% similarity, which suggests a similar 3D structure (Promdonkoy et al., 2008). Despite their homology, the two proteins have distinct functions: BinB is responsible for receptor binding, whereas BinA acts as a toxic component (Oei et al., 1992; Charles et al., 1997; Shanmugavelu et al., 1998; Elangovan et al., 2000). It is thus possible that the different functions of these two proteins are contributed by the nonhomologous segments. For example, an amino acid sequence alignment shows that two regions in BinB are absent in BinA (Fig. 1). These regions are located in the N-terminal part of BinB. It is possible that some amino acids in these regions confer distinct functionality to BinB. To identify these possible functional elements, we have performed amino acid substitutions at residues spanning positions 111–117 and 143–150. Our results demonstrate that the aromaticity of F149 and Y150 plays a crucial role in larvicidal activity, with these residues possibly being involved in interaction with the epithelial membrane and receptor. Escherichia coli K-12 JM109 was used as a host strain for mutagenesis.

coli clones unable to grow into colonies after transformation. In contrast, asRNA clones in which highly expressed genes are being targeted would

be able to grow into colonies and selected during the subsequent phenotypic (+IPTG) screens. This hypothesis is supported by data from DNA array-based E. coli gene expression profiling (Tao et al., 1999). For example, 53 of the 79 essential genes (67%) targeted by asRNA constructs (Table S1) are within the top 10% highly expressed genes among the 4290 ORFs examined when E. coli cells were grown exponentially in LB broth plus glucose (Tao et al., 1999). To increase the diversity of asRNA clones identified, possible technical improvements include replacing Ptrc with a more stringent promoter element on the cloning vector or employing a number of plasmid vectors each containing a promoter with different range of activities (Nakashima et al., 2006; Xu et al., 2010). The recovery of 18 asRNA constructs derived selleck compound from 10 nonessential genes which share operons with essential genes provides strong support for a hypothesis that expressed asRNAs silence gene function in E. coli at Natural Product Library cost the operon level. The mechanism of asRNA inhibition in S. aureus was examined previously by Young and coworkers (Young et al., 2006) who demonstrated that asRNAs exert their inhibition by eliciting degradation of mRNAs upstream (5′) of the regions where the asRNAs bind, which lends support to

our hypothesis. If the hypothesis is confirmed, an asRNA construct or synthetic oligonucleotide could inhibit as many as 11 essential

genes simultaneously on the rplN operon (Fig. 2a), rendering it difficult for multiple resistant mutations to occur in multiple genes. If such multigene mechanism of gene silencing turns out to be prevalent among bacteria, it will facilitate design and development of antisense-based antimicrobial therapeutics which are ‘polypharmaceutical’ (Good & Stach, 2011) or ‘multitargeting’ (Silver, 2007): antibiotics (e.g. most of the successful antibiotics in clinical use) target or interact with two or more bacterial target proteins. In this study, two genomic libraries were constructed successfully and screened for inducible Gemcitabine manufacturer growth inhibitory asRNA clones. The asRNA constructs discovered could knock-down or silence the expression of 79 E. coli essential genes. While the genes being targeted are not yet comprehensive, likely due to a leaky Ptrc promoter of pHN678, this communication represents a first published report to successfully apply regulated asRNA technology to discover E. coli asRNA clones at the genome level. Such conditional asRNA clones will not only stimulate studies of global functions of genes and operons in E. coli but also facilitate discovery and development of novel antimicrobial agents to combat multidrug-resistant pathogens. Funding for this project has been provided by NIH grant SC3GM083686 (to H.H.X.).

By comparison of the Ct differences of the different dilutions, it was verified that the PCR was exponential at least up to the threshold DNA concentration used for the analysis (i.e. a 10-fold dilution corresponds to a Ct difference of about 3.32). The size of the analysis product and the absence of other products were verified using analytical

agarose selleck gel electrophoresis. A standard curve was generated and used to calculate the genome copy numbers present in the dilutions of the cell extract. Together with the known cell densities (see above), this number was used to calculate the genome copy number per cell. At least three independent experiments (biologic replicates) were performed for each species, and average values and standard deviations were calculated. Dialyzed cytoplasmic extracts of Synechocystis Doxorubicin datasheet PCC6803 (see above) were used to record spectra from 220 to 340 nm. The spectra had the typical shapes of nucleic acids spectra and E260/E280 quotients typical for pure nucleic acids. The cell densities (see above) and the absorption at 260 nm were used to calculate the genome copy numbers per cell using the following parameters: absorption of one equals a DNA concentration of 50 μg mL−1, the average molecular mass of one base pair is 660 g mol−1, and the Avogadro number. The best value for the genome size is less clear, the chromosome size is 3.57 Mbp, and the genome size including

plasmids is 3.96 Mbp. The plasmid copy number is unknown and e.g. in Halobacterium salinarum, two plasmids have a copy number of five, whereas the genome has a copy number of 25 (Breuert et al., 2006). To take the unknown plasmid copy numbers into account, genome sizes of 3.96 Mbp (high plasmid copy number) and 3.65 Mbp (low plasmid copy number) were used to calculate the ploidy level of the chromosome. It should be noted that in highly polyploid species, the absorbance of RNA Ixazomib supplier is much lower than that of genomic DNA and can be neglected. A short calculation should demonstrate this point: E. coli cells growing with a doubling time of 100 min. contain about 7000 ribosomes

per cell (Bremer & Dennis, 1996). If the same number is assumed for Synechocystis with a much longer doubling time, the cells would contain 3.2 × 107 nt ribosomal RNA, which makes up nearly 90% of cellular RNA. Fifty copies of a genome of 3.6 Mbp are equal to 3.6 × 108 nt. Therefore, under these conditions, DNA outnumbers RNA by more than a factor of 10. The real time PCR method for the quantification of genome copy numbers had been established for haloarchaea (Breuert et al., 2006), but, in the meantime, was also applied to methanogenic archaea and proteobacteria (Hildenbrand et al., 2011; Pecoraro et al., 2011). It has been validated against several independent methods, i.e. quantitative Southern blotting (Breuert et al., 2006), DNA isolation, and spectroscopic quantification (Hildenbrand et al., 2011), and the wealth of results published for E.

By comparison of the Ct differences of the different dilutions, it was verified that the PCR was exponential at least up to the threshold DNA concentration used for the analysis (i.e. a 10-fold dilution corresponds to a Ct difference of about 3.32). The size of the analysis product and the absence of other products were verified using analytical

agarose R788 gel electrophoresis. A standard curve was generated and used to calculate the genome copy numbers present in the dilutions of the cell extract. Together with the known cell densities (see above), this number was used to calculate the genome copy number per cell. At least three independent experiments (biologic replicates) were performed for each species, and average values and standard deviations were calculated. Dialyzed cytoplasmic extracts of Synechocystis Vismodegib clinical trial PCC6803 (see above) were used to record spectra from 220 to 340 nm. The spectra had the typical shapes of nucleic acids spectra and E260/E280 quotients typical for pure nucleic acids. The cell densities (see above) and the absorption at 260 nm were used to calculate the genome copy numbers per cell using the following parameters: absorption of one equals a DNA concentration of 50 μg mL−1, the average molecular mass of one base pair is 660 g mol−1, and the Avogadro number. The best value for the genome size is less clear, the chromosome size is 3.57 Mbp, and the genome size including

plasmids is 3.96 Mbp. The plasmid copy number is unknown and e.g. in Halobacterium salinarum, two plasmids have a copy number of five, whereas the genome has a copy number of 25 (Breuert et al., 2006). To take the unknown plasmid copy numbers into account, genome sizes of 3.96 Mbp (high plasmid copy number) and 3.65 Mbp (low plasmid copy number) were used to calculate the ploidy level of the chromosome. It should be noted that in highly polyploid species, the absorbance of RNA Buspirone HCl is much lower than that of genomic DNA and can be neglected. A short calculation should demonstrate this point: E. coli cells growing with a doubling time of 100 min. contain about 7000 ribosomes

per cell (Bremer & Dennis, 1996). If the same number is assumed for Synechocystis with a much longer doubling time, the cells would contain 3.2 × 107 nt ribosomal RNA, which makes up nearly 90% of cellular RNA. Fifty copies of a genome of 3.6 Mbp are equal to 3.6 × 108 nt. Therefore, under these conditions, DNA outnumbers RNA by more than a factor of 10. The real time PCR method for the quantification of genome copy numbers had been established for haloarchaea (Breuert et al., 2006), but, in the meantime, was also applied to methanogenic archaea and proteobacteria (Hildenbrand et al., 2011; Pecoraro et al., 2011). It has been validated against several independent methods, i.e. quantitative Southern blotting (Breuert et al., 2006), DNA isolation, and spectroscopic quantification (Hildenbrand et al., 2011), and the wealth of results published for E.

These short-chain carbon molecules have also been reported to have inhibitory properties against S. cerevisiae and C. albicans (Bergsson et al., 2001; Kubo et al., 2003). The size of the chain length is clearly an important factor, which was confirmed in studies of the activity of 40 isomers of farnesol, which concluded that subtle changes in the structure of farnesol can have dramatic effects on the activity against C. albicans (Shchepin et al., 2003). At the molecular level, it is likely that these molecules act to influence key transcription factors, leading

to hyphal repression. Both farnesol and dodecanol were shown to affect the cAMP-controlled Ras1-Cdc35 pathway, which is integral to filamentation (Davis-Hanna et al., 2008). Genome analysis of Aspergillus species indicates that JQ1 order cAMP signalling is conserved, thus indicating that these small 10 carbon molecules may play a pivotal role in fungal population control (Lafon et al., 2006). Moreover, recent transcriptional studies to examine the effects of P. MLN8237 manufacturer aeruginosa supernatant on C. albicans biofilm formation demonstrated that 236 genes were differentially

regulated, and interestingly, genes involved in adhesion and biofilm formation were downregulated, in particular YHP1, which encodes a protein known to inhibit biofilm formation (Holcombe et al., 2010). The suppression of other microbial pathogens via the secretion Rutecarpine of small molecules may play a pivotal role in microbial competition. Within the environment of the CF lung, bacteria and fungi

exist within close proximity, and given that bacterial quorum-sensing molecules have been identified directly from sputum samples of CF patients, it is plausible that complex microbial interactions are modulated through small defined chemical messengers to allow different bacteria and cross-kingdom interactions to take place that impact microbial pathogenicity (Singh et al., 2000; Shirtliff et al., 2009). Investigation of P. aeruginosa clinical isolates from CF patients has shown that the genetic diversity of quorum-sensing networks is common, with 19 out of 30 CF patients reported to contain lasR mutants (Smith et al., 2006). This indicates that P. aeruginosa may evolve within the complex microbial environment to allow its coexistence with eukaryotes, which is supported by data from a recent study describing mutual inhibition (Bandara et al., 2010b). Interesting observations from the same group showed that exogenous lipopolysaccharide was able to inhibit and disrupt Candida spp. biofilms in a time- and concentration-dependent manner (Bandara et al., 2010a). Collectively, the data demonstrate that P. aeruginosa has the ability to modulate C. albicans behaviour in a number of ways, and under certain circumstances, it can mutually coexist.

3% of patients (95% CI = 43.5 – 83.7%) (19 medications) with at least one moderately severe discrepancy and 45.5% of patients (95% CI = 24.6 – 66.3%) (10 medications) with a minor discrepancy. The results shows that discrepancies occur between the hospital discharge prescription and the patient’s further supply of medication as reported by the parent. The results indicate that 36.8% of patients experienced discrepancies post hospital discharge which is higher HDAC inhibitor than the 14.1% of post discharge discrepancies experienced in older adults aged 65 from an adult study[2]. The results indicate that 7.6% of

patients (95% CI = 1.1% – 16.0%) who are discharged will experience an unintended moderately severe medication discrepancy post discharge. 1. Dean BD, Barber N. A validated reliable method of scoring the severity of medication

errors. click here American Journal of Health-System Pharmacists. 1999; 56: 57–62. 2. Coleman EA, Smith JD, Raha D, Min S-J. Post hospital medication discrepancies. Prevalence and contributing factors. Archives of internal medicine. 2005; 165: 1842–1847. Rowan Yemm1, Debi Bhattacharya1, David Wright1, Anne Regan2, David Green2, Lorna Hollister2 1University of East Anglia, Norwich, Norfolk, UK, 2Colchester Hospital University NHS Foundation Trust, Colchester, Essex, UK In recent guidance, RPS emphasises the importance of communicating medication changes at discharge Charts were amended to allow better annotation of changes, which it was hoped would translate onto Electronic Discharge summaries (EDS) Whilst changes on charts increased from 51.7% to 62.8%, no improvement was seen on EDS or the general practitioner’s (GP) list after discharge More work is needed to establish how, if not from charts, doctors source information for preparing EDS. In 2011, RPS published guidance to support the transfer of care1, which emphasises the importance of communicating changes in medication across the interface. Colchester hospital volunteered as an early adopter, participating in a 6-month programme to assess the effect of amending inpatient medication charts PIK3C2G to include additional fields for annotating medication changes. This

study aimed to investigate the effect of these amendments on the annotation of new medicines, dose changes and discontinuations on charts, and whether this improves the quality of information provided on EDS, and GP-held information after discharge. Data were collected over 7-day periods in November 2011 (pre implementation), March and May (2 & 4 months post implementation) from 2 medical wards purposively selected for high patient turnover. Charts and EDS for patients discharged from study wards during data collection were reviewed. Researchers identified where medication changes had occurred, and whether these were annotated in new chart fields and explicitly stated on EDS. Fisher’s exact test was used to compare proportions. Short-term changes (e.g.