To analyze the activity and specificity of the different OM cytoc

To analyze the activity and specificity of the different OM cytochromes, we compared electron transfer to metals

and an anode surface. The reduction of an anode is as surface limited as the Verteporfin purchase reduction of an insoluble metal. However, anode reduction experiments can provide an additional set of information due to the possibility to change the rate of electron abstraction from the anode surface and thus the potential. The reduction experiments conducted showed that MtrCstrep and MtrFstrep could partly rescue the ΔOMC phenotype, while the production of other OM cytochromes resulted only in minor effects, if at all. A central role of MtrC in metal reduction is in agreement with earlier results (Beliaev et al., 2001; Myers & Myers, 2001) and might reflect the recently discovered capability of a complex of MtrC, with the β-barrel protein MtrB and the decaheme cytochrome MtrA, to

transport electrons over a liposome membrane and hence most probably also over the OM of S. oneidensis cells (Hartshorne et al., 2009). mtrF is part of a gene cluster that includes with mtrD and mtrE genes that are highly Fluorouracil cost similar to mtrA and mtrB (McLean et al., 2008). We could show that MtrFstrep is a functional reductase that has, under several conditions, an even accelerated activity compared with MtrCstrep. McLean et al. (2008) speculate that the mtrDEF gene cluster could encode a reductase that is active under oxic or suboxic conditions and might have a function in Selleckchem Palbociclib reduction-based detoxification of radionuclides. The experiments presented here underline at least that MtrF is a reductase that could have this hypothetical function. The relative reduction activities of MtrFstrep compared with MtrCstrep follow the same pattern for all electron acceptors, except for an electrode in an MFC. Here, the LCD of MtrFstrep-producing cells is only 46% compared with the LCD achieved with MtrCstrep-producing cells. Therefore, we hypothesize that MtrFstrep might be not as well connected to the periplasmic electron pool, which could be due to

a reduced capability of forming a complex with MtrA and MtrB. This interprotein electron transfer might not be rate limiting under mineral-reducing conditions, but could become important when a certain current is applied to the MFC. OmcA production did not lead to accelerated reduction rates compared with the ΔOMC mutant in ferric iron reduction assays. This effect does not seem to be due to the reported partial mislocalization of OmcA in a ΔmtrC mutant (Myers & Myers, 2001) since proteinase K assays clearly demonstrated the surface exposure of OmcA in the ΔOMC mutant. OmcA is part of the core proteins that can be found in ferric iron-reducing S. oneidensis cells (Shi et al., 2007). We hypothesize that OmcA is an in vivo ferric iron reductase that is dependent on electron transport by another OM cytochrome. This cytochrome would most probably be MtrC.

In this study, the mutant JX22MT1 was obtained by the EZ-Tn5 tran

In this study, the mutant JX22MT1 was obtained by the EZ-Tn5 transposon mutation and showed no antifungal activity against Fusarium oxysporum f. sp. lycopersici as compared with wild-type strain JX22.

The pqqC gene was disrupted in the mutant. Antifungal activity at the wild-type level was restored from the mutant JX22MT1 with the introduction of the functional pqqC gene, which encodes pyrroloquinoline–quinone synthesis protein C. The results suggest that pqqC is essential for antifungal activity of P. kilonensis JX22 against F. oxysporum f. sp. lycopersici. “
“Consumption HSP inhibitor of Vibrio parahaemolyticus via contaminated shellfish results in inflammatory gastroenteritis characterised by severe diarrhoea, nausea and stomach cramps. This study investigated

the translocation of V. parahaemolyticus across a Peyer’s patch M cell-like Caco-2/Raji B co-culture model system, as M cells represent a primary site of infection for many pathogenic bacteria. Vibrio parahaemolyticus translocated across co-culture monolayers in higher numbers as compared to Caco-2 monolayers. Moreover, the bacteria induced a greater disruption of the transepithelial resistance in M cell-like co-cultures than in Caco-2 monocultures. Virulence factors associated with this pathogen include two type three secretion systems (TTSS-1 and BIBW2992 TTSS-2). TTSS-1 had no effect on translocation efficiency, with TTSS-2 exhibiting a modest enhancing effect. ERK activity was required for optimal translocation 1 h postinfection, however,

neither ERK nor the JNK and p38 MAPK were required at 2 h pi. Additionally, TER disruption in response to bacterial infection occurred independently of the TTSS and MAPK activation. It was concluded that V. parahaemolyticus causes TER disruption of M cell-like co-cultures and translocates in high numbers across the M cell-like co-culture monolayer. These data implicate M cells as important sites for V. parahaemolyticus invasion across the intestinal epithelium during infection. The human gastrointestinal pathogen Farnesyltransferase Vibrio parahaemolyticus is a Gram-negative bacterium whose natural habitat is marine and estuarine sediment (Daniels et al., 2000; Makino et al., 2003). Infection is characterised by severe gastroenteritis following consumption of contaminated, uncooked shellfish. Infection of the host epithelium by V. parahaemolyticus is associated with the presence of two haemolysins and two type three secretion systems, namely TTSS-1 and TTSS-2. While TTSS-1 is involved in the cytotoxic effects of the bacterium, TTSS-2 is responsible for bacterial enterotoxicity (Park et al., 2004a, b). The intestinal monolayer is an important defensive barrier following the consumption of contaminated seafood (Catalioto et al., 2011).

Analysis on travelers with German origin has not shown any signif

Analysis on travelers with German origin has not shown any significant correlation between type of travel and acquired infectious disease; also there was no significant correlation found between the type of travel “visiting friends and relatives” and destination or the risk to acquire a certain infectious disease. Among 48 travelers of African see more origin, almost all (47: 98%) traveled to Africa and

acquired infectious diseases which are highly endemic there, such as malaria (5 cases), schistosomiasis (6 cases), and diarrheal diseases (23 cases). The correlation between African origin and these infectious diseases was highly confounded by travel destination. For travelers with other origins, sample size was low and no correlation with any infectious disease was found. Among the very young travelers of age 0 to

4 years, the duration of travel was significantly longer than that for travelers of age 5 to 19 years. This result was caused by the fact that almost half of the parents with children of age 0 to 4 years stayed abroad for visiting friends and relatives. In the age group 0 to 4 years, the risk for diarrhea, especially acute diarrhea, E7080 cost was higher than in the age group 5 to 14 years, as shown in other studies.21,22 Among the travelers of age 5 to 9 years, the risk for acquiring schistosomiasis was significantly higher than that for travelers of the other age groups. This result is caused by the fact that more travelers in that age group stayed in Africa, where schistosomiasis is highly endemic in many regions. In this study, the following trends depending on the age of young travelers were found. With decreasing age, there was an increasing duration

of travel, increasing number of travelers visiting friends and relatives abroad, mafosfamide and increasing risk for acquiring acute diarrhea and dermatologic disorders during travel. Furthermore, with increasing age, there was an increasing number of backpackers (as teenagers prefer traveling by backpacking) and increasing risk for acquiring mononucleosis (as teenagers have an elevated risk mainly caused by kissing) abroad. Besides mononucleosis, dengue fever and malaria were the most frequently detected febrile/systemic diseases, whereas the majority of dengue fever cases were imported by young travelers from Asia (especially in age group 10–14 y) and the majority of malaria cases from sub-Saharan Africa with steady pattern of distribution among the age groups.23 Dermatologic disorders were mainly caused by insect bites and cutaneous larva migrans, which are diseases that can be prevented by some simple precaution.24,25 However, the number of causes for dermatologic disorders was large and an elevated risk for travelers <10 years.

22 Hepatitis B) Proportion of patients with CD4 cell count <350

2.2 Hepatitis B). Proportion of patients with CD4 cell count <350 cells/μL not on ART. Proportion of patients with CD4 find more cell count >350 cells/μL and

an indication to start ART not on ART. To date there have been no published randomized trials that directly assess whether treatment-naïve people with higher CD4 cell counts should initiate ART immediately rather than defer until the CD4 cell count falls to ≤350 cells/μL; while the START trial is addressing this question, results are not expected until 2015. Only one trial [1] has randomized people with a CD4 cell count >350 cells/μL, but this used a comparator arm of delay of initiation of ARVs until the CD4 cell count has fallen below 250 cells/μL, and thus is likely to overestimate the apparent

benefits of immediate treatment compared with starting at <350 cells/μL. There have been a number of observational studies that have attempted to address this issue [2-9], which have produced conflicting findings. Some of these studies have failed to take into account the lead time between an individual's CD4 cell count falling below the threshold for treatment and the date of starting treatment [8]; as this may introduce serious bias into treatment comparisons, these results do not resolve the question whether it is better to start ART at higher CD4 cell counts. Where studies have used methods that take lead time into account, the statistical methods used are novel and different approaches Alectinib molecular weight have been used. The analyses reached substantially different

conclusions on the mortality benefits of early ART initiation in people with a CD4 cell count >350 cells/μL, and particularly in those with CD4 cell count >500 cells/μL. Critically, none of these methods is able fully to adjust for potential confounding, which might well be large in this scenario and could Etomidate create a bias that is in the same direction in all studies. Thus, we do not believe that the evidence is currently sufficiently strong to recommend a change in guidelines. We recommend patients presenting with an AIDS-defining infection, or with a serious bacterial infection and a CD4 cell count <200 cells/μL, start ART within 2 weeks of initiation of specific antimicrobial chemotherapy (1B). Proportion of patients presenting with an AIDS-defining infection or with a serious bacterial infection and a CD4 cell count <200 cells/μL started on ART within 2 weeks of initiation of specific antimicrobial chemotherapy. This recommendation is largely based on the ACTG 5164 study that demonstrated fewer AIDS progressions/deaths and improved cost-effectiveness when ART was commenced within 14 days (median 12 days; IQR 9–13 days) compared with after completion of treatment for the acute infection (median 45 days; IQR 41–55 days) [1, 2].

22 Hepatitis B) Proportion of patients with CD4 cell count <350

2.2 Hepatitis B). Proportion of patients with CD4 cell count <350 cells/μL not on ART. Proportion of patients with CD4 Proteasome inhibitor cell count >350 cells/μL and

an indication to start ART not on ART. To date there have been no published randomized trials that directly assess whether treatment-naïve people with higher CD4 cell counts should initiate ART immediately rather than defer until the CD4 cell count falls to ≤350 cells/μL; while the START trial is addressing this question, results are not expected until 2015. Only one trial [1] has randomized people with a CD4 cell count >350 cells/μL, but this used a comparator arm of delay of initiation of ARVs until the CD4 cell count has fallen below 250 cells/μL, and thus is likely to overestimate the apparent

benefits of immediate treatment compared with starting at <350 cells/μL. There have been a number of observational studies that have attempted to address this issue [2-9], which have produced conflicting findings. Some of these studies have failed to take into account the lead time between an individual's CD4 cell count falling below the threshold for treatment and the date of starting treatment [8]; as this may introduce serious bias into treatment comparisons, these results do not resolve the question whether it is better to start ART at higher CD4 cell counts. Where studies have used methods that take lead time into account, the statistical methods used are novel and different approaches selleck compound have been used. The analyses reached substantially different

conclusions on the mortality benefits of early ART initiation in people with a CD4 cell count >350 cells/μL, and particularly in those with CD4 cell count >500 cells/μL. Critically, none of these methods is able fully to adjust for potential confounding, which might well be large in this scenario and could Ketotifen create a bias that is in the same direction in all studies. Thus, we do not believe that the evidence is currently sufficiently strong to recommend a change in guidelines. We recommend patients presenting with an AIDS-defining infection, or with a serious bacterial infection and a CD4 cell count <200 cells/μL, start ART within 2 weeks of initiation of specific antimicrobial chemotherapy (1B). Proportion of patients presenting with an AIDS-defining infection or with a serious bacterial infection and a CD4 cell count <200 cells/μL started on ART within 2 weeks of initiation of specific antimicrobial chemotherapy. This recommendation is largely based on the ACTG 5164 study that demonstrated fewer AIDS progressions/deaths and improved cost-effectiveness when ART was commenced within 14 days (median 12 days; IQR 9–13 days) compared with after completion of treatment for the acute infection (median 45 days; IQR 41–55 days) [1, 2].

coli ArgDC mutant in an acid shock assay

coli ArgDC mutant in an acid shock assay. click here Active AaxB was detected in four additional species: Chlamydia caviae, Chlamydia pecorum, Chlamydia psittaci, and Chlamydia muridarum. Of the C. trachomatis

serovars, only E appears to encode active enzyme. To determine when functional enzyme is present during the chlamydial developmental cycle, we utilized an anti-AaxB antibody to detect both uncleaved and cleaved enzyme throughout infection. Uncleaved enzyme production peaked around 20 h postinfection, with optimal cleavage around 44 h. While the role ArgDC plays in Chlamydia survival or virulence is unclear, our data suggest a niche-specific function. Infection with Chlamydia, a genus of Gram-negative obligate intracellular

bacteria, may result in ocular, genital, or pneumonic disease, depending on the route of entry and bacterial species/serovar. While the majority of Chlamydia species are zoonotic, infecting a wide range of mammalian and avian hosts, the Chlamydia trachomatis serovars are human-specific pathogens (Carlson et al., 2005; Rohde et al., 2010). All species undergo a unique biphasic developmental cycle transitioning between the extracellular, infectious elementary body (EB) and the intracellular, replicative form known as the reticulate body (RB; AbdelRahman & Belland, 2005). Arginine decarboxylases CHIR-99021 order (ArgDCs), which catalyze the conversion of arginine into agmatine, are conserved in bacteria and play dual roles in acid resistance and the metabolism of polyamines such as putrescine (Tabor & Tabor, 1984; Lin et al., 1995). In bacteria such as Yersinia, functional ArgDC is required to produce biofilms, making this enzyme essential for virulence (Patel et al., 2006). Two ArgDC are encoded by Escherichia coli: the acid-inducible adiA and a constitutive speA that functions in polyamine biosynthesis (Stim & Bennett, 1993). In Chlamydia, the only known ArgDC is encoded by aaxB, which resides in an operon between the putative porin aaxA and the characterized arginine–agmatine antiporter, aaxC (Giles & Graham,

2007; Fig. 1a). Although AaxB is either functionally equivalent to E. coli AdiA, the enzyme itself is actually a member of the pyruvoyl-dependent ArgDC (PvlArgDC) and shares more similarities with ArgDC from organisms such as Methanococcus jannaschii (Graham et al., 2002). The AaxB proteins of Chlamydia pneumoniae and C. trachomatis serovars D and L2 were previously characterized (Giles & Graham, 2007; Giles et al., 2009). All sequenced C. pneumoniae encode a 25 kDa proenzyme, which requires autocleavage between the conserved Thr52Ser53residues to produce 16 kDa α and 9 kDa β subunits. The cleaved subunits are then free to assemble into the active (αβ)3 complex. In contrast, C. trachomatis serovars D and L2 have inactivated AaxB through one of two independent mutations (Giles et al., 2009).

coli ArgDC mutant in an acid shock assay

coli ArgDC mutant in an acid shock assay. selleck inhibitor Active AaxB was detected in four additional species: Chlamydia caviae, Chlamydia pecorum, Chlamydia psittaci, and Chlamydia muridarum. Of the C. trachomatis

serovars, only E appears to encode active enzyme. To determine when functional enzyme is present during the chlamydial developmental cycle, we utilized an anti-AaxB antibody to detect both uncleaved and cleaved enzyme throughout infection. Uncleaved enzyme production peaked around 20 h postinfection, with optimal cleavage around 44 h. While the role ArgDC plays in Chlamydia survival or virulence is unclear, our data suggest a niche-specific function. Infection with Chlamydia, a genus of Gram-negative obligate intracellular

bacteria, may result in ocular, genital, or pneumonic disease, depending on the route of entry and bacterial species/serovar. While the majority of Chlamydia species are zoonotic, infecting a wide range of mammalian and avian hosts, the Chlamydia trachomatis serovars are human-specific pathogens (Carlson et al., 2005; Rohde et al., 2010). All species undergo a unique biphasic developmental cycle transitioning between the extracellular, infectious elementary body (EB) and the intracellular, replicative form known as the reticulate body (RB; AbdelRahman & Belland, 2005). Arginine decarboxylases Vorinostat order (ArgDCs), which catalyze the conversion of arginine into agmatine, are conserved in bacteria and play dual roles in acid resistance and the metabolism of polyamines such as putrescine (Tabor & Tabor, 1984; Lin et al., 1995). In bacteria such as Yersinia, functional ArgDC is required to produce biofilms, making this enzyme essential for virulence (Patel et al., 2006). Two ArgDC are encoded by Escherichia coli: the acid-inducible adiA and a constitutive speA that functions in polyamine biosynthesis (Stim & Bennett, 1993). In Chlamydia, the only known ArgDC is encoded by aaxB, which resides in an operon between the putative porin aaxA and the characterized arginine–agmatine antiporter, aaxC (Giles & Graham,

2007; Fig. 1a). Although AaxB is Thymidine kinase functionally equivalent to E. coli AdiA, the enzyme itself is actually a member of the pyruvoyl-dependent ArgDC (PvlArgDC) and shares more similarities with ArgDC from organisms such as Methanococcus jannaschii (Graham et al., 2002). The AaxB proteins of Chlamydia pneumoniae and C. trachomatis serovars D and L2 were previously characterized (Giles & Graham, 2007; Giles et al., 2009). All sequenced C. pneumoniae encode a 25 kDa proenzyme, which requires autocleavage between the conserved Thr52Ser53residues to produce 16 kDa α and 9 kDa β subunits. The cleaved subunits are then free to assemble into the active (αβ)3 complex. In contrast, C. trachomatis serovars D and L2 have inactivated AaxB through one of two independent mutations (Giles et al., 2009).

This subgroup analysis showed similar unadjusted and adjusted odd

This subgroup analysis showed similar unadjusted and adjusted odds ratios

for maternal cART and CD4 cell count, indicating little confounding by other maternal risk factors. Odds ratios for smoking were also substantial. Results of this analysis did not reach statistical significance, probably because of the limited sample size available for this analysis. Nevertheless, these findings correspond to the results of other evaluations (time trend analysis and analysis 1) in the present study, rendering coincidental results of analysis 4 quite unlikely. We were unable to adjust for the effect of drinking habits as this information was recorded only recently in the SHCS database. Other socioeconomic and obstetric factors identified and summarized in the literature [10] were also not selleck chemical available or outside the focus of our BIBW2992 in vitro analysis. Given the high inclusion rates of the SHCS [6], the time trend analysis and our multivariate analysis (analysis

4) are representative for HIV-1-infected pregnant women living in Switzerland. In concordance with our data, the initial confirmation of an increased prematurity rate associated with ART during pregnancy by Thorne et al. [2] has consistently been supported by additional analyses reported by the ECS. In their most recent analysis of 2326 mother–child pairs, Hanking et al. [11] reported an overall prematurity rate of 17% and a significant association of antenatal ART exposure with prematurity in univariable and multivariable analyses

adjusting for maternal CD4 cell count, IDU and maternal age. Women receiving a protease inhibitor (PI)-sparing cART regimen were nearly three times more likely to deliver prematurely than those receiving no therapy, and those with a PI-based cART regimen were four times more likely to deliver prematurely. Overall, 2% (40 of 2326) of infants had a gestational age of less than 32 weeks, but this proportion was 4% (8 of 188) in infants exposed to combination therapy Liothyronine Sodium with a PI (P=0.005). Our data suggest an increased rate of extreme prematurity (<32 weeks) in the case of exposure to any kind of ART. In a subsequent analysis, Thorne et al. [9] reported a significant increase in the prematurity rate from 16.4% in 1985–1989 to 24.9% in 2000–2004, similar to our findings. Increased prematurity rates associated with maternal cART were also reported in studies based on data from Germany/Austria [12], the UK/Ireland [13] and Italy [14]. In a large US study, however, including more than 11 000 infants, evidence was found that both the proportion of low birth weight infants and the preterm birth rate declined over time, while use of any ART regimen increased substantially during the same period [15]. This study found an association between preterm birth and both no ART and cART with a PI. Of note, maternal CD4 cell counts and viral load data were not available in this analysis. Kourtis et al.

5 End-stage liver disease and its complications 351 Recommendat

5 End-stage liver disease and its complications 3.5.1 Recommendations 3.6 The role of clinical networks 4.0 Coinfection with HIV and hepatitis B virus 4.1 Background 4.1.1 Prevalence 4.1.2 Natural history 4.1.2.1 The influence of HBV on HIV infection 4.1.2.2 The influence of HIV on HBV infection 4.1.2.3 Chronic hepatitis B: classification 4.2 Assessment and investigations 4.2.1 Diagnosis of HBV infection in HIV-infected individuals 4.2.2 Molecular and serological tests in HBV

infection 4.2.2.1 The use of serum HBV DNA 4.2.2.2 Measuring HBV serology during and after therapy 4.2.2.3 HBV resistance testing 4.2.2.4 selleck chemical HBV genotyping 4.2.3 Screening for hepatocellular carcinoma (see 3.5 General section) 4.3 Therapy 4.3.1 Who to treat? 4.3.1.1 Recommendations 4.3.2 What to treat with? 4.3.2.1 HIV therapy not indicated 4.3.2.2 HIV therapy indicated 4.3.2.3 Recommendations for patients with a CD4 ≥500 cells/μL 4.3.2.4 Recommendations for patients with

a CD4 <500 cells/μL 4.3.2.5 Goals of therapy 4.3.2.6 Clevudine (L-FMAU) 4.4 Acute hepatitis B 4.4.1 Recommendations 4.5 Hepatitis delta virus (HDV) 4.5.1 Recommendations 5.0 Coinfection with HIV and hepatitis C virus 5.1 Background 5.1.1 Prevalence 5.1.2 Natural history 5.1.2.1 The influence of HCV on HIV infection 5.1.2.2 The influence of HIV on HCV infection 5.2 Assessment and investigations 5.2.1 Diagnosis of HCV infection in HIV-infected individuals 5.3 Therapy Y-27632 chemical structure 5.3.1 The coadministration of anti-HCV and anti-HIV treatment agents 5.3.2 Recommendations 5.3.3 General principles of anti-HCV therapy 5.3.4 Treatment options 5.3.4.1 Peginterferon 5.3.4.2 Ribavirin 5.3.4.3 Monitoring

5.3.4.4 Treatment duration 5.3.4.5 filipin ‘Easier-to-treat’ genotypes 5.3.4.6 ‘Harder-to-treat’ genotypes 5.3.4.7 Recommendations 5.3.5 Nonresponders and relapsers 5.3.6 New therapies for hepatitis C 5.4 Acute hepatitis C 5.4.1 Epidemiology 5.4.2 Clinical picture and natural history 5.4.3 Diagnosis of acute HCV infection 5.4.4 Management 5.4.5 Recommendations I =randomized controlled trial (RCT) or meta-analysis of several RCTs II =other good quality trial evidence III =observational studies/case reports IV =expert opinion 1 All new HIV-positive patients should be screened for hepatitis B virus (HBV) and hepatitis C virus (HCV) markers. The 2010 guidelines have been updated to incorporate all new relevant information that has become available since the previous versions were published in 2005. The 2005 versions came as separate hepatitis B and C guidelines but for 2010 we have decided to amalgamate them into a single document. This is to avoid duplication, as the general management of chronic liver disease is similar for both infections. The guidelines follow the methodology outlined below and all the peer-reviewed publications and important, potentially treatment-changing abstracts from the last 4 years have been reviewed.

NNH was calculated as the reciprocal of the difference between th

NNH was calculated as the reciprocal of the difference between the underlying risks of MI with and without abacavir use. A parametric statistical model was used to calculate the underlying risk of MI over 5 years. The relationship between NNH and Pirfenidone in vivo underlying risk of MI is reciprocal, resulting in wide variation in the NNH with small changes in underlying risk of MI. The smallest changes in NNH are in the medium- and high-risk groups of MI. The NNH changes as risk components are modified;

for example, for a patient who smokes and has a systolic blood pressure (sBP) of 160 mmHg and a 5-year risk of MI of 1.3% the NNH is 85, but the NNH increases to 277 if the patient is a nonsmoker and to 370 if sBP is within the normal range (120 mmHg). We have illustrated that the impact of abacavir use on risk of MI varies according to the underlying risk and it may be possible to

increase considerably the NNH by decreasing the underlying risk of MI using standard of care interventions, such as smoking cessation or control of hypertension. Abacavir is a common antiretroviral used in the treatment of HIV-1 infection and is currently recommended as one of the possible components of initial combination antiretroviral treatment [1–3]. The D:A:D study group recently reported an increased risk of myocardial infarction (MI) related to current or recent use of abacavir [4,5]. Some of the HIV-1 treatment guidelines have already taken into account the Enzalutamide manufacturer clinical implications of the D:A:D findings by emphasizing that clinicians should consider Loperamide careful assessment of patients who are on abacavir and at high risk of MI [2,6,7]. It is therefore of great importance

to ensure that the risk of MI attributed to abacavir use, together with the underlying risk of MI, is correctly interpreted and understood. Presenting results as relative risks (RRs) is standard in observational studies [8], but may be difficult to translate into clinical practice. The number needed to treat (NNT) and absolute risk reduction may be more clinically relevant, when assessing the beneficial effect of treatment [9–11], and the number needed to harm (NNH), together with absolute risk increase (ARI), will better reflect any adverse effect of treatment than RR in clinical terms [12]. Both NNH and RR are measures that attempt to summarize two numbers (the risks of MI with and without abacavir). RR summarizes the relative increase in the underlying risk of an event according to whether the patient receives a given treatment or not and the NNH indicates the number of patients that need to be treated to observe the adverse effect of a treatment in one additional patient. This approach was first proposed in 1988 [13], but it is still infrequently used to describe risk of adverse events of medicines [14–17]. NNH is a tool that can be used in different settings [18].