We compared all-cause mortality, major macrovascular events (MACE) and diabetes-related hospitalizations in T2DM-incident patients newly treated with metformin (MET) versus sulphonylureas (SU) monotherapy and in T2DM-prevalent patients newly treated with MET+SU versus MET+DPP4-inhibitor combination therapy.We analysed anonymized data obtained from a German health fund. Patients were included when they had started MET versus SU therapy or MET+SU versus MET+DPP4 therapy between 01/07/2010 and 31/12/2011. Observation started with the first MET/SU prescription or the first prescription of the second agent of a MET+SU/MET+DPP4 combination therapy. Follow-up time lasted until the end of data availability (a minimum of 12 months), death or therapy discontinuation.In total, 434,291 T2DM-prevalent and 35,661 T2DM-incident patients were identified. Of the identified T2DM-incident patients, 904/7,874 started SU/MET monotherapy, respectively, with a mean age of 70.1/61.4 years  1.4/2.2; 933/7,350 observed SU/MET patient years). 4,157/1,793 SU+MET/DPP4+MET therapy starters had a mean age of 68.1/62.2 years .In a propensity score matched (PSM) comparison, the HRs (95 % CIs) associated with SU monotherapy compared to MET monotherapy exposure were 1.4 (0.9–2.3) for mortality, 1.4 (0.9–2.2) for MACE, 4.1 (1.5–10.9) for T2DM hospitalizations and 1.6 (1.2–2.3) for composite event risk. In a multivariable Cox regression model, SU monotherapy was associated with higher mortality , higher MACE  and higher T2DM hospitalizations , which corresponded with a higher composite event risk .No significant differences in event rates were observed in the PSM comparison between DPP4+MET/SU+MET combination therapy starters and in the multivariable Cox regression analysis.Our results show that SU monotherapy may be associated with increased mortality, MACE and T2DM hospitalizations, compared to MET monotherapy. When considering SU therapy, the associated cardiovascular risk should also be taken into account.The online version of this article (doi:10.1186/s40200-016-0251-9) contains supplementary material, which is available to authorized users. Amongst the most common chronic diseases, type 2 diabetes mellitus (T2DM) presents some of the greatest clinical and health economic challenges . In addiThe primary goal of diabetes treatment is to control blood glucose levels , 9. If tPrevious observational studies have shown that a substantial number of T2DM patients receive SUs , 11. In In this study, we assessed all-cause mortality, major macrovascular events (MACE) and diabetes-related hospitalizations in T2DM-incident patients newly treated with MET versus SU monotherapy and in T2DM-prevalent patients newly treated with MET+DPP4 versus MET+SU combination therapy.We used an anonymized dataset obtained from the German health fund AOK PLUS (2010–2012) which initially included all T2DM-prevalent patients [at least one outpatient or inpatient T2DM diagnosis (ICD-10 codes: E11.-) in 01/07/2010-31/12/2011] who were insured by this health fund for the entire study period. The dataset contained information on patient socio-demographics, outpatient prescriptions, diagnosis-associated outpatient visits to GPs and specialists, and finally inpatient treatment in hospitals.All patients were followed from the moment they were enrolled in the study until the occurrence of the outcomes of interest or until the end of the study period (whichever came first). By applying additional inclusion criteria, T2DM-incident patients were identified as a subgroup of all T2DM-prevalent patients. These patients had at least one outpatient/inpatient T2DM diagnosis recorded in 01/07/2010–31/12/2011 without any previous T2DM diagnosis and without any prescriptions of an antidiabetic agent (ATC groups: A10*) in the preceding 6 months.○ Hospitalizations with stroke (ICD-10 codes: I60.-/I61.-/I62.-/I63.-/I64.-)○ Hospitalizations with acute myocardial infarction (ICD-10 codes: 10 I21.-)○ Hospitalizations with congestive heart failure (CHF) (ICD-10 codes: 10 I50.-)○ Hospitalizations with coronary revascularizations (OPS 5-361/5-362/5-363)○ Hospitalizations with percutaneous transluminal vascular interventions and stent implantations (OPS 8-836/8-837/8-84)○ Hospitalizations with peripheral vascular disease (ICD-10 code: 10 I73.9)○ Hospitalizations with angina pectoris (ICD-10 codes: 10 I20.-)MACE○ Hospitalizations with T2DM/acute hypoglycaemia as main diagnosis (ICD-10 codes: E11.-/ E16.0/E16.1/E16.2)T2DM-related hospitalizationsDeath (any cause)Composite outcome consisting of MACE, T2DM-related hospitalizations, and all-cause death.The study included T2DM-incident patients who started either MET or SU monotherapy between 01/07/2010 and 31/12/2011 without having received any prior antidiabetic medication during the preceding 180 days  to represent an event if they were the main motivation for acute hospitalization. The main outcome used in this study was a composite outcome (occurrence of any of the above events); in secondary analyses, the three event types were analysed separately.Our analyses of SU+MET combination therapy versus DPP4+MET combination therapy exclusively included T2DM-prevalent patients who had been prescribed MET monotherapy before and who started either MET-SU or MET-DPP4 combination therapy  between 01/07/2010 and 31/12/2011 without having received any prior SU/DPP4 medication (for the preceding 180 days). Data are presented in Figs. Differences in event risk for patients who received MET/SU monotherapy or SU+MET/DPP4+MET combination therapy were reported as unadjusted hazard ratios (HRs) in a Cox regression model censoring for death in the analyses addressing time to first MACE and time to first T2DM-related hospitalization and, additionally, censoring for therapy discontinuation/end of follow-up period for all outcome categories including death. Furthermore, the percentage of event-free patients over time was depicted by means of Kaplan Meier (KM) curves, and log-rank tests were used for testing statistical significance of differences.To address the issue of confounding, two additional analyses were conducted: an analysis of event rates in propensity score matched patient samples and a multivariate Cox regression analysis using time to event as the dependent variable and reporting adjusted HRs (aHRs).In the propensity score matching (PSM) procedure, SU-exposed patients (either mono or in combination with MET) were matched to SU non-exposed patients (MET mono or DPP4+MET) by propensity score. Only patients with complete (non-imputed) data were included in the analyses. Propensity scores were calculated using logistic regression estimation (with group affiliation as the dependent variable) including age, gender, age-adjusted Charlson Comorbidity Index  and SU+MET/DPP4+MET combination therapy patients (Model 2); results were reported as aHRs. In addition to the exposure to either MET/SU monotherapy or SU+MET/DPP4+MET combination therapy, age (as dichotomous variable with a cut-off point at 65 years), gender, age-adjusted CCI and aDCSI were included in these models as independent variables.p-values were two-sided, and 95 % CIs were calculated for HRs/aHRs. All descriptive analyses were performed with Microsoft SQL Server 2008 and Microsoft Excel 2010. All other statistical analyses were performed with SPSS 17.0.All reported In our study population, a total of 434,291 T2DM-prevalent and a subgroup of 35,661 T2DM-incident patients were identified (Table p <0.001), 50.3 % female (p <0.050), mean age-adjusted CCI of 1.44 (p <0.001); Table Of the T2DM-incident patients in our study, 904 patients who were new initiators of SU monotherapy were significantly older (mean age of 70.1 years), were more likely to be female (54.6 %) and had a significantly higher mean age-adjusted CCI (2.23) than the 7,874 therapy-naïve users of MET monotherapy [mean age of 61.4 years ; 50.8 % female (p <0.050) and a mean age-adjusted CCI of 2.56 (p <0.001); Table Among the T2DM-prevalent patients, 4,157 patients who were newly prescribed with a SU+MET combination therapy were significantly older (mean age of 68.1 years), were more likely to be female (53.4 %) and had a significantly higher mean age-adjusted CCI (2.79) than the 1,793 patients with newly prescribed DPP4+MET combination therapy [mean age of 62.2 years . In choosing SU therapy, MET contraindications may have played a major role. We observed MET contraindications in 44 % of the patients contained in our database. This may also explain event/mortality rate differences in the unmatched comparisons between MET/SU and MET+SU/MET+DPP4 groups. Other reasons for choosing a specific antidiabetic therapy were unknown to us, but could have confounded the results. Furthermore, we observed comparatively old/comorbid T2DM patients. This is due to the characteristics of those insured in the health care fund which provided the data. This means that T2DM patients with higher comorbidity levels are over-represented in our study.Our data show that patients receiving SU therapy (mono or combo) differ significantly from other T2DM patients treated with MET in any combination: they tend to be older, have greater comorbidity and are more often female. So, for example, the mean ages of patients who received MET mono, GLP-1+OAD, GLP-1+OAD+insulin or MET+DPP4 combination therapy were 69.0, 57.5, 58.0 and 66.8 years, respectively. In comparison, the mean ages of patients who received SU mono or SU+MET combination therapy were 76.8 and 72.2 years, respectively. This makes a real-world comparison of SU with GLP-1s/DPP4s a challenging task because, obviously, new antidiabetic agents address completely different T2DM patient cohorts in real-life practice than SUs. Consequently, a substantial number of patients were excluded in the PSM comparisons. To reduce the bias risk for those patients included in the PSM cohorts, we used all available variables that significantly influenced group exposition, even if there was a certain overlap between these variables, as was the case with CCI and aDCSI.The current study is an observational cohort study with several limitations commonly associated with observational studies. First of all, it is limited with regard to its sample size and, more importantly, to the relatively short duration of follow-up. In addition, a significant number of patients was lost to follow-up, with 42.8 % of SU monotherapy patients and 47.8 % of SU+MET combination therapy patients discontinuing their treatment (treatment gap >180 days or prescription of another agent) or suffering a fatal event within the first 12 months after initiation of therapy. Thus, these patients had a much shorter follow-up than the planned minimum period of 12 months, and they were censored prematurely before the end of the study period.Finally, certain information concerning several risk factors known from patient demographics and clinical characteristics associated with event risk were not available in our claims data. This included information about HbA1C , 38–40 aOur study suggests that SU monotherapy may be associated with an increased risk of mortality, MACE, T2DM hospitalizations and/or all-cause events, compared to MET monotherapy. Current German and European guidelines mostly recommend the use of SU as second-line therapy or, in case of MET contraindications, the use of SU as first-line therapy, and SU therapy is still prescribed in an important part of T2DM patients in Germany , 9. Our AD medication, antidiabetic medication; aDCSI, adapted diabetes complications severity index; aHR, adjusted Hazard ratio; ATC, anatomical therapeutic chemical; CCI, Charlson comorbidity index; DMP, disease management programme; DPP-4, dipeptidyl peptidase-4; GLP-1, glucagon-like peptide-1; HR, Hazard ratio; ICD, International statistical classification of diseases; IRR, incidence rate ratio; KM, Kaplan Meier; MACE, macrovascular event; MET, metformin; OAD, oral antidiabetic drugs; PS, propensity score; SU, sulfonyl urea; T2DM, type 2 diabetes mellitusAdditional file 1: Table S1.Components of the aDSCI. The table contains the components of the adapted Diabetes Complications Severity Index and describes the score methodology used, based on observed outpatient/inpatient ICD-10 codes in 2010. (TIF 141 kb)Additional file 2: Table S2.Charlson Comorbidity Index (CCI) and its components. The table outlines the components of the Charlson Comorbidity Index (CCI) and describes the score methodology used, based on observed outpatient/inpatient ICD-10 codes in 2010. (TIF 122 kb)Additional file 3: Figure S3.Kaplan-Meier (KM) curves for crude all-cause death rates, macrovascular event rates and T2DM-related hospitalizations for patients with either MET or SU monotherapy. The figure shows KM curves representing the percentage of event-free patients  for two T2DM-incident cohorts: patients who received SU monotherapy and patients who received MET monotherapy. Observation started with the first observed SU/MET prescription. (TIF 498 kb)Additional file 4: Figure S1.Distribution of propensity scores as calculated by logistic regression for MET/SU monotherapy users. This figure describes the overlap of propensity scores in Cohort 1, incorporating patients who received MET/SU monotherapy. (TIF 198 kb)Additional file 5: Figure S5.Multivariable Cox regression models estimating time to event for four outcome categories (MET/SU monotherapy). The figure shows the results of the multivariable Cox regression analysis with regard to independent factors influencing time until an event  in the T2DM-incident sample that received either SU or MET monotherapy. (TIF 164 kb)Additional file 6: Figure S4.Kaplan-Meier (KM) curves for all-cause death rates, macrovascular event rates and T2DM-related hospitalizations for patients with either MET or SU monotherapy (PS matched groups). The figure shows KM curves representing the percentage of event-free patients  for two T2DM-incident cohorts: patients who received SU monotherapy and patients who received MET monotherapy. Cohorts are matched by PSM. Observation started with the first observed SU/MET prescription. (TIF 546 kb)Additional file 7: Figure S2.Distribution of propensity scores as calculated by logistic regression for SU+MET and DPP4-MET combination therapy users. This figure describes the overlap of propensity scores in Cohort 2, incorporating patients who received SU+MET or DPP4-MET combination therapy. (TIF 227 kb)Additional file 8: Figure S8.Multivariable Cox regression models estimating time to event for four outcome categories (MET+SU/MET+DPP-4 therapy). Factors associated with event risk. The figure shows the results of the multivariable Cox regression analysis with regard to independent factors influencing time until an event  in the T2DM-prevalent sample that received either SU+MET or DPP4+MET combination therapy. (TIF 160 kb)Additional file 9: Figure S6.Kaplan-Meier (KM) curves for crude all-cause death rates, macrovascular event rates and T2DM-related hospitalizations for patients with either MET+SU or MET+DPP-4 therapy. The figure shows KM curves representing the percentage of event-free patients  for the two cohorts defined above. Observation started with the first observed prescription of the second combination agent. (TIF 604 kb)Additional file 10: Figure S7.Kaplan-Meier (KM) curves for crude all-cause death rates, macrovascular event rates and T2DM-related hospitalizations for patients with either MET+SU or MET+DPP-4 therapy (PS matched groups). The figure shows KM curves representing the percentage of event-free patients  for the two cohorts defined above. Observation started with the first observed prescription of the second combination agent. (TIF 629 kb)


RD can also present in the skeletal muscle, mimicking several other diseases. It is unusual for this relatively new classification of diseases to present in the muscles and can be mistakenly diagnosed as other autoimmune diseases rendering a delay in the appropriate management and progression of the disease.IgG4‐ A 68‐year‐old lady of an African American descent presented to the office with complains of unintentional weight loss of thirty pounds over the last year. She had a history of follicular lymphoma that had transformed to a diffuse large B‐cell lymphoma (DLBCL) diagnosed more than 20 years ago. It was treated with eight cycles of chemotherapy  followed by radiotherapy. She underwent complete remission with no evidence of recurrence until now.She was noted to have pancytopenia in September 2014. Owing to a concern for the recurrence of lymphoma, a positron emission computerized tomography (PET–CT) was obtained which revealed a mass in her psoas muscle. Biopsy of the mass showed the presence of a few macrophages and failed to reveal any evidence of malignancies or reoccurrence of lymphoma.The patient then started noticing further weight loss and decrease in her appetite since, and presented to the office again after a year. A repeat PET–CT was performed which demonstrated an overall enlargement of the left iliac and psoas muscles Fig. . The FDGCore biopsy of the masses performed thereafter revealed fibrosis with sparse lymphocytic infiltrate and hemosiderin deposition, unremarkable plasma cells, without evidence of a lymphoma (histopathology slides 1–3). A quantitative IgG was performed that showed a value of 2030 mg/dL (reference range: >19 years of age 700–1600 mg/dL). IgG4 subclass was also significantly elevated at 1022 (reference range 7–89). Workup for multiple myeloma was negative with serum protein electrophoresis showing a chronic inflammatory pattern and did not identify a monoclonal protein, but rather a polyclonal increased in IgG. Other laboratory investigations were as follows: Creatinine 0.75 mg/dL, LDH 135 U/L, BUN 18 mg/dL; .The patient was seen in consultation, and a recommendation was made to treat her with steroids after discussing her case with the pathologist.Formerly known as IgG4‐related systemic disease, IgG4‐related disease (IgG4‐RD) is a relatively newly discovered fibro‐inflammatory condition and is named so due to the presence of antibody subtype IgG4‐producing plasma cells, that are present in large amounts on tissue samples from involved organs. It has a characteristic histologic appearance and elevated IgG4 concentrations in the acute phase of approximately 60–70% of its patients IgG4‐RD can virtually occur in any organ of the body with the most common sites as the salivary glands, periorbital tissues, pancreas, biliary tree, kidneys, lungs, lymph nodes, breast, aorta, thyroid, prostate, and skin IgG4‐RD has been labeled as a slow condition as usually symptoms tend to be mild in spite of considerable organ destruction, if any. People are often described feeling relatively well at the time of diagnosis, although some may give a history of weight loss. Pain is usually not a feature of the inflammation but may occur as a secondary effect due to some form of obstruction or compression. A diagnosis is often formulated due to the presence of painless swellings or mass lesions that may lead to complications. Incidental lesions may also be detected on radiological studies and can be easily misdiagnosed as a malignancy.Helicobacter pylori and constituents of pancreatic epithelial cells suggesting gastric H. pylori infection may set off autoimmune pancreatitis in genetically predisposed individuals via cross‐reactivity of the antibodies, yet autoimmunity has not been completely proved. Antibodies directed against potential auto‐antigens to some degree, may be associated with systemic manifestations of IgG4‐RD Several genetic studies suggest the involvement of several human leukocyte antigen (HLA) and non‐HLA haplotypes/genotypes that may be associated with susceptibility to IgG4‐RD or to disease relapse post therapy Radiographic features are generally nonspecific and may not provide a reliable distinction between IgG4‐RD and malignancy. A majority of patients with IgG4‐RD have elevated serum IgG4 levels of varying ranges with approximately 30% of patients having normal serum IgG4 despite classic histopathological and immunohistochemical features Induction and maintenance of remission are the main treatment goals to prevent progression of fibrosis and organ damage. All cases of symptomatic IgG4‐RD warrant treatment though some cases of asymptomatic IgG4‐RD may require early management to prevent severe complications like aoritis, pericarditis, and pachymeningitis Glucocorticoids are the recommended first‐line agents for induction unless contraindications exist resulting in rapid improvements of symptoms and a resolution of radiographic findings. Steroid‐induced flares are not uncommon. Although their efficacy has never been tested in clinical trials, rituximab, mycophenolate mofetil, methotrexate, and azathioprine are used frequently as glucocorticoid‐sparing agents or remission‐maintenance drugs after glucocorticoid‐induced remissions κB) Bortezomib, an excellent proteasome inhibitor has been a novel drug which is currently approved for and used in the management of relapsed leukemias and multiple myelomas in the posttransplant setting. Several preclinical trials showed antimyeloma effects of bortezomib including the disruption of the cell cycle and apoptosis induction, alteration of the bone marrow microenvironment, and inhibition of nuclear factor kappa B (NFIgG4‐RD encompasses a large number of medical disorders previously referred to as confined to a single organ. As a recently recognized condition, links among the increased quantities of IgG4 plasma cells, varying quantities of serum IgG4, and its histological features needs to be determined. Despite being a rare case in itself, to the knowledge of the authors, this is the second known case of IgG4‐RD to occur in the skeletal muscles.None declared.


Bacterial antibiotic resistance is typically quantified by the minimum inhibitory concentration (MIC), which is defined as the minimal concentration of antibiotic that inhibits bacterial growth starting from a standard cell density. However, when antibiotic resistance is mediated by degradation, the collective inactivation of antibiotic by the bacterial population can cause the measured MIC to depend strongly on the initial cell density. In cases where this inoculum effect is strong, the relationship between MIC and bacterial fitness in the antibiotic is not well defined. Here, we demonstrate that the resistance of a single, isolated cell—which we call the single-cell MIC (scMIC)—provides a superior metric for quantifying antibiotic resistance. Unlike the MIC, we find that the scMIC predicts the direction of selection and also specifies the antibiotic concentration at which selection begins to favor new mutants. Understanding the cooperative nature of bacterial growth in antibiotics is therefore essential in predicting the evolution of antibiotic resistance. This quantity predicts both the direction of selection and the approximate antibiotic concentration at which there is selection for increased resistance. Importantly, these two key predictive properties of the scMIC are independent of the density of the bacterial culture in which selection occurs, and thus, the scMIC can provide valuable guidance for researchers and clinicians studying the evolution of antibiotic resistance.E. coli strains  as the MIC*.Throughout the remainder of this paper, we use the abbreviation “MIC” to describe the lowest concentration of antibiotic that inhibits growth of a culture over 20 h; this MIC is a function of the initial cell density. We will denote the specific MIC value for the standard initial cell density , we monitored the behavior of a single cell on agar with various antibiotic concentrations Fig. InitialWe next compared the antibiotic concentration required to prevent colony formation after overnight growth with the scMIC measured in liquid culture. These quantities should be equivalent: each colony observed on an agar plate develops from a single cell that was able to reproduce in a given antibiotic environment. Encouragingly, we found that the single-cell resistance measured on agar is within a factor of two of the scMIC obtained by the liquid dilution method Fig, with boGiven that the scMIC of a strain is often significantly lower than its MIC*, an important question is what antibiotic concentrations will lead to selection of one strain over another when two strains are in competition, that is, which conditions promote the evolution of increased resistance. Antibiotic concentrations below the scMIC of both competing strains are not expected to be strongly selective. A mutant with a higher scMIC value than the background population gains a relative advantage when the antibiotic concentration is at least the scMIC of the background population. At that concentration, the background population will begin to die, but the mutant will not. As a result, below the scMIC of the reference strain, the fractional composition of the bacterial population will not change overnight, while if the antibiotic concentration in the environment is above the scMIC of the reference strain, the mutant will rapidly increase in fraction Fig. ImportaWe tested this prediction experimentally by directly competing what we call the reference strain  with its high scMIC mutant . In this experiment, the two strains were labeled with plasmids expressing either yellow or cyan fluorescent proteins, thus allowing us to measure fractions by flow cytometry; labels were swapped in replicates of these experiments . Consistent with the argument in the previous paragraph, selection favoring the E104K mutant began when the antibiotic concentration approached the scMIC of the reference strain Fig. Note thde novo mutants with higher scMIC can arise. To test this prediction, we performed laboratory evolution experiments at multiple antibiotic concentrations both above and below the scMIC of the starting strain  to prevent heat shock and death of the worms.Briefly, synchronized adult tions Fig. After 2in vitro competition experiments described above, we found that selection for the more resistant mutant (TEM-52) starts at the scMIC value of the less resistant background allele ..6A). At acrit, at which point the cells die at a rate ∼2 per h . Thus, within this model, a mutant strain with a more efficient enzyme (higher Vmax and/or lower KM) will have a higher scMIC. This equation has been proposed to quantify MIC* . At higher antibiotic concentrations, the hydrolysis rate becomes independent of the antibiotic concentration, and the model predicts that MIC increases linearly with the initial cell density. However, the experimentally measured MIC grows slower than linearly with the initial cell density. This phenomenon could be explained by the fact that in this regime, the population spends a significant amount of time in the death phase and degradation of the released enzyme could become significant (Supplementary Information).In our model, the inoculum effect curve can be derived analytically in the limit of low and high cell densities. These two regimes are determined by how MIC compares to Our model agrees with the experimental finding that independent of initial cell density, selection favoring the competitor with the higher scMIC will begin when the antibiotic concentration approaches the scMIC of the less resistant strain Fig. In our in vitro and in vivo experiments  would also have a large difference between the scMIC and the high-density MIC*.E. coli strains with different versions of the TEM β-lactamase enzyme , whereas scMIC reflects the “selfish” hydrolysis in the periplasmic space . This distinction may be relevant for other resistance mechanisms governed by enzymatic inactivation of a drug. Enzymatic inactivation has been an observed mechanism of resistance against several classes of antibiotics, including β-lactams, aminoglycosides  There is no cost in being more resistant, (ii) the resistance mechanism is cooperative, and (iii) there is no gradual dependence of the growth rate on the antibiotic concentration: For any concentration below, the scMIC growth is exponential with a rate that does not depend on the antibiotic concentration; above the scMIC, death is exponential with a rate that is again independent of the antibiotic concentration.The first assumption is applicable here because we study the evolution of a protein and consider very few mutations that change its enzymatic properties. This assumption generally can be made whenever small improvements of already existing adaptations drive the evolution, as compared, for example, to the acquisition of a plasmid carrying an antibiotic resistance gene.et al, The second assumption states that the effect of the global decrease of antibiotic due to hydrolysis is significant when compared to the effect of the local decrease of periplasmic antibiotic concentration due to partial localization of the enzyme. Broadly, whenever the global effects of antibiotic breakdown are strong enough as compared to local, this assumption is valid. Although our experiments have focused on the β-lactam cefotaxime, it is possible that similar phenomena may be observed for other drugs that show an inoculum effect. The inoculum effect can often be caused by enzymatic degradation of antibiotics, and plasmid-borne antibiotic-degrading enzymes are widespread among bacteria in natural environments Bennett, . Even whet al, The third assumption is that the transition from growth to death is sudden as a function of the antibiotic concentration Fig, which iet al, et al, therefore, very low concentrations of antibiotic have a modest but potentially significant effect on bacterial growth. In this situation, it is possible to get selection for antibiotic resistance at sub-MIC concentrations of antibiotic, even in the absence of collective inactivation of the antibiotic . Collective antibiotic degradation is therefore not the only mechanism for sub-MIC selection for antibiotic resistance.Other work has suggested a distinct mechanism by which sub-MIC* concentrations of antibiotic may select for increased resistance. For example, a recent study demonstrated that sub-MIC* levels of tetracycline, aminoglycosides, and fluoroquinolone antibiotics can select for cells carrying an antibiotic resistance plasmid  for 18–20 h with 300 rpm shaking in 50-ml falcon tubes. Cultures were then diluted to the initial optical densities and grown in serial dilutions of cefotaxime in 96-well plates at 37°C for 20 h with 500 rpm shaking. Minimum inhibitory concentration was determined by the lowest concentration that prevented bacterial growth (OD < 0.3). All measurements were done in triplicate.For competition experiments, we transformed TEM strains with plasmids constitutively expressing either CFP or YFP (plasmids pZS25O1 + 11-Cerluean and pZS25O1 + 11-YFP). Two cultures of different colors were grown from single colonies for 18–20 h in 50 μg/ml of piperacillin and 50 μg/ml of kanamycin for plasmid selection. These cultures were then mixed and grown for another 20–22 h in 50 μg/ml of piperacillin and 50 μg/ml of kanamycin to synchronize the growth phases of the two strains. The purpose of synchronization was to eliminate any experimental variability and experimental effects due to the difference in the growth phases of the two cultures in the beginning of the experiment . The synchronized mixed culture was diluted to multiple initial cell densities and exposed to various cefotaxime concentrations on 96-well plates. After 25 h of growth at 37°C with shaking, the cultures were diluted in PBS 1:900 and measured at the flow cytometer. For the competition of TEM-15 and A42G mutant of TEM-20, the second day of growth of the two strains together before the addition of cefotaxime was done with no piperacillin present. The reason for that is that piperacillin scMIC of TEM-15 is smaller than 50 μg/ml and the prepared initial fraction shifted significantly over the course of 20–22 h growth. We confirmed that this did not happen with the other strains that we used for competition experiments.C. elegans were produced according to standard protocols  on NGM agar plates with E. coli OP50 as a food source; recently starved plates were washed to retrieve adults for bleach/NaOH synchronization. Eggs were incubated 24 h at 23°C in M9 worm buffer with shaking at 300 rpm, and L1 larvae were transferred to NGM + OP50 plates at 23°C to produce sterile adults. Young adult worms were washed from agar plates and incubated 24 h in liquid S medium with heat-killed OP50 as a food source and 100 μg/ml kanamycin to remove any adhered or internalized OP50, producing microbe-free 2-day adults for colonization.Synchronized cultures of adult in vitro competition experiments, resuspended to uniform densities (∼109 cells/ml) in liquid S medium, and mixed to obtain feeder cultures containing 90% TEM-20 and 10% TEM-52. Synchronized adult worms were colonized by feeding for 36 h in 1-ml bacterial cultures in 24-well plates, which were covered with Breathe-Easy transparent membranes (Diversified Biotech) to allow gas exchange and loosely covered with foil to protect cultures from light. After colonization, worms were washed to remove external bacteria, then transferred to fresh 24-well plates in 1-ml liquid cultures of S medium containing heat-killed OP50 as a food source and different concentrations of cefotaxime (0–0.8 μg/ml) for competition. After 20-h incubation with cefotaxime, worms were washed and mechanically disrupted by grinding in 25 μl M9 worm buffer + 0.1% Triton X-100 using a Kimble Kontes motorized pestle. The resulting bacterial suspension was diluted in M9 worm buffer and plated on LB agar. Colony-forming units per worm were determined for each bacterial strain by counting YFP and CFP colonies after 48 h.Bacteria were grown as described for For evolution experiments, we started with TEM-19, TEM-20, and the A42G mutant of TEM-17. All strains were exposed to four antibiotic concentrations, and for each antibiotic condition, six independent populations were evolved. Every day, we diluted 1:225 the evolving cultures to new media with fresh antibiotic. After 13 days, scMICs of all cultures were measured and the β-lactamase genes were sequenced.


Several c-MET targeting inhibitory molecules have already shown promising results in the treatment of patients with Non-small Cell Lung Cancer (NSCLC). Combination of EGFR- and c-MET-specific molecules may overcome EGFR tyrosine kinase inhibitor (TKI) resistance. The aim of this study was to allow for the identification of patients who might benefit from TKI treatments targeting MET and to narrow in on the diagnostic assessment of MET.222 tumor tissues of patients with NSCLC were analyzed concerning c-MET expression and activation in terms of phosphorylation (Y1234/1235 and Y1349) using a microarray format employing immunohistochemistry (IHC). Furthermore, protein expression and MET activation was correlated with the amplification status by Fluorescence in Situ Hybridization (FISH).s = 0.41; p < 0.0001). No significant correlation was shown between MET expression and phosphorylation (p > 0.05). c-MET gene amplification was detected in eight of 214 patients (3.7 %). No significant association was observed between c-MET amplification, c-MET protein expression and phosphorylation.Correlation was observed between phosphorylation of c-MET at Y1234/1235 and Y1349 (spearman correlation coefficient rOur data indicate, that neither expression of c-MET nor the gene amplification status might be the best way to select patients for MET targeting therapies, since no correlation with the activation status of MET was observed. We propose to take into account analyzing the phosphorylation status of MET by IHC to select patients for MET targeting therapies. Signaling of the receptor and the activation of downstream molecules might be more crucial for the benefit of therapeutics targeting MET receptor tyrosine kinases than expression levels alone. Targeted therapies constitute promising strategies in the personalized treatment of cancer. Increasing knowledge of expression patterns and molecular pathophysiology led to improved outcomes of patients with non-small cell lung cancer (NSCLC). The Mesenchymal Epithelial Transition factor (MET) receptor tyrosine kinase (RTK) and its ligand hepatocyte growth factor/scatter factor (HGF/SF) are predominantly involved in epithelial-to-mesenchymal transition (EMT)  and tissSeveral MET-targeting inhibitors have already shown promising data in clinical trials –13. MostTivantinib, a c-MET selective, small molecule inhibits MET phosphorylation leading to reduced capacity of invasion, proliferation and metastasis , 21. ResCrizotinib, a non-selective MET inhibitor targeting c-MET, ALK and ROS1 exhibits its antitumoral effect in c-MET, ALK-positive and ROS positive patients , 22, 23 MET amplification leads to gefitinib resistance in lung cancer patients lacking the point mutation T790M in exon 20 of EGFR . Bean etFor that purpose, we investigated in a retrospective study, MET expression on protein level by IHC using antibody clone SP44 in 222 formalin fixed paraffin embedded (FFPE) - and HOPE (HEPES-Glutamic Acid Buffer Mediated Organic Solvent Protection Effect) fixed - NSCLC tissues. Because not only expression but also activation of MET is essential for tumor progression, we also analyzed the phosphorylation status of the receptor by IHC with two phosphorylation specific antibodies. To obtain more insights into the relation between MET expression, phosphorylation and amplification, MET amplification was assessed by FISH analysis. For a limited number of tumor samples, MET expression was also evaluated on mRNA level and compared with MET expression evaluated by Western Blot analysis.Finally, we compared MET- and EGFR-expression within these tumor tissues to investigate, whether a correlation exists between both biomarkers. The aim of the present study was to assess, if the expression and amplification is correlated with the activation status of the MET receptor, because we hypothesize, that not only expression and amplification but phosphorylation can be a relevant marker to select patients for MET specific therapies.A total of 222 lung tumor specimens from patients with NSCLC were obtained from the Biomaterial Bank North after resection from the surgical department of LungenClinic Grosshansdorf Table , includiSpecimens were arranged on TMAs for enhanced comparability of immunohistochemical stainings as previously described . ApproprMET protein expression was assessed by IHC on 2 μm thick deparaffinized TMA sections, using rabbit anti-human c-Met monoclonal antibody (clone SP44)  directed against the synthetic peptide derived from C-terminus of human c-Met protein displaying membranous and/or cytoplasmic epitope. Staining procedures were conducted according to manufacturer’s protocol in a final 1:1000 dilution.Phosphorylated MET-expression was assessed by two different primary antibodies purchased from Cell Signaling . Phospho-Met (Y1234/1235) (D26) and Phospho-Met (Y1349) (130H2) in a final dilution of 1:100.2O2 for 10 min. Negative controls omitting the primary antibody were always included.HOPE-fixed, paraffin-embedded sections were deparaffinized by xylene incubation (two times 10 min) before SP44 was applied for 30 min at room temperature. Endogenous peroxidases were blocked by incubation with 3 % HFormalin-fixed samples from the same tumors were deparaffinized following standard procedure. Antigen retrieval was achieved by boiling in citrate buffer  for 10 min  with subsequent cooling at room temperature for 20 min. Antigen detection was carried out with DAB substrate kit (DAB chromogen and DAB substrate), used for 15 min to visualize specific binding. Sections were counterstained using Meyer’s hemalum and mounted with Pertex  for further evaluation.Two observers quantified staining intensities. Samples were evaluated with the MET scoring algorithm as previously described . MET posPhosphorylated MET expression was evaluated according to the intensity of cytoplasmic staining  and the percentage of stained tumor cells . If ≥ 50 % of tumor cells showed staining intensity ≥ 2, tumor samples were categorized as positive in this study.EGFR expression is considered as positive, if ≥10 % of the tumor cells show membranous staining of any intensity using x10 and x20 magnification assessed by Dako EGFR PharmDx data sheet.c-MET gene copy numbers were assessed by fluorescence in situ hybridization (FISH) using ZytoLight SPEC MET/CEN7 Dual Color Probe . Before hybridization, sections were deparaffinized, dehydrated and immersed in citrate buffer  pH 6 at 98 °C for 15 min, and subsequently washed twice in distilled water for 2 min. The sections were air dried and pretreated with pepsin for 5 min before denatured for 10 min at 75 °C. After hybridization at 37 °C for 20 h, slides were washed and counterstained with 1.5 μg/ml 4’,6’-diamidino-2-phenylindole (DAPI) mounting medium  and coverslips were fixed with nail polish.Analysis of FISH signals was performed on an epifluorescence microscope Nikon Eclipse 80i H550L (Nikon) with interference filters .MET/CEP7 ratio was > 2.2 orsmall gene clusters (≥4 copies) independent of the MET to CEP 7 ratioAt least 50 non-overlapping interphase nuclei of tumor cells were counted per core. The nuclei were selected using the DAPI filter under high magnification (x600). For each probe, the numbers of c-MET and CEN7 per nuclei were separately scored and mean cMET/CEN7 ratio was determined. FISH MET gene amplification was defined as FISH positive, whenThese analysis criteria were adapted to previous publications for the evaluation of MET amplification .Increased MET gene copy number (GCN) >3 of Chromosome 7 and MET-locus was defined as polysomy.Evaluation was performed independently by two scientists well-vised in FISH analysis.HOPE-fixed, paraffin-embedded specimens were deparaffinized as previously described by Olert et al. . ProteinTotal RNA was isolated from HOPE-fixed tissue samples as described previously  using RNAll statistical analysis in this study were performed with Spearman’s rank nonparametric correlation test using Prism 6 software. All reported p values are two sided .A total of 222 surgically resected NSCLC patients were included in this study. Clinical parameters are summarized in Table We compared staining intensities of the MET specific antibody clone SP44 in formalin fixed paraffin embedded tissue versus HOPE-fixed tumor samples. When MET expression was evaluated in HOPE-fixed samples, staining intensities were mostly stronger compared to the appropriate FFPE tissue samples within one specimen Fig. . In FFPEOf the corresponding 209 HOPE fixed NSCLC tissues, 77 (36.8 %) were scored positive (72 (34.4 %) of the tumor samples were scored as 2+ and 5 (2.4 %) were classified as 3+). Negative MET expression was shown for 132 (63.2 %) tumor tissue samples (28 (13.4 %) samples were scored as 0 and 104 (49.8 %) samples were scored as 1) Fig. . SubtypeThere was no significant association with clinical characteristics and also not with the histological entities (data not shown). Of 77 (36.8 %) HOPE positive samples and 45 (21.5 %) FFPE- positive samples, the intersection between HOPE and formalin fixed tumor tissue was 29 (13.9 %) Fig. . Mean MEs = 0.482 p < 0.0001). Correlation with any clinicopathological status was not shown.Correlation between c-Met expression evaluated by IHC in FFPE versus HOPE fixed samples was shown . 30 (14 %) tumor tissue samples showed Met phosphorylation. Of 209 tumor tissues, evaluated by IHC for the expression of MET and positive for phosphorylation at Y1234/1235, 20 (9.6 %) were classified as ADC, 9 (4.3 %) were categorized as SCC and 1 (0.5 %) as LCC. For phosphorylation at Y1349 (docking site of MET), 215 tissues could be analyzed. 38 (17.7 %) samples were phosphorylated at that phosphorylation site. Classified into the corresponding histological entities, MET phosphorylation of Y1349 was present in 17 (8.1 %) of ADC, 18 (8.6 %) of SSC and 3 (1.4 %) of LCC related to the 209 tissues evaluated for MET expression . Staining patterns for phosphorylated MET (Y1234/1235 and Y1349) were both cytoplasmic and membranous. Immunoreactivity was exclusively restricted to tumor cells . Likewise, no association with any clinicopathological parameter was shown.Correlation between phosphorylation of MET at Y1234/1235 and Y1349 was determined with rOut of total of 444 tumor samples (222 patients in duplicates), valid results were obtained for 214 patients (96.4 %). Invalid results were due to the lack of adequate tumor cells.C-MET gene amplification was detected in eight of 214 patients (3.7 %). Concerning the 209 tumor tissues evaluated for MET expression, percentage acounts 3.8 %. These clustered gene amplifications showed mean ratio range between 1.5 and 6.26 (cMET/CEN7 ratio), distributed in 5 (2.4 %) of ADC and 3 (1.4 %) of SCC whereas no amplification was observed in LCC and other tumor entities .No significant association was observed between c-MET amplification and MET protein expression or phosphorylation . No association was found for any other clinical characteristic. .MET gene copy number correlated with tumor size by trend and lymph node status (both: spearman correlation coefficient rA few NSCLC tissue samples (11 tumor samples are shown) could be selected for the comparison of MET expression levels evaluated on protein level by IHC and western blot analysis and on mRNA-level by real-time PCR. Strong relationship is observed between IHC and western blot analysis Fig. . Whereass = 0.2086; p = 0.0026). 207 tumor tissues could be analyzed for both MET- and EGFR-expression. 185 tumor samples were scored as positive for the expression of EGFR, 44 were scored positive for MET expression and 43 tumor tissues were double positive for EGFR and MET. Thus, nearly all of MET expressing tumor samples were also positive for MET expression.In a previous publication, we analyzed EGFR expression by different EGFR specific antibody clones . TherefoPersonalized therapies will only be effective if target molecules are exactly determined or quantified. MET is currently one of the target proteins that are utilized for several anticancer therapies in patients with NSCLC , 15, 31.Dziadziuszko et al.  demonstrIn the trial of Spigel et al.  52 % of There are many studies evaluating the expression level of c-MET, but only few that investigated phosphorylated c-MET in human cancer tissues. Whether MET-expression is correlated with its phosphorylation status in NSCLC tissue, still remains unclear. Recently, in the case of gastric cancer, Inoue et al.  have shoIn our study, MET phosphorylation at Y1234/1235 was detected in 14 % of the investigated NSCLC tumor samples, phosphorylation of Y1349 was observed in 17.7 %. No association between MET expression and phosphorylation was found. In contrast to the study of Nakamura et al., differences might be due to distinct statistical analysis. Nakamura et al., determined association with chi-square test, whereas in our study, correlation was computed with spearman rank correlation. Another reason could be the application of different antibody clones for activated MET Y1234/1235 compared to the study of Nakamura et al. phosphorylation at [Y1349] has not been investigated by Nakamura et al. .Unfortunately, association analysis between the expression and phosphorylation of MET with clinical characteristics of the patients was not possible, because we do not know anything about course of disease, e.g. disease progression or treatment with TKIs.Several studies have already been addressed to evaluate the MET amplification status , 32, 37 Unfortunately, we have almost no data about the therapeutic management and the course of disease.Finally, we have shown that there is a tendency of association between MET and EGFR expression. Almost tumor samples expressing MET are also positive for EGFR expression. Cross-talk between MET and EGFR in NSCLC has been previously shown by Acunzo et al. . These dOur study depicts, that definition of MET positive signaling together with MET-positivity might be required to predict the benefit of MET targeting therapies. We hypothesize that not MET expression is crucial for efficacy of MET inhibitory molecules but the evaluation of the activated RTK by determination of the phosphorylation status of MET is more important. Phosphorylation and thereby activation can also occur if MET is not overexpressed; due to mutation or the activation of MET by secreted HGF.In conclusion, investigation just of one receptor independently of the quantification method might be extended to other RTKs, maybe the focus should not be only on the expression level of RTKs, but on the determination of the activation status.The results of this study might have consequential clinical implication for therapeutic administration of MET specific drugs, in particular for MET targeting TKIs, namely, that not the expression alone might be of therapeutical relevance, but also the determination of the phosphorylation status.


Ventilator-associated pneumonia (VAP) is a common and serious problem in ICUs. Several studies have been conducted to determine the effectiveness of Gram stain of tracheal aspirates for diagnosing VAP. However, the effectiveness for predicting causative microorganisms and guiding appropriate initial antibiotic therapy has not been evaluated. The purpose of this study is to determine whether Gram stain of tracheal aspirates can guide appropriate initial antibiotic therapy for VAP.We retrospectively assessed two hypothetical empirical antibiotic treatment algorithms for VAP on an 18-bed ICU. Data on consecutive episodes of microbiologically confirmed VAP were collected over a period of 22 months and divided into a derivation (1 February 2013 to 30 November 2013) and validation (1 December 2013 until 15 November 2014) cohort. We constructed two algorithms in the derivation cohort. One is a local ecology-based algorithm (LEBA), according to clinical risk factors for MDR and susceptibility results in our hospital. The other is a Gram stain-based algorithm (GSBA). The selection of antibiotics on GSBA was directed against pathogens predicted from the results of bedside Gram staining of tracheal aspirates collected just before antibiotic therapy. Subsequently, LEBA and GSBA were retrospectively reviewed and compared with actually prescribed antibiotics in the validation cohort.P < 0.001). GSBA recommended carbapenems in significantly less episodes than LEBA (P < 0.001) and the same episodes as actually prescribed initial therapy (P = 1). However, there was significant increase of antibiotic coverage rates in GSBA compared with the actually prescribed initial therapy .The first 50 VAP episodes made up the derivation cohort and the subsequent 50 VAP episodes the validation cohort. Antibiotic coverage rates by applying LEBA and GSBA were identical (96% vs. 96%). GSBA proposed more narrow spectrum therapy as compared with LEBA (Antibiotic coverage rates on GSBA were comparable with LEBA. The use of GSBA would result in a significant reduction of the administration of broad-spectrum antibiotics. Bedside Gram staining may be useful to guide appropriate initial antibiotic therapy for VAP.


Although there are several models of integrated architecture, we still lack models and theories about the integration process of health system responses to HIV/AIDS and NCDs.The overall purpose of this study is to design an action model, a systematic approach, for the integration of health system responses to HIV/AIDS and NCDs in developing countries.An iterative and progressive approach of model development using inductive qualitative evidence synthesis techniques was applied. As evidence about integration is spread across different fields, synthesis of evidence from a broad range of disciplines was conducted.An action model of integration having 5 underlying principles, 4 action fields, and a 9-step action cycle is developed. The INTEGRATE model is an acronym of the 9 steps of the integration process: 1) Interrelate the magnitude and distribution of the problems, 2) Navigate the linkage between the problems, 3) Testify individual level co-occurrence of the problems, 4) Examine the similarities and understand the differences between the response functions, 5) Glance over the health system’s environment for integration, 6) Repackage and share evidence in a useable form, 7) Ascertain the plan for integration, 8) Translate the plan in to action, 9) Evaluate and Monitor the integration.Our model provides a basis for integration of health system responses to HIV/AIDS and NCDs in the context of developing countries. We propose that future empirical work is needed to refine the validity and applicability of the model. Integration could also be partial or full; specific or generalized; strong or weak; localized or universal. Integration may also be classified based on the foci of integration, the units that are going to be integrated. Besides, integration can be internal (e.g. intra-program), external (inter-program), across stakeholders, across levels and with sector-wide responses.Integration is a means to an end rather than an end by itself . Based ooutput of integration, the configuration of an integrated whole, and how it works  is rapidly increasing in these countries. As HIV/AIDS and NCDs share many characteristics, an integrated approach could be a more effective and efficient alternative to curb the tide of the two epidemics. Given the political recognition of the need for integrated approach and the resource constraints in developing countries, there is an urgent need for evidence-based models for integrating the responses to HIV/AIDS and NCDs.process of integrating two or more health system response functions like that of HIV/AIDS and NCDs. Therefore, this study was designed to develop an action model, a step-by-step approach, for the integration of health system responses to HIV/AIDS and NCDs in the context of developing countries. The new model is expected to be useful for assessment, strategy development, healthcare management and in refinement of existing strategies related to integration.However, to the knowledge of the authors, there is no systematic and systemic model that could guide the scoping review of the literature to explore the rationale for integrating the responses to HIV/AIDS and NCDs in developing countries  model of integration management for the rest of the steps. We detailed the application of all the steps in using the HIV/AIDS and NCD integration as a working example.Following the generation of evidence for integration, the next logical step is communication. In order for evidence to better inform decisions, it needs to be iterative and progressive. We used descriptive, integrative and configurative evidence synthesis techniques at different levels. We considered the model to be cyclical rather than linear. The primary information sources during the design of the model were the sub-studies conducted as part of a larger research project and additional trans-disciplinary literature review.In overall, this model development process was integration managers should implement to arrive at an effective integration of functions. If integration managers use a systematic process of integration, there will be a higher chance of successful integration as compared to the use of fragmented and unsystematic processes of integration.Integration consists of a series of steps that This article describes a model for integration process of health system response functions of HIV/AIDS and Noncommunicable diseases using the acronym INTEGRATE. Each letter of the acronym INTEGRATE stands for a step in the action cycle that needs to be carried out before proceeding to the next step. The nine steps in the INTEGRATE Model are shown in the figure below.As described in the above figure, the resulting action model has five underpinning principles, five key processes, four action fields and a nine-step action cycle. These principles, key processes and steps are illustrated in the following sections.Key process I: Analyze connections between the problemssyndemic theory and ecological model, analysis of the connection between HIV/AIDS and NCDs can be conducted at three levels: Population, Problem and Individual levels.As it is the case for many other management functions, integration starts with understanding of HIV/AIDS and NCDs, more specifically the connections between them. Using the Step 1: Interrelate the magnitude and distribution of the problemspopulation level is essential to identify epidemiological overlaps between the problems. Evidence from population level overlap informs overall policy approaches and priorities. It also informs the need for a more detailed analysis. The magnitude of HIV/AIDS and NCDs can be interrelated at point in time , across time (in a time-series manner), across different geographic settings, and across different segments of a population. The interrelationships between patterns and trends of HIV/AIDS and NCDs across different dimensions could be explored using a cluster analysis, trend analysis and correlational analysis techniques.Interrelating the magnitude and distribution  of HIV/AIDS and NCDs at overlap between HIV/AIDS and Diabetes (considered as a prototype NCD) in developing countries, Diabetes was found to have higher prevalence and HIV was found to have higher disability-weight-adjusted prevalence. Diabetes had an increasing trend while HIV had a stabilizing trend. Countries with high diabetes prevalence tend to have lower HIV prevalence. Four clusters of countries were identified from the cluster analysis of the patterns in the prevalence of HIV/AIDS and Diabetes , six major pathways of linkage were found. These were direct cause-effect relationship, common underlying/background factors, lifestyle factors, treatment effects, common complications, and other disease conditions . Apart fStep 3: Testify individual level co-occurrence of the problemsThe third level in the analysis of the connections between HIV/AIDS and NCDs is their level of co-occurrence - (Comorbidity and Multimorbidity). This is analysis of individual level co-occurrence of the health problems. This evidence is important in planning and resource allocations. As most health systems in developing countries can’t afford to assign more than a single health care provider (team) to manage a patient with comorbidity and patients in those settings have the right to receive all the healthcare services they need from a single service delivery point, analysis of magnitude of co-occurrence of HIV/AIDS and NCDs is important to design effective strategies that can address the needs of multi-morbid patients.Perspectives, constructs, and methods in the measurement of comorbidity and multimorbidity are detailed elsewhere . In our Key process II: Examine the similarities and differences between responsesStep 4: Examine the similarities and understand the differences between response functionsAfter establishing the need for integrated response through analysis of connections between HIV/AIDS and NCDs, the next step is to identify eligible units for integration by examining similarities and differences between response functions. This step has four sub-steps.How health systems are responding to HIV/AIDS and NCDs? What constitutes a Health system response to HIV/AIDS and NCDs? What are the major processes/functions in a health system response? There are different classifications of the functions of a health system including the WHO Health system framework . Qualitative analysis of the similarities and differences between responses to HIV/AIDS and NCDs revealed four inter-related categories of functions .policy related functions, program related functions, institutional arrangement/coordination/ related functions, and strategic information related functions. Analysis of parallels and differences between the national responses to HIV/AIDS and NCDs yielded a fifth additional category which was labelled as management related functions. The functions under these major categories are shown in the table below.These were specialized and administrative functions get more converged. In the process of integration, these functions/processes are integrated to arrive at an integrated whole.The scope and details of the above functions would vary across the three levels of the health system: Strategic (Macro), Managerial (Meso) and Operational (Micro). When one goes upwards in a health system, programmatic/technical/functions get more Once the functions relevant for integration management are identified, the next step is to assess the relational similarities (and differences) between these functions. The basic question then will be ‘what parameters should be used to assess the similarities between response functions?’ These are the comparators, instruments for comparison. Below is a list of possible comparators. Although all these comparators may not apply to each and every function, the list is believed to include most of the relevant comparators.In a health system response to a HIV/AIDS and NCDs, it is possible for some functions to be more or less integrated than others. Though any set of functions can be assessed for degree of similarity and thus be eligible for integration management, the practice is common for parallel functions . The degree of similarity between response functions can be rated using either a dichotomous or a likert-type scale. Below is a five point likert-type scale for rating two functions using the parameters identified in the above steps. The scores can be summed up to get a single summary score.deliberative approach where a panel of experts, preferably from the concerned functions, deliberate on the similarities and provide an agreed up on score; 2) The investigative approach where an investigator assess the similarity between the functions and give a score based on the findings.Who should rate the similarities? We propose two approaches: 1) The In addition to the degree of similarity, the importance  of the similarities and differences between functions is essential for integration. Finally, the examination of similarities/differences should come up with short list of functions that can undergo the integration process.Key process III: Scan the health system environment for integrationStep 5: Glance over the Health system’s environment for integrationinternal environment – internal to the units to be integrated , the task environment , and the external environment .As integration happens in the real environment, the other major factor that is important for integration is the health system environment, the set of forces surrounding the health system that have the potential to affect the way it operates and its access to scarce resources. These include Acceptability of the level of integration by target users is also important. Other important elements are capacity for integration, external influences of different stakeholders on integration and the impacts of integration on important stakeholders.Among the prominent system factors in the context of developing countries is motivation among policy makers, health managers and providers for integration. Key process IV: Repackage evidence for integrationStep 6: Repackage and share evidence in a usable formsystem level and service level are different  integration, vertical  integration, horizontal (same level) integration, functional integration, clinical integration, and physician integration. In general, repackaging of integration related evidence should consider the audience, the content, the purpose and the method of communication.Key process V: Manage integrationStep 7: Ascertain the plan of integrationLevels of integration can be considered as parts of a continuum. There are several models of levels of integration that are developed based on health service integration . It is pPlan of integration that describes the components of responses are going to be integrated, the existing and the desired level of integration, the strategies to be used, the resource requirements, and the benefits and the risks of the integration. This will serve as a roadmap for the overall integration process. Assessment of local and global experiences and best practices relevant to the integration is essential. Communication and coordination (e.g. through consultative meetings with relevant stakeholders) is very crucial at this stage. Measurable objectives should be developed and agreed up on. Contextual factors, like personal preferences and urgency of the problem and interests of the various stakeholders involved may affect the planning and implementation integration. The required level of system integration will also depend on the type of interdependence  in the structure of the systems Gestational Diabetes screening in to HIV treatment/PMTCT HIV/AIDS, Diabetes, and Hypertension services in to a chronic disease clinic Leveraging HIV programs to support diabetes services Integrating smoking cessation in to HIV care -Integrating HIV/AIDS and Alcohol The selection of approach of integration depends of local contexts. For instance, policy integration of HIV/AIDS and NCDs can be realized in terms of one policy governing both HIV/AIDS and NCDs or a special policy guiding the integration of HIV/AIDS and NCD responses. Policy statements that support the integration of HIV/AIDS and NCD responses could also be included in both HIV/AIDS and NCD policy documents. Such policies/strategies could guide integration at program, management and information levels.Step 8: Translate the plan to actionThe action fields for Health system response are identified as policy response, programmatic response, institutional mechanism, and strategic information. The integration strategies to be used can vary based on both the action field and the desired level of integration. The common system level strategies in the implementation of health system integration include patient engagement and participation, well-developed performance management system, well-functioning information system, cohesive organizational culture, relationship development, right sizing and controlled growth, and sound financial management. The level, type and combination of strategies required are highly contextual and have to be geared towards better outcomes. System level integration may begin at any level. But it must extend to all other levels. Integration between two functions could be at the development of a plan, implementation of activities and at Monitoring and Evaluation of a program.Successful implementation of integration requires time, sufficient resources and a defined, multi-model intervention. A formal Strategic plan with measurable objectives, time lines, responsibilities, and outcomes is essential. Structural changes and resource sharing along with sufficient attention to relationships are required at all levels of a system. Flexibility of leadership is essential to adapt to the changes. Development and execution of strategies is progressive. Never expect to “finish” the integration – Integration is an on-going process .specialization barriers and political barriers. In contrast, mechanisms that facilitate the implementation of integration include standardization , direct supervision, coordinated planning, and mutual adjustment. The suitability of the mechanism of integration depends on task complexity and task interdependence  often refers to configuration. Integrated policies, integrated programs, integrated management, integrated organizational structures and integrated monitoring and evaluation systems are the outputs of strategic level integration. The changes in configurations are expected to reduce complexity but may increase connections. Configurations in most models of degree of integration consider a continuum extending from full segregation through a number of intermediate forms to full integration  and the achievement of the goals of integration (effectiveness). The change in performance of a system that could be attributed to the integration process is the effect of the integration. Accordingly, integration effectiveness can be measured at community, integration/network and organization levels  and allocative efficiency  (outcome) .Balanced Score Card (BSC). BSC is appropriate to evaluate both the implementation and impact of integration (clinical microsystem assessment tool (scale of functional integration which is validated for several forms of integration (The widely used measurement tool for integration is the egration . The secent tool . This toegration .Developing countries are facing a double-burden of HIV/AIDS and Noncommunicable diseases. As the intersection between HIV/AIDS and NCDs is significantly high, an integrated response can maximize synergy and improve efficiency of the responses. The need for integrated response is therefore clear.Integration is an iterative, dynamic and complex process. Using synthesis of evidence from various fields, we have developed an action model that could guide the integration of health system responses to HIV/AIDS and NCDs in developing countries. The model has 5 underpinning principles, 5 key processes and 9 steps. It could serve as a step-wise framework for systematic integration of health system responses to HIV/AIDS and NCDs in the context of developing countries. Although this model is prepared as an action cycle, users may use the steps out of sequence, as appropriate, depending on their context. The model can be a good basis for the development tools that could be used to operationalize the different steps stated in this model.This model is developed based on synthesis of best available evidence about integration of responses to HIV/AIDS and NCDs. The principles and the steps developed in this action model could be adapted to other disease conditions in similar contexts. This action model is conceptually enriched through a review of literature from different disciplines. However, it hasn’t yet been empirically tested. Besides, the steps in this model are stated as general guiding statement and are not operationalized in to specific tasks and activities.Therefore, we propose that future empirical work is needed to refine the validity and applicability the model. The model should also be translated in to tools that facilitate its application to meet the intended purpose. Further research work is also needed to refine this model.


We report a case of a 33-year-old man who presented with immunoglobulin (Ig)G4-related disease (IgG4-RD) forming a pseudotumor in the left paratesticular region during oral administration of corticosteroid for Wells syndrome, which involves cellulitis with eosinophilia.The patient was introduced to our institution from a private hospital with a 3-month history of asymptomatic left scrotal mass. A 5-cm diameter nodule was palpable in the left scrotum. Tumor lesion in the left paratestis involving the epididymis and spermatic cord was observed on computed tomography and magnetic resonance imaging. Blood testing showed no abnormalities other than a minimal increase in C-reactive protein levels. Urine examination likewise revealed no significant findings. Left radical orchidectomy was performed under a diagnosis of left paratesticular neoplasm suspected as malignant tumor. The tumor was pathologically identified as IgG4-RD of the left paratestis involving the epididymis and spermatic cord.We present a first description of IgG4-RD in a patient with Wells syndrome and the ninth case of IgG4-RD in a scrotal organ, and discuss this very rare entity with reference to the literature.http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_225The virtual slide(s) for this article can be found here:  Immunoglobulin (Ig)G4-related disease (IgG4-RD) is a recently defined, emerging clinical entity characterized by diffuse fibrosis or mass-forming pseudotumor with infiltration of IgG4-positive plasma cells . IgG4-RDWells syndrome is a rare dermatosis, also known as eosinophilic cellulitis, characterized by recurrent inflammatory dermatosis with erythematous plaques . We presContrast-enhanced computed tomography (CT) of the left scrotum revealed a 31 × 28-mm diameter left epididymal mass showing irregular contrast and poorly defined margins. Magnetic resonance imaging (MRI) of the left scrotum revealed a hypointense mass in the left epididymis on T1- and T2-weighted imaging. Part of the capsule of the left testis showing as a low-intensity layer was poorly marginated on T2 imaging. On diffusion-weighted imaging, the mass showed some high signals . Histopathology of the tumor demonstrated spindle-shaped epithelial and polygonal cell proliferations with storiform fibrosis. Little atypia and few mitoses were identified among spindle-shaped epithelial cells. Plasmacytes, lymphocytes and eosinophils had infiltrated into the tumor. Typical obstructive phlebitis was also observed. Positive immunostaining was obtained for vimentin, α-smooth muscle actin (αSMA) and desmin , but negative results were seen for CD34, S100 protein, p53, anaplastic lymphoma kinase (ALK), cytokeratin (CAM5.2), calretinin, Wilms’ tumor-1, thrombomodulin, epithelial membrane antigen and lymphatic endothelial marker in the spindle cells, identifying the myofibroblastic cells. IgG4-positive cells comprised 50% among the cells staining positively for IgG, and the number of IgG4-positive plasma cells/high-power fields (HPF) were more than 10  in the left lung on FDG-positron emission tomography/CT (FDG-PET/CT)  clinical examination showing characteristic diffuse/localized swelling or masses in single or multiple organs; 2) hematological examination showing elevated serum IgG4 concentrations (>135 mg/dl); and 3) histopathological examination showing marked lymphocyte and plasmacyte infiltration and fibrosis, and infiltration of IgG4-positive plasma cells (ratio of IgG4-positive/IgG-positive cells >40% and >10 IgG4-positive plasma cells/HPF) . The preVarious differential diagnoses show inflammation-related tumors involving true or pseudo-neoplasia. Inflammatory pseudotumor related to microbial infection, trauma or postoperative status must be diagnosed by excluding other possibilities. In the present case, histopathological findings of less mitotic myofibroblastic proliferation with storiform and swirling fibrosis, lymphoplasmacytic infiltration, obliterative phlebitis and an abundance of IgG4-positive cells met the criteria allowing final diagnosis of pseudotumor associated with IgG4-RD. Immunomarkers offered additional definitive and exclusive diagnosis of IgG4-RD. In the present case, the differential diagnosis should have included inflammatory myofibroblastic tumor (IMT), a typical neoplastic entity with positive immunostaining of ALK. Staining for vimentin and αSMA was diffusely positive and desmin was focally positive, but negative results were seen for CD34, S100 protein, p53 and ALK in the present case, indicating myoepithelial cell proliferation and excluding neoplasias such as IMT. However, consideration should be given to the fact that cases of scrotal IMT have been reported to often show negative immunostaining for ALK [ for ALK .but not positive immunostaining with anti-IgG4 antibody in the present case. A common immune-etiology of Wells syndrome and IgG4-RD were still controversial.Wells syndrome is an uncommon inflammatory dermatosis, first described in 1971 by Wells. Clinical appearance is variable, combined with the histopathological presence of eosinophilic infiltrates and flame figures in the absence of vasculitis, and a relapsing remitting course is usually seen. The present case was diagnosed as Wells syndrome based on systemic cellulitis combined with histopathological presence of eosinophilic infiltration of the skin 6 years earlier. A case with hypereosinophilic syndrome was reported with overlapping IgG4-RD in 2012. The author implied that hypereosinophilic syndrome interacted with IgG4-RD . In WellIn the literature, not all patients could be diagnosed preoperatively because of the lack of characteristic findings for scrotal IgG4-RD. Our patient also underwent radical orchidectomy, even though CT, MRI and biological testing were performed. Orchidectomy should be avoided for pseudotumor associated with IgG4-RD and pharmacotherapy such as corticosteroid and immunosuppressive agents should be applied instead.The paratestis is a clinically rare region for IgG4-RD. We have reported a case of IgG4-RD of the paratestis in a patient treated with corticosteroid for Wells syndrome, a systemic eosinophilic disease.Written informed consent was obtained from the patient for publication of this Case report and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.


The optimal duration of antibiotic treatment in critically ill patients remains a subject of debate. In our multidisciplinary ICU, a short course of antibiotic monotherapy (5 to 7 days) is generally used as a strategy to treat bacteraemia, unless specifically indicated otherwise . We aimed to determine the impact of this strategy on antibiotic resistance patterns and patient outcomes compared with a similar exercise we conducted in 2000 .We conducted a retrospective study of all patients with bacteraemia or fungaemia  treated in our university hospital ICU over a 6-month period (December 2012 to May 2013). We compared this against data from blood culture-positive patients admitted between February and July 2000. Information was collected on bacteraemia episodes, causative pathogens, antimicrobial resistance patterns, antibiotic use and duration, and patient outcomes. Notably, our ICU admits many immunosuppressed patients .Staphylococcus aureus (MRSA)  Figure . The numA strategy of short-course antibiotic monotherapy is associated with low breakthrough and relapse rates and a low rate of antibiotic resistance.


The main objective of this study is to evaluate the workability of fresh portland cement concrete while it is still in the mixing truck by determining fundamental rheological parameters (plastic viscosity and yield stress). Nine concrete mixtures with different values of yield stress and plastic viscosity were tested in a concrete truck. The measurements made with the truck were based on the typical method of determining the flow behavior in a traditional fluid rheometer; that is, the shear rate in the mixing truck was swept from high to low by varying the rotation speed of the drum. The results of these experiments are discussed and compared with data provided by the ICAR rheometer, a portable rheometer designed for measuring concrete rheology. The test results indicate that the mixing truck equipment is sufficiently sensitive to detect differences in yield stress, slump, and plastic viscosity. However, the plastic viscosity determined by the truck measurement did not correlate with plastic viscosity as measured by the ICAR rheometer, while the yield stress determined by the truck measurement did correlate well with the measured slump and the ICAR rheometer resultsSuggestions are given on how to improve the mixing truck for better use as a rheometer. The use of highly fluid concretes, the rheology of which cannot be suitably characterized with the slump test  was a polycarboxylate-based admixture with a specific gravity of 1.1. A viscosity modifying admixture was also used.Two distinct control mixtures of concrete—with the same types of materials but with different proportions—were used in the experimental program. As summarized in To transform a truck mixer into a rheometer requires that at least two entities be measured: the rotational speed of the drum and the power consumption or torque used by the mixer motor during rotation. To obtain both the yield stress and the viscosity it is necessary to obtain data at several speeds. The methodology proposed here requires the measurement of the power during mixing, the load volume, the mass of concrete, and the shear rate in the concrete, which is deduced from the drum rotational speed and geometrical characteristics.The values of these two variables (power and shear rate) at different speeds may be plotted against each other. The slope of this resulting curve according to the Bingham model will give the plastic viscosity and the intercept at zero shear rate will give the yield stress. The concrete truck mixer used  was fitt3, with a drum radius, R, of 1.20 m. The maximum drum speed, n, was 1.74 rad/s (16.66 rpm or 0.278 rps). These data were provided without uncertainty information by the manufacturer of the truck. The tangential velocity of concrete in the drum during mixing , versus rotation speed, N (rad/s):For each concrete mixture, the ICAR rheometer was used to perform a stress growth test and to measure a flow curve. In the stress growth test, the vane was rotated at a constant speed of 0.16 rad/s (0.025 rps) while the torque was measured. The peak torque was recorded as an approximation of the yield stress as discussed in Ref. ,16,17. AY(N·m), and the slope, V(N·m·s), of this line were considered to be related to yield stress and plastic viscosity, respectively. Due to the geometry of this rheometer, it is not possible to determine the shear rate analytically in fundamental units [The intercept, al units .The concrete was placed in a 410 mm diameter container and filled to a height of 390 mm, as shown in The truck with an empty drum was tested initially by measuring the oil pressure versus the rotation speed. This procedure, which was done only once, is shown in The concrete was mixed in the central plant mixer for 10 min and then transferred to the concrete truck mixer. For the first set of tests (C10 to C14), the truck was filled to 50 % of its maximum capacity, and then more concrete was added on top for the second set (C20 to C23) to reach 100 % of its maximum capacity. The purpose of this sequence was to determine the influence of the load on the results. Since the concrete was setting and therefore the second series was quite different from the first, it was not possible to really detect the influence of load volume on the results.After loading, the truck was moved to the laboratory location: therefore, the first laboratory test on the concrete began 30 min after the first contact of water and cement. The truck drum turned about 100 revolutions during the transport of the concrete between the central plant and the laboratory. For each mixture, a small volume of concrete was discharged from the truck for testing with the ICAR rheometer and the slump test. These tests were conducted concurrently with the measurements from the truck. The temperature of the concrete was also recorded.After a set of measurements, the concrete was modified by incorporating an admixture or adding water see . The conTo use the truck as a rheometer, the highest speed of the drum (1.74 rad/s or 16.66 rpm) was maintained for 10 revolutions while the oil pressure was recorded. The speed of the drum was then reduced in increments of 0.21 rad/s (2 rpm). The oil pressure and speed were recorded at each increment of speed. These measurements produced the curve of oil pressure (related to the torque) vs. rotational speed used to calculate the yield stress and plastic viscosity.The fresh concrete measurements are summarized in R2 value of 0.965 for the nine flow curves. Typical stress growth test plots of torque versus time from the ICAR rheometer are shown in In general, the linear fit of the data for the ICAR rheometer is excellent, as indicated by an average In In the second series of mixtures, the addition of the first dosage of HRWRA resulted in a decrease in viscosity as recorded by both the truck and ICAR rheometer. Like the first series, the magnitude of the decrease in relative viscosity was greater for the ICAR rheometer than for the truck measurement. For the final two mixtures, the setting of the concrete began to dominate the rheology. The addition of a second dosage of HRWRA for mix C22 resulted in an increase in viscosity as measured by the ICAR rheometer, while the truck rheometer recorded a value of viscosity that was essentially the same as mix C21. Finally, the addition of water for mix C23 resulted in a decrease in viscosity as recorded by both the truck and the ICAR rheometer.In addition to the flow curve measurements indicated above, a second flow curve was measured with the ICAR rheometer over a lower range of rotation speeds (from 3.1 rad/s to 0.31 rad/s). The concrete sample was remixed by hand between each flow curve measurement; therefore, the second flow curve was measured approximately 3 min to 4 min after the first flow curve. In the first measurements (C10 to C14), the second series of flow curve points simply extended the original flow curve closer to the origin. However, as the day progressed and the concrete began to set, torque readings at low rotation speeds suggested a negative slope of the curve at low shear rates, as illustrated in The correlations between the ICAR rheometer and truck measurements for the viscosity values are shown in The relative variations in yield stress as recorded from the truck measurements, ICAR rheometer, and the slump test are shown in Based on the limited investigation (only one day of testing) of the feasibility of measuring rheological properties directly in a mixing truck without any modifications, it was determined that the mixing truck can be used as a tool to obtain flow curves of the mixed material, with the same procedure used with a concrete rheometer, and that the flow curves measured by the mixing truck were sensitive to changes in yield stress and plastic viscosity.The comparison of the yield stress measured with the slump test, the ICAR rheometer, and the mixing truck showed a good correlation between the values measured. On the other hand, the plastic viscosity measured by the truck or the ICAR rheometer did not show a high correlation. The results of the ICAR rheometer measurements appeared to be more realistic than the truck measurements for changes in plastic viscosity due to addition of admixtures or water. This situation could be attributed to various factors. For instance, the truck measurements had several sources of uncertainty in the precision of the measurements of the drum rotation speed and torque. A more precise gauge for the torque is essential, as it is probably the largest source of uncertainty. An automated speed measurement would also be desirable, although it is probably not a major source of error in this study. Calibration methods are needed to obtain the results in fundamental units and to better compare the test results with other rheometers. A more accurate knowledge of the drum geometry might also lead to the calculation of the rheological parameters in fundamental units.In summary, this preliminary study showed the feasibility of measuring the slope and intercept of the torque vs. speed plot from a mixing truck drum as a means of determining concrete workability. The yield stress measured with this method correlated well with the results of the slump test and the ICAR rheometer. More extensive studies are needed for a reliable measurement of the viscosity.