The spectra for the same samples before gold deposition are also shown for comparison purposes. The spectra are divided this website in the AZD5153 research buy UV-visible region (left) and in the near-IR region (right) to improve the visibility of the oscillations, as their frequency is higher in the UV-visible region. With the deposition of gold, the FI of the samples increases significantly while the number of oscillations remains constant and only a small blue shift of the

oscillations can be realized. The increase in FI is due to the increase in refractive index contrast between the NAA film and the deposited gold layer. However, for increasing NAA film porosity, the FI of the gold-coated samples decreases in the same way as it happened for the as-produced samples. Another remarkable feature of the spectra in the UV-visible range is that the maximum measured reflectance decreases for increasing t PW. In this region, gold has its Rabusertib concentration stronger absorption at 500 nm, making the reflectivity of light decrease [26]. This decrease is stronger for the samples with 20 nm of deposited gold. Figure 3 Reflectance spectra of samples with different t PW before gold deposition and after sputtering 10- and 20-nm

gold on NAA. Solid black line represents samples without gold. Dashed blue line represents samples with 10 nm sputtered gold. Red symbols joined with red lines represent samples with 20 nm of gold. Plots on the left correspond to the UV–vis spectral region, while plots on the right correspond to the near-IR spectral region. (a, b) t PW = 0 min, (c, d) t PW = 6 min,

(e, f) t PW = 12 min, and (g, h) t PW = 18 min. In the near-IR range, the spectra show bigger differences: the reflectance for the samples with 10 nm of gold show Orotidine 5′-phosphate decarboxylase symmetric oscillations with respect to the reflectance minima, while for 20 nm of gold, the oscillations are asymmetric. Furthermore, the position of the minima is clearly blue shifted in the samples with 20 nm of gold with respect to the samples without and with 10 nm of gold. It is important to remark that this asymmetry and blue shift decrease with increasing t PW and that for the two lower porosities (corresponding to t PW = 0 min and t PW = 6 min), this asymmetry results in narrow valleys with small width and a well-defined minimum wavelength that can be useful in the detection of spectral shifts. If the FI between the samples with 10 and 20 nm of deposited gold is compared, it can be concluded that the relation of the FI with the gold thickness is strongly dependent on the porosity of the NAA film: for the lower porosities, the FI for the 10 nm gold-coated samples is bigger, but this trend is reversed as the porosity increases.

Despite an early induction of STX2-transcripts, meropenem does not enhance the release of STX from STEC O104:H4. The 4x MIC of meropenem even decreases STX titers and activity in supernatants of O104:H4. Since after i.v.

application of meropenem peak concentrations in the relevant tissues are reached within about 1 h [13], the observed moderate induction of STX2-transcripts should not be clinically relevant. Indeed, our data suggest that meropenem is safe for the treatment of STEC O104:H4. Similarly, ciprofloxacin at concentrations equal to or beyond 4x MIC reduces the release of STX2 by STEC O104:H4 below that of untreated controls and therefore should be a safe therapeutic option against this STEC strain. These conclusions are of clinical relevance because with standard doses of either meropenem selleck products [13] or ciprofloxacin [12] concentrations far beyond the 4x MIC are achieved in humans within 1 h. The antibiotics fosfomycin, gentamicin and chloramphenicol also appear to be suited to treat patients infected with STEC O104:H4 without increasing the release of STX. This means that there are several well-established antibiotics at hand for the treatment of infections with STEC O104:H4. Since inhibitory concentrations of these antibiotics can be achieved in patients rapidly,

treatment with these substances would greatly diminish the number of, if not eradicate the bacteria and thereby prevent the sustained production and release of STX. Previous recommendations to refrain from antibiotic treatment of STEC were not Batimastat cost only deduced from in vitro data [3, 4]. They were also drawn from clinical observations of more frequent and more severe symptoms of STEC infection up to increased frequencies of fatalities after treatment with antibiotics (reviewed in [2]). However, those in vitro as well as in vivo studies have to be interpreted cautiously

with regard to the specific experimental conditions or to the particular STEC outbreaks. Some in vitro studies addressed the response of STEC only to subinhibitory concentrations of antibiotics [3, 4]. A find more rationale for this may have been the consideration that in the beginning of antibiotic therapy, the STEC may be exposed to such low concentrations of antibiotics. However, after application of standard antibiotic doses to humans, rapid achievement of high tissue concentrations within 1 h has been reported e.g. for ciprofloxacin Carnitine palmitoyltransferase II [12] or for meropenem [13] more than 20 or 10 years ago, respectively. Published clinical studies are mostly retrospective studies rather than well-controlled, blinded studies which is due to the unexpected outbreaks of STEC. As a consequence, they allow only correlative conclusions rather than revealing causative mechanisms. One carefully designed prospective study [14] suffered from its small sample size as reported in a recent metaanalysis [15]. Other clinical studies have individual limitations depending on the specific conditions of the respective outbreaks.

Lung Cancer 2006, 52:155–163.PubMedCrossRef 20. Belani CP, Waterhouse H, Ghazal H, et al.: Phase III study of maintenance gemcitabine (G) and best supportive care (BSC) versus BSC, following standard combination therapy with gemcitabine-carboplatin (G-Cb) for patients with advanced non-small cell lung cancer Linsitinib (NSCLC). J Clin Oncol 2010,28(15s):abstr 7506. 21. Perol M, Chouaid C, Milleron J, et al.: Maintenance with either gemcitabine or erlotinib versus observation with predefined second-line treatment after cisplatin-gemcitabine induction chemotherapy

in advanced NSCLC: IFCT-GFPC 0502 phase III study. J Clin Oncol 2010,28(15s):abstr 7507. 22. Belani CP, Barstis J, Perry MC, La Rocca RV, Nattam SR, Rinaldi D, Clark R, Mills GM: Multicenter, randomized trial for stage IIIB or IV non small cell lung cancer using weekly paclitaxel or observation. J Clin Oncol 2003, 21:2933–2939.PubMedCrossRef 23. Goldie JH, Coldman AJ: A mathematic model for relating the drug sensitivity of tumours to their spontaneous mutation rate. Cancer Treat Rep 1979, 63:1727–17233.PubMed 24. Coate LE, Shepherd FA: Maintenance therapy in advanced

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A: Randomized study of maintenance vinorelbine in responders with advanced PD0332991 cell line non-small cell lung cancer. J Natl Cancer Inst 2005, 97:499–506.PubMedCrossRef 26. Fidias PM, Dakhil SR, Lyss AP, Loesch DM, Waterhouse DM, Bromund JL, Chen R, Kazmierski MH, Treat J, Obasaju CK, Marciniak M, Gill J, Schiller JH: Phase III study of immediate versus delayed docetaxel after front line therapy with gemcitabine plus carboplatin in advanced non-small cell lung cancer. J Clin Oncol 2009, 27:591–8.PubMedCrossRef 27. Ciuleanu T, Brodowicz T, Zielinski C Kim JH, Krzakowski M, Laack E, Wu YL, Bover I, Begbie S, Tzekova V, Cucevic B, Pereira J, Yang SH, Madhavan J, Sugarman KP, Peterson P, John WJ, Tariquidar mw Krejcy K, Belani CP: Maintenance pemetrexed plus best supportive care vesus placebo plus best supportive care for non-small cell lung cancer: a randomized double-blind, phase III study. Lancet 2009, 374:1432–4.PubMedCrossRef 28. Scagliotti GV, Hanna N, Fossella F, Sugarman K, Blatter J, Peterson P, Simms L, Shepherd FA: The differential efficacy of pemetrexed according to NSCLC histology, a review of two phase III studies. Oncologist 2009, 14:253–63.PubMedCrossRef 29.

When assaying for competence related phenotypes in the two other biofilm models, the effects of quorum sensing were different. The second microtiter biofilm model, more frequently used in pneumococcal research, relies on incubation of high numbers of stationary-phase cells

[24]. In this model, the addition of synthetic CSP was not a necessary, however strains unable to synthesize or sense CSP were found to attach to a lower extent the surface compared to the wt. By microscopic analysis we verified that this phenotype was not due to a reduction in the number of single NCT-501 manufacturer attached Trichostatin A molecular weight cells, but it was due to a reduction in number and size of surface attached microbial aggregates. Microcolony formation, already described as an important phenotype in pneumococcal biofilm [7, 15, 24], could be restored in comC mutant strains by addition of synthetic CSP to levels similar to wt strains. The fact that none of the well known genes directly or indirectly regulated by competence has a direct link to attachment of biofilm underlines that effects seen in planktonic exponentially

growing competent cells differ from the biofilm stabilisation phenotype seen here [36]. There DNA Damage inhibitor are parallelisms between our findings and recent work in S. mutans where biofilm formation was also linked to the ComCDE system [37], although if genomic and genetic data indicate that the S. mutans ComDE is orthologous to the S.

pneumoniae BlpRH system and does not directly control transformation [33, 38]. Competence quorum sensing defects in S. mutans were found to determine reduction in biofilm biomass, and addition of CSP partially restored wt biofilm architecture [39]. aminophylline In contrast to S. pneumoniae these ComCD-dependent phenotypes were correlated to the initial stages of biofilm development [39]. Biofilm microcolonies are examples of non-homogeneous microbial populations. In this context, our data indicate a significant effect of the competence quorum sensing system on the capacity of pneumococci to form these aggregates. Such aggregation behaviour in a non-homogeneous population is consistent with the observed clumping in a mixture of competent and non-competent cells which depends on the release of DNA into the medium [40, 41]. Correlation of competence, cell clumping and DNA release fit well with the presence of DNA in the extracellular matrix of attached pneumococci and to subsequent sensitivity of pneumococcal biofilm to DNAse [23, 24]. The release of DNA into the extracellular matrix through the endogenous CSP pathway has also been described to have a significant impact on biofilm biomass in S. mutans [42]. We lack a precise molecular characterisation of the events and we cannot exclude that some of the effects may be indirect and determined through an unknown regulatory pathway.

PubMedCrossRef 29. Riedl SJ, Shi Y: Molecular mechanisms of caspase regulation during apoptosis. Nature Review:Molecular Cell Biology 2004, 5: 897–907.CrossRef 30. Pommier Y, Sordet O, Antony S, Haywrd RL, Kohn KW: Apoptosis Eltanexor purchase defects and chemotherapy resistance: molecular interaction maps and networks. Oncogene 2004, 23: 2934–2949.PubMedCrossRef 31. Malik F, Kumar A, Bhushan S, Khan S, Bhatia A, Suri KA, Qazi GN, Bafilomycin A1 cell line Singh J: Reactive oxygen species generation and mitochondrial dysfunction in the apoptoticcell death of human myeloid leukemia HL-60 cells by a dietary compoundwithaferin A with concomitant protection

by N-acetyl-cysteine. Apoptosis 2008, 12: 2115–2133.CrossRef 32. Johnstone RW, Ruefli AA, Lowe SW: Apoptosis: A link between cancer genetics and chemotherapy. Cell 2000, 108: 153–164.CrossRef 33. Fridman JS, Lowe SW: Control of apoptosis by p53. Oncogene 2003, 22: 9030–9040.PubMedCrossRef 34. Michalak E, Villunger A, Erlacher M, Strasser A: Death squads enlisted by the tumor suppressor p53. Biochemical and Biophysical Research Communications 2005, 331: 786–798.PubMedCrossRef 35. Takaoka A, Hayakawa S, Yanai H, Stoiber D, Negishi H, Kikuchi H, Sasaki S, Imai K, et al.: Integration of interferon-alpha/beta signalling to p53 responses in tumour suppression signaling pathway and antiviral defence. Nature 2003, 424: 516–23.PubMedCrossRef 36. Pekar O, Molotski N,

Savion S, Fein A, Toder V, Torchinsky A: p53 regulates cyclophosphamide teratogenesis by controlling caspases 3, 8, 9 activation

and NF-κB DNA binding. Reproduction 2007, 134: 379–388.PubMedCrossRef Competing interests The author declares that they have no competing interests.”
“Background Prostate cancer (PC) has become the most prevalent malignant tumour in men in the Western World Axenfeld syndrome and the second leading cause of male cancer-related death. Initially, most tumours present androgen-sensitive carcinomas but the proportion of undifferentiated histology becomes more apparent when correlated to clinical progression and the development of hormone resistance occurrence [1, 2]. The explanation of the conversion of a hormone-sensitive status to a hormone-insensitive one is currently one of the most critical areas of debate in prostate carcinoma. Prostate specific antigen (PSA) is at present the better pre-treatment predictor of the disease and of its outcome after treatment. However, its sensitivity and specificity are not yet sufficient to make it the perfect screening test for prostate cancer. Prostate tumour is composed of a heterogeneous population of cells with different levels of androgen dependency. A decline in serum PSA does not always indicate a cure of cancer, as PSA production is androgen dependent and as a result the dedifferentiation of neoplastic cells gradually lose their capacity to produce PSA. Consequently, serum PSA is less reliable as a tumour marker in patients with high tumour grades and in hormonally treated patients with disseminated disease.

After 30 min, the CO2 flow rate was reduced to 10 mL/min. When equilibrium was reached, the UV light was turned on, and the reaction products were analyzed by means of MI-503 datasheet the GC. Blank tests were also conducted to ensure that the product was due to the photocatalytic reaction. The blank tests consisted of a UV illumination without the photocatalyst and a reaction in the dark with the catalyst. Results and discussion Physicochemical properties of the synthesized materials Table 1 shows the physical and textural properties of the KIT-6 and Ti-KIT-6 materials, which

were obtained by means of N2 sorption. A noticeable decrease can be seen in the surface area and pore volume of KIT-6, after Ti incorporation with different Si/Ti ratios. However, the surface area and pore volume of the Ti-KIT-6 (dried) materials were slightly higher than those of the Ti-KIT-6 (calcined) ones, which might be due to the easy incorporation of Ti in the dried weak structure of KIT-6. However, Ti can be trapped in the bulk of the dried KIT-6 material, but not in that of the rigid structure of the calcined KIT-6 one. The average pore diameter

did not change significantly and remained uniform, which might be due to the 3-D pore structure of KIT-6, which is able to accommodate the uniform isolated Ti dispersion. Table 1 Comparison of the physical properties, bandgap energy of the synthesized materials, and methane production Samples N2sorption UV-vis CH4production comparison S BET PV APD WL BE P Reference VRT752271 cost [Ti-K-6 (dried) (Si/Ti = 200)] calcined 865 1.11 6.55 – - – - [Ti-K-6 (dried) (Si/Ti = 100)] calcined 767 0.80 6.48 – - – - [Ti-K-6 (dried) (Si/Ti = 50)] calcined 730

0.67 6.45 – - – - KIT-6 (K-6) calcined 772 1.04 6.49 – - – - [Ti-K-6 (calcined) (Si/Ti = 200)] calcined 726 0.95 6.45 320 3.87 – - [Ti-K-6 (calcined) (Si/Ti = 100)] calcined 700 0.85 6.40 330 3.75 4.1 This work [Ti-K-6 (calcined) (Si/Ti = 50)] calcined 684 0.73 6.41 372 3.33 – - Anatase TiO2 powder – - – - – 0.4 [18] Aeroxide/degussa P25 TiO2 – - – - – 0.6 This work Titanium silicate (TS-1) zeolite – - – - – 2.7 [16] Ti-MCM-41 – - – - – 2.9 [16] S BET, BET specific surface area in m2/g; PV, cumulative pore volume in cm3/g; APD, average pore diameter in nm; WL, absorption edge wave length, λ, in nm; BE, bandgap energy in eV; P, production rate in μmol · gcat.−1 · h−1). The UV-vis Protirelin spectra of the calcinated Ti-KIT-6 (calcined, Si/Ti = 200, 100, and 50) are shown in Figure 1. It has been observed that with the GLUT inhibitor increased Ti content, the absorption spectra are shifted to higher wavelengths since the absorption edge wavelength changes from 320 to 372 nm (Table 1), that is, moving towards the trend of pure TiO2. Therefore, it can be observed that this increased Ti might also have more chance of making the agglomerates of TiO2 with the moisture present during the synthesis. The bandgap energies of the Ti-KIT-6 materials, corresponding to a bandgap of 3.33 to 3.

In turn, biology has long exploited similar iterative strategies in biochemical synthetic pathways; one this website example is provided by fatty acid biosynthesis [39] (Figure 4). Figure 4 Cascade reaction sequences developed for the synthesis of ‘non-skid-chain like’ polyazamacrocyclic compounds [40] . The synthesis of dendrimers follows

either a divergent or convergent approach Dendrimers can be synthesized by two major approaches. In the divergent approach, used in early periods, the synthesis starts from the core of the dendrimer to which the arms are attached by adding building blocks in an exhaustive and step-wise manner. In the convergent approach, synthesis starts from the exterior, beginning with the molecular structure that ultimately becomes the outermost arm of the final dendrimer. In this strategy, the final generation number is pre-determined, necessitating

the synthesis of branches of a variety of requisite sizes beforehand for each generation [41] (Figure 5). Figure 5 Approaches for the synthesis if dendrimers. (A) Divergent approach: synthesis of radially symmetric polyamidoamine (PAMAM)dendrimers using ammonia as the trivalent core; the generations are added at each synthetic cycle (two steps), leading to an exponential increase in the number of surface functional groups [37]. (B) Convergent approach: synthesis of dendrons or wedges or branches that will become the periphery of AZD1152 chemical structure the dendrimer when coupled to a multivalent core in the last step of the synthesis [13]. Properties of dendrimers When comparing dendrimers with other nanoscale synthetic structures (e.g., traditional polymers, enough buck balls, or carbon nanotubes), these are either highly non-defined or have limited structural diversity. Pharmacokinetic properties Pharmacokinetic properties are one of the most significant aspects that need to be considered for the successful biomedical application of dendrimers, for instance, drug delivery, imaging, photodynamic therapy, and neutron capture therapy. The diversity of potential applications of dendrimers in medicine results

in increasing interest in this area. For example, there are several modifications of dendrimers’ peripheral groups which enable to obtain antibody-dendrimer, peptide-dendrimer conjugates or dendritic boxes that encapsulate guest molecules [42]. Covalent conjugation strategies The strategy of coupling small molecules to polymeric scaffolds by covalent Trichostatin A nmr linkages to improve their pharmacological properties has been under experimental test for over three decades [43–46]. In most cases, however, the conjugated dendritic assembly functions as ‘pro-drug’ where, upon internalization into the target cell, the conjugate must be liberated to activate the drug (Figure 6). Figure 6 Requirements for dendrimer-based, cancer-targeted drug delivery.

From literature [9] and our own experiments, we know that the folded OmpA TM domain does not unfold at all at 50°C. Increasing the temperature further from 50°C to 99°C, the OmpA TM domain unfolds and the intact fusion (HMW band) shifts to its

expected molecular weight of 49 kDa. These results demonstrate that the OmpA TM domain selleckchem remains heat-modifiable and therefore is correctly assembled into the OM when mCherry is fused to its C-terminus. With increasing exposure to heat, the initially faint LMW (degradation) band also increased in intensity, and displays the exact same heat-modifiability behavior as the intact fusion between the OmpA β-barrel and mCherry. Because we know that mCherry does not exhibit heat-modifiability, the degradation band must consist of the OmpA β-barrel with (based on a MW of 28 kDa and assuming C-terminal degradation) the N-terminal part of mCherry (~55 residues), which appears to contain the epitope recognized by the monoclonal antibody. We conclude that cells expressing OmpA-177-SA-1-mCherry contain a mixture of intact fusion assembled

in the OM, and OmpA-177-SA-1 with a C-terminal part of mCherry proteolytically removed. Assuming C-terminal degradation, the removed part then contains the chromophore [30], and therefore this would represent a dark sub-population of OmpA TM domain in the OM. For the full-length OmpA-mCherry fusion (pGI10), we already knew that the full-length OmpA with C -terminal linker, but without mCherry (pGI9), was inserted properly in the OM [10]. Therefore, we only checked that the mCherry fluorescence was AR-13324 clinical trial associated with eFT-508 the PG/OM layer by fluorescence microscopy of plasmolyzed cells (Figure 2) [31]. This was indeed the case. FRAP results on cytoplasmic mCherry To maximize the likelihood of observing OmpA mobility, we avoided the cell poles (poles contain

inert PG and retain some OM proteins [7]) and performed the FRAP experiments in the cylindrical part of elongated cells. To create elongated cells (filaments) we grew the cells in the presence of the antibiotic cephalexin which blocks cell division but allows further elongation [11, 12]. The effect of cephalexin on bacterial cells is well-known: it binds with high affinity to PBP3, interfering with its ability to function in cell division. In addition, it has recently been shown that PBP3 Adenylyl cyclase only interacts with PBP2 (part of the protein complex responsible for elongation) during division at mid-cell [32]. We expect therefore that the structure of the cell wall in filaments will be highly similar to that of normal length cells. We tested our setup by starting with cells expressing cytoplasmic mCherry, which should give a recovery rate similar to that observed for cytoplasmic GFP, for which diffusion constants of 6–9 μm2/s are reported [11, 12]. The average length scale that corresponds with such a diffusion constant is = 2–3 μm when t = 0.5 s.

). Images were analyzed with Fingerprinting II Informatix software (Version 3.0, Bio-Rad). Band matching and cluster analysis was performed using an unweighted pair group method with arithmetic averages (UPGMA) and the Dice coefficient with 1% optimization and tolerance levels. Based on the dendrogram obtained from the cluster analysis, letters were assigned

to designate fla types and numbers were assigned to designate PFGE types. Isolates with > 90% similarity were assigned to the same fla type or PFGE type. Composite cluster analysis including fla typing, PFGE, and antimicrobial resistance testing Pevonedistat datasheet data was performed using the Fingerprinting II Informatix software. The composite dendrogram was determined by UPGMA using the average from

the experiment as a coefficient for similarity and correction for internal weights. Statistical analysis The χ2 test was used to analyze the significance of the difference between ciprofloxacin and erythromycin resistance rates, including C. jejuni compared to C. coli in each plant, and pre chill compared to post chill in plant A. An α of 0.01 was used for statistical significance. The discriminatory ability of fla typing, PFGE, antimicrobial resistance profiling, and composite analysis was calculated using the numerical index of discrimination (D) according to the method of Hunter and Gaston [60]. The discriminatory index represents the probability that two unrelated strains sampled from the test population will be placed into different TGF-beta assay typing groups [60]. Acknowledgements The authors gratefully acknowledge the Staurosporine U.S. RXDX-101 chemical structure Food and Drug Administration for financial and technical assistance. We also thank Curt Doetkott, North Dakota State University (NDSU), for statistical consultation and Dr. Mohamed Fakhr, University of Tulsa, for assistance with data analysis and manuscript review. References 1. Mead PS, Slutsker L, Dietz V, McCaig LF, Bresee JS, Shapiro C, Griffin PM, Tauxe RV: Food-related illness and death in the United States. Emerg Infect Dis 1999, 5:607–625.CrossRefPubMed 2. Butzler JP:Campylobacter , from

obscurity to celebrity. Clin Microbiol Infect 2004, 10:868–876.CrossRefPubMed 3. Allos BM:Campylobacter jejuni infections: update on emerging issues and trends. Clin Infect Dis 2001, 32:1201–1206.CrossRefPubMed 4. Jacobs-Reitsma W:Campylobacter in the food supply. Campylobacter American Society for Microbiology, Washington, D.C 2 Edition (Edited by: Nachamkin I, Blaser MJ). 2000, 467–481. 5. Cox NA, Stern NJ, Craven SE, Berrang ME, Musgrove MT: Prevalence of Campylobacter and Salmonella in the cecal droppings of turkeys during production. J Appl Poult Res 2000, 9:542–545. 6. Luangtongkum T, Morishita TY, Ison AJ, Huang S, McDermott PF, Zhang Q: Effect of conventional and organic production practices on the prevalence and antimicrobial resistance of Campylobacter spp. in poultry.

Standard deviations of on-screen adjusted Sirscan readings were comparable to the manual method (1.3 mm, 1.4 mm, and 1.0 mm, for S. aureus ATCC 29213, E. coli ATCC 25922, and P. aeruginosa ATCC 27853, respectively). The lower standard deviation of fully automated Sirscan readings was pronounced for certain antibiotics (Table 3): E.g. for trimethoprim-sulfamethoxazole and S. aureus ATCC 29213 (0.9 mm

versus 4.7 mm for fully automated Sirscan and manual readings, respectively) or for trimethoprim-sulfamethoxazole Cytoskeletal Signaling and nitrofurantoin in E. coli ATCC 25922 (0.4 and 0.5 mm versus 0.9 and 1.6 mm for fully automated Sirscan and manual readings, respectively). Table 3 Comparison of standard deviations

of measurements with calliper, the Sirscan system KPT-8602 price adaped on-screen by the human eye and the Sirscan fully automated mode S. aureus ATCC 29213                                           TOB AK CN CIP LEV P FOX E DA SXT RA average                 EUCAST QC range 20-26 18-24 19-25 21-27 23-29 12-18 24-30 23-29 23-29 29-32 30-36                     Sirscan fully automated                             INK1197 concentration                   Mean value 23.2 23.4 23.6 27.8 28.1 15.9 25.0 27.8 29.4 29.4 32.7 26.0                       Standard deviation 0.8 0.5 0.8 0.9 1.3 0.3 1.2 0.8 0.7 0.9 1.0 0.8*                   Sirscan on-screen adjusted                                               Mean value 24.7 25.5 25.2 Tryptophan synthase 27.8 29.5 15.8 26.1 30.4 29.9 29.8 33.6 27.1                       Standard deviation 1.2 0.7 1.4 1.7 1 0.4 0.9 2.2 3 1.3 0.7 1.3                   Calliper                                               Mean value 23.4 23.2 23.8 22.7 27.2 17.2 26.1 26.2 26.7 26.2 32.9 25.1                       Standard deviation 1 1.6 1.2 1.1 2 0.6 0.8 1.1 1.2 4.7 2.1 1.6*                   E. coli ATCC 25922                                           TOB AK CN NA NOR CIP LEV AM AMC TPZ CXM CAZ CTX CPD CRO FEP MEM ETP SXT NF average EUCAST QC range 18-26 19-26 19-26 22-28

28-35 30-40 29-37 16-22 18-24 21-27 20-26 23-29 25-31 23-28 29-35 31-37 28-34 29-36 23-29 17-23   Sirscan fully automated                                               Mean value 22.4 20.6 20.4 25.9 28.1 28.4 28.4 20.6 21.8 23.3 24.8 26.0 27.5 24.7 29.3 31.0 29.2 34.0 26.3 17.5 25.5     Standard deviation 1.1 0.8 0.5 0.8 0.6 1.0 0.7 0.9 0.6 0.4 0.4 0.0 0.5 0.5 0.7 0.7 0.9 0.8 0.4 0.5 0.7* Sirscan on-screen adjusted                                               Mean value 23.2 24.5 25.1 25.9 34 37.3 35.4 25.9 23.3 27.6 26.1 27.8 31.1 29.3 32.3 35 35.9 34.3 28.4 24.8 29.4     Standard deviation 1.5 1.3 1.4 1.3 2.4 1.6 1.5 1.8 1 1 1.2 1.2 1.9 1.2 1.3 1 1.2 1.2 1.4 1 1.4 Calliper                                               Mean value 22.4 24.4 23.3 27.6 31.1 34.1 31.5 22.3 25.1 25.7 24.8 25.5 28.5 27.6 30.2 33.7 23.9 34.3 27.3 17.4 27.0     Standard deviation 1.1 2.5 1.2 1.3 1 1.6 1.5 1.2 0.7 1.1 1.2 1 1.5 2.4 1.4 1.4 1.3 2.4 0.9 1.