Am J Pathol 2010, in press. 42. Li F: Every single cell clones from cancer cell lines growing tumors in vivo may not invalidate the cancer stem cell concept. Mol Cells 2009, 27:491–492.PubMedCrossRef 43. Ling X, Bernacki RJ, Brattain MG, Li F: Induction of survivin expression by taxol (paclitaxel) is an early event which is independent on taxol-mediated G2/M arrest. J Biol Chem 2004, 279:15196–15203.PubMedCrossRef

44. Jatoi A, Dakhil SR, Foster NR, Ma C, Rowland KM Jr, Moore DF Jr, Jaslowski AJ, Thomas SP, Hauge MD, Flynn PJ, et al.: Bortezomib, paclitaxel, and carboplatin as a first-line regimen for patients with metastatic esophageal, gastric, and gastroesophageal cancer: phase II results from the North Central Cancer Treatment Group (N044B). J Thorac Oncol 2008, 3:516–520.PubMedCrossRef 45. Chang H, Gao Y, Zhang JY, Shi F, Chen YZ: [Expression of survivin Tipifarnib price and NF-kappaB in peripheral T-cell lymphoma and its significance.]. Zhongguo Shi Yan Xue Ye Xue Za Zhi 2008, 16:1079–1081.PubMed 46. Sato A, Oya M, Ito K, Mizuno R, Horiguchi Y, Umezawa K, Hayakawa M, Murai M: Survivin associates with cell proliferation in renal cancer cells: regulation of survivin expression by insulin-like growth factor-1, interferon-gamma and a novel NF-kappaB inhibitor. Int J Oncol 2006, 28:841–846.PubMed

47. Yang DT, Young KH, Kahl BS, Markovina S, Miyamoto S: Prevalence of bortezomib-resistant constitutive NF-kappaB activity in mantle cell lymphoma. Mol Cancer 2008, 7:40.PubMedCrossRef 48. Liu learn more Q, Hilsenbeck S, Gazitt Y: Arsenic trioxide-induced apoptosis in myeloma cells: p53-dependent G1 or G2/M cell cycle arrest, activation of caspase-8 or caspase-9, and synergy with APO2/TRAIL. Blood 2003, 101:4078–4087.PubMedCrossRef 49. Ooi MG, Hayden PJ, Kotoula V, McMillin DW, Charalambous Olopatadine E, Daskalaki E, Raje NS, Munshi NC, Chauhan D, Hideshima T,

et al.: Interactions of the Hdm2/p53 and proteasome pathways may enhance the antitumor activity of bortezomib. Clin Cancer Res 2009, 15:7153–7160.PubMedCrossRef 50. Hurt EM, Thomas SB, Peng B, Farrar WL: Reversal of p53 epigenetic silencing in multiple myeloma permits apoptosis by a p53 activator. Cancer Biol Ther 2006, 5:1154–1160.PubMed Competing interests The authors declare that they have no competing interests. Authors’ contributions XL carried out the experimental design, performed most of the experiments and organized data for manuscript. DC performed the rest of experiments and involved in results discussion and organization. AAC initiated bortezomib-related projects in our institute, helped experimental design and revised the manuscript. FL initiated the project, participated in experimental design and wrote the manuscript. All authors read and approved the final manuscript.

In the block light experiment, F m values were highest after the light treatment. Therefore, the maximal F m , which was reached at the end of the dark

phase following the block light treatment, was used for NPQ calculations (Fig. 2). For the purpose of this article, block light treatment is referring LGK-974 to a dark to light transition, where the PF is constant during the light phase. Because F m in the dark was lower than at low PF (Fig. 3), NPQ calculations were based on maximal fluorescence measured during the light experiments using consecutive increasing PF. This coincided with F m ′ during lowest PF treatment (Fig. 3). Fig. 2 Representative fluorescence parameters measured by FRRF during a dark to light transition using a single irradiance intensity (‘block light treatment’) and darkness. a F′, F m ′ on the primary ordinate,

and NPQ on the secondary Y-axis; b σPSII (Sigma PSII) and maximal quantum yields as well as effective quantum yields during the irradiance treatment. The upward arrow indicates the start of the light period using a photon flux of 440 μmol photons m−2 s−1 (approx. 4 × growth light intensity) after dark incubation (1–2 h). The downward arrow indicates the end of the light treatment. An addition of 160 μM dissolved inorganic carbon aimed for detection of nutrient depletion (double arrowhead), which should not have occurred due to low cell densities in this experiment. Results were confirmed in two independent experiments Akt inhibitor Fig. 3 Representative fluorescence parameters measured by FRRF during consecutive increasing photon flux treatments (dark–light transient and following increases in photon flux, indicated by upward arrows) and darkness (downward arrow). a F′, F m ′ on the primary ordinate, and NPQ on the secondary Y-axis; b σPSII (Sigma PSII) and maximal quantum yields as well as effective quantum yield during the irradiance treatment. Photon fluxes were 50, 200, 340 and 470 μmol photons m−2 s−1. Results were confirmed in two independent experiments

77 K fluorescence and measurements in the presence of CCCP Cells were cultured in 500-ml conical glass flasks with a minimum of 200-ml head space at Obatoclax Mesylate (GX15-070) a constant PF of 100 μmol photons m−2 s−1 (Cool White light, Silvania fluorescent tubes) and a temperature of 18°C. Cells from the log-phase were harvested for the experiments. After washing in fresh F/2 pH 8.2 medium, cells were concentrated to a final density of 1 × 107 cells/ml and dark incubated for 1 h prior to exposure to a saturating PF (660 μmol photons m−2 s−1; measured using a spherical (4π) light sensor). This was carried out in an open chamber (8-ml cylindrical Perspex Rod Oxygraph, Hansatech, UK) to allow gas exchange while the sample was stirred.

University of Florida IFAS Economic Information Report 01–2 2001, 1–14. 10. Chung KR, Brlansky RH: Citrus diseases exotic to Florida: huanglongbing Erlotinib (citrus greening). [http://​edis.​ifas.​ufl.​edu] Plant Pathology Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida 2009. PP-201 11. Duan Y, Zhou L, Hall DG, Li W, Doddapaneni H, Lin H, Liu L, Vahling CM, Gabriel DW, Williams KP, et al.: Complete genome sequence of citrus huanglongbing bacterium, ‘ Candidatus Liberibacter asiaticus’ Obtained Through Metagenomics. Mol Plant Microbe In 2009,22(8):1011–1020.CrossRef 12. Nelson AJ, Elias KS, Arévalo GE, Darlington LC, Bailey BA:

Genetic characterization by RAPD analysis of isolates of Fusarium oxysporum f. sp. erythroxyli associated with an emerging epidemic in Peru. Phytopathology 1997,87(12):1220–1225.PubMedCrossRef 13. Wickert E, Machado MA, Lemos EGM: Evaluation of the genetic diversity of Xylella fastidiosa strains from citrus and coffee hosts by single-nucleotide polymorphism markers. Phytopathology 2007,97(12):1543–1549.PubMedCrossRef 14. Yuan X, Morano L, Bromley R, Spring-Pearson S, Stouthamer R, Nunney L: Multilocus sequence

typing of Xylella fastidiosa causing Pierce’s disease and oleander leaf scorch in the United States. Phytopathology 2010,100(6):601–611.PubMedCrossRef 15. Coletta-Filho HD, Bittleston LS, Almeida RPP: Spatial genetic structure of a vector-borne generalist pathogen. enough Appl Environ Microb 2011,77(8):2596–2601.CrossRef Selleckchem PD332991 16. Byrnes EJ III, Li W, Lewit Y, Ma H, Voelz K, Ren P, Carter DA, Chaturvedi V, Bildfell RJ, May RC, et al.: Emergence and pathogenicity of highly virulent Cryptococcus gatti genotypes in the Northwest United States. PLoS Pathog 2010,6(4):e1000850.PubMedCrossRef 17. Tomimura K, Miyata S, Furuya N, Kubota K, Okuda M, Subandiyah S, Hung TH, Su HJ, Iwanami T: Evaluation of genetic diversity among ‘ Candidatus

Liberibacter asiaticus’ isolates collected in Southeast Asia. Phytopathology 2009,99(9):1062–1069.PubMedCrossRef 18. Adkar-Purushothama CR, Quaglino F, Casati P, Ramanayaka JG, Bianco PA: Genetic diversity among ‘ Candidatus Liberibacter asiaticus’ isolates based on single nucleotide polymorphisms in 16S rRNA and ribosomal protein genes. Ann Microbiol 2009,59(4):681–688.CrossRef 19. Liu R, Zhang P, Pu X, Xing X, Chen J, Deng X: Analysis of a prophage gene frequency revealed population variation of ‘ Candidatus Liberibacter asiaticus’ from two citrus-growing provinces in China. Plant Dis 2011, 95:431–435.CrossRef 20. Katoh H, Subandiyah S, Tomimura K, Okuda M, Su HJ, Iwanami T: Differentiation of “” Candidatus Liberibacter asiaticus”" isolates by variable-number tandem-repeat analysis. Appl Environ Microbiol 2011,77(5):1910–1917.PubMedCrossRef 21.

Fair: Evidence is sufficient to determine effects on outcomes, but the strength of the evidence is limited by the number, quality or consistency of the individual studies, i.e. studies that did not meet the criteria for either good or poor and met some but not all quality criteria. Poor: Evidence is insufficient to assess the effects on outcomes because of limited number or power of studies,

important flaws in their design or conduct, gaps in the chain of evidence or lack of information. Criteria were: a retrospective study, study duration of less than 1 year, not population based, inadequate definition of fracture and abstract only available or no definition of ethnicities provided where relevant. Where assessment find more was not possible, the study was discarded. Selection criteria From the publications available, one dataset CH5424802 price was chosen to characterise hip fracture risk in that country which could be

a single study or the mean of several studies where appropriate. Criteria for selecting a study or studies over others to represent a country are listed below and details are provided in the Appendix. 1. FRAX model available   2. National rather than regional data   3. Higher quality   4. Most recent study   5. Mean of several regional estimates   6. Sole study available   7. Additional

details supplied by the author, see notes in tables   Where a FRAX model was available for a particular country, the hip fracture rates used for FRAX were selected since these used recent data were available and had been PLEKHM2 vetted previously for quality or consistency [13, 14]. Notwithstanding, recent publications, appearing between May 2010 and November 2011 (search cut-off dates) were reviewed to determine the adequacy of the data used for the FRAX models. In the case of China, more recent regional data had been published [15] and were preferentially selected for this report. For Belgium, we used more extensive national estimates (2005–2007 rather than 2006) supplied by the same author [16, 17], M Hiligsmann 2011, personal communication]. For Italy, we used recent national data for 2007 [18] rather than the four regional estimates used in FRAX (version 3.4) [14]. In the absence of a FRAX model, national studies were preferred over regional estimates. For regional estimates, the most recent and higher quality studies were preferred.

ΔΔCT = ΔCT (drugs treated) – ΔCT (control) for RNA samples. ΔCT is the log2 difference in CT between the target gene and endogenous controls by C59 wnt subtracting the average CT of controls from each replicate. The fold change for each treated sample relative to the control sample = 2-ΔΔCT. Statistical analysis All experiments were conducted in triplicate and the results expressed as the mean ± (sd), with differences assessed statistically p values determined by Student’s t- test. p < 0.05 was accepted as significant. Median dose effect analysis, a measure of synergism or antagonism, was determined by the method of Chou and Talalay, using their computer program (Biosoft CalcuSyn,

Ferguson, MO, USA) to assess drug interaction. We chose this method because it takes into account both the potency of each drug or combination of drugs and the shape of dose-effect curve. CalcuSyn software which is based on this method was used to calculate the CI. Synergy, additivity and antagonism were defined as CI < 1, CI = 1, CI > 1, respectively, where CI ≤ 0.5 characterizes strong synergy. For this analysis, concentrations of ATRA and zoledronic acid were chosen as clinically achievable concentrations and below the IC50 values [22]. Results Effect of either single ATRA or zoledronic acid on the viability of OVCAR-3 and MDAH-2774

cells To evaluate the effects of ATRA on the viability of human ovarian cancer cells, OVCAR-3 and MDAH-2774 cells were exposed to increasing concentrations of ATRA (40 to 140 nM) for 24, 48 and 72 h, and XTT cell viability assay was performed.

selleck compound ATRA decreased cell viability in a time- and dose dependent manner both in OVCAR-3 and MDAH-2774 cells (data not shown). As shown in figure 1, there were 20-, 41-, and 73% decrease in cell SPTLC1 viability of OVCAR-3 cells exposed to 40-, 100-, and 120 nM of ATRA, respectively, when compared to untreated controls at 72 h (p < 0.05). In addition, there were there were 28-, 49.5-, and 58% decrease in cell viability of MDAH-2774 cells exposed to 40-, 100-, and 120 nM of ATRA, respectively, when compared to untreated controls at 72 h (figure 1) (p < 0.05). Highest cytotoxicity was observed at 72 h and IC50 values of ATRA were calculated from cell proliferation plots and found to be 85 and 82 nM in OVCAR-3 and MDAH-2774 cells, respectively. Figure 1 Effect of ATRA on viability of OVCAR-3 and MDAH-2774 cells at 72 h in culture. The data represent the mean of three different experiments (p < 0.05). We also examined the effect of zoledronic acid on OVCAR-3 and MDAH-2774 cells. Cells were exposed to increasing concentrations of zoledronic acid (2.5- to 40 μM) for 24, 48 and 72 h. There were 18-, 26-, and 60% decreases in cell viability of OVCAR-3 cells exposed to 5-, 10-, and 20 μM of zoledronic acid, respectively, when compared to untreated controls at 72 h (figure 2) (p < 0.05).

The glycolytic pathway was clearly repressed, supporting previous findings [15, 19]. Among these genes were pfk (0.5-1.1) encoding 6-phosphofructokinase (Pfk), and fba (0.7-1.1) coding for fructose-bisphosphate aldolase, both acting at the initial steps of glycolysis. In addition, gpm3 encoding Ferroptosis assay one of the five phosphoglycerate mutases present in the 23K genome, acting in the lower part of glycolysis, was also down-regulated (0.7-0.9). MF1053 down-regulated pyk (0.7) encoding pyruvate kinase (Pyk)

that competes for PEP with the PTS (Figure 2). Its activity results in the production of pyruvate and ATP, and it is of major importance in glycolysis and energy production in the cell. MF1053 also showed a stronger down-regulation of pfk than the other strains (Table 1). Similar to several other lactobacilli, pfk is transcribed together with pyk [43, 44], and in many microorganisms the glycolytic flux depends on the activity of the two enzymes encoded from this operon [43, 45]. At the protein level, we previously

observed both Pfk and Pyk expressed at a lower level for all the three strains [19], however this was not confirmed at the level of gene expression for 23K and LS 25. We could also not confirm the lower protein expression of glyceraldehyde-3-phosphate dehydrogenase, phosphoglycerate kinase and enolase previously seen in LS 25 [19]. The latter three enzymes are encoded from the central glycolytic operon (cggR-gap-pgk-tpi-eno) together with triose-phosphate isomerase and the putative central glycolytic genes regulator Saracatinib datasheet (CggR) [46]. Besides the cggR gene being down-regulated in MF1053 and LS 25, no change in gene expression was seen of these central glycolytic genes. Thus at the transcription level it is not obvious that the LS

25 strain down-regulate the glycolytic pathway more efficiently than the other strains, Dipeptidyl peptidase as previously suggested [19]. Interestingly, all the strains showed an induction (1.4-2.3) of mgsA encoding methylglyoxal synthase, which catalyzes the conversion of dihydroxyacetone-phosphate to methylglyoxal (Figure 2). The presence of this gene is uncommon among LAB and so far a unique feature among the sequenced lactobacilli. The methylglyoxal pathway represents an energetically unfavourable bypass to the glycolysis. In E. coli, this bypass occurs as a response to phosphate starvation or uncontrolled carbohydrate metabolism, and enhanced ribose uptake was shown to lead to the accumulation of methylglyoxal [47, 48]. As suggested by Chaillou et al. [7], such flexibility in the glycolytic process in L. sakei may reflect the requirement to deal with glucose starvation or to modulate carbon flux during co-metabolism of alternative carbon sources. Breakdown of methylglyoxal is important as it is toxic to the cells [49]. An induction of the lsa1158 gene contiguous with mgsA was seen for 23K and MF1053.

Conventional photolithography and photoresist stripping processes were employed to construct channels with

the desired depth. A silicon (Si) wafer was cleaned in H2SO4:H2O2 solution find protocol (volume ratio of 10:1) at 120°C for 10 min, followed by deionized water (DI) for 4 cycles, then HF:H2O solution (1:50) at 22°C for 1 min and DI water for 4 cycles, and finally spin-dried in hot N2 gas for 15 min. Then, the Si wafer was processed by hexamethyldisiloxane (HMDS) coating and positive photoresist HPR 504 spin-coated at 4,000 rpm for 30 s. The wafer was soft-baked on a hot plate at 110°C for 60 s before exposing to UV via the Mask Aligner (SUSS Microtec MA6-2, Garching Germany) for 5 s. The photoresist was developed using FHD-5 for 60 s and post-baked on a hot plate at 120°C for 60 s. The micropatterns were successfully defined at this stage. The Si wafer was then selleck etched by a DRIE machine (Surface Technology Systems, Newport, UK) and followed by photoresist stripping in PS210 Photoresist Asher (PVA Tepla AG, Kirchheim, Germany) for 25 min. After constructing the microchannels, 10 nm of thermal oxide was grown using a diffusion furnace to form silica on the channel wall. After drilling the inlets and outlets on the Si chip by a mechanical driller, the chip has to be sealed to form a closed channel. A thin film of polydimethylsiloxane (PDMS) was applied for such purpose due to the good adhesion between PDMS and the Si chip. PDMS was formulated

from Sylgard 184 silicone elastomer mixture (Dow Corning Corporation, Midland, MI, USA) at a weight ratio of base:curing agent = 10:1. Then, it was poured onto a Si wafer with saline coating on the surface and pressed against a cleaned glass slide. After curing PDMS in an oven at 60°C for 2 h, the microchip was constructed by pressing the Si chip against the glass slide Vildagliptin with the thin layer of PDMS on its surface. The fabricated microchip is shown in Figure  2a. The microreactor is comprised of two microchannels: channels A and B with a width of 300 μm and a depth of 12 μm and an array (20 channels) of 1D nanochannels that connected the two microchannels

to demonstrate the injection process. It is not necessary to adopt 20 nanochannels. One can increase or decrease the number according to their applications. Fewer nanochannels will result in higher precision, and more nanochannels will give a higher throughput. The inset (a1) in Figure  2a illustrates the multilayer structure showing the PDMS, the silicon chip, and the glass slide. Another inset (a2) shows the structure of the two microchannels connected by the nanochannel array that is highlighted by the green dashed square. When the electric field across channel A and channel B was applied, fluid flowed from channel A to channel B through the nanochannel array as indicated by the green arrow in the same figure. The enlarged scanning electron microscopy (SEM) image of the nanochannel array is shown in Figure  2b. The channel width observed was 10 μm.

J Mater

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for effective detection of CO gas. Sensor Actuat B 2013, 181:529–536.CrossRef 42. Tulliani JM, Cavalieri A, Musso S, Sardella E, Geobaldo F: Room temperature ammonia

sensors based on zinc oxide and functionalized graphite and multi-walled carbon nanotubes. Sensor Actuat B 2011, 152:144–154.CrossRef 43. Yang MZ, Dai CL, Wu CC: A zinc oxide nanorod ammonia microsensor integrated Ketotifen with a readout circuit on-a-chip. Sensors 2011, 11:11112–11121.CrossRef 44. Watson J: The tin oxide gas sensor and its applications. Sensor Actuat B 1984, 5:29–42. 45. Nanto H, Minami T, Takata S: Zinc-oxide thin-film ammonia gas sensors with high sensitivity and excellent selectivity. J Appl Phys 1986, 60:482–484.CrossRef 46. Verplanck N, Coffinier Y, Thomy V, Boukherroub R: Wettability switching techniques on superhydrophobic surfaces. Nanoscale Res Lett 2007, 2:577–596.CrossRef 47. Autumn YA, Liang ST, Hsieh W, Zesch WP, Chan TW, Kenny R, Fearing RJ: Full, adhesive force of a single gecko foot-hair. Nature 2000, 405:681–685.CrossRef 48. Geim K, Dubonos SV, Grigorieva IV, Novoselov KS, Zhukov AA, Shapoval SY: Microfabricated adhesive mimicking gecko foot-hair. Nat Mater 2003, 2:461–463. 49. Jin M, Feng X, Feng L, Sun T, Zhai J, Li T, Jiang L: Superhydrophobic aligned polystyrene nanotube films with high adhesive force. Adv Mater 2005, 17:1977–1981.CrossRef 50. Hong X, Gao X, Jiang L: Application of superhydrophobic surface with high adhesive force in no lost transport of superparamagnetic microdroplet. J Am Chem Soc 2007, 129:1478–1479.

Taken together these results suggest that Tc38 changes the internal localization pattern only in the replicative stages of T. cruzi life cycle.

Figure 7 Tc38 patterns in T. cruzi metacyclic trypomastigotes and amastigotes. Phase contrast, DAPI staining and Tc38 signal are indicated. For the merge images, Tc38-Alexa 488 signal is shown in green and DAPI nucleic acid staining in blue. “”N”" indicates the nucleus see more and “”K”" indicates the kinetoplast. Selected metacyclic trypomastigotes and amastigotes that show the most frequent patterns observed are presented. Bars = 5 μm. The dotted box in the phase contrast corresponds to the position of the fluorescent images. Discussion We had previously reported the isolation of Tc38 as a novel single stranded DNA binding protein without known functional domains [12]. It bears a well-defined N-terminal mitochondrial targeting signal and the orthologous protein in T. brucei has been proposed to be a mitochondrial RNA binding protein [11] and more recently to associate with the kDNA [10]. Here we found that anti-Tc38 causes a specific supershift of the complexes formed by total protein extracts of T. cruzi and [dT-dG] rich oligonucleotides including [dT-dG]40, the Universal Minicircle Sequence, a repeated maxicircle sequence putatively related to replication, and the telomere repeat. Biochemical data obtained with both digitonin titration and differential centrifugation suggested that

Tc38 preponderantly resides in the mitochondrion. The fact that Tc38 presents an extraction BAY 80-6946 price profile similar to citrate synthase indicates that it is a soluble matrix protein. Therefore, the previous isolation of Tc38 from nuclear enriched fractions in T. cruzi [12] and its orthologous protein in L. amazonensis [13], and the identification of a 38 kDa putative minicircle DNA binding protein in T. cruzi nuclear extracts [7], could be explained by the contamination of the nuclear fraction with fragmented mitochondria. In fact, there seems to be an intimate association between the mitochondrial and the nuclear membrane in the proximity of the kinetoplast in epimastigotes. The extent of mitochondrial contamination could be masking

a putative nuclear localization if the protein nuclear abundance is low. The subcellular PRKACG localization of Tc38 shown by immunohistochemistry was consistent with the biochemical data, and further evidenced the association with the kinetoplast, depending on the cell cycle stage. The analysis of Tc38 distribution in asynchronic cultures and in parasites obtained with the T. cruzi culture synchronization elegantly described by Galanti et al. [27] indicates that Tc38 localization within the mitochondrion is not static. Yet, exit from the mitochondria in mitosis cannot be excluded. Tc38 shows a homogeneous distribution in G1, a discrete antipodal position in S and a more extended location including the antipodes and the kDNA between them in G2.

96 (0.72–1.27)  Useful specialist 0.41 (0.08–2.12)  Useful CME 0.23 (0.05–1.18) Explaining the inheritance pattern Country selleck compound (reference UK)  France 1.91 (1.26–2.89)  Germany 1.31 (0.87–1.98)  Netherlands 0.91 (0.59–1.38)  Sweden 1.48 (0.98–2.23)

Gender (reference male)  Female 1.05 (0.82–1.35) Age (reference >50)  ≤50 1.44 (1.14–1.83) Years in practice (reference >20)  11–20 1.40 (1.08–1.81)  ≤10 1.23 (0.87–1.74) Highest genetic education (reference none)  Undergraduate 1.48 (1.07–2.04)  During specialist training 1.96 (1.07–3.61)  CME 1.09 (0.71–1.67) Value of genetic education (reference useless)  Useful undergraduate 1.55 (1.17–2.05)  Useful specialist 1.45 (0.37–5.66)  Useful CME 0.84 (0.19–3.65) Explaining the risk to Mr Smith’s children Country (reference UK)  France 2.95 (1.85–4.70)  Germany 1.64 (1.02–2.63)  Netherlands 1.31 (0.81–2.13)  Sweden 1.38 (0.85–2.21) Gender (reference male)  Female 0.64 (0.48–0.84) Age (reference >50) ≤50 1.20 (0.93–1.55) Years in practice (reference >20)  11–20

1.03 (0.78–1.36)  ≤10 0.89 (0.61–1.31) Highest genetic education (reference none)  Undergraduate 1.05 (0.75–1.47)  During specialist training 1.49 (0.79–2.81)  CME 0.89 (0.57–1.40) Value of genetic education (reference useless)  Useful undergraduate 1.50 (1.10–2.05)  Useful specialist training 1.62 (0.38–6.88)  Useful CME 0.56 (0.13–2.43) Giving information about available gene tests Country (reference UK)  France 2.17 (1.30–3.63)  Germany 1.84 (1.10–3.07)  Netherlands 1.27 (0.75–2.16)  Sweden 1.59 (0.95–2.67) Gender (reference male)  Female 0.63 (0.46–0.85) Age check details (reference >50)  ≤50 0.69 (0.52–0.91) Years in practice (reference >20)  11–20 0.79 (0.59–1.07)  ≤10 0.56 (0.36–0.88) Highest genetic education crotamiton (reference none)  Undergraduate 0.87 (0.61–1.24)  During specialist training 1.10 (0.56–2.18)  CME 0.73 (0.45–1.19) Value of genetic education (reference useless)  Useful undergraduate 1.48 (1.05–2.09)  Useful specialist training 3.77 (0.44–31.96)  Useful CME

0.73 (0.14–3.77) Informing Mr Smith of the implications if no mutation were to be found Country (reference UK)  France 4.01 (1.82–8.80)  Germany 23.97 (11.29–50.87)  Netherlands 7.76 (3.63–16.62)  Sweden 5.58 (2.59–12.03) Gender (reference male)  Female 0.58 (0.43–0.77) Age (reference >50)  ≤50 1.06 (0.82–1.37) Years in practice (reference >20)  11–20 1.02 (0.78–1.35)  ≤10 0.65 (0.43–0.98) Highest genetic education (reference none)  Undergraduate 0.99 (0.71–1.40)  During specialist training 1.53 (0.81–2.88)  CME 1.09 (0.70–1.70) Value of genetic education (reference useless)  Useful undergraduate 1.27 (0.93–1.74)  Useful specialist training 0.68 (0.17–2.69)  Useful CME 0.61 (0.14–2.66) Informing Mr Smith of the implications if a mutation were to be found Country (reference UK)  France 4.46 (1.83–10.89)  Germany 8.51 (3.58–20.20)  Netherlands 3.42 (1.39–8.42)  Sweden 4.64 (1.92–11.21) Gender (reference male)  Female 0.52 (0.36–0.76) Age (reference >50)  ≤50 0.85 (0.61–1.