Micropores (approximately 60 μm in diameter) and micropapillae (20 to 30 μm in diameter) were scattered on the surface of porous gel network, which were similar with cauliflower selleck chemicals pattern (Figure  1d). This porous structure could be selleck products attributed to phase separation of PPS phase [18, 20, 24]. Furthermore, thin and long PTFE nano-fibers with dimensions of 5 to 10 μm in length and

100 nm in width exhibited a needle-like morphology. They were distributed layer by layer on the surface of P2 coating (Figure  1e,f). The fluorine (F) was enriched at the top surface of P1 and P2 coating, as shown by the peak at 691.1 eV in the XPS survey spectra (Figure  2a). In addition, the C1s peak for P2 coating observed at 293.5 eV binding energy (C-F3) is similar to the peak at 292.1 eV (C-F2) for P1 coating (Figure  2b) [27, 28]. The above data indicates Lonafarnib in vivo the composition of the nano-fibers on P2 coating surface is mainly PTFE. In our previous

work, disorderly willow-like PTFE nano-fibers (20 to 30 μm in width) formed on the PTFE/PPS coating during the cooling process in the furnace that was exposed to air [18, 20]. In our current work, these PTFE nano-fibers of P2 coating distinctly extended at a certain direction under continuous H2 gas flow; therefore, nano-wires and ‘nano-bridges’ formed with good directional consistency as well as uniform nano-pores (approximately 100 to 500 nm in width). In conclusion, the P2 coating surface shows superior superhydrophobicity as verified Inositol monophosphatase 1 by WCA (170°) and WSA (0° to 1°) values. Compared with P1 coating with only nano-scale fiber structure, nano-wires and nano-bridges with good directional consistency covered the microscale papillae and the interface between them on P2 coating surface, leading to formation of uniform nano-scale pores (100 to 500 nm in width). As large amount of air was captured by the nano-scale pores, the actual contact area between the water droplet and the coating surface greatly decreased [29, 30]; therefore, the WCA of P2 coating

increased. Moreover, the adhesion of water droplets on the orderly thin and long nano-fibers was weakened resulting in the decrease of contact angle hysteresis [29]; therefore, water droplets on P2 coating rapidly rolled down. Furthermore, the P2 coating shows better superhydrophobicity than the PTFE/PPS coating (WCA of 165° and WSA of 5°) by the same composition and curing process [20]. It is mainly because external macroscopic force interference (H2 gas flow) can help to form MNBS structure with well-ordered nano-bridges and uniform nano-pores (approximately 100 to 500 nm in width) (Figure  1f). Therefore, external macroscopic force interference by H2 gas flow during the curing and cooling processes can be a good new method for controllable fabrication of well-ordered polymer MNBS structure with lotus effect.

Samples were dried and treated with 3 M nitric acid overnight at room temperature then quickly boiled. Total manganese content was determined by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) at North Carolina State University Analytical Service Laboratory. Total manganese and iron was measured selleck chemicals in LB medium as above using a 5X concentration of medium. Results Growth of Δfur under anaerobic and aerobic conditions Iron is an essential element for redox reactions in biology. However, it is an important factor in oxygen toxicity due to its involvement in hydroxyl radicals (HO·)

formation via Fenton chemistry [57]. Therefore, we compared the effects of a deletion of fur on growth kinetics under both anaerobic and aerobic conditions. Data in Figure 1 demonstrate that Δfur was not compromised in its growth kinetics under either anaerobic or aerobic conditions. Figure 1 Growth kinetics of Δ fur (black square compared to 14028s (white square). this website Cells were grown in LB-MOPS-X medium as described in Methods; (A) Anaerobic growth; (B) Aerobic growth. Effect of Fur on the anaerobic transcriptome of S. eFT508 mw Typhimurium Under anaerobic conditions, the absence of fur resulted in the differential

expression of 298 genes (Additional File 2: Table S2). These genes were organized by Cluster of Orthologous Groups (COGs) and the numbers of genes within each COG are shown in Table 2. The absence of fur resulted in increased expression (i.e., Fur acted as a repressor) of 226 genes. However, the absence of Fur resulted in decreased expression (i.e., Fur acted as an activator) of 72 genes, most likely via an indirect mechanism. Table 2 Number of Differentially Expressed Genes in Δfur Differentially Expressed Genes in Δfur Cluster of Orthologous Groups Number of Genes “”Fur Repressed”" a Number

of Genes “”Fur Activated”" b Total No COG 30 9 39 Energy Production and Conversion 16 18 34 Cell Cycle Control 3 0 3 Amino Acid Metabolism and Transport 7 16 23 Nucleotide Metabolism and Transport 7 4 11 Carbohydrate Metabolism and Transport 9 4 13 Coenzyme Metabolism and Transport 6 0 6 Lipid Metabolism and Transport 5 0 5 Translation 46 0 46 Transcription 9 2 11 Replication, Recombination, and Repair 5 1 6 Cell Wall/Membrane/Envelope Biogenesis 14 3 17 Cell Motility 1 0 1 Post-Translational Modification, Arachidonate 15-lipoxygenase Protein Turnover, Chaperone Functions 10 1 11 Inorganic Ion Transport and Metabolism 20 2 22 Secondary Metabolite Biosynthesis, Transport, and Catabolism 5 4 9 General Functional Prediction Only 15 4 19 Function Unknown 9 2 11 Signal Transduction Mechanisms 5 2 7 Intracellular Trafficking and Secretion 3 0 3 Defense Mechanisms 1 0 1 Total 226 72 298 Categorized According to Cluster of Orthologous Groups (COGs) a Genes with increased expression in the absence of fur b Genes with decreased expression in the absence of fur A Fur information matrix, specific for S.

These processes undoubtedly disrupt intracellular iron homeostasis, leading to the up-regulation of iron acquisition and sequestration systems. The evidence provided here and in our previous work strongly points to an integral role of SO2426 in such iron control systems. Methods Bacterial strains, plasmids, and culture

conditions All PLK inhibitor strains and plasmids used in this study are described in Table 2. E. coli strains were cultured aerobically in Luria-Bertani click here (LB) [Difco, Detroit, MI] medium at 37°C with shaking. For recombinant E. coli strains, ampicillin was added to LB at a concentration of 50 μg/ml. S. oneidensis strains were grown aerobically in LB medium at 30°C with shaking at 200 RPM. Table 2 Bacterial strains and plasmids used in this study Bacterial Strains Genotype Source/Reference Shewanella oneidensis MR-1 Wild type ATCC 7005500 Lab stock MR-1/Δso2426 Deletion of so2426 locus [21] E. coli TOP10 Cloning and expression strain Invitrogen E. coli ER2508 Major proteinase-deficient strain New England Biolabs Lenvatinib in vitro His-ER-2426-1-1 Expresses full-length SO2426 protein This study His-Top-26s-4 Expresses truncated SO2426 protein This study E. coli (pTOPO) Vector-only control Invitrogen Plasmids     pTrcHis-2426sh so2426sh cloned in frame with N-terminal

polyhistidine This study pTrcHis-2426 so2426 cloned in frame with N-terminal polyhistidine This study SO2426 weight matrix development and identification of a putative SO2426 recognition site MEME Fenbendazole [30], MotifSampler [31], and Gibbs Recursive Sampler [32] were used to predict promoter recognition sequences potentially bound by SO2426. To facilitate motif searching, the time-series microarray expression profiles of the Δso2426 relative to the parental strain were clustered using Hierarchical Clustering Explorer (HCE) [49]. During the clustering process, only genes with an expression value of at least ≥ 2-fold or ≤ 0.5-fold in one or more of 6 expression profiling time points were included in the analyses. As a result, a dataset of 841 genes was clustered based on the average linkage

using Euclidean distance [21]. We extracted a sub-cluster comprising 46 similarly down-regulated genes throughout the 6 time points, and this dataset was used as the input data for putative SO2426 binding-site prediction. The consensus SO2426-binding sequence was predicted with MEME using the following parameters: (i) the motif width ranged from 6 to 50; (ii) the total number of sites in the training set where a single motif occurred was 3; and (iii) the sequence had 0 or 1 binding site. MAST [50] was used to scan the sequence database with the predicted MEME-derived motif. The Gibbs Recursive Sampler program was performed as described previously [12]. MotifSampler [31] was employed to confirm the consensus motif predicted using MEME and Gibbs Recursive Sampler.

Typhimurium (data not shown). Overall, these results confirm that mutating the luxS genomic region can have a significant impact on MicA sRNA levels, consequently affecting the MicA regulated biofilm phenotype, independently of quorum sensing. Figure 5 RT-qPCR analysis of different S . Typhimurium luxS mutants with MicA primers. MicA sRNA expression levels were measured

with RT-qPCR as described in the Methods section. Representative means and standard deviations of three RT-qPCRs are shown. Gene expression is expressed relative to the wildtype SL1344 level. CMPG5602: SL1344 ΔluxS deletion mutant; CMPG5702: SL1344 luxS::KmR insertion mutant; CMPG5630: SL1344 ΔluxS2 deletion learn more mutant. Discussion In several bacteria, biofilm formation GSK461364 ic50 capacity has been linked to luxS based quorum sensing, mediated by AI-2 signaling molecules [4–9]. In Salmonella Typhimurium, it was previously reported that a deletion mutant of the AI-2 synthase enzyme luxS has an impaired biofilm formation capacity [10]. However, this phenotype could not be chemically complemented by extracellular addition

of synthetic DPD, nor by expressing luxS from a constitutive promoter on a plasmid. On the other hand, introduction of luxS with its native promoter did complement the biofilm phenotype [10]. In this study, we showed that both a luxS::Km insertion mutant and a deletion mutant of the 3′ end of the luxS coding sequence are still able to form GSK126 datasheet a mature biofilm, despite the fact that these strains are unable to form the type-2 quorum sensing signaling molecule AI-2. Adjacent to the luxS coding sequence, a small non-coding RNA molecule named MicA is encoded in the opposite strand [15]. Using MicA depletion and overexpression constructs, respectively, we showed that a tightly balanced MicA concentration is essential for proper biofilm formation in S. Typhimurium. This suggests MTMR9 that the final impact of MicA regulation on biofilm formation is based on a complex interplay of several of its targets, a fine-tuning process in which timing is also likely to play a role. It is interesting to note that the MicA depletion strain does not completely abolish the biofilm formation capacity. This could be

explained by an incomplete silencing of MicA in this strain or by the fact that other sRNA molecules take over the role of MicA. It is not uncommon that mRNA targets are redundantly regulated by multiple sRNA molecules fine-tuning their expression in a complex way [28, 29]. The fact that deletion of both rpoE or hfq fully inhibited biofilm formation supports the hypothesis that other sRNA molecules are implicated in regulation of biofilm formation. In literature, two MicA targets known to date were previously linked to biofilm formation. An E. coli ompA mutant is unable to form a mature biofilm on plastic substrates [27]. We showed that also in Salmonella Typhimurium, OmpA is involved in biofilm formation as an ompA deletion mutant is unable to form a mature biofilm.

Rather, the decrease in MreB abundance may be due to the P. gingivalis cells entering a State resembling stationary phase or responding in a previously unseen way to the formation of the three species community. Protein synthesis Extensive changes were observed in ribosomal proteins and in translation elongation and initiation proteins. While overall more proteins showed reduced abundance in the three species community, the changes to the translational Cell Cycle inhibitor machinery were almost exclusively increases in abundance. Of 49 ribosomal proteins detected, 27 showed increased abundance, while only one showed decreased abundance. Of nine translation

elongation and initiation proteins detected, none showed significant abundance decreases but five showed increased abundance (EfG (PGN1870), putative EfG (PGN1014), EfTs (PGN1587),

EfTu (PGN1578), and If2 (PGN0255)). This represents not only a substantial portion of the translational machinery but also a large portion, 36%, of the proteins showing increased abundance. It is well known that ribosomal content is generally proportional to growth rate [36]; however, given that the cells were not in culture medium VX-770 clinical trial during the assay, rapid growth is an unlikely explanation for these results. The increased ribosomal content presumably indicates increased translation, consistent with the community providing physiologic support to P. gingivalis and allowing higher levels of protein synthesis. Vitamin synthesis Celecoxib Pathways for synthesizing several vitamins showed reduced protein abundance in the three species community. Most of the proteins involved in thiamine diphosphate (vitamin B1) biosynthesis

were downregulated (Fig. 4). Thiamine is a cofactor for the 2-oxoglutarate dehydrogenase complex that converts 2-oxoglutarate to succinyl-CoA and for the transketolase reactions of the anaerobic pentose phosphate pathway [37]. However, transketolase (PGN1689, Tkt) showed no abundance change while of the three components of the 2-oxoglutarate dehydrogenase complex (PGN1755, KorB) only the beta subunit showed an abundance increase. Figure 4 Thiamine biosynthetic pathway, showing protein abundance changes for the P. gingivalis – F. nucleatum – S. gordonii / P. gingivalis comparison. Proteins catalyzing each step in the pathway are shown by their P. gingivalis ATCC 33277 gene designation (PGN number) and protein name, where applicable. Green downward arrows indicate decreased abundance in the three species community. Yellow Ferrostatin-1 cost squares indicate no statistically significant abundance change. Empty squares indicate that the protein was not detected in the proteomic analysis. Thiamine diphosphate is shown in bold. Only incomplete pathways have been identified for many of the other vitamin biosynthesis activities in P. gingivalis.

Cells were infected with a multiplicity of infection of 2-10 bacteria per cell and incubated for 3 hours at 37°C in 5% CO2. After incubation, monolayers were thoroughly washed with phosphate-buffered saline to remove extracellular bacteria and fresh medium was added. To evaluate the bacterial growth, supernatants were aspirated and monolayers were lysed with 0.5% Nonidet P40 (Roche Diagnostics, Mannheim, Germany) at 3 hours and days 1, 4, and 7 after infection. Serial 10-fold dilutions

of cellular lysates were plated on Middlebrook 7 H11 plates and incubated for 3 weeks at 37°C in 5% CO2, and colonies were counted. Intracellular growth was expressed as the growth rate, which is the slope of the function of log10 CFU values throughout the infection period (3 hours and days 1, 4, and 7). Three #Selleckchem GSK1210151A randurls[1|1|,|CHEM1|]# or more independent experiments were performed for each assayed strain. Cytokine analysis Culture PND-1186 nmr supernatants from control and infected THP-1 cells were harvested after 3 hours and on days 1, 4, and 7, frozen

at -70°C, and assayed using an enzyme-linked immunosorbent assay (ELISA) kit according to the manufacturer’s instructions (BD Biosciences, Lincoln Park, NJ) to measure levels of tumor necrosis factor alpha (TNF-α) and interleukin 10 (IL-10). Statistical analysis Three independent experiments were performed per strain. The means and standard errors were determined for each measurement in both intracellular growth and cytokine production. One-way analysis of variance with repetitive measures was used to determine P values, which were adjusted using the Bonferroni method. All the comparisons were carried out using the program SPSS 17.0. Acknowledgements This study was partially funded by the Fondo de Investigaciones Sanitarias (FIS060882; FIS061467; FIS06/90490; 06/90357), Junta de Andalucía (0453/06, 151/05), and the Instituto de Salud Carlos III (CIBER Enfermedades Respiratorias CB06/06/0058 and

the Spanish Network for the Research in Infectious Diseases [REIPI RD06/0008]). N.A.R. received a grant from the Consejería de Educación de la Comunidad de Madrid and the European Social Fund (3334/2004). We are grateful to Joaquin Navarro from the Immunology Ribonucleotide reductase Department in Gregorio Marañón Hospital for assessing us with the cytokine assays and to the INDAL-TB group in Almería for the recruitment of cases and compilation of clinical data. We are grateful to Thomas O’Boyle for editing and proofreading the final version of the manuscript. References 1. WHO: Global tuberculosis control: surveillance, planning, financing. WHO report 2008. WHO/HTM/TB/2008.393.Geneva. 2008. 2. Frieden TR, Sterling TR, Munsiff SS, Watt CJ, Dye C: Tuberculosis. Lancet 2003,362(9387):887–899.PubMedCrossRef 3.

Acad Emerg Med 1998, 5:951–960.PubMedCrossRef 21. Bignardi T, Burnet S, Alhamdan D, et al.: Management of women referred to an acute gynecology unit: impact of an ultrasound-based model of care. Ultrasound Obstet Gynecol 2010, 35:344–348.PubMedCrossRef 22. Toret-Labeeuw F, Huchon C, Popowski T, Chantry A, Dumont A, Fauconnier A: Routine ultrasound examination by OB/GYN residents increase the accuracy of diagnosis for emergency surgery in gynecology. World J Emerg Surg 2013,8(1):16.PubMedCentralPubMedCrossRef 23. Moll HA: Challenges selleck compound in the validation of triage systems at emergency departments. J Clin Epidemiol 2010, 63:384–388.PubMedCrossRef 24. Rouzier R, Coutant C, Lesieur

CHIR-99021 B, et al.: Direct comparison of logistic regression and recursive partitioning to predict chemotherapy

response of breast cancer based on clinical pathological variables. Breast Cancer Res Treat 2009, 117:325–331.PubMedCrossRef 25. Shariat SF, Karakiewicz PI, Suardi N, Kattan MW: Comparison of nomograms with other methods for predicting outcomes in prostate cancer: a critical analysis of the literature. Clin Cancer Res 2008, 14:4400–4407.PubMedCrossRef 26. Abbott J: Pelvic pain: lesson from anatomy and physiology. J Emerg Med 1990, 8:441–447.PubMedCrossRef 27. Lamvu G, Steege JF: The anatomy and neurophysiology of pelvic pain. J Minim Invasive Gynecol 2006, 13:516–522.PubMedCrossRef 28. Houry D, Abbott JT: Ovarian torsion: a fifteen-year review. Ann Emerg Med Molecular motor 2001, 38:156–159.PubMedCrossRef 29. Milholland AV, Wheeler SG, Heieck JJ: Medical assessment by a Delphi group opinion technic. N Engl J Med 1973, 288:1272–1275.PubMedCrossRef Competing interest The authors declare that they have no competing interests. Authors’ contributions CH and AF wrote the manuscript. AF, AD and BF designed the study. AAC, CH and AF collected the datas. CH, AD and AF performed the statistical analysis.”
“Diagnosis and treatment of perforated peptic ulcer (Dr. S. Di Saverio MD) Introduction Every year peptic ulcer disease (PUD) affects 4

milion people around the world [1]. Complications are encountered in 10%-20% of these patients and 2%-14% of the ulcers will perforate [2, 3]. Perforated peptic ulcer (PPU) is relatively rare, but life-threatening with the mortality varying from 10% to 40% [2, 4–6]. More than half of the cases are female and they are usually older and have more comorbidities than their male counterparts [6]. Main etiologic factors include use of non-steroidal anti-inflammatory drugs (NSAIDs), steroids, smoking, Helicobacter pylori and a diet high in salt [3, 7]. All these factors have in common that they affect acid secretion in the gastric mucosa. Defining the exact etiological factor in any given patient may often be Copanlisib clinical trial difficult, as more than one risk factor may be present and they tend to interact [8].

The MICs for ftlC, tolC, acrA, and acrB (MIC = 25 μg/ml Az) were greater than the wild-type (MIC of 0.78 μg/ml Az) Tozasertib datasheet and had a higher EC50 (EC50 > 12 μg/ml Az) compared

to the wild-type of 0.16 μg/ml Az (p-value < 0.002), indicating decreased sensitivity to the antibiotic. These results are consistent between the MIC and disc inhibition assay for acrA, acrB, and ftlC (Figure 4B, Table 5). The tolC sensitivity to Az results in the solid agar and liquid broth assay were inconsistent. The disc-inhibition assay suggests increased sensitivity, while the MIC assay demonstrated increased resistance. We are currently investigating the basis of this difference. Table 6 Az Disk Inhibition Assay with Francisella transposon RND Efflux mutants.   Antibiotic No Growth Zone (mm) F. novicida Avg p-value wild-type 31.4 ± 1.0   ftlC 28.0 ± 3.1 0.006 tolC 33.2 ± 1.4 0.007 dsbB 30.7 ± 1.2 0.162 acrA 23.5 ± 0.7 <0.001 acrB 25.2 ± 1.1 <0.001 F. tularensis Schu S4 Avg p-value wild-type

25.5 ± 1.9 ——– ΔacrA 41.7 ± 2.7 0.0001 ΔacrB 35.7 Palbociclib mw ± 4.3 0.001 For F. novicida RND efflux mutants, 15 ug Az discs were from Remel, while for F. tularensis Schu S4, 15 ug Az discs were from Fluka. The zone of inhibition was measured in mm. In the disc inhibition assay of the disulfide bond protein mutant dsbB, there was no significant difference compared to the wild-type (p-value = 0.162) (Table 6). Similarly, the MIC for dsbB was not significantly different than the wild-type value (p-value = 0.400) (Table 5). Thus, mutation Aldehyde dehydrogenase of dsbB does not seem to have a significant impact on the ability of the organism to resist Az, whereas transposon insertion mutants in the tolC, ftlC, acrA and acrB components of the RND efflux GSK1210151A supplier system appear to decrease the sensitivity of F. novicida to Az. This result for tolC and ftlC may be in contrast to Gil et al. [12], who found that F. tularensis LVS deletion of tolC or ftlC did not alter the sensitivity to erythromycin (15 μg disc). The MIC of F. tularensis LVS is higher than can be achieved

using a 15 μg disc, reported at >256 μg/ml erythromycin [28]. Therefore, any alteration in sensitivity due to tolC deletion would not be observed at this low concentration of antibiotic. In contrast to the F. novicida results, the F. tularensis Schu S4 ΔacrA mutant and ΔacrB mutants had greater sensitivity to Az compared to the wild-type F. tularensis Schu S4 (p-value < 0.001) (Table 6). This is consistent with the findings of Qin et al. [16] who found an increased sensitivity of ΔacrB to 50 μg disc erythromycin. The MICs for Az against F. tularensis Schu S4 RND efflux mutants were also determined. The MICs for ΔacrA and ΔacrB (MIC > 1.5 μg/ml Az) are higher than the wild-type MIC of 0.78 μg/ml Az (p-value < 0.02) (Figure 4C, Table 5). However, the F. tularensis Schu S4 mutants for ΔacrA (EC50 of 0.085 μg/ml) and ΔacrB (EC50 0f 0.

Here we report an analysis of the role of HGF/c-Met related β-catenin activation and CTNNB1 mutation activation of β-catenin in a large cohort of 84 patients with hepatoblastoma.

This characterisation of β-catenin activation by the c-Met pathway may have clinical relevance because several HGF/c-Met small molecule inhibitors are now in early phase clinical trials. Materials and methods Patients and SIOPEL HB clinical ARRY-162 trials SIOPEL Liver tumor clinical trials are international, prospective, clinical this website trials run under the auspices of the SIOP Liver Tumor Strategy Group (SIOPEL). Our cohort comprises patients prospectively enrolled into the SIOPEL 3 clinical trial, a randomised study which opened in March 1998, designed to evaluate the effectiveness of preoperative chemotherapy for standard risk (SR) HB with either cisplatin (CDDP) alone or in combination with CFTRinh-172 research buy doxorubicin (PLADO). A detailed description of the SR patient cohort, its clinical features, staging and outcome has previously been reported [33]. SIOPEL 3 patients with high risk (HR) HB were all treated preoperatively with SUPERPLADO, a three-drug combination of Cisplatin, Doxorubicin and Carboplatin and the results have been reported [34]. All patients were recruited to the SIOPEL 3 clinical trial

with appropriate informed consent. This specific study was reviewed and approved by the New Zealand Health Research Council Multi-regional ethics committee (MREC). Tumor samples In this study we have accessed a representative cohort

of 84 HB patients with clinical, histologic and survival data available for most samples. Both diagnostic and post-chemotherapy samples were available for fourteen patients bringing the total number of samples analysed to 98. In the case of diagnostic samples there was generally just a single formalin-fixed paraffin-embedded (FFPE) tumor block available containing the entire biopsy material on which the diagnosis was made. For each post-chemotherapy Arachidonate 15-lipoxygenase case, the most representative FFPE block was identified by examination of slides stained with haematoxylin and eosin (H+E). From the H+E slides, representative tumor and adjacent normal tissue areas were selected by a pathologist (C.M.) for subsequent tissue array construction. Tissue Array Construction A tissue microarray (TMA) was constructed by depositing a 1 mm core of each tumor or normal tissue into a wax recipient block using the Manual Tissue Arrayer I (Beecher Instruments Inc., Sun Prairie, WI, USA). In cases where tumor heterogeneity was evident, different representative areas of the tumor were sampled for TMA construction.

4), Didea alneti (3.54; 69.7), Doros conopseus (3.76; 51.5), Microdon analis (3.5; 66.7), Parasyrphus annulatus (3.82; 84.8), Parasyrphus malinellus (3.16; 72.7), Parasyrphus vittiger (2.88; 75.8), Platycheirus discimanus (3.43; 30.3), Sphaerophoria virgata (3.83; 57.6) 24  S3 S. Limburg Cheilosia barbata (23.37; 79.2), Cheilosia lenis (21.71; 70.8), Pipizella virens (20.9; 75), Platycheirus parmatus (18.68; 54.2), Pipizella annulata (15.86; 62.5), Platycheirus tarsalis (15.81; 45.8), Chrysogaster chalybeata (14.94;

75), Orthonevra nobilis (14.87; 70.8), Criorhina ranunculi (13.04; 58.3), Cheilosia nigripes (12.93; 37.5) 77  S4 Fen area Eristalis anthophorina (3.74; 59.1), Lejogaster tarsata (1.64; 72.7), Orthonevra Tubastatin A clinical trial geniculata (5.16; 54.5), Orthonevra intermedia (8.53; 81.8), Parhelophilus consimilis (7.92; 54.5), Platycheirus fulviventris (1.19; 95.5), Platycheirus occultus (1.87; 59.1) 7  S5 Coastal dunes Brachyopa insensilis (3.50; 36.7) 1  S6 Gradient H 89 Cheilosia grossa (2.36; 76.5), Cheilosia semifasciata (3.68; 64.7), Cheilosia uviformis (5.06; 58.8), Melanogaster aerosa (2.45; 41.2), Eristalis similis (2.41; 82.4), Myolepta dubia (6.54; 47.1), Neoascia geniculata (2.48; 70.6), Neoascia interrupta (4.27; 70.6), Parasyrphus https://www.selleckchem.com/products/PLX-4032.html nigritarsis (3.22; 29.4), Pipiza luteitarsis (6.18; 76.5) 25 Mosses  B1 Southeast Atrichum tenellum (1.8; 56.1)), Pogonatum aloides (1.53; 47.2), Pohlia lescuriana (1.32; 36.1), Pohlia camptotrachela

(1.31; 32.7), Pohlia annotina (1.24; 57), Dicranum montanum (1.21; 78.5), Philonotis fontana (1.19; 55.6), Dicranum tauricum (1.15; 43.5), Fossombronia wondraczekii (0.72; 24.8), Pogonatum urnigerum (0.67; 22.0) 25  B2 Pleistocene sand Odontoschisma sphagni (2.43; 65.8), Sphagnum magellanicum (2.31; 58.1),

Sphagnum tenellum (2.27; 56.8), Sphagnum molle (1.8; 47.1), Mylia anomala (1.61; 35.5), Cephalozia connivens (1.58; 68.4), Dicranum spurium (1.51; 45.8), Cephalozia macrostachya (1.10; 45.5), Barbilophozia kunzeana (0.93; 21.9), Barbilophozia hatcheri (0.78; 20.0) 40  B3 S. Limburg Leiocolea bantriensis (16.54; 33.3), Lophocolea minor (15.36; 45.8), Mnium marginatum (15.14; 70.8), Eurhynchium pumilum (13.65; 66.7), Plagiothecium cavifolium (13.24; 45.8), Pohlia cruda (13.02; 20.8), Plagiochila asplenioides (12.36; 58.3), triclocarban Trichostomum crispulum (11.6; 25), Campylophyllum calcareum (11.4; 29.2), Eurhynchium schleicheri (10.81; 33.3) 102  B4 Fen (meadow) area Sphagnum teres (4.75; 47.6), Riccardia multifida (3.02; 38.1), Sphagnum contortum (2.73; 25.4), Pallavicinia lyellii (2.57; 55.6), Sphagnum rubellum (2.35; 54), Rhizomnium pseudopunctatum (2.2; 23.8), Dicranum bonjeanii (2.09; 58.7), Pellia neesiana (2; 49.2), Plagiomnium ellipticum (1.86; 69.8), Straminergon stramineum (1.74; 58.7) 19  B5 Coastal dunes Tortella flavovirens (8.71; 58.6), Ditrichum flexicaule (7.45; 48.3), Rhodobryum roseum (4.9; 44.8), Bryum provinciale (4.42; 22.4), Rhynchostegium megapolitanum (4.05; 69), Pleurochaete squarrosa (3.