Previous studies consistently identified several spectrum-related acoustic features that contribute to the perception of timbre, such as the spectral center of gravity and spectrum fine structure (Caclin et al., Tyrosine Kinase Inhibitor Library clinical trial 2005, 2008). Therefore, greater sensitivity to such spectral properties of sound may lead to better neural encoding and enhanced perceptual processing of various timbres, both familiar and novel. This issue requires further study. Another interpretation of a larger N1 peak amplitude in musicians is possible – namely, it may index a greater attentional allocation to auditory stimuli in this group of participants. Whether the enhancement of early

sensory components in musicians is due at least in part to differences in attentional

modulation is a topic of ongoing debate. However, in a recent study, Baumann et al. (2008) directly compared the N1 and P2 components in musicians to the same sounds in two different tasks. In one, participants Selleckchem Trametinib had to attend to certain sound properties (such as pitch and timbre) while in another they did not. The authors demonstrated that intentionally directing attention to sound properties did not increase the amplitude of the N1 and P2 components and therefore concluded that the previously reported enhancement of these components in musicians is due to greater auditory expertise and not to differences 5-FU supplier in attentional allocation between musicians and non-musicians. Studies on vocal and musical timbre perception tend to focus either on musical timbre perception

in musicians or on vocal timbre perception in the general population; however, few bridge these two broad areas. For example, Pantev et al. (2001) compared magnetoencephalographic recordings to violin and trumpet notes in violinists and trumpeters and found that the amplitude of N1m was larger to violin notes than to trumpet notes in the group of violinists and larger to trumpet notes than to violin notes in the group of trumpeters. The authors concluded that their results support timbre-specific enhancement of brain responses in musicians, which was dependent on the instrument of training. This finding has been supported by other studies. Shahin et al. (2008) reported greater induced gamma band activity in pianists and violinists, specifically for the instrument of practice. Musicians also show greater activation in an extensive network of brain regions in the left hemisphere (including the precentral gyrus, the inferior frontal gyrus, the inferior parietal lobule and the medial frontal gyrus) when listening to a musical piece played in their instrument of training as compared with a different instrument (Margulis et al., 2009). Such sensitivity to the timbre of the instrument of training is already evident at the subcortical level as has been shown by Strait et al.

25 in the extracts of WT, and the activity level was significantly higher in the supernatant extract (Fig. 3e and f). This activity was later confirmed to be from galbonolide A by HPLC-MS analysis. Note that the TLC plates were developed three times for better separation. Notably absent was the activity of galbonolide A in the SK-galI-5 extracts (Fig. 3e and f). The mycelia extracts of WT, as well as SK-galI-5, exhibited another antifungal activity that did not migrate under Proteasome inhibitor the elution conditions (Fig. 3f). Next, we used HPLC-MS

analysis to identify galbonolides A and B from the extracts. Extracted ion chromatograms (EICs) of m/z 381 ([M+H]+ for galbonolide A), m/z 365 ([M+H]+ for galbonolide B), m/z 379 ([M−H]− find more for galbonolide A), and m/z 363 ([M−H]− for galbonolide B) revealed

the presence of galbonolides A and B, at 7.2 and 8.7 min, respectively, in the supernatant extract of WT (Fig. 4a). As expected, SK-galI-5 produced galbonolide B, but not galbonolide A (Fig. 4b). In a separate HPLC experiment, elution fractions were collected at 7.0–8.0 min [fraction (fr.) 1)] and 8.0–9.0 min (fr. 2), concentrated, and applied to the antifungal activity assay after TLC separation (Fig. 4c). The antifungal assay demonstrated that the WT fractions retained the high antifungal activity at an Rf value of approximately 0.25, with higher activity in fr. 1. This activity is clearly absent in the SK-galI-5 fractions. Elution fractions from SK-galI-5 had low activity in fr. 2 at an Rf value of approximately 0.35. Although this activity is too low to be reproducibly observed, the Rf value is comparable to the published value for galbonolide B (Abe et al., 1985). Overall, these experiments demonstrate that SK-galI-5 Thiamet G produces galbonolide B, but does not synthesize galbonolide A. The HPLC-MS analysis with gradient elution further supported that SK-galI-5 lost the ability to synthesize galbonolide A (Fig. S2). The proximity of the KAS-related genes (orf3, 4, and 5) to galGHIJK suggests the possibility that these genes are involved in the biosynthesis of galbonolides. Thus, an orf4-disruption mutant was generated and the genotype

of the resulting mutant was confirmed by Southern analysis using the 1.4-kb EcoRV–BamHI fragment as a probe (Fig. 5a and b). A 3.1-kb PstI–NotI fragment was evident in the WT chromosome and it was replaced by 2.8- and 1.7-kb fragments in two progeny of an orf4-disruption mutant (dKS-6 and -7). The 1.4-kb fragment seen in dKS-6 and -7 likely originated from the disruption plasmid, pSK1-dKS. The antifungal activity assay indicated that dKS strains produced a trace level of galbonolide A, while the production of the unknown antifungal compound (the nonmigrating one in TLC) was slightly reduced (Fig. S3). It is certain that the galbonolide A biosynthesis is severely impaired in the dKS mutant, but it is unclear whether a reduction of the unknown compound is associated with a disruption of orf4 or not.

The monkeys were trained to perform a sequential delayed non-matching-to-sample (DNMS) task that requires discrimination of faces, face-like schematics and simple patterns (Fig. 1). The task was initiated by a buzzer tone; then, a fixation cross appeared on the center of the display. When the monkeys fixated on the cross for 1.5 s, a sample stimulus was presented for 500 ms (sample phase). The control phase was defined as the period of 100 ms before the sample phase. When facial photos were used as sample stimuli, gaze directions

of the stimuli were either directed to or averted from the monkey. Then, after an interval of GSI-IX solubility dmso 1.5 s, the same stimulus appeared again for 500 ms, between one and four times (selected randomly for each trial). Finally, a new stimulus with different gaze direction was presented (target phase). When the target appeared, the monkey was required

to press a button within 2 s to receive a juice reward (0.8 mL). When the monkey failed to respond correctly during the target phase or press the button before the target phase, the trials were aborted and a 620-Hz buzzer tone was presented. The inter-trial intervals were 15–25 s (Fig. 2). In the DNMS task, the monkey compared a pair of stimuli in each trial (i.e. sample and target stimuli). Stimulus pairs consisted of the same category of stimuli; only pairs of facial stimuli and pairs of geometric patterns were used check details (i.e. facial stimuli were not paired with geometric patterns). In the facial pairs, averted gazes were always paired with directed gazes; stimulus pairs of gazes averted to the left and the right were not used. Furthermore, the facial stimuli presented in the target phase were the same as in the comparison phase, apart from gaze direction (i.e. same model and same head orientation); thus, the monkeys were required to detect a difference in gaze direction

(directed vs. averted gaze). For the geometric patterns selleck (Fig. 1B), only stimuli within the same category (cartoon faces, face-like patterns, eye-like patterns and simple geometric patterns) were paired. Thus, a total of 72 stimulus pairs (for each of the five models – frontal faces, four pairs; profile faces, four pairs; cartoon faces, four pairs; face-like patterns, 12 pairs; eye-like patterns, four pairs; simple geometric patterns, 12 pairs) were used. These procedures facilitated the monkeys in learning that a shift in gaze direction was an important clue for solving the task. The monkeys were trained in the DNMS task for 3 h/day, 5 days/week. The monkeys required about 11 months of training to reach a 97% correct-response rate. After completion of this training period, a head-restraining device (a U-shaped plate made of epoxy resin) was attached to the skull under aseptic conditions (Nishijo et al., 1988a,b; Tazumi et al., 2010).

cibaria and W. confusa strains was until now only occasional. Several authors reported fructan and/or glucan production by W. confusa and W. cibaria strains (Tieking et al., 2003; Di Cagno et al., 2006; van der Meulen et al., 2007). Based on enzymatic degradation, the presumption of a dextran structure was first suggested by Kang et al. (2006) and Schwab et al. (2008) Selleck XL765 for

W. cibaria strains. Maina et al. (2008) recently reported the production of a linear dextran with >97%α-(16) glucosidic linkages by the W. confusa strain DSM 20194 (VTT E-90392). The aim of the present study is to characterize several Weissella strains that were previously reported as dextran producers (Bounaix et al., 2009). Characterization of polymers by 1H and 13C nuclear magnetic resonance spectroscopy analysis showed that these strains synthesize linear dextran with only a few (2.4–3.3%) α-(13)-linked branches from sucrose. Here, carbohydrate fermentation patterns, repetitive element (rep)-PCR fingerprinting and dextransucrase activity from six W. cibaria and two W. confusa strains are reported. Five strains of W. cibaria (LBAE-C36-1, -D38, -D39, -H25 and -K39) and one strain of W. confusa (LBAE-C39-2) belonging to the culture collection of the Laboratoire de Biologie appliquée à l’Agroalimentaire et à l’Environnement, Université

Paul Sabatier (LBAE-UPS, Auch, France) were used in this study. They were initially collected from traditional French Sunitinib in vitro sourdoughs (Gabriel et al., 1999). Species affiliation was achieved previously using molecular methods (Robert CHIR-99021 cost et al., 2009). Three other LAB strains have been used as reference: W. cibaria DSM 15878T, W. confusa DSM 20196T and Leuconostoc mesenteroides NRRL B-512F. All strains were routinely propagated in De Man, Rogosa and Sharpe (MRS) medium at 30 °C (Biokar). Carbohydrate fermentation patterns of Weissella strains were determined at least in duplicate using API 50CH® strips (API System, BioMérieux,

France) according to the manufacturer’s instructions. The results were recorded after 24 and 48 h of incubation at 30 °C. Dextransucrase activity of the strains was checked as described previously in Bounaix et al. (2009). Briefly, after strain precultivation in MRS broth at 25 °C, a 100 mL culture was prepared (initial OD550 nm=0.3) in plain MRS (glucose medium) or in MRS containing 4% w/v sucrose instead of 2% w/v glucose (sucrose medium). The pH of the media was initially adjusted to 6.9, and bacteria were grown at 25 °C, 100 r.p.m. The culture was stopped when a pH value of 5.0 was reached. The pH was adjusted at 5.4, an appropriate value for dextransucrase activity, with 5 M sterile NaOH. The culture supernatant containing soluble glucansucrase and the pellet exhibiting cell-associated activity were separated by centrifugation (12 100 g, 20 min, 4 °C). Cells were washed twice with 20 mM sodium acetate buffer pH 5.

Contrary to our predictions, shock-associated tones did not evoke significant differential processing on an earlier AEF component between 20 and 50 ms after CS onset (P20–50 m). Results in two different behavioural tests measuring rather explicit learning effects suggested that subjects were not explicitly aware of the predictive CS–UCS relationship, owing to the large number

of complex tones and few learning instances. An indirect measure of acquired valence (affective priming), however, demonstrated an effect of emotional learning on behaviour. RAD001 manufacturer Human affective neuroscience research was rarely concerned with the auditory system in the past. Studies are mainly restricted

to physiological measures (e.g. skin conductance responses) and neuroimaging techniques such as functional MRI or positron emission tomography providing high spatial but rather low temporal resolution. These investigations showed affect-specific prioritised processing of emotionally salient auditory stimuli (Bradley & Lang, 2000) within a distributed network of emotion-related and sensory-specific cortical and subcortical brain regions, such as the amygdala, the medial geniculate nucleus of the thalamus and prefrontal and parietal cortex (Hugdahl et al., 1995; Morris et al., 1997; Royet et al., 2000; Sander & Scheich, 2001; Zald & Parvo, 2002). As these findings corresponded to results in vision (e.g. Lang et al., 1998a; Bradley et al., 2003; Junghöfer et al., 2005; Sabatinelli et al., 2005) FK866 in vitro it was suggested that the same neural mechanisms might be relevant to affective processing in the two modalities

3-mercaptopyruvate sulfurtransferase (Bradley & Lang, 2000). However, only very few studies have investigated the temporal dynamics of auditory emotion processing with time-resolving neurophysiological measures, such as high-density EEG or whole-head MEG in the same way as in vision to further clarify this issue. Using a classical conditioning design with two different tones as CS and median nerve electric shock as US, Moses et al. (2010) demonstrated a so-called CR in the form of an enhanced CS+ beta-band desynchronisation in CS+ conditioning trials with omitted US. This CR was localised at somatosensory areas contralateral to the left or right stimulation side and was interpreted as reflecting the UCS association during CS processing. Although the CR in this study occurred rather late (150–350 ms after omitted shock presentation), previous electrophysiological studies revealed that CRs usually ‘…occur around the time that activation elicited by the US would be expected’ (Moses et al., 2010, p. 276). Non-CR effects were not reported by Moses and colleagues.

, 2010). A similar effect can also be expected in cells LY2157299 order of filamentous fungi. This research indicates that the combination of oxidative stress induced by CTBT and chemical stress induced by itraconazole is more harmful for fungal cells than each stress induced by either compound alone. These findings suggest that the possible effective use of CTBT alone, or in combination with other antifungals, can enhance the treatment of drug-resistant fungal strains. In conclusion,

CTBT was found to induce an increased formation of ROS in cells of filamentous fungi leading to inhibition of their growth and the loss of viability. CTBT also possessed a chemosensitizing capacity enhancing the efficacy of itraconazole that might be useful in a combination treatment of fungal infection caused by multidrug-resistant pathogens. Further studies, using animal models, are necessary to determine whether the activities demonstrated here can translate to in vivo treatment efficacy and safety. We thank P. Polcic for help with fluorescence microscopy and D. Hanson for careful reading

of the manuscript. This work was supported by grants from the Slovak Grant Agency of Science (VEGA 1/0001/09, VEGA 1/0867/12) and Slovak Research and Developmental Agency (VVCE-0282-10). “
“Membrane peptides appear as an emerging class of regulatory molecules in bacteria, which can interact with membrane proteins, including transporters and sensor kinases. The KdpF peptide, which PI3K inhibitor is cotranscribed with kdpABC genes and regulated by the KdpDE two-component system, is supposed to stabilize the KdpABC potassium transporter complex but may also exhibit unsuspected regulatory function(s). The mycobacterial KdpF can interact with the KdpD histidine kinase, and kdpF overexpression has been shown to reduce intramacrophage replication of Mycobacterium bovis BCG. In this study,

we investigated whether KdpF displays Baricitinib similar behavior in another intracellular pathogen, Salmonella enterica serovar Typhimurium. We show that Salmonella KdpF can interact with KdpD in a bacterial two-hybrid assay. We have constructed a Salmonella strain overexpressing kdpF, and we have investigated expression of the kdp regulon, as well as intramacrophage survival. We show that kdpF overexpression reduces expression of kdpA and kdpD genes under potassium limitation. Moreover, kdpF overexpression increases intramacrophage multiplication of S. Typhimurium. Hence, our results indicate that KdpF can play a regulatory role in S. Typhimurium, modulating kdp gene expression and intramacrophage survival, but in a way that differs from the one reported for M. bovis BCG.

Furthermore, the term ‘adverse drug event’ was used as a medication error search term. This returned over 10 000 additional results. The first 300 articles were related to the harm due to drug use. However, this review aimed to identify failures in the medication use process in order to provide an overview of the overall reliability, efficiency and safety. The search strategy, tailored for each database, therefore included two concepts, medication error and primary care,

and excluded a third, secondary care (Table 1). ‘Medication error’ was used as MeSH term and keyword. A hand search of Selleck RG7420 key journals, which included International Journal of Pharmacy Practice (IJPP), Quality and Safety in Healthcare and Pharmacy World and Science, was also performed. Studies conducted in any country between January 1999 and November 2012 and reported in English were included. Studies, which reported the frequency of errors in the medicines management process, and interventions to prevent errors, were included. All definitions of error such as inappropriate prescribing; prescribing, dispensing, administration and monitoring errors; irrational drug use; hazardous prescribing; and drug interactions

were included. Studies estimating error rates of one medication or therapeutic group, and those that did not report the method used for collecting error data or evaluating interventions, were excluded. Apoptosis inhibitor The first author (JOO) screened all titles and abstracts to determine whether Mannose-binding protein-associated serine protease the article met the inclusion criteria and should be retrieved. Another reviewer (MG)

screened a random 5% sample to check the reliability of the screening. JOO then read and extracted data from the articles included in this review. Search results were exported to Endnote X5 (Thomson Reuters, Times Square, New York, NY, USA). Duplicates were removed. Article titles and abstracts were initially reviewed for relevance followed by actual article review to clarify any ambiguities. Information from incidence studies was extracted onto a pro-forma showing primary author, year of publication, study design and setting, sample size, error type, error definitions and reported error rates (Table 2a). Intervention studies were grouped into broad categories (Table 3). Near miss’ incident that was detected up to, including the point at which medication was handed over to patient or their representative’ Incidents detected after patients had taken possession of medication were recorded as ‘dispensing errors The output of the search process is shown in Figure 1. Thirty-two studies, which estimated the incidence of medication errors in primary care, were identified; a manual search retrieved one additional study.[19] Thus, 33 studies were identified and reviewed (Table 2b).

We confirmed this by showing that CD4 cell count trajectories among patients who subsequently died were markedly lower than

for other patients (data available on request). Although random-effects models account for dropout, estimates from these models may also be biased if the dropout mechanism is not predicted by observed CD4 measurements. One solution is to jointly model the dropout mechanism and CD4 cell counts, GS-1101 datasheet although these types of model can be highly sensitive to model misspecification [27,28]. Our analysis was restricted to the subset of patients who had eligible pre- and post-cART CD4 cell counts, and viral load measurements within 6 months of each CD4 measurement. CCI-779 solubility dmso Over the study period, CD4 cell count and HIV-1 RNA were generally measured at least every 3 months. Although this restriction resulted in exclusion of 3682 patients, the only difference in the characteristics of patients who were and were not excluded was a longer median follow-up time among those excluded. As this was an observational study, we were unable to rule out

unmeasured confounding. Individuals who choose to start cART at high CD4 cell counts often have very different characteristics to those who delay cART. Patients starting cART at very low counts were more likely to be female, of Black African ethnicity, and heterosexual, consistent with findings in the UK that individuals with these characteristics are more likely to be diagnosed with HIV at late stages of disease. There may be many other characteristics, particularly in terms of participant attitudes, beliefs and health-seeking behaviours [29], that differ among patients starting cART with different CD4 cell counts, many of which cannot be captured in a cohort such as ours. In summary, CD4 cell counts continued to increase up to 8 years after initiation of cART in patients who maintained virological

suppression, Silibinin although differences according to baseline CD4 cell count were maintained. Periods of virological failure were associated with reductions in subsequent geometric mean CD4 cell counts. The impact of virological failure was greater if the viral load was higher, but declined with time since last failure. Adverse effects of treatment interruption on subsequent CD4 cell counts appeared to be largely mediated through virological failure. These results support hopes that, given continuing virological suppression, many patients will ultimately be able to attain normal or near-normal CD4 cell counts regardless of their baseline CD4 cell count. The authors would like to thank all the clinicians, data managers and research nurses in participating clinical centres who have assisted with the provision of data for this project. Funding was provided by UK Medical Research Council (grants G0600337 and G0000199) and R.H.

, 2007; Lee et al., 2009; Torgomyan et al., 2011a, b). In this respect, F0F1-ATPase is of significance. Note that the enhanced effects of extremely high-frequency EMI in combination with antibiotics on En. hirae are similar to those reported with E. coli (Tadevosyan selleck compound et al., 2008; Torgomyan et al., 2011a, b). General mechanisms for these effects might therefore be suggested in spite of differences between these bacteria. However, some peculiarities of En. hirae may be of importance. The changes in energy (glucose)-dependent H+ and K+

fluxes through the cell membrane by extremely high-frequency EMI have been established with E. coli (Tadevosyan et al., 2008; Tadevosyan & Trchounian, 2009; Torgomyan et al., 2011b), suggesting a role of alterations in membrane

properties by EMI on bacterial EGFR activity cell growth. En. hirae acidifies the medium due to sugar (glucose) fermentation, secreting H+ from the cell either through F0F1 or in the form of organic acids (Trchounian & Kobayashi, 1998). Simultaneously, K+ is taken up through the K+ uptake system, KtrI (Trchounian & Kobayashi, 1998). This H+–K+ exchange is carried out by F0F1, associated with KtrI; F0F1-ATPase activity is therefore K+-dependent (Trchounian & Kobayashi, 1998; Vardanyan & Trchounian, 2010). This kind of H+–K+ exchange plays an important role in bacterial cell physiology (Trchounian, 2004) and its disturbance might affect bacterial cell cycle and activity. This might be caused by EMI. Indeed, 51.8- and 53.0-GHz EMI promoted suppression of energy-dependent H+ efflux by En. hirae ATCC 9790 ~ 2.8- and ~ 3.2 fold, respectively (Fig. 2a). Moreover, in contrast to total H+ fluxes, energy-dependent DCCD-sensitive H+ effluxes were almost the same

for non-irradiated and irradiated cells (Fig. 2b). As DCCD appears to be an inhibitor of F0F1 (Trchounian & Kobayashi, 1998; Betskii et al., 2000; Vardanyan & Trchounian, 2010), these findings might indicate that EMI disturbs second H+ efflux differently from F0F1. Alternatively, a change of F0F1 sensitivity toward DCCD is possible. The EMI effect on K+ influx was more considerable. K+ influx was suppressed ~ 2.8- and ~ 6-fold, respectively (Fig. 2c). This might be the result of disturbing F0F1, associated with KtrI. These two membrane transport and enzyme systems interact with each other, forming protein–protein supercomplexes (Trchounian & Kobayashi, 1998; Poladyan & Trchounian, 2006; Vardanyan & Trchounian, 2010). F0F1 associated with KtrI is probably acting as a main integrated mechanism within the bacterial membrane. The significant decrease of H+ efflux as a result of irradiation may be the consequence of the effect of the final steps of sugar (glucose) fermentation which depresses the production of end organic acids.

Sequences were deposited in the NCBI database under accession numbers: GU139965–GU140004. To design two diagnostic primer/probe sets for esyn1 homologues present in genomes of F. avenaceum/F. tricinctum and F. poae, the sequences were aligned with geneious pro 4.0.0 (Biomatters Ltd, Auckland, New Zealand). Sequences of the esyn1 gene of F. avenaceum/F. tricinctum (EF029060, EF026103, AF351600, AF351597, AF351594, AF351591, AF351588, AF351585, EF040582) and F. scirpi (Z18755) used for alignment were obtained from the NCBI database. Conserved nucleotide sites within esyn1 homologues present RAD001 concentration in genomes of

F. avenaceum/F. tricinctum and F. poae, respectively, were used to design primers and probes using primer express 3.0 (Applied Biosystems) (Table 2). esyn1 probes, conjugated with an MGB group, were labeled at the 5′-end with FAM, while the IPC probe was labeled at the 5′-end with VIC. All primers were synthesized by genomed (Warsaw, Poland), while MGB probes were ordered from ABI PRISM Primers and TaqMan Probe Synthesis Service. TaqMan reaction conditions were used for each esyn1 homologue, including fungal IPC control as recommended by the manufacturer in the fast PCR protocol: 95 °C for 20 s (95 °C for 3 s, 60 °C for 30 s) × 36. TaqMan reagents were optimized

as follows: 2 μL DNA, 10 μL H2O, click here 5 μL Real-Time 2 × PCR Master Mix Probe [Taq DNA polymerase 1 U μL−1, reaction buffer (2 ×), MgCl2 (10 mM), dNTP mix (0.5 mM each), stabilizers], 0.2 μL ROX 50 × (A&A Biotechnology, Gdynia, Poland), 1.8 pM of each IPC primer, 0.5 pM of IPC probe, 6 pM of either F. avenaceum/F. tricinctum or F. Carnitine palmitoyltransferase II poae esyn1-based primers and 1.7 pM of either F. avenaceum/F. tricinctum or F. poae esyn1-based probe. All PCR amplifications were carried out in a 7500 Fast Real-Time PCR System (Applied Biosystems) in a final volume of 17 μL. The threshold value was 0.1 U. To determine the efficiency and sensitivity of the assay, 10.5 ng of genomic DNA of F. avenaceum and 35 ng of F. poae DNA isolates were

serially diluted by a factor of 5 with water and used as a template. In order to eliminate false-positive results, a PCR reaction was considered positive only if the CT value was <35. The relationships between the quantified DNA and enniatins A+B concentrations were determined by Pearson’s correlation analysis using statistica software (Data Analysis Software System, ver. 6.1; StatSoft Inc., 2003, http://www.statsoft.com). Samples with enniatins values below limit of quantifications (LOQs) were considered as LOQs values. Original enniatins values were transformed using Box–Cox transformation, with λ=−0.73 and 0.29 for F. avenaceum/F. tricinctum and F. poae esyn1 amounts, respectively. The coefficients of the Pearson correlation (R) were calculated. Because of the high polymorphism of the esyn1 gene, two pairs of primers/probes potentially specific for F. avenaceum/F. tricinctum and F.