They then recorded the activity of individual cells in the face p

They then recorded the activity of individual cells in the face patches in response to the artificial faces and found that the cells do indeed respond to contrasts between facial features. Ohayon and his colleagues later studied the cells’ response to images of real faces and found that, again, responses increased with the number of contrast-defined features. Tsao, Freiwald, and their colleagues had found earlier that cells in the face patches respond selectively to the shape of

some facial features, such as noses and eyes (Tsao et al., 2008). Ohayon’s findings now showed that this selective response depends on luminance relative to other parts of the face. Most of the cells they studied respond both selleck kinase inhibitor to contrast and to the shape of facial features, which leads us to an important conclusion: contrast is useful for face detection, and shape is useful for face recognition. These studies have shed new light on the nature of the templates the brain uses to detect faces. Behavioral studies suggest a powerful link between the brain’s face detection machinery and the areas Selleck Akt inhibitor of the brain that control attention, which may account for why faces—and particularly portraits—draw our attention so strongly. When psychoanalysis emerged from Vienna early in the twentieth century, it represented a revolutionary way of thinking about the human mind and its disorders. The excitement

surrounding the theory of unconscious mental processes increased as psychoanalysis was brought

to the United States by immigrants from Germany and Austria. Under the influence of psychoanalysis, psychiatry was transformed in the decades following World War II from an experimental medical discipline closely related to neurology into a nonempirical specialty focused on psychotherapy. In the 1950s academic psychiatry abandoned some of its roots in biology and experimental medicine and gradually became a therapeutic discipline based on psychoanalytic theory. Over the next 50 years, psychoanalysis exhausted much of its novel investigative power. It also failed to submit its assumptions to the sort of rigorous tests that are needed to inspire confidence. Indeed, it was far better at generating ideas than at testing them. Fortunately, some people in the psychoanalytic community thought that first empirical research was essential to the future of the discipline. Because of them, two trends have gained momentum in the last several decades. One is the insistence on evidence-based psychotherapy; the other is an effort to align psychoanalysis with the emerging biology of mind. Perhaps the most important driving force for evidence-based therapy has been Aaron Beck, a psychoanalyst at the University of Pennsylvania. Whereas traditional psychoanalysis teaches that mental problems arise from unconscious conflicts, Beck became convinced that conscious thought processes also play a role in mental disorders.

The existence of basal Na+ conductance was first reported more th

The existence of basal Na+ conductance was first reported more than 60 years ago. In the squid giant axon, Hodgkin and Katz estimated that the resting relative permeability of Na+ and K+ (PNa/PK) was 0.04 (4%) (Hodgkin and Katz, 1949b). Several cellular mechanisms contribute to the resting background Na+ conductance. First, Na+-dependent cotransporters and some of the electrogenic exchangers allow Na+ into neurons. Second, in some neurons, the hyperpolarization-activated cation channels (HCN, If/Ih current), which conduct Na+, are open at rest

(Robinson and Siegelbaum, 2003). HCN channels are not present in some animals, such as the nematode C. elegans. Third, persistent Na+ currents (INaP) at RMPs can be generated by voltage-gated Na+ (NaV) channels through the “window” current, or by non-inactivating ion channels ( Crill, 1996). The LY2109761 solubility dmso generation of INaP through NaVs is influenced by the voltage-dependence of the channel’s activation and inactivation, which can also be regulated by modulators such as G protein βγ subunits ( Ma et al., 1997). During interspike intervals, NaVs in some neurons can also generate “resurgent” current upon

repolarization because of channel’s recovery from inactivation/block during depolarization ( Grieco et al., 2005 and Raman and Bean, 1997). These subthreshold, NaV-dependent conductances are highly sensitive to voltage and are mostly blocked Ibrutinib by tetrodotoxin (TTX) Suplatast tosilate in the central

nervous system. Finally, many neurons also exhibit a TTX-resistant, voltage-independent, “true” background Na+ conductance (Na+ leak current, IL-Na) ( Atherton and Bevan, 2005, Eggermann et al., 2003, Jackson et al., 2004, Jones, 1989, Khaliq and Bean, 2010, LeSauter et al., 2011, Peña and Ramirez, 2004, Raman et al., 2000 and Russo et al., 2007). The most obvious function of the tonically active background Na+ conductance is perhaps to balance the K+ leak to set the RMP, which would be at ∼−90 mV (EK) in all the neurons if there were only basal K+ conductance. A tonic leak of other ions such as Ca2+, Mg2+, and H+ can hypothetically achieve the same goal, but excessive leak of these ions into neurons can be damaging to the cells because of the cellular metabolism’s high sensitivity to the intracellular concentrations of the ions. By varying the basal PNa/PK, the nervous system can have a wide range of RMPs among different neurons, a heterogeneity in neuronal intrinsic properties known to exist in the brain (Kandel et al., 2000 and Llinás, 1988). Another function of the Na+ conductance is to provide a regulation of the membrane potential by environmental stimuli. One such example was demonstrated in the excitation of sympathetic ganglion neurons in the frog (Jan and Jan, 1982 and Kuffler and Sejnowski, 1983).

The pEPSP sublinearity could be observed for just under 2 quanta

The pEPSP sublinearity could be observed for just under 2 quanta (∼10% sublinearity; Figure 5C, inset, arrow). This sublinearity is less than predicted by simulations (18%, Figure 5C, inset, solid black line), possibly due to the sublinearity of single quantal EPSPs, which simulations predict to be 10%. Voltage-dependent conductances, in particular those mediated by NMDARs and Ca2+ channels, can produce supralinear summation of synaptic inputs (Branco and Häusser, 2011, Cash and Yuste, 1999, Margulis and Tang, 1998 and Urban and Barrionuevo, 1998), whereas K+ channels can produce sublinear summation (Cash and Yuste, 1999, Hu et al., 2010, Margulis

and Tang, 1998 and Urban and Barrionuevo, 1998). In SCs, see more the synaptic input-output relationships remained sublinear in presence of NMDAR, Na+, Ca2+, K+ and HCN channel blockers (Figures 5D and 5E), a condition in which nearly all voltage-dependent conductances are blocked (Figure S5). KU-57788 chemical structure These data and simulations demonstrate that, for synaptic depolarizations induced by up to 15 simultaneously evoked quanta, sublinear dendritic integration in SCs is determined largely by its passive cable properties. Thus far, experimental and modeling results indicate that larger synaptic conductances will produce larger sublinearities (Figure 5C). We therefore tested

the hypothesis that, during paired-pulse facilitation, a sublinear “readout” of the second, potentiated synaptic conductance could underlie the distance-dependent reduction in EPSC PPR (Figure 1). We repeated the PPR stimulation protocol (Figure 1) in presence of submaximal concentrations of a noncompetitive AMPAR antagonist (GYKI 53655 or 53784,

3–9 μM; Paternain et al., 1995). We reasoned that a reduction in synaptic conductance would reduce local depolarization and hence minimize the sublinear report of the facilitated synaptic conductance. Indeed, when EPSC amplitudes were reduced by more than 75% the difference between dendritic and somatic PPRs was no longer observed (Figure 6A). To confirm that synaptic currents were mediated solely by AMPARs, EPSCs were entirely blocked by a saturating concentration of GYKI (40 μM; data not shown). Also, the distance dependence of PPR was not not affected by blockade of voltage-dependent Na+, K+, Ca2+, HCN channels, or mGluRs (Figures S6A–S6D), further supporting a passive cable mechanism. These data show that, although the paired-pulse facilitation is mediated through a presynaptic mechanism, the distance-dependent gradient of short-term plasticity results from a postsynaptic sublinear “readout” of synaptic conductances. These results were confirmed by simulations showing that passive cable properties are sufficient to produce a distance-dependent decrease in PPR (Figure 6B). A conductance ratio of 2.25 produced a simulated EPSC PPR of 2.

It would be interesting to find out whether the brain state switc

It would be interesting to find out whether the brain state switches triggered by single neuron burst in vivo is related to the bidirectional effects of cortical stimulation on the occurrence of UP states in slices (Rigas see more and Castro-Alamancos, 2007) (Figure 5B). Cortical neurons are also highly interconnected with thalamic neurons, and those from the prefrontal cortex provide strong descending inputs to the neuromodulatory circuits in the basal forebrain (Golmayo et al., 2003; Sarter et al., 2005; Zaborszky et al., 1997) and brainstem (Jodo and Aston-Jones, 1997). Thus, the brain state switch triggered by single-neuron stimulation could also be mediated by the activation

of thalamic neurons or the neuromodulatory circuits. In addition to the areas reviewed above, which are core components of the neural machinery controlling sleep and wake states, many other brain structures also play modulatory roles. For example, sleep is strongly regulated by the circadian rhythms, which are controlled by the suprachiasmatic nucleus (SCN) in the hypothalamus. Dissecting the

synaptic pathways between these structures and the core components described above will be essential for understanding how sleep-wake transitions are regulated by both internal and environmental factors. Wakefulness is not a unitary brain state, and the ensemble neural activity exhibits clear changes at different levels of vigilance. When the animal is drowsy or quietly resting, there is considerable delta-band activity in EEG and LFP, although the power is generally lower than that during NREM sleep. When the animal is in an aroused/attentive state (e.g., actively engaged in sensory processing or motor tasks), the cortical activity is highly desynchronized, as measured by both LFP (Bezdudnaya et al., 2006; Niell and Stryker, 2010) and intracellular recordings (Crochet and Petersen, 2006; Okun et al., 2010; Poulet and Petersen, 2008) (Figures 1A and

1B). In addition to the general arousal, selective attention to specific STK38 stimuli is also associated with changes in ensemble cortical activity, although at a more local level. Attention to visual stimuli within the receptive fields of recorded neurons is accompanied by decreases in the low-frequency LFP activity (Fries et al., 2001; Khayat et al., 2010), and it can cause either increase or decrease in gamma activity (30–80 Hz), depending on the cortical area (Chalk et al., 2010; Fries et al., 2001). The subcortical neuromodulatory circuits involved in sleep-wake control also play important roles in the regulation of arousal and attention, and malfunctioning of these circuits causes a variety of cognitive impairments. Both the monoaminergic and cholinergic neurons in the brainstem and basal forebrain receive inputs from the prefrontal cortex (Berridge, 2008; Jodo and Aston-Jones, 1997; Sarter et al., 2005), a key circuit exerting cognitive control of behavior (Miller and Cohen, 2001) (Figure 6).

The nano-LC was equipped with homemade precolumn (150 × 5 mm) and

The nano-LC was equipped with homemade precolumn (150 × 5 mm) and analytical column (75 × 150 mm) packed with Jupiter Proteo C12 resin (particle size 4 mm, Phenomenex, Torrance, CA, USA). The dried peptides were resuspended in 1% formic acid (FA) solution. Six microliters of sample solution was loaded to the precolumn for each LC-MS/MS

run. The precolumn was washed with the loading solvent (0.1% FA) for 4 min before the sample was injected onto the LC column. The eluents used for the LC were 0.1% FA (solvent A) and 95% ACN containing 0.1% FA (solvent B). The flow rate was 200 nl/min, and the following gradient was used: 3% B to 35% B in 72 min, 35% B to 80% B in 18 min, which was maintained at 80% B for 9 min. The column was finally equilibrated with 3% B for 15 min prior to the next run. Electrospray ionization was performed using a

30 mm (i.d.) nanobore stainless see more LY294002 solubility dmso steel online emitter (Proxeon, Odense, Denmark) and a voltage set at 1900 V. Sequences were searched against Swiss-Prot mouse and mammalian genomes using MASCOT software versions 2.1.0 and 2.1.04 (Matrix Science, London, UK). Peptides were required to have a rank = 1 and a score >18. We constructed a weighted correlation network as previously described using the R software package (Langfelder and Horvath, 2008). We used proteins with unique tryptic peptide counts coming from at least three IP conditions as an input (n = 411). See Supplemental Experimental Procedures for complete WGCNA procedure. Using a population of 15 age-matched (± 4 hr) virgin female flies, we estimated the percentage of animals able to climb past a line set at 9 cm in during 15 s. These tests were repeated ten consecutive times for each replicate per experimental day. The experiment was carried out in duplicate (two populations of 15 animals) in flies that were 8, 10, 12, 14, and 16 days old. Tests were always performed in the same time of the day and in the same place to avoid circadian rhythm and environmental

variability. The average number of flies climbing per day is averaged and plotted independently for each replicate. All values are presented as the mean ± SEM, and p < 0.05 was considered statistically significant. X.W.Y. is supported by the National Institute of Neurological Disorders and Stroke/National Institutes of Health (NINDS NIH) (grants R01NS049501 and R01NS074312), CHDI Foundation, the Hereditary Disease Foundation (HDF), David Weil Fund to the Semel Institute at University of California, Los Angeles, and Neuroscience of Brain Disorders Award from The McKnight Endowment Fund for Neuroscience. D.S. was supported by the NIH Chemistry-Biology Interface Research Training Program at UCLA (T32GM008496). D.S. and E.G. were supported by the UCLA Dissertation Year Fellowship Program. J.A.L. is supported by an NIH grant (R01RR20004) and by the W. M. Keck Foundation for the establishment of the UCLA Functional Proteomics Center. S.H.

Diverse pharmacological, molecular, and

physiological app

Diverse pharmacological, molecular, and

physiological approaches are being examined for modulating neural plasticity and to treat neurological and psychiatric diseases. Targets of Afatinib price modulation include neuromodulatory systems, cortical inhibition, as well as molecules that may actively promote or inhibit plasticity (Barbay and Nudo, 2009, Bavelier et al., 2010 and Cramer, 2008). Examples include improving function in animal models of neurodevelopmental disorders (Ebert and Greenberg, 2013), neuropsychiatric disorders (Lakhan et al., 2013 and Stephan et al., 2006), and stroke (Cramer et al., 2011 and Overman et al., 2012). While some are highly targeted (e.g., specific pharmacological blockade of inhibition), others likely recruit multiple cellular processes and neural circuits (e.g., cell-based therapies and noninvasive stimulation). The noradrenergic system has been extensively studied for neural repair after brain injury (Barbay and Nudo, 2009 and Walker-Batson, 2013). D-amphetamine has been shown to improve functional recovery in both rodents and nonhuman primates (Barbay and Nudo, 2009 and Feeney et al., 1982), possibly through augmentation of neural plasticity. However, d-amphetamine

treatment of stroke patients with motor and language deficits has yielded mixed outcomes (Walker-Batson, 2013). This highlights the challenge associated with translation from animal models to patient care. Moreover, CP-868596 mw the selective serotonin reuptake inhibitor (SSRI) fluoxetine, which is used widely for depression and other psychiatric illness, has effects on synaptic plasticity, neurogenesis, and the BDNF level in

the brain (Pilar-Cuéllar et al., 2013). It has been demonstrated to improve motor recovery after stroke in a recent clinical trial (Chollet et al., 2011) and is a promising drug for patients with amblyopia (Maya Vetencourt et al., 2008), presumably through modulation of cortical inhibition (Espinosa and Stryker, 2012). Since inhibitory interneurons play a key role in shaping cortical function and plasticity, modulation of cortical inhibition offers a general mechanism of enhancing recovery by engaging neural plasticity (Ramamoorthi and Lin, 2011). Reduction of inhibition in the visual system, for example, can restore a juvenile state of plasticity in the adult Levetiracetam rodent brain (Espinosa and Stryker, 2012 and Maya Vetencourt et al., 2008). Many genetic disorders with cognitive deficits, such as autism and Down syndrome, are also associated with excessive inhibition (Ramamoorthi and Lin, 2011 and Wetmore and Garner, 2010). In the case of Down syndrome, reducing inhibition in a genetic model was found to improve cognitive function (Fernandez et al., 2007). Reduction of extrasynaptic GABAergic currents has also improved motor recovery in animal models of focal stroke (Clarkson et al., 2010). Cell-based therapies also have a great potential to result in novel treatments (Leong et al., 2013, Sanberg et al.

The space-only model provided a better fit (ρ=0 66ρ=0 66) as comp

The space-only model provided a better fit (ρ=0.66ρ=0.66) as compared to the local orientation information (ρ=0.22ρ=0.22), and,

in fact, the combined orientation and spatial information in the full model slightly worsens the prediction (ρ=0.60ρ=0.60). This neuron may thus be largely nonselective to orientation but nevertheless exhibits curvature selectivity at the boundaries of the RF due to spatial inhomogeneity. This highlights to what extent texture- or nonorientation-selective units can exhibit curvature-selective responses at their spatial boundaries. Other cells tuned for high-curvature shapes exhibited similar orientation heterogeneity (Figure 6, top row) and had selectivity LBH589 molecular weight for curved shapes typically at the RF boundary (see examples in Figure S3). To test the predictive power of the model, we computed a null distribution of the correlation coefficients

by repeatedly shuffling the fine-scale orientation maps and then generating response patterns from these shuffled maps (Figure S5A; see Experimental Procedures). This shuffling procedure perturbed the relative spatial structure of the fine-scale CX-5461 price map within a coarse grid location. It thus serves as a comparison against which to test whether contour preferences at a given location depend on the spatial arrangement of the local orientation map. Using this procedure, we calculated whether any of the model correlations (across all spatially significant locations) were significantly different from chance (p = 0.05) after correcting for multiple comparisons. The spatial locations where the model correlations are significant are demarcated with “x” for our example neurons (Figure 7A, lower left panels). Across the population, 80% of neurons showed a significant prediction (i.e., at least one RF location with significant p value; on average

40% of the RF locations had significant p values). The linear pooling model accounts for a substantial fraction of the response variance (see Experimental Procedures) across neurons with varied shape preferences. Figure 7B shows a scatterplot of the mean explained variance (averaged across RF locations) ADAMTS5 for the full model versus average shape preference. The marginal distribution of the mean explained variance has a median value of 0.25. Examining the histogram of explained variance for the full and reduced models (Figure 7C), we see that the orientation-only model plays a dominant role for the straight/low-curvature categories (linear Pearson correlation, r = −0.4, p < 0.001). Note that the local orientation significantly improved fits for medium-curvature neurons (p < 0.001), though not for high-curvature neurons. Thus, for medium curvature, local orientation plays a significant role. Meanwhile, the space-only model plays a key role across all shape categories (r = 0.09, p = 0.02). In general, the full model is the best predictor across the population.

, 2010) OHC forces generated from changes in length of the cell-

, 2010). OHC forces generated from changes in length of the cell-body are attributed to perturbations in cell membrane potential triggered by current entering through the mechanotransduction (MT) channels in the stereocilia.

These somatic forces have been traced to the protein prestin that is densely packed into the cell’s basolateral membrane, and which undergoes rapid changes of area when the receptor potential changes. Isolated OHCs generate forces in response to voltage stimuli Cilengitide ic50 up to at least 80 kHz (Frank et al., 1999). In the intact cochlea, however, the electrical filtering effect of the cell membrane, effectively possessing an electrical time constant = RmCm, would reduce potential changes to negligible levels at

any significant acoustic frequencies. Consequently, even though prestin-knockout mice are deaf (Liberman et al., 2002 and Mellado-Lagarde et al., 2008), the proposal that the prestin-dependent cell body forces account for functional amplification in the Venetoclax chemical structure cochlea has never quite held together. The central issue is known as the “RC time-constant problem.” There have been numerous solutions proposed to address this conundrum. However, the paper by Johnson et al. (2011) in this issue of Neuron indicates a clear way out of the impasse for prestin-based mechanisms, for it shows that the OHC time constants may have been significantly overestimated. Methods for recording in the mammalian cochlea have developed slowly compared to recordings Casein kinase 1 made in other vertebrate species, and it is only relatively recently that reliable recordings of transduction currents have been made

from mature mammalian hair cells. Johnson et al. (2011) have recorded from both rats and gerbils where OHCs can be selected from known frequency points along the cochlea. By measuring the transduction and basolateral membrane currents in OHCs from different cochlear positions in excised cochleas, the paper shows that the OHC membrane filtering may be an order of magnitude less than previously thought. As a result, receptor potentials would be uniformly larger. The authors present several lines of experimental evidence to support these arguments. First, they find that MT channel currents are significantly larger when recorded from OHCs taken toward the high-frequency end of the cochlea. This observation has been inferred several times from in silico cochlear model studies (Mammano and Nobili, 1993 and Ramamoorthy et al., 2007) and is seen in data from nonmammalian cochleas, but the records here show the effect clearly in mammalian hair cells. Second, the paper shows that resting transducer currents, irrespective of cochlear place of origin, are further enhanced when the OHC stereocilia face low Ca2+ concentrations (20 μM) as they do in the living cochlea (in vivo the stereocilia project into a low Ca2+/high K+ containing compartment, referred to as the scala media).

g , the slightly reduced pHGluA2 fluorescence decrease seen with

g., the slightly reduced pHGluA2 fluorescence decrease seen with DHHC5 transfection; Figure 6D). In addition, the presence of transfected DHHC5 in long, aspiny neurites that are likely axons, suggests that DHHC5 may palmitoylate additional axonal/presynaptic substrates in addition to its dendritic regulation of GRIP1b described here. The identification of additional DHHC5/8 substrates remains an exciting area for future investigation. We note with interest find more that other PATs cannot compensate for loss of DHHC5/8 to palmitoylate GRIP1 in neurons, and in transfected cells even PATs that display broad substrate specificity (DHHC3, DHHC7; Fukata et al., 2004, Fernández-Hernando et al., 2006, Greaves

et al., 2008, Ponimaskin et al., 2008 and Tsutsumi et al., 2009) or preferentially palmitoylate cysteines located close to the N termini of

their substrates (DHHC20; Draper and Smith, 2010) do not palmitoylate GRIP1b (Figure S1). These findings suggest that GRIP1b palmitoylation by DHHC5/8 has distinct requirements, namely that the PDZ domain interaction unique to DHHC5 and DHHC8 is essential to render GRIP1b accessible as a substrate. DHHC5, in particular, is a major GRIP1b PAT in neurons but cannot palmitoylate several other palmitoyl-proteins (Fukata et al., 2004, Fernández-Hernando et al., 2006, Greaves et al., 2008 and Tsutsumi et al., 2009), suggesting that PDZ domain-dependent recognition is a

key determinant of DHHC5 substrate specificity. Multiple studies link DHHC5 and DHHC8 to both normal higher brain function and neuropsychiatric disease (Mukai et al., 2004, Mukai et al., 2008 and Li et al., 2010). However, to our knowledge, no neuronal substrates have been identified for DHHC5, and although PSD-95 palmitoylation is reduced in DHHC8 knockout mice (Mukai et al., 2008), other PATs are also reported to directly palmitoylate PSD-95 in neurons (Noritake et al., 2009), raising the Terminal deoxynucleotidyl transferase possibility that this may be an indirect effect. Thus, our identification of GRIP1b as the first bona fide neuronal substrate for DHHC5/8 has broad implications, since GRIP1 is also genetically linked to neuropsychiatric conditions and to autism (Gratacòs et al., 2009 and Mejias et al., 2011). This raises the possibility that abnormal dendritic and/or synaptic palmitoylation of PDZ domain proteins such as GRIP1 contributes to the pathogenesis of these conditions. Indeed, another PDZ domain protein linked to neuropsychiatric disease is also palmitoylated by DHHC5 and DHHC8 in a PDZ ligand manner (G.M.T., T.H., and R.L.H., unpublished data). These findings raise the hope that therapeutic targeting of specific PATs and/or their interactions with specific substrates may provide a new approach to better therapeutic treatments for these diseases. The following antibodies, from the indicated sources, were used in this study.

These samples were derived from cattle epithelial tissues (except

These samples were derived from cattle epithelial tissues (except one of ovine origin), and ZD1839 were initially grown in primary bovine thyroid cells with subsequent passage in either BHK-21 or IB-RS2 cells. Stocks of virus were prepared by infecting IB-RS2 cell monolayers and were stored as clarified tissue culture harvest at −70 °C until required. Supplementary Table S1.   List of serotype A viruses used in this study. nd: not designated; nk: not known. The P1 sequences have been submitted to Gene Bank and awaiting accession numbers. Antisera were prepared against serotype A FMD viruses (A22/Iraq

and A/TUR/2006) by immunising five cattle per v/s with inactivated, purified 146S FMD virus particles in ISA-206 adjuvant. Bulk blood was collected on 21 day post-vaccination for preparation of sera. For each antigen, a pool of sera from five animals was used in the serological tests. The A22/Iraq and A/TUR/2006 antisera exhibited equivalent homologous titres (log10 2.43 and 2.54, respectively) by virus neutralisation test (VNT). The 2D-VNT was carried out using the 21-day post-vaccination sera following established methodology [14]. Antibody titres were calculated from regression data as the log10 reciprocal antibody dilution required for 50% neutralisation of 100 tissue culture infective

units of virus (log10SN50/100 TCID50). The antigenic relationship of viruses based on their neutralisation by antibodies Bcl-2 protein family is given by the ratio: ‘r1′ = neutralising antibody titre against the heterologous virus/neutralising antibody titre against the homologous virus. Differences in the r1-values obtained by the polyclonal antiserum were evaluated according to standard criteria Farnesyltransferase [15]. The sequences of the entire capsid coding

region (P1) of selected viruses were generated. RNA extraction from the cell culture grown viruses and reverse transcription (RT) were performed as described [16]. PCR was carried out using the “KOD hot-start DNA polymerase” kit (Novagen) as recommended by the manufacturer, using the forward primer L463F (5′-ACCTCCRACGGGTGGTACGC-3′) and one of the reverse primers NK72 (5′-Libraries GAAGGGCCCAGGGTTGGACTC-3′) or EUR2B52R (5′-GACATGTCCTCCTGCATCTGGTTGAT-3′). PCR products were purified using the QIAquick PCR purification kit (Qiagen) according to the manufacturer’s instructions and sequenced using BigDye® Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems, Carlsbad, CA, USA) using the PCR primers and additional internal sequencing primers (sequences available on request). Sequences (from the ABI 3730 machine) were assembled and analysed using SeqMan II (DNAStar Lasergene 8.0). Nucleotide sequences of the viruses were aligned using the CLUSTAL X multiple sequence alignment program [17] and the predicted aa sequences were translated using BioEdit 7.0.1 [18].