During development, cortical layers form in an “inside-out”

fashion and deep layers are composed of early-born Entinostat molecular weight neurons, while superficial layers are composed of later-born neurons ( Rakic, 2009). The cortical layers of E18.5 PP4cfl/fl;Emx1Cre brains were thinner and more disorganized than their control counterparts ( Figure 1). Brn2-positive neurons, which are produced during late neurogenesis and form the upper cortical layers II-III, did not form a cohesive layer in the cortex of PP4cfl/fl;Emx1Cre brains. Some Brn2-positive neurons are found even in the deep cortical layers ( Figures 1E and 1H). Layer V neurons, produced around the peak of neurogenesis ( Molyneaux et al., 2007) and positive for Ctip2, were dispersed throughout the cortex in PP4c-deficient brains ( Figures 1F and 1I). In contrast, the majority of neurons in the cerebral cortex of PP4cfl/fl;Emx1Cre brains are Tbr1 Cabozantinib purchase positive, although they are not organized into a cohesive layer ( Figures 1G and 1J). Thus, PP4c is required in RGPs at the onset of neurogenesis for

proper cortical layer formation. To identify the cellular basis for the layering defect, we examined neuronal differentiation by immunostaining for the early neuronal marker Tuj1. At E11.5, shortly after Emx1Cre activation, we did not observe any obvious differences in neuronal differentiation between heterozygous control and PP4c mutant mouse brains ( Figures 2A and 2D). At E12.5, however, more neurons were generated in the mutants when compared to control brains ( Figures 2B and 2E). This phenotype is even stronger at E13.5 when almost the entire cortex Dipeptidyl peptidase including the VZ and SVZ is occupied by differentiated neurons in mutant mice ( Figure 2F), while only a few neurons in the cortical plate are seen in controls ( Figure 2C). To examine whether supernumerary neurons are generated at the expense of progenitors, we stained control and mutant brain sections for phospho-Histone H3 (PH3) to mark mitotic progenitors. At E11.5, the

numbers of PH3-positive progenitors in mutant and control brains were comparable (Figures 2G, 2J, and 2M). At E12.5, however, the number of mitotic progenitors was significantly reduced in the mutant brains and this effect became even stronger at E13.5 (Figures 2H, 2I, 2K, 2L, and 2M). When we examined the number of Pax6-positive RGPs and Tbr2-positive BPs, we found that both types of progenitors were depleted in the PP4c mutant brains ( Figures 2N–2S). Interestingly, loss of PP4c seems to have stronger effects on Tbr2-positive BPs (37.5% of control) compared to Pax6-positive RGPs (67.5% of control). The reduction in BP cell number could be an indirect consequence of the reduction in RGPs, although we cannot rule out that PP4c directly regulates BPs. To test whether the observed generation of supernumerary neurons correlates with increased cell-cycle exit, we labeled cycling progenitors by EdU incorporation at E12.

5, n = 9) probably due to the prolonged inhibitory effect of AON stimulation. Using 50 ms bins,

we were unable to find evidence for fast excitation that was observed in the in vitro experiments. We therefore constructed PSTHs using 1 ms bins. By comparing these PSTHs to randomly aligned PSTHs, we found significant fast excitation in 9 out of 20 cells (see Experimental Procedures). An example of this excitation is find more shown in Figure 8. While only inhibition was seen with 50 ms bins (Figure 8A), a very brief and precise excitation was evident with finer binning (Figure 8B). Excitation in this cell was manifested as a 1 bin (1 ms) of increased probability of firing from 1% to 8.9%, with a latency of 5 ms (Figure 8C). This latency was markedly Selleck PD0325901 different from the latency to the photoelectric artifact that always coincided with the first bin of light stimulation (Figure 8D). On average, AON axon stimulation increased firing probability 9.5 ± 3.3 times with a latency of 6 ± 1.8 ms (n = 9). Average population PSTHs pooling data from the nine cells that were excited by the AON

fibers and of the whole population, are shown in Figure 8E. Figure 8F shows the nine cell histogram at an enlarged scale. The duration of the excitatory response in the average PSTH mostly reflects the variability in the latency among the cells. Indeed, if responses were aligned on the peaks of each cell’s excitation, the average PSTH exhibited a narrow peak of less than 5 ms (Figure 8G).

Importantly, no excitation was evident in any of the control cells (n = 11, Figure 8H). We did not find any evidence of rapid excitation in odor-evoked responses. These results reveal that activation of AON axons in vivo leads to an immediate and brief increase in firing probability of MCs, followed by a longer lasting inhibition. We used optogenetic methods to selectively activate feedback axons to the OB, and determine their cellular targets and their functional effects on bulbar output neurons. The major findings of Mephenoxalone our study are that: (1) AON axons have a dual effect on MCs: fast, brief depolarization and more prolonged hyperpolarization, (2) the fast depolarization is likely to be due to direct monosynaptic excitation, (3) the inhibitory effect of AON activation on MCs is mediated through GCs as well as glomerular layer interneurons, and (4) as a result of these synaptic effects, activation of AON axons could impose precisely timed spikes on output neurons, followed by suppression of spikes for tens of milliseconds. Broadly similar results, but with some interesting specific differences, have been reported for feedback projections from the piriform cortex in independent work (Boyd et al., 2012). Cortical inputs to the OB are diverse (Price and Powell, 1970; Pinching and Powell, 1972; Davis et al.

NDEL1 is another

DISC1 interacting protein that regulates neuronal development in vivo (Duan et al., 2007, Sasaki et al., 2005 and Shu et al., 2004). Consistent with our previous findings (Duan et al., 2007), expression of a specific shRNA against mouse ndel1 (shRNA-N1) led to developmental defects of newborn dentate granule cells, mostly in the appearance of ectopic dendrites and aberrant positioning ( Figure 4). Thus, FEZ1 and NDEL1 appear to mediate DISC1 signaling in a complementary set of neuronal developmental processes. To determine whether FEZ1 and NDEL1 also functionally interact to regulate development of Ribociclib mouse newborn neurons, we performed double knockdown experiments in vivo. The effect of coexpressing shRNA-F1 and shRNA-N1 on dendritic growth and soma size of newborn neurons was very similar to those expressing

shRNA-F1 alone ( Figures 4A–4C), whereas the effect on ectopic dendrites and neuronal positioning was similar to those expressing shRNA-N1 alone ( Figures 4D and 4E). Thus, concomitant suppression of NDEL1 and FEZ1 only leads to buy BGB324 additive effects of individual knockdown, instead of a synergistic action. These results further support the notion that FEZ1 and NDEL1 differentially regulate distinct aspects of new neuron development in the adult brain. KIAA1212/Girdin is also a DISC1 binding partner that regulates development of newborn dentate granule cells in the hippocampus (Enomoto et al., 2009 and Kim et al., 2009). We next examined whether KIAA1212 interacts with FEZ1 or NDEL1 in regulating neuronal development. Consistent with previous findings, DISC1 was co-IPed with each of whatever the three proteins, NDEL1, FEZ1, or KIAA1212, when each pair was coexpressed in the heterologous system (Figure S4A).

Furthermore, these four proteins could be co-IPed together with DISC1 when all were coexpressed (Figure S4A). Also consistent with the previous finding (Kim et al., 2009), overexpression of KIAA1212 led to increased total dendritic length, number of primary dendrites, and soma size in newborn neurons in the adult dentate gyrus (Figures S4B–S4D). Compared with KIAA1212 overexpression or FEZ1 knockdown alone, comanipulation exacerbated phenotypes of increased dendritic length and soma size, but not the number of primary dendrites and positioning of newborn neurons (Figures S4B–S4E). On the other hand, simultaneous KIAA1212 overexpression and NDEL1 knockdown exhibited phenotypes very similar to those of NDEL1 knockdown alone (Figures S4B–S4E). Taken together, these results support a model that DISC1 interacts with FEZ1 and KIAA1212 mainly to regulate dendritic growth and soma size of newborn neurons during adult neurogenesis, whereas DISC1 interacts with NDEL1 mainly to regulate positioning of newborn neurons (Table 1).

26 pA, n = 14 and ET33-Cre::VGLUT2flox/flox = 1136.36 ± 126.19 pA, n = 12; p > 0.05 by Student’s t test), whereas ipsilateral responses were significantly reduced (Figures 2H and 2J; VGLUT2flox/flox = 256.08 ± 49.90pA, n = 17 and ET33-Cre::VGLUT2flox/flox = 7.54 ± 3.60 pA, n = 22; p < 0.0001 by Mann-Whitney U test). In P10 ET33-Cre::VGLUT2flox/flox slices, only 18% of dLGN neurons responded to ipsilateral axon stimulation (4 of 22 compared to 17 of 19 in controls) and selleck chemical their average response sizes were reduced by 97%. AMPAR-mediated ipsilateral responses were also further reduced

between P5 and P10 (Figures S2H–S2M). Collectively, our electrophysiological findings demonstrate that glutamatergic

Src inhibitor synaptic transmission is selectively and progressively reduced in the ipsilateral retinogeniculate pathway of early postnatal ET33-Cre::VGLUT2flox/flox mice. What role does synaptic competition play in eye-specific retinogeniculate refinement? To address this question, we analyzed ipsilateral and contralateral projections at different developmental stages in ET33-Cre::VGLUT2flox/flox animals by labeling axons from each eye with CTb-488 or CTb-594. In wild-type mice, ipsilateral and contralateral axon territories overlap in the dLGN at P4 (Godement et al., 1984 and Jaubert-Miazza et al., 2005) and we found that on P4 both Cre-negative and Cre-expressing VGLUT2flox/flox littermates exhibited overlapping axonal projection patterns typical for this age (Figures 3A–3C). In wild-type mice, Parvulin eye-specific territories are clearly visible by P10 (Godement et al., 1984, Jaubert-Miazza et al., 2005 and Muir-Robinson et al., 2002) (Figure 3A). Based on previous studies (Penn et al., 1998 and Stellwagen and Shatz, 2002), we predicted that the synaptically weakened ipsilateral axons would fail to outcompete and eject contralateral axons from their territory

and that the ipsilateral eye territory would be reduced. Indeed, we found that in the ET33-Cre::VGLUT2flox/flox mice, contralateral eye axons failed to retract from the ipsilateral region of the dLGN (Figure 3A), resulting in a greater than normal degree of overlap between ipsilateral and contralateral axons (Figure 3D; n = 8 mice for each genotype). The increased overlap was significant over a wide range of signal-to-noise thresholds (Figure 3D) (see Experimental Procedures). The abnormal degree of overlap did not occur in animals expressing ET33-Cre alone or ET33-Cre and one floxed VGLUT2 allele (Figure S3D). These data provide evidence that effective glutamatergic transmission is crucial for mediating axon-axon competition during CNS refinement. Surprisingly, however, reducing ipsilateral synaptic transmission did not alter the overall pattern of the ispilateral terminal field (Figures 3A and 3E and Figure S3).

By comparing rat CSF from several ages, we determined that the effects of CSF on survival and proliferation are strikingly age dependent and mimicked the temporal profile of CSF-Igf2 expression (Figure 3C). E17 CSF (near the middle of neurogenesis) maintained the healthiest explants and produced the maximal increase in the frequency of PH3-labeled proliferating cells in E16 cortical explants compared to explants cultured with E13 (early in neurogenesis), P6, or adult CSF

(Figures 4D, 4E, S2C, and data not shown). Many mitotic cells were identified as proliferating neuroepithelial progenitor cells by their immunoreactivity for phospho-Vimentin (4A4; Figures 4F and S2C). In contrast, no differences were Selleck Kinase Inhibitor Library seen in Tbr2-positive basal progenitors, which do not contact the CSF directly (data not shown). Together, these data suggest that age-dependent differences in CSF signals are both supportive Selleck DAPT and instructive for neuroepithelial

precursor proliferation in the developing cortex. The CSF effects may be specific to neuroepithelial progenitors, which contact the ventricle through the apical complex, without affecting the intermediate progenitors of the SVZ. We tested directly whether CSF-borne Igf2 was necessary to explain the effects of age-specific CSF on rat cortical explants. The frequency of proliferating cells declined in explants grown in E17 CSF in the presence of Igf2 neutralizing antibodies (Igf2 Nab; Figure 4G). Igf2 neutralization with Igf2 NAb did not interfere with

Igf1 levels in CSF compared to control as assayed by ELISA (data not shown). While Igf signaling is known to promote neuronal survival (Popken et al., 2004), we did not observe differences in ventricular progenitor cell survival in these explant experiments (data not shown), suggesting that Igf actions on neural cell survival likely depends on the cell type, developmental stage, and microenvironment. These data confirm the important role for CSF borne Igf2 in regulating cerebral cortical progenitor cells but do not rule out roles of other CSF borne factors as well. Neural stem cells Dipeptidyl peptidase cultured as neurospheres confirmed the age-dependent capacity of CSF to maintain neural stem cells (Reynolds and Weiss, 1996) and provided additional evidence suggesting that Igf2-mediated signaling is an essential determinant of CSF activity on neural stem cells. CSF from any age supported the proliferation and maintenance of isolated cortical stem cells cultured as primary or secondary neurospheres (Figure 4H and data not shown; Vescovi et al., 1993). However, E17 CSF was maximally effective in generating increased numbers of neurospheres, larger neurospheres, and maintained neurospheres even in long-term cultures for up to 44 days in vitro (Figures 4H, S2D–S2G, and data not shown).

Third, the iso-response

measurements can assess nonlinearities of stimulus integration by retinal ganglion cells independent of the cell’s intrinsic nonlinear processing. This cell-intrinsic nonlinearity implicates, for example, that it is typically not possible to check for linear summation of inputs by comparing the response for multiple simultaneous stimulus components to the sum of responses for the individual components. Such a measurement would require an accurate model of cell-intrinsic signal processing in order to tease apart the different nonlinearities that ultimately affect the response. Fourth, focusing on a fixed response level Linsitinib naturally keeps the neuron close to a constant adaptation level and thus minimizes confounding adaptation effects, as might result from sporadically driving the neuron at particularly high firing rates. And fifth, iso-response stimuli seem a natural way for investigating the dimensional reduction that results when neurons integrate several inputs and map these inputs onto a low-dimensional response, such as the neuron’s spike count. A fundamental consequence is that different input patterns will be mapped click here onto the same output. This contributes to establishing invariances, which represent a hallmark of neural computation (Riesenhuber and Poggio, 2000) and underlie complex recognition and decision tasks. It thus appears

appropriate to assess computation at the single-neuron level also by identifying which stimuli are classified as equal. Indeed, measuring iso-response stimuli can provide a new perspective

on nonlinear signal integration not apparent in other, standard approaches. For example, a simple model simulation shows that homogeneity detectors look just like typical Y-type cells for contrast-reversing gratings (Figure S1 available online), the classical stimulus to test for nonlinear spatial integration. A caveat of the closed-loop experiments is that they rely on accurate online detection nearly of the incoming signals, here the ganglion cell spikes. Systematic errors in spike detection could, in principle, lead the search for the predefined response astray. We avoided such pitfalls by selecting only ganglion cells whose spikes were sufficiently large for simple and unambiguous detection through threshold crossing. In addition, we verified the accuracy of the online spike detection by additional in-depth offline analysis of the spike waveforms. The selection of large and reliable spikes, however, may add to a potential recording bias (Olshausen and Field, 2005); ganglion cell types with small cell bodies, for example, might not always create spikes with sufficient size in the extracellular recordings (Towe and Harding, 1970 and Olshausen and Field, 2005) to pass our criterion of reliable spike detection and may therefore be underrepresented in our analysis.

Rabbit polyclonal antibodies against mSYD1A were raised against a synthetic peptide (MAEPLLRKTFSRLRGREK) and CH5424802 molecular weight affinity purified on the antigen. Anti-pan-neuroligin was described previously (Taniguchi

et al., 2007). Rabbit anti-munc18 was a gift from Matthijs Verhage (de Vries et al., 2000). Other antibodies were purchased from commercial sources: mouse anti-actin (clone AC-40, Sigma-Aldrich), goat anti-cyclinA (#sc-31086, Santa-Cruz), mouse anti-PSD95 (#73-028, Neuromab), mouse anti-VAMP2 (clone 69.1, Synaptic Systems), anti-vesicular glutamate transporter 1 (vGluT1, #1353303, Synaptic Systems), rabbit anti-GAPDH (#E1C604, Enogene), mouse anti-CASK (#75-000, Neuromab), rabbit anti-munc13-1 (#126103, Synaptic Systems), rabbit anti-munc18-1 (#116002, Synaptic Systems), mouse anti-beta-tubulin (E7, DSHB), rabbit anti-ELKS 1b/2 (#143003, Synaptic Systems), rat anti-HA (clone 3F10, Roche Applied Science), rabbit anti-c-myc (#sc-789, Santa-Cruz), mouse anti-flag (#F1804, Sigma), rabbit anti-homer (#160003, Synaptic Systems), mouse anti-bassoon (#GTX13249, GeneTex), rabbit anti-calbindin (#CB38a, Swant), mouse anti-NeuN (#MAB377, Chemicon). Secondary

antibodies conjugated to cyanine dyes or Alexa 488 or 643 (Jackson ImmunoResearch and Invitrogen) were used for visualization in immunostainings. Candidate intrinsically disordered protein domains were predicted using the PrDOS server, an online tool that combines local amino acid information and template protein references (http://prdos.hgc.jp/cgi-bin/top.cgi) (Ishida and Kinoshita, 2008). The thermostability test for confirmation of intrinsically OSI-744 mw disordered sequences was performed as described previously (Galea et al., 2006). Briefly, HEK293T cells on 10 cm diameter dishes were transfected with expression constructs for mSYD1A. After 24 hr, cells were harvested in PBS with a cell scraper and resuspended

in 300 μl of Buffer A (10 mM sodium phosphate buffer [pH 7.0], 50 mM NaCl, 50 mM DTT, 0.1 mM sodium orthovanadate, complete protease inhibitor Roche]). Cells were mechanically cracked by passing L-NAME HCl through a 25G needle and centrifuged at 16,000 × g for 30 min at 4°C. The supernatant was transferred to a fresh tube and the protein concentration was adjusted to 1 mg/ml with Buffer A. The cell lysate was heated for 30 min or 1 hr at 90°C. The protein mixture was placed on ice for 15 min and centrifuged at 16,000 × g for 30 min at RT. Soluble proteins in the supernatant were precipitated with 10% trichloracetic acid. The pellets were resuspended in SDS-PAGE buffer and analyzed by western blotting. Förster-resonance energy transfer (FRET) assays were performed as described previously (Itoh et al., 2002). Briefly, HEK293T cells were transfected with the RhoA sensor (Pertz et al., 2006) and expression constructs of interest. After 48 hr cells were suspended in 1× PBS.

The degree of enhancement did not depend on the distance of the dendritic recording site from the soma (Figure S1). The enhancement of dendritic CF response amplitudes

was associated with an increase in the number of spikelets within the somatically recorded complex spike (144.8% ± 3.7%; n = 7; p = 0.028; Figure 2B). Under control conditions, these parameters remained stable (amplitude: 97.0% ± 5.9%; p = 0.636; spikelet number: 102.6% ± 5.3%; n = 6; p = 0.652; Figures 2B and S2). Repeated current injection did not result in significant input resistance changes (dendrite: 90.2% ± 8.2%; p = 0.276; soma: 96.3% ± 6.9%; p = 0.613; n = 7; Figure S3). Patch-clamp recordings Anti-cancer Compound Library solubility dmso from the rat cerebellum in vivo show that sensory stimulation results in brief high-frequency bursts in granule cells, identifying a physiologically relevant activity pattern of PF synaptic Z-VAD-FMK concentration signals (Chadderton et al., 2004). PF burst stimulation (50Hz bursts; 5 pulses; repeated at 5Hz for 3 s) caused an increase in the CF response (112.2% ± 2.7%; p = 0.010) that was associated with an increase in the spikelet number (128.7% ± 9.6%; n = 5; p = 0.040; Figures 2C and 2D). Moreover, the PF

burst protocol enhanced the number of depolarization-evoked spikes (Figure S4). Taken together, these data show that dendritic plasticity can be triggered by synaptic or nonsynaptic activity patterns. Repeated depolarizing current injections into the soma also increased the amplitude of dendritic Na+ spikes that were elicited by somatic test

current pulses (139.5% ± 15.2%; n = 10; p = 0.029; Figure 3). This enhancement was accompanied by an increase in the number of evoked spikes (spike count) in somatic and dendritic recordings (179.4% ± 29.7%; n = 10; p = 0.028; Figure 3). Under control conditions, both the dendritic spike amplitude (96.7% ± 8.3%; p = 0.711) and the spike count remained constant (105.5% ± 10.1%; n = 5; p = 0.613; Figures 3 and S2). The finding that somatic depolarization, a nonsynaptic activation protocol, causes an increase in the amplitude of dendritic Na+ spikes, a nonsynaptic response, indicates that the underlying process involves modifications of intrinsic membrane properties, and that this modification occurs in Purkinje cells. SK channel activity else influences Purkinje cell firing frequency and regularity (Edgerton and Reinhart, 2003 and Womack and Khodakhah, 2003). It has previously been shown that Purkinje cell intrinsic plasticity, measured as an increase in the number of spikes evoked by depolarizing current pulses, involves SK channel downregulation (Belmeguenai et al., 2010). To examine whether the changes in dendritic Na+ spike and CF response amplitudes described here are also mediated by downregulation of SK channel activity, we used the selective SK channel blocker, apamin. Bath-application of apamin (10nM) enhanced the amplitude of dendritic CF responses (119.0% ± 6.2%; p = 0.028; Figure 4A) and the number of spikelets in the somatic complex spike (137.

The secreted form of recombinant FSTL1 was glycosylated and had a molecular mass of ∼37–45 kDa (Figure S3D). Deglycosylated FSTL1 had a molecular weight of ∼34 kDa (Figure S3D). Recombinant glycosylated FSTL1 was used to examine the effect of

exogenous FSTL1 on synaptic transmission between afferent terminals and local neurons in lamina II (substantia gelatinosa), a translucent band in the superficial dorsal horn. We found that among ∼50% (16/31) of recorded neurons, application of FSTL1 (60 or 300 nM) resulted in a reduction of more than 10% in the mean frequency or mean amplitude Vorinostat mw of spontaneous excitatory postsynaptic currents (sEPSCs) (Figure 3B). Similar application of FSTL1 also reduced the amplitude of C-fiber stimulation evoked EPSCs (eEPSCs), which were present in 50% (12/24) of recorded monosynaptic neurons (Figures 3C and 3D). A similar inhibitory effect of FSTL1 (60 nM) was found in polysynaptic neurons

(Figure S3E). Further studies of miniature EPSCs (mEPSCs) in the presence of tetrodotoxin (0.5 μM) showed that FSTL1 also reduced the frequency, but not the amplitude, of mEPSCs (Figure 3E), suggesting that there is presynaptic suppression of glutamate release by FSTL1. The decay kinetics of eEPSCs were unaffected by FSTL1 (Figure 3D), indicating that FSTL1 had no direct effect on postsynaptic glutamate receptor channel properties. Together, these results suggest that FSTL1 acts presynaptically on neurotransmitter release, rather than postsynaptically on glutamate responses. selleck chemicals llc In addition, for neurons that showed FSTL1-induced eEPSC reduction, the synaptic delay after C-fiber stimulation was reversibly increased (Figure 3C),

oxyclozanide suggesting a presynaptic reduction of excitation-secretion coupling and/or impeded action potential (AP) propagation in the C-fiber. Finally, the specificity of FSTL1 function was indicated by the lack of synaptic suppression effects of follistatin or two mutated forms of FSTL1 that either have a pair of EF-hands deleted (FSTL1ΔEF) or a loss-of-function mutation at the Ca2+-binding site Glu165 (FSTL1E165A), which is conserved across species (Figures 3C and 3E and Figures S3F and S3G). Thus, exogenous FSTL1 suppresses afferent synaptic transmission in the dorsal horn through presynaptic inhibition. How does FSTL1 act on presynaptic nerve terminals? To identify the protein’s membrane target, we used the membrane-impermeant bifunctional reagent bis[sulfosuccinimidyl] suberate (BS3) to chemically crosslink recombinant FSTL1 with myc and His tags to components present on the surface of cultured rat DRG neurons. The cell lysate was analyzed by an immunoblot with myc antibodies.

contortus ( Fig. 1) and T. colubriformis ( Fig. 2). There was no difference between the breeds (P > 0.05) and there was a low variation in serum IgG levels against GIN antigens tested throughout the experiment, except for the levels of IgG against L5 for T. colubriformis and IgG against L3 for H. contortus, which increased significantly until the end of the experiment for both breeds (P < 0.05). No significant interactions were observed between time x group regarding parasite

specific IgG levels or FEC (P > 0.05). The IgA levels in nasal, Crizotinib mouse abomasal and intestinal mucus were similar in both breeds ( Fig. 5). Although the experimental groups were composed of a limited number of animals, a significant (P < 0.05) positive correlation was observed in both breeds between the number of O. ovis larvae × IgG against Oestrus CE in IF (r = 0.58) and SI (r = 0.66),

between O. ovis larvae × IgG against Oestrus ESP in IF (r = 0.59) and SI (r = 0.63). IF lambs showed a significant positive correlation between the number of O. ovis larvae x globule leucocytes in the nasal meatus (r = 0.71; P < 0.05). With regard to GIN burden and immune response, significant correlations were observed just in SI lambs: abomasum mast cells × H. contortus burden (r = −0.73; P < 0.05); IgG against L3 Hc × H. contortus burden (r = −0.72; P < 0.05); IgA against L5 Hc × H. contortus burden 3-mercaptopyruvate sulfurtransferase (r = −0.61; P = 0.07); and mast cells from small intestine × T. Caspase inhibitor colubriformis burden (r = −0.60; P = 0.07). No significant correlation coefficients were observed between inflammatory cells from nasal tract and from GIN tract, with the exception of globule leucocyte values of the nasal conchae and small intestine

in IF lambs (r = 0.63; P < 0.05). Parasitism with GIN and O. ovis causes an increase in inflammatory cell numbers of the upper respiratory and gastrointestinal tract mucosas and the production of anti-parasite specific immunoglobulins ( Yacob et al., 2002, Bricarello et al., 2005, Terefe et al., 2005 and Cardia et al., 2011), changes that were observed in the present study. Such an immune response was similar in the animals of both breeds and resulted in no breed difference regarding O. ovis infestation or GIN worm burdens. However, SI lambs showed a higher proportion of L1 of O. ovis compared to IF, indicating a possible delay in larval development caused by a more intense immune response in the former breed ( Silva et al., 2012). The immune response is involved in the regulation of O. ovis populations ( Jacquiet et al., 2005), and may have an inhibitory effect on O. ovis larval growth, delaying development ( Frugère et al., 2000 and Angulo-Valadez et al., 2007b). At the beginning of this experiment the serum IgG levels against O.