Since NGL-2 affects synaptic transmission selectively in the SR pathway but does not affect the properties of individual synapses, we sought to determine whether NGL-2 exerts a cell-autonomous and pathway-specific effect on synapse density. We investigated the role of postsynaptic NGL-2 in regulating spine density by knocking down NGL-2 in a subset of CA1 pyramidal

cells. We electroporated the GFP-containing shNGL2 or control plasmids into embryonic day 15 (E15) mouse embryos (Figure 5A). Animals were perfused at P13–P15, the brains were sectioned and immunostained for GFP (Figure 5B), and spine density was analyzed on secondary apical dendrites in the stratum Raf inhibitor radiatum (Figure 5C). Consistent with the electrophysiological experiments, we found that NGL-2 knockdown caused a significant decrease in spine density on CA1 dendrites in stratum radiatum as compared to the GFP control (Figures 5D and 5G). To determine whether

the effect on spine density was selective to the dendritic segment traversing the SR, we also measured CA1 spine density on secondary apical dendrites in the SLM and found that shNGL2 expression did not affect spine density in this domain (Figures INCB018424 molecular weight 5D and 5H). Thus, postsynaptic knockdown of NGL-2 selectively affects spine density in the stratum radiatum without affecting spine density in the SLM, indicating that a major role of NGL-2 is to regulate synapse density in the SR pathway.

To identify the domains of NGL-2 that mediate its synaptic effects, we coelectroporated shNGL2 with an shRNA-insensitive full-length NGL2∗ or domain deletion mutants and quantified spine density in the SR and SLM (Figures 5E–5H). Expressing NGL2∗ rescued spine density back to control levels on dendrites in the SR (Figures 5F and 5G). We observed no change in spine density in the SLM (Figures 5F and 5H), which is consistent with the targeting of NGL-2 to SR synapses. To determine whether the LRR and PDZ-binding domains of NGL-2 contribute to the spine effects of NGL-2, we generated shRNA-resistant deletion mutants NGL2∗ΔLRR and NGL2∗ΔPDZ (Figure 5E). Like the full-length rescue construct, both mutants are insensitive to shNGL2 (Figure S3B) and reach the surface of HEK293T Electron transport chain cells (Figure S3C). Unlike the full-length NGL2∗, neither NGL2∗ΔLRR nor NGL2∗ΔPDZ could rescue the shNGL2-mediated decrease in spine density in SR (Figures 5F and 5G). Furthermore, neither mutant had an effect in SLM (Figures 5F and 5H). Thus, both the LRR and PDZ-binding domains are required for NGL-2-mediated regulation of spine density in CA1. To further explore the roles of the LRR and PDZ-binding domains in excitatory synapse formation, we overexpressed these mutants, full-length NGL2∗ or EGFP control in cultured hippocampal neurons and analyzed excitatory synapse density by staining for excitatory synapse markers PSD-95 and VGlut1 (Figure S3A).

, 1997). Noonan et al. (2010) report just such an effect (Figure 4A). The lesions were made in the medial orbitofrontal cortex in macaques, in the region Mackey and Petrides (2010) argue corresponds to the human reward-related vmPFC/mOFC region (Figure 2B). The vmPFC/mOFC reward signal in human fMRI studies is often discussed in the context of neural recordings and lesion studies of the orbital cortex of macaques and rats (Murray et al., 2007). The focus of studies conducted in SB203580 mw animals, however, is often on the more accessible lOFC rather than the vmPFC/mOFC itself. Although there

is evidence that neurons on the orbital surface of the frontal lobe encode the value of offered and chosen rewards (Tremblay and Schultz, 1999, Padoa-Schioppa and Assad, 2006, Kennerley et al., 2009 and Morrison and Salzman, 2009) the majority of recordings are made in the tissue that lies lateral to the medial orbital sulcus in the lOFC. Comparatively little is known of the activity of single neurons in vmPFC. The lOFC has distinct anatomical connections to vmPFC/mOFC selleck kinase inhibitor that suggest it has access to different types of information and is able to exert different types of influences on the rest of the brain; in other words, its functions are likely to be distinct

(Ray and Price, 1993, Carmichael and Price, 1994, Carmichael and Price, 1995a, Carmichael and Price, 1995b, Carmichael and Price, 1996, Ongür et al., 1998, Ferry et al., 2000, Kondo et al., 2003, Kondo et al., 2005 and Saleem et al., 2008). One influential idea is that lOFC and vmPFC/mOFC are relatively more concerned with negative and positive outcomes, respectively (O’Doherty et al., 2001). There have certainly been frequent replications of the finding

that vmPFC/mOFC activity is higher when reward outcomes are received for choices while lOFC activity is higher after punishment or on error trials when potential rewards are not given (Kringelbach and Rolls, 2004). As we have already seen, however, one problem for the reward versus error view of vmPFC versus lOFC is that vmPFC/mOFC appears sufficient to signal both aversive and STK38 rewarding value expectations (Tom et al., 2007 and Plassmann et al., 2010). Even more problematic for a view that emphasizes the separation of appetitive and aversive outcomes in OFC is evidence that information about both converges on the same OFC neurons. Morrison and Salzman (2009) reported no anatomical separation within the orbitofrontal area bounded by the medial and lateral orbitofrontal sulci, in neurons that responded to aversive and appetitive outcomes, such as air puffs and juice rewards, respectively. They even found neurons that responded to both types of outcome and that responded to conditioned stimuli predictive of either type of outcome.

These data indicate that Rich regulates CadN in a cell type specific manner. Loss of CadN leads to defects in cartridge formation in lamina and mistargeting of R7 cells ( Lee et al., 2001), similar to the defects we observed in rich and Rab6 mutants, suggesting that Rich and Rab6 function in a common pathway to regulate CadN trafficking. To test this, we removed one copy of CadN from eyFLP; rich1 or eyFLP; rich2 mutant animals. Loss of one copy of CadN greatly enhanced the targeting phenotype of the hypomorphic allele rich2 but not the of the null allele rich1, providing further evidence that rich and CadN function in a common pathway

( Figures 8I–8L). Moreover, homozygous double mutants for rich and CadN exhibit Selleck MK 2206 very similar phenotypes to CadN mutants. The data therefore indicate that Rich and Rab6 regulate CadN trafficking to affect axon target selection in the eye. To assess the specificity of this genetic interaction we also tested weather rich interacted genetically with other genes, including DLAR, liprin

α, or Jeb. We did not observe any interactions between rich and DLAR, liprin α, or Jeb ( Figure S6B), Small Molecule Compound Library consistent with our previous data. CadN is broadly expressed in the fly CNS and also plays important roles in determining synaptic specificity of olfactory receptor neurons (ORNs) (Hummel and Zipursky, 2004 and Zhu and Luo, 2004). To test whether rich and Rab6 mutants exhibit similar phenotypes in other neurons we focused on the ORNs. In Drosophila, around 1500 ORNs are present in the antenna and the maxillary palps. The ORNs send their axons into the antennal lobe (AL), where they form around 50 highly organized neuropilar structures, the glomeruli ( Laissue et al., 1999). The axons of

ORNs in CadN mutant typically target the appropriate region of the AL but fail to converge on a single glomerulus and instead spread out on the surface of different glomeruli ( Hummel and Zipursky, 2004 and Zhu and Luo, 2004). We generated mosaic flies with rich or Rab6 mutant ORN and wild-type AL targets using the MARCM system. eyFLP was used to induce mitotic recombination in the ORN progenitor cells but not their targets ( Hummel and Zipursky, 2004). To distinguish different subclasses of ORNs, different olfactory receptor Gal4s were used to label the mutant ORNs. We tested three different subclasses of ORNs, including two from the crotamiton antenna (OR22a, Or47b) and one from maxillary palps (Or46a). These three ORNs were previously shown to require CadN to establish proper connections with their targets ( Hummel and Zipursky, 2004). In both rich and Rab6 mutants, the AL Or47b and Or46a neurons fail to converge their axons into a single glomerulus, very similar to CadN mutants, indicating that rich, Rab6, and CadN regulate a common process in the antenna ( Figure S8C). However, the Or22a neurons do not have any obvious defects when rich or Rab6 is lost ( Figure S8C), in contrast to CadN mutants.

g., an adolescent who normally eats breakfast, but has completed some measurements after an overnight fast as part of an experimental study). Various inter-related factors have contributed to the large multi-national increase in numbers of overweight and obese young people.30 An imbalance between energy intake and expenditure is, however, often posited as the root of the problem. Breakfast consumption

and composition represent modifiable factors that are both directly and indirectly related to the balance between energy intake and expenditure. A large body of cross-sectional evidence has shown consistently an inverse association between breakfast consumption and measures of obesity (most often body mass CX-5461 in vitro index (BMI)) in large diverse samples of young people and with the adjustment selleck chemicals of potential confounding factors.3, 31 and 32 Moreover, prospective studies indicate that habitual breakfast consumption is predictive of lower BMI.11 and 31 In a longitudinal study with 2216 adolescents and a 5-year follow-up, Timlin et al.11 reported a dose–response inverse relationship between breakfast frequency and weight gain. Subsequently, a recent systematic review of 16 studies concluded that breakfast consumption was associated with reduced overweight and obesity risk in young people,3 although it should be noted that these relationships have not always been

second observed; for example, a reduction in BMI over time was associated with breakfast consumption in non-overweight, but breakfast skipping in overweight adolescents.33 Further longitudinal research with a 20-year follow-up indicated that skipping breakfast over prolonged periods of time led

to more pronounced changes in weight gain and disease risk; participants who skipped breakfast in both childhood and adulthood had a higher BMI, waist circumference, HOMA-IR score, fasting insulin concentration and total and LDL-cholesterol concentration than those who consumed breakfast at both time points.34 Breakfast consumption has also been associated with lower plasma total cholesterol concentration in young people,35 but more research is required on relationships between breakfast consumption and cardiometabolic health markers. Nutrition, meal patterns, physical activity (PA), and other lifestyle factors are likely to contribute to the lower BMI and disease risk markers in breakfast consumers. However, it is important to highlight that breakfast consumption may simply be a marker for a healthy lifestyle in general; research that can infer causality between breakfast consumption and health-related variables would be required to refute such claims. Since common breakfast foods come from the core food groups (breads and cereals, dairy products, and fruit), breakfast is typically a nutritious meal, low in fat and high in CHO.

While performing a bulk screen for editing sites in mouse brain mRNAs, Robert Reenan and colleagues identified a new candidate in mRNAs encoding Kv1.1 (Hoopengardner et al., 2003). This edit changes an isoleucine to a valine at codon 400, a highly conserved position in the sixth transmembrane span that lies along the ion

conduction pathway. Intriguingly, this site is also edited in the human brain (Figure 2). Past studies on how organic compounds block K+ currents hinted at why the I400V edit might be important: mutations at this position reduced block by quaternary amines by close to Stem Cell Compound Library 400-fold (Zhou et al., 2001). It was reasonable to speculate that I400V may have a similar effect on block by its endogenous “ball and chain,” which for human Kv1.1 is attached to the Kvβ1.1 subunit. As hypothesized, I400V had a profound effect on fast inactivation, specifically targeting the rate of recovery (Bhalla et al., 2004). While the onset of inactivation was largely unchanged, recovery from inactivation was ∼20 times faster, an outcome best explained by an increase in the inactivation particle’s rate of release from its receptor. These

selleck screening library results raised some intriguing questions. The I400V edit removes a single methyl group. Are the faster kinetics due to a reduction in hydrophobicity at position 400 and is this position within the receptor? Miguel Holmgren and colleagues provided answers to these questions with exceptional clarity (Gonzalez et al., 2011). By substituting a cysteine at position 400, they were able to independently modify either the hydrophobicity or bulk at this site by direct chemical modification. In doing so, they showed that hydrophobicity

at position 400 was the principal determinant of recovery. Further, by also substituting a cysteine at the very tip of the inactivation particle at codon 2, they were able to lock it to position crotamiton 400 through the formation of a disulfide bond. These data carry important structural implications. First of all, position 400 is located at the top of a large inner vestibule of the channel, right under the selectivity filter. Accordingly, to block current, the inactivation particle must reach deeply into the vestibule, where it’s very tip makes contact with the residue affected by the editing site. Interestingly, this mechanism may bear relevance to more than block by traditional inactivation particles. For quite some time it has been known that highly unsaturated fatty acids like arachidonic acid, which are commonly found in the mammalian brain, can block in an analogous manner, converting noninactivating K+ currents into A currents (Oliver et al., 2004). A recent report shows that the I400V edit affects block by polyunsaturated fatty acids in a similar fashion (Decher et al., 2010). Although the I400V edit is now very well understood on a mechanistic level, its importance to higher order physiology is just beginning to be explored.

This delay in the appearance of Tbx3 is consistent with a requirement for Tbx3 transcription and translation following retrograde BMP4 signaling. Similar increases in pSMAD and Tbx3 levels in the soma following axonal BMP4 treatment were also observed using western blotting ( Figures S1H and S1I). Notably,

the retrograde signal generated by axonal application of BMP4 is as robust as BMP4 signals generated by activation of BMP4 receptors in the cell body, based on their similar ability to elevate pSMAD and Tbx3 levels ( Figures S1J and S1K). We next asked if the retrograde signal is conveyed to the cell body by molecular motors. Application of the dynein inhibitor erythro-9-[3-(2-hydroxynonyl)] adenine (EHNA) (Penningroth, 1986) Small molecule library to the axonal compartment blocked the appearance of pSMAD1/5/8 and Tbx3 induced by axonal application of BMP4 (Figures 1B and 1C). Furthermore, expression of dynamitin, which disassembles the dynactin complex required for dynein motor transport (Burkhardt et al., 1997), similarly blocked the increase in nuclear pSMAD by BMP4 treatments in axons (Figure 1D). Together, these data suggest that signaling molecules conveyed from distal axons in a dynein-dependent manner mediate axonal BMP4 signaling. In the case of the neurotrophins,

retrograde signaling has been shown to be mediated by “signaling endosomes” containing endocytosed receptors that are translocated in an active ligand-bound form to the cell body where they activate their effectors (Cosker et al., learn more 2008 and Ibáñez, 2007). To test whether a similar mechanism may be involved in retrograde BMP4 signaling, we first asked whether the activity of BMP receptors is required in the cell body after axonal application of BMP4. Dorsomorphin, DMH2, and LDN193189, selective and reversible inhibitors of BMP type I receptors ALK2, ALK3, and ALK6, block BMP signaling, but not signaling by related TGF-β family for members (Yu et al., 2008). Application of these inhibitors to the cell body blocked

the increase in pSMAD1/5/8 and Tbx3 that was induced by application of BMP4 to axons (Figures 1B, 1C, and S1L–S1N). These data suggest that retrograde BMP4 signaling results in the appearance of active BMP4 receptors in the cell body, which is required for retrograde BMP4 signaling. In these experiments, we confirmed that cell body levels of SMAD1/5/8 were unchanged (Figure S1F) and no signs of cytotoxicity were observed during the time course of the experimental treatments (Figure S1O). Local action of the inhibitor in the microfluidic chambers was also confirmed (Figure S1P). To further test the idea that retrograde BMP4 signaling involves axonally derived activated BMP4 receptors, we monitored the translocation of BMP4 from the axon to the soma.

T3 was completed with 81.4% of the original number of participants (N = 1816), mean age 16.27 years; SD Epigenetic Reader Domain inhibitor 0.73 (52.3% girls). At T3, 42 subjects were unable to participate in the study, due to mental/physical health problems, death, emigration, detention or by being untraceable. With these subjects left out, response rate increases to 83.0%. More detailed information on the selection procedures and non-response bias can be found elsewhere ( de Winter et al., 2005 and Huisman et al., 2008). Analyses in the present study were based on 1.449 adolescents (53.3% girls, 46.7% boys) with non-missing data on all variables

of interest (described below). Cannabis use was assessed at T2 and T3 by self-report questionnaires filled out at school, supervised by TRAILS assistants. Confidentiality of the study was emphasized so that adolescents Selleck Epacadostat were reassured that their parents or teachers would not have access to the information they provided. Among others, participants were asked about lifetime use and

use in the last year with the following questions: ‘How often have you used cannabis in your life/in the last year’, with answer categories: ‘I have never used’, ‘used it once’, ‘used it twice’, ‘three times’,……, ‘10 times’, ‘11–19 times’, ‘20–39’ times, ‘40 times or more’). Items were recoded into five categories; (1) those who had never used; (2) those who had used but not during the past year (discontinued use); (3) those who used once or twice during the past year (experimental all use); (4) those who reported using cannabis between 3 and 39 times during the past year (regular use); and (5) those who reported using it 40 times or more during the last year (heavy use). The construction of these categories was similar to that used in other studies investigating cannabis use and mental health in young adolescents (e.g. Monshouwer et al., 2006). Internalizing and externalizing behaviour were assessed with the Youth Self Report (YSR), which

is one of the most commonly used self report questionnaires in current child and adolescent psychiatric research (Achenbach, 1991 and Verhulst and Achenbach, 1995). The YSR contains 112 items on behavioural and emotional problems in the past 6 months. Participants can rate the items as being not true (0), somewhat or sometimes true (1), or very or often true (2). The YSR covers the following domains: anxious/depressed, withdrawn/depressed, somatic complaints, social problems, thought problems, attention (hyperactivity) problems, aggressive behaviour, and rule-breaking behaviour. For the present study, we used two broad-band dimensions of the YSR (Achenbach, 1991): (a) internalizing problems, consisting of items measuring anxious/depressed, withdrawn/depressed, and somatic complaints; and (b) externalizing problems, with items measuring aggressive and rule-breaking behaviour.

We found that a simple integrate and fire model applied to the subthreshold activity

was sufficient to explain deprivation-induced changes in suprathreshold activity. The membrane voltage distribution was shifted by the amount of depolarization EGFR inhibitor (method 1) or recalculated for each time step around stimulation (method 2). The probability of firing was then calculated and used to create a predicted PSTH, which could be compared to the real PSTHs (see Figure S2). The exact shapes of the PSTHs were not closely reproduced for IB cells, but the effects of sensory deprivation were. The complex time-specific modifications observed for RS cells were also reproduced by the model. In conclusion, changes observed in suprathreshold activity

directly MG-132 reflected changes at the subthreshold level, which implies that synaptic and not spike generation mechanism explain the observed plasticity. As whisker deprivation affected the timing as well as the amplitude of the responses to whisker stimulation, we analyzed the time course of response for RS and IB cells. Figure 5 represents averaged wPSPs and PSTHs for one trimmed and one spared whisker only. Note that the early spikes (<15 ms poststimulus) were significantly depressed for PW stimulation in the IB cell population GBA3 (t(38) = 3.2, p < 0.005; see Figure S1), but not for the other trimmed whiskers, as

revealed in Figure 5A. The potentiation in IB cells and the depression in RS cells appear to be roughly uniform throughout the whole time course of the response. In contrast, depression of PW responses in IB cells was greater in the early part of the response (<30 ms poststimulus). Similarly for RS cells, the best spared whisker was potentiated for the early part of the response (<25 ms poststimulus) but depressed for the late component. The latter observation held when all the spared whiskers were considered. We quantified the area of the subthreshold response in four time windows (0–25; 25–50; 50–75; 75–100 ms poststimulus) and the suprathreshold response in three time-windows (0–15; 15–30; 30–45 ms poststimulus). RS cells’ response to spared whisker stimulation displayed a significant interaction between deprivation and time both for suprathreshold (F(2,2) = 6.8, p < 0.005) and subthreshold (F(3,3) = 5.5, p < 0.005) parameters. These data suggest that the early component of the response can be potentiated (as with the RS cells) or depressed (as with the IB cells) independently of later components of the wPSP. Latency and jitter of evoked action potentials are important temporal parameters for coding sensory information.

Apart from dynein-based transport of glycine receptors (Maas et al., 2006), the detailed retrograde trafficking route of inhibitory neurotransmitter receptors remains elusive. Here, we identified muskelin as a direct GABAAR α1 subunit binding protein that participates in receptor endocytosis and degradation. Muskelin is a widely expressed intracellular multidomain protein (Adams et al., 1998 and Adams et al., 2000), with high expression levels in hippocampus and cerebellum (Tagnaouti et al., 2007). Our data show that muskelin accompanies receptor transport through different motor protein complexes along both actin filament and MT networks. To identify GABAAR binding proteins that might

participate in the regulation Navitoclax mw of receptor targeting and/or turnover,

we BVD523 applied the LexA yeast two-hybrid system by using the intracellular GABAAR α1 TMIII-TMIV loop sequence (aa 334–420, Figure 1A) as bait. From 2.4 million clones of an adult rat brain library, we identified five putative GABAAR α1 binding partners including a single clone that coded for residues 90–200 of the multidomain protein muskelin (accession number NM_031359) containing a discoidin domain, a lissencephaly-1 (LIS1) homology (LISH) and C-terminal to LisH (CTLH) tandem domain, as well as repeated kelch motifs (Adams et al., 1998) (Figure 1B). The muskelin binding site of GABAAR α1 was mapped through TMIII-TMIV deletion mutants, which identified residues 399–420 as being sufficient for muskelin interaction (Figure 1A). Notably, TMIII-TMIV sequences of GABAAR α2, α3, α5, β2, or γ2 subunits

did not directly bind to muskelin in this assay (Figures 1C and 1D), while USP14 (a positive control) displayed binding (Figure S5 available online). To biochemically substantiate this interaction, we performed GST pull-down and coimmunoprecipitation (co-IP) experiments. Despite GABAAR α1, GABAAR α2 TMIII-TMIV loop-GST fusion proteins also, but not GST alone or fusions to α3, α5, β2 or γ2, displayed specific binding to myc-muskelin derived from HEK293 cells (Figure 1E). GABAAR α2 might associate with muskelin-GABAAR α1 complexes, as it binds to gephyrin (Tretter et al., 2008), which can also interact with muskelin (Figures S1A and S1B); however, GABAAR α2 does heptaminol not seem to be a direct muskelin binding partner (Figures 1C and 1D). Notably, as a control for muskelin-GABAAR α1 binding, deletion of the minimal muskelin-binding motif of GABAAR α1 (aa 399–420) abolished this interaction (Figure 1E). Accordingly, precipitation of endogenous GABAAR α1 led to specific coprecipitation of endogenous muskelin and vice versa with brain lysates (Figures 1F and 1G). Coimmunostaining of hippocampal neurons cultured for 12–14 days in vitro (DIV 12–14) indicated colocalization of muskelin and GABAAR α1 puncta in somata and neurites.

, 2008). However, DRGs in E10.5 Erk1/2CKO(Wnt1) embryos appear to be morphologically Selleck RG-7204 intact (see Figures S1A and

S1B available online). ERK1/2 expression is significantly reduced in the DRG by E10.5, and western blotting of E12.5 Erk1/2CKO(Wnt1) or Mek1/2CKO(Wnt1) DRG lysates shows a near-complete loss of ERK1/2 or MEK1/2 protein, respectively ( Figures S1C–S1E). RSK3, a downstream substrate of ERK1/2, showed significantly reduced phosphorylation further indicating functional inactivation of ERK1/2 signaling ( Figure S1E). We therefore utilized Erk1/2CKO(Wnt1) mice to ask whether the loss of Erk1/2 disrupts PNS development in vivo. Compared to controls ( Figures 1A and 1C), massive cell loss was observed at both brachial and lumber levels in E17.5 Erk1/2CKO(Wnt1) DRGs ( Figures 1B, 1D, and S1F–S1J). We found that homozygous deletion of both genes was necessary for the decreased neuronal number in the DRG (data not shown). E17.5 Mek1/2CKO(Wnt1) embryos show a qualitatively similar, though more severe phenotype, than in stage matched Erk1/2CKO(Wnt1) embryos ( Figures S1F–S1H). Endogenous levels

of MEK1/2 protein are reported to be lower than ERK1/2, likely resulting in more Selleck Dasatinib rapid protein clearance following recombination and a relatively accelerated phenotypic onset ( Ferrell, 1996). Whole-mount neurofilament immunolabeling of E15.5 control and Erk1/2CKO(Wnt1) forelimbs revealed that nearly all peripheral projections are absent in mutant forelimbs ( Figures 1E and 1F). It is notable that motor neurons do not undergo recombination in the Wnt1:Cre line, yet their projections totally degenerate. Overall, these data demonstrate that inactivation of Erk1/2 in the PNS results in the loss of all peripheral projections and massive DRG neuron death. ERK5 is another well-known stimulus-dependent MAPK under trophic control during PNS development (Watson et al., 2001). We tested the role of this pathway in Erk5fl/fl Wnt1:Cre (Erk5CKO(Wnt1)) mice ( Figure S1K–S1N).

Oxalosuccinic acid In contrast to Erk1/2CKO(Wnt1) mice, Erk5CKO(Wnt1) mice are viable and able to breed. However, Erk5CKO(Wnt1) adult mice are smaller than controls and exhibit external ear truncation and mandibular shortening, likely due to an alteration in the development of the craniofacial neural crest ( Figure S1M). Perhaps surprisingly, markers for proprioceptive (Parvalbumin) and nociceptive (CGRP and TrkA) sensory neurons, exhibited relatively normal expression in P1 Erk5CKO(Wnt1) DRGs ( Figures 1G–1J and data not shown). Whole-mount neurofilament immunolabeling did not reveal any deficit in the peripheral projections of E14.5 Erk5CKO(Wnt1) forelimbs compared to controls ( Figures 1K–1L). Both CGRP and Parvalbumin positive central afferents within the spinal cord appeared intact as well ( Figures 1G–1J). Overall, these data suggest that ERK5 does not play a primary role in early aspects of PNS morphogenesis in vivo.