The impact of the mutations on Aβ accumulation and plaque deposition was further assessed by crossing these ADAM10 transgenic mice with Tg2576 mice, a well-characterized AD mouse model that overexpresses human APP Swedish mutation (APPswe) and is known to cause an APP ectodomain

cleavage shift that favors the β- over the α-site. We also assessed the effect of the LOAD mutations on adult hippocampal neurogenesis and, finally, we explored the underlying molecular check details mechanisms by which the LOAD mutations in the ADAM10 prodomain attenuate α-secretase activity. To test the in vivo effects of the two LOAD-associated ADAM10 mutations on α-secretase activity, we generated transgenic mice overexpressing human WT ADAM10, ADAM10 harboring the LOAD-associated mutations Q170H or R181G, and an artificial dominant-negative (DN) mutation, E384A. All transgenes were driven by the mouse prion protein promoter (MoPrP) and tagged with hemagglutinin (HA) at the C terminus of the protein (Figures S1A and S1B available online). For each ADAM10 genotype, we obtained three WT, three Q170H, eight R181G, and three DN F1 transgenic mice, which were bred with nontransgenic littermates to maintain mouse lines. The brains from F2 and F3 progenies of each line were analyzed for ADAM10 expression and APP processing. Western blot analysis of 12-week-old

mouse brains revealed Selleck Vorinostat that a WT transgenic line (WT-58) expressed ∼2.5-fold higher level of mature ADAM10 in brain than nontransgenic control (Figure S1C). In addition to the pro and mature forms of ADAM10, high levels of ADAM10-CTF (∼10 kDa) were detected in the

membrane fraction (Figures 1A–1C and S1D). Previous studies have shown that these ADAM10-CTFs are generated by ectodomain shedding of ADAM10 mature forms (Parkin and Harris, 2009 and Tousseyn et al., 2009). Interestingly, as compared to the ADAM10-WT transgenic mice, the levels of ADAM10-CTF were significantly reduced in mice expressing either of the two LOAD mutations and were undetectable in mice expressing DN mutation (Figures 1A and 1C). This pattern of reduced ADAM10-CTF was consistently observed too in all the ADAM10 LOAD and DN mutant lines as compared to WT transgenic lines (two WT, three Q170H, six R181G, and three DN ADAM10 transgenic lines) and in the three single F1 mice (one WT and two R181G, which failed to produce progeny). The decrease in ADAM10-CTF generation was also detected in primary cortical neurons derived from the LOAD mutant mice (Figure S1E). These results indicate that both the LOAD and DN ADAM10 mutations decreased ectodomain shedding of the metalloprotease. Consistent with our findings, previous studies have shown that artificial mutations at the prodomain cleavage or catalytic sites, which block enzyme activity of the corresponding ADAM proteases (ADAM13 and ADAM19), also result in the prevention of its own ectodomain shedding at their cysteine-rich domains (Gaultier et al., 2002 and Kang et al.

In this way, the trajectories of receptor complexes could be related to the internal morphology of the gephyrin cluster (Figure 2D). Endogenous GlyRs generally colocalized with gephyrin clusters and were confined within subdomains of the PSD. A1210477 Synaptic GlyR complexes displayed a restricted movement, changing their position

within gephyrin clusters on a time scale of tens of seconds. This exchange of GlyRs between subdomains of the gephyrin cluster is seen as a shift in the distribution of individual QD detections, likely representing receptor binding at spatially separated binding sites. Taken together, our observations show that gephyrin clusters have an intricate internal organization and that their ultrastructure determines the subsynaptic distribution and diffusion properties of GlyRs. In the previous experiments, the organization of inhibitory PSDs was deduced from two-dimensional (2D) image projections, which could influence the apparent distribution of synaptic components. We therefore implemented 3D nanoscopic imaging using adaptive optics (Izeddin et al., 2012) to resolve the spatial organization of inhibitory synapses in spinal cord neurons. This technique makes use of a deformable

mirror in the imaging path to optimize BKM120 the signal detection and, by way of an astigmatic deformation, to retrieve 3D information about the position of single fluorophores below the diffraction limit (Huang et al., 2008). Dual-color 3D-PALM/STORM experiments were carried out on mEos2-gephyrin clusters and Alexa 647-tagged GlyRα1 complexes in fixed spinal cord neurons. As in the 2D experiments, the distribution of GlyRs closely matched the internal organization of the gephyrin clusters. However, rotation of the 3D images showed that scaffold proteins and receptor domains were shifted relative to one another (Figure 3A). We determined the distance between the gephyrin

molecules and the receptors along an axis across the PSD by measuring the distribution of fluorophore detections within a 200 nm radius (Figure 3B). The mean distance between the labeled GlyRs and MTMR9 mEos2-gephyrin was 44 ± 6 nm (mean ± SEM, n = 26 clusters). The GlyR profile itself was, on average, 135 ± 20 nm wide; and that of gephyrin was 140 ± 11 nm (full width at half maximum [FWHM] of fluorophore detections, n = 10 cluster profiles). Since the surface labeling of GlyRs can be considered as essentially 2D, the distribution of the Alexa 647 fluorophores reflects the limit of resolution of our imaging conditions (z axis pointing accuracy σz = 20–30 nm; Izeddin et al., 2012). In addition, we rendered the surfaces of gephyrin and GlyR clusters in order to calculate the volumes of the two domains (Figure 3C; Movie S1 available online). The mean volume of the GlyR domain was 0.010 ± 0.006 μm3, and that of the gephyrin clusters was 0.012 ± 0.

What are the molecular mechanisms by which PCDH17 regulates SV assembly in developmental synapses? One report showed that homophilic interactions of PCDH8, in cis or trans, decrease dendritic spine density

( Yasuda et al., 2007). Evidence that PCDH17 mediates intercellular homophilic interactions and is localized www.selleckchem.com/products/BIBW2992.html at perisynaptic sites may imply that homophilic interactions of PCDH17 regulate SV assembly in presynaptic terminals, although the cellular and molecular mechanisms need to be clarified. Several lines of evidence demonstrate that the N-cadherin-β-catenin adhesion complex plays a central role in recruiting SVs to presynaptic terminals ( Arikkath and Reichardt, 2008). SV clusters are surrounded by actin filaments, suggesting that localization of SVs is dependent upon F-actin ( Bamji 2005). Thus, the N-cadherin-β-catenin complex and its associated F-actin regulation are thought to play a part in presynaptic SV assembly. Given that some δ-protocadherin members, such as PCDH8 and PCDH10, act as negative regulators of N-cadherin

( Nakao et al., 2008; Yasuda et al., 2007), it is likely that PCDH17 also perturbs the function of the N-cadherin-β-catenin complex and inhibits SV assembly forces. Furthermore, as the cytoplasmic domain of PCDH17, like that of PCDH10 and PCDH19, interacts with the WAVE complex (our unpublished data; Nakao et al., 2008; Tai et al., 2010), PCDH17-WAVE complex machinery might affect the N-cadherin-β-catenin INK1197 order complex and its associated actin cytoskeleton, resulting in delocalization of SVs in presynaptic terminals. Further detailed analyses are required for clarification of the role of PCDH17 in SV assembly.

The abundance and localization of presynaptic SVs are critical for regulation of synaptic physiology. In N-cadherin and β-catenin knockout synapses, the response with respect to the EPSC amplitude during repetitive stimulation is significantly smaller, suggesting that the cadherin-catenin complex positively regulates the availability of Histamine H2 receptor SVs for release during high activity (Bamji et al., 2003; Jüngling, et al., 2006). Considering the possible negative regulation of N-cadherin by δ-protocadherins (Nakao et al., 2008; Yasuda et al., 2007), increased numbers of SVs in PCDH17 knockout synapses could contribute to the ready availability of SVs for neurotransmitter release. This idea is supported by our electrophysiological data that PCDH17 knockout synapses exhibited less synaptic depression following repetitive stimulation of input fibers. It is assumed that paired-pulse depression is affected by SV transitions in the pools as well as by neurotransmitter release probability ( Regehr, 2012). It might be possible that PCDH17 deficiency decreases paired-pulse depression as a result of higher vesicle replenishment into release sites.

Parametric maps of the interaction between gender and scan time for the learning group reveal differences in regional changes between the two genders (Figure 3): the MD is decreased in the right caudate head in males but not in females (Figure 3D), and increased in the superior frontal gyrus in females but not in males (Figure 3G). Further investigation of the biological correlates of the DTI changes observed in humans

necessitates an animal study with similar short-term memory protocol. Previous studies on rodents focused on long-term training (Blumenfeld-Katzir et al., 2011 and Lerch et al., 2011). In order to provide supporting biological relevance PI3K cancer to the current human study, we conducted a short-term water maze study on rats. A cohort of 24 rats underwent two MRI scans 1 day a part. Between the MRI scans a water maze task was performed including 12 trials performed within 2 hr. As in the human study, two control groups were also examined: a passive group that did not perform any task between the MRI scans, and a cued group that performed the water maze but with a visible platform

(for more details see Supplemental Experimental mTOR inhibitor Procedures; Figure S3). In the statistical analysis (same as in the human study), we found MD decrease in the posterior parts of the hippocampus (Figures 4A and 4B). Histological analysis of the brain following the second MRI scan revealed an increase in the immunoreactivity of the following markers in the learning group compared with the control group: synaptophysin,

glial fibrillary acidic protein (GFAP), and brain-derived neurotrophic factor (BDNF) (Figures 4C and S3). No immune-reactivity differences were observed when staining for microtubule-associated protein 2 (MAP2), a marker of dendrites. This result indicates that within the regions of MD decrease, the following no occurred: an increase in the number of synaptic vesicles, astrocyte activation (reflected also by increase in the number of astrocytic processes; Figure 4D), as well as increase in BDNF expression, which may be indicative of LTP. The results of this study indicated that short-term learning (2 hr) in humans leads to significant changes in diffusion MRI indices. This surprising observation was strengthened by a rigorous statistical analysis, was repeated in a replica of the study (Figure S2A), and was obtained in a supporting study in rats (Figures 4 and S3). It is reasonable to assume that this MRI observation reflects structural aspects of neuroplasticity. Because DTI can be considered to be a marker of tissue microstructure, structural remodeling of the tissue will lead to a change in its water-diffusion properties (Assaf and Pasternak, 2008, Barazany et al., 2009, Blumenfeld-Katzir et al., 2011 and Scholz et al., 2009).

However, even

with proper oversight, this may in the end be one of the biggest safety hurdles to overcome. In addition to making transplantation of reprogrammed cells affordable and safe, one of the major hurdles thus far left unsolved is to incorporate all of the sequential steps of neuronal differentiation and synaptic development. In particular, forming new projection neurons in the human brain will be a monumental challenge. Consider the case of a Betz cell, which synapses in the lower spinal cord and which is frequently Ibrutinib mouse lost in ALS (Udaka et al., 1986). If we were to imagine that the cell body was the size of a tennis ball, the axon would then extend several miles and would be roughly the diameter of

a garden hose. Besides the tens of thousands of dendritic synapses that would Ivacaftor research buy need to be formed, the axon would need to find its target, starting as a growth cone a considerable distance way. This would all have to transpire within a milieu lacking the guidance cues that are normally present only during a limited window during development. Apart from these practical issues and the host of other intrinsic issues involved in neuronal regeneration and transplantation (accurate cell delivery, potential immune suppression, etc.), there is the growing appreciation that NSCs, whether in vitro or in vivo, have intrinsic specification that may limit the cell types that can be produced upon differentiation (Gaspard et al., 2008, Hochstim et al., 2008, Merkle et al., 2007 and Rakic et al., 2009). Indeed, transplanted hESC-derived neurons seem to obey the in vitro specification program when transplanted in vivo (Gaspard et al., 2008). Beyond this, there was a flurry of findings recently that a small proportion of transplanted cells acquired the pathology of the host tissue (Brundin et al., 2008, Kordower et al., 2008 and Li et al., 2008). Thus, even if we can successfully coax stem cells to replace neurons in vivo, the

battle may already be lost for some of them. Others have taken advantage of the “bystander” or “chaperone” effect of NSCs in transplantation strategies aimed at preventing or ameliorating neurodegeneration (see Breunig et al., 2007 for review). Basically, it has been found that NSCs secrete neurotrophins, see more growth factors, and other beneficial proteins that promote neuronal health and function. For example, it was found that NSCs ameliorated cognitive functions in a model of Alzheimer’s disease not through neuronal replacement but due to their secretion of BDNF (Blurton-Jones et al., 2009). Other groups are taking these properties of transplanted cells and enhancing them with transgenes such as GDNF. In a rat model of ALS, such cells migrated to the sites of degeneration, differentiated into glia, and were able to preserve motor neurons at early and end stages of disease (Klein et al., 2005 and Suzuki et al., 2007).

Yanamandra et al. (2013) designed the infusions to produce CNS antibody levels similar to what are achieved following peripheral dosing studies, thereby circumventing the issue of low levels of antibody getting into the CNS. All antibodies almost certainly cycle between the plasma into CNS and rapid cycling can result in reasonably high CNS exposure of the total antibody dosed (Golde et al., 2009). Thus, tau may be a better target

for peripheral immunotherapy then Aβ. Unlike Aβ, tau is present at undetectable levels in plasma; thus, there is no significant peripheral pool of tau to bind to the antibody before it reaches its target in the CNS. In addition, the levels of extracellular interstitial Autophagy inhibitor fluid and CSF tau are quite low relative to Aβ (Yamada et al., 2011). Even small amounts of antibody could significantly deplete this pool. Irrespective of

whether the antibodies work when injected peripherally, it is important to consider that direct cerebral administration of antibodies selleck compound may have potential benefits. Direct infusion would obviate concerns about insufficient CNS exposure. For clinical use, direct infusion would likely dramatically reduce the amount of antibody needed, reducing the cost of therapy and potentially limiting induction of antibodies against the injected antibody. The potential benefits of direct infusion, however, must be weighed against the invasiveness of the technique. Issues such as timing, duration, and frequency of dosing, as well as safety and tolerability, could critically impact the feasibility of direct administration. Delivery issues will need to be resolved for such therapy to be viable and available to our ever increasing patient population. The current study will likely bolster ongoing efforts to rapidly move tau immunotherapy toward human trials. The screen developed by Yanamandra et al. (2013) to identify antibodies capable of

blocking tau seeding may be transformative, as it provides a method to rapidly select antibodies most likely to work in vivo. A remaining challenge is the ability of tau immunotherapy to alter tau-induced neurodegenerative changes. Given the huge expense associated with AD therapeutics Sitaxentan trials and additional expenses incurred when using a biological therapy, it may be well warranted to thoroughly evaluate such immunotherapy in multiple preclinical models before rushing to the clinic. Though many would argue that tau dysfunction and pathology is a secondary but extremely important “hit” in AD, whether there is a true temporal distinction between Aβ accumulation and tau dysfunction in human brain is still a subject of great debate. Thus, the field should be cautious and ensure that trial design for future anti-tau immunotherapies matches the situations in which preclinical studies show significant efficacy.

We thus hypothesized that learned task relevance influenced interneuronal correlations, a

distributed neural feature. Learning is known to alter noise correlations in cortical brain regions (Gu et al., 2011). We thus asked whether noise correlations between pairs of CLM neurons during stimulation with motifs depended on the task relevance of the motif. Figures 2E and 2F show the individual trial spike counts (normalized by the Romidepsin manufacturer Z score to measure noise correlations independently from signal correlations) of the same two neurons from Figures 2A and 2B ( Experimental Procedures). The task-relevant motifs elicited nearly uncorrelated responses from this pair (Pearson correlation coefficient, r = 0.01), while the task-irrelevant motifs elicited responses between the pair that were positively correlated (r = 0.20), meaning that when one neuron fired more spikes than average, the other neuron was likely to do so as well. This effect, however, was not observed in all neuron pairs. Figures 2I and 2J show a second example pair in which noise correlations were very similar between task-relevant and task-irrelevant motifs. To investigate potential differences in the population, we compared noise correlations between all three classes of motif (task-relevant, task-irrelevant, and novel) for all pairs of simultaneously recorded neurons. Consistent with previous

reports (Cohen and Kohn, 2011; Gu et al., 2011; Kohn see more and Smith, 2005; Zohary et al., 1994), we observed broad distributions of noise correlations that had small, but positive, mean values (task relevant: 0.082 ± 0.012; task irrelevant: 0.100 ± 0.012; novel: 0.087 ± 0.012; Figure 3A). Surprisingly, there were no differences in the mean noise correlation between motif classes (repeated-measures ANOVA, p = 0.21; Figures 3A and 3C). A difference in mean noise correlation by itself is thus unlikely to contribute to learning-dependent differences in population coding of motifs Rolziracetam in CLM. Because learning

can alter the receptive fields of cortical sensory neurons, we asked whether signal correlation between pairs of CLM neurons depends on task relevance of motifs. As with noise correlations, the effects of task relevance on signal correlations were variable. While the first example pair does not show a considerable difference in signal correlations between task-relevant and task-irrelevant motifs (Figures 2C and 2D), the second example pair shows a large difference (Figures 2G and 2H). We investigated whether signal correlations exhibited a systematic relationship with task relevance. We observed a broad distribution of signal correlation values for all three motif classes, indicative of the large range of tuning within CLM (Figure 3B). However, we found no evidence that task relevance influenced the magnitude of signal correlations (Figure 3B; Friedman test, p = 0.18).

Using the chicken embryo as an experimental model, we have shown that corridor-like cells share all the intrinsic characteristics of their mouse homologs (Lopez-Bendito et al., 2006), including a remarkably similar capacity to guide TAs, but these neurons converge toward the midline and, hence, are never in contact with TAs in vivo. Thus, the specification and overall migration of corridor-like cells seem independent of their role in TA guidance, thereby suggesting that these neurons may exert other ancestral functions and that their

guidepost function for TAs has been acquired secondarily. Most importantly, our observations indicate that a cardinal difference between living reptiles and mammals lays in the orientation of migration of neurons that have the cellular capacity to guide TAs. Furthermore, using PI3K inhibitor Slit2−/− mutant mice, we showed that the proper positioning of corridor cells by migration is required and sufficient to switch TAs from an external default path to a mammalian internal route ( Figure 8H). Thus, the corridor acts in mice as an anatomical “hotspot” in which local changes in cell migration have long-range and large-scale effects on the guidance of TAs. Taken together, our experiments strongly support a surprising evolutionary scenario in which changes in the

migration of intermediate neurons have provided an opportunity for the opening of a major axonal highway. To unravel the molecular mechanisms mTOR inhibitor cancer underlying the evolutionary change in corridor neuron migration, we focused on the secreted factor Slit2. In this study we showed that (1) Slit2 is differently expressed in the vMGE&POA of mouse and chicken embryos; (2) Slit2 acts as a short-range repellent on the no migration of corridor cells; (3) modifying Slit2 levels in the ventral telencephalon of chicken embryos distorts the shape of the corridor; and (4) Slit2 inactivation impairs the mammalian-specific

migration of corridor neurons by shifting them toward the midline, a behavior reminiscent of chicken corridor-like cells. These results reveal that Slit2 is a major determinant in the orientation of mouse corridor neuron migration, by acting at short-range from the vMGE&POA, and thereby controls TA trajectory. Thus, in contrast to a direct role of Slit2 on axonal navigation ( Bagri et al., 2002, Braisted et al., 2009, Nguyen-Ba-Charvet et al., 2002 and Shu et al., 2003b), our study provides a different mechanism of Slit function on longitudinal axonal positioning through a short-range activity in guidepost cell migration. This relay of midline signaling by an early and, thus, local activity in intermediate target cells may more generally explain how midline cues can act at long range in very large structures, such as the mammalian telencephalon.

Some sections were processed for immunoperoxidase staining ( Zhang et al., 1998b). For quantification, three sections from each mouse were analyzed. The specificity Veliparib price of the antibodies was tested by preabsorption with the corresponding immunogenic peptides (10−6 M). The specificity of the DOR13–17 antiserum was further examined in Myc-DOR1-expressing HEK293 cells and sections of the spinal cord from Oprd1 exon 1-deleted mice. Pre-embedding immunogold-silver labeling was processed as previously described

(Zhang et al., 1998a). Briefly, mice were fixed with 4% paraformaldehyde and 0.05% glutaraldehyde. Vibratome sections of the spinal cord were incubated with Rb anti-GST antibody (1:600) and labeled with the 1.4 nm gold particle-conjugated secondary antibody (1:200, Nanoprobes). Ultrathin sections were examined with an electron microscope. Cell surface biotinylation was performed before or after treatment with 1 μM Delt I or SNC80 for 30 min as previously described (Bao et al., 2003). The lysates were precipitated with streptavidin. For detection of the receptor phosphorylation, cells were treated with 1 μM Delt I, SNC80, or DAMGO for 30 min. Cells were lysed in ice-cold RIPA buffer (50 mM Tris [pH 7.5], 150 mM NaCl, 10% glycerol, 0.1% Triton X-100, 0.5 mg/ml BSA). Samples were subjected to SDS-PAGE, transferred to membranes, probed with the indicated

antibodies, and visualized with enhanced chemiluminescence. Sitaxentan L4–5 spinal segments of wild-type mice and Oprd1 exon 1-deleted mice were prepared for immunoblotting. Antibodies Tanespimycin mw against Flag (1:1,000, Sigma), Myc (1:2,000),

DOR13–17 (1:5,000), DOR11–60 (1:1,000, Santa Cruz), phospho-DOR (Ser363) (1:1,000, Neuromics), phospho-MOR (Ser375) (1:1,000, Neuromics), and actin (1:10,000, Santa Cruz) were used. The specificity of the DOR13–17 antiserum was examined by using spinal cord extracts from Oprd1 exon 1-deleted mice. Intensities of immunoreactive bands of the proteins versus actin were quantified. Detailed procedure is provided in Supplemental Information. Briefly, the suspended lysate of cells and tissues was precipitated with 0.5∼2 μg of antibodies. For detection of the receptor ubiquitination, cells or tissues were lysed in 0.1 ml RIPA buffer with 10 mM N-ethylmaleimide and then mixed with 0.3 ml of 8 M urea. The lysate-urea suspension was diluted to reduce the urea concentration to 2 M and subjected to immunoprecipitation. Immunoprecipitates were processed for immunoblotting. The specificity of the DOR11–60 antiserum was tested using spinal cord extracts from Oprd1 exon 1-deleted mice. GST- and TAT-fused proteins were expressed and purified. Briefly, the proteins were expressed in Escherichia coli BL21 (DE3). The bacteria were harvested by centrifugation, resuspended, and sonicated. The proteins were purified with glutathione-Sepharose beads, concentrated and quantitatively analyzed.

, 2002) and, in even more extreme cases,

to neurodegeneration (Schwarz et al., 2006). Apparently, tight control selleckchem over cholinergic systems, operating at several levels, can counteract such imbalances at both extremes. Proteins that engage nAChRs within stable complexes, such as lynx family members, provide a homeostatic influence over nicotinic receptor systems. Through functionally driven regulation of lynx expression, the inhibition exerted over the system can be released or enhanced selectively within neuronal circuits. The lynx genes belong to the ly-6/PLAUR superfamily, which shares a marked structural similarity with elapid snake venom proteins such as α-bungarotoxin; all have a characteristic three-looped motif. These α-neurotoxins are secreted proteins with sub-nM affinity for nAChRs (Tsetlin et al., 2009) and other receptors

(Auer et al., 2010). α-neurotoxins interact on the extracellular face of the nAChR near ligand binding sites (Figure 1B), in contrast to most other nAChR-interacting proteins, which bind to the intracellular loops. Extrapolating from these interactions, the structurally similar lynx proteins may bind at such sites as well (Lyukmanova et al., 2011). Five interfaces occur in each nAChR pentamer (Figure 1); we do not yet know which, if any, interfaces form the binding sites for various lynx paralogs (Hansen and Taylor, 2007). Most previous MAPK inhibitor studies of lynx have emphasized interactions at the plasma membrane. As GPI-anchored proteins can bind to transmembrane receptors intracellularly,

the interactions of lynx with nAChRs could potentially alter receptor trafficking, stoichiometry, and surface number (Lester et al., 2009). The high level of conservation with toxins implies that lynx genes are prototoxins—evolutionary antecedents to α-neurotoxins (Miwa et al., 1999, Chimienti et al., 2003, Dessaud et al., 2006, Arredondo et al., 2007 and Hruska et al., 2009). The lynx family occurs in other species, including C. elegans ( Chou et al., 2001) and Drosophila ( Wu et al., 2010)—and in nonvenomous snakes, where it is distinct from the neurotoxin genes. We note that, in several cases, snake toxins employ functional mimicry of proteins in normal physiological processes. Often, virulent gene variants distort endogenous pathways at sensitive or rate-limiting steps. Therefore, the evolutionary relationship between Calpain lynx modulators and the α-neurotoxins agrees with the view that lynx modulators govern critical control points in the pathway of nicotinic receptor signaling. Lynx1, the first discovered member of this family expressed in the brain (Miwa et al., 1999), has an overall inhibitory effect on nAChR function. In an α4β2∗ nAChR-expressing cell, coexpression of lynx1 results in reduced agonist sensitivity, accelerated onset of desensitization, and slower recovery from desensitization (Ibañez-Tallon et al., 2002). Each lynx paralog has a relative binding specificity and modulatory capability on α4β2 (Miwa et al.