We noticed that expression of Ndel1SE, but not Ndel1SA, led to a defect on the Notch activity ( Figures 6G, 6H, and 6I), which most likely is due to the spindle orientation defect ( Figures 5B and 5C). We also examined whether the Notch targets, like Hes1, are reduced in PP4c mutant brains. Quantitative real-time

PCR revealed that the level of Hes1 mRNA is significantly reduced in PP4c mutant cortex compared to the control cortex ( Figure 6J). These results selleck products suggest that the misoriented spindle in the neural progenitors of PP4c knockouts could affect Notch signaling activity. Given that Notch signaling activity regulates neural progenitor proliferation and differentiation in the developing neocortex ( Gaiano et al., 2000 and Pierfelice et al., 2011), these data indicate that PP4c regulates neural progenitor proliferation through spindle orientation-dependent Notch signaling activity. In this study, we have examined the role of PP4c in Selleck INCB024360 regulating neural progenitor proliferation and differentiation in the mouse neocortex. Our data suggest that PP4c regulates Ndel1 phosphorylation and its interaction with Lis1 to control the orientation of the mitotic spindle in cortical progenitors.

When PP4c is deleted at the onset of neurogenesis, the resulting spindle orientation defects lead to premature differentiation of cortical progenitors into Suplatast tosilate neurons and severe defects in cortical layering and brain cytoarchitecture. When deleted at E12.5, however, these defects are no longer observed, although mitotic spindles in progenitor cells assume a random orientation. Thus, our data indicate that correct spindle orientation is essential in RGPs during a critical time window at the onset of neurogenesis to prevent differentiation of neural progenitors and the maintenance of cortical

integrity. During the initial neuroepithelial stages of cortical development (E8.5–E9.5), neural progenitors expand by dividing symmetrically. Neurogenesis ensues at E10.5 and gradually increases until E14.5, when most neuroepithelial divisions are asymmetric, generating one progenitor and one neuron or basal progenitor. This transition is accompanied by a gradual change of spindle orientation: while most mitotic spindles are parallel to the epithelial surface at E10.5, almost half of them show an oblique orientation at E14.5 (Postiglione et al., 2011). We propose that this gradual transition in spindle orientation is important to allow a gradual increase in neurogenesis rates and proper cortical morphogenesis. Upon the removal of PP4c at the onset of neurogenesis through Emx1Cre-mediated recombination, the number of progenitors with oblique orientation of the mitotic spindle was significantly increased.

SnoN2 knockdown unexpectedly led to a striking branching phenotype in granule neurons characterized by numerous protrusions emanating from the axon shaft (Figure 1C and Figure S1A, available online). In time course analyses, the percentage of cells with exuberant axon branching increased over time (Figure 1D). Quantification of the number of axon branches per neuron revealed that SnoN2 knockdown

increased the number of both secondary and tertiary axon branches (Figure 1E). By contrast to the robust axon-branching Selleck INCB018424 phenotype in SnoN2 knockdown neurons, SnoN1 knockdown failed to increase axon branching (Figures 1C–1E and Figure S1A). Interestingly, neither SnoN1 RNAi nor SnoN2 RNAi reduced axon length (Figure S1B). Because pan-SnoN RNAi reduces axon length in granule neurons Selleckchem Antidiabetic Compound Library (Stegmüller et al., 2006), these results suggest that SnoN1 and SnoN2 have redundant functions in axon growth. In agreement with this conclusion, the combination of SnoN1 RNAi and SnoN2 RNAi reduced axon length, thus phenocopying the effect of pan-SnoN RNAi on axon growth (Figure 1J and Figures S1C and S1D) (Stegmüller et al., 2006). In addition, although pan-SnoN RNAi induced robust downregulation of the axon growth-promoting signaling molecule Ccd1, a transcriptional target of SnoN (Ikeuchi et al., 2009), SnoN1 RNAi or SnoN2

RNAi alone failed to reduce Ccd1 mRNA levels in neurons (Figure S1E). In other experiments, SnoN1 RNAi and SnoN2 RNAi had little or no effect on neuron survival suggesting that the morphological phenotypes were not due to impaired cell health (Figure S1F). SnoN1 RNAi and SnoN2 RNAi failed to alter the expression of the granule neuron marker MEF2A (data not shown) suggesting that the morphology phenotypes were not secondary to a change in the general differentiation state of granule neurons. Taken together, these results suggest that SnoN2 RNAi specifically impairs the restriction of axon branching in neurons. To determine whether the SnoN2 RNAi-induced effect on neuronal morphology is the result

of specific knockdown of SnoN2, we performed a rescue experiment. We generated an expression plasmid encoding SnoN2 by using a cDNA containing silent mutations. SnoN2 RNAi induced knockdown Thymidine kinase of SnoN2 encoded by wild-type cDNA (SnoN2-WT) but not the RNAi-resistant cDNA (SnoN2-RES) (Figure 1F). Importantly, expression of SnoN2-RES but not SnoN2-WT in the background of SnoN2 RNAi in granule neurons restored axon branching to levels similar to that of control-transfected neurons (Figures 1G and 1H). Expression of SnoN2 in the absence of SnoN2 RNAi in granule neurons had little or no effect on axon branching (data not shown). These results support the conclusion that the SnoN2 RNAi-induced axon-branching phenotype is the result of specific knockdown of SnoN2. Because exuberant branching is not observed in neurons expressing pan-SnoN shRNAs (Stegmüller et al.

, 2013). This general approach may also synergize with the studies of the development and assembly of neural structures beginning

from the other direction, with biology rather than chemistry, as in the stem cell/brain organoid (Lancaster et al., 2013) approach described above. A newly emerged concept at the interface of neuroscience and chemical learn more engineering, CLARITY (Figure 3), involves the chemical construction of new physical forms from within biological systems such as the brain (Chung and Deisseroth, 2013 and Chung et al., 2013). For example, hydrogel infrastructures can be constructed from within intact brains to covalently stabilize native proteins and nucleic acids in preparation for stringent removal

of membrane phospholipids with strong ionic detergents and active electrophoresis of the entire brain. This lipid removal, in turn, allows interrogation of the intact brain with photons (which no longer scatter heavily due to removal of the lipid-aqueous interfaces) and macromolecules (such as antibodies and oligonucleotide probes, which can at that point penetrate the tissue without interference from intact plasma membranes). We expect this kind of approach to find utility in mapping volumetric anatomical features from animal models as well as clinical samples; moreover, many kinds of gels and scaffolds could be constructed in this way with a range of passive and active properties for a broad range of different kinds of structural and functional GS-7340 clinical trial studies of nervous systems. Finally, distinct from gel and scaffold diversity, there also exists

a broad diversity of macromolecular probe type that can be used to interrogate the resulting nanoporous hybrid structures, including functionalized proteins and active enzymes. As exciting as these domains of neuroscience have become, the future may hold even greater opportunities—for example, via combinations of multiple engineering subdisciplines (e.g., computer science with chemical engineering, or optical instrumentation with bioengineering, for applications to increasingly sophisticated questions in increasingly complex nervous systems; Figure 3). CLARITY is already being used in human tissue, and advanced electrical and optical interfaces else have already been designed for human and nonhuman primate applications. Emerging optical methods may bring among the most exciting synergistic possibilities for integrative studies of neural circuit dynamics, connectivity, cytoarchitecture, and molecular composition. Specifically, in vivo optical recordings of neural activity and optogenetic manipulations in cells defined genetically or by anatomical projections can be naturally combined and registered with technologically advanced studies of circuitry, synaptic structure, and other macromolecular information (e.g., using CLARITY).

Our data also support this view. Typical of CCGs, peaks are centered on zero, indicating a predominance of common input, arising either from thalamic inputs or other cortical sources. This pedestal of common input is accompanied by a prominent feedforward direction of information flow, as indicated by the strength of interareal interactions (Figure 7C) and the predominantly positive asymmetry indices (Figure 7E). In visual cortex, V1-V2 interactions are on average stronger than

V1-V1 interactions, reflecting the larger degree of spatial integration in V2 and concomitant larger network size (Hung et al., 2010; Livingstone and Hubel, 1984; Ts’o and Gilbert, 1988; Roe and Ts’o, 1999). In somatosensory cortex, greater interareal integration may also be expected due to the larger receptive field sizes in area 1 than in area 3b. Steady-state

BMS-754807 order Ulixertinib clinical trial intrinsic interactions within area 3b and within area 1 may also provide a baseline configuration upon which sensory stimuli or other active states are further elaborated (Reed et al., 2008; cf Steinmetz et al., 2000). Thus, sensory stimulation may further enhance the preexisting biases, producing in SI a strongly feedforward direction of information flow in the stimulated state. Such hypotheses have been supported by studies of macroscale networks. This study now extends these ideas to the local microscale network. Eighteen squirrel monkeys (fMRI, 11 monkeys; anatomy, 3 monkeys; electrophysiology, 4 monkeys) were anesthetized with ketamine hydrochloride (10 mg/kg)/atropine first (0.05 mg/kg) and maintained with isoflurane anesthesia (0.8%–1.1%) delivered in a 70:30 O2/N2O mixture. All procedures were in compliance with and approved

by the Institutional Animal Care and Use Committee of Vanderbilt University. All MRI scans were performed on a 9.4-T Varian Inova spectrometer (Varian Medical Systems) using a 3-cm surface coil. T2-weighted oblique structural images (echo time [TE], 16; repetition time [TR], 200 ms) at 78 × 78 × 1,000 μm3 resolution were acquired and coregistered with fMRI maps and with blood-vessel maps. Functional MRI data acquired from the same slices using a gradient echo planar sequence (TE, 16 ms; TR, 1.5 s) at voxel sizes of 575 × 575 × 2,000 μm3 (and for one case at 275 × 275 × 2,000 μm3) were reconstructed and imported into MATLAB (MathWorks) for analysis. Within each imaging session, both tactile stimulus-driven and resting-state BOLD images were acquired. Eighteen sets of resting-state fMRI data were acquired from eleven anesthetized squirrel monkeys. Determination of seed voxels in areas 3b and 3a in each animal were based on stimulus-driven fMRI activation maps and the available electrophysiology maps for each animal. Voxel-wise correlation was calculated and then thresholded at r ≥ 0.7 for display. Fingers were secured and tactile stimulation (8 Hz vibrotactile stimulation) of fingerpads was delivered with a piezoceramic device.

In boxing, about ten deaths have occurred

annually during the 20th century; most were related to knockout or technical knockout (deaths due to boxing are registered in the Manuel Velazquez Boxing Fatality Collection, available at http://ejmas.com/jcs/jcsart_svinth_b_0700.htm). The most common cause Ibrutinib ic50 of death is subdural hematoma (Guterman and Smith, 1987; Unterharnscheidt, 1995). Most deaths (about 80%) are among professional boxers, and boxing-related deaths due to brain damage occur in all rounds and in all weight classes, but somewhat surprisingly, most deaths are in lower weight classes. Deaths declined since 1983, which might be related to lower exposure to repetitive head trauma among professional boxers with shorter careers and fewer fights (Baird et al., 2010). Catastrophic brain injury also occurs

in American Dasatinib supplier football. During the second half of the 20th century, more than 400 players died from brain or spinal cord injury in the United States while playing (McIntosh and McCrory, 2005). Repetitive brain trauma may cause chronic neurological problems. For example, in 1928, Martland (1928) described chronic brain damage in boxers, which was termed punch drunk syndrome. A few years later, Millspaugh (1937) called this syndrome dementia pugilistica, which is more commonly used. Forty years ago, Corsellis et al. (1973) described neuropathological changes in a series of professional boxers with dementia pugilistica. Their key findings included neurofibrillary tangles in cortical areas, cerebellar atrophy and gliosis, hypopigmentation of the substantia nigra, and cavum septum pellucidum. Many years after these early studies documenting the histopathological

Ketanserin changes in career boxers, it became evident that a similar chronic brain condition occurred in athletes who practiced other contact sports and had a history of repeated head trauma, and it was only recently that the first autopsy report from a football player was published (Omalu et al., 2005). Neuropathological changes were similar to those in boxers with dementia pugilistica, findings that have now been verified in larger studies (McKee et al., 2009). These authors introduced the more general term chronic traumatic encephalopathy (CTE), which has gained broader usage (Stern et al., 2011). CTE is regarded as a chronic brain syndrome due to effects of repetitive brain trauma, but there are no generally accepted guidelines for a clinical diagnosis of CTE or for how to distinguish neuropathological changes due to CTE from those due to aging and Alzheimer’s disease (AD). CTE is regarded as a neurodegenerative disorder that often occurs in midlife, years or decades after the sports career has ended (McKee et al., 2009). About one-third of CTE cases are progressive (Roberts, 1969), but clinical progression is not sequential or predictable.

In this interpretation, a first layer encompasses the distinct tuning properties, sensitivities, and adaptation properties of the various LTMR subtypes (and HTMRs and myelinated nociceptors). A second layer incorporates the observation that combinations of LTMR subtype endings associate with morphologically unique end organs, such as corpuscles and hair follicles. The third layer unites the unique spatial distributions of end organs

and their BIBW2992 cell line reiterative patterns that exist throughout glabrous and hairy skin. A final layer considers the unique conduction velocities of LTMR subtypes. Indeed, Aβ-, Aδ-, and C-LTMR impulses propagate to the spinal cord at markedly different rates, and so there must be a temporal component R428 manufacturer to the manner in which the CNS interprets ensembles of LTMR activities. In considering this integrative view, touch perception is the product of how these four layers meld together to translate a complex touch into ensembles of activities of individual LTMRs subtypes (Figure 2). The patterns of hairy skin innervation

thus allow us to formulate a simple model of how tactile stimuli may be dissected into LTMR activity codes. Indentation on hairy skin, for example, as with a poke, would most optimally activate SAI-LTMRs associated with guard hair touch domes (Figure 2A). Thus, SAI-LTMRs would be a dominant, but not the only, LTMR represented in the ensemble of impulses traveling to the CNS. A firm stroke, on the other hand, like rubbing a cat’s back, would result in a distinct ensemble of the activities of SA- and RA-LTMRs as well as the ultrasensitive Aδ- and C-LTMRs, which respond well to hair follicle deflection (Figure 2B). A gentle breeze is likely to activate all of the hair follicle LTMRs forming longitudinal lanceolate endings, ADP ribosylation factor the Aβ RA-, Aδ-, and C-LTMRs, whereas SAI-LTMRs would be relatively silent in this ensemble response (Figure 2C). A slow caress of the skin is likely to activate many LTMR subtypes and

especially C-LTMRs, which are particularly well tuned to gentle stroking of the skin, thus providing a unique “LTMR caress ensemble. Our skin, the largest sensory organ that we possess, is well adapted for size, shape, weight, movement, and texture discrimination, and with an estimated 17,000 mechanoreceptors, the human hand, for example, rivals the eye in terms of sensitivity. In fact, many of the same principles that underlie visual processing in the retina may also be at play in the processing of light touch information. Indeed, just as photoreceptors of the retina are uniquely tuned to particular wavelengths of light, LTMR endings in the skin are optimally and distinctly tuned to particular qualities of complex tactile stimuli.

, 2008), and axon fasciculation ( Bossing and Brand, 2002 and Orioli et al., 1996). Therefore, the developmental expression pattern of EphA4 in the cochlea was examined ( Figures 4A–4F). Through the use of in situ hybridization, we Vemurafenib found that Epha4 mRNA is broadly distributed at E14.5 (data not shown) and E16.5 ( Figures

4A and 4B), localizing to mesenchyme, the spiral ganglion, and the cochlear epithelium. However, we saw a remarkably limited pattern of expression with antibodies specific to the extracellular domain of EphA4 protein: virtually all immunoreactivity was observed in otic mesenchyme cells ( Figures 4C–4F). A high-magnification view of the SGN peripheral axons ( Figures 4G and 4H) shows that EphA4 protein is expressed only by the adjacent mesenchyme cells in a “guide rails” fashion (see asterisk, Figures 4G and 4H) but is not detectable in the SGN axons (arrowheads) themselves. Importantly, whole-mount preparations and orthogonal reconstructions of E18.5 cochleae show that EphA4 is distributed in the Pou3f4-positive mesenchyme bands

between the SGN fascicles but does not overlap with Tuj1 ( Figures 4I–4N). These results indicate that EphA4 protein is distributed in a spatial and temporal manner consistent with a role in SGN fasciculation. It is unclear why there is a discrepancy between EphA4 mRNA and protein distribution, but a posttranscriptional regulatory program that limits EphA4 protein to the mesenchyme may be present. To confirm that EphA4 expression in the mesenchyme depends on Pou3f4, we used too Selleckchem Adriamycin quantitative PCR

to show an approximate 5-fold reduction in Epha4 expression in Pou3f4y/− cochleae ( Figure 4O). Moreover, analyses of whole-mount preparations from Pou3f4y/− cochleae show that EphA4 protein is substantially reduced in the otic mesenchyme at E17.5 ( Figures 4P–4U). If Pou3f4 transcriptional activity regulates Epha4 expression in the otic mesenchyme to promote SGN fasciculation, we reasoned that Epha4-deficient mice should also have fasciculation defects. We therefore examined the SGNs from Epha4−/− embryos at late embryonic ages ( Helmbacher et al., 2000 and North et al., 2009). Compared to their wild-type littermates ( Figures 5A, 5C, 5E, and 5G), Epha4−/− mice presented fasciculation defects that were remarkably similar to those observed in the Pou3f4y/− animals ( Figures 5B, 5D, 5F, and 5H; compare to Figure 2). Whereas wild-type cochleae showed tight SGN bundles and well-defined mesenchyme bands ( Figures 5A and 5C), the SGNs in Epha4−/− cochleae displayed dispersed, poorly fasciculated bundles that aberrantly traversed the mesenchymal space ( Figures 5B and 5D) and occupied significantly more area at the basal, midmodiolar, and apical regions of the cochlea ( Figure 5I).

When stimulation is distributed over all available bipolar cells, but locally weaker, suppression is less effective and gain stays high. Furthermore, this local gain control can be viewed as a dynamic process; it affects the later part of the spike burst, but not its initial phase, which determines the first-spike latency. In the following, we test neuronal mechanisms that may implement such a dynamic local gain control mechanism. A first candidate mechanism for local gain control in

homogeneity detectors is synaptic depression at bipolar cell terminals. Indeed, bipolar cell signals can display substantial depression (Burrone and Lagnado, CH5424802 cell line 2000 and Singer and Diamond, 2006), which could partly

suppress responses to strong local activation. When activation is distributed over more bipolar cells, on the other hand, as in the case of homogeneous receptive field activation, synaptic depression is likely to be less effective and thus should permit longer spike bursts. We therefore tested whether homogeneity detectors are cells with particularly strong local adaptation, as would result from synaptic depression. To do so, we used a stimulus that aimed at predepressing synapses in one half of the receptive field. We assessed the effect of this predepression on the iso-rate curves by a brief activation of one receptive field half shortly before each stimulus of the iso-rate-curve http://www.selleckchem.com/products/chir-99021-ct99021-hcl.html measurement (Figure 6A). As expected, the predepression stimulus reduced sensitivity of the ganglion cells, which is reflected by the increased radius of the iso-rate curves

(Figures 6B and 6C) as compared to the control condition without the predepression stimulus. The reduction in sensitivity may L-NAME HCl contain both global and local components; a symmetric scaling of the predepressed iso-rate-curve radius along all directions reflects a global loss in sensitivity, whereas an asymmetric scaling provides evidence for a local loss in sensitivity and thus a local adaptation mechanism. If the nonconvex iso-rate curves of the homogeneity detectors were to result from particularly strong synaptic depression, this asymmetric scaling should be particularly strong for these cells. However, this was not supported by the experimental data. In fact, homogeneity detectors typically displayed rather global adaptation effects and less local sensitivity loss (Figure 6C) than cells with a convex iso-rate curve (Figure 6B). Synaptic depression is thus not a plausible mechanism for the particular features of homogeneity detectors. As an alternative model, we explored whether local inhibitory signaling could mediate a local gain control.

AAK1′s yeast homologs Prk1p/Ark1p are also necessary for endocytosis (Sekiya-Kawasaki et al., Forskolin solubility dmso 2003).

Importantly, a potential Cbk1p phosphorylation site is present in Prk1p. Prk1p’s role on endocytosis depends on its ability to destabilize actin cytoskeleton at endocytic zones (Toshima et al., 2005). A similar mechanism of actin destabilization could underlie the loss of dendritic spines in NDR1-CA or AAK1-SD-expressing hippocampal neurons. Thus, several lines of evidence suggest that AAK1 regulates intracellular vesicle trafficking. How AAK1 function regulates dendrite morphogenesis remains to be investigated. Intriguingly, AAK1 was recently implicated in regulating various signaling pathways, including Notch (Gupta-Rossi et al., 2011), ErbB4 (Kuai et al., 2011), and Drosophila Neuroglian ( Yang et al., 2011). Rabin8, first identified as a Rab3-interacting protein (Brondyk et al., 1995), is known to act as a guanine exchange factor for Rab8 rather than Rab3 (Hattula et al., 2002). Rab8 is a small GTPase specialized in post-Golgi vesicle budding and plasma membrane transport (Stenmark, 2009). In hippocampal cultures, we find that Rabin8

is predominantly enriched in the Golgi in soma and proximal dendrites. In yeast, Rabin8 homolog Sec2p was found to be phosphorylated by the yeast NDR1 Cbk1p and was shown to account for a subset of the Cbk1p mutant defects (Kurischko et al., 2008). Importantly, the phosphorylation site is conserved between Sec2p and Rabin8. It thus appears Wnt assay that the NDR kinase regulation of vesicle trafficking is an evolutionarily conserved function Phosphoprotein phosphatase for controlling polarization and cell morphology. Our data suggest that Rabin8,

and its phosphorylation by NDR1/2, is involved in mushroom spine development, in cultured neurons, and in vivo. Rabin8 could affect Rab8 function to form and/or deliver post-Golgi vesicles to dendritic membrane contributing to synapse development and increase in spine head diameter. In support of this hypothesis, Rab8 GTPase dominant negative mutant expression in cultured hippocampal slices alters AMPA receptor delivery to surface (Brown et al., 2007 and Gerges et al., 2004). Reducing Rabin8 activity causes a spine phenotype milder than that caused by reducing NDR1/2 activity, indicating that other NDR1/2 substrates likely contribute to spine morphogenesis. Loss of NDR1/2 affects preferentially the proximal dendritic branching, causing an increase in proximal branching and a decrease in distal branching. At the same time, NDR1-CA and activated NDR1-as cause increased dendrite branching in the distal regions as is shown in Sholl analysis. Therefore, NDR1/2 may function in promoting distal growth at the expense of proximal branch additions. NDR1/2′s role on branch extension and its potential downstream effectors remain to be investigated.

, 2010). For vector-based RNA interference (RNAi) analysis, we used a BLOCK-iT Pol II miR RNAi Expression Vector Kit (Invitrogen). The engineered miRNA constructs were produced by PCR amplification click here of miRNA region in BLOCK-iT Pol II miR RNAi expression vector followed by subcloning into pCL20c-L7 at 5′- or 3′-side of a fluorescent protein or ChR2 as indicated in the figures. Other details for preparation of viral vector constructs and

methods for virus infection are described in the Supplemental Experimental Procedures. Recordings from PCs in the cocultures were performed as described previously (Uesaka et al., 2012) and are detailed in the Supplemental Experimental Procedures. To stimulate CFs, square voltage pulses (duration, 0.1 ms; amplitude, 0–90 V) were applied between two of the eight tungsten electrodes placed in the medullary explants. All possible combinations of two electrodes were tested, and stimulus

intensity was carefully increased from 0 V to 90 V for each stimulation pair so as not to miss the CFs innervating the recorded PC. Preparation of acute cerebellar slices and recording from PCs were made as described previously (Hashimoto and Kano, 2003 and Hashimoto et al., 2009b) and are detailed in the Supplemental Experimental Procedures. To record CF-EPSCs, stimuli (duration, 0.1 ms; amplitude, PI3K Inhibitor Library solubility dmso 0-90 V) were applied at 0.2 Hz through a patch pipette filled with normal external solution. CFs were stimulated in the granule cell layer 20–100 μm away from the PC soma. For each PC, the pipette for CF stimulation was moved systematically by about 20 μm isothipendyl step around the PC soma, and the stimulus intensity was increased gradually from 0 V to about 90 V at each stimulation site. The number of CFs innervating the recorded PC was estimated by the number of discrete CF-EPSC steps as previously described (Hashimoto and Kano, 2003 and Hashimoto et al., 2009b). All statistical values were presented as mean ± SEM unless

indicated otherwise. The Mann-Whitney U test or Student’s t test was used as indicated in the text when two independent samples were compared. For multiple comparison, Kruskal-Wallis test, Steel-Dwass test, Dunnett test, and two-way ANOVA were used as indicated in the text. Statistical analysis was conducted with JMP Pro. Differences between data sets were judged to be significant at p < 0.05. ∗, ∗∗, ∗∗∗, and ∗∗∗∗ represents p < 0.05, p < 0.01, p < 0.001, and p < 0.0001, respectively. The authors thank A. Nienhuis, St. Jude Children’s Research Hospital, and George Washington University for the gifts of the lentiviral backbone vector and the packaging plasmid, T. Nakazawa for helpful advice for real-time PCR, K. Kitamura and K. Hashimoto for helpful discussions, M. Mahoney for critically reading this manuscript, and K. Matsuyama, M. Sekiguchi, S. Tanaka, and A. Koseki for technical assistance.