In particular, an insomniac-Gal4 reporter is expressed in regions of the Drosophila brain that are implicated in regulating sleep, including the mushroom bodies and the pars intercerebralis ( Pitman et al., 2006, Joiner et al., 2006 and Foltenyi et al., 2007), although driving insomniac expression in these areas individually does not rescue the sleep defect of insomniac mutants, with the exception of a weak rescue provided by the pars-intercerebralis-specific Mai301-Gal4 driver. Further manipulations of insomniac within the nervous system are necessary to understand the neuroanatomical basis by which it regulates sleep. Several lines of

evidence indicate that insomniac exerts its effects on sleep by a mechanism functionally distinct from the circadian clock. The circadian clock is intact in insomniac mutants, and insomniac expression is not regulated in a circadian fashion. Furthermore, the expression

of insomniac BI 2536 mouse Dolutegravir molecular weight in clock neurons is unable to restore normal sleep patterns in insomniac mutant backgrounds. Consistent with these data, daily sleep profiles indicate that the circadian control of sleep is intact in insomniac mutants. As is the case for wild-type animals, the highest probability of sleep during the dark phase is observed soon after the onset of darkness, with a decreasing sleep drive as the dark phase proceeds. The profile of sleep probability during the light phase is similarly intact. The principal alteration of sleep in insomniac animals is a reduced likelihood of sleeping throughout the day and night, consistent with the inference that insomniac may contribute to homeostatic

mechanisms that regulate sleep need. Cullins are scaffold proteins that assemble multisubunit E3 ubiquitin ligase complexes that ubiquitinate and degrade a variety of protein substrates in diverse TCL biological contexts (Petroski and Deshaies, 2005). The C termini of cullins interact with RING-domain ubiquitin ligases, while the N termini interact with adaptor proteins that recruit substrates for ubiquitination. Cul3 complexes utilize proteins of the BTB superfamily as their adaptors (Pintard et al., 2003, Xu et al., 2003 and Geyer et al., 2003), including members of the nonchannel KCTD subfamily (Chen et al., 2009 and Canettieri et al., 2010). In addition to the KCTD proteins that are known to function as Cul3 adaptors, more than half of the non-channel KCTD proteins, including the three vertebrate orthologs of Insomniac, are candidate Cul3 adaptors, as they copurify specifically with Cul3, but not with other cullins (Bennett et al., 2010). For several of these candidate adaptors, including KCTD5 and TAG-303, the C. elegans ortholog of Insomniac, independent biochemical evidence confirms their ability to associate physically with Cul3 ( Xu et al., 2003, Bayón et al., 2008 and De Smaele et al., 2011).

An anterogradely transported, cell-targetable variant of VSV has shown promise in hippocampal slice cultures (Beier et al., 2011), but this conditional variant has not yet been tested and validated in vivo. The HSV-1 strain H129 (Dix et al., 1983) is an attractive candidate for developing a conditional anterograde transneuronal tracer virus (Zemanick et al., 1991). In its native form, H129 has been utilized to trace circuitry in the rodent visual (Archin et al., 2003 and Sun et al., 1996), viscerosensory (Rinaman and Schwartz, 2004), trigeminal

(Barnett et al., 1995), and white adipose sensory pathways (Song et al., 2009), as well as primary motor cortex (Kelly and Strick, 2003 and Zemanick et al., 1991), and spinothalamic (Dum et al., 2009) pathways in nonhuman primates. However, a conditional, selleck chemicals Cre-dependent version of H129 that can be used to trace neural circuitry in vivo has not previously been reported. Here we develop, characterize, and validate such a virus in vivo. Our results provide a method for mapping the synaptic outputs of genetically PD0325901 in vivo marked neuronal

subsets. To develop a conditional H129 strain-based tracer, we simultaneously inactivated the endogenous H129 viral HTK gene and replaced its coding sequence with a Cre-dependent loxP-STOP-loxP-tdTomato-2A-TK cassette ( Figure 1A) via homologous recombination ( Archin et al., 2003 and Weir and Dacquel, 1995), using a codon-modified form of HTK to prevent recombination within the coding sequence (cmHTK; Supplemental Experimental Procedures, available online). After cotransfection of the HTK targeting vector and native H129 genomic DNA into host cells, H129 recombinants were selected by picking acyclovir-resistant plaques ( Figure 1B; see Experimental Procedures) and validated using PCR ( Figure 1C). The resulting H129 recombinant was named H129ΔTK-TT (tdT HTK). Infection of cultured Vero cells with this virus revealed specific expression of tdT only in the presence of Cre ( Figures 1D and 1E). Recombined virus recovered from such cells and used to infect naive Vero cells rendered the latter sensitive

to only acyclovir-dependent killing, indicating that the cmHTK was enzymatically active (data not shown). As an initial test of the Cre-dependent H129ΔTK-TT system in vivo, virus was injected intracranially into the medial cerebellar vermis of PCP2/L7-Cre transgenic mice (JAX Stock #006207), which express Cre and GFP specifically in Purkinje cells (Barski et al., 2000, Oberdick et al., 1990 and Zhang et al., 2004). Four days after infection, GFP-positive Purkinje cells in PCP2/L7-Cre/GFP mice coexpressed tdT, and all tdT-positive cells were GFP positive (Figure 2C). We rarely saw tdT expression in other cell types in the cerebellar cortex, except in regions close to the site of injection exhibiting substantial tissue necrosis, where we observed some labeled granule cells (not shown).

Our data so far indicate that motor axonal EphA3/4 act in a non-cell-autonomous manner to determine sensory axon projections in vitro and in vivo. This prompted us to ask whether EphA proteins would directly influence sensory axon extension in a simplified in vitro environment. To test http://www.selleckchem.com/screening/selective-library.html this, sensory axons were allowed to extend on control substrates or substrates containing recombinant EphA3 ectodomain (EphA3ECD) or paralogous EphA7ECD protein. Exposure to the EphAECD-containing substrates resulted

in markedly enhanced sensory axon extension compared to the control substrates (Figures 8A and 8B). The activity of the EphAECD proteins on sensory axon extension was observed irrespective of whether nerve growth factor (NGF) or neurotrophin-3 (NT-3) was used as neurotrophic supplements (Figures 8A and 8B). This was consistent with the requirements of EphA3/4 observed by us in vivo, which comprised both NGF-dependent cutaneous and NT3-dependent muscle sensory projections. We next asked whether EphAECD would act through ephrin-As to promote sensory axon extension. Sensory axons derived from Efna2/5null embryos displayed significantly

reduced extension in response to EphA3ECD compared to control sensory axons ( Figures 8C to 8E). Thus, EphAECDs are sufficient to promote sensory axon extension in vitro, at least in part by operating through Compound Library cost sensory neuron-expressed ephrin-As. The present study reveals an absolute requirement of motor axon-derived signals for establishing normally patterned peripheral sensory projections and provides mechanistic insights into the axonal interactions that couple peripheral sensory and motor pathways. Below, we discuss these findings in light of previous data by us and others. In a previous study we have shown that EphA3/4

contribute to the anatomical and functional segregation of epaxial motor projections from sensory pathways and DRGs (Gallarda et al., 2008). In EphA3/4 null mutant embryos, epaxial motor axons misproject into those proximal sensory pathways and DRGs, while electrophysiological recordings revealed that this results in the aberrant incorporation of motor input into sensory afferents. Sensory and/or motor neuron culture assays further showed that these phenotypes reflect a requirement for EphA3/4 repulsive signaling in motor growth cones, likely activated by their cognate ephrin-As on sensory axons (see Figures 9A–9A″). Herein, loss of EphA3/4 abolished motor growth cone repulsion induced by recombinant ephrin-A proteins or wild-type sensory axons in vitro ( Gallarda et al., 2008).

, 1998). Exactly which of these models explains axonal exclusion

will have to be determined by higher-resolution analyses of AP-1 localization and dynamics in relation to those of cargo proteins. The role of signal-AP-1 interactions in somatodendritic sorting is not limited to hippocampal neurons but is also observed in cortical neurons (G.G.F., selleck products unpublished data). Moreover, this basic role appears to be evolutionarily conserved. Indeed, studies in C. elegans have shown that the μ1 ortholog UNC-101 is required for sorting of transmembrane proteins such as the odorant receptor ODR-10 ( Dwyer et al., 2001; Kaplan et al., 2010) and the polycystin 2 channel TRPP2 ( Bae et al., 2006) to olfactory cilia, a specialized dendritic subdomain of chemosensory neurons. C. elegans UNC-101 also plays a role in the sorting of several postsynaptic receptors to dendrites of RIA interneurons ( Margeta et al., 2009). Despite this conservation, there are important Autophagy inhibitor differences in the way that UNC-101/μ1A promotes dendritic

sorting in C. elegans and mammalian neurons. In chemosensory neurons from unc-101 mutant worms, ODR-10 is completely absent from both anterograde and retrograde dendritic vesicles ( Dwyer et al., 2001), in contrast to μ1A-deficient rat hippocampal neurons, in which dendritic transport in both directions is not affected. More strikingly, in RIA interneurons, UNC-101 localizes predominantly to the axonal compartment, suggesting a transcytotic mechanism in which postsynaptic receptors are not prevented from entering the axonal compartment but are efficiently retrieved to the soma for eventual delivery to dendrites ( Margeta et al., 2009). This is clearly distinct from rat hippocampal neurons wherein μ1A is depleted from axons and functions

to prevent transport of somatodendritic proteins to the axon ( Figure 5). These differences could be cargo below specific or due to the different anatomical organization of rat hippocampal neurons and C. elegans chemosensory and RIA neurons. Indeed, chemosensory neurons are bipolar cells, with a single dendrite that ends in a sensory cilium ( Dwyer et al., 2001), and RIA interneurons are pseudounipolar, with a single neurite that bifurcates into an axon and a dendrite ( Margeta et al., 2009). In addition to its role in epithelial cells and neurons, AP-1 is required for Nak-dependent localization of the Dlg protein to the basolateral surface of distal cells of Drosophila salivary glands ( Peng et al., 2009) and for preventing the Notch activator Sanpodo from recycling from endosomes to adherens junctions in Drosophila sensory organ precursor cells ( Benhra et al., 2011).

The “target images” (M1, M2, M3, 100% A, and 100% B) were followed by a 500 ms blank, after which the names of the two persons of the corresponding stimulus pair were shown and the subject had to indicate which one (s)he perceived with the left/right arrow key (Figure 1A). From the continuous wide-band data, spike detection and sorting were carried out using “Wave_Clus,” an adaptive and stochastic clustering algorithm (Quian Quiroga selleck chemical et al., 2004). As in previous works (Quian Quiroga et al., 2009), a response was considered significant if, for the presentation of the “target images”—either

for the 100% A, 100% B (when available), the “recognized A” or “recognized B” presentations (pulling together the responses for the three morphs)—it

fulfilled the following criteria: (1) the firing in the response period (defined as the 1 s interval following the stimulus onset) was significantly larger than in the baseline period (the 1 s preceding stimulus onset) according to a paired t test with p < 0.01; (2) the median number of spikes in the response period was at least 2; (3) the response contained at least five trials (given that the number of HIF cancer trials in the conditions “recognized A” and “recognized B” was variable). For the average population plots (Figure 3), we normalized each response by the maximum response across conditions (100% A, 100% (-)-p-Bromotetramisole Oxalate B, M1, M2, M3, separated according to the decision: A or B). Statistical comparisons were performed using nonparametric Wilcoxon rank-sum tests (Zar, 1996). A linear classifier was used to decode the subjects’ decision upon the presentation of the ambiguous morphed images (recognized picture A or B) in those cases where we had at least five trials for each decision. One at a time, the firing in each trial was used to test the classifier, which was trained with the remaining trials (all-but-one cross-validation). As in previous works (Quian Quiroga et al., 2007 and Quian Quiroga

and Panzeri, 2009), to evaluate the statistical significance of decoding performance, we used the fact that since the outcomes of the predictions of each decision are independent trials with two possible outcomes, success or failure, the probability of successes in a sequence of trials follows the Binomial distribution. Given a probability p   of getting a hit by chance (p = 1/K  , K  : number of possible decisions), the probability of getting k   hits by chance in n   trials is P(k)=(nk)pk(1−p)n−k, where (nk)=n!(n−k)!k! is the number of possible ways of having k   hits in n   trials. From this, we assessed statistical significance and calculated a p value by adding up the probabilities of getting k   or more hits by chance: p-value=∑j=knP(j). We considered a significance level of p = 0.05, thus expecting 5% of the responses to reach significance just by chance.

, 2007) and future studies could compare it to edge-FGM within a single task. Here, we modeled the boundary-detection process with a connection scheme where units tuned to the same orientation inhibit each other (Itti and Koch, 2001, Li, 1999 and Roelfsema et al., 2002) so that singletons and orientation boundaries evoke stronger activity. Our result that the edge-FGM in V1 and the FGM in

V4 occurred at approximately the same time is in accordance with such a local computational scheme: the edge enhancement in V1 does not depend on feedback, in accordance with a study demonstrating that the V1 pop-out signal also occurs if V2 is not active (Hupé et al., 2001). FGM in the center of the figure depends on task relevance, which suggests that it is controlled by feedback from higher areas. Accordingly, our model implemented Lapatinib price iso-orientation excitation in the feedback connections. Thus, if the figure orientation is 135°, V4 neurons tuned to this orientation increase their response and propagate the enhanced activity back to V2 and V1 neurons tuned to 135° so that FGM is confined to the figure. The attentional effect uses the same route and as a result it is object-based (Figures 1A and 1C). The influence of attention on center-FGM

accounts for a discrepancy in the AUY-922 order literature. In contrast to a number of other studies (Lamme, 1995, 1999; Marcus and Van Essen, 2002 and Zipser et al., 1996), Rossi et al. (2001) did not observe center modulation in area V1. Interestingly, the monkeys of their study did not have to detect the figure, except in one experiment with a monkey that discriminated between a figure at a fixed location and a homogeneous background, which is a task that could be solved by detecting one of the boundaries. In contrast, the monkeys of our study

made eye movements to the center of a figure that varied in its location, which presumably required perception of the entire figure and presumably depends on FGM at the figure center (Supèr et al., 2001). Moreover, our monkeys had a lot of experience in localizing the figure, and training amplifies the modulation of V1 activity (Li et al., 2008). The influence of attention on center-FGM may have also contributed to the absence of FGM in V1 in two fMRI studies because the subjects’ attention was directed away from the Endonuclease figure (Kastner et al., 2000 and Schira et al., 2004). A previous study by Marcus and Van Essen (2002) also investigated the effects of figure-ground segregation and attention in V1 and V2 in monkeys. Attention enhanced V2 activity but it did not increase FGM and had little effect on activity in V1. However, in this study the monkeys always attended one of two similar figures and it is possible that the monkeys perceived both figures, because increases in the number of figures does not diminish FGM (Lamme et al., 1998b and Landman et al., 2003).

A one-way analysis of variance was used to determine the difference between time and frequency domain acceleration variables between the RF and FF groups running with their habitual footfall pattern

(α = 0.05) using SPSS Statistics version 21.0 (IBM, Amonk, NY, USA). Effect sizes (d) were also calculated to determine if the differences between groups were biologically meaningful MG-132 manufacturer (small d ≤ 0.3, moderate d ≤ 0.5, large d ≤ 0.8). 47 Ankle joint angles measured during the treadmill running confirmed that the RF group ran with a dorsiflexion angle at touchdown whereas the FF group ran with a plantar flexion angle at touchdown (Fig. 1). Tibial and head acceleration in the time domain were plotted in Fig. 2. There was no significant difference in HP1 or HP2 between footfall patterns (p > 0.05) ( Table 2). However, RF running resulted in a greater PPA compared with FF running (p = 0.009). Tibial and head acceleration

signals in the frequency domain were plotted in Fig. 3A and B, respectively. HPFlow was statistically greater during FF compared with RF running (p = 0.001). TPFhigh was statistically greater during RF compared with FF running (p < 0.001). No statistical difference was observed for HPFhigh or TPFlow Metabolism inhibitor (p > 0.05) ( Table 2). No statistical difference was detected between footfall patterns for HSMlow or HSMhigh (p > 0.05) ( Table 2). Both TSMlow and TSMhigh were statistically greater during RF running than FF running (p < 0.001) ( Table 2). The lowest frequency that was attenuated was 5.1 ± 0.5 Hz (mean ± SD) in RF running and 6.9 ± 0.9 Hz

in FF running (p < 0.001, d = 2.5) ( Fig. 3C). RF running resulted in attenuation of frequencies contained in ATTlow whereas FF running resulted in a gain of these frequencies (p < 0.001) ( Table 2). ATTlow was positive in FF running because the gain of frequencies between 3 and 5 Hz was larger than the attenuation of frequencies between 6 and 8 Hz ( Fig. 3C). RF running resulted in significantly greater ATThigh than FF running as indicated by a larger negative value for ATThigh (p < 0.001) ( Table 2). The aim of this study was to determine if there were differences in the frequency content of impact shock and its subsequent attenuation between RF and FF running patterns. The first hypothesis, that RF running would result in greater peak tibial acceleration and signal power in the higher Terminal deoxynucleotidyl transferase frequency range (9–20 Hz) than FF running, was supported whereas tibial acceleration power in the lower frequency range (3–8 Hz) would be greater in FF than in RF running, was not supported. The higher frequency range is representative of the vertical impact peak and the rapid deceleration of the foot and leg following initial ground contact.13 and 17 RF running resulted in greater tibial acceleration power in the higher range because of the greater peak positive acceleration observed in the time domain with this pattern compared with FF running.

This concise idea has become a central frame of reference for understanding cortical computation. Yet, it stands in contrast to many models of sensory processing. Since Hartline first described lateral inhibition in the retina

(Hartline, 1949), lateral inhibition has been either found experimentally or proposed on theoretical grounds to operate in almost every sensory modality, and at every level of the brain, from the sensory periphery to cognitive and perceptual processing. It has been invoked to sculpt the crude selectivity of excitatory inputs for everything from sound frequency, to odorants, to phonemes. Hubel and Wiesel’s model, by its omission, raises the question Dorsomorphin concentration of whether, and how, inhibition contributes to generating the quintessential feature of cortical receptive fields. A number of cortical receptive field properties have seemed at odds with the simple account provided by Hubel and Wiesel. These response properties have challenged the essence of the feedforward model and forced a critical evaluation of the mechanisms underlying cortical computation. Most of the nonlinear response properties discussed here can be described quantitatively within a theoretical framework in which the feedforward synaptic drive is normalized by a signal related to stimulus

contrast (Carandini and Heeger, 2012, Carandini et al., 1997, Geisler and Albrecht, 1992 and Heeger, 1992). Formally,

the response, R, of a cortical neuron can be described as: R=Rmax[hcc502+c2]nwhere h is the linear, orientation-selective, feedforward drive, c is stimulus find protocol contrast, and c50 is the contrast at which R reaches half its maximal value (Rmax). With proper selection of parameters, this one equation can fit the complete array of simple cell behaviors, including contrast saturation, cross-orientation inhibition, and surround suppression. The equation itself is agnostic regarding the mechanism underlying contrast-dependent normalization; the normalization computation fits simple cell behavior well regardless of the origin of the contrast-dependent normalization signal (Carandini and Heeger, 1994). One widely discussed mechanism is shunting inhibition, in which contrast-dependent changes in input resistance scale the depolarization during generated by the feedforward drive. Inhibition could arise either from pooling the input from orientation-specific interneurons with a range of preferred orientations or from interneurons that are unselective for orientation (Azouz et al., 1997, Cardin et al., 2007 and Hirsch et al., 2003). In addition, the change in input conductance, through its effect on the membrane time constant, τ, could account for the temporal nonlinearities of simple cells (contrast-dependent changes in preferred temporal frequency and response phase).

Depending on the relative expression of the various

transcripts, the loss of C9ORF72 transcript 1 may have a significant impact on Linsitinib research buy selective tissues or cell types. Although preliminary analyses of C9ORF72 protein levels in cultured cells and whole brain tissue homogenate did not show an obvious change in the steady-state levels, we cannot exclude the possibility that reduced transcript levels of C9ORF72 affect protein translation under conditions of stress or may affect protein turnover and/or function. We also cannot guarantee the specificity of the commercial C9ORF72 antibodies used in this study since careful characterization of these antibodies has not yet been performed. In future experiments it will be crucial to generate more specific C9ORF72 antibodies and develop more quantitative approaches to measure SB203580 chemical structure C9ORF72 levels to further clarify the expression and localization of each of the C9ORF72 isoforms in different tissues and at various stages of disease progression. Although speculative at this time, it is possible that the expression pattern of C9ORF72 in individual patients may contribute to the variability in disease phenotype (FTD versus ALS) or course. A common feature of non-coding

repeat expansion disorders which has gained increased attention in recent years is the accumulation of RNA fragments composed of the repeated nucleotides as RNA foci in the nucleus and/or cytoplasm of affected cells (Todd and Paulson, 2010). In several disorders, the RNA foci have been shown to sequester RNA-binding

proteins, leading to dysregulation of alternative mRNA splicing (Miller nearly et al., 2000, Sofola et al., 2007, Timchenko et al., 1996 and White et al., 2010). Using an oligonucleotide probe specific for the GGGGCC repeat we confirmed the presence of such nuclear RNA foci in postmortem cerebral cortex and spinal cord tissue of C9ORF72 expanded repeat carriers. The GGGGCC sequence motif predicts the potential binding of several RNA-binding proteins, including the serine/arginine-rich splicing factor 1 (SRSF1) and the heterozygous nuclear ribonucleoprotein (hnRNP) A2/B1 ( Cartegni et al., 2003, Smith et al., 2006 and Sofola et al., 2007). Although future studies are needed to clarify whether these or other RNA-binding proteins play any role in disease pathogenesis, aberrant RNA splicing is a highly plausible mechanism in chromosome 9p-linked FTD/ALS given the accumulating evidence for RNA misprocessing in the pathogenesis of both ALS and FTD ( Bäumer et al., 2010). Dysregulation of hnRNP A2/B1 is a particularly interesting possibility since this protein is known to interact with the C/G-rich repeats that form RNA foci in another neurodegenerative condition (FXTAS) and because hnRNP A2/B1 has been shown to interact directly with TDP-43 ( Buratti et al., 2005 and Sofola et al., 2007).

, 2011). Injections of graded concentrations of NaCl (0.3, 0.9, and 2.1 Osm/l) were delivered through an internal carotid artery (ICA) catheter in a volume of 300 μl over a period of 10–15 s. For microdialysis, microdialysis probes Dinaciclib were stereotaxically implanted with the U-shaped tip located within or adjacent to the right SON, as previously described (Ludwig et al., 2002): 1.0 mm posterior to bregma, 1.7 mm

lateral to midline, 9.3 mm below the surface of the skull. After an equilibration period of at least 1 hr, consecutive 30 min dialysis samples were collected at a flow rate of 3 μl/min. After two 30 min baseline periods, rats were stimulated osmotically as described above, and a further two consecutive dialysate samples were collected, frozen, and stored at −20°C until assay for VP. The VP content in the microdialysates was measured by a highly sensitive and selective radioimmunoassay (Landgraf et al., 1995). Rats were anesthetized with pentobarbital (50 mg kg−1) and perfused transcardially in 4% paraformaldehyde in 0.01 M PBS. Brains were then removed, and coronal slices (30 μm) containing the PVN were cut and incubated with one or a combination of the following primary antibodies: rabbit (1:100; Millipore) or goat (1:50; Santa Cruz Biotechnology) anti-V1a receptor; goat anti-CTB (1:2500; List Biological Laboratories); rabbit anti-TRPM4 (1:2,000;

kindly NLG919 research buy donated by Dr. Teruyama, LHSU); rabbit anti-MAP2 (1:500; Sigma-Aldrich); and mouse anti-DBH (1:20,000; Millipore). Incubation in primary antibodies was followed by specific fluorescently labeled secondary antibodies (1:250; Jackson ImmunoResearch Laboratories) for 4 hr. Slices were then

found rinsed and visualized using confocal microscopy (Carl Zeiss MicroImaging; 63× oil immersion, zoomed ×2; single optical plane = 0.5 μm thick) (Biancardi et al., 2010). Single-cell RT-PCR was carried out as previously described with minor modification (Sonner et al., 2011). The cytoplasm of the patched neuron, taking care not to contain the nucleus, was pulled into a patch pipette containing 2 μl DEPC-treated water and then mixed with 1 μl of RNase inhibitor (Applied Biosystems). A nested approach was used to quantify V1a receptor mRNA. The primers used included first-nested PCR (5′-CGAGGTGAACAATGGCACTAAAAC-3′ and 5′-TGTGATGGAAGGGTTTTCTGAATC-3′), second-nested PCR (5′-TCATCTGCTACCACATCTGGCG-3′ and 5′-GTGTAACCAAAAGCCCCTTATGAAAG-3′), primers for TRPM4 (5′-CCTGCAGGCCCAGGTAGAGA-3′ and 5′-TTCAGCAGAGCGTCCATGAG-3′), and GAPDH primers (5′-TTCAACGGCACAGTCAAGG-3′ and 5′-TGGTTCACACCCATCACAAA-3′). All primers were synthesized by Integrated DNA Technologies. Final PCR products were electrophoresed on a 2% agarose gel in TAE buffer (40 mM Tris-acetate, 1 mM EDTA [pH 8]) containing 0.