1 is the only known factor specifically expressed within MGE by a

1 is the only known factor specifically expressed within MGE by all progenitors in the ventricular zone (VZ) and subventricular zone (SVZ) (Flames et al.,

2007 and Marín and Rubenstein, 2001). In addition, Lhx6 and Er81 are expressed in subdomains of MGE and CGE (Figure 2A) (Flames et al., 2007 and Butt et al., 2008). We have generated inducible CreER drivers targeting these transcription factor genes (see Table 1 and Table 2). Although several Nkx2.1 transgenic lines have been generated expressing a constitutive Afatinib chemical structure form of Cre (Fogarty et al., 2007 and Xu et al., 2008), they deviate from the spatiotemporal pattern of endogenous Nkx2.1 to varying degrees, and offer no temporal control over Cre activity. In contrast, our Nkx2.1-CreER driver appeared to precisely recapitulate the endogenous expression and allows temporal regulation of Cre activity, thereby establishing reliable genetic access to the MGE progenitors ( Figure 2). E12 tamoxifen induction resulted in robust labeling of the VZ and SVZ progenitors in MGE and POA but not lateral ganglionic eminence (LGE) ( Figures 2B and 2C). Low-dose tamoxifen induction (0.5 mg/30 g body weight) further revealed radial columns of cells, which likely represent putative

progenitor clones in MGE ( Figure 2D). Consistent with previous studies ( Miyoshi et al., 2007), E12 induction gave rise to cortical GABA neurons expressing parvalbumin (PV), somatostatin (SST), but not vasoactive intestinal peptide (VIP) ( Figures 2J–2L). Recent studies demonstrate Selleck Ixazomib that Nkx2.1 expression continues beyond mid-gestation and persists the in the ventral ridge of SVZ during late embryonic and postnatal ages (Marin et al., 2000 and Magno et al., 2009). Indeed,

we found Nkx2.1-Cre activity in ventral SVZ beyond E17 ( Figures 2E–2G), when the characteristic eminence of MGE had already fused with the adjacent LGE. This raised the issue of whether these ventral SVZ cells derived from earlier MGE or acquired Nkx2.1 expression independently. We found that these Nkx2.1+ cells continued to incorporate BrdU labeling at E17 (administered 4 times every 4 hr) and thus retained mitotic competence, which is a key indication of progenitor properties. Using genetic fate mapping, we further demonstrated that Nkx2.1+ progenitors in ventral SVZ derived from earlier progenitors in MGE (e.g., from E12 MGE progenitors; Figures 2H and 2I) but not the LGE. Members of the Dlx family of homeobox transcription factors, Dlx1, Dlx2, Dlx5, and Dlx6, are expressed mainly in the SVZ of embryonic LGE, MGE, and CGE (Eisenstat et al., 1999). Dlx genes continue to express in subsets of GABAergic neurons in embryonic, postnatal, and mature brains, and have been implicated in regulating their migration, differentiation, survival, and function ( Cobos et al., 2005, Cobos et al., 2007 and Long et al., 2009). Whether and how different members control the development and function of subpopulations of interneurons is not well understood.

We analyzed all postsynaptic partners (labeled and unlabeled, as

We analyzed all postsynaptic partners (labeled and unlabeled, as shown in Figures 3E and 3F) of axonal boutons that contact mHRP-labeled dendritic processes, and found that presynaptic boutons contacting stable dendritic branches had fewer postsynaptic partners than those contacting extended branches (stable: 1.38 ± 0.06, extended: 2.19 ± 0.12 postsynaptic profiles/presynaptic bouton, n = 78 and 47, respectively, p < 0.001; Figure 3I). Furthermore, 79% of synapses on extending dendrites contacted MSBs whereas 38% of synapses on stable dendrites

contacted MSBs. Our previous studies showed that mechanisms that increased synaptic strength and maturation also stabilize dendritic branches (Haas et al., 2006), suggesting that synapses on stable branches may be more mature PLX3397 order than those on dynamic branches. DAPT We previously reported that the proportion of the presynaptic terminal area that is occupied by clustered synaptic vesicles increased during development when synapses mature and termed this metric the maturation index (Li and Cline, 2010). Here, we mapped the maturation index of synapses on stable, extended, and retracted branches (Figures 4A–4C). We found that synapses on stable dendrites had a higher maturation index compared to those on

extended dendrites (stable: 45.2 ± 1.7, n = 78; extended: 35.5 ± 2.5, n = 47, p < 0.001; Figure 4D). We also found that synapses Rolziracetam on retracted dendrites had a low maturation index (17.7 ± 10.2, n = 4 synapses), suggesting that disassembly of synaptic components occurs

prior to branch retraction, consistent with our previous in vivo imaging studies (Ruthazer et al., 2006) and studies in the neuromuscular junction (Colman et al., 1997). This analysis demonstrates that synapses on stable dendrites were significantly more mature than those on extended or retracted dendrites. Data presented above showed that synapses on extended branches tended to be clustered within 1 μm of each other. Analysis of synapse maturation relative to synapse distribution on extended branches showed that synapses that were clustered within 1 μm of each other were less mature, with an average maturation index of 28.9 ± 2.9 (n = 33), while synapses spaced further apart than 1 μm were more mature, with an average maturation index of 42.6 ± 5.0 (n = 12, p < 0.05; Figure 4E). By contrast, synapses on stable branches were relatively mature and their maturation indices were independent of the distance between synapses (maturation index of synapses within 1μm and larger than 1 μm: 45.6 ± 2.3 versus 44.7 ± 2.8, n = 47 and 28, respectively). This analysis indicates that extending branches tend to have clustered immature synapses, whereas synapses on stable branches are more mature and more sparsely spaced. The MSBs that contact mHRP-positive dendrites also contact unlabeled dendrites (Figures 3E and 3F).

We would like to thank the volleyball players for volunteering to

We would like to thank the volleyball players for volunteering to participate in this investigation. Extended appreciation goes out to the coaches who were willing to help us development the necessary experimental protocol

for this investigation. Lastly, the authors are gratified for the technical assistance, skillful expertise, and enthusiastic involvement of Mr. Clevidence, Mr. Kelly, http://www.selleckchem.com/products/AG-014699.html and Mr. Knutson. “
“Physical activity (PA) has been deemed important in child development due to its associated positive outcomes in terms of musculoskeletal and cardiovascular health, socialization, and discipline.1, 2 and 3 The World Health Organization (WHO) recommends that young people should accumulate at least 60 min of moderate to vigorous physical activity (MVPA) daily.4 Children with physical disabilities tend to have lower PA levels compared LY2157299 to those without disability, as has been shown in those with cerebral palsy (CP).5 and 6 Children with CP are affected by impairments that hinder their ability to move and control posture,7

potentially impacting PA participation. In children without disability, fundamental movement skills (FMS) proficiency has been found to be positively associated with the time allocated to PA. Children who have greater FMS proficiency tend to be more active.8, 9, 10 and 11 FMS consist of locomotor and object control skills that form the basis of movement skills that are used in sports and games12 and are believed to develop the foundations of PA patterns that persist throughout a lifetime.13 In children with CP, gross motor function has been suggested to be one of the important factors that influence PA participation,14 possibly as a consequence of delayed FMS development associated with motor impairments. The relationship of FMS with PA can be understood through the International Classification of Functioning, Disability and Health (ICF) model for children and youth.15 The ICF model is considered as the universal framework to describe function, health, and disability and categorizes human function under three components: body functions and structures, activities, and participation.16

In children, these the relevant body function is the motor ability of a child, which could be affected by developmental delay as in the case of those with CP. FMS are complex skills that fall under the activity component, while PA level represents a participation component. The bi-directional relationship of ICF components suggests that targeting the FMS proficiency of children could generate positive effects on their PA engagement. Such relationship may be affected by developmental delay due to a physical disability. As such, this study piloted an FMS training program and examined one direction of a causal relationship between FMS proficiency and PA engagement in two groups of children: those with CP and those without disability.

We scanned alert monkeys while they passively viewed 20 s blocks<

We scanned alert monkeys while they passively viewed 20 s blocks

of Learned symbols, Untrained shapes (other human symbols differing in shape from the Learned symbols), and Faces, alternating with 20 s blocks of a small fixation spot (Figure 3). We first calculated maximum likelihood selleck chemicals llc maps of responsiveness to each stimulus category (Learned symbols, Untrained shapes, Faces) using general linear model methods (Boynton et al., 1996), wherein a hemodynamic impulse response function was convolved with the stimulus paradigm. We defined three category contrasts by performing t tests between responses to different pairs of stimulus categories: Learned symbols versus Faces (LvsF), Learned symbols versus Untrained shapes (LvsU), and Faces versus Untrained shapes (FvsU). Then we defined three category selectivity maps using a conjunction analysis ( Bell et al., 2009 and Price et al., 1997) on the three contrast conditions, using odd-numbered scans:

Face-selective voxels were defined as being more responsive to both F > U AND F > L, both contrasts p < 0.001 (corrected for multiple comparisons, see methods), Shape-selective regions satisfied both L > F AND U > F at p < 0.001, and Learned symbol-selective regions satisfied selleck products both L > U AND L > F at p < 0.001. The maps in Figure 4 and Figure 5 show these category-selective regions, projected onto semi-inflated anatomical maps for each monkey. In all six monkeys, several bilateral regions of the inferior temporal lobe were tuclazepam more active to Faces than to either shape category (F > U AND F > L), consistent with previous reports of face selective regions in the temporal lobe (Tsao et al., 2003). These Face-selective regions showed >90% overlap between the left and right hemispheres for all six monkeys (see Table S1 available online); therefore, we averaged together the left and right Face-selective activations. We identified the three largest Face patches in each monkey as f1, f2, and f3 (posterior to anterior).

We projected the Face-selective patches from each individual monkey onto a common semi-inflated left hemisphere (Figure 6A, red patches); the patches were roughly overlapping in this projection, indicating some consistency in location from monkey to monkey, except for the most anterior Face region, which could comprise two patches or may simply be less reproducible in location from monkey to monkey. The location of the maximally selective voxels in each of the Face-selective patches in each monkey are given in Table S1. The most posterior Face patch (f1) was located in posterior area TEO, sometimes extending into anterior V4, on the ventral bank of the STS near the anterior tip of IOS, with the region of maximum overlap between monkeys at A1. The middle Face patch (f2) was mostly in area TEa with the region of maximum overlap at A8.

, 2005) This phenomenon was reproduced in E18 5 control mice by

, 2005). This phenomenon was reproduced in E18.5 control mice by the combined application of the GABAA receptor blocker picrotoxin (PTX, 10–30 μM) and the glycine receptor blocker strychnine (Strych, 0.3–0.5 μM; n = 5) (Figure 6A: left, control; right, PTX plus Strych). These effects are seen as progressive changes in the phase values of ventral root bursts that are shifted from left-right

and flexor-extensor alternation (phase values around 0.5) to left-right and flexor-extensor synchrony (phase values around 0) (Figure 6A1). The circular plots summarize the normal left-right and flexor-extensor alternation (black squares) and their change into synchronization after total blockade of inhibition (red circles) in five independent experiments using control E18.5 embryos (Figure 6A2). A prominent LY2835219 difference in this pattern was seen in Vglut2-KO mice.

Here, during NMDA/5-HT/DA induced rhythmic activity, the combined application of the same doses of PTX and strychnine initially increased the frequency of the activity, then slowed it down and eventually led to the uncoupling selleck screening library of bursts in all roots (Figure 6B: left, control; right, PTX plus strychnine; n = 8, Figure 6B1). This effect is seen as an insignificant coupling between individual roots after blockade of inhibition (Figures 6B1 and 6B2, red circles), and it was observed in all the experiments carried out in Vglut2-KO mice (n = 8). Thus, blockade of inhibition in Vglut2-KO mice resulted in low amplitude and slow frequency oscillations Terminal deoxynucleotidyl transferase in MNs. In induced Vglut2-KO mice that otherwise had a locomotor phenotype similar to chronic Vglut2-KO mice, there was a change from alternation into synchronization after

total blockade of inhibition, similar to controls (n = 4; data not shown). The 10%–20% remaining Vglut2 protein seen in induced Vglut2-KO was apparently enough to coordinate synchronous activity. These experiments show that coordination of the drug-induced rhythmic activity observed in chronic Vglut2-KO mice is completely dependent on a GABAA/glycinergic inhibitory network. The experiments blocking inhibitory synaptic transmission suggest that rhythm and pattern generation in the Vglut2 knockout is produced by a network of inhibitory neurons. Well-known inhibitory neurons that provide rhythmic inhibition of MNs during normal locomotor activity are the RCs and the rIa-INs. We first assessed whether the rIa-IN pathway was present in E18.5 Vglut2-KO mice. We took advantage of the recent demonstration that, like cats, newborn mice display a strong Ia-mediated reciprocal inhibition between the knee extensor quadriceps and the knee flexor posterior biceps-semitendinosus (PBST) (Wang et al., 2008).

In addition,

In addition, ALK inhibitor Wnt-5a treatment reduced the pool of previously surface biotinylated and internalized GABAARs, suggesting that increased clustering of GABAARs reflected enhanced recycling of endocytosed receptors. In support of this mechanism, treatment of neurons with a Wnt-5a-mimicking peptide (Foxy-5) that specifically activates noncanonical Wnt pathways replicated the Wnt-5a effect on GABAAR clustering. Moreover, cotreatment with Foxy-5 and pathway-specific pharmacological inhibitors allowed the conclusion that Wnt-5A-induced clustering of GABAARs

involved the noncanonical Wnt/Ca2+ pathway and CaMKII. The CaMKII targets that are phosphorylated in response to Wnt-5a have so far not been determined. In addition to the Wnt/Ca2+ pathway the canonical Wnt pathway is strongly implicated in the regulation of GABAergic inhibition by the aforementioned effects of Li+ and GSK3β on the stability and postsynaptic clustering of gephyrin (Tyagarajan et al., 2011). However, in apparent conflict with this study, the canonical Wnt ligand Wnt-7A and Li+ had no significant effect on GABAAR clustering in the study by Cuitino et al. (2010). There has been remarkable progress in understanding the mechanisms that regulate GABAergic transmission. Dynamic changes Selleckchem Afatinib in GABAAR trafficking

represent prevalent forms of GABAergic neural plasticity, although changes in subunit gene expression, Cl− reversal potential, and GABA release are also important, especially under pathological conditions. GABAAR-associated proteins and signaling factors involved in GABAAR trafficking are shared with other signal transduction pathways, thereby allowing for complex interactions among multiple neurotransmitter and signaling systems. Developmental imbalances between neural excitation and inhibition are broadly implicated in the etiology of the most prevalent neuropsychiatric disorders. Such imbalances may be further amplified by trafficking deficits in GABAARs, as suggested by activity and anoxia-induced loss of postsynaptic GABAARs (Mielke and Wang, 2005, Terunuma et al., 2008 and Arancibia-Cárcamo et al., 2009). PD184352 (CI-1040) Indeed, deficits in GABAergic transmission may

be central to the etiology of neuropsychiatric disorders such as major depressive disorder (Luscher et al., 2011), bipolar disorder (Craddock et al., 2010), and schizophrenia (Charych et al., 2009). Conversely, the cell surface trafficking and synaptic accumulation of GABAARs is modulated by Wnt pathway kinases (GSK3β, Akt) that are central to the therapeutic action of mood stabilizing and antidepressant drugs (Logan and Nusse, 2004, Okamoto et al., 2010 and Tyagarajan et al., 2011). Further progress in understanding of GABAAR trafficking mechanisms should provide better mechanistic insights into these disorders and facilitate the development of more effective drug therapies. Despite the recent progress, diverse aspects of GABAAR trafficking remain poorly understood.

In addition to splicing, our HITS-CLIP analysis revealed that abo

In addition to splicing, our HITS-CLIP analysis revealed that about half of Mbnl2 targets are located in annotated 3′ UTRs. Since microarray and RNA-seq analyses did not detect major changes in transcript levels, Mbnl2 may play important roles

in RNA localization and/or translation and these pathways Selleckchem Sorafenib could also be affected in the DM brain. Mbnl2 knockout mice show several phenotypes consistent with abnormalities observed in myotonic dystrophy. For example, EDS is a common and disabling feature of DM1 ( Ciafaloni et al., 2008; Pincherle et al., 2012; Yu et al., 2011). However, the molecular basis of this sleep disturbance is unknown. In some cases with advanced disease, EDS may result from obstructive sleep apnea ( Pincherle et al., 2012). DM1 may also have direct effects on sleep regulatory circuits in the CNS and REM sleep changes in patients, including an increase in daytime and nighttime REM sleep propensity and higher frequency

of sleep onset REM period(s) and REM density, have been reported ( Bennett et al., 2007; Ciafaloni et al., 2008; Pincherle et al., 2012). Here, we demonstrate related REM sleep changes in Mbnl2 knockout mice, including increased REM sleep amounts and episode numbers. These changes were observed over 24 hr but were more profound during the active, or dark, period. Mbnl2 knockouts had twice as many REM sleep episodes compared to wild-type mice, and a large portion of these episodes had short latencies from the proceeding wake episodes. Profound REM sleep rebound was CHIR-99021 molecular weight also seen in Mbnl2 knockout mice after sleep deprivation and, in contrast, there were no apparent changes in wake and NREM sleep parameters in these mutants. Our results indicate that Mbnl2 knockout mice will be useful to study DM1-associated splicing alternations that impact sleep regulatory mechanisms. Additional phenotypes characteristic of DM include mental retardation in congenital DM1, while childhood through adult onset disease is associated with learning disabilities, autistic behavior, impaired cognitive function, cerebral structural changes, and nonverbal episodic

memory impairment (Meola and Sansone, 2007; Weber et al., 2010). Interestingly, PDK4 Mbnl2 knockout mice exhibit impaired learning on a hippocampal-dependent task, a decrease in NMDAR-mediated synaptic transmission, and an impairment of hippocampal synaptic plasticity. Several of the misregulated splicing events identified during this study might contribute to these impairments, including Cacna1d ( McKinney et al., 2009), Tanc2 ( Han et al., 2010), Ndrg4 ( Yamamoto et al., 2011), and Grin1 ( Shimizu et al., 2000). For example, DM1 patients exhibit increased expression of a splice variant of GRIN1 that includes exon 5 ( Jiang et al., 2004), which is thought to contribute to the age-related decline in frontotemporal functions, including memory ( Modoni et al., 2008; Romeo et al., 2010; Weber et al., 2010).

However, the effect of risk pressure on dACC activity reversed de

However, the effect of risk pressure on dACC activity reversed depending on choice. A positive effect of risk pressure on dACC activity was apparent when subjects chose

the safer option, whereas a negative effect was apparent when subjects chose the riskier option. In other words, dACC activity increased with increasing risk pressure when choices went against the prevailing risk pressure but decreased EGFR inhibitor with increasing risk pressure when subjects chose in agreement with risk pressure (Figures 4C and 5A). The dACC risk pressure signal cannot be explained away as a signal-indexing approach toward a reward that might be delivered at the end of the block (Croxson et al., 2009 and Shidara and Richmond, 2002), because progress through the sequence selleck screening library of trials itself was present as a separate regressor in the general linear model (GLM) and associated with an independent effect on dACC activity (this is the effect already shown; Figure 3B). The risk

pressure signal cannot be explained away as a consequence of differing average reward expectations associated with different target levels because the use of a “multiplier” procedure (see the Experimental Task section in Experimental Procedures) ensured that average reward expectations were the same at the beginning of a block regardless of the target. It is, however, the case either that expectations about the reward that would be received at the end of the block (as opposed to just after the current trial within the block) began to diverge as soon as participants began to make choices and were either lucky or unlucky. However, when we included an additional term in the GLM indexing the expected value of the reward at the end of the block we found that it had an independent

effect on dACC activity (Figure 5B). No similar signal was observed in vmPFC (Figure S6). In summary, dACC exhibited a number of signals related to progress through the sequence of decisions, the expected reward at the end of the sequence, and a risk pressure signal indexing the need to take riskier choices as a function of contextual factors (accumulated resources, target, and remaining foraging opportunities). The risk pressure signal flipped with the decision strategy that subjects pursued (safer versus riskier); it was positive when subjects needed to change their behavior and switch to riskier choices as opposed to the default safer choice. In addition to these contextual effects, the same dACC region also exhibited activity that was tied to specific patterns of choice and choice valuation. dACC activity was higher in decisions in which the riskier rather than the safer choice was taken (choiceriskier − choicesafer; Figure 4A).

081 144) Scanning costs were in part funded by the Amsterdam gra

081.144). Scanning costs were in part funded by the Amsterdam graduate school for the neurosciences (ONWA). P.N.T. was supported by a University Research Fellowship of the Royal Society (UF080591) and by the Swiss National Science Foundation (Grants PP00P1_128574 and

CRSII3_141965). Study 1 was completed at the Behavioural and Clinical Neuroscience Institute, University of Cambridge, which is supported by a joint award from the Medical Research Council and Wellcome Trust (G00001354). We thank Anna Barnes for assistance with image preprocessing, Todd Hare for comments on the manuscript and assistance with the PPI analysis, Zeb Kurth-Nelson for comments on the manuscript, Bortezomib in vivo and our three anonymous reviewers for helpful feedback and suggestions. “
“(Neuron 78, 440–455; May 8, 2013) The original version of Figure 6 contained incorrect sequences for the two CGG KI mouse lines

used in this study. This typographical error does not affect our interpretation of the data. We apologize for any inconvenience that this error has caused. The corrected figure is below and has also been corrected in the online version of the paper. Figure 6.  Sequence Differences 5′ of the Repeat Explain Divergent Inclusion Formation in Two Mouse Knockin Models of FXTAS “
“The existence Paclitaxel price and role of a centrifugal pathway from higher visual centers back to the retina have been controversial issues since the end of the 19th century. Dogiel and Cajal first described centrifugal nerve axons projecting into the bird retina in the Astemizole 1880s using Golgi impregnation, and since then centrifugal axons have been identified in a number of other nonmammalian species including fish and amphibians. The existence of centrifugal axons in the mammalian retina, however, has long been disputed (Repérant et al., 2006); the view expressed by many is that central effects on

visual responses are mediated at the level of the lateral geniculate nucleus in the thalamus and not by axons extending into the retina. Recent evidence has definitively shown the existence of centrifugal axons entering the mammalian retina, but the number of such axons is exceptionally small, probably explaining why their existence was difficult to demonstrate. In primates, including man, the number given is no more than 25–30 such axons. These axons and their terminals do, however, spread widely across the retina, contain both histamine and serotonin, and are part of the arousal system that projects axons to many brain areas (Gastinger et al., 2005). The role of these centrifugal axons is not well understood; they are active when an animal is awake, but they also appear to play a role regulating blood vessels and blood flow in the retina. In other retinas such as birds and fish, the number of centrifugal axons is substantial—10,000 or more such axons in the chicken, for example.

3 μCi/mmol) and [3H]DA ([3H]dihydroxyphenylethylamine, [3H]dopami

3 μCi/mmol) and [3H]DA ([3H]dihydroxyphenylethylamine, [3H]dopamine; 46 μCi/mmol) were purchased from PerkinElmer, Boston, MA. [3H]1-Methyl-4-phenylpyridinium

([3H]MPP+; 85 μCi/mmol) was supplied by American Radiolabeled Libraries Chemicals (St. Louis, MO). FRAX597 chemical structure Paroxetine was from Santa Cruz Biotechnology, mazindole, serotonin, levamisole, cocaine, aminorex, nisoxetine, D-amphetamine, and monensin were purchased from Sigma–Aldrich Co. The samples used in this study were obtained from drug users participating voluntarily and anonymously in the ‘checkit!’ drug prevention program. Three to ten milligrams of substance were scraped into a tapered 2 ml test vial and weighed with an analytical balance. The substance was dissolved in 1 mL of methanol and vortex mixed for 1 min. The solution was centrifuged for 3 min at 10,000g in an Eppendorf centrifuge. Ten microliters of the supernatant were diluted with 0.4 mL of internal standard solution (trazodone 50 μg/mL dissolved in 10 mM aqueous ammonium formate buffer), 2 μl of the solution was analysed

with reversed phase HPLC and LC/mass spectrometry coupling as described in a previous study ( Rosenauer et Capmatinib concentration al. 2013). The generation of HEK293 cell lines expressing the human isoforms of SERT, NET, or DAT (HEK-SERT, HEK-DAT, or HEK-NET, respectively) was described earlier (Scholze et al., 2002). HEK293 cells stably expressing either neurotransmitter transporter were seeded onto poly-d-lysine-coated 96-well

plates (40,000 cells/well), 24 h prior to the experiment. For inhibition experiments, the specific activity of the tritiated substrate was kept constant: [3H]DA, 0.1 μM; [3H]MPP+, 0.015 μM; [3H]5-HT, 0.1 μM. Assay conditions were used as outlined earlier ( Sucic et al., 2010). In brief, the cells were washed twice with Krebs–Ringer–HEPES buffer (KHB; composition: 25 mM HEPES·NaOH, pH 7.4, 120 mM NaCl, 5 mM KCl, 1.2 mM CaCl2, and 1.2 mM the MgSO4 supplemented with 5 mM d-glucose). Then, the diluted reference and sample compounds were added and incubated for 5 min to allow for equilibration with the transporters. Subsequently, the tritiated substrates were added and the reaction was stopped after 1 min (SERT and DAT) and 3 min (NET), respectively. Cells were lysed with 1% SDS and the released radioactivity was quantified by liquid scintillation counting. All determinations were performed in duplicate or triplicate. For release studies, HEK-SERT, HEK-NET, or HEK-DAT cells were grown overnight on round glass coverslips (5-mm diameter, 40,000 cells per coverslip) placed in a 96-well plate and preloaded with 0.4 μM [3H]dopamine, 0.1 μM [3H]MPP+, or 0.4 μM [3H]5-HT for 20 min at 37 °C in a final volume of 0.1 mL/well. Coverslips were then transferred to small superfusion chambers (0.2 ml) and superfused with KHB (25 °C, 0.7 ml × min−1) as described (Scholze et al., 2002).