Subgroup analyses stratified by age group, performance status, hi

Subgroup analyses stratified by age group, performance status, histology/tumor grade, or stage/debulking status were also conducted. A total of 462 patients were enrolled in this study, with 276 evaluable for inclusion in the analysis (Figure 1). Patient characteristics are displayed in Table 1. The median age of

the study population was 61 years, and most patients had tumors that were classified as papillary serous (84%), poorly differentiated (83%), stage III (85%), and optimally debulked (72%) (Table 1). The majority (94%) completed 4-8 cycles of chemotherapy. The median follow-up period was 23 months (range, 12–37 months), and 193 (70%) patients experienced selleck chemicals disease progression within this time frame. The median PFS was estimated to be 15.9 months (95% confidence interval [CI], 14.3–17.1 months). Assay results for carboplatin were available for 231 patients, with 44 (19.1%) patients identified as resistant to this therapy in the chemoresponse assay. Assay data for paclitaxel were available for 226 patients, 49 (21.7%) of whom were classified as resistant. Assay resistance by age, performance status, histology/grade,

and stage/debulking status is summarized in Table 2. There is no evidence that assay result for either carboplatin or paclitaxel is correlated with patient characteristics. Assay result for carboplatin was significantly associated with clinical outcome (Figure 2). The median PFS was 16.6 and 11.8 months for assay Libraries nonresistant (sensitive + IS) and resistant tumors, respectively. Patients displaying assay resistance to find more carboplatin were at a higher risk of disease progression as compared to those who were nonresistant (HR, 1.87; 95% CI, 1.29–2.70; P < .001). These results were 17-DMAG (Alvespimycin) HCl consistent in multivariate analysis after controlling for clinical covariates (HR, 1.71; 95% CI, 1.12–2.62; P = .013) ( Table 3). Analysis of subgroups (age group, performance status, histology, stage/debulking status) was also conducted ( Figure 3), and the association between PFS and assay result for carboplatin was suggested across all subgroups.

The data also suggest that patients with assay resistance to paclitaxel would experience shortened PFS, but the association did not reach the level of statistical significance ( Table 3). Assay results for carboplatin and paclitaxel were highly correlated. For 220 patients with assay data available for both agents, 75.5% were nonresistant to both agents and 15.9% were resistant to both agents, while only 8.6% of patients were resistant to only 1 agent (5.9% to carboplatin and 2.7% to paclitaxel). Patients resistant to both agents experienced the worst outcomes (HR, 1.66; 95% CI, 1.10–2.52; P = .017, as compared to patients nonresistant to both agents). Multivariate analysis indicated the same tendency, although the association was not statistically significant ( Table 3).

Finally talc was added as an anti-sticking agent based on the sol

Finally talc was added as an anti-sticking agent based on the solid dry weight of the polymers with continuous stirring for approximately 10 min. In this

way all the coating dispersions were prepared and was sprayed onto the drug loaded pellets until the pellets achieved desired coating level. Compositions were given in Table 3. The above pellets were evaluated for various parameters like particle size analysis, size distribution, shape and surface roughness, flow properties, drug content and in vitro dissolution profile. selleck screening library Particle size analysis was done by optical microscopy method. Drug content was carried out by UV method. 4, 14 and 15 The particle size of drug loaded formulations were measured by an optical microscope fitted with an ocular Epacadostat mw and stage micrometer and particle size

distribution was calculated. The Weswox model having resolution of 45× was used for this purpose. The instrument was calibrated at 1 unit of eyepiece micrometer was equal to 30.07 μm. Angle of repose (θ) was assessed to know the flowability of pellets, by a fixed funnel method using the formula: Angleofrepose(θ)=tan−1(h/r) Tap density and bulk density of the pellets were determined using tap density tester. The percentage Carr’s index (I, %) was calculated using the formula: Carr’sindex(I,%)=Tappeddensity−Bulkdensity/Tappeddensity Hausner’s ratio was measured by the ratio of tapped density to bulk density. Hausner’sratio=Tappeddensity/Bulkdensity The ADP ribosylation factor Libraries friability test was performed on the pellets to ensure their mechanical strength. Lower friability values indicate good mechanical strength. Pellets of known mass

were placed in a Roche Friability tester and subjected to impact testing at 25 RPM for 5 min. Prior to and following the test, the weights of the formulation were accurately recorded and friability ratios were calculated with the given equation. F=W1−W2/W1×100F=W1−W2/W1×100where, W1 = Initial weight of the formulation, W2 = Final weight of the formulation. Shape and morphological features of pellets were observed by scanning electron microscopy (SEM). Surface and shape of the formulated pellets were observed to be varying depending on composition of polymer and plasticizer. The shape of the pellets was investigated by JEOL, JSM-6610LL, Scanning electron microscope, Japan. Compatibility of aceclofenac with polymers EC N50 and HPMC E5 in 1:1 ratio of physical mixtures were analyzed by Fourier transform-infrared spectroscopic analysis (FT-IR) and the IR spectra were taken. The aceclofenac content of the pellet formulation was evaluated over accurately weighed 100 mg pellets which were dissolved in a little quantity of ethanol and then the volume was made upto the mark with pH 6.8 phosphate buffer. The resulted solution was analyzed spectrophotometrically at 274 nm (LAB INDIA, UV-3092) after suitable dilution with pH 6.8 phosphate buffer.

Similarly, adding a novel constituent active to an anthelmintic c

Similarly, adding a novel constituent active to an anthelmintic combination product that includes

existing constituent actives, as opposed to using it alone or in rotation in areas where resistance already exists, should not predispose it to a more rapid selection for evolution of parasite resistance as demonstrated in recent modeling and empirical studies (Dobson et al., 2011a, Dobson et al., 2011b, Leathwick, 2012 and Leathwick et Bcl-2 inhibitor al., 2012). Proof of efficacy of combinations against existing resistant parasite isolates in dose-determination experiments will alleviate this concern to some extent, although only field use will reliably reveal if selection of a resistance mechanism that crosses anthelmintic classes can occur in nematode populations following the use of a new drug. As noted above, few farmers test selleck chemicals for AR (Lawrence et al., 2007, Dobson et al., 2011a and Morgan et al., 2012). Under these circumstances, a concern is that fixed-dose combination anthelmintic products could mask the development of resistance. This may be considered a technology transfer

or compliance problem that does not change the conclusions from modeling studies that resistance will be substantially delayed by administering anthelmintic combination products in comparison to rotation or sequential use strategies of single-constituent active products (Smith, 1990, Barnes et al., 1995 and Leathwick, 2012). Fixed-dose combination anthelmintic products appear to slow the development of resistance because they afford the highest possible kill of nematodes (Bartram et al., 2012). Parasites that survive one constituent active in the combination are killed by the other constituent active(s); individual parasites that possess two distinct R-alleles, each of which is present in the population at very low frequencies, will initially be very rare. However,

the use of anthelmintic combination products does not eliminate the significant risk for resistance posed by dosing strategies that allow livestock to graze clean (low contamination) pastures after treatment. This tuclazepam practice readily selects for resistant populations as the parasites that survive the treatment become the major source of subsequent contamination on these pastures (LeJambre, 1978, Cawthorne and Whitehead, 1983, Michel, 1985, Taylor and Hunt, 1988 and Taylor and Hunt, 1989). This concern is obviously more acute if resistance to one of the constituent actives in the combination product is already present and unsuitable treatment regimes are implemented. The benefits of maintaining a population of nematodes in refugia, as a means of slowing the development of drug resistance, were first advanced by Martin et al. (1981) and should not be underestimated; van Wyk (2001) and Dobson et al. (2001) proposed that refugia could be the most important factor in determining the rate at which AR develops.

Such recycling of proteins is natural because actin network dynam

Such recycling of proteins is natural because actin network dynamics are essential for such processes as growth of axonal filopodia, which are used in searching learn more for growth cone guidance cues (Tessier-Lavigne and Goodman, 1996). The presence of DCC protein in the identified network ( Figure 2 and Figure 3), also suggests an important role of perturbed axonal guidance in autism. Although DCC is also involved in dendrite development ( Suli et al., 2006), this receptor and its signaling protein, netrin, are primarily essential for guiding

axons to their final destinations ( Tessier-Lavigne and Goodman, 1996). Several signaling pathways highlighted in Figure 3, such as the WNT and reelin pathways, also play prominent roles in neuron motility ( Reiner and Sapir, 2005 and Salinas and Zou, 2008). In addition,

several specific proteins, such as PAKs and LIMK, which regulate the dynamics of actin network, are reused in axonal morphogenesis. Consequently, malfunction of many proteins shown in Figure 3 may influence autistic phenotypes through their role in either dendrite or axon signaling, or possibly a combination of these processes. Considering the genes hit by rare de novo variants from the perspective of the functional molecular network (Figure 3) allowed us to investigate the likely morphological consequences of some CNVs. There is growing evidence that changes in dendritic spine morphology contribute to a number of neurological disorders (Halpain et al., 2005). A decrease high throughput screening compounds in the density of dendritic spines in regions of the cerebral cortex has been linked

to schizophrenia (Blanpied and Ehlers, 2004, Garey et al., 1998 and Glantz and Lewis, 2000). On the other hand, an increase in spine size or density has been connected to Fragile X syndrome, a disorder frequently associated with autism (Fiala et al., 2002 and Kaufmann and Moser, 2000). Following the logic that CNV deletions should decrease while duplications increase the dosage of the affected genes, we can infer—based on the structure and regulatory logic of the functional network in Figure 3—the morphological effects of 13 gene perturbations on dendritic spines. Specifically, we found that in 11 out of 13 cases (∼85%) the gene perturbations caused by the observed CNV events should increase either dendritic 3-mercaptopyruvate sulfurtransferase spine growth or their density (see Table S4). This result is consistent with recent findings that autistic individuals have increased spine density in portions of their cerebral cortex (Hutsler and Zhang, 2010 and Woolfrey et al., 2009) and possibly a local brain overconnectivity (Scott-Van Zeeland et al., 2010). Overall, the results of this study, the first to our knowledge, demonstrate that autism-associated rare de novo CNVs, observed in an unbiased genome-wide study, form a large and statistically significant functional network responsible for synaptogenesis, axon guidance, and related molecular processes.

At the other

At the other Birinapant solubility dmso extreme, high-amplitude waves occurred

in unison across the brain. Nearly all waves fell somewhere along this gradual continuum, with most waves being more local than global given our working definition. Finally, we examined whether specific pairs of brain structures had a strong tendency to express local slow waves concordantly and whether particular brain regions had a strong degree of involvement in slow waves (Figure 4E). Medial prefrontal regions, such as the anterior cingulate and orbitofrontal cortex, were typically more involved than regions in MTL. In addition, homotopic cortical regions across hemispheres tended to be concordant in prefrontal cortex (but not MTL), and there was a slight bias of regions in the left hemisphere to be more involved in slow waves. Our results thus far demonstrate that slow waves, this website the most prominent EEG event of NREM sleep, occur mostly

locally. This finding suggests that sleep, which usually is associated with highly synchronized activity, has an important local component. We thus wondered whether sleep spindles, the other hallmark of NREM sleep EEG (Loomis et al., 1935), also occur locally. Spindles are generated in the highly interconnected thalamic reticular nucleus, and the neocortex governs their synchronization through corticothalamic projections (McCormick and Bal, 1997 and Steriade, 2003). Asynchronous

spindles were reported in nonphysiological conditions (Contreras et al., 1996, Contreras et al., 1997 and Gottselig et al., 2002). To examine this issue, spindles were detected automatically in each depth electrode separately (Experimental Procedures; Figure S5), and we examined to what extent spindles occurred concurrently across frontal and parietal channels. Examination of local versus coincident spindles was performed only in cortical sites that had regular spindle occurrences, thereby excluding the possibility that local occurrence of spindles arises merely from their total absence in remote brain structures. As defined for slow waves, we operationally define a local (global) sleep spindle as an event detected in less (more) than 50% of recording locations. Numerous incidences 4-Aminobutyrate aminotransferase of sleep spindles occurring in specific brain areas were found (Figure 5A). Regional spindles occurred without spindle activity in other regions, including homotopic regions across hemispheres and regions with equivalent signal-to-noise ratio (SNR) showing the same slow waves. We set out to quantitatively establish to what extent local sleep spindles occur across the entire dataset. We determined for each spindle in a given region whether spindles were present or not in other brain structures (Experimental Procedures).

We next tested whether the kinetics of somatic current injections

We next tested whether the kinetics of somatic current injections can affect the CpS waveform. By adjusting the amplitude of the somatic current injection (range: 5–18 nA), we triggered

complex-like spikes that closely resembled synaptically stimulated CpSs (Figure 7; McKay et al., 2005 and Davie et al., 2008). First, we injected a current (Ifast; Figure 7A; 0.4 ms rise and 4 ms decay) that triggered a complex-like spike with the maximal number of spikelets without inactivation that occurs with increasing current injection ( Davie et al., 2008). Repetitive 2 Hz injection of Ifast did not alter any parameter of complex-like spikes, suggesting that 2 Hz stimulation does not alter learn more CpSs simply by inactivation of voltage-gated conductances ( Figure S4). We

then reduced the amplitude of the injected current by 20% without altering the kinetics (Ifast-20%Q ; Figure 7A). This value matches the reduction of the current-time integral that occurs with 2 Hz synaptic stimulation ( Figure 1; charge is reduced by 20.4 ± 2.6%). Decreasing the amplitude (and charge) by 20% did not alter the number of spikelets ( Figure 7B; n = 6; p > 0.05; ANOVA), although there was a slight reduction in the amplitude of the first spikelet ( Figures 7C and 7D; n = 6). With further reduction of the somatically injected charge (30% of Ifast) CFTR modulator the number of spikelets decreased ( Figure S5; n = 6; p < 0.05; ANOVA). Finally, we imposed the same charge as Ifast-20%Q but with altered kinetics by decreasing the injected current peak amplitude and slowing the decay time to 5 ms. The resulting current waveform (Islow-20%Q; Figure 7A) had a peak amplitude and a current-time integral that was reduced by 36% and 20%, respectively, compared to Ifast. The number of spikelets evoked by Islow-20%Q was reduced compared to those evoked by Ifast ( Figure 7B; 2.8 ± 0.17 and 4.2 ±

0.3; n = 6; p < 0.05; ANOVA). This suggests that the quantity of somatic charge is not the sole determinant of the number of spikelets until and that the kinetics of the injected current can regulate the shape of the complex-like spike waveform. Remarkably, the Islow-20%Q waveform altered the spike height, rising rate, and ISI of the complex-like spike response in the same manner as 2 Hz synaptic stimulation affected the CpS (compare Figures 6C–6E and 7C–7E). For the second and third spikelet, the increase in spike height (69.3 ± 23.5% and 166.5 ± 68.0%; n = 6 and 5; p < 0.05; ANOVA), rate of rise (80.4 ± 43.1% and 101.9 ± 37.8%; n = 6 and 5; p < 0.05; ANOVA), and ISI (22.2 ± 7.7% and 30.8 ± 10.1%; n = 6 and 5; p < 0.05; ANOVA) caused by Islow-20%Q is predicted to increase the reliability of spikelet propagation. The decrease in the first spikelet height (−18.8 ± 2.4%; n = 6; p < 0.

In contrast, expression of DN-nectin3 or DN-afadin caused electro

In contrast, expression of DN-nectin3 or DN-afadin caused electroporated cells to accumulate

near the IZ (Figures 2E and 2F), indicating that nectin3 and afadin act in neurons, at least in part, to regulate glia-independent somal translocation. We next determined the mechanism by which nectin3 and afadin regulate radial migration. We reasoned that the two proteins might help to anchor the leading processes of neurons in the MZ. We therefore evaluated neuronal morphology following perturbation of nectin3 or afadin function by knockdown and dominant-negative approaches, which gave similar results. Although neurons largely failed to migrate into the CP following perturbation of nectin3 or afadin, they still properly polarized the Golgi apparatus ahead of the nucleus (Figure 3A) and also developed stereotypical polarized morphologies characterized by leading processes (Figures 3B–3D). At 2–3 days after electroporation, leading processes that

extended toward or even into the MZ were ON-01910 in vivo observed in both control neurons and neurons expressing shRNAs against nectin3 or afadin (Figures 3B and 3C). A small decrease in the number of branches was observed after 3 days in the case of afadin shRNA electroporation, suggesting onset of leading-process retraction. However, only control neurons had their cell bodies located close to the MZ, indicative of somal translocation. Cell bodies in the knockdown experiments failed to translocate toward the MZ (Figures 3B and 3C) and remained near the IZ and lower CP, as nonelectroporated cells bypassed them to expand the CP. This CP expansion initially caused the leading processes of affected neurons to appear

longer than those of controls neurons TCL 2–3 days after electroporation (Figures 3B and 3C), but many of these processes were subsequently retracted by 4 days after electroporation (Figures 2C and 2F). Additionally, whereas the leading processes of control neurons extensively branched in the MZ, no such branching was observed after nectin3 or afadin knockdown (Figure 3D). Together, these data indicate that nectin3 and afadin are not required for neuronal polarization or initial process extension, but are important for leading-process anchorage and arborization in the MZ and subsequent somal translocation. To directly determine whether nectin3 and afadin are required for somal translocation, we carried out time-lapse imaging experiments. Neurons from E13.5 animals were electroporated with control, nectin3, or afadin shRNAs, and neocortical slice cultures were prepared at E15.5. As reported (Franco et al., 2011), control neurons translocated their cell bodies along their leading processes toward the MZ (Figure 3E). In contrast, neurons expressing shRNAs for afadin or nectin3 extended leading processes but failed to undergo somal translocation (Figure 3E).

, 2013b) (3) Intersubject registration The convolutions of huma

, 2013b). (3) Intersubject registration. The convolutions of human cerebral cortex are highly variable across

individuals in many regions ( Ono et al., 1990). In order to compensate for this variability and thereby enable accurate intersubject comparisons, it is vital to register each individual to a common atlas target. For the mouse and macaque, an individual brain is reasonable for an atlas target ( Figure 1, columns 1 and 2), though MRI-based population-average macaque atlases are available as volumes ( Kovacević et al., 2005 and McLaren et al., 2009) and surfaces (M.F. Glasser et al., 2012, OHBM, abstract; M.F. Glasser et al., 2013, SfN, abstract). For human cortex, early surface-based atlases used individual brains find more ( Van Essen and Drury, 1997 and Van Essen, 2002a), but these have

been supplanted by population-average atlases. Volume registration achieves accurate intersubject alignment of subcortical nuclei, as shown by the group average of 120 HCP subjects ( Figure 1D), but blurring CHIR99021 of cortical sulci and gyri occurs even when using high-dimensional nonlinear registration. Instead, surface-based cortical registration provides clear advantages ( Fischl et al., 1999a, Fischl et al., 1999b, Fischl et al., 2008, Van Essen, 2005, Yeo et al., 2010, Van Essen et al., 2012a, Van Essen et al., 2012b and Wang et al., 2011). For cerebral cortex, registration to a population-average surface-based template avoids biases associated with the idiosyncratic convolutions of any individual subject. Phosphoprotein phosphatase One widely used atlas template is FreeSurfer’s “fsaverage,” which uses an energy-based registration method to align individual folding patterns to a population average map based on the pattern of folding ( Fischl et al., 1999b and Fischl et al., 2008). A recent extension of this is the “fs_LR” surface mesh and the “Conte69” atlas, which capitalize on FreeSurfer’s energy-based registration but achieve geographic correspondence between left and right hemispheres using landmark-constrained interhemispheric registration ( Van Essen et al., 2012b).

In the average midthickness surfaces from 120 HCP subjects ( Figure 1, right column), only the major sulci and gyri are visible; the distinctive secondary and tertiary folds of individual subjects are not well preserved owing to imperfect alignment, especially in regions of high variability. The cerebellar atlas surfaces shown in Figure 1 are useful for surface-based visualization but unfortunately not for surface-based analysis (e.g., smoothing or intersubject alignment). Higher-quality structural images and cerebellum-specific segmentation algorithms will be needed in order to enable cerebellar surface reconstructions in individual subjects as a matter of routine. Subcortical nuclei constitute a major fraction of the mouse brain, but progressively much smaller fractions of the macaque and human (Figure 1, top row).

Likewise, BrmDN-overexpressing (n = 10;

Likewise, BrmDN-overexpressing (n = 10; Torin 1 concentration Figure 4E) and brm MARCM (n = 6; data not shown) ddaF neurons survived, whereas the wild-type ddaF neurons underwent apoptosis by 18 hr APF (n = 15; Figure 4D). CBP RNAi partially inhibited ddaD/E dendrite pruning (n = 15; Figure 4C′) because

the knockdown of CBP using the Gal42-21 driver was less efficient (data not shown). RNAi knockdown of CBP using the Gal4109(2)80 driver completely blocked ddaF apoptosis (n = 13; Figure 4F). Thus, Brm and CBP, like EcR-B1 and Sox14, are involved in regulating ddaD/E dendrite pruning as well as ddaF apoptosis. We then assessed the effects of brm and CBP on axon pruning of MB γ neurons. In wild-type MB γ neurons, the medial and dorsal axon branches that formed Selleck FK228 during the larval stages (data not shown) were pruned by 24 hr APF (n = 11; Figure 4G). The axon branches of BrmDN-overexpressing MB γ neurons

persisted at 24 hr APF (100%, n = 18; Figure 4H). Overexpression of CBP-ΔQ exhibited severe axon pruning defects in MB γ neurons at 24 hr APF as well (78%, n = 18; Figure 4I). Taken together, Brm and CBP play critical roles in the remodeling of sensory neurons and MB γ neurons during early metamorphosis. Given the essential role of CBP as both a transcriptional coactivator and a HAT during gene activation, we next tested whether CBP acts at the top of the EcR-B1/Sox14/Mical cascade to facilitate EcR-B1 expression in response to ecdysone. Surprisingly, EcR-B1 expression does not require CBP function, because upregulation of EcR-B1 expression

could be observed at the WP stage in CBP RNAi ddaC neurons (n = 13; Figures 5D and 5G; wild-type ddaC neurons, n = 11; Figures 5A and 5G). In contrast, Sox14 was absent or strongly reduced in 89% of CBP RNAi ddaCs (n = 17; Figures 5E and 5H; wild-type ddaC neurons, n = 11; Figures 5B and 5H), suggesting that CBP, like Brm, activates sox14 expression at the WP stage. Accompanying Sox14 downregulation, Mical expression was significantly reduced in the majority of CBP RNAi ddaC neurons (87.5%, n = 8; Figures 5F and 5I), as compared to that in wild-type (n = 23; Figures 5C else and 5I). Sox14 overexpression fully restored Mical expression (n = 46; Figure 5J compared with Figure 5F) and rescued the pruning defects (n = 25; Figure 5K, compared with the MicalN-term overexpression control, Figure 5L) in CBP RNAi ddaCs, suggesting that CBP functions upstream of Sox14 to promote dendrite pruning and seems to not be required for the expression of Mical. Thus, CBP appears to play a specific role in regulating EcR-B1/Usp-induced Sox14 expression in the activation of the EcR-B1/Sox14/Mical pathway during ddaC dendrite pruning. The levels of Usp and Brm remained largely unchanged in CBP RNAi ddaC neurons (n = 16 and n = 11, respectively; Figures S4B and S4D).

Cryosections or vibratome sections (embedded in 3% agarose) were

Cryosections or vibratome sections (embedded in 3% agarose) were blocked (2% bovine serum albumin, Sigma; 5% normal goat or donkey serum plus 0.3% Triton X-100 or 0.3% Triton X-100 plus 1% DMSO) and stained overnight with biotinylated PNA (1:200, Sigma), with the nuclear stain TO-PRO-3 (1:1000,

Invitrogen) or with primary antibodies directed against CRALBP (mouse, 1:1000, Enzalutamide Abcam), GFAP (mouse, 1:200, Sigma), Kv3.1b/KCNC1 (mouse, 1:200, Sigma), GFP (rabbit, 1:1000; Abcam), protein kinase C alpha (PKCα; rabbit, 1:200, Genetex), vesicular glutamate transporter 1 (VGLUT1/SLC17A7; guinea pig, 1:200, Synaptic Systems), and with secondary antibodies coupled to Alexa Fluor 488 and Alexa Fluor 555 (Invitrogen) or Cy2-conjugated streptavidin (Jackson Immunoresearch) for 1–3 hr at room temperature. Sections were mounted in Mowiol (16.6% w/v, in PBS: glycerin 2:1; Calbiochem). Images were taken with a laser scanning microscope (LSM 510 Meta) and an Achroplan 63×/0.9 water immersion objective (Zeiss). Mice were anesthetized by intraperitoneal injection of Ketamine (200 mg/kg) and Xylazine (25 mg/kg) and fixed by transcardiac perfusion with glutaraldehyde (2.5% in PBS at 7.4). Eyes were dissected and fixed for 1 hr in glutaraldehyde (2.5%) at

room temperature (20°C–24°C). After three washes with PBS, eyes were postfixed (1% OsO4 in PBS for 1 hr), dehydrated (ethanol at VE-821 research buy 25% for 10 min; 50% for 10 min, 70% for 10 min, 95% for 10 min and 100% for 3 × 10 min; propylene oxide for 3 × 10 min) and embedded (Araldite M: propylene oxide at 1:1 for 1 hr followed by Araldite M for 2 × 2 hr at room temperature; polymerization at 60°C for 3 days). Ultrathin sections were contrasted with uranyl acetate and inspected on a transmission electron microscope (HITACHI 7500 with AMT camera, Hamamatsu). Acutely isolated retinal slices (thickness, 1 mm; custom-made cutter) were incubated in extracellular solution (see

above) containing the vital dye Mitotracker Orange (10 μM, excitation: 543 nm, emission: 560 nm long-pass filter; Invitrogen), which too is taken up by Müller cells (Uckermann et al., 2004). Somata of Müller cells were imaged at the plane of their maximal size using confocal microscopy (LSM 510 Meta). In bigenic mice cells, which displayed EGFP fluorescence (excitation: 488 nm; emission: 505 nm long-pass filter), were selected. Hypotonic solution (60% of control osmolarity using distilled water) and test substances were applied for 4 min. Barium chloride (1 mM) was added to the extracellular solution 10 min before measurements. To study volume changes in neuronal cell bodies, retinae were positioned in a perfusion chamber with their vitreal surface up, labeled with FM1-43 (2 μM, Invitrogen for 3 min; excitation 488 nm; emission 505 nm long-pass filter) to outline cells and examined by confocal microscopy (LSM 510; Achroplan 63×/0.9 water immersion objective, Zeiss; pinhole 172 μm; optical section 1 μm).