, 2004). Thus, we considered the possibility that some Ca2+-dependent genes regulate CF synapse elimination in the cerebellum. We focused on an immediate early gene, Arc, because its expression is tightly coupled to neural activity downstream of multiple signaling pathways ( Bramham et al., 2008 and Shepherd and Bear, 2011), including Ca2+ influx through VDCCs ( Adams et al., 2009). Arc messenger RNA (mRNA) is detectable in PCs in the mouse cerebellum at an early postnatal stage, and its expression increases

during postnatal development (Allen drug discovery Brain Atlas; http://mouse.brain-map.org). We confirmed this expression pattern by comparing Arc mRNA expression levels in the mouse cerebellum at postnatal day 9 (P9) and P16 by real-time PCR. Arc mRNA expression level at P16 was more than 2-fold higher than at P9, indicating that the expression of Arc significantly increases during the period of CF synapse elimination ( Figure 3A; left, normalized by HPRT,

p = 0.0005; right, normalized by GAPDH, p = 0.0159, Student’s t test). To examine whether Arc expression in PCs is activity dependent, we used Arc-pro-Venus-pest transgenic mice in which a Venus fluorescent reporter is expressed under the control of Arc promoter ( Kawashima et al., 2009). We made cocultures of cerebellar slices derived from Arc-pro-Venus-pest transgenic mice and explants of medulla oblongata. Robust expression of Arc was observed mainly in 3-Methyladenine solubility dmso PCs by either membrane depolarization (high K+, 60 mM) ( Figures 3B) or optogenetic excitation (1 s blue light exposure at 0.1 Hz) ( Figure S3A). The increase of Arc expression was suppressed when ω-agatoxin IVA (0.4 μM) was applied in the high K+-containing culture medium ( Figure 3B). Similar suppression of high K+-induced elevation of Arc expression was observed in cocultures with PC-specific P/Q knockdown ( Figure S3B).

We further almost confirmed the activity-dependent expression of endogenous Arc in PCs by immunohistochemistry using anti-Arc antibody ( Figure 3C). These results indicate that Arc is expressed in PCs in an activity-dependent manner, which requires the activation of P/Q-type VDCCs in PCs. Because neural activity along PFs is considered to activate mGluR1 in PCs and to drive CF synapse elimination (Ichise et al., 2000, Kakizawa et al., 2000 and Kano et al., 1997), we tested whether activation of mGluR1 in cocultures could elevate Arc expression in PCs. We applied an mGluR1 agonist, RS-3, 5-dihydroxyphenylglycine (DHPG, 100 μM), to cocultures from Arc-pro-Venus-pest transgenic mice and found that DHPG failed to elevate Arc expression ( Figure S3C). We also found that the high K+-induced increase of Arc expression was not suppressed by an mGluR1 antagonist, LY367385 (100 μM) ( Figure S3C). These results indicate that mGluR1 itself is not essential for inducing Arc expression in PCs.

In LiGluR-expressing neurons preincubated with agonist MAG (10 μM), whole-cell patch-clamp C59 wnt research buy recordings

confirmed that a brief UV exposure (1 s) could reliably induce rapid membrane depolarization, leading to lasting high-frequency firing of action potentials ( Szobota et al., 2007), with an average firing rate of about 9 Hz (8.7 ± 1.3 Hz, n = 15) during the initial UV exposure ( Figures 1E and 1F). Compared with low basal firing of about 0.5 Hz (0.47 ± 0.09 Hz, n = 5), UV stimulation drastically elevated neuronal activity. The membrane depolarization and firing by a single UV exposure (1 s) decayed gradually and typically ceased firing in 30–60 s. Consistent with previous work ( Szobota et al., 2007), we found that UV-induced firing was reliably terminated by blue light ( Figure 1G). To further confirm the UV effect, we found that in neurons expressing the calcium sensor protein GCaMP3 ( Tian et al., Palbociclib 2009), UV exposure (1 s)

induced a rapid and repeatable rise in GCaMP3 intensity (1.62 ± 0.13, n = 9), consistent with membrane depolarization and neuron activation ( Figures 1H and 1I). Because a single UV exposure triggered spiking of about 1 min or less, we adopted a protocol of UV stimulation cycles to achieve sustained firing. Throughout this study, light treatment was given as a combination of 0.3 s of blue light (480 nm) followed by 1 s of UV light (380 nm), repeated every 20 s (Figure 1J). A brief blue light was applied before UV light to reset neuronal activity in order to eliminate desensitization and ensure subsequent lasting UV-induced firing. Whole-cell recordings of LiGluR-expressing neurons revealed reliable firing by the UV stimulation protocol (Figures

2A and 2B), which was effectively blocked by AMPA/KA receptor antagonist CNQX (20 μM) (Figure S2). To confirm that neuronal activation upon UV illumination does indeed affect axonal terminal release, Sclareol we performed FM4-64 uptake assays on LiGluR-expressing neurons. Transfected hippocampal neurons were incubated with LiGluR agonist MAG (10 μM) and then stimulated with UV in the presence of FM dye. Following five cycles of UV stimulation (100 s), FM intensity at terminals of LiGluR neurons (indicated by syn-YFP) was markedly enhanced compared to neighboring clusters, or syn-YFP terminals without UV treatment (Control: Neighboring sites, 372.4 ± 7.5, n = 83; LiGluR sites, 441.2 ± 18.1, n = 83, p < 0.05; UV treatment: Neighboring sites, 388.4 ± 10.3, n = 80; LiGluR sites, 752.3 ± 51.1, n = 80, p < 0.05) (Figures 2C and 2D). In contrast in the presence of TTX, UV exposure failed to increase FM labeling, indicating that the UV effect is mediated via the firing of action potentials (UV+TTX: Neighboring sites, 179.8 ± 5.4, n = 62; LiGluR sites, 193.1 ± 32.1, n = 62; p > 0.05) (Figures 2C and 2D).

How then do distal tuft inputs influence neuronal output? Recently, the same group obtained in vivo two-photon imaging results showing that large, synchronous, tuft-wide Ca2+ transients are induced during sensory-motor behavior in mice (Xu et al., 2012). These could be induced R428 experimentally by pairing trunk spikes with tuft depolarization, leading to increased frequency and duration of dendritic trunk Ca2+ spikes, which influenced AP output. Guided by previous findings in hippocampal

CA1 pyramidal neuron dendrites showing that dendritic signaling is controlled by voltage-gated K+ channels (Cai et al., 2004, Hoffman et al., 1997 and Losonczy et al., 2008), Harnett et al. (2013) reasoned that these may also compartmentalize signals between L5 integration zones. In outside-out patches from the trunk and tuft, Harnett et al. (2013) mapped the expression pattern and measured the properties of both transient (rapidly inactivating) and sustained (slowly/noninactivating) voltage-gated K+ channels.

The data revealed a similar distribution pattern for both currents throughout the apical dendritic trunk and tuft. Harnett et al. (2013) then investigated the pharmacological profile of the currents, finding two drugs (quinidine and barium), which, at the concentrations used, appeared to selectively Selleck LBH589 reduce both types of K+ currents. These K+ channel blockers were then used to determine in which also ways K+ channels affected excitability for each compartment. With recording electrodes in the soma and nexus, K+ channel blockers boosted trunk spikes initiated with nexus current injection, which induced repetitive AP firing. Blockers did not, however, affect AP firing induced by somatic current injection, demonstrating specific K+ channel control spiking in the dendritic

trunk. This finding was supported by an additional set of experiments in which subthreshold current injections into the soma, to simulate barrages of synaptic input, were paired with simulated synaptic input to the trunk. The enhanced trunk electrogenesis upon K+ channel block was found to increase AP output. Recording simultaneously in the trunk and the tuft, K+ channel block decreased the threshold current required for trunk spike initiation and enhanced their propagation into the tuft, allowing full invasion of tuft branches. Signals traveling from the tuft to the trunk were also enhanced, with blockers again reducing the threshold current required to induce tuft spikes, which were increased in both amplitude and duration. Simulated subthreshold synaptic input delivered simultaneously into the tuft and trunk generated plateau potentials in the tuft, which then spread to the trunk. This same group had recently shown that such signals are induced during whisking behavior during an object localization task in mouse L5 neurons (Xu et al., 2012).

The ultra-thin sections prepared for TEM examination revealed a large parasitophorous vacuole (PV) containing the parasite inside the cytosol of infected cardiomyocytes ( Fig. 2C). The results of T. theileri attachment assays in BHK,

H9c2, SVEC and RAW 264.7 cells revealed 64 ± 20, 72 ± 12, 19 ± 4 and 84 ± 6 parasite-attached cells/100 cells, and 115 ± 37, 209 ± 49, 24 ± 5 and 197 ± 21 attached parasites/100 cells, respectively ( Table 1). The numbers of parasite-attached cells and attached parasites were significantly higher in BHK, H9c2 and RAW 264.7 cells as compared with SVEC cells ( Table 1, P < 0.001). In addition, the invasion assays showed 19 ± 7, 27 ± 16, 12 ± 3 and 22 ± 11 parasite-invaded cells/100 cells, respectively ( Table 1). The invasion rate was significantly higher in H9c2 and RAW 264.7 cells than in SVEC cells (P < 0.001 and 0.05). Cobimetinib concentration To determine whether T. theileri entry underlies membrane rafts of host cells, H9c2 cells were labeled with CTX-B. GM1 (green) enrichment was observed at the entry site of the plasma membrane around infected TCT ( Fig. 3A and B, arrowheads). In contrast, GM1 enrichment was not observed in non-infected Ixazomib datasheet control H9c2 cells ( Fig. 3A and B, upper right panel). According to a recent

study, the CATL sequence fragment is highly suitable as the target for phylogenetic analysis in T. theileri ( Rodrigues et al., 2010). We therefore sequenced this gene of Taiwan T. theileri isolates as previously described ( Cortez et al., 2009). Phylogenetic analyses revealed the sequence of TWTth1 trypanosomes was clustered within the clade of the T. theileri lineage TthIB genotype. Its sequence was completely identical with NCBI GenBank accession numbers of genes: GU299391.1, GU299394.1, GU299397.1, GU299399.1, and GU299400.1, with length 477, identities 477/477 (100%) and gaps 0/477 (0%), among the TthIB lineage. After TCTs were added to H9c2 cells, the gelatinolytic activity was significant increased and accumulated in the body of T. theileri and at the attachment site of the cell membrane ( Fig.

4B–D, arrowheads). In contrast, gelatinolytic activity was only present at the adjacent cell junction in the control ( Fig. 4A). Gelatin gels were incubated with TCT lysates of T. theileri, unwashed parasites ( Fig. 4E, lane 1) and washed twice with PBS ( Fig. 4E, lane 2). The gel contained prominent activity revolving Amisulpride in a molecular mass of approximately 65 kDa, the only visible activity on the gel ( Fig. 4E). Lyso-Tracker Red pre-stained H9c2 (Fig. 5A–C) or SVEC cells (Fig. 5D and E) were inoculated with TCTs (Fig. 5A, upper right panel) and amastigotes (Fig. 5D, upper right panel) for 24 h. Confocal laser scanning images corresponding to the stack of serial confocal sections and a larger magnification of one single-plane section is shown. TCTs stain as two dots, corresponding to the nucleus and kinetoplast in Hoechst stain, and were co-localized with lysosomes in Lyso-Tracker pre-stained H9c2 cells (Fig.

, 2011). To specifically manipulate L4 function, we replaced the Gal4 drivers with either half of the split-Gal4 system ( Luan et al., 2006) and obtained a splitL4-Gal4 line (L40980-VP16AD, L40987-Gal4DBD) that was expressed only in L4 and in no other neurons ( Figures 2J–2L).

To generate tools that would allow independent manipulations of L4 and other cell types using different binary expression systems, selleck we also replaced the Gal4 in the L4 drivers with two other transcription factors, LexA and QF ( Lai and Lee, 2006 and Potter et al., 2010). The L40987-LexA, L40987-QF, and L40980-QF lines recapitulated the expression pattern of their Gal4 progenitors ( Figures 2M–2O). L40987-QF was additionally expressed in trachea, which, however, did not interfere with our experiments. We first sought to determine the visual response properties of L4 (Figures 3A and 3B). We measured in vivo calcium signals from L4 terminals in medulla layers M2 and M4 (Figures 3B and 3C) using two-photon imaging of the genetically encoded calcium indicator TN-XXL ( Figures 3D–3G) ( Mank et al., 2008 and Reiff et al., 2010). When presented

with alternating increases and decreases in light intensity, the average ratiometric calcium signal of all cells decreased when the light was on and increased when the light was off, in both layers M2 Afatinib and M4 ( Figure 3D and data not shown). This is consistent with L4 hyperpolarizing to brightening and depolarizing to darkening ( Douglass and Strausfeld, 1995). Very similar calcium signals were seen when either Gal4 or QF transcription factors were used to drive TN-XXL expression ( Figure 3D; see Experimental Procedures). Next we tested whether

L4 displays direction-selective responses to motion. In response to a narrow bright bar, moving on a dark background at 10°/s, L4 terminals responded with an initial decrease in calcium signal associated with the light increment when the bar reached their receptive field, followed by an increase in calcium signal and as the bar left the receptive field (Figure 3E). Using bars that moved either horizontally or vertically, we found no signs of direction selectivity (Figure 3E). Similar results were obtained for bars moving at 20°/s and 50°/s (data not shown). To characterize the response properties of L4 under continuous, dynamic stimulation, we used a rapidly flickering, uniform-field stimulus with Gaussian distributed intensity changes. Using linear-filter estimation procedures, we extracted the temporal linear filter that best captured the calcium response as a function of time (Chichilnisky, 2001 and Sakai et al., 1988). This linear filter had a large negative lobe consistent with a sign inversion of the input contrast (Figure S3), results that are similar to those previously described for L2 (Clark et al., 2011).

These genes are significantly enriched for the GO categories’ cytokine receptor activity (p = 6.0 × 10−3) and the JAK/STAT signaling pathways (p = 1.0 × 10−3) in the FP (IL11RA, IL13RA2, and GHR), for carboxylic acid catabolic process (p = 3.3 × 10−3) in the HP (ASRGL1, CYP39A1, and SULT2A1), and for synaptic transmission (p = 3.5 × 10−2) in the CN (LIN7A, MYCBPAP, and EDN1). Together, http://www.selleckchem.com/products/Vorinostat-saha.html these data suggest that human-specific gene evolution is important for signaling pathways in the brain. We next applied weighted gene coexpression network analysis (WGCNA) (Oldham et al., 2008) to build both combined

and species-specific coexpression networks, so as to examine the systems-level organization of lineage-specific gene expression differences. We constructed networks in each

species separately and performed comparisons Rucaparib solubility dmso of these networks to insure a robust and systematic basis for comparison (Oldham et al., 2008). The human transcriptional network was comprised of 42 modules containing 15 FP modules, 6 CN modules, 2 HP modules, and 19 modules not representing a specific brain region (Figure 3 and Tables S2 and S3; Supplemental Experimental Procedures). The FP samples correlated less with the CN and HP samples, using a composite measure of module gene expression, the module eigengene, or first principal component (Oldham et al., 2008) (data not shown). The chimp network analysis yielded 34 modules, including 7 FP modules, 9 CN modules, 7 HP modules, and 11 modules that were unrelated to a specific brain region (Figure 3 and Tables S2 and S3). The macaque analysis yielded 39 modules with 6 FP science modules, 8 CN modules, 5 HP modules, and 20 modules not related to a specific brain region (Figure 3 and Tables S2 and S3). Thus, only in human brain were more modules related to FP than either of the other regions, consistent with increased cellular and hence transcriptional complexity in

FP relative to the other regions. While the smaller number of chimpanzee (n = 15) and macaque (n = 12) samples compared to human (n = 17) samples could potentially affect the outcome of the network analysis, we used the same thresholding parameters, and there were equivalent numbers of human and chimpanzee FP samples (n = 6), similar numbers of total modules in human and macaque samples (42 and 39, respectively), and proportionally more FP modules compared to total modules in human samples (18/42 = 43%) compared to chimpanzee (8/34 = 23%) or macaque (5/39 = 13%), mitigating this concern. This indicates that even within a single region of human frontal lobe, transcriptome complexity is increased with regards to other primates. We next determined the conservation of the modules defined in humans in the other species (see Supplemental Experimental Procedures; Table S3).

While it is presumed that the dense collection of axons located GDC-0068 supplier in layer V is primarily targeting projection neurons located within this layer, the target of the lost presynaptic terminals cannot be known for certain, and the reduction in synaptophysin-GFP puncta may not be specific to any particular postsynaptic partner. In order to evaluate the functional consequences of reduced Boc expression

and its effect on connectivity to postsynaptic partners located in either layer II/III or layer V, we used an optogenetic approach. We coelectroporated Channelrhodopsin-2 (ChR2) ( Nagel et al., 2003) into layer II/III cortical neurons, thus allowing us to photoactivate the cells and identify their postsynaptic target cells ( Petreanu et al., 2007) ( Figures 8A and 8C). We examined the strength of layer II/III to layer V connectivity by flashing the cells with blue light, causing the ChR2-electroporated neurons to fire action potentials. We

found a significant reduction in the excitatory postsynaptic current (EPSC) amplitude in layer V neurons in which functional Boc had been disrupted when compared to controls ( Figures 8E and 8F). We also tested for a similar deficit in Shh conditional knockouts and found an 8-fold reduction in EPSC amplitude, suggesting that loss of either ligand in the target cell or receptor from the input neuron yields similar deficits in layer V connectivity selleck products ( Figure 8F). In contrast, when we compared the strength of layer II/III to layer II/III connections, we did not find a significant difference in EPSC amplitude between conditions where Boc function is perturbed and control conditions ( Figure 8E). Taken together, these findings suggest that the reduction in presynaptic terminal formation observed science when Boc function is disrupted is specific to layer II/III to layer V cortical circuits, while the strength of connectivity of layer II/III to layer II/III cells remains unchanged. Using a combination of genetics,

anatomy, and electrophysiology, we have shown that Shh and its receptor Boc are required for the formation of specific cortical microcircuits. A common theme in developmental biology is the multitude of cellular functions a signaling molecule will regulate depending upon the cellular context in which it is expressed. Shh is most well known and best characterized for its functions in regulating unspecified populations of stem and progenitor cells to regulate the fate of their progeny. However, as development proceeds, so too does the context of expression, where Shh function shifts from specifying the cell types within the spinal cord to guiding axons to their targets.

During recording, data from some birds were low-pass filtered at 3 kHz and others at 5 kHz. Because differences in this cutoff frequency

can alter the spike shape (Vigneswaran et al., 2011), we applied a first-order low-pass Butterworth filter with cutoff frequency at 3 kHz to all spike shapes to equalize these differences. All mean this website spike waveforms were cubic spline interpolated to a 2.5 μs sampling interval. The filtering slightly increased the spike widths of all neurons. Thus, our threshold of 425 μs between WS and NS neurons is toward the upper end of the distribution of thresholds used in previous reports (Mitchell et al., 2007; Vigneswaran et al., 2011) but is conservative. Because connectivity and correlation within neural populations depends on cell type (Constantinidis and Goldman-Rakic, 2002; Hofer et al., 2011; Lee et al., 1998), we divided our data set into wide spiking (WS) and

narrow spiking (NS) neurons on the basis of action potential width (trough-to-peak duration; Figures S2Q–S2S) (Barthó et al., 2004; Mitchell et al., 2007). The distribution of action potential widths is bimodal (Hartigan’s dip test, p = 0.041; Figure S2S) (Hartigan and Hartigan, 1985; Mitchell et al., 2007). Based Fulvestrant manufacturer on network interactions and correlations with intracellular properties, previous studies have established that WS and NS neurons correspond to excitatory principal neurons and inhibitory interneurons, respectively (Barthó et al., 2004; Harris et al., 2000; Tamura et al., 2004). Consistent with these classifications, our sample of NS neurons (n = 36) elicited significantly higher spontaneous firing rates (4.61 ± 0.76 Hz) than our sample of WS neurons (n = 98; 1.80 ± 0.21 Hz; Wilcoxon rank-sum test, p = 1.03 × 10−4). Because our sample of simultaneously

recorded pairs of NS neurons was relatively small (n = 17 pairs), we focus our population analysis on pairs of WS neurons (n = 176 pairs from 6 birds). Signal correlations were computed for each pair of neurons as the Pearson product-moment correlation coefficient between the mean (averaged over trials) firing rates to the four motifs within the task-relevant, 3-mercaptopyruvate sulfurtransferase task-irrelevant, and novel classes. Noise correlations were computed for each individual motif for each pair across trials then averaged for all motifs within a class. Because motifs were variable in duration (range: 565–957 ms, mean: 756 ms) and the size of the analysis window can affect measured correlation values (Cohen and Kohn, 2011), we use only the first 565 ms (the minimum motif duration) of each response in the analyses reported here. We note, however, that reanalyzing our data using the full duration of each motif yields similar patterns of correlations. Motif discrimination ability was assessed using a predictive multinomial logistic regression model (Long, 1997).

, 2010 and Dreher et al., 2009). Finally, a second puzzle with respect to the effects of the DAT1 genotype was that the relationship between performance during acquisition and perseveration during reversals actually reverses sign as a function of genotype. The computational model explains this as the tradeoff between Selleckchem NVP-BKM120 two opposing effects.

For low ρ, as observed in 10R homozygotes, the computational model approaches standard temporal difference learning. In such a model, as discussed above, performance on the acquisition and reversal phases are coupled by a common, local adjustment mechanism, with the degree of correct choices versus errors in both phases determined by choice randomness (the inverse temperature) and the sluggishness of adjustment (the learning rate). This produces a negative correlation between correct choices at acquisition and errors at reversal (equivalently, a positive correlation between errors in either phase). However, as described above, for high ρ, as in the 9R genotype, the experience weighting mechanism produces the opposite effect. That is, increased choice of the correct stimulus during acquisition

will lead to increased perseveration on reversal and therefore predict a positive relationship between the two. This study revealed a functional double dissociation between the effects of polymorphisms in regulatory regions of the SERT and DAT1 genes. We showed that FDA approved Drug Library chemical structure within the same individuals, SERT is involved in behavioral adaptation following losses, whereas DAT1 plays a role in experience-based perseveration. Our results provide strong and direct evidence for a suggested, but hitherto untested, functional dissociation, but fail to find a direct opponency between serotonin and dopamine systems. Dichloromethane dehalogenase This study was part of the Brain Imaging Genetics (BIG) project at the Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen. In the current study, 810 healthy, predominantly right-handed, Caucasian, highly

educated subjects completed an online probabilistic reversal learning task among a set of other tests (60.4% female; age 26.3 ± 11.1 years (mean ± SD); see Table S1 for full demographic information). The study was approved by the local ethics committee (CMO 2001/095) and written informed consent was obtained from all subjects prior to participation. Visual stimuli were probabilistically associated with positive (green, happy emoticon) and negative (red, sad/angry emoticon) feedback (Figure 1). We will refer to these positive and negative feedback events as “reward” and “punishment,” consistent with prior literature and the psychological definition of their tendency to increase/reduce response tendencies. On each trial, two stimuli were presented in two of four locations (left, right, top, or bottom of screen) and the subject was asked to select the usually rewarded stimulus with a mouse click.

As more people seek influenza vaccinations

at community pharmacies, pharmacists have the ability to identify at-risk patients, educate them on benefits of PPSV, and provide concurrent vaccinations. Therefore, the objective of this study was Pomalidomide to evaluate the impact of pharmacists educating at-risk patients on the importance of receiving a pneumococcal vaccination. The study hypothesis was that PPSV coverage would be greater for patients who were identified as at-risk for IPD by pharmacists during influenza vaccination compared to patients in traditional care. When patients received influenza immunizations at a pharmacy, the pharmacist asked patients about their risk of pneumococcal disease (e.g., age, smoking status, co-morbid conditions). Pharmacists recommended PPSV if any risk was identified and the patient had not previously been vaccinated. For every immunization administered, a physician

notification letter is generated and either given to the patient or sent to their primary care physician. Pharmacy claims data, which contain vaccination records from Walgreens’ Enterprise Data Warehouse (EDW) between November 15, 2009 and November 14, 2010, were included in the analysis. Influenza pneumococcal Libraries vaccinations were defined as pharmacy fills for the relevant vaccinations. To focus on PPSV education concurrent with an influenza vaccination, a sample was derived of all patients who had been immunized for influenza BIBW2992 between August 1, 2010 and November 14, 2010. This sample was further limited below to patients who had evidence of at least two non-influenza prescriptions to identify them as regular Walgreens customers with sufficient data to infer whether they had a chronic

condition. Finally, because revaccination with PPSV is not recommended within 5 years, and only four years of EDW data was available, patients with evidence of a previous PPSV claims were excluded. As outlined by ACIP, at-risk patients were identified in pharmacy claims data as aged 65 and older or as aged 2–64 with a comorbid conditions. Comorbid conditions were defined as conditions identified in the ACIP recommendations for PPSV, which included pulmonary disease, cardiovascular disease, liver disease, anatomic asplenia, diabetes, and immune compromising conditions (e.g., HIV, leukemia, malignancy). Although smoking status was also considered at-risk per ACIP guidelines, this variable was not available in pharmacy claims data. To derive a comparison PPSV vaccination rate typical of traditional care delivery, Walgreens contracted with Solucia Consulting to identify PPSV vaccinations within Solucia’s national medical and pharmacy claims database of commercial and Medicare health plan members. Due to medical claims lag, 2010 data were not available, and a blended average PPSV rate was calculated based on 2008 and 2009 influenza seasons.