, 2010) The studies on subunit assembly of AMPA-type receptors a

, 2010). The studies on subunit assembly of AMPA-type receptors and the study by Kumar et al. on kainate-type receptor subunit assembly are consistent with the subunit arrangement observed in the crystal structure of a the membrane-spanning,

tetrameric glutamate receptor (Das et al., 2010 and Sobolevsky et al., 2009) (see also Figure 1). Furthermore, recent results suggest that glutamate receptors of the AMPA-type assemble via a mechanism that involves initial ATD Selleckchem Gemcitabine dimer formation and, subsequently, a dimerization of dimers to form the tetrameric receptor, similar to the observations made by Kumar et al. (2009) for the GluR6/KA2 heterotetramer. Interestingly, the mechanism for subunit assembly of NMDA-type receptors could be different from those of AMPA- and kainate-type receptors (Farina et al., 2011; see also Karakas et al., 2011). The possibility of differences in

receptor assembly raises the potential of a striking variation in the domain organization of NMDA- versus AMPA- and kainate-type receptors, underscoring the need for more information on the fundamental process of glutamate receptor assembly. An undeniable axiom of science is that more detail always brings more questions; in this context, the findings presented by Kumar et al. certainly provide an exciting opportunity to think at a new level about questions related to glutamate receptor biogenesis. “
“The dynamics of synchronous activity MycoClean Mycoplasma Removal Kit in immature

and mature cortical networks are strikingly different. I-BET151 supplier In the neonate rat, much of the neocortical activity takes the form of “spindle bursts” (SBs; also termed “spontaneous activity transients” and “delta brushes”), which are self-organized, long-lasting (1–3 s) network events generated by both glutamatergic and GABAergic neurons (Minlebaev et al., 2007). So far, SBs have been mainly studied in the rat somatosensory and visual cortices (Khazipov et al., 2004, Mohns and Blumberg, 2010 and Colonnese et al., 2010), where they are present immediately after birth. During development, the SBs disappear within a very narrow time window, e.g., in the barrel cortex at around postnatal day (P) 8 and in the primary visual cortex at about P11, to be replaced by continuous oscillatory rhythms. A similar, most likely homologous, reorganization of gross network dynamics is also evident in humans. The highly discontinuous EEG patterns characteristic of preterm babies (Dreyfus-Brisac, 1962), which are largely attributable to the presence of spontaneous activity transients (Vanhatalo et al., 2002), give way to a more continuous EEG around the time of normal birth. Dating back to the classical work by Hubel and Wiesel in visual cortex, there is now overwhelming evidence pointing to a crucial role for precisely patterned neuronal activity in the formation of cortical connectivity.

Among so-called secondary olfactory structures (Haberly, 2001), t

Among so-called secondary olfactory structures (Haberly, 2001), tdT expression was seen in the dorsal, posterior ventral, lateral, and medial parts of the anterior olfactory nucleus AON (Figures 4J–4L), olfactory tubercles (Figures S4A–S4C), piriform cortex (Figures 4M–4O), anterior cortical amygdala (Figures S4J–S4L), and entorhinal cortex (Figures S4D–S4F). In animals

with more severe symptoms, tdT labeling was observed in tertiary olfactory structures including the insular cortex (Figures 4P–4R), orbital frontal cortex (ORB, Figure S4G–S4I), and hippocampus (HPF, Figures S4M–S4O). To investigate further the anterograde specificity of H129ΔTK-TT, we examined the labeling NLG919 concentration of several classes of neuromodulatory neurons that project directly to the olfactory bulb. We performed this analysis Panobinostat concentration in OMP-Cre mice that exhibited milder symptoms at 6–7 DPI. These mice exhibited tdT expression in the MOE, MOB, piriform cortex (Figures S4P–S4QQ), and olfactory tubercles (data not shown). Despite this multisynaptic anterograde labeling, we did not detect tdT expression in any of the

neuromodulatory populations that project to the MOB, including noradrenergic neurons in the LC (Figures S4R–S4SS, green) (Guevara-Aguilar et al., 1982 and Shipley et al., 1985), cholinergic neurons in the horizontal limb of the diagonal band (HDB) (Figures S4T–S4UU) (Záborszky et al., 1986), or serotonergic neurons in the raphe nuclei (Figures S4V–S4W) (McLean and Shipley, 1987). In mice that showed more advanced symptoms and a wider spread of expression (7–8 DPI), tdT was detected in these neuromodulatory populations (Table S3c). However, this labeling may derive from higher-order olfactory structures known to project to these neuromodulatory centers, including the insular cortex (Peyron et al., 1998), periaqueductal

gray (PAG), medial preoptic area (MPO), medial prefontal cortex, central nucleus of the amygdala not (CEA), and nucleus tractus solitarius (NTS) (Ennis et al., 1998), all of which structures contained tdT+ cells in these mice (Table S3c and Figure S5C). Pheromone-sensing neurons of the vomeronasal organ (VNO) also express OMP and were labeled in OMP-Cre mice infected intranasally with H129ΔTK-TT virus (Figures 5B and 5C). The VNO projects to the accessory olfactory bulb (AOB) through the vomeronasal nerves. The AOB in turn projects to a few areas including the medial amygdala (MeA) and the bed nucleus of the stria terminalis (BST) (Scalia and Winans, 1975 and Yoon et al., 2005), which send further projections to the medial hypothalamic area (Swanson and Petrovich, 1998). We detected tdT expression in the AOB (Figures 5D–5F), MeA (Figures 5G–5I), BST (Figures 5J–5L), and medial preoptic area (MPOA) in the medial hypothalamus (Figures 5M–5O), consistent with labeling of the VNO pathway. In contrast to the relatively limited labeling of brain structures by H129ΔTK-TT in the visual and cerebellar systems, 13.

While unattended stimuli still evoked negative afterimages, we fo

While unattended stimuli still evoked negative afterimages, we found that without attention the competitor had no effect on afterimage strength, and this was true for both the large competitor and the small competitor (Figure 8C; Figure S5B). Fits with the afterimage functions revealed a similar pattern of

effects across all observers: for none DAPT supplier did afterimage strength differ across conditions (Figure 8D; Figure S5B). This is consistent with the model predictions: the response gain reduction brought about by the small competitor is the byproduct of attentional modulation of normalization, and without attention, the gain change consists of only a contrast gain shift—just like what we observed with the large suppressor. These results suggest that the type of modulation of awareness through rivalry hinges critically on attention. Without attention, the suppression

of competing stimuli is substantially weakened at high contrasts. We propose a computation model, under the normalization framework, whereby attention plays a pivotal role in modulating competition for visual awareness. Previous studies have reported that, without attention, rivalry is weakened or altogether abolished in visual area V1 (Zhang et al., 2011; Watanabe et al., 2011) and in other, extrastriate cortical areas (Lee et al., 2007). The model proposed by us can accommodate the results PLX3397 purchase from these studies, because in this model attentional modulation is a driving force behind the suppression of awareness typically observed under rivalry. The present results, however, do not compel us to conclude that rivalry suppression simply does not occur at all without attention. Rather, the model proposes

that the interaction between attention and awareness is more nuanced, with Phosphatidylinositol diacylglycerol-lyase the magnitude of suppression relying on a variety of factors that include stimulus size, attentional state, and contrast of the competing stimuli. It is possible, for instance, that previous failures to find evidence for suppression without attention were working in a high-contrast regimen where suppression may not reveal itself when under the influence of contrast gain modulation. While the effects of binocular rivalry suppression have been observed throughout the visual hierarchy (Tong et al., 2006), the results from our experiments hint at a very early cortical locus for the effects suppression, due to the small size (1.5°) of the probe stimulus used in our study. Under the normalization framework, reductions in the response gain of a stimulus would occur only if probe stimuli were large enough to encompass not only the excitatory field, but the inhibitory field as well. Otherwise, we would observe no difference between competitor sizes.

Different forms of STDP are often intermixed in a seemingly synap

Different forms of STDP are often intermixed in a seemingly synapse-specific manner. For example, parallel fiber synapses onto fusiform cells in the dorsal cochlear nucleus exhibit Hebbian STDP, while those onto cartwheel neurons show anti-Hebbian LTD (Tzounopoulos et al., 2004). STDP rules also vary by postsynaptic cell type in Selleck Nintedanib striatum (Fino et al., 2008; 2009). However, STDP is also dramatically shaped by dendritic depolarization and neuromodulation. For example, anti-Hebbian

LTD on cortical pyramidal cells is converted into Hebbian STDP by manipulations that depolarize dendrites or promote the spread of back-propagating action potentials (bAPs) (Sjöström and Häusser, 2006; Letzkus et al., 2006; Zilberter et al., 2009), and Trametinib solubility dmso dopamine and inhibition alter the sign of STDP in the hippocampus and striatum (Fino et al., 2005; Shen et al., 2008; Zhang et al., 2009). The combination of synapse specificity and modulation may be useful in specializing different synapses for different types

of information storage, while providing dynamic control over plasticity. STDP depends not only on spike timing, but also on firing rate, synaptic cooperativity, and postsynaptic voltage (Markram et al., 1997; Sjöström et al., 2001). Cooperativity refers to the need for multiple coactive synaptic inputs to generate sufficient depolarization (or spiking) to drive LTP in classical hippocampal experiments (McNaughton et al., 1978). In slice experiments, unitary connections (which lack cooperativity and generate only modest dendritic depolarization) exhibit Hebbian STDP only when pre- and postsynaptic spikes occur at moderate firing rates (10–20 Hz). Higher firing rates (>30 Hz) induce LTP independent of spike timing, and lower firing rates (<10 Hz) generate only LTD for pre-leading-post spike intervals (Markram et al., 1997; Sjöström et al., 2001; Wittenberg and Wang, 2006; Zilberter et al., 2009).

Thus, Hebbian STDP operates primarily in a permissive middle range of firing frequency, superimposed on a standard Bienenstock, Cooper & Munro (BCM) plasticity function in which high firing rates drive LTP, and low firing rates drive LTD (Bienenstock et al., 1982; Figures 3A and 3B). The underlying constraint is all that LTP requires additional postsynaptic depolarization beyond a pre- and postsynaptic spike. This depolarization can also be provided by cooperative activation of multiple nearby synapses, which allows Hebbian STDP to be induced at lower frequency (Sjöström et al., 2001; Stuart and Häusser, 2001; Sjöström and Häusser, 2006; Figure 3C). The firing rate and depolarization requirements demonstrate that a single postsynaptic somatic spike is not a sufficient signal for associative plasticity, nor the basis for cooperativity—multiple spikes are required, and these must interact with local dendritic depolarization produced in part by spatial summation of local synaptic potentials.

In summary, it is argued that lOFC is relatively more specialized

In summary, it is argued that lOFC is relatively more specialized for assigning credit for both rewards and errors to specific stimulus choices. When different types of reward GSI-IX chemical structure outcome are available then lOFC represents the assignment of a particular reward type to a particular stimulus. By contrast, it is argued that vmPFC/mOFC value representations are not so much of the specific identify of a reward outcome but of its value and that it is these value representations that determine the goals and choices that primates pursue. The few neuron recording studies that have compared the areas support this interpretation. Rolls (2008) reports that neurons encoding dimensions

of reward outcomes, such as taste and JQ1 nmr texture, are more prevalent in lOFC than vmPFC/mOFC in the macaque. Bouret and Richmond (2010) report that lOFC neurons are more active than vmPFC/mOFC neurons when macaques see visual stimuli that predict rewards. By contrast vmPFC/mOFC neurons have greater access to information about the macaque’s current motivational state; the activity of vmPFC/mOFC neurons, but not lOFC neurons, was modulated by satiety (Figure 6). A very influential observation has been the report of neurons encoding the values of potential choices (“offer-value”-correlated activity) and the values of choices that are actually taken (“chosen-value”-correlated activity) in the lateral bank of the medial orbital sulcus

of and the adjacent posterior orbitofrontal cortex (Padoa-Schioppa and Assad, 2006, Padoa-Schioppa and Assad, 2008 and Padoa-Schioppa, 2009), a region at the transition between vmPFC/mOFC and lOFC divisions (Ongür and Price, 2000). It is tempting to relate the activity of such neurons to human vmPFC/mOFC BOLD signals that reflect the values of available choices and of taken choices (Boorman et al., 2009, FitzGerald et al., 2009, Philiastides et al., 2010 and Wunderlich et al.,

2010) but it is not clear whether the frequency of such neural patterns changes between vmPFC/mOFC and lOFC. In many experiments it is assumed that during decision-making people first weigh and compare the values of all of the different options that are available in order to make a choice and second, that these values are learned from the experience of previously choosing these options. Neither of these assumptions may be true. Instead the choice made and the best alternative may each have a special status. Moreover, learning about the value of choices can sometimes occur even without taking the choice if the right feedback is provided. Recent studies of aPFC provide the key evidence for both of these propositions. The aPFC carries a very distinct signal to the vmPFC. While vmPFC/mOFC encodes the value of the choice that is being made the aPFC encodes information about the value of alternative options that are not chosen (Boorman et al., 2009).

, 2001 and Takahashi et al , 2001), add to uncertainty about the

, 2001 and Takahashi et al., 2001), add to uncertainty about the environment. Moreover, in the real world outside the laboratory, we can be uncertain what our tasks are and which actions or tasks might lead to reward rather than punishment. Such uncertainty makes the control problem more difficult. The motor system is also nonstationary, in that its properties can change on multiple timescales. Throughout growth and development, the properties of our motor system change dramatically as our limbs lengthen and change in weight. Similarly, our muscles become stronger, so that similar activation

patterns give rise to larger forces. Nerve conduction delays initially decrease in the first 2 years after birth but then increase in proportion to the lengthening of the limbs (Eyre et al., 1991). click here As we age, other changes occur with delays becoming larger (Dorfman and Bosley, 1979) and muscle strength decreasing (Lindle et al., 1997) due to the decrease in cross-sectional area (Jubrias et al., 1997) and changes in muscle fiber properties (Brooks and Faulkner, 1994). Moreover, sensory acuity also decreases with age, for example, visual acuity is reduced as we become older (Owsley et al., 1983), adding uncertainty to the visual feedback. On a shorter timescale the way our motor system responds to our motor commands can change as we interact with objects or as our muscles become fatigued. The ever-changing nature of the motor system places

a premium on our ability to adapt control appropriately. Control is further AZD6244 cost complicated by the highly nonlinear nature of our motor system. In linear systems, once the response to two different time series of motor command is known, it is straightforward to predict the response to both applied together as simply the sum of the responses. This makes control of linear systems relatively simple, because by knowing the response of the system to a simple input such as

a pulse, one knows the response to any arbitrary input. For nonlinear systems this is no longer the case. The descending motor command undergoes a highly nonlinear transformation as it is converted into endpoint force or movement. Although the output from the nervous system sets the activation level of the motor neuron pool, the number, strength, and temporal properties of the motor units crotamiton that are activated exhibit nonlinearity. Although the measured activation level of muscle fibers exhibits a roughly linear relation with muscle force in an isometric situation, this simple relation disappears once the muscles and limbs move. The force of a muscle depends on activation level in a very nonlinear manner with respect to both the muscle velocity and muscle length and is further affected by tendon properties (for a review see Zajac, 1989). In addition, the moment arms of muscles can vary by a factor of three as the joint angles change during limb movements (Murray et al., 1995 and Murray et al., 2000).

We did this for both behavior and anatomical variables ( Figures

We did this for both behavior and anatomical variables ( Figures 1D and 1E). This led to the removal of two individuals in the data set we gathered (n = 16 instead of n = 18), zero individuals in Poppenk et al. (2010b) (n = 16), one individual in the data set collected by Skinner

et al. (2010) (n = 13 instead of n = 14), and zero individuals in the data set collected by Cohn et al. (2009) (n = 13). For the RM aggregate analysis, we combined our measure from the current study (source memory accuracy) with that from Poppenk et al. (2010b) (source memory accuracy), Skinner et al. (2010) (proportion of hits subjectively recollected), and Cohn et al. (2009) (proportion of hits subjectively recollected). Measures selleckchem were Z scored within-study to help control for between-study effects. One individual participated in three of these studies and was sampled only once; all other participants participated in only one of the studies. In total, 56 individuals were included in the aggregate RM analysis. For the digit span aggregate analysis, we combined our WAIS-III digit

span measurements with those of Skinner et al. (2010). One individual participated in both studies and was sampled only once, and digit Apoptosis Compound Library cost span data were not available from two individuals in our data set. In total, 26 individuals were included in the aggregate digit span analysis. We thank M. Cohn, E. Skinner, and M. Fernandes for contributing data sets, N. Bakker, S. Freel, and P. Lin for manual segmentations, M. Ziegler for stimulus programming, F. Tam for imaging sequences, W. Cunningham and A. Yonelinas for statistical PD184352 (CI-1040) advice, and H. Chapman for helpful comments. Supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) postgraduate scholarship (J.P.), NSERC postdoctoral scholarship (J.P.), NSERC A8347 (M.M.), Canadian Institutes of Health Research MOP49566 (M.M), and

J.S. McDonnell Foundation 22002082 (A.R. McIntosh). “
“A central objective in deciphering the neural circuitry of the brain is to define the synaptic inputs and outputs of specific neuronal subpopulations in different regions (Bohland et al., 2009). These input/output relationships can be comprehensively mapped by serial electron microscope (EM) reconstruction (Jurrus et al., 2009, Kleinfeld et al., 2011 and Ward et al., 1975). However, such methods are currently best suited to elucidating microcircuitry within relatively small volumes of brain tissue (Bock et al., 2011 and Briggman et al., 2011), rather than to mapping long-range projections (Seung, 2009). The latter can be visualized using neuroanatomical tracers to sample connections between regions (reviewed in Köbbert et al., 2000 and Vercelli et al., 2000). Classical tracers, such as biotin-dextran amine (BDA), fluorescent latex microspheres (Katz et al., 1984), or phytohemagglutinin lectin (PHAL), have provided much useful information (e.g.

We found only one area of labeling in the midline thalamic nuclei

We found only one area of labeling in the midline thalamic nuclei localized to the dorsal portion of the ipsilateral parafascicular thalamic nucleus (Figure 1A). selleck chemical Importantly, no labeling was observed in the thalamus in the hemisphere contralateral to the infusion (Figures 1B and 1C). Next, we examined

the effect of an NMDA-induced unilateral cell body lesion of the Pf on the function of CINs in the pDMS ipsilateral and the pDMS contralateral to the lesion. For this experiment, 5- to 6-week-old rats (n = 18) were first given a unilateral lesion of the Pf (Figure 2A). After 1 week, we took 300 μm coronal sections through the pDMS and, using a cell-attached configuration of patch-clamp electrophysiology with least perturbation of intracellular AP24534 chemical structure content, compared the spike frequency in CINs located in the pDMS either ipsilateral or contralateral to the Pf lesion (Figures 2B–2E). As we have done previously (Bertran-Gonzalez et al., 2012), determination of CINs was based on their well-described morphological and electrophysiological characteristics (Bennett and Wilson, 1999), as well as post hoc biocytin-labeled histochemistry (Figures 2C and 2D). Importantly, we found that the frequency of action potentials was significantly

reduced in CINs recorded in the hemisphere ipsilateral to the Pf lesion relative to those recorded in the contralateral hemisphere, F (1,17,) = 26.09, p < 0.001, (Figure 2E, Table S1 available online). To confirm that the lesion-induced reduction in firing rate was specific to changes in the intrinsic activity of CINs, we used a recently described means of measuring functionally relevant

changes in CIN activity based on fluctuations in phosphorylation levels of the ribosomal protein S6 (S6rp) assessed by immunofluorescence (Bertran-Gonzalez et al., 2012) (Figures 2F and 2G). We explored the state of phosphorylation of different C-terminal residues of S6rp, an integrant of the ribosomal complex modulated in striatal neurons (Bertran-Gonzalez et al., 2012; Santini et al., 2009; Valjent et al., 2011). In untreated rats, we have recently described a persistent phosphorylation of the Ser240-244 over phospho-pair of S6rp specifically in CINs of different striatal regions (Bertran-Gonzalez et al., 2012) (Figure 2F), probably reflecting the intrinsic translational tone of these neurons (Ruvinsky and Meyuhas, 2006). Accordingly, in rats with unilateral PF lesions, we detected a reduction in the phospho-Ser240-244 signal in CINs in the pDMS ipsilateral to the lesion compared to those in the contralateral pDMS, F (1,49) = 42.573, p < 0.001, (Figures 2G, left). This effect was not observed in CINs in the adjacent dorsolateral striatum (DLS) (Figure 2G, right) F (1, 48) = 1.046, p = 0.312. Together, these results suggest that the functional activity of CINs in the pDMS is heavily regulated by the parafascicular thalamus via the thalamostriatal projection.

Aβo alters mGluR5 trafficking in neurons, with reduced diffusion,

Aβo alters mGluR5 trafficking in neurons, with reduced diffusion, clustering, aberrant activation, and neurotoxicity (Renner et al., 2010). The results here provide a PrPC-based mechanism for these findings and for downstream signaling. Direct coupling of PrPC to mGluR5 has been reported for an unrelated ligand, the

laminin gamma-1 selleck screening library chain (Beraldo et al., 2011). Aβo from synthetic, cellular, and human AD brain sources suppresses LTP and enhances LTD. These actions are mimicked by mGluR5 agonists and inhibited by mGluR5 antagonists (Rammes et al., 2011, Shankar et al., 2008 and Wang et al., 2004). In human AD, mGluR ligand binding is decreased in brain relative to controls and the loss is correlated with disease progression (Albasanz et al., 2005). Proteins titrated by mGluRs, eEF-2, Arc, and p70 S6 kinase are dysregulated in AD brain (An et al., 2003, Li et al., 2005 and Wu et al., 2011). Canonical mGluR5 signaling couples to Gq/G11 GTPases that activate phospholipase C to produce IP3 and release calcium stores (Lüscher and Huber, 2010). mGluR5 also modulates

plasma membrane potassium, calcium, and transient receptor potential channels. Src family tyrosine kinases, including Fyn, have been implicated in linking to NMDA-R (Heidinger et al., 2002 and Nicodemo Lumacaftor mw et al., 2010). The proline rich tyrosine kinase 2 (Pyk2) participates in Src/Fyn interaction with mGluR signaling (Heidinger et al., 2002 and Nicodemo et al., 2010). The calcium/calmodulin-dependent Ketanserin eEF2 kinase (eEF2K) is bound to mGluR5 in the basal state, but is released during activation to phosphorylate eEF2 (Lüscher and Huber, 2010).

Phospho-eEF2 reduces global translation, but allows increased Arc/Arg3.1 expression (Park et al., 2008). The Homer family plays a role in mGluR signaling, interacting with receptor and eEF2K (Hu et al., 2010, Lüscher and Huber, 2010 and Ronesi et al., 2012). Homer interactions with SHANK contribute to PSD localization, specific isoforms have roles in homeostatic scaling. We show that Aβo-PrPC complexes lead to several mGluR5 outputs. Fyn activation by Aβo in cortical neurons requires mGluR5 genetically and pharmacologically. Fyn is implicated in Aβo-induced dysregulation of NMDA-R trafficking and activation (Um et al., 2012). Because Fyn binds directly to Tau (Ittner et al., 2010 and Lee et al., 2004), this may have implications for AD beyond dysregulation of GluRs. The Aβo-PrPC-mGluR5 complex also activates phospholipase C, as detected by monitoring calcium-activated chloride channels in oocytes. The ability of Aβo or human AD brain TBS-soluble extract to increase calcium in cortical neurons requires mGluR5 and PrPC. The calcium increase in neurons may occur by the IP3 pathway and also by regulation of NMDA-Rs. Fyn activation by Aβo-PrPC is as strong as that by Glu, whereas calcium mobilization appears to be an order of magnitude less effective for Aβo-PrPC than for Glu.

Specifically, approximately 10 h after

Specifically, approximately 10 h after Talazoparib manufacturer receipt of a 60-μg dose of rLP2086 vaccine, Prevenar®, Infanrix hexa®, Meningitec®, and Rotarix®, the subject developed

a fever (39.0 °C). A Libraries lumbar puncture was performed, and initial results showed 500 cells (95% PMNs), protein 0.5 mg/dl (normal), glucose 60 mg/dl (normal), and red blood cell count of 10 mm3. The subject was treated with cefotaxime and vancomycin after the lumbar puncture; the fever cleared by the next evening and the child remained afebrile and well. The workup did not identify a causative organism; blood and cerebrospinal fluid (CSF) bacterial and viral cultures were negative; polymerase chain reaction tests of the Panobinostat research buy CSF were also negative. Although the aseptic meningitis was ultimately considered not vaccine related by the treating physician, review of safety data by a project-independent safety committee revealed 80% of vaccine recipients at the 60-μg dose experienced

mild to moderate fever (90% including the case of aseptic meningitis). The sponsor decided to terminate the trial after the vaccine was deemed not acceptable in this population. Forty-six subjects were randomized: 22 received 20 μg rLP2086, 10 received 60 μg rLP2086, and 14 received routine childhood vaccines only. Mean age was 65.5 days; 48% were girls; all were white. All subjects received 1 vaccine dose; no postvaccination blood samples were drawn. At least

1 local reaction was reported for 11 (50%) subjects in the 20-μg group, 7 (70%) subjects in the 60-μg group, and 5 (36%) subjects in the control group. The rates of all reactions, except erythema, were lowest in the control group and highest in the 60-μg group (Table 1). The most common local reaction was tenderness, with a mean duration of 1.3 days, 2.7 days, and 1.0 day in the 20-μg, 60-μg, and control groups, respectively. Five subjects receiving rLP2086 experienced tenderness that interfered with limb movement. Most subjects experienced ≥1 systemic event. The most common event was irritability, reported for 17 (77%), 9 (90%), and 9 (64%) subjects in the 20-μg, 60-μg, and control groups. Rates of the other systemic reactions PAK6 and anti-pyretic medication use were lowest in the control group and highest in the 60-μg group, with the exception of decreased sleep (Table 1). Duration of events was 1.0–3.3 days. Fever ≥38 °C was reported in the majority of rLP2086 vaccine recipients: 14 (64%) in the 20-μg group and 8 (80%) in the 60-μg group compared with 4 (29%) in the control group (Fig. 2). In most cases, the temperature was 38.0–39.0 °C; 2 subjects in the 20-μg group and 1 subject in the 60-μg group had fever of >39.0–40.0 °C. No fevers were >40.0 °C. The mean duration of fever was 1.0–2.1 days. The subject with aseptic meningitis also reported a fever between >39.0 and 40.