These data confirmed the finding of a peak knee flexion moment an

These data confirmed the finding of a peak knee flexion moment and a peak of hip extension moment immediately after the foot strike by Mann and Sprague.43 and 44 These data, however, also demonstrated that knee and hip joint resultant powers were all positive when the peak knee flexion moment and peak hip extension moment occurred immediately after the foot strike. This suggests that the hamstring FG-4592 cell line muscle group is in a concentric contraction after the foot strike, in which a hamstring muscle strain injury is not likely to occur.45 The hamstring muscle length and EMG data demonstrated that hamstring muscles were in

eccentric contractions during the late swing phase before foot strike and late stance phase before takeoff.45 These data suggest that hamstring muscle strain injury may occur before foot strike and before takeoff. Two recent studies confirmed find more the data in the previous study.45 Thelen et al.46

also found a hamstring muscle eccentric contraction during the late swing phase of treadmill sprinting, and suggested that the potential for hamstring muscle strain injury existed during the late swing phase. Their results, however, did not show a hamstring muscle eccentric contraction during the stance phase as Wood45 did. Yu et al.47 analyzed the biomechanics of ground sprinting, and also found that the hamstring was in eccentric contraction during the late swing phase as well as during the late stance phase as reported by Wood. Yu et al.47 suggested that hamstring muscles were at the risk for strain injury during the late stance phase as well as during the late swing phase. However, hamstrings may have higher risk for strain injury during the late swing phase than during the late stance phase because the lengths of the hamstring muscles were significantly longer during the late swing phase than

during the late stance phase.47 Understanding risk factors for hamstring strain injury is critical for developing prevention and rehabilitation strategies. Many risk factors for hamstring muscle strain injury have been identified in the literature, however, only a few of these are evidence-based while the majority are theory-based. These risk factors can be categorized as modifiable Etomidate factors and non-modifiable factors.48 Modifiable risk factors include shortened optimum muscle length, lack of muscle flexibility, strength imbalance, insufficient warm-up, fatigue, low back injury, and increased muscle neural tension (Table 1). Non-modifiable risk factors include muscle compositions, age, race, and previous injuries (Table 1). Optimum muscle length is defined as the muscle length at which the muscle contractile element generates maximum force, which is similar to the muscle resting length.49 and 50 Brocket et al.

We characterized these tools in brain slices and used them to def

We characterized these tools in brain slices and used them to define

the spatiotemporal dynamics of opioid signaling with unprecedented resolution. Enkephalins and dynorphins are the most prominent opioid peptides in the brain (Khachaturian et al., 1985). We chose to work with LE and Dyn-8 (Figure 1A) because they are the smallest and most chemically stable endogenous opioids from these peptide families. LE activates delta and mu opioid receptors with nanomolar affinity but is inactive at kappa receptors (Toll et al., 1998). The three additional C-terminal amino acids found in Dyn-8 confer nanomolar potency at kappa receptors in addition to mu and delta receptors (Toll et al., 1998). To render these peptides inactive until exposed to light, we produced analogs modified find more at the N-terminal tyrosine side chain with the carboxynitrobenzyl (CNB) chromophore,

which photoreleases tyrosine with high quantum yield (∼0.3) (Sreekumar et al., 1998) on the microsecond timescale (Tatsu et al., 1996) (see Supplemental Information, available online, for information on peptide production and handling). Extensive studies into the structure-activity relationships of enkephalins (Morley, 1980) and dynorphins (Chavkin and Goldstein, 1981) have revealed an essential role for their common N-terminal tyrosine (Y) in receptor activation. In particular, alkylation (Beddell et al., 1977) or removal (Terenius et al., 1976) of the phenolic OH group reduces the potency of enkephalin analogs, suggesting that modification of the tyrosine side chain of LE and Dyn-8 may be a viable caging strategy. HDAC inhibitor Based on these considerations, we designed Dipeptidyl peptidase CNB-Y-[Leu5]-enkephalin (CYLE) and CNB-Y-Dyn-8 (CYD8) (Figure 1A) to release LE and Dyn-8, respectively, in response to illumination with UV light. The chemical structure of CYLE is shown in Figure 1B. Reverse-phase high-pressure

liquid chromatography experiments confirmed that both peptides cleanly photorelease their parent peptides in pH 7.4 phosphate-buffered saline in response to 355 nm laser illumination (Figure S1) and that they are stable in the dark at room temperature for >48 hr (data not shown). To determine whether CYLE and CYD8 are inactive at opioid receptors prior to photolysis, we compared their activity on opioid receptors relative to that of LE and Dyn-8, respectively, using an in vitro functional cellular assay. To detect opioid receptor activation, we utilized HEK293 cells that stably express a Gαs-Gαi chimera (S.D. Liberles and L.B. Buck, personal communication). This chimeric protein allows GPCRs that normally do not signal through Gαs to stimulate adenylate cyclase and control the transcription of a cAMP-dependent reporter construct. Cells were cotransfected with the opioid receptor of interest and the reporter construct such that receptor activation leads to production of secreted alkaline phosphatase (SEAP).

Total RNA was extracted and qPCR analysis of the complementary DN

Total RNA was extracted and qPCR analysis of the complementary DNA (cDNA) product was carried out using primers against the transgenic human tau construct. The qPCR data clearly show that the neurons that were human tau protein-positive and RNA-negative by FISH indeed did not express detectable levels of the tau transgene (Figure 3G), in contrast to robust detection of tau mRNA in neurons positive for tau mRNA by FISH. Taken together, these data strongly suggest that the human

tau protein may be undergoing neuron-to-neuron transmission. The above experiments strongly suggest the spread of human tau protein from neuron to neuron, which could cause seeding of misfolding and aggregation of tau. It has been shown in cell culture experiments that extracellular tau aggregates could be internalized DNA Damage inhibitor transmitting tau misfolding from the outside to the inside of the cell, where these aggregates could seed fibril formation of recombinant tau monomer. Moreover, the same study showed that tau aggregates were transferred between cocultured cells (Frost et al., 2009). Another recent study reported that brain extracts from neurofibrillary tangle-bearing mouse brain injected in wild-type tau-expressing mice induces seeding of tau fibrils

in neurons (Clavaguera et al., 2009). To determine whether mouse tau is recruited by human tau to aggregate, we performed immunohistochemical analysis using an antibody specific for mouse

tau that revealed that mouse tau HA-1077 indeed accumulates in the somatodendritic compartment of MEC neurons of 24-month-old rTgTauEC mice (Figure 4A). Age-matched control mice have diffuse axonal staining with the mouse tau antibody, and tau knockout mice show no immunoreactivity, as expected. Human however AD cases also have no immunoreactivity to mouse tau, indicating that the observed immunoreactivity is not due to human tau becoming reactive to the mouse tau antibody during pathological changes. Results from double labeling using Alz50 and mouse tau antibodies showed that Alz50 and mouse tau staining colocalized in neuronal cell bodies of the MEC, which is further evidence for mouse tau recruitment into aggregates in the rTgTauEC mouse model (Figure 4B). Immunoblotting using the mouse tau-specific antibody also revealed that mouse tau increased with age in rTgTauEC mice (Figure 4C), indicating that it may accumulate in tangles. In confirmation of this idea, sarkosyl-insoluble and -soluble fractions both contain endogenous mouse tau (Figure 4D). The specificity of the mouse tau antibody was confirmed by western blot analysis (Figure 4E), which revealed mouse tau (mTau) reactivity in rTgTauEC and control mouse brain but not in tau knockout mouse brain or human AD brain.

, 2007, Milstein et al , 2007, Soto et al ,

, 2007, Milstein et al., 2007, Soto et al., 3-MA mouse 2009 and Tomita et al., 2003), the cornichon homologs (CNIH-2, CNIH-3; Schwenk et al., 2009), and the CKAMP44 protein ( von Engelhardt et al., 2010). Alone or in combination, these auxiliary subunits

control the gating and pharmacology of the AMPARs and profoundly impact their biogenesis and protein processing ( Bats et al., 2007, Chen et al., 2000, Gill et al., 2011, Harmel et al., 2012, Kato et al., 2010, Schober et al., 2011, Schwenk et al., 2009, Soto et al., 2007, Tomita et al., 2005, Vandenberghe et al., 2005 and von Engelhardt et al., 2010). It is not clear, however, whether these auxiliary proteins represent the whole set of building blocks for native AMPARs or whether they contain additional yet unknown protein constituents. Likewise, quantitative data on the subunit composition of native AMPAR complexes are not yet available. This information may be obtained from comprehensive

and quantitative proteomic analyses as have recently been presented for the Cav2 family of voltage-gated calcium channels (Müller et al., 2010). Here we used two orthogonal biochemical strategies, multiepitope and target knockout-controlled affinity purifications (Bildl et al., 2012 and Müller et al., 2010) and newly developed high-resolution quantitative analyses of protein complexes separated on native gels (BN-MS), for investigation of the subunit composition of AMPARs PLX3397 cell line from total brain. These analyses unravel native AMPARs as macromolecular complexes of

unanticipated complexity and identify 21 novel protein constituents, mostly transmembrane or secreted proteins of low molecular mass and with distinct functions. Subsequent studies using antibody shift assays, binding studies, and electrophysiological recordings reveal the architecture of native AMPARs and demonstrate that properties and function of the receptor complexes may be quite distinct strongly depending on the particular subunit composition. For Resminostat comprehensive proteomic analysis of native AMPARs, we performed multiepitope affinity purifications (ME-APs) (Müller et al., 2010 and Schwenk et al., 2010) with ten different antibodies (ABs) specific for the GluA1-4 proteins on membrane fractions prepared from total brains of adult rats, wild-type (WT) mice, and AB-target knockout mice (see Experimental Procedures). For ME-APs the membrane fractions were treated with detergent buffers of either mild (CL-47) or intermediate (CL-91) stringency (Müller et al., 2010 and Schwenk et al., 2010) solubilizing ∼40% and 100% of the total pool of AMPARs, respectively (Figures S1A and S1B). These buffers were selected as the two extremes in a test series probing the solubilization efficiency of various CL-buffers as well as of RIPA and Triton X-100, the buffers most widely used with AMPARs (Kim et al.

Others have proposed that serotonin is primarily involved in the

Others have proposed that serotonin is primarily involved in the inhibition of thoughts and actions associated

with aversive outcomes (Daw et al., 2002), including the process of heuristically disregarding unpromising branches of decision trees (Dayan and Huys, 2008; Huys et al., 2012). According to this view, depressed individuals would expect a lower rate of reward from their actions, because insufficient serotonin would expose the negative outcomes of potential actions that would be normally subject to pruning. More research is needed, however, for understanding the nature of neural processes mediating the effects of various neuromodulators, such as serotonin, during decision making. Compound Library Autism is a neurodevelopmental disorder, characterized by impaired social cognition, poor communicative abilities, repetitive behaviors, this website and narrow interests (Geschwind and Levitt, 2007). In particular, individuals with autism are impaired in their ability to make inferences regarding the intentions and beliefs of others, namely, theory of mind, as reflected in their poor performance with the false-belief task (Baron-Cohen et al., 1985;

Frith, 2001). Such reduced abilities to mentalize the intentions of others might underlie differences in the strategies of autistic individuals and control subjects during socially interactive decision-making tasks. For example, children with autism tend to offer a smaller amount of money as proposers during the ultimatum game, and they are also more likely to accept even very small offers as responders (Sally and Hill, 2006). In Phosphoprotein phosphatase addition, whereas control subjects donated more money to charity in the presence of observers, this effect was absent in individuals with autism (Izuma et al., 2011). Autistic individuals are also impaired in their abilities to infer mentalizing strategies of others (Yoshida et al., 2010). Some of these social impairments in autism are ameliorated by oxytocin, but precisely how oxytocin influences

affective and social functions of the brain remains poorly understood and must be more carefully characterized (Yamasue et al., 2012). Although autism has heterogeneous etiology, abnormality in the long-range connections between different association cortical areas is often considered important (Geschwind and Levitt, 2007). Such anatomical changes might underlie reduced inter-hemispheric synchronization in neural activity recorded from toddlers with autism (Dinstein et al., 2011). Anatomical and physiological abnormalities in autism might produce their most prominent effect in the domain of social cognition. Consistent with the possibility that the default network might be important for mental simulation in social contexts, the default network is hypoactive in individuals with autism (Figure 4B; Kennedy et al., 2006).

While final angular size was not always a strong predictor of the

While final angular size was not always a strong predictor of the occurrence of cocontraction (Figures S4A and S4B), the probability distribution of the DCMD maximum firing rate for trials with cocontraction was shifted to larger firing rates compared to trials without cocontraction (Figure 6B). Using a linear discriminant, we could predict with an accuracy of 83% the occurrence

of cocontraction based on whether the maximum DCMD firing rate exceeded 248 spike [spk]/s (Figure S4C). Second, in a subset of these trials (nT = 9, nL = 6) only one or two extensor spikes were recorded after the stimulus had stopped and the DCMD had reached its maximum activity (Figure S4D). Thus, the maximum DCMD activity this website in these trials, 300 spk/s on average, was just above the

threshold required Inhibitor Library concentration to trigger the cocontraction (SD: 72). This value is close to that suggested to trigger collision avoidance in flight (Santer et al., 2006) and not significantly higher than that estimated with a linear discriminant (t test, p = 0.073). Furthermore, in these trials the average delay between the maximum DCMD firing rate and the start cocontraction was 36 ms (SD: 23). As a third approach for assessing the role of a DCMD firing rate threshold in triggering cocontraction, we carried out a correlation analysis on the data recorded in trials with full stimulus expansion. We hypothesized that if the cocontraction is triggered when a fixed delay has elapsed following a threshold DCMD firing rate, the value of the firing rate at that delay must be independent of l/|v|. Consistent with this hypothesis, the DCMD firing rate and the stimulus size to speed ratio were uncorrelated 40 ms prior to cocontraction onset (Figure 6C). The firing rate at this delay did not significantly change with l/|v| (pKWT = 0.6) and had an average of 225 spk/s (SD: 73; Figure 6D), Bay 11-7085 close to the values predicted by the two other methods considered above. Taking into account

the observed variability, we conclude that the cocontraction is triggered approximately 40 ms after the DCMD approximately exceeds a firing rate of 250 spk/s. Using data from the same experiments, we next checked that the total number of DCMD spikes from trial start to cocontraction onset was only weakly correlated with the time of cocontraction (ρ = 0.07, p = 0.6). This result is also consistent with a change in DCMD firing rate immediately before cocontraction onset, such as a firing rate threshold, being more critical than accumulation of spikes over the entire trial. The trial-by-trial correlation of the firing rate threshold time with that of cocontraction onset was high (ρ = 0.6, p < 10−9; Figure S4E) and predicted 36% of the variance of cocontraction onset. Furthermore, this correlation value decreased by 1/3 when we randomly shuffled these two variables across trials (ρ = 0.39, p = 0.01; mean over 100 shuffles, SD: 0.

2 mM of

dNTP, 0 1–0 2 μM of each primer, 2–3 75 mM of MgC

2 mM of

dNTP, 0.1–0.2 μM of each primer, 2–3.75 mM of MgCl2, 1.5 units of Taq Platinum DNA polymerase (Invitrogen), 0.04 μL of Sybr Green 100×, 2 μL of buffer 10× 50 mM of KCl, 10 mM of Tris–HCl pH 9.0 (Invitrogen), and 0.5 μL of dimethyl sulfoxide (DMSO; Sigma). For each sample, the cycle threshold (Ct) mean was obtained and normalized to a reference gene. Three reference genes were evaluated: GAPDH (glyceraldehyde-3-phosphate dehydrogenase), HPRT-1 (hypoxanthine phosphoribosyltransferase 1) and RPL-19 (ribosomal protein L19). The relative quantification was evaluated by mathematic modeling based on JQ1 the PCR efficiencies (E) of the target and endogenous genes and on Ct variation of samples from the experimental groups, according to Pfaffl et al. (2002). For this analysis, the Relative Expression Software Tool (REST©) was used, which applies a nonparametric significance test called the Pair Wise Fixed Reallocation Randomisation Test©. LBH589 Histological data (eosinophils, mast cells and globule leukocytes) were analyzed by the GLM procedure using the SAS program (SAS, 2002/2003). The average eosinophil and mast cell counts were 30.96 (±S.D. 5.55) and 10.31 (±S.D. 9) in the non-infected group and 28.41 (±S.D. 2.35) and 17.12 (±S.D. 1.95) in the infected group, respectively. No significant

differences were found between groups for the eosinophil counts (p = 0.30) and mast cell counts (p = 0.32) in the mucous membrane of the abomasum ( Fig. 1). No globular leukocyte was observed in the slides in any group. Among the three reference genes tested to be used in the relative quantification, the RPL-19 gene was chosen because it presented more constant Ct values (19 ± S.D. 2.3 in the abomasum and 20.7 ± S.D. 1.2

in lymph node) than the other two genes analyzed. Relative quantification of target genes showed that IL-4 (14×; p = 0.002), IL-13 (26×; p = 0.003) and TNF-α (10×; p = 0.03) were up-regulated in the abomasal lymph nodes of the infected group in comparison with control group ( Fig. 2). In the abomasum tissue, IL-13 was up-regulated (4.8×; p = 0.03) in the infected group and TNF-α was down-regulated (4.0×; p = 0.032) in the same group ( Fig. 3). The mRNA levels of the other genes were not influenced by H. placei Rebamipide larval exposure in the abomasal lymph node, as well as in the abomasum tissue (p > 0.05). In this study, we compared cytokine gene expression of Nellore calves in primary infection with H. placei infections caused by helminths have been studied in many species and have usually been associated with Th2 response in infected animals. In cattle, these infections are not characterized by a severe immune response and most become chronic. Reduction in the number of adult parasites begins after exposure to the parasite and at the same time there is a significant increase in eosinophil, globular leukocyte and mast cell counts in the sites of the infection ( Grencis, 2001 and Bricarello et al., 2004).

Biofeedback increased walking compared with usual therapy (SMD = 

Biofeedback increased walking compared with usual therapy (SMD = 0.57, 95% CI 0.10 to 1.03, I2 = 0%, see Figure 8 on the eAddenda for the detailed forest plot). This systematic review provides evidence that biofeedback

has a moderate effect (Cohen 1988) in improving activities of the lower limb such as standing up, standing, and walking in the short term compared with usual therapy/placebo. Furthermore, the benefits are still present in the longer term although slightly diminished. This suggests that learning has taken place in addition to short-term improvements in performance. Biofeedback delivers feedback that is Libraries continuous, objective and concurrent with the activity, ie, knowledge of performance. In healthy populations, evidence suggests that concurrent feedback is beneficial to performance, but detrimental to learning (van Vliet and Wulf 2006). However, this review provides evidence that after stroke the provision of concurrent biofeedback during SRT1720 cost the practice of activities resulted in learning because lower limb activities were permanently improved. The mean PEDro score of 4.7 for the

22 trials included in this review represents only moderate quality. However, in order to decrease the substantial amount of statistical heterogeneity, only higher quality trials (PEDro score >4) were included in the final meta-analyses. This resulted in the 11 trials contributing to the findings having a mean PEDro score of 5.7, adding LBH589 to the credibility of the conclusions. There was some clinical heterogeneity in these trials. Participant characteristics of age and gender were similar, and the time since stroke was generally subacute (70%), with three trials of participants whose time post stroke was chronic (10 mth, 18 mth, 4 yr). There was a range

of duration of intervention (3 to 8 weeks), however the majority of trials examined interventions Resminostat of 4 to 6 weeks in duration. Taken together, this suggests that the findings are credible and can be generalised cautiously. Our subgroup analysis of lower limb activities suggests that biofeedback may be slightly more effective at improving walking (SMD 0.57) than standing (SMD 0.42). However, another explanation may be that the tools used to measure outcome were usually more congruent with the activity practised in trials of walking (eg, outcome of biofeedback of step length during walking practice measured as step length during walking) than in trials of standing (eg, outcome of biofeedback of weight distribution during standing practice measured with the Berg Balance Scale). In terms of walking, our result is similar to Tate and Milner (2010) who reported a moderate-to-large effect of all types of biofeedback on walking (7 trials, no meta-analysis). In contrast, Woodford and Price (2009) reported no effect of biofeedback on walking speed (SMD 0.13, 95% CI –0.55 to 0.80, 3 trials) and Langhorne et al (2009) reported being unable to draw conclusions.

This group also demonstrated a late asthmatic response between 8

This group also demonstrated a late Modulators asthmatic response between 8 and 9 h. The mean peak response during this period was − 19.9 ± 4.9%

compared to protocol 4, 1.3 ± 2.6%. No significant bronchoconstriction to histamine was observed in any experimental animal 24 h before Ova or saline challenge (Fig. 2). Small changes were observed in some groups which represent the normal variation in sensitivity to a threshold concentration of histamine. In animals challenged with saline, no histamine-induced bronchoconstriction was observed 24 h after saline (Fig. 2A). Animals sensitised with 2 injections of 100 μg/ml Ova and 100 mg Al(OH)3 and challenged with 100 μg/ml Ova (protocol 1, Fig. 2B) also lacked histamine-induced bronchoconstriction, indicating the absence of AHR. Increasing the Ova challenge

concentration to 300 μg/ml (protocol 2, Fig. 2C) caused a significant bronchoconstriction Epigenetic inhibitor ic50 to histamine 24 h after Ova challenge (− 38.5 ± 7.9% compared to pre- − 4.1 ± 2.3%) which resolved within 10 min. Increasing the Al(OH)3 concentration (protocol 5, Fig. 2D), increasing Ova sensitisation concentration (protocol 4) and the number of injections (protocol 3) did not further alter the nature of this response (data not shown). Increasing the time between Ova sensitisation and challenge (protocol 6, Fig. 2E) increased the size of the immediate bronchoconstriction to histamine 24 h post-challenge (− 53.9.4 ± 11.4%) compared to pre-Ova challenge, (− 10.1 ± 2.4%). The duration of the bronchoconstriction was also increased, at 10 min into the response, the bronchoconstriction was − 26.7 ± 11.4% VX-770 mouse compared to the pre-Ova challenge level of 1.6 ± 2.7%. 100 μg/ml many Ova challenge significantly increased total lavage cells (protocol 1, Fig. 3A, 3.2 ± 0.5 × 106/ml) compared to saline (1.6 ± 0.13 × 106/ml). Eosinophils (Fig. 3C) made up most of this increase (1.3 ± 0.3 × 106/ml) compared to saline (0.05 ± 0.01 × 106/ml). Increasing the Ova challenge concentration (protocol 2) significantly increased the total cell numbers (5.3 ± 0.4 × 106/ml) compared to protocol 1 (3.2 ± 0.5 × 106/ml).

Eosinophils were significantly elevated (2.0 ± 0.2 × 106/ml) compared to protocol 1 (1.3 ± 0.3 × 106/ml). Increasing the number of 100 μg Ova sensitisation injections (protocol 3) had no effect on any cell type measured. Increasing the Ova sensitisation concentration to 150 μg (protocol 4) significantly increased total cells (8.3 ± 0.9 × 106/ml) compared to protocol 3 (4.8 ± 0.4 × 106/ml). Eosinophils (3.9 ± 0.3 × 106/ml compared to 2.4 ± 0.3 × 106/ml) and macrophages (Fig. 3B, 3.5 ± 0.3 × 106/ml compared to 2.2 ± 0.2 × 106/ml) were also significantly increased. Increasing the Al(OH)3 sensitisation concentration to 150 mg (protocol 5) significantly increased eosinophils (6.9 ± 0.8 × 106/ml) compared to protocol 4 (4.6 ± 0.5 × 106/ml). Lymphocytes (Fig. 3D) were also significantly increased (0.15 ± 0.02 × 106/ml) compared to protocol 4 (0.3 ± 0.

Examination of the supportive Th cells revealed a spectrum of Th1

Examination of the supportive Th cells revealed a spectrum of Th1-, Th2-, and Th17-type cytokines. I.m. immunization influenced the production of Th17 cell responses, further supporting the notion that LTN can be used as a molecular adjuvant for vaccine to Libraries enhance protective immunity against plague. In mice immunized Imatinib concentration with LTN DNA vaccine by either i.n. or i.m. route, Ab responses to F1- and V-Ag began to increase by wk 6. Although three DNA immunizations were insufficient to elevate the anti-F1- and -V-Ag Ab responses, robust Ag-specific responses were induced in mice nasally boosted with F1-Ag protein.

These results were consistent with previous observations that DNA immunization effectively primes the host [25], [36] and [37], and the combination of DNA and protein immunizations

offers one means to effect optimal immunity to plague. Our results also showed that i.n. and i.m. LTN DNA vaccinations provide sufficient priming effect on induction of immunity to F1- and V-Ag in the peripheral immune compartment, resulting in improved efficacy when compared to nasal application of recombinant F1-Ag alone. Thus, LTN DNA vaccines provide effective priming that ultimately leads to protective immunity against plague. The stimulation of neutralizing Abs when using LTN adjuvant was less apparent when applied nasally. Nasal LTN DNA vaccinations conferred less protection than the same vaccines given by the i.m. route. These results were unexpected, since we previously showed that Salmonella-based [27] and IL-12-based DNA vaccines [25] check details were effective against pneumonic plague challenge. Our results also showed, although serum Ab responses to F1- and V-Ag between i.n. and i.m. LTN DNA-vaccinated mice were similar after boosting with F1-Ag protein, found Ab responses induced during the priming phase by the nasal LTN DNA vaccines were slightly lower than those Abs obtained by i.m.-vaccinated mice. Moreover, nasal immunization with LTN/F1-V produced less robust nasal Ab responses when compared to mice similarly immunized via the i.m. route. Although there did appear to be some tissue specificity, the

cytokine analysis revealed the Th cell responses to V-Ag in the nasally DNA-immunized mice were dampened, particularly the Th1 cell responses, when the same Th cell responses were compared to i.m.-immunized mice. Such differences could account for the dampened efficacy by the nasally immunized mice. Thus, the molecular adjuvant, LTN, when given as a DNA vaccine, seems to perform better when given parenterally and provides better protection against pneumonic plague than the same vaccines given nasally. These data differ from that previously shown for the LTN protein when applied nasally with Ag [24]. No differences in IgG subclass responses were observed in mice nasally vaccinated with LTN DNA vaccines. However, IgG1 and IgG2a anti-F1-Ag responses were significantly greater than IgG2b responses in i.m.-immunized mice with LTN/V-Ag and LTN/F1-V DNA vaccines.