It is important to point out that this tab was idealized to allow

It is important to point out that this tab was idealized to allow only the visualization of eplets. For that reason, in the Recipient × Donor tab the EpHLA Software shows zero PD-0332991 clinical trial for the MFI value of the subunits DQA1* and DQB1* shown separately in the columns “Normal” (Fig. 5 and Fig. 6). The actual MFI values associated to the beads of the panel containing the subunits DQA1* and DQB1* studied can be visualized in the remaining tabs. The Histocompatibility

Map report also shows in the upper right corner the Eplet’s Report tab, where the laboratory personnel can easily verify if an eplet plays a potential role in allosensitization and observe, quickly, if a certain eplet appears only in positive molecules or also in negative ones (Fig. 3). In order to carry out the post-transplant follow-up or to study the potential donors for a certain recipient, the EpHLA program allows registering for donor on the Local repository form. It is only necessary to register the following data: name, laboratory unique number and the HLA alleles, represented by the fields A, B, Cw, DRB1, DRB3, DRB4, DRB5, DQA and DQB. One or more registers of potential donors can be associated to a recipient registration — using the Potential Donors tab accessible

Osimertinib research buy on the Local repository form. For each recipient/donor pair, the EpHLA program generates a report showing the donor’s alleles and their respective non-self eplets, as previously shown. To test the tool’s functionalities, the EpHLA software was used to determine the antibody profile of two sensitized recipients from the renal transplant program studied at the Federal University of Piauí’s Immunogenetics and Molecular Biology Laboratory (LIB-UFPI). The first recipient exhibited a positive CDC assay with B-lymphocytes due to IgG antibodies, and the second recipient had a negative CDC assay with a current serum and a positive CDC assay with historical serum. The HLA typings were carried out at medium-resolution using Sequence-specific Oligonucleotide Probe Hybridization – SSOPH (One Lambda, Canoga Park, CA, USA) – for

the loci A, B, Cw, DRB1, DQB1. HLA alleles were inferred using the NMDP codes and the allele frequency tables available at http://bioinformatics.nmdp.org/ [17]. The HLA alleles of the loci DRB345 and Cytidine deaminase DQA1 were generated on the basis of their linkage with the DRB1 allele, using the HLAMatchmaker software (DRDQ Allele Antibody Screen) — available at http://www.hlamatchmaker.net/ [5]. In this study we used the following MFI cutoff values to classify antibody–antigen reactions: strong reaction — MFI higher than 3,000; moderate reaction — MFI between 500 and 3,000, and weak or negative reaction — lower than 500. In order to obtain the calculated PRA we used the public program cPRA, available at Organ Procurement and Transplantation Network’s website: http://optn.transplant.hrsa.gov/resources/professionalResources.

Clarifying the relationship between the time histories and cellul

Clarifying the relationship between the time histories and cellular responses and/or fate determination is one of the more BYL719 chemical structure important issues in patterning studies. Computer simulation can be a powerful tool for understanding such complex dynamics. From an engineering viewpoint, exploring optimal designs for achieving accurate spatial recognition in dynamically changing environments is an interesting problem; cells need to update the estimates of their positions over time. In the field of neural networks or brain science, there is an accumulation of technical knowledge on such estimation problems [56]. Especially, concepts

of sequential inference based on Bayesian updating will be useful for understanding general mechanisms for robustly achieving dynamic patterning. Much knowledge and information about pattern generating GRNs has been gathered in recent years. By contrast, research on mechanisms for generating robust patterns in growing tissues with time-variant morphogen information is just beginning. In particular, there are few reports about higher-dimensional patterning. General principles for robust patterning adopted by real systems will be elucidated only by quantitatively analyzing the interdependent relationships among gradient dynamics, cell trajectory in growing tissues, and time series of cellular responses. To do that,

it goes without saying that mathematical modeling of spatial information coding and simulation studies, as well as advanced measurement techniques, will play crucial roles. Papers of particular interest, published within the period

of review, have been highlighted E7080 manufacturer as: • of special interest “
“In the article, “Clinical outcomes of endoscopic submucosal dissection for rectal tumor close to the dentate line,” in the August issue of Gastrointestinal Endoscopy (Gastrointest Endosc 2012;76:444-50), there was a typographical error in Table 2. The complete corrected table appears below. “
“Current Opinion in Genetics & Development 2012, 22:398–400 Available online 27th July 2012 0959-437X/$ – see front matter, Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.gde.2012.07.008 Current Comments are a rapid outlet for scientific opinions on DOCK10 a topic of general interest. Biglycan is an extracellular matrix component of many parts of the skeleton including bone, cartilage, tendon, teeth and muscle. Biglycan is predominantly expressed as a proteoglycan, but a mature form lacking GAG side chains (‘nonglycanated’) has recently been shown to have specific functions in muscle, synapses and Wnt signaling in bone. The biglycan gene is on the X (and not Y) chromosome and is dysregulated in Turner (XO) and Kleinfelter’s Syndromes (supernumery X) diseases, characterized by short and tall stature respectively. Biglycan deficient mice have shorter bones as well as lower bone mass (ostepenia/osteoporosis) [1], another notable feature observed in Turner Syndrome.

The author greatly appreciates financial support provided by the

The author greatly appreciates financial support provided by the National Natural Science Foundation of China project, No. 311712494. The author also appreciates the financial support provided by NATP, BARC, Dhaka, Bangladesh. “
“Acid soils are widespread and limit plant production all over the world. They cover 30%–40% of arable land and more than 70% of potential arable land [1]. Constraints to production in acid soils are caused by a combination of lack of essential nutrients, reduced water uptake and mineral toxicity. The initial visual symptom on plant growth is reduced root length [2]. Although approaches such as adding lime, magnesium or calcium to the soil can ameliorate

adverse effects on plant growth, they are both costly and ecologically unsound.

Breeding tolerant cultivars is the most efficient way to cope with soil acidity. Plants vary significantly in acid PF-02341066 price VX-809 research buy soil tolerance. Variation in acid soil tolerance makes it possible to breed tolerant cultivars. The success of breeding programs relies on an understanding of the physiology, genetics and gene regulatory information of acid soil tolerance. Decades of study have revealed that the tolerance is due to both internal and external mechanisms. The external mechanism, organic acid exudation, is common in higher plants. Various genes and QTL in different species are responsible for different tolerance mechanisms. Molecular markers have been developed to assist gene cloning and to provide useful resources for marker-assisted Progesterone selection for breeding tolerant cultivars. This paper reviews recent progress in molecular approaches to improve Al tolerance in plants. Soil pH has significant adverse effects on the availability of plant nutrients [3], solubility of toxic heavy metals [4], soil microorganism activity [5], breakdown of root cells [6], and cation exchange capacity in soils [7]. The toxic effects can be classified as morphological and physiological. Both lead to poor plant development and consequently

yield reduction [8]. Acid soil is a worldwide problem (Fig. 1) mainly located in two belts: viz., the northern belt in the cold humid temperate zone covering North America, South Asia and Russia; and the southern belt in humid high rainfall tropical areas including South Africa, South America, Australia and parts of New Zealand [1]. There are 3950 million ha of arable land affected by soil acidity. It affects about 38% of farmland in Southeast Asia, 31% in Latin America, 20% in East Asia, 56% in Sub-Saharan Africa, and parts of North America [9] and [10]. In the Americas, 1616 million ha is affected, mostly in South America. In Australia and New Zealand, 239 million ha of agricultural land is acidic [11]. In China and India, 212 million ha or 12% of agricultural land is classified as acidic. Acid soils not only cause plant production losses, but also affect plant distribution.

Although many researchers assume the temperature regime to be a s

Although many researchers assume the temperature regime to be a sensitive marker for the testing of climate changes, other characteristics VX-809 in vivo such as the duration of the ‘biological summer’

(the period with temperatures > 10°C, Efremova & Palshin 2012) can be used as an important marker of climate change, because it determines the initial biomass growth rate and the reproduction rate (abundance) of aquatic organisms. The example of six lakes in Karelia from 1953 to 2009 shows that the duration of the ‘biological summer’ has increased by 12–23 days and that the trend of the prolongation of the ‘biological summer’ is positive (p < 0.05) ( Efremova & Palshin 2012). The majority of the lakes in East Fennoscandia are characterised by an increase in the ice-free period (Filatov Z-VAD-FMK order et al. 2012). Earlier ice-melting in Lake Onega can result in a shift of the spring bloom period of diatoms. The negative correlation between the ice-free period and plankton characteristics (Chl a and N phytoplankton) may be explained by the predominance of large-sized diatoms (Tabellaria fenestrata and Aulacoseira islandica) in the summer phytoplankton. Chl a in these species is lower than in other algae (diatoms). The negative correlations between NAO, AO, precipitation

and zoobenthos abundance and biomass testify that nutrient and organic matter loads from the catchment area can increase together with the increase of precipitation in years with a positive NAO. In turn, eutrophication PD184352 (CI-1040) phenomena (hypoxia, H2S production etc.) can reduce the numbers of sensitive species (relict amphipods) and, conversely, favour eurybiotic taxa (oligochaetes). Oxygen depletion and higher temperatures accelerate nutrient release processes at the sediment-water

interface (Søndergaard et al. 2003) and increase the stress on aquatic organisms (Weider and Lampert, 1985, Saeger et al., 2000 and Wilhelm and Adrian, 2007), resulting in a decrease in their abundance. Significant correlations between climate indices, physical parameters in Petrozavodsk Bay, Lake Onega, and some characteristics of its biota (phytoplankton, zoobenthos) were found in this research. We conclude that global climate primarily determines the regional hydrological variables of a lacustrine ecosystem and its productivity level, whereas biotic characteristics are a reflection principally of the variability in the water temperature and the ice-free period, both of which determine the duration of the ‘biological summer’ (WT > 10°C). At the same time, the responses of biological communities and whole ecosystems to climate variability are complex and often difficult to recognise, especially in the case of large ecosystems with a long period of water exchange. We cordially thank Professor Nikolai N. Filatov, Dr Natalia M. Kalinkina for the valuable discussion and also Mrs Y.

35, n = 372) over the Adriatic and Aegean sub-basins ( Figure 5h)

35, n = 372) over the Adriatic and Aegean sub-basins ( Figure 5h). However, the maximum positive correlation between Fos and SST (R > 0.6, n = 372)

occurs over the Adriatic and Aegean sub-basins and the Black Sea. The effect of air-sea heat fluxes on SST displays seasonal behaviour. The percentage of the study area in which Fn significantly affects SST ranges from 14% in winter to 59% in autumn. However, the percentage of the study area in which Fos significantly affects SST ranges from 45% in summer to 100% in autumn. This result supports selleck inhibitor the previous findings of Skliris et al. (2012), who found that the Mediterranean SST variability is largely explained by air-sea heat fluxes. Analysis of results for the different Fn components indicates that the study area SST is explained by

the sensible heat flux, net long-wave radiation and latent heat flux values. This is in disagreement with the previous findings of Skliris et al. (2012), who stated that the latent heat explains more of the Mediterranean SST than do the other Fn components. This disagreement is probably because Skliris et al. (2012) examined a study period extending only from 1985 to 2008 and used a different database to extract air-sea heat fluxes. Annual correlations between SST and NAO, SLP, P, TCC, τax, τay, T2m, Fn and Fos were significant over 38%, 55%, Daporinad nmr 16%, Liothyronine Sodium 55%, 18%, 25%, 100%, 54% and 26% of the study area respectively (data not shown). This may indicate that the interannual correlations of the studied atmospheric parameters explain less of the Mediterranean SST variability over the study area than do the monthly correlations.

The only exception is Fn, the inter-annual correlations of which explain more of the Mediterranean SST variability than do the monthly correlation. In this section, time series analysis is used to reveal the SST variation between the 10 sub-basins of the study area, all of which display an annual positive trend ranging from 0.024 °C yr− 1 to 0.05 °C yr− 1 (Figure 6 and Table 2). The 10 studied sub-basins display a range of annual average SST values of approximately 6.2 °C, ranging from 15.0 °C in the Black Sea to 21.2 °C in the Levantine sub-basin. The annual average SST of the AAM sub-basin is approximately 0.6 °C higher than that of the adjacent Mediterranean Sea sub-basin, i.e. the Alboran sub-basin, most markedly in autumn. However, the annual average SST of the Black Sea is approximately 4.1 °C lower than that of the adjacent Mediterranean Sea sub-basin, i.e. the Aegean sub-basin, most markedly in winter (Figure 6 and Table 2). The annual average COV of the study area SST displays important spatial variability: the maximum variability occurs over the Black Sea (COV = 42%), while the minimum variability occurs over the AAM sub-basin (COV = 11.8%).

6 The only way of removing most of the WBCs is by filtering the b

6 The only way of removing most of the WBCs is by filtering the blood with leukodepletion filters. Roughly speaking, if the total content of PMNs per million RBCs is 1000 in whole blood, it will decrease, at best, to 100 in washed blood and to < 10 in

filtered blood.6 A simple and reliable procedure for RBC purification that is suitable for samples of small volumes and easy to implement in every lab is filtration through cellulose, as was originally proposed by Beutler et al.13 and described in detail in the supplementary material of Achilli et al.14 We propose this simple concept as a standard method and good laboratory practice in RBC research. It should be emphasised, however, that filtration might not be applicable in all instances, e.g., for pathological RBCs, because its functioning

principle appears to be based largely Trichostatin A on the difference in deformability between RBCs and WBCs.15 The latter are much less deformable than normal RBCs and are therefore retained in the filter for a longer time than RBCs. However, in certain RBC pathologies, RBC deformability is abnormally reduced, and this may result in reduced filterability (hereditary spherocytosis, hereditary elliptocytosis, ovalocytosis, sickle cell anaemia). The task of quantifying low WBC levels is by Proteases inhibitor no means a simple one, and special techniques have been devised for this purpose. As a general remark, microscope counting using conventional haemocytometer chambers is impractical and not sensitive enough. The flow cytometry (FCM) approach is meaningful only if the number of total events counted in each analysis is sufficiently high to reveal 1 WBC per 106 RBCs, which implies long analysis times.16 An extremely sensitive and inexpensive method for the quantification of PMNs in blood samples that can be easily implemented in all labs is the technique of gelatin zymography, Aspartate as recently adapted.14 The consequences of having a PMN-contaminated RBC suspension can be deleterious. Two main types of artefacts can result from such a situation: (i) attribution to the RBCs of a component/function that in fact belongs to the PMNs; (ii) damage

to RBCs resulting from hydrolases and oxidases released by activated or broken PMNs. The first issue has already been exemplified in the Introduction. The wrong method used in a recent Nature article12 for the purification of RBCs results, instead, in the isolation of a fraction of RBCs together with all the PMNs that were originally present in the blood sample, without even reducing the number of PMNs, as would occur if a conventional centrifugation-based wash of the blood and removal of the “buffy-coat” were performed. Fig. 1A indicates the amount of PMNs left by different separation methods. The artefactual results that originate from PMN hydrolases damaging RBC components are exemplified by the controversy on the isolation and characterisation of lipid rafts from RBCs.

None of these companies produces the antidiabetics studied in the

None of these companies produces the antidiabetics studied in the paper, and these potential conflicts did not affect the given contributions to this article. L.P. in the previous years has received honoraria for lectures at continuing medical education programs for healthcare professionals not focused on specific products. The authors are indebted to Marisa De Rosa, Anna Covezzoli, and Andrea Roncadori (CINECA, Casalecchio di Reno) for providing some

of the additional analyses presented in the article. The essential contribution of the several thousands of diabetes specialists who uploaded their data in the monitoring database is also hereby acknowledged. “
“Genome-wide association studies (GWAS) have identified multiple loci www.selleckchem.com/products/Verteporfin(Visudyne).html at which common variants modestly but reproducibly influence risk of type-2 diabetes (T2D) [1], [2], [3], [4], [5] and [6]. Currently, Fluorouracil single nucleotide polymorphisms (SNPs) in ∼40 genetic loci have been associated with T2D [7] and [8], most of which relate to insulin secretion rather than insulin resistance [8] and [9], have been distinct from previously studied candidate genes [10],

and do not seem to offer greater predictive value in determining diabetes risk than do commonly used phenotypic risk factors and family history [11] and [12]. Rung and colleagues [13] identified rs2943641C > T, located 500 kb downstream of the insulin receptor substrate-1 gene (IRS1), as a T2D risk locus, with the major C-allele being associated with 19% increased risk of T2D. Importantly, unlike other reported T2D loci, the rs2943641C allele was associated

with increased fasting- and glucose-stimulated hyperinsulinemia and impaired insulin sensitivity. Lower IRS1-associated phosphatidylinositol-3–OH kinase activity in human skeletal muscle biopsies was also shown for the C-allele during insulin infusion, Palbociclib and in vitro studies showed that this allele was associated with lower IRS1 protein expression in the basal state, suggesting a direct regulatory link between rs2943641 and IRS1 [13]. The Diabetes Genetics Replication and Meta-analysis Consortium (DIAGRAM) in an earlier meta-analysis did not identify this SNP as a T2D risk variant [4]; however, in a subsequent publication [6] a different IRS1 SNP (rs7578326) adjacent to and in strong linkage disequilibrium (LD) with rs2943641 (r2 = 0.79, in HapMap CEU) was reported to be associated with T2D. The purpose of this study was to validate the rs2943641 association with T2D risk and diabetes-related quantitative traits using data from UK population-based cohorts and T2D patients. In addition, using data from 4752 Caucasians participating in the Whitehall-II study who had been genotyped for 33 IRS1 SNPs using the HumanCVD BeadChip [14] and [15] and with follow-up direct genotyping of IRS1 SNPs in the other study cohorts, we explored the potential association with the risk of T2D of SNPs within and flanking IRS1.

Further, this null effect of awareness is consistent with Joorden

Further, this null effect of awareness is consistent with Joordens and Merikle’s (1992) finding that brief masked primes (57 msec) produce the Jacoby–Whitehouse effect whether participants are told of the

primes’ existence in advance (“aware” instructions) or not (“unaware instructions”). While previous fMRI studies have implicated the hippocampus as well as parietal cortex in recollection, we did not find activity in hippocampus for the R Hit > K Hit comparison that survived whole-brain correction (though it is likely to have had survived correction for a smaller search space, e.g., hippocampi alone). Nonetheless, the hippocampus was clearly identified by the CR > K Hit comparison, and further examination suggested that it also showed greater activity for R Hits than K Hits. Indeed, the U-shaped pattern across Osimertinib R Hit, K Hit and CR judgment types has been observed in numerous previous fMRI studies,

and often interpreted in terms of hippocampal involvement in both (1) the recollection of studied items and (2) the encoding of novel, unstudied items (with evidence of the latter occurring even during a recognition memory test; Buckner et al., 2011; Stark and Okado, 2003). Indeed, using intracranial electroencephalography (EEG) during a recognition memory test, we have recently found both recollective and novelty effects in hippocampus, but with different latencies (Staresina et al., 2012): An early, pre-recognition-decision LY294002 in vivo recollection effect and a later, post-recognition-decision novelty effect, which would simply summate to produce the U-shaped pattern in the magnitude of the BOLD response (at least, using the standard fMRI analysis Janus kinase (JAK) employed here). The present fMRI findings reinforce these previous findings, and go further in that the lack of an effect

of conceptual priming in hippocampus, in contrast with that found in the parietal regions, further supports a functional dissociation between the roles of hippocampus and parietal cortices during recollection/recall (Ramponi et al., 2011). The regions showing greater BOLD responses for K Hits than Correct Rejections are broadly consistent with many previous fMRI studies of the basic “old-new” effect, particularly in that they appeared to be driven by the distinction between Hits and Correct Rejections, rather than between Remembering and Knowing. Most notable in this respect are the more superior parietal regions, which concur with many previous dissociations between inferior and superior parietal activations during recognition memory (Wagner et al., 2005; Cabeza et al., 2008). Nonetheless, it should be noted that Hits and Correct Rejections differ not only in the study status of the target item, but also in the “old-new” decision given (and possibly perceived “targetness”; Herron et al., 2004).

The word was preceded by a central fixation cross for one of 400,

The word was preceded by a central fixation cross for one of 400, 600, or 800 msec (selected from a random uniform distribution) and followed by a blank screen for 1000 msec. On Test trials, participants performed a yes/no recognition task: They read a centrally presented

word (see Fig. 1 for stimulus timing) and first indicated whether they thought it had (old) or had not (new) appeared previously in a Study trial. If they responded “old”, they were then prompted to decide whether they remembered seeing the test cue (“R” judgment) or whether they simply felt that the item was familiar (“K” judgment; instructions are described below). Note that we used the label “familiar”, rather than the traditional “know” judgment, for reasons given in Footnote 1. Response times (RTs) were recorded;

however, accuracy was emphasized over speed. If the participant responded “new” to the test cue, or if they failed to respond (time Selleck CHIR 99021 limit = 2000 msec), then they were prompted (“Left/Right”) to randomly press one of the response keys. This helped match the timing and motor demands of “old” and “new” trials (over which the fMRI response averages). Critically, each test cue (“target”) was preceded by a brief, masked prime word. In the Conceptual Priming condition, the prime and target were either conceptually related or unrelated; in the Repetition RG7422 Priming condition, the prime and target were either the same word or unrelated words, as described in Stimuli, above. Primes were presented in lower case and targets in upper case, to minimize visual overlap on Repetition priming trials. Before entering the MRI scanner, participants were given task instructions

and completed a brief practice session (eight Study and 16 Test trials). The instructions, based on Rajaram (1993), described the Remember/Familiar distinction as follows: “Respond REMEMBER if you recollect GABA Receptor the event of seeing the word, some aspect of the context (how the word looked, what it made you think or feel, etc.). Respond FAMILIAR if you are certain you saw the word previously but you cannot recollect any contextual details.” At the end of the practice trials, participants were asked to recall the instructions and explain the difference between the Remember and Familiar response categories; any confusion was resolved by repeating the relevant part of the instructions. For example, if the participant seemed to equate Remember/Familiar responses with high/low confidence, the experimenter suggested that high-confidence Familiar responses were possible, such as when one is sure the word was presented previously but no contextual details of the event of seeing the word could be recalled. The experiment consisted of four cycles of interleaved Study and Test blocks, all conducted during functional MRI scanning. Each Study block (duration: approximately 2.

Flt-1 baseline level of CA1 and CA2 neurons occupied the intermed

Flt-1 baseline level of CA1 and CA2 neurons occupied the intermediary position relative to CA3 and DG; CA1 and CA2 neurons showed quite the same baseline distribution pattern of Flt-1. In all four regions the expression of Flt-1 at basal level was visibly higher in P14 rats than in 8–10 wks rats. In Etoposide cost animals of both ages i.p.-injected with PNV there was immediate upregulation of the level of Flt-1 expression in all the four hippocampal regions studied. CA1 and DG were the regions with most dramatic rise of Flt-1 expression 1 h after injection: Flt-1 level of PNV-exposed rats was upregulated by 90% in CA1, 135% in DG whereas CA2 and CA3 just showed a trend for rising. Also, it is of interest to observe

that CA1 and DG neurons of animals of both ages displayed a similar time-course changes of the VEGF’s Flt-1 receptor density of pixels (compare Fig. 4A and D). Likewise, neurons of CA2 and CA3 in animals of both ages showed quite the same pattern of time-course changes in their immunolabeling (compare Fig. 4B and C). In animals of both ages, the neurons of CA2 were the least susceptible to change the expression of Flt-1 receptor (Fig. 4B). The two-way analysis of variance showed that there was interaction between time after PNV injection versus age of animals for CA3 and DG in relation to the expression of the receptor. The Flt-1 expression was

influenced by the two variables “time after envenoming” and “age of animals” in all the four regions scanned. To investigate a potential involvement of the vascular endothelial growth factor (VEGF) in the neurotoxic effects caused by P. nigriventer venom in the hippocampus, find more we analyzed whether the expression of VEGFR-1, also named Flt-1, was changed after i.p. administration of venom. Using immunohistochemistry for the Flt-1 it was possible to determine that neurons were the principal cells constitutively expressing the receptor and that anti-Flt-1 was immunodetected in the nucleus of neurons; by immunohistochemistry labeling the distribution

and expressional level of Flt-1 was demonstrated in all the four selected regions of the hippocampus: CA1, CA2, CA3 and DG. Nuclear location of Flt-1 has been found in the dorsal root AZD9291 datasheet ganglion sensory neurons ( Dhondt et al., 2011), ventral root motor neurons ( Poesen et al., 2008), and lumbar motor neurons ( Islamov et al., 2004) and others. In hippocampus, Flt-1 mRNA is restricted to pyramidal neurons of CA regions and granular neurons of DG ( Choi et al., 2007). In all these regions the upregulation of Flt-1 has been associated with neuroprotective signals mediating VEGF effects in different injury conditions. Herein, the investigation was focused on hippocampus as one of the brain regions particularly targeted by PNV as has been shown by our laboratory (Le Sueur et al., 2003; Rapôso et al., 2007; da Cruz-Höfling et al., 2009). These previous studies have shown that the i.v.