Approximately 300 genes are identified that are involved in codin

Approximately 300 genes are identified that are involved in coding ECM proteins in mammals by searching domains characteristic to ECM molecules through the whole genome sequence [52]. The total number of ECM molecules corresponds to about 1.5% of proteasomes, a list of all proteins expressed by the genome. ECM proteins typically consist of repeated domains, which are coded in Ibrutinib mouse the genome as separate

exonic units and evolve through multiple processes such as exon duplication and shuffling, and gene duplication and conversion [53] and [54]. Analyses of the genomes in different organisms suggest that some ECM molecules in mammals retain ancient forms, which are found in all metazoans, while some are derived from newer proteins. Mineralization is one of the hallmark processes that has taken place during vertebrate evolution. Three major mineralized tissues, enamel, dentin, and bone, have evolved over 500 million years likely from a common ancestral process [55]. The genes for enamel matrix proteins expressed Trichostatin A datasheet by ameloblasts, AMEL, ENAM, AMBN, AMTN, and Apin/ODAM, have evolved from a common ancestral gene encoding an SCPP [56] and [57]. Enamel matrix genes are clustered on human chromosome 4q13. However, AMEL is located on sex chromosomes. AMELX and AMELY are located on the X and Y chromosomes, respectively. About 90% of the AMEL transcripts are expressed on the X locus. SCPP family genes are also mapped on

human chromosome 4. Analysis of the enamel matrix genes in different species has shown that ENEM is the most ancient gene and the other four enamel genes are derived from ENEM. AMEL is derived from AMBN and was later translocated to sex chromosomes [57]. The chromosomal synteny of these genes is conserved in primates and rodents. In birds, which lost their teeth about 100 million years ago, the enamel matrix gene cluster is lacking [58]. Initially, enamel

matrices were identified as enamel-specific molecules. However, the expression of enamel matrix proteins has been shown in other tissues outside of the tooth germ as a result of improved sensitivity in detection analyses. Furthermore, the overexpression or knockdown of these matrices not only causes enamel Oxymatrine defects, but also aberrant tooth roots, bone formation, and tumor phenotypes. The enamel matrix proteins are evolutionally related, but have distinct functions. The newly identified activities of enamel matrix proteins will provide a better understanding of the mechanisms of craniofacial development, including enamel, dentin, and craniofacial bone formation. This work was supported by grants-in-aid (20679006 to S.F., 21792054 to A.Y., 21792154 to E.F.) from the Ministry of Education, Science, and Culture of Japan, the NEXT program (LS010 to S.F.), and by grants from the Intramural Program of National Institute of Dental and Craniofacial Research, National Institutes of Health to Y.Y.

Even though for normal dentin, the mild acidity of self-etch syst

Even though for normal dentin, the mild acidity of self-etch systems is not sufficiently effective in the dissolution of smear plugs, therefore smear plugs are retained in the dentinal tubules as part of the hybridized complex with less resin tag formation. In this situation, lateral penetration of the adhesive

monomers from the dentinal tubules could not contribute to hybrid layer formation of self-etch adhesives. Therefore, for self-etch systems, the presence of mineral deposits in dentinal tubules would not be an important reason why caries-affected dentin causes less penetration of adhesive monomers, leading to Epigenetics Compound Library nmr lower bond strength than normal dentin, but a deeper mineralized zone would be the main reason. On the other hand, in the case of self-etch systems, the dentin smear layer would affect penetration of the adhesive monomers into the underlying dentin. Several studies using normal dentin have demonstrated that dentin smear layer characteristics have been reported to compromise the bonding efficacy of self-etch systems. The smear layer on dentin is composed of disorganized collagen debris binding submicron mineral particles

[33] and [34]. The smear layer of caries-affected dentin is thick and irregular, and appears to be enriched with organic components compared with that of Dinaciclib cell line normal dentin [36] and [37]. The disorganized collagen and/or

the mineral trapped within the gelatinized collagen cannot be easily removed even when etched with phosphoric acid [43]. The disorganized collagen and the gelatinous layer within the smear layer may hinder resin monomer infiltration and prevent a perfect seal at the resin–dentin interface [34] and [43]. Therefore, the caries-affected dentin smear layer enriched with organic components would contribute to the inferior adhesion of self-etch adhesives to caries-affected dentin (Fig. 7). Sodium hypochlorite solution (NaOCl) can effectively dissolve organic substrates from biological materials. Taniguchi et al. [36] demonstrated that NaOCl treatment of smear layer-covered caries-affected Inositol monophosphatase 1 dentin eroded and thinned the smear layer due to dissolution of superficial organic components of smear layer (Fig. 8). Furthermore, they reported that pretreatment with 6% NaOCl for 15 s could significantly improve the bond strengths of 1-step and 2-step self-etch system to caries-affected dentin, while NaOCl-30 s pretreatment did not affect them [36]. On the other hand, for normal dentin, NaOCl-15 s pretreatment did not alter the bond strengths, but NaOCl-30 s pretreatment reduced them [36].

The carbonyl content was determined as previously described by Sm

The carbonyl content was determined as previously described by Smith (1967). A dry sample (4 g) of starch was dispersed in distilled water (100 ml) and heated in a boiling water bath for 30 min. The solution was

continuously stirred until the starch was completely gelatinised. The gelatinised samples were kept at 40 °C. The pH value was adjusted to 3.2 with 0.1 M HCl, and 15 ml of a hydroxylamine chloride solution was then added. The hydroxylamine reagent was prepared by dissolving 25 g of reagent grade hydroxylamine chloride in water and adding 100 ml of 0.5 M NaOH; distilled water was then added to reach a final volume of 500 ml. The samples were covered with plastic film and placed in an oven at 38 °C for 4 h, check details and they were then rapidly titrated to a pH value of 3.2 with 0.1 M HCl. The carbonyl content was expressed as the quantity of carbonyl groups per 100 glucose units (CO/100 GU) as calculated by Eq. (1). equation(1) CO/100GU=(Vb-Vs)×M×0.028×100Wwhere Vb is the volume of HCl used for the blank (ml), Vs is the volume of HCl required for the sample (ml) M is the molarity of HCl, and W is the sample weight (d.b). The carboxyl content was determined according to the method previously described by Parovuori, Hamunen, Forssell, Autio, and Poutanen (1995). A dry sample

(5 g) of starch was dispersed in distilled water (25 ml). The dispersions were stirred for 30 min and then centrifuged. Quisqualic acid The residue was washed with distilled water, and 300 ml of distilled water was then added to the residue. The dispersion was heated in a boiling water bath with selleckchem continuous stirring for 30 min until the starch was completely gelatinised. While still hot, the samples were titrated to a pH value of 8.2 with 0.01 M NaOH. The carboxyl content was expressed as the quantity of carboxyl groups per 100 glucose units (COOH/100 GU) as calculated by Eq. (2).

equation(2) COOH/100GU=(Vs-Vb)×M×0.045×100Wwhere Vs is the volume of NaOH required for the sample (ml), Vb is the volume of NaOH used to test the blank (ml), M is the molarity of NaOH, and W is the sample weight (d.b). The swelling power and solubility of the starches were determined as described by Leach, McCowen, and Schoch (1959). Samples (1.0 g) were mixed with 50 ml of distilled water in centrifuge tubes. The suspensions were heated at 90 °C for 30 min. The gelatinised samples were then cooled to room temperature and centrifuged at 1000g for 20 min. The supernatants were dried at 110 °C until a constant weight was achieved so that the soluble fraction could be quantified. The solubility was expressed as the percentage of the dried solid weight based on the dry sample weight. The swelling power was represented as the ratio of wet sediment weight to initial dry sample weight (deducting the amount of soluble starch).

This cycle was repeated until the enzymatic activity become null

This cycle was repeated until the enzymatic activity become null. The influences of pH and temperature on β-glucosidase activities were determined using the standard assay for the free and immobilised enzymes, except that the pH values were modified to a range of 2.0–8.0 (Mcllvaine, 1921) and the temperature values Selleck MAPK Inhibitor Library ranged from 10 to 60 °C. The pH stability

of β-glucosidase was determined by incubating the free enzyme solution or the alginate beads in the pH range of 2.0–8.0 for 30 min, on ice. After incubation, the mixture was used for determining residual activity, according to standard assay, using pNPβGlc as the substrate. Thermal stability was investigated by incubating the enzymatic solution or the alginate beads in 50 mM sodium phosphate buffer, pH 6.0 or 5.5, respectively, at temperatures of 45 and 50 °C for different times. After pre-incubation, aliquots of the enzymes or 4 alginate beads were collected and submitted to the standard DZNeP concentration assay, measuring the remaining activity. The relative activities were calculated in

relation to β-glucosidase activity without pre-incubation, which was considered to be 100%. Results of the analyses are presented as mean ± SD for three measurements. The Michaelis–Menten constant (KM) and Vmax for substrate hydrolysis by the free enzyme and the KMapp value for the immobilised enzyme were calculated by the Michaelis–Menten plot. Concentrations of pNPβGlc varied from 0.2 to 5.0 mM. The inhibition Dipeptidyl peptidase constant (Ki) for the free enzyme using glucose as inhibitor was determined by varying the pNPβGlc concentrations from 0.05 to 1.2 mM in the presence of 50, 100 or 120 mM of glucose. Enzymatic assays were performed with various synthetic, natural and polymeric substrates. The reaction mixtures contained 650 μL of 50 mM sodium phosphate buffer pH 6.0, 0–100 μL of enzyme solution and 250 μL of synthetic substrates (0.5 mM)

or celobiose, lactose, maltose, gentiobiose, melibiose and sucrose (2.5 mM) or cellulose (0.025%). Activities were measured under standard assay conditions at 40 °C. The data presented for all enzyme activity determinations are mean values ± SD of three measurements. The effects of ions, simple sugars and reducing agents on enzyme activity were assayed by the standard methods. Reaction mixtures contained 450 μL of 50 mM sodium phosphate buffer pH 6.0, 0–100 μL of the enzyme solution and 200 μL of the compounds (0.2 and 2 mM). The data presented for all enzyme activity assays are mean values ± SD of measurements performed in triplicate. The soy molasses samples were kindly donated by Melaços Brasileiros Ltda., Saltinho, São Paulo, Brazil. One gram samples of soy molasses were incubated with either 10 U of free β-glucosidase in 50 mM sodium phosphate buffer pH 6.0 (10 mL) or with a calculated number of beads corresponding to 10 U of β-glucosidase in 50 mM sodium phosphate buffer pH 5.

Volatile components were identified by comparing a private librar

Volatile components were identified by comparing a private library spectra, built with chemical standards, and the spectral library (NIST 98 /EPA/MSDC 49 K Mass Spectral Database, Hewlett–Packard Co., Palo Alto, CA, USA). When available, MS identifications were confirmed by comparing GC retention times with pure standards. Total RNA was extracted according to manufacturer’s instructions (Pure Link, Invitrogen®). For RT- PCR, DNase-treated RNA (2 μg) was reverse transcribed in find more a total volume of 20 μl using Omniscript Reverse Transcription Kit (Qiagen, Valencia, CA, USA) and then PCR was performed using 2 μl of cDNA in a 25 μl reaction

volume using SYBR GREEN PCR Master Mix (PE-Applied Biosystems, Foster City, CA, USA) on an ABI PRISM 7500 sequence-detection system. Primer Express software (Applied Biosystems) was used to design gene-specific primers ( Table 1). Fourteen genes were chosen based on putative roles in strawberry quality traits, such as cell wall disassembling (Exp2 from Civello, Powell, Sabehat, & Bennett, 1999; Exp5 from Harrison, McQueen-Mason, and Manning, 2001; PLa, PLb and PLc from Benítez-Burraco et al., Gefitinib 2003;

PME from Castillejo, Fluente, Iannetta, Botella, & Valpuesta, 2004; PG from Redondo-Nevado et al., 2001; and β-Gal from Trainotti et al., 2001), phenolic and anthocyanin compounds synthesis (PAL from Usami, Kantou, & Amemiya, 2007; and ANS from Almeida et al., 2007), ascorbic acid synthesis (LGalDH from Gatzek, Wheeler, & Smirnoff, 2002; and GLDH from Pineau, Layoune, Danon, & De Paepe, 2008) and esters synthesis (ADH from Longhurst et al., 1990; AAT

from Aharoni et al., 2000). Optimal primer Digestive enzyme concentration was 50 nM. Real time-PCR conditions were as follows: 50 °C for 2 min, 95 °C for 10 min, followed by 40 cycles of 95 °C for 30 s, 60 °C for 1 min, 72 °C for 1 min, and one cycle 72 °C for 5 min. Samples were run in triplicate on a 96-well plate. For each sample, a Ct (threshold cycle) value was calculated from the amplification curves by selecting the optimal ΔRn (emission of reporter dye over starting background fluorescence) in the exponential portion of the amplification plot. Relative quantitation (RQ) was calculated based on the comparative Ct method ( Livak & Schmittgen, 2001), using β-actin ( Almeida et al., 2007) as an internal standard. All experiments were done in triplicate. Data was analysed using analysis of variance (ANOVA) and means comparison using Tukey’s test at P ⩽ 0.05 using SAS. Transcript accumulation of Exp2 and Exp5, and of genes encoding enzymes acting in cell wall disassembly (PLa, PLb, PLc, PME, PG and β-Gal) was monitored in order to understand the role of these putative genes during the development of strawberry. Firmness decreased over time during fruit development; descending from 26.5 N at stage 1 (green, 3.0 g ± 0.9) to 2.7 N at stage 5 (red, 16.2 g ± 1.2) ( Fig. 1A).

We would also like to thank Xiaoliu Zhou, Tao Jia, and Ryan Henni

We would also like to thank Xiaoliu Zhou, Tao Jia, and Ryan Hennings for measuring the urinary BPA concentrations. “
“Perfluoroalkyl acids (PFAAs) have gained considerable attention as environmental LDN-193189 purchase pollutants due to their persistence, their bioaccumulative potential (Kelly et al.,

2009 and Martin et al., 2004b) and their toxic properties. They have been associated with liver toxicity and developmental toxicity in laboratory animals (Lau et al., 2007), and immunotoxicity in both laboratory and wild animals (DeWitt et al., 2012 and Kannan et al., 2006). PFAAs are released into the environment, both directly from manufacturing and indirectly through products such as surfactants and surface protectors (Paul et al., 2008 and Prevedouros et al., 2006). Due to their unique properties of being both water and oil repellent, perfluoroalkyl and polyfluoralkyl substances are extensively used in a wide range of industrial and consumer applications, such as nonstick coatings on cookware, some waterproof clothes, and in fire-fighting

foams. Two fluorinated compound classes, the perfluorinated carboxylic acids (PFCAs) and sulfonic acids (PFSAs) have been studied substantially in recent years. Members of both classes are globally distributed and have been detected in wildlife as well as in humans (Gamberg et al., 2005, Giesy and Kannan, 2001, Houde et al., 2011, Kannan et al., 2001 and Kärrman et al., 2007). In addition to direct emission, several precursor compounds have been identified as an indirect source of PFCAs and PFSAs in environmental matrices PCI-32765 supplier (Young and Mabury, 2010). So far, perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) have been subjected

to most attention as they are among the most toxic PFAAs (Kudo and Kawashima, 2003 and Lau et al., 2004) and have been found at relatively high levels (Houde et al., 2006b). In 2009, PFOS was added to the Stockholm convention list of persistent organic pollutants (Stockholm Convention on Persistent Organic Pollutants, 2009) and the largest producer of PFOS-based products, the 3M company, phased out their production by 2002 (3M, 2000). The replacement compound for PFOS is perfluorobutane sulfonate (PFBS) (3M, 2002), Telomerase which seems to be less potent in rat toxicity tests (Lieder et al., 2009) and has a shorter half-life in human and rat serum (Olsen et al., 2009) than PFOS. However, compared to PFOS and PFOA, the bioaccumulation and toxicity of PFBS have been less investigated, although the literature is increasing. The wild American mink has been acknowledged as a useful sentinel species for chemical pollution and related health effects (Basu et al., 2007 and Persson et al., 2012). The arguments are mainly that it is a semi-aquatic top predator with a widespread distribution and it can, especially where it is an invasive species, be captured in large numbers.

As our results indicated, sometimes the opposite can occur Such

As our results indicated, sometimes the opposite can occur. Such trends in the evaluation data set are difficult to account for, because they cannot simply be corrected by a plot-specific adjustment of the intercept term. Height growth differences in this study ranged from 0.01 to 0.12 m year−1. These results are consistent with similar research. Height increment bias previously reported ranged from 0.01 to 0.30 m year−1 (Sterba et al., 2001 and Härkönen et al., 2010). As with diameter increment, temporal or spatial trends or size effects can occur. Our results indicate that differing height growth patterns can partly be attributed to an incorrect shape

of the site-index function. For example, the particularly good prediction Selleck Ribociclib results for spruce in Arnoldstein with the growth model Moses result from a run with the site-index functions of Assmann and Franz (1965). These site-index functions are known to very closely match the height growth patterns in Arnoldstein. In contrast, we did not find any spruce yield table that adequately represents dominant height growth in Litschau. Even though the model run with spruce “Hochgebirge” was better than with any other yield table, bias still remained. FK228 molecular weight Another example is Prognaus: comparing the height growth patterns resulting from the Prognaus

height increment model ( Nachtmann, 2006) to the height growth patterns in Arnoldstein and to the yield tables of Assmann and Franz (1965) showed

that the Prognaus height increment pattern was notably too steep at advanced ages, resulting in biased predictions. In contrast, observed and predicted height growth patterns for Prognaus were nearly identical in Litschau, resulting in a good performance. Therefore, an appropriate curve form for a particular region is crucial to correctly predict height growth. Whereas the shape of the site-index curves is routinely examined before the application of a yield table for a region, evaluations of forest growth models so far have mostly focused on overall bias, ignoring shape. In individual-tree growth models that derive potential height increment from yield tables, often only one curve form per species is implemented (e.g. BWIN, and the first version of Moses). The assumption of one Phosphoribosylglycinamide formyltransferase curve shape per species is certainly too stringent, since it is known that the pattern of height growth can vary considerably for different climatic regions, vegetation types, soils, or degrees of competition ( Stage, 1963, Monserud, 1984 and Sterba and Eckmüllner, 2009). Here, a modification that allows for different site-index curves (e.g. Kindermann and Hasenauer, 2005) may help to solve this problem. Site-index functions developed from site factors appear flexible enough to represent different height growth patterns (Prognaus and Silva).

In relation to plant species (Fig 4), average and total herb and

In relation to plant species (Fig. 4), average and total herb and

tree species richness were both highest in pine plantations (in total 31 and 11 species, respectively), followed by mixed forests (in total 26 and 10 species, respectively), while average and total shrub diversity was highest in birch (in total 6 species) forests. The lowest vascular plant species richness in all three layers both on average and in total was recorded in oak forests (in total 19 herb, 2 shrub and mTOR inhibitor 4 subdominant tree species). Analysis of the community composition of carabid assemblages (Fig. 5) reveals that the pine plantation and oak forest harbour distinct communities relative to the other forest types. Furthermore, it is apparent that oak, pine and mixed forests show greater heterogeneity in community composition and therefore a higher species turnover between plots than the other forest types. By contrast, birch and larch forest plots show relatively little variation in the species composition. The environmental parameters investigated in this study (Table 1) exerted only a limited amount of control over the beetle distribution patterns, with the first two RDA axes explaining only 16.2% and 5.9% of species variation, respectively. Both canopy cover and dry weight of the litter layer exerted

some influence, with larch and birch forests being characterised by a high amount of litter and open canopies (Fig. 6). Oak and Ureohydrolase pine forests were both characterised by closed canopies, but oak forest litter buy Ruxolitinib had a lower relative dry weight. Mixed forests were most heterogeneous in relation to environmental parameters, mirroring the high levels of heterogeneity observed in carabid species composition between samples in this forest type. Most carabid species are clustered towards the centre of the RDA plot. The abundances of some of these species are likely too low to result in a clear environmental response pattern, while

other species may be unaffected by the recorded variables or prefer intermediate environmental settings. However, all five dominant species are clearly associated with distinct habitat conditions. C.vladimirskyi associates strongly with high canopy cover and low leaf litter mass that characterises oak forest samples, while C. crassesculptus also associates strongly with high canopy cover, but only intermediate leaf litter mass and low ground cover. By contrast, P.acutidens has a strong association with open canopies and a high leaf litter mass. P.adstrictus and C.manifestus associate with intermediate values of these parameters. Furthermore, Synuchus sp. and Harpalus coreanus (Tschitscherin, 1895) are notable due to their association with higher ground vegetation cover values.

Finally, the average microhap heterozygosity globally should be g

Finally, the average microhap heterozygosity globally should be greater than any of the SNPs alone can achieve. Over the past decade we have accumulated SNP genotype data at multiple genomic regions for 50+ Duvelisib datasheet populations. In many of those regions the SNPs are densely packed with many SNPs within the targeted expanse. We used these genotypes already available on our set of 40+ populations as pilot data. Based on these analyses we then applied an average heterozygosity of >0.4 as an additional criterion when screening the Human Genome Diversity Project dataset [29] and the HapMap integrated (phases 1 + 2 + 3) dataset [30] for candidate microhaps.

These searches identified many candidate microhap loci; we have subsequently genotyped a few of the most promising of these as individual SNPs by TaqMan and statistically phased the genotype data into haplotypes. Those with the highest global average heterozygosity have been included in this study. During the course of our studies Nakahara et al. [28] presented a set of microhaps identified and studied in Japanese. We tested

one of them (COG2) and found it met our global criteria for the current panel; we have not tested the others. Everolimus solubility dmso We note that while the ultimate objective is a panel of microhaplotypes for typing by sequencing, this initial characterization and selection of candidate loci is more efficiently and economically done with individual SNP typings, using preexisting data and new typings by TaqMan. The 54 populations studied, organized by geographical region of the world, are listed in Supplemental Table S1 along with

the sample size for each and the Sample UID in ALFRED [19] for additional information. These are the same population samples used in multiple publications [1], [2], [6], [17], [24], [31] and [32]. Collectively, these populations originate from most major regions of the world and include Histone demethylase a total of 2530 individuals of which 349 constitute about a third of the HGDP panel of around 1000 individuals. Table S1.   The 54 populations studied organized by geographical region. Column ABBREV shows the 3-character abbreviation employed in some figures and tables. Column Population UID holds the unique population identifier in ALFRED; Column Sample UID has the unique sample identifier in ALFRED. The DNA used has been extracted from lymphoblastoid cell lines. All individuals were typed with TaqMan assays from the Applied Biosystems Assays on Demand catalog. Typing was done in 3 μl reactions in 384-well plates using the manufacturer’s protocol. Following PCR in separate thermocyclers the plates were read using an AB7900 and the SDS software. Failed reactions were repeated once. In general, data were complete for >96% of individuals for each of the 66 SNPs (on average 98.9% complete).

There is evidence from animal models that ventilatory failure is

There is evidence from animal models that ventilatory failure is associated with a failure of voluntary motor drive (Ferguson, 1994 and Sassoon

et al., 1996), and recent human data suggest that maximal central neural output cannot be achieved during exercise either in COPD (Qin et al., 2010) or other pulmonary conditions (Reilly et al., 2011). We hypothesized that the abnormalities in corticospinal transmission that we had previously observed in patients with COPD would be more pronounced in patients who required NIV but this was not confirmed, with no significant difference observed in any TMS parameter assessed. Because the NIV patients had been successfully established on ventilation for several months (and had therefore much improved arterial blood gas parameters) Roxadustat clinical trial we cannot exclude the possibility that predisposing cortical factors present at the initiation of therapy had been reversed by ventilator use. The issue is further complicated by the fact that nocturnal NIV itself alters daytime blood gas parameters that might themselves alter the response to TMS. Further studies SCR7 cell line undertaken before and after the initiation of therapy would be required to clarify this. During the part of the study where the acute effect

of NIV was assessed we maintained PetCO2 at its baseline value as we wanted to assess the neuromechanical effect of mechanical ventilation alone rather than in combination with any possible chemical effect. This of course differs from conventional ventilator use which by increasing minute ventilation

and recruiting alveoli should produce a reduction in PaCO2 as well as an increase in PaO2. A related issue is the problem of distinguishing cortical from brainstem and spinal influences on the response Interleukin-2 receptor to TMS. The observation that the diaphragm response to TMS is the same in normocapnic as in hypocapnic conditions, when the respiratory oscillator is assumed to be silent and also that the response is similar during volitional and hypercapnia driven hyperventilation has been taken as evidence that the corticospinal pathways ‘bypass’ the brainstem (Corfield et al., 1998 and Murphy et al., 1990). However, phrenic spinal motor neurons are distinctive in having an ‘automatic’ bulbospinal input as well as a volitional, ‘higher’ corticospinal one, so that their output is dependent both on the amplitude of the corticospinal volley and the output from brainstem respiratory centers. Thus it has been argued that the increase in diaphragm MEP observed during hypercapnia driven hyperventilation is a consequence of an increased brainstem output pre-activating spinal motor neurons rather than an increased cortical response (Straus et al., 2004).