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From a different perspective, other

studies have in investigated the antioxidant effect of creatine supplementation. In a cell-free experiment, the ability of creatine to quench reactive oxygen and nitrogen species, such as H2O2 and ONOO−, in muscle homogenates was observed [5]. On the other hand, the first study reporting antioxidant activity related to creatine supplementation in living cells was performed by Sestili and colleagues in 2006 [6]. However, few studies have assessed the antioxidant effect of creatine supplementation in biological systems, such as in humans or animals. A recent study pointed out the pleiotropic effects of creatine and its possible direct antioxidant effect in scavenging Reactive Oxygen Species (ROS) and Reactive Nitrogen Species (RNS) [7]. Oxidative stress and the subsequent damage to lipids, proteins and nucleic acids in acute response to aerobic exercise is well established CB-5083 in the literature [8–10]. In the same way, some studies have demonstrated an oxidative response

when resistance exercises are performed [11–13]. Since systematic training can lead to increases in the activity of antioxidant enzymes (modulated by exercise adaptations) [14], it is still not clear whether Resistance Training (RT) can attenuate the acute oxidative damage experienced after exercise. Moreover, until now, there have been few studies that have evaluated the learn more effect of creatine supplementation on resistance training Terminal deoxynucleotidyl transferase maximum strength gain and oxidative stress. Considering this, it is not clear whether creatine supplementation exerts intra and/or extracellular antioxidant effects and it plays a synergistic role in the adaptation of antioxidant enzymes associated with RT. Thus, the aim of this study was to evaluate the effects of monohydrate creatine supplementation associated, or not, with RT on oxidative stress and antioxidant enzymatic activity in the plasma, the heart, the liver and the gastrocnemius of rats. Materials and methods Animals Forty

male Wistar rats (250 to 300 g; 90 days old) from the UFCSPA Breeding Unit were divided into four groups: selleck products Sedentary (SED, n = 10), Sedentary + Creatine (SED-Cr, n = 10), Resistance Training (RT, n = 10) and Resistance Training + Creatine (RT-Cr, n = 10). The animals were housed under standard conditions (food and water ad libitum, temperature between 22 and 24°C, light–dark cycle of 12 hours). The handling of the animals obeyed Law nº 11,794 of 10/08/2008, Law nº 6,899 of 07/15/2009, and Resolution nº 879 of 02/15/2008 (CFMV), as well as other provisions applicable to the use of animals for teaching and research, in particular the resolutions of the National Council on Animal Experimentation. This study was approved by CEUA/UFCSPA, under the protocol number 060/11.

pylori strains. CCUG 17874 untreated SB273005 bacteria (Figure 2A) show homogeneous cytoplasm and rare membrane/cytoplasm detachments (arrow). M/C-R2 untreated bacteria (Figure 2B) show homogeneous cytoplasm, flagella and vesicles (arrow). CCUG 17874 bacteria treated with polysorbate 80 (Figure 2C) are swollen and

morphologically altered; cytoplasm is granular and detached from the inner membrane (arrow head); vesicles (arrow) are present. M/C-R2 bacteria treated with polysorbate 80 (Figure 2D) are swollen and morphologically altered; cytoplasm is not homogeneous and numerous vesicles are present (arrow). CCUG 17874 bacteria Selleck BKM120 treated with clarithromycin (Figure 2E) show altered shape, typical

“holes” in the cytoplasm (arrow head), membrane/cytoplasm detachment (arrows) and fragments of flagella. Some M/C-R2 organisms treated with clarithromycin (Figure 2F) have a conserved morphology, others LEE011 mw show granular cytoplasm and altered membranes. Flagella and vesicles (arrows) are present. CCUG 17874 bacteria incubated with metronidazole (Figure 2G) are severely altered and show detachment of cytoplasm, often fragmented, from inner membrane (arrows). M/C-R2 bacteria treated with metronidazole (Figure 2H) are morphologically similar to control. CCUG 17874 treated with polysorbate 80 and clarithromycin (Figure 2I) displays alterations typical of organisms treated with the two substances used alone: swollen cells and detachment

membrane/cytoplasm (arrow). M/C-R2 bacteria treated with polysorbate 80 and clarithromycin (Figure 2J) are Glutamate dehydrogenase mostly swollen, their cytoplasm is granular and numerous vesicles are present (arrows). CCUG 17874 strain treated with polysorbate 80 and metronidazole (Figure 2K) displays swollen bacteria, granular cytoplasm, presence of vesicles (arrows) and detachment of fragmented cytoplasm from the inner membrane (arrow head). M/C-R2 bacteria treated with polysorbate 80 and metronidazole (Figure 2L) are swollen; cytoplasm is granular and displays the presence of “holes”. Vesicles are present (arrows). Bars 2A-L: 1000 nm. To examine the ultrastructural characteristics of the organisms treated with the studied substances, the bacteria were incubated overnight with the single drugs and with antibiotics associated with polysorbate 80 at concentrations corresponding to the respective MBCs. In both strains treated with polysorbate 80 (Table 3), we observed swollen bacteria and alterations of the outer membrane (Figures 2C, 2D), particularly evident in CCUG 17874 H. pylori strain. The cytoplasm showed a typical granular texture; in both strains, we noted the presence of vesicles, which were more numerous in C/M-R2 strain. The two strains challenged with clarithromycin showed different ultrastructural alterations. CCUG 17874 H.

Blood was centrifuged at 460 g for 8 min at

room temperature. After centrifugation, 3 components were obtained: red blood cells, a thin layer of leukocytes referred to as “buffy coat” and plasma. The 1 ml plasma fraction located above the red cell fraction, but not including the buffy coat, was collected. Determination of platelet and leukocyte count Platelet concentration in whole blood and P-PRP was counted automatically using a hematology analyzer (Sismex XE-2100, Norderstedt, GER). To evaluate the purity of P-PRP, we have also performed a white blood cells count both in whole blood and P-PRP. According to Anitua et al. [8], leukocyte levels in P-PRP must be lower than in whole blood (< 103/μl). Activation of P-PRP P-PRP was activated shortly before use. In order to initiate clotting and trigger the release of platelet content, CaCl2 was added (50 μl per ml of P-PRP). Bacterial strains Clinical isolates collected from patients Q-VD-Oph solubility dmso with oral

and dental infectious diseases have been used. Microorganisms were stored at −80°C before analysis. In particular, we selected the most representative microorganisms colonizing and affected the oral cavity belonging to gram positive, gram negative and fungi, such as E. faecalis (3 vancomycin-sensitive enterococcus (VSE) and 2 vancomycin-resistant enterococcus (VRE)), C. albicans, S. agalactiae, S. oralis and P. aeruginosa. This strains were previously selleckchem identified by biochemical identification (API system and Vitek2 Compact, Biomerieux, Marcy l’Etoile, France) and confirmed by DNA sequencing of about 80 pb of variable regions V1 and V3 of the 16S rRNA gene by Pyrosequencing (PSQ96RA, Diatech, Jesi, Italy). For each species, we used five strains isolated from different patients that presented dental abscesses. Each strain presented different characteristics (e.g. different antibiotic resistance). In addition, ATCC strains were used as control: E. faecalis ATCC #29212, C. albicans ATCC #928, S. agalactiae ATCC #13813, S. oralis ATCC #35037 and P. aeruginosa ATCC #27853. Before use, strains were thawed and

reconstituted in appropriate medium (e.g. Brain Heart Infusion broth why (BHI; Biomerieux, Marcy l’Etoile, France) additioned with 5% defibrinated blood) at 37°C for 24 hours. Determination of antibacterial activity The minimum inhibitory concentration (MIC), defined as the lowest concentration of an Epigenetics inhibitor antimicrobial substance that will inhibit the visible growth of a microorganism, was determined by broth microdilution method. After seeding in appropriate medium (Trypticase Soy Agar or Columbia Blood Agar; Biomerieux, Marcy l’Etoile, France), a suspension in BHI was prepared for each strain, with an optical density equal to 0,5 McFarland (1 × 108 CFU/mL). After obtaining a concentration of 1 × 104 CFU/mL using appropriate dilutions, 10 μl of each suspension were inoculated in a 96-wells microplate containing 100 μl of BHI and a serial dilution of activated P-PRP.

sp. BNC1 1 3 Chr Chr Methylobacterium this website extorquens AM1 1 4 Chr Chr M. radiotolerans JCM2831 1 8 Chr Chr M. nodulans ORS2060 1 7 Chr pMNOD2 Bradyrhizobium sp. BTAi1 1 1 Chr Chr Nitrobacter hamburgensis X14 1 3 Chr Chr Xantobacter autotrophicus Ry2 1 1 Chr Chr Abbreviations are as follows: Chr, chromosome of those Rhizobiales with one chromosome; Chr I and Chr II, chromosome I and chromosome II respectively

in those Rhizobiales harboring two chromosomes; p, plasmid. *Rhizobium species in which localization of panCB genes was done by Southern blot hybridization of plasmid profiles. †Plasmids with very similar electrophoretic mobility gave as result ambiguous plasmid PRIMA-1MET localization of panC and panB homologous sequences. Phylogenetic analysis of rhizobial panCB genes indicates a common origin of chromosomal and plasmid-borne sequences Two possible hypotheses

were considered to explain the presence of panCB genes in plasmids of R. etli and R. leguminosarum strains: (1) an intragenomic rearrangement of panCB genes from chromosome to plasmid, which must have occurred in the last common ancestor of both species; (2) by xenologous gene displacement, that is, a horizontal transfer event in which a gene is displaced by a horizontally transferred ortholog acquired from another lineage [16]. In the latter hypothesis we assume that the presence of these xenolog genes in plasmids conferred a selective advantage that may have eventually led to the loss of the chromosome-EX 527 cost located panCB genes. To test these hypotheses the phylogeny of 16 rhizobial species inferred from ten orthologous single copy housekeeping genes (fusA, guaA, ileS, infB, recA, rplB, rpoB, rpoC, secY and valS) located on primary out chromosomes, was

compared with the phylogeny of the same rhizobial species inferred from the panCB genes located on plasmids and chromosomes. The rationale for this comparison was that if the plasmid-borne panCB phylogeny agrees with the current phylogeny of the Rhizobiales, inferred from the housekeeping genes, it would support the hypothesis of intragenomic transfer of the panCB genes. On the other hand, if both phylogenies are incongruent, it would favor the hypothesis of horizontal transfer of the panCB genes. Concatenated nucleic acids multiple alignments were used to infer both phylogenies with the maximum likelihood method described in materials and methods. The resulting phylogenetic trees are shown in Figure 2. The housekeeping genes inferred tree (Figure 2a) was consistent with the recently reported phylogeny of 19 Rhizobiales performed on a data set of 507 homologous proteins from the primary chromosome [17]. Both trees are in close agreement with the phylogeny inferred from the panCB genes (Figure 2b). Thus the phylogeny of R. etli and R.

The two approaches are complementary: alone, neither achieves a complete description, but together, they offer good comparisons from which one may draw the firmest conclusions available regarding experimental devices. The second approach, dwelt upon in this work, also offers

descriptions of systems that should become available AUY-922 with improvements to the manufacturing processes mentioned above. As such, this is the focus of our discussion. Whilst single-monolayer studies converge properties by increasingly isolating the layers [11, 14, 16], at closer separations, it is impossible to divorce specific interactions between two layers from those between all of their (infinite) periodic replications. Further, effects arising due to atomic-scale mismatches in each layer’s doping locations cannot be seen when the neighbouring layer is a perfect replica. Building upon the methodology established whilst click here investigating single δ layers [16], expanded upon when

considering thicker layers comprised of multiple adjacent δ layers [19], and further extended to consider δ-doped nanowires [21], here, we model Si: δP bilayers, varying both their vertical separation (Figure 1a) and their relative in-plane alignment (Figure 1b). Figure 1 Model schematics. (a) Type-A bilayer system: tetragonal cell (lines), donors (P 1, P 2), periodic images (translucent circles), and effective donor PIK3C2G layers (translucent sheets). Varying separation within bilayers (arrows). (b) Second-layer dopant (in-plane) positions: P 1 projection (black circle), coplanar Si atoms (circles), type-A, -B, and -C positions, other monolayers’ atoms’ projections (dashed circles), and periodic boundary (square). Methods δ layers of P are created on Si (001) terraces before being epitaxially coated with further Si [24–27]. It is easy to envision this coating process being monitored and halted at

a desired buffer thickness, before a new δ layer of P is created (and/or patterned). Single δ layer findings [16] suggest that layers interact when less than 80 monolayers (approximately 10.9 nm) of silicon separate them, and that at 80 ML, their properties converge with ARRY-438162 order respect to silicon cladding depth. In that model, periodic replications of the layers were identical by construction, with no possibility of any deviation. Here, we explicitly allow for such differences by including a second layer in the model. c(2×2) cells including two δ-layers at N ML separation and 80 ML of Si cladding were built (N ∈ 4,8,16,40,60,80). Doping into a new layer can be accomplished at several locations [19]. For Nmod(4) = 0 systems, this can occur in three ways (Figure 1b): directly above the original dopant (type A), at either position nearest A in the plane (type B), or at maximal in-plane separation (type C).

When CENP-E is reduced to a larger extent, the accumulation of the signals may not

be sufficient to arrest mitosis, and cells possessing mitosis with large loss or gain of chromosome may suffer apoptosis or death.   Despite the fact that reduced expression of CENP-E protein was found in HCC tissues and could induced apoptosis and aneuploidy in LO2 cells, our results do not provide direct evidence that reduced expression of CENP-E can initiate hepatocarcinogenesis. However, this problem might be solved if we down-regulate the level of CENP-E to various Lazertinib degrees by constructing interfere vector or finding microRNA to target CENP-E, and investigate the relationship between the reduced CENP-E expression

and hepatocarcinogenesis. In a word, we found that CENP-E expression was reduced in HCC tissue, and reduced CENP-E expression could interfere with the separation of chromosome in LO2 cells. Conclusions Together with other results, these results reveal that CENP-E expression was reduced in human HCC tissue, and low CENP-E expression result in aneuploidy in LO2 cells. Acknowledgements We thank Drs. T-C He (The University of Chicago Molecular Oncology laboratory) for critically reading the manuscript. References 1. Jallepalli PV, Lengauer C: Chromosome segregation and cancer: cutting through the mystery. Nat Rev Cancer 2001, 1 (2) : 109–117.CrossRefPubMed Selleck MK-8776 2. Wassmann K, this website Benezra R: Mitotic checkpoints: from yeast to cancer. Curr Opin Genet Dev 2001, 11 (1) : 83–90.CrossRefPubMed 3. Cleveland DW, Mao Y, Sullivan KF: Centromeres and kinetochores: from epigenetics to mitotic checkpoint Bay 11-7085 signaling. Cell 2003, 112 (4) : 407–421.CrossRefPubMed 4. Chan GK, Jablonski SA, Sudakin V, Hittle JC, Yen TJ: Human BUBR1 is a mitotic checkpoint kinase that monitors CENP-E functions at kinetochores and binds the cyclosome/APC. J Cell Biol 1999, 146 (5) : 941–954.CrossRefPubMed 5. Chan GK, Schaar BT, Yen TJ: Characterization of the kinetochore binding domain of CENP-E reveals interactions with the kinetochore proteins CENP-F and

hBUBR1. J Cell Biol 1998, 143 (1) : 49–63.CrossRefPubMed 6. Mao Y, Abrieu A, Cleveland DW: Activating and silencing the mitotic checkpoint through CENP-E-dependent activation/inactivation of BubR1. Cell 2003, 114 (1) : 87–98.CrossRefPubMed 7. Lombillo VA, Nislow C, Yen TJ, Gelfand VI, McIntosh JR: Antibodies to the kinesin motor domain and CENP-E inhibit microtubule depolymerization-dependent motion of chromosomes in vitro. J Cell Biol 1995, 128 (1–2) : 107–115.CrossRefPubMed 8. Yao X, Anderson KL, Cleveland DW: The microtubule-dependent motor centromere-associated protein E (CENP-E) is an integral component of kinetochore corona fibers that link centromeres to spindle microtubules. J Cell Biol 1997, 139 (2) : 435–447.CrossRefPubMed 9.

**Classification of cefazolin as ‘active’ or ‘less active’: When difference in cleavage rates (fluorescence change) in the absence and presence of cefazolin was minimal, antibiotic predicted to be ‘active’. Drastically lowered cleavage rate in presence of cefazolin compared to when probe assayed alone led to prediction of cefazolin as ‘less active’ respectively (also see Figure 2). Details of Disk Diffusion results are presented in Table 3. Bacteria-free controls (PBS only) were included in each assay-set to account for non-specific probe cleavage that may occur. As expected, a negligible fluorescence change over time was observed. Comparison of cleavage rates (mRFU/min) for

#1, #2 and the PBS only control are shown in Additional file 1: Figure S1. AP26113 nitrocefin test for detection of β-lactamase validates results from β-LEAF BMN 673 ic50 assay In order to validate the β-lactamase phenotypes determined by the β-LEAF assay, a CLSI recommended β-lactamase screening method, the chromogenic nitrocefin test, was utilized [41]. All bacterial isolates that were strongly positive by the β-LEAF assay were also found to be positive by nitrocefin conversion with the nitrocefin disks, showing a change in colour from yellow to deep orange in a positive reaction for β-lactamase (Table 1, right-most

column). Comparison of conventional disk diffusion and β-LEAF assay results In order to compare predictions of cefazolin activity by the β-LEAF assay to a conventional AST method, we performed cefazolin disk diffusion selleck screening library assays with the S. aureus isolates. Based on respective zone of inhibition diameters, each isolate was classified as susceptible, intermediate or resistant using the CLSI zone interpretive criteria (Table 3, Additional file 2: Figure S2). Interestingly, all the isolates

fell in the cefazolin ‘susceptible’ range with this methodology (Table 3). Table 3 Cefazolin disk diffusion results S. aureus isolate # Zone of inhibition diameter (mm) AS* Zone edge Interpretation as per zone edge test criteria& 1 21.5 ± 1.0 S Sharp β 2 31.0 ± 1.0 S Fuzzy   3 33.5 ± 0.5 S Fuzzy   4 33.0 ± 2.0 S Fuzzy   5 32.5 ± 0.5 S Fuzzy   6 36.5 ± 0.5 Rutecarpine S Sharp β 7 32.0 ± 0.5 S Fuzzy   8 39.5 ± 1.5 S Fuzzy   9 29.5 ± 1.5 S Fuzzy   10 41.5 ± 0.5 S Fuzzy   11 34.5 ± 2.5 S Little fuzzy Weak β? 12 41.0 ± 1.6 S Fuzzy   13 32.5 ± 0.5 S Fuzzy   14 33.0 ± 0.0 S Fuzzy   15 35.5 ± 2.5 S Fuzzy   16 36.5 ± 0.5 S Fuzzy   17 36.5 ± 0.5 S Fuzzy   18 33.5 ± 0.5 S Sharp β 19 31.0 ± 0.0 S Sharp β 20 20.5 ± 0.3 S Sharp β 21 38.0 ± 1.0 S Fuzzy   22 34.0 ± 1.1 S Little fuzzy Weak β? 23 33.5 ± 1.5 S Fuzzy   24 34.5 ± 1.5 S Fuzzy   25 30.5 ± 0.5 S Fuzzy   26 34.0 ± 0.0 S Fuzzy   27 36.0 ± 2.0 S Little fuzzy/sharpish Weak β? *The Antibiotic Susceptibility (AS) was determined using the CLSI Zone Diameter Interpretive Criteria for Cefazolin Disk Diffusion [41].

Br J Oral Maxillofac Surg 2008, 46: 1–5.CrossRefPubMed 21. de Aguiar AF Jr, Kowalski LP, de Almeida OP: Clinicopathological and immunohistochemical evaluation GSK690693 purchase of oral squamous cell carcinoma in patients with early local recurrence. Oral Oncol 2007, 43: 593–601.CrossRefPubMed 22. Xie X, Lu J, Kulbokas EJ, Golub TR, Mootha V, Lindblad-Toh K: Systematic

discovery of regulatory motifs in human promoters and 3′UTRs by comparison of several mammals. Nature 2005, 434: 338–345.CrossRefPubMed 23. Watanabe T, Takeda A, Mise K, Okuno T, Suzuki T, Minami N: Stage-specific expression of microRNAs during Xenopus development. FEBS Lett 2005, 579: 318–324.CrossRefPubMed 24. Thomson JM, Parker J, Perou CM, Hammond SM: A custom microarray platform for analysis of microRNA gene expression. Nat Methods 2004, 1: 47–53.CrossRefPubMed

25. Tusher VG, Tibshirani R, Chu G: PF-6463922 Significance analysis of microarrays applied to the ionizing radiation response. PNAS 2001, 98: 5116–5121.CrossRefPubMed GS-9973 cell line 26. Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. PNAS 1998, 95: 14863–14868.CrossRefPubMed 27. Schmittgen TD, Jiang J, Liu Q, Yang L: A high-throughput method to monitor the expression of microRNA precursors. Nucleic Acids Research 2004, 32: e43.CrossRefPubMed 28. Shi L, Reid LH, Jones WD, Shippy R, Warrington JA, Baker SC: The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol 2006, 24: 1151–1161.CrossRefPubMed 29. Salley JJ: Experimental carcinogenesis in the cheek pouch of the Syrian hamster. J Dent Res 1954, 33: 253–262.CrossRefPubMed 30. Calin GA, Liu CG, Sevignani C, Ferracin M, Felli Nintedanib (BIBF 1120) N, Dumitru CD, Shimizu M, Cimmino A, Zupo S, Dono M, Dell’Aquila ML, Alder H, Rassenti L, Kipps TJ, Bullrich F, Negrini M, Croce CM: MicroRNA profiling reveals distinct signatures in B cell chronic lymphocytic

leukemias. PNAS 2004, 101: 11755–11760.CrossRefPubMed 31. Patterson TA, Lobenhofer EK, Fulmer-Smentek SB, Collins PJ, Chu TM, Bao W, Fang H, Kawasaki ES, Hager J, Tikhonova IR, Walker SJ, Zhang L, Hurban P, de Longueville F, Fuscoe JC, Tong W, Shi L, Wolfinger RD: Performance comparison of one-color and twocolor platforms within the MicroArray Quality Control (MAQC) project. Nat Biotechnol 2006, 24: 1140–1150.CrossRefPubMed 32. Luo MY, Tian ZG, Xu Z: Construction and application of a microarray for profiling microRNA expression. Prog Biochem Biophys 2007, 34: 31–41. 33. Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA, Downing JR, Jacks T, Horvitz HR, Golub TR: MicroRNA expression profiles classify human cancers. Nature 2005, 435: 834–838.CrossRefPubMed 34. Tong AW, Nemunaitis J: Modulation of miRNA activity in human cancer: a new paradigm for cancer gene therapy? Cancer Gene Ther 2008, 15: 341–355.CrossRefPubMed 35.

Heart rate increased from rest and peaked 90 minutes into exercise (Rest 61.9 ± 2.9, 30 min 137.4 ± 3.3, 60 min 140.4 ± 3.3, 90 min 142.5 Sapitinib supplier ± 3.5 bpm). SC79 clinical trial Perceived exertion was significantly different between all three collections (30 min 11.2 ± 0.3, 60 min 12.0 ± 0.3, 90 min 12.6 ± 0.4, p < .05). Carbohydrate oxidation significantly decreased from 30 to 90 minutes (30 min 1.9 ± 0.1, 60 min 1.9 ± 0.2, 90 min 1.7 ± 0.1 g/min, p < .001) while fat oxidation significantly increased from 30 to 90 minutes (30 min 0.5 ± 0.05, 60 min 0.48 ± 0.05, 90

min 0.59 ± 0.04 g/min, p < .001). Plasma measurements Insulin Pre-exercise plasma insulin values were not significantly different between treatments (Figure 2). Plasma insulin Quisinostat cell line dropped during exercise and was lowest immediately post exercise (Drink 47.8 ± 3.0, Cereal 47.2 ± 2.4 pmol/L). Insulin increased and remained higher than pre-exercise levels 60 minutes after both treatments (Drink 123.1 ± 11.8, p < .01; Cereal 191.0 ± 12.3 pmol/L, p < .001). There was a significant difference

between Drink and Cereal treatment effects (p < .05); however, the post-exercise AUC was smaller for Drink as compared to Cereal (Drink 11,898.99 ± 1208.57, Cereal 15,464.79 ± 1247.92 pmol/L•60 min, p < .05). Sixty minutes after the treatment, insulin was higher for Drink compared to Cereal (p < .001). Figure 2 Insulin changes by treatment. Measured pre-exercise (Pre), at end of exercise (End), and 15, 30 and 60 minutes after supplementation (Post15, Post30 and Post60). Values are M ± SEM. * Significant difference between Drink and Cereal (p < .001). Glucose Pre-exercise plasma glucose values were not significantly different between treatments (Figure 3) (Drink 4.0 ± 0.1, Cereal 4.1 ± 0.1 mmol/L). Plasma glucose dropped during exercise and was lowest immediately at the end of exercise (Drink 3.3 ± 0.2, Cereal 3.8 ± 0.1 mmol/L).

Glucose increased and remained higher than pre-exercise levels 60 minutes after both treatments (Drink, isothipendyl 5.7 ± 0.3 mmol/L, p < .01; Cereal 5.4 ± 0.3 mmol/L, p < .05). The post-exercise AUC was higher for Drink as compared to Cereal (Drink 484.67 ± 15.57, Cereal 438.54 ± 18.31 mmol/L•60 min, p < .05). There was no significant difference between the Drink and Cereal treatment effects (p = .395). Figure 3 Glucose changes by treatment. Measured pre-exercise (Pre), at end of exercise (End), and 15, 30 and 60 minutes after supplementation (Post15, Post30 and Post60). Values are M ± SEM. * Significant difference between Drink and Cereal (p < .05). Lactate Pre-exercise plasma lactate values were not significantly different between treatments (Figure 4). Plasma lactate increased during exercise (Drink 1.5 ± 0.2, Cereal 1.4 ± 0.2 mmol/L). There was a significant difference between the Drink and Cereal treatment effects (p < .05). After Drink, lactate continued to rise at 15 minutes, peaked at 30 minutes and remained significantly higher than pre-exercise levels at 60 minutes (1.3 ± 0.1, 1.5 ± 0.1, 1.4 ± 0.