Furthermore, enforcement of the law of seatbelt usage, strict penalties for high speed, and a public educational

program are highly needed in our community. We hope that our study is a small step in that direction. In summary, the incidence of hospitalized vascular injury due to road traffic collisions in Al-Ain city is 1.87 cases/100 000 inhabitants. These INCB018424 order injuries occurred mainly in the upper part of the body. Seatbelt compliance of car occupants having vascular injuries was very low. Compliance with safety measures needs more enforcement in our community. Ethical approval The Local Ethics Committee of Al-Ain Health District Area, Al-Ain, (UAE RECA/02/44) Acknowledgements This study was supported by a UAE University Interdisciplinary Grant (#02-07-8-1/4). References 1. World Health Organization: Global status report on road safety: time for action. Geneva 2009. [http://​www.​who.​int/​violence_​injury_​prevention/​road_​safety_​status/​2009] Accessed on 6 January 2010 2. United Arab Emirates Ministry

of Health. Abu Dhabi, UAE: Preventive Medicine Sector. Annual Statistic Report. 2004, 213–214. 3. Barss P, Al-Obthani M, Al-Hammadi A, Al-Shamsi H, El-Sadig M, Grivna M: Prevalence and issues in non-use of safety belts and child restraints in a high-income developing country: lessons for the future. Traffic Inj Prev 2008, 9:256–263.CrossRefPubMed 4. El-Sadig M, Sarfraz Alam M, Carter AO, Fares K, Al-Taneuiji H, Romilly P, Norman JN, Lloyd O: Evaluation of effectiveness of safety seatbelt legislation in the United Arab Emirates. Accid Anal Prev 2004, 36:399–404.CrossRefPubMed 5. Eid HO, Barss Venetoclax in vitro P, Adam SH, Torab FC, Lunsjo K, Grivna M, Abu-Zidan FM: Factors affecting anatomical region of injury, severity, and mortality for road trauma in a high-income developing country: lessons for prevention. Injury 2009, 40:703–707.CrossRefPubMed 6. Annual report

2006, Preventive Medicine Sector, Ministry of Health, United Arab Emirates, published on November 2007. 7. Association of the Advancement of Automotive Medicine: Abbreviated Injury Scale, Association of the Advancement of Automotive Medicine. IL, USA 1998. 8. Maurer E, Morris JM Jr: Injury Severity Scoring in Trauma. Edited by: Selleck Rucaparib Moore EE, Feliciano DV, Mattox KL. McGraw-Hill companies: New York; 2004:87–91. 9. Fingerhut A, Leppaniemi AK, Androulakis GA, Archodovassilis F, Bouillon B, Cavina E, Davidovic E, Delgado-Millan MA, Goris J, Gunnlaugsson GH, Jover JM, Konstandoulakis M, Kurtoglu M, Leoantalo M, Llort-Pont C, Meneu-Diaz JC, Moreno-Gonzales E, Navarro-Soto S, Panoussis P, Ryan J, Salenius JP, Seccia M, Takolander R, Taviloglu K, Tiesenhausen K, Torfason B, Uranus S: The European experience with vascular injuries. Surg Clin North Am 2002, 82:175–188.CrossRefPubMed 10. Al-Salman M, Al-Khawashki H, Sindigki A, Rabee H, Al-Saif A, Fachartz FA: Vascular injuries associated with limb fractures.

Here we concentrated in L. johnsonii, a potentially probiotic bacterial species that is of major interest to the pharmaceutical and food industries as it includes several known probiotic strains [25, 28, 29]. We successfully identified and isolated 39 L. johnsonii strains from fecal-bacterial populations of few host species. Strain typing of these isolates together with six additional strains of human origin revealed

LGK974 high levels of genetic variation among the L. johnsonii strains. Both SSR and MLST analyses were found to be effective for typing, providing high-resolution discrimination also among isolates originated in the same animal species. The genetic relationships among the strains inferred by the two analyses were similar, clearly dividing the L. johnsonii strains into three clusters. buy INK 128 Each cluster consisted of strains from different diverse hosts, i.e., chickens, humans or mice (Figure 2). These consistent results, obtained by different typing methods, suggest far phylogenetic separation among L. johnsonii isolates presenting host specificity. Such association of particular L. johnsonii strains with the host taxonomy could arise as a result of co-evolution of the host and its GIT microbiota [2, 41–43]. Interestingly, host driven evolution was observed in another

lactobacilli species, L. reuteri[44]. According to the recently suggested “”hologenome theory”" [45], the host and its symbiont microbiota (together defined as the “”holobiont”") are one unit of selection in evolution. Indeed, previous analysis of the L. johnsonii genome showed the absence of genes required for several metabolic pathways [29] emphasizing the high dependence of L. johnsonii on its host and further supports the concept that L. johnsonii and its host are one evolutionary unit of selection. Since chickens, humans and mice are distinct genetic species divided during evolution, L. johnsonii strains associated with them may be evolutionary separated as part of the distinct holobionts. In addition, analysis conducted

on the tRFLP results of 50 host individuals suggest an association of L. intestinalis and E. faecium cluster with host taxonomic Obatoclax Mesylate (GX15-070) groups (Figure 1), and further support co-evolution of the host and its intestinal bacteria. The E. faecium species cluster was relatively rare in hosts belonging to the Rodentia taxonomic order, and alternatively, L. intestinalis was found to be more frequent within that group. These observations may indicate possible competition or a similar function of these two bacteria in the same niche, each within its appropriate microenvironment. Environmental factors, such as diet, are highly important in shaping the host gut’s microbiota composition [4–6, 46]. However, in our study, no correlation was found between the presence of each of the four bacterial species tested and the hosts’ food consumption (herbivore, omnivore and carnivore) or geographical location. Conclusions L.

Although phase 1 clinical trials have found that high doses (12 g/day) of systemic CCM are safe [19], the use of polyphenols as antimicrobials is likely to

be limited to use as topical agents. The toxicity of EGCG was limited to minor skin irritation in mammalian models [20] at high concentrations and no adverse effects were seen with preparations containing up to 500 mg/Kg/day. GSK2126458 In this study we present data on the activity of CCM alone and in combination with EGCG against a well characterised collection of MDR A. baumannii clinical isolates. Methods Chemicals reagents and media Curcumin powder (≥90% purity) extracted from Curcuma longa was purchased from the Cayman Chemical Company

(Michigan, USA). Epigallocatechin gallate (≥95% purity) was donated by Unilever PLC (Bedford, UK). All growth media (Iso-Sensitest broth) was purchased from Thermo Scientific (Basingstoke, UK), sterilised and made up locally according to the manufacturer’s instructions. Bacterial strains Nine Acinetobacter see more baumannii isolates were studied. These included the antibiotic susceptible type strain ATCC 19606 and 8 MDR clinical isolates. These have been extensively characterised previously and were chosen to be representative of UK epidemic clones (OXA-23 clones 1, 2, ‘Burn’) and/or exhibit resistance to colistin, tigecycline or produce metallo-β-lactamases (NDM enzymes) [21] Properties of the strains are detailed in Table 1. All isolates were stored at -70°C in microbank vials (Thermofisher, UK) and thawed prior to their use. Table 1 Resistant determinants and sources of multidrug-resistant clinical isolates of Acinetobacter baumannii Isolate Properties Isolate source AB 19606 Antibiotic Susceptible type Strain. National Collection of type cultures AB 14 MDR PFGE defined UK OXA-23 clone 1 OXA-23-like carbapenemase producer. Dr J Turton, Public Health Loperamide England, Colindale, UK AB 16 MDR PFGE defined

UK OXA-23 clone 2 OXA-23 carbapenemase producer. Dr J Turton, Public Health England, Colindale, UK AB 186 MDR PFEG defined UK ‘burn’ strain, OXA-23 producer. Dr J Turton, Public Health England, Colindale, UK AB 202 Tigecycline-resistant strain UK OXA-23 clone 1 isolate. Barts Health NHS Trust, London, UK AB 205 Colistin resistant UK OXA-23 clone 1 isolate. Barts Health NHS Trust, London, UK AB 292 MDR PFGE-defined OXA-23-like carbapenemase producer. Barts Health NHS Trust, London, UK AB 306 MDR NDM-1 carbapenemase producer. Barts Health NHS Trust, London, UK AB 308 MDR NDM-2 carbapenemase producer. S. Gottig, Goethe Universistat, Frankfurt, Germany Determination of minimum inhibitory concentrations Minimum inhibitory concentrations (MICs) were determined in corning 96-well microtitre plates (Corning, Amsterdam, The Netherlands).

CrossRefPubMed 8. Passik SD,

Kirsh KL, Theobald DE, Dicherson P, Trowbridge R, Gray D, Beaver M, Comparet J, Brown J: A retrospective chart review of the use of olanzapine for the prevention of delayed emesis in cancer patients. J Pain Symptom Selleck FK506 Manage 2003, 25: 485–488.CrossRefPubMed 9. Passik SD, Navari RM, Jung SH, Nagy C, Vinsor J, Kirsh KL, Loehrer P: A phase I trial of olanzapine (Zyprexa) for the prevention of delayed emesis in cancer patients: a Hoosier Oncology Group study. Cancer Invest 2004, 22: 383–388.CrossRefPubMed 10. Navari RM, Einhorn LH, Passik SD, Loehrer PJ Sr, Johnson C, Mayer ML, McClean J, Vinson J, Pletcher W: A phase II trial of olanzapine for the prevention of chemptherapy-induced nausea and vomiting: a Hoosier Oncology Group study. Support Care Cancer 2005, 13: 529–534.CrossRefPubMed

11. Herrestedt J, koeller JM, Roilla F, Hesketh PJ, Warr D, Rittenberg C, Dicato M: Acute emesis: moderately emetogenic chemotherapy. Support Care Cancer BYL719 mw 2005, 13: 97–103.CrossRef 12. Kris MG, Hesketh PJ, Herrstedt J, Rittenberg C, Einhorn LH, Grunberg S, Koeller J, Olver I, Borjeson S, Ballatori E: Consensus proposals for the prevention of acute and delayed vomiting and nausea following high-emetic-risk chemotherapy. Support Care Cancer 2005, 13: 85–96.CrossRefPubMed 13. American Society of Clinical Oncology, Kris MG, Hesketh PJ, Somerfield MR, Feyer P, Clark-Snow R, Koeller JM, Morrow GR, Chinnery LW, Chesney MJ, Gralla RJ, Grunberg SM: American Society of clinical oncology guideline for antiemetics in oncology: update 2006.

J Clin Oncol 2006, 24: Inositol oxygenase 2932–2947.CrossRefPubMed 14. Roila F, Warr D, Clarck-Snow RA, Tonato M, Gralla RJ, Einhorn LH, Herrstedt J: Delayed emesis: moderately emetogenic chemotherapy. Support Care Cancer 2005, 13: 104–108.CrossRefPubMed 15. Vardy J, Chiew KS, Galica J, Pond GR, Tannock IF: Side effects associated with the use of dexamethasone for prophylaxis of delayed emesis after moderately emetogenic chemotherapy. Br J Cancer 2006, 94: 1011–1015.CrossRefPubMed 16. Dube S, Tollefson GD, Thase ME, Briggs SD, Van Campen LE, Case M, Tohen M: Onset of antidepressant effect of olanzapine and olanzapine/fluoxetine combination in bipolar depression. Bipolar Disord 2007, 9: 618–627.CrossRefPubMed 17. Corya SA, Williamson D, Sanger TM, Briggs SD, Case M, Tollefson G: A randomized, double-blind, comparison of olanzapine/fluoxetine combination, olanzapine, fluoxetine, and venlafaxine in treatment-resistant depression. Depress Anxiety 2006, 23: 364–372.CrossRefPubMed Competing interests The authors declare that they have no competing interests. Authors’ contributions LT designed and carried out this study, drafted the manuscript. DZ conceived of the study, JL participated in its design and modified the manuscript. XL, JC, ZY and HY provided the patients for study. JP, JL and YR helped with the clinical observation. All authors read and approved the final manuscript.

The experimental protocol was approved by the Office for the Protection of Research

Subjects at the University of Illinois, Chicago. All volunteers gave informed consent to participate in the trial. Experimental design and randomization A 12-week, randomized, controlled, parallel-arm feeding trial was implemented to test the effects of ADF, exercise, and ADF combined with exercise (combination group) on eating behaviors and weight loss. Eligible subjects were stratified on the basis of BMI, age, and sex, and then randomized into 1 of 4 groups: 1) combination group; 2) ADF group; 3) exercise group; 4) control GS 1101 group. Diet protocol As previously described [2], only the combination and ADF groups participated in the dietary intervention, which consisted of two periods: 1) a 4-week controlled feeding period, and 2) an 8-week self-selected feeding period. During the controlled feeding period (week 1–4) participants consumed 25% of their baseline energy needs on the fast day (24 h) and consumed food ad libitum on each feed day (24 h). Baseline energy requirements were assessed by the Mifflin equation [7]. The diet consisted of a 3-day rotating menu plan, and all fast day meals were prepared in the metabolic kitchen of the Human Nutrition Research Unit (HNRU). Fast day meals were consumed between 12.00 pm and 2.00 pm to ensure that each subject

was undergoing the same duration of fasting. Meals were formulated on the basis of the American Heart Association guidelines (30% kcal from fat, 15% kcal buy Ensartinib from protein, and 55% kcal from carbohydrate). All meals were consumed outside of the research center. Participants were requested to eat only the foods provided on the fast days and to bring back any leftover foods to be weighed and recorded. Calorie-free foods, such as black coffee, tea, and diet sodas were permitted as desired. Subjects were also encouraged to drink plenty of water. During the self-selected feeding period (week 8–12) subjects continued with the ADF regimen but no fast day food was

provided to them. Instead, each subject met with a dietician at the beginning of each week to learn how to maintain Amobarbital the ADF regimen at home. Subjects were also taught how to monitor energy intake by reading food labels, reducing portion sizes, and choosing low fat meat and dairy options. Control and exercise group subjects were asked to maintain their regular food habits, and were not provided with any food or dietary counseling. Exercise protocol Only the combination and exercise groups participated the exercise intervention. These subjects participated in a moderate intensity exercise program 3 times per week under supervised conditions, for 12 weeks. Exercise was performed using stationary bikes and elliptical machines at the HNRU.

5G illumination using the BQP method. The calculated solar cell parameters are shown in Table 3. Also, the calculated quantum efficiencies are shown in Figure 7. The simulated quantum efficiencies are

multiplied by 0.12 for comparison with the experimental one. The calculated short-circuit current densities (J sc) and quantum efficiencies are much higher than those of the experimental results. There are two possible reasons. The first reason is due to the difference of the doping concentration in a Si-QDSL layer. In an actual solar cell, the phosphorus concentration in the Si-QDSL absorber layer is more than 1 × 1019 cm-3 due to the high-temperature annealing process [34]. From the simulations, the J sc and the quantum efficiency in the whole wavelength region becomes lower if the phosphorus concentration in the Si-QDSL layer increases. The phosphorus in the Si-QDSL layer degrades the J sc due to the reduction of the electrical this website field in the Si-QDSL layer. Unfortunately, simulations were not possible when the dopant concentration in the Si-QDSL was higher than 1 × 1017 cm-3 due to the convergence problem of the BQP calculations. It is expected that J sc will decrease more if the dopant concentration becomes higher. We previously reported that the quantum efficiency Sorafenib clinical trial in the whole wavelength region decreases as the dopant concentration in the Si-QDSL increases from experiments and the simulations using classical model [35], which is similar to

the results of the BQP method. The second reason is due to the optical losses in the n-type poly-Si layer. In this calculation, the surface roughness of the textured quartz substrate was not taken into account. The effective optical path length in the n-type layer of the simulated structure should be shorter than that of the actual solar cell structure. As a result, the simulated quantum efficiency in the short-wavelength region is higher than that of the experimental because of the low optical absorption loss in the n-type poly-Si layer. Even though the J sc mismatch, the absorption edge can be estimated from the simulated quantum efficiency. The calculated quantum efficiencies

at the long-wavelength region are in agreement with those of the experimental one. This suggests that the absorption edge of the solar cell can be theoretically reproduced using this simulation. Moreover, the absorption edge was estimated Interleukin-3 receptor to be 1.49 eV, which is quite similar to the absorption edge of the Si-QDSL estimated from the optical measurements. This indicates that the photogeneration in the Si-QDSL solar cell is thought to be the contribution from Si-QDs, and it is possible to fabricate the solar cells with silicon nanocrystal materials, whose bandgaps are wider than that of a crystalline silicon. Conclusions The fundamental optical properties of Si-QDSLs were investigated, and the solar cell structure using the Si-QDSL as an absorber layer was fabricated and characterized.

Comparative gut metagenomics In this study, we examined the functional similarity of the Yorkshire pig fecal metagenome by comparing it to currently available metagenomic projects. Hierarchical clustering of functional profiles derived from gut metagenomes available in the MG-RAST database revealed that the GS20 and FLX swine fecal datasets shared approximately 70% similarity to other human metagenomes (Figure 4B). This analysis also showed the swine gut metagenome clustered more closely with chicken cecal and cow rumen metagenomes click here than to the human gut metagenomes (Figure 4B). We further investigated

subsystems associated with specialized cell wall and capsule enzymes, MS275 DNA recombination, and prophage genes since they were very abundant in the swine fecal metagenome (Additional File 1, Fig. S8). Within the DNA recombination and prophage subsystem, the

swine fecal metagenome was enriched for RstA phage-related replication proteins, terminases, and portal proteins. Additionally, more than 30 metagenomic contigs (i.e., > 500 bp) shared high homology to unknown phage proteins. For proteins involved in the cell wall and capsule subsystem, unknown glycosyl transferases, a phosphoglucosamine mutase, and a phosphotransferase were over abundant in the swine metagenome (Table 3). N-acetyl glucosamine-specific PTS system, proteins involved in mannose uptake, and novel capsular polysaccharide synthesis enzymes

were exclusively found within the swine fecal metagenome. Hierarchical clustering of all genes retrieved from the cell wall and capsule functional subsystem for each gut microbiome revealed that swine fecal cell wall/capsule profiles were greater than 60% similar to those of the cow rumen. Additionally, cell wall and capsule profiles in the swine samples were more similar to termite gut than the human gut (Additional File 1, Fig. S9). When carbohydrate subsystems were compared across gut microbiomes, maltose and maltodextrin utilization were the most abundant carbohydrate GPX6 subsystem in the swine, termite, and cow rumen. Analysis of carbohydrate metabolism using the SEED subsystem approach, revealed several proteins unique to the swine gut metagenome such as an outer surface protein part of the cellobiose operon, a beta-glucoside-specific IIA component and a cellobiose-specific IIC component of the PTS system, and a protein similar CDP-glucose 4,6-dehydratase. Table 3 List of cell wall and capsule SEED subsystem functions overabundant in swine fecal metagenome   Pig Feces Human Adult Human Infant Cow Rumen Termite Gut Mouse Cecum Fish gut putative glycosyltransferase – possibly involved in cell wall localization and side chain formation of rhamnose-glucose polysaccharide 112 9 10 10 0 1 0 Phosphoglucosamine mutase (EC 5.4.2.

The youngest age group experienced least workload and best support from supervisor. Two explanations may fit. The youngest workers are relatively inexperienced and starting their career through which they probably have less tasks and responsibilities. Also, many of these workers may be PhD students, whom are clearly assigned a supervisor and who receive relatively much support. Only in skill discretion and in “I expect positive results from clarifying the work objectives”, they had least favourable scores. When work experience grows and tasks are expanded, more possibilities to use skills and knowledge will appear. Older workers scores may reflect their years of experience

on the job, which was significantly higher than in the other age groups (see Table 1). It is to be expected Vemurafenib clinical trial that older workers

have accomplished many of their goals in working life. This might explain why their mean scores for readiness for further education, “I am ready to take on new selleck tasks all the time” and “I expect positive results from regular attention to career and development opportunities” where least favourable. This tendency that older workers are less enthusiastic to join in further education is also found in other research (Muffels 2003; Ilmarinen 2005). However, supplementary analysis on a separate item from the ‘opportunities for further education’ scale does not support this explanation. Older employees felt significantly more responsible for keeping pace with the new knowledge and skills needed for further development than the workers in the younger age groups (almost 90 vs. about 75%, respectively). This attitude was also found among alumni at a US state university’s School of Business.

Age did not appear to be associated with the hours the alumni invested in professional development (Greller 2006). All in all, the mean scores suggested that working conditions were good. Interesting is that three of the six work characteristics with disappointing scores in all the age groups were related to support and appreciation. Most favourable work characteristics were reported by the youngest and the oldest age groups. This does not correspond with the negative beliefs, Edoxaban many employers (especially the younger ones) were found to have about older employees (Chiu et al. 2001; Visser et al. 2003; Remery et al. 2003; Peeters et al. 2005; Henkens 2005), although not all the research confirmed this (Munnel et al. 2006). For instance, older workers were expected to be less able to cope with a heavy workload (Visser et al. 2003) and hard to (re)train, while depletion of professional knowledge and skills were considered to be the most important obstacles against employing older workers (Taylor and Walker 1998). Our results show that statistical differences are present, but that these differences are small.

Thus, the purpose of this study was to examine the efficacy

of two different doses (1 g per 500 ml and 2 g per 500 ml) of AG on basketball performance, including jump power, Lumacaftor datasheet reaction time, shooting ability and fatigue during a basketball game. Methods Subjects Ten women volunteered for this study (21.2 ± 1.6 years; height: 177.8 ± 8.7 cm; body mass: 73.5 ± 8.0 kg). Following an explanation of all procedures, risks, and benefits, each subject gave her informed consent to participate in this study. The Institutional Review Board of the University approved the research protocol. Subjects were not permitted to use any additional nutritional supplementation during the course of the study. Screening for additional supplement use was accomplished via a health history questionnaire completed during subject recruitment. All subjects were scholarship athletes playing for the University’s Women’s basketball team. The study protocol was a double-blind cross-over design. Testing protocol Data collection occurred on four separate occasions. Each session required subjects to participate in a 40-min basketball game (normal duration for a NCAA college basketball game). To simulate an actual competition,

a 2-min time out was used at the 10-min mark of each half, and a 10-min halftime separated the first and second halves. Subjects were divided into two equally talented teams as determined by the team’s player captains. The team members remained the same for each game. Thus level of competition (subjects competing

against each other) was the same for each contest. Interestingly, Decitabine manufacturer each team won two games. The difference between each contest was the type of hydration fluid that was provided. During the first session (DHY) subjects were not allowed to rehydrate. During this session the total weight lost during the contest was determined, which was then used to determine the fluid replenishment during the subsequent three experimental sessions. During these three sessions subjects were provided fluid every 10 min in equal amounts for a total of six hydration times. The fluid consumed at each ingestion point was equal to the fluid loss observed PAK6 during session one, divided by six. During one of these sessions subjects consumed only water (W), while during the other two session subjects consumed the AG supplement marketed as Sustamine™ (Kyowa Hakko USA, New York, NY) mixed in water using either a low dose (1 g per 500 ml) (AG1) or high dose (2 g per 500 ml) (AG2) concentration. The order of the three sessions was randomly determined per subject. All subjects were expected to begin each game in a euhydrated state. Prior to each contest a urine sample was analyzed for urine specific gravity (Usg) by refractometry to document euhydration; Usg ≤ 1.020 was defined as euhydration [12]. If a subject’s Usg > 1.020 she was requested to ingest 500 ml of water and retested.

Data analysis All data was analyzed in SPSS using a mixed-factorial ANOVA [treatment (DBX vs PLC) x time Ibrutinib (HR1 vs HR2 vs HR3 vs HR4)]. Results REE and RER

A significant group x time interaction for change in resting energy expenditure (p = 0.001) was determined. From baseline to hour 4, REE increased by 147.33 ± 83.52 for DBX and 32.17 ± 86.72 kcal/day for PLC (p = 0.003). Changes in kcal/day for all time points can be seen in Figure 1. A significant main effect for time was also reported (p = 0.001). Changes in REE from baseline for each time point

are as follows: hour 1 (DBX: 123.4 ± 78.2 kcal/day vs. PLC: -3.1 ± 88.4 kcal/day), hour 2 (DBX: 125.5 ± 62.2 kcal/day vs. PLC: -20.3 ± 72.6 kcal/day), hour 3 (DBX: 142.4 ± 101.16 kcal/day vs. PLC: 9 ± 114.77 kcal/day), and hour 4 (DBX: 147.3 ± 83.5 kcal/day vs. PLC: 32.1 ± 86.7 kcal/day). Changes were significant (p < .05) between groups at all time points for REE. There were no significant time or interaction effects for RER at any time point. Figure 1 Resting energy expenditure changes. REE increased across all time points for DBX (active) ranging from a 123.4 to 147.3 SCH772984 manufacturer kcal/day increase above baseline values. Changes were statistically different between groups at all time points post-supplementation. * indicates statistically significant changes (p ≤ 0.05). Hemodynamic and ECG There were no significant FER (p > 0.05) group x time interactions and

no main effects for time for SBP, DBP, or HR (Figure 2). There was no significant main effect for group (p > 0.05). At hour 1, SBP increased by 12.4 ± 11.8 mmHG and 1.75 ± 10.4 mmHG for DBX and PLC, respectively from baseline values. From baseline to hour 2, SBP increased by 10.0 ± 14.0 mmHg (DBX) versus 0.0 ± 7.9 mmHg (PLC). Hour 3 SBP deviated from baseline by 13.5 ± 22.4 mmHg for DBX and −2.5 ± 8.1 mmHg for PLC. Hour 4 SBP increased above the baseline mean by 8.3 ± 10.5 mmHg (DBX) and 1.5 ± 10.6 mmHg (PLC). DBP changes from baseline to hour 1 were 4.8 ± 7.4 mmHg (DBX) versus 0.6 ± 7.9 mmHg (PLC). At hour 2, DBP changed from baseline by −0.25 ± 13.2 (DBX) and −1.0 ± 7.2 mmHg (PLC). Hour 3 values for DBP from baseline for DBX were 6.7 ± 20.9 mmHg and for PLC were −4.5 ± 10.1 mmHg. The comparison against DBP baseline measurement for the DBX group at hour 3 was 1.25 ± 6.8 mmHg and 1.1 ± 11.0 mmHg for the PLC group. DBX versus PLC comparison to baseline in HR are as follows: hour 1 (−3.0 ± 6.2 vs. -2.5 ± 5.5 bpm), hour 2 (−2.9 ± 6.5 vs. -1.0 ± 10.0 bpm), hour 3 (−2.3 ± 5.6 vs. -0.5 ± 8.7 bpm), and hour 4 (−1.4 ± 6.8 vs. -0.3 ± 7.4 bpm). (Data can be seen in Table 2 for SBP, DBP, and HR.