31 resultados para Amphibole (Intensity, 8.45Å)
em Queensland University of Technology - ePrints Archive
Resumo:
We have determined the effect of two exercise-training intensities on the phospholipid profile of both glycolytic and oxidative muscle fibers of female Sprague-Dawley rats using electrospray-ionization mass spectrometry. Animals were randomly divided into three training groups: control, which performed no exercise training; low-intensity (8 m/min) treadmill running; or high-intensity (28 m/min) treadmill running. All exercise-trained rats ran 1,000 m/session for 4 days/wk for 4 wk and were killed 48 h after the last training bout. Exercise training was found to produce no novel phospholipid species but was associated with significant alterations in the relative abundance of a number of phospholipid molecular species. These changes were more prominent in glycolytic (white vastus lateralis) than in oxidative (red vastus lateralis) muscle fibers. The largest observed change was a decrease of ∼20% in the abundance of 1-stearoyl-2-docosahexaenoyl-phosphatidylethanolamine [PE(18:0/22:6); P < 0.001] ions in both the low- and high-intensity training regimes in glycolytic fibers. Increases in the abundance of 1-oleoyl-2-linoleoyl phopshatidic acid [PA(18:1/18:2); P < 0.001] and 1-alkenylpalmitoyl-2-linoleoyl phosphatidylethanolamine [plasmenyl PE (16:0/18:2); P < 0.005] ions were also observed for both training regimes in glycolytic fibers. We conclude that exercise training results in a remodeling of phospholipids in rat skeletal muscle. Even though little is known about the physiological or pathophysiological role of specific phospholipid molecular species in skeletal muscle, it is likely that this remodeling will have an impact on a range of cellular functions.
Resumo:
It is frequently reported that the actual weight loss achieved through exercise interventions is less than theoretically expected. Amongst other compensatory adjustments that accompany exercise training (e.g., increases in resting metabolic rate and energy intake), a possible cause of the less than expected weight loss is a failure to produce a marked increase in total daily energy expenditure due to a compensatory reduction in non-exercise activity thermogenesis (NEAT). Therefore, there is a need to understand how behaviour is modified in response to exercise interventions. The proposed benefits of exercise training are numerous, including changes to fat oxidation. Given that a diminished capacity to oxidise fat could be a factor in the aetiology of obesity, an exercise training intensity that optimises fat oxidation in overweight/obese individuals would improve impaired fat oxidation, and potentially reduce health risks that are associated with obesity. To improve our understanding of the effectiveness of exercise for weight management, it is important to ensure exercise intensity is appropriately prescribed, and to identify and monitor potential compensatory behavioural changes consequent to exercise training. In line with the gaps in the literature, three studies were performed. The aim of Study 1 was to determine the effect of acute bouts of moderate- and high-intensity walking exercise on NEAT in overweight and obese men. Sixteen participants performed a single bout of either moderate-intensity walking exercise (MIE) or high-intensity walking exercise (HIE) on two separate occasions. The MIE consisted of walking for 60-min on a motorised treadmill at 6 km.h-1. The 60-min HIE session consisted of walking in 5-min intervals at 6 km.h-1 and 10% grade followed by 5-min at 0% grade. NEAT was assessed by accelerometer three days before, on the day of, and three days after the exercise sessions. There was no significant difference in NEAT vector magnitude (counts.min-1) between the pre-exercise period (days 1-3) and the exercise day (day 4) for either protocol. In addition, there was no change in NEAT during the three days following the MIE session, however NEAT increased by 16% on day 7 (post-exercise) compared with the exercise day (P = 0.32). During the post-exercise period following the HIE session, NEAT was increased by 25% on day 7 compared with the exercise day (P = 0.08), and by 30-33% compared with the pre-exercise period (day 1, day 2 and day 3); P = 0.03, 0.03, 0.02, respectively. To conclude, a single bout of either MIE or HIE did not alter NEAT on the exercise day or on the first two days following the exercise session. However, extending the monitoring of NEAT allowed the detection of a 48 hour delay in increased NEAT after performing HIE. A longer-term intervention is needed to determine the effect of accumulated exercise sessions over a week on NEAT. In Study 2, there were two primary aims. The first aim was to test the reliability of a discontinuous incremental exercise protocol (DISCON-FATmax) to identify the workload at which fat oxidation is maximised (FATmax). Ten overweight and obese sedentary male men (mean BMI of 29.5 ¡Ó 4.5 kg/m2 and mean age of 28.0 ¡Ó 5.3 y) participated in this study and performed two identical DISCON-FATmax tests one week apart. Each test consisted of alternate 4-min exercise and 2-min rest intervals on a cycle ergometer. The starting work load of 28 W was increased every 4-min using 14 W increments followed by 2-min rest intervals. When the respiratory exchange ratio was consistently >1.0, the workload was increased by 14 W every 2-min until volitional exhaustion. Fat oxidation was measured by indirect calorimetry. The mean FATmax, ƒtV O2peak, %ƒtV O2peak and %Wmax at which FATmax occurred during the two tests were 0.23 ¡Ó 0.09 and 0.18 ¡Ó 0.08 (g.min-1); 29.7 ¡Ó 7.8 and 28.3 ¡Ó 7.5 (ml.kg-1.min-1); 42.3 ¡Ó 7.2 and 42.6 ¡Ó 10.2 (%ƒtV O2max) and 36.4 ¡Ó 8.5 and 35.4 ¡Ó 10.9 (%), respectively. A paired-samples T-test revealed a significant difference in FATmax (g.min-1) between the tests (t = 2.65, P = 0.03). The mean difference in FATmax was 0.05 (g.min-1) with the 95% confidence interval ranging from 0.01 to 0.18. Paired-samples T-test, however, revealed no significant difference in the workloads (i.e. W) between the tests, t (9) = 0.70, P = 0.4. The intra-class correlation coefficient for FATmax (g.min-1) between the tests was 0.84 (95% confidence interval: 0.36-0.96, P < 0.01). However, Bland-Altman analysis revealed a large disagreement in FATmax (g.min-1) related to W between the two tests; 11 ¡Ó 14 (W) (4.1 ¡Ó 5.3 ƒtV O2peak (%)).These data demonstrate two important phenomena associated with exercise-induced substrate oxidation; firstly, that maximal fat oxidation derived from a discontinuous FATmax protocol differed statistically between repeated tests, and secondly, there was large variability in the workload corresponding with FATmax. The second aim of Study 2 was to test the validity of a DISCON-FATmax protocol by comparing maximal fat oxidation (g.min-1) determined by DISCON-FATmax with fat oxidation (g.min-1) during a continuous exercise protocol using a constant load (CONEX). Ten overweight and obese sedentary males (BMI = 29.5 ¡Ó 4.5 kg/m2; age = 28.0 ¡Ó 4.5 y) with a ƒtV O2max of 29.1 ¡Ó 7.5 ml.kg-1.min-1 performed a DISCON-FATmax test consisting of alternate 4-min exercise and 2-min rest intervals on a cycle ergometer. The 1-h CONEX protocol used the workload from the DISCON-FATmax to determine FATmax. The mean FATmax, ƒtV O2max, %ƒtV O2max and workload at which FATmax occurred during the DISCON-FATmax were 0.23 ¡Ó 0.09 (g.min-1); 29.1 ¡Ó 7.5 (ml.kg-1.min-1); 43.8 ¡Ó 7.3 (%ƒtV O2max) and 58.8 ¡Ó 19.6 (W), respectively. The mean fat oxidation during the 1-h CONEX protocol was 0.19 ¡Ó 0.07 (g.min-1). A paired-samples T-test revealed no significant difference in fat oxidation (g.min-1) between DISCON-FATmax and CONEX, t (9) = 1.85, P = 0.097 (two-tailed). There was also no significant correlation in fat oxidation between the DISCON-FATmax and CONEX (R=0.51, P = 0.14). Bland- Altman analysis revealed a large disagreement in fat oxidation between the DISCONFATmax and CONEX; the upper limit of agreement was 0.13 (g.min-1) and the lower limit of agreement was ¡V0.03 (g.min-1). These data suggest that the CONEX and DISCONFATmax protocols did not elicit different rates of fat oxidation (g.min-1). However, the individual variability in fat oxidation was large, particularly in the DISCON-FATmax test. Further research is needed to ascertain the validity of graded exercise tests for predicting fat oxidation during constant load exercise sessions. The aim of Study 3 was to compare the impact of two different intensities of four weeks of exercise training on fat oxidation, NEAT, and appetite in overweight and obese men. Using a cross-over design 11 participants (BMI = 29 ¡Ó 4 kg/m2; age = 27 ¡Ó 4 y) participated in a training study and were randomly assigned initially to: [1] a lowintensity (45%ƒtV O2max) exercise (LIT) or [2] a high-intensity interval (alternate 30 s at 90%ƒtV O2max followed by 30 s rest) exercise (HIIT) 40-min duration, three times a week. Participants completed four weeks of supervised training and between cross-over had a two week washout period. At baseline and the end of each exercise intervention,ƒtV O2max, fat oxidation, and NEAT were measured. Fat oxidation was determined during a standard 30-min continuous exercise bout at 45%ƒtV O2max. During the steady state exercise expired gases were measured intermittently for 5-min periods and HR was monitored continuously. In each training period, NEAT was measured for seven consecutive days using an accelerometer (RT3) the week before, at week 3 and the week after training. Subjective appetite sensations and food preferences were measured immediately before and after the first exercise session every week for four weeks during both LIT and HIIT. The mean fat oxidation rate during the standard continuous exercise bout at baseline for both LIT and HIIT was 0.14 ¡Ó 0.08 (g.min-1). After four weeks of exercise training, the mean fat oxidation was 0.178 ¡Ó 0.04 and 0.183 ¡Ó 0.04 g.min-1 for LIT and HIIT, respectively. The mean NEAT (counts.min-1) was 45 ¡Ó 18 at baseline, 55 ¡Ó 22 and 44 ¡Ó 16 during training, and 51 ¡Ó 14 and 50 ¡Ó 21 after training for LIT and HIIT, respectively. There was no significant difference in fat oxidation between LIT and HIIT. Moreover, although not statistically significant, there was some evidence to suggest that LIT and HIIT tend to increase fat oxidation during exercise at 45% ƒtV O2max (P = 0.14 and 0.08, respectively). The order of training treatment did not significantly influence changes in fat oxidation, NEAT, and appetite. NEAT (counts.min-1) was not significantly different in the week following training for either LIT or HIIT. Although not statistically significant (P = 0.08), NEAT was 20% lower during week 3 of exercise training in HIIT compared with LIT. Examination of appetite sensations revealed differences in the intensity of hunger, with higher ratings after LIT compared with HIIT. No differences were found in preferences for high-fat sweet foods between LIT and HIIT. In conclusion, the results of this thesis suggest that while fat oxidation during steady state exercise was not affected by the level of exercise intensity, there is strong evidence to suggest that intense exercise could have a debilitative effect on NEAT.
Resumo:
The increasing prevalence of obesity in society has been associated with a number of atherogenic risk factors such as insulin resistance. Aerobic training is often recommended as a strategy to induce weight loss, with a greater impact of high-intensity levels on cardiovascular function and insulin sensitivity, and a greater impact of moderate-intensity levels on fat oxidation. Anaerobic high-intensity (supramaximal) interval training has been advocated to improve cardiovascular function, insulin sensitivity and fat oxidation. However, obese individuals tend to have a lower tolerance of high-intensity exercise due to discomfort. Furthermore, some obese individuals may compensate for the increased energy expenditure by eating more and/or becoming less active. Recently, both moderate- and high-intensity aerobic interval training have been advocated as alternative approaches. However, it is still uncertain as to which approach is more effective in terms of increasing fat oxidation given the issues with levels of fitness and motivation, and compensatory behaviours. Accordingly, the objectives of this thesis were to compare the influence of moderate- and high-intensity interval training on fat oxidation and eating behaviour in overweight/obese men. Two exercise interventions were undertaken by 10-12 overweight/obese men to compare their responses to study variables, including fat oxidation and eating behaviour during moderate- and high-intensity interval training (MIIT and HIIT). The acute training intervention was a methodological study designed to examine the validity of using exercise intensity from the graded exercise test (GXT) - which measured the intensity that elicits maximal fat oxidation (FATmax) - to prescribe interval training during 30-min MIIT. The 30-min MIIT session involved 5-min repetitions of workloads 20% below and 20% above the FATmax. The acute intervention was extended to involve HIIT in a cross-over design to compare the influence of MIIT and HIIT on eating behaviour using subjective appetite sensation and food preference through the liking and wanting test. The HIIT consisted of 15-sec interval training at 85 %VO2peak interspersed by 15-sec unloaded recovery, with a total mechanical work equal to MIIT. The medium term training intervention was a cross-over 4-week (12 sessions) MIIT and HIIT exercise training with a 6-week detraining washout period. The MIIT sessions consisted of 5-min cycling stages at ±20% of mechanical work at 45 %VO2peak, and the HIIT sessions consisted of repetitive 30-sec work at 90 %VO2peak and 30-sec interval rests, during identical exercise sessions of between 30 and 45 mins. Assessments included a constant-load test (45 %VO2peak for 45 mins) followed by 60-min recovery at baseline and the end of 4-week training, to determine fat oxidation rate. Participants’ responses to exercise were measured using blood lactate (BLa), heart rate (HR) and rating of perceived exertion (RPE) and were measured during the constant-load test and in the first intervention training session of every week during training. Eating behaviour responses were assessed by measuring subjective appetite sensations, liking and wanting and ad libitum energy intake. Results of the acute intervention showed that FATmax is a valid method to estimate VO2 and BLa, but is not valid to estimate HR and RPE in the MIIT session. While the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax (0.16 ±0.09 and 0.14 ±0.08 g/min, respectively), fat oxidation was significantly higher at minute 25 of MIIT (P≤0.01). In addition, there was no significant difference between MIIT and HIIT in the rate of appetite sensations after exercise, but there was a tendency towards a lower rate of hunger after HIIT. Different intensities of interval exercise also did not affect explicit liking or implicit wanting. Results of the medium-term intervention indicated that current interval training levels did not affect body composition, fasting insulin and fasting glucose. Maximal aerobic capacity significantly increased (P≤0.01) (2.8 and 7.0% after MIIT and HIIT respectively) during GXT, and fat oxidation significantly increased (P≤0.01) (96 and 43% after MIIT and HIIT respectively) during the acute constant-load exercise test. RPE significantly decreased after HIIT greater than MIIT (P≤0.05), and the decrease in BLa was greater during the constant-load test after HIIT than MIIT, but this difference did not reach statistical significance (P=0.09). In addition, following constant-load exercise, exercise-induced hunger and desire to eat decreased after HIIT greater than MIIT but were not significant (p value for desire to eat was 0.07). Exercise-induced liking of high-fat sweet (HFSW) and high-fat non-sweet (HFNS) foods increased after MIIT and decreased after HIIT (p value for HFNS was 0.09). The intervention explained 12.4% of the change in fat intake (p = 0.07). This research is significant in that it confirmed two points in the acute study. While the rate of fat oxidation increased during MIIT, the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax. In addition, manipulating the intensity of acute interval exercise did not affect appetite sensations and liking and wanting. In the medium-term intervention, constant-load exercise-induced fat oxidation significantly increased after interval training, independent of exercise intensity. In addition, desire to eat, explicit liking for HFNS and fat intake collectively confirmed that MIIT is accompanied by a greater compensation of eating behaviour than HIIT. Findings from this research will assist in developing exercise strategies to provide obese men with various training options. In addition, the finding that overweight/obese men expressed a lower RPE and decreased BLa after HIIT compared with MIIT is contrary to the view that obese individuals may not tolerate high-intensity interval training. Therefore, high-intensity interval training can be advocated among the obese adult male population. Future studies may extend this work by using a longer-term intervention.
Resumo:
Objective: In the majority of exercise intervention studies, the aggregate reported weight loss is often small. The efficacy of exercise as a weight loss tool remains in question. The aim of the present study was to investigate the variability in appetite and body weight when participants engaged in a supervised and monitored exercise programme. ---------- Design: Fifty-eight obese men and women (BMI = 31·8 ± 4·5 kg/m2) were prescribed exercise to expend approximately 2092 kJ (500 kcal) per session, five times a week at an intensity of 70 % maximum heart rate for 12 weeks under supervised conditions in the research unit. Body weight and composition, total daily energy intake and various health markers were measured at weeks 0, 4, 8 and 12. ---------- Results: Mean reduction in body weight (3·2 ± 1·98 kg) was significant (P < 0·001); however, there was large individual variability (−14·7 to +2·7 kg). This large variability could be largely attributed to the differences in energy intake over the 12-week intervention. Those participants who failed to lose meaningful weight increased their food intake and reduced intake of fruits and vegetables. ---------- Conclusion: These data have demonstrated that even when exercise energy expenditure is high, a healthy diet is still required for weight loss to occur in many people.
Resumo:
Purpose: To examine the influence of two different fast-start pacing strategies on performance and oxygen consumption (V˙O2) during cycle ergometer time trials lasting ∼5 min. Methods: Eight trained male cyclists performed four cycle ergometer time trials whereby the total work completed (113 ± 11.5 kJ; mean ± SD) was identical to the better of two 5-min self-paced familiarization trials. During the performance trials, initial power output was manipulated to induce either an all-out or a fast start. Power output during the first 60 s of the fast-start trial was maintained at 471.0 ± 48.0 W, whereas the all-out start approximated a maximal starting effort for the first 15 s (mean power: 753.6 ± 76.5 W) followed by 45 s at a constant power output (376.8 ± 38.5 W). Irrespective of starting strategy, power output was controlled so that participants would complete the first quarter of the trial (28.3 ± 2.9 kJ) in 60 s. Participants performed two trials using each condition, with their fastest time trial compared. Results: Performance time was significantly faster when cyclists adopted the all-out start (4 min 48 s ± 8 s) compared with the fast start (4 min 51 s ± 8 s; P < 0.05). The first-quarter V˙O2 during the all-out start trial (3.4 ± 0.4 L·min-1) was significantly higher than during the fast-start trial (3.1 ± 0.4 L·min-1; P < 0.05). After removal of an outlier, the percentage increase in first-quarter V˙O2 was significantly correlated (r = -0.86, P < 0.05) with the relative difference in finishing time. Conclusions: An all-out start produces superior middle distance cycling performance when compared with a fast start. The improvement in performance may be due to a faster V˙O2 response rather than time saved due to a rapid acceleration.
Resumo:
Background The preservation of meniscal tissue is important to protect joint surfaces. Purpose We have an aggressive approach to meniscal repair, including repairing tears other than those classically suited to repair. Here we present the medium- to long-term outcome of meniscal repair (inside-out) in elite athletes. Study Design Case series; Level of evidence, 4. Methods Forty-two elite athletes underwent 45 meniscal repairs. All repairs were performed using an arthroscopically assisted inside-out technique. Eighty-three percent of these athletes had ACL reconstruction at the same time. Patients returned a completed questionnaire (including Lysholm and International Knee Documentation Committee [IKDC] scores). Mean follow-up was 8.5 years. Failure was defined by patients developing symptoms of joint line pain and/or locking or swelling requiring repeat arthroscopy and partial meniscectomy. Results The average Lysholm and subjective IKDC scores were 89.6 and 85.4, respectively. Eighty-one percent of patients returned to their main sport and most to a similar level at a mean time of 10.4 months after repair, reflecting the high level of ACL reconstruction in this group. We identified 11 definite failures, 10 medial and 1 lateral meniscus, that required excision; this represents a 24% failure rate. We identified 1 further patient who had possible failed repairs, giving a worst-case failure rate of 26.7% at a mean of 42 months after surgery. However, 7 of these failures were associated with a further injury. Therefore, the atraumatic failure rate was 11%. Age and size and location of the tears were not associated with a higher failure rate. Medial meniscal repairs were significantly more likely to fail than lateral meniscal repairs, with a failure rate of 36.4% and 5.6%, respectively (P < .05). Conclusion Meniscal repair and healing are possible, and most elite athletes can return to their preinjury level of activity.
Resumo:
Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.
Resumo:
Photocatalytic water splitting is a process which could potentially lead to commercially viable solar hydrogen production. This thesis uses an engineering perspective to investigate the technology. The effect of light intensity and temperature on photocatalytic water splitting was examined to evaluate the prospect of using solar concentration to increase the feasibility of the process. P25 TiO2 films deposited on conducting glass were used as photocatalyst electrodes and coupled with platinum electrodes which were also deposited on conducting glass. These films were used to form a photocatalysis cell and illuminated with a Xenon arc lamp to simulate solar light at intensities up to 50 suns. They were also tested at temperatures between 20°C and 100°C. The reaction demonstrated a sub-linear relationship with intensity. Photocurrent was proportional to intensity with an exponential value of 0.627. Increasing temperature resulted in an exponential relationship. This proved to follow an Arrhenius relationship with an activation energy of 10.3 kJ mol-1 and a pre-exponential factor of approximately 8.7×103. These results then formed the basis of a mathematical model which extrapolated beyond the range of the experimental tests. This model shows that the loss of efficiency from performing the reaction under high light intensity is offset by the increased reaction rate and efficiency from the associated temperature increase. This is an important finding for photocatalytic water splitting. It will direct future research in system design and materials research and may provide an avenue for the commercialisation of this technology.
Resumo:
Although there is a paucity of scientific support for the benefits of warm-up, athletes commonly warm up prior to activity with the intention of improving performance and reducing the incidence of injuries. The purpose of this study was to examine the role of warm-up intensity on both range of motion (ROM) and anaerobic performance. Nine males (age = 21.7 +/- 1.6 years, height = 1.77 +/- 0.04 m, weight = 80.2 +/- 6.8 kg, and VO2max = 60.4 +/- 5.4 ml/kg/min) completed four trials. Each trial consisted of hip, knee, and ankle ROM evaluation using an electronic inclinometer and an anaerobic capacity test on the treadmill (time to fatigue at 13 km/hr and 20% grade). Subjects underwent no warm-up or a warm-up of 15 minutes running at 60, 70 or 80% VO2max followed by a series of lower limb stretches. Intensity of warm-up had little effect on ROM, since ankle dorsiflexion and hip extension significantly increased in all warm-up conditions, hip flexion significantly increased only after the 80% VO2max warm-up, and knee flexion did not change after any warm-up. Heart rate and body temperature were significantly increased (p < 0.05) prior to anaerobic performance for each of the warm-up conditions, but anaerobic performance improved significantly only after warm-up at 60% VO2max (10%) and 70% VO2max (13%). A 15-minute warm-up at an intensity of 60-70% VO2max is therefore recommended to improve ROM and enhance subsequent anaerobic performance.
Resumo:
AIMS: Increases in inflammatory markers, hepatic enzymes and physical inactivity are associated with the development of the metabolic syndrome (MetS). We examined whether inflammatory markers and hepatic enzymes are correlated with traditional risk factors for MetS and studied the effects of resistance training (RT) on these emerging risk factors in individuals with a high number of metabolic risk factors (HiMF, 2.9 +/- 0.8) and those with a low number of metabolic risk factors (LoMF, 0.5 +/- 0.5). METHODS: Twenty-eight men and 27 women aged 50.8 +/- 6.5 years (mean +/- sd) participated in the study. Participants were randomized to four groups, HiMF training (HiMFT), HiMF control (HiMFC), LoMF training (LoMFT) and LoMF control (LoMFC). Before and after 10 weeks of RT [3 days/week, seven exercises, three sets with intensity gradually increased from 40-50% of one repetition maximum (1RM) to 75-85% of 1RM], blood samples were obtained for the measurement of pro-inflammatory cytokines, C-reactive protein (CRP), gamma-glutamyltransferase (GGT) and alanine aminotransferase (ALT). RESULTS: At baseline, HiMF had higher interleukin-6 (33.9%), CRP (57.1%), GGT (45.2%) and ALT (40.6%) levels, compared with LoMF (all P < 0.05). CRP, GGT and ALT correlated with the number of risk factors (r = 0.48, 0.51 and 0.57, respectively, all P < 0.01) and with other anthropometric and clinical measures (r range from 0.26 to 0.60, P < 0.05). RT did not significantly alter inflammatory markers or hepatic enzymes (all P > 0.05). CONCLUSIONS: HiMF was associated with increased inflammatory markers and hepatic enzyme concentrations. RT did not reduce inflammatory markers and hepatic enzymes in individuals with HiMF.
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The purpose of this study was to compare the effects of exercise intensity and exercise-induced muscle damage on changes in anti-inflammatory cytokines and other inflammatory mediators. Nine well-trained male runners completed three different exercise trials on separate occasions: (1) level treadmill running at 60% VO2max (moderate-intensity trial) for 60 min; (2) level treadmill running at 85% VO2max (high-intensity trial) for 60 min; (3) downhill treadmill running (-10% gradient) at 60% VO2max (downhill running trial) for 45 min. Blood was sampled before, immediately after and 1 h after exercise. Plasma was analyzed for interleukin-1 receptor antagonist (IL-1ra), IL-4, IL-5, IL-10, IL-12p40, IL-13, monocyte chemotactic protein-1 (MCP-1), prostaglandin E(2), leukotriene B(4) and heat shock protein 70 (HSP70). The plasma concentrations of IL-1ra, IL-12p40, MCP-1 and HSP70 increased significantly (P<0.05) after all three trials. Plasma prostaglandin E(2) concentration increased significantly after the downhill running and high-intensity trials, while plasma IL-10 concentration increased significantly only after the high-intensity trial. IL-4 and leukotriene B(4) did not increase significantly after exercise. Plasma IL-1ra and IL-10 concentrations were significantly higher (P<0.05) after the high-intensity trial than after both the moderate-intensity and downhill running trials. Therefore, following exercise up to 1 h duration, exercise intensity appears to have a greater effect on anti-inflammatory cytokine production than exercise-induced muscle damage
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The purpose of the present study was to examine the influence of 3 different high-intensity interval training regimens on the first and second ventilatory thresholds (VT1 and VT2), anaerobic capacity (ANC), and plasma volume (PV) in well-trained endurance cyclists. Before and after 2 and 4 weeks of training, 38 well-trained cyclists (VO2peak = 64.5 +/- 5.2 ml[middle dot]kg-1[middle dot]min-1) performed (a) a progressive cycle test to measure VO2peak, peak power output (PPO), VT1, and VT2; (b) a time to exhaustion test (Tmax) at their VO2peak power output (Pmax); and (c) a 40-km time-trial (TT40). Subjects were assigned to 1 of 4 training groups (group 1: n = 8, 8 3 60% Tmax at Pmax, 1:2 work-recovery ratio; group 2: n = 9, 8 x 60% Tmax at Pmax, recovery at 65% maximum heart rate; group 3: n = 10, 12 x 30 seconds at 175% PPO, 4.5-minute recovery; control group: n = 11). The TT40 performance, VO2peak, VT1,VT2, and ANC were all significantly increased in groups 1, 2, and 3 (p < 0.05) but not in the control group. However, PV did not change in response to the 4-week training program. Changes in TT40 performance were modestly related to the changes in VO2peak, VT1, VT2, and ANC (r = 0.41, 0.34, 0.42, and 0.40, respectively; all p < 0.05). In conclusion, the improvements in TT40 performance were related to significant increases in VO2peak, VT1,VT2, and ANC but were not accompanied by significant changes in PV. Thus, peripheral adaptations rather than central adaptations are likely responsible for the improved performances witnessed in well-trained endurance athletes following various forms of high-intensity interval training programs.
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Diet Induced Thermogenesis (DIT) is the energy expended consequent to meal consumption, and reflects the energy required for the processing and digestion of food consumed throughout each day. Although DIT is the total energy expended across a day in digestive processes to a number of meals, most studies measure thermogenesis in response to a single meal (Meal Induced Thermogenesis: MIT) as a representation of an individual’s thermogenic response to acute food ingestion. As a component of energy expenditure, DIT may have a contributing role in weight gain and weight loss. While the evidence is inconsistent, research has tended to reveal a suppressed MIT response in obese compared to lean individuals, which identifies individuals with an efficient storage of food energy, hence a greater tendency for weight gain. Appetite is another factor regulating body weight through its influence on energy intake. Preliminary research has shown a potential link between MIT and postprandial appetite as both are responses to food ingestion and have a similar response dependent upon the macronutrient content of food. There is a growing interest in understanding how both MIT and appetite are modified with changes in diet, activity levels and body size. However, the findings from MIT research have been highly inconsistent, potentially due to the vastly divergent protocols used for its measurement. Therefore, the main theme of this thesis was firstly, to address some of the methodological issues associated with measuring MIT. Additionally this thesis aimed to measure postprandial appetite simultaneously to MIT to test for any relationships between these meal-induced variables and to assess changes that occur in MIT and postprandial appetite during periods of energy restriction (ER) and following weight loss. Two separate studies were conducted to achieve these aims. Based on the increasing prevalence of obesity, it is important to develop accurate methodologies for measuring the components potentially contributing to its development and to understand the variability within these variables. Therefore, the aim of Study One was to establish a protocol for measuring the thermogenic response to a single test meal (MIT), as a representation of DIT across a day. This was done by determining the reproducibility of MIT with a continuous measurement protocol and determining the effect of measurement duration. The benefit of a fixed resting metabolic rate (RMR), which is a single measure of RMR used to calculate each subsequent measure of MIT, compared to separate baseline RMRs, which are separate measures of RMR measured immediately prior to each MIT test meal to calculate each measure of MIT, was also assessed to determine the method with greater reproducibility. Subsidiary aims were to measure postprandial appetite simultaneously to MIT, to determine its reproducibility between days and to assess potential relationships between these two variables. Ten healthy individuals (5 males, 5 females, age = 30.2 ± 7.6 years, BMI = 22.3 ± 1.9 kg/m2, %Fat Mass = 27.6 ± 5.9%) undertook three testing sessions within a 1-4 week time period. During the first visit, participants had their body composition measured using DXA for descriptive purposes, then had an initial 30-minute measure of RMR to familiarise them with the testing and to be used as a fixed baseline for calculating MIT. During the second and third testing sessions, MIT was measured. Measures of RMR and MIT were undertaken using a metabolic cart with a ventilated hood to measure energy expenditure via indirect calorimetry with participants in a semi-reclined position. The procedure on each MIT test day was: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard 576 kcal breakfast (54.3% CHO, 14.3% PRO, 31.4% FAT), comprising muesli, milk toast, butter, jam and juice, and 3) six hours of measuring MIT with two, ten-minute breaks at 3 and 4.5 hours for participants to visit the bathroom. On the MIT test days, pre and post breakfast then at 45-minute intervals, participants rated their subjective appetite, alertness and comfort on visual analogue scales (VAS). Prior to each test, participants were required to be fasted for 12 hours, and have undertaken no high intensity physical activity for the previous 48 hours. Despite no significant group changes in the MIT response between days, individual variability was high with an average between-day CV of 33%, which was not significantly improved by the use of a fixed RMR to 31%. The 95% limits of agreements which ranged from 9.9% of energy intake (%EI) to -10.7%EI with the baseline RMRs and between 9.6%EI to -12.4%EI with the fixed RMR, indicated very large changes relative to the size of the average MIT response (MIT 1: 8.4%EI, 13.3%EI; MIT 2: 8.8%EI, 14.7%EI; baseline and fixed RMRs respectively). After just three hours, the between-day CV with the baseline RMR was 26%, which may indicate an enhanced MIT reproducibility with shorter measurement durations. On average, 76, 89, and 96% of the six-hour MIT response was completed within three, four and five hours, respectively. Strong correlations were found between MIT at each of these time points and the total six-hour MIT (range for correlations r = 0.990 to 0.998; P < 0.01). The reproducibility of the proportion of the six-hour MIT completed at 3, 4 and 5 hours was reproducible (between-day CVs ≤ 8.5%). This indicated the suitability to use shorter durations on repeated occasions and a similar percent of the total response to be completed. There was a lack of strong evidence of any relationship between the magnitude of the MIT response and subjective postprandial appetite. Given a six-hour protocol places a considerable burden on participants, these results suggests that a post-meal measurement period of only three hours is sufficient to produce valid information on the metabolic response to a meal. However while there was no mean change in MIT between test days, individual variability was large. Further research is required to better understand which factors best explain the between-day variability in this physiological measure. With such a high prevalence of obesity, dieting has become a necessity to reduce body weight. However, during periods of ER, metabolic and appetite adaptations can occur which may impede weight loss. Understanding how metabolic and appetite factors change during ER and weight loss is important for designing optimal weight loss protocols. The purpose of Study Two was to measure the changes in the MIT response and subjective postprandial appetite during either continuous (CONT) or intermittent (INT) ER and following post diet energy balance (post-diet EB). Thirty-six obese male participants were randomly assigned to either the CONT (Age = 38.6 ± 7.0 years, weight = 109.8 ± 9.2 kg, % fat mass = 38.2 ± 5.2%) or INT diet groups (Age = 39.1 ± 9.1 years, weight = 107.1 ± 12.5 kg, % fat mass = 39.6 ± 6.8%). The study was divided into three phases: a four-week baseline (BL) phase where participants were provided with a diet to maintain body weight, an ER phase lasting either 16 (CONT) or 30 (INT) weeks, where participants were provided with a diet which supplied 67% of their energy balance requirements to induce weight loss and an eight-week post-diet EB phase, providing a diet to maintain body weight post weight loss. The INT ER phase was delivered as eight, two-week blocks of ER interspersed with two-week blocks designed to achieve weight maintenance. Energy requirements for each phase were predicted based on measured RMR, and adjusted throughout the study to account for changes in RMR. All participants completed MIT and appetite tests during BL and the ER phase. Nine CONT and 15 INT participants completed the post-diet EB MIT and 14 INT and 15 CONT participants completed the post-diet EB appetite tests. The MIT test day protocol was as follows: 1) a baseline RMR measured for 30 minutes, 2) a 15-minute break in the measure to consume a standard breakfast meal (874 kcal, 53.3% CHO, 14.5% PRO, 32.2% FAT), and 3) three hours of measuring MIT. MIT was calculated as the energy expenditure above the pre-meal RMR. Appetite test days were undertaken on a separate day using the same 576 kcal breakfast used in Study One. VAS were used to assess appetite pre and post breakfast, at one hour post breakfast then a further three times at 45-minute intervals. Appetite ratings were calculated for hunger and fullness as both the intra-meal change in appetite and the AUC. The three-hour MIT response at BL, ER and post-diet EB respectively were 5.4 ± 1.4%EI, 5.1 ± 1.3%EI and 5.0 ± 0.8%EI for the CONT group and 4.4 ± 1.0%EI, 4.7 ± 1.0%EI and 4.8 ± 0.8%EI for the INT group. Compared to BL, neither group had significant changes in their MIT response during ER or post-diet EB. There were no significant time by group interactions (p = 0.17) indicating a similar response to ER and post-diet EB in both groups. Contrary to what was hypothesised, there was a significant increase in postprandial AUC fullness in response to ER in both groups (p < 0.05). However, there were no significant changes in any of the other postprandial hunger or fullness variables. Despite no changes in MIT in both the CONT or INT group in response to ER or post-diet EB and only a minor increase in postprandial AUC fullness, the individual changes in MIT and postprandial appetite in response to ER were large. However those with the greatest MIT changes did not have the greatest changes in postprandial appetite. This study shows that postprandial appetite and MIT are unlikely to be altered during ER and are unlikely to hinder weight loss. Additionally, there were no changes in MIT in response to weight loss, indicating that body weight did not influence the magnitude of the MIT response. There were large individual changes in both variables, however further research is required to determine whether these changes were real compensatory changes to ER or simply between-day variation. Overall, the results of this thesis add to the current literature by showing the large variability of continuous MIT measurements, which make it difficult to compare MIT between groups and in response to diet interventions. This thesis was able to provide evidence to suggest that shorter measures may provide equally valid information about the total MIT response and can therefore be utilised in future research in order to reduce the burden of long measurements durations. This thesis indicates that MIT and postprandial subjective appetite are most likely independent of each other. This thesis also shows that, on average, energy restriction was not associated with compensatory changes in MIT and postprandial appetite that would have impeded weight loss. However, the large inter-individual variability supports the need to examine individual responses in more detail.
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Purpose Commencing selected workouts with low muscle glycogen availability augments several markers of training adaptation compared with undertaking the same sessions with normal glycogen content. However, low glycogen availability reduces the capacity to perform high-intensity (>85% of peak aerobic power (V·O2peak)) endurance exercise. We determined whether a low dose of caffeine could partially rescue the reduction in maximal self-selected power output observed when individuals commenced high-intensity interval training with low (LOW) compared with normal (NORM) glycogen availability. Methods Twelve endurance-trained cyclists/triathletes performed four experimental trials using a double-blind Latin square design. Muscle glycogen content was manipulated via exercise–diet interventions so that two experimental trials were commenced with LOW and two with NORM muscle glycogen availability. Sixty minutes before an experimental trial, subjects ingested a capsule containing anhydrous caffeine (CAFF, 3 mg-1·kg-1 body mass) or placebo (PLBO). Instantaneous power output was measured throughout high-intensity interval training (8 × 5-min bouts at maximum self-selected intensity with 1-min recovery). Results There were significant main effects for both preexercise glycogen content and caffeine ingestion on power output. LOW reduced power output by approximately 8% compared with NORM (P < 0.01), whereas caffeine increased power output by 2.8% and 3.5% for NORM and LOW, respectively, (P < 0.01). Conclusion We conclude that caffeine enhanced power output independently of muscle glycogen concentration but could not fully restore power output to levels commensurate with that when subjects commenced exercise with normal glycogen availability. However, the reported increase in power output does provide a likely performance benefit and may provide a means to further enhance the already augmented training response observed when selected sessions are commenced with reduced muscle glycogen availability. It has long been known that endurance training induces a multitude of metabolic and morphological adaptations that improve the resistance of the trained musculature to fatigue and enhance endurance capacity and/or exercise performance (13). Accumulating evidence now suggests that many of these adaptations can be modified by nutrient availability (9–11,21). Growing evidence suggests that training with reduced muscle glycogen using a “train twice every second day” compared with a more traditional “train once daily” approach can enhance the acute training response (29) and markers representative of endurance training adaptation after short-term (3–10 wk) training interventions (8,16,30). Of note is that the superior training adaptation in these previous studies was attained despite a reduction in maximal self-selected power output (16,30). The most obvious factor underlying the reduced intensity during a second training bout is the reduction in muscle glycogen availability. However, there is also the possibility that other metabolic and/or neural factors may be responsible for the power drop-off observed when two exercise bouts are performed in close proximity. Regardless of the precise mechanism(s), there remains the intriguing possibility that the magnitude of training adaptation previously reported in the face of a reduced training intensity (Hulston et al. (16) and Yeo et al.) might be further augmented, and/or other aspects of the training stimulus better preserved, if power output was not compromised. Caffeine ingestion is a possible strategy that might “rescue” the aforementioned reduction in power output that occurs when individuals commence high-intensity interval training (HIT) with low compared with normal glycogen availability. Recent evidence suggests that, at least in endurance-based events, the maximal benefits of caffeine are seen at small to moderate (2–3 mg·kg-1 body mass (BM)) doses (for reviews, see Refs. (3,24)). Accordingly, in this study, we aimed to determine the effect of a low dose of caffeine (3 mg·kg-1 BM) on maximal self-selected power output during HIT commenced with either normal (NORM) or low (LOW) muscle glycogen availability. We hypothesized that even under conditions of low glycogen availability, caffeine would increase maximal self-selected power output and thereby partially rescue the reduction in training intensity observed when individuals commence HIT with low glycogen availability.
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Purpose: Hyperactive platelets contribute to the thrombotic response in humans, and exercise transiently increases platelet function. Caffeine is routinely used by athletes as an ergogenic aid, but the combined effect of exercise and caffeine on platelet function has not been investigated. Methods: Twelve healthy males were randomly assigned to one of four groups and undertook four experimental trials of a high-intensity aerobic interval training (AIT) bout or rest with ingestion of caffeine (3 mg·kg-1) or placebo. AIT was 8 × 5 min at approximately 75% peak power output (approximately 80% V?O2peak) and 1-min recovery (approximately 40% peak power output, approximately 50% V?O2peak) intervals. Blood/urine was collected before, 60, and 90 min after capsule ingestion and analyzed for platelet aggregation/activation. Results: AIT increased platelet reactivity to adenosine diphosphate (placebo 30.3%, caffeine 13.4%, P < 0.05) and collagen (placebo 10.8%, caffeine 5.1%, P < 0.05) compared with rest. Exercise placebo increased adenosine diphosphate-induced aggregation 90 min postingestion compared with baseline (40.5%, P < 0.05), but the increase when exercise was combined with caffeine was small (6.6%). During the resting caffeine protocol, collagen-induced aggregation was reduced (-4.3%, P < 0.05). AIT increased expression of platelet activation marker PAC-1 with exercise placebo (P < 0.05) but not when combined with caffeine. Conclusion: A single bout of AIT increases platelet function, but caffeine ingestion (3 mg·kg) does not exacerbate platelet function at rest or in response to AIT. Our results provide new information showing caffeine at a dose that can elicit ergogenic effects on performance has no detrimental effect on platelet function and may have the potential to attenuate increases in platelet activation and aggregation when undertaking strenuous exercise.