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- Genre: Masters Thesis
This study investigated the effect of environmental heat stress on physiological and performance measures during a ~4 mi time trial (TT) mountain hike in the Phoenix metropolitan area. Participants (n = 12; 7M/5F; age 21.6 ± 2.47 [SD]) climbed ‘A’ mountain (~1 mi) four times on a hot day (HOT; wet bulb globe temperature [WBGT] = 31.6°C) and again on a moderate day (MOD; WBGT = 19.0°C). Physiological and performance measures were made before and throughout the course of each hike. Mean pre-hike hydration status (urine specific gravity [USG]) indicated that participants began both HOT and MOD trials in a euhydrated state (1.016 ± 0.010 and 1.010 ± 0.008, respectively) and means did not differ significantly between trials (p = .085). Time trial performance was impaired by -11% (11.1 minutes) in the HOT trial (105 ± 21.7 min), compared to MOD (93.9 ± 13.1 min) (p = .013). Peak core temperatures were significantly higher in HOT (38.5 ± 0.36°C) versus MOD (38.0 ± 0.30°C) with progressively increasing differences between trials over time (p < .001). Peak ratings of perceived exertion were significantly higher in HOT (14.2 ± 2.38) compared to MOD (11.9 ± 2.02) (p = .007). Relative intensity (percent of age-predicted maximal heart rate [HR]), estimated absolute intensity (metabolic equivalents [METs]), and estimated energy expenditure (MET-h) were all increased in HOT, but not significantly so. The HOT condition reduced predicted maximal aerobic capacity (CRFp) by 6% (p = .026). Sweat rates differed significantly between HOT (1.38 ± 0.53 L/h) and MOD (0.84 ± 0.27 L/h) (p = .01). Percent body mass loss (PBML) did not differ significantly between HOT (1.06 ± 0.95%) and MOD (0.98 ± 0.84%) (p = .869). All repeated measures variables showed significant between-subjects effects (p < .05), indicating individual differences in response to test conditions. Heat stress was shown to negatively affect physiological and performance measures in recreational mountain hikers. However, considerable variation exists between individuals, and the degree of physiological and performance impairment is probably due, in part, to differences in aerobic fitness and acclimatization status rather than pre- or during-performance hydration status.
An algebraic representation of the nucleotide bases is developed. This algebraic representation makes it possible to convert nucleotide sequences into algebraic sequences, apply mathematical ideas and convert results back into nucleotide terms. Using the algebra developed, a mapping is found from the naturally-occurring codons to an alternative set of codons which makes genes constructed from them mutation-tolerant, provided no more than one substitution mutation occurs per codon. The ideas discussed naturally extend to finding codons that can tolerate t arbitrarily chosen number of mutations per codon. Finally, random substitution events are simulated in both a wild-type green fluorescent protein (GFP) gene and its mutol variant and the amino acid sequence expressed from each post-mutation is compared with the amino acid sequence pre-mutation.
This work assumes the existence of synthetic protein-assembling entities that function like tRNAs but can read k nucleotides at a time, with k greater than or equal to 5. The realization of this assumption is presented as a challenge to the research community.
Exertional heat stroke continues to be one of the leading causes of illness and death in sport in the United States, with an athlete’s experienced microclimate varying by venue design and location. A limited number of studies have attempted to determine the relationship between observed wet bulb globe temperature (WBGT) and WBGT derived from regional weather station data. Moreover, only one study has quantified the relationship between regionally modeled and on-site measured WBGT over different athletic surfaces (natural grass, rubber track, and concrete tennis court). The current research expands on previous studies to examine how different athletic surfaces influence the thermal environment in the Phoenix Metropolitan Area using a combination of fieldwork, modeling, and statistical analysis. Meteorological data were collected from 0700–1900hr across 6 days in June and 5 days in August 2019 in Tempe, Arizona at various Sun Devil Athletics facilities. This research also explored the influence of surface temperatures on WBGT and the changes projected under a future warmer climate. Results indicate that based on American College of Sports Medicine guidelines practice would not be cancelled in June (WBGT≥32.3°C); however, in August, ~33% of practice time was lost across multiple surfaces. The second-tier recommendations (WBGT≥30.1°C) to limit intense exercise were reached an average of 7 hours each day for all surfaces in August. Further, WBGT was calculated using data from four Arizona Meteorological Network (AZMET) weather stations to provide regional WBGT values for comparison. The on-site (field/court) WBGT values were consistently higher than regional values and significantly different (p<0.05). Thus, using regionally-modeled WBGT data to guide activity or clothing modification for heat safety may lead to misclassification and unsafe conditions. Surface temperature measurements indicate a maximum temperature (170°F) occurring around solar noon, yet WBGT reached its highest level mid-afternoon and on the artificial turf surface (2–5PM). Climate projections show that WBGT values are expected to rise, further restricting the amount of practice and games than can take place outdoors during the afternoon. The findings from this study can be used to inform athletic trainers and coaches about the thermal environment through WBGT values on-field.
changes in the diffusion, growth, and death parameters was performed, in order to find a set of parameter values that accurately model observed tumor growth for a given patient. Additional changes were made to the diffusion parameters to account for the arrangement of nerve tracts in the brain, resulting in varying rates of diffusion. In general, small changes in the growth rates had a large impact on the outcome of the simulations, and for each patient there exists a set of parameters that allow the model to simulate a tumor that matches observed tumor growth in the patient over a period of two or three months. Furthermore, these results are more accurate with anisotropic diffusion, rather than isotropic diffusion. However, these parameters lead to inaccurate results for patients with tumors that undergo no observable growth over the given time interval. While it is possible to simulate long-term tumor growth, the simulation requires multiple comparisons to available MRI scans in order to find a set of parameters that provide an accurate prognosis.
This study aimed to investigate the effects of specific macronutrient feedings on competitive golf performance and perceived levels of fatigue and alertness. Participants played three, nine hole rounds of golf, consuming an isocaloric beverage as a control (CON), with the addition of carbohydrate (CHO), or combination of protein and carbohydrate (COM). Physiological and performance measurements were taken before, during, and following each nine hole round. Performance measurements include driving accuracy (DA), driving distance (DD), iron accuracy (IA), chipping accuracy (CA), and putting accuracy (PA). Pre-golf hydration status (urine specific gravity [USG]) and Sweat Rate during golf performance showed no significant differences between trials. All nine hole rounds were performed in ~2 hours. Environmental conditions were similar for all three testing days (mean WBGT=10.946). No significant differences were seen in Driving Distance, Driving Accuracy, and Iron Accuracy for all nine holes between groups receiving different macronutrient feedings. Chipping Accuracy was significantly better in CON trial compared to CHO (p=0.004) and COM (p=0.019). No significant differences were seen in putting make percentages. COM trial significantly lowered Perceived Levels of Fatigue (p=0.019) compared to CON. The CHO trial showed significant improvements in DA compared to CON (13.7 vs. 44.1, p=0.012) and COM (13.7 vs. 33.6, p=0.004) in the first four holes. In the last five holes, the COM trial showed significant improvements in DA compared to CHO (17.5 vs. 29.7, p=0.007). Low Handicap golfers (3 +/- 3) performed significantly better than High Handicap golfers (14 +/- 3.6) in DD (265 vs. 241, p<0.001), DA (15.0 vs. 29.3, p=0.004), IA (15.2 vs. 25.2, p<0.001), CA (52.0 vs. 61.5, p=0.027), and PA 5ft (64% vs. 40%, p=0.003). High Handicap players showed no significant differences between the three trials for any golf performance measurements. Low Handicap players showed significant improvements in DA for COM trial compared to CON trial (13.6 vs. 27.6, p=0.003). The results suggest that carbohydrates at the start and a combination of carbohydrate and protein is beneficial at the second part of 9 holes to improve golf performance and maintain levels of fatigue, however, it needs to be investigated how this knowledge will relate to playing more holes.
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.