A review of the scientific literature revealed a lack of information regarding the integrated daily activity levels of low-risk pregnant women in contemporary Western society. A prospective, longitudinal study was therefore undertaken to (i) assess the impact of low-risk pregnancy on the daily activity levels of healthy, British primigravid women and (ii) examine the relationship between total maternal daily activity level and pregnancy outcome. The best combination of methods to measure daily activity levels during pregnancy was considered to be a subjective self-report measure used in conjunction with an objective ambulatory activity monitor. These methods were developed and were demonstrated to be both reliable and valid in non-pregnant women. However, the study identified some unique problems in using activity monitors in pregnant women. These problems emanated both from women's reluctance to wear an activity monitor when pregnant and from a need to measure extremely low levels of activity in late gestation. Both data from the ambulatory monitor and the new activity questionnaire demonstrated a overall decrease in mean maternal daily activity levels between 25 & 38 weeks gestation (n=51; p<0.01). This decline masked different maternal responses in different activity domains. The mean occupational activity ratios of women working full-time declined steadily between 16 & 34 weeks gestation (n=25, p<0.01). Women's working hours and the more flexible elements of their work were reduced whilst the frequency of work breaks increased. Between 25 & 38 weeks gestation, mean recreational activity ratios also declined (n=50, p<0.05). Participation in structured sports and exercise ceased and increasing amounts of time were spent within the home. In contrast, mean overall domestic activity ratios were maintained. Between 16 & 38 weeks gestation mean nocturnal activity ratios increased steadily (n=47; p=0.01) To maintain waking activity during pregnancy, women actively engaged in a number of different balancing strategies. These strategies comprised monitoring, prioritising, pacing and forward planning. Despite the changes that occurred in maternal activity behaviour, one of the strongest and most consistent predictors of maternal activity behaviour during pregnancy was that of maternal activity behaviour prior to pregnancy. Occupational activity levels pre-pregnancy were independently associated with maternal daily activity levels at 12,16 & 25 weeks gestation (p=0.004-0.020). Self-efficacy was the only significant predictor of the change in maternal daily activity levels between 25 & 38 weeks gestation (p=0.013). The women who reduced their activity the most were likely to be those individuals who had more difficulty in overcoming perceived barriers to physical activity participation. Five main barriers to physical activity were identified: (i) the physical symptoms of pregnancy (ii) the effect of outside influences (iii) a lack of motivation (iv) a low maternal body image and (v) a lack of time and/or appropriate facilities. Findings suggested that maternal daily activity may impact significantly on pregnancy outcome. Higher maternal daily activity at 16 weeks gestation was independently associated with a lower incidence of emergency caesarean section (p<0.05). Higher maternal daily activity at 38 weeks gestation was independently associated with a higher incidence of an induction of labour (p<0.05). Total daily activity at 25 & 34 weeks gestation was independently and negatively associated with infant birthweight (p<0.05).

Bovine plasmin activity was measured on H-D-valyl-L-leucyl-L-lysyl-4-nitroanilide by following absorbance changes at 405 nm. Steady-state kinetic parameters Vmax, Km, KI, and KI' were estimated. Bovine plasmin is competitively inhibited by casein and has a Kcat of .0158 ΔA405/min/nM, Km of .107 mM substrate, and KI of .86 mg/ml casein. Bovine plasmin can be measured directly in bovine milk without interference from casein. A total of 380 milk samples from nineteen Holstein (one herd) and nineteen Jersey (one herd) cows was collected monthly during one lactation period. Samples from each cow were analyzed for fat, protein, plasmin activity, plasminogen, pH, SCC, clotting time, curd firming rate, and final curd firmness. Three age groups form each breed/herd were chosen; first, third, and fourth and later lactations. Plasmin activity in milk was most affected by lactation number, with milk from fourth- and later-lactation cows having higher activity than milk from first- or third- lactation cows. Plasmin activity in milk increased during lactation but was not affected by breed/herd, pH, protein, or fat. Plasminogen averaged 5.4 times the plasmin activity in milk and increased during the first five months of lactation. Plasmin activity was higher in milk collected ruing summer and fall but plasminogen was higher in milk collected during fall and winter. Percentage of the total (plasmin+plasminogen) enzyme activated to plasmin increased in late-lactation milk and in milk from fourth- and later-lactation cows. Plasmin activity did not affect any milk clotting parameters in this study. Increased protein in milk resulted in shorter clotting times. When statistically adjusted for protein content, clotting time was longer in milk from the Holstein herd compared to the Jersey herd. Curd firming rate was increased in milk with higher protein and fat. Milk samples collected in the fall had faster firming rates than milk from other seasons. Firming rates remained constant during lactation but increased with higher protein and fat content. Jersey herd milk produced firmer curd than Holstein herd milk and milk collected in the fall had firmer curd than during the other seasons.

Technological advances in physical activity measurement have increased the development and utilization of accelerometers and pedometers for assessing physical activity in controlled and free-living conditions. Individual differences in leg length, stride length and stride frequency may affect the reliability and validity of accelerometers in estimating energy expenditure. To address this theory, this thesis investigated the influence of leg length, stride length and stride frequency on accelerometer counts and energy expenditure using four accelerometers (AMP, Actical, MTI, and RT3) and one pedometer (Yamax). Eighty-six participants, age 8 to 40 (17.6 ± 8.0) years performed three ten-minute bouts of treadmill activity at self-selected speeds (4 to 12 km/h). Energy expenditure (kcal/min) was measured through expired gas analysis and used as the criterion standard to compare physical activity data from activity monitors. A 3 (models) x 2 (duplicates of each model) x 3 (speeds) x 7 (minutes) repeated measures ANOVA was used to assess intra-device, inter-device, and inter-model reliability. Coefficients of variation were calculated to compare within-device variation and between-device variation in accelerometer counts. Differences between measured and predicted energy expenditure were assessed across five height categories to determine the influence of leg length on the validity of accelerometer/pedometer data. Regression equations for each model were developed using mean activity counts/steps generated for each speed, adjusting for various predictor variables (i.e., age, weight, leg length). These were compared to model-specific equations to determine whether the addition of certain variables might explain more variance in energy expenditure. Leg length and stride frequency directly influenced variability in accelerometer data and thus predicted energy expenditure. At high speeds and stride frequencies counts began to level off in the Actical, however this did not occur in the other devices. Intra-device and inter-device variation in accelerometer counts was less than 10% and was lowest at very high speeds for the Actical, MTI, and RT3 (p<0.05). When compared to measured values, energy expenditure was consistently underestimated by the AMP, Actical, and Yamax models and consistently overestimated by the RT3 across speed. The MTI underestimated and overestimated energy expenditure depending on speed. Energy expenditure was both underestimated and overestimated to the greatest extent during the treadmill run for the tallest participants (p<0.05). Accelerometer counts or pedometer steps, when entered into regression equations with age, weight and leg length, explained from 85 to 94 % of the variance in measured energy expenditure, supporting the inclusion of these variables within manufacturer-based equations. These results suggest that individual differences in leg length and stride frequency affect the reliability and validity of accelerometer data and therefore must be controlled for when using accelerometry to predict energy expenditure.

Technological advances in physical activity measurement have increased the development and utilization of accelerometers and pedometers for assessing physical activity in controlled and free-living conditions. Individual differences in leg length, stride length and stride frequency may affect the reliability and validity of accelerometers in estimating energy expenditure. To address this theory, this thesis investigated the influence of leg length, stride length and stride frequency on accelerometer counts and energy expenditure using four accelerometers (AMP, Actical, MTI, and RT3) and one pedometer (Yamax). Eighty-six participants, age 8 to 40 (17.6 ± 8.0) years performed three ten-minute bouts of treadmill activity at self-selected speeds (4 to 12 km/h). Energy expenditure (kcal/min) was measured through expired gas analysis and used as the criterion standard to compare physical activity data from activity monitors. A 3 (models) x 2 (duplicates of each model) x 3 (speeds) x 7 (minutes) repeated measures ANOVA was used to assess intra-device, inter-device, and inter-model reliability. Coefficients of variation were calculated to compare within-device variation and between-device variation in accelerometer counts. Differences between measured and predicted energy expenditure were assessed across five height categories to determine the influence of leg length on the validity of accelerometer/pedometer data. Regression equations for each model were developed using mean activity counts/steps generated for each speed, adjusting for various predictor variables (i.e., age, weight, leg length). These were compared to model-specific equations to determine whether the addition of certain variables might explain more variance in energy expenditure. Leg length and stride frequency directly influenced variability in accelerometer data and thus predicted energy expenditure. At high speeds and stride frequencies counts began to level off in the Actical, however this did not occur in the other devices. Intra-device and inter-device variation in accelerometer counts was less than 10% and was lowest at very high speeds for the Actical, MTI, and RT3 (p<0.05). When compared to measured values, energy expenditure was consistently underestimated by the AMP, Actical, and Yamax models and consistently overestimated by the RT3 across speed. The MTI underestimated and overestimated energy expenditure depending on speed. Energy expenditure was both underestimated and overestimated to the greatest extent during the treadmill run for the tallest participants (p<0.05). Accelerometer counts or pedometer steps, when entered into regression equations with age, weight and leg length, explained from 85 to 94 % of the variance in measured energy expenditure, supporting the inclusion of these variables within manufacturer-based equations. These results suggest that individual differences in leg length and stride frequency affect the reliability and validity of accelerometer data and therefore must be controlled for when using accelerometry to predict energy expenditure.

INTRODUCTION: Direct observation (DO) systems have been used for decades to assess free-living PA in children. These traditional DO systems identify the highest intensity observed during alternating observe-and-record periods. Using video-taped DO would allow researchers to code activities and contextual information each time the participant changes their behavior. PURPOSE: To develop and test a novel video-based DO system for children’s free-play activity. METHODS: Following iterative DO system development (The Observer XT, Noldus), 28 children (age=8.4 ± 1.5 years) participated in a 30-minute simulated free-play session that was recorded with a GoPro camera. Participants wore a portable indirect calorimetry (IC) device and an accelerometer on the hip (AG-H) and non-dominant wrist (AG-W). The DO system includes Whole Body Movement (body position, main movement pattern) that was further described with four modifiers: 1) Locomotion, 2) Limb Movement, 3) Activity Type, and 4) MET value. To assess intrarater reliability, an expert coder coded six randomly selected videos from the main sample and recoded the same videos one week later. Six novice coders were trained and coded three videos from the subsample to assess interrater reliability. To assess construct validity, total energy expenditure and time spent in activity intensity categories from DO were compared with IC and accelerometer estimates. RESULTS: Percent agreement for intrarater reliability was above 80% except for Locomotion (47%; video 3) and Limb Movement, MET value and Locomotion (19%, 78%, 26%), respectively, video 4). Across all variables, percent agreement for interrater reliability ranged widely from 12%-96%, 0-100%, and 36%-97% for videos 1, 2 and 3, respectively. Mean estimated time spent in PA intensity categories from AG-H overestimated sedentary (SED) and underestimated light, moderate, and moderate-to-vigorous PA (LPA, MPA, and MVPA; p < 0.001-0.008). AG-W and IC underestimated SED (p=0.03, p=0.03) and LPA (p< 0.001, pONCLUSION: The current DO system is feasible for observing detailed changes in children’s free-play activity. However, refinement to the system must be made to improve reliability before it is adopted as a criterion measure for free-play activity in children.

Pain and movement are intimately connected and nearly universal human experiences. However, our understanding of the extent, significance, and mechanisms of pain-movement relationships is limited. While pain is a normal, protective response to injury and potentially harmful stimuli, prolonged or dysfunctional neuromuscular adaptions in response to pain can contribute to a variety of pain conditions. Alternatively, movement (in the form of global physical activity, individual exercise programs, and/or specific motor learning/functional tasks) is often prescribed to help decrease pain and improve function. While attempts have been made to show an effect of movement on pain or to better understand altered movement strategies in response to pain, much of the research has been limited to animal models or to those with specific persistent or chronic pain conditions limiting generalizability and interpretability. Therefore, this research sought to advance current understanding of the relationships between physical activity and normal variability in centrally- and peripherally-mediated pain in healthy adults. Additionally, we sought to characterize changes in reflexive motor responses in the upper extremity to an endogenous, naturally-occurring, long-lasting acute muscle pain. The results of these investigations indicate that greater, self-reported intense (i.e. vigorous) and leisure activity are more strongly associated with decreased pain sensitivity than is pain modulation or measured activity (via accelerometry). Future research is needed to determine directionality of these relationships. Further, reflexive motor responses to endogenous, acute muscle pain in the upper extremity were not significantly altered indicating that changes in pain-related, movement strategies may be more strongly influenced by supraspinal adaptations. These results may have value in improving understanding of pain-related, movement sequelae and directing future research in this area.

Protein arginine methyltransferases (PRMTs) are enzymes that catalyze the methylation of protein arginine residues, resulting in the formation of monomethylarginine, and/or asymmetric or symmetric dimethylarginines. Although understanding of the PRMTs has grown rapidly over the last few years, several challenges still remain in the PRMT field. Here, we describe the development of two techniques that will be very useful in investigating PRMT regulation, small molecule inhibition, oligomerization, protein-protein interaction, and substrate specificity, which will ultimately lead to the advancement of the PRMT field. Studies have shown that having an N-terminal tag can influence enzyme activity and substrate specificity. The first protocol tackles this problem by developing a way to obtain active untagged recombinant PRMT proteins. The second protocol describes a fast and efficient method for quantitative measurement of AdoMet-dependent methyltranseferase activity with protein substrates. In addition to being very sensitive, this method decreases the processing time for the analysis of PRMT activity to a few minutes compared to weeks by traditional methods, and generates 3000-fold less radioactive waste. We then used these methods to investigate the effect of truncating the NT of human PRMT1 variant 1 (hPRMT1-V1) on enzyme activity, protein-protein interactions, and substrate specificity. Our studies show that the NT of hPRMT1-V1 influences enzymatic activity and protein-protein interactions. In particular, methylation of a variety of protein substrates was more efficient when the first 10 amino acids of hPRMT1v1 were removed, suggesting an autoinhibitory role for this small section of the N-terminus. Likewise, as portions of the NT were removed, the altered hPRMT1v1 constructs were able to interact with more proteins. Overall, my studies suggest the the sequence and length of the NT of hPRMT1v1 is capable of enforcing specific protein interactions.

Conductive polymer composite sensors have shown great potential in identifying gaseous analytes. To more thoroughly understand the physical and chemical mechanism of this type of sensors, a model was developed by combining two sub-models: a conductivity model and a thermodynamic model, which gives a relationship between the vapor concentration of analyte(s) and the change of the sensor signals. In this work, 64 chemiresistors representing eight different carbon concentrations (8–60 vol.% carbon) were constructed by depositing thin films of a carbon black–polyisobutylene composite onto concentric spiral platinum electrodes on a silicon chip. The responses of the sensors were measured in dry air and at various vapor pressures of toluene and trichloroethylene. Three parameters in the conductivity model were determined by fitting the experimental data. It was shown that by applying this model, the sensor responses can be predicted if the vapor pressure is known; furthermore the vapor concentration can be estimated based on the sensor responses. This model will guide the improvement of the design and fabrication of conductive polymer composite sensors for detecting and identifying organic vapors. A novel method was developed to optimize the selection of polymeric materials to be used within a chemiresistor array for anticipated samples without performing preliminary experiments. It is based on the theoretical predicted responses of chemiresistors and the criterion of minimizing the mean square error (MSE) of the chemiresistor array. After the number of chemiresistors to be used in an array and the anticipated sample chemistry are determined, the MSE values of all combinations of the candidate chemiresistors are calculated. The combination which has the minimum MSE value is the best choice. This can become computationally intensive for selection of polymers for large arrays from candidates in a large database. The number of combinations can be reduced by using the branch and bound method to save computation time. This method is suitable for samples at low concentrations where thermodynamic multi-component interactions are linear. To help users apply this polymer selection method for the sensors, a website including 10 solvents and 10 polymers was developed. Users can specify a target sample and obtain the best set of polymers for a sensor array to detect the sample. The activities of trichloroethylene and toluene in polyisobutylene were measured at very low concentrations. The activities for toluene are consistent with published values at higher concentrations. The values for trichloroethylene are a new contribution to the literature.

The radioactive ion implantation wear measuring method (RII) has been used for many years as a tool to make highly sensitive real-time in-situ measurements of wear and corrosion in metallic or ceramic materials. The method consists of the controlled implantation of radioactive ions of limited decay time in a thin layer at the surface of the material. The progressive abrasion of the material results in a decline in radioactivity which is followed to monitor material losses. The application of RII to control the wear of polymers is potentially of interest, but it has been lagging behind because of uncertainties related to possible changes in material properties during and after the implantation, and to the exact shape of implantation profiles. In this thesis, we investigate these issues on two thermoplastic elastomers typically used for making the soles of sport shoes, among which one contains radiation-sensitive unsaturated bonds, using as ions 7Be, 7Li and Kr. The results of the sample characterisation indicate that the 7Be and 7Li implantations, under properly-selected conditions, do not induce significant modifications in the materials. The implantation of a stack of polymer thin films and the activity measurements performed to determine the implantation profile are also presented. The experimental results on the ion implantation profiles and the determination of calibration curves are presented and discussed in comparison with simulated results. The results indicate that it is possible to predict the implantation profile by means of simulations. This bodes well for the application of the RII method to polymer materials. In the last part, an experimental study is presented regarding the possible redistribution of the implanted 7Be after implantation. Since very few existing experimental techniques are able to detect light elements implanted in polymer targets at fluences less or equal to 1012 cm-2, with implantation depths of a few µm, a new method is presented, which implies the use of plasma etching techniques in order to remove layers of polymers and measuring the remaining activity after each step. Our results indicate that a redistribution of the implanted ions takes place during the implantation process, resulting in a scrambling of the initial implantation profile. Nevertheless, provided a suitable methodology be used, wear measurements in polymers by using the RII method are still possible, as we propose in the thesis.

This paper deals with the problem of monitoring the occurrence of the minority events in thermodynamic systems by using thermodynamic sensors based on the principle of balance equilibrium. The basis of this work is to find new sensor arrangement of thermodynamic sensors that allows work in a wide range of workloads of monitored system while maintaining the required sensitivity. Newly designed balance circuit for the sensor arrangement with four active sensors allows active setup of the default balance equilibrium and power matching of the sensor to its immediate surroundings in the system. By designing and optimization of balance circuit was achieved measuring the output response and its conversion to digital format. This enabled numerical analysis of output signal, algorithmic processing of the results and generate a feedback control signal to adjust the equilibrium conditions.