The role of inflammation in vascular function and pregnancy outcome in the pregnant stroke prone spontaneously hypertensive rat

During pregnancy, the maternal cardiovascular system undergoes major adaptation. One of these changes is a 40-50 % increase in circulating blood volume which requires a systemic remodelling of the vasculature in order to regulate maternal blood pressure and maximise blood supply to the developing placenta and fetus. These changes are broadly conserved between humans and rats making them an appropriate pre-clinical model in which to study the underlying mechanisms of pregnancy-dependent cardiovascular remodelling. Whilst women are normally protected against cardiovascular disease; pregnancy marks a period of time where women are susceptible to cardiovascular complications. Cardiovascular disease is the leading cause of maternal mortality in the United Kingdom; in particular hypertensive conditions are among the most common complications of pregnancy. One of the main underlying pathologies of these pregnancy complications is thought to be a failure of the maternal cardiovascular system to adapt. The remodelling of the uterine arteries, which directly supply the maternal-fetal interface, is paramount to a healthy pregnancy. Failure of the uterine arteries to remodel sufficiently can result in a number of obstetric complications such as preeclampsia, fetal growth restriction and spontaneous pregnancy loss. At present, it is poorly understood whether this deficient vascular response is due to a predisposition from existing maternal cardiovascular risk factors, the physiological changes that occur during pregnancy or a combination of both. Previous work in our group employed the stroke prone spontaneously hypertensive rat (SHRSP) as a model to investigate pregnancy-dependent remodelling of the uterine arteries. The SHRSP develops hypertension from 6 weeks of age and can be contrasted with the control strain, the Wistar Kyoto (WKY) rat. The phenotype of the SHRSP is therefore reflective of the clinical situation of maternal chronic hypertension during pregnancy. We showed that the SHRSP exhibited a deficient uterine artery remodelling response with respect to both structure and function accompanied by a reduction in litter size relative to the WKY at gestational day (GD) 18. A previous intervention study using nifedipine in the SHRSP achieved successful blood pressure reduction from 6 weeks of age and throughout pregnancy; however uterine artery remodelling and litter size at GD18 was not improved. We concluded that the abnormal uterine artery remodelling present in the SHRSP was independent of chronic hypertension. From these findings, we hypothesised that the SHRSP could be a novel model of spontaneously deficient uterine artery remodelling in response to pregnancy which was underpinned by other as yet unidentified cardiovascular risk factors. In Chapter 1 of this thesis, I have characterised the maternal, placental and fetal phenotype in pregnant (GD18) SHRSP and WKY. The pregnant SHRSP exhibit features of left ventricular hypertrophy in response to pregnancy and altered expression of maternal plasma biomarkers which have been previously associated with hypertension in human pregnancy. I developed a protocol for accurate dissection of the rat uteroplacental unit using qPCR probes specific for each layer. This allowed me to make an accurate and specific statement about gene expression in the SHRSP GD18 placenta; where oxidative stress related gene markers were increased in the vascular compartments. The majority of SHRSP placenta presented at GD18 with a blackened ring which encircled the tissue. Further investigation of the placenta using western blot for caspase 3 cleavage determined that this was likely due to increased cell death in the SHRSP placenta. The SHRSP also presented with a loss of one particular placental cell type at GD18: the glycogen cells. These cells could have been the target of cell death in the SHRSP placenta or were utilised early in pregnancy as a source of energy due to the deficient uterine artery blood supply. Blastocyst implantation was not altered but resorption rate was increased between SHRSP and WKY; indicating that the reduction in litter size in the SHRSP was primarily due to late (>GD14) pregnancy loss. Fetal growth was not restricted in SHRSP which led to the conclusion that SHRSP sacrifice part of their litter to deliver a smaller number of healthier pups. Activation of the immune system is a common pathway that has been implicated in the development of both hypertension and adverse pregnancy outcome. In Chapter 2, I proposed that this may be a mechanism of interest in SHRSP pregnancy and measured the pro-inflammatory cytokine, TNFα, as a marker of inflammation in pregnant SHRSP and WKY and in the placentas from these animals. TNFα was up-regulated in maternal plasma and urine from the GD18 SHRSP. In addition, TNFα release was increased from the GD18 SHRSP placenta as was the expression of the pro-inflammatory TNFα receptor 1 (Tnfr1). In order to investigate whether this excess TNFα was detrimental to SHRSP pregnancy, a vehicle-controlled intervention study using etanercept (a monoclonal antibody which works as a TNFα antagonist) was carried out. Etanercept treatment at GD0, 6, 12 and 18 resulted in an improvement in pregnancy outcome in the SHRSP with an increased litter size and reduced resorption rate. Furthermore, there was an improved uterine artery function in GD18 SHRSP treated with etanercept which was associated with an improved uterine artery blood flow over the course of gestation. In Chapter 3, I sought to identify the source of this detrimental excess of TNFα by designing a panel for maternal leukocytes in the blood and placenta at GD18. A population of CD3- CD161+ cells, which are defined as rat natural killer (NK) cells, were increased in number in the SHRSP. Intracellular flow cytometry also identified this cell type as a source of excess TNFα in blood and placenta from pregnant SHRSP. I then went on to evaluate the effects of etanercept treatment on these CD3- CD161+ cells and showed that etanercept reduced the expression of CD161 and the cytotoxic molecule, granzyme B, in the NK cells. Thus, etanercept limits the cytotoxicity and potential damaging effect of these NK cells in the SHRSP placenta. Analysing the urinary peptidome has clinical potential to identify novel pathways involved with disease and/or to develop biomarker panels to aid and stratify diagnosis. In Chapter 4, I utilised the SHRSP as a pre-clinical model to identify novel urinary peptides associated with hypertensive pregnancy. Firstly, a characterisation study was carried out in the kidney of the WKY and SHRSP. Urine samples from WKY and SHRSP taken at pre-pregnancy, mid-pregnancy (GD12) and late pregnancy (GD18) were used in the peptidomic screen. In order to capture peptides which were markers of hypertensive pregnancy from the urinary peptidomic data, I focussed on those that were only changed in a strain dependent manner at GD12 and 18 and not pre-pregnancy. Peptide fragments from the uromodulin protein were identified from this analysis to be increased in pregnant SHRSP relative to pregnant WKY. This increase in uromodulin was validated at the SHRSP kidney level using qPCR. Uromodulin has previously been identified to be a candidate molecule involved in systemic arterial hypertension but not in hypertensive pregnancy thus is a promising target for further study. In summary, we have characterised the SHRSP as the first model of maternal chronic hypertension during pregnancy and identified that inflammation mediated by TNFα and NK cells plays a key role in the pathology. The evidence presented in this thesis establishes the SHRSP as a pre-clinical model for pregnancy research and can be continued into clinical studies in pregnant women with chronic hypertension which remains an area of unmet research need.

Nurse-determined assessment of cardiac output. Comparing a non-invasive cardiac output device and pulmonary artery catheter: a prospective observational study.

Background The accurate measurement of Cardiac output (CO) is vital in guiding the treatment of critically ill patients. Invasive or minimally invasive measurement of CO is not without inherent risks to the patient. Skilled Intensive Care Unit (ICU) nursing staff are in an ideal position to assess changes in CO following therapeutic measures. The USCOM (Ultrasonic Cardiac Output Monitor) device is a non-invasive CO monitor whose clinical utility and ease of use requires testing. Objectives To compare cardiac output measurement using a non-invasive ultrasonic device (USCOM) operated by a non-echocardiograhically trained ICU Registered Nurse (RN), with the conventional pulmonary artery catheter (PAC) using both thermodilution and Fick methods. Design Prospective observational study. Setting and participants Between April 2006 and March 2007, we evaluated 30 spontaneously breathing patients requiring PAC for assessment of heart failure and/or pulmonary hypertension at a tertiary level cardiothoracic hospital. Methods SCOM CO was compared with thermodilution measurements via PAC and CO estimated using a modified Fick equation. This catheter was inserted by a medical officer, and all USCOM measurements by a senior ICU nurse. Mean values, bias and precision, and mean percentage difference between measures were determined to compare methods. The Intra-Class Correlation statistic was also used to assess agreement. The USCOM time to measure was recorded to assess the learning curve for USCOM use performed by an ICU RN and a line of best fit demonstrated to describe the operator learning curve. Results In 24 of 30 (80%) patients studied, CO measures were obtained. In 6 of 30 (20%) patients, an adequate USCOM signal was not achieved. The mean difference (±standard deviation) between USCOM and PAC, USCOM and Fick, and Fick and PAC CO were small, −0.34 ± 0.52 L/min, −0.33 ± 0.90 L/min and −0.25 ± 0.63 L/min respectively across a range of outputs from 2.6 L/min to 7.2 L/min. The percent limits of agreement (LOA) for all measures were −34.6% to 17.8% for USCOM and PAC, −49.8% to 34.1% for USCOM and Fick and −36.4% to 23.7% for PAC and Fick. Signal acquisition time reduced on average by 0.6 min per measure to less than 10 min at the end of the study. Conclusions In 80% of our cohort, USCOM, PAC and Fick measures of CO all showed clinically acceptable agreement and the learning curve for operation of the non-invasive USCOM device by an ICU RN was found to be satisfactorily short. Further work is required in patients receiving positive pressure ventilation.

A comparison of two procedures for increasing spontaneous requests in children with autism

The missing-item format and interrupted behaviour chain strategy have been used to increase spontaneous requests among children with developmental disabilities, but their relative effectiveness has not been compared. The present study compared the extent to which each strategy evoked spontaneous requests and challenging behaviour in three children with autism. Sessions where a needed item was withheld (missing-item format) were compared to sessions involving the removal of a needed item (interrupted behaviour chain strategy). Comparisons were conducted across three activates in an alternating treatments design. Both strategies evoked spontaneous requests with no significant difference in effectiveness. Few differences were obtained in the amount of challenging behaviour evoked but the two conditions, although a moderate inverse relationship between spontaneous requesting and challenging behaviour was observed. The results suggest that theses two procedures yield similar outcomes. Concurrent use of both strategies may enable teachers to create a greater number of opportunities for requesting.

Spontaneous pacing during overground hill running

Purpose: To investigate speed regulation during overground running on undulating terrain. Methods: Following an initial laboratory session to calculate physiological thresholds, eight experienced runners completed a spontaneously paced time trial over 3 laps of an outdoor course involving uphill, downhill and level sections. A portable gas analyser, GPS receiver and activity monitor were used to collect physiological, speed and stride frequency data. Results: Participants ran 23% slower on uphills and 13.8% faster on downhills compared with level sections. Speeds on level sections were significantly different for 78.4 ± 7.0 seconds following an uphill and 23.6 ± 2.2 seconds following a downhill. Speed changes were primarily regulated by stride length which was 20.5% shorter uphill and 16.2% longer downhill, while stride frequency was relatively stable. Oxygen consumption averaged 100.4% of runner’s individual ventilatory thresholds on uphills, 78.9% on downhills and 89.3% on level sections. 89% of group level speed was predicted using a modified gradient factor. Individuals adopted distinct pacing strategies, both across laps and as a function of gradient. Conclusions: Speed was best predicted using a weighted factor to account for prior and current gradients. Oxygen consumption (VO2) limited runner’s speeds only on uphill sections, and was maintained in line with individual ventilatory thresholds. Running speed showed larger individual variation on downhill sections, while speed on the level was systematically influenced by the preceding gradient. Runners who varied their pace more as a function of gradient showed a more consistent level of oxygen consumption. These results suggest that optimising time on the level sections after hills offers the greatest potential to minimise overall time when running over undulating terrain.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

New drugs for the treatment of coronary artery syndromes

Background: Acute coronary syndromes are a major cause of mortality and morbidity. Objectives/Methods: The objective of this evaluation is to review the clinical trials of two new drugs being developed for the treatment of acute coronary syndromes. The first drug is the anti-coagulant otamixaban, and the trial compared otamixaban with unfractionated heparin and eptifibatide in acute coronary syndromes. The second drug is the anti-platelet ticagrelor, and the trial compared ticagrelor with clopidogrel in acute coronary syndromes. Results: In the SEPIA-ACS1 TIMI 42 trial, the primary efficacy endpoint occurred in 6.2% of subjects treated with unfractionated heparin and eptifibatide, and to a significantly lesser extent with otamixaban. In the PLATO trial, the primary efficacy endpoint had occurred less in the ticagrelor group (9.8%) than in the clopidogrel group (11.7%) at 12 months. Conclusions: Two new drugs for acute coronary syndromes, otamixaban and ticagrelor, have recently been shown to have benefits in subjects undergoing percutaneous interventions compared to the present standard regimens for this condition.

Geometry vs appearance for discriminating between posed and spontaneous emotions

Spontaneous facial expressions differ from posed ones in appearance, timing and accompanying head movements. Still images cannot provide timing or head movement information directly. However, indirectly the distances between key points on a face extracted from a still image using active shape models can capture some movement and pose changes. This information is superposed on information about non-rigid facial movement that is also part of the expression. Does geometric information improve the discrimination between spontaneous and posed facial expressions arising from discrete emotions? We investigate the performance of a machine vision system for discrimination between posed and spontaneous versions of six basic emotions that uses SIFT appearance based features and FAP geometric features. Experimental results on the NVIE database demonstrate that fusion of geometric information leads only to marginal improvement over appearance features. Using fusion features, surprise is the easiest emotion (83.4% accuracy) to be distinguished, while disgust is the most difficult (76.1%). Our results find different important facial regions between discriminating posed versus spontaneous version of one emotion and classifying the same emotion versus other emotions. The distribution of the selected SIFT features shows that mouth is more important for sadness, while nose is more important for surprise, however, both the nose and mouth are important for disgust, fear, and happiness. Eyebrows, eyes, nose and mouth are important for anger.