But the Flesh Is: A Collection of Essays

Believing that it is with the genre of creative non-fiction that I can most accurately narrate my experience, I use this writing to explore themes of appetite, disability, and desire in my life. Perhaps best summarized as chasing honesty, in writing, my work seeks to ground abstract thought in tangible moments, treating those moments as key contexts in which to ask complex spiritual questions without answering them

Numerically Approximating Parabolic PDEs using Deep Learning

In this thesis, we demonstrate the use of machine learning in numerically solving both linear and non-linear parabolic partial differential equations. By using deep learning, rather than more traditional, established numerical methods (for example, Monte Carlo sampling) to calculate numeric solutions to such problems, we can tackle even very high dimensional problems, potentially overcoming the curse of dimensionality. This happens when the computational complexity of a problem grows exponentially with the number of dimensions. In Chapter 1, we describe the derivation of the computational problem needed to apply the deep learning method in the case of the linear Kolmogorov PDE. We start with an introduction to a few core concepts in Stochastic Analysis, particularly Stochastic Differential Equations, and define the Kolmogorov Backward Equation. We describe how the Feynman-Kac theorem means that the solution to the linear Kolmogorov PDE is a conditional expectation, and therefore how we can turn the numerical approximation of solving such a PDE into a minimisation. Chapter 2 discusses the key ideas behind the terminology deep learning; specifically, what a neural network is and how we can apply this to solve the minimisation problem from Chapter 1. We describe the key features of a neural network, the training process, and how parameters can be learned through a gradient descent based optimisation. We summarise the numerical method in Algorithm 1. In Chapter 3, we implement a neural network and train it to solve a 100-dimensional linear Black-Scholes PDE with underlying geometric Brownian motion, and similarly with correlated Brownian motion. We also illustrate an example with a non-linear auxiliary Itô process: the Stochastic Lorenz Equation. We additionally compute a solution to the geometric Brownian motion problem in 1 dimensions, and compare the accuracy of the solution found by the neural network and that found by two other numerical methods: Monte Carlo sampling and finite differences, as well as the solution found using the implicit formula for the solution. For 2-dimensions, the solution of the geometric Brownian motion problem is compared against a solution obtained by Monte Carlo sampling, which shows that the neural network approximation falls within the 99\% confidence interval of the Monte Carlo estimate. We also investigate the impact of the frequency of re-sampling training data and the batch size on the rate of convergence of the neural network. Chapter 4 describes the derivation of the equivalent minimisation problem for solving a Kolmogorov PDE with non-linear coefficients, where we discretise the PDE in time, and derive an approximate Feynman-Kac representation on each time step. Chapter 5 demonstrates the method on an example of a non-linear Black-Scholes PDE and a Hamilton-Jacobi-Bellman equation. The numerical examples are based on the code by Beck et al. in their papers "Solving the Kolmogorov PDE by means of deep learning" and "Deep splitting method for parabolic PDEs", and are written in the Julia programming language, with use of the Flux library for Machine Learning in Julia. The code used to implement the method can be found at https://github.com/julia-sand/pde_appro

“You get to know the people and whether they’re talking sense or not”: Negotiating trust on health-related forums

AbstractThe internet is increasingly being used as a source of health advice and information by individuals with long term conditions (LTCs). Specifically, online forums allow people to interact with others with similar conditions. However, it is not clear how online health information is assessed by those with LTCs. This study aims to address this gap by exploring how individuals with contested and uncontested LTCs utilise internet forums. Semi-structured interviews were conducted with 20 participants with ME/CFS and 21 participants with type 1 and 2 diabetes and analysed using thematic analysis. Participants were recruited via online and offline routes, namely forums, email lists, newsletters, and face-to-face support groups. The findings indicate that the use of online forums was a complex and nuanced process and was influenced by a number of individual and illness-specific factors. Participants trusted those with similar experiences and perspectives as themselves, while also valuing conventional biomedical information and advice. By accessing support online, forum users were able to draw on a personalised form of support based on the lived experiences of their peers. However, the role of digital literacy in developing and maintaining online relationships must be acknowledged

Women’s knowledge, attitudes and views of preconception health and intervention delivery methods:a cross-sectional survey

Background: Several preconception exposures have been associated with adverse pregnancy, birth and postpartum outcomes. However, few studies have investigated women’s knowledge of and attitudes towards preconception health, and the acceptability of potential intervention methods. Methods: Seven primary care centres in the West of England posted questionnaires to 4330 female patients aged 18 to 48 years. Without providing examples, we asked women to list maternal preconception exposures that might affect infant and maternal outcomes, and assessed their knowledge of nine literature-derived risk factors. Attitudes towards preconception health (interest, intentions, self-efficacy and perceived awareness and importance) and the acceptability of intervention delivery methods were also assessed. Multivariable multilevel regression examined participant characteristics associated with these outcomes. Results: Of those who received questionnaires, 835 (19.3%) responded. Women were most aware of the preconception risk factors of diet (86.0%) and physical activity (79.2%). Few were aware of weight (40.1%), folic acid (32.9%), abuse (6.3%), advanced age (5.9%) and interpregnancy intervals (0.2%), and none mentioned interpregnancy weight change or excess iron intake. After adjusting for demographic and reproductive covariates, women aged 18–24-years (compared to 40–48-year-olds) and nulligravid women were less aware of the benefit of preconception folic acid supplementation (adjusted odds ratios (aOR) for age: 4.30 [2.10–8.80], gravidity: aOR 2.48 [1.70–3.62]). Younger women were more interested in learning more about preconception health (aOR 0.37 [0.21–0.63]) but nulligravid women were less interested in this (aOR 1.79 [1.30–2.46]). Women with the lowest household incomes (versus the highest) were less aware of preconception weight as a risk factor (aOR: 3.11 [1.65–5.84]) and rated the importance of preconception health lower (aOR 3.38 [1.90–6.00]). The most acceptable information delivery methods were websites/apps (99.5%), printed healthcare materials (98.6%), family/partners (96.3%), schools (94.4%), television (91.9%), pregnancy tests (91.0%) and doctors, midwives and nurses (86.8–97.0%). Dentists (23.9%) and hairdressers/beauticians (18.1%) were the least acceptable. Conclusions: Our findings demonstrate a need to promote awareness of preconception risk factors and motivation for preconception health changes, particularly amongst younger and nulligravid women and women with lower incomes. Interventions to improve preconception health should focus on communication from healthcare professionals, schools, family members, and digital media

“Anxious and traumatised”: Users’ experiences of maternity care in the UK during the COVID-19 pandemic

The COVID-19 pandemic saw universal, radical, and ultra-rapid changes to UK National Health Services (NHS) maternity care. At the onset of the pandemic, NHS maternity services were stripped of many of the features which support woman and family centred care. In anticipation of unknown numbers of pregnant women and maternity staff potentially sick with COVID-19, services were pared back to the minimum level considered to be required to keep women and their babies safe. The aim of this survey was to understand the impact of COVID-19 public health messaging and pandemic-related service changes on users of maternity care in the UK during the pandemic. Methods We conducted an online survey to explore user's experiences of COVID-19 public health messaging and ‘socially-distanced’ maternity care across the UK. The study population consisted of women who had experienced pregnancy after the 11th March 2020 (when the WHO declared a pandemic), whether or not they were still pregnant. We collected data between June and September 2020. We used framework analysis for the free-text data and generated descriptive statistics. Findings Women were generally happy to adopt a precautionary approach and stringently social distance in the context of a relatively unknown pathogen and in an environment of extreme anxiety and uncertainty, but were acutely aware of the negative impacts. The survey found that the widespread changes to services caused unintended negative consequences including essential clinical care being missed, confusion over advice, and distress and emotional trauma for women. COVID-19 restrictions have resulted in women feeling their antenatal and postnatal care to be inadequate and has also come at great emotional cost to users. Women reported feeling isolated and sad in the postnatal period, but also frustrated and upset by a lack of staff to help them care for their new baby. Key conclusions With growing evidence of the impact of the virus on pregnant women and an increased understanding of the unintended consequences of unclear public health messaging and overly precautious services, a more nuanced, evidence-based approach to caring for women during a pandemic must be prioritised. Implications for practice All maternity services should ensure they have clear lines of communication with women to keep them updated on changing care and visiting arrangements. Services should ensure that opportunities to provide safe face-to-face care and access for birth partners and visitors are maximised

Preferential utilization of inorganic polyphosphate over other bioavailable phosphorus sources by the model diatoms Thalassiosira spp.

Polyphosphates and phosphomonoesters are dominant components of marine dissolved organic phosphorus (DOP). Collectively, DOP represents an important nutritional phosphorus (P) source for phytoplankton growth in the ocean, but the contribution of specific DOP sources to microbial community P demand is not fully understood. In a prior study, it was reported that inorganic polyphosphate was not bioavailable to the model diatoms Thalassiosira weissflogii and Thalassiosira pseudonana. However, in this study, we show that the previous finding was a misinterpretation based on a technical artefact of media preparation and that inorganic polyphosphate is actually widely bioavailable to Thalassiosira spp. In fact, orthophosphate, inorganic tripolyphosphate (3polyP), adenosine triphosphate (ATP) and adenosine monophosphate supported equivalent growth rates and final growth yields within each of four strains of Thalassiosira spp. However, enzyme activity assays revealed in all cultures that cell‐associated hydrolysis rates of 3polyP were typically more than ~10‐fold higher than degradation of ATP and the model phosphomonoester compound 4‐methylumbelliferyl phosphate. These results build on prior work, which showed the preferential utilization of polyphosphates in the cell‐free exudates of Thalassiosira spp., and suggest that inorganic polyphosphates may be a key bioavailable source of P for marine phytoplankton

Preconception exposures and adverse pregnancy, birth and postpartum outcomes:Umbrella review of systematic reviews

Background Preconception exposures have been associated with adverse pregnancy, birth and postpartum outcomes. However, the reports, statements and guidelines of national and international health organisations vary in what they recommend individuals should monitor, avoid, reduce or practise in the preconception period. Objectives To synthesise and evaluate the evidence across systematic reviews for associations between exposures before conception and adverse pregnancy, birth and postpartum outcomes. Data sources MEDLINE, Embase, Epistemonikos (to May 2020) and reference lists of included reviews, without language or date restrictions. Study selection, data extraction and synthesis Systematic literature reviews of observational and/or interventional studies reporting associations between preconception exposures in women and/or men of reproductive age and pregnancy, birth or postpartum health outcomes were included. The methodological quality of reviews and the certainty of the evidence underlying each exposure-outcome association were assessed using AMSTAR 2 and the GRADE approach. Results We identified 53 eligible reviews reporting 205 unique exposure-outcome associations. Methodological quality was generally low with only two reviews rated as ‘high’ quality and two as ‘moderate’. We found high-certainty, randomised trial evidence that maternal folate supplementation reduces the risk of neural tube defects and anomaly-related terminations. Moderate-certainty, observational evidence was found that maternal physical activity is associated with reduced risk of pre-eclampsia and gestational diabetes, and that paternal age of ≥40 years and maternal body mass index (BMI) and interpregnancy weight gain are associated with increased risk of various adverse pregnancy and birth outcomes. Low- and very low-certainty evidence was found for other associations. Conclusions Clinicians and policymakers can be confident that maternal folate supplementation should be encouraged during the preconception period. There is moderate certainty in the evidence base that maternal physical activity, BMI and interpregnancy weight gain and advanced paternal age are important preconception considerations. High-quality research is required to better understand other exposure-outcome associations

Monitoring adverse social and medical events in public health trials: assessing predictors and interpretation against a proposed model of adverse event reporting

Background Although adverse event (AE) monitoring in trials focusses on medical events, social outcomes may be important in public or social care trials. We describe our approach to reporting and categorising medical and other AE reports, using a case study trial. We explore predictors of medical and social AEs, and develop a model for conceptualising safety monitoring. Methods The Building Blocks randomised controlled trial of specialist home visiting recruited 1618 first-time mothers aged 19 years or under at 18 English sites. Event reports collected during follow-up were independently reviewed and categorised as either Medical (standard Good Clinical Practice definition), or Social (trial-specific definition). A retrospectively developed system was created to classify AEs. Univariate analyses explored the association between baseline participant and study characteristics and the subsequent reporting of events. Factors significantly associated at this stage were progressed to binary logistic regressions to assess independent predictors. Results A classification system was derived for reported AEs that distinguished between Medical or Social AEs. One thousand, three hundred and fifteen event reports were obtained for mothers or their babies (1033 Medical, 257 Social). Allocation to the trial intervention arm was associated with increased likelihood of Medical rather than Social AE reporting. Poorer baseline psycho-social status predicted both Medical and Social events, and poorer psycho-social status better predicted Social rather than Medical events. Baseline predictors of Social AEs included being younger at recruitment (OR = 0.78 (CI = 0.67 to 0.90), p = 0.001), receiving benefits (OR = 1.60 (CI = 1.09 to 2.35), p = 0.016), and having a higher antisocial behaviour score (OR = 1.22 (CI = 1.09 to 1.36), p < 0.001). Baseline predictors of Medical AEs included having a limiting long-term illness (OR = 1.37 (CI = 1.01 to 1.88), p = 0.046), poorer mental health (OR = 1.03 (CI = 1.01 to 1.05), p = 0.004), and being in the intervention arm of the trial (OR = 1.34 (CI = 1.07 to 1.70), p = 0.012). Conclusions Continuity between baseline and subsequent adverse experiences was expected despite potentially beneficial intervention impact. We hypothesise that excess events reported for intervention-arm participants is likely attributable to surveillance bias. We interpreted our findings against a new model that explicates processes that may drive event occurrence, presentation and reporting. Focussing only upon Medical events may miss the well-being and social circumstances that are important for interpreting intervention safety and participant management

Access to healthcare for victims of human trafficking: a focus group with third sector agencies

Human Trafficking is becoming increasingly recognised as a global public health epidemic with an estimated 45.8 million individuals affected by some type of exploitation. The effects of trauma and exploitation have profound health implications and often leave victims isolated from society. Victims of Human Trafficking are commonly associated with vulnerability, comorbidities, poor access to, and engagement with, healthcare services. Given this situation, an exploration of trafficking and access to healthcare was indicated. A focus group explored the experiences of six third sector workers in supporting victims of Human Trafficking. Thematic analysis was used and four overarching themes emanated: a call for improved access to treatment for victims affected by mental illness; improved knowledge and training of health professionals in identifying victims; the challenges for victims navigating two complex systems (National Referral Mechanism/Asylum Process) and victim’s self-identification. The findings highlighted the associated complexities that victims commonly face when accessing healthcare and emphasised the fundamental need for ensuring that equitable services are available. To enable safeguarding and individualised care to become embedded, a shift in culture and a move away from judging healthcare need on immigration status was recognised as a key requirement. Improved access to psychological therapy for victims was also suggested, alongside better education for all health professionals and frontline staff. To improve healthcare for victims of Human Trafficking in the ways recommended would require Government and National Health Service (NHS) support including increased financial and staff resources