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On health inequality in the past and present
Get PDFThis thesis explores socioeconomic gradients in health outcomes through evidence from the past and present. Studying health inequality is fundamental to revealing how socioeconomic factors create unfair variations in health outcomes across populations, which is esssential for developing targeted interventions to promote equal opportunity for well-being. Historical analysis provides crucial insights into the long-run implications of socioeconomic inequalities on health, with particular significance during the mortality transition—a period characterised by unprecedented improvements in population health alongside profound transitions that established enduring patterns of health disparities that persisted for generations. Chapters 1 and 2 examine the past by analysing mortality dynamics in London and its constituent areas from the 1850s to the 1950s. Chapter 3 investigates present-day health inequality by focusing on a key health risk factor—physical (in)activity.
The first two chapters draw on novel datasets I constructed by digitising and compiling information and data from historical administrative records, including Medical Officer of Health reports, censuses, and Registrar General’s reports. The final chapter leverages the Understanding Society survey, a nationally representative panel dataset that captures comprehensive and nuanced measures of socioeconomic status across UK households.
Chapter 1 utilises a new time series dataset of London mortality spanning 1841–1964, encompassing four mortality measures: crude mortality, corrected death rate (adjusted for age and sex composition), infant mortality, and non-infant mortality. The annual, long-term, and continuous mortality data illuminate an S-shaped decline curve, characterised by an initial period of slow reductions before faster reductions and ultimately a slow-down in improvements. This pattern is observed across all mortality measures, enabling analysis through a four-parameter logistic model. This formal statistical method yields key parameters that capture the underlying dynamics effectively. The inflection point, occurring around 1896 for crude mortality, indicates the point of the most rapid mortality reduction. To explain the sigmoid pattern, an economic model is developed where higher socioeconomic groups adopt health technologies earlier, thereby experiencing mortality transitions earlier. The model underscores how socioeconomic inequality shapes the sigmoid dynamics of mortality decline.
Chapter 2 expands the analysis to constituent areas in London. The new panel data-set comprises three fundamental components: first, geographic areas whose boundaries remained stable for a long enough period; second, three mortality measures: crude mortality, infant mortality, and non-infant mortality for these areas; third, measures of socioeconomic inequality for these areas, including, for example, the proportion of professional occupations and middle-class residents. Application of the four-parameter logistic model reveals substantial spatial heterogeneity in mortality dynamics, with inflection points varying by decades across areas. The economic model developed in Chapter 1 predicts that this variation stems from socioeconomic differences—areas with more high socioeconomic residents adopted health technologies earlier, facilitating earlier mortality transitions. Empirical testing through an augmented logistic model confirms this hypothesis, demonstrating a significant negative relationship between an area’s socioeconomic status and the inflection point of the mortality dynamics. For example, areas that had a 1% higher proportion of individuals in professional classes experienced an inflection point in mortality declines around a year and a half earlier. These findings indicate that the mortality transition proceeded through a prolonged period of mortality divergence across socioeconomic groups before eventual convergence, rather than immediate convergence across social groups.
Taken together, the first two chapters provide the first formal examination of how socioeconomic inequality shaped the sigmoid pattern of mortality decline and generated the “divergence-convergence” pattern of mortality inequality during the period of mortality transition. This historical analysis yields twofold implications: it reveals how uneven access to health innovations historically perpetuated and amplified health disparities in today’s developed economies, whilst providing an analytical framework for contemporary developing economies where ongoing epidemiological transitions, absent policies addressing socioeconomic inequalities, risk exacerbating existing health inequalities.
Shifting focus from historical London to contemporary UK, Chapter 3 investigates the distinct mechanisms through which education and household income shape physical activity (PA) patterns among working-age adults in the UK from 2015–2019, using Understanding Society survey data. Employing an ordered logit model to distinguish three PA levels—zero physical activity, engagement in at least some physical activity, and meeting WHO-recommended guidelines—the study yields three principal findings, contributing to the understudied aspects of the relationship between socioeconomic status and physical activity behaviour. First, while both education and income positively influence PA, their relative magnitudes differ substantially—the effect of upgrading from GCSE to degree-level education equals that of a four-and-a-half-fold increase in household disposable income, which suggests that educational interventions may be more effective at promoting physical activity than income support policies. Second, household disposable income has approximately twice the impact of household gross labour earnings on physical activity engagement, highlighting the necessity of using correct income measures and the effectiveness of redistributive policies. Third, women’s physical activity is more strongly associated with educational attainment, while household income demonstrates a greater influence on men’s activity patterns.
Drawing from this thesis, socioeconomic inequality functions as a crucial determinant of health outcomes, operating both through contemporaneous mechanisms and by shaping the long-run dynamics of health disparities. These findings underscore the importance of examining the persistent effects of socioeconomic conditions across temporal horizons to fully understand their implications for population health
Investigating the clinical importance of fungi in diabetic wounds
Get PDFDFU is often manifested as a chronic open wound predisposed to invasion by many pathogenic and opportunistic microorganisms including bacteria and fungi. Impaired wound healing characterised by clinically infected ulcers can be a consequence of ineffective eradication of polymicrobial biofilms by antibiotic treatments, leading to limb amputation. A universal microbiome picture is necessary, especially for empirical therapy. Still, the dynamic of individual microbiomes can only be precisely depicted by periodic sampling of the wounds revealing the ongoing response to the antibiotic treatments.
Initially, standard microbiology culture data was analysed as part of the standard wound care for the patients. Of 306 samples with growth, 85.6% of the wounds were polymicrobial, and Candida was always found in mixed growth. Mixed skin, enterics and S. aureus were the topmost isolated organisms in descending order. Despite stratification of the wounds into different grades and stages according to the University of Texas wound classification systems, wounds were not found to be different. The data obtained from the standard culture showed that DFUs are predominated by bacteria from the skin and gut.
Secondly, Oxford Nanopore sequencing technology was utilised to scrutinize the 16S wound microbiomes of 349 extracted wound DNA. Corynebacterium, Staphylococcus and Streptococcus were the major taxa identified from the wounds. Moreover, Finegoldia magna was the most predominant obligate anaerobes identified, and commonly found with all Candida species. The wound diversity stratified according to the grades and stages showed no clustering. A subset of patients with multiple visits was then analysed for changes in microbiome as the wound progressed. Individual patient microbiomes were indeed unique.
An enhanced mycology culture was performed using Sabouraud dextrose agar (SAB) with chloramphenicol and CHROMagarTM for Malassezia to confirm the presence of fungi in the wounds. Thirty fungi isolated were Candida species mainly C. parapsilosis, C. albicans and C. glabrata. All fungi could form biofilms with C. albicans forming the most robust biofilms.
Lastly, real-world biofilm models grown from individual wounds were assessed for biofilm inhibition using Flucloxacillin, Fluconazole and a combination of both using concentrations typically found in the tissue. This model is based on an undefined microbial species found in the wounds.The bacteria and fungal load were quantified using 16S and ITS, respectively and changes in the 16S microbiome were assessed by nanopore sequencing. Antimicrobial treatments have minimal impact on the interkingdom biofilms that were formed consisting of bacteria and fungi.
In conclusion, the dynamics of diabetic wound microbiomes may represent interkingdom interactions between bacteria and fungi that exist as biofilms. This implicates the potential treatment of DFU, as systemic antibiotics alone may not be adequate to eliminate infection when fungi are present. Therefore, treatment targeting both infective aetiologies should be pursued to enhance the elimination of polymicrobial biofilms in chronic diabetic wounds
A comparative approach to identify potential control targets for filarial nematode infections
No full textAbstract not currently available
Task-oriented communication for edge intelligence enabled connected robotics systems
Get PDFTraditional digital communication systems are built on the principle of source-channel separation, guided by rate-distortion theory and channel coding. This reconstruction-oriented communication paradigm served as a cornerstone through multiple generations of communication technologies. However, with the rise of machine-to-machine communications and human-to machine interactions, task-specific representations are often more compact and more efficient than full-scale reconstructions, and End-to-End (E2E) trained communication systems have demonstrated superior task performance over traditional communications. This thesis explores task-oriented communication as a paradigm shift from traditional reconstruction-oriented transmission, focusing on optimizing data exchange for machine-driven decision-making rather than full data fidelity.
We develop a Task-Oriented Source-Channel Coding (TSCC) framework designed for edge-enabled autonomous driving. By integrating deep learning-based Joint Source-Channel Coding (JSCC) with an end-to-end autonomous driving agent, TSCC minimizes communication overhead while maintaining high inference accuracy, ensuring robustness against noisy channels. Our results demonstrate a 98.36% reduction in communication bandwidth while maintaining driving performance under low Signal-to-Noise Ratio (SNR) conditions.
To enhance compatibility with existing digital communication infrastructures, we propose Aligned Task- and Reconstruction-Oriented Communication (ATROC), which bridges task-oriented communication with traditional reconstruction-oriented paradigms. By leveraging an information reshaper and variational information bottleneck (VIB) theory, ATROC improves AI-driven inference on edge servers while ensuring seamless integration with digital communication standards. Experimental results validate that ATROC reduces 99.19% of the communication load while preserving autonomous driving efficiency.
Recognizing the need for a holistic approach, we introduce a task-oriented co-design of communication, computing, and control framework tailored for edge-enabled industrial Cyber-Physical Systems (CPS). This framework jointly optimizes data transmission, computational efficiency, and control decisions, and integrates task-oriented JSCC with Delay-aware Trajectory-guided Control Prediction (DTCP) to reduce E2E delay. Experimental results in autonomous driving simulations demonstrate that our co-design approach significantly improves driving performance under high latency scenarios
Inflammatory mechanisms after ischaemic stroke: characterisation of central nervous system (CNS) border-associated macrophages (BAMs) and dimethylarginine dimethylaminohydrolase (DDAH2)
Get PDFCentral nervous system (CNS) border-associated macrophages (BAMs) are a rare and specialised population of immune cells in the brain with emerging functions in ischaemic stroke. Preliminary work from our group has identified BAMs as CD45+highCD11b+CD206+Lyve1+ cells by flow cytometry and indicated increased numbers of BAMs 24 hours following stroke in a mouse model of focal ischaemic stroke (transient middle cerebral artery occlusion, tMCAo). Work presented in this thesis establishes the accumulation of BAMs beyond the period of infarct development. The numbers of BAMs in the ipsilateral hemisphere after tMCAo increased in the acute phase after stroke, peaked one week later and subsequently declined in the chronic stages. BAMs were identified in perivascular and in meningeal spaces as CD206+aSMA+ and CD206+Lyve1+ cells and their localisation with respect to the infarct and peri-infarct zones was investigated.
The signalling molecule nitric oxide (NO) has deleterious roles in ischaemic stroke and macrophages are an immune cell source of inducible nitric oxide synthase (iNOS)-produced NO. Work from Prof Leiper’s lab has shown that dimethylarginine dimethylaminohydrolase (DDAH2) enzymatically regulates NO signalling in hypoxic and septic conditions and thereby controls macrophage function. Work presented here demonstrates that Ddah2 mRNA expression increased following oxygen and glucose deprivation in RAW264 macrophage cell line, while DDAH2 protein levels remained unchanged after tMCAo in C57BL6/J mice. The expression of the pro-inflammatory genes Il-1b, Tnfa, Il-6 and Ccl2 was reduced in peritoneal macrophages from naïve monocytes/macrophages specific Ddah2 knockout mice, indicating that DDAH2 may regulate the inflammatory phenotype of these cells.
To explore the potential implications of DDAH2-mediated altered macrophage phenotype on ischaemic stroke outcomes, a study was conducted in monocytes/macrophages specific Ddah2 knockout mice. Preliminary evidence suggests that infarct and oedema volume did not differ between knockout and control mice. There was a slight reduction in neurological deficit and reduced levels of apoptosis in knockout mice after tMCAo. The rate of immune cell infiltration into the brain after tMCAo was not altered, as the numbers of total leukocytes, myeloid cells and lymphocytes were comparable between genotypes.
This thesis reinforces the emerging significance of BAMs in the pathophysiology of ischaemic stroke. Through detailed characterisation and temporal mapping, it establishes BAMs as dynamic responders that accumulate during the acute and subacute phases of stroke and recede in the chronic stages. Although modulation of nitric oxide signalling via DDAH2 showed limited impact on infarct size and immune infiltration, subtle improvements in neurological deficits and reduced apoptosis suggest that DDAH2 may fine-tune the inflammatory profile of macrophages in ways that are neuroprotective. These findings open a window into targeted immune modulation as a therapeutic avenue in stroke recovery.
This work points to a paradigm shift in how we understand neuroimmune regulation in stroke. Far from being passive residents at CNS borders, BAMs may play active, time-sensitive roles in brain injury and repair. By linking BAM behaviour with nitric oxide signalling and the regulatory role of DDAH2, the thesis lays groundwork for future exploration into cell-specific interventions—aimed not at altering infarct size, but at refining the inflammatory environment to promote neurological resilience. The immune landscape of the brain is more intricate than previously assumed, and the key to healing might lie not in suppressing inflammation broadly, but in sculpting it precisely
New dosimetry methods for radiological and nuclear emergency management
Get PDFDuring all phases following a nuclear or radiological incident analyses of doses received by members of the public and responders are required. Rapid and reliable dose assessment is critical for the effective management of radiological emergencies; for medical triage, understanding exposure levels, directing protective actions, and conducting subsequent analyses of the impact of the incident. Current practice has been reviewed, highlighting the potential for near real-time luminescence dosimetry to assist with such assessments, including low dose response that supports public reassurance below doses of medical significance, using common materials present at the time of the incident. A number of materials which might be found in the immediate vicinity of people have previously been investigated with regard to their potential to act as radiation dosimeters. The work in this thesis investigates the properties of common household salt and talc, using portable Optically Stimulated Luminescence (OSL) and Infra-Red Stimulated Luminescence (IRSL) instruments capable of rapid measurements in the field. The potential of these materials to measure radiation levels and provide rapid, cost-effective insights into exposure patterns using new methods is explored. This approach aims to support emergency response strategies by leveraging accessible materials to improve decision-making in radiological incidents, bridging a key gap in large-scale radiation measurements and initial triage support.
Common salt has previously been shown to have the potential for retrospective dosimetry in the mGy dose range using laboratory instrumentation. This thesis investigates the use of portable instruments, with unprepared commercially sourced salt, in dose ranges below mGy. Responses from pulsed IRSL laboratory systems and portable OSL instruments were compared. For OSL measurements, detection limits of 7µGy have been demonstrated, with detection limits of 30-340µGy for the other instruments investigated. Linear dose responses in the 0-500µGy range were determined over this dose range. This work examines the effects of signal stability and sample storage conditions. The OSL signals initially show a brief decrease in luminescence during the first few days after irradiation, followed by a gradual increase with longer storage periods. Between days 8 and 64, the results remain relatively stable, which is crucial for dose estimation during both the early and later stages of responding to radiological emergencies, and methods for correcting for these signal variations at shorter and longer periods have been developed and demonstrated. However, exposure to light and moisture leads to a rapid loss of OSL signals.
Three practical experiments were conducted using salt to simulate real accident scenarios, measure radiation, estimate dose, and compare the results with gamma systems (backpack). The first experiment was conducted under controlled laboratory conditions. The second mapped natural and artificial radiation fields in an outside environment. The final experiment mapped complex radiation fields within an accelerator laboratory. The results demonstrate that salt has considerable potential for use in dosimetry below mGy and that measurements can be conducted with portable OSL instruments. Furthermore, the results of the first two experiments compared well to theoretical doses and measurements with different systems. The results confirmed that this approach can provide reliable dose estimates for radiological accidents. The salt system has demonstrated its ability to map the spatial boundaries of radiation fields, serving as a low cost radiation mapping tool. Protocols must be instituted for testing and assessment during exercises, taking into account variables such as zeroing, ambient conditions, and the necessity for fading adjustments.
The studies of talc focused on the optimal conditions for measuring the radiation-induced OSLsignal using the SUERC Portable OSL Reader. It also addressed the inherent complexities associated with geological residual signals observed in talc sourced from Luzenac Pharma's packing line. This residual signal can be removed through thermal treatment, specifically at 400°C for 1 hour, after which the talc exhibits sufficient sensitivity to detect doses in the mGy range through to the radiologically significant range of 0.5 to 3 Gy, making it a promising candidate for field-deployable radiation assessment, such as in emergency response scenarios following radiological incidents. However, the observed fading and zeroing behaviours of talc introduce critical considerations that must be addressed to ensure reliable dose estimation. The fading data exhibit a complex decay pattern, suggesting the presence of multiple trap depths, with an initial signal loss of approximately 6% within 24 hours post-irradiation, escalating toa substantial 65% reduction of the original OSL signal within 128 days at ambient temperature. Such behaviour necessitates the incorporation of fading correction factors tailored to the time elapsed between irradiation and measurement, as an uncorrected signal loss could lead to systematic underestimation of doses, particularly in retrospective dosimetry applications. Additionally, the zeroing behaviour poses further challenges. Incomplete zeroing could leave residual signals that overlap with those induced by a recent radiation event. This overlap complicates the ability to accurately distinguish between background dose contributions and acute doses from a specific incident, potentially compromising the method’s specificity.
The work presented here has demonstrated that the novel approach of using salt or talc with portable OSL systems is capable of delivering dose estimates in the range from a few µGy to several Gy in near real-time, complementing existing techniques. To optimize this approach, comprehensive protocols should be developed for both testing exercises and evaluations, which could lead to wider acceptance of these approaches offering a robust, low-cost solution for rapid dose assessment for both emergency response and environmental dosimetry
Svetlana Alexievich: a polyphonic writer in translation
Get PDFThis thesis is an explorative study into polyphony and its transformation in translation. It aims to identify individual voices in Alexievich’s polyphonic writing in Russian and by analysing changes they undergo in the existing translations into English to compare how voices transition and polyphony is portrayed from the source texts to the target texts. In doing so, this work seeks to contribute to the discourse surrounding the translation of Alexievich’s works and provide future translators with a tool to reflect the multivocal nature of her narratives. To do so, it develops a new methodological framework for identifying and analysing individual voices which offers a systematic approach to translating polyphonic texts.
First, this thesis to understand the specific nature of polyphony in Alexievich’s writing and explores a range of attitudes towards that polyphony in the source-text culture(-s) and society(-ies), where her writing challenged a well-established representation of historical events as well as of the places where those events unfolded. To devise an appropriate research methodology, this thesis looks at Alexievich’s polyphonic texts through the prism of the Bakhtinian polyphonic approach supplemented with a range of theoretical scholarship to shape a conceptual understanding of the written polyphonic voice. The methodology establishes four dimensions of voice which are applied to the two-stage comparative textual analysis.
The analysis identifies polyphonic voices in the Russian-language source texts then explores their transformation in translation into English. The source-text analysis confirms the presence of polyphonic voices distinguishable at a textual level. They come across as diverse, unique and different from each other. The subsequent analysis of the voices in the existing translations has identified shifts and alterations that lead to changes of those in various ways, as well as the presence of the voice of an individual translator. The outcome of this research is that some characteristics of individual voices could be preserved in translation if the dimensions of voice devised in the research methodology are applied during pre-translation analysis
Investigating focused ion beam irradiation effects in synthetic antiferromagnetic systems: a Lorentz microscopy study
No full textAbstract not currently available
The impact of time of the day on muscle and metabolic responses to resistance exercise in healthy adults
Get PDFMetabolic disorders is a term used for a group of diseases including obesity, insulin resistance and type 2 diabetes. Today more than 537 million adults (age: 20–79 years)worldwide are living with diabetes, with a prevalence of 10%. This number is projected by international diabetes federation to reach 643 million by 2030 and 784 million by 2045(Al Ozairi et al., 2023, Federation, 2021). Regular exercise is a powerful strategy for the treatment and prevention of metabolic disease with previous studies demonstrating that this improves insulin sensitivity over time. Concurrently there are data indicating there are circadian rhythms in metabolism and that these might interact with exercise performance. However, data remains unclear on the impact of time of the day at which exercise is performed and how this influences metabolic responses.
Therefore, the aim of Chapter 2 is to systematically review and carry out a meta-analysis on the impact of exercise timing on metabolic responses to exercise in adults, considering both acute and more chronic studies and those with and without disease. The narrative analysis showed that the time of the day at which the exercise is performed does not have a clear impact on metabolic responses. Furthermore, the quantitative analysis found no significant difference in 24-hour CGM measured glucose levels, on the day of exercise or the following day regardless of whether the exercise was performed either in the morning or afternoon/evening.
Although aerobic exercise can improve insulin sensitivity acutely, resistance exercise has been less well studied in that regard. Therefore, the aim of Chapter 3 is to determine whether the time of the day has an effect on insulin sensitivity, measured during an oral glucose tolerance test, in response to a single resistance exercise session in healthy adultsin a cross over study. The two-way repeated measures ANOVA revealed no significant effect of time (p=0.586), group (p=0.720) or time*group interactions (p=0.511) for glucose area under the curve. Similarly, insulin area under the curve revealed no significant effect of time (p=0.735), group (p=0.663) or time*group interaction (p=0.973). Finally, insulin sensitivity revealed no significant effect of time (p=0.134), group (p=0.780) or time*group interactions (p=0.250). This finding indicate that a single session of resistance exercise has little effect on insulin sensitivity in healthy young adults, with no differences if this was performed in the morning or afternoon.
One of the main benefits of regular resistance exercise is that it increases muscle strength and mass which are important for maintenance of physical function, glucose control, and morbidity/mortality risk. However, the time at which resistance exercise is performed may be related to in improvements in muscle strength, muscle mass and metabolic responses. Therefore, the aim of Chapter 4 is to determine the effect of time of day at which resistance exercise is performed on the muscle and metabolic responses in healthy adults. We recruited 38 participants (30±7 years old; and 28±4 kg/m2) who were randomised to either a control, exercise in the morning (6:00-10am) or exercise in the evening (4:00-8:00pm) group. Those in the exercise groups performed 8 resistance exercises 3 times a week for 6 weeks, at their allocated time of day. The findings demonstrated that over the 6-week intervention period there were effects of time on insulin sensitivity (p<0.001), muscle thickness (p=0.008) and knee extensor maximal torque (p<0.001) but no interactions with time of day. Post-hoc tests revealed increases in insulin sensitivity and knee extensor maximal torque in the morning group (+7.55 [3.33 to 11.77] mg l2 mmol−1 mU−1 min−1p=0.003), with increases in muscle thickness (+1.17 [0.37 to 1.97] mm p=0.009) and knee extensor maximal torque in the evening group (+5.68 [2.36 to 8.99] Nm p=0.003). However, there was no clear effect of time of day. These results suggest that the benefits of resistance exercise may be achieved regardless of the time of day for healthy young adults and this should be the focus of public health strategies.
Overall, the current thesis demonstrated that there was no clear effect of the time of day on metabolic responses with exercise, the benefits of resistance exercise may be achieved regardless of the time of day for healthy young adults, and this should be the focus of public health strategies. Limitations, such as, a small sample sizes mean that further work is needed to corroborate these findings
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