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Mixed Waste Streams for Bioproduction: Exploring Bacterial Wax Ester Production in Nitrogen‐Rich Acidogenic Fermentate
Get PDFMicrobial lipids offer a promising alternative to petrochemicals, but high associated costs and low conversion efficiencies pose barriers to their commercialisation. In particular, sugar‐based feedstocks are too expensive for the production of commodity chemicals, and recently attention has turned to volatile fatty acids (VFAs) as a cheaper, more widely available carbon source. Acidogenic fermentation can be used to produce high concentrations of VFAs from municipal and agricultural waste. By harnessing metabolically engineered Acinetobacter baylyi ADP1, the suitability of VFAs as sole carbon sources for wax ester (WE) production was investigated. These studies resulted in the highest WE accumulation in ADP1 achieved to date, at 37% of cell dry weight, and the first reported production of bacterial WEs from a raw, mixed waste stream, utilising fermentate as the sole carbon source. WE titres of over 160 mg/L from VFAs were achieved, highlighting the unique benefits of mixed feedstocks typically considered problematic for bioproduction. Finally, the potential advantages of employing fermentates rich in longer chain VFAs are explored. In synthetic media, WE titres up to 190 mg/L were achieved, but translation to fermentate was challenging, emphasising the need for continued research in this area
Evaluation of the experience of people referred under the NHS enhanced service incentive for obesity to the NHS digital weight management programme: a mixed method study
Get PDFBackground: Internationally, guidelines recommend clinicians identify patients living with obesity and offer referral to weight management programmes, especially patients with related co-morbidities. In 2021, NHS England introduced the NHS Digital Weight Management Programme for people living with obesity and a diagnosis of hypertension or diabetes or both. The programme is offered at three levels of intensity with people triaged to the appropriate level determined through age, sex, ethnicity, and deprivation. The aim of this study was to assess the experiences of people referred to the programme. Methods: A mixed methods evaluation, involving questionnaires and semi-structured interviews with patients. Questionnaires were sent to everyone who registered and chose a preferred service Provider between March 2022 and June 2023, and responses are reported as proportions. Differences in health status, demographic characteristics and experience on the programme were assessed using ordinal logistic regression. A sample of patients were interviewed, and data were analysed using a framework. Results: 17,553 questionnaires were distributed, with 3885 (22.1%) completed. We interviewed 24 patients (27 to 79 years of age; 15 females, 9 males), who had various levels of support and rates of completion. The programme was reported to be easy to use, and around half of survey respondents felt the programme helped them change their diet or activity or improved their wellbeing, regardless of the level of support received. Participants from minority ethnic groups were less likely to describe the programme or the coaching as helpful in terms of changing behaviour. Interview participants valued weight tracking, goal setting, and meal planning, but some felt the service was too generic for their individual needs. Some participants reported they did not receive sufficient in-person or group support, and that online forums were not a suitable alternative. Around half of participants found coaching helpful, but some described the coaches as unresponsive or scripted. Conclusion: The NHS Digital Weight Management Programme was moderately well received by most participants, and facilitated weight loss, behaviour change, and continued engagement. It was less helpful for people from minority ethnic groups, and some participants wanted more frequent contact and greater personalization in interactions with health coaches
Mapping changes to consumer-mediated ecosystem function across African savannas
Get PDFThis thesis seeks to clarify how humans are changing ecosystem function in consumer-controlled African savannas. As a framework, it adopts the theory of consumer control (Bond 2005), which argues that vegetation structure in savannas is controlled not only by plants’ ability to fix solar energy, but also by fire and animals’ ability to consume the energy plants fix. The corollary of consumer control is that fire and animals exercise far greater control over function—flows of energy and material—in savannas than in other biomes. As a methodology, this thesis examines two links between land use change and ecosystem function: changes to physical vegetation structure and changes to trophic energy flows from plants through animals. The theory of consumer control suggests that in savannas the first link, vegetation structure, is molded by the second, animal energy consumption. By investigating how global change is altering savannas’ vegetation structure and trophic efficiency, this thesis clarifies how humans are changing ecosystem function and ultimately ecosystems’ ability to support biodiversity and livelihoods. The objective of the first article, entitled “Energy flows reveal declining ecosystem functions by animals across Africa”, was to measure how changes to land use and biodiversity intactness have altered bird and mammal-mediated ecosystem functions across sub-Saharan Africa. Adopting an energetics framework, it found that the total food energy consumption by birds and mammals in sub-Saharan Africa has declined by over one third since ~1700. That decline included a ~75% decrease in functions performed by megafauna. The pattern of decreasing function varied by biome, driven by arboreal birds and primates in forests, terrestrial herbivores in grassy systems, and burrowing mammals in arid systems. Compared to other approaches, the article’s energetics approach highlighted the functional importance of keystone species such as elephants and mole rats, and of smaller animals. The article concluded that approaches relating biodiversity intactness to energy and material flows can help advance efforts to integrate animal-driven functions into biosphere and earth system models, and possibly to identify regional or planetary boundaries for biodiversity. The objective of the second article, entitled “Extensive Woody Encroachment Altering Angolan Miombo Woodlands Despite Cropland Expansion and Frequent Fires”, was to assess how changing land use and fire regimes have altered the vegetation structure of the Angolan miombo woodlands by driving and/or inhibiting woody encroachment. It found that from 2000 to 2020, the woody cover of the Angolan miombo woodlands increased by 8.3%, while open grassy ecosystems declined by 62%. Woody encroachment advanced rapidly even in areas experiencing extraordinarily high burn frequencies, and was concentrated far from the agricultural frontier, in remote areas with low population densities. These results challenge the hypothesis that human-altered fire regimes are the primary driver of woody encroachment in mesic savannas, and instead point to increased CO2 concentrations. The large scale of changes to vegetation structure also indicates that woody encroachment is likely threatening open-ecosystem biodiversity as it transforms savannas’ species composition and ecosystem function, a hypothesis I investigated in my third article. The objective of the third article, entitled “Woody Plant Encroachment Alters Bird Community Composition but not Ecological Function in a Zimbabwean Savanna”, was to quantify how fire suppression and resulting changes to savanna woody cover have altered bird-mediated ecosystem functions in a Zimbabwean savanna. It found that among 70 common savanna bird species, increasing woody cover caused the abundances of 27% of species to decrease and 34% to increase, with losing species distributed evenly across functional lifestyle, diet, and nesting categories. Although increasing woody cover dramatically shifted the bird community’s structure, it did not change the absolute strength of bird-mediated ecosystem functions. These results highlight the risk that woody encroachment homogenizes bird communities across African savannas, threatening the diversity and conservation of open-habitat specialists. The results also suggest, however, that the high functional redundancy of savanna birds may make bird-mediated ecosystem functions resilient to woody encroachment, even as woody encroachment causes an overall decrease in consumer control of the ecosystem. Together, the results of this thesis reveal two major consequences of the change transforming African savannas. First, African savannas are becoming less trophically efficient. As woody plants become more abundant in savannas, they lock up a greater proportion of the ecosystem’s energy, leaving consumers—fire and animals—less able to alter vegetation structure and control ecosystem function. Second, savannas are becoming more homogenous. They are experiencing structural homogenization as woody vegetation encroaches into open areas; functional homogenization as human activity depletes unique megafauna-mediated functions; and taxonomic homogenization as communities of open-ecosystem animals are steadily replaced by closed-ecosystem specialists. Combined, these processes are making African savannas more like ecosystems elsewhere: more closed, more dominated by plants, and more devoid of the big animals that trample and devour vegetation and in doing so transform landscapes
Models of COVID-19 transmission based on behavioural heterogeneity at different scales
No full textHuman behaviour plays a vital yet often under-explored role in infectious disease transmission. The COVID-19 pandemic made this apparent by revealing gaps in current epidemiological models, which largely focus on pathogen-specific parameters while underestimating the complexity of human actions and decisionmaking. This thesis investigates the impact of behaviour on the spread of respiratory pathogens across multiple scales — from small, closed populations such as care homes to the wider community — and highlights how integrating behavioural data can enhance both modelling efforts and public health policy. First, I examine how researchers and policymakers integrated behavioural assumptions during the UK’s rapid-response COVID-19 modelling efforts (Chapter 2). By analysing several of my contributed mathematical models, I show that even minor variations in adherence and compliance can profoundly alter projections, underscoring the need for better-informed, evidence-based behavioural inputs. Next, I investigate a high-resolution contact dataset from a long-term care facility (Chapter 3), focusing on staff–resident interactions. This work demonstrates the substantial heterogeneities within care home contact patterns, suggesting that more nuanced modelling can improve outbreak control strategies in these vulnerable settings. Building on these insights, I developed a stochastic network-based model based on the data (Chapter 4). Simulation results reveal how targeted surveillance and intervention policies can greatly reduce infection risk, depending on staff–resident contact patterns. I then shifted to large-scale population-level data, using repeated surveys to explore how adherence to non-pharmaceutical interventions and risk perception varied over time and across demographic groups in the UK ( Chapter 5). Finally, I broaden the scope further by examining vaccine hesitancy in a Brazilian cohort, investigating how social and demographic factors drive individual 8 decisions about vaccination (Chapter 6). Throughout, I argue that capturing the interplay between pathogen dynamics and human behaviour is crucial for more accurate epidemic models and effective policy interventions. By bridging quantitative modelling, real-world data analysis, and behavioural insights, this thesis offers a multifaceted perspective on respiratory disease control. The findings hold relevance beyond COVID-19, providing actionable strategies for future outbreaks where behaviour remains a critical, but frequently overlooked, determinant of transmission
Joint associations of device-measured step count and sleep duration with incident major adverse cardiovascular events: prospective analysis of the UK Biobank
Get PDFBackgroundThe interaction between physical activity and sleep with cardiovascular disease remains poorly understood, despite both being key risk factors. This study investigated the independent and joint associations of device-measured step count and sleep duration with incident major adverse cardiovascular events (MACE).MethodsProspective analysis of UK Biobank participants who wore a wrist-based accelerometer for seven days between 2013 and 2015. Open-source machine learning algorithms derived daily step count and overnight sleep duration. The outcome was incident MACE (cardiovascular death, non-fatal myocardial infarction or stroke, or revascularisation procedure), identified through electronic health record linkage. Cox proportional hazards models were used to examine independent and joint associations of median daily step count (low [11,000]) and median overnight sleep duration (short [7.5 h]) with incident MACE.FindingsAmong 88,012 participants (mean age 62.2 years [standard deviation, SD 7.8]), 3817 were diagnosed with MACE during follow-up (median 7.9 years [interquartile range, IQR 7.3-8.4]). Low step count and short sleep duration were independently associated with a higher risk of MACE, but there was no evidence of an interaction between step count and sleep duration (P for interaction = 0.42). Compared with the reference group-participants with high step count and intermediate sleep duration-the highest risk of MACE was observed in participants with both low step count and short sleep duration (hazard ratio, HR: 1.84, 95% CI: 1.62-2.10, p < 0.0001).InterpretationThe results of this study show that higher daily step count does not fully attenuate the higher risk of cardiovascular disease associated with short sleep duration, reinforcing the importance of sufficient levels of both daily step count and sleep for the prevention of cardiovascular disease.FundingWellcome Trust (223100/Z/21/Z)
Machine learning for retrosynthesis and synthesisable molecule generation in drug discovery
Get PDFDrug discovery is a notoriously difficult and slow process, with high research and development costs and a decreasing success rate. Computer-Aided Drug Design methods show promise in improving the efficiency of early stage drug discovery, increasing the number of compounds that can be evaluated per design cycle and allowing for pre-filtering of molecules with fast computational methods before they are synthesised. However, many of the compounds designed in silico are not synthesisable in practice or the synthesis routes towards them are not obvious. This leads to computational resources being wasted on designing molecules that can never be tested experimentally. This thesis explores new methods for two approaches assessing and improving synthesisability in drug discovery: retrosynthesis prediction and synthesisability-constrained molecule generation.First, the problem of retrosynthesis prediction for molecules containing heterocyclic scaffolds is considered. Four domain adaptation approaches are benchmarked to develop a single-step retrosynthesis prediction model with improved performance for ring disconnections. Accuracy for heterocycle formations and all reaction classes, as well as computational cost, are considered. A further fine-tuning workflow for continual retraining of the model with newly published data is introduced. The application of the most versatile model, trained with a mixed fine-tuning strategy, is then demonstrated in multi-step retrosynthesis in a retrospective analysis for two drug-like compounds.Next, the development of retro-active, a method for synthesisable molecule generation and optimisation, is described. Retro-active generates molecules based on a known synthesis route and a provided starting material pool. The use of active learning for starting material selection allows for the optimisation of the resulting product molecules for user-defined scoring functions. A benchmark of starting material acquisition and product enumeration methods is included, as well as a comparison to alternative non-machine learning-based starting material selection approaches. The applicability of retro-active for both ligand-based and structure-based drug discovery is demonstrated.The use case of retro-active is then extended to multi-parameter optimisation, to simulate a real-life drug discovery scenario. The compounds are optimised for their structural, physicochemical, and ADMET properties, with a scoring function that combines physics-based and machine learning-based scores. The robustness of the method is demonstrated with both convergent and linear synthesis route topologies and ligands for different target proteins.The thesis concludes with final remarks regarding retrosynthesis prediction and synthesisable molecule generation with retro-active, including future research directions and challenges in the field
Sleep Improvement for Metabolic Health: A Feasibility Trial of a Digital Sleep Treatment in People With Insomnia and Non‐Diabetic Hyperglycaemia
Get PDFInsomnia may play a causal role in type 2 diabetes (T2D). Addressing insomnia through cognitive behavioural therapy (CBTi) in people with non‐diabetic hyperglycaemia could potentially reduce the risk of progression to T2D. To inform a future randomised trial, we performed a feasibility study of digital CBT (dCBTi) in individuals at increased risk of T2D. Participants were identified from 10 primary care practices in the UK and given access to dCBTi. Outcomes were evaluated at baseline (Week‐0) and post‐treatment (Week‐11). Primary feasibility outcomes were ability to recruit and treatment engagement. We also quantified within‐group mean change (95% CI) in insomnia severity (Insomnia Severity Index), health‐related quality of life (EQ‐5D‐3L), depression (Center for Epidemiologic Studies Depression Scale), chronotype (reduced Morningness‐Eveningness Questionnaire), sleep (7‐day actigraphy and diary), continuous glucose monitoring (7‐days) and fasting blood metabolites (insulin, lipids, glucose and C‐reactive protein). The recruitment target was 20. Of 242 people completing screening, 36 were eligible and 24 were enrolled (age 65.5 ± 12.4 years, 70.8% female). Twenty‐three (96%) completed post‐intervention assessments. Treatment engagement was excellent (83.3% completed ≥ 4 sessions). The intervention was associated with a large reduction in insomnia severity [−4.7 (95% CI: −6.2 to −3.2), d = −1.4] and medium reduction in depressive symptoms [−2.7 (95% CI: −5.1 to −0.2), d = −0.5]. Sleep diary parameters tended to show greater improvement following intervention relative to actigraphy. There was evidence of a reduction in serum lactate, glycerol and triglycerides but no clear change in glucose or insulin. Results suggest a full trial is likely feasible and that people with NDH find the intervention acceptable and beneficial. Trial Registration: This trial was prospectively registered on the UKs clinical study registry, the ISRCTN (ISRCTN19682964, https://doi.org/10.1186/ISRCTN19682964
Design strategies, methods, and photophysical insights in polymeric photocatalysts for solar-driven hydrogen evolution
Get PDFSolar-driven hydrogen evolution is emerging as a pivotal strategy in the sustainable energy transition, offering a viable pathway for renewable hydrogen production. Inorganic photocatalysts, such as metal oxides, sulfides, and carbon-based materials, have been extensively studied; however, their performance is often limited by poor tunability of energy levels and structures, low processability, and inadequate utilization of visible light. In contrast, polymeric photocatalysts offer distinct advantages, including precise molecular tunability, scalable fabrication via solution processing, and adjustable energy levels for optimized solar absorption. This review highlights recent advances in polymeric photocatalysts, with particular emphasis on molecular- and particle-level design strategies, fabrication methodologies, and photophysical insights. Molecular design approaches, such as backbone engineering, side-chain modification, and heteroatom incorporation, are discussed alongside particle-level optimization through control of size, morphology, and molecular ordering. Emerging fabrication techniques, including direct polymer dispersions and nanoparticle-based processing, are examined in relation to their effects on dispersibility, light harvesting, and catalytic activity. Photophysical studies are also emphasized to elucidate charge-carrier dynamics and to establish structure–property–performance correlations. Finally, evaluation methodologies, such as hydrogen evolution performance metrics, benchmarking practices, and ongoing challenges in standardization, are critically assessed. This review aims to synthesize current achievements and provide perspectives to guide future research toward the practical implementation of polymeric photocatalysts for solar-driven hydrogen evolution
In vivo CRISPR screening identifies SAGA complex members as key regulators of hematopoiesis
Get PDFThe biological mechanisms that sustain the vast blood production required for healthy life remain incompletely understood. To search for cell intrinsic regulators of hematopoiesis, we perform a genome-wide in vivo hematopoietic stem and progenitor cell (HSPC)-based CRISPR knockout screen. We discover SAGA complex members, including Tada2b and Taf5l, as key regulators of hematopoiesis. Loss of Tada2b or Taf5l strongly inhibits hematopoiesis in vivo, causing a buildup of immature hematopoietic cells in the bone marrow. The SAGA complex deposits histone H3 lysine 9 acetylation (H3K9ac) and removes histone H2B ubiquitination (H2Bub). Loss of Tada2b leads to a reduction in H3K9ac levels and altered H2Bub enrichment in HSPCs, implicating disruption of SAGA complex activity. This is associated with upregulation of interferon pathway genes, reduced mitochondrial activity, and increased megakaryocyte progenitor cell commitment. Loss of these factors also enhances the cell outgrowth and the interferon pathway in an in vivo human myelodysplastic syndrome cell line model. In summary, this study identifies the SAGA complex as an important regulator of hematopoiesis