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Developing an AI-based approach to predict response to anti-EGFR treatment for metastatic colorectal cancer patients using super-resolution imaging of EREG
Get PDFEvery year, there are approximately two million new cases of colorectal cancer worldwide. Globally, there is a growing number of cases of early-onset (< 50 years old) colorectal cancer, which is often diagnosed at an advanced stage. The outcomes for metastatic patients are grim, with a 5-year net survival rate of only 1 in 10. For these patients, treatment that targets epidermal growth factor receptor (EGFR), a cell surface protein that is involved in cell signalling, division and growth, can help shrink metastases for resection or slow cancer progression for palliative care. However, approximately 40% of patients receiving this treatment do not respond. The objective of this study was to investigate whether the nanoscale spatial organisation of epiregulin (EREG), one of the ligands for EGFR, could help predict response to anti-EGFR treatment for metastatic colorectal cancer patients.
To achieve this objective, we imaged tissue samples from metastatic colorectal cancer patients using single-molecule localisation microscopy (SMLM), which could resolve the high-precision positions of EREG proteins. We then developed and tested artificial intelligence (AI) based pipelines, locpix and ClusterNet, to segment and classify large-scale structures in SMLM data, such as cells. These pipelines were then applied to the SMLM data from the patients to manually segment the cells and classify them by response to treatment.
This approach may improve over an existing method for predicting response, which uses the protein expression level of EREG, but was inconclusive due to the small sample size in this study. More broadly, this study showed that the organisation of EREG may help predict response to anti-EGFR treatment. Further, we anticipate that the two novel AI-based pipelines may be generally useful for the analysis of SMLM data. This includes the first example of a graph-neural network designed for whole-graph classification of SMLM data. These pipelines could help to realise the use of SMLM data to characterise phenotypes and predict response to treatment across a wide variety of disorders
Exploring British Pakistani Muslims’ Experiences of Family Involvement in Family Work for Psychosis: An Interpretative Phenomenological Analysis
Get PDFIntroduction: Research suggests that British South Asian individuals, including
those of Pakistani heritage, face a higher risk of developing psychosis compared to
White individuals. Pakistani culture, Islamic teachings and clinical guidelines
strongly emphasise family support, cohesion, and emotional connection. Despite
this, little is known about the experience or effectiveness of family work (FW) for
British Pakistani Muslims experiencing psychosis. Most research on FW has
focused on quantitative outcomes for individuals and carers, in which British
Pakistani Muslim voices remain largely unheard. This is problematic as some
Pakistani studies suggest that individual therapy approaches may not be culturally
appropriate. UK-based research has similarly highlighted the importance of family
involvement in mental healthcare for South Asian communities. The current study,
therefore, aimed to address this critical gap by providing an in-depth exploration of
British Pakistani Muslims’ experiences and understanding of family involvement in
FW for psychosis.
Method: A qualitative approach was used. Five British Pakistani Muslim
individuals who had participated in FW within the context of psychosis were
recruited from Early Intervention in Psychosis Services (EIPs). Semi-structured
interviews were conducted and analysed using Interpretative Phenomenological
Analysis.
Results: Six Group Experiential Themes were identified: 1) A Test of Family
Support and Commitment; 2) Opening Up: A Journey to Safety; 3) Healing Through
Connection; 4) Integrating the Heart, Mind and Soul; 5) Navigating Systems: Family
Work in an EIP Context; and 6) The Toll of Therapy.
Discussion: Findings are discussed in relation to broader theories and literature on mental health, family support, cultural and religious principles, systemic factors, and FW
approaches for psychosis. The study’s strengths and limitations are considered,
followed by an examination of implications for clinical practice and future research.
Key themes include access to FW, implicit narratives, perceived benefits, and the
importance of cultural and religious sensitivity
Educational games and their impact on mathematics anxiety in university students
Get PDFThis study explores the potential of educational computer games to reduce mathematics
anxiety among university students at the University of Sheffield and extends existing
literature by mapping everyday mathematics activities and identifying design attributes linked to anxiety. A systematic review of mathematics‐anxiety scales informed the selection of the instrument used in this work, and four mixed‐methods studies were conducted, combining pre/post questionnaires, diary studies, eye tracking and interviews. We observed that playing educational games resulted in a modest 13% reduction in self‐reported mathematics anxiety over a 30‑day period. Eye‐tracking data revealed that participants with higher mathematics anxiety spent more time fixating on problem statements than on potential solutions, suggesting that working‑memory constraints may underlie some of their anxiety. Study 2 expanded Bishop’s (1988) framework of everyday mathematics by identifying a new “Predicting” category (e.g. estimating dimensions, costs or time), underscoring the breadth of mathematics embedded in students’ daily lives. Diary entries also showed that fluctuations in mathematics anxiety closely mirrored general anxiety, pointing to the importance of broader wellbeing when designing interventions. Familiar real‑life contexts and customisable difficulty levels were found to enhance engagement and reduce anxiety, and these insights were synthesised into a fishbone model of game attributes that affect mathematics anxiety.
However, the evidence is limited by the small, self‐selected sample (n = 17), the adaptation of the MARS scale for a UK context and the exploratory design of the study, which restrict generalisability. Nevertheless, the research offers a preliminary framework for understanding how educational games might influence mathematics anxiety and provides practical recommendations for game developers and educators seeking to foster positive attitudes toward mathematics through gaming interventions
Summer Mesoscale Convective Systems over East China under Current and Future Climate
No full textMesoscale convective systems (MCSs) are large, organized deep convective storms producing intense, widespread rainfall. East China, strongly influenced by the summer monsoon, is a key hotspot where lives of citizens and economy are threatened by MCS related rainstorm, winds, and lightning. Understanding summer MCSs in current and future climate is therefore essential for risk assessment. Convection-permitting (CP) regional Numerical Weather Prediction (NWP) models have been widely used to study MCSs, yet their skill remains uncertain, especially in terms of capturing storm responses to background circulation. This study investigates climatological characteristics and life cycles of summer MCSs over eastern China under current and future climate, and examines the accompanying (thermo-)dynamic atmospheric environment and soil moisture (SM) conditions. The ability of a CP Weather Research and Forecasting (WRF) model to represent MCSs and their impacting factors has been systematically evaluated.
MCSs are mostly found in regions with abundant warm-moist air or complex topography. MCSs contribute approximately 20% of total rainfall. They typically initiate in the afternoon and intensify at night over low-elevation eastern and coastal regions, whereas initiating at midnight on the leeward sides of complex terrain. MCSs initially show rapid expansion of convective cloud with weakening, then peak and transition to stratiform-dominated cloud, after which rainfall decays quickly while system area shrinks more slowly.
CP WRF model shows reliable skill in reproducing climatology of MCSs. It shows added value over ERA5 in simulating MCS diurnal cycle. Large uncertainties remain in the diurnal peak time over complex terrain and the distribution of rainfall intensities. Using CP WRF model and ERA5 data, this study identifies total column water vapor (TCWV) and convective available potential energy (CAPE) as key thermodynamic factors. The product of storm-time TCWV and maximum vertical motion indicated by square root of CAPE scales MCS maximum precipitation. Storms are also found to be related to low-level zonal wind shear. Intense MCSs are associated with strong wind shear, and propagation of storms are correlated with shear. This is the first study to demonstrate that WRF model reproduces these effects, confirming its skill in simulating the organized thunderstorm response to background circulation.
A mechanism of SM favoring intensification of mature MCSs was further revealed with CP WRF simulations. Convective cores of mature MCSs tend to occur on the drier side of mesoscale (∼200 km) SM gradients. These gradients generate strong boundary-layer thermal structures, which enhance local moisture convergence and vertical wind shear. Precipitation and MCS cloud cover feed back positively on soil moisture and surface energy heterogeneity. This result highlights the importance of land-atmospheric interactions and suggests that improved land-surface representation could enhance MCS prediction.
Pseudo-Global Warming experiments under the high-end warming scenario Shared Socioeconomic Pathway (SSP)5-8.5 project a future shift toward fewer but more intense, convectively dominated MCSs with larger precipitation areas and longer lifespans. Projected extreme rainfall increases with super Clausius–Clapeyron scaling, reflecting enhanced updrafts and mesoscale circulation besides the thermodynamic profile. Stronger storm-time shear combined with higher TCWV and CAPE leads to greater peak convective precipitation and expanded convective areas. The increases in intensity, spatial coverage and life duration produce higher total rainfall per event, together with reduced frequency, amplifying flood hazards and climatic vulnerability
Ice-contact lakes and their influence on Himalayan glacier evolution
No full textMountain glaciers are rapidly losing mass due to climate warming. In the Himalaya, this threatens downstream communities that rely on the meltwater for hydropower, irrigation and sanitation. However, projections of future glacier change are hindered by limited empirical data and the omission of key processes, particularly interactions with ice-contact lakes, which can enhance melt and flow but are often oversimplified or excluded from numerical models. This thesis addresses this gap through a multi-temporal, multi-disciplinary investigation of the role of ice-contact lakes in past, present and future Himalayan glacier evolution. Remotely sensed datasets of glacier velocity, surface elevation change, and lake area were combined to quantify the evolution of >350 lake- and land-terminating glaciers across the Himalaya between 2000 and 2019. Glacier response varied according to the lake evolutionary stage. In the Eastern Himalaya, where lakes are larger and more numerous, lake-terminating glaciers showed significantly enhanced surface lowering (by 0.14 m a-1), and ice velocity anomaly (by 0.29 m a-1 decade-1) compared with land-terminating glaciers, differences not observed further west. In situ observations provided the first seasonal assessment of thermal dynamics at a Himalayan ice-contact lake (Thulagi Lake, Nepal), revealing a brief but thermally intense stratification period during early monsoon (May to July), with surface temperatures exceeding 9°C. However, in comparison to observations from other glacierised regions, the summer stratification period was shortened from ~5 to ~2 months by glacial meltwater inputs and the monsoon. Numerical modelling of Thulagi Glacier assessed the combined influence of supraglacial debris, which prolonged glacier extent by up to 122 years, and ice-contact lakes, which accelerate short-term mass loss by up to 35%. Although ice-contact lakes may not significantly alter total glacier mass loss projections over centennial timescales, neglecting their short-term effects generates substantial uncertainties in the timing of mass loss
Speech Analytics for the Detection of Neurological Conditions in Global Varieties of English
No full textDementia refers to the decline of cognition and memory due to neurological conditions. Both speech content and acoustics can be analysed as biomarkers to detect dementia, offering a promising, cost-effective alternative to traditional methods. While speech-based dementia classification has shown success for L1 (native) speakers, this thesis explores the challenges posed by L2 (non-native) English speakers.
Investigating Automatic Speech Recognition (ASR) and its performance across global English varieties, we identify a disconnect between advertised and real-world system capabilities. ASR systems often reduce L2 language diversity, treating fine-tuned derivations of the same models as unique systems. We analyse ASR evaluation methods and propose a new multi-metric standard inspired by advances in Machine Translation. Examining ASR performance in dementia datasets, we find only a small deviation between L1 and L2 speech using the latest models, suggesting potential reliability for transcribing non-native speech. However, L2 speech produces speech analytics that cluster more closely with L1 speakers with dementia than with healthy L1 speakers, particularly in lexical and syntactic complexity metrics. This thesis proposes a framework for classification pipeline evaluation focused on measuring feature fluctuation as an interpretable framework for understanding inaccuracies within analytics directly fed into our classification models.
This system design approach aims to support clinician-facing reports and improve awareness of healthcare equity outcomes. To deploy these systems, we must better understand how different configurations impact minority voices. We propose longitudinal, speaker-dependent analytics as a means of calibrating dementia classification pipelines to a profile of speech analytics rather than single-session data. This approach would contextualise ‘healthy’ in the context of each speaker’s voice. Additionally, we suggest redefining healthy control classifications to better reflect cognitive concerns. Finally, we advocate for a more integrated approach to Speech Technology development for dementia detection, ensuring system outputs align with clinician-facing reports, patient-facing reports, and assurance protocols
The Godly Ministry of Oliver Heywood (1630-1702): His Experience and Significance
Get PDFOliver Heywood (1630-1702) lived through a period of fluctuating religious persecution and toleration after the Restoration in 1660. As a moderate Presbyterian minister, he provoked local opposition from some of his congregation in Coley near Halifax and was suspended from office in 1662, before being formally ejected under the Act of Uniformity later that year. However, supported by his lay hearers, a group of sympathetic gentry families and an informal network of like-minded Nonconformist clergy, he continued to preach and minister across a broad area of Yorkshire and Lancashire for the next thirty years. He experienced bouts of fierce persecution, harassment and imprisonment under the penal acts, which he survived through sustained and, at times, dramatic acts of resistance. Heywood’s archive consists of a wealth of first-person primary sources, including an autobiographical work, diaries and reflections in the tradition of Puritan self-scrutiny, together with published treatises, sermons and letters. Using this material and applying a microhistorical perspective to his accounts of specific events, alongside contextual, literary and quantative analysis, this thesis takes a thematic approach to analysing Heywood’s experience and establishing his significance. It considers the areas of life-writing, community, patronage, itinerancy and his published oeuvre to argue that Heywood deserves greater recognition from historians of post-Restoration religion. This derives from a number of reasons: his substantial literary output, his success in sustaining Presbyterianism under challenging circumstances and his influence and legacy over a wide area of Northern England. Thus, this thesis aims to establish Heywood’s importance in two related fields of scholarship: Puritan life-writing and the social dynamics of seventeenth-century Protestant Dissent
Identification of BRD4 as a Synthetic Lethal Gene to Treat MCPH1 deficient Ovarian Cancer
No full textDrivers of larval connectivity variability among coral reefs in Southeast Sulawesi
Get PDFCoral reef patches are connected via dispersal of larvae, i.e., larval connectivity, that varies across space and time. Larval connectivity supports gene flow, sustains fisheries, and stabilizes larval supply. Connectivity also enhances the effectiveness of marine reserves by facilitating valuable conservation processes. How larval connectivity responds to environmental factors, excluding oceanographic factors, is largely unknown, with little
information available on the influence of external factors on connectivity patterns. I address this knowledge gap by identifying how environmental, climate, and habitat factors drive variability in larval connectivity. I correlate graph-theoretic proxies of larval connectivity with sea surface temperature (SST) and climate variables using Generalized Additive Models (GAM) and recursive partitioning with regression trees to assess each factor’s effect on connectivity between 487 reefs in Southeast Sulawesi, Indonesia over a 20-year period. I further simulate how coral reef habitat degradation over that period may change patterns of larval connectivity. There is a significant effect of El Nino, Pacific Decadal Oscillation (PDO), and Sea Surface Temperature (SST) on larval connectivity. SST above 28°C decreased out-degree and in-degree by an average of 0.65 standard deviations and increased self-recruitment by an average of 0.74 standard deviations. This result means that as SST increases above 28°C, there is a decrease in both incoming and outgoing connections between reefs, and more larvae remaining within their source reef. Generalized Additive Model (GAM) analysis of the effect of SST on connectivity metrics shows higher explanation of variance at higher SST. This result supports the existence of an SST threshold at which connectivity for fish species in the region will predictably decline. Spatial analysis using spectral clustering shows a larger effect of reef location (spatial cluster) on connectivity metrics compared to SST. Generally, two out of six clusters have high self-recruitment while the remaining four clusters have high out-degree and in-degree. Habitat degradation decreases cumulative flow of larvae by 73 percent when comparing flow matrices before and after habitat degradation. Additionally, habitat degradation reduces variance of cumulative flow for coral trout and rabbitfish species. Further, these trends are predicted to continue under future habitat degradation values. These results allow us to predict how connectivity will change as SST and habitat degradation increase due to climate change
Secondary electron hyperspectral imaging of electrode components in lithium-ion batteries
No full textThis thesis presents secondary electron hyperspectral imaging (SEHI) as a technique to gain novel insights into the surfaces of lithium-ion battery (LIB) electrodes and their components through spatially localised surface chemical characterisation down to the nanoscale. The transition to renewable energy has placed huge demand on materials used in LIBs. There is a significant cost associated with materials degradation in LIB electrodes causing unpredictable capacity fade. Many of these degradation mechanisms are effective (and observed) at electrode material surfaces. SEHI is a proven analysis workflow in several fields including polymers, biomaterials, solar cells and carbon thin films, and has application in the focussed ion beam scanning electron microscope (FIBSEM), which is a workhorse of materials characterisation. This work is the first SEHI characterisation of LIB materials. The methods for SEHI developed here were used to image surface chemistry in LIB electrodes and identify (in-)homogeneity which can cause increased surface degradation and unpredictable capacity fade at the LIB cell level. Starting with an assessment of the suitability of SEHI for the task of characterising thin surface layers comprised of carbon, lithium and transition metal oxides, the approach was taken to build knowledge of the available spectral information with a set of reference material systems, before application to the most complex surface chemistries found in charge-discharge cycled LIB electrodes. In doing so, new sample preparation, data processing and analysis approaches were developed. These included peak fitting SE spectra of graphitic and amorphous carbons to identify spectral ranges for sp2, sp3 and amorphous carbon. Sensitivity to Li metal and compounds of Li followed. Finally, this knowledge was applied to SEHI characterisation of NMC811 cathode material pre- and post-charge-discharge cycling. The established workflows for surface chemical imaging demonstrated application to characterising graphitic carbons and show promise for further positive electrode solid-electrolyte interphase studies
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