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Machine Learning-Driven Biomarker Discovery for Depression and PTSD in Traumatic Brain Injury
Get PDFIntroduction
Machine Learning holds significant promise in advancing precision psychiatry. Post-psychiatric complications such as PTSD and depression are common after a Traumatic Brain Injury (TBI) (Mayer & Quinn, 2022, Ahmed et al., 2017). Yet, we still lack standard diagnostic criteria for post-TBI psychiatric complications, leaving many individuals undiagnosed and without appropriate healthcare. Through the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Brain Injury working group, we addressed this issue by applying state-of-the-art machine learning and imaging analysis techniques to identify specific and localized neural markers of psychiatric illness in TBI. The findings of this research can assist in developing sensitive, personalised biomarkers for early diagnosis of psychiatric disorders in TBI, guiding treatment strategies (Siqueira Pinto et al., 2023).
Methods
Machine learning using logistic regression with Elastic Net regularization was applied to segmented 3D T1-weighted and diffusion MRI data of the brain to classify 1) individuals with TBI only (n= 547) vs healthy controls with no TBI (HC) (n=150) 2) TBI with psychiatric diagnosis vs HC (TBI/PTSD: n = 196, HC: n = 132; TBI/Depression: n = 194, HC: n = 150; TBI/PTSD & Dep: n = 144, HC: n = 123). Age, sex, and intracranial volume were included as covariates in all models. Participants consisted of n=73 females and n = 624 males (mean age: 47.2 ± 15.6 years). The dataset consisted of LIMBIC-CENC, ADNI-DoD and Duke University datasets. Data was harmonised across consortia using the ComBat algorithm and consisted mostly of deployment-related TBI. White matter features were segmented using the JHU White Matter atlas in a TBSS approach; grey matter cortical and subcortical features were segmented using FreeSurfer. The total number of grey and white matter features included in each model was 239.
Results
Neuroimaging data classified individuals with TBI and depression vs HCs returning an area under the curve (AUC) of 0.66. The cingulum section adjoining the hippocampus (CGH) was a top discriminant feature - revealing reductions in mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) in right and left CGH and increases in fractional anisotropy (FA) in the cingulum in the cingulated cortex (CGC) predominantly in the left hemisphere. The TBI/Depression/PTSD vs HC model returned an AUC of 0.64 again showing reductions in MD, AD, RD in CGH. The TBI/PTSD vs HC model returned an AUC
of 0.58 with reductions in MD, AD and RD in tracts such as ALIC, CST and CGH. The TBI-only vs HC model returned an AUC of 0.59. There were increases in FA across a range of limbic and association tracts, including pathways involved in emotion regulation and cognitive processing, while reductions in MD, AD, and RD were observed in projection and cingulum-related tracts. All models performed significantly better than a null model.
Conclusion
The results from four machine learning models identify distinct neuroimaging biomarkers associated with traumatic brain injury (TBI) and psychiatric comorbidities. In TBI and depression, disruptions in the microstructural organization of the CGH may contribute to both cognitive and emotional symptoms commonly seen in post-TBI depression. The cingulum is critical for emotional processing, mood regulation, and linking the hippocampus to other emotion-related areas. Its involvement in depression is well established. In this group, increased FA in the CGC may reflect compensatory structural changes in response to CGH damage. As one of the last white matter tracts to mature— reaching peak FA around 42 years old—the cingulum may be particularly vulnerable to environmental impacts (Dennis et al., 2023). Its disruption could serve as a neurobiological marker for post-TBI depression, aiding in early identification of at-risk patients and enabling targeted interventions to mitigate long-term psychological consequences
Optical coherence tomography angiography for assessing retinal microvascular changes in Alzheimer's disease: the potential of retinal metrics in the asymptomatic stage
No full textAlzheimer’s disease (AD) presents a significant global health challenge. AD is usually diagnosed
in its advanced stages after permanent cerebral damage, making it very difficult
to treat. Microvascular dysfunction is a crucial aspect of dementia and is believed to be a
driving factor in its progression. If quantifiable metrics for the early stage could be identified,
it would contribute to a more accurate estimation of an individual’s risk of developing the
disease. While existing biomarkers such as cerebrospinal fluid (CSF) Aβ42 amyloid, medial
temporal-lobe atrophy, and white matter lesion volumes aid in identifying and monitoring
symptomatic AD, they have not been able to reliably identify AD in its early stage.
The retina is linked to the brain’s cognitive areas and shares embryological origin. Optical
coherence tomography angiography (OCTA) is a non-invasive imaging modality that visualizes
the retinal microvasculature in high resolution. Being a non-invasive imaging modality
has consolidated OCTA as a valuable tool for detecting vascular changes related to the retina
and brain diseases such as cerebral small vessel disease and symptomatic AD. This sets a
solid foundation for the extension of OCTA research to asymptomatic AD.
This thesis used a previously published framework designed to extract quantitative metrics
from OCTA images that characterize the retinal microvasculature through various retinal
metrics. To further validate the framework for use in this thesis, it was important to establish
the reproducibility of the framework. The first analysis investigated whether previously
reported retinal metrics computed from the framework were reproducible across repeated
scans of 22 eyes from 22 unique patients (mean age = 64.86+/-7.30 years, 77% female).
Furthermore, the impact of different vessel segmentation methods was investigated on the
reproducibility of these metrics (optimally oriented flux (OOF) and Frangi filter segmentation).
Results demonstrated the reproducibility of OCTA retinal metrics across repeated
scans and suggest that the choice of vessel segmentation method can significantly impact the reproducibility of OCTA retinal metrics.
Once reproducibility of the framework was established, retinal microvascular changes
in midlife participants at risk of developing AD later in life were investigated. The aim
was to identify OCTA retinal metrics that show a significant difference between control
and participants at risk of developing AD (mean age = 51.2 years). Three different risk
groups were investigated from a single cohort study. Participants with and without the
Apolipoprotein E4 (APOE4) gene, participants with and without a known family history of
dementia (FH), and participants with high and low Cardiovascular Risk Factors, Aging, and
Dementia (CAIDE) scores. This was carried out at baseline and over a two-year follow-up.
Results demonstrated that there were retinal metrics that showed differences between control
and participants at risk of developing AD across risk groups at baseline and over a two-year
follow-up.
In addition to investigating retinal microvascular changes in mid-life individuals at risk of
developing AD, it was important to explore the relationship between retinal microvasculature
changes and established neuroimaging biomarkers for symptomatic AD. Results demonstrated
significant associations between OCTA retinal metrics and increased WMH burden across
various brain regions. This included the whole brain, deep, and periventricular areas. These
significant associations carried over across the brain’s four lobes, including the left and right
occipital, frontal, temporal, and frontal lobes. The thesis also investigated whether there were
potential correlations between retinal microvasculature changes and gray matter volumes
(GMV). There was a significant association between OCTA retinal metrics and the whole
brain, subcortical, and left and right hippocampus.
The final analysis on retinal microvascular changes investigated how OCTA retinal metrics
progress between a mid-life cohort that is at risk of developing AD to an elderly cohort
that consists of individuals diagnosed with mild cognitive impairment (MCI) and AD. To
explore the progression of OCTA retinal metrics, the analyses leveraged the use of two
distinct cohorts: the PREVENT cohort with participants at risk of developing AD and Duke
University’s study cohort with participants consisting of a diagnosis of elderly controls, MCI
and AD. The findings revealed that a retinal metric related to vascular density was significantly
different between mid-life at-risk participants (high CAIDE score) and elderly participants with
AD and MCI even when the same metric remained constant between the control groups of
both cohorts. This highlights the potential of OCTA for tracking the progression of AD from
asymptomatic to symptomatic stages.
The scarcity of publicly available OCTA datasets and privacy concerns with sharing real
patient data hinder the development of robust diagnostic models. This thesis proposed the
use of Latent Diffusion Models (LDM) for generating novel and anatomically accurate synthetic
OCTA images as a method for sharing health-protected OCTA datasets. Anatomical
accuracy was confirmed as there were no significant differences in the OCTA retinal metrics
between the synthetic and real images in both conditions (AD and control). A Logistic
Regression model trained only on synthetic retinal metrics achieved comparable AUC scores
(AUC: 0.614, CI: 0.546, 0.668) to the model trained only on real metrics (AUC: 0.616,
CI: 0.546, 0.642). Increasing the number of synthetic samples improved the model’s performance
and robustness (AUC of 0.634 CI: 0.618, 0.654 using 3500 synthetic samples).
LDMs can generate synthetic OCTA images that encapsulate diagnostic information present
within real images.
In conclusion, this thesis contains novel analyses that add to growing evidence on the
potential use of OCTA as a valuable tool for detecting early vascular changes associated
with AD. Further research should be conducted to validate the retinal metrics as reliable
biomarkers for early-stage detection
On unifying heterogeneous data management: from philosophy foundation to system implementation
No full textThis thesis aims to unify heterogeneous data anagement with a revised relational model for uniformly querying and updating across data in different formats without performance degradation. To address this well-recognized crucial challenge for extracting value from the variety of big data, the discussion begins with a prior philosophical reflection, though its necessity is often overlooked, on this variety itself: the existence of numerous incompatible data models. We clarify that various data models are all essentially cognitions of the task of database management, artificially developed under different considerations but all with the identical goal of making raw data manageable in the same physical world, rather than Cartesian mirror-images of distinct objective realities. The typical ignorance of this neglects the identity behind the opposites among the structures and operations they impose, thereby undermining the ideal of developing a general method for the task of database management.
Regaining this long-dusted ideal, we recognize a pathway to achieving it through an investigation into the distinctiveness of the relational model that has enabled it to dominate the field of database management for decades. We show that the key characteristics of the relational model can directly address the model-independent challenges inherent in this task, thereby enabling the systems developed accordingly to perform better, which thus makes them indispensable for any data model to succeed in practice and therefore renders them also “relational”. This is not meant to establish the relational model as a “codex”, but rather to shed light on the principle of evolving it to catch up with the continuously progressing task of database management, so that the overall landscape of this task, amidst endless emerging challenges, can still be addressed by a single model rather than a combination of heterogeneous ones.
In light of this, as a preliminary step toward unified database management, we provide an overarching framework to uniformly adopt different standpoints in accomplishing this task without combining heterogeneous models. Specifically, surrounding a proposed RG (Relational Generative) model, we develop different components for the options within the following aspects to be configurable: the connections can be represented either explicitly or implicitly; the consistency can be annotated on different data items and operations, across distinct isolation levels; and the analysis of data can be programmed both in the declarative and imperative paradigms. Practitioners would then no longer need to turn to an alternative, purpose-built model or system to adopt a particular method for managing their data, at least within these aspects, thereby paving the way toward the unification of heterogeneous data management.
More technically, in the first part, we introduce the RG model, an extension of the relational model with logic-level pointers to connect different tuples, to represent graphs in relations while preserving its topology. By incorporating graph exploration via logical-level pointers as an operator, we generalize the relational query evaluation workflow to provide an enlarged unified plan space for graph-relation hybrid queries. The optimal query plan can then be generated and executed on a typical relational database system seamlessly without the need for a customized execution engine, retaining the battle-hardened optimizations embedded in relational databases while enabling hybrid queries over graphs and relations.
In the second part, still concentrating on the analytical task, we identify redundant computations in query evaluation and introduce a recursive execution paradigm to eliminate them accordingly. Namely, we show that different subqueries might be automorphisms of each other, causing redundant computations that can only be eliminated by sharing results among subqueries. This will thus introduce recursive data passing, which breaks the separate execution of each join, even if those queries can still be described without recursion. We theoretically prove that such a recursive execution paradigm can help query evaluation to reach a complexity lower bound in string pattern matching that was once unachievable.
In the third part, we concentrate on transactional tasks. Building upon the approach above for unifying relations and graphs, we develop a way of running transactions across relations and graphs. In addition, we further propose a fine-grained isolation level to warrant data-driven isolation guarantees according to user-defined annotations in each transaction, reflecting the heterogeneity of the data. This allows data items touched by a single transaction to be treated separately and differently, protecting only the critical logic with relatively high isolation while avoiding unnecessary isolation guarantees, thereby improving transaction throughput without impairing the correctness of application logic during concurrent execution.
Finally, as a practical and accessible implementation of the proposed mechanisms, WhiteDB has been developed to assess the benefits they offer when applied to real-world data. It allows the same piece of data to be viewed both as “data model” and “object” and also to be accessed using both declarative and the imperative programming paradigms. Such a Versatility enables it to function as both C++ library with a variety of frequently utilized functionalities as well as an embedding database, thereby supporting an integrated multi-paradigm data analysis
Personalised screening intervals in diabetes care: evaluating risk-based models for diabetic retinopathy and diabetic foot disease
No full textBACKGROUND AND AIMS:
Diabetes is a major public health concern, affecting 4.4 million people in the UK, with complications such as diabetic retinopathy and diabetic foot leading to significant morbidity. Routine screening programs aim to detect these complications early, but current guidelines rely on fixed screening intervals based on prior test results. This approach overlooks variations in individual risk profiles, potentially leading to unnecessary screening for low-risk individuals and delayed detection for high-risk patients. This research investigates whether personalised, risk-based screening schedules can improve upon current guidelines.
THIS STUDY AIMS TO:
Develop and validate survival models for diabetic retinopathy and diabetic foot complications.
Compare risk-based screening schedules with existing guidelines to evaluate their ability to stratify patients according to risk, and their impact on healthcare workload.
Collect feedback from healthcare professionals on the utility of those models and gain insight into the barriers and requirements for implementation.
materials and methods:
This retrospective cohort study analysed data from 102,638 individuals with type 1 or type 2 diabetes, attending Greater Glasgow and Clyde NHS clinics between 2006 and 2021. Interval-censored parametric survival models, and a GLM-cloglog were developed using forward selection from over 200 features, including laboratory results, comorbidities and prescriptions. Model performance was assessed using precision-recall (PR) AUC, receiver-operating characteristic (ROC) AUC, and Uno’s concordance (C) index, while calibration was evaluated using calibration plots. Separate models were developed for diabetic foot and retinopathy, each predicting time to severe or any (mild or severe) adverse outcomes.
Personalised time-to-screen recommendations were obtained by sampling the survival function, conditional on individual covariates, at risk thresholds matching the prevalence of the corresponding outcome. The proposed screening strategy was compared with current guidelines using confusion matrix metrics and workload change analyses. Additionally, the calculated survival estimates were reviewed by diabetes care professionals and their views were gathered on: 1) whether the model’s predictions align with clinicians’ expectations, and 2) their opinions on extending the screening interval length limits.
RESULTS:
Among 401,550 retinopathy screening appointments, 4.8% resulted in severe outcomes, while 27.6% resulted in mild or severe outcomes. Similarly, in 368,042 foot screenings, 9.4% led to severe and 28.1% to mild or severe outcomes.
The retinopathy model (log-normal accelerated failure times) for severe outcomes contained 13 covariates and on the withheld test set achieved ROC AUC 0.92, PR AUC 0.34 and C 0.70, while the model for any outcomes contained 12 features and achieved ROC AUC 0.89, PR AUC 0.81 and C 0.74. The diabetic foot model (log-normal proportional hazards) for severe outcomes contained 19 covariates and achieved ROC AUC 0.89, PR AUC 0.81 and C 0.76, while the model for any outcomes contained 19 features and achieved ROC AUC 0.73, PR AUC 0.34 and C 0.70.
When applying the best-performing models at a decision threshold equal to outcome prevalence, the proposed approach outperformed current policy in terms of sensitivity, negative predictive value, specificity and precision.
Due to the generally low risk across the cohort, models recommend longer re-screening intervals for the majority of appointments in the dataset compared to current guidelines. Personalised screening intervals, with interval length limits identical to that of current guidelines, achieve 11% reduction in workload for retinopathy and 3% for diabetic foot screening. Lowering risk thresholds by 40% for retinopathy and 20% for foot screening, therefore facilitating earlier detection, allowed for a 2% and 0% reduction in workload compared to current policy.
An expert panel of seven diabetologists and two nurses found that the model’s risk predictions aligned with their clinical intuition. They supported extending screening intervals but expressed concerns about dynamic risk changes, patient adherence, and potential anxiety over missed healthcare opportunities.
CONCLUSION:
This thesis successfully developed an analytical framework for generating models for personalised screening of diabetic complications. The resulting risk trajectories were favourably assessed by healthcare professionals, who recognised their potential for improving risk stratification. Overall, personalised screening schedules, coupled with a reduction of the level of risk at the time of screening, could enhance healthcare resource efficiency while improving patient outcomes
The contribution of prophage degredation and a novel fusion protein to the success of emm4 Streptococcus pyogenes
No full textStreptococcus pyogenes (S. pyogenes) is a Gram-positive human pathobiont responsible for a
diverse spectrum of infections, including scarlet fever, necrotizing fasciitis, and rheumatic
fever. A new clonal lineage of emm4 S. pyogenes—designated Clade B—has been reported in
Europe and the United States, distinct from the previously dominant Clade A. Clade B is
associated with enhanced virulence, yet the molecular mechanisms underlying its
evolutionary success remain largely unexplored. This thesis investigates key genetic and
phenotypic adaptations in Clade B, particularly the degradation of prophage elements and
the emergence of a novel fusion protein, emm::enn, and their implications for bacterial
fitness.
Through comparative in silico and phenotypic analyses of Clade A and Clade B emm4 isolates,
we identified a defining genomic feature of Clade B: a rearrangement of genome segments
around ribosomal RNA operons, leading to altered genome architecture and a shifted
positioning of the terminus. The prophage elements present within Clade B strains are
degraded rendering them cryptic, however the impact of this on streptococcal fitness has not
been robustly assessed. To address this, prophage induction assays using mitomycin C were
performed and showed that while intact prophages in Clade A isolates were excisable, the
degraded prophages in Clade B remained unresponsive. This loss of inducibility significantly
reduced prophage-mediated bacterial lysis, suggesting a survival advantage for the emergent
lineage. RNA sequencing further revealed that genes within the spd3-carrying prophage were
highly expressed upon induction in Clade A but remained transcriptionally silent in Clade B.
To elucidate the molecular mechanisms that underpin prophage induction in S. pyogenes, we
generated isogenic mutants in a representative Clade A strain, targeting CovS a key regulatory
protein and RecA, a well-characterized regulator of DNA damage-induced prophage
activation in Gram-negative bacteria. Interestingly, deletion of covS suppressed spd3
prophage expression, enhancing bacterial survival upon mitomycin C exposure. In contrast to
previous studies, recA deletion did not inhibit prophage induction; rather, transcriptomic
analysis revealed upregulation of prophage-associated genes, suggesting a previously
unrecognized RecA-independent pathway of DNA damage-mediated prophage induction.
Furthermore, we investigated biofilm formation as a potential contributor to Clade B fitness.
Biofilm quantification assays demonstrated a significant increase in biofilm formation in Clade
B compared to Clade A, implicating the novel emm::enn fusion protein in this phenotype.
Heterologous expression of emm::enn in Lactococcus lactis confirmed its role in promoting
biofilm formation, while proteinase K treatment suggested a protein-mediated mechanism.
Adhesion assays using tonsil keratinocytes revealed that emm and enn contributed to S.
pyogenes adherence to the host epithelium by Clade A but not Clade B isolates, suggesting
functional divergence between the lineages, possibly mediated by the novel emm::enn fusion
protein.
Taken together, our findings reveal that Clade B emm4 S. pyogenes have undergone genetic
adaptations that enhance bacterial fitness. The degradation of prophages reduces prophagemediated
lysis enhancing in vivo survival, while the acquisition of novel genetic elements,
such as emm::enn, promotes biofilm formation. Moreover, this study identifies CovS as a
previously unrecognized regulator of prophage induction, and challenges the prevailing
notion that S. pyogenes prophage activation is entirely RecA-dependent. These findings
highlight an additional selection pressure acting on CovS in vivo and accentuates an alarming
trajectory toward increased persistence and virulence, with potential implications for S.
pyogenes epidemiology and treatment strategies
Stories of Decolonisation: Experiences from Children and Young People
Get PDFOn Tuesday 10 June 2025, from 9:30 to 14:30 in Room 1.55 at Edinburgh Futures Institute at the University of Edinburgh, the public engagement symposium, ‘Stories of Decolonisation: Experiences from Children and Young People,’ brought together university scholars from diverse disciplinary backgrounds to create sociological fiction, narrating stories inspired by children and young people with whom they worked in their research. Through these narratives, we explored how children challenge, navigate, and transform the colonial structures that shape their daily experiences
Gender, affect and art's alternative workplaces: a feminist critique of socially engaged art paradigms in Europe
No full textSocially engaged art has become fully integrated into international artistic events
and policy programmes, particularly in the aftermath of social movements such as
Occupy in the United States or the Indignados in Spain (2010s), that emerged in
response to the 2007-08 global financial crisis. Against this background, the overlaps
– in values, vocabulary, management, and production models – between alternative
artistic practices and late capitalist production paradigms are increasingly evident.
Drawing on materialist feminism, Social Reproduction Theory, and the legacy of
practices and theories associated with the Wages for Housework campaign (1970s),
this thesis aims to re-centre labour within discussions of socially engaged art and to
deepen the critical analysis of the interrelations between social practices and
feminist politics. Working from the suggestion of ‘art's alternative workplaces’, the
analysis reveals that while conventional working and organising patterns are
indeed a primary site of feminist critique and action, these tend to be reiterated
through such projects.
Rather than focus narrowly on artworks, in the study I examine the artistic,
curatorial and organisational processes initiated by feminist collectives and
practitioners, as well as by art workers' advocacy groups, across Europe. I discuss
how these initiatives engage with labour as a site of political prefiguration, tracing
an analytical trajectory that connects feminist artistic practices from the 1970s to the
2010s and beyond. The thesis thus investigates the transgenerational and
transgeographical articulation of demands, figures, and strategies, as well as the
ways in which they might inform extant positions and research paths. Although
Europe constitutes the overarching geographical framework of the research, I
consider the historical and political specificities of different nations to develop a
more nuanced understanding of how these contexts have influenced the evolution
and present form of social practices and their study.
While grounded in historical contextualisation, the thesis refrains from
proposing a feminist canonisation of socially engaged art. Instead, the main goal is
to critically examine how art workers navigate the power and economic structures
that underpin feminist or feminist-informed socially engaged art experiences,
alongside the modes of collaboration and the subjectivities engendered in these
processes. The thesis combines case studies with theoretical analyses and is
organised around three positions – the activist, the artistic, and the curatorial –
which converge in the final section. This structure enables an examination of the
subject at hand from diverse historical and professional perspectives, shedding light
on trends and overlaps. For instance, I discuss the debates and contradictions
surrounding the ‘wage demand’ by art workers' advocacy groups in light of the
WfH campaign, along with the challenges presented by instituting practices in
grassroots self-organising and curatorial-led institutional reconfiguration. The case
studies examined demonstrate a heightened awareness in challenging the potential
ambiguity of ‘social engagement’ by working through contingent material issues
and needs, engaging as possible with extant contradictions and compromises to
materialise such alternatives into shared practices and infrastructures. This
approach, often disenchanted yet committed, frequently stretches beyond the
confines of art to reflect on wider political mobilisations, redirecting energies,
strategies, and demands when the opportunities for counter-hegemonic political
action against capital’s imperative are increasingly restricted and controlled.
By adopting a more expansive framework for the study of socially engaged
art – in terms of theoretical frameworks, methods, subjects and processes
considered – the thesis aims to develop a feminist critique of the forms of labour
and material-social infrastructures underpinning these practices. It also considers
the potentials that such practices continue to offer within the contemporary
European geopolitical context, characterised by significant power and economic
disparities and a highly uneven art scene and infrastructure, along with the rise of
authoritarian liberalism and the progressive weakening and restriction of political
action
Hydrogel based depth standards and phantoms for optical imaging applications
No full textMedical imaging technology is advancing rapidly making disease diagnostics faster,
efficient, and detailed. Currently much effort is focused on designing and fabricating
new NIR laser sources and detectors, devising novel label free imaging
methodologies, which along with applications of machine learning are helping to
optimise imaging at ever greater depths. To aid the development of deeper tissue
optical imaging methodologies and to allow system validation and robust comparison
of imaging methods and techniques, there is a need for the generation of readily
available, robust, and reliable standards and phantoms. Human tissue, although a
natural and most realistic model for this purpose, possesses heterogeneity among
samples, lacks long term stability and is unsuitable for system calibration or
comparison. Alternatively, synthetic phantoms constructed using materials ranging
from solids, semi-solids and liquids, incorporating molecules that respond to different
imaging modalities, can overcome the limitations human tissues.
Here, a new material/construct that can be used in the fabrication of tissue phantoms
is introduced. The material was comprised of a double network hydrogel matrix made
using two interpenetrating polymers: agarose and polyacrylamide. The double network
hydrogel was robust and was used for the fabrication of stable multi-layered depth
phantoms incorporating specific imaging modality markers between the layers. The
generated phantoms ranged from single layers to more complex constructs consisting
of up to seven layers, each layer being variable in depth and tuneable in terms of
scattering and absorbance properties. Once fabricated, the phantoms were found to
be stable for several months.
These phantoms allowed a comparison of imaging depths with different imaging
modalities including conventional one photon fluorescence, two photon fluorescence,
second harmonic generation and coherent anti-Stokes Raman scattering allowing
imaging at depths of 1550 µm, 1550 µm, 1240 µm, and 1240 µm, respectively. These
standards/phantoms also proved useful to understand the light interaction with
biologically relevant material, resulting in the determination of an axial scaling factor
for light microscopy. The ability to image at depth, the phantom’s robustness and their
flexible layered structure and the ready incorporation of “optical markers” make these
ideal depth standards for the validation of a variety of novel imaging modalities
Western Tigray: The Unresolved Challenge and a Test for Ethiopia
Get PDFContests over administrative boundaries and identity-based demands have become a major source of conflict in contemporary Ethiopia, with virtually no regional state unaffected. This paper examines the case of Western Tigray to explore the nature of these disputes, concluding that they are symptoms of a broader national political crisis rather than isolated issues. Ethiopia’s multinational federation, while recognising national identities, risks fuelling reactionary and exclusionary nationalism, exacerbated by rent-seeking political elites. The study argues that constitutional mechanisms, including referenda, cannot resolve these deep-rooted problems. Instead, it proposes an incremental, transformative three-stage process: securing a temporary political settlement and nationwide cessation of hostilities; restoring the constitutional status quo as a foundation for credible, inclusive dialogue; and conducting multi-level national dialogues to address fundamental political challenges. Only through such a comprehensive and collaborative approach can sustainable peace be achieved
Individual variation in chronic and acute parasitism in seabirds
No full textParasitism is ubiquitous in wild populations, with host-parasite interactions forming an integral aspect of ecosystems. Infections with parasites can range from acute to chronic, and lead to sublethal or lethal impacts on hosts. Individual hosts may vary in their exposure, susceptibility, tolerance to parasitism, which can be linked to both intrinsic differences between individuals and extrinsic factors which may vary in both space and time. Seasonal variation in host life histories, such as the timing of breeding, conditions during early life or variation in migratory strategies can vary between components of the host population. This variation may lead to different experiences of extrinsic factors such as resources, exposure to parasites or environmental conditions, culminating in variation in the prevalence and abundance of infection, and its fitness consequences. Investigating the links between individual variation and parasitism is crucial to understanding the impacts of disease on wild populations. As anthropogenic driven environmental change alters host life history patterns, and increases the rate of infectious disease emergence with impacts across species boundaries, such understanding is vital for predicting and mitigating against the impacts of parasitism on wildlife, domestic animal and human health.
In this thesis we investigate how variation in host traits and life history is associated with chronic and acute infections, with a focus on seasonal variation. We focus on an individually marked population of colonially breeding, partially migratory wild seabirds, European shags (Gulosus aristotelis), on the Isle of May in Scotland, a population where life history data is collected throughout life. This population shows extensive variation seasonal life history, both in the timing of breeding, leading to seasonal differences in early life of offspring, and in migration, with some individuals migrating and others remaining resident during the non-breeding season. We investigate the responses to two types of parasites on shag hosts: chronic infections caused by nematode gut parasites and acute infections caused by avian paramyxovirus-1, the causative agent of Newcastle disease.
Firstly, we use 8 years of data on individual nematode parasite burdens to investigate how temporal variation in early life (during the natal year) and breeding conditions impact infection throughout life. We reveal sex differences in the impact of current and early-life conditions on nematode burdens. In breeding adults, female burdens vary according to seasonality in current conditions but early life effects are more important in males. We found seasonal variation in burdens associated with current conditions: later breeding adult females and later hatched young of both sexes had higher burdens than birds from earlier breeding events. For males, we found that those that had hatched later in the season when they were chicks (early life conditions) had lower burdens when they were adults. Second, we therefore considered the importance of early life parasitism and hatching phenology, using a parasite manipulation experiment to investigate trade-offs between parasitism, growth and immunity across the nestling period in chicks. We find that hatch date was associated with differences in immune cell counts, but that these relationships were not mediated by parasitism. Third, we move on from chronic macro-parasite infections to compare the importance of seasonal behaviour and sex in shaping exposure and susceptibility to an acute microparasite infection, for which cormorant species are known to be a reservoir. We use multiple years of antibody data to investigate patterns of avian paramyxovirus-1, in shag chicks and adults. We found evidence of consistent but fluctuating prevalence of antibodies across years in adults, which produced differences in antibody profiles of their offspring, with maternal antibodies detected in recently hatched chicks of positive females. In adults, antibody prevalence was higher in females than males, but did not differ between migrants and residents. Finally, in response to an unprecedented outbreak of another viral pathogen in seabirds, highly pathogenic avian influenza, we develop a minimally invasive, and logistically beneficial method for the detection of viral antibodies in multiple species of seabird. We find it is possible to differentiate antibody positive and negative individuals using cloacal and choanal swabs, but the sensitivity of the technique is low and variable between swab type and species. Further feedback between field collection and laboratory optimisation is required before this technique can provide a useful tool for wildlife disease surveillance.
The findings of this thesis highlight that individual variation in host traits shape host burden and responses to infection across both acute and chronic infections in wild populations. By monitoring individuals across their life time, we find that sex differences, seasonality and early life conditions are key in mediating the relationship of individual hosts with both chronic and acute parasitism. These studies emphasise the importance of long-term population studies for understanding individual level responses to parasitism
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