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Toward multisensory digital interfaces
No full textThe integration of haptic sensing and feedback into digital interfaces presents an opportunity to enhance human-machine interactions by enabling users to engage with digital content through touch. This thesis addresses the design of compact, efficient, and user-friendly haptic systems capable of capturing and rendering tactile information. The first contribution identifies haptic features in bare-finger interactions (force, vibration, and friction) using a multimodal dataset of synchronised force, vibration, auditory, and visual signals collected during fingertip exploration of textured surfaces. Unlike previous tool-mediated studies, this dataset links physical measurements with perceptual evaluations, revealing complementary roles of modalities in texture classification. Friction-induced vibrations recorded on the nail and phalanx highlight the finger's mechanical role in encoding tactile information, consistent with recent neuromechanical models of the skin. To experimentally evaluate such models, a modular, multimodal, and multinodal electronic skin (e-skin) was developed using accessible components and straightforward fabrication techniques, including 3D printing and silicone moulding. Mounted on a robotic arm, the e-skin captured normal and shear forces as well as friction-induced vibrations during 6D interactions with deformable objects. Results show that combining its signals with computational models enables extraction of invariant object parameters from noisy sensor data, establishing the e-skin as an accessible bioinspired platform for studying haptic encoding. Beyond sensing, the thesis explores feedback rendering with lightweight, unobtrusive devices: DeepScreen, an actuated touchscreen providing controllable normal-force feedback, and NaptX, a nail-mounted device delivering tactile cues without interfering with fingertip use. Both preserve natural interaction while enhancing tactile realism. User studies demonstrate their effectiveness and reveal perceptual ambiguities between nail- and fingertip-based stimulation, suggesting potential for exploiting haptic illusions to simplify rendering systems. Finally, a haptic selector integrates these technologies to enable texture-based search and retrieval within digital interfaces, demonstrating applications in e-commerce, training, and teleoperation.Open Acces
Investigating the germinal centre biology of an authentic Epstein-Barr virus strain
No full textEpstein-Barr virus (EBV) is a gamma-herpesvirus that infects most of the human population. Although most EBV infection cases are asymptomatic, they are associated with different cancers and autoimmune diseases.
As a herpesvirus, EBV switches between lytic and latent states. The most widely accepted hypothesis of EBV latency establishment (suggested by Thorley-Lawson’s lab) is that viruses exploit the mechanism of the germinal centre (GC) reaction, so the EBV-infected B cells are differentiated into latent memory B cells with plasma cell differentiation, allowing lytic reactivation. In addition, a recent single-cell RNA sequencing experiment showed that EBV-positive lymphoblastoid cell lines (LCLs) exhibited heterogeneity, with some cells showing a germinal centre reaction phenotype.
Both cancer- and lab-adapted EBV strains are widely used as models of EBV. However, these EBVs have mutations and do not exhibit the natural biology of EBV. Thus, a new authentic EBV strain helps determine the true biology of EBV-infected B cells.
To study the germinal centre biology of EBV-infected B cells, a cloning strategy was developed to capture the EBV genome from the lymphoblastoid cell line BM209-2. Then, the BM209-2 virus was characterised: this reportedly Kenya-derived EBV strain was similar to East-Asian EBVs. B cells infected with BM209-2, unlike the common lab EBV strain B95-8, predominantly differentiated into antibody-secreting cells, whereas the transformation of naïve B cells was inefficient. Finally, flow cytometry was used to study the heterogeneity of EBV-infected B cells at the early stage of infection and LCLs. These analyses showed that: (a) Naïve and memory B cells had distinct EBV-driven differentiation pathways. (b) EBV-infected B cells exhibited a GC phenotype. (c) The latent protein EBNA3B was essential for the GC phenotype of infected B cells. (d) The Ig isotypes on B cells changed after EBV infection. (f) EBV infection inhibited the transport of BCRs to cell membranes.Open Acces
Health insurance coverage in Mexico: progress, inequalities and remaining challenges towards UHC2030
No full textBackground
Universal health coverage (UHC) requires strong institutional capacity, equity-oriented policies, sustained political and financial commitment and public trust. However, public confidence in many health systems, including Mexico’s, has been chronically undermined. This study aims to document Mexico’s health coverage trajectory by offering a comprehensive, disaggregated and longitudinal assessment of insurance coverage from 2000 to 2023 – highlighting both achievements and setbacks in the context of UHC2030 goals.
Methods
This study used nationally representative data from Mexico’s National Household Income and Expenditure Survey (ENIGH) from 2000 to 2022, with projections for 2023. Households were classified into mutually exclusive health insurance categories on the basis of institutional affiliation. National and subnational trends in coverage were analysed, with attention to major reforms and disruptions. A distance-to-frontier metric quantified the gap between 2023 coverage and each state’s historical maximum, enabling assessment of progress toward UHC goals.
Results
Between 2000 and 2015, Mexico reduced the uninsured population from 55% to 6.2%, largely driven by Seguro Popular (SP) expansion benefiting Indigenous peoples, rural and low-income households in high-deprivation states. Following SP’s dismantling in 2019, the launch of Health Institute for Welfare (INSABI), and the COVID-19 pandemic, uninsured rates rose sharply to 29.1% by 2023. The greatest losses in coverage occurred in southern states and among marginalized groups, deepening territorial and social inequalities. The decline in mixed public coverage further reflects system fragmentation and eroding public trust. The distance-to-frontier analysis revealed that several states need to more than double their coverage to regain previous levels.
Conclusions
Mexico’s experience highlights that health coverage gains are reversible without strong institutional foundations, political consensus and social legitimacy. Rebuilding and sustaining UHC requires deliberate efforts to address structural inequalities, strengthen institutions and restore public trust. For other low- and middle-income countries, this case emphasizes the urgent need for institutions restructured to foster adaptive capacity alongside equity-focused strategies to achieve and sustain UHC
Evolution of grain boundary distributions in MG2SIO4 with temperature and water content
No full textOlivine is one of the most geologically significant minerals, constituting at least 60 volume % of the upper mantle. As the only fully interconnected phase, it’s physical and electrical properties have a profound influence on mantle rheology, seismological observations, and conductivity measurements used to understand the dynamics of the deep Earth. Rocks are aggregates of minerals, connected by grain and phase boundaries. Many of the properties of interest: rheology, strength, and conductivity, are all affected by the presence of these boundaries. The diverse conditions and assemblages within the deep Earth give rise to a variety of observed behaviours governed by complex mechanisms and reconciling these observations is an ongoing challenge for the field.
Grain boundaries can exhibit phase-like behaviour, with the most stable (lowest energy) structure varying with a range of thermodynamic variables. In ceramic and metal systems, complexion transitions have been observed and linked to changes in macroscopic materials properties.
This work examines changes in the grain boundary populations of the magnesium end-member of olivine, Mg2SiO4 (forsterite), with varying temperature and water content, using stereological methods and electron backscatter diffraction (EBSD). By analysing the relative areas of grain boundaries with different interfacial characters, a temperature-dependent change in the most stable boundary is identified, indicative of a complexion transition. Validation of these results is achieved using multiple indexing methods for EBSD data and transmission electron microscope-based orientation mapping. Additionally, the introduction of hydrogen via water is shown to alter the grain boundary population, highlighting another potential mechanism of water-weakening influencing the strength of the upper mantle. In addition to olivine, the grain boundary population in a compositionally-complex perovskite oxide with hydrogen transport properties is also evaluated. This behaviour is believed to be associated with grain boundary processes and demonstrates the applicability of this analysis to engineering materials.Open Acces
Structure and energetics of magnetic reconnection using machine learning
No full textMagnetic reconnection is a fundamental process in plasmas that enables magnetic energy to be rapidly converted into particle energy. It governs dynamics across scales, from Earth’s magnetosphere to astrophysical systems and laboratory plasmas, yet many aspects of its structure and energetics remain poorly constrained. This thesis addresses five outstanding problems: how to identify key spatial regions of reconnection, how energy is partitioned across these regions, what particle velocity distribution functions (VDFs) reveal about local kinetic physics, whether consistent patterns emerge across events, and what these findings imply for reconnection in other environments.
Using statistical surveys of Magnetospheric Multiscale (MMS) data, established trends in energy conversion are confirmed, with ion enthalpy flux dominating in outflows and Poynting flux concentrated in separatrices, while highlighting the limitations of proxy-based classification. To overcome these, scalable machine learning methods are used: k-means clustering to identify inflows, outflows, and separatrices in particle-in-cell simulations, and recurrent neural networks to map these regions onto MMS time series. This provides reproducible classifications and enables direct simulation to observation comparison.
Particle energisation is further investigated by applying density-based clustering to ion VDFs, revealing multiple populations whose contributions substantially increase bulk kinetic energy density, particularly in outflows. This demonstrates the importance of population-resolved analysis for understanding energisation pathways. Simulation studies show that guide fields alter energy transport by enhancing Poynting flux while reducing cross-tail particle fluxes, with implications for solar and astrophysical plasmas. Finally, the extension of these results to planetary magnetospheres, the solar corona, relativistic astrophysical environments, and laboratory plasmas is discussed, where reconnection plays a key role in energy release and transport.
Overall, this thesis demonstrates that combining spacecraft observations, simulations, and machine learning provides new insight into the spatial structure, energy partition, and kinetic physics of magnetic reconnection, and establishes scalable methods applicable across plasma environments.Open Acces
Recognition of Loss & Damage from wildfires is key for climate justice
No full textWildfires are becoming one of the defining climate-related crises of the twenty-first century. We argue that their inclusion in the Loss & Damage framework of the United Nations Framework Convention on Climate Change is essential to support prevention, recovery and justice for the most affected communities
Integrating functional diversity into the global conservation agenda
No full textBiodiversity is declining at an unprecedented rate, driven largely by anthropogenic pressures. This thesis explores the multifaceted nature of biodiversity, focusing on phylogenetic diversity (PD) and functional diversity (FD), to provide insights into the current and future state of global biodiversity. Using comprehensive datasets on sharks, rays, and birds, I examine the relationship between PD and FD, revealing that these facets often diverge, particularly when decoupled from species richness, and are therefore complementary rather than interchangeable. Building on these findings, I develop the FuDGE framework to prioritise species for conservation based on their functional distinctiveness and extinction risk. This framework incorporates intraspecific trait variation, future trait space predictions, and uncertainties in extinction risk, providing a robust tool for identifying species whose loss would result in irreplaceable functional deficits. Applying this framework to sharks highlights 76 species with high functional distinctiveness that are threatened with extinction, offering actionable priorities for conservation efforts. Finally, I introduce a probabilistic approach to quantify expected FD losses under current extinction trajectories. By simulating potential erosion of trait space, I identify vulnerable ecological strategies and regions at heightened risk. This research underscores the urgency of protecting species that contribute disproportionately to FD, especially in marine ecosystems where overexploitation and climate change are accelerating biodiversity loss. The findings presented in this thesis highlight the need to move beyond taxonomic measures to capture the full breadth of biodiversity. By integrating PD and FD metrics, and by prioritising functionally irreplaceable species, this work aims to provide critical tools to inform policy and enhance global conservation strategies. These advances will offer new insights into the global decline of FD and safeguarding ecological strategies essential for human well-being.Open Acces
Bioengineered scaffolds as a tool to decode the complexity of cancer cell interactions in vivo
No full textFollowing primary tumour removal, many cancer types undergo delayed relapse at distant sites, and this represents the leading cause of cancer related death. It is now apparent that cancer cells not only change their local tissue environment, but also the primary tumour can perturb distant tissues creating a more permissive environment for disseminating cancer cells. Towards a deeper understanding of metastatic growth, we set out to create an artificial system that would allow us to manipulate and dissect key aspects of cancer cell interactions in vivo. Here we successfully engineer an implantable biomaterial scaffold, with defined physicochemical properties. This scaffold integrates with the host to create a biocompatible microenvironment in vivo, incorporating stromal cells, endothelial cells, and immune cells, with macrophages as the predominant infiltrating population. In the presence of a primary fat pad tumour, our scaffold achieves to attract and capture spontaneously disseminated tumour cells from the circulation, which subsequently alter the surrounding cellular composition of the scaffold, by increasing the level of non-immune cells. Leveraging the full functionality of the scaffolds, we show that increasing the stiffness of the scaffold or functionalisation of the scaffold with the pro-angiogenic factor VEGF leads to a difference in their cellular infiltrate and subsequent increased cancer cell seeding. Collectively, this tool allows us to modify specific parameters of the disseminating cancer cell niche revealing this way their contribution to different aspects of cancer cell growth.Open Acces
Decidual macrophages as therapeutic targets in preterm labour
No full textThe initiation of labour in humans remains poorly understood, although there is mounting evidence for a role for decidual macrophages. These may trigger labour by promoting a proinflammatory state, thereby modulating progesterone signalling and weakening fetal membranes. Preclinical work targeting macrophages therapeutically shows promise in preventing preterm labour, underscoring their significance in this process
Heavy chain deposition disease in monoclonal gammopathy of renal significance: a prodrome of multiple myeloma case and literature review
No full textMonoclonal immunoglobulin deposition disease (MIDD) is a complication of plasma cell dyscrasias, resulting in abnormal immunoglobulin deposition along basement membranes. We describe a case of a 60-year-old male with a complex hospital admission, presenting with critical illness accompanied by acute kidney injury, nephrotic syndrome and moderately elevated serum free light chain (SFLC) ratio, on a background of well-controlled diabetes, hypertension and chronic kidney disease. There was no clear aetiology for his presentation following preliminary examination and investigations, which led to a biopsy diagnosis of heavy chain deposition disease (HCDD) in the context of monoclonal gammopathy of renal significance (MGRS). We explore the importance of understanding the disease course to allow timely biopsy diagnosis and treatment initiation. Our patient required very close follow-up and a wide multi-disciplinary approach, including haematologists, nephrologists and histopathologists, to guide management in a disease for which therapeutic strategies are poorly defined due to limited clinical trial data