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Locus-specific proteomics identifies novel regulators of Epstein-Barr virus lytic reactivation
No full textThe Epstein Barr virus (EBV) is a human gammaherpesvirus which infects over 90% of the global population and is associated with lymphoid and epithelioid cancers. After infection, EBV enters a latent state in B-cells, whereby the viral genome persists as a nuclear episome maintained by expression of a small number of latency-associated viral proteins. The lytic viral proteins, required for DNA replication and virion production, are silenced by cellular epigenetic mechanisms. The immediate-early lytic gene BZLF1 is the most important target for transcriptional repression, as its expression triggers the lytic cascade. To gain insight into the factors restricting BZLF1 expression, we used the PICh method of locus-specific proteomics (Proteomics of Isolated Chromatin segments) to identify proteins which occupy BZLF1 promoter DNA. We identified more than 30 proteins associated with the BZLF1 promoter, including the nucleosome remodeler CHD4 and components of the Polycomb PRC1 complex. We show that CHD4 and PRC1 components are novel repressors of BZLF1 gene expression and that both are required to prevent spontaneous lytic reactivation in Burkitt lymphoma cells. We also reveal a marked, cell-wide loss of the PRC1 histone mark (H2AK119Ub) during the lytic cycle which is dependent on immediate-early and early lytic gene expression. A proteomic analysis of Burkitt lymphoma cells containing lytic EBV identified upregulation of USP17, a de-ubiquitinase capable of H2AK119Ub removal. Taken together, our study demonstrates the power of proteomic approaches to identify repressors o
A Performance-Based Earthquake Fatality Modeling Framework Using Collapse Volume Ratios
No full textConventional earthquake fatality models are commonly implemented using a binary representation of building collapse, an assumption that overlooks severe failure modes and systematically underestimates fatalities. To address this limitation, this study advances the collapse volume ratio—a continuous metric quantifying the reduction of survivable space during collapse—into a probabilistic framework that directly links structural failure to fatality risk. Although previously introduced and quantified in limited studies, we extend its role from a primarily descriptive measure to an analytical component of performance-based earthquake engineering modeling. The framework is designed for versatility, allowing implementation with different levels of data availability, including site-specific collapse observations, collapse fragility functions, or complete-damage fragility functions. Its applicability is demonstrated by leveraging post earthquake data from reinforced concrete moment frame buildings affected by the 2023 Kahramanmaraş earthquakes and through case studies of mid-1970s non-ductile and post- 1997 ductile concrete space-frame archetypes in California. Results show that conventional approaches, constrained by binary collapse assumptions, may under predict fatalities by up to fortyfold at high shaking intensities. In contrast, the proposed framework reproduces observed fatality rates, estimating that under Maximum Considered Earthquake shaking, non-ductile buildings may experience fatality rates of
65%, compared to 11% for ductile buildings. These findings provide quantitative evidence of the life-safety benefits of modern seismic design and highlight the urgent need for retrofit policies addressing older, non-ductile construction
New Route to Battery Grade NaPF6 for Na‐Ion Batteries: Expanding the Accessible Concentration
No full textAbstract Sodium‐ion batteries represent a promising alternative to lithium‐ion systems. However, the rapid growth of sodium‐ion battery technology requires a sustainable and scalable synthetic route to high‐grade sodium hexafluorophosphate. This work demonstrates a new multi‐gram scale synthesis of NaPF 6 in which the reaction of ammonium hexafluorophosphate with sodium metal in THF solvent generates the electrolyte salt with the absence of the impurities that are common in commercial material. The high purity of the electrolyte (absence of insoluble NaF) allows for concentrations up to 3 M to be obtained accurately in binary carbonate battery solvent. Electrochemical characterization shows that the degradation dynamics of sodium metal‐electrolyte interface are different for more concentrated (>2 M) electrolytes, suggesting that the higher concentration regime (above the conventional 1 M concentration) may be beneficial to battery performance
The dynamics of wild and alternative meat consumption across Gabon, Central Africa
No full textAbstract Long‐term overharvesting of wild animals for their meat threatens wildlife and the people dependent on wild animal meat for their diets and incomes. Interventions to reduce wild meat consumption must be built upon a complete understanding of the roles of wild meat and its alternatives within food systems. Here, we conduct a national‐scale analysis of how urbanization, market access and price impact the use of wild and alternative meat and fish in Gabon. We obtained data on the acquisition and consumption of wild and alternative meat and fish for >6900 households from the WILDMEAT database, the largest dataset for Gabon to date. We then analysed associations between settlement size, market access, and price with the probability of consuming wild meat, alternatives, or no meat, and how these foodstuffs were acquired by households. We found the probability of consuming wild meat and no meat to be negatively associated with settlement population size, whereas consumption of alternative meats was more likely in larger settlements. In villages, consumption of both wild and alternative meats became more likely as market access increased. Consumption of all meat types was then negatively associated with price, except traded fish products, which were consumed more in villages at higher prices. Acquiring meat through hunting and fishing was more likely in the most isolated and smallest villages and, as population sizes and market access increased, buying meat became more likely. Our results suggest that more isolated, rural households depend on harvesting wild meat and fish from the environment, alongside a narrow range of traded, tinned fish products, as alternatives to hunting and fishing. Conversely, households in larger settlements and high‐market‐access villages can purchase and consume alternative meats and traded wild meat. Policy Implications : In Gabon, settlements >3500 people, where most wild meat is bought and alternatives are usually available, may suit market‐based and behaviour change interventions. Settlements of 900–3500 people may be effective targets of livelihood support projects. Nutritional analyses should be conducted in settlements <900 people, to understand the conditions under which wild meat is essential to nutritional security. Read the free Plain Language Summary for this article on the Journal blog.
Read the free Plain Language Summary for this article on the Journal blog
‘Three Circles’: Winston Churchill's Approach to International Relations
No full textABSTRACT This article introduces a special issue that explores Winston Churchill's relationship with different countries. As its starting point, this piece takes Churchill's world view that Britain derived her status from its position at the focal point of three intersecting circles: Europe, the British Empire and the wider English‐speaking world. Although there was a fair degree of consistency in his approach, he progressively adjusted his outlook as the comparative size of the three circles changed over the course of his lifetime. His Victorian youth was dominated by the empire, but by the time of his death in 1965, Europe was divided by the Cold War, and the United States, rather than Britain, dominated the English‐speaking circle. The authors argue that modern representations of Churchill's world view have been further complicated by the impact of his own writings and by the debates on his contested legacy over empire and Europe. They conclude that detailed examinations of his approach towards different countries reveal a shifting, nuanced, pragmatic and political picture, with Churchill's views and actions evolving over time in response to Britain's relative position within the wider ‘three circles’ paradigm. In doing so, they introduce the overall premise of this special issue, namely, that exploring Churchill's attitude to a series of specific countries is a way of taking ‘core samples’ that illustrate his world view more generally
Chapter 12 - Assemblage Studies (Digital Supplementary Material to "Kavos and the Special Deposits: The sanctuary on Keros and the origins of Aegean ritual practice: the excavations of 2006–2008. Volume II")
No full textChapter 7 - The Spools (Digital Supplementary Material to "Kavos and the Special Deposits: The sanctuary on Keros and the origins of Aegean ritual practice: the excavations of 2006–2008. Volume II")
No full textCoupling geometric morphometrics and machine learning for mandibular sex estimation in Late Pleistocene and Late Modern populations
No full textAccurate sex estimation is crucial for studying both modern and ancient human populations, yet methods are often limited to well-preserved skeletons. Here, we combine Geometric Morphometrics (GM) and Machine Learning (ML) to assess mandibular sexual dimorphism and classify sex across a wide chronological and geographic range to bracket the potential of this approach. Sixty-seven individuals from the modern, identified Luis Lopes collection (Portugal) and 18 Late Pleistocene individuals from Jebel Sahaba (Sudan) were surface scanned. Anatomical landmark coordinates were extracted and analyzed with GM, and ML models were trained on a subset of the modern sample to predict sex in both the remaining modern individuals and the Late Pleistocene specimens. GM revealed significant sexual dimorphism in all samples, and ML achieved high intrapopulation classification accuracy. However, predictions were less reliable when applied across the temporally and geographically distant Jebel Sahaba population, reflecting interpopulation differences in mandibular size and shape. These results demonstrate that while GM–ML approaches are powerful tools for sex estimation within populations, caution is required when extending models to other populations
Continuous Representations in Machine Learning - With applications to medical imaging and operator learning
No full textMachine learning has led to significant advancements in many areas of our everyday lives, in addition to various fields in science. Machine and particularly deep learning methods have been used for applications such as protein structure prediction, drug discovery, climate modelling and medical imaging. Despite their successes, fundamental challenges remain regarding their theoretical understanding and interpretability, generalisation capabilities particularly in low data regimes, robustness to noise and training in restricted resource settings. Many real-world observations can naturally be described as continuous processes rather than discrete data points -- making their data inherently continuous. Consequently, in recent years, the deep learning research community has increasingly explored continuous representations, which refer to both continuous representations of data and neural networks. They enable resolution independent evaluation, as well as physics-informed and geometry-aware learning.
In this thesis, the implications of continuous representations on open questions in machine learning research are investigated. We explore theoretical understanding, generalisation capabilities, robustness to noise, training in restricted resource settings and learning on arbitrary geometries. We show that continuous representations enable theoretical insights and improve interpretability by leveraging findings from well-established fields like ordinary differential equation theory. Through numerical experiments in the field of operator learning, we demonstrate that continuous representations improve generalisation, particularly in low data regimes, and provide theoretical and numerical insights into adaptive sampling strategies for continuous representations of neural networks. Furthermore, we demonstrate their robustness against noise, making them particularly well-suited for medical imaging, a field often challenged by significant noise levels. While neural networks are becoming increasingly more expressive and their number of parameters increases, their training and inference also becomes more and more challenging due to greater computational and memory costs. Thus, we propose a method to reduce memory and computational requirements during inference without the need to retrain the model. Additionally, owing to the resolution-invariant evaluation capability of continuous representations, we show that continuous representations enable efficient inference across varying resolutions. In the context of learning on irregular domains, we introduce a technique for operator learning on arbitrary geometries. As machine learning advances, continuous representations provide a powerful and flexible framework that addresses fundamental open questions in the field and promises to redefine current boundaries