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Global chemoproteomic profiling of bromodomain inhibitors
No full textBromodomain-containing proteins (BCPs) are epigenetic readers that regulate gene expression and play key roles in many diseases including cancer, making them prime targets for drug discovery. While several high-quality chemical probes and inhibitors have been developed for various bromodomains, mainly BET inhibitors have advanced to clinical trials albeit with limited success due toxicity. Despite the potential of proteome-wide selectivity assessments to reveal mechanisms of action for endogenously expressed BCPs, which often function within large multi-protein complexes, this approach has not been widely adopted.In this thesis, we profiled 17 bromodomain inhibitors using chemoproteomics to map direct and indirect drug-protein interactions across the proteome. Building on extensive optimization efforts, we were able to enrich all chemically accessible human BCPs and demonstrate the co-purification of complex partners as well as unexpected non-bromodomain off-targets. By leveraging our highly characterised selection of affinity probes, we developed a generic bromodomain profiling matrix, termed “bromobeads”, that allows for the profiling of unmodified compounds against a broad array of BCPs in parallel. The matrix composition was optimised to create a suitable assay window and robust detection was achieved with S-Trap-based sample processing combined with DIA LC-MS/MS.Using the bromobeads platform, we characterized 10 clinical BET inhibitors in dose-dependent experiments, determining apparent binding constants and revealing differential behaviour in complex partner binding. To demonstrate the platform’s versatility, we extended our experiments to parasites whose bromodomain proteins are emerging drug targets. Additionally, we utilised our set of bespoke affinity probes to expand the bromodomain chemical biology toolbox by developing NanoBRET tracers and PROTACs. The workflow described herein also enabled us to explore how BRD4 inhibitor target occupancy is affected by cellular perturbations, suggesting our chemoproteomic platform as versatile platform for drug discovery and tool to enhance our understanding of bromodomain inhibitor interactions in cells
Mode locking between helimagnetism and ferromagnetism
Get PDFNon-collinear spin textures, such as spin spirals and skyrmions, exhibit rich emergent physics in their spin dynamics. Nevertheless, the potential to utilize their distinctive spin resonance characteristics for on-chip microwave magnonic applications is rarely explored. Here we demonstrate microwave emission and mode coupling from the resonating spin spiral lattice in a Cu2OSeO3/Pt/NiFe heterostructure. We use time-resolved resonant elastic X-ray scattering to visualize the exact vectorial spin precession modes from the two magnetic species in real time. Our results show that the ferromagnetic NiFe layer dynamically captures the excitation modes of the conical order in helimagnet Cu2OSeO3. The off-resonance NiFe spin precession is phase locked to the helimagnet with a fixed offset, thereby presenting distinct chiral dynamics. This demonstrates that the magnons produced in the process—referred to as helimagnons—can wirelessly transmit spin information at gigahertz frequencies, opening new avenues for on-chip microwave magnonics
Ambient temperature and the variability between neighbouring days impacts in-patient hospitalizations in the United Kingdom
Get PDFAbstract
Background
Acute health effects of temperature extremes and variability in temperate zones has been rarely quantified. We examine the associations of ambient temperature and temperature change between neighbouring days with all-cause and cause-specific hospitalizations.
Methods
Daily hospital admission data were identified through hospital record linkage with UK Biobank, a cohort of half-a-million participants during 2006-2022. Temperature exposure was measured at 1×1 Km
2
spatial resolution based on participants’ residential addresses. We used a time-stratified case-crossover design to examine short-term associations of ambient temperature and change in temperature between neighbouring days with all-cause and cause-specific hospitalizations.
Results
We identify 709,052 warm-season hospitalizations and 676,686 cold-season hospitalizations. During warm season, high temperature cumulated over lag 0-3 days is associated with 9% [odds ratio (OR) = 1.09, 95% confidence interval (CI) = 1.02, 1.16] and 18% (OR = 1.18, 95% CI = 1.05, 1.34) higher odds of hospitalizations for renal disease and heat-related illness, respectively. During cold season, high temperature is associated with 4% (OR = 1.04, 95% CI = 1.01, 1.06) higher odds of overall hospitalizations from any cause, and also for cardiovascular disease (OR = 1.06, 95% CI = 1.02, 1.09), respiratory disease (OR = 1.05, 95% CI = 1.00, 1.11), mental disorders (OR = 1.08, 95% CI = 1.00, 1.16) and heat-related illness (OR = 1.25, 95% CI = 1.05, 1.48). We observe more pronounced associations between ambient temperature and overall hospitalization among subgroups residing in the most deprived neighbourhoods and with the least greenspace coverage during both warm and cold seasons.
Conclusions
Our findings suggest the need for multilevel mitigation and adaptation strategies for strengthening individual and urban resilience to minimize adverse health effects attributable to temperature extremes
Parents’ experiences of their adolescent child’s depression: a qualitative systematic review and meta-synthesis
Get PDFA third of adolescents aged 11 to 19 years report depression symptoms, yet many go undiagnosed or do not receive timely treatment. Those who do seek support often face barriers including stigma and long waiting times, resulting in a significant needs-access gap for adolescents looking to access treatment for depression. Parents play a central role in recognizing adolescents’ symptoms and seeking treatment for them. To deepen the understanding on how to better support parents to support their adolescent child, this meta-synthesis aimed to systematically review qualitative studies on parents’ lived experiences of having an adolescent with depression. A pre-planned systematic search using five databases identified 25 papers meeting full inclusion criteria. Data were extracted and a thematic synthesis was conducted using NVivo, with reporting following PRISMA guidelines. Six themes were generated: (1) How do you know when your adolescent has depression?; (2) Understanding the causes of adolescent depression; (3) Emotional turbulence in parents; (4) Effects on the whole family; (5) Experiences with help-seeking; and (6) Stigma and judgment from others. The findings collectively highlight the need for increased parental involvement in professional treatment provision for adolescent depression, alongside better support for parents’ own wellbeing, and improved access to psychoeducation and parent-directed interventions for adolescents with depression. PROSPERO registration ID CRD42024527144
Carbon–phosphorus exchange rate constrains density–speed trade-off in arbuscular mycorrhizal fungal growth
Get PDFSymbiotic nutrient exchange between arbuscular mycorrhizal (AM) fungi and their host plants varies widely depending on their physical, chemical, and biological environment. Yet dissecting this context dependency remains challenging because we lack methods for tracking nutrients such as carbon (C) and phosphorus (P). Here, we developed an approach to quantitatively estimate C and P fluxes in the AM symbiosis from comprehensive network morphology quantification, achieved by robotic imaging and machine learning based on roughly 100 million hyphal shape measurements. We found that rates of C transfer from the plant and P transfer from the fungus were, on average, related proportionally to one another. This ratio was nearly invariant across AM fungal strains despite contrasting growth phenotypes but was strongly affected by plant host genotype. Fungal phenotype distributions were bounded by a Pareto front with a shape favoring specialization in an exploration–exploitation trade-off. This means AM fungi can be fast range expanders or fast resource extractors, but not both. Manipulating the C/P exchange rate by swapping the plant host genotype shifted this Pareto front, indicating that the exchange rate constrains possible AM fungal growth strategies. We show by mathematical modeling how AM fungal growth at fixed exchange rate leads to qualitatively different symbiotic outcomes depending on fungal traits and nutrient availability
Quantum computing fundamentals with mixed qubit types in 137Ba+
Get PDFTrapped-ion systems are leading candidates for quantum computing, offering long coherence times and high-fidelity gate operations. Scaling them, however, requires advanced capabilities such as mid-circuit measurement, qubit reset, and cooling, which together enable quantum error correction. One approach is the use of mixed qubit types, for example employing different ion species for cooling and computation. Recently, the omg blueprint [1] has gained attention as a method for coherently converting between qubit types within a single ion species, removing the overhead of mixed-species architectures while retaining their flexibility.In this thesis, we realise mixed qubit types in 137Ba+ using optical and metastable qubits. We demonstrate coherent control of both, as well as their coherent interconversion, achieving error rates at the 10−4 level suitable for NISQ applications. To enable selective control in multi-ion chains, we integrate a novel photonic chip for individual addressing of Raman beams [2]. We achieve cross-talk levels at or below 10−3 across all zones, and as low as 10−5 in some cases, establishing the scalability of our approach.Building on this, we present a new protocol for heralded state preparation and measurement (SPAM) [3]. This approach combines high-fidelity measurement with coherent conversion between qubit types to mitigate errors associated with qubit loss, decay, and imperfect SPAM. We demonstrate record-low SPAM error rates across optical, metastable, and ground-state qubits, with a minimum of 5(4)×10−6. This protocol can be integrated with erasure conversion techniques to enable in-sequence qubit loss correction, providing a pathway to scalable error correction even with finite qubit lifetimes.Finally, we introduce two-qubit operations through an implementation of the optical-transition dipole force (OTDF) gate [4]. This is the first implementation of the OTDF gate in 137Ba+, or in any ion with hyperfine structure, and it is directly compatible with our existing 532 nm laser system. Crucially, this gate operates in the σZ basis, avoiding the need for phase coherence between the driving field and the qubit, making it an excellent candidate for use in mixed-qubit-type systems.These results demonstrate the application of mixed-qubit-type architectures within a single ion species and establish a foundation for scaling trapped-ion quantum computers
LLM-EmBEditor: universal base editing efficiency prediction via large language model embeddings
Get PDFBase editing efficiency varies dramatically across experiments, creating critical bottlenecks for therapeutic applications. While current specialized computational models achieve good performance on individual base editor types, they require extensive feature engineering, custom architectures, and editor-specific optimization that limit practical applicability across diverse base editing systems. We introduce LLM-EmBEditor, a holistic base editing efficiency rate prediction model that leverages Large Language Models (LLMs). By encoding base editing features as comma-separated key-value strings, our method extracts rich contextual embeddings and trains lightweight regression heads, eliminating both specialized architectures and manual feature engineering while seamlessly integrating sequence and numerical features through natural language formatting. To our knowledge, our model, LLM-EmBEditor, is the first to successfully leverage mixed base editor datasets, enabling effective transfer learning across different base editor types (ABE and CBE), while existing models are limited to a single editor type. This cross-editor generalization capability allows LLM-EmBEditor to achieve strong performance, outperforming traditional benchmarks by 13.5% in Pearson’s R and 18.8% in Spearman’s on the ABE combined dataset (Pearson’s = 0.717, Spearman’s = 0.797 vs. = 0.632, = 0.671 for FORECasT-BE) and achieving competitive performance on the CBE combined dataset ( = 0.662, = 0.689 vs. = 0.739, = 0.816 for igRNA-ABE), while uniquely providing predictions across all editor types with = 0.705, = 0.775, and 2 = 0.496. Our ablation study confirms the robustness of our approach across multiple model components, such as transformer architecture, pooling strategy, and model size
Changes in the Metabolome of Different Tissues in Response to Streptozotocin Diabetes and Mildronate Exposure: A Metabolomic Assessment
Get PDFBackground: Uncontrolled diabetes is characterised by a loss of blood glucose control and increased oxidation of fatty acids to produce ATP. Use of metabolic inhibitors to blunt fatty acid oxidation and restore glucose metabolism is a poorly studied intervention for diabetes. Methods: Steptozotocin-induced diabetes was developed in Wistar male rats. A subset was supplemented with mildronate (100 mg/kg-14 days). Exploiting liquid chromatography-mass spectrometry for workflows including ion exchange-, C18-reverse phase- and HILIC-based chromatography methods, metabolite levels were quantified in plasma liver and brain tissue. Using both untargeted and targeted metabolomic analysis changes to the global tissue metabolome and individual metabolic pathways were estimated. Results: We document that an inhibitor of carnitine synthesis, mildronate, decreased plasma (50% p < 0.01) carnitine abundance and decreased plasma glucose concentration by one-third compared to streptozotocin (STZ)-treated rats (p < 0.001). Targeted metabolomic analysis of the liver showed decreased alpha-ketoglutarate abundance (35% p < 0.05) by STZ diabetes that was further decreased following mildronate treatment (50% p < 0.05). For both beta-hydroxybutyrate and succinate levels, STZ diabetes increased hepatic abundance by 50% (p < 0.05 for both), which was restored to control levels by mildronate (p < 0.05 for both). In contrast, brain TCA intermediate abundances were unaffected by either STZ diabetes or mildronate (NS for all). STZ diabetes also decreased abundance of pentose phosphate pathway (PPP) metabolites in the liver (glucose-6-phosphate, 6-phosphogluconolactone, 6-phosphogluconate 50% for all; p < 0.05), which was not restored by mildronate treatment. However, brain PPP metabolite abundance was unchanged by STZ diabetes or mildronate (NS for all). However, mildronate treatment did not affect the increased abundance of brain sorbitol, sorbitol-6-phosphate and glucose-6-phosphate as a result of STZ diabetes. Conclusions: Together, these observations highlight the potential role that metabolic inhibitors, like mildronate, may play in restoring blood glucose for diabetic patients, without a direct effect of tissues that represent obligate consumers of glucose (e.g., brain) whilst manipulating fat oxidation in tissues such as the liver
The Gut–Extracellular Vesicle–Mitochondria Axis in Reproductive Aging: Antioxidant and Anti-Senescence Mechanisms
Get PDFCellular senescence, mitochondrial dysfunction, and cumulative oxidative stress (OS) are the main causes of the progressive decreases in oocyte and sperm quality that define reproductive age. There is growing evidence that these processes are controlled by systemic variables, such as metabolites produced from the gut microbiome and extracellular vesicle (EV)-mediated intercellular communication, rather than being exclusively regulated at the tissue level. Antioxidant enzymes, regulatory microRNAs, and bioactive lipids that regulate mitochondrial redox balance, mitophagy, and inflammatory signaling are transported by EVs derived from reproductive organs, stem cells, immune cells, and the gut microbiota. Concurrently, microbiome-derived metabolites such as urolithin A, short-chain fatty acids, and polyphenol derivatives enhance mitochondrial quality control, activate antioxidant pathways, and suppress senescence-associated secretory phenotypes. This narrative review integrates the most recent research on the relationship between redox homeostasis, mitochondrial function, gut microbiota activity, and EV signaling in the context of male and female reproductive aging. We propose an emerging gut–EV–mitochondria axis as a unified framework through which systemic metabolic and antioxidant signals affect gamete competence, reproductive tissue function, and fertility longevity. Finally, we discuss therapeutic implications, including microbiome modulation, EV-based interventions, and senotherapeutic strategies, highlighting key knowledge gaps and future research directions necessary for clinical translation
Modern Coral Taxonomy Requires Reproducible Data Alongside Field Observations—Comments on Veron et al. (2025)
Get PDFThe recent review by Veron et al. (2025) posits that quantitative genomic evidence used to understand coral evolution should be secondary to species hypotheses derived from expert opinion based on field experience. The authors argue that morphological “biological entities” should take precedence over molecular evidence when conflicts arise. This perspective required the rejection of extensive, independent molecular datasets that have progressively converged on a robust evolutionary framework for reef corals. Here, we reaffirm how prioritising subjective visual assessments over quantitative genetic and genomic data is methodologically unsound and scientifically regressive. We reject the framing of this perspective as “morphology versus molecules”. Rather, it is a fundamental divergence between two opposing philosophies: a static system anchored in non-reproducible expert judgement, and an integrative framework where genetic data provide the necessary independent test of morphological hypotheses. We show how a reliance on “field entities” obscures true morphological patterns by failing to distinguish between phenotypic plasticity, convergence, and evolutionary divergence. Effective taxonomy requires species hypotheses to be testable, and to stand or fall on the strength of reproducible evidence. Such a framework does not replace morphology; it validates it by providing an explicit, testable basis for evaluating morphological hypotheses. The integration of testable, reproducible molecular analysis with other lines of evidence including morphology is the benchmark of modern taxonomy across all Kingdoms of Life. We address the logical inconsistencies in the general arguments put forward by Veron et al. (2025) and refute their specific rejection of recent Acropora species-level revision with reproducible data