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Beyond scents: calling on the fragrance industry to champion plant diversity
No full textSince the Convention on Biological Diversity (1992), international frameworks have emphasized benefit-sharing and private-sector engagement in conservation, a call reinforced by the Kunming–Montreal Global Biodiversity Framework (2022). Yet biodiversity continues to decline, highlighting the need for funding models that effectively link commerce with conservation. Here, we examine how the fragrance industry—a sector deeply dependent on plant diversity and cultural value chains—can contribute more meaningfully to global plant conservation. Drawing on international policy frameworks, published literature, and illustrative conservation–industry partnerships, we assess mechanisms through which fragrance-related initiatives support biodiversity protection, accountability, and culturally grounded conservation narratives. We then examine The Red List Project as a conservation-first model that integrates biodiversity objectives directly into fragranced product development, using scent inspiration rather than wild harvesting. We argue that scaling such approaches could reposition the fragrance industry as an active partner in safeguarding plant diversity, biocultural heritage, and equitable benefit-sharing
Consortium‐Based Patient and Public Involvement and Engagement for Long COVID Research: A Pirit‐Focused Impact Evaluation of the PHOSP‐COVID Study
No full textBackground: At the start of the coronavirus disease‐2019 (COVID‐19) pandemic in early 2020, the long‐term outcomes for survivors of COVID‐19 were unknown. The PHOSP‐COVID cohort study was set up at scale and pace in Spring 2020 to determine the short‐ to long‐term health consequences of COVID‐19 in post‐hospitalisation survivors; to understand the impact of interventions during and after the acute illness on these long‐term sequelae and to build the foundation for multiple in‐depth studies. A consortium infrastructure of hospital trusts, academic partners, industry, patients and charities was created. From the study inception, patients were central to the PHOSP‐COVID consortium, whereby a Patient and Public involvement and Engagement (PPIE) group was convened, including charity groups, people with lived experience recruited through clinical care from NHS sites, and patient support groups through Long Covid Support. Embedding high‐quality, meaningful PPIE within a large consortium brings challenges and benefits. In this article, we describe our experiences of setting up and sustaining the PHOSP‐COVID Consortium PPIE group, including a PIRIT‐focussed evaluation of the impact of our PPIE work and provide top tips for researchers to take forward when embedding PPIE in future consortium research. Methods: This article outlines the set‐up and sustainability of the PHOSP‐COVID study PPIE group, in consultation with the National Institute for Health and Care Research (NIHR) guidance. To evaluate PPIE impact, we used PIRIT (Public Involvement in Research Impact Tool, 2023‐ Cardiff), and we provide our honest reflections of our PPIE work according to the PIRIT planning tool. The results highlight the benefits of a consortium approach to PPIE as well as the challenges, with quotes from PPIE contributors and academics. In addition, we have created top tips for researchers to take forward when embedding PPIE in future consortium research, linked to the NIHR standards. Learning and Reflection: This manuscript has identified gaps in PPIE considerations for the PHOSP‐COVID study and specific challenges around a consortium‐based approach for PPIE. These are largely due to time scale (i.e. the pace of setting up the study within a pandemic) and communication factors (diverse and large numbers of people to include/inform). Through reflection on the challenges and successes experienced in the PHOSP‐COVID consortium PPIE via a PIRIT‐focused impact evaluation, we have developed recommendations to support future good practice. Patient or Public Contribution: Patients and members of the public were involved in all aspects of this work from idea inception, design and conduct of the work, analysis and interpretation of the data. Eight patients prepared the manuscript and are included as co‐authors
Chiral Metal Halide Perovskites for Spin‐Polarized Light‐Emitting Diodes
No full textWith the growing importance of displays, reducing their power consumption has become crucial for developing energy‐efficient photonic–electronic platforms. Conventional light emitting diodes (LEDs) rely on external polarizers and waveplates to control light polarization in displays, but these optics cause at least half of the incident energy of the LEDs to be lost, demanding higher drive currents and accelerating degradation. Generating circularly polarized light (CPL) directly at the source offers a low‐power alternative by eliminating such optical losses and enabling direct spin–photon interfaces. Recently, chiral metal halide perovskites (MHPs) have emerged as efficient, solution‐processable semiconductors that intrinsically couple light polarization and spin. Their strong spin–orbit coupling and broken inversion symmetry enable spin‐selective charge transport via the chiral‐induced spin selectivity effect, allowing both spin manipulation and its impact on emission to be observed within the same layer. In colloidal nanocrystal form they can emit CPL with high photoluminescence quantum yield, making them promising candidates for chiral light emission, although their use is still limited by low polarization anisotropy. This perspective discusses intrinsic and extrinsic routes to achieve circularly polarized electroluminescence (CP‐EL) using chiral MHPs, highlights progress in low‐dimensional films and chiral‐ligand nanocrystals, and discusses prospects for room‐temperature spin control and filter‐free, spin‐LEDs for next‐generation energy‐efficient optoelectronic displays
Structural basis for prostaglandin and drug transport via SLCO2A1
No full textOrganic anion-transporting polypeptide transporters (SLCO/OATPs) function as cellular gatekeepers, regulating intestinal absorption, hepatic and renal clearance, and the tissue distribution of drugs and metabolites in the human body. However, the mechanisms underlying substrate selection within the SLCO superfamily remain unclear, hampering efforts to rationalize the interaction of drugs and metabolites with these transporters. SLCO2A1 (also known as OATP2A1) is responsible for the distribution of eicosanoids, including prostaglandins (PGs) and thromboxanes, throughout the body, in addition to several families of nonsteroidal anti-inflammatory drugs (NSAIDs). Here, we present cryogenic electron microscopy structures of SLCO2A1 bound to endogenous PGs and to four widely prescribed medications for treating inflammation, chronic asthma, and Parkinson’s disease (PD). Complementary molecular dynamics and in vivo cellular assays elucidate the molecular basis for PG and drug recognition. Our study reports essential mechanistic details that underpin substrate selection and subfamily adaptation within the broader SLCO superfamily of drug and metabolite transporters
The influence of phonon symmetry and electronic structure on the electron-phonon coupling momentum dependence in cuprates
No full textThe experimental determination of the magnitude and momentum dependence of electron-phonon coupling (EPC) is an outstanding problem in condensed matter physics. The intensity of phonon peaks in Resonant Inelastic X-ray Scattering (RIXS) spectra can be related to the underlying EPC strength under significant approximations whose validity deserves careful verification. We measured the Cu L3 RIXS phonon intensity as a function of incident photon energy and momentum transfer in several layered cuprates. For CaCuO2, La2−xSrxCuO4+δ, and YBa2Cu3O6, using a generally accepted theoretical model, we quantitatively estimate the EPC for the bond-stretching mode along the high-symmetry directions (ζ,0) and (ζ,ζ), and as a function of the azimuthal angle φ at fixed q∥. We compare our results with theoretical predictions and find that the q∥-dependence of the phonon RIXS intensity can be largely ascribed to the phonon symmetry. However, a more satisfactory prediction of the experimental results requires an accurate description of the electronic structure close to the Fermi level. Our extensive investigation indicates that Cu L3 RIXS can reliably determine the momentum dependence of EPC for the bond-stretching modes of cuprates. Moreover, the large experimental basis provided here constitutes a stringent test for advanced theoretical predictions on the EPC
Multiverse Mechanica: a testbed for learning game mechanics via counterfactual worlds
No full textWe study how generative world models trained on video games can go beyond mere reproduction of gameplay visuals to learning game mechanics—the modular rules that causally govern gameplay. We introduce a formalization of the concept of game mechanics that operationalizes mechanic-learning as a causal counterfactual inference task and uses the causal consistency principle to address the challenge of generating gameplay with world models that do not violate game rules. We present Multiverse Mechanica, a playable video game testbed that implements a set of ground truth game mechanics based on our causal formalism. The game natively emits training data, where each training example is paired with a set of causal DAGs that encode causality, consistency, and counterfactual dependence specific to the mechanic that is in play—these provide additional artifacts that could be leveraged in mechanic-learning experiments. We provide a proofof-concept that demonstrates fine-tuning a pre-trained model that targets mechanic learning. Multiverse Mechanica is a testbed that provides a reproducible, low-cost path for studying and comparing methods that aim to learn game mechanics—not just pixels
High-dose vs standard-dose influenza vaccine in older adults with diabetes: a secondary analysis of the DANFLU-2 Randomized Clinical Trial
No full textImportance: Influenza infection poses a substantial risk of severe complications, particularly in older adults and high-risk populations, such as individuals with diabetes. The high-dose inactivated influenza vaccine (HD-IIV) has demonstrated superior efficacy against influenza infection compared with the standard-dose inactivated influenza vaccine (SD-IIV) among adults 65 years or older. However, there is limited evidence on its effectiveness in preventing severe respiratory and cardiovascular outcomes in individuals with diabetes.
Objective: To investigate the relative vaccine effectiveness (rVE) of HD-IIV vs SD-IIV against severe respiratory and cardiovascular outcomes according to diabetes status and across diabetes subgroups.
Design, Setting, and Participants: This was a prespecified secondary analysis of DANFLU-2, a pragmatic, open-label, individually randomized clinical trial conducted in Denmark during the 2022/2023 to 2024/2025 influenza seasons. Adults 65 years or older were eligible for inclusion regardless of comorbidities. Data were obtained from nationwide health registries and analyzed from June to October 2025.
Interventions: Participants were randomly allocated 1:1 to receive HD-IIV or SD-IIV.
Main Outcomes and Measures: Outcomes included respiratory and cardiovascular hospitalizations. The potential effect modification by diabetes status and across diabetes subgroups was tested.
Results: Among 332 438 participants (mean [SD] age, 73.7 [5.8] years; 161 538 female individuals [48.6%]), 43 881 (13.2%) had diabetes. Overall, HD-IIV compared with SD-IIV was associated with reduced cardiorespiratory hospitalization, cardiovascular hospitalization, and influenza hospitalization. Effect estimates were similar for participants with and without diabetes for cardiorespiratory hospitalization (diabetes: rVE, 7.4%; 95% CI, −2.5% to 16.3%; no diabetes: rVE, 5.3%; 95% CI, 0.4%-10.0%; interaction P = .69), cardiovascular hospitalization (diabetes: rVE, 12.0%; 95% CI, −0.9% to 23.3%; no diabetes: rVE, 6.0%; 95% CI, −0.4% to 12.0%; interaction P = .38), and influenza hospitalization (diabetes: rVE, 41.6%; 95% CI, 5.0%-64.7%, vs no diabetes: rVE, 44.3%; 95% CI, 25.3%-58.7%; interaction P = .87). Duration of diabetes appeared to modify the effect of HD-IIV vs SD-IIV for cardiorespiratory hospitalization, with suggested benefit of HD-IIV in participants with diabetes duration longer than 5 years (rVE, 20.4%; 95% CI, 5.3%-33.1%), but not in those with shorter duration (rVE, −0.4%; 95% CI, −13.8% to 11.5%; interaction P = .03).
Conclusions and Relevance: The trial results suggest that, among adults 65 years or older, HD-IIV provided consistent benefit for cardiorespiratory, cardiovascular, and influenza hospitalizations compared with SD-IIV, regardless of diabetes status.
Trial Registration: ClinicalTrials.gov Identifier: NCT0551717
Generation of T cells with reduced off-target cross-reactivities by engineering co-signalling receptors
No full textAdoptive T cell therapy using T cells engineered with novel T cell receptors (TCRs) targeting tumor-specific peptides is a promising immunotherapy. However, these TCR-T cells can cross-react with off-target peptides, leading to severe autoimmune toxicities. Current efforts focus on identifying TCRs with reduced cross-reactivity. Here, we show that T cell cross-reactivity can be controlled by the co-signalling molecules CD5, CD8, and CD4, without modifying the TCR. We find the largest reduction in cytotoxic T cell cross-reactivity by knocking out CD8 and expressing CD4. Cytotoxic T cells engineered with a CD8-to-CD4 co-receptor switch show reduced cross-reactivity to random and positional scanning peptide libraries, as well as to self-peptides, while maintaining their on-target potency. Therefore, co-receptor switching generates super selective T cells that reduce the risk of lethal off-target cross-reactivity, and offers a universal method to enhance the safety of T cell immunotherapies for any TCR
Self-supervised learning on camera trap footage yields a strong universal face embedder
Get PDFCamera traps are revolutionising wildlife monitoring by capturing vast amounts of visual data; however, the manual identification of individual animals remains a significant bottleneck. This study introduces a fully self-supervised approach to learning robust chimpanzee face embeddings from unlabeled camera-trap footage. Leveraging the DINOv2 framework, we train Vision Transformers on automatically mined face crops, eliminating the need for identity labels. Our method demonstrates strong open-set re-identification performance, surpassing supervised baselines on challenging benchmarks such as Bossou, despite utilising no labelled data during training. This work underscores the potential of selfsupervised learning in biodiversity monitoring and paves the way for scalable, non-invasive population studie
TAIBOM: bringing trustworthiness to AI-enabled systems
Get PDFThe growing integration of open-source software and AIdriven technologies has introduced new layers of complexity into the software supply chain, challenging existing methods for dependency management and system assurance. While Software Bills of Materials (SBOMs) have become critical for enhancing transparency and traceability, current frameworks fall short in capturing the unique characteristics of AI systems — namely, their dynamic, data-driven nature and the loosely coupled dependencies across datasets, models, and software components. These challenges are compounded by fragmented governance structures and the lack of robust tools for ensuring integrity, trust, and compliance in AI-enabled environments. In this paper, we introduce Trusted AI Bill of Materials (TAIBOM) — a novel framework extending SBOM principles to the AI domain. TAIBOM provides (i) a structured dependency model tailored for AI components, (ii) mechanisms for propagating integrity statements across heterogeneous AI pipelines, and (iii) a trust attestation process for verifying component provenance. We demonstrate how TAIBOM supports assurance, security, and compliance across AI workflows, highlighting its advantages over existing standards such as SPDX and CycloneDX. This work lays the foundation for trustworthy and verifiable AI systems through structured software transparency