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Flourish:co-designing a nature-based programme to support people in recovery
No full textInteracting with nature is associated with a range of health benefits, including stabilising blood pressure, reducing the prevalence of depression and anxiety (Stott et al., 2024), and increasing social engagement and cohesion (Hunter et. al. 2019). Research (Berry et. al., 2021) has shown that nature-based activities could be effective for people who misuse substances. Masterton and colleagues (2022) in their realist interview study suggest that one key component that makes greenspace programmes successful for people who misuse substances is providing a recovery or prevention focus. Across Scotland, Dundee has the highest age-standardised and largest in drug misuse death rate (National Records of Scotland 2025). There are many people on Opioid Substitution Therapy and people in recovery can often feel stigmatised by an ‘addict’ label (Donaldson, Radley and Dillon, 2022) and/or feel trapped in treatment (Scott, 2025). Funded by Art and Humanities Research Council, the REALITIES (Researching Evidence-based Alternatives in Living, Imaginative, Traumatised, Integrated, Embodied Systems in health disparities) project led by the University of Edinburgh explores how might we re-imagine health and social care systems to better respond to the needs of the communities who use them. Within five geographic hubs, the Dundee hub consist of practitioners from Ninewells Community Garden, as well as academics from University of Dundee’s School of Dentistry, School of Medicine, and Duncan of Jordanstone College of Art and Design, and University of St Andrew’s School of Psychology and Neuroscience. Our work uses a place-based and design thinking approach to understand how social prescribing pathways play a role in the general health and civic engagement. The Dundee hub seeks to 1) understand the experiences of people who use drugs and who may experience homelessness in relation to health and social care system and explore 2) how might we integrate a community asset into the health and social care system (i.e. social prescribing) and 3) in what ways nature-based activities delivered by Ninewells Community Garden supports people in their recovery. Placing people from the communities and professionals from the healthcare system in the centre of our process, we use a transdisciplinary research approach adopting design and arts led as well as ethnographic and participatory research to answer our research questions and co-create knowledge together. In the paper, we will share how we co-designed with 18 participants from health and social care, third sectors and people with lived experience to design a nature-based activities programme for people in recovery. We discussed timings and durations, types of activities, benefits to stakeholders, and what does ‘good’ look like. Participants recommended the need for structure and consistency but also recognised that flexibility is required in the programme. There were concerns about transport and access and how to mitigate these issues. Consideration around the purpose of activities and the articulation of purpose to those in recovery were highlighted. Additionally, how do we measure success was considered. This program has run twice (summer, autumn), and the findings provide key considerations and learnings for planning, implementing, and evaluating nature-based activities to support people in recovery
Shaking up photochemistry:the future frontiers of mechanophotocatalysis
No full textSolution-state photocatalysis is fundamentally reliant on the use of organic solvents, which are associated with significant safety, sustainability, and implementation challenges for conducting light-driven reactions. Mechanophotocatalysis tantalizingly addresses these issues by significantly reducing the use of reaction solvents, using mechanical mixing to mediate light-driven transformations. In this Outlook, we examine the motivations for combining photocatalysis with mechanochemistry, assess how this nascent methodology has evolved, and speculate on future research directions that should be explored in order for mechanophotocatalysis to emerge as a useful and complementary methodology for conducting photochemical reactions under solvent-minimized conditions
"These cameras are just like the Eye of Sauron":A Sociotechnical Threat Model for AI-Driven Smart Home Devices as Perceived by UK-Based Domestic Workers
No full textThe growing adoption of AI-driven smart home devices has introduced new privacy risks for domestic workers (DWs), who are frequently monitored in employers' homes while also using smart devices in their own households. We conducted semi-structured interviews with 18 UK-based DWs and performed a human-centered threat modeling analysis of their experiences through the lens of Communication Privacy Management (CPM). Our findings extend existing threat models beyond abstract adversaries and single-household contexts by showing how AI analytics, residual data logs, and cross-household data flows shaped the privacy risks faced by participants. In employer-controlled homes, AI-enabled features and opaque, agency-mediated employment arrangements intensified surveillance and constrained participants' ability to negotiate privacy boundaries. In their own homes, participants had greater control as device owners but still faced challenges, including gendered administrative roles, opaque AI functionalities, and uncertainty around data retention. We synthesize these insights into a sociotechnical threat model that identifies DW agencies as institutional adversaries and maps AI-driven privacy risks across interconnected households, and we outline social and practical implications for strengthening DW privacy and agency
Global perspectives on telemedicine-enabled medication for opioid use disorder:practices, priorities, and barriers
No full textIntroduction: Telemedicine (TM) has potential to address the global opioid use disorder treatment gap, yet its uptake, priorities, and barriers have not been mapped internationally.Methods: We conducted a cross-sectional, web-based survey (July to November 2024) of clinicians and clinical leaders via the International Society of Addiction Medicine, World Psychiatric Association, and allied contacts. The questionnaire captured telemedicine facilitated medication for opioid use disorder (TMOUD) practices, priorities, and barriers. Responses were summarised overall and stratified by World Bank country-income group and by current TMOUD availability.Results: Sixty-eight experts from 37 countries, 32% from low/middle-income countries (LMICs), participated. General TM use rose from 57% before COVID-19 to 94% in 2024. TMOUD was available in 26 jurisdictions (38%), more often in high-income than LMIC settings (58% vs 11%). Barriers to prescribing were identified, and few settings reimbursed video and telephone consultations equally. Improving treatment retention (69%), reducing missed appointments (62%), and expanding medications to underserved (60%) or remote (57%) populations as top priorities, yet fewer than 40% reported that TMOUD was currently used to meet those goals. Key barriers were inadequate policy support (60%), lack of professional guidance (63%), restrictive regulation (48%), poor digital infrastructure (broadband 29%; e-prescribing 56%), and limited clinician training (54%); almost every barrier was more common in LMICs.Discussion: TMOUD remains uneven and concentrated in high-income countries. Updated clinical guidance, digital connectivity investment and interoperable e-health systems, and targeted workforce development, particularly in LMICs, are needed to realise TM's potential for equitable and effective treatment of opioid use disorder. This global survey fills a critical knowledge gap by documenting expert perspectives across income settings, offering cross-national evidence to inform equitable expansion of TMOUD worldwide
The diffusion of cooperative and solo bubble net feeding in Canadian Pacific humpback whales
No full textAnimal culture, information and behaviours acquired and shared by social learning are a form of biodiversity with intrinsic and practical value. Cooperative foraging, a mutualistic resource acquisition behaviour observed across diverse taxa, is strongly connected to social networks via behavioural states, cues and often social learning, as it typically involves high interaction rates. Understanding the distribution, diffusion and learning mechanisms of such cooperative behaviours is an important but understudied aspect of nonhuman culture. Bubble net feeding (‘bubble netting’) is a specialized foraging technique practised by certain humpback whale (Megaptera novaeangliae) populations globally. Over 20 years in the northern Canadian Pacific, we observed the diffusion of two forms: cooperative group and independent (or ‘solo’) bubble netting. Network-based diffusion analysis—a tool to test for social learning—finds strong evidence for social learning of bubble netting when the overall social network is used, even after accounting for traits such as site fidelity and sex (10.6 × 103 to 35.4 × 103 times more support for social versus asocial learning; p < 0.0001). A homophily check using pre-acquisition association data returned ambiguous results, likely due to the inherent sociality of this cooperative foraging behaviour. Nonetheless, the rapid diffusion of bubble netting is clearly important for population viability and should inform conservation planning for this threatened population
Genomic analyses in <i>Drosophila </i>do not support the classic allopatric model of speciation
No full textThe allopatric model of speciation has dominated our understanding of speciation biology and biogeography since the Modern Synthesis. It is uncontroversial because reproductive isolation may readily emerge as a by-product of evolutionary divergence during allopatry unopposed by gene flow. Recent genomic studies have found that gene flow between species is common, but whether allopatric speciation is common has rarely been systematically tested across a continuum of closely related species. Here, we fit a range of demographic models of evolutionary divergence to whole-genome sequence data from 93 pairs of Drosophila species to infer speciation histories and levels of post-divergence gene flow. We find that speciation with gene flow is common, even between currently allopatric pairs of species. Estimates of historical gene flow are not predicted by current range overlap. Whilst evidence for secondary contact is generally limited, a few sympatric pairs showed strong support for a secondary contact model. Our analyses suggest that most speciation processes involve some long-term gene flow, perhaps due to repeated cycles of allopatry and contact, without requiring an extensive allopatric phase
Should I stay or should I go – does protein localisation to plasmodesmata depend on targeting signals?
No full textPlasmodesmata (PDs), the cell junctions of plants, are specialized plasma membrane (PM)–endoplasmic reticulum (ER) contact sites structured as nanochannels providing intercellular cytoplasmic and membrane continuity. Given their importance, the identification of structural and functional PD proteins has long been a research aim. Discovering conserved PD localization signals would allow prediction of PD proteins and artificial PD targeting. Proteomic studies have now identified many bona fide PD proteins, and various sequence motifs responsible for PD localization have been characterized. However, no conserved targeting signals have emerged. Here, we ask if a focus on protein PD targeting might be a misleading concept
Modelling follicular growth during ovarian stimulation using agent-based artificial intelligence
No full textContext: Ovarian stimulation is a key step in medically assisted reproduction (MAR), whereby supraphysiological doses of FSH extend the “FSH window” and induce multifollicular growth. However, only limited data exist that examine individual follicular growth rates during fertility treatment.Objective: To model growth rates of individual ovarian follicles during ovarian stimulation in MAR cycles using an agent-based artificial intelligence model.Design: Observational cohort study.Setting: Eleven assisted conception clinics in Europe.Patients: 11 572 patients (2005-2023) who underwent ovarian stimulation during MAR.Intervention: Predictive modeling was conducted using 39 698 scans including 434 082 follicles from 12 950 cycles during ovarian stimulation.Main Outcome Measures: Daily growth rates of individual ovarian follicles during stimulation were modeled to enable prediction of follicle sizes at the end of ovarian stimulation.Results: Mean follicle growth rate of ovarian follicles was 1.350 mm/day (95% CI: 1.346–1.353 mm/day) and was significantly associated with antral follicle count and FSH dose changes (both P < .001). Using only the first scan, the model enabled prediction of follicles sizes within 2 mm at the end of ovarian stimulation with 75.0% accuracy (95% CI: 74.6–75.3%), increasing to 80.1% (95% CI: 79.8–80.5%) when incorporating the first 2 scans. Predictive performance was stable across clinics, with a mean accuracy of 78.0% in a random training-test split, and 77.1% using cross-validation by clinic.Conclusion: We used advanced artificial intelligence techniques to progress our understanding of follicle growth dynamics during ovarian stimulation. This model can reliably predict follicle size profiles at the end of stimulation enabling moderation of the number of scans required
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