Action Network

IntroductionIn Philadelphia there are racial disparities in health outcomes during the perinatal period, such that Black infants and their parents experience a disproportionately higher burden of poor outcomes compared to their White counterparts. These excess risks are driven at least in part by high rates of poverty and other manifestations of structural racism. The provision of guaranteed income (GI) or unconditional cash payments during and after pregnancy, is a bold and evidence-based approach to advancing equity in financial security and health. The objective of this protocol paper is to describe the community-centered approach to the design of (a) the Philly Joy Bank (PJB), a perinatal GI program in Philadelphia, and (b) the evaluation of PJB’s impact.MethodsPJB was conceived by an established coalition of community partners through a collective impact model. Decisions related to the design and implementation of PJB are made through a consensus building process that centers the voices of Lived Experience Experts (i.e., Black birthing people in Philadelphia). Congruent with the community-driven design of PJB, the evaluation of the impact of PJB is grounded in the principles of community-based participatory research and is co-designed by the community.ResultsThe study purpose is to assess the feasibility and acceptability of PJB (Aim 1); to examine whether and how GI affects ability to meet basic needs and parental stress (Aim 2); and to explore the impact of PJB on parental mental health and the preliminary impact on infant prematurity (low birthweight and preterm birth) (Aim 3). Descriptive statistics, mixed effects regression analyses, and participatory qualitative analysis approaches will be used to achieve study aims.DiscussionGI is a promising upstream structural intervention to address persistent health inequities during the perinatal period: a critical period of the life course. Understanding if and how GI improves health for birthing people and their infants can inform implementation and policy to advance health equity.

The mainland eastern barred bandicoot (Perameles gunnii) has been the subject of a recovery effort since 1988 due to threats posed by introduced predators and habitat destruction. Despite a concerted effort to recover the species, they came perilously close to extinction in the early 2000s. A change of tactics and securing populations in multiple fox-free safe havens was required to save the species from imminent extinction. Through the release of eastern barred bandicoots onto Phillip and French Islands, made possible by support from the local island communities, the trajectory of eastern barred bandicoots has been reversed. They are now widespread and abundant across both islands, and in 2021 were reclassified from ‘Extinct in the Wild’ to ‘Endangered’ largely due to these island releases. However, this does not mean that the eastern barred bandicoot is secure and no longer requires management. As mainland eastern barred bandicoots only occur within safe havens, which have a history of intermittent incursions and failure, it is essential that sites remain vigilantly monitored and managed to secure the species and the hard-won conservation gains. We document the lengthy process of releasing eastern barred bandicoots onto Victoria’s two largest islands, including assessing suitability, garnering community support and managing uncertainties.

Coastal fisheries are essential to Pacific Island communities, providing vital nutrition, livelihoods, and cultural value, yet microplastic (MP) contamination poses a growing threat to both ecosystem and human health. This study presents a regional assessment of microplastic contamination in coastal fish across four Pacific Island Countries and Territories (Fiji, Tonga, Tuvalu, and Vanuatu), based on the compilation of four methodologically standardized datasets, enabling us to evaluate whether regional patterns of contamination are linked to the ecological traits of fish. A total of 878 fish from 138 species were analysed to reveal widespread ingestion (32.7% prevalence; 0.76 ± 0.05 MPs/individual), with Fiji exhibiting the highest contamination (74.5% frequency). Reef-associated invertivores such as Lethrinus harak showed elevated risks (80% contaminated in Fiji), driven by fiber-dominated particles (65–95%), while ecological traits (benthic feeding, reef habitats) increased exposure compared to nearshore pelagic species. Disparities emerged between nations, with Fiji’s sites exceeding global averages despite remoteness, whereas Vanuatu’s low fish contamination suggests restricted dispersal, successful waste management influences, or differential bioaccumulation pathways. Polypropylene, polyethylene, polyethylene terephthalate, and nylon were the dominant (~11–43%) polymer types across all countries. The findings highlight the essential need to incorporate the Pacific Island data into global pollution assessments to better represent tropical Pacific marine ecosystems. This work establishes a standardized baseline for microplastics in the Pacific coastal fish, providing a framework to guide future research on ecological impacts while highlighting the need to integrate these data into regional and global plastics negotiations. The study underscores the importance of expanding monitoring to underrepresented PICTs to better understand contamination drivers in island ecosystems.

Abstract Precipitation patterns in the northwestern Himalayas have shifted markedly over the past four decades. Using MERRA-2/GEOS reanalysis data (1983–2022) coupled with non-parametric trend analysis, Sen’s slope estimates, and Intensity–Duration–Frequency (IDF) modeling, we document a significant increase in annual and monsoonal rainfall across southern and mid-altitude belts, alongside persistently low but increasingly variable precipitation in high-altitude cold deserts such as Ladakh. The Seasonality Index (0.46–1.26) indicates growing temporal clustering of rainfall, heightening flood and drought exposure. IDF-curves reveal the most severe short-duration extremes in orographically enhanced monsoon catchments, highlighting heightened flash-flood risk, while arid zones face sporadic but impactful extremes. Although reanalysis products can underestimate localized extremes in steep terrain, especially cloudburst-like events, the four-decade consistency of MERRA-2 provides robust regional-scale diagnostics of changing rainfall variability. These findings support region-specific adaptation strategies, including resilient infrastructure design and early-warning systems, for these ecologically sensitive mountain landscapes.

• ML predicts tillage and stubble practices from 22 years of soil data. • Random forest outperforms spatial baseline in predicting farm practices. • Year and latitude are key drivers of no-till and stubble grazing adoption. • Gridded maps reveal national trends in tillage and residue management. • Framework supports GHG accounting modelling and soil health policy development. Tillage and stubble management are key drivers of soil health, crop productivity, and greenhouse gas (GHG) emissions, yet long-term spatially explicit data on these practices remain scarce. Using data from two Australian national soil monitoring programs Soil Carbon Research Project (SCaRP) and Soil Organic Carbon Monitoring (SOC-M) we analyzed over two decades (2001–2023) of tillage and stubble management records collated across 300 Australian farmer paddock scale datasets. We developed machine learning models based on random forest to predict spatial and temporal trends in these practices, incorporating crop type, soil classification, climate variables, and spatial coordinates as predictors. Our models were benchmarked against multinomial logistic regression and a nearest-neighbour baseline, demonstrating that random forest consistently achieved higher accuracy, particularly for dominant practices such as no-tillage and stubble grazing. Variable importance analyses identified “Year” as the most influential predictors, capturing widespread no-tillage adoption post-2010, while latitude and crop type further explained regional variations. Partial dependence plots revealed sharp inflection points in adoption trajectories around 2010, coinciding with major policy and technological shifts. We applied the models to generate gridded predictions (0.5° resolution) across the Australian cropping zone, providing insights into the evolving distribution of tillage and stubble practices. These spatial products not only improve GHG accounting frameworks and Earth system models but also offer actionable intelligence for soil health policy and targeted extension programs. Our approach demonstrates how combining ground-based monitoring with machine learning can fill critical data gaps and provide a scalable framework for agricultural management assessment and climate mitigation strategies.

First described in the 19th century, Marfan syndrome is a rare hereditable genetic disease, mainly caused by mutations in FBN1 leading to connective tissue defects. While the patient phenotype is highly variable, many affected present with tall stature, long and flexible limbs and joints, eye disorders, and life-threatening aortic enlargements. Modern medical treatments can alleviate these symptoms, but it is important for people living with connective tissue disorders to learn about their situation and connect with others facing the same challenges. The Marfan Europe Network (M.E.N.) is an umbrella organization of 14 national Marfan patient organizations, integrating efforts to inform the public and improve the lives of those affected. Here, we interview Tuija Ekegren, Françoise Steinbach, and Margit Aschenbrenner from the Board of Directors of the M.E.N.

Abstract The accurate perception of moving objects is a fundamental challenge for the visual system, which must compensate for neural processing delays. Motion extrapolation is a proposed mechanism whereby the brain predicts an object’s future position. We investigated how an object’s motion history shapes its perceived position using the flash-jump illusion, in which a brief color change in a moving bar is mislocalized as further along the direction of motion. Across two experiments, we found that longer preceding motion sequences improved localization accuracy, consistent with motion adaptation. This effect occurred regardless of whether motion continued after the flash. Notably, mislocalization transiently reappeared as the object crossed the vertical midline, suggesting that motion adaptation and motion extrapolation operate independently between within each hemifield. Manipulating the length of the sequence in each hemifield in Experiment 2 confirmed that this adaptation is spatially confined to each hemifield, with limited interhemispheric transfer. The results align with a Bayesian framework in which the brain integrates signals from both hemispheres, with midline crossings triggering a shift from adapted to unadapted neural populations. We identify motion extrapolation, supported by hemifield-specific adaptation in area MT and integration in area MST, as the mechanism behind these midline discontinuities. This work reframes smooth pursuit not just as a tracking behaviour, but as a functional solution to overcome the inherent limits of interhemispheric motion processing.