Non-Fungible Tokens for Organoids: Decentralized Biobanking to Empower Patients in Biospecimen Research.

Introduction: Scientists use donated biospecimens to create organoids, which are miniature copies of patient tumors that are revolutionizing precision medicine and drug discovery. However, biobanking platforms remove donor identifiers to protect privacy, precluding patients from benefiting from their contributions or sharing information that may be relevant to research outcomes. Decentralized biobanking (de-bi) leverages blockchain technology to empower patient engagement in biospecimen research. We describe the creation of the first de-bi prototype for an organoid biobanking use case. Methods: We designed and developed a proof-of-concept non-fungible tokens (NFTs) framework for an organoid research network of patients, physicians, and scientists within a synthetic dataset modeled on a real-world breast cancer organoid ecosystem. Our implementation deployed multiple smart contracts on Ethereum test networks, minting NFTs representing each stakeholder, biospecimen, and organoid. The system architecture was designed to be composable with established biobanking programs. Results: Our de-bi prototype demonstrated how NFTs representing patients, physicians, scientists, and organoids may be united in a privacy-preserving platform that builds upon relationships and transactions of existing biobank research networks. The mobile application simulated key features, enabling patients to track their biospecimens, view organoid images and research updates from scientists, and allow physicians to participate in peer-to-peer communications with basic scientists and patients alike, all while ensuring compliance with de-identification requirements. Discussion: We demonstrate proof-of-concept for a web3 platform engaging patients, physicians, and scientists in a dynamic research community, unlocking value for a model organoid ecosystem. This initial prototype is a critical first step for advancing paradigm-shifting de-bi technology that provides unprecedented transparency and suggests new standards for equity and inclusion in biobanking. Further research must address feasibility and acceptability considering the ethical, legal, economic, and technical complexities of organoid research and clinical translation.

Farmland biodiversity monitoring through citizen science: A review of existing approaches and future opportunities.

Biodiversity monitoring in agricultural landscapes is important for assessing the effects of both land use change and activities that influence farmland biodiversity. Despite a considerable increase in citizen science approaches to biodiversity monitoring in recent decades, their potential in farmland-specific contexts has not been systematically examined. This paper therefore provides a comprehensive review of existing citizen science approaches involving biodiversity monitoring on farmland. Using three complementary methods, we identify a range of programmes at least partially covering farmland. From these, we develop a typology of eight programme types, reflecting distinctions in types of data collected and nature of volunteer involvement, and highlight their respective strengths and limitations. While all eight types can make substantial contributions to farmland biodiversity monitoring, there is considerable scope for their further development-particularly through increased engagement of farmers, for whom receiving feedback on the effects of their own practices could help facilitate adaptive management.

AgroEcoList 1.0: A checklist to improve reporting standards in ecological research in agriculture.

Many publications lack sufficient background information (e.g. location) to be interpreted, replicated, or reused for synthesis. This impedes scientific progress and the application of science to practice. Reporting guidelines (e.g. checklists) improve reporting standards. They have been widely taken up in the medical sciences, but not in ecological and agricultural research. Here, we use a community-centred approach to develop a reporting checklist (AgroEcoList 1.0) through surveys and workshops with 23 experts and the wider agroecological community. To put AgroEcoList in context, we also assessed the agroecological community's perception of reporting standards in agroecology. A total of 345 researchers, reviewers, and editors, responded to our survey. Although only 32% of respondents had prior knowledge of reporting guidelines, 76% of those that had said guidelines improved reporting standards. Overall, respondents agreed on the need of AgroEcolist 1.0; only 24% of respondents had used reporting guidelines before, but 78% indicated they would use AgroEcoList 1.0. We updated AgroecoList 1.0 based on respondents' feedback and user-testing. AgroecoList 1.0 consists of 42 variables in seven groups: experimental/sampling set-up, study site, soil, livestock management, crop and grassland management, outputs, and finances. It is presented here, and is also available on github (https://github.com/AgroecoList/Agroecolist). AgroEcoList 1.0 can serve as a guide for authors, reviewers, and editors to improve reporting standards in agricultural ecology. Our community-centred approach is a replicable method that could be adapted to develop reporting checklists in other fields. Reporting guidelines such as AgroEcoList can improve reporting standards and therefore the application of research to practice, and we recommend that they are adopted more widely in agriculture and ecology.

'Small Data' for big insights in ecology.

Big Data science has significantly furthered our understanding of complex systems by harnessing large volumes of data, generated at high velocity and in great variety. However, there is a risk that Big Data collection is prioritised to the detriment of 'Small Data' (data with few observations). This poses a particular risk to ecology where Small Data abounds. Machine learning experts are increasingly looking to Small Data to drive the next generation of innovation, leading to development in methods for Small Data such as transfer learning, knowledge graphs, and synthetic data. Meanwhile, meta-analysis and causal reasoning approaches are evolving to provide new insights from Small Data. These advances should add value to high-quality Small Data catalysing future insights for ecology.

Grand challenges in entomology: Priorities for action in the coming decades.

Entomology is key to understanding terrestrial and freshwater ecosystems at a time of unprecedented anthropogenic environmental change and offers substantial untapped potential to benefit humanity in a variety of ways, from improving agricultural practices to managing vector-borne diseases and inspiring technological advances.We identified high priority challenges for entomology using an inclusive, open, and democratic four-stage prioritisation approach, conducted among the membership and affiliates (hereafter 'members') of the UK-based Royal Entomological Society (RES).A list of 710 challenges was gathered from 189 RES members. Thematic analysis was used to group suggestions, followed by an online vote to determine initial priorities, which were subsequently ranked during an online workshop involving 37 participants.The outcome was a set of 61 priority challenges within four groupings of related themes: (i) 'Fundamental Research' (themes: Taxonomy, 'Blue Skies' [defined as research ideas without immediate practical application], Methods and Techniques); (ii) 'Anthropogenic Impacts and Conservation' (themes: Anthropogenic Impacts, Conservation Options); (iii) 'Uses, Ecosystem Services and Disservices' (themes: Ecosystem Benefits, Technology and Resources [use of insects as a resource, or as inspiration], Pests); (iv) 'Collaboration, Engagement and Training' (themes: Knowledge Access, Training and Collaboration, Societal Engagement).Priority challenges encompass research questions, funding objectives, new technologies, and priorities for outreach and engagement. Examples include training taxonomists, establishing a global network of insect monitoring sites, understanding the extent of insect declines, exploring roles of cultivated insects in food supply chains, and connecting professional with amateur entomologists. Responses to different challenges could be led by amateur and professional entomologists, at all career stages.Overall, the challenges provide a diverse array of options to inspire and initiate entomological activities and reveal the potential of entomology to contribute to addressing global challenges related to human health and well-being, and environmental change.

Species turnover in ant assemblages is greater horizontally than vertically in the world's tallest tropical forest.

Abiotic and biotic factors structure species assembly in ecosystems both horizontally and vertically. However, the way community composition changes along comparable horizontal and vertical distances in complex three-dimensional habitats, and the factors driving these patterns, remains poorly understood. By sampling ant assemblages at comparable vertical and horizontal spatial scales in a tropical rainforest, we tested hypotheses that predicted differences in vertical and horizontal turnover explained by different drivers in vertical and horizontal space. These drivers included environmental filtering, such as microclimate (temperature, humidity, and photosynthetic photon flux density) and microhabitat connectivity (leaf area), which are structured differently across vertical and horizontal space. We found that both ant abundance and richness decreased significantly with increasing vertical height. Although the dissimilarity between ant assemblages increased with vertical distance, indicating a clear distance-decay pattern, the dissimilarity was higher horizontally where it appeared independent of distance. The pronounced horizontal and vertical structuring of ant assemblages across short distances is likely explained by a combination of microclimate and microhabitat connectivity. Our results demonstrate the importance of considering three-dimensional spatial variation in local assemblages and reveal how highly diverse communities can be supported by complex habitats.

Respect, justice and learning are limited when patients are deidentified data subjects.

Introduction: Critical for advancing a Learning Health System (LHS) in the U.S., a regulatory safe harbor for deidentified data reduces barriers to learning from care at scale while minimizing privacy risks. We examine deidentified data policy as a mechanism for synthesizing the ethical obligations underlying clinical care and human subjects research for an LHS which conceptually and practically integrates care and research, blurring the roles of patient and subject. Methods: First, we discuss respect for persons vis-a-vis the systemic secondary use of data and tissue collected in the fiduciary context of clinical care. We argue that, without traditional informed consent or duty to benefit the individual, deidentification may allow secondary use to supersede the primary purpose of care. Next, we consider the effectiveness of deidentification for minimizing harms via privacy protection and maximizing benefits via promoting learning and translational care. We find that deidentification is unable to fully protect privacy given the vastness of health data and current technology, yet it imposes limitations to learning and barriers for efficient translation. After that, we evaluate the impact of deidentification on distributive justice within an LHS ethical framework in which patients are obligated to contribute to learning and the system has a duty to translate knowledge into better care. Such a system may permit exacerbation of health disparities as it accelerates learning without mechanisms to ensure that individuals' contributions and benefits are fair and balanced. Results: We find that, despite its established advantages, system-wide use of deidentification may be suboptimal for signaling respect, protecting privacy or promoting learning, and satisfying requirements of justice for patients and subjects. Conclusions: Finally, we highlight ethical, socioeconomic, technological and legal challenges and next steps, including a critical appreciation for novel approaches to realize an LHS that maximizes efficient, effective learning and just translation without the compromises of deidentification.

Assessing the Governance of Digital Contact Tracing in Response to COVID-19: Results of a Multi-National Study.

This paper describes the results of a multi-country survey of governance approaches for the use of digital contact tracing (DCT) in response to the COVID-19 pandemic. We argue that the countries in our survey represent two distinct models of DCT governance, both of which are flawed. The "data protection model" emphasizes privacy protections at the expense of public health benefit, while the "emergency response model" sacrifices transparency and accountability, prompting concerns about excessive governance surveillance. The ethical and effective use of DCT in the future requires a new governance approach that is better suited to this novel use of mobile phone data to promote public health."

The data-index: An author-level metric that values impactful data and incentivizes data sharing.

Author-level metrics are a widely used measure of scientific success. The h-index and its variants measure publication output (number of publications) and research impact (number of citations). They are often used to influence decisions, such as allocating funding or jobs. Here, we argue that the emphasis on publication output and impact hinders scientific progress in the fields of ecology and evolution because it disincentivizes two fundamental practices: generating impactful (and therefore often long-term) datasets and sharing data. We describe a new author-level metric, the data-index, which values both dataset output (number of datasets) and impact (number of data-index citations), so promotes generating and sharing data as a result. We discuss how it could be implemented and provide user guidelines. The data-index is designed to complement other metrics of scientific success, as scientific contributions are diverse and our value system should reflect that both for the benefit of scientific progress and to create a value system that is more equitable, diverse, and inclusive. Future work should focus on promoting other scientific contributions, such as communicating science, informing policy, mentoring other scientists, and providing open-access code and tools.

A solution scan of societal options to reduce transmission and spread of respiratory viruses: SARS-CoV-2 as a case study.

Societal biosecurity - measures built into everyday society to minimize risks from pests and diseases - is an important aspect of managing epidemics and pandemics. We aimed to identify societal options for reducing the transmission and spread of respiratory viruses. We used SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) as a case study to meet the immediate need to manage the COVID-19 pandemic and eventually transition to more normal societal conditions, and to catalog options for managing similar pandemics in the future. We used a 'solution scanning' approach. We read the literature; consulted psychology, public health, medical, and solution scanning experts; crowd-sourced options using social media; and collated comments on a preprint. Here, we present a list of 519 possible measures to reduce SARS-CoV-2 transmission and spread. We provide a long list of options for policymakers and businesses to consider when designing biosecurity plans to combat SARS-CoV-2 and similar pathogens in the future. We also developed an online application to help with this process. We encourage testing of actions, documentation of outcomes, revisions to the current list, and the addition of further options.

Dynamic meta-analysis: a method of using global evidence for local decision making.

BACKGROUND: Meta-analysis is often used to make generalisations across all available evidence at the global scale. But how can these global generalisations be used for evidence-based decision making at the local scale, if the global evidence is not perceived to be relevant to local decisions? We show how an interactive method of meta-analysis-dynamic meta-analysis-can be used to assess the local relevance of global evidence. RESULTS: We developed Metadataset ( www.metadataset.com ) as a proof-of-concept for dynamic meta-analysis. Using Metadataset, we show how evidence can be filtered and weighted, and results can be recalculated, using dynamic methods of subgroup analysis, meta-regression, and recalibration. With an example from agroecology, we show how dynamic meta-analysis could lead to different conclusions for different subsets of the global evidence. Dynamic meta-analysis could also lead to a rebalancing of power and responsibility in evidence synthesis, since evidence users would be able to make decisions that are typically made by systematic reviewers-decisions about which studies to include (e.g. critical appraisal) and how to handle missing or poorly reported data (e.g. sensitivity analysis). CONCLUSIONS: In this study, we show how dynamic meta-analysis can meet an important challenge in evidence-based decision making-the challenge of using global evidence for local decisions. We suggest that dynamic meta-analysis can be used for subject-wide evidence synthesis in several scientific disciplines, including agroecology and conservation biology. Future studies should develop standardised classification systems for the metadata that are used to filter and weight the evidence. Future studies should also develop standardised software packages, so that researchers can efficiently publish dynamic versions of their meta-analyses and keep them up-to-date as living systematic reviews. Metadataset is a proof-of-concept for this type of software, and it is open source. Future studies should improve the user experience, scale the software architecture, agree on standards for data and metadata storage and processing, and develop protocols for responsible evidence use.

Eating our way through the Anthropocene.

This paper examines the complex interactions between food systems, diets, and the environment. We discuss the challenges facing the food system as a result of environmental degradation and climate change. We review the state of current diets and their effects on human health outcomes. As we consider paths forward, we examine holistic solutions that align nutrition, health, and environmental goals. Finally, we identify ethical questions relevant to the changing global food system. We consider our moral obligations to other people - both now and in the future - and the planet, and we posit that eating is an ethical act requiring reflection at all scales.

Network reorganization and breakdown of an ant-plant protection mutualism with elevation.

Both the abiotic environment and the composition of animal and plant communities change with elevation. For mutualistic species, these changes are expected to result in altered partner availability, and shifts in context-dependent benefits for partners. To test these predictions, we assessed the network structure of terrestrial ant-plant mutualists and how the benefits to plants of ant inhabitation changed with elevation in tropical forest in Papua New Guinea. At higher elevations, ant-plants were rarer, species richness of both ants and plants decreased, and the average ant or plant species interacted with fewer partners. However, networks became increasingly connected and less specialized, more than could be accounted for by reductions in ant-plant abundance. On the most common ant-plant, ants recruited less and spent less time attacking a surrogate herbivore at higher elevations, and herbivory damage increased. These changes were driven by turnover of ant species rather than by within-species shifts in protective behaviour. We speculate that reduced partner availability at higher elevations results in less specialized networks, while lower temperatures mean that even for ant-inhabited plants, benefits are reduced. Under increased abiotic stress, mutualistic networks can break down, owing to a combination of lower population sizes, and a reduction in context-dependent mutualistic benefits.