Towton, 1461: An integrated approach to battlefield archaeology

Ye

Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security

Challenging claims in the study of migratory birds and climate change

Recent shifts in phenology in response to climate change are well established but often poorly understood. Many animals integrate climate change across a spatially and temporally dispersed annual life cycle, and effects are modulated by ecological interactions, evolutionary change and endogenous control mechanisms. Here we assess and discuss key statements emerging from the rapidly developing study of changing spring phenology in migratory birds. These well-studied organisms have been instrumental for understanding climate-change effects, but research is developing rapidly and there is a need to attack the big issues rather than risking affirmative science. Although we agree poorly on the support for most claims, agreement regarding the knowledge basis enables consensus regarding broad patterns and likely causes. Empirical data needed for disentangling mechanisms are still scarce, and consequences at a population level and on community composition remain unclear. With increasing knowledge, the overall support (‘consensus view’) for a claim increased and between-researcher variability in support (‘expert opinions') decreased, indicating the importance of assessing and communicating the knowledge basis. A proper integration across biological disciplines seems essential for the field's transition from affirming patterns to understanding mechanisms and making robust predictions regarding future consequences of shifting phenologies

The Brief Solastalgia Scale: A Psychometric Evaluation and Revision

Witnessing degradation and loss to one’s home environment can cause the negative emotional experience of solastalgia. We review the psychometric properties of the 9-item Solastalgia subscale from the Environmental Distress Scale (Higginbotham et al. (EcoHealth 3:245–254, 2006)). Using data collected from three large, independent, adult samples (N = 4229), who were surveyed soon after the 2019/20 Australian bushfires, factor analyses confirmed the scale’s unidimensionality, while analyses derived from Item Response Theory highlighted the poor psychometric performance and redundant content of specific items. Consequently, we recommend a short-form scale consisting of five items. This Brief Solastalgia Scale (BSS) yielded excellent model fit and internal consistency in both the initial and cross-validation samples. The BSS and its parent version provide very similar patterns of associations with demographic, health, life satisfaction, climate emotion, and nature connectedness variables. Finally, multi-group confirmatory factor analysis demonstrated comparable construct architecture (i.e. configural, metric, and scalar invariance) across validation samples, gender categories, and age. As individuals and communities increasingly confront and cope with climate change and its consequences, understanding related emotional impacts is crucial. The BSS promises to aid researchers, decision makers, and practitioners to understand and support those affected by negative environmental change

The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos

Criminology or Zemiology? Yes, please! on the refusal of choice between false alternatives

Buried deep within the zemiological movement and its supportive literature is the implicit assumption that the word zemia, the organising concept around which zemiology is built, simply represents ‘the Greek word for harm’. This interpretation has supported numerous drives to ‘move beyond criminology’ and erect strict borders between the study of crime and harm. However, a deeper, albeit still rather brief, exploration of zemia reveals that it possesses a broader range of meaning than that commonly afforded to it. By beginning to unpick zemia’s semantic genealogy, it appears that the conventional use of the word to support the imposition of false alternatives between criminology and zemiology is untenable. Accordingly, this chapter attempts to foreground a more integrated approach to the study of crime and harm

Phenotypes of Non-Attached Pseudomonas aeruginosa Aggregates Resemble Surface Attached Biofilm

For a chronic infection to be established, bacteria must be able to cope with hostile conditions such as low iron levels, oxidative stress, and clearance by the host defense, as well as antibiotic treatment. It is generally accepted that biofilm formation facilitates tolerance to these adverse conditions. However, microscopic investigations of samples isolated from sites of chronic infections seem to suggest that some bacteria do not need to be attached to surfaces in order to establish chronic infections. In this study we employed scanning electron microscopy, confocal laser scanning microscopy, RT-PCR as well as traditional culturing techniques to study the properties of Pseudomonas aeruginosa aggregates. We found that non-attached aggregates from stationary-phase cultures have comparable growth rates to surface attached biofilms. The growth rate estimations indicated that, independently of age, both aggregates and flow-cell biofilm had the same slow growth rate as a stationary phase shaking cultures. Internal structures of the aggregates matrix components and their capacity to survive otherwise lethal treatments with antibiotics (referred to as tolerance) and resistance to phagocytes were also found to be strikingly similar to flow-cell biofilms. Our data indicate that the tolerance of both biofilms and non-attached aggregates towards antibiotics is reversible by physical disruption. We provide evidence that the antibiotic tolerance is likely to be dependent on both the physiological states of the aggregates and particular matrix components. Bacterial surface-attachment and subsequent biofilm formation are considered hallmarks of the capacity of microbes to cause persistent infections. We have observed non-attached aggregates in the lungs of cystic fibrosis patients; otitis media; soft tissue fillers and non-healing wounds, and we propose that aggregated cells exhibit enhanced survival in the hostile host environment, compared with non-aggregated bacterial populations

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.

Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch\u27s APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch\u27s data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch\u27s analytic tools by developing a customized plugin for OpenAI\u27s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app

A Simple Standard for Sharing Ontological Mappings (SSSOM).

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

Stem cell-derived porcine macrophages as a new platform for studying host-pathogen interactions

BACKGROUND: Infectious diseases of farmed and wild animals pose a recurrent threat to food security and human health. The macrophage, a key component of the innate immune system, is the first line of defence against many infectious agents and plays a major role in shaping the adaptive immune response. However, this phagocyte is a target and host for many pathogens. Understanding the molecular basis of interactions between macrophages and pathogens is therefore crucial for the development of effective strategies to combat important infectious diseases. RESULTS: We explored how porcine pluripotent stem cells (PSCs) can provide a limitless in vitro supply of genetically and experimentally tractable macrophages. Porcine PSC-derived macrophages (PSCdMs) exhibited molecular and functional characteristics of ex vivo primary macrophages and were productively infected by pig pathogens, including porcine reproductive and respiratory syndrome virus (PRRSV) and African swine fever virus (ASFV), two of the most economically important and devastating viruses in pig farming. Moreover, porcine PSCdMs were readily amenable to genetic modification by CRISPR/Cas9 gene editing applied either in parental stem cells or directly in the macrophages by lentiviral vector transduction. CONCLUSIONS: We show that porcine PSCdMs exhibit key macrophage characteristics, including infection by a range of commercially relevant pig pathogens. In addition, genetic engineering of PSCs and PSCdMs affords new opportunities for functional analysis of macrophage biology in an important livestock species. PSCs and differentiated derivatives should therefore represent a useful and ethical experimental platform to investigate the genetic and molecular basis of host-pathogen interactions in pigs, and also have wider applications in livestock. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01217-8