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Over the last decade or so, the rate of growth of academic publications involving discussion of 'citizen science' and 'community science', and similar variants, has risen exponentially. These fluid terms, with no fixed definition, cover a continuum of public participation within a range of scientific activities. It is, therefore, apposite and timely to examine the evolving typologies of citizen science and community science and to ask how particular disciplinary actors are shaping content and usage. Do certain approaches to citizen science and community science activity remain siloed within specific disciplines or do some approaches resonate more widely? In this study, we use mixed methods--bibliometric and textual analysis--to chart the changing academic interpretations of this scientific activity over time. We then ask what these analyses mean for the future direction of academic research into citizen science and community science. The results suggest that, while certain disciplinary-based interpretations have been particularly influential in the past, a more epistemically mixed array of academic interests than was previously evident are currently determining expectations of what citizen science and community science should look like and what they can be expected to deliver.

This paper presents a new theory and model of the teaching of decoding, reading and writing. The first part of the paper reviews a selection of influential models of learning to read and write that to varying degrees have been used as the basis for approaches to teaching, including the "Simple View of Reading." As well as noting some strengths of the models in relation to children's learning, limitations are identified in terms of their applicability as models of teaching. The second part of the paper presents seven components that are central to teaching reading and writing derived from social, cultural and cognitive research and theory. Explanations for the relevance of the components are offered, and seminal and more recent research that underpin them summarised. The final part of the paper introduces a new theory and model of teaching, "The Double Helix of Reading and Writing." It is argued that this model provides a rationale for a balanced approach to teaching, and an alternative to synthetic phonics.

ChatGPT represents a transformative technology in healthcare, with demonstrated impacts across clinical practice, medical education, and research. Studies show significant efficiency gains, including 70% reduction in administrative time for discharge summaries and achievement of medical professional-level performance on standardized tests (60% accuracy on USMLE, 78.2% on PubMedQA). ChatGPT offers personalized learning platforms, automated scoring, and instant access to vast medical knowledge in medical education, addressing resource limitations and enhancing training efficiency. It streamlines clinical workflows by supporting triage processes, generating discharge summaries, and alleviating administrative burdens, allowing healthcare professionals to focus more on patient care. Additionally, ChatGPT facilitates remote monitoring and chronic disease management, providing personalized advice, medication reminders, and emotional support, thus bridging gaps between clinical visits. Its ability to process and synthesize vast amounts of data accelerates research workflows, aiding in literature reviews, hypothesis generation, and clinical trial designs. This paper aims to gather and analyze published studies involving ChatGPT, focusing on exploring its advantages and disadvantages within the healthcare context. To aid in understanding and progress, our analysis is organized into six key areas: (1) Information and Education, (2) Triage and Symptom Assessment, (3) Remote Monitoring and Support, (4) Mental Healthcare Assistance, (5) Research and Decision Support, and (6) Language Translation. Realizing ChatGPT’s full potential in healthcare requires addressing key limitations, such as its lack of clinical experience, inability to process visual data, and absence of emotional intelligence. Ethical, privacy, and regulatory challenges further complicate its integration. Future improvements should focus on enhancing accuracy, developing multimodal AI models, improving empathy through sentiment analysis, and safeguarding against artificial hallucination. While not a replacement for healthcare professionals, ChatGPT can serve as a powerful assistant, augmenting their expertise to improve efficiency, accessibility, and quality of care. This collaboration ensures responsible adoption of AI in transforming healthcare delivery. While ChatGPT demonstrates significant potential in healthcare transformation, systematic evaluation of its implementation across different healthcare settings reveals varying levels of evidence quality–from robust randomized trials in medical education to preliminary observational studies in clinical practice. This heterogeneity in evidence quality necessitates a structured approach to future research and implementation.

Background: Distributed ledger technology (DLT) enables the creation of tamper-resistant, decentralized, and secure digital ledgers. A non-fungible token (NFT) represents a record on-chain associated with a digital or physical asset, such as a whole-slide image (WSI). The InterPlanetary File System (IPFS) represents an off-chain network, hypermedia, and file sharing peer-to-peer protocol for storing and sharing data in a distributed file system. Today, we need cheaper, more efficient, highly scalable, and transparent solutions for WSI data storage and access of medical records and medical imaging data. Methods: WSIs were created from non-human tissues and H&E-stained sections were scanned on a Philips Ultrafast WSI scanner at 40× magnification objective lens (1 μm/pixel). TIFF images were stored on IPFS, while NFTs were minted on the Ethereum blockchain network in ERC-1155 standard. WSI-NFTs were stored on MetaMask and OpenSea was used to display the WSI-NFT collection. Filebase storage application programing interface (API) were used to create dedicated gateways and content delivery networks (CDN). Results: A total of 10 WSI-NFTs were minted on the Ethereum blockchain network, found on our collection “Whole Slide Images as Non-fungible Tokens Project” on Open Sea: https://opensea.io/collection/untitled-collection-126765644. WSI TIFF files ranged in size from 1.6 to 2.2 GB and were stored on IPFS and pinned on 3 separate nodes. Under optimal conditions, and using a dedicated CDN, WSI reached retrieved at speeds of over 10 mb/s, however, download speeds and WSI retrieval times varied significantly depending on the file and gateway used. Overall, the public IPFS gateway resulted in variably poorer WSI download retrieval performance compared to gateways provided by Filebase storage API. Conclusion: Whole-slide images, as the most complex and substantial data files in healthcare, demand innovative solutions. In this technical report, we identify pitfalls in IPFS, and demonstrate proof-of-concept using a 3-layer architecture for scalable, decentralized storage, and access. Optimized through dedicated gateways and CDNs, which can be effectively applied to all medical data and imaging modalities across the healthcare sector. DLT and off-chain network solutions present numerous opportunities for advancements in clinical care, education, and research. Such approaches uphold the principles of equitable healthcare data ownership, security, and democratization, and are poised to drive significant innovation.

OBJECTIVE: Interventions to support patients engagement in shared decision making (SDM) are lacking within high-grade glioma (HGG) healthcare. Consultation Planning, Recording and Summarising (CPRS) has shown evidence of increasing patient decision self-efficacy, reducing uncertainty, and regret of decisions. This is the first study of CPRS within a HGG population and delivered over serial medical consultations. METHOD: A one-arm prospective qualitative longitudinal design was used to evaluate the CPRS intervention and evaluated with participants at sequential clinic appointments depending on their care, in Edinburgh, Scotland. We report on serial semi structured interviews of 16 patients and their partners. RESULTS: Consultation planning before the consultation supported patients to feel known by strengthening the patient voice within the consultation. It prepared patients to actively participate in the consultation, despite the distressing nature of the content. Recording and summarising supported patients to understand their situation. The provision of a consultation record enabled accurate recall, a paced uptake of information and supported the family to feel fully informed. Ultimately, patients understood why decisions were being made rather than being part of making decisions. CONCLUSIONS: The CPRS intervention helped patients to understand and to feel known by increasing patient capacity for communication in the consultation, with support before, during, and after the consultation. The intervention focused on preparing patients for SDM but patients did not perceive that they had meaningful choices to make. Further research could look at the inclusion of patient decision aids to support this process.

This article offers a novel foray into international mindedness and posthuman theory. International mindedness underpins the International Baccalaureate's aim to achieve a better and more peaceful world. However, in a global context of planetary emergency and widening inequalities, it seems imperative to rethink international mindedness within a posthumanist frame, that is, beyond anthropocentric notions of education that privilege human exceptionalism. The reconceptualization of international mindedness as relational becoming is illuminated through five theoretical propositions which are illustrated empirically using 'material moments'. Relational becoming rejects mind and body binaries, affirms nonhuman-human assemblages, enables distributed agency, enacts ethics of response-ability and engages with past and present entanglements. 'Posthumanizing' international mindedness, through the concept of relational becoming, prompts more nuanced insights into educational privilege, nation-states, globalism and enduring colonialist inheritances.

Abstract Background Exercise intervention research has shown promising results in preventing and reversing the side effects caused by prostate cancer and its’ treatment. However, there are still unanswered questions and the need for additional research. As the field of exercise oncology in the context of prostate cancer presents unique challenges and complexities, seeking the advice of experienced exercise oncology researchers before initiating a similar trial could help to design more effective and efficient studies and help avoid pitfalls. Methods A qualitative descriptive study design and a nonprobability, purposive sampling method was employed. An interview guide was developed and included topics such as recruitment, retention, programme goals, research design, health considerations, treatment considerations, adverse events, exercise prescription and outcome tools. Individual semi-structured interviews were conducted and interviews were transcribed and analysed using thematic analysis. Results Eight individuals with extensive experience working with prostate cancer patients in exercise oncology research settings were interviewed. Four main themes and seven subthemes were generated and supported by the data. Theme 1 highlighted the critical role of recruitment, with associated subthemes on recruitment barriers and recruitment methods. Theme 2 explored the positives and negatives of home-based programmes. Theme 3 focused on specific health characteristics, exercise prescription and outcome measure factors that must be considered when working with prostate cancer cohorts. Finally, theme 4 centered around the emotional dimensions present in exercise oncology trials, relating to both researchers and study participants. Conclusion Exercise oncology remains a challenging area in which to conduct research. Learning from experienced personnel in the field offers valuable information and guidance that could impact the success of future trials.

The generative artificial intelligence (AI) model ChatGPT holds transformative prospects in medicine. The development of such models has signaled the beginning of a new era where complex biological data can be made more accessible and interpretable. ChatGPT is a natural language processing tool that can process, interpret, and summarize vast data sets. It can serve as a digital assistant for physicians and researchers, aiding in integrating medical imaging data with other multiomics data and facilitating the understanding of complex biological systems. The physician’s and AI’s viewpoints emphasize the value of such AI models in medicine, providing tangible examples of how this could enhance patient care. The editorial also discusses the rise of generative AI, highlighting its substantial impact in democratizing AI applications for modern medicine. While AI may not supersede health care professionals, practitioners incorporating AI into their practices could potentially have a competitive edge.

Abstract Primary breast neuroendocrine (NE) neoplasms are uncommon, and definitions harbor controversy. We retrospectively collected 73 triple‐negative breast cancers (TNBC) and evaluated NE biomarker expression along with p53 aberrant staining (which correlates with TP53 gene mutation) and Rb protein loss by immunohistochemistry. In the study cohort, we found 11 (15%) cases of TNBC with neuroendocrine differentiation (TNBC‐NED) showing positivity for one or more NE markers (synaptophysin/chromogranin/insulinoma‐associated protein 1 [INSM1]). We also identified one separate small cell neuroendocrine carcinoma. Histologic types for these 11 TNBC‐NED cases were as follows: 8 invasive ductal carcinoma (IDC) not otherwise specified (NOS), 2 IDC with apocrine features, 1 IDC with solid papillary features. INSM1 had the highest positivity and was seen in all 11 carcinomas. Seven (64%) cases showed p53 aberrant staining, 6 (55%) had Rb protein loss, while 6 (55%) had p53/Rb co‐aberrant staining/protein loss. TNBC‐NED was associated with Rb protein loss (p