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This paper explores what the virtual biodiversity e-infrastructure will look like as it takes advantage of advances in ‘Big Data’ biodiversity informatics and e-research infrastructure, which allow integration of various taxon-level data types (genome, morphology, distribution and species interactions) within a phylogenetic and environmental framework. By overcoming the data scaling problem in ecology, this integrative framework will provide richer information and fast learning to enable a deeper understanding of biodiversity evolution and dynamics in a rapidly changing world. The Atlas of Living Australia is used as one example of the advantages of progressing towards this future. Living in this future will require the adoption of new ways of integrating scientific knowledge into societal decision making. This article is part of the themed issue ‘From DNA barcodes to biomes’.

\"In proving the existence of stem cells, Ernest Armstrong McCulloch and James Edgar Till formed the most important partnership in Canadian medical research since Frederick Banting and Charles Best, the discoverers of insulin. Together, Till and McCulloch instructed, influenced, and inspired successive generations of researchers who have used their findings to make huge advances against disease. Thousands of people who would have died from leukemia and immunological disorders now owe their lives to therapies supported by their seminal discoveries\"-- Dust jacket flap.

The integration of artificial intelligence (AI) into clinical workflows is advancing even before full compliance with the European Union Cross-Border eHealth Network (MyHealth@EU) framework is achieved. While AI-based clinical decision support systems are automatically classified as high risk under the European Union’s AI Act, cross-border health data exchange must also satisfy MyHealth@EU interoperability requirements. This creates a dual-compliance challenge: vertical safety and ethics controls mandated by the AI Act and horizontal semantic transport requirements enforced through Open National Contact Point (OpenNCP) gateways, many of which are still maturing toward production readiness. This paper provides a practical, phase-oriented tutorial that enables developers and providers to embed AI Act safeguards before approaching MyHealth@EU interoperability tests. The goal is to show how AI-specific metadata can be included in the Health Level Seven International Clinical Document Architecture and Fast Healthcare Interoperability Resources messages without disrupting standard structures, ensuring both compliance and trustworthiness in AI-assisted clinical decisions. We systematically analyzed Regulation (EU) 2024/1689 (AI Act) and the OpenNCP technical specifications, extracting a harmonized set of overlapping obligations. The AI Act provisions on transparency, provenance, and robustness are mapped directly onto MyHealth@EU workflows, identifying the points where outgoing messages must record AI involvement, log provenance, and trigger validation. To operationalize this mapping, we propose a minimal extension set, covering AI contribution status, rationale, risk classification, and Annex IV documentation links, together with a phase-based compliance checklist that aligns AI Act controls with MyHealth@EU conformance steps. A simulated International Patient Summary transmission demonstrates how Clinical Document Architecture/Fast Healthcare Interoperability Resources extensions can annotate AI involvement, how OpenNCP processes such enriched payloads, and how clinicians in another member state view the result with backward compatibility preserved. We expand on security considerations (eg, Open Worldwide Application Security Project generative AI risks such as prompt injection and adversarial inputs), continuous postmarket risk assessment, monitoring, and alignment with MyHealth@EU’s incident aggregation system. Limitations reflect the immaturity of current infrastructures and regulations, with real-world validation pending the rollout of key dependencies. AI-enabled clinical software succeeds only when AI Act safeguards and MyHealth@EU interoperability rules are engineered together from day 0 . This tutorial provides developers with a forward-looking blueprint that reduces duplication of effort, streamlines conformance testing, and embeds compliance early. While the concept is still in its early phases of practice, it represents a necessary and worthwhile direction for ensuring that future AI-enabled clinical systems can meet both European Union regulatory requirements from day 1. risks such as prompt injection and adversarial inputs), continuous postmarket risk assessment, monitoring, and alignment with MyHealth@EU’s incident aggregation system. Limitations reflect the immaturity of current infrastructures and regulations, with real-world validation pending the rollout of key dependencies.

Electronic health records are often extracted and combined with environmental data to conduct research or public health surveillance. However, to date, electronic health record systems do not integrate environmental data to aid real-time decision-making that could mitigate the health impacts of environmental hazards, including those related to climate change. Pursuing this goal requires enhancements to health record systems and modifications to the financial incentives driving health care innovation and delivery.

With the increasing use of social media platforms for health communication, the quality of health educational short videos (HESVs) has become a key concern. However, no standardized framework exists to evaluate the quality of health videos on social media, highlighting the need for a comprehensive evaluation system. This study aimed to develop a valid and structured evaluation tool for assessing the quality of HESVs on social media. The initial evaluation indicators obtained from the literature review and brainstorming undertaken in the study group were provided to the nominal group reference Lasswell's 5W communication model, and 2 rounds of nominal group technique (NGT) were carried out to screen, add, revise, and adjust indicators, and reach a consensus of evaluation system. The indicators were then ranked based on their significance, as scored by the experts using the analytic hierarchy process. The content validity was assessed by experts who rated the relevance of each indicator on a 4-point Likert scale. The primary indicators include communicator, communication content, communication channel, and communication effect, along with 13 secondary indicators and 34 tertiary indicators. In total, 11 experts were enrolled in the NGT, 45% (5/11) of experts had a doctoral degree, and 80% (9/11) of them were ranked as an associate professor or professor. The average values of the expert judgment coefficient and authority coefficient were 0.93 (SD 0.08) and 0.85 (SD 0.10), respectively. In round 1 of NGT, the \"communication target\" of 5 primary indicators, 7 of 20 secondary indicators, and 66 of 94 tertiary indicators did not reach a consensus, and therefore, they were not deleted and proceeded to the next round of NGT. In round 2 of NGT, 1 primary indicator, 7 secondary indicators, and 59 tertiary indicators were deleted based on the consensus criteria. Among primary indicators, communication content was found to be the most influential, accounting for 45.68%. Among secondary indicators, credibility, scientificity, availability, and social attention were the most influential indicators, with priorities of 56.67%, 24.26%, 74.62%, and 39.89% in their respective categories. Among tertiary indicators, \"become a hot search recommended by the platform\" was the most influential indicator with a weight of 0.07. The content validity of all the evaluation indicators was 0.73-1.0, and the scale-level content validity index (average) was 0.87 (SD 0.15), which was indicated as acceptable. The evaluation system for the quality of HESVs on social media (LassVQ; the Lasswell's Video Quality scale) was developed, and its validity was acceptable. The proposed evaluation system can be used in conjunction with qualitative methods to gain a holistic perspective on the multidimensional quality of HESVs on social media.

Health literacy, the ability to understand and act on health information, is critical for patient outcomes and health care system effectiveness. While plain language guidelines enhance text-based communication, audio-based health information remains underexplored, despite the growing use of digital assistants and smart devices in health care. Traditional readability formulas, such as Flesch-Kincaid, provide limited insights into the complexity of health-related texts and fail to address challenges specific to audio formats. Factors like syntax and semantic features significantly influence comprehension and retention across modalities. This study investigates features that affect comprehension of medical information delivered via text or audio formats. We also examine existing readability formulas and their correlation with perceived and actual difficulty of health information for both modalities. We developed a parallel corpus of health-related information that differed in delivery format: text or audio. We used text from the British Medical Journal (BMJ) Lay Summary (n=193), WebMD (n=40), Patient Instruction (n=40), Simple Wikipedia (n=243), and BMJ journal (n=200). Participants (n=487) read or listened to a health text and then completed a questionnaire evaluating perceived difficulty of the text, measured using a 5-point Likert scale, and actual difficulty measured using multiple-choice and true-false questions (comprehension) as well as free recall of information (retention). Questions were generated by generative artificial intelligence (ChatGPT-4.0). Underlying syntactic, semantic, and domain-specific features, as well as common readability formulas, were evaluated for their relation to information difficulty. Text versions were perceived as easier than audio, with BMJ Lay Summary scoring 1.76 versus 2.1 and BMJ journal 2.59 versus 2.83 (lower is easier). Comprehension accuracy was higher for text across all sources (eg, BMJ journal: 76% vs 58%; Patient Instructions: 86% vs 66%). Retention was better for text, with significant differences in exact word matching for Patient Instructions and BMJ journal. Longer texts increased perceived difficulty in text but reduced free recall in both modalities (-0.23,-0.25 in audio). Higher content word frequency improved retention (0.23, 0.21) and lowered perceived difficulty (-0.20 in audio). Verb-heavy content eased comprehension (-0.29 in audio), while nouns and adjectives increased difficulty (0.20, 0.18). Readability formulas' outcomes were unrelated to comprehension or retention, but correlated with perceived difficulty in text (eg, Smog Index: 0.334 correlation). Text was more effective for conveying complex health information, but audio can be suitable for easier content. In addition, several textual features affect information comprehension and retention for both modalities. Finally, existing readability formulas did not explain actual difficulty. This study highlighted the importance of tailoring health information delivery to content complexity by using appropriate style and modality.

Patient-centeredness has become a guiding principle of delivering quality health care. Integrating self-help services in health care facilities through collaboration is a vital part of this, specifically in rehabilitation. Despite increasing efforts to promote cooperation between rehabilitation clinics and self-help groups and organizations in Germany, implementation remains inconsistent, and research on this is particularly limited. This study sought to examine the \"self-help friendliness\" (SHF) of rehabilitation clinics, considering the significance of self-help in their internet presence as a central source of patient information. The research objectives are thus to measure and compare the self-help orientation among rehabilitation clinics' websites as an indicator of SHF to assess which clinic criteria are associated with self-help presentation on the clinic websites. A quantitative content analysis of 400 randomly chosen rehabilitation clinic websites was conducted as part of the KoReS project (self-help friendliness and cooperation with self-help among rehabilitation clinics in Germany) that is co-designed, conducted, and disseminated in collaboration with public health and patient representatives. Websites were systematically screened using a newly developed 16-criteria coding instrument assessing self-help orientation. A score was formed from these criteria ranging from 0 to 16 points. Univariate analyses describe the score distributions. Binomial logistic regression analyses were performed to determine the self-help orientation on the websites depending on characteristics of the rehabilitation clinics (size, indication area, and sponsorship). Of the 400 clinics, 61.0% (n=242) scored low on self-help orientation, with the majority (41.8%; n=167) not being self-help oriented at all. Conversely, 39.5% (n=158) of the clinic websites demonstrated high self-help orientation, with 7.3% (n=29) of them achieving exceptional scores. Overall, a mean 4.4 (SD 4.1) of 16 points was reached and basic self-help orientation criteria were fulfilled by the clinics. Regression analysis revealed clinics covering the indication areas: oncology (odds ratio [OR] 2.64; P=.01), neurology (OR 2.73; P=.003) or addiction (OR 3.04; P<.001) to significantly predict higher self-help orientation scores. Facility size, sponsorship type, and the number of specialist indication areas did not impact the self-help orientation of the websites overall. This is the first analysis measuring the self-help orientation of rehabilitation clinic websites and indicates that it falls short of its potential. The findings suggest that greater emphasis on self-help display and collaboration with self-help in rehabilitation is needed. It can be achieved by using the concept of SHF, integrating self-help closely into clinic missions and treatment plans and considering the criteria developed in designing clinic websites to increase patient orientation.