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Abstract: Global change is impacting biodiversity across all habitats on earth. New selection pressures from changing climatic conditions and other anthropogenic activities are creating heterogeneous ecological and evolutionary responses across many species' geographic ranges. Yet we currently lack standardised and reproducible tools to effectively predict the resulting patterns in species vulnerability to declines or range changes. We developed an informatic toolbox that integrates ecological, environmental and genomic data and analyses (environmental dissimilarity, species distribution models, landscape connectivity, neutral and adaptive genetic diversity, genotype‐environment associations and genomic offset) to estimate population vulnerability. In our toolbox, functions and data structures are coded in a standardised way so that it is applicable to any species or geographic region where appropriate data are available, for example individual or population sampling and genomic datasets (e.g. RAD‐seq, ddRAD‐seq, whole genome sequencing data) representing environmental variation across the species geographic range. To demonstrate multi‐species applicability, we apply our toolbox to three georeferenced genomic datasets for co‐occurring East African spiny reed frogs (Afrixalus fornasini, A. delicatus and A. sylvaticus) to predict their population vulnerability, as well as demonstrating that range loss projections based on adaptive variation can be accurately reproduced from a previous study using data for two European bat species (Myotis escalerai and M. crypticus). Our framework sets the stage for large scale, multi‐species genomic datasets to be leveraged in a novel climate change vulnerability framework to quantify intraspecific differences in genetic diversity, local adaptation, range shifts and population vulnerability based on exposure, sensitivity and landscape barriers.

PurposeUse of the electronic health record (EHR) has motivated the need for data standardization. A gap in knowledge exists regarding variations in existing terminologies for defining diabetic retinopathy (DR) cohorts. This study aimed to review the literature and analyze variations regarding codified definitions of DR.DesignLiterature review and quantitative analysis.SubjectsPublished manuscripts.MethodsFour graders reviewed PubMed and Google Scholar for peer-reviewed studies. Studies were included if they used codified definitions of DR (e.g., billing codes). Data elements such as author names, publication year, purpose, data set type, and DR definitions were manually extracted. Each study was reviewed by ≥ 2 authors to validate inclusion eligibility. Quantitative analyses of the codified definitions were then performed to characterize the variation between DR cohort definitions.Main outcome measuresNumber of studies included and numeric counts of billing codes used to define codified cohorts.ResultsIn total, 43 studies met the inclusion criteria. Half of the included studies used datasets based on structured EHR data (i.e., data registries, institutional EHR review), and half used claims data. All but 1 of the studies used billing codes such as the International Classification of Diseases 9th or 10th edition (ICD-9 or ICD-10), either alone or in addition to another terminology for defining disease. Of the 27 included studies that used ICD-9 and the 20 studies that used ICD-10 codes, the most common codes used pertained to the full spectrum of DR severity. Diabetic retinopathy complications (e.g., vitreous hemorrhage) were also used to define some DR cohorts.ConclusionsSubstantial variations exist among codified definitions for DR cohorts within retrospective studies. Variable definitions may limit generalizability and reproducibility of retrospective studies. More work is needed to standardize disease cohorts.Financial disclosuresProprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

The overarching goal of the third scientific oral health symposium was to introduce the concept of a learning health system to the dental community and to identify and discuss cutting-edge research and strategies using data for improving the quality of dental care and patient safety. Conference participants included clinically active dentists, dental researchers, quality improvement experts, informaticians, insurers, EHR vendors/developers, and members of dental professional organizations and dental service organizations. This report summarizes the main outputs of the third annual OpenWide conference held in Houston, Texas, on October 12, 2022, as an affiliated meeting of the American Dental Association (ADA) 2022 annual conference.

Objectives To quantify utilization and impact on documentation time of a large language model-powered ambient artificial intelligence (AI) scribe. Materials and Methods This prospective quality improvement study was conducted at a large academic medical center with 45 physicians from 8 ambulatory disciplines over 3 months. Utilization and documentation times were derived from electronic health record (EHR) use measures. Results The ambient AI scribe was utilized in 9629 of 17 428 encounters (55.25%) with significant interuser heterogeneity. Compared to baseline, median time per note reduced significantly by 0.57 minutes. Median daily documentation, afterhours, and total EHR time also decreased significantly by 6.89, 5.17, and 19.95 minutes/day, respectively. Discussion An early pilot of an ambient AI scribe demonstrated robust utilization and reduced time spent on documentation and in the EHR. There was notable individual-level heterogeneity. Conclusion Large language model-powered ambient AI scribes may reduce documentation burden. Further studies are needed to identify which users benefit most from current technology and how future iterations can support a broader audience. [ABSTRACT FROM AUTHOR]

Objective This study evaluates the pilot implementation of ambient AI scribe technology to assess physician perspectives on usability and the impact on physician burden and burnout. Materials and Methods This prospective quality improvement study was conducted at Stanford Health Care with 48 physicians over a 3-month period. Outcome measures included burden, burnout, usability, and perceived time savings. Results Paired survey analysis (n  = 38) revealed large statistically significant reductions in task load (−24.42, p <.001) and burnout (−1.94, p <.001), and moderate statistically significant improvements in usability scores (+10.9, p <.001). Post-survey responses (n  = 46) indicated favorable utility with improved perceptions of efficiency, documentation quality, and ease of use. Discussion In one of the first pilot implementations of ambient AI scribe technology, improvements in physician task load, burnout, and usability were demonstrated. Conclusion Ambient AI scribes like DAX Copilot may enhance clinical workflows. Further research is needed to optimize widespread implementation and evaluate long-term impacts. [ABSTRACT FROM AUTHOR]

Prescribing errors are a source of preventable harm in healthcare, which may be mitigated using Electronic Prescribing (EP) systems. Anyone who routinely prescribes medication could benefit from digitally assisted automated checks to identify whether a prescription should potentially not be allowed (e.g. drug allergy). National Health Service (NHS) Trusts have implemented a range of EP systems; however, their performance has not hitherto been evaluated. We developed the web-based Electronic Prescribing Risk and Safety Evaluation (ePRaSE) tool, which comprises a bank of prescribing scenarios to evaluate the performance of EP systems. We solicited ePRaSE testing: 68 pharmacists from across 45 English NHS Trusts, utilising 13 different EP systems volunteered for the study. We found considerable variability in mitigation performance (systems correctly identifying risk of error when prescribing) across both NHS Trusts and EP systems. Moreover, we found that mitigation performance varied considerably across NHS Trusts using the same EP system, strongly suggesting there are opportunities to optimise performance within systems. The ePRaSE tool is effective in identifying variability in risk management between NHS Trusts and EP systems. Wider use of this tool may facilitate improvements in EP system configurations, thus minimising potential harm from prescribing errors. [ABSTRACT FROM AUTHOR]

Background: Wall shear stress (WSS) plays a crucial role in the natural history of intracranial aneurysms (IA). However, spatial variations among WSS have rarely been utilized to correlate with IAs' natural history. This study aims to establish the feasibility of using spatial patterns of WSS data to predict IAs' rupture status (i.e., ruptured versus unruptured). Methods: "Patient-specific" computational fluid dynamics (CFD) simulations were performed for 112 IAs; each IA's rupture status was known from medical records. Recall that CFD-simulated hemodynamics data (wall shear stress and its derivatives) are located on unstructured meshes. Hence, we mapped WSS data from an unstructured grid onto a unit disk (i.e., a uniformly sampled polar coordinate system); data in a uniformly sampled polar system is equivalent to image data. Mapped WSS data (onto the unit disk) were readily available for Radiomics analysis to extract spatial patterns of WSS data. We named this innovative technology "WSS-informatics" (i.e., using informatics techniques to analyze WSS data); the usefulness of WSS-informatics was demonstrated during the predictive modeling of IAs' rupture status. Results: None of the conventional WSS parameters correlated to IAs' rupture status. However, WSS-informatics metrics were discriminative (p-value < 0.05) to IAs' rupture status. Furthermore, predictive models with WSS-informatics features could significantly improve the prediction performance (area under the receiver operating characteristic curve [AUROC]: 0.78 vs. 0.85; p-value < 0.01). Conclusion: The proposed innovations enabled the first study to use spatial patterns of WSS data to improve the predictive modeling of IAs' rupture status. [ABSTRACT FROM AUTHOR]

Purpose: To investigate community-acquired pressure injuries (CAPIs) in older people by utilizing big data. Design: Retrospective data curation and analysis of inpatient data from two general medical centers between 1 January 2016 and 31 December 2018. Methods: Nursing assessments from 44,449 electronic medical records of patients admitted to internal medicine departments were retrieved, organized, coded by data engineers, and analyzed by data scientists. Potential explanatory patient characteristics tested were gender, age, admission indices, nursing assessments including CAPIs, CAPI type and location, vital signs, and the results of lab tests within the first 36 h of admission. Findings: Most CAPIs were located in the buttocks (56.9%), followed by the sacrum (11.8%), ankle (10.8%), trochanter (5.1%), and leg (3.9%). Tissue associated with CAPIs was described as necrotic, serotic, bloody, granolithic, epithelial, and infected. There were 31% of first-degree CAPIs, 41% second-degree, and 18% third-degree. Previously unacknowledged patient characteristics associated with CAPIs are as follows: age, oxygen use, intestinal function, the touch senses of heat and pain, albumin, RDW (red cell distribution width), and systolic blood pressure. Conclusions: The novel indicators for CAPIs underscore the importance of data-driven approaches in detecting and preventing CAPIs in community care. These markers can detect and prevent pressure ulcers in the community, particularly among the elderly. Relevance for Clinical Practice: Nursing management is called upon to integrate information about novel patient characteristics associated with CAPI into clinical practice. Assimilating the insights from this hospital nursing-led study into community nursing will enhance the safety and quality of care for the elderly. [ABSTRACT FROM AUTHOR]

In the era where digital technologies are becoming increasingly prevalent, it is anticipated that a majority of the global population will have at least a basic understanding of informatics. However, empirical evidence suggests that a significant portion of the global population remains digitally illiterate. This phenomenon is particularly pronounced in the case of the senior adult population. In light of the aforementioned challenges, this work integrates Computer Science Unplugged exercises, based on games and recreational activities without the use of computers, and L2T2L, a learning-by-teaching methodology whereby university students learn and then, in turn, teach that learning to other populations in a cascading manner. A case study was conducted in Lima, Peru, with the participation of 140 volunteers from centres for the elderly. Thirty-five students and one teacher from the Universidad Científica del Sur were responsible for initiating the transfer of knowledge from the university to the senior citizens, with the assistance of twelve individuals responsible for their care. The results demonstrate that the participants attained a commendable level of comprehension when attempting to complete all of the assigned tasks. Furthermore, the efficacy of L2T2L is evident in its adaptability and suitability for scenarios beyond those for which it was originally designed. [ABSTRACT FROM AUTHOR]

Objectives There is rapidly growing interest in learning health systems (LHSs) nationally and globally. While the critical role of informatics is recognized, the informatics community has been relatively slow to formalize LHS as a priority area. Materials and Methods We compiled results from a short survey of LHS leaders and American Medical Informatics Association (AMIA) members, discussion from an LHS reception at the AMIA annual meeting, and a follow-up survey to inform priorities at the intersection of LHS and informatics. Results We present opportunities between informatics and LHS which fell into themes of: Understanding and Context, Shared Resources, Collaboration, Education, Data, Evaluation, and Patient Centeredness. Immediate LHS informatics priorities identified include establishing informatics LHS forum(s), case reports of LHS informatics successes and failures, LHS informatics education resources, and improved understanding of LHS principles in informatics. Conclusion Increased informatics and LHS alignment is critical for advancing this transformative national priority. [ABSTRACT FROM AUTHOR]

Objectives To examine changes in technology-related errors (TREs), their manifestations and underlying mechanisms at 3 time points after the implementation of computerized provider order entry (CPOE) in an electronic health record; and evaluate the clinical decision support (CDS) available to mitigate the TREs at 5-years post-CPOE. Materials and Methods Prescribing errors (n  = 1315) of moderate, major, or serious potential harm identified through review of 35 322 orders at 3 time points (immediately, 1-year, and 4-years post-CPOE) were assessed to identify TREs at a tertiary pediatric hospital. TREs were coded using the Technology-Related Error Mechanism classification. TRE rates, percentage of prescribing errors that were TREs, and mechanism rates were compared over time. Each TRE was tested in the CPOE 5-years post-implementation to assess the availability of CDS to mitigate the error. Results TREs accounted for 32.5% (n  = 428) of prescribing errors; an adjusted rate of 1.49 TREs/100 orders (95% confidence interval [CI]: 1.06, 1.92). At 1-year post-CPOE, the rate of TREs was 40% lower than immediately post (incident rate ratio [IRR]: 0.60; 95% CI: 0.41, 0.89). However, at 4-years post, the TRE rate was not significantly different to baseline (IRR: 0.80; 95% CI: 0.59, 1.08). "New workflows required by the CPOE" was the most frequent TRE mechanism at all time points. CDS was available to mitigate 32.7% of TREs. Discussion In a pediatric setting, TREs persisted 4-years post-CPOE with no difference in the rate compared to immediately post-CPOE. Conclusion Greater attention is required to address TREs to enhance the safety benefits of systems. [ABSTRACT FROM AUTHOR]

Lipidomics is a well-established field, enabled by modern liquid chromatography mass spectrometry (LC-MS) technology, rapidly generating large amounts of data. Lipid extracts derived from biological samples are complex, and most spectral features in LC-MS lipidomics data sets remain unidentified. In-depth analyses of commercial triacylglycerol, diacylglycerol, and cholesterol ester standards revealed the expected ammoniated and sodiated ions as well as five additional unidentified higher mass peaks with relatively high intensities. The identities and origin of these unknown peaks were investigated by modifying the chromatographic mobile-phase components and LC-MS source parameters. Tandem MS (MS/MS) of each unknown adduct peak yielded no lipid structural information, producing only an intense ion of the adducted species. The unknown adducts were identified as low-mass contaminants originating from methanol and isopropanol in the mobile phase. Each contaminant was determined to be an alkylated amine species using their monoisotopic masses to calculate molecular formulas. Analysis of bovine liver extract identified 33 neutral lipids with an additional 73 alkyl amine adducts. Analysis of LC-MS-grade methanol and isopropanol from different vendors revealed substantial alkylated amine contamination in one out of three different brands that were tested. Substituting solvents for ones with lower levels of alkyl amine contamination increased lipid annotations by 36.5% or 27.4%, depending on the vendor, and resulted in >2.5-fold increases in peak area for neutral lipid species without affecting polar lipid analysis. These findings demonstrate the importance of solvent selection and disclosure for lipidomics protocols and highlight some of the major challenges when comparing data between experiments. [ABSTRACT FROM AUTHOR]

The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user‐friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data‐sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science. [ABSTRACT FROM AUTHOR]

Background: Digital health technology is progressively transforming physiotherapy practice. Despite a maturing body of literature relating to physiotherapy digital health capability, research examining digital health physiotherapy competency standards is both lacking and lagging. Objective: Examine international professional practice competency standards for physiotherapists to identify themes common to digital health practice competency, published by international peak organizations governing physiotherapy practice. Methods: Systematic meta-synthesis of international peak organization physiotherapy practice competency standards. The study was undertaken over nine stages. Competency statements related to digital health were extracted, and further coded into resultant themes. Results: Eleven documents were analyzed. Fifty-two statements explicitly referenced digital health competency. Identified themes were as follows: 1) digital health data governance; 2) digital health data translation; and 3) digital health technologies. Where digital health-related competency statements do exist, they are skewed toward health information management activities. Conclusions: Digital health practice is currently under-represented in competency standards for physiotherapists. Workforce advancement in light of the burgeoning impact of digital health will prompt further updates to professional competency standards set by our peak organizations. This will have a flow on effect, whereby education providers (e.g. universities and other professional development providers) should consider curriculum and training that prepares individuals for digitally enabled practice. [ABSTRACT FROM AUTHOR]

Creating software tools that address the needs of a wide range of decision-makers requires the inclusion of differing perspectives throughout the development process. Software tools for biodiversity conservation often fall short in this regard, partly because broad decision-maker needs may exceed the toolkits of single research groups or even institutions. We show that participatory, collaborative codesign enhances the utility of software tools for better decision-making in biodiversity conservation planning, as demonstrated by our experiences developing a set of integrated tools in Colombia. Specifically, we undertook an interdisciplinary, multi-institutional collaboration of ecological modelers, software engineers, and a diverse profile of potential end users, including decision-makers, conservation practitioners, and biodiversity experts. We leveraged and modified common paradigms of software production, including codesign and agile development, to facilitate collaboration through all stages (including conceptualization, development, testing, and feedback) to ensure the accessibility and applicability of the new tools to inform decision-making for biodiversity conservation planning. [ABSTRACT FROM AUTHOR]

When medication administration record (MAR) "hold" capability is enabled in the electronic health record (EHR) during patient transfers, medication doses appear as "held" rather than due. We sought to quantify the incidence of delayed and missed doses of critical medications during MAR hold periods and to implement and evaluate interdisciplinary efforts and technical interventions to reduce missed medication doses during these periods. A list of critical medications was identified. MAR data were collected in patients with at least 1 critical medication dose due during the MAR hold period. MAR times were used to determine if delayed doses or missed doses occurred. Our interventions included: (1) implementation of a patient list indicator to retrospectively identify recently "held" medication doses, and (2) a report for operating room pharmacists to prospectively identify upcoming doses and ensure they were administered on time. Pre- and post-intervention period data were compared using a chi-squared test. During the pre-intervention study period, there were 1044 instances of delayed or missed doses during MAR hold. Most MAR times evaluated were on MAR hold during perioperative patient transfers. Delayed, missed, and multiple missed doses were defined in accordance with internal medication administration policies. There was no significant difference in the incidence of delayed and missed doses (69% vs 66%, P =.31), however, there was a significant reduction in the number of critical medication doses missed multiple times (0.8% vs 6.7%, P <.001) and all missed doses (35% vs 42%, P =.05) between the pre- and post-intervention period. As demonstrated across in both the pre- and post-intervention period of our study, MAR hold is commonly associated with dose delays and missed doses, which has potential negative consequences on patient outcomes. Future considerations will include implementation of a best practice alert (BPA) that directs users to a MAR tab highlighting doses held during transfers. [ABSTRACT FROM AUTHOR]

Information Science has become a pivotal force driving progress in science and technology. In today's era, Information and Communication Technology (ICT) plays a significant role in enhancing organizational efficiency and enabling individual growth. By facilitating seamless communication and data management, ICT allows businesses to optimize their relationships with clients, suppliers, and distributors. Moreover, ICT has transformed education, empowering learners to access resources globally and enabling personalized learning experiences. Informatics, as an interdisciplinary field, encompasses computer science, information systems, and data analytics, all of which contribute to solving complex challenges. This paper explores the diverse applications of Informatics and its role in shaping a technologically advanced society. Through its integration across various sectors, Informatics not only drives innovation but also bridges the gap between technological potential and practical implementation. [ABSTRACT FROM AUTHOR]

The first books in Polish about the Pascal programming language appeared in the late 1970s, and were soon followed by a Polish translation of Niklaus Wirth's book Algorithms + Data Structures = Programs. At that time, many efforts were made to prepare teachers to teach informatics in schools, and Pascal was one of the topics taught, often with no access to computers. The situation improved significantly after the first informatics curriculum was approved for schools by the Ministry of National Education (MEN) in 1985, in response to the increasing number of microcomputers in schools and students' interest in programming. As a confirmation of the conclusions drawn from the discussion in the ABACUS magazine (1984) on "Which is the best programming language for a first course in computer science," Pascal very quickly became the basic programming language in Polish schools as a tool for practicing algorithmics. The first informatics textbook was published in 1988 and in it, after a short Logo course, Pascal took the main place as a language for developing solutions to algorithmic problems in the form of computer programs. In the following years, many teaching aids were developed for programming education in schools, as well as other aids, e.g., an authoring system, programmed in Pascal. Pascal was the primary programming language in informatics education until the end of the first decade of the 21st century, subsequently replaced by Python. It is interesting that Polish winners of national and international Olympiads in Informatics for many years used Pascal, demonstrating the enormous professional values of this language. In this article we present in detail, among others things: the role and influence of Pascal on the development and level of informatics education in schools in Poland, as well as other scientific activities and initiatives supported by this language. Many students educated in this technical and mental environment found their place in professional development teams in the best computer and technology corporations, and evidently most of them joined the national working force. [ABSTRACT FROM AUTHOR]

The work of Niklaus Wirth, designer of the Pascal programming language, has led to the introduction of programming in schools in many countries often leading to a transformation in the way of thinking. In this article, we provide a retrospective analysis of the Lithuanian experience driven by Pascal and discuss the main ideas about teaching programming originating from this experience. We conducted a qualitative study by means of interviews with experts involved in the development of programming education during its early phases to examine their memories and perspectives. Programming education in Lithuania started with the Pascal-inspired Young Programmers' School by Correspondence, founded in 1981, which had a great influence on the Lithuanian programming elite. For this purpose, a compiler for a subset of Pascal was developed for students taking their first steps towards programming, or more precisely, algorithmic thinking. Many innovations were developed and brought into practice. The ones that have proved their worth and have not lost their relevance are the subject of this article. These include assessing program text readability, cultivating programming style, program reading tasks, creative thinking tasks, problem-solving approaches, detailed compiler error messages, automatic error fixing, and compiler advice to novice programmers. While some concepts became obsolete with technological advancements, others remain relevant, directly or as inspiration for new ideas, forming the basis of this study. [ABSTRACT FROM AUTHOR]

Objective We aimed to evaluate the feasibility of using ChatGPT as programming support for nursing PhD students conducting analyses using the All of Us Researcher Workbench. Materials and Methods 9 students in a PhD-level nursing course were prospectively randomized into 2 groups who used ChatGPT for programming support on alternating assignments in the workbench. Students reported completion time, confidence, and qualitative reflections on barriers, resources used, and the learning process. Results The median completion time was shorter for novices and certain assignments using ChatGPT. In qualitative reflections, students reported ChatGPT helped generate and troubleshoot code and facilitated learning but was occasionally inaccurate. Discussion ChatGPT provided cognitive scaffolding that enabled students to move toward complex programming tasks using the All of Us Researcher Workbench but should be used in combination with other resources. Conclusion Our findings support the feasibility of using ChatGPT to help PhD nursing students use the All of Us Researcher Workbench to pursue novel research directions. [ABSTRACT FROM AUTHOR]

The work of Niklaus Wirth, designer of the Pascal programming language, has led to the introduction of programming in schools in many countries often leading to a transformation in the way of thinking. In this article, we provide a retrospective analysis of the Lithuanian experience driven by Pascal and discuss the main ideas about teaching programming originating from this experience. We conducted a qualitative study by means of interviews with experts involved in the development of programming education during its early phases to examine their memories and perspectives. Programming education in Lithuania started with the Pascal-inspired Young Programmers’ School by Correspondence, founded in 1981, which had a great influence on the Lithuanian programming elite. For this purpose, a compiler for a subset of Pascal was developed for students taking their first steps towards programming, or more precisely, algorithmic thinking. Many innovations were developed and brought into practice. The ones that have proved their worth and have not lost their relevance are the subject of this article. These include assessing program text readability, cultivating programming style, program reading tasks, creative thinking tasks, problem-solving approaches, detailed compiler error messages, automatic error fixing, and compiler advice to novice programmers. While some concepts became obsolete with technological advancements, others remain relevant, directly or as inspiration for new ideas, forming the basis of this study.

The first books in Polish about the Pascal programming language appeared in the late 1970s, and were soon followed by a Polish translation of Niklaus Wirth’s book Algorithms + Data Structures = Programs. At that time, many efforts were made to prepare teachers to teach informatics in schools, and Pascal was one of the topics taught, often with no access to computers. The situation improved significantly after the first informatics curriculum was approved for schools by the Ministry of National Education (MEN) in 1985, in response to the increasing number of microcomputers in schools and students’ interest in programming. As a confirmation of the conclusions drawn from the discussion in the ABACUS magazine (1984) on “Which is the best programming language for a first course in computer science,” Pascal very quickly became the basic programming language in Polish schools as a tool for practicing algorithmics. The first informatics textbook was published in 1988 and in it, after a short Logo course, Pascal took the main place as a language for developing solutions to algorithmic problems in the form of computer programs. In the following years, many teaching aids were developed for programming education in schools, as well as other aids, e.g., an authoring system, programmed in Pascal. Pascal was the primary programming language in informatics education until the end of the first decade of the 21st century, subsequently replaced by Python. It is interesting that Polish winners of national and international Olympiads in Informatics for many years used Pascal, demonstrating the enormous professional values of this language. In this article we present in detail, among others things: the role and influence of Pascal on the development and level of informatics education in schools in Poland, as well as other scientific activities and initiatives supported by this language. Many students educated in this technical and mental environment found their place in professional development teams in the best computer and technology corporations, and evidently most of them joined the national working force.

Superior rodent management is critical to preserve the diversity of wildlife, and to mitigate environmental and social damage. Pest management strategies can employ 21st century methods to balance the human-animal conflict, especially regarding rodents. Non-toxic fertility control has several advantages over the use of poison when the following parameters are true: 1) rate of removal exceeds rate of population increase; 2) compounds do not bioaccumulate in the rodents or the environment; 3) non-lethal method targets both males and females; 4) animals can be detected at low densities; 5) cost analysis favors fertility control over lethality; 6) method has socio-political acceptance. Our fertility control system meets each of these requirements. Utilizing plant-root-based extracts from Tripterygium wilfordii Hook F, we have formulated a proprietary rodent feed pellet that is efficacious in reducing mice and rat populations in multiple settings. The pellets target rodents with a population reduction capacity of 98% that is sustainable over 12 months. The cost of the pellet solution is less than 90% of other fertility control products, and less than 47% of poison products. The functional key to the success of fertility-control approaches is optimizing feeding protocols to achieve maximum population reduction. We have developed an application-based system to provide sustainable cost-effective management. The monitoring system captures consumption and feeder service data. Point-of-entry data validation is enforced. Compliance with the service program is monitored and configurable alerts are issued for outlying events. These data are ingested into a data analytics engine which generates real-time dashboards for oversight and analysis. Administrative features provide user management, project definition and configuration. In-line instructional documentation and pellet supply order forms provide support for field technicians. As a 501(c)3 non-profit charity we are funded by Open Philanthropy to provide the rigorous data sets presented: a 21st century solution to rodent management.

Aim: To describe barriers to implementation of diabetic retinopathy (DR) teleretinal screening programs and artificial intelligence (AI) integration at the University of California (UC). Methods: Institutional representatives from UC Los Angeles, San Diego, San Francisco, Irvine, and Davis were surveyed for the year of their program's initiation, active status at the time of survey (December 2021), number of primary care clinics involved, screening image quality, types of eye providers, image interpretation turnaround time, and billing codes used. Representatives were asked to rate perceptions toward barriers to teleretinal DR screening and AI implementation using a 5-point Likert scale. Results: Four UC campuses had active DR teleretinal screening programs at the time of survey and screened between 246 and 2,123 patients at 1-6 clinics per campus. Sites reported variation between poor-quality photos (

Abstract Many studies have reported the presence of tertiary lymphoid structures (TLSs) in cancer, but the research progress of TLSs in cancer has not been systematically analyzed. Therefore, we analyzed the global scientific knowledge in the field using informatics methods. The results showed that TLSs in cancer have received increasing attention since the 21st century, with an annual publication growth rate of 27.86%. Unsupervised hierarchical clustering based on machine learning further categorized the research features into four clusters, with the cluster related to immunotherapy being considered an emerging cluster. TLSs and immunotherapy were identified as the top two hotspots with the highest occurrence frequency and total link strength. The Walktrap algorithm indicated that “TLSs, carcinoma, prognostic value” and “high endothelial venules, germinal-centers, node-like structures” are important to TLSs but remain underexplored, representing promising research directions. These findings suggest that cancer-related TLSs have brought new insights into antitumor immunity, and targeting TLSs has the potential to transform the landscape of antitumor immunotherapy.

Abstract Background There have been many efforts to expand existing data collection initiatives to include COVID-19 related data. One program that expanded is UK Biobank, a large-scale research and biomedical data collection resource that added several COVID-19 related data fields including questionnaires (exposures and symptoms), viral testing, and serological data. This study aimed to analyze this COVID-19 data to understand how COVID-19 data was collected and how it can be used to attribute COVID-19 and analyze differences in cohorts and time periods. Methods A cohort of COVID-19 infected individuals was defined from the UK Biobank population using viral testing, diagnosis, and self-reported data. Changes over time, from March 2020 to October 2021, in total case counts and changes in case counts by identification source (diagnosis from EHR, measurement from viral testing and self-reported from questionnaire) were also analyzed. For the questionnaires, an analysis of the structure and dynamics of the questionnaires was done which included the amount and type of questions asked, how often and how many individuals answered the questions and what responses were given. In addition, the amount of individuals who provided responses regarding different time segments covered by the questionnaire was calculated along with how often responses changed. The analysis included changes in population level responses over time. The analyses were repeated for COVID and non-COVID individuals and compared responses. Results There were 62 042 distinct participants who had COVID-19, with 49 120 identified through diagnosis, 30 553 identified through viral testing and 934 identified through self-reporting, with many identified in multiple methods. This included vast changes in overall cases and distribution of case data source over time. 6 899 of 9 952 participants completing the exposure questionnaire responded regarding every time period covered by the questionnaire including large changes in response over time. The most common change came for employment situation, which was changed by 74.78% of individuals from the first to last time of asking. On a population level, there were changes as face mask usage increased each successive time period. There were decreases in nearly every COVID-19 symptom from the first to the second questionnaire. When comparing COVID to non-COVID participants, COVID participants were more commonly keyworkers (COVID: 33.76%, non-COVID: 15.00%) and more often lived with young people attending school (61.70%, 45.32%). Conclusion To develop a robust cohort of COVID-19 participants from the UK Biobank population, multiple types of data were needed. The differences based on time and exposures show the important of comprehensive data capture and the utility of COVID-19 related questionnaire data.

Abstract Background Rural populations experience ongoing health inequities with disproportionately high morbidity and mortality rates, but digital health in rural settings is poorly studied. Our research question was: How does digital health influence healthcare outcomes in rural settings? The objective was to identify how digital health capability enables the delivery of outcomes in rural settings according to the quadruple aims of healthcare: population health, patient experience, healthcare costs and provider experience. Methods A multi-site qualitative case study was conducted with interviews and focus groups performed with healthcare staff (n = 93) employed in rural healthcare systems (n = 10) in the state of Queensland, Australia. An evidence-based digital health capability framework and the quadruple aims of healthcare served as classification frameworks for deductive analysis. Theoretical analysis identified the interrelationships among the capability dimensions, and relationships between the capability dimensions and healthcare outcomes. Results Seven highly interrelated digital health capability dimensions were identified from the interviews: governance and management; information technology capability; people, skills, and behaviours; interoperability; strategy; data analytics; consumer centred care. Outcomes were directly influenced by all dimensions except strategy. The interrelationship analysis demonstrated the influence of strategy on all digital health capability dimensions apart from data analytics, where the outcomes of data analytics shaped ongoing strategic efforts. Conclusions The study indicates the need to coordinate improvement efforts targeted across the dimensions of digital capability, optimise data analytics in rural settings to further support strategic decision making, and consider how consumer-centred care could influence digital health capability in rural healthcare services. Digital transformation in rural healthcare settings is likely to contribute to the achievement of the quadruple aims of healthcare if transformation efforts are supported by a clear, resourced digital strategy that is fit-for-purpose to the nuances of rural healthcare delivery.

The research section of the paper explores elementary school students’ satisfaction with informatics. This research was carried out using the American Customer Satisfaction Index (ACSI). Four subscales were used: Expectation, Satisfaction, Quality, and Values. The number of Croatian elementary school pupils investigated (from Brod-Posavina County) is 135 (N). Research results show that pupils have high expectations of informatics, including that it will progressively meet their expectations and help them to receive a quality education. It can also be concluded that the problems once faced by students, such as classroom and equipment quality, are becoming much smaller compared to previous years.

Many studies have reported the presence of tertiary lymphoid structures (TLSs) in cancer, but the research progress of TLSs in cancer has not been systematically analyzed. Therefore, we analyzed the global scientific knowledge in the field using informatics methods. The results showed that TLSs in cancer have received increasing attention since the 21st century, with an annual publication growth rate of 27.86%. Unsupervised hierarchical clustering based on machine learning further categorized the research features into four clusters, with the cluster related to immunotherapy being considered an emerging cluster. TLSs and immunotherapy were identified as the top two hotspots with the highest occurrence frequency and total link strength. The Walktrap algorithm indicated that "TLSs, carcinoma, prognostic value" and "high endothelial venules, germinal-centers, node-like structures" are important to TLSs but remain underexplored, representing promising research directions. These findings suggest that cancer-related TLSs have brought new insights into antitumor immunity, and targeting TLSs has the potential to transform the landscape of antitumor immunotherapy. [ABSTRACT FROM AUTHOR]

Introduction Disease and non-battle injuries (DNBIs) cause substantial losses among military personnel. NATO has monitored DNBIs among its personnel since 1996 using multiple versions of a tool now called EpiNATO-2, but the surveillance system has never been systematically evaluated. Following a request from NATO to the CDC, the objective of this study was to assess surveillance system attributes of EpiNATO-2 using CDC's updated guidelines for evaluating public health surveillance systems. Materials and Methods Between June and October 2022, a literature review and key informant interviews were conducted to assess the following attributes: usefulness, simplicity, flexibility, data quality, acceptability, sensitivity, positive predictive value, representativeness, timeliness, stability, informatics system quality, informatics service quality, and informatics interoperability. Key informant interviews were conducted in Kosovo, Germany, and remotely with EpiNATO-2 users spanning three levels: clinical and data entry personnel (tactical level); regional medical and public health officers (operational level); and senior commanders and other governmental entities (strategic level). Results Fourteen EpiNATO-2 users participated in interviews, representing 3 of the 5 major NATO missions, 3 partner entities, and 7 nationalities. All users (100%) reported that the system did not meet their needs, with most users noting the following challenges: lack of clearly defined system objectives; poor data quality due to ambiguous case definitions and frequently unsubmitted reports (37% missing during January to June 2022); long delay between the occurrence of health events and the availability of corresponding data (≥2 weeks); and an antiquated and inflexible data management system. Overall, performance was deemed unsatisfactory on 11 of the 13 attributes. Conclusions This multinational sample of EpiNATO-2 users at all military levels reported that the system is currently not useful with respect to its stated objectives. Opportunities exist to improve the performance and usefulness of EpiNATO-2: improve case definitions, modernize data infrastructure, and regularly evaluate the surveillance system. [ABSTRACT FROM AUTHOR]

The article in this journal will bring readers more specifically to university students to see easier access to money for additional living expenses. A new perspective when students are more specifically informatics students who are taught and nurtured so that they have skills and knowledge about program development not only live with money given by parents, but with money from the creation and development of their own programs or platforms. Access and dissemination of this journal will be expanded to make it more accessible and useful to all readers not only for informatics students but for prospective students and former students who have dived into the sea of computer code more specifically on the creation and development of programs or platforms. [ABSTRACT FROM AUTHOR]

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