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The degree to which artificial intelligence healthcare research is informed by data and stakeholders from community settings has not been previously described. As communities are the principal location of healthcare delivery, engaging them could represent an important opportunity to improve scientific quality. This scoping review systematically maps what is known and unknown about community-engaged artificial intelligence research and identifies opportunities to optimize the generalizability of these applications through involvement of community stakeholders and data throughout model development, validation, and implementation. Embase, PubMed, and MEDLINE databases were searched for articles describing artificial intelligence or machine learning healthcare applications with community involvement in model development, validation, or implementation. Model architecture and performance, the nature of community engagement, and barriers or facilitators to community engagement were reported according to PRISMA extension for Scoping Reviews guidelines. Of approximately 10,880 articles describing artificial intelligence healthcare applications, 21 (0.2%) described community involvement. All articles derived data from community settings, most commonly by leveraging existing datasets and sources that included community subjects, and often bolstered by internet-based data acquisition and subject recruitment. Only one article described inclusion of community stakeholders in designing an application-a natural language processing model that detected cases of likely child abuse with 90% accuracy using harmonized electronic health record notes from both hospital and community practice settings. The primary barrier to including community-derived data was small sample sizes, which may have affected 11 of the 21 studies (53%), introducing substantial risk for overfitting that threatens generalizability. Community engagement in artificial intelligence healthcare application development, validation, or implementation is rare. As healthcare delivery occurs primarily in community settings, investigators should consider engaging community stakeholders in user-centered design, usability, and clinical implementation studies to optimize generalizability.

Abstract Cancer cells must develop strategies to adapt to the dynamically changing stresses caused by intrinsic or extrinsic processes, or therapeutic agents. Metabolic adaptability is crucial to mitigate such challenges. Considering metabolism as a central node of adaptability, it is focused on an energy sensor, the AMP‐activated protein kinase (AMPK). In a subtype of pancreatic ductal adenocarcinoma (PDAC) elevated AMPK expression and phosphorylation is identified. Using drug repurposing that combined screening experiments and chemoproteomic affinity profiling, it is identified and characterized PF‐3758309, initially developed as an inhibitor of PAK4, as an AMPK inhibitor. PF‐3758309 shows activity in pre‐clinical PDAC models, including primary patient‐derived organoids. Genetic loss‐of‐function experiments showed that AMPK limits the induction of ferroptosis, and consequently, PF‐3758309 treatment restores the sensitivity toward ferroptosis inducers. The work established a chemical scaffold for the development of specific AMPK‐targeting compounds and deciphered the framework for the development of AMPK inhibitor‐based combination therapies tailored for PDAC.

Abstract Studies have implicated the importance of longwave (LW) cloud‐radiative forcing (CRF) in facilitating or accelerating the upscale development of tropical moist convection. While different cloud types are known to have distinct CRF, their individual roles in driving upscale development through radiative feedback is largely unexplored. Here we examine the hypothesis that CRF from stratiform regions has the greatest positive effect on upscale development of tropical convection. We do so through numerical model experiments using convection‐permitting ensemble WRF (Weather Research and Forecasting) simulations of tropical cyclone formation. Using a new column‐by‐column cloud classification scheme, we identify the contributions of five cloud types (shallow, congestus, and deep convective; and stratiform and anvil clouds). We examine their relative impacts on longwave radiation moist static energy (MSE) variance feedback and test the removal of this forcing in additional mechanism‐denial simulations. Our results indicate the importance stratiform and anvil regions in accelerating convective upscale development.

Introduction Quality of life (QoL) is of paramount importance as an outcome to monitor and guide therapies for people with Parkinson’s disease (PwPD). In particular, due to the heterogeneous symptoms that PwPD may experience during their disease course, QoL can deteriorate not only in patients but also in their caregivers, with a variety of psychosocial consequences. However, there is a lack of longitudinal studies that explore how QoL evolves over time and what factors are significant. Furthermore, holistic approaches that consider bio-psycho-social determinants are rare. In the worst cases, these gaps can lead to suboptimal care and therefore unmet needs for patients and their caregivers, resulting in unnecessary symptom burden and increased healthcare costs for society.Methods and analysis This prospective, longitudinal study will follow 1000 PwPD along with their caregivers for 20 years, with up to 40 semi-annual assessments. Patient data and sample collection will include clinical assessments, self-reported outcome measures focusing on QoL, biospecimen collection and MRI. Caregiver burden will be systematically assessed through self-administered questionnaires. The use of digitised surveys will allow efficient data collection and convenient assessment at home. Our primary objective is to attain a holistic understanding of QoL in PwPD and establish a tool to measure it. The secondary objective is to explore the psycho-social and biological variables associated with QoL of patients and caregivers over the progression of the disease. This will provide key information for diagnostic and prognostic prediction, therapeutic patient stratification and adaptation of therapy in the future.Ethics and dissemination The study was approved by the local ethics committee of the University Hospital of Marburg (study number: 209/19). The results will be disseminated by means of publication in peer-reviewed journals, international conference contributions, annual patient meetings and a dedicated website.Trial registration number German Clinical Trials Register (DRKS00023598).

Abstract Cupriavidus necator, despite lacking direct electron transfer capabilities, demonstrates efficient reduction of various redox mediators in oxygen‐free cultivation within bioelectrochemical systems. This study investigates the reduction site of ferricyanide through inhibition and expression rate analysis of oxygen and nitrate respiration chain complexes, comparing aerobic cultivation conditions with fructose as carbon and electron donor to autotrophic (CO2/H2/O2) and anodic cultivation conditions (fructose/anode). Azide inhibition identified cytochrome c oxidase as the primary complex facilitating electron transfer to ferricyanide, with a secondary role proposed for nitrite reductase NirS, demonstrating a 3.9±1.1‐fold higher expression when exposed to anodic conditions. The 2.9±0.6‐fold increase in the expression of the natural porin OmpA under anodic conditions implies its potential involvement in ferricyanide uptake. Additionally, chemically permeabilizing cell membranes with cetyltrimethylammonium bromide doubles ferricyanide reduction rates without an anode present, offering insights for optimizing redox mediation in C. necator based bioelectrochemical systems. This study opens up new possibilities for the targeted optimization of mediated electron transfer in C. necator and other organisms.

Het heersende oordeel over de praktijk van het naoorlogse rechtsherstel van Joodse tegoeden was decennialang gebaseerd op meer algemene informatie. In 2018 werden de persoonsarchieven van het Nederlandse Beheersinstituut (NBI) openbaar gemaakt. Aan de hand van een steekproef van 600 persoonsdossiers van Joodse ‘afwezigen’ biedt dit artikel belangrijke aanvullende inzichten in de wijze waarop dit rechtsherstel in de periode vanaf 1944 tot 1952 verliep en in hoeverre het bevredigend was. Het onderzoek toont dat bewindvoerders zich zo goed als mogelijk van hun taak kweten en dat het NBI toezicht op hen uitoefende. Tegelijkertijd kostte het bewindvoerders grote moeite om tegoeden terug te krijgen. Zij kregen weinig hulp van het NBI of andere instanties. De houding van het NBI naar de bewindvoerders was afstandelijk, bureaucratisch, op rechtmatigheid gericht en star. Dit bevestigt het gebrek aan erkenning dat de Joodse gemeenschap in de directe naoorlogse periode heeft ervaren.

ABSTRACT The majority of people with dementia live in low or middle-income countries (LMICs) where resources that play a crucial role in brain health, such as quality education, are still not widely available. In Brazil, illiteracy remains a prevalent issue, especially in communities with lower socioeconomic status (SES). The PROAME study set out to explore basic education in illiterate adults as a means to improve cognitive reserve. Objective: This manuscript aims to explore the relationship between SES and learning, as well as cognitive outcomes, in an older illiterate population. Methods: This six-month clinical trial (NCT04473235) involved 108 participants, of which 77 concluded all assessments, enrolled in late-life basic education. SES assessments included Quality of Urban Living Index, Municipal Human Development Index and Household SES calculated for each participant. Cognitive assessments encompassed the Free and Cued Selective Reminding Test (FCSRT), a word list to assess reading, and the Beta III matrix. Results: The sample consisted primarily of women, with a mean age of 58.5. Participants improved their reading (p=0.01) and their FCSRT (p=0.003). Regarding episodic memory, women outperformed men (p=0.007) and younger participants improved more than their older counterparts (p=0.001). There was no association observed between SES and cognitive outcomes. Conclusion: Irrespective of SES, participants demonstrated positive outcomes after attending basic education. These findings highlight that late life education could be an important non-pharmacologic preventative measure, especially in LMICs.

Objective:. To determine whether certain patients are vulnerable to errant triage decisions immediately after major surgery and whether there are unique sociodemographic phenotypes within overtriaged and undertriaged cohorts. Background:. In a fair system, overtriage of low-acuity patients to intensive care units (ICUs) and undertriage of high-acuity patients to general wards would affect all sociodemographic subgroups equally. Methods:. This multicenter, longitudinal cohort study of hospital admissions immediately after major surgery compared hospital mortality and value of care (risk-adjusted mortality/total costs) across 4 cohorts: overtriage (N = 660), risk-matched overtriage controls admitted to general wards (N = 3077), undertriage (N = 2335), and risk-matched undertriage controls admitted to ICUs (N = 4774). K-means clustering identified sociodemographic phenotypes within overtriage and undertriage cohorts. Results:. Compared with controls, overtriaged admissions had a predominance of male patients (56.2% vs 43.1%, P < 0.001) and commercial insurance (6.4% vs 2.5%, P < 0.001); undertriaged admissions had a predominance of Black patients (28.4% vs 24.4%, P < 0.001) and greater socioeconomic deprivation. Overtriage was associated with increased total direct costs [$16.2K ($11.4K–$23.5K) vs $14.1K ($9.1K–$20.7K), P < 0.001] and low value of care; undertriage was associated with increased hospital mortality (1.5% vs 0.7%, P = 0.002) and hospice care (2.2% vs 0.6%, P < 0.001) and low value of care. Unique sociodemographic phenotypes within both overtriage and undertriage cohorts had similar outcomes and value of care, suggesting that triage decisions, rather than patient characteristics, drive outcomes and value of care. Conclusions:. Postoperative triage decisions should ensure equality across sociodemographic groups by anchoring triage decisions to objective patient acuity assessments, circumventing cognitive shortcuts and mitigating bias.

IntroductionThe German health and care system is transforming due to advancing digitalization. New technological applications in nursing, such as social and assistance robotics, artificial intelligence and legal framework conditions are increasingly focused in numerous research projects. However, the approaches to digitalization in nursing are very different. When integrating technologies such as robotics and artificial intelligence into nursing, it is particularly important to ensure that ethical and human aspects are taken into account. A structured classification of the development of digitalization in nursing care is currently hardly possible. In order to be able to adequately deal with this digital transformation, the acquisition of digital competences in nursing education programs is pivotal. These include the confident, critical and creative use of information and communication technologies in a private and professional context. This paper focuses on the question which specific training offers already exist at national and international level for nursing professions to acquire digital competences.MethodsA scoping review according to the PRISMA scheme was conducted in the PubMed and CINAHL databases. The search period for the scoping review extended from 2017 to 2024.ResultsThe selection of the studies took place by inclusion and exclusion criteria and the content-related orientation of the publications. After reviewing the titles and abstracts, eight studies were included. Of these, four were published in German-speaking countries and another four in international English-language journals.DiscussionThe topic of digitization of the nursing professions and the question of how nurses can acquire digital competences is gaining international attention. Nevertheless, the research on explicit continuing education programs for nursing professions is still undifferentiated. No specific continuing education offer for the development of digital competences of nursing professionals was identified. Many authors remained at the meta-level when developing methodological concepts for the acquisition of digital competences. The systematic integration of digitalization into higher education and continuing vocational training is mentioned in the publications. The development of theory- and research-based educational frameworks, which can be used as a basis for curricula in nursing studies and continuing education, is highly recommendable.

In the fall of 2020, due to COVID, our pre-service teachers did not have access to student work samples early in the semester. In order to learn how to assess student learning I reached out to an Arts and Sciences faculty who teaches a freshman course. The Arts and Sciences faculty was a former middle school teacher who was scheduled to talk about the teaching of writing in our methods class. We decided to add using work samples from her current students to provide an assessment experience. This exercise allowed pre-service teachers to create a one-point rubric, analyze student work, give feedback, examine patterns of learning for the whole class, as well as give suggestions for each student based on their work. The practice prepared them for their own fall teaching assignment, and all were able to analyze their students' works successfully.

Abstract Sodium–glucose cotransporter 2 (SGLT2) inhibitors reduce major adverse cardiovascular events (MACE) in type 2 diabetic (T2DM) patients. Pharmacological selectivity of these agents to SGLT2 over SGLT1 is highly variant, with unknown clinical relevance. Genetically reduced SGLT1—but not SGLT2—activity correlates with lower risk of heart failure and mortality, therefore additional non-selective SGLT1 inhibition might be beneficial. In this prespecified meta-analysis, we included 6 randomized, placebo-controlled cardiovascular outcome trials of SGLT2 inhibitors assessing MACE in 57,553 patients with T2DM. Mixed-effects meta-regression revealed that pharmacological selectivity of SGLT2 inhibitors (either as continuous or dichotomized variable) had no significant impact on most outcomes. However, lower SGLT2 selectivity correlated with significantly lower risk of stroke (pseudo-R2 = 78%; p = 0.011). Indeed, dual SGLT1/2 inhibitors significantly reduced the risk of stroke (hazard ratio [HR], 0.78; 95% confidence interval [CI], 0.64–0.94), unlike selective agents (p for interaction = 0.018). The risk of diabetic ketoacidosis and genital infections was higher in both pharmacological groups versus placebo. However, hypotension occurred more often with non-selective SGLT2 inhibitors (odds ratio [OR], 1.87; 95% CI, 1.20–2.92) compared with selective agents (p for interaction = 0.044). In conclusion, dual SGLT1/2 inhibition reduces stroke in high-risk T2DM patients but has limited additional effect on other clinical outcomes.

The rapid advancement of technology related to Industry 4.0 has brought about a paradigm shift in the way we interact with assets across various domains. This progress has led to the emergence of the concept of a Human Digital Twin (HDT), a virtual representation of an individual’s cognitive, psychological, and behavioral characteristics. The HDT has demonstrated potential as a strategic tool for enhancing productivity, safety, and collaboration within the framework of Industry 5.0. In response to this challenge, this paper outlines a process for tracking human cognitive load using the galvanic skin response as a physiological marker and proposes a novel method for managing cognitive load based on the extended Human Asset Administration Shell (HAAS). The proposed HAAS framework integrates real-time data streams from wearable sensors, user skills, contextual information, task specifics, and environmental and surrounding conditions to deliver a comprehensive understanding of an individual’s cognitive state, physical wellness, and skill set. Through the incorporation of skills set, physical, physiological, and psychological variables, and task parameters, the developed HAAS framework enables the identification, management, and development of individual capabilities, thereby facilitating individualized training and knowledge exchange. The applicability of the developed framework is proved by an experiments in the Operator 4.0 laboratory with the detailed HAAS parameters.

Machine learning (ML) revolutionized traditional machine fault detection and identification (FDI), as complex-structured models with well-designed unsupervised learning strategies can detect abnormal patterns from abundant data, which significantly reduces the total cost of ownership. However, their opaqueness raised human concern and intrigued the eXplainable artificial intelligence (XAI) concept. Furthermore, the development of ML-based FDI models can be improved fundamentally with machine learning operations (MLOps) guidelines, enhancing reproducibility and operational quality. This study proposes a framework for the continuous development of ML-based FDI solutions, which contains a general structure to simultaneously visualize and check the performance of the ML model while directing the resource-efficient development process. A use case is conducted on sensor data of a hydraulic system with a simple long short-term memory (LSTM) network. Proposed XAI principles and tools supported the model engineering and monitoring, while additional system optimization can be made regarding input data preparation, feature selection, and model usage. Suggested MLOps principles help developers create a minimum viable solution and involve it in a continuous improvement loop. The promising result motivates further adoption of XAI and MLOps while endorsing the generalization of modern ML-based FDI applications with the HITL concept.

The COVID-19 pandemic has accelerated a transition to flexible remote and hybrid work arrangements. This shift presents a challenge to colleges and universities as they prepare the next generation of STEM professionals in the knowledge economy. This case study of student experiential learning during the time of critical change from the Spring of 2020 through Spring of 2022 focused on how students, typically aged 20-23, contended with their professional development amidst changing patterns in workplace community, culture, and activities. We expected that students would struggle to achieve a greater understanding of situated workplace community practices; however, the data problematised these general assumptions. The findings highlight the variation in student experiences around these themes and are discussed in the context of scaffolding of student internships in intrapersonal, interpersonal, and cognitive domains.

Collaborations between the National Association of Professors of Middle Level Education (NAPOMLE) and European League for Middle Level Education (ELMLE) can be mutually beneficial. This article reflects on NAPOMLE's past experiences with our global affiliate ELMLE and promotes future partnerships expanding our commitment to supporting the development of middle schools and middle level leaders. We advocate a global approach to preparing and empowering the next generation of middle school leaders.

Over the past two years, middle school advocates have been sharing their thoughts on the following prompt: "What drives your spirit and commitment to middle level education?" The purpose has been to capture 'the spirit' of middle school educators?' From these stories five characteristics emerged that can help us consider how to promote the next generation of middle school leaders. Perhaps using the findings from this exercise can help us advocate for the next generation of middle school leaders. For the purpose of this study, middle school refers to those who work with 10-15 year olds and includes intermediate schools, a K-8, middle schools, junior highs, or 9th grade academies.