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A 40-year-old man was referred for evaluation of cough of a few weeks duration and a history of recurrent respiratory tract infections for several years. Clinical examination revealed no abnormalities. Routine hematologic and biochemical evaluation were normal. Contrast-enhanced computed tomography of the thorax showed a hypoplastic right lung, hyperinflation of the left lung with cardiomediastinal shift to the right. Absence of the right pulmonary artery was noted and replaced by an extensive collateral network of hypertrophied vessels originating from bronchial, intercostal and mammaria interna arteries, and right arteria subclavia (Fig. A, B). Discrete bronchiectasis with thickened bronchial walls in a hypoplastic right lung was noted (Fig. C). A normal bronchial tree and normal parenchyma in the left lung was seen.

Aims: As transcatheter mitral valve (MV) interventions are expanding and more device types and sizes become available, a tool supporting operators in pre-procedural planning and the clinical decision-making process is highly desirable. We sought to develop a finite element computational simulation model to predict the results of transcatheter edge-to-edge repair (TEER) interventions., Methods and Results: We prospectively enrolled patients with secondary mitral regurgitation (MR) referred for a clinically indicated TEER. The 3D trans-oesophageal echocardiograms performed at the beginning of the procedure were used to perform the simulation. On the 3D dynamic model of the MV that was first obtained, we simulated the clip implantation using the same clip type, size, number, and implantation location that was used during the intervention. The 3D model of the MV obtained after the simulation of the clip implantation was compared with the clinical results obtained at the end of the intervention. We analysed the degree and location of residual MR and the shape and area of the diastolic MV area. We performed computational simulation on five patients. Overall, the simulated models predicted well the degree and location of the residual regurgitant orifice(s) but tended to underestimate the diastolic mitral orifice area., Conclusion: In this proof-of-concept study, we present preliminary results on our algorithm simulating clip implantation in five patients with functional MR. We show promising results regarding the feasibility and accuracy in terms of predicting residual MR and the need to improve the estimation of the diastolic MV area., Competing Interests: Conflict of interest: D.M.-Z. is a consultant for PrediSurge and receives research grants from Edwards Lifesciences. J.M., M.P., and F.C. are PrediSurge employees. J.D. received speaker and proctoring fees from Abbott. M.N. is a proctor for Abbott vascular, Boston Scientific, and Medtronic and received consulting fees from Boston Scientific, Abbott vascular, Medtronic, and Robocath. D.A. is a proctor for Abbott and also received speaker fees. M.K. received speaker and proctoring fees from Abbott and GEHC. S.G. is a proctor for Medtronic and Abbott. R.P. is a proctor for Abbott. M.H. received consultant fees from Abbott. J.-N.A. is the chairman of PrediSurge. A.E., F.L., Y.L.d. R.H., I.G.B., A.D., D.N., M.L., V.C., and T.M. none declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Until recently the application of artificial intelligence (AI) in precision oncology was confined to activities in drug development and had limited impact on the personalisation of therapy. Now, a number of approaches have been proposed for the personalisation of drug and cell therapies with AI applied to therapy design, planning and delivery at the patient's bedside. Some drug and cell-based therapies are already tuneable to the individual to optimise efficacy, to reduce toxicity, to adapt the dosing regime, to design combination therapy approaches and, preclinically, even to personalise the receptor design of cell therapies. Developments in AI-based healthcare are accelerating through the adoption of foundation models, and generalist medical AI models have been proposed. The application of these approaches in therapy design is already being explored and realistic short-term advances include the application to the personalised design and delivery of drugs and cell therapies. With this pace of development, the limiting step to adoption will likely be the capacity and appropriateness of regulatory frameworks. This article explores emerging concepts and new ideas for the regulation of AI-enabled personalised cancer therapies in the context of existing and in development governance frameworks., (© 2024. The Author(s).)

Digital health tools, platforms, and artificial intelligence- or machine learning-based clinical decision support systems are increasingly part of health delivery approaches, with an ever-greater degree of system interaction. Critical to the successful deployment of these tools is their functional integration into existing clinical routines and workflows. This depends on system interoperability and on intuitive and safe user interface design. The importance of minimizing emergent workflow stress through human factors research and purposeful design for integration cannot be overstated. Usability of tools in practice is as important as algorithm quality. Regulatory and health technology assessment frameworks recognize the importance of these factors to a certain extent, but their focus remains mainly on the individual product rather than on emergent system and workflow effects. The measurement of performance and user experience has so far been performed in ad hoc, nonstandardized ways by individual actors using their own evaluation approaches. We propose that a standard framework for system-level and holistic evaluation could be built into interacting digital systems to enable systematic and standardized system-wide, multiproduct, postmarket surveillance and technology assessment. Such a system could be made available to developers through regulatory or assessment bodies as an application programming interface and could be a requirement for digital tool certification, just as interoperability is. This would enable health systems and tool developers to collect system-level data directly from real device use cases, enabling the controlled and safe delivery of systematic quality assessment or improvement studies suitable for the complexity and interconnectedness of clinical workflows using developing digital health technologies., (©Cindy Welzel, Fabienne Cotte, Magdalena Wekenborg, Baptiste Vasey, Peter McCulloch, Stephen Gilbert. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.12.2023.)

Background: Increasing use of emergency departments (EDs) by patients with low urgency, combined with limited availability of medical staff, results in extended waiting times and delayed care. Technological approaches could possibly increase efficiency by providing urgency advice and symptom assessments., Objective: The purpose of this study is to evaluate the safety of urgency advice provided by a symptom assessment app, Ada, in an ED., Methods: The study was conducted at the interdisciplinary ED of Marburg University Hospital, with data collection performed between August 2019 and March 2020. This study had a single-center cross-sectional prospective observational design and included 378 patients. The app's urgency recommendation was compared with an established triage concept (Manchester Triage System [MTS]), including patients from the lower 3 MTS categories only. For all patients who were undertriaged, an expert physician panel assessed the case to detect potential avoidable hazardous situations (AHSs)., Results: Of 378 participants, 344 (91%) were triaged the same or more conservatively and 34 (8.9%) were undertriaged by the app. Of the 378 patients, 14 (3.7%) had received safe advice determined by the expert panel and 20 (5.3%) were considered to be potential AHS. Therefore, the assessment could be considered safe in 94.7% (358/378) of the patients when compared with the MTS assessment. From the 3 lowest MTS categories, 43.4% (164/378) of patients were not considered as emergency cases by the app, but could have been safely treated by a general practitioner or would not have required a physician consultation at all., Conclusions: The app provided urgency advice after patient self-triage that has a high rate of safety, a rate of undertriage, and a rate of triage with potential to be an AHS, equivalent to telephone triage by health care professionals while still being more conservative than direct ED triage. A large proportion of patients in the ED were not considered as emergency cases, which could possibly relieve ED burden if used at home. Further research should be conducted in the at-home setting to evaluate this hypothesis., Trial Registration: German Clinical Trial Registration DRKS00024909; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00024909., (©Fabienne Cotte, Tobias Mueller, Stephen Gilbert, Bibiana Blümke, Jan Multmeier, Martin Christian Hirsch, Paul Wicks, Joseph Wolanski, Darja Tutschkow, Carmen Schade Brittinger, Lars Timmermann, Andreas Jerrentrup. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 28.03.2022.)

Background: Establishing rapport and empathy between patients and their health care provider is important but challenging in the context of a busy and crowded emergency department (ED)., Objective: We explore the hypotheses that rapport building, documentation, and time efficiency might be improved in the ED by providing patients a digital tool that uses Bayesian reasoning-based techniques to gather relevant symptoms and history for handover to clinicians., Methods: A 2-phase pilot evaluation was carried out in the ED of a German tertiary referral and major trauma hospital that treats an average of 120 patients daily. Phase 1 observations guided iterative improvement of the digital tool, which was then further evaluated in phase 2. All patients who were willing and able to provide consent were invited to participate, excluding those with severe injury or illness requiring immediate treatment, with traumatic injury, incapable of completing a health assessment, and aged <18 years. Over an 18-day period with 1699 patients presenting to the ED, 815 (47.96%) were eligible based on triage level. With available recruitment staff, 135 were approached, of whom 81 (60%) were included in the study. In a mixed methods evaluation, patients entered information into the tool, accessed by clinicians through a dashboard. All users completed evaluation Likert-scale questionnaires rating the tool's performance. The feasibility of a larger trial was evaluated through rates of recruitment and questionnaire completion., Results: Respondents strongly endorsed the tool for facilitating conversation (61/81, 75% of patients, 57/78, 73% of physician ratings, and 10/10, 100% of nurse ratings). Most nurses judged the tool as potentially time saving, whereas most physicians only agreed for a subset of medical specialties (eg, surgery). Patients reported high usability and understood the tool's questions. The tool was recommended by most patients (63/81, 78%), in 53% (41/77) of physician ratings, and in 76% (61/80) of nurse ratings. Questionnaire completion rates were 100% (81/81) by patients and 96% (78/81 enrolled patients) by physicians., Conclusions: This pilot confirmed that a larger study in the setting would be feasible. The tool has clear potential to improve patient-health care provider interaction and could also contribute to ED efficiency savings. Future research and development will extend the range of patients for whom the history-taking tool has clinical utility., Trial Registration: German Clinical Trials Register DRKS00024115; https://drks.de/drks&#95;web/navigate.do?navigationId=trial.HTML&TRIAL&#95;ID=DRKS00024115., (©Justus Scheder-Bieschin, Bibiana Blümke, Erwin de Buijzer, Fabienne Cotte, Fabian Echterdiek, Júlia Nacsa, Marta Ondresik, Matthias Ott, Gregor Paul, Tobias Schilling, Anne Schmitt, Paul Wicks, Stephen Gilbert. Originally published in JMIR Formative Research (https://formative.jmir.org), 07.02.2022.)

The cultivation of wheat (Triticum aestivum L.) was performed in controlled environment chambers with the continuous monitoring of photosynthesis, dark respiration, transpiration and main nutrient uptakes. A protocol in twin chambers was developed to compare the specific effects of low O2 and high CO2. Each parameter is able to influence photosynthesis but different effects are obtained In the development, fructification and seed production, because of the different effects of each parameter on the ratio of reductive to oxidative cycle of carbon. The first main conclusion is that low level of O2, at the same rate of biomass production, strongly acts on the rate of ear appearance and on seed production. Ear appearance was delayed and seed production reduced with a low O2 treatment (approximately 4%). The O2 effect was not mainly due to the repression of the oxidative cycle. The high CO2 treatment (700 to 900 microl l-1) delayed ear appearance by 4 days but did not reduce seed production. High CO2 treatment also reduced transpiration by 20%. Two hypothesis were proposed to explain the similarities and the difference in the O2 and CO2 effects on the growth of wheat.