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BACKGROUND: On February 25, 2022, Russian forces took control of the Chernobyl power plant after continuous fighting within the Chernobyl exclusion zone. Continual events occurred in the month of March, which raised the risk of potential contamination of previously uncontaminated areas and the potential for impacts on human and environmental health. The disruption of war has caused interruptions to normal preventive activities, and radiation monitoring sensors have been nonfunctional. Open-source intelligence can be informative when formal reporting and data are unavailable.
OBJECTIVE: This paper aimed to demonstrate the value of open-source intelligence in Ukraine to identify signals of potential radiological events of health significance during the Ukrainian conflict.
METHODS: Data were collected from search terminology for radiobiological events and acute radiation syndrome detection between February 1 and March 20, 2022, using 2 open-source intelligence (OSINT) systems, EPIWATCH and Epitweetr.
RESULTS: Both EPIWATCH and Epitweetr identified signals of potential radiobiological events throughout Ukraine, particularly on March 4 in Kyiv, Bucha, and Chernobyl.
CONCLUSIONS: Open-source data can provide valuable intelligence and early warning about potential radiation hazards in conditions of war, where formal reporting and mitigation may be lacking, to enable timely emergency and public health responses.

Objective: We evaluated the safety and feasibility of open-source automated insulin delivery AndroidAPS in adolescents and young adults with type 1 diabetes (T1D) and compared its efficacy in three different scenarios: hybrid closed loop (HCL) with meal boluses, meal announcement only (MA), and full closed loop (FCL). Research Design and Methods: In an open-label, prospective, randomized crossover trial (clinicaltrials.gov NCT04835350), 16 adolescents with T1D (10 females) with mean age of 17 years (range 15-20), glycated hemoglobin 56 mmol/mol (range 43-75), and mean duration of diabetes 5.9 years (9-15) underwent three distinct 3-day periods of camp living, comparing the above-mentioned scenarios of AndroidAPS. We used modified and locked version of AndroidAPS 3.1.03, which was called Pancreas4ALL for study purposes. The order of MA and FCL periods was assigned randomly. The primary endpoints were feasibility and safety of the system represented by percentage of time of glucose control by the system and time in hypoglycemia below 3 mmol/L. Results: The glycemia was controlled by the system 95% time of the study and the proportion of time below 3 mmol/L did not exceed 1% over the whole study period (0.72%). The HCL scenario reached significantly higher percentage of time below 3 mmol/L (HCL 1.05% vs. MA 0.0% vs. FCL 0.0%; P = 0.05) compared to other scenarios. No difference was observed among the scenarios in the percentage of time between 3.9 and 10 mmol/L (HCL 83.3% vs. MA 79.85% vs. FCL 81.03%, P = 0.58) corresponding to mean glycemia (HCL 6.65 mmol/L vs. MA 7.34 mmol/L vs. FCL 7.05 mmol/L, P = 0.28). No difference was observed in the mean daily dose of insulin or in the daily carbohydrate intake. No serious adverse event occurred during the study period. Conclusions: Our pilot study showed that FCL might be a realistic mode of treatment for people with T1D.

There is growing awareness of the need for mathematics and computing to quantitatively understand the complex dynamics and feedbacks in the life sciences. Although several institutions and research groups are conducting pioneering multidisciplinary research, communication and education across fields remain a bottleneck. The opportunity is ripe for using education research-supported mechanisms of cross-disciplinary training at the intersection of mathematics, computation, and biology. This case study uses the computational apprenticeship theoretical framework to describe the efforts of a computational biology lab to rapidly prototype, test, and refine a mentorship infrastructure for undergraduate research experiences. We describe the challenges, benefits, and lessons learned, as well as the utility of the computational apprenticeship framework in supporting computational/math students learning and contributing to biology, and biologists in learning computational methods. We also explore implications for undergraduate classroom instruction and cross-disciplinary scientific communication.

Web-based data collection is increasingly popular in both experimental and survey-based research because it is flexible, efficient, and location-independent. While dedicated software for laboratory-based experimentation and online surveys is commonplace, researchers looking to implement experiments in the browser have, heretofore, often had to manually construct their studies\' content and logic using code. We introduce lab.js, a free, open-source experiment builder that makes it easy to build studies for both online and in-laboratory data collection. Through its visual interface, stimuli can be designed and combined into a study without programming, though studies\' appearance and behavior can be fully customized using HTML, CSS, and JavaScript code if required. Presentation and response times are kept and measured with high accuracy and precision heretofore unmatched in browser-based studies. Experiments constructed with lab.js can be run directly on a local computer and published online with ease, with direct deployment to cloud hosting, export to web servers, and integration with popular data collection platforms. Studies can also be shared in an editable format, archived, re-used and adapted, enabling effortless, transparent replications, and thus facilitating open, cumulative science. The software is provided free of charge under an open-source license; further information, code, and extensive documentation are available from https://lab.js.org/ .

Complex regional pain syndrome (CRPS) is a rare and severe chronic pain condition, with effective treatment options not established for many patients. The underlying pathophysiology remains unclear, but there is a growing appreciation for the role of central mechanisms which have formed the basis for brain-based therapies such as transcranial magnetic stimulation and mirror visual feedback (MVF). MVF has been deployed in the treatment of CRPS using both conventional mirrors and virtual reality (VR).
The aim of this study was to further investigate the use of VR in the treatment of patients with unilateral upper limb CRPS. VR has the potential advantage of more flexible and more motivating tasks, as well as the option of tracking patient improvement through the use of movement data.
We describe the development, acceptability, feasibility, and usability of an open-source VR program MVF module designed to be used with consumer VR systems for the treatment of CRPS. The development team was an interdisciplinary group of physical therapists, pain researchers, and VR researchers. Patients recruited from a pain clinic completed 3-5 visits each to trial the system and assessed their experiences in pre- and post-treatment questionnaires.
All 9 (100%) participants were able to use the system for 3, 4, or 5 trials each. None of the participants quit any trial due to cybersickness. All 9 (100%) participants reported interest in using the module in the future. Participants\' reported average pain scores in the affected limb were not significantly different from baseline during treatment or after treatment (P=.16). We did not find a statistically significant effect on participants\' self-reported average pain scores.
We propose that this module could be a useful starting point for modification and testing for other researchers. We share modifications to make this module usable with standalone headsets and finger tracking. Next steps include adapting this module for at-home use, or for use with participants with lower limb pain.

The COVID-19 pandemic poses new challenges to health care providers and the delivery of continuous care. Although many diabetes technologies, such as insulin pumps and continuous glucose monitors, have been established, the data from these devices are rarely assessed. Furthermore, telemedicine has not been sufficiently integrated into clinical workflows.
We sought to remotely support children with type 1 diabetes and their caregivers, enhance the clinical outcomes and quality of life of children with diabetes, increase multiple stakeholders\' engagement with digital care via a participatory approach, evaluate the feasibility of using an interoperable open-source platform in a university hospital setting, and analyze the success factors and barriers of transitioning from conventional care to digital care.
Service design methods were used to adapt clinical workflows. Remote consultations were performed on a monthly and on-demand basis. Diabetes device data were uploaded from patients\' homes to an open-source platform. Clinical and patient-reported outcomes were assessed before, during, and after the COVID-19 lockdown period in Germany.
A total of 28 children with type 1 diabetes and their caregivers enrolled in this study and completed 6 months of remote visits. Of these 28 participants, 16 (57%) also opted to attend at least one of their regular visits remotely. After 3 months of remote visits, participants\' time in range (P=.001) and time in hyperglycemia (P=.004) significantly improved, and their time in hypoglycemia did not increase. These improvements were maintained during the COVID-19 lockdown period (ie, between months 3 and 6 of this study). Participants\' psychosocial health improved after 6 months.
Remote consultations and commonly shared data access can improve the clinical outcomes and quality of life of children with type 1 diabetes, even during challenging circumstances. A service design approach helped with the delivery of comprehensive and holistic solutions that accounted for the needs of multiple stakeholders. Our findings can inform the future integration of digital tools into clinical care during and beyond the pandemic.
German Clinical Trials Register DRKS00016170; https://tinyurl.com/skz4wdk5.

Electronic Health Records (EHRs) are at the heart of reforms aimed at improving the efficiency and quality of healthcare services provided to citizens. Although there is still some skepticism, open source (OS) EHR is a growing phenomenon in health informatics. Given the widespread adoption of OS software (OSS) in several domains, including operating systems, and enterprise systems, the repeated shortfalls faced by healthcare organizations with dominant proprietary EHRs create an opportunity for other alternatives, such as OSS to demonstrate their abilities in addressing these well-documented problems, including inflexibility, high costs, and low interoperability. However, scholars have expressed extensive concerns about the sustainability of OS EHR. Recognizing that OSS project sustainability relies on their governance arrangements, this case study reports on the evolution of the governance and sustainability of a Japanese OS EHR project and provides rich insights to other open source EHR initiative stakeholders, including physicians, developers, researchers, and policy-makers.

OBJECTIVE: To evaluate the accuracy of implant placement position using two different dental implant planning software.
METHODS: A set of Digital Imaging and Communications in Medicine (DICOM) files from a cone beam computed tomography of a patient missing maxillary right first premolar was used. Implant planning was done using two open-source programs: A nondental 3D Slicer/Blender (3DSB) software and a commercial dental implant treatment planning program: Blue Sky Plan 4 (BSP4). An intraoral scan of the same patient was used to create a standard tessellation language (STL) file of the maxillary arch and later printed into 20 identical casts. Ten surgical guides were printed for each group as well. A dental implant (3.8 mm × 12 mm, Biohorizons) was placed into each cast using fully guided surgical protocol. The horizontal displacements at the implant cervical platform and at the implant apex as well as the angulation displacements were measured using digital scanning of the implant scan bodies and were analyzed using a 3D compare software. Statistical analyses were conducted (⍺ = 0.05) using t-test and F-test to examine differences in trueness and precision, respectively.
RESULTS: The average horizontal deviations for the platform and the apex, respectively, were 0.33 ± 0.12 mm and 0.76 ± 0.30 mm for 3DSB and 0.44 ± 0.21 mm and 0.98 ± 0.48 mm for BSP4. The average angulation deviations for 3DSB and BSB4 were 2.34 ± 0.93° and 3.07 ± 1.57°, respectively. There were no statistical differences in the means (t-test) of the platform, apex, and angulation deviations (p = 0.16, p = 0.19, and p = 0.18, respectively). There were statistical differences in the variances (F test) of the platform (p = 0.043) and angulation (p = 0.049) deviations but not the apex (p = 0.059) deviations.
CONCLUSIONS: The combination of nondental open-source software, 3D Slicer/Blender can be used to plan implant guided surgery with an accuracy similar to commercial dental software with slightly higher precision. Open-source nondental software can be considered as an alternative in dental implant treatment planning and guided surgery.

OBJECTIVE: A contour propagation study has been conducted to benchmark three algorithms for Deformable Image Registration (DIR) freely available online against well-established commercial solutions.
METHODS: ElastiX, BRAINS and Plastimach, available as modules in the open source platform 3DSlicer, were tested as the recent AAPM Task group 132 guidelines proposes. The overlap of the DIR-mapped ROIs in four computational anthropomorphic phantoms was measured. To avoid bias every algorithm was left to run without any human interaction nor particular registration strategy. The accuracy of the algorithms was measured using the Dice Similarity Coefficient (DSC) and Mean Distance to Conformity (MDC) metrics. The registration quality was compared to the recommended geometrical accuracy suggested by AAPM TG132 and to the results of a large population-based study performed with commercial DIR solutions.
RESULTS: The considered free-to-use DIR solutions generally meet acceptable accuracy and good overlap (DSC > 0.85). Mild failures (DSC < 0.75) were detected only for the smallest structures. In case of extremely severe deformations acceptable accuracy was not met (MDC > 3 mm). The morphing capability of the tested algorithms equals those of commercial systems when the user interaction is avoided. Underperformances were detected only in cases where a specific registration strategy is mandatory to obtain a satisfying match.
CONCLUSIONS: All of the considered algorithms show performances not inferior to previously published data and have the potential to be good candidates for use in the clinical routine. The results and conclusions only apply to the considered phantoms and should not be considered to be generally applicable and extendable to patient cases.