Empowering personalized oncology: evolution of digital support and visualization tools for molecular tumor boards.

Background: Molecular tumor boards (MTBs) play a pivotal role in personalized oncology, leveraging complex data sets to tailor therapy for cancer patients. The integration of digital support and visualization tools is essential in this rapidly evolving field facing fast-growing data and changing clinical processes. This study addresses the gap in understanding the evolution of software and visualization needs within MTBs and evaluates the current state of digital support.

Dreaming of electrical waves: Generative modeling of cardiac excitation waves using diffusion models.

Electrical waves in the heart form rotating spiral or scroll waves during life-threatening arrhythmias, such as atrial or ventricular fibrillation. The wave dynamics are typically modeled using coupled partial differential equations, which describe reaction-diffusion dynamics in excitable media. More recently, data-driven generative modeling has emerged as an alternative to generate spatio-temporal patterns in physical and biological systems.

Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review.

Background: Understanding the similarities of patients with cancer is essential to advancing personalized medicine, improving patient outcomes, and developing more effective and individualized treatments. It enables researchers to discover important patterns, biomarkers, and treatment strategies that can have a significant impact on cancer research and oncology. In addition, the identification of previously successfully treated patients supports oncologists in making treatment decisions for a new patient who is clinically or molecularly similar to the previous patient.

A Governance Framework for the Implementation and Operation of AI Applications in a University Hospital.

Background: Artificial intelligence (AI) is becoming increasingly important in everyday life and medical care with a notable gap between AI development in medicine there and its practical implementation in university hospitals.

Objective: The aim was to develop a governance framework to guide the procurement and implementation of AI applications in university hospitals.

Methods: Seven role-play expert interviews were conducted with interviewees from two university hospitals, simulating realistic AI system implementation scenarios.

Physicians' Attitudes Towards Artificial Intelligence: Results of the PEAK Project.

Artificial intelligence (AI) is rapidly reshaping the medical field. This study aimed to investigate the attitudes of physicians towards AI in medical care using focus groups. Most participants seemed to be open to the use of AI in medicine if transparency in AI systems is ensured, regulatory barriers are addressed and personal contact to the patient is maintained.

Individualized neoantigen peptide immunization of a metastatic pancreatic cancer patient: a case report of combined tumor and liquid biopsy.

This report details a case of pancreatic cancer with liver metastasis that exhibited a positive immune response to personalized immunization therapy. Our study involved the identification of neoantigens and their corresponding immunogenic peptides using an in-house bioinformatic pipeline. This process included the identification of somatic mutations through DNA/RNA sequencing of solid tumor tissue and blood liquid biopsy.

Dreaming of Electrical Waves: Generative Modeling of Cardiac Excitation Waves using Diffusion Models.

Electrical waves in the heart form rotating spiral or scroll waves during life-threatening arrhythmias such as atrial or ventricular fibrillation. The wave dynamics are typically modeled using coupled partial differential equations, which describe reaction-diffusion dynamics in excitable media. More recently, data-driven generative modeling has emerged as an alternative to generate spatio-temporal patterns in physical and biological systems.

Data Visualization Support for Tumor Boards and Clinical Oncology: Protocol for a Scoping Review.

Background: Complex and expanding data sets in clinical oncology applications require flexible and interactive visualization of patient data to provide the maximum amount of information to physicians and other medical practitioners. Interdisciplinary tumor conferences in particular profit from customized tools to integrate, link, and visualize relevant data from all professions involved.

Objective: The scoping review proposed in this protocol aims to identify and present currently available data visualization tools for tumor boards and related areas.

German primary care data collection projects: a scoping review.

Background: The widespread use of electronic health records (EHRs) has led to a growing number of large routine primary care data collection projects globally, making these records a valuable resource for health services and epidemiological and clinical research. This scoping review aims to comprehensively assess and compare strengths and limitations of all German primary care data collection projects and relevant research publications that extract data directly from practice management systems (PMS).

Methods: A literature search was conducted in the electronic databases in May 2021 and in June 2022.

Extending cBioPortal for Therapy Recommendation Documentation in Molecular Tumor Boards: Development and Usability Study.

Background: In molecular tumor boards (MTBs), patients with rare or advanced cancers are discussed by a multidisciplinary team of health care professionals. Software support for MTBs is lacking; in particular, tools for preparing and documenting MTB therapy recommendations need to be developed.

Objective: We aimed to implement an extension to cBioPortal to provide a tool for the documentation of therapy recommendations from MTB sessions in a secure and standardized manner.

Usability Analysis of a Medication Visualization Tool for Decision Support.

Background: In Germany, patients are entitled to a medication plan. While the overview is useful, it does not contain explicit information on various potential adverse drug events (ADEs). Therefore, physicians must continue to seek information from various sources to ensure medication safety.

Demand Analysis of a German Emergency Medical Service Feedback System.

Background: The number of emergency medical service (EMS) calls in Germany is continuously increasing. The initial assessment, the pre-hospital care and the choice of hospital for further care by the EMS influences the patient's outcome and are the basis for further care in hospital. However, the EMS does not receive any official feedback on its decisions.

MIRACUM-Pipe: An Adaptable Pipeline for Next-Generation Sequencing Analysis, Reporting, and Visualization for Clinical Decision Making.

(1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection.

Improved Survival of a HER2-Positive Metastatic Breast Cancer Patient Following a Personalized Peptide Immunization.

Cancer neoantigens that arise from somatic mutations have emerged as important targets for personalized immunization. Here, we report an improved overall survival of a HER2-positive metastatic breast cancer patient using a bioinformatic-based personalized peptide immunization called BITAP (BioInformatic Tumor Address Peptides). The epitopes were predicted using our in-house bioinformatic pipeline, and the immunogenicity was tested by IFN-γ ELISPOT and intracellular cytokine staining assays.

[BeoNet-Halle-development of a multifunctional database for the automated extraction of healthcare data from general practitioner and specialist practices].

The Beobachtungspraxennetzwerk Halle (BeoNet-Halle) is an innovative database of outpatient care that has been collecting patient data from participating primary care and specialty practices throughout Germany since 2020 and making it available for research and care. The database is set up and maintained by the Institute of Medical Epidemiology, Biometrics and Informatics and the Institute of General Practice and Family Medicine of the Martin Luther University Halle-Wittenberg. Furthermore, the Data Integration Center of the University Medical Center Halle is involved in the project.

Optical mapping of contracting hearts.

Optical mapping is a widely used tool to record and visualize the electrophysiological properties in a variety of myocardial preparations such as Langendorff-perfused isolated hearts, coronary-perfused wedge preparations, and cell culture monolayers. Motion artifact originating from the mechanical contraction of the myocardium creates a significant challenge to performing optical mapping of contracting hearts. Hence, to minimize the motion artifact, cardiac optical mapping studies are mostly performed on non-contracting hearts, where the mechanical contraction is removed using pharmacological excitation-contraction uncouplers.

Direct LDL-C estimation in preschoolers: Practicable first step for FH screening.

Background: Individuals with FH develop cardiovascular disease due to lifelong cumulative exposure to elevated LDL-C. Effective screening for FH is not yet established.

Objective: To evaluate the practicability of a FH screening by measuring directly the LDL-C in preschoolers.

Reconstruction of three-dimensional scroll waves in excitable media from two-dimensional observations using deep neural networks.

Scroll wave dynamics are thought to underlie life-threatening ventricular fibrillation. However, direct observations of three-dimensional electrical scroll waves remain elusive, as there is no direct way to measure action potential wave patterns transmurally throughout the thick ventricular heart muscle. Here we study whether it is possible to reconstruct simulated scroll waves and scroll wave chaos using deep learning.

N-glycosylation Regulates Intrinsic IFN-γ Resistance in Colorectal Cancer: Implications for Immunotherapy.

Background & Aims: Advanced colorectal carcinoma (CRC) is characterized by a high frequency of primary immune evasion and refractoriness to immunotherapy. Given the importance of interferon (IFN)-γ in CRC immunosurveillance, we investigated whether and how acquired IFN-γ resistance in tumor cells would promote tumor growth, and whether IFN-γ sensitivity could be restored.

Methods: Spontaneous and colitis-associated CRC development was induced in mice with a specific IFN-γ pathway inhibition in intestinal epithelial cells.

Repolarization indicates electrical instability in ventricular arrhythmia originating from papillary muscle.

Aims: Cardiac arrhythmia originating from the papillary muscle (PM) can trigger ventricular fibrillation (VF) and cause sudden cardiac death even in the absence of structural heart disease. Most premature ventricular contractions, however, are benign and hitherto difficult to distinguish from a potentially fatal arrhythmia. Altered repolarization characteristics are associated with electrical instability, but electrophysiological changes which precede degeneration into VF are still not fully understood.

Space Weathering Effects in Troilite by Simulated Solar-Wind Hydrogen and Helium Ion Irradiation.

Space weathering is a key process in the interpretation of airless planetary surfaces. As we engage new missions to planetary objects with potentially novel surfaces such as 16 Psyche, there is renewed interest in expanding our knowledge of space weathering effects to a wider variety of analog materials, including the physical/chemical effects of solar-wind ions on planetary regoliths. We have experimentally simulated the effects of solar ions on two polished thick sections of meteoritic troilite (FeS) via irradiation with 1 keV hydrogen (H) and 4 keV helium (He), to investigate effects resulting from different ion species.

Real-Time Optical Mapping of Contracting Cardiac Tissues With GPU-Accelerated Numerical Motion Tracking.

Optical mapping of action potentials or calcium transients in contracting cardiac tissues are challenging because of the severe sensitivity of the measurements to motion. The measurements rely on the accurate numerical tracking and analysis of fluorescence changes emitted by the tissue as it moves, and inaccurate or no tracking can produce motion artifacts and lead to imprecise measurements that can prohibit the analysis of the data. Recently, it was demonstrated that numerical motion-tracking and -stabilization can effectively inhibit motion artifacts, allowing highly detailed simultaneous measurements of electrophysiological phenomena and tissue mechanics.

Attitudes and Acceptance Towards Artificial Intelligence in Medical Care.

Background: Artificial intelligence (AI) in medicine is a very topical issue. As far as the attitudes and perspectives of the different stakeholders in healthcare are concerned, there is still much to be explored.

Objective: Our aim was to determine attitudes and aspects towards acceptance of AI applications from the perspective of physicians in university hospitals.

Searching of Clinical Trials Made Easier in cBioPortal Using Patients' Genetic and Clinical Profiles.

Background: Molecular tumor boards (MTBs) cope with the complexity of an increased usage of genome sequencing data in cancer treatment. As for most of these patients, guideline-based therapy options are exhausted, finding matching clinical trials is crucial. This search process is often performed manually and therefore time consuming and complex due to the heterogeneous and challenging dataset.