Safety and toxicity of Iopofosine I 131 (CLR 131) with external beam radiation therapy in recurrent or metastatic head and neck cancer: results of a phase 1 single-centre, open-label, single-arm, dose escalation and dose expansion study.

Background: Re-irradiation of recurrent head and neck cancer (HNC) is often limited by tumour adherence to critical structures and/or radiation tolerance of critical normal tissues. Iopofosine I 131 (CLR 131) is a targeted small molecular phospholipid ether (PLE) drug conjugate that delivers iodine-131 selectively to tumour cells. We conducted a phase 1, single-centre, open-label study to determine whether CLR 131 given with reduced dose of external beam radiation therapy (EBRT) would be tolerable and feasible.

Recommendations for the quantitative basic evaluation of mind-body medicine courses for university students - results of a consensus-based, systematic decision-making process by experts.

Background: There is an increasing range of mind-body medicine (MBM) courses in Germany to support university students in dealing with stress. The evaluation of these varies and often only has a small number of participants due to the limited group size of the courses. The aim of this project was the development of a quantitative basic evaluation that can be used across all sites that conduct MBM courses.

Synaptic-like coupling of macrophages to myofibers regulates muscle repair.

Peripheral injury responses essential for muscle repair and nociception require complex interactions of target tissues, immune cells and primary sensory neurons. Nociceptors and myofibers both react robustly to signals generated from circulating immune cells, which promote repair, growth, and regeneration of muscle while simultaneously modulating peripheral sensitization. Here, we found that macrophages form a synaptic-like contact with myofibers to hasten repair after acute incision injury and to facilitate regeneration after major muscle damage.

Early Detection of Left Ventricular Dysfunction With Machine Learning-Based Strain Imaging in Aortic Stenosis Patients.

Purpose: Aortic stenosis (AS) is a common cardiovascular condition where early detection of left ventricular (LV) dysfunction is essential for timely intervention and optimal management. Current echocardiographic measurements, such as ejection fraction (EF), are insensitive to minor changes in LV function, and strain imaging is typically limited to the global longitudinal strain (GLS) parameter due to robustness issues. This study introduces a novel, fully automatic algorithm to enhance the detection of LV dysfunction in AS patients using multiple strain imaging parameters.

Integrating Contact Tracing Data to Enhance Outbreak Phylodynamic Inference: A Deep Learning Approach.

Phylodynamics is central to understanding infectious disease dynamics through the integration of genomic and epidemiological data. Despite advancements, including the application of deep learning to overcome computational limitations, significant challenges persist due to data inadequacies and statistical unidentifiability of key parameters. These issues are particularly pronounced in poorly resolved phylogenies, commonly observed in outbreaks such as SARS-CoV-2.