SLiM 5: Eco-evolutionary simulations across multiple chromosomes and full genomes.

Evolutionary simulations of multiple chromosomes, even up to the scale of full-genome simulations, are becoming increasingly important in population genetics and evolutionary ecology. Unfortunately, the popular simulation framework SLiM has always been intrinsically limited to simulations of a single diploid chromosome. Modeling multiple chromosomes of different types, such as sex chromosomes, has always been cumbersome even with scripting, presenting a substantial barrier to the development of full-genome simulations.

Purifying selection shapes the dynamics of P-element invasion in Drosophila simulans populations.

Background: Transposable elements (TEs) are DNA sequences that can move within a host genome. Many new TE insertions have deleterious effects on their host and are therefore removed by purifying selection. The genomic distribution of TEs thus reflects a balance between new insertions and purifying selection.

Long-term prediction of mortality by heart rate turbulence in hemodialysis patients and the impact of diabetes mellitus-a longitudinal observational study.

Background: Diabetes-driven impaired autonomic nervous system function might contribute to increased mortality in hemodialysis patients. Our study aimed to validate heart rate turbulence as a long-term predictor of mortality in this vulnerable cohort.

Methods: Heart rate turbulence is a non-invasive, 24 h electrocardiography-Holter-based assessment of cardiovascular autonomic responses.

Raising Awareness: Real World Data On Palliative Care for Advanced Pediatric Cancers in Bavaria.

Introduction: Early integration of palliative care in children with cancer provides a variety of positive effects and is recommended at diagnosis. However, barriers often delay its implementation, and palliative care remains underutilized. This study provides real-world data on palliative care and integration in pediatric oncology in a high-income country.

Two-dimensional analysis of plasma-derived extracellular vesicles to determine the HER2 status in breast cancer patients.

Breast cancer, one of the most common cancers in women, is classified by the expression of hormone receptors and the growth factor receptor HER2, which is important for personalised tumour treatment with HER2-targeted therapies. Tumour biopsies are required for histopathological diagnosis of HER2 expression by breast cancer cells but are subject to sampling error. In this study, we present a method for identifying and analysing cancer-derived EVs from plasma for the detection of HER2 expression in breast cancer without the need for additional processing steps.