Resilience of genetic diversity in forest trees over the Quaternary.

The effect of past environmental changes on the demography and genetic diversity of natural populations remains a contentious issue and has rarely been investigated across multiple, phylogenetically distant species. Here, we perform comparative population genomic analyses and demographic inferences for seven widely distributed and ecologically contrasting European forest tree species based on concerted sampling of 164 populations across their natural ranges. For all seven species, the effective population size, N, increased or remained stable over many glacial cycles and up to 15 million years in the most extreme cases.

7T-high resolution MRI-derived radiomic analysis for the identification of symptomatic intracranial atherosclerotic plaques.

Introduction: High-resolution magnetic resonance imaging (HR-MRI) allows for detailed visualization of intracranial atherosclerotic plaques. Radiomics can be used as a tool for objective quantification of the plaque's characteristics. We analyzed the radiomics features (RFs) obtained from 7 T HR-MRI of patients with intracranial atherosclerotic disease (ICAD) to determine distinct characteristics of culprit and non-culprit plaques.

The use of a recombinant equine chorionic gonadotropin (reCG) in fixed-time AI programs in beef cattle.

The aim of the current study was to evaluate the effect of a novel recombinant eCG (reCG) on pregnancy rates to AI (P/AI) in suckled beef cows of different breeds that were synchronized with an estradiol/progesterone (P4)-based protocol for fixed-time AI (TAI). In experiment 1, 1244 Bos taurus suckled cows were used. On Day 0 all cows received an intravaginal P4 device (600 mg P4) and 2 mg of estradiol benzoate.

Radiomics-Based Predictive Nomogram for Assessing the Risk of Intracranial Aneurysms.

Aneurysm wall enhancement (AWE) has the potential to be used as an imaging biomarker for the risk stratification of intracranial aneurysms (IAs). Radiomics provides a refined approach to quantify and further characterize AWE's textural features. This study examines the performance of AWE quantification combined with clinical information in detecting symptomatic IAs.