High-resolution genomic history of early medieval Europe.

Many known and unknown historical events have remained below detection thresholds of genetic studies because subtle ancestry changes are challenging to reconstruct. Methods based on shared haplotypes and rare variants improve power but are not explicitly temporal and have not been possible to adopt in unbiased ancestry models. Here we develop Twigstats, an approach of time-stratified ancestry analysis that can improve statistical power by an order of magnitude by focusing on coalescences in recent times, while remaining unbiased by population-specific drift.

Effect of Proximal Blood Flow Arrest During Endovascular Thrombectomy (ProFATE): A Multicenter, Blinded-End Point, Randomized Clinical Trial.

Background: The effect of temporary blood flow arrest during endovascular thrombectomy for acute ischemic stroke is uncertain due to the lack of evidence from randomized controlled trials. We aimed to investigate whether temporary blood flow arrest during endovascular thrombectomy using a balloon guide catheter improves intracranial vessel recanalization compared with nonflow arrest.

Methods: The ProFATE trial (Proximal Blood Flow Arrest During Endovascular Thrombectomy) was a multicenter, randomized, participant- and outcome-blinded trial at 4 thrombectomy centers in the United Kingdom.

Machine Learning-based Prognostic Subgrouping of Glioblastoma: A Multi-center Study.

Background: Glioblastoma is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification.

Methods: We developed a highly reproducible, personalized prognostication and clinical subgrouping system using machine learning (ML) on routine clinical data, MRI, and molecular measures from 2,838 demographically diverse patients across 22 institutions and 3 continents. Patients were stratified into favorable, intermediate, and poor prognostic subgroups (I, II, III) using Kaplan-Meier analysis (Cox proportional model and hazard ratios [HR]).

MIBiG 4.0: advancing biosynthetic gene cluster curation through global collaboration.

Specialized or secondary metabolites are small molecules of biological origin, often showing potent biological activities with applications in agriculture, engineering and medicine. Usually, the biosynthesis of these natural products is governed by sets of co-regulated and physically clustered genes known as biosynthetic gene clusters (BGCs). To share information about BGCs in a standardized and machine-readable way, the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard and repository was initiated in 2015.