Leukemia in users of contemporary hormonal contraception: A nationwide registry-based cohort study among premenopausal women in Denmark. [PDF]
Hemmingsen CH +6 more
europepmc +1 more source
Two‐photon polymerization enables high‐resolution microfabrication, but performing alignment when printing multiple structures is difficult. Here, we present a fast, robust, and open‐source protocol for automated alignment on Nanoscribe systems. Achieving ≈0.4 μm accuracy in under 5 s, our protocol reduces time and error in multimaterial printing. This
Daniel Maher +4 more
wiley +1 more source
Patient experiences with group consultations when treated with semaglutide for obesity: a qualitative case study in a Danish general practice. [PDF]
Dahl-Larsen R +4 more
europepmc +1 more source
This article describes a multimodal fusion data acquisition and processing system about electromyography for dynamic movement recognition and bioelectrical impedance for key posture recognition. In addition, a new dynamic–static fusion algorithm strategy is designed.
Chenhao Cao +5 more
wiley +1 more source
Melatonin for chronic back pain (the MOCHA trial): study protocol for a randomized, double-blind, placebo-controlled trial. [PDF]
Kilic K +8 more
europepmc +1 more source
Job Satisfaction as an Assessment Criterion of Labor Market Policy Efficiency. Lesson for Poland from International Experience [PDF]
Kwiatkowska-Ciotucha, Dorota +1 more
core
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng +7 more
wiley +1 more source
Association of Fibrin Clot Characteristics with Development of Ischemic Stroke in Patients with Recently Diagnosed Type 2 Diabetes. [PDF]
Daugaard N +6 more
europepmc +1 more source
Comparing the Latent Features of Universal Machine‐Learning Interatomic Potentials
This study quantitatively assesses how universal machine‐learning interatomic potentials encode the chemical space into latent features, showing unique model‐specific representations with high cross‐model reconstruction errors. It explores how training datasets, protocols, and targets affect these encodings.
Sofiia Chorna +5 more
wiley +1 more source

