NMR Spectral Editing, Water Suppression, and Dipolar Decoupling in Low-Field NMR Spectroscopy Using Optimal Control Pulses and Multiple-Pulse Sequence.

Spectral dispersion in low-field nuclear magnetic resonance (NMR) can significantly affect NMR spectral analysis, particularly when studying complex mixtures like metabolic profiling of biological samples. To address signal superposition in these spectra, we employed spectral editing with selective excitation pulses, proving it to be a suitable approach. Optimal control pulses were implemented in low-field NMR and demonstrated their capability to selectively excite and eliminate specific amino acids, such as phenylalanine and taurine, either individually or simultaneously.

Automated abdominal aortic calcification and major adverse cardiovascular events in people undergoing osteoporosis screening: the Manitoba Bone Mineral Density Registry.

Vertebral fracture assessment (VFA) images from bone density machines enable the automated machine learning assessment of abdominal aortic calcification (ML-AAC), a marker of cardiovascular disease (CVD) risk. The objective of this study was to describe the risk of a major adverse cardiovascular event (MACE, from linked health records) in patients attending routine bone mineral density (BMD) testing and meeting specific criteria based on age, BMD, height loss, or glucocorticoid use have a VFA in the Manitoba Bone Mineral Density Registry. The cohort included 10 250 individuals (mean 75.

GEMLI: Gene Expression Memory-Based Lineage Inference from Single-Cell RNA-Sequencing Datasets.

Gene expression memory-based lineage inference (GEMLI) is a computational tool allowing to predict cell lineages solely from single-cell RNA-sequencing (scRNA-seq) datasets and is publicly available as an R package on GitHub. GEMLI is based on the occurrence of gene expression memory, i.e.

Domain adaptation strategies for 3D reconstruction of the lumbar spine using real fluoroscopy data.

In this study, we address critical barriers hindering the widespread adoption of surgical navigation in orthopedic surgeries due to limitations such as time constraints, cost implications, radiation concerns, and integration within the surgical workflow. Recently, our work X23D showed an approach for generating 3D anatomical models of the spine from only a few intraoperative fluoroscopic images. This approach negates the need for conventional registration-based surgical navigation by creating a direct intraoperative 3D reconstruction of the anatomy.