Chemical shift encoding based double bonds quantification in triglycerides using deep image prior.

Fatty acid can potentially serve as biomarker for evaluating metabolic disorder and inflammation condition, and quantifying the double bonds is the key for revealing fatty acid information. This study presents an assessment of a deep learning approach utilizing deep image prior (DIP) for the quantification of double bonds and methylene-interrupted double bonds of triglyceride derived from chemical-shift encoded multi-echo gradient echo images, all achieved without the necessity for network training. The methodology implemented a cost function grounded in signal constraints to continually refine the neural network's parameters on a single slice of images through iterative processes.

Real time monitoring of intrarenal pressures while using the flexible and navigable suction ureteral access sheath.

Purpose: To report on in-vivo intrarenal pressure (IRP) during flexible ureteroscopy for treatment of kidney stones while using the novel flexible and navigable suction ureteral access sheath (FANS).

Methods: A retrospective observational analysis was performed for 25 patients undergoing routine flexible ureteroscopy for treatment of renal stones between February 2024 and June 2024 from two centres in Canada. The LithoVue Elite™ ureteroscope (Boston Scientific Corp.

3D-printed poly(ethylene) glycol diacrylate (PEGDA)-chitosan-nanohydroxyapatite scaffolds: Structural characterization and cellular response.

Polymer-based scaffolds with bioactive materials offer great potential in bone tissue engineering. Polyethylene glycol diacrylate (PEGDA) scaffolds fabricated via liquid crystal display 3D printing technique lack inherent osteoconductivity. To improve such properties, chitosan of 10 and 20 wt% and nanohydroxyapatite (nHA) (3-10 wt%) were incorporated into PEGDA scaffolds.