Corrigendum: Research progress of gut microbiome and diabetic nephropathy.

[This corrects the article DOI: 10.3389/fmed.2024.

[Short-term efficacy of rituximab in children with calcineurin inhibitor resistant steroid resistant nephrotic syndrome].

To investigate the short-term efficacy and safety of rituximab (RTX) in children with calcineurin inhibitor (CNI) resistant steroid resistant nephrotic syndrome (SRNS). A retrospective case analysis was conducted. Thirteen children with CNI resistant SRNS who were regularly treated with RTX (375 mg/m per dose (maximum dose 500 mg), 1 dose per week, a total of 4 doses) in Department of Nephrology, Children's Hospital of Fudan University from January 2016 to December 2023 were enrolled.

Characterization of a 4'-O-rhamnosyltransferase and de novo biosynthesis of bioactive steroidal triglycosides from Paris polyphylla.

Steroidal saponins in Paris polyphylla featuring complicated sugar chains exhibit notable biological activities, but the sugar chain biosynthesis is still not fully understood. Here, we identified a 4'-O-rhamnosyltransferase (UGT73DY2) from P. polyphylla, which catalyzes the 4'-O-rhamnosylation of polyphyllins V and VI, producing dioscin and pennogenin 3-O-β-chacotrioside, respectively.

Kinetic-pharmacodynamic model to predict post-rituximab B-cell repletion as a predictor of relapse in pediatric idiopathic nephrotic syndrome.

Purpose: Rituximab has proven efficacy in children with idiopathic nephrotic syndrome (INS). However, vast majority of children inevitably experience relapse with B-cell repletion, necessitating repeat course of rituximab, which may increase the risk of adverse effects. The timing of additional dosing and optional dosing regimen of rituximab in pediatric patients with INS have yet to be determined.

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.