New insights into the dissolution mechanisms of iron oxides and combusted iron particles in oxalic acid.

The influence of oxidation state and crystalline structure on the dissolution mechanisms of both pure iron oxides and combusted iron particles in aqueous oxalic acid (0.5 mol/l) at 60 °C was systematically investigated. Dissolution experiments were carried out in a temperature-controlled, continuous-flow capillary reactor, allowing for the removal of reaction products and thereby suppressing the autocatalytic reaction mechanism.

Machine learning progressive CKD risk prediction model is associated with CKD-mineral bone disorder.

Background: Recently, we developed the machine learning (ML)-based Progressive CKD Risk Classifier (PCRC), which accurately predicts CKD progression within 5 years. While its performance is robust, it is unknown whether PCRC categorization is associated with CKD-mineral bone disorder (CKD-MBD), a critical, yet under-recognized, downstream consequence. Therefore, we aimed to 1) survey real-world testing utilization data for CKD-MBD and 2) evaluate ML-based PCRC categorization with CKD-MBD.

Viscosity Modeling for Blood and Blood Analog Fluids in Narrow Gap and High Reynolds Numbers Flows.

For the optimization of ventricular assist devices (VADs), flow simulations are crucial. Typically, these simulations assume single-phase flow to represent blood flow. However, blood consists of plasma and blood cells, making it a multiphase flow.

Health-related quality of life of adults with spinal muscular atrophy: insights from a nationwide patient registry in Germany.

Purpose: Spinal muscular atrophy (SMA) is a rare, autosomal-recessive disease characterized by progressive muscular atrophy and weakness resulting in substantial disability and short life expectancy. The objective of this cross-sectional study was to assess health-related quality of life (HRQoL) of adults with SMA in Germany in the era of disease-modifying therapy.

Methods: Adults with SMA were recruited via the German national TREAT-NMD SMA patient registry.

Progression from Prediabetes to Diabetes in a Diverse U.S. Population: A Machine Learning Model.

To date, there are no widely implemented machine learning (ML) models that predict progression from prediabetes to diabetes. Addressing this knowledge gap would aid in identifying at-risk patients within this heterogeneous population who may benefit from targeted treatment and management in order to preserve glucose metabolism and prevent adverse outcomes. The objective of this study was to utilize readily available laboratory data to train and test the performance of ML-based predictive risk models for progression from prediabetes to diabetes.