Current hemodialysis (HD) methods inefficiently remove protein-bound uremic toxins (PBUTs) due to their high binding affinity to plasma proteins, mainly albumin. This study aimed to investigate electromagnetic (EM) fields and temperature as potential extracorporeal, non-systemic methods to increase HD PBUT clearance. PBUT release was measured in infusible (caprylate-stabilized) albumin solutions spiked with indoxyl sulfate (IS) using an in vitro dialysis setup including a real-time, in-line IS-sensor. No measurable influence on PBUT release was observed during EM field-tests (f = 1–600 MHz, E <= 1 kV/m), but temperature tests (35–40 °C range) showed an absolute increase in IS free fraction of 0.7%/°C. Furthermore, static equilibrium dialysis tests, including IS, p-cresyl sulfate (pCS) and hippuric acid (HA), showed a free fraction increase for all three PBUTs upon a temperature increase from 37 °C to 43 °C (IS 1.30-fold, pCS 1.12-fold, HA 1.15-fold). Mathematical modeling showed a 1.14-fold decrease in plasma IS concentration after 5 weeks of HD, and exploratory hemocompatibility tests did not reveal pronounced changes over 15 heating cycles at 43 °C under static conditions. Extracorporeal temperature elevation is a promising technique to enhance PBUT removal during hemodialysis, which may be easily combined with current HD machines, does not break sterility, and avoids elevating free PBUTs inside the body.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· SSE@SIGSOFT FSE· 56 citations· ⚡4
This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.
Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson· International Conference on...· 44 citations· ⚡5
It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.