Publications by authors named "Fengyuan Zou"
Article Synopsis
- Recent advancements in wearable hydrogel sensors emphasize their high stretchability and improved mechanical properties compared to traditional hydrogels, which are often weak and unstable.
- A new ice crystal extrusion-crosslinking method has been developed to create a polyvinyl alcohol (PVA) hydrogel that incorporates conductive elements and tough polymer segments, resulting in enhanced hydrogen bonding and stability.
- The resulting optimal hydrogel sensor shows impressive structural stability, high sensitivity, a wide operating temperature range, and durability, making it suitable for applications like monitoring human movement and detecting ammonia for health and environmental purposes.
Nylon fibers have great potentials in smart textiles due to excellent wear resistance, resilience, and chemical stability, whereas poor combination between fibers and conductive materials causes discontinuous signal capture. In this work, nylon fibers/di-aldehyde cellulose nanocrystals/polypyrrole (NFACP) biosensors with robust scrub-resistant and signal-capture ability were fabricated by interfacial multiple covalent reactions. The best NFACP biosensor exhibited high conductivity (354 S/m), robust mechanical strength and stretching-releasing dynamic durability.
View Article and Find Full Text PDFObjectives: To determine the factors that affect recurrent stroke after acute ischemic stroke, specifically between male and female groups.
Methods: We examined relative factors associated with recurrent stroke in Chinese patients with first-ever ischemic stroke. LASSO (least absolute shrinkage and selection operator) Cox regression were used to determine the predictors of recurrent stroke in the male and female groups.
Background: Postoperative sepsis is one of the main causes of mortality after liver transplantation (LT). Our study aimed to develop and validate a predictive model for postoperative sepsis within 7 d in LT recipients using machine learning (ML) technology.
Methods: Data of 786 patients received LT from January 2015 to January 2020 was retrospectively extracted from the big data platform of Third Affiliated Hospital of Sun Yat-sen University.
Objective: To develop and validate a simple-to-use prognostic scoring model based on clinical and pathological features which can predict overall survival (OS) of patients with oral squamous cell carcinoma (OSCC) and facilitate personalized treatment planning.
Materials And Methods: OSCC patients (n = 404) from a public hospital were divided into a training cohort (n = 282) and an internal validation cohort (n = 122). A total of 12 clinical and pathological features were included in Kaplan-Meier analysis to identify the factors associated with OS.