Publications by authors named "B K Zhang"

Ferroptosis combined with photodynamic therapy (PDT) has emerged as a powerful approach to induce cancer cell death by producing and accumulating lethal reactive oxygen species (ROS) in the tumor microenvironment (TME). Despite its efficacy and safety, challenges persist in delivering multiple drugs to the tumor site for enhanced antitumor efficacy and improved tissue targeting. Hence, we designed a method of inducing ferroptosis through laser-mediated and human homologation-specific efficient activation, which is also a ferroptosis therapy with higher safety through ROS-mediated.

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Pediatric high-grade gliomas (pHGGs) are the most common brain malignancies in children and are characterized by blocked differentiation. The epigenetic landscape of pHGGs, particularly the H3K27-altered and H3G34-mutant subtypes, suggests these tumors may be particularly susceptible to strategies that target blocked differentiation. Differentiation therapy aims to overcome this differentiation blockade by promoting glioma cell differentiation into more mature and less malignant cells.

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Considering that the human microbiota plays a critical role in health and disease, an accurate and high-resolution taxonomic classification is thus essential for meaningful microbiome analysis. In this study, we developed an automatic system, named MultiTax pipeline, for generating taxonomy from full-length 16S rRNA sequences using the Genome Taxonomy Database and other existing reference databases. We first constructed the MultiTax-human database, a high-resolution resource specifically designed for human microbiome research and clinical applications.

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Objective: To develop and validate a nomogram model for predicting central venous catheter-related infections (CRI) in patients with maintenance hemodialysis (MHD).

Methods: MHD patients with central venous catheters (CVCs) visiting the outpatient hemodialysis (HD) center of Xuzhou Medical University Affiliated Hospital from January 2020 to December 2023 were retrospectively selected through a HD monitoring system. Patient data were collected, and the patients were divided into training and validation sets in a 7:3 ratio.

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