Publications by authors named "G K Pang"

Background: Hepcidin, a peptide hormone primarily produced by the liver, regulates iron metabolism by interacting with its receptor, ferroportin. Studies have demonstrated that hepcidin participates in the progression of liver fibrosis by regulating HSC activation, but its regulatory effect on hepatocytes remains largely unknown.

Methods: A carbon tetrachloride (CCl4)-induced liver fibrosis model was established in C57BL/6 wild-type (WT) and hepcidin knockout (Hamp-/-) mice.

View Article and Find Full Text PDF

Background: Preoperative prediction of human epidermal growth factor receptor 2 (HER2)-low expression using magnetic resonance imaging (MRI) can enhance the selection of clinical treatment strategies and enhance patient outcomes. Herein, we investigated the value of a neural network model constructed with multiparametric MRI in diagnosing HER2-low breast cancer.

Methods: This retrospective study involved two different centers.

View Article and Find Full Text PDF

Background: Glioblastoma multiforme (GBM), the most prevalent and aggressive primary brain tumor, poses substantial challenges in both treatment and prognosis. Post-translational modifications, like palmitoylation, are known to have critical roles in the development and progression of glioma. Yet, the molecular mechanisms involved in palmitoylation and its prognostic significance in GBM are still not fully understood.

View Article and Find Full Text PDF

Male-typical behaviors such as aggression and mating, which reflect sexual libido in male mice, are regulated by the hypothalamus, a crucial part of the nervous system. Previous studies have demonstrated that microRNAs (miRNAs), especially , play a vital role in reproduction and the neural control of behaviors. However, it remains unclear whether affects reproduction through the hypothalamus-mediated regulation of male-typical behaviors.

View Article and Find Full Text PDF

Introduction: Chinese Herbal Medicine (CHM), with its deep-rooted history and increasing global recognition, encounters significant challenges in automation for microscopic identification. These challenges stem from limitations in traditional microscopic methods, scarcity of publicly accessible datasets, imbalanced class distributions, and issues with small, unevenly distributed, incomplete, or blurred features in microscopic images.

Methods: To address these challenges, this study proposes a novel deep learning-based approach for Chinese Herbal Medicine Microscopic Identification (CHMMI).

View Article and Find Full Text PDF