Advanced whole transcriptome sequencing and artificial intelligence/machine learning (AI/ML) in imiquimod-induced psoriasis-like inflammation of human keratinocytes.

Introduction: Although the HaCaT keratinocyte model has been used in previous research to study the effects of antipsoriatic agents, there is still a lack of comprehensive understanding of the mechanism of imiquimod (IMQ)-induced proliferation and signal transduction in psoriasis-like keratinocytes.

Objectives: This study aimed to investigate the molecular mechanisms and pathways associated with psoriasis-like inflammation caused by IMQ in human keratinocytes.

Materials And Methods: HaCaT cells were exposed to different concentrations of IMQ to induce inflammation similar to that observed in psoriasis.

Artificial intelligence-driven prediction and validation of blood-brain barrier permeability and absorption, distribution, metabolism, excretion profiles in natural product research laboratory compounds.

Introduction: Our previous research demonstrated that a large language model (LLM) based on the transformer architecture, specifically the MegaMolBART encoder with an XGBoost classifier, effectively predicts the blood-brain barrier (BBB) permeability of compounds. However, the permeability coefficients of compounds that can traverse this barrier remain unclear. Additionally, the absorption, distribution, metabolism, and excretion (ADME) characteristics of substances obtained from the Natural Product Research Laboratory (NPRL) at China Medical University Hospital (CMUH) have not yet been determined.

Artificial intelligence (AI)-powered bibliometric analysis of global trends in mesenchymal stem cells (MSCs)-derived exosome research: 2014-2023.

Introduction: In recent years, significant progress has been made in regenerative medicine, specifically in using mesenchymal stem cells (MSCs) due to their regenerative and differentiating abilities. An exciting development in this area is the utilization of exosomes derived from MSCs, which have shown promise in tissue restoration, immune system modulation, and cancer treatment.

Objectives: This study aims to analyze global research trends and the academic impact of MSCs-derived exosomes from 2014 to 2023, providing a comprehensive overview of this emerging field.

Integrating natural product research laboratory with artificial intelligence: Advancements and breakthroughs in traditional medicine.

The Natural Product Research Laboratory (NPRL) of China Medical University Hospital (CMUH) was established in collaboration with CMUH and Professor Kuo-Hsiung Lee from the University of North Carolina at Chapel Hill. The laboratory collection features over 6000 natural products worldwide, including pure compounds and semi-synthetic derivatives. This is the most comprehensive and fully operational natural product database in Taiwan.