Publications by authors named "L O CHANG"

Isoferulic acid (IA), a derivative of cinnamic acid, is derived from Danshen and exhibits anticancer properties by disrupting cancer cell activities. However, its role in pancreatic cancer, the "king of cancer", was unknown. In this study, pancreatic cancer cells were subjected to treatment with IA (6.

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Recurrent fusions drive the pathogenesis of many hematological malignancies. Compared to routine cytogenetic/fluorescence in situ hybridization (FISH) studies, the RNA-based next-generation sequencing (NGS) fusion assay enables the identification of both known and novel fusions. In many cases, these recurrent fusions are crucial for diagnosis and are associated with prognosis, relapse prediction, and therapeutic options.

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The target reservoir is a typical blocky bottom water reservoir. There are several interlayers of varying scales inside it, which impact the characteristics of the oil production and water breakthrough curves of the wells in the water flooding development oilfield, resulting in strong heterogeneity within the reservoir. The Sangtamu Oilfield has an average well spacing of approximately 600 m, causing a challenge in accurately identifying the range of small-scale interlayer spreading.

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Intrauterine adhesion (IUA) is an endometrial damage repair disorder that leads to menstrual loss, amenorrhea, and infertility in women; therefore, addressing this dilemma is a critical challenge. In this study, a multifunctional hydrogel, comprising oxidized sodium alginate (OSA), strontium carbonate (SrCO), and betamethasone 21-phosphate sodium (BSP), was formulated to facilitate angiogenesis, reduce fibrosis, and support tissue repair in the treatment of IUA. The composite hydrogels showed significant bioactivity on human endometrial stromal cells (HESCs) and human umbilical vein endothelial cells (HUVECs), promoting the injured HESCs repair, reversing the degree of fibrosis to a certain extent, and enhancing the proliferation and migration of HUVECs.

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Objective: This paper presents a novel dual-branch framework for estimating blood pressure (BP) using photoplethysmogram (PPG) signals. The method combines deep learning with clinical prior knowledge and models different time periods (morning, afternoon, and evening) to achieve precise, cuffless BP estimation.

Approach: Preprocessed single-channel PPG signals are input into two feature extraction branches.

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