Publications by authors named "C T Kao"

Background: Obesity is a risk factor for developing cancer but is also associated with improved outcomes after treatment with immune checkpoint inhibitors (ICIs), a phenomenon called the obesity paradox. To interrogate mechanisms of divergent immune responses in obese and non-obese patients, we examined the relationship among obesity status, clinical responses, and immune profiles from a diverse, pan-tumor cohort of patients treated with ICI-based therapy.

Methods: From June 2021 to March 2023, we prospectively collected serial peripheral blood samples from patients with advanced or metastatic solid tumors who received ICI as standard of care at Johns Hopkins.

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An 8-week regimen of glecaprevir/pibrentasvir is recommended for treatment-naïve patients with chronic hepatitis C (CHC). In alignment with the Taiwanese government's objective to eliminate hepatitis C by 2025, this study aimed to provide real-world evidence on the use of this regimen in treatment-naïve patients with chronic kidney disease (CKD) by using data from the Taiwan Association for the Study of the Liver HCV Registry (TACR). CKD was defined by an estimated glomerular filtration rate (eGFR) of <60 mL/min/1.

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Direct sampling mass spectrometry (MS) has rapidly advanced with the development of ambient ionization MS techniques. Swab touch-spray (TS)-MS has shown promise for rapid clinical diagnostics. However, commercially available swabs are notorious for their high background signals, particularly in the positive ionization mode.

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Background: Caffeic acid phenethyl ester (CAPE) is the main bioactive component of poplar type propolis. We previously reported that treatment with caffeic acid phenethyl ester (CAPE) suppressed the cell proliferation, tumor growth, as well as migration and invasion of prostate cancer (PCa) cells via inhibition of signaling pathways of AKT, c-Myc, Wnt and EGFR. We also demonstrated that combined treatment of CAPE and docetaxel altered the genes involved in glycolysis and tricarboxylic acid (TCA) cycle.

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Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans.

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