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The increasing role of the allergist in the management of infusion reactions at the Oncology Infusion Center.
Front Allergy
December 2024
Allergy Department, Castellon University General Hospital, Castellon de la Plana, Spain.
Background: Hypersensitivity reactions to chemotherapy disrupt treatment schedules and compromise patient outcomes. Rapid Drug Desensitization (RDD) enables patients to tolerate future treatments after an allergy workup. However, Same-Day Desensitization (SDD) is a novel approach that capitalizes on RDD to allow the continuation of chemotherapy on the same day as the index reaction, preventing treatment delays.
View Article and Find Full Text PDFAdvances in biomarkers for immunotherapy in small-cell lung cancer.
Front Immunol
December 2024
Medical Oncology Translational Research Lab, Jilin Cancer Hospital, Changchun, China.
Small-cell lung cancer (SCLC) is a refractory cancer with rapid growth and high aggressiveness. Extensive-stage SCLC is initially sensitive to chemotherapy; however, drug resistance and recurrence occur rapidly, resulting in a poor survival outcome due to lack of subsequently efficient therapy. The emergence of immune checkpoint inhibitors (ICIs) generated a new landscape of SCLC treatment and significantly prolonged the survival of patients.
View Article and Find Full Text PDFEvidence of compensatory neural hyperactivity in a subgroup of breast cancer survivors treated with chemotherapy and its association with brain aging.
Front Aging Neurosci
December 2024
Division of Adult Health, School of Nursing, University of Texas at Austin, Austin, TX, United States.
Introduction: Chemotherapy-related cognitive impairment (CRCI) remains poorly understood in terms of the mechanisms of cognitive decline. Neural hyperactivity has been reported on average in cancer survivors, but it is unclear which patients demonstrate this neurophenotype, limiting precision medicine in this population.
Methods: We evaluated a retrospective sample of 80 breast cancer survivors and 80 non-cancer controls, aged 35-73, for which we had previously identified and validated three data-driven, biological subgroups (biotypes) of CRCI.
Gut microbes with the genes determine TMAO production from L-carnitine intake and serve as a biomarker for precision nutrition.
Gut Microbes
December 2025
Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
Gut microbial metabolism of L-carnitine, which leads to the production of detrimental trimethylamine N-oxide (TMAO), offers a plausible link between red meat consumption and cardiovascular risks. Several microbial genes, including , the operon, and the recently identified gene cluster, have been implicated in the conversion of dietary L-carnitine into TMA(O). However, the key microbial genes and associated gut microbes involved in this pathway have not been fully explored.
View Article and Find Full Text PDFDifferent association of HDLC, apoA-I, and HDL-C/apoA-I with multiple outcomes in HFrEF patients.
Int J Cardiol
December 2024
Department of Cardiology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou 510120, China; Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou 510120, China; Nanhai Translational Innovation Center of Precision Immunology, Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Foshan 528200, China; Guangdong Province Key Laboratory of Arrhythmia and Electrophysiology, Guangzhou 510120, China. Electronic address:
Background: High-density lipoprotein-cholesterol (HDLC) has been considered a cardioprotective factor for several decades. However, its association with outcomes in patients with heart failure with reduced ejection fraction (HFrEF) remains controversial. We aimed to investigate the association of HDLC, apolipoprotein A-I (apoA-I), and the HDL-C/apoA-I ratio with multiple outcomes of HFrEF patients and establish prognostic models using machine learning methods.
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