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Immune checkpoint inhibitors have improved the treatment of metastatic renal cell carcinoma (RCC), with the combination of nivolumab (NIVO) and ipilimumab (IPI) showing promising results. However, not all patients benefit from these therapies, emphasizing the need for reliable, easily assessable biomarkers. This multicenter study involved 116 advanced RCC patients treated with NIVO + IPI across nine oncology centers in Poland.

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Effects of photobiomodulation in mitochondrial quantity, biogenesis and mitophagy-associated genes in breast cancer cells.

Lasers Med Sci

January 2025

Departamento de Biofísica e Biometria Instituto de Biologia Roberto Alcântara Gomes, Universidade do Estado do Rio de Janeiro, Avenida 28 de Setembro, 87, fundos, Vila Isabel, Rio de Janeiro, 20551030, Brazil.

In this article, we aim to evaluate the effects of photobiomodulation on mitochondria quantity, biogenesis, and mitophagy-associated genes in breast cancer (BC) cells. Both models were irradiated with a low-power infrared laser (880 nm, 150 mW) and amber LED (617 nm, 1500 mW), alone or simultaneously. We evaluated the mRNA expression of PINK1 and PGC-1α genes, and the mitochondrial number was assessed based on the ratio of mitochondrial DNA/genomic DNA (mtDNA/gDNA).

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Interactions Between Toxic Metals and Serum Micronutrient Level in Auto-mechanics in Ibadan Metropolis, Nigeria: a Pilot study.

Biol Trace Elem Res

January 2025

Laboratory for Toxicology and Micronutrient Metabolism, Chemical Pathology Department, College of Medicine, University of Ibadan, Ibadan, Nigeria.

Auto-mechanics who often work without safety measures are vulnerable to the harmful effects of toxic metals like lead (Pb) and cadmium (Cd). These toxic metals exert their deleterious effect by interacting with the micronutrients at their primary site of action. This study aimed to investigate the effects of toxic metal exposure on serum micronutrient levels of auto-mechanics in Nigeria.

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Currently, the World Health Organization (WHO) grade of meningiomas is determined based on the biopsy results. Therefore, accurate non-invasive preoperative grading could significantly improve treatment planning and patient outcomes. Considering recent advances in machine learning (ML) and deep learning (DL), this meta-analysis aimed to evaluate the performance of these models in predicting the WHO meningioma grade using imaging data.

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