Protein is modified by carbonyl compound in the Maillard reaction, and the irreversible structure is formed as the advanced glycation end product (AGE). We identified GLAP (glyceraldehyde-derived pyridinium compound) as an AGE formed from glyceraldehyde and lysine residue of protein. In the present study, we investigated detection and determination of GLAP from glycated protein using fluorescence HPLC method. Albumin (BSA) and carbonyls (glyceraldehyde, glycolaldehyde, methylglyoxal, glyoxal, three pentoses or three hexoses) were dissolved in phosphate buffed solution (pH 7.4), and incubated at 37 degrees C for a week. GLAP was formed only in the glyceraldehyde-modified BSA. It is suggested that GLAP was specific AGE derived from glyceraldehyde. In addition, GLAP depressed the intracellular glutathione level and induced the reactive oxygen species (ROS) in HL-60 cells. GLAP caused the oxidative stress. Therefore, GLAP will be a biomarker in the AGE related disease such as diabetic complications or chronic renal failure.
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http://dx.doi.org/10.1002/biof.552210176 | DOI Listing |
Pharmazie
December 2024
Department of Pharmacology and Toxicology, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia.
: Major Depressive Disorder (MDD) is a prevalent and debilitating mental disorder that has been linked to hyperhomocysteinemia and folate deficiency. These conditions are influenced by the methylenetetrahydrofolate reductase () gene, which plays a crucial role in converting homocysteine to methionine and is essential for folate metabolism and neurotransmitter synthesis, including serotonin. : This study explored the association between and polymorphisms among Saudi MDD patients attending the Erada Complex for Mental Health and Erada Services outpatient clinic in Jeddah, Saudi Arabia.
View Article and Find Full Text PDFJ Assist Reprod Genet
January 2025
Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Clinical Sciences, Research Group Genetics, Reproduction and Development, Centre for Medical Genetics, Laarbeeklaan 101, 1090, Brussels, Belgium.
Purpose: Primary ovarian insufficiency (POI) is an important cause of female infertility, stemming from follicle dysfunction or premature oocyte depletion. Pathogenic variants in genes such as NOBOX, GDF9, BMP15, and FSHR have been linked to POI. NOBOX, a transcription factor expressed in oocytes and granulosa cells, plays a pivotal role in folliculogenesis.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.
Analysis of the symmetry of the brain hemispheres at the level of individual structures and dominant tissue features has been the subject of research for many years in the context of improving the effectiveness of imaging methods for the diagnosis of brain tumor, stroke, and Alzheimer's disease, among others. One useful approach is to reliably determine the midline of the brain, which allows comparative analysis of the hemispheres and uncovers information on symmetry/asymmetry in the relevant planes of, for example, CT scans. Therefore, an effective method that is robust to various geometric deformations, artifacts, varying noise characteristics, and natural anatomical variability is sought.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
College of Engineering, Department of Computer Engineering, Koç University, Rumelifeneri Yolu, 34450, Sarıyer, Istanbul, Turkey.
This study explores a transfer learning approach with vision transformers (ViTs) and convolutional neural networks (CNNs) for classifying retinal diseases, specifically diabetic retinopathy, glaucoma, and cataracts, from ophthalmoscopy images. Using a balanced subset of 4217 images and ophthalmology-specific pretrained ViT backbones, this method demonstrates significant improvements in classification accuracy, offering potential for broader applications in medical imaging. Glaucoma, diabetic retinopathy, and cataracts are common eye diseases that can cause vision loss if not treated.
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