Diabetes mellitus requires constant care. The main goal of this is prevention of interference with daily life and prevention of long-term complications. Laboratory methods mostly used include HbAlc and microalbuminuria testing. Several methods exist for these determinations. Moreover, no worldwide standards are available. Studies have shown that with the current techniques improvement of laboratory standardization is clearly required, but have also shown that this is possible even without 'synthetic standards', the ultimate standards which will not be available within the next 3-5 years.
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http://dx.doi.org/10.1159/000053106 | DOI Listing |
Genes Chromosomes Cancer
January 2025
Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Medical Research Center Oulu and Biocenter Oulu, University of Oulu, Oulu, Finland.
Myelodysplastic neoplasia with complex karyotype (CK-MDS) poses significant clinical challenges and is associated with poor survival. Detection of structural variants (SVs) is crucial for diagnosis, prognostication, and treatment decision-making in MDS. However, the current standard-of-care (SOC) cytogenetic testing, relying on karyotyping, often yields ambiguous results in cases with CK.
View Article and Find Full Text PDFPrenat Diagn
January 2025
Key Laboratory of Reproductive Genetics (Ministry of Education) and Department of Reproductive Endocrinology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Prenatal cell-free DNA (cfDNA) screening has advanced significantly, extending beyond detecting aneuploidies to sub-chromosomal copy number variations. However, its application for screening dominant single-gene conditions, often caused by de novo variants, remains underutilized in the general obstetric population. This study reviews recent data and experience on prenatal cfDNA screening for dominant monogenic conditions using multiple-gene panels, highlighting its potential to enhance early detection and management of genetic disorders.
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting millions worldwide, leading to cognitive and functional decline. Early detection and intervention are crucial for enhancing the quality of life of patients and their families. Remote Monitoring Technologies (RMTs) offer a promising solution for early detection by tracking changes in behavioral and cognitive functions, such as memory, language, and problem-solving skills.
View Article and Find Full Text PDFCurr Environ Health Rep
January 2025
School of Health Sciences, Purdue University, West-Lafayette, IN, 47906, USA.
Purpose Of Review: This review explores the use of Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and X-ray Fluorescence (XRF) for quantifying metals and metalloids in biological matrices such as hair, nails, blood, bone, and tissue. It provides a comprehensive overview of these methodologies, detailing their technological limitations, application scopes, and practical considerations for selection in both laboratory and field settings. By examining traditional and novel aspects of each method, this review aims to guide researchers and clinical practitioners in choosing the most suitable analytical tool based on their specific needs for sensitivity, precision, speed, and sample preparation.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China.
Purpose: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pelvic lymph node dissection (ePLND) by preoperative nomograms.
Methods: [Ga]Ga-PSMA-617 PET/CT scan of 116 eligible PCa patients (82 in the training cohort and 34 in the test cohort) who underwent radical prostatectomy with ePLND were analyzed in our study. The Med3D deep learning network was utilized to extract discriminative features from the entire prostate volume of interest on the PET/CT images.
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