Background: The GH-2000 project developed a method for detecting GH misuse based on the measurement of insulin-like growth factor-I (IGF-I) and the amino-terminal pro-peptide of type III collagen (P-III-NP). The objective of this study was to develop decision limits for the GH-2000 score to detect GH misuse in elite athletes using two currently available commercial assays for each analyte.
Subjects: 404 male (mean age 23.9 yrs, range 12-37 yrs) and 94 female elite athletes (mean age 24.5 yrs, range 18-34 yrs) participated. Blood samples were collected according to World Anti-Doping Agency (WADA) guidelines at various sporting events including 238 samples collected as part of the UK Anti-Doping Testing Programme. Laboratory analysis: IGF-I was measured by Siemens Immulite IGF-I assay and Immunotech A15729 IGF-I IRMA. P-III-NP was measured by RIA-gnost P-III-P and the UniQ™ PIIINP RIA.
Statistical Analysis: The GH-2000 score decision limits were developed through the analysis of the elite athlete samples.
Results: For males and females separately, the distributions of GH-2000 scores were consistent with Normal distributions. Using a specificity of 99.99% new decision limits were determined which included an allowance for uncertainty associated with calculations based on a finite sample size. One outlier was identified with results incompatible with normal physiology and tested positive with the current isoform GH test.
Conclusions: We have developed decision limits using currently available commercial assays to measure IGF-I and P-III-NP in elite athletes. This should allow the introduction of a test for GH misuse based on the measurement of these GH sensitive biomarkers.
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http://dx.doi.org/10.1016/j.ghir.2011.12.005 | DOI Listing |
Curr Opin Crit Care
January 2025
Department of Critical Care Medicine.
Purpose Of Review: Neuroprognostication after acute brain injury (ABI) is complex. In this review, we examine the threats to accurate neuroprognostication, discuss strategies to mitigate the self-fulfilling prophecy, and how to approach the indeterminate prognosis.
Recent Findings: The goal of neuroprognostication is to provide a timely and accurate prediction of a patient's neurologic outcome so treatment can proceed in accordance with a patient's values and preferences.
Cell Regen
January 2025
Guangzhou National Laboratory, Guangzhou, 510005, China.
Organoid technology provides a transformative approach to understand human physiology and pathology, offering valuable insights for scientific research and therapeutic development. Human gastric organoids, in particular, have gained significant interest for applications in disease modeling, drug discovery, and studies of tissue regeneration and homeostasis. However, the lack of standardized quality control has limited their extensive clinical applications.
View Article and Find Full Text PDFRheumatol Ther
January 2025
LBAI, UMR1227, Univ Brest, Inserm, Brest, France.
Introduction: Celiac disease (CD) affects the small intestine, leading to a progressive disappearance of intestinal villi, and can be found in association with several other autoimmune and inflammatory conditions. The main objective of this study was to determine the prevalence and the clinical significance of anti-transglutaminase and anti-endomysium antibodies in patients diagnosed with early rheumatoid arthritis (RA) and spondyloarthritis (SpA).
Methods: We measured anti-transglutaminase and anti-endomysium antibodies in biobanked serum samples at inclusion in two French prospective multicenter cohorts of patients with suspected early rheumatoid arthritis (ESPOIR, n = 713) and spondyloarthritis (DESIR, n = 709).
Environ Monit Assess
January 2025
Department of Environmental Management, Graduate School of Agriculture, Kindai University, Nara, Japan.
Efficient agricultural management often relies on farmers' experiential knowledge and demands considerable labor, particularly in regions with challenging terrains. To reduce these burdens, the adoption of smart technologies has garnered increasing attention. This study proposes a convolutional neural network (CNN)-based model as a decision-support tool for smart irrigation in orchard systems, focusing on persimmon cultivation in mountainous regions.
View Article and Find Full Text PDFJ Clin Microbiol
January 2025
Department of Pathology and Immunology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA.
Unlabelled: Rapid and accurate identification of cultured molds is important to determine clinical significance and therapeutic decision-making. Conventional mold identification uses phenotypic macroscopic and microscopic characterization; however, this can take days or weeks for colony maturity and definitive microscopic structure formation, be limited to genus-level identification, and be misidentified due to morphologic mimics or similarities between closely related species. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) revolutionized bacterial and yeast identification but remains uncommon for molds in part because of limited reference libraries.
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