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In 2011, Watson and Barnes proposed a schema for classifying biobanks into 3 groups (mono-, oligo-, and poly-user), primarily based upon biospecimen access policies. We used results from a recent comprehensive survey of cancer biobanks in New South Wales, Australia to assess the applicability of this biobank classification schema in an Australian setting. Cancer biobanks were identified using publically available data, and by consulting with research managers. A comprehensive survey was developed and administered through a face-to-face setting. Data were analyzed using Microsoft Excel™ 2010 and IBM SPSS Statistics™ version 21.0. The cancer biobank cohort (n=23) represented 5 mono-user biobanks, 7 oligo-user biobanks, and 11 poly-user biobanks, and was analyzed as two groups (mono-/oligo- versus poly-user biobanks). Poly-user biobanks employed significantly more full-time equivalent staff, and were significantly more likely to have a website, share staff between biobanks, access governance support, utilize quality control measures, be aware of biobanking best practice documents, and offer staff training. Mono-/oligo-user biobanks were significantly more likely to seek advice from other biobanks. Our results further delineate a biobank classification system that is primarily based on access policy, and demonstrate its relevance in an Australian setting.
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http://dx.doi.org/10.1089/bio.2015.0007 | DOI Listing |
JACC Heart Fail
September 2025
Cardiovascular Pathology, Department of Cardiac, Thoracic Vascular Sciences and Public Health, University of Padova, Padova, Italy. Electronic address:
BMJ Open Diabetes Res Care
September 2025
NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK.
Introduction: Frequent glycated hemoglobin A1c (HbA1c) monitoring is recommended in individuals with type 2 diabetes mellitus (T2D). We aimed to identify distinct, long-term HbA1c trajectories following a T2D diagnosis and investigate how these glycemic control trajectories were associated with health-related traits and T2D complications.
Research Design And Methods: A cohort of 12,435 unrelated individuals of European ancestry with T2D was extracted from the UK Biobank data linked to primary care records.
Diabetes Obes Metab
September 2025
Phase I Clinical Trial Research Ward, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is an emerging global health concern, and its presence increases the risk of multi-system diseases. This study aimed to investigate the multimorbidity trajectories of chronic diseases in people living with MASLD.
Methods: We identified 137 859 MASLD patients in UK Biobank and used 'propensity score matching' to match an equal number of non-MASLD controls.
iScience
September 2025
Guangdong Provincial Key Laboratory of Mathematical and Neural Dynamical Systems, School of Computing and Information Technology, Great Bay University, Dongguan, China.
Distinguishing similar cancer subtypes and predicting responses to immune checkpoint blockade (ICB) are critical for improving clinical outcomes. However, existing gene expression signatures often suffer from batch effects and poor generalizability across cohorts. To address these limitations, we propose adaptive individualized gene pair signatures (AIGPS), a robust method that adaptively quantifies gene pair reversals and selects informative features using machine learning.
View Article and Find Full Text PDFDiabetes Metab J
September 2025
Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea.
Background: This study aimed to investigate the association between adiponectin levels and the incidence of metabolic dysfunction- associated steatotic liver disease (MASLD) and nonalcoholic fatty liver disease (NAFLD), and to explore the predictive value of adiponectin in the onset of these conditions.
Methods: A 17-year follow-up of 35,026 individuals from the Korean Cancer Prevention Study-II biobank cohort (2004-2021) was conducted. Adiponectin levels were categorized into quintiles.