Gene expression profiling of dedifferentiated human articular chondrocytes in monolayer culture

Objective\ud When primary chondrocytes are cultured in monolayer, they undergo dedifferentiation during which they lose their phenotype and their capacity to form cartilage. Dedifferentiation is an obstacle for cell therapy for cartilage degeneration. In this study, we aimed to systemically evaluate the changes in gene expression during dedifferentiation of human articular chondrocytes to identify underlying mechanisms.\ud \ud Methods\ud RNA was isolated from monolayer-cultured primary human articular chondrocytes at serial passages. Gene expression was analyzed by microarray. Based on the microarray analysis, relevant genes and pathways were identified. Their functions in chondrocyte dedifferentiation were further investigated.\ud \ud Results\ud In vitro expanded human chondrocytes showed progressive changes in gene expression. Strikingly, an overall decrease in total gene expression was detected, which was both gradual and cumulative. DNA methylation was in part responsible for the expression downregulation of a number of genes. Genes involved in many pathways such as the ERK and BMP pathways exhibited significant changes in expression. Inhibition of ERK pathway didn’t show dramatic effects in counteracting dedifferentiation process. BMP-2 was able to decelerate the dedifferentiation and reinforce the maintenance of chondrocyte phenotype in monolayer culture.\ud \ud Conclusion\ud Our study not only improves our knowledge of the intricate signaling network regulating maintenance of chondrocyte phenotype, but also contributes to improved chondrocyte expansion and chondrogenic performance for cell therapy

Preventing overuse of laboratory diagnostics: a case study into diagnosing anaemia in Dutch general practice

BACKGROUND: More information is often thought to improve medical decision-making, which may lead to test overuse. This study assesses which out of 15 laboratory tests contribute to diagnosing the underlying cause of anaemia by general practitioners (GPs) and determines a potentially more efficient subset of tests for setting the correct diagnosis. METHODS: Logistic regression was performed to determine the impact of individual tests on the (correct) diagnosis. The statistically optimal test subset for diagnosing a (correct) underlying cause of anaemia by GPs was determined using data from a previous survey including cases of real-world anaemia patients. RESULTS: Only 9 (60%) of the laboratory tests, and patient age, contributed significantly to the GPs' ability to diagnose an underlying cause of anaemia (CRP, ESR, ferritin, folic acid, haemoglobin, leukocytes, eGFR/MDRD, reticulocytes and serum iron). Diagnosing the correct underlying cause may require just five (33%) tests (CRP, ferritin, folic acid, MCV and transferrin), and patient age. CONCLUSIONS: In diagnosing the underlying cause of anaemia a subset of five tests has most added value. The real-world impact of using only this subset should be further investigated. As illustrated in this case study, a statistical approach to assessing the added value of tests may reduce test overuse