Fetal mesenchymal stromal cells differentiating towards chondrocytes acquire a gene expression profile resembling human growth plate cartilage.

We used human fetal bone marrow-derived mesenchymal stromal cells (hfMSCs) differentiating towards chondrocytes as an alternative model for the human growth plate (GP). Our aims were to study gene expression patterns associated with chondrogenic differentiation to assess whether chondrocytes derived from hfMSCs are a suitable model for studying the development and maturation of the GP. hfMSCs efficiently formed hyaline cartilage in a pellet culture in the presence of TGFβ3 and BMP6.

A family history of breast cancer will not predict female early onset breast cancer in a population-based setting.

Background: An increased risk of breast cancer for relatives of breast cancer patients has been demonstrated in many studies, and having a relative diagnosed with breast cancer at an early age is an indication for breast cancer screening. This indication has been derived from estimates based on data from cancer-prone families or from BRCA1/2 mutation families, and might be biased because BRCA1/2 mutations explain only a small proportion of the familial clustering of breast cancer. The aim of the current study was to determine the predictive value of a family history of cancer with regard to early onset of female breast cancer in a population based setting.

Inclusion body myositis. Clinical features and clinical course of the disease in 64 patients.

The clinical features of inclusion body myositis (IBM) were of minor importance in the design of consensus diagnostic criteria, mainly because of controversial views on the specificity of signs and symptoms, although some authors reported "typical" signs. To re-assess the clinical spectrum of IBM, a single investigator using a standard protocol studied a cohort of 64 patients cross-sectionally. Symptom onset was before the age of 50 years in 20% of cases.

Modeling familial clustered breast cancer using published data.

The purpose of this research was to model the familial clustering of breast cancer and to provide an accurate risk estimate for individuals from the general population, based on their family history of breast and ovarian cancer. We constructed a genetic model as an extension of a model by Claus et al. (E.