Assessment of age-related bone loss in normal South African women by means of the Hologic QDR 1000 system

No Abstract

Trabecular bone density in premenopausal rheumatoid arthritis patients

Objective. This study was undertaken to compare trabecular bone mineral density (BMD) in premenopausal rheumatoid arthritis. (RA) patients and normal age-matched controls.Method. A protocol was designed to record age, duration of disease, use of corticosteroids (CS) and/ or slow-acting antirheumatic drug (SAARD) therapy together with duration of such therapy. BMD was measured using the Hologic QDR 1 000 dual energy X-ray absorptiometer. The first four lumbar vertebrae and the left femur were measured in 56 RA patients and 165 controls. Height and weight were measured. Comparisons were made between RA patients and controls, as well as between subgroups of RA patients based on CS therapy.Results. Patients with RA had significantly lower BMD (P < 0.05) at all the sites than the normal controls. The mean duration of RA at the time of study was 60 months (standard deviation 58 months). Thirteen RA patients had used CS in doses less than 10 mg daily for 6 months or longer (mean 19 months), while 25 patients had been on SAARD for an excess of 6 months (mean 23 months). The CS-treated patients had significantly lower BMD than untreated subjects at the femoral neck and inter-trochanteric region (P < 0.05), but not at the lumbar spine. However, when compared with normal controls, the CS-treated subgroups had significantly lower BMD at the lumbar spine and all femoral areas. Trochanteric BMD was the best determinant of the RA group, with a sensitivity of 65% and specificity of 77%. The positive predictive value was 16%, while the negative predictive value was 10%. Using Bayes' theorem, the prevalence of osteopenia in RA was found to be6%.Conclusion. We conclude that generalised bone loss is a systemic feature of RA and that loss at the spine and femur may be aggravated by CS therapy

Colloids in light fields: particle dynamics in random and periodic energy landscapes

The dynamics of colloidal particles in potential energy landscapes have mainly been investigated theoretically. In contrast, here we discuss the experimental realization of potential energy landscapes with the help of light fields and the observation of the particle dynamics by video microscopy. The experimentally observed dynamics in periodic and random potentials are compared to simulation and theoretical results in terms of, e.g. the mean-squared displacement, the time-dependent diffusion coefficient or the non-Gaussian parameter. The dynamics are initially diffusive followed by intermediate subdiffusive behaviour which again becomes diffusive at long times. How pronounced and extended the different regimes are, depends on the specific conditions, in particular the shape of the potential as well as its roughness or amplitude but also the particle concentration. Here we focus on dilute systems, but the dynamics of interacting systems in external potentials, and thus the interplay between particle-particle and particle-potential interactions, is also mentioned briefly. Furthermore, the observed dynamics of dilute systems resemble the dynamics of concentrated systems close to their glass transition, with which it is compared. The effect of certain potential energy landscapes on the dynamics of individual particles appears similar to the effect of interparticle interactions in the absence of an external potential

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

A complementary study approach unravels novel players in the pathoetiology of Hirschsprung disease

Hirschsprung disease (HSCR, OMIM 142623) involves congenital intestinal obstruction caused by dysfunction of neural crest cells and their progeny during enteric nervous system (ENS) development. HSCR is a multifactorial disorder; pathogenetic variants accounting for disease phenotype are identified only in a minority of cases, and the identification of novel disease-relevant genes remains challenging. In order to identify and to validate a potential disease-causing relevance of novel HSCR candidate genes, we established a complementary study approach, combining whole exome sequencing (WES) with transcriptome analysis of murine embryonic ENS-related tissues, literature and databas

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

Assessing the symmetry of bone loss in the femur using the lunar densitometer

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Matrix-Dependent Regulation of AKT in Hepsin-Overexpressing PC3 Prostate Cancer Cells12

The serine-protease hepsin is one of the most prominently overexpressed genes in human prostate carcinoma. Forced expression of the enzyme in mice prostates is associated with matrix degradation, invasive growth, and prostate cancer progression. Conversely, hepsin overexpression in metastatic prostate cancer cell lines was reported to induce cell cycle arrest and reduction of invasive growth in vitro. We used a system for doxycycline (dox)-inducible target gene expression in metastasis-derived PC3 cells to analyze the effects of hepsin in a quantitative manner. Loss of viability and adhesion correlated with hepsin expression levels during anchorage-dependent but not anchorage-independent growth. Full expression of hepsin led to cell death and detachment and was specifically associated with reduced phosphorylation of AKT at Ser473, which was restored by growth on matrix derived from RWPE1 normal prostatic epithelial cells. In the chorioallantoic membrane xenograft model, hepsin overexpression in PC3 cells reduced the viability of tumors but did not suppress invasive growth. The data presented here provide evidence that elevated levels of hepsin interfere with cell adhesion and viability in the background of prostate cancer as well as other tissue types, the details of which depend on the microenvironment provided. Our findings suggest that overexpression of the enzyme in prostate carcinogenesis must be spatially and temporally restricted for the efficient development of tumors and metastases