Fracture risk assessment relies on clinical tools such as bone mineral density (BMD) and biomarkers, providing information on the mineral content and bone turnover status. Although useful in the clinic, it is recognized that fracture risk (based on these two outcomes) and actual incidence are not indistinguishable. One of the reasons for this discrepancy is that clinical diagnostic tools rely exclusively on bone mineral content considerations, while ignoring ones pertaining to either the amount or the quality of the organic matrix and the tissue water; yet the mechanical behavior of bone is dependent on the content and quality of all of its three major components (mineral, organic matrix, tissue water).

The proposed studies will test the hypothesis that patients sustaining fragility fractures have common, altered organic matrix properties, irrespective of age and diagnosis. Specifically, that alterations in glycosaminoglycan and pyridinoline content at actively forming bone surfaces strongly correlate with fragility fracture incidence, independent of bone mineral density values and clinical diagnosis.

The proposed experiments will help us better understand what determines bone strength, thus complementing existing fracture risk assessment methods. We aim to establish organic matrix quality indices (collagen- and proteoglycan-related), by Raman spectroscopic analysis of bone biopsies, that identify fragility fracture sustaining patients and those who do not, irrespective of age, clinical diagnosis and fracture risk assessment.

This will offer the possibility of dropping the need of a bone biopsy to determine bone quality, a rather invasive procedure. This may become a reality as both skin and bone mainly consist of type I collagen, and both tissues contain the same proteoglycans.

Thus, it is plausible that a diagnostic test based on spectroscopic analysis of skin that outperforms the already available methods in the clinic to identify patients at risk for fragility fracture will be feasible.

This project requires a high interest and skills in experimentation. Furthermore, spectral data analysis and processing is essential. Consequently, some programming experience is recommended (Matlab, python or similar).

In particular, your work will consist of:

• Acquisition of Raman spectra
• Spectral processing to obtain outcomes of interest
• Statistical analysis

Who we are

The Ludwig Boltzmann Institute of Osteology (LBIO) is a non-university research institute that   is dedicated to the elucidation of the mechanisms underlying the basic function of bone, and musculoskeletal diseases, leading to the discovery and development of effective strategies for diagnosis, prevention, and treatment. To achieve this goal the LBIO employs a multidisciplinary team consisting of clinicians, physicists, biologists, chemists and epidemiologists. The institute has two main laboratories, both located in hospitals in Vienna: one in the Hanusch Hospital (place of employment for the current position), the other in the AUVA Trauma Centre Meidling.

Your qualifications

• Academic degree (PhD) in physics, biology, (biomedical) engineering or similar
• A strong interest in experimental work as well as data analysis is necessary (basic knowledge of programming in languages like Matlab, python, or similar is recommended)
• Excellent communication and teamwork skills, as well as the ability to work independently

We offer

• Participation in cutting-edge research. LBIO employs a variety of modern analysis tools, including Raman spectrometers, TERS-AFM-Raman spectrometers, FTIR Imaging spectrometers, Scanning acoustic microscopy, electron microscopy, light microscopy, histomorphometry, as well as a cell biology facility
• A vibrant multidisciplinary research team
• International collaborations
• 2-year contract

Competitive salary: 4794,96 euros monthly salary (14× per year), 40 hours/week.

If interested, please send your application including a CV via email to: ryrsgurevbf.cnfpunyvf@bfgrbybtvr.yot.np.ng