Publication activities of German junior researchers in academic medicine: which factors impact impact factors?

Previous studies have shown medical students in Germany to have little interest in research while at the same time there is a lack of physician scientists. This study’s aim is to investigate factors influencing publication productivity of physicians during and after finishing their medical doctorate. We conducted a PubMed search for physicians having received their doctoral degree at Ludwig-Maxmilians-University Munich Faculty of Medicine between 2011 and 2013 (N = 924) and identified the appropriate impact factor (IF) for each journal the participants had published in. Gender, age, final grade of the doctorate, participation in a structured doctoral study program and joint publication activities between graduate and academic supervisor were defined as factors. For analyses we used nonparametric procedures. Men show significantly more publications than women. Before their doctoral graduation men publish 1.98 (SD ± 3.64) articles on average, women 1.15 (±2.67) (p < 0.0001, d = 0.27). After completion of the doctorate (up to 06/2015), 40 % of men still publish, while only 24.3 % of women (p < 0.0001, φ = 0.17) continue to publish. No differences were found concerning the value of IFs. Similar results were found regarding the variable ‘participation in a structured doctoral study program’. Until doctoral graduation, program participants publish 2.82 (±5.41) articles, whereas participants doing their doctorate individually only publish 1.39 (±2.87) articles (p < 0.0001, d = 0.46). These differences persist in publication activities after graduation (45.5 vs. 29.7 %, p = 0.008, φ = 0.09). A structured doctorate seems to have positive influence on IFs (4.33 ± 2.91 vs. 3.37 ± 2.82, p = 0.006, d = 0.34). Further significant results concern the variables ‘final grade’ and ‘age’: An early doctoral graduation and an excellent or very good grade for the doctoral thesis positively influence publication productivity. Finally, joint publication activities between the graduate and his/her academic supervisor result in significantly higher IFs (3.64 ± 3.03 vs. 2.84 ± 2.25, p = 0.007, d = 0.28). The study’s results support the assumption about women’s underrepresentation in science as well as the relevance of structured doctoral study programs for preparing and recruiting young academics in medicine for scientific careers. Promoting women and further development of structured doctoral study programs are highly recommended.

Image-based biomechanical assessment of vertebral body and intervertebral disc in the human lumbar spine

Life expectancy continuously increases but our society faces age-related conditions. Among musculoskeletal diseases, osteoporosis associated with risk of vertebral fracture and degenerative intervertebral disc (IVD) are painful pathologies responsible for tremendous healthcare costs. Hence, reliable diagnostic tools are necessary to plan a treatment or follow up its efficacy. Yet, radiographic and MRI techniques, respectively clinical standards for evaluation of bone strength and IVD degeneration, are unspecific and not objective. Increasingly used in biomedical engineering, CT-based finite element (FE) models constitute the state-of-art for vertebral strength prediction. However, as non-invasive biomechanical evaluation and personalised FE models of the IVD are not available, rigid boundary conditions (BCs) are applied on the FE models to avoid uncertainties of disc degeneration that might bias the predictions. Moreover, considering the impact of low back pain, the biomechanical status of the IVD is needed as a criterion for early disc degeneration. Thus, the first FE study focuses on two rigid BCs applied on the vertebral bodies during compression test of cadaver vertebral bodies, vertebral sections and PMMA embedding. The second FE study highlights the large influence of the intervertebral disc’s compliance on the vertebral strength, damage distribution and its initiation. The third study introduces a new protocol for normalisation of the IVD stiffness in compression, torsion and bending using MRI-based data to account for its morphology. In the last study, a new criterion (Otsu threshold) for disc degeneration based on quantitative MRI data (axial T2 map) is proposed. The results show that vertebral strength and damage distribution computed with rigid BCs are identical. Yet, large discrepancies in strength and damage localisation were observed when the vertebral bodies were loaded via IVDs. The normalisation protocol attenuated the effect of geometry on the IVD stiffnesses without complete suppression. Finally, the Otsu threshold computed in the posterior part of annulus fibrosus was related to the disc biomechanics and meet objectivity and simplicity required for a clinical application. In conclusion, the stiffness normalisation protocol necessary for consistent IVD comparisons and the relation found between degeneration, mechanical response of the IVD and Otsu threshold lead the way for non-invasive evaluation biomechanical status of the IVD. As the FE prediction of vertebral strength is largely influenced by the IVD conditions, this data could also improve the future FE models of osteoporotic vertebra.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.