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Aim: To assess outcomes in patients with advanced adenocarcinoma non-small-cell lung cancer who received nintedanib plus docetaxel after progression on prior chemotherapy followed by immune checkpoint inhibitor (ICI) therapy. Patients & methods: VARGADO is a prospective, noninterventional study. We describe initial data from a cohort of 22 patients who received nintedanib plus docetaxel after chemotherapy and ICI therapy. Results: Median progression-free survival with nintedanib plus docetaxel was 5.5 months (95% CI: 1.9–8.7 months). The objective response rate was 7/12 (58%) and the disease control rate was 10/12 (83%). Data for overall survival rate 12 months after the start of treatment (primary end point) are not yet mature and are not reported. Of 22 patients, 73% experienced drug-related adverse events; adverse events led to treatment discontinuation in 32% of patients. Conclusion: These data highlight the potential clinical benefit of nintedanib plus docetaxel in patients who failed prior ICI therapy.
Trial registration number: NCT02392455
Aims: Balloon pulmonary angioplasty (BPA) is an interventional treatment modality for inoperable chronic thromboembolic pulmonary hypertension (CTEPH). Therapy monitoring, based on non-invasive biomarkers, is a clinical challenge. This post-hoc study aimed to assess dynamics of high-sensitivity cardiac troponin T (hs-cTnT) as a marker for myocardial damage and its relation to N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels as a marker for cardiac wall stress.
Methods and results: This study included 51 consecutive patients who underwent BPA treatment and completed a 6-month follow-up (6-MFU) between 3/2014 and 3/2017. Biomarker measurement was performed consecutively prior to each BPA and at 6-MFU.
In total, the 51 patients underwent an average of 5 BPA procedures. The 6-month survival rate was 96.1%. The baseline (BL) meanPAP (39.5±12.1mmHg) and PVR (515.8±219.2dyn×sec×cm-5) decreased significantly within the 6-MFU (meanPAP: 32.6±12.6mmHg, P<0.001; PVR: 396.9±182.6dyn×sec×cm-5, P<0.001). At BL, the median hs-cTnT level was 11 (IQR 6–16) ng/L and the median NT-proBNP level was 820 (IQR 153–1872) ng/L. The levels of both biomarkers decreased steadily after every BPA, showing the first significant difference after the first procedure. Within the 6-MFU, hs-cTnT levels (7 [IQR 5–12] ng/L; P<0.001) and NT-proBNP levels (159 [IQR 84–464] ng/l; P<0.001) continued to decrease. The hs-cTnT levels correlated with the PVR (rrs = 0.42; p = 0.005), the meanPAP (rrs = 0.32; p = 0.029) and the NT-proBNP (rrs = 0.51; p<0.001) levels at BL.
Conclusion: Non-invasive biomarker measurement provides valuable evidence for the decreasing impairment of myocardial function and structure during BPA therapy. Changes in hs-cTNT levels are suggestive for a reduction in ongoing myocardial damage.
Seit über zehn Jahren werden am Institut für Sportwissenschaften die Auswirkungen von Vibrationen auf die Bewegungssteuerung des Menschen erforscht. Das Team um Dr. Christian Haas und Prof. Dietmar Schmidtbleicher fand dabei ein weites Funktionsspektrum mit physiologisch positiven, aber auch negativen Effekten. So können gleichförmige hochfrequente Vibrationen zu Wahrnehmungsstörungen führen oder einen Verlust der Reflextätigkeit bewirken. Andererseits verbessert ein Training mit variablen Vibrationsreizen, so genannten »Stochastischen Resonanzen«, die Koordination. Diese ständig wechselnden Reize trainieren das Zusammenspiel zwischen Sensoren, Gehirn und Muskulatur und bewirken effizientere, an die jeweilige Anforderungssituation angepasste Bewegungsabläufe. Interessanterweise zeigen sich diese Effekte sowohl bei Hochleistungsathleten als auch bei Patienten mit Bewegungsstörungen.
Assessing the uncertainties of simulation results of ecological models is becoming increasingly important, specifically if these models are used to estimate greenhouse gas emissions on site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure, and (iv) accurateness of measurements (e.g., soil-atmosphere greenhouse gas exchange) which are used for model testing and development.
The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO) and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used.
Our approach shows that by means of the joint parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange. In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of an calibration set (6 yr) and an independent validation set of 4 yr. The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Root-mean-squared error (RMSE) NO: 2.4 to 18.95 g N ha−1 d−1, N2O: 0.14 to 21.12 g N ha−1 d−1, CO2: 5.4 to 11.9 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes still limited to accurately predict observed seasonal variations in fluxes.
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon source was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
Environmental change impacts on the C- and N-cycle of European forests: a model comparison study
(2013)
Forests are important components of the greenhouse gas balance of Europe. There is considerable uncertainty about how predicted changes to climate and nitrogen deposition will perturb the carbon and nitrogen cycles of European forests and thereby alter forest growth, carbon sequestration and N2O emission. The present study aimed to quantify the carbon and nitrogen balance, including the exchange of greenhouse gases, of European forests over the period 2010–2030, with a particular emphasis on the spatial variability of change. The analysis was carried out for two tree species: European beech and Scots pine. For this purpose, four different dynamic models were used: BASFOR, DailyDayCent, INTEGRATOR and Landscape-DNDC. These models span a range from semi-empirical to complex mechanistic. Comparison of these models allowed assessment of the extent to which model predictions depended on differences in model inputs and structure. We found a European average carbon sink of 0.160 ± 0.020 kgC m−2 yr−1 (pine) and 0.138 ± 0.062 kgC m−2 yr−1 (beech) and N2O source of 0.285 ± 0.125 kgN ha−1 yr−1 (pine) and 0.575 ± 0.105 kgN ha−1 yr−1 (beech). The European average greenhouse gas potential of the carbon sink was 18 (pine) and 8 (beech) times that of the N2O source. Carbon sequestration was larger in the trees than in the soil. Carbon sequestration and forest growth were largest in central Europe and lowest in northern Sweden and Finland, N. Poland and S. Spain. No single driver was found to dominate change across Europe. Forests were found to be most sensitive to change in environmental drivers where the drivers were limiting growth, where changes were particularly large or where changes acted in concert. The models disagreed as to which environmental changes were most significant for the geographical variation in forest growth and as to which tree species showed the largest rate of carbon sequestration. Pine and beech forests were found to have differing sensitivities to environmental change, in particular the response to changes in nitrogen and precipitation, with beech forest more vulnerable to drought. There was considerable uncertainty about the geographical location of N2O emissions. Two of the models BASFOR and LandscapeDNDC had largest emissions in central Europe where nitrogen deposition and soil nitrogen were largest, whereas the two other models identified different regions with large N2O emission. N2O emissions were found to be larger from beech than pine forests and were found to be particularly sensitive to forest growth.
Assessing the uncertainties of simulation results of ecological models is becoming of increasing importance, specifically if these models are used to estimate greenhouse gas emissions at site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure and (iv) accurateness of measurements (e.g. soil-atmosphere greenhouse gas exchange) which are used for model testing and development.
The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO), and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used.
Our approach showed that by means of the joined parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange.
In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of the calibration set (6 yr) and an independent validation set of 4 yr.
The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Residual mean squared error (RMSE) NO: 2.5 to 21.3 g N ha−1 d−1, N2O: 0.2 to 21.4 g N ha−1 d−1, CO2: 5.8 to 12.6 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes limited to accurately predict observed seasonal variations in fluxes.
Background: Balloon pulmonary angioplasty is an evolving, interventional treatment option for inoperable patients with chronic thromboembolic pulmonary hypertension (CTEPH). Pulmonary hypertension at rest as well as exercise capacity is considered to be relevant outcome parameters. The aim of the present study was to determine whether measurement of pulmonary hemodynamics during exercise before and six months after balloon pulmonary angioplasty have an added value.
Methods: From March 2014 to July 2018, 172 consecutive patients underwent balloon pulmonary angioplasty. Of these, 64 consecutive patients with inoperable CTEPH underwent a comprehensive diagnostic workup that included right heart catheterization at rest and during exercise before balloon pulmonary angioplasty treatments and six months after the last intervention.
Results: Improvements in pulmonary hemodynamics at rest and during exercise, in quality of life, and in exercise capacity were observed six months after balloon pulmonary angioplasty: WHO functional class improved in 78% of patients. The mean pulmonary arterial pressure (mPAP) at rest was reduced from 41 ± 9 to 31 ± 9 mmHg (p < 0.0001). The mPAP/cardiac output slope decreased after balloon pulmonary angioplasty (11.2 ± 25.6 WU to 7.7 ± 4.1 WU; p < 0.0001), and correlated with N-terminal fragment of pro-brain natriuretic peptide (p = 0.035) and 6-minute walking distance (p = 0.01).
Conclusions: Exercise right heart catheterization provides valuable information on the changes of pulmonary hemodynamics after balloon pulmonary angioplasty in inoperable CTEPH patients that are not obtainable by measuring resting hemodynamics.
Background: Dentists are at a higher risk of suffering from musculoskeletal disorders (MSD) than the general population. However, the latest study investigating MSD in the dental profession in Germany was published about 20 years ago. Therefore, the aim of this study was to reveal the current prevalence of MSD in dentists and dental students in Germany. Methods: The final study size contained 450 (287 f/163 m) subjects of different areas of specialization. The age of the participants ranged from 23 to 75 years. The questionnaire consisted of a modified version of the Nordic Questionnaire, work-related questions from the latest questionnaire of German dentists, typical medical conditions and self-developed questions. Results: The overall prevalence showed that dentists suffered frequently from MSD (seven days: 65.6%, twelve months: 92%, lifetime: 95.8%). The most affected body regions included the neck (42.7%–70.9%–78.4%), shoulders (29.8%–55.6%–66.2%) and lower back (22.9%–45.8%–58.7%). Overall, female participants stated that they suffered from pain significantly more frequently, especially in the neck, shoulders and upper back. Conclusion: The prevalence of MSD among dentists, especially in the neck, shoulder and back area, was significantly higher than in the general population. In addition, women suffered more frequently from MSD than men in almost all body regions.
Background: Dental professionals are subjected to higher risks for musculoskeletal disorders (MSDs) than other professional groups, especially the hand region. This study aims to investigate the prevalence of hand complaints among dentists (Ds) and dental assistants (DAs) and examines applied therapies. Methods: For this purpose, an online questionnaire analysed 389 Ds (240female/149male) and 406 DAs (401female/5male) working in Germany. The self-reported data of the two occupational groups were compared with regard to the topics examined. The questionnaire was based on the Nordic Questionnaire (self-reported lifetime, 12-month and 7-day MSDs prevalence of the hand, the conducted therapy and its success), additional occupational and sociodemographic questions as well as questions about specific medical conditions. Results: 30.8% of Ds affirmed MSDs in the hand at any time in their lives, 20.3% in the last twelve months and 9.5% in the last seven days. Among DAs, 42.6% reported a prevalence of MSDs in the hand at any time in their lives, 31.8% in the last 12 months and 15.3% in the last seven days. 37.5% of the Ds and 28.3% of the DAs stated that they had certain treatments. For both, Ds and DAs, physiotherapy was the most frequently chosen form of therapy. 89.7% of Ds and 63.3% of DAs who received therapy reported an improvement of MSDs. Conclusion: Although the prevalence of MSDs on the hand is higher among DAs than among Ds, the use of therapeutic options and the success of therapy is lower for DAs compared to Ds.