Protestant University of Applied Sciences Freiburg

Most patients with relapsed or refractory multiple myeloma (RRMM) have previously received lenalidomide (LEN) and proteasome inhibitors (PIs). This real-world study describes treatment patterns and clinical outcomes for RRMM patients post-LEN and PI in Germany. The BasecaMMp cohort included patients with prior LEN and PI therapy within the first to third line of treatment (LOT) between May 2016 and December 2023. Patient characteristics, treatment regimens and progression-free survival (PFS), overall survival (OS) and time to next treatment (TTNT) were analyzed. Of 1834 patients included (median age: 72.5 years; 59.5% male; median of 2 prior LOTs), around 30.4% were double-refractory, and 47.7% were LEN-refractory. Index therapies (first therapies received after exposure to LEN and a PI in the first to third lines) were highly heterogeneous. Median PFS was 12.7 (95% confidence interval [CI], 12.2-13.14) months overall and 11.3 (95% CI, 10.3-12.1) months in LEN-refractory patients, while median OS was 37.1 (95% CI, 34.2-40.7) months overall and 34.3 (95% CI, 31.1-41.0) months in LEN-refractory patients. These findings highlight the lack of a clear standard of care, poor clinical outcomes, and the need for more effective therapies and treatment strategies for this population.

The evolutionary conserved TOR kinase positively controls growth and development of the moss Physcomitrella, development and function of its chloroplasts, its protein synthesis, and cell-cycle progression. Target of Rapamycin (TOR) is a conserved protein kinase and an important signalling hub in eukaryotes. The moss Physcomitrella (Physcomitrium patens) is a model organism for plant physiology, development, and evolution. However, little is known about TOR signalling in non-vascular plants, including Physcomitrella. Here, we report the effects of inhibiting TOR signalling in Physcomitrella. We identified and characterised Physcomitrella 12-kDa FK506-binding protein (FKBP12), which binds TOR in the presence of rapamycin. Whereas the growth of wild-type protonema is unaffected by rapamycin, overexpressing endogenous FKBP12 rendered the plant susceptible to the inhibitor in a dose-dependent manner. Likewise, protonema growth was inhibited when the TOR-specific inhibitor AZD8055 was present in the culture. We show that rapamycin and AZD8055 have pleiotropic effects, as they delay cell-cycle progression and development, induce chlorosis, inhibit photosynthesis, and alter total protein content. Additionally, we identified and characterised PpTOR, PpLST8, and PpRAPTOR, key components of TOR complex 1 (TORC1), whereas RICTOR and mSIN1 of TORC2 are not encoded by the P. patens genome. We found that PpLST8 substitutes its homolog in yeast to allow cell growth. Physcomitrella mutants were generated with a conditional downregulation of PpTOR, PpLST8, and PpRAPTOR, respectively. They were impaired in growth. Finally, we show TOR-dependent phosphorylation of a well-known TOR phospho-target, the ribosomal protein RPS6, via LC-MS/MS. Collectively, our results show that Physcomitrella growth and development is positively controlled by a conserved TOR kinase. We suggest to further dissect TOR signalling in Physcomitrella in order to elucidate signalling integration via TORC1 in plants.

We present an approach to simulate and validate the effect of dynamic soft tissue and sensor attachment on inertial sensor data. Our approach extends sensor data synthesis from personalised biomechanical dynamics and human body surface models. Tetrahedralisation is employed to the surface mesh of body models to represent internal tissue dynamics. A position-based dynamics algorithm is employed to simulate soft attachment motion. We synthesised acceleration and angular velocity data for the thigh segment during jumping trials of 13 participants. We compare the synthesised inertial sensor data, with and without soft attachment simulation, to physical IMU measurements obtained concurrently to video motion capture data. Results show an average mean absolute error of 19.98°/s vs. 21.45°/s and 2.19m/s2 vs. 2.25m/s2, with and without soft attachment simulation, respectively. The proposed soft attachment modelling approach showed lower error and higher correlation, along with considerably decreased error standard deviation of up to 42% compared to the model without soft attachment. We conclude that dynamic soft attachment simulation can enhance existing body surface models and provide a more realistic representation of dynamic motion for the analysis and optimisation of wearable inertial sensor systems.

BackgroundSARS-CoV-2 vaccines have significantly reduced human and economic losses. Nevertheless, vaccine hesitancy remains a major issue in many countries, including Germany. Recent studies have shown that public health framing and incentives can boost immunization rates. However, available evidence is fragmented and inconclusive regarding the effectiveness of different framing messages, types of incentives, and the size of financial incentives across different populations.MethodsThis randomized, controlled survey experiment elicited the attitudes of 6,685 Germans towards 4 financial/non-financial SARS-CoV-2 immunization incentives (food voucher, football tickets, participation in lottery, immediate monetary compensation), and tested whether framing (individual/collective, health/economic consequences) affected said attitudes. We assigned participants to five study arms (control: no frame; experiment: 1 of 4 frames) and measured attitudes towards immunization incentives, and the amount of monetary compensation deemed appropriate, should such an incentive be considered.ResultsWhile > 75% of our sample considered all 4 incentives to be not meaningful, all frames increased favorable views towards the financial incentives lottery/money and the average amount deemed acceptable for immediate monetary compensation. Interaction models showed that all frames have similar effects across core subgroups, e.g. age-cohorts, gender, vaccine doses.ConclusionsAcross a sample of 6,685 Germans, we show that 4 different frames detailing the potential individual/collective consequences of COVID-19 have very similar effects on attitudes towards monetary incentives for SARS-CoV-2 immunization. Our results suggest that the existence of frames rather than specific narratives is key to increasing favorable views towards immunization incentives.Clinical trial numberNot applicable.

The approach of socio-technical systems (STS) for asuccessful life in old age focuses on the combination of technical and sociocultural factors in one. Technological systems have long since ceased to be limited to simple functions; instead, they enable customizable applications, interactive use combined with complex communication and action strands. The associated interactions with the technical system suggest aperspective on interactions and relationships. Research results show that individualizable functions of STSs are rated positively in terms of acceptance and use by older people. From ageragogical perspective, questions arise regarding the appropriation of older people and the design of learning processes (socio-technical learning arrangements). Arelational view of learning and educational processes relating to the appropriation and acquisition of competences for designing and using STS in real-world situations is developed based on aformative qualitative research design of the "RUBYDemenz" project. In particular, data/results from interviews with voluntary learning facilitators, professional practice facilitators, focus groups and research workshops are utilized. Empirical findings can be used to develop starting points for educational and learning processes to expand competences in the context of technology use. Approaches to education, training and further training follow on from this as does the question of whether the research/development process itself must be designed as alearning process in which all participants are involved as learners, with the aim of achieving the best possible fit between the technical solutions and the intended areas of application in real-world situations.

Abstract This paper is about the history of the Mathematical Institute of the University of Freiburg with special reference to the applied mathematician Henry Görtler.

In this article, the authors present a new deep trend-following strategy that selectively buys constituents of the S&P 500 Index that are estimated to be upward trending. Therefore, they construct a binary momentum indicator based on a recursive algorithm and then train a convolutional neural network combined with a long short-term memory model to classify periods that are defined as upward trends. The strategy, which can be used as an alternative to traditional quantitative momentum ranking models, generates returns up to 27.3% per annum over the out-of-sample period from January 2010 to December 2019 and achieves a Sharpe ratio of 1.3 after accounting for transaction costs on daily data. The authors show that volatility scaling can further increase the risk–return profile and lower the maximum drawdown of the strategy.

Depressive disorders are related to social withdrawal and a loss of social contacts. Moreover, a lack of social integration and social support are risk factors for relapse and rehospitalization. Despite the crucial role of social networks for mental health and social support, knowledge about the structure of social networks or how they promote social support in terms of coping with depressive disorders is scarce. The present study aims to analyze social support in people with depressive disorders using ego-centered social network analysis for formal description. Ninety-seven former psychiatric inpatients participated in the study. Network size and density, a small number of conflicts in the relationships of ego to alters, and the multiplexity of social support dimensions were associated with perceived social support—measured via Social Support Questionnaire (F-Soz-U-K-14). Considering relational ratios which correlated with perceived social support, five types of social support networks were differentiated by means of cluster analysis: (1) no social support, (2) professionally supported birth family, (3) the more the merrier, (4) concentrated support, (5) overchallenged nuclear family. More than each relational characteristic on its own, their co-occurring patterns as network types provide the very structures of social support. This underpins the crucial role of structural approaches and networking skills in social work practice. German Clinical Trials Register (DRKS): DRKS00011561. Trial registration date: 10. March 2017.