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Background
To date, targeted tyrosine kinase inhibitors have been approved for FGFR2 and FGFR3 fusions (pemigatinib and erdafitinib, respectively), but the importance of FGFR2 mutations for transformation activity and as a druggable gene variant with response to different FGFR inhibitors is poorly understood. FGFR2 inhibitors present a mainstay of treatment for locally advanced or metastatic intrahepatic cholangiocellular carcinoma (iCCA).
Methods
A 74-year-old male was diagnosed with iCCA in liver segments seven and eight with infiltration of the hepatic veins and inferior vena cava revealed a C382R mutation of the intramembrane domain of FGRR2 receptor. We performed an in-silico study to understand the potential mode-of-action of the mutant FGFR2 targets. Based on experimentally determined structures we then used a structure generated by AlphaFold2 as the variation in question is located at a position not determined well in the experiments. This revealed that the C382R mutation is located in the trans-membranal domain at a position crucial for signal transduction, both for activation and inhibition of downstream-signaling. The Molecular Tumor Board decided to start the treatment with 13.5 mg pemigatinib once daily for 14 days, followed by 7 days of free therapy interval resulting in a sustained partial response. The patient continues to be treated of 13.5 mg as described above.
Results
In our case report, we were able to show that the patient in whom an C382R mutation was detected responded to the therapy with pemigatinib. This shows that real-world scenarios differ from the data of the approval studies, thereby illustrating how complex data on patients with FGFR mutations is. One of the main problems of large approval studies is that the functionality of the respective alterations is often disregarded.
Conclusions
Our results suggest that respective mutation may be successfully targeted by FGFR-selective tyrosine-kinase inhibitors, demonstrating the importance of the functional characterization of mutations.
no conflicts of interest.
Purpose: This study aimed to gain knowledge about environmental factors (EFs) that impact work and social life participation of people with multiple sclerosis (MS) in Austria and Switzerland to extend the knowledge of participation and to identify key areas for measuring participation.
Method: A three-round Delphi study was conducted defining patients as experts. In the 1st round, qualitative data was gathered through questionnaires, analyzed with content analysis, and factors were assigned to EFs as classified in the ICF. In the 2nd and 3rd round, experts judged EFs according to its relevance to obtain consensus (cut-off 75%). Categories were ranked on a scale from mostly important to important.
Results: One hundred and twelve Austrian and 109 Swiss experts were recruited. The content analysis revealed 768 EFs. The study resulted in a list of 176 consensus factors for Austria and 177 Switzerland. Five categories revealed to be highly important, 12 moderately important, 6 fairly important, and 10 important.
Conclusions: This study indicates that participation in work or social life is influenced by physical, social, attitudinal, and policy factors. Consensus factors afford insights into areas for consideration in the development of participation outcome measurements and support a comprehensive and inclusive rehabilitation approach.
A quantitative physical model for potential induced degradation of the shunting type (PID-s) in solar modules is introduced. Based on a drift and diffusion approach for sodium ions and atoms, it gives insight into the kinetics of degradation and the corresponding regeneration. A simple drift/source term is used to describe the time-dependent flux of Na-ions towards stacking faults at the surface of the solar cell. The assumed transport mechanism for Na+ ions through the SiN-layer uses the modified Stern-Eyring rate theory but our approach can also be adapted to other mechanisms. Several PID-s and regeneration curves of one-cell solar modules at T = 49°C and T = 90°C with 1000V potential difference between modul frame and cell were measured and least-square fits of the in-situ measured parallel resistance Rsh to the model were performed giving very good accordance.
Based on a few measurements, the model can predict PID-s and regeneration characteristics of solar modules under different conditions.
A high-order finite element model for vibration analysis of cross-laminated timber assemblies
(2017)
The vibration behavior of cross-laminated timber components in the low-frequency range can be predicted with high accuracy by the finite element method. However, the modeling of assembled cross-laminated timber components has been studied only scarcely. The three-dimensional p-version of the finite element method, which is characterized by hierarchic high-order shape functions, is well suited to consider coupling and support conditions. Furthermore, a small number of degrees of freedom can be obtained in case of thin-walled structures using p-elements with high aspect ratios and anisotropic ansatz spaces. In this article, a model for cross-laminated timber assemblies made of volumetric high-order finite elements is presented. Two representative types of connections are investigated, one with an elastomer between the cross-laminated timber components and the other without. The model is validated, and suitable ranges for the stiffness parameters of the finite elements which represent the junctions are identified.
Environmental regulations force car manufacturers to renew the powertrain technology portfolio offered to the customer to comply with greenhouse gas (GHG) emission targets. In turn, automotive companies face the task of identifying the “right” powertrain technology portfolio consisting of, for example, internal combustion engines and electric vehicles, because the selection of a particular powertrain technology portfolio affects different company targets simultaneously. What makes this decision even more challenging is that future market shares of the different technologies are uncertain. Our research presents a new decision-support approach for assembling optimal powertrain technology portfolios while making decision-makers aware of the trade-offs between the achievable profit, the achievable market share, the market share risk, and the GHG emissions generated by the selected vehicle fleet. The proposed approach combines “a posteriori” decision-making with multi-objective optimization. In an application case, we feed the outlooks of selected market studies into the proposed decision-support system. The result is a visualization and analysis of the current real-world decision-making problem faced by many automotive companies. Our findings indicate that for the proposed GHG restriction at work in 2030 in the European Union, no optimal powertrain technology portfolio with less than 35% of vehicles equipped with an electric motor exists.
A new approach for the friction and wear characterisation of polymer fibres under dry, mixed, and hydrodynamic sliding conditions is developed. The production process of the tested polymer fibres is described and an introduction in fibre-reinforced concrete is given. Tribotesting is done on an optimised tribometer capable of measuring the friction and wear behaviour of polymer fibres with diameters of a few 100 µm under lubricated conditions. Three extruded polypropylene macro fibres with varying diameters are characterised under tribological conditions found in an industrial concrete mixing process. It is shown that detailed friction and wear data of polymer fibres can be gathered.
Point mutations of the fibroblast growth factor receptor (FGFR)2 receptor in intrahepatic cholangiocarcinoma (iCC) are mainly of unknown functional significance compared to FGFR2 fusions. Pemigatinib, a tyrosine kinase inhibitor, is approved for the treatment of cholangiocarcinoma with FGFR2 fusion/rearrangement. Although it is hypothesized that FGFR2 mutations may cause uncontrolled activation of the signaling pathway, the data for targeted therapies for FGFR2 mutations remain unclear. In vitro analyses demonstrated the importance of the p.C382R mutation for ligand-independent constitutive activation of FGFR2 with transforming potential. The following report describes the clinical case of a patient diagnosed with an iCC carrying a FGFR2 p.C382R point mutation which was detected in liquid, as well as in tissue-based biopsies. The patient was treated with pemigatinib, resulting in a sustained complete functional remission in fluorodeoxyglucose-positron emission tomography/computed tomography over 10 months to date. The reported case is the first description of a complete functional remission under the treatment with pemigatinib in a patient with p.C383R mutation.
The effectiveness of hot-melt coating depends on its uniformity and the extent to which the surface is completely covered. Compared with solvent-based coating, spreading is more limited in hot-melt coating; thus, the coating uniformity is more affected by the process parameters. This study presents a new method for identifying and quantifying factors influencing coating uniformity. The proposed method facilitates the determination of coating-thickness distribution and non-covered surface proportion based on micro-computed tomography measurements. The proposed method is based on particles that have undergone hot-melt coating in a fluidized bed, and it is compared to common methods for layer-thickness determination. The influencing factors are quantified in terms of the dependency of coating uniformity on the coating amount and material. Material properties have a significant impact because stearin and palm fat create different coating layers. The proposed method is confirmed to be well suited for analyzing coating qualities.
The objective of this research project is to develop a solar-powered refrigerator in the lower capacity range of up to 5 kW of cooling power. With the use of liquid pistons and one of the most efficient thermodynamic cycles known, the Stirling cycle, this product has the potential to outperform rival solar cooling technologies while providing inexpensive, reliable, quiet, environmentally-friendly, and efficient solar cooling for residential use, due to its straightforward manufacturing, simple design and inert working gas. Presented in this paper are the newest results of the theoretical and experimental investigation into deducing the key design parameters and system configuration of the so-called Liquid Piston Stirling Cooler (LPSC), which will help lead to optimal performance. Computer models of the complex unconstrained system have been constructed and validated using the modelling software Sage and shown to replicate system behavior with reasonable accuracy in experiments. The models have been used to predict system improvements and identify limitations imposed by the use of liquid pistons. The results to date provide a unique insight into a relatively little studied area in Stirling cycle research.
Predictive Modeling (PM) techniques are gaining importance in the worldwide health insurance business. Modern PM methods are used for customer relationship management, risk evaluation or medical management. This article illustrates a PM approach that enables the economic potential of (cost-)effective disease management programs (DMPs) to be fully exploited by optimized candidate selection as an example of successful data-driven business management. The approach is based on a Generalized Linear Model (GLM) that is easy to apply for health insurance companies. By means of a small portfolio from an emerging country, we show that our GLM approach is stable compared to more sophisticated regression techniques in spite of the difficult data environment. Additionally, we demonstrate for this example of a setting that our model can compete with the expensive solutions offered by professional PM vendors and outperforms non-predictive standard approaches for DMP selection commonly used in the market.
A DDR2 SDRAM test setup implemented on the Griffin III ATE test system from HILEVEL Technologies is used to analyse the row hammer bug. Row hammer pattern experiments are compared to standard retention tests.
The analysis confirms that the row hammer effect is caused by a charge excitation process depending on the number of stress activation cycles. The stress has to occur in the local neighborhood of the cells under test.
Shallow impurity levels support the responsible charge carrier transport process in the used DDR2 SDRAM technology
The International Spinal Cord Injury (InSCI) community survey has been developed to collect internationally comparable data on the lived experience of persons with spinal cord injury (SCI) in all 6 WHO regions.
The InSCI survey provides a crucial first step to generate evidence on functioning, health maintenance, and subjective well-being in persons with SCI globally.
A major challenge in setting up the InSCI community survey was to develop a data model and questionnaire that comprehensively captures what matters to people and, at the same time, is feasible and parsimonious in terms of participant’s burden.
This paper outlines the components of the InSCI data model and presents the question selection to operationalize the data model along the 4 guiding principles of efficiency, feasibility, comparability, and truth and discrimination.
The data model consists of 6 components operationalized with 125 questions including functioning (n = 28 body functions and structures; n = 42 activities and participation), contextual factors (n = 26 environmental; n = 19 personal factors), lesion characteristics (n = 2), and appraisal of health and well-being (n = 8).
The InSCI questionnaire presents an efficient and feasible solution with satisfying comparability to other populations; however, its validity and reliability still needs to be confirmed.
This study investigates the impact of generative AI systems like ChatGPT on semi-structured decision-making, specifically in evaluating undergraduate dissertations. We propose using Davis’ technology acceptance model (TAM) and Schulz von Thun’s four-sides communication model to understand human–AI interaction and necessary adaptations for acceptance in dissertation grading. Utilizing an inductive research design, we conducted ten interviews with respondents having varying levels of AI and management expertise, employing four escalating-consequence scenarios mirroring higher education dissertation grading. In all scenarios, the AI functioned as a sender, based on the four-sides model. Findings reveal that technology acceptance for human–AI interaction is adaptive but requires modifications, particularly regarding AI’s transparency. Testing the four-sides model showed support for three sides, with the appeal side receiving negative feedback for AI acceptance as a sender. Respondents struggled to accept the idea of AI, suggesting a grading decision through an appeal. Consequently, transparency about AI’s role emerged as vital. When AI supports instructors transparently, acceptance levels are higher. These results encourage further research on AI as a receiver and the impartiality of AI decision-making without instructor influence. This study emphasizes communication modes in learning-ecosystems, especially in semi-structured decision-making situations with AI as a sender, while highlighting the potential to enhance AI-based decision-making acceptance.
Functioning information constitutes a relevant component for determining patients’ service needs and respective resource use. Diagnosis-Related Group (DRG) systems can be optimized by integrating functioning information.
First steps toward accounting for functioning information in the German DRG (G-DRG) system have been made; yet, there is no systematic integration of functioning information. The G-DRG system is part of the health system; it is embedded in and as such dependent on various stakeholders and vested interests.
This study explores the stakeholder’s perspective on integrating functioning information in the G-DRG system. A qualitative interview study was conducted with national stakeholders in 4 groups of the G-DRG system (health policy, administration, development, and consultations).
Interviews were analyzed using inductive thematic analysis. In total, 14 interviews were conducted (4 administration and 10 consultation group). Three main themes were identified: (1) functioning information in the G-DRG system: opportunities and obstacles, (2) general aspects concerning optimizing G-DRG systems by integrating additional information, and (3) ideas and requirements on how to proceed.
The study offers insights into the opportunities and obstacles of integrating functioning information in the G-DRG system. The relevance of functioning information was evident. However, the value of functioning information for the G-DRG system was seen critically. Integrating functioning information alone does not seem to be sufficient and a systems approach is needed.
Outdoor performance analyses of photovoltaic modules can be advantageous compared to indoor investigations, as they take into account the influences of natural test conditions on the modules. However, such outdoor performance assessments usually suffer from poor accuracies due to undefined test conditions for the modules. This paper reports on a comprehensive concept for improved outdoor analysis which results in performance data with indoor laboratory precision. The approach delivers current-voltage characteristics for even more test conditions than required by the standard IEC 61853-1. Hence, curves of modules’ electrical parameters above irradiance can be deduced for any temperatures. The concept allows precise determination of temperature coefficients for user-defined irradiances taking into account outdoor effects like light-soaking or light-induced degradation. The calibration and measurement uncertainty of the presented outdoor analysis method is evaluated quantitatively. For the measurements an advanced outdoor set-up was used.