julilili42/papers huggingface dataset:
Mechanical Strain Activates Planar Cell Polarity Signaling to Coordinate Vascular Cell Dynamics
2024-06-26

SUMMARY Mechanical stimuli, particularly laminar blood flow, play a crucial role in shaping the vascular system. Changes in the rate of blood flow manifest in altered shear stress, which activates signaling cascades that drive vascular remodeling. Consistently, dysregulation of the endothelial response to fluid shear forces and aberrant flow patterns both lead to pathological conditions, including impaired blood vessel development and atherosclerosis. Despite its importance, the mechanisms driving the coordinated cell behavior underlying vascular remodeling are not fully understood. Combining classical cell biological approaches with advanced image analysis, mathematical modeling, biomimetic strategies, and in vivo studies, we identify the planar cell polarity (PCP) protein Vangl1 as an enforcer of flow-dependent cell dynamics in the vascular system. We demonstrate that shear stress triggers the relocation of Vangl1 from an internal reservoir to the plasma membrane at the initiation of cell remodeling. Membrane enrichment of Vangl1 is mediated by a Coronin1C-dependent shift in the equilibrium between endo- and exocytosis and results in the spatial reorganization of another essential PCP protein, Frizzled6 (Fzd6). The resulting mutual exclusion of the core PCP proteins Fzd6 and Vangl1 augments differential junctional and cytoskeletal dynamics along the flow axis. Loss of Vangl1 limits the ability of endothelial cells to respond to shear forces in a coordinated fashion, resulting in irregular cell alignment along the flow direction and erroneous vessel sprouting. Together, these studies introduce core PCP signaling as a determinant of collective cell dynamics and organization of the vascular system.
Impact Assessment as a Legal Design Pattern—A “Timeless Way” of Managing Future Risks?
2024-06-26

Abstract Impact assessments are increasingly employed and debated as instruments for mitigating the fundamental rights risks associated with artificial intelligence, platforms and personal data processing. However, before their adoption in connection with technology and fundamental rights, impact assessments have been used for decades to mitigate large undertakings’ environmental and social impacts. An impact assessment is a process for collecting information to identify a future action’s effects and mitigate its unwanted effects. This article proposes that impact assessments represent a distinct legal design pattern with core elements that can be replicated in new legal contexts requiring ex-ante identification and mitigation of foreseeable risks. The tensions between diverging interests, temporality, epistemics and economics characterise this legal design pattern. The impact assessment process seeks to resolve these tensions by enabling translation between the regulator, the executor of the planned action and the stakeholders impacted by it. Awareness of the underlying patterns allows the lawmaker or the regulator to learn across diverse impact assessment models. Design pattern thinking advances research both on law and regulation by uncovering the tensions underling the design solution, as well as pattern interaction between legally mandated impact assessments and those representing other regulatory instruments. Finally, the approach raises awareness of the instrument’s shortcomings, including spheres where relying on complementary legal design patterns, such as precautionary principle, is more justified.
Changes in lean body mass with glucagon‐like peptide ‐1‐based therapies and mitigation strategies
2024-06-27

Abstract Weight loss induced by glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) and dual glucagon‐like peptide‐1 receptor (GLP‐1R)/glucose‐dependent insulinotropic polypeptide receptor agonists is coming closer to the magnitudes achieved with surgery. However, with greater weight loss there is concern about potential side effects on muscle quantity (mass), health and function. There is heterogeneity in the reported effects of GLP‐1‐based therapies on lean mass changes in clinical trials: in some studies, reductions in lean mass range between 40% and 60% as a proportion of total weight lost, while other studies show lean mass reductions of approximately 15% or less of total weight lost. There are several potential reasons underlying this heterogeneity, including population, drug‐specific/molecular, and comorbidity effects. Furthermore, changes in lean mass may not always reflect changes in muscle mass as the former measure includes not only muscle but also organs, bone, fluids, and water in fat tissue. Based on contemporary evidence with the addition of magnetic resonance imaging‐based studies, skeletal muscle changes with GLP‐1RA treatments appear to be adaptive: reductions in muscle volume seem to be commensurate with what is expected given ageing, disease status, and weight loss achieved, and the improvement in insulin sensitivity and muscle fat infiltration likely contributes to an adaptive process with improved muscle quality, lowering the probability for loss in strength and function. Nevertheless, factors such as older age and severity of disease may influence the selection of appropriate candidates for these therapies due to risk of sarcopenia. To further improve muscle health during weight loss, several pharmacological treatments to maintain or improve muscle mass designed in combination with GLP‐1‐based therapies are under development. Future research on GLP‐1‐based and other therapies designed for weight loss should focus on more accurate and meaningful assessments of muscle mass, composition, as well as function, mobility or strength, to better define their impact on muscle health for the substantial number of patients who will likely be taking these medications well into the future.
A Language Model–Powered Simulated Patient With Automated Feedback for History Taking: Prospective Study
2024-06-27

Background Although history taking is fundamental for diagnosing medical conditions, teaching and providing feedback on the skill can be challenging due to resource constraints. Virtual simulated patients and web-based chatbots have thus emerged as educational tools, with recent advancements in artificial intelligence (AI) such as large language models (LLMs) enhancing their realism and potential to provide feedback. Objective In our study, we aimed to evaluate the effectiveness of a Generative Pretrained Transformer (GPT) 4 model to provide structured feedback on medical students’ performance in history taking with a simulated patient. Methods We conducted a prospective study involving medical students performing history taking with a GPT-powered chatbot. To that end, we designed a chatbot to simulate patients’ responses and provide immediate feedback on the comprehensiveness of the students’ history taking. Students’ interactions with the chatbot were analyzed, and feedback from the chatbot was compared with feedback from a human rater. We measured interrater reliability and performed a descriptive analysis to assess the quality of feedback. Results Most of the study’s participants were in their third year of medical school. A total of 1894 question-answer pairs from 106 conversations were included in our analysis. GPT-4’s role-play and responses were medically plausible in more than 99% of cases. Interrater reliability between GPT-4 and the human rater showed “almost perfect” agreement (Cohen κ=0.832). Less agreement (κ&lt;0.6) detected for 8 out of 45 feedback categories highlighted topics about which the model’s assessments were overly specific or diverged from human judgement. Conclusions The GPT model was effective in providing structured feedback on history-taking dialogs provided by medical students. Although we unraveled some limitations regarding the specificity of feedback for certain feedback categories, the overall high agreement with human raters suggests that LLMs can be a valuable tool for medical education. Our findings, thus, advocate the careful integration of AI-driven feedback mechanisms in medical training and highlight important aspects when LLMs are used in that context.
Evolution of Defects, Morphology, and Strain during FAMAPbI3 Perovskite Vacuum Deposition: Insights from In Situ Photoluminescence and X-ray Scattering
2024-06-27

At present, the power conversion efficiency of single-junction perovskite-based solar cells reaches over 26%. The further efficiency increase of perovskite-based optoelectronic devices is limited mainly by defects, causing the nonradiative recombination of charge carriers. To improve efficiency and ensure reproducible fabrication of high-quality layers, it is crucial to understand the perovskite nucleation and growth mechanism along with associated process control to reduce the defect density. In this study, we investigate the growth kinetics of a promising narrow bandgap perovskite, formamidinium methylammonium lead iodide (FAMAPbI<sub>3</sub>), for high-performance single-junction solar cells. The temporal evolution of structural and optoelectronic properties during FAMAPbI<sub>3</sub> vacuum codeposition was inspected in real time by grazing-incidence wide-angle X-ray scattering and photoluminescence. Such a combination of analytical techniques unravels the evolution of intrinsic defect density and layer morphology correlated with lattice strain from the early stages of the perovskite deposition.
Implementation of Patient-Individualized 3D-Printed Models in Undergraduate Students’ Education for Various Prosthetic Treatments: A Cross-Sectional Survey Study
2024-06-27

Background: Due to rapid changes in dental practice, digital technologies have become prominent in undergraduate dental education at German universities in recent years. This shift has prompted a re-evaluation of content as well as teaching methods, particularly in courses where students are prepared for patient treatment. Traditional training on standardized models with resin teeth cannot cover the complexity of individual dental arch configuration encountered in patient situations. This study explores the use of 3D printing technology to create individualized models for prosthetic treatment simulations, aiming to evaluate students’ feedback towards their experience with this training setting. Methods: First, the study describes the design and fabrication of individualized models with exchangeable teeth based on intraoral scans, mounted on connected plates with distance holders that can be fixed to standard phantom heads. Second, students provided feedback through a questionnaire, assessing various aspects such as the effectiveness of the 3D-printed models compared to traditional frasaco models for preparation exercises. Results: The results indicated that the design of the realized models was feasible for preparation training (question no. 4: 93% positive rating) and showed positive perceptions of the 3D-printed models, with students finding them effective for preparation exercises and beneficial in bridging the gap between simulation and real patient situations (question no. 6: 69% positive rating). Conclusions: The study suggests that 3D printing technology offers a valuable tool in dental education, providing realistic and patient-specific scenarios for students to enhance their skills and readiness for clinical practice. Further improvements in material properties in hand with cost-effective approaches are essential for widespread implementation.
Quasinormal modes in modified gravity using physics-informed neural networks
2024-06-27

In this paper, we apply a novel approach based on physics-informed neural networks to the computation of quasinormal modes of black hole solutions in modified gravity. In particular, we focus on the case of Einstein-scalar-Gauss-Bonnet theory, with several choices of the coupling function between the scalar field and the Gauss-Bonnet invariant. This type of calculation introduces a number of challenges with respect to the case of general relativity, mainly due to the extra complexity of the perturbation equations and to the fact that the background solution is known only numerically. The solution of these perturbation equations typically requires sophisticated numerical techniques that are not easy to develop in computational codes. We show that physics-informed neural networks have an accuracy which is comparable to traditional numerical methods in the case of numerical backgrounds, while being very simple to implement. Additionally, the use of GPU parallelization is straightforward thanks to the use of standard machine learning environments.
KCa channel targeting impairs DNA repair and invasiveness of patient‐derived glioblastoma stem cells in culture and orthotopic mouse xenografts which only in part is predictable by KCa expression levels
2024-06-27

Abstract Prognosis of glioblastoma patients is still poor despite multimodal therapy. The highly brain‐infiltrating growth in concert with a pronounced therapy resistance particularly of mesenchymal glioblastoma stem‐like cells (GSCs) has been proposed to contribute to therapy failure. Recently, we have shown that a mesenchymal‐to‐proneural mRNA signature of patient derived GSC‐enriched (pGSC) cultures associates with in vitro radioresistance and gel invasion. Importantly, this pGSC mRNA signature is prognostic for patients' tumor recurrence pattern and overall survival. Two mesenchymal markers of the mRNA signature encode for IK Ca and BK Ca Ca 2+ ‐activated K + channels. Therefore, we analyzed here the effect of IK Ca ‐ and BK Ca ‐targeting concomitant to (fractionated) irradiation on radioresistance and glioblastoma spreading in pGSC cultures and in pGSC‐derived orthotopic xeno graft glioma mouse models. To this end, in vitro gel invasion, clonogenic survival, in vitro and in vivo residual DNA double strand breaks (DSBs), tumor growth, and brain invasion were assessed in the dependence on tumor irradiation and K + channel targeting. As a result, the IK Ca ‐ and BK Ca ‐blocker TRAM‐34 and paxilline, respectively, increased number of residual DSBs and (numerically) decreased clonogenic survival in some but not in all IK Ca ‐ and BK Ca ‐expressing pGSC cultures, respectively. In addition, BK Ca ‐ but not IK Ca ‐blockade slowed‐down gel invasion in vitro. Moreover, systemic administration of TRAM‐34 or paxilline concomitant to fractionated tumor irradiation increased in the xeno graft model(s) residual number of DSBs and attenuated glioblastoma brain invasion and (numerically) tumor growth. We conclude, that K Ca ‐blockade concomitant to fractionated radiotherapy might be a promising new strategy in glioblastoma therapy.
Parental verbal communication and modeling behavior during mealtimes shape offspring eating behavior – A systematic review with a focus on clinical implications for eating disorders
2024-06-27

The review outlines major fields of parent-child communication and modeling behavior around family meals which might be relevant to investigate and integrate into models of intergenerational transmission of eating behavior and disordered eating.
Inside Cover: Facile Energy Release from Substituted Dewar Isomers of 1,2‐Dihydro‐1,2‐Azaborinines Catalyzed by Coinage Metal Lewis Acids (Angew. Chem. Int. Ed. 30/2024)
2024-06-27

Coinage metals catalyze energy release from the Dewar isomer of 1,2-dihydroazaborinine—a promising molecular solar thermal (MOST) storage system, as shown by Holger F. Bettinger, Ivana Fleischer and co-workers in their Research Article (e202405818). Mechanistic studies corroborated by computations provide insights into the catalytic system, while showcasing the first crystal structure of the energy-rich Dewar dihydroazaborinine isomer coordinated to Ag(I).
Differential effects of hypnotherapy and cognitive behavioral therapy on the default mode network of depressed patients
2024-06-27

Hypnosis has been applied in healing procedures since the earliest of recorded history and today it is implemented in a wholesome concept Hypnotherapy (HT 1 ). On a neurophysiological level, hypnosis has been associated with parts of the Default Mode Network (DMN 2 ), but its effects on this network when induced in a treatment setting of a widespread disorder, namely depression, have never been investigated. Depression is associated with abnormal functional connectivity (FC 3 ) of the DMN. Cognitive Behavioral Therapy (CBT 4 ) has proven itself to be an effective treatment for depression; effects of CBT on DMN-related regions are heterogeneous. In the past years, HT was found to be a promising alternative or helpful adjunction. Yet, its underlying mechanisms remain to be unclear. In this original study 75 depressed patients receiving either CBT or HT were included and measured during resting-state before and after therapy with functional near-infrared-spectroscopy (fNIRS 5 ). On symptom level, results show a significant reduction in both groups. On a neurophysiological level, first exploratory analyses hint toward treatment effects in two components of the DMN. However, these effects do not withstand correction for multiple testing. Still, our study is a first stepstone in the investigation of neural mechanisms of HT and offers first ideas about possible implications.
Ophthalmological research in Germany: suggestions by an international expert panel
2024-06-27

Abstract Purpose To evaluate the research performance in ophthalmology in Germany based on the findings of the recent research map of the German Ophthalmological Society (DOG) and to suggest strategies for future improvements on a national level both to DOG as well as to politics. The focus is on preclinical and translational clinical research. Methods International expert panel evaluation and discussion organized by the Task Force Research of the German Ophthalmological Society (DOG). Results The international view on the German ophthalmological research landscape was generally positive. The value for money relationship was judged as very good. As Germany is facing an aging society and vision impairment will create an ever-increasing socioeconomic burden, the reviewers suggested several lines of future activities: an increased activity of securing intellectual property, more lay audience lobbying, intensified collaboration and critical mass building between “lighthouses” of ophthalmic research in Germany, as well as the establishment of a German national eye institute equivalent. Conclusion The ophthalmological research performance in Germany was rated to be very good by an international expert panel. Nonetheless significant improvements were requested in the fields of translation (clinical trials, IP), synergy between specialized institutions and governmental funding for a German center for eye research.
Innentitelbild: Facile Energy Release from Substituted Dewar Isomers of 1,2‐Dihydro‐1,2‐Azaborinines Catalyzed by Coinage Metal Lewis Acids (Angew. Chem. 30/2024)
2024-06-27

Coinage metals catalyze energy release from the Dewar isomer of 1,2-dihydroazaborinine—a promising molecular solar thermal (MOST) storage system, as shown by Holger F. Bettinger, Ivana Fleischer and co-workers in their Research Article (e202405818). Mechanistic studies corroborated by computations provide insights into the catalytic system, while showcasing the first crystal structure of the energy-rich Dewar dihydroazaborinine isomer coordinated to Ag(I).
Comparative analysis of open-source federated learning frameworks - a literature-based survey and review
2024-06-28

Abstract While Federated Learning (FL) provides a privacy-preserving approach to analyze sensitive data without centralizing training data, the field lacks an detailed comparison of emerging open-source FL frameworks. Furthermore, there is currently no standardized, weighted evaluation scheme for a fair comparison of FL frameworks that would support the selection of a suitable FL framework. This study addresses these research gaps by conducting a comparative analysis of 15 individual open-source FL frameworks filtered by two selection criteria, using the literature review methodology proposed by Webster and Watson. These framework candidates are compared using a novel scoring schema with 15 qualitative and quantitative evaluation criteria, focusing on features, interoperability, and user friendliness. The evaluation results show that the FL framework Flower outperforms its peers with an overall score of 84.75%, while Fedlearner lags behind with a total score of 24.75%. The proposed comparison suite offers valuable initial guidance for practitioners and researchers in selecting an FL framework for the design and development of FL-driven systems. In addition, the FL framework comparison suite is designed to be adaptable and extendable accommodating the inclusion of new FL frameworks and evolving requirements.
Delayed Overshooting: The Case for Information Rigidities
2024-06-28

We provide evidence that the delayed overshooting puzzle reflects a slow adjustment of exchange rate expectations to monetary policy shocks rather than a failure of uncovered interest parity. Consistent with this evidence, we put forward a New Keynesian model in which uncovered interest parity holds, but there are information rigidities: investors do not observe monetary policy shocks but learn rationally from unanticipated shifts in monetary policy about the state of the economy. We estimate the model and find it can account for the joint responses of the spot exchange rate, forward exchange rates, and excess currency returns to monetary policy shocks. (JEL D83, E12, E31, E43, E52, F31)
Plasma amyloid beta X‐42/X‐40 ratio and cognitive decline in suspected early and preclinical Alzheimer's disease
2024-06-28

Abstract INTRODUCTION Blood‐based biomarkers are a cost‐effective and minimally invasive method for diagnosing the early and preclinical stages of amyloid positivity (AP). Our study aims to investigate our novel immunoprecipitation‐immunoassay (IP‐IA) as a test for predicting cognitive decline. METHODS We measured levels of amyloid beta (Aβ)X‐40 and AβX‐42 in immunoprecipitated eluates from the DELCODE cohort. Receiver‐operating characteristic (ROC) curves, regression analyses, and Cox proportional hazard regression models were constructed to predict AP by Aβ42/40 classification in cerebrospinal fluid (CSF) and conversion to mild cognitive impairment (MCI) or dementia. RESULTS We detected a significant correlation between AßX‐42/X‐40 in plasma and CSF ( r = 0.473). Mixed‐modeling analysis revealed a substantial prediction of AßX‐42/X‐40 with an area under the curve (AUC) of 0.81 for AP (sensitivity: 0.79, specificity: 0.74, positive predictive value [PPV]: 0.71, negative predictive value [NPV]: 0.81). In addition, lower AβX‐42/X‐40 ratios were associated with negative PACC5 slopes, suggesting cognitive decline. DISCUSSION Our results suggest that assessing the plasma AβX‐42/X‐40 ratio via our semiautomated IP‐IA is a promising biomarker when examining patients with early or preclinical AD. Highlights New plasma Aβ42/Aβ40 measurement using immunoprecipitation–immunoassay Plasma Aβ42/Aβ40 associated with longitudinal cognitive decline Promising biomarker to detect subjective cognitive decline at‐risk for brain amyloid positivity