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1. PRISMe: A Novel LLM-Powered Tool for Interactive Privacy Policy Assessment

Author

Freiberger, Vincent, Fleig, Arthur, and Buchmann, Erik

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence, H.m, I.2.7
Abstract

Protecting online privacy requires users to engage with and comprehend website privacy policies, but many policies are difficult and tedious to read. We present PRISMe (Privacy Risk Information Scanner for Me), a novel Large Language Model (LLM)-driven privacy policy assessment tool, which helps users to understand the essence of a lengthy, complex privacy policy while browsing. The tool, a browser extension, integrates a dashboard and an LLM chat. One major contribution is the first rigorous evaluation of such a tool. In a mixed-methods user study (N=22), we evaluate PRISMe's efficiency, usability, understandability of the provided information, and impacts on awareness. While our tool improves privacy awareness by providing a comprehensible quick overview and a quality chat for in-depth discussion, users note issues with consistency and building trust in the tool. From our insights, we derive important design implications to guide future policy analysis tools., Comment: 30 pages

Published
2025

2. Assessing Privacy Policies with AI: Ethical, Legal, and Technical Challenges

Author

Aydin, Irem, Diebel-Fischer, Hermann, Freiberger, Vincent, Möller-Klapperich, Julia, Buchmann, Erik, Färber, Michael, Lauber-Rönsberg, Anne, and Platow, Birte

Subjects
Computer Science - Computers and Society
Abstract

The growing use of Machine Learning and Artificial Intelligence (AI), particularly Large Language Models (LLMs) like OpenAI's GPT series, leads to disruptive changes across organizations. At the same time, there is a growing concern about how organizations handle personal data. Thus, privacy policies are essential for transparency in data processing practices, enabling users to assess privacy risks. However, these policies are often long and complex. This might lead to user confusion and consent fatigue, where users accept data practices against their interests, and abusive or unfair practices might go unnoticed. LLMss can be used to assess privacy policies for users automatically. In this interdisciplinary work, we explore the challenges of this approach in three pillars, namely technical feasibility, ethical implications, and legal compatibility of using LLMs to assess privacy policies. Our findings aim to identify potential for future research, and to foster a discussion on the use of LLM technologies for enabling users to fulfil their important role as decision-makers in a constantly developing AI-driven digital economy., Comment: Published at AISyS 2024

Published
2024

3. Integrating Novel Stellarator Single-Stage Optimization Algorithms to Design the Columbia Stellarator Experiment

Author

Baillod, A., Paul, E. J., Rawlinson, G., Haque, M., Freiberger, S. W., and Thapa, S.

Subjects
Physics - Plasma Physics
Abstract

The Columbia Stellarator eXperiment (CSX), currently being designed at Columbia University, aims to test theoretical predictions related to QA plasma behavior, and to pioneer the construction of an optimized stellarator using three-dimensional, non-insulated high-temperature superconducting (NI-HTS) coils. The magnetic configuration is generated by a combination of two circular planar poloidal field (PF) coils and two 3D-shaped interlinked (IL) coils, with the possibility to add windowpane coils to enhance shaping and experimental flexibility. The PF coils and vacuum vessel are repurposed from the former Columbia Non-Neutral Torus (CNT) experiment, while the IL coils will be custom-wound in-house using NI-HTS tapes. To obtain a plasma shape that meets the physics objectives with a limited number of coils, novel single-stage optimization techniques are employed, optimizing both the plasma and coils concurrently, in particular targeting a tight aspect ratio QA plasma and minimized strain on the HTS tape. Despite the increased complexity due to the expanded degrees of freedom, these methods successfully identify optimized plasma geometries that can be realized by coils meeting engineering specifications. This paper discusses the derivation of the constraints and objectives specific to CSX, and describe how two recently developed single-stage optimization methodologies are applied to the design of CSX. A set of selected configurations for CSX is then described in detail., Comment: 36 pages, 12 figures

Published
2024

4. Relevance in Three Dimensions: Teaching Religion with the Comparative Method

Author

Oliver Freiberger

Abstract

This article argues that three dimensions of relevance can be identified for the academic study of religion as it is taught at the university: (1) Foundations; (2) General Education; and (3) Application. The analytical distinction of these dimensions also reveals that they are inextricably linked and co-dependent. This model may help to sort out the tasks and opportunities of a secular, comparative study of religion in academia and society. Importantly, for each dimension, the comparative method has a crucial role.

Published
2024
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5. First Access to ELM-free Negative Triangularity at Low Aspect Ratio

Author

Nelson, A. O., Vincent, C., Anand, H., Lovell, J., Parisi, J. F., Wilson, H. S., Imada, K., Wehner, W. P., Kochan, M., Blackmore, S., McArdle, G., Guizzo, S., Rondini, L., Freiberger, S., and Paz-Soldan, C.

Subjects
Physics - Plasma Physics
Abstract

A plasma scenario with negative triangularity (NT) shaping is achieved on MAST-U for the first time. While edge localized modes (ELMs) are eventually suppressed as the triangularity is decreased below $\delta$ < -0.06, an extended period of H-mode operation with Type-III ELMs is sustained at less negative $\delta$ even through access to the second stability region for ideal ballooning modes is closed. This documents a qualitative difference from the ELM-free access conditions documented in NT scenarios on conventional aspect ratio machines. The electron temperature at the pedestal top drops across the transition to ELM-free operation, but a steady rise in core temperature as $\delta$ is decreased allows for similar normalized beta in the ELM-free NT and H-mode positive triangularity shapes.

Published
2024

6. LayerShuffle: Enhancing Robustness in Vision Transformers by Randomizing Layer Execution Order

Author

Freiberger, Matthias, Kun, Peter, Løvlie, Anders Sundnes, and Risi, Sebastian

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Due to their architecture and how they are trained, artificial neural networks are typically not robust toward pruning or shuffling layers at test time. However, such properties would be desirable for different applications, such as distributed neural network architectures where the order of execution cannot be guaranteed or parts of the network can fail during inference. In this work, we address these issues through a number of training approaches for vision transformers whose most important component is randomizing the execution order of attention modules at training time. With our proposed approaches, vision transformers are capable to adapt to arbitrary layer execution orders at test time assuming one tolerates a reduction (about 20\%) in accuracy at the same model size. We analyse the feature representations of our trained models as well as how each layer contributes to the models prediction based on its position during inference. Our analysis shows that layers learn to contribute differently based on their position in the network. Finally, we layer-prune our models at test time and find that their performance declines gracefully. Code available at https://github.com/matfrei/layershuffle.

Published
2024

10. AI-generated art perceptions with GenFrame -- an image-generating picture frame

Author

Kun, Peter, Freiberger, Matthias, Løvlie, Anders Sundnes, and Risi, Sebastian

Subjects
Computer Science - Human-Computer Interaction
Abstract

Image-generation models are changing how we express ourselves in visual art. However, what people think of AI-generated art is still largely unexplored, especially compared to traditional art. In this paper, we present the design of an interactive research product, GenFrame - an image-generating picture frame that appears as a traditional painting but offers the viewer the agency to modify the depicted painting. In the current paper, we report on a study where we deployed the GenFrame in a traditional art museum and interviewed visitors about their views on AI art. When provoked by AI-generated art, people need more of the artist's backstory and emotional journey to make the artwork commensurate with traditional art. However, generative AI-enabled interactive experiences open new ways of engaging with art when a turn of a dial can modify art styles or motifs on a painting. A demo can be seen here: https://youtu.be/1rhW4fazaBY., Comment: Design Research Society conference 2024 (DRS2024), Boston 24-28 June 2024

Published
2024
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11. Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Exploration

Author

Meyer, Louie Søs, Aaen, Johanne Engel, Tranberg, Anitamalina Regitse, Kun, Peter, Freiberger, Matthias, Risi, Sebastian, and Løvlie, Anders Sundnes

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Computer Vision and Pattern Recognition
Abstract

This Research through Design paper explores how object detection may be applied to a large digital art museum collection to facilitate new ways of encountering and experiencing art. We present the design and evaluation of an interactive application called SMKExplore, which allows users to explore a museum's digital collection of paintings by browsing through objects detected in the images, as a novel form of open-ended exploration. We provide three contributions. First, we show how an object detection pipeline can be integrated into a design process for visual exploration. Second, we present the design and development of an app that enables exploration of an art museum's collection. Third, we offer reflections on future possibilities for museums and HCI researchers to incorporate object detection techniques into the digitalization of museums.

Published
2024
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12. Legally Binding but Unfair? Towards Assessing Fairness of Privacy Policies

Author

Freiberger, Vincent and Buchmann, Erik

Subjects
Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, K.4.m
Abstract

Privacy policies are expected to inform data subjects about their data protection rights and should explain the data controller's data management practices. Privacy policies only fulfill their purpose, if they are correctly interpreted, understood, and trusted by the data subject. This implies that a privacy policy is written in a fair way, e.g., it does not use polarizing terms, does not require a certain education, or does not assume a particular social background. We outline our approach to assessing fairness in privacy policies. We identify from fundamental legal sources and fairness research, how the dimensions informational fairness, representational fairness and ethics / morality are related to privacy policies. We propose options to automatically assess policies in these fairness dimensions, based on text statistics, linguistic methods and artificial intelligence. We conduct initial experiments with German privacy policies to provide evidence that our approach is applicable. Our experiments indicate that there are issues in all three dimensions of fairness. This is important, as future privacy policies may be used in a corpus for legal artificial intelligence models., Comment: Accepted at IWSPA 2024

Published
2024

14. The Current State of Biotransformation Science – Industry Survey of In Vitro and In Vivo Practices, Clinical Translation, and Future Trends

Author

Savaryn, John P., Coe, Kevin, Cerny, Matthew A., Colizza, Kevin, Moliner, Patricia, King, Lloyd, Ma, Bin, Atherton, Jim, Auclair, Adam, Cancilla, Mark T., Eno, Marsha, Jurva, Ulrik, Yue, Qin, Zhu, Sean Xiaochun, Freiberger, Elyse, Zhong, Guo, Barlock, Ben, Nachtigall, Jonny, Laboureur, Laurent, Pusalkar, Sandeepraj, Guo, Runcong, Niehues, Michael, Hauri, Simon, Carreras, Ester Tor, Maurer, Christine, Prakash, Chandra, and Jenkins, Gary J.

Published
2024
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17. Fairness Certification for Natural Language Processing and Large Language Models

Author

Freiberger, Vincent and Buchmann, Erik

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Machine Learning, 68T50, I.2.7
Abstract

Natural Language Processing (NLP) plays an important role in our daily lives, particularly due to the enormous progress of Large Language Models (LLM). However, NLP has many fairness-critical use cases, e.g., as an expert system in recruitment or as an LLM-based tutor in education. Since NLP is based on human language, potentially harmful biases can diffuse into NLP systems and produce unfair results, discriminate against minorities or generate legal issues. Hence, it is important to develop a fairness certification for NLP approaches. We follow a qualitative research approach towards a fairness certification for NLP. In particular, we have reviewed a large body of literature on algorithmic fairness, and we have conducted semi-structured expert interviews with a wide range of experts from that area. We have systematically devised six fairness criteria for NLP, which can be further refined into 18 sub-categories. Our criteria offer a foundation for operationalizing and testing processes to certify fairness, both from the perspective of the auditor and the audited organization., Comment: In depth discussion of our results can be found in the Appendix B

Published
2024

22. PATHFINDER-CHD: prospective registry on adults with congenital heart disease, abnormal ventricular function, and/or heart failure as a foundation for establishing rehabilitative, prehabilitative, preventive, and health-promoting measures: rationale, aims, design and methods

Author

Freilinger, Sebastian, Kaemmerer, Harald, Pittrow, Robert D., Achenbach, Stefan, Baldus, Stefan, Dewald, Oliver, Ewert, Peter, Freiberger, Annika, Gorenflo, Matthias, Harig, Frank, Hohmann, Christopher, Holdenrieder, Stefan, Hörer, Jürgen, Huntgeburth, Michael, Hübler, Michael, Kohls, Niko, Klawonn, Frank, Kozlik-Feldmann, Rainer, Kaulitz, Renate, Loßnitzer, Dirk, Mellert, Friedrich, Nagdyman, Nicole, Nordmeyer, Johannes, Pittrow, Benjamin A., Pittrow, Leonard B., Rickers, Carsten, Rosenkranz, Stefan, Schelling, Jörg, Sinning, Christoph, Suleiman, Mathieu N., von Kodolitsch, Yskert, von Scheidt, Fabian, and Kaemmerer-Suleiman, Ann-Sophie

Published
2024
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25. Short physical performance battery is not associated with falls and injurious falls in older persons: longitudinal data of the SCOPE project

Author

Freiberger, Ellen, Fabbietti, Paolo, Corsonello, Andrea, Lattanzio, Fabrizia, Sieber, Cornel, Tap, Lisanne, Mattace-Raso, Francesco, Ärnlöv, Johan, Carlsson, Axel C., Roller-Wirnsberger, Regina, Wirnsberger, Gerhard, Moreno-Gonzalez, Rafael, Formiga, Francesc, Martinez, Sara Lainez, Gil, Pedro, Kostka, Tomasz, Guligowska, Agnieszka, Yehoshua, Ilan, Melzer, Itshak, and Kob, Robert

Published
2024
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26. Fooling Contrastive Language-Image Pre-trained Models with CLIPMasterPrints

Author

Freiberger, Matthias, Kun, Peter, Igel, Christian, Løvlie, Anders Sundnes, and Risi, Sebastian

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Models leveraging both visual and textual data such as Contrastive Language-Image Pre-training (CLIP), are the backbone of many recent advances in artificial intelligence. In this work, we show that despite their versatility, such models are vulnerable to what we refer to as fooling master images. Fooling master images are capable of maximizing the confidence score of a CLIP model for a significant number of widely varying prompts, while being either unrecognizable or unrelated to the attacked prompts for humans. The existence of such images is problematic as it could be used by bad actors to maliciously interfere with CLIP-trained image retrieval models in production with comparably small effort as a single image can attack many different prompts. We demonstrate how fooling master images for CLIP (CLIPMasterPrints) can be mined using stochastic gradient descent, projected gradient descent, or blackbox optimization. Contrary to many common adversarial attacks, the blackbox optimization approach allows us to mine CLIPMasterPrints even when the weights of the model are not accessible. We investigate the properties of the mined images, and find that images trained on a small number of image captions generalize to a much larger number of semantically related captions. We evaluate possible mitigation strategies, where we increase the robustness of the model and introduce an approach to automatically detect CLIPMasterPrints to sanitize the input of vulnerable models. Finally, we find that vulnerability to CLIPMasterPrints is related to a modality gap in contrastive pre-trained multi-modal networks. Code available at https://github.com/matfrei/CLIPMasterPrints., Comment: This work was supported by a research grant (40575) from VILLUM FONDEN

Published
2023

27. Artificial intelligence-based, non-invasive assessment of the central aortic pressure in adults after operative or interventional treatment of aortic coarctation

Author

Renate Oberhoffer, Peter Ewert, Harald Kaemmerer, Nicole Nagdyman, Oliver Dewald, Frank Klawonn, Michael Huntgeburth, Andreas Eicken, Christian Meierhofer, Sebastian Freilinger, Martin Middeke, Pinar Bambul Heck, Annika Freiberger, Frank Harig, Manuel Lösch, Fritz Mellert, Fabian von Scheidt, Elsa Ury, Nicole Wolfrum, Ann-Sophie Kaemmerer-Suleiman, and Mathieu N. Suleiman

Subjects
Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Aortic coarctation (CoA) is a congenital anomaly leading to upper-body hypertension and lower-body hypotension. Despite surgical or interventional treatment, arterial hypertension may develop and contribute to morbidity and mortality. Conventional blood pressure (BP) measurement methods lack precision for individual diagnoses and therapeutic decisions. This study evaluated the use of artificial intelligence-based pulse wave analysis (AI-PWA) to assess central aortic blood pressure (CABP) and related parameters in post-treatment CoA patients.Methods This exploratory, cross-sectional study enrolled 47 adults with CoA, between June 2023 and May 2024. Peripheral BP (PBP) was conventionally measured, and CABP was assessed using the VascAssist2 (inmediQ, Butzbach, Germany). Hypertension was defined by systolic BP≥140 mm Hg and/or diastolic BP≥90 mm Hg for PBP. Using AI-PWA, patients with systolic CABP≥130 mm Hg and/or diastolic BP≥90 mm Hg were classified as hypertensive.Results The study cohort’s age was 41.5±13.7 years, with all patients having undergone previous aortic surgery or intervention. PBP measurements showed a systolic BP of 135.4±14.4 mm Hg at the upper and 147.8±20.3 mm Hg at the lower extremities. CABP measurements were significantly lower, with a systolic BP of 114.3±15.8 mm Hg (p

Published
2025
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28. MarioGPT: Open-Ended Text2Level Generation through Large Language Models

Author

Sudhakaran, Shyam, González-Duque, Miguel, Glanois, Claire, Freiberger, Matthias, Najarro, Elias, and Risi, Sebastian

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

Procedural Content Generation (PCG) is a technique to generate complex and diverse environments in an automated way. However, while generating content with PCG methods is often straightforward, generating meaningful content that reflects specific intentions and constraints remains challenging. Furthermore, many PCG algorithms lack the ability to generate content in an open-ended manner. Recently, Large Language Models (LLMs) have shown to be incredibly effective in many diverse domains. These trained LLMs can be fine-tuned, re-using information and accelerating training for new tasks. Here, we introduce MarioGPT, a fine-tuned GPT2 model trained to generate tile-based game levels, in our case Super Mario Bros levels. MarioGPT can not only generate diverse levels, but can be text-prompted for controllable level generation, addressing one of the key challenges of current PCG techniques. As far as we know, MarioGPT is the first text-to-level model and combined with novelty search it enables the generation of diverse levels with varying play-style dynamics (i.e. player paths) and the open-ended discovery of an increasingly diverse range of content. Code available at https://github.com/shyamsn97/mario-gpt.

Published
2023

32. A Prospective Study of the IlluminOss Photodynamic Nail System for Pelvic Stabilization

Author

Santiago A. Lozano-Calderon, MD, PhD, Marcos R. Gonzalez, MD, Joseph O. Werenski, BS, Kayla Quinn, NP, Diana Freiberger, NP, and Kevin A. Raskin, MD

Subjects
Orthopedic surgery, RD701-811
Abstract

Background:. The stabilization of metastatic lesions in the periacetabular region can be successfully performed using percutaneous techniques. Photodynamic nails (PDNs) are among the available tools for stabilization. Data on postoperative complications and functional outcomes are, however, scarce. Methods:. Patients undergoing percutaneous stabilization using PDNs (IlluminOss Medical) for impending or actual minimally displaced pathological fractures of the pelvis from metastatic bone disease, multiple myeloma, or primary bone lymphoma were enrolled prospectively. Outcomes were assessed preoperatively and postoperatively at the 2-day, 2-week, 6-week, 3-month, 6-month, and 1-year time points. Functional outcomes assessed included the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function, PROMIS Pain Interference, Combined Pain and Ambulatory Function (CPAF), EuroQol-Visual Analogue Scale (EQ-VAS), and Musculoskeletal Tumor Society (MSTS) scores. Pain was assessed using a VAS. Results:. A total of 30 patients treated with PDNs were included. The median VAS pain score dropped from 60 points preoperatively to 30 at 6 weeks postoperatively (p = 0.004). The median CPAF score improved from 6 preoperatively to 7 postoperatively at the 6-week mark. The median EQ-VAS score showed significant improvement at 6 weeks (70 versus 50; p = 0.006). The median 2-week PROMIS Pain Interference score was significantly lower than preoperatively (64.1 versus 66.9; p = 0.03). An improvement in the median PROMIS Physical Function score was seen at 6 weeks following surgery compared with preoperatively (37 versus 30.1; p = 0.001). A significant improvement in the MSTS score was seen as soon as 2 days after surgery (77% versus 40%; p < 0.0001). Conclusions:. Among patients with pelvic bone metastases, multiple myeloma, or primary bone lymphoma, we found that treatment using PDNs resulted in immediate return to ambulation and rapid functional outcome improvement, with low complication rates. In this population, this technique represents a safe alternative to open surgery. Level of Evidence:. Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Published
2024
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33. Hardware-aware mobile building block evaluation for computer vision

Author

Bonnaerens, Maxim, Freiberger, Matthias, Verhelst, Marian, and Dambre, Joni

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this work we propose a methodology to accurately evaluate and compare the performance of efficient neural network building blocks for computer vision in a hardware-aware manner. Our comparison uses pareto fronts based on randomly sampled networks from a design space to capture the underlying accuracy/complexity trade-offs. We show that our approach allows to match the information obtained by previous comparison paradigms, but provides more insights in the relationship between hardware cost and accuracy. We use our methodology to analyze different building blocks and evaluate their performance on a range of embedded hardware platforms. This highlights the importance of benchmarking building blocks as a preselection step in the design process of a neural network. We show that choosing the right building block can speed up inference by up to a factor of 2x on specific hardware ML accelerators.

Published
2022

36. Integrating novel stellarator single-stage optimization algorithms to design the Columbia stellarator experiment

Author

A. Baillod, E.J. Paul, G. Rawlinson, M. Haque, S.W. Freiberger, and S. Thapa

Subjects
optimization, stellarator, CSX, quasisymmetry, coil, single-stage optimization, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

The Columbia Stellarator eXperiment (CSX), currently being designed at Columbia University, aims to test theoretical predictions related to QA plasma behavior, and to pioneer the construction of an optimized stellarator using three-dimensional, non-insulated high-temperature superconducting (NI-HTS) coils. The magnetic configuration is generated by a combination of two circular planar poloidal field (PF) coils and two 3D-shaped interlinked (IL) coils, with the possibility to add windowpane coils to enhance shaping and experimental flexibility. The PF coils and vacuum vessel are repurposed from the former Columbia Non-Neutral Torus experiment, while the IL coils will be custom-wound in-house using NI-HTS tapes. To obtain a plasma shape that meets the physics objectives with a limited number of coils, novel single-stage optimization techniques are employed, optimizing both the plasma and coils concurrently, in particular targeting a tight aspect ratio QA plasma and minimized strain on the HTS tape. Despite the increased complexity due to the expanded degrees of freedom, these methods successfully identify optimized plasma geometries that can be realized by coils meeting engineering specifications. This paper discusses the derivation of the constraints and objectives specific to CSX, and describe how two recently developed single-stage optimization methodologies are applied to the design of CSX. A set of selected configurations for CSX is then described in detail.

Published
2025
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38. Does Heart Rate Variability Predict Impairment of Operational Performance in Divers?

Author

John Freiberger, Bruce Derrick, Ki H. Chon, Md Billal Hossain, Hugo F. Posada-Quintero, Mary Cooter, and Richard Moon

Subjects
heart rate variability, diving, narcosis, nitrogen, carbon dioxide, oxygen toxicity, Chemical technology, TP1-1185
Abstract

We examined data from Naval Sea Systems Command grant project N0463A-12-C-001, “Hypercapnia: cognitive effects and monitoring”, with the objective of validating or repudiating heart rate variability (HRV) as a warning sign of cognitive impairment from diving gas narcosis or oxygen toxicity. We compared HRV feature scores to their temporally corresponding cognitive outcomes under normal and narcotizing conditions to identify specific HRV features associated with cognitive changes. N0463A-12-C-001 was conducted between 17 September 2013 and 29 January 2016 and employed NASA’s multi-attribute task battery (MATB-II) flight simulator to examine the independent effects of CO2, N2, and O2 partial pressure on diver performance at simulated depths up to 61 msw (200 fsw). We assessed the association of 23 distinct HRV features scores from 432 of the study’s analyzable exposure stages in relation to MATB-II’s four performance subclasses (motor, memory, attention, strategy) while controlling for exercise and CO2, N2, and O2 gas partial pressure. Performance decrements were associated with normalized high-frequency HRVfeatures (HFnu, p = 0.0016) and the number of pairs of successive R-R intervals that differed by more than 50 ms (NN50count1, p = 0.04). Secondary analysis with stratification restricted to non-exercise stages showed that several HRV parameters, including root mean square of the successive difference (RMSSD, p = 0.0015), width of Poincaré plot (p = 0.0017), NN50count1 (p = 0.0019), and standard deviation of normal-to-normal R peaks (p = 0.0082), were associated with performance impairment. The RMSSD association retained statistical significance after Bonferroni correction for multiple tests. HRV features collected from divers tested under narcotizing conditions of breathing gas partial pressure and exercise were associated with performance impairment.

Published
2024
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39. World guidelines for falls prevention and management for older adults: a global initiative

Author

Montero-Odasso, Manuel, van der Velde, Nathalie, Martin, Finbarr C, Petrovic, Mirko, Tan, Maw Pin, Ryg, Jesper, Aguilar-Navarro, Sara, Alexander, Neil B, Becker, Clemens, Blain, Hubert, Bourke, Robbie, Cameron, Ian D, Camicioli, Richard, Clemson, Lindy, Close, Jacqueline, Delbaere, Kim, Duan, Leilei, Duque, Gustavo, Dyer, Suzanne M, Freiberger, Ellen, Ganz, David A, Gómez, Fernando, Hausdorff, Jeffrey M, Hogan, David B, Hunter, Susan MW, Jauregui, Jose R, Kamkar, Nellie, Kenny, Rose-Anne, Lamb, Sarah E, Latham, Nancy K, Lipsitz, Lewis A, Liu-Ambrose, Teresa, Logan, Pip, Lord, Stephen R, Mallet, Louise, Marsh, David, Milisen, Koen, Moctezuma-Gallegos, Rogelio, Morris, Meg E, Nieuwboer, Alice, Perracini, Monica R, Pieruccini-Faria, Frederico, Pighills, Alison, Said, Catherine, Sejdic, Ervin, Sherrington, Catherine, Skelton, Dawn A, Dsouza, Sabestina, Speechley, Mark, Stark, Susan, Todd, Chris, Troen, Bruce R, van der Cammen, Tischa, Verghese, Joe, Vlaeyen, Ellen, Watt, Jennifer A, Masud, Tahir, Singh, Devinder Kaur Ajit, Aguilar-Navarro, Sara G, Caona, Edgar Aguilera, Allen, Natalie, Anweiller, Cedric, Avila-Funes, Alberto, Santos, Renato Barbosa, Batchelor, Francis, Beauchamp, Marla, Birimoglu, Canan, Bohlke, Kayla, Bourke, Robert, Bouzòn, Christina Alonzo, Bridenbaugh, Stephanie, Buendia, Patricio Gabriel, Cameron, Ian, Canning, Colleen, Cano-Gutierrez, Carlos Alberto, Carbajal, Juan Carlos, de Abreu, Daniela Cristina Carvalho, Casas-Herrero, Alvaro, Ceriani, Alejandro, Cesari, Matteo, Chiari, Lorenzo, Alemǻn, Luis Manuel Cornejo, Dawson, Rik, Doody, Paul, Dyer, Suzanne, Ellmers, Toby, Fairhall, Nicola, Ferruci, Luigi, and Frith, James

Subjects
Biomedical and Clinical Sciences, Health Services and Systems, Public Health, Health Sciences, Clinical Sciences, Aging, Prevention, Clinical Research, Patient Safety, Physical Injury - Accidents and Adverse Effects, Health and social care services research, 8.1 Organisation and delivery of services, 7.1 Individual care needs, Management of diseases and conditions, Good Health and Well Being, Aged, Caregivers, Humans, Independent Living, Quality of Life, Risk Assessment, falls, injury, aged, guidelines, recommendations, clinical practice, world, global, consensus, older people, Task Force on Global Guidelines for Falls in Older Adults, Public Health and Health Services, Psychology, Geriatrics, Clinical sciences, Health services and systems, Applied and developmental psychology
Abstract

Backgroundfalls and fall-related injuries are common in older adults, have negative effects on functional independence and quality of life and are associated with increased morbidity, mortality and health related costs. Current guidelines are inconsistent, with no up-to-date, globally applicable ones present.Objectivesto create a set of evidence- and expert consensus-based falls prevention and management recommendations applicable to older adults for use by healthcare and other professionals that consider: (i) a person-centred approach that includes the perspectives of older adults with lived experience, caregivers and other stakeholders; (ii) gaps in previous guidelines; (iii) recent developments in e-health and (iv) implementation across locations with limited access to resources such as low- and middle-income countries.Methodsa steering committee and a worldwide multidisciplinary group of experts and stakeholders, including older adults, were assembled. Geriatrics and gerontological societies were represented. Using a modified Delphi process, recommendations from 11 topic-specific working groups (WGs), 10 ad-hoc WGs and a WG dealing with the perspectives of older adults were reviewed and refined. The final recommendations were determined by voting.Recommendationsall older adults should be advised on falls prevention and physical activity. Opportunistic case finding for falls risk is recommended for community-dwelling older adults. Those considered at high risk should be offered a comprehensive multifactorial falls risk assessment with a view to co-design and implement personalised multidomain interventions. Other recommendations cover details of assessment and intervention components and combinations, and recommendations for specific settings and populations.Conclusionsthe core set of recommendations provided will require flexible implementation strategies that consider both local context and resources.

Published
2022

40. Association of BMI, lipid-lowering medication, and age with prevalence of type 2 diabetes in adults with heterozygous familial hypercholesterolaemia: a worldwide cross-sectional study

Author

Elshorbagy, Amany, Lyons, Alexander R.M., Vallejo-Vaz, Antonio J., Stevens, Christophe A.T., Dharmayat, Kanika I., Brandts, Julia, Catapano, Alberico L., Freiberger, Tomas, Hovingh, G. Kees, Mata, Pedro, Raal, Frederick J., Santos, Raul D., Soran, Handrean, Watts, Gerald F., Abifadel, Marianne, Aguilar-Salinas, Carlos A., Alhabib, Khalid F., Alkhnifsawi, Mutaz, Almahmeed, Wael, Alonso, Rodrigo, Al-Rasadi, Khalid, Al-Sarraf, Ahmad, Ashavaid, Tester F., Banach, Maciej, Binder, Christoph J., Bourbon, Mafalda, Brunham, Liam R., Chlebus, Krzysztof, Corral, Pablo, Cruz, Diogo, Davletov, Kairat, Descamps, Olivier S., Ezhov, Marat, Gaita, Dan, Groselj, Urh, Harada-Shiba, Mariko, Holven, Kirsten B., Kayikcioglu, Meral, Khovidhunkit, Weerapan, Lalic, Katarina, Latkovskis, Gustavs, Laufs, Ulrich, Liberopoulos, Evangelos, Lima-Martinez, Marcos M., Lin, Jie, Maher, Vincent, Marais, A. David, März, Winfried, Mirrakhimov, Erkin, Miserez, André R., Mitchenko, Olena, Nawawi, Hapizah, Nordestgaard, Børge G., Panayiotou, Andrie G., Paragh, György, Petrulioniene, Zaneta, Pojskic, Belma, Postadzhiyan, Arman, Reda, Ashraf, Reiner, Željko, Reyes, Ximena, Sadiq, Fouzia, Sadoh, Wilson E., Schunkert, Heribert, Shek, Aleksandr B., Stroes, Erik, Su, Ta-Chen, Subramaniam, Tavintharan, Susekov, Andrey V., Tilney, Myra, Tomlinson, Brian, Truong, Thanh-Huong, Tselepis, Alexandros D., Tybjærg-Hansen, Anne, Vázquez, Alejandra C., Viigimaa, Margus, Vohnout, Branislav, Wang, Luya, Yamashita, Shizuya, Arca, Marcello, Averna, Maurizio, Schreier, Laura, Pang, Jing, Ebenbichler, Christoph, Dieplinger, Hans, Innerhofer, Reinhold, Winhofer-Stöckl, Yvonne, Greber-Platzer, Susanne, Krychtiuk, Konstantin, Speidl, Walter, Toplak, Hermann, Widhalm, Kurt, Stulnig, Thomas, Huber, Kurt, Höllerl, Florian, Rega-Kaun, Gersina, Kleemann, Lucas, Mäser, Martin, Scholl-Bürgi, Sabine, Säly, Christoph, Mayer, Florian J., Sperone, Alexandra, Tanghe, Chloé, Gérard, Anne-Catherine, Pojskic, Lamija, Sisic, Ibrahim, Durak Nalbantic, Azra, Ejubovic, Malik, Jannes, Cinthia E., Pereira, Alexandre C., Krieger, Jose E., Petrov, Ivo, Goudev, Assen, Nikolov, Fedya, Tisheva, Snejana, Yotov, Yoto, Tzvetkov, Ivajlo, Baass, Alexis, Bergeron, Jean, Bernard, Sophie, Brisson, Diane, Cermakova, Lubomira, Couture, Patrick, Francis, Gordon A., Gaudet, Daniel, Hegele, Robert A., Khoury, Etienne, Mancini, G.B. John, McCrindle, Brian W., Paquette, Martine, Ruel, Isabelle, Iatan, Iulia, Cuevas, Ada, Wang, Xumin, Meng, Kang, Song, Xiantao, Yong, Qiang, Jiang, Tao, Liu, Ziyou, Duan, Yanyu, Hong, Jing, Ye, Pucong, Chen, Yan, Qi, Jianguang, Liu, Zesen, Li, Yuntao, Zhang, Chaoyi, Peng, Jie, Yang, Ya, Yu, Wei, Wang, Qian, Yuan, Hui, Cheng, Shitong, Jiang, Long, Chong, Mei, Jiao, Jian, Wu, Yue, Wen, Wenhui, Xu, Liyuan, Zhang, Ruiying, Qu, Yichen, He, Jianxun, Fan, Xuesong, Wang, Zhenjia, Chow, Elaine, Pećin, Ivan, Perica, Dražen, Symeonides, Phivos, Vrablik, Michal, Ceska, Richard, Soska, Vladimir, Tichy, Lukas, Adamkova, Vera, Franekova, Jana, Cifkova, Renata, Kraml, Pavel, Vonaskova, Katerina, Cepova, Jana, Dusejovska, Magdalena, Pavlickova, Lenka, Blaha, Vladimir, Rosolova, Hana, Nussbaumerova, Barbora, Cibulka, Roman, Vaverkova, Helena, Cibickova, Lubica, Krejsova, Zdenka, Rehouskova, Katerina, Malina, Pavel, Budikova, Milena, Palanova, Vaclava, Solcova, Lucie, Lubasova, Alena, Podzimkova, Helena, Bujdak, Juraj, Vesely, Jiri, Jordanova, Marta, Salek, Tomas, Urbanek, Robin, Zemek, Stanislav, Lacko, Jan, Halamkova, Hana, Machacova, Sona, Mala, Sarka, Cubova, Eva, Valoskova, Katerina, Burda, Lukas, Benn, Marianne, Bendary, Ahmed, Daoud, Ihab, Emil, Sameh, Elbahry, Atef, Rafla, Samir, Sanad, Osama, Kazamel, Ghada, Ashraf, Dr Mohamed, Sobhy, Mohamed, El-Hadidy, Amro, Shafy, Mohamed Abdoul, Kamal, Saif, Bendary, Mohamed, Talviste, Grete, Christmann, Jutta, Dressel, Alexander, Fath, Felix, Ferraro, Chiara, Frenzke, Lydia, Gopon, Alica, Klein, Isabel, Pienkowska, Dominika, Sietmann, Tobias, Sonntag, Antonia, Adjan, Omar, Bahrmann, Philipp, Baessler, Andrea, Barkowski, Rasmus, Beckerdjian, Raffi, Berr, Christina, Birkenfeld, Andreas, Böll, Gereon, Carstensen, Avisha, Demuth, Ilya, Finkernagel, Holger, Gouni-Berthold, Ioanna, Hahmann, Harry, Hamerle, Michael, Halder, Julian, Heide, Maria, Julius, Ulrich, Kassner, Ursula, Katzmann, Julius L, Kirschbaum, Anja, Klose, Gerald, Könemann, Stephanie, König, Christel, König, Wolfgang, Krämer, Bernhard, Kuprat, Gerrit, Koschker, Ann-Cathrin, Kilic, Özlem, Lindenmeier, Gerd, Van de Loo, Iris, Lorenz, Babette, Lorenz, Elke, Löhr, Birgit, McChord, Johanna, Maslarska, Mariya, Methe, Heiko, Merkel, Martin, Moussaoui, Zineb, Müller-Kozarez, Irina, Olivier, Christoph B, Ong, Peter, Otte, Britta, Parhofer, Klaus, Partsch, Carl-Joachim, Paulus, Michael, Pehlivanli, Sinan, Pflederer, Tobias, Pusl, Thomas, Richter, Veronika, Rosner, Stefanie, Sanin, Veronika, Schäfer, Sebastian, Schäfer, Christoph, Schatz, Ulrike, Schirmer, Stephan, Schmidt, Christine, Seeger, Wolfgang, Sisovic, Snezna, Spens, Antje, Jablonski, Ksenija Stach, Stadelmann, Alexander, Steinhagen-Thiessen, Elisabeth, Stürzebecher, Paulina, Tafelmeier, Maria, Tillack, Dörthe, Tselmin, Sergey, Tünnemann-Tarr, Adrienn, Vogt, Anja, Beckerath, Jens von, Wilke, Andreas, Wolf, Ulrich, Zemmrich, Claudia, Rizos, Christos V., Skoumas, Ioannis, Tziomalos, Konstantinos, Rallidis, Loukianos, Kotsis, Vasileios, Doumas, Michalis, Athyros, Vasileios, Skalidis, Emmanouil, Kolovou, Genovefa, Kolovou, Vana, Garoufi, Anastasia, Bilianou, Eleni, Koutagiar, Iosif, Kiouri, Estela, Antza, Christina, Zacharis, Evangelos, Attilakos, Achilleas, Sfikas, George, Koumaras, Charalambos, Anagnostis, Panagiotis, Anastasiou, Georgia, Liamis, George, Koutsogianni, Amalia-Despoina, Petkou, Ermioni, Milionis, Haralambos, Koulouri, Anastasia, Prodromiadou, Elisavet, Karányi, Zsolt, Harangi, Mariann, Bajnok, László, Audikovszky, Mária, Márk, László, Benczúr, Béla, Reiber, István, Nagy, Gergely, Nagy, András, Reddy, Lakshmi Lavanya, Shah, Swarup A. V, Ponde, Chandrashekhar K., Dalal, Jamshed J., Sawhney, Jitendra P.S., Verma, Ishwar C., Altaey, Mays, Al-Jumaily, Khalid, Rasul, Dilshad, Abdalsahib, Ali Fawzi, Jabbar, Amer Abdl, Al-ageedi, Mohanad, Dhamin, Mohammed, AlFil, Sarmad, Khadhim, Foad, Miahy, Sabah, Agar, Ruth, Catapano, Alberico Luigi, Calandra, Sebastiano, Tarugi, Patrizia, Casula, Manuela, Galimberti, Federica, Olmastroni, Elena, Sarzani, Riccardo, Ferri, Claudio, Repetti, Elena, Piro, Salvatore, Suppressa, Patrizia, Meregalli, Giancarla, Borghi, Claudio, Muntoni, Sandro, Calabrò, Paolo, Cipollone, Francesco, Purrello, Francesco, Pujia, Arturo, Passaro, Angelina, Marcucci, Rossella, Pecchioli, Valerio, Pisciotta, Livia, Mandraffino, Giuseppe, Pellegatta, Fabio, Mombelli, Giuliana, Branchi, Adriana, Fiorenza, Anna Maria, Pederiva, Cristina, Werba, Josè Pablo, Parati, Gianfranco, Carubbi, Francesca, Iughetti, Lorenzo, Fortunato, Giuliana, Iannuzzi, Arcangelo, Iannuzzo, Gabriella, Cefalù, Angelo Baldassare, Biasucci, Giacomo, Zambon, Sabina, Pirro, Matteo, Sbrana, Francesco, Trenti, Chiara, D'Erasmo, Laura, Federici, Massimo, Ben, Maria Del, Bartuli, Andrea, Giaccari, Andrea, Pipolo, Antonio, Citroni, Nadia, Guardamagna, Ornella, Lia, Salvatore, Benso, Andrea, Biolo, Gianni, Maroni, Lorenzo, Lupi, Alessandro, Bonanni, Luca, Rinaldi, Elisabetta, Zenti, Maria Grazia, Matsuki, Kota, Hori, Mika, Ogura, Masatsune, Masuda, Daisaku, Kobayashi, Takuya, Nagahama, Kumiko, Al-Jarallah, Mohammed, Radovic, Mirjana, Lunegova, Olga, Bektasheva, Erkayim, Abilova, Saamay, Erglis, Andrejs, Gilis, Dainus, Nesterovics, Georgijs, Saripo, Vita, Meiere, Ruta, Skudrina, Gunda, Terauda, Elizabete, Jambart, Selim, Ayoub, Carine, Ghaleb, Youmna, Aliosaitiene, Urte, Kutkiene, Sandra, Abdul Kadir, Siti Hamimah Sheikh, Kasim, Noor Alicezah Mohd, Nor, Noor Shafina Mohd, Abdul Hamid, Hasidah, Abdul Razak, Suraya, Al-Khateeb, Alyaa, Abd Muid, Suhaila, Abdul Rahman, Thuhairah, Kasim, Sazzli Shahlan, Radzi, Ahmad Bakhtiar Md, Ibrahim, Khairul Shafiq, Rosli, Marshima Mohd, Razali, Rafezah, Chua, Yung An, Razman, Aimi Zafira, Nazli, Sukma Azureen, Aziz, Nazirul, Rosman, Azhari, Abdul Murad, NorAzian, Jalaludin, Mohd Amin, Abdul Latif, Ahmad Zubaidi, Azzopardi, C., Mehta, Roopa, Martagon, Alexandro J., Ramirez, Gabriela A. Galan, Villa, Neftali E Antonio, Vazquez, Arsenio Vargas, Elias-Lopez, Daniel, Retana, Gustavo Gonzalez, Rodriguez, Betsabel, Macías, Jose J. Ceballos, Zazueta, Alejandro Romero, Alvarado, Rocio Martinez, Portano, Julieta D. Morales, Lopez, Humberto Alvares, Sauque-Reyna, Leobardo, Herrera, Laura G. Gomez, Mendia, Luis E. Simental, Aguilar, Humberto Garcia, Cooremans, Elizabeth Ramirez, Aparicio, Berenice Peña, Zubieta, Victoria Mendoza, Gonzalez, Perla A. Carrillo, Ferreira-Hermosillo, Aldo, Portilla, Nacu Caracas, Dominguez, Guadalupe Jimenez, Garcia, Alinna Y. Ruiz, Cazares, Hector E. Arriaga, Gonzalez, Jesus R., Valencia, Carla V. Mendez, Padilla, Francisco G., Prado, Ramon Madriz, Ibarra, Manuel O. De los Rios, Villicaña, Ruy D. Arjona, Rivera, Karina J. Acevedo, Carrera, Ricardo Allende, Alvarez, Jose A., Martinez, Jose C. Amezcua, Bustillo, Manuel de los Reyes Barrera, Vargas, Gonzalo Carazo, Chacon, Roberto Contreras, Andrade, Mario H. Figueroa, Ortega, Ashanty Flores, Alcala, Hector Garcia, de Leon, Laura E. Garcia, Guzman, Berenice Garcia, Garcia, Jose J. Garduño, Cuellar, Juan C. Garnica, Cruz, Jose R. Gomez, Garcia, Anell Hernandez, Almada, Jesus R. Holguin, Herrera, Ursulo Juarez, Sobrevilla, Fabiola Lugo, Rodriguez, Eduardo Marquez, Sibaja, Cristina Martinez, Rodriguez, Alma B. Medrano, Oyervides, Jose C. Morales, Vazquez, Daniel I. Perez, Rodriguez, Eduardo A. Reyes, Osorio, Ma. Ludivina Robles, Saucedo, Juan Rosas, Tamayo, Margarita Torres, Talavera, Luis A. Valdez, Arroyo, Luis E. Vera, Carrillo, Eloy A. Zepeda, Stroes, Erik S, Defesche, J, Zuurbier, L, Reeskamp, L, Ibrahim, S, Roeters van Lennep, Jeanine, Wiegman, Albert, Isara, Alphonsus, Obaseki, Darlington E., Al-Waili, Khalid, Al-Zadjali, Fahad, Al-Zakwani, Ibrahim, Al-Kindi, Mohammed, Al-Mukhaini, Suad, Al-Barwani, Hamida, Rana, Asim, Shah, Lahore Saeed Ullah, Al-Nouri, Fahad, Starostecka, Ewa, Konopka, Agnieszka, Bielecka-Dabrowa, Agata, Lewek, Joanna, Sosnowska, Bozena, Gąsior, Mariusz, Dyrbuś, Krzysztof, Jóźwiak, Jacek, Pajkowski, Marcin, Romanowska-Kocejko, Marzena, Żarczyńska-Buchowiecka, Marta, Chmara, Magdalena, Wasąg, Bartosz, Stróżyk, Aneta, Michalska-Grzonkowska, Aleksandra, Medeiros, Ana Margarida, Alves, Ana Catarina, Silva, Francisco, Lobarinhas, Goreti, Palma, Isabel, de Moura, Jose Pereira, Rico, Miguel Toscano, Rato, Quitéria, Pais, Patrícia, Correia, Susana, Moldovan, Oana, Virtuoso, Maria João, Araujo, Francisco, Salgado, Jose Miguel, Colaço, Ines, Dumitrescu, Andreea, Lengher, Calin, Mosteoru, Svetlana, Meshkov, Alexey, Ershova, Alexandra, Rozhkova, Tatiana, Korneva, Victoria, Yu, Kuznetsova T., Zafiraki, Vitaliy, Voevoda, Mikhail, Gurevich, Victor, Duplyakov, Dmitry, Ragino, Yulia, Chubykina, Uliana, Shaposhnik, Igor, Alkaf, Fahmi, Khudari, Alia, Rwaili, Nawal, Al-Allaf, Faisal, Alghamdi, Mohammad, Batais, Mohammed A, Almigbal, Turky H, Kinsara, Abdulhalim, AlQudaimi, Ashraf Hammouda Ahmed, Awan, Zuhier, Elamin, Omer A, Altaradi, Hani, Popovic, Ljiljana, Singh, Sandra, Rasulic, Iva, Petakov, Ana, Lalic, Nebojsa M., Lam, Carolyn, Le, Tan Ju, Siang, Eric Lim Tien, Dissanayake, Sanjaya, I-Shing, Justin Tang, Shyong, Tai E, Jin, Terrance Chua Siang, Ting, Sharon Pek Li, Ming, Jeremy Hoe Kian, Drum, Chester Lee, Nastar, Fathima Ashna, Jia, Loh Wann, Ya, Natalie Koh Si, Jie, Marvin Chua Wei, Dalan, Rinkoo, Wei, Yong Quek, sian, Tiong Yee, Keong, Yeo Khung, Rong, Siau Kai, Jin, Darren Seah Ee, Ming, Ian Koh Jan, Chang, Tan Hong, Peng, Fabian Yap Kok, Vasanwala, Rashida Farhad, Raslova, Katarina, Balinth, Karin, Buganova, Ingrid, Fabryova, Lubomira, Kadurova, Michaela, Klabnik, Alexander, Kozárová, Miriam, Sirotiakova, Jana, Battelino, Tadej, Cevc, Matija, Debeljak, Marusa, Torkar, Ana Drole, Fras, Zlatko, Jug, Borut, Cugalj, Barbara Kern, Kovac, Jernej, Mlinaric, Matej, Sikonja, Jaka, Pilcher, Gillian Joan, Blom, D J, Wolmarans, K H, Brice, B C, Muñiz-Grijalvo, Ovidio, Díaz-Díaz, Jose Luis, de Isla, Leopoldo Pérez, Fuentes, Francisco, Badimon, Lina, Martin, François, Miserez, Eleonore B., Shipton, Janine L., Ganokroj, Poranee, Chattranukulchai, Pairoj, Jiamjarasrungsi, Wiroj, Thongtang, Nuntakorn, Krittayaphong, Rungroj, Vathesatogkit, Prin, Sriphrapradang, Chutintorn, Phimphilai, Mattabhorn, Leelawattana, Rattana, Anthanont, Pimjai, Suraamornkul, Swangjit, Deerochanawong, Chaicharn, Senthong, Vichai, Torpongpun, Artit, Suteerayongprasert, Panuwat, Pengpong, Nawarat, Sathavarodom, Nattapol, Sunanta, Usanee, Porntharukchareon, Thachanun, Kiatpanabhikul, Phatharaporn, Kaewkrasaesin, Chatchon, Kongkit, Jaruwan, Umphonsathien, Mongkontida, Akbulut, Mehmet, Alici, Gökhan, Bayram, Fahri, Can, Levent Hürkan, Celik, Ahmet, Ceyhan, Ceyhun, Coskun, Fatma Yilmaz, Demir, Mesut, Demircan, Sabri, Dogan, Volkan, Durakoglugil, Emre, Dural, İbrahim Etem, Gedikli, Omer, Hacioglu, Aysa, Ildizli, Muge, Kilic, Salih, Kirilmaz, Bahadir, Kutlu, Merih, Oguz, Aytekin, Ozdogan, Oner, Onrat, Ersel, Ozer, Savas, Sabuncu, Tevfik, Sahin, Tayfun, Sivri, Fatih, Sonmez, Alper, Temizhan, Ahmet, Topcu, Selim, Tokgozoglu, Lale, Tuncez, Abdullah, Vural, Mirac, Yenercag, Mustafa, Yesilbursa, Dilek, Yigit, Zerrin, Yildirim, Aytul Belgi, Yildirir, Aylin, Yilmaz, Mehmet Birhan, Atallah, Bassam, Traina, Mahmoud, Sabbour, Hani, Abdul Hay, Dana, Luqman, Neama, Elfatih, Abubaker, Abdulrasheed, Arshad, Manla, Yosef, Kwok, See, DellOca, Nicolas, Alieva, Rano B., Fozilov, Khurshid G., Hoshimov, Shavkat U., Nizamov, Ulugbek I., Kan, Liliya E., Kim, Andrey R., Abdullaeva, Guzal J., Abdullaev, Alisher A., Do, Doan Loi, Nguyen, Mai Ngoc Thi, Kim, Ngoc Thanh, Le, Thanh Tung, Le, Hong An, and Ray, Kausik K.

Published
2024
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41. Variants in IGLL1 cause a broad phenotype from agammaglobulinemia to transient hypogammaglobulinemia

Author

Soomann, Maarja, Bily, Viktor, Elgizouli, Magdeldin, Kraemer, Dennis, Akgül, Gülfirde, von Bernuth, Horst, Bloomfield, Markéta, Brodszki, Nicholas, Candotti, Fabio, Förster-Waldl, Elisabeth, Freiberger, Tomas, Giżewska, Maria, Klocperk, Adam, Kölsch, Uwe, Nichols, Kim E., Krüger, Renate, Oak, Ninad, Pac, Małgorzata, Prader, Seraina, Schmiegelow, Kjeld, Šedivá, Anna, Sogkas, Georgios, Stittrich, Anna, Stoltze, Ulrik Kristoffer, Theodoropoulou, Katerina, Wadt, Karin, Wong, Melanie, Zeyda, Maximillian, Pachlopnik Schmid, Jana, and Trück, Johannes

Published
2024
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46. Correction: Epidemiological Changes and Improvement in Outcomes of Infective Endocarditis in Europe in the Twenty-First Century: An International Collaboration on Endocarditis (ICE) Prospective Cohort Study (2000–2012)

Author

Ambrosioni, Juan, Hernández-Meneses, Marta, Durante-Mangoni, Emanuele, Tattevin, Pierre, Olaison, Lars, Freiberger, Tomas, Hurley, John, Hannan, Margaret M., Chu, Vivian, Hoen, Bruno, Moreno, Asunción, Cuervo, Guillermo, Llopis, Jaume, and Miró, José M.

Published
2023
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47. Local energetic frustration conservation in protein families and superfamilies

Author

Maria I. Freiberger, Victoria Ruiz-Serra, Camila Pontes, Miguel Romero-Durana, Pablo Galaz-Davison, Cesar A. Ramírez-Sarmiento, Claudio D. Schuster, Marcelo A. Marti, Peter G. Wolynes, Diego U. Ferreiro, R. Gonzalo Parra, and Alfonso Valencia

Subjects
Science
Abstract

Abstract Energetic local frustration offers a biophysical perspective to interpret the effects of sequence variability on protein families. Here we present a methodology to analyze local frustration patterns within protein families and superfamilies that allows us to uncover constraints related to stability and function, and identify differential frustration patterns in families with a common ancestry. We analyze these signals in very well studied protein families such as PDZ, SH3, ɑ and β globins and RAS families. Recent advances in protein structure prediction make it possible to analyze a vast majority of the protein space. An automatic and unsupervised proteome-wide analysis on the SARS-CoV-2 virus demonstrates the potential of our approach to enhance our understanding of the natural phenotypic diversity of protein families beyond single protein instances. We apply our method to modify biophysical properties of natural proteins based on their family properties, as well as perform unsupervised analysis of large datasets to shed light on the physicochemical signatures of poorly characterized proteins such as the ones belonging to emergent pathogens.

Published
2023
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48. Systematic Approach Revealed SERPING1 Splicing-Affecting Variants to be Highly Represented in the Czech National HAE Cohort

Author

Grombirikova, Hana, Bily, Viktor, Soucek, Premysl, Kramarek, Michal, Hakl, Roman, Ballonova, Lucie, Ravcukova, Barbora, Ricna, Dita, Kozena, Karolina, Kratochvilova, Lucie, Sobotkova, Marta, Zachova, Radana, Kuklinek, Pavel, Kralickova, Pavlina, Krcmova, Irena, Hanzlikova, Jana, Vachova, Martina, Krystufkova, Olga, Dankova, Eva, Jesenak, Milos, Novackova, Martina, Svoboda, Michal, Litzman, Jiri, and Freiberger, Tomas

Published
2023
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