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Nanopore sequencing identifies parent-of-origin specific age-associated methylation changes at imprinted loci in the human genome
(2026-12) Sigurpalsdottir, Brynja; Holley, Guillaume; Sverrisson, Sverrir; Magnusdottir, Droplaug N.; Olafsson, Pall I.; Gylfason, Arnaldur; Magnusson, Olafur; Masson, Gisli; Stefansson, Olafur A.; Halldorsson, Bjarni V.; Department of Engineering
Aging is accompanied by widespread DNA methylation changes, yet their full genomic scope and parent-of-origin dynamics remain poorly understood. Here, we apply nanopore long-read sequencing to 7,284 whole blood samples enabling methylation measurements of 17,959,684 high-quality CpG units. Over 20% of the measured high quality CpG units undergo age-associated changes, predominantly hypomethylation. From these data, we construct a methylation aging clock from 1,373 high-quality CpG units, with median absolute prediction error of 2.43 years. Importantly, phasing the methylation to parental haplotypes enables systematic analysis of age effects in parent-of-origin specific context, uncovering 702 high-quality CpG units with parent-of-origin specific age-association, most of which are located at imprinted genomic regions. At the DIRAS3 locus, we detect age-dependent hypermethylation on the active paternal allele, indicative of attenuation of parent-of-origin specific methylation with age. Together, these findings establish nanopore sequencing as a powerful tool for mapping both genome-wide and parent-of-origin specific signatures of methylation aging and provide evidence that methylation patterns at imprinted loci become progressively altered with age.
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One Size Still Does Not Fit All : Configuration Pathways of Environmental, Social, and Governance and Board Diversities for Higher Firm Performances Across One- and Two-Tier Systems
(2026-02) Zhu, Baoying; Brozkova, Dominika; Ahmadov, Tarlan; Durst, Susanne; Prokop, Viktor; Department of Business and Economics
There is an ongoing, albeit uncertain, debate among stakeholders regarding the benefits of environmental, social, and governance (ESG) reporting, reflected in mixed empirical findings on its impact on firm performance. In addition to this reporting, diversity (gender and cultural) on boards, which is strongly promoted at the EU level, has gained increasing importance. However, prior research offers inconsistent results and leaves significant shortcomings regarding how the interaction of this diversity with the ESG pillars affects firm performance across governance structures. This study employs a fuzzy-set qualitative comparative analysis and Refinitiv Eikon data of 554 European Union companies from 2023 to examine configuration pathways that combine gender and cultural diversity with ESG pillars, thus influencing firm performance across different governance forms. Drawing on Upper Echelons and Contingency Theories—enhanced by insights from Resource Dependence and Social Identity Theory lenses—we show that configurations combining gender and cultural diversity with the social pillar of ESG are linked to higher performance within one-tier firms. In two-tier firms, this higher performance is driven by environmental and social ESG pillars combined with cultural diversity. Recognizing that there is no single governance structure in the ESG and diversity context, we offer practitioners guidance on aligning ESG and diversity strategies with their governance architectures, developing governance-sensitive policies, increasing transparency in diversity integration, promoting ESG competency training, and providing targeted incentives.
Verk
Knowledge management in the age of generative artificial intelligence – from SECI to GRAI
(2026-02-03) Böhm, Karsten; Durst, Susanne; Department of Business and Economics
Purpose – Generative Artificial Intelligence (GenAI) models are now able not only to recognize complex patterns from large amounts of input data but also to display them in context. This fact invites a critical analysis of the SECI model and its further applicability as an analytical framework for knowledge generation and transfer in organizations. This conceptual paper aims to take the SECI model with the individual SECI phases and analyze how GenAI changes the assumptions and descriptions of the original SECI framework. More specifically, the aim is to propose a revised SECI framework. Design/methodology/approach – This paper aims to contribute to theory development of theories present in the literature. More specifically, it seeks to make a conceptual contribution that draws on one of the four types of conceptual contributions proposed by Deborah J. MacInnis, namely, envisioning, and is based on previous literature and the authors’ thoughts and experiences to propose a revised SECI framework called GRAI, which stands for Generative Receptive Artificial Intelligence. Findings – A better understanding of the further applicability of the SECI framework that arises with the introduction and application of GenAI models is not only relevant to the existing knowledge management (KM) theory but also to organizations. The proposed revised perspective of the SECI model, summarized in the GRAI framework, reflects the use of GenAI technologies in the corporate environment and thus allows the necessary stimulation of a discussion on how KM in general, and knowledge generation, in particular, will be affected and augmented by AI. Originality/value – To the authors’ knowledge, this paper is the first to systematically and comprehensively examine the established SECI framework and its wider applicability in terms of the potential impact of GenAI models on KM practices in organizations. The proposed GRAI framework is seen as a relevant contribution to the further development of KM theory.
Verk
It’s Not Easy : Applying Supervised Machine Learning to Detect Malicious Extensions in the Chrome Web Store
(2026-02) Rosenzweig, Ben; Dalla Valle, Valentino; Apruzzese, Giovanni; Fass, Aurore; Department of Computer Science
Google Chrome is the most popular Web browser. Users can customize it with extensions that enhance their browsing experience. The most well-known marketplace of such extensions is the Chrome Web Store (CWS). Developers can upload their extensions on the CWS, but such extensions are made available to users only after a vetting process carried out by Google itself. Unfortunately, some malicious extensions bypass such checks, putting the security and privacy of downstream browser extension users at risk. In this article, we carry out a comprehensive real-world security analysis of malicious extensions in the CWS. Specifically, we scrutinize the extent to which automated mechanisms reliant on supervised machine learning (ML) can be used to detect malicious extensions on the CWS. To this end, we first collect 7,140 malicious extensions published in 2017–2023 and which have been flagged as malicious by Google. We combine this dataset with 63,598 benign extensions published or updated on the CWS before 2023, and we develop three supervised-ML-based classifiers—leveraging both original features as well as techniques inspired by prior work. We show that, in a “lab setting”, our classifiers work well (e.g., 98% accuracy). Then, we collect a new, and more recent, set of 35,462 extensions from the CWS, published or last updated in 2023, with unknown ground truth. We were eventually able to identify 68 malicious extensions that bypassed the vetting process of the CWS. However, our classifiers also reported over 1k likely malicious extensions which may overestimate their true number. Based on this finding (further supported with other experiments and realistic analyses), we elucidate, for the first time, a strong concept drift effect on browser extensions. We also provide factual evidence that commercial detectors (e.g., VirusTotal) work poorly to detect known malicious extensions. Altogether, our results highlight the fact that detecting malicious browser extensions is a fundamentally hard problem which has not (yet) received an adequate degree of attention. This requires additional work both by the research community and by Google itself—potentially by revising their approaches. In the meantime, we informed Google of our discoveries, and we released our artifacts.
Verk
High Energy Proximal Tibial Fractures at Landspítali University Hospital 2003-2021 : Háorku nærendabrot á sköflungsbeini á Landspítala 2003-2021
(2026-09-01) Hardarson, Hlynur Breki; Sigurdarson, Hjorturo Vidar; Sigbergsdottir, Audur; Jonsson, Halldor; Ingvarsson, Thorvaldur; Snaebjornsson, Thorkell Snaebjornsso; Department of Engineering
OBJECTIVE: The aim of this study was to investigate the epidemiology of proximal tibial fractures treated at Landspítali National University Hospital following high energy trauma. MATERIALS AND METHODS: This study reviewed patient records of individuals who sustained proximal tibial fractures and were treated at Landspítali between 2003 and 2021. Data on age, sex, mechanism of injury, treatment plan, hospital stay, and outcomes were recorded. Fracture classification was based on evaluation and imaging reviewed in the Agfa system and categorized using the Schatzker classification system. RESULTS: A total of 195 high energy proximal tibial fractures were identified during the study period. The mean age of patients was 42 years, and 62,1% were male. Traffic accidents were the most common mechanism of injury, followed by horse-related accidents and recreational injuries. Most fractures occured in June, and incidence was higher during the summer months. The most common fracture type was Schatzker type II (32,8%), with type I and VI also frequently observed. Surgical treatment was perfomed in 56,9% of cases, most commonly involving internal fixation with plates and screws (used in 74,8% of surgeries). Among those undergoing surgery, Schatzker type VI was the most common. Associated injuries were found in 31,2% of cases, most frequently in patients with complex Schatzker type VI fractures. Only one death occured in relation to the fractures (0,5%). Other complications, such as infections or thromboembolism, were rare. Twelve cases had undergone total knee arthroplasty by the end of the study period. CONCLUSIONS: The incidence of proximal tibial fractures in Iceland (2003-2021) has increased and is comparable to reports from neighboring countries. These injuries are most common in middle-aged men and often result from high energy trauma. Traffic accidents were the leading cause, followed by horse-related and recreational injuries. Most patients who sustained high energy proximal fractures underwent surgery.

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