Jumbo phages protect their genomes from DNA-sensing bacterial defense systems by enclosing them within vesicles and nucleus-like compartments. Very little is known about defense systems specialized to counter these phages. Here, we show that AVAST Type 5 (Avs5) systems, part of the STAND superfamily and spanning three phylogenetic Avs5 clades, confer conserved immunity against jumbo phages. Using localization microscopy and biotin proximity labeling we demonstrate that Avs5 localizes to early infection vesicles, where it senses an essential, early expressed
phage protein named JADA—Jumbophage AVAST5 Defense Activator. Recognition of phage infection triggers the Sir2-like effector domain of Avs5 across all three Avs5 clades, resulting in rapid NAD+ hydrolysis, disruption of phage nucleus formation, and arrest of infection. These findings reveal a spatially coordinated bacterial immune strategy that targets an early vulnerability in jumbo phage infection.

Addressing non-idealities in Resistive Random Access Memories (RRAMs) is crucial for their successful commercialization. For example, the inherent resistance drift that occurs during consecutive read operations can induce Read Disturb Faults (RDF), leading to functional errors. This paper analyzes and characterizes the resistance drift and the RDF based on data measurements and presents a physics-based RRAM compact model that incorporates these non-idealities. Additionally, an in-field mitigation scheme is proposed, leveraging bidirectional read operations to balance the resistance. The scheme is implemented and validated through circuit simulations, both for RRAM used as memory and for RRAM-based computation-in-memory microarchitectures for deep neural networks. The results demonstrate that RRAM without any mitigation scheme can start failing after 8,000 consecutive reads, while our mitigation scheme ensures that the memory remains functional even after 10⁶ consecutive reads. Furthermore, the results indicate that using the MNIST dataset as a case study, the accuracy can drop significantly from 86% to as low as 12.5% without any mitigation scheme. In contrast, the proposed mitigation scheme improves this accuracy up to 84.2%.

In this paper, we present the Amsterdam Modeling Suite (AMS), a comprehensive software platform designed to support advanced molecular and materials simulations across a wide range of chemical and physical systems. AMS integrates cutting-edge quantum chemical methods, including Density Functional Theory (DFT) and time-dependent DFT, with molecular mechanics, fluid thermodynamics, machine learning techniques, and more, to enable multi-scale modeling of complex chemical systems. Its design philosophy allows for seamless coupling between components, facilitating simulations that range from small molecules to complex biomolecular and solid-state systems, making it a versatile tool for tackling interdisciplinary challenges, both in industry and in academia. The suite also emphasizes user accessibility, with an intuitive graphical interface, extensive scripting capabilities, and compatibility with high-performance computing environments.

The goal of the NEUROKIT2E project is to create an open-source Deep Learning framework for edge and embedded AI built around an established European value chain. This framework, called AIDGE, supports a wide range of application areas that operate independently and serve a global user community. It provides easy and fast full-stack solutions from Neural Network design and optimization to AI application development all the way down to hardware implementations while enabling code generation for application-specific targets. This platform provides flexibility for academic users in the AI domain to explore and innovate while allowing them the possibility to prototype systems, ensuring their work aligns well with industrial needs. This paper presents the results and achievements of the first part of this three-year project, along with its roadmap and expected outcomes.

The disease burden from Legionella spp. infections has been increasing in many industrialized countries and, despite decades of scientific advances, ranks amongst the highest for waterborne diseases. We review here several key research areas from a multidisciplinary perspective and list critical research needs to address some of the challenges of Legionella spp. management in engineered environments. These include: (i) a consideration of Legionella species diversity and cooccurrence, beyond Legionella pneumophila only; (ii) an assessment of their environmental prevalence and clinical relevance, and how that may affect legislation, management, and intervention prioritization; (iii) a consideration of Legionella spp. sources, their definition and prioritization; (iv) the factors affecting Legionnaires' disease seasonality, how they link to sources, Legionella spp. proliferation and ecology, and how these may be affected by climate change; (v) the challenge of saving energy in buildings while controlling Legionella spp. with high water temperatures and chemical disinfection; and (vi) the ecological interactions of Legionella spp. with other microbes, and their potential as a biological control strategy. Ultimately, we call for increased interdisciplinary collaboration between multiple research domains, as well as transdisciplinary engagement and collaboration across government, industry, and science as the way toward controlling and reducing Legionella-derived infections.

Application-specific quantum computers offer the most efficient means to tackle problems intractable by classical computers. Realizing these architectures necessitates a deep understanding of quantum circuit properties and their relationship to execution outcomes on quantum devices. Our study aims to perform for the first time a rigorous examination of quantum circuits by introducing graph theory-based metrics extracted from their qubit interaction graph and gate dependency graph (GDG) alongside conventional parameters describing the circuit itself. This methodology facilitates a comprehensive analysis and clustering of quantum circuits. Furthermore, it uncovers a connection between parameters rooted in both qubit interaction and GDGs, and the performance metrics for quantum circuit mapping, across a range of established quantum device and mapping configurations. Among the various device configurations, we particularly emphasize modular (i.e. multi-core) quantum computing architectures due to their high potential as a viable solution for quantum device scalability. This thorough analysis will help us to: i) identify key attributes of quantum circuits that affect the quantum circuit mapping performance metrics; ii) predict the performance on a specific chip for similar circuit structures; iii) determine preferable combinations of mapping techniques and hardware setups for specific circuits; and iv) define representative benchmark sets by clustering similarly structured circuits.

To better understand the increasing human impact on the water cycle and the feedbacks between hydrology and society, the International Association of Hydrological Sciences (IAHS) organized the scientific decade “Panta Rhei–Everything Flows: Change in hydrology and society” (2013–2022). A key finding is the need to use integrated approaches to assess the co-evolution of human–water systems in order to avoid unintended consequences of human interventions over long periods of time. Additionally, substantial progress has been made in leveraging new data sources on human behaviour, e.g. through text mining of social media posts. Much has been learned about detecting hydrological changes and attributing them to their drivers, e.g. quantifying climate effects on floods. To achieve further progress, we recommend broadening the understanding, the discipline and training activities, while at the same time pursuing synthesis by focusing on key themes, developing innovative approaches and finding sustainable solutions to the world’s water problems.

To show compliance to structural engineering codes and implement quality control measures, it is critical to obtain reliable mechanical properties of the materials in question. For conventional cast and precast concrete, the experimental procedures and relationships between mechanical properties, the material composition, and the production methods are globally known, but for 3D concrete printing (3DCP), these relations have not yet been established. Previous studies have shown little consistency in results, and the underlying experimental methods have not been established broadly. There is an urgent need to address these issues as the application of 3DCP in practice projects is growing rapidly. Therefore, RILEM TC 304-ADC: Assessment of Additively Manufactured Concrete Materials and Structures has set up a large interlaboratory study into the mechanical properties of 3D printed concrete. This paper presents key elements of the experimental approach detailed in the Study Plan and the supporting considerations. Furthermore, it reports on the response, consisting of 34 contributions from 30 laboratories, detailing global coverage, properties of the applied mixture designs and characteristics of the printing facilities that have been used. Subsequently, some fundamental results from compression, flexural, and E-modulus testing are presented and—considering cast specimens as a reference—discussed. On average, a reduction in strength was found in compression and E-modulus (all tested orientations). For flexure, on the other hand, an increase was found in two testing orientations, while a decrease was observed in the third orientation. Importantly, even though the applied experimental methods were found to be reasonably appropriate to obtain the required data, the differences found between individual contributions are significant and sometimes non-consistent, suggesting that testing on specific material-facility combinations is necessary to reliably determine the mechanical properties of objects produced from them. Furthermore, a theoretical framework needs to be developed to further explain the variations that were observed. Extensive analyses of all acquired data are out of the scope of this contribution, but presented in two associated papers, whereas a third presents the data management approach used to process the approximately 5,000 test results.

The early DNA damage on the surface of the Moon due to GCR protons and alpha particles were assessed using a multiscale approach in Geant4. This consisted of three simulation stages. A periodic boundary conditions approach was used to obtain the radiation field on the surface and inside a proposed lunar habitat. The radiation field on the cellular scale was obtained in the organs of male and female astronauts using the ICRP145 tetrahedral mesh phantoms. This was subsequently simulated using a full human cell model in Geant4-DNA to obtain the early DNA damage. Geant4-DNA track structure ionisation models upper energy limits were extended to be able to model the interactions of the GCR at sub-cellular level, covering an energy range from a few eV up to 1 TeV. Hadronic interactions and the modelling of induced radiochemical species were also implemented. The early DNA damage was assessed using the Geant4-DNA molecularDNA example. A greater yield of DNA damage was observed on the lunar surface compared with the habitat, and indirect damage due to induced hydroxyl radicals constituted most of the damage. This study demonstrates a complete simulation pipeline for the assessment of early DNA damage in astronauts in the space radiation environment.

DNA loop extrusion by SMC proteins is a key process underlying chromosomal organization. It is unknown how loop extruders interact with telomeres where DNA is densely covered with proteins. Using complementary in vivo and in vitro single-molecule approaches, we study how loop-extruding condensin interacts with Rap1, the telomeric DNA-binding protein of Saccharomyces cerevisiae. We show that dense linear Rap1 arrays can completely halt DNA loop extrusion, with a blocking efficiency depending on the array length and the DNA gap size between proteins. In anaphase cells, dense Rap1 arrays are found to accumulate condensin and to cause a local chromatin decompaction, as monitored with a microscopy-based approach, with direct implications for the resolution of dicentric chromosomes produced by telomere fusions. Our findings show that linear arrays of DNA-bound proteins can efficiently halt DNA loop extrusion by SMC proteins, which may impact cellular processes from telomere functions to transcription and DNA repair.

Background
In life-threatening illnesses, open information provision can benefit patients and families. However, not all patients prefer to have all information. There is a lack of clinical guidance on how to handle patient preferences for non-disclosure.

Aim
To develop a conceptual framework and practical guidance for clinicians regarding the spectrum of patients’ information provision preferences with a focus on when patients do not desire to have full information.

Methods
Multidisciplinary expert stakeholder meeting.

Results
20 expert stakeholders from various disciplines and continents participated in the expert meeting. Based on the qualitative results, a conceptual framework was created. Our framework highlights that information is never value-free but attains value via healthcare provider and patient/family factors, including how information is interpreted by clinicians and patients/families. In this process, ethical and sociocultural tensions can arise, such as between patient and family autonomy, that can influence harmful effects of the attained value of information along several axes such as empowerment versus disempowerment. To mitigate tensions and minimise harm, our framework produces practical guidance for clinicians such as making a connection and having an open attitude.

Conclusions
Our framework has clinical, research and policy implications and can be further refined and tested. Ultimately, it serves as a starting point to reduce social and cultural inequities in end-of-life care information in a global context.

HollandPTC is an independent outpatient center for proton therapy, scientific research, and education. Patients with different types of cancer are treated with Intensity Modulated Proton Therapy (IMPT). Additionally, the HollandPTC R&D consortium conducts scientific research into the added value and improvements of proton therapy. To this end, HollandPTC created clinical and pre-clinical research facilities including a versatile R&D proton beamline for various types of biologically and technologically oriented research. In this work, we present the characterization of the R&D proton beamline of HollandPTC. Its pencil beam mimics the one used for clinical IMPT, with energy ranging from 70 up to 240 MeV, which has been characterized in terms of shape, size, and intensity. For experiments that need a uniform field in depth and lateral directions, a dual ring passive scattering system has been designed, built, and characterized. With this system, field sizes between 2 × 2 cm² and 20 × 20 cm² with 98 % uniformity are produced with dose rates ranging from 0.5 Gy/min up to 9 Gy/min. The unique and customized support of the dual ring system allows switching between a pencil beam and a large field in a very simple and fast way, making the HollandPTC R&D proton beam able to support a wide range of different applications.

Molten Salt Reactors (MSR) are Generation IV nuclear systems in which the fuel is dissolved in a molten salt circulating through the primary system. There is growing interest in this advanced technology in Europe, but also in the US, China, South Korea, Japan and Russia, due to their inherently high safety level, flexibility, reliability, load-following capabilities, and potential for multi-recycling of materials contained in light-water reactors’ spent nuclear fuels. These advantages could position MSRs as ideal complements to other decarbonized energy sources in a future sustainable energy mix. In this respect, it is probably one of the most promising advanced technologies and, at the same time, the least mature and studied one. Two ongoing EURATOM-funded projects, MIMOSA and ENDURANCE projects are exploring molten salt reactors’ safety and performance features, as well as fuel cycle aspects, in order to assess and demonstrate their potential for future deployment in Europe. The MIMOSA and ENDURANCE projects have the common objective of improving the maturity of MSR technology. The MIMOSA project develops and analyses multi-recycling strategies for the European Union based on the use of MSR and demonstrates several key aspects of their technical feasibility and performance by both calculations and experimental investigations. The ENDURANCE project supports the safe operation and the development of Critical Technology Elements by connecting design developers and industry with universities and research centres while ensuring alignment with regulatory requirements. Whereas ENDURANCE is in its starting phase, MIMOSA has already delivered important results.

INTRODUCTION: Cognitive resilience refers to maintaining cognitive function despite Alzheimer's disease (AD) pathophysiology. METHODS: We analyzed amyloid-positive individuals across clinical stages of AD in two cohorts: the Amsterdam Dementia Cohort (ADC, N = 1036) and Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 685). Cognitive resilience was conceptualized from a canonical correlation analysis of magnetic resonance imaging and neuropsychological data in each cohort separately. Model validation involved education as a resilience proxy and key genetic factors (apolipoprotein E [APOE] ε4 and APOE ε2) of AD. We explored associations between 83 AD risk loci and cognitive resilience. RESULTS: Resilience was correlated with education (ADC: β = 0.144, p < 0.001; ADNI: β = 0.149, p < 0.001) and APOE ε4 (β_{meta-analysis}= –0.052, p = 0.014). Exploratory single nucleotide polymorphism meta-analysis identified potential involvement of genetic variants around genes UNC5CL, USP6NL, and TPCN1 in lower, and genes COX7C and MINDY2 in higher resilience. DISCUSSION: Our novel resilience approach showed conceptual validity and potential for future discovery of resilience-related genetic variants. Highlights: ·We define a novel approach to resilience using canonical correlation analysis (CCA). ·Apolipoprotein E ε4 is linked to lower resilience, suggesting increased vulnerability. ·Genetic loci around COX7C and MINDY2 are potentially involved in higher resilience. ·This novel approach may be used for multi-cohort studies such as genome-wide association studies in the future.

This article presents a 4096-element ultrasound probe for high volume-rate (HVR) cardiovascular imaging. The probe consists of two application-specific integrated circuits (ASICs), each of which interfaces with a 2048-element monolithically-integrated capacitive micro-machined ultrasound transducer (CMUT) array. The probe can image a 60° × 60° × 10-cm volume at 2000 volumes/s, the highest volume-rate with in-probe channel-count reduction reported to date. It uses 2 × 2 delay-and-sum micro-beamforming (μBF) and 2× time-division multiplexing (TDM) to achieve an 8× receive (RX) channel-count reduction. Equalization, trained using a pseudorandom bit-sequence generated on the chip, reduces TDM-induced crosstalk by 10 dB, enabling power-efficient scaling of the cable drivers. The ASICs also implement a novel transmit (TX) beamformer (BF) that operates as a programmable digital pipeline, which enables steering of arbitrary pulse-density modulated (PDM) waveforms. The TX BF drives element-level 65 V unipolar pulsers, which in turn drive the CMUT array. Both the TX BF and RX μBF are programmed with shift-registers (SRs) that can either be programmed in a row-column fashion for fast upload times, or daisy-chain fashion for a higher flexibility. The layout of the ASICs is matched to the 365-μm-pitch monolithically-integrated CMUT array. While operating, the RX and logic power consumption per element is 0.85 and 0.10 mW, respectively. TX power consumption is highly waveform dependent, but is nominally 0.34 mW. Compared to the prior art, the probe has the highest volume rate, and features among the largest imaging arrays (both in terms of element-count and aperture) with a high flexibility in defining the TX waveform. These properties make it a suitable option for applications requiring HVR imaging of a large region of interest.

Assessing cognitive demand is crucial for research on self-regulated learning; however, discrepancies in translating essential concepts across languages can hinder the comparison of research findings. Different languages often emphasize various components and interpret certain constructs differently. This paper aims to develop a translingual set of items distinguishing between intentionally invested mental effort and passively perceived mental load as key differentiations of cognitive demand in a broad range of learning situations, as they occur in self-regulated learning. Using a mixed-methods approach, we evaluated the content, criterion, convergent, and incremental validity of this scale in different languages. To establish content validity, we conducted qualitative interviews with bilingual participants who discussed their understanding of mental effort and load. These participants translated and back-translated established and new items from the cognitive-demand literature into English, Dutch, Spanish, German, Chinese, and French. To establish criterion validity, we conducted preregistered experiments using the English, Chinese, and German versions of the scale. Within those experiments, we validated the translated items using established demand manipulations from the cognitive load literature with first-language participants. In a within-subjects design with eight measurements (N = 131), we demonstrated the scale’s criterion validity by showing sensitivity to differences in task complexity, extraneous load manipulation, and motivation for complex tasks. We found evidence for convergent and incremental validity shown by medium-size correlations with established cognitive load measures. We offer a set of translated and validated items as a common foundation for translingual research. As best practice, we recommend four items within a reference point evaluation.

The high thermal stability of a thermoelectric material, which maintains a stable conversion efficiency under prolonged heat exposure, is essential for sustainable thermoelectric applications. Despite the well-known relationship between thermal degradation and microstructural evolution, their underlying interplay remains unclear, with contradictory findings reported in the literature owing to the complex dependence of microstructural changes on the material composition. Herein, the effect of Sb doping on the thermal stability of NbCoSn half-Heusler compounds is investigated in detail by comprehensively analyzing their microstructural evolution. The results reveal that introducing 3.3 at.% Sb into NbCoSn markedly enhances the thermal stability, by preserving the lattice thermal conductivity after heat exposure. Advanced techniques, including atom probe tomography, scanning transmission electron microscopy, and neutron diffraction, show that this improvement is driven by the evolution of Sb-induced complementary point defects. Although heat exposure significantly reduces lattice disorder in intrinsic NbCoSn, NbCoSn_0.9Sb_0.1 retains its lattice disorder by forming alternative point defects, thereby maintaining its lattice thermal conductivity. This detailed experimental work, corroborated by ab initio calculations, highlights the pivotal role of the point defect dynamics in achieving robust thermoelectric performances in half-Heusler compounds for high-temperature applications.

Solar radiation modification (SRM) is increasingly discussed as a potential method to ameliorate some negative effects of climate change. However, unquantified uncertainties in physical and environmental impacts of SRM impede informed debate and decision making. Some uncertainties are due to lack of understanding of processes determining atmospheric effects of SRM and/or a lag in development of their representation in models, meaning even high-quality model intercomparisons will not necessarily reveal or address them. Although climate models at multiple scales are advancing in complexity, there are specific areas of uncertainty where additional model development (often requiring new observations) could significantly advance understanding of SRM's effects, and improve our ability to assess and weigh potential risks against those of choosing to not use SRM. We convene expert panels in the areas of atmospheric science most critical to understanding the three most widely discussed forms of SRM. Each identifies three key modeling gaps relevant to either stratospheric aerosols, cirrus, or low-altitude marine clouds. Within each area, key challenges remain in capturing impacts due to complex interactions in aerosol physics, atmospheric chemistry/dynamics, and aerosol-cloud interactions. Across all three, in addition to arguing for more observations, the panels argue that model development work to either leverage different capabilities of existing models, bridge scales across which relevant processes operate, or address known modeling gaps could advance understanding. By focusing on these knowledge gaps we believe the modeling community could advance understanding of SRM's physical risks and potential benefits, allowing better-informed decision-making about whether and how to use SRM.

Objective
To study the association between various radiographic definitions of acetabular dysplasia (AD) and incident radiographic hip osteoarthritis (RHOA), and to analyze in subgroups.

Methods
Hips free of RHOA at baseline and with follow-up within 4–8 years were drawn from the World COACH consortium. The Wiberg center edge angle (WCEA), acetabular depth width ratio (ADR), and the modified acetabular index (mAI) were calculated. AD was defined as WCEA≤25°, and for secondary analyses as WCEA≤20°, ADR ≤250, mAI ≥ 13°, and a combination. A logistic regression model with generalized mixed effects with 3 levels adjusted for age, biological sex, and body mass index (BMI) was used. Descriptive statistics stratified by age, biological sex and BMI were reported.

Results
A total of 18,807 hips from 9 studies were included. Baseline characteristics: age 61.84 (± 8.32) years, BMI 27.40 (± 4.49) kg/m², 70.1% women. 4766 hips (25.3%) had WCEA≤25°. Within 4–8 years (mean 5.8 ±1.6) follow-up, 378 hips (2.0%) developed incident RHOA. We found an association between AD and RHOA (adjusted OR [aOR] 1.80 95% confidence interval [CI] 1.40–2.34). In secondary analyses, all other definitions of AD were also associated with incident RHOA (aOR ranging from 1.52 95% CI 1.19–1.94 to 1.96 95% CI 1.26–3.02). Descriptive statistics showed that the relative risk (RR) in AD hips to develop RHOA was higher compared to non-AD hips in age group 61–70 (RR 1.70), BMI<25 (RR 1.66), and in female hips (RR 1.73).

Conclusion
AD was consistently associated with incident RHOA. Explorative analyses show that AD hips in women and age group 61–70 years seem to be more at risk of developing RHOA compared to non-AD hips.

Recycling-oriented alloy design is a crucial part of material sustainability, as it reduces the need for raw material extraction and minimises environmental impact. This requires that scraps be reused or repurposed effectively, even when the scraps are co-mingled and have higher costs for further sorting and separation. In this work, we explore an alloy design concept by creating a compositionally flexible domain that can recycle multiple alloy grades and yet maintain relatively consistent properties across chemical variations. This is demonstrated through the Fe-Cr-Ni-Mn system to identify compositionally flexible austenitic stainless steels (CF-ASS) and accommodate the recycling of mixed austenitic stainless steel scraps. Alloys within the nominal composition spaces exhibit relatively consistent mechanical properties and corrosion resistance despite significant variations in different alloy compositions. We illustrate how we can utilise the compositionally flexible austenitic stainless steels to recycle mixed 200 and 300-series stainless steel and ferronickel scraps, demonstrating its practical viability. While this demonstration focuses on the stainless steel system, the underlying principles can be extended to other systems related to mixed scrap recycling.