Reykjavík University

Continuous geodetic measurements near volcanic systems can image magma transport dynamics, yet resolving dike intrusions with high spatiotemporal resolution remains challenging. We introduce fiber-optic geodesy, leveraging low-frequency distributed acoustic sensing (LFDAS) recordings along a telecommunication fiber-optic cable, to track dike intrusions near Grindavík, Iceland, on a minute timescale. LFDAS reveals distinct strain responses from nine intrusive events, six resulting in fissure eruptions. Geodetic inversion of LFDAS strain reveals detailed magmatic intrusions, with inferred dike volume rate peaking systematically 15 to 22 min before the onset of each eruption. Our results demonstrate DAS’s potential for a dense strainmeter array, enabling high-resolution, nearly real-time imaging of subsurface quasi-static deformations. In active volcanic regions, LFDAS recordings can offer critical insights into magmatic evolution, eruption forecasting, and hazard assessment.

Introduction Feeding intolerance complicates enteral nutrition in intensive care unit (ICU) patients but is poorly defined. Prokinetic agents are administered to facilitate the uptake of enteral nutrition, but preferences for their use among clinicians in ICUs are unknown. Methods We conducted an international electronic survey targeting ICU doctors. The survey included 76 questions that focused on symptoms considered when assessing feeding intolerance, preferences for using prokinetic agents, and willingness to participate in a future randomised trial on prokinetic agents. Results We received 830 responses from 17 countries, with an overall response rate of 29%. Most respondents were specialists working in mixed ICUs. Feeding intolerance was assessed by 90% of respondents in their clinical work, though only 36% considered it well defined. Gastric residual volume and vomiting were symptoms most frequently used for defining feeding intolerance. Metoclopramide was the preferred prokinetic agent (54% of respondents), followed by erythromycin (42%). Four out of five considered using combination therapy, primarily a combination of metoclopramide and erythromycin (89%). Concerns about side effects were reported for all agents, with extrapyramidal symptoms and QT prolongation being the most common across agents. The majority (91%) of respondents supported a future randomised trial comparing prokinetic agents to placebo. Conclusion This international survey found practice variations in the symptoms reportedly used to assess feeding intolerance. Metoclopramide was the preferred prokinetic agent, followed by erythromycin. Most respondents supported a future randomised trial.

Cetacean interactions can be diverse and complex, spanning agonistic to affiliative behaviors. While killer whales are known for complex hunting strategies and a wide range of prey worldwide, they also engage in various non‐predatory interspecific interactions. This study describes two encounters off south Iceland, on the 23rd of June 2022 and the 20th of June 2023, where neonate pilot whales were observed with killer whale groups. No other pilot whales were sighted in the area for the duration of these encounters. The killer whale groups, of mixed age and sex classes, engaged in slow travel, foraging and social behaviors throughout the encounters. The pilot whale calves were seen surfacing in front of killer whales or in echelon position, and at times being lifted out of the water. Photo‐identification revealed that, while different individual whales participated in each event, all were likely fish‐eating specialists. The interactions with the calves displayed no clear signs of predation. We explore several hypotheses for the function of these interactions, which appear suggestive of play behavior (whether affiliative or agonistic in nature), or possibly practice hunting, or epimeletic behavior. However, because neither interaction between killer whales and a pilot whale neonate was observed from start to end, the true motivation and function of the interactions remain unknown. Our observations not only highlight the complexity of these interactions but also underscore the broader importance of investigating interspecific encounters among cetaceans and other mammals, where such behaviors can offer insights into ecological and social processes.

Background Early initiation of effective treatment is associated with positive long-term prognosis for patients with rheumatoid arthritis (RA). Currently, there are no biomarkers in clinical use to predict treatment response. A predictor of treatment response may be the B-cell compartment, as this is altered in RA patients, making it a potential candidate for predicting treatment response. In this study, we sought to identify B-cell subset(s) at diagnosis that might be associated with Clinical Disease Activity Index (CDAI) remission at 24-week follow-up. Methods Seventy early RA patients from the NORD-STAR trial, recruited from two Swedish sites, and 28 matched healthy controls, were included in this spin-off study. In NORD-STAR, all patients were randomized to methotrexate (MTX) combined with 1) prednisolone, 2) anti-TNF (certolizumab-pegol), 3) CTLA4-Ig (abatacept), or 4) anti-IL-6R (tocilizumab). Circulating B-cell subsets at diagnosis were assessed by flow cytometry. The primary outcome measure was remission according to CDAI ≤ 2.8. A multivariate two-part discriminant analysis was performed to assess whether B-cell subpopulations at diagnosis could predict remission at 24 weeks. Subsequent univariable statistical analyses were performed using t-tests, Mann-Whitney U, or Kruskal-Wallis tests, as appropriate. Correlations were analyzed using Spearman or Pearson tests, depending on data type. The impact of specific B-cell populations on remission at week 24 was assessed using logistic regression models. The logistic regression model was also used to simultaneously visualize the sensitivity and specificity of the model for all possible values of the exposure (B-cell subpopulations) in predicting the outcome. Results Patients who achieved CDAI remission at 24 weeks had higher proportions of transitional (p < 0.01) and CD21⁻ PD-1⁺ (p < 0.01) B cells at diagnosis compared to those who did not. When the two B-cell populations were combined, the sensitivity and specificity for remission, including all treatment arms, were 59% and 86%, respectively. Stratification of the patients by treatment arm revealed a significant negative correlation between the proportion of transitional B cells at baseline and disease activity after 24 weeks of treatment with either MTX and prednisolone or anti-IL-6R. Conclusions Our results indicate that transitional and CD21⁻ PD-1⁺ B cells are associated with remission in early RA. Clinical trial number Not applicable.

Background and Aims It can be difficult to distinguish between drug‐induced liver injury (DILI) and liver injury associated with sepsis (sepsis induced liver injury, SILI). The aims of the study were to compare clinical and biochemical features between DILI and SILI and identify distinguishing characteristics that might assist in diagnosing these conditions. Methods Retrospective cohorts of all DILI cases diagnosed in Iceland 2009–2024 and SILI 2006–2024 were divided into hepatocellular and cholestatic (CS/mixed) patterns. Patients had: > 5× upper limit of normal (ULN) of ALT and/or > 2× ULN in ALP. RUCAM and expert opinion were used in the causality assessment of DILI, and SILI patients had to fulfil international consensus criteria. Results Overall 275 DILI patients (median age 59 years, 63% females), 153 with SILI (67 years, 49% females) were included. Among patients with HC type, 57% with SILI and only one (0.9%) with DILI had normal liver tests 2 weeks after the event. The peak value of AST was 1794 (IQR 931–3526) IU/L in HC type of SILI but 584 (315–1013) IU/L in DILI, p < 0.001. CS/mixed type of SILI resolved also significantly faster while CS/mixed pattern of DILI had significantly higher ALP at onset and peak ALT than SILI. SILI had 30% mortality compared to DILI (2%) p < 0.001. Conclusions Marked elevation of AST and rapid resolution with a HC pattern of liver injury favours the diagnosis of SILI. Cholestatic/mixed SILI also resolves rapidly in contrast to CS/mixed DILI that is associated with markers of more pronounced liver injury.

The magnetic telechemistry hypothesis proposes that hotspot mantle contains elevated Fe and Ti leading to enhanced crustal magnetic anomaly strength. Ridge segmentation and other geologic factors also influence oceanic crustal magnetization, potentially complicating the identification of a hotspot signature. At the Reykjanes Ridge, distinct segmented (offset) and unsegmented (linear axis) crustal terrains formed at different times over the Iceland hotspot allow an examination of these effects as well as contrasting hotspot models. We use ship magnetic anomaly data to invert for basement magnetization and examine variations in its root‐mean‐square intensity. We find that the unsegmented “linear” terrains indeed have greater magnetization intensities than the “segmented” terrain, in agreement with some models in which mantle plume material advanced, retreated, and advanced again forming these terrains. However, we also resolve a magnetization intensity low centered along a flowline at 61°N that cuts across the basin and coincides on axis with a previously identified geochemical boundary. We conclude that crustal age, resolution effects, and ridge segmentation create the main magnetization variations among the various terrains of the Reykjanes Ridge. The coincidence of a major geochemical boundary with a basin‐crossing magnetization low, however, indicates a stably zoned hotspot mantle anomaly rather than a rapidly upwelling and radially flowing mantle plume.

Electromagnetic (EM) simulation is widespread in microwave engineering. EM tools ensure evaluation reliability but incur significant expenses. These can be mitigated by employing surrogate modeling methods, especially to expedite design workflows like local/global optimization or uncertainty quantification. However, building accurate surrogates is a daunting task beyond simple cases (low dimensionality, narrow geometry parameter and frequency ranges). This research suggests a new technique for dependable modeling of microwave circuits. Its main ingredient is a recurrent neural network (RNN) with the main architectural components being bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers. These are incorporated to accurately represent frequency relationship within circuit characteristics as well as dependencies between its dimensions and outputs considered as vector-valued functions parameterized by frequency. The network’s hyperparameters are adjusted through Bayesian Optimization (BO). Utilization of frequency as a sequential variable handled by RNN is a distinguishing feature of our approach, which leads to the enhancement of dependability and cost efficiency. Another critical factor is dimension- and volume-wise reduction of the model’s domain achieved through global sensitivity analysis. It allows for additional and dramatic accuracy improvements without diminishing the surrogate’s coverage regarding circuit’s operating parameters. Our methodology has been extensively validated using several microstrip structures. The results demonstrate its competitive performance over a range of kernel-based regression techniques and diverse neural networks. The proposed procedure ensures building models of outstanding predictive power while using small training datasets, which is beyond the capabilities of benchmark algorithms.

This research focuses on designing a novel miniaturized biosensor for early-stage detection of leukemia. The proposed sensor operates in the low Petahertz (PHz) range. The primary prerequisites for the development process include multi-band operation, compact physical size, near-perfect absorption at resonant frequencies, and insensitivity to the angle of incidence. These features are crucial for ensuring high-performance operation in microwave imaging (MWI) and have been achieved through meticulous design of the absorber’s geometry and dimensions. The sensor incorporates a dipole and two rings made of gold or silver, implanted on a silicon dioxide dielectric substrate with a fully metallic backplane. The evolution of the biosensor’s topology is detailed, along with comprehensive simulation studies conducted using a commercial full-wave electromagnetic (EM) solver. The operating principles are explained through parametric studies, analysis of absorption and refraction characteristics, and discussions of electric and magnetic fields, as well as surface current density distributions. The device’s suitability for blood cancer diagnostics is demonstrated through full-wave analysis of the MWI system, highlighting the sensor’s ability to discriminate between healthy and cancerous samples through noticeable frequency shifts in absorption responses. Extensive comparisons with the state-of-the-art biosensors reported in recent literature show that the proposed device significantly improves spectral properties and achieves remarkable spatial resolution due to its PHz range operation when compared to the benchmark.

Laboratory and animal studies indicate that melatonin exerts a negative impact on breast cancer progression and metastasis. These actions are both receptor-dependent and -independent. Of the two transmembrane melatonin receptors identified in humans, breast cancer expresses only MT1. The aim of this study was to investigate the expression of MT1 in hormone-receptor-positive, HER2-negative invasive ductal breast carcinoma in postmenopausal women and its possible correlations with clinicopathological parameters and survival. A total of 118 patients with luminal A/B primary breast cancer with or without axillary metastases were identified. The MT1 receptor expression was immunohistochemically assessed as a percentage of stained cells and a weighted index (WI) (percentage multiplied by staining intensity). Most tumor samples (84.7%) and metastasized lymph nodes (96%) stained positive for MT1, with varying intensity. No statistically significant correlations were found between the MT1 expression or the WI in the primary tumor and the patient and tumor characteristics, or the MT1 and WI in the metastasized lymph nodes. The survival analysis did not reveal a significant effect of MT1 expression or the WI on the risk of recurrence or survival.

Genome-wide association studies (GWASs) may help inform the etiology of infertility. Here, we perform GWAS meta-analyses across seven cohorts in up to 42,629 cases and 740,619 controls and identify 25 genetic risk loci for male and female infertility. We additionally identify up to 269 genetic loci associated with follicle-stimulating hormone, luteinizing hormone, estradiol and testosterone through sex-specific GWAS meta-analyses (n = 6,095–246,862). Exome sequencing analyses reveal that women carrying testosterone-lowering rare variants in some genes are at risk of infertility. However, we find no local or genome-wide genetic correlation between female infertility and reproductive hormones. While infertility is genetically correlated with endometriosis and polycystic ovary syndrome, we find limited genetic overlap between infertility and obesity. Finally, we show that the evolutionary persistence of infertility-risk alleles may be explained by directional selection. Taken together, we provide a comprehensive view of the genetic determinants of infertility across multiple diagnostic criteria.

Orbital angular momentum (OAM) of light appears when the phase of an electromagnetic wavefront winds around its direction of propagation, also known as optical vorticity. Contrary to the binary‐valued photon spin, the integer‐valued optical vortex charge is unbounded with many advantages in optical communication and trapping and enhancing the capacity of data encoding and multiplexing. Singular optoelectronic and chiroptic quantum technologies rely on the development of coherent and compact light sources of well‐defined and reconfigurable OAM. An optically tunable discrete chiral exciton‐polariton microlaser is proposed, which leverages strong spin‐dependent polariton interactions, structured pumping, and inherent cavity photon spin‐to‐angular momentum conversion to emit coherent nonlinear light of variable OAM. By choosing pumping patterns with broken inversion symmetry in the microcavity plane, geometric frustration is invoked between spinor ballistic condensates which spontaneously obtain a high‐charge circulating current locked with the pump polarization. This optically configurable system requires only a planar cavity, thus avoiding the need for specialized irreversible cavity patterning or metasurfaces.

This chapter aims to identify positive and negative risks related to the three IC dimensions that may arise in connection with the increasing use of AI-based tools. From the perspective of smaller companies, it will be made clear not only how manifold these risks related to IC are, but that they need not be negative per se. More precisely, in this chapter positive and negative risks for each IC dimension are identified and described. The findings presented in this chapter are likely to be valuable for different target groups. The chosen approach can not only give academics new food for thought but also provide practitioners with an alternative way of thinking about IC risks (the IC dimensions) in connection with the use of AI. This alternative way of thinking is reinforced by viewing AI as augmentation and substitution, which allows for a more detailed discussion of the topic.

Purpose Accurately identifying sleep states (REM, NREM, and Wake) and brief awakenings (arousals) is essential for diagnosing sleep disorders. Polysomnography (PSG) is the gold standard for such assessments but is costly and requires overnight monitoring in a lab. Home sleep testing (HST) offers a more accessible alternative, relying primarily on breathing measurements but lacks electroencephalography, limiting its ability to evaluate sleep and arousals directly. This study evaluates a deep learning algorithm which determines sleep states and arousals from breathing signals. Methods A novel deep learning algorithm was developed to classify sleep states and detect arousals from respiratory inductance plethysmography signals. Sleep states were predicted for 30-s intervals (one sleep epoch), while arousal probabilities were calculated at 1-s resolution. Validation was conducted on a clinical dataset of 1,299 adults with suspected sleep disorders. Performance was assessed at the epoch level for sensitivity and specificity, with agreement analyses for arousal index (ArI) and total sleep time (TST). Results The algorithm achieved sensitivity and specificity of 77.9% and 96.2% for Wake, 93.9% and 80.4% for NREM, 80.5% and 98.2% for REM, and 66.1% and 86.7% for arousals. Bland–Altman analysis showed ArI limits of agreement ranging from - 32 to 24 events/hour (bias: - 4.4) and TST limits from - 47 to 64 min (bias: 8.0). Intraclass correlation was 0.74 for ArI and 0.91 for TST. Conclusion The algorithm identifies sleep states and arousals from breathing signals with agreement comparable to established variability in manual scoring. These results highlight its potential to advance HST capabilities, enabling more accessible, cost-effective and reliable sleep diagnostics.

Having a child with a disability undoubtedly affects parents in many ways, including their well‐being. However, the specific mental health trajectories of parents, differentiated by the severity of impairments and parental roles, remain under‐explored. We investigate the mental‐health effects of having a child with a disability. Using individual‐level register data from Sweden, we exploit the epidemiological features of Cerebral Palsy (CP) to estimate causal effects. Results show that prescriptions for mental‐health disorders increase after the birth of a child with CP. While fathers are more likely to be dispensed anti‐anxiety medications, dispensed medications for anti‐depressants increase for mothers. Further, the effects are larger for parents of children with severe impairments but do not differ across parental characteristics. Our findings highlight the need for support and assistance for families with children with disabilities.

This paper presents a compact tri-band omnidirectional antenna designed for CubeSat applications, operating at UHF (0.755 GHz), L-band (1.25 GHz), and S-band (2.28–3.74 GHz). The antenna features a defected ground structure (DGS) and metallic vias, which enhance impedance matching and enable stable multi-band resonance while maintaining a small footprint of 0.26λ × 0.26λ × 0.013λ within a 1U CubeSat. Unlike conventional CubeSat antennas that require external deployment, the proposed design is fully enclosed within the CubeSat, ensuring easy integration and mechanical robustness. The antenna exhibits omnidirectional radiation patterns across all frequency bands, making it suitable for reliable satellite-ground communication. The measured results confirm a high radiation efficiency exceeding 90%, and strong agreement between simulated and experimental results. The combination of compact size, multi-band operation, and high efficiency makes this antenna an ideal candidate for next-generation CubeSat communication systems.

Background Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but individual response varies and remains difficult to predict. The role of genetics remains unclear, but studies suggest its importance. Methods Incident RA patients starting MTX‐monotherapy were identified through a large‐scale Swedish register linkage. Demographic, clinical, medical, and drug history features were combined with fully imputed genotype data and used to train and evaluate multiple learning models to predict key MTX treatment outcomes. Results Among 2432 patients, we consistently observed an estimated area under the curve (AUC) of ∼0.62, outperforming models trained on sex and age. The best performance was observed for EULAR primary response (AUC = 0.67), whereas models struggled the most with predicting discontinuation. Genetics provided negligible improvements to prediction quality. Conclusions Despite an extensive study population with broad multi‐modal data, predicting MTX treatment outcomes remains a challenge. Common genetic variants added minimal predictive power over clinical features.

Optimization methods have been rapidly entering the realm of antenna design over the last several years. Despite many available algorithms, practical optimization is demanding due to the high electromagnetic (EM) analysis cost necessary for dependable antenna assessment. This is particularly troublesome in global parameter tuning, routinely conducted using nature-inspired procedures. Unfortunately, these methods are known for their poor computational efficiency. Surrogate modeling may mitigate this issue to a certain extent, yet dimensionality and parameter range issues severely impede the construction of accurate metamodels. This research suggests an innovative algorithm for global parameter adjustment of antenna systems. It conducts a simplex-based search in the space of the structure’s performance figures (e.g., center frequencies, bandwidth, etc.). Operating at this level regularizes the objective function. Low cost is achieved by the simplex updating strategy requiring only one EM analysis per iteration, and multi-resolution simulations. The global search state involves coarse-discretization full-wave analysis, whereas final (gradient-based) parameter tuning involves medium-fidelity simulations for sensitivity estimation and high-fidelity models for design verification. The developed algorithmic framework is validated using four microstrip antennas. The results generated in multiple runs demonstrate global search capability and remarkably low expenses, corresponding to around a hundred high-fidelity analyses on average. The performance level is competitive over local and global optimizers.