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The Prion protein is the molecular hallmark of the incurable prion diseases affecting mammals, including humans. The protein-only hypothesis states that the misfolding, accumulation, and deposition of the Prion protein play a critical role in toxicity. The cellular Prion protein (PrP^C) anchors to the extracellular leaflet of the plasma membrane and prefers cholesterol- and sphingomyelin-rich membrane domains. Conformational Prion protein conversion into the pathological isoform happens on the cell surface.In vitroandin vivoexperiments indicate that Prion protein misfolding, aggregation, and toxicity are sensitive to the lipid composition of plasma membranes and vesicles. A picture of the underlying biophysical driving forces that explain the effect of Prion protein - lipid interactions in physiological conditions is needed to develop a structural model of Prion protein conformational conversion. To this end, we use molecular dynamics simulations that mimic the interactions between the globular domain of PrP^Canchored to model membrane patches. In addition, we also simulate the Doppel protein anchored to such membrane patches. The Doppel protein is the closest in the phylogenetic tree to PrP^C, localizes in an extracellular milieu similar to that of PrP^C, and exhibits a similar topology to PrP^Ceven if the amino acid sequence is only 25% identical. Our simulations show that specific protein-lipid interactions and conformational constraints imposed by GPI anchoring together favor specific binding sites in globular PrP^Cbut not in Doppel. Interestingly, the binding sites we found in PrP^Ccorrespond to prion protein loops, which are critical in aggregation and prion disease transmission barrier (β2-α2 loop) and in initial spontaneous misfolding (α2-α3 loop). We also found that the membrane re-arranges locally to accommodate protein residues inserted in the membrane surface as a response to protein binding. 

We use galaxy cluster abundance measurements from the South Pole Telescope enhanced by multicomponent matched filter confirmation and complemented with mass information obtained using weak-lensing data from Dark Energy Survey Year 3 (DES Y3) and targeted Hubble Space Telescope observations for probing deviations from the cold dark matter paradigm. Concretely, we consider a class of dark sector models featuring interactions between dark matter (DM) and a dark radiation (DR) component within the framework of the effective theory of structure formation (ETHOS). We focus on scenarios that lead to power suppression over a wide range of scales, and thus can be tested with data sensitive to large scales, as realized, for example, for DM–DR interactions following from an unbroken non-Abelian $SU\left(N\right)$gauge theory (interaction rate with power-law index $n=0$within the ETHOS parametrization). Cluster abundance measurements are mostly sensitive to the amount of DR interacting with DM, parametrized by the ratio of DR temperature to the cosmic microwave background (CMB) temperature, ${\xi }_{\mathrm{DR}}=T_{\mathrm{DR}}/T_{\mathrm{CMB}}$. We find an upper limit ${\xi }_{\mathrm{DR}}<17\%$at 95% credibility. When the cluster data are combined with Planck 2018 CMB data along with baryon acoustic oscillation (BAO) measurements we find ${\xi }_{\mathrm{DR}}<10\%$, corresponding to a limit on the abundance of interacting DR that is around 3 times tighter than that from CMB + BAO data alone. We also discuss the complementarity of weak lensing informed cluster abundance studies with probes sensitive to smaller scales, explore the impact on our analysis of massive neutrinos, and comment on a slight preference for the presence of a nonzero interacting DR abundance, which enables a physical solution to the $S_8$tension. Published by the American Physical Society2025 

Context. The interaction between active galactic nuclei (AGNs) and their host galaxies is scarcely resolved. Narrow-line Seyfert 1 (NLS1) galaxies are believed to represent AGN at early stages of their evolution and to allow one to observe feeding and feedback processes at high black hole accretion rates. Aims. We aim to constrain the properties of the ionised gas outflow in Mrk 1044, a nearby super-Eddington accreting NLS1. Based on the outflow energetics and the associated timescales, we estimate the outflow’s future impact on the ongoing host galaxy star formation on different spatial scales. Methods. We applied a spectroastrometric analysis to observations of Mrk 1044’s nucleus obtained with the adaptive-optics-assisted narrow field mode of the VLT/MUSE instrument. This allowed us to map two ionised gas outflows traced by [O  III ], which have velocities of −560 ± 20 km s −1 and −144 ± 5 km s −1 . Furthermore, we used an archival spectrum from the Space Telescope Imaging Spectrograph on HST to identify two Ly- α absorbing components that escape from the centre with approximately twice the velocity of the ionised gas components. Results. Both [O  III ] outflows are spatially unresolved and located close to the AGN (< 1 pc). They have gas densities higher than 10 5 cm −3 , which implies that the BPT diagnostic cannot be used to constrain the underlying ionisation mechanism. We explore whether an expanding shell model can describe the velocity structure of Mrk 1044’s multi-phase outflow. In the ionised gas emission, an additional outflowing component, which is spatially resolved, is present. It has a velocity of −211 ± 22 km s −1 and a projected size of 4.6 ± 0.6 pc. Our kinematic analysis suggests that significant turbulence is present in the interstellar medium around the nucleus, which may lead to a condensation rain, potentially explaining the efficient feeding of Mrk 1044’s AGN. Within the innermost 0.5″ (160 pc), we detect modest star formation hidden by the beam-smeared emission from the outflow. Conclusions. We estimate that the multi-phase outflow was launched < 10 4 yr ago. Together with the star formation in the vicinity of the nucleus, this suggests that Mrk 1044’s AGN phase started only recently. The outflow carries enough mass and energy to impact the host galaxy star formation on different spatial scales, highlighting the complexity of the AGN feeding and feedback cycle in its early stages. 

SUMMARY It is well known that the axial dipole part of Earth’s magnetic field reverses polarity, so that the magnetic North Pole becomes the South Pole and vice versa. The timing of reversals is well documented for the past 160 Myr, but the conditions that lead to a reversal are still not well understood. It is not known if there are reliable ‘precursors’ of reversals (events that indicate that a reversal is upcoming) or what they might be. We investigate if machine learning (ML) techniques can reliably identify precursors of reversals based on time-series of the axial magnetic dipole field. The basic idea is to train a classifier using segments of time-series of the axial magnetic dipole. This training step requires modification of standard ML techniques to account for the fact that we are interested in rare events—a reversal is unusual, while a non-reversing field is the norm. Without our tweak, the ML classifiers lead to useless predictions. Perhaps even more importantly, the usable observational record is limited to 0–2 Ma and contains only five reversals, necessitating that we determine if the data are even sufficient to reliably train and validate an ML algorithm. To answer these questions we use several ML classifiers (linear/non-linear support vector machines and long short-term memory networks), invoke a hierarchy of numerical models (from simplified models to 3-D geodynamo simulations), and two palaeomagnetic reconstructions (PADM2M and Sint-2000). The performance of the ML classifiers varies across the models and the observational record and we provide evidence that this is not an artefact of the numerics, but rather reflects how ‘predictable’ a model or observational record is. Studying models of Earth’s magnetic field via ML classifiers thus can help with identifying shortcomings or advantages of the various models. For Earth’s magnetic field, we conclude that the ability of ML to identify precursors of reversals is limited, largely due to the small amount and low frequency resolution of data, which makes training and subsequent validation nearly impossible. Put simply: the ML techniques we tried are not currently capable of reliably identifying an axial dipole moment (ADM) precursor for geomagnetic reversals. This does not necessarily imply that such a precursor does not exist, and improvements in temporal resolution and length of ADM records may well offer better prospects in the future. 

Nitrogen hydrides such as NH3 and N2H+ are widely used by Galactic observers to trace the cold dense regions of the interstellar medium. In external galaxies, because of limited sensitivity, HCN has become the most common tracer of dense gas over large parts of galaxies. We provide the first systematic measurements of N2H+ (1-0) across different environments of an external spiral galaxy, NGC 6946. We find a strong correlation (r > 0.98, p < 0.01) between the HCN (1-0) and N2H+ (1-0) intensities across the inner ∼8 kpc of the galaxy, at kiloparsec scales. This correlation is equally strong between the ratios N2H+ (1-0)/CO (1-0) and HCN (1-0)/CO (1-0), tracers of dense gas fractions (fdense). We measure an average intensity ratio of N2H+ (1-0)/HCN (1-0) = 0.15 ± 0.02 over our set of five IRAM-30m pointings. These trends are further supported by existing measurements for Galactic and extragalactic sources. This narrow distribution in the average ratio suggests that the observed systematic trends found in kiloparsec-scale extragalactic studies of fdense and the efficiency of dense gas (SFEdense) would not change if we employed N2H+ (1-0) as a more direct tracer of dense gas. At kiloparsec scales our results indicate that the HCN (1-0) emission can be used to predict the expected N2H+ (1-0) over those regions. Our results suggest that, even if HCN (1-0) and N2H+ (1-0) trace different density regimes within molecular clouds, subcloud differences average out at kiloparsec scales, yielding the two tracers proportional to each other. 

Context.The determination of accurate photometric redshifts (photo-zs) in large imaging galaxy surveys is key for cosmological studies. One of the most common approaches is machine learning techniques. These methods require a spectroscopic or reference sample to train the algorithms. Attention has to be paid to the quality and properties of these samples since they are key factors in the estimation of reliable photo-zs. Aims.The goal of this work is to calculate the photo-zsfor the Year 3 (Y3) Dark Energy Survey (DES) Deep Fields catalogue using the Directional Neighborhood Fitting (DNF) machine learning algorithm. Moreover, we want to develop techniques to assess the incompleteness of the training sample and metrics to study how incompleteness affects the quality of photometric redshifts. Finally, we are interested in comparing the performance obtained by DNF on the Y3 DES Deep Fields catalogue with that of the EAzY template fitting approach. Methods.We emulated – at a brighter magnitude – the training incompleteness with a spectroscopic sample whose redshifts are known to have a measurable view of the problem. We used a principal component analysis to graphically assess the incompleteness and relate it with the performance parameters provided by DNF. Finally, we applied the results on the incompleteness to the photo-zcomputation on the Y3 DES Deep Fields with DNF and estimated its performance. Results.The photo-zsof the galaxies in the DES deep fields were computed with the DNF algorithm and added to the Y3 DES Deep Fields catalogue. We have developed some techniques to evaluate the performance in the absence of “true” redshift and to assess the completeness. We have studied the tradeoff in the training sample between the highest spectroscopic redshift quality versus completeness. We found some advantages in relaxing the highest-quality spectroscopic redshift requirements at fainter magnitudes in favour of completeness. The results achieved by DNF on the Y3 Deep Fields are competitive with the ones provided by EAzY, showing notable stability at high redshifts. It should be noted that the good results obtained by DNF in the estimation of photo-zsin deep field catalogues make DNF suitable for the future Legacy Survey of Space and Time (LSST) andEucliddata, which will have similar depths to the Y3 DES Deep Fields. 

Selenium (Se) is an essential micronutrient for growth and immune function in beef cattle. We previously showed that supranutritional maternal organic Se supplementation during late pregnancy improves immune function in their newborn calves; however, the effects of maternal organic Se-supplementation on fetal programming during different pregnancy stages have yet to be elucidated. Herein, we investigated the effects of supranutritional maternal organic Se-supplementation in different pregnancy trimesters on their beef calf’s genome-wide transcriptome profiles. Within 12 to 48 h of birth, whole blood and Longissimus dorsi (LD) muscle biopsies were collected from calves born to 40 crossbred Angus cows that received, except for the control group (CTR), Se-yeast boluses (105 mg of Se/wk) during the first (TR1), second (TR2), or third (TR3) trimester of gestation. Whole-blood Se concentrations of newborn calves increased from CTR, TR1, TR2 to TR3, whereas muscle Se concentrations of newborn calves were only increased in TR3 group. We identified 3048 unique differentially expressed genes (DEGs) across all group comparisons (FDR ≤ 0.05 and |log2FC| ≥ 1.5). Furthermore, we predicted 237 unique transcription factors that putatively regulate the DEGs. Independent of supplementation trimester, supranutritional maternal organic Se supplementation downregulated genes involved in adaptive immunity in all trimesters. Dependent on supplementation trimester, genes involved in muscle development were upregulated by TR3 Se supplementation and downregulated by TR1 Se-supplementation, and genes involved in collagen formation were downregulated by TR2 Se-supplementation. Supranutritional maternal organic Se supplementation in the last trimester of pregnancy resulted in upregulation of myosin and actin filament associated genes, potentially allowing for optimal muscle function and contraction. Our findings suggest a beneficial effect of supranutritional maternal organic Se supplementation during late gestation on Se-status and muscle development and function of newborn calves. 

Context. The host galaxy conditions for rapid supermassive black hole growth are poorly understood. Narrow-line Seyfert 1 (NLS1) galaxies often exhibit high accretion rates and are hypothesized to be prototypes of active galactic nuclei (AGN) at an early stage of their evolution. Aims. We present adaptive optics (AO) assisted VLT MUSE NFM observations of Mrk 1044, the nearest super-Eddington accreting NLS1. Together with archival MUSE WFM data, we aim to understand the host galaxy processes that drive Mrk 1044’s black hole accretion. Methods. We extracted the faint stellar continuum emission from the AGN-deblended host and performed spatially resolved emission line diagnostics with an unprecedented resolution. Combining both MUSE WFM and NFM-AO observations, we used a kinematic model of a thin rotating disk to trace the stellar and ionized gas motion from 10 kpc galaxy scales down to ∼30 pc around the nucleus. Results. Mrk 1044’s stellar kinematics follow circular rotation, whereas the ionized gas shows tenuous spiral features in the center. We resolve a compact star-forming circumnuclear ellipse (CNE) that has a semi-minor axis of 306 pc. Within this CNE, the gas is metal-rich and its line ratios are entirely consistent with excitation by star formation. With an integrated star formation rate of 0.19 ± 0.05  M ⊙  yr −1 , the CNE contributes 27% of the galaxy-wide star formation. Conclusions. We conclude that Mrk 1044’s nuclear activity has not yet affected the circumnuclear star formation. Thus, Mrk 1044 is consistent with the idea that NLS1s are young AGN. A simple mass budget consideration suggests that the circumnuclear star formation and AGN phase are connected and the patterns in the ionized gas velocity field are a signature of the ongoing AGN feeding.