Upernavik Isstrøm, the largest contributor to sea-level rise in northwest Greenland, has experienced complex and contrasting ice-flow-speed changes across its five outlets over the last two decades. In this study, we present a detailed remote-sensing analysis of the ice dynamics at Upernavik's outlets from 2000 to 2021 to evaluate the details of these changes. Previous research suggested that the presence or absence of floating ice tongues strongly influences Upernavik's ice dynamics. We use several lines of evidence to document the presence of floating ice tongues, and find that, while several outlets experienced ice-tongue formation and/or loss during the study period, these changes do not explain observed fluctuations in ice-flow velocity. Further exploration of ice-dynamic forcings using a flowline model suggests that changes in basal slipperiness near the terminus have a strong impact on upstream ice dynamics and can explain the velocity variations. Our results suggest that speed fluctuations at Upernavik's outlets may be seasonally and interannually controlled by bed conditions near the terminus, and highlight the need for further research on the influence of basal conditions on complex tidewater glacier dynamics.

Background: There is growing body of evidence linking abnormal eye movements in people with multiple sclerosis (MS) to disease severity and cognition which could better detect disease progression. The objective of this study is to determine if a novel eye-tracking tool can accurately predict disease severity and cognitive status based on eye movement metrics and characterize how they evolve with progression. Methods: Persons with MS (n=132) will be followed over 4 years with clinical assessments every 6 months. Eye movements are also assessed while performing oculomotor tasks using Innodem Neurosciences’ patented eye-tracking technology. The eye movement metrics will be inputted into machine learning classifying algorithms to identify which metrics can serve as reliable Eye Movement Biomarkers (EMB) for MS progression and cognitive status. Results: There were 16 participants recruited as of January 2022 with mean age 47. 3 (SD 10.4; range 26-67), gender (12F/4M), EDSS 2.59 (SD 1.49; range 1.5-6.5), SDMT 51.4 (SD 14.1, range 24-78). With current enrollment, there is a negative correlation between EDSS and SDMT (r = -0.47) as observed in the literature. Conclusions: This trial will demonstrate the utility of EMBs for monitoring MS progression by improving physicians’ access to a reliable, non-invasive, sensitive and accessible marker of disease progression.

The 2019 coronavirus disease (COVID-19) pandemic has demonstrated the importance of predicting, identifying, and tracking mutations throughout a pandemic event. As the COVID-19 global pandemic surpassed one year, several variants had emerged resulting in increased severity and transmissibility. Here, we used PCR as a surrogate for viral load and consequent severity to evaluate the real-world capabilities of a genome-based clinical severity predictive algorithm. Using a previously published algorithm, we compared the viral genome-based severity predictions to clinically derived PCR-based viral load of 716 viral genomes. For those samples predicted to be “severe” (probability of severe illness >0.5), we observed an average cycle threshold (Ct) of 18.3, whereas those in in the “mild” category (severity probability <0.5) had an average Ct of 20.4 (P = 0.0017). We also found a nontrivial correlation between predicted severity probability and cycle threshold (r = −0.199). Finally, when divided into severity probability quartiles, the group most likely to experience severe illness (≥75% probability) had a Ct of 16.6 (n = 10), whereas the group least likely to experience severe illness (<25% probability) had a Ct of 21.4 (n = 350) (P = 0.0045). Taken together, our results suggest that the severity predicted by a genome-based algorithm can be related to clinical diagnostic tests and that relative severity may be inferred from diagnostic values.

We propose a semi-analytical solution for the advection–diffusion equation in cylindrical domains, with an aim towards extracting blood flow rates from contrast variations in a coronary computed tomography angiography image. The solution proposed in this work, in contrast with existing methods, which only consider advection, incorporates both radial velocity variation and diffusion. By means of a Galerkin approach using Bessel functions, a solution for a three-dimensional concentration field at a single time point is obtained after a Laplace transformation. This semi-analytical solution forms the basis for a novel advection–diffusion flow estimation (ADFE) method. The ADFE is derived, validated through numerical spectral-element method computations, and shown to exhibit improved accuracy against the state-of-the-art method for image-based blood flow extraction.

AA amyloidosis (AAA) is a disease known as amyloid arthropathy in chicken, which represents substantial economic losses, in addition to welfare concerns. Enterococcus faecalis (E. faecalis) is the major pathogen found in field outbreaks of amyloid arthropathy and its specific association with this disease has been extensively confirmed. The following review discusses the sequence types of E. faecalis associated with AAA that have been identified and characterised both poultry and humans and provide different hypotheses and theories about pathogenesis and transmission of this disease. This article covers the pathology both in field and induced cases of avian amyloidosis and concludes with approaches for a possible treatment, needs for further research and future perspectives. This paper is a consolidation of current knowledge on AAA in chickens which has been obtained over the last twenty years.

The radiocarbon content of dissolved organic carbon (DOC) in rivers, lakes, and other non-saline waters can provide valuable information on carbon cycling dynamics in the environment. DOC is typically prepared for 14C analysis by accelerator mass spectrometry (AMS) either by ultraviolet (UV) oxidation or by freeze-drying and sealed tube combustion. We present here a new method for the rapid analysis of 14C of DOC using wet chemical oxidation (WCO) and automated headspace sampling of CO2. The approach is an adaption of recently developed methods using aqueous persulfate oxidant to determine the δ13C of DOC in non-saline water samples and the 14C content of volatile organic acids. One advantage of the current method over UV oxidation is higher throughput: 22 samples and 10 processing standards can be prepared in one day and analyzed in a second day, allowing a full suite of 14C processing standards and blanks to be run in conjunction with samples. A second advantage is that there is less potential for cross-contamination between samples.

The present study examined the possibilities and consequences of selecting pigs for reduced aggression and desirable maternal behaviour. Data were recorded from 798 purebred Large White gilts, with an age of 217±17.7 (mean±SD) days, which were observed at mixing with unfamiliar conspecifics. The reaction of the sows towards separation from their litter was assessed for 2022 litters from 848 Large White sows. Sows’ performance during their time in the farrowing unit was scored based on the traits farrowing behaviour (i.e. need of birth assistance), rearing performance (i.e. litter quality at day 10 postpartum (pp)), usability (i.e. additional labour input during lactation period e.g. for treatments) and udder quality of the sow (i.e. udder attachment). For agonistic behaviour, traits heritabilities of h2=0.11±0.04 to h2=0.28±0.06 were estimated. For the sow’s reaction towards separation from her litter low heritabilities were found (h2=0.03±0.03 for separation test on day 1 pp and h2=0.02±0.03 for separation test on day 10 pp). Heritabilities for lactating sow’s performance (farrowing behaviour, rearing performance, usability of the sow and udder quality) in the farrowing unit ranged from h2=0.03±0.02 to h2=0.19±0.03. Due to these results it can be assumed that selection for these traits, for example, for udder quality or reduced aggression, is possible. Antagonistic associations were found between separation test on day 1 pp and different measures of aggressiveness (rg=−0.22±0.26 aggressive attack and rg=−0.41±0.33 reciprocal fighting). Future studies should determine economic as well as welfare-related values of these traits in order to decide whether selection for these traits will be reasonable.

Our team at the University of Barcelona has contributed since the early phases of the mission to the definition, evaluation and calibration modelling of the Gaia photometry. To maximise the Gaia scientific exploitation, we have frequently shared many different tools and data with the astronomical community. Among this information we have defined several relationships among colours involving Gaia magnitudes and colours from other commonly used photometric systems (Johnson-Cousins, SDSS, Hipparcos, Tycho and 2MASS) for several types of stars (including white dwarfs). These relationships can be used for planning scientific exploitation of Gaia data, performing simulations of the Gaia-like sky, planning ground-based complementary observations and for building catalogues with auxiliary validation data. During the commissioning phase our team (as part of the Payload Experts group) has been intensively checking the first photometric data to analyse the health and properties of the real instrument. These preliminary analyses allowed us to monitor the throughput variations with time, assess the spectral resolution and re-evaluate the performances of the end-of-mission photometry. The Payload Experts group activities continue beyond the commissioning phase aiming to optimize the operations onboard for maximizing the scientific return. Some example of first spectra and photometry are shown.

In 2011, Bailes et al. reported on the discovery of a detached companion in a 131 minute orbit around PSR J1719–1438, a 173 Hz millisecond pulsar. The combination of the very low mass function and such a short orbital period is unique. The discoverers suggested that the progenitor system could be an ultracompact X-ray binary (UCXB), which is a binary with a sub-hour orbital period in which a (semi-)degenerate donor fills its Roche lobe and transfers mass to a neutron star. The standard gravitational-wave driven UCXB scenario, however, cannot produce a system like PSR J1719–1438 as it would take longer than the age of the Universe to reach an orbital period of 131 min. We investigate two modifications to the standard UCXB evolution that may resolve this discrepancy. The first involves significant heating and bloating of the donor by pulsar irradiation, and in the second modification the system loses orbital angular momentum via a fast stellar wind from the irradiated donor, additional to the losses via the usual gravitational wave radiation. In particular a donor wind is effective in accelerating orbital expansion, and even a mild wind could produce the 131 minute period within the age of the Universe. We note that UCXBs could be an important class of progenitors of solitary millisecond radio pulsars.

Ultracompact X-ray binaries (UCXBs) have orbital periods shorter than about 80 minutes and typically consist of a neutron star that accretes hydrogen-poor matter from a white dwarf companion. Angular momentum loss via gravitational wave radiation drives mass transfer via Roche-lobe overflow. The late-time evolution of UCXBs is poorly understood – all 13 known systems are relatively young and it is not clear why. One question is whether old UCXBs actually still exist, or have they become disrupted at some point? Alternatively they may be simply too faint to see. To investigate this, we apply the theories of dynamical instability, the magnetic propeller effect, and evaporation of the donor, to the UCXB evolution. We find that both the propeller effect and evaporation are promising explanations for the absence of observed long-period UCXBs.