The evolutionary mechanisms by which SARS-CoV-2 viruses adapt to mammalian hosts and, potentially, undergo antigenic evolution depend on the ways genetic variation is generated and selected within ...and between individual hosts. Using domestic cats as a model, we show that SARS-CoV-2 consensus sequences remain largely unchanged over time within hosts, while dynamic sub-consensus diversity reveals processes of genetic drift and weak purifying selection. We further identify a notable variant at amino acid position 655 in Spike (H655Y), which was previously shown to confer escape from human monoclonal antibodies. This variant arises rapidly and persists at intermediate frequencies in index cats. It also becomes fixed following transmission in two of three pairs. These dynamics suggest this site may be under positive selection in this system and illustrate how a variant can quickly arise and become fixed in parallel across multiple transmission pairs. Transmission of SARS-CoV-2 in cats involved a narrow bottleneck, with new infections founded by fewer than ten viruses. In RNA virus evolution, stochastic processes like narrow transmission bottlenecks and genetic drift typically act to constrain the overall pace of adaptive evolution. Our data suggest that here, positive selection in index cats followed by a narrow transmission bottleneck may have instead accelerated the fixation of S H655Y, a potentially beneficial SARS-CoV-2 variant. Overall, our study suggests species- and context-specific adaptations are likely to continue to emerge. This underscores the importance of continued genomic surveillance for new SARS-CoV-2 variants as well as heightened scrutiny for signatures of SARS-CoV-2 positive selection in humans and mammalian model systems.
The cold dark matter (CDM) model faces persistent challenges on small scales. In particular, taken at face value, the model significantly overestimates the number of satellite galaxies around the ...Milky Way. Attempts to solve this problem remain open to debate and have even led some to abandon CDM altogether. However, current simulations are limited by the assumption that dark matter feels only gravity. Here, we show that including interactions between CDM and radiation (photons or neutrinos) leads to a dramatic reduction in the number of satellite galaxies, alleviating the Milky Way satellite problem and indicating that physics beyond gravity may be essential to make accurate predictions of structure formation on small scales. The methodology introduced here gives constraints on dark matter interactions that are significantly improved over those from the cosmic microwave background.
Weakly Interacting Massive Particles are often said to be the best Dark Matter candidates. Studies have shown that large Dark Matter-photon or Dark Matter-baryon interactions could be allowed by ...cosmology. Here we address the question of the role of the Dark Matter interactions in more detail to determine at which extent Dark Matter has to be necessarily weakly interacting. To this purpose, we compute the collisional damping (and free-streaming) scales of generic interacting Dark Matter candidates and investigate the effects on structure formation. Our calculations are valid provided the Dark Matter particles have experienced a phase of statistical equilibrium at some stage during their evolution. By comparing these damping lengths to the scale of the smallest primordial structures known to exist in the Universe, we obtain necessary conditions that any candidate must satisfy. These conditions are expressed in terms of the Dark Matter particles' mass and either the total Dark Matter interaction rate or the interaction rate of Dark Matter with a specific species. The case of Dark Matter interacting with neutrinos or photons is considered in full detail. Our results are valid even for energy dependent cross-sections and for any possible initial fluctuations spectrum. We point out the existence of new Dark Matter scenarios and exhibit new damping regimes. For example, an interacting candidate may bear a similar damping than that of collisionless Warm Dark Matter particles. The main difference is due to the Dark Matter coupling to interacting (or even freely-propagating) species. Our approach yields a general classification of Dark Matter candidates which extends the definitions of the usual Cold, Warm and Hot Dark Matter scenarios when interactions, weak or strong, are considered.
SUMMARY
We present a new approach to the solution of the Poisson equation present in the coupled gravito-elastic equations of motion for global seismic wave propagation in time domain aiming at the ...inclusion of the full gravitational response into spectral element solvers. We leverage the Salvus meshing software to include the external domain using adaptive mesh refinement and high order shape mapping. Together with Neumann boundary conditions based on a multipole expansion of the right-hand side this minimizes the number of additional elements needed. Initial conditions for the iterative solution of the Poisson equation based on temporal extrapolation from previous time steps together with a polynomial multigrid method reduce the number of iterations needed for convergence. In summary, this approach reduces the extra cost for simulating full gravity to a similar order as the elastic forces. We demonstrate the efficacy of the proposed method using the displacement from an elastic global wave propagation simulation (decoupled from the Poisson equation) at $200\, \mbox{s}$ dominant period to compute a realistic right-hand side for the Poisson equation.
We report observations of Rayleigh waves that orbit around Mars up to three times following the S1222a marsquake. Averaging these signals, we find the largest amplitude signals at 30 and 85 s central ...period, propagating with distinctly different group velocities of 2.9 and 3.8 km/s, respectively. The group velocities constraining the average crustal thickness beneath the great circle path rule out the majority of previous crustal models of Mars that have a >200 kg/m3 density contrast across the equatorial dichotomy between northern lowlands and southern highlands. We find that the thickness of the Martian crust is 42–56 km on average, and thus thicker than the crusts of the Earth and Moon. Considered with the context of thermal evolution models, a thick Martian crust suggests that the crust must contain 50%–70% of the total heat production to explain present‐day local melt zones in the interior of Mars.
Plain Language Summary
The NASA InSight mission and its seismometer installed on the surface of Mars is retired after ∼4 years of operation. From the largest marsquake recording during the entire mission, we observe clear seismic signals from surface waves called Rayleigh waves that orbit around Mars up to three times. By measuring the wavespeeds with which these surface waves travel at different frequencies, we obtain the first seismic evidence that constrains the average crustal and uppermost mantle structures beneath the traveling path on a planetary scale. Using the new seismic observations together with gravity data, we confirm that the density of the crust in the northern lowlands and the southern highlands is similar, differing by no more than 200 kg/m3. Furthermore, we find that the global average crustal thickness on Mars is 42–56 km, much thicker than the Earth's and Moon's crusts. By exploring Mars' thermal history, a thick Martian crust requires about 50%–70% of the heat‐producing elements such as thorium, uranium, and potassium to be concentrated in the crust in order to explain local regions in the Martian mantle that can still undergo melting at present day.
Key Points
We present the first observation of Rayleigh waves that orbit around Mars up to three times
Group velocity measurements and 3‐D simulations constrain the average crustal and uppermost mantle velocities along the great‐circle propagation path
The global average crustal thickness is 42–56 km and requires a large enrichment of heat‐producing elements to explain local melt zones
SUMMARY
An order of magnitude speed-up in finite-element modelling of wave propagation can be achieved by adapting the mesh to the anticipated space-dependent complexity and smoothness of the waves. ...This can be achieved by designing the mesh not only to respect the local wavelengths, but also the propagation direction of the waves depending on the source location, hence by anisotropic adaptive mesh refinement. Discrete gradients with respect to material properties as needed in full waveform inversion can still be computed exactly, but at greatly reduced computational cost. In order to do this, we explicitly distinguish the discretization of the model space from the discretization of the wavefield and derive the necessary expressions to map the discrete gradient into the model space. While the idea is applicable to any wave propagation problem that retains predictable smoothness in the solution, we highlight the idea of this approach with instructive 2-D examples of forward as well as inverse elastic wave propagation. Furthermore, we apply the method to 3-D global seismic wave simulations and demonstrate how meshes can be constructed that take advantage of high-order mappings from the reference coordinates of the finite elements to physical coordinates. Error level and speed-ups are estimated based on convergence tests with 1-D and 3-D models.
Summary
The bone marrow proton density fat fraction (PDFF) assessed with MRI enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures. Therefore, PDFF ...may be a potentially useful biomarker for bone fragility assessment.
Introduction
To evaluate whether magnetic resonance imaging (MRI)-based proton density fat fraction (PDFF) of vertebral bone marrow can differentiate between osteoporotic/osteopenic patients with and without vertebral fractures.
Methods
Of the 52 study patients, 32 presented with vertebral fractures of the lumbar spine (66.4 ± 14.4 years, 62.5% women; acute low-energy osteoporotic/osteopenic vertebral fractures,
N
= 25; acute high-energy traumatic vertebral fractures,
N
= 7). These patients were frequency matched for age and sex to patients without vertebral fractures (
N
= 20, 69.3 ± 10.1 years, 70.0% women). Trabecular bone mineral density (BMD) values were derived from quantitative computed tomography. Chemical shift encoding-based water-fat MRI of the lumbar spine was performed, and PDFF maps were calculated. Associations between fracture status and PDFF were assessed using multivariable linear regression models.
Results
Over all patients, mean PDFF and trabecular BMD correlated significantly (
r
= − 0.51,
P
< 0.001). In the osteoporotic/osteopenic group, those patients with osteoporotic/osteopenic fractures had a significantly higher PDFF than those without osteoporotic fractures after adjusting for age, sex, weight, height, and trabecular BMD (adjusted mean difference 95% confidence interval, 20.8% 10.4%, 30.7%;
P
< 0.001), although trabecular BMD values showed no significant difference between the subgroups (
P
= 0.63). For the differentiation of patients with and without vertebral fractures in the osteoporotic/osteopenic subgroup using mean PDFF, an area under the receiver operating characteristic (ROC) curve (AUC) of 0.88 (
P
= 0.006) was assessed. When evaluating all patients with vertebral fractures, those with high-energy traumatic fractures had a significantly lower PDFF than those with low-energy osteoporotic/osteopenic vertebral fractures (
P
< 0.001).
Conclusion
MR-based PDFF enables the differentiation between osteoporotic/osteopenic patients with and without vertebral fractures, suggesting the use of PDFF as a potential biomarker for bone fragility.
Abstract There are two known mechanisms by which natural killer (NK) cells recognize and kill diseased targets: (i) direct killing and (ii) antibody-dependent cell-mediated cytotoxicity (ADCC). We ...investigated an indirect NK cell activation strategy for the enhancement of human NK cell killing function. We did this by leveraging the fact that toll-like receptor 9 (TLR9) agonism within pools of human peripheral blood mononuclear cells (PBMCs) results in a robust interferon signaling cascade that leads to NK cell activation. After TLR9 agonist stimulation, NK cells were enriched and incorporated into assays to assess their ability to kill tumor cell line targets. Notably, differential impacts of TLR9 agonism were observed—direct killing was enhanced while ADCC was not increased. To ensure that the observed differential effects were not attributable to differences between human donors, we recapitulated the observation using our Natural Killer—Simultaneous ADCC and Direct Killing Assay (NK-SADKA) that controls for human-to-human differences. Next, we observed a treatment-induced decrease in NK cell surface CD16—known to be shed by NK cells post-activation. Given the essential role of CD16 in ADCC, such shedding could account for the observed differential impact of TLR9 agonism on NK cell-mediated killing capacity.
•We provide a comprehensive overview on earth observation (EO) indicators for biodiversity (BD).•We focus on taxonomic, structural and functional biodiversity.•EO is not able to record BD according ...to taxonomical classifications of in-situ species.•Spectral traits (ST) and spectral trait variations (STV) are the basis concept of EO to quantify BD.•Coupling different approaches, developing sensor networks and new concepts, tools and models in handling complex and big data are important.
Impacts of human civilization on ecosystems threaten global biodiversity. In a changing environment, traditional in situ approaches to biodiversity monitoring have made significant steps forward to quantify and evaluate BD at many scales but still, these methods are limited to comparatively small areas. Earth observation (EO) techniques may provide a solution to overcome this shortcoming by measuring entities of interest at different spatial and temporal scales.
This paper provides a comprehensive overview of the role of EO to detect, describe, explain, predict and assess biodiversity. Here, we focus on three main aspects related to biodiversity − taxonomic diversity, functional diversity and structural diversity, which integrate different levels of organization − molecular, genetic, individual, species, populations, communities, biomes, ecosystems and landscapes. In particular, we discuss the recording of taxonomic elements of biodiversity through the identification of animal and plant species. We highlight the importance of the spectral traits (ST) and spectral trait variations (STV) concept for EO-based biodiversity research. Furthermore we provide examples of spectral traits/spectral trait variations used in EO applications for quantifying taxonomic diversity, functional diversity and structural diversity. We discuss the use of EO to monitor biodiversity and habitat quality using different remote-sensing techniques. Finally, we suggest specifically important steps for a better integration of EO in biodiversity research.
EO methods represent an affordable, repeatable and comparable method for measuring, describing, explaining and modelling taxonomic, functional and structural diversity. Upcoming sensor developments will provide opportunities to quantify spectral traits, currently not detectable with EO, and will surely help to describe biodiversity in more detail. Therefore, new concepts are needed to tightly integrate EO sensor networks with the identification of biodiversity. This will mean taking completely new directions in the future to link complex, large data, different approaches and models.
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