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Establishing the host range for novel viruses remains a challenge. Here, we address the challenge of identifying non-human animal coronaviruses that may infect humans by creating an artificial neural network model that learns from spike protein sequences of alpha and beta coronaviruses and their binding annotation to their host receptor. The proposed method produces a human-Binding Potential (h-BiP) score that distinguishes, with high accuracy, the binding potential among coronaviruses. Three viruses, previously unknown to bind human receptors, were identified: Bat coronavirus BtCoV/133/2005 and Pipistrellus abramus bat coronavirus HKU5-related (both MERS related viruses), andRhinolophus affiniscoronavirus isolate LYRa3 (a SARS related virus). We further analyze the binding properties of BtCoV/133/2005 and LYRa3 using molecular dynamics. To test whether this model can be used for surveillance of novel coronaviruses, we re-trained the model on a set that excludes SARS-CoV-2 and all viral sequences released after the SARS-CoV-2 was published. The results predict the binding of SARS-CoV-2 with a human receptor, indicating that machine learning methods are an excellent tool for the prediction of host expansion events.

 

Individual-level interactions shape societal or economic processes, such as infectious diseases spreading, stock prices fluctuating and public opinion shifting. Understanding how the interaction of different individuals affects collective outcomes is more important than ever, as the internet and social media develop. Social networks representing individuals' influence relations play a key role in understanding the connections between individual-level interactions and societal or economic outcomes. Recent research has revealed how the topology of a social network affects collective decision-making in a community. Furthermore, the traits of individuals that determine how they process received information for making decisions also change a community's collective decisions. In this work, we develop stochastic processes to generate networks of individuals with two simple traits: Being a conformist and being an anticonformist. We introduce a novel deterministic voter model for a trait-attributed network, where the individuals make binary choices following simple deterministic rules based on their traits. We show that the simple deterministic rules can drive unpredictable fluctuations of collective decisions which eventually become periodic. We study the effects of network topology and trait distribution on the first passage time for a sequence of collective decisions showing periodicity.

 

Genomic epidemiology plays an ever-increasing role in our understanding of and response to the spread of infectious pathogens. Phylogeography, the reconstruction of the historical location and movement of pathogens from the evolutionary relationships among sampled pathogen sequences, can inform policy decisions related to viral movement among jurisdictions. However, phylogeographic reconstruction is impacted by the fact that the sampling and virus sequencing policies differ among jurisdictions, and these differences can cause bias in phylogeographic reconstructions. Here we assess the potential impacts of geographic-based sampling bias on estimated viral locations in the past, and on whether key viral movements can be detected. We quantify the effect of bias using simulated phylogenies with known geographic histories, and determine the impact of the biased sampling and of the underlying migration rate on the accuracy of estimated past viral locations. We find that overall, the accuracy of phylogeographic reconstruction is high, particularly when the migration rate is low. However, results depend on sampling, and sampling bias can have a large impact on the numbers and nature of estimated migration events. We apply these insights to the geographic spread of Ebolavirus in the 2014-2016 West Africa epidemic. This work highlights how sampling policy can both impact geographic inference and be optimized to best ensure the accuracy of specific features of geographic spread. 

We introduce a graph polynomial that distinguishes tree structures to represent dependency grammar and a measure based on the polynomial representation to quantify syntax similarity. The polynomial encodes accurate and comprehensive information about the dependency structure and dependency relations of words in a sentence, which enables in-depth analysis of dependency trees with data analysis tools. We apply the polynomial-based methods to analyze sentences in the ParallelUniversal Dependencies treebanks. Specifically, we compare the syntax of sentences and their translations in different languages, and we perform a syntactic typology study of available languages in the Parallel Universal Dependencies treebanks. We also demonstrate and discuss the potential of the methods in measuring syntax diversity of corpora. 

We present the characterization of the low-gravity M6 dwarf 2MASS J06195260-2903592, previously identified as an unusual field object based on its strong IR excess and variable near-IR spectrum. Multiple epochs of low-resolution (R≈ 150) near-IR spectra show large-amplitude (≈0.1–0.5 mag) continuum variations on timescales of days to 12 yr, unlike the small-amplitude variability typical for field ultracool dwarfs. The variations between epochs are well-modeled as changes in the relative extinction (ΔA_V≈ 2 mag). Similarly, Panoramic Survey Telescope and Rapid Response System 1 optical photometry varies on timescales as long as 11 yr (and possibly as short as an hour) and implies comparableA_Vchanges. Near Earth Object Wide-field Infrared Survey Explorer mid-IR light curves also suggest changes on 6 month timescales, with amplitudes consistent with the optical/near-IR extinction variations. However, near-IR spectra, near-IR photometry, and optical photometry obtained in the past year indicate that the source can also be stable on hourly and monthly timescales. From comparison to objects of similar spectral type, the total extinction of 2MASS J0619-2903 seems to beA_V≈ 4–6 mag, with perhaps epochs of lower extinction. Gaia Early Data Release 3 (EDR3) finds that 2MASS J0619-2903 has a wide-separation (1.′2 = 10,450 au) stellar companion, with an isochronal age of${31}_{-10}^{+22}$Myr and a mass of${0.30}_{-0.03}^{+0.04}$M_☉. Adopting this companion’s age and EDR3 distance (145.2 ± 0.6 pc), we estimate a mass of 0.11–0.17M_☉for 2MASS J0619-2903. Altogether, 2MASS J0619-2903 appears to possess an unusually long-lived primordial circumstellar disk, perhaps making it a more obscured analog to the “Peter Pan” disks found around a few M dwarfs in nearby young moving groups.

 

We present JWST Early Release Science coronagraphic observations of the super-Jupiter exoplanet, HIP 65426b, with the Near-Infrared Camera (NIRCam) from 2 to 5μm, and with the Mid-Infrared Instrument (MIRI) from 11 to 16μm. At a separation of ∼0.″82 (87${}_{-31}^{+108}$au), HIP 65426b is clearly detected in all seven of our observational filters, representing the first images of an exoplanet to be obtained by JWST, and the first-ever direct detection of an exoplanet beyond 5μm. These observations demonstrate that JWST is exceeding its nominal predicted performance by up to a factor of 10, depending on separation and subtraction method, with measured 5σcontrast limits of ∼1 × 10⁻⁵and ∼2 × 10⁻⁴at 1″ for NIRCam at 4.4μm and MIRI at 11.3μm, respectively. These contrast limits provide sensitivity to sub-Jupiter companions with masses as low as 0.3M_Jupbeyond separations of ∼100 au. Together with existing ground-based near-infrared data, the JWST photometry are fit well by aBT-SETTLatmospheric model from 1 to 16μm, and they span ∼97% of HIP 65426b's luminous range. Independent of the choice of model atmosphere, we measure an empirical bolometric luminosity that is tightly constrained between$\log \left(L_{\mathrm{bol}}/L_{\odot }\right)$= −4.31 and −4.14, which in turn provides a robust mass constraint of 7.1 ± 1.2M_Jup. In totality, these observations confirm that JWST presents a powerful and exciting opportunity to characterize the population of exoplanets amenable to high-contrast imaging in greater detail.

 

We present the highest fidelity spectrum to date of a planetary-mass object. VHS 1256 b isa<20M_Jupwidely separated (∼8″,a= 150 au), young, planetary-mass companion that shares photometric colors and spectroscopic features with the directly imaged exoplanets HR 8799c, d, and e. As an L-to-T transition object, VHS 1256 b exists along the region of the color–magnitude diagram where substellar atmospheres transition from cloudy to clear. We observed VHS 1256 b with JWST's NIRSpec IFU and MIRI MRS modes for coverage from 1 to 20μm at resolutions of ∼1000–3700. Water, methane, carbon monoxide, carbon dioxide, sodium, and potassium are observed in several portions of the JWST spectrum based on comparisons from template brown dwarf spectra, molecular opacities, and atmospheric models. The spectral shape of VHS 1256 b is influenced by disequilibrium chemistry and clouds. We directly detect silicate clouds, the first such detection reported for a planetary-mass companion.