Cross-Instrument Comparison of MapCam and OVIRS on OSIRIS-REx.

Two of the instruments onboard the OSIRIS-REx spacecraft, the MapCam color imager and the OVIRS visible and infrared spectrometer, observed the surface of asteroid (101955) Bennu in partially overlapping wavelengths. Significant scientific advances have been enabled by using data from these two instruments in tandem, but a robust statistical understanding of their relationship is needed for future analyses to cross-compare their data as accurately and sensitively as possible. Here we present a cross-instrument comparison of data acquired by MapCam and OVIRS, including methods and results for all global and site-specific observation campaigns in which both instruments were active. In our analysis, we consider both the absolute radiometric offset and the relative (normalized) variation between the two instruments; we find that both depend strongly on the photometric and instrumental conditions during the observation. The two instruments have a large absolute offset (>15%) due to their independent radiometric calibrations. However, they are very consistent (relative offset as low as 1%) when each instrument's response is normalized at a single wavelength, particularly at low phase angles where shadows on Bennu's rough surface are minimized. We recommend using the global datasets acquired at 12:30 pm local solar time for cross-comparisons; data acquired at higher phase angles have larger uncertainties.

Applying and improving AlphaFold at CASP14.

We describe the operation and improvement of AlphaFold, the system that was entered by the team AlphaFold2 to the "human" category in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The AlphaFold system entered in CASP14 is entirely different to the one entered in CASP13. It used a novel end-to-end deep neural network trained to produce protein structures from amino acid sequence, multiple sequence alignments, and homologous proteins. In the assessors' ranking by summed z scores (>2.0), AlphaFold scored 244.0 compared to 90.8 by the next best group. The predictions made by AlphaFold had a median domain GDT_TS of 92.4; this is the first time that this level of average accuracy has been achieved during CASP, especially on the more difficult Free Modeling targets, and represents a significant improvement in the state of the art in protein structure prediction. We reported how AlphaFold was run as a human team during CASP14 and improved such that it now achieves an equivalent level of performance without intervention, opening the door to highly accurate large-scale structure prediction.

Use of direct oral anticoagulants for acute pulmonary embolisms in obesity: a propensity-matched, multicentre case-control study.

Assessment of efficacy and safety of DOACs in treatment of pulmonary embolisms in obese patients provides reassurance that treatment with DOACs carries similar rates of recurrent VTE and bleeding complications to warfarin https://bit.ly/2VdrSXX.

Highly accurate protein structure prediction with AlphaFold.

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort1-4, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences6,7. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence-the structure prediction component of the 'protein folding problem'8-has been an important open research problem for more than 50 years9. Despite recent progress10-14, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14)15, demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.

Highly accurate protein structure prediction for the human proteome.

Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure1. Here we markedly expand the structural coverage of the proteome by applying the state-of-the-art machine learning method, AlphaFold2, at a scale that covers almost the entire human proteome (98.5% of human proteins). The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence. We introduce several metrics developed by building on the AlphaFold model and use them to interpret the dataset, identifying strong multi-domain predictions as well as regions that are likely to be disordered. Finally, we provide some case studies to illustrate how high-quality predictions could be used to generate biological hypotheses. We are making our predictions freely available to the community and anticipate that routine large-scale and high-accuracy structure prediction will become an important tool that will allow new questions to be addressed from a structural perspective.

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation.

Biomedical imaging is a driver of scientific discovery and a core component of medical care and is being stimulated by the field of deep learning. While semantic segmentation algorithms enable image analysis and quantification in many applications, the design of respective specialized solutions is non-trivial and highly dependent on dataset properties and hardware conditions. We developed nnU-Net, a deep learning-based segmentation method that automatically configures itself, including preprocessing, network architecture, training and post-processing for any new task. The key design choices in this process are modeled as a set of fixed parameters, interdependent rules and empirical decisions. Without manual intervention, nnU-Net surpasses most existing approaches, including highly specialized solutions on 23 public datasets used in international biomedical segmentation competitions. We make nnU-Net publicly available as an out-of-the-box tool, rendering state-of-the-art segmentation accessible to a broad audience by requiring neither expert knowledge nor computing resources beyond standard network training.

Ice giant system exploration in the 2020s: an introduction.

The international planetary science community met in London in January 2020, united in the goal of realizing the first dedicated robotic mission to the distant ice giants, Uranus and Neptune, as the only major class of solar system planet yet to be comprehensively explored. Ice-giant-sized worlds appear to be a common outcome of the planet formation process, and pose unique and extreme tests to our understanding of exotic water-rich planetary interiors, dynamic and frigid atmospheres, complex magnetospheric configurations, geologically-rich icy satellites (both natural and captured), and delicate planetary rings. This article introduces a special issue on ice giant system exploration at the start of the 2020s. We review the scientific potential and existing mission design concepts for an ambitious international partnership for exploring Uranus and/or Neptune in the coming decades. This article is part of a discussion meeting issue 'Future exploration of ice giant systems'.

Asteroid (101955) Bennu's weak boulders and thermally anomalous equator.

Thermal inertia and surface roughness are proxies for the physical characteristics of planetary surfaces. Global maps of these two properties distinguish the boulder population on near-Earth asteroid (NEA) (101955) Bennu into two types that differ in strength, and both have lower thermal inertia than expected for boulders and meteorites. Neither has strongly temperature-dependent thermal properties. The weaker boulder type probably would not survive atmospheric entry and thus may not be represented in the meteorite collection. The maps also show a high-thermal inertia band at Bennu's equator, which might be explained by processes such as compaction or strength sorting during mass movement, but these explanations are not wholly consistent with other data. Our findings imply that other C-complex NEAs likely have boulders similar to those on Bennu rather than finer-particulate regoliths. A tentative correlation between albedo and thermal inertia of C-complex NEAs may be due to relative abundances of boulder types.

Bright carbonate veins on asteroid (101955) Bennu: Implications for aqueous alteration history.

The composition of asteroids and their connection to meteorites provide insight into geologic processes that occurred in the early Solar System. We present spectra of the Nightingale crater region on near-Earth asteroid Bennu with a distinct infrared absorption around 3.4 micrometers. Corresponding images of boulders show centimeters-thick, roughly meter-long bright veins. We interpret the veins as being composed of carbonates, similar to those found in aqueously altered carbonaceous chondrite meteorites. If the veins on Bennu are carbonates, fluid flow and hydrothermal deposition on Bennu's parent body would have occurred on kilometer scales for thousands to millions of years. This suggests large-scale, open-system hydrothermal alteration of carbonaceous asteroids in the early Solar System.

A review of the in situ probe designs from recent Ice Giant mission concept studies.

For the Ice Giants, atmospheric entry probes provide critical measurements not attainable via remote observations. Including the 2013-2022 NASA Planetary Decadal Survey, there have been at least five comprehensive atmospheric probe engineering design studies performed in recent years by NASA and ESA. International science definition teams have assessed the science requirements, and each recommended similar measurements and payloads to meet science goals with current instrument technology. The probe system concept has matured and converged on general design parameters that indicate the probe would include a 1-meter class aeroshell and have a mass around 350 to 400-kg. Probe battery sizes vary, depending on the duration of a post-release coast phase, and assumptions about heaters and instrument power needs. The various mission concepts demonstrate the need for advanced power and thermal protection system development. The many completed studies show an Ice Giant mission with an in situ probe is feasible and would be welcomed by the international science community.

Evidence for widespread hydrated minerals on asteroid (101955) Bennu.

Early spectral data from the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) mission reveal evidence for abundant hydrated minerals on the surface of near-Earth asteroid (101955) Bennu in the form of a near-infrared absorption near 2.7 µm and thermal infrared spectral features that are most similar to those of aqueously altered CM carbonaceous chondrites. We observe these spectral features across the surface of Bennu, and there is no evidence of substantial rotational variability at the spatial scales of tens to hundreds of meters observed to date. In the visible and near-infrared (0.4 to 2.4 µm) Bennu's spectrum appears featureless and with a blue (negative) slope, confirming previous ground-based observations. Bennu may represent a class of objects that could have brought volatiles and organic chemistry to Earth.

Jupiter's Mesoscale Waves Observed at 5 µm by Ground-based Observations and Juno JIRAM.

We characterize the origin and evolution of a mesoscale wave pattern in Jupiter's North Equatorial Belt (NEB), detected for the first time at 5 µm using a 2016-17 campaign of "lucky imaging" from the VISIR instrument on the Very Large Telescope and the NIRI instrument on the Gemini observatory, coupled with M-band imaging from Juno's JIRAM instrument during the first seven Juno orbits. The wave is compact, with a 1°.1-1°.4 longitude wavelength (wavelength 1300-1600 km, wavenumber 260-330) that is stable over time, with wave crests aligned largely north-south between 14°N and 17°N (planetographic). The waves were initially identified in small (10° longitude) packets immediately west of cyclones in the NEB at 16°N but extended to span wider longitude ranges over time. The waves exhibit a 7-10 K brightness temperature amplitude on top of an ∼210 K background at 5 µm. The thermal structure of the NEB allows for both inertio-gravity waves and gravity waves. Despite detection at 5 µm, this does not necessarily imply a deep location for the waves, and an upper tropospheric aerosol layer near 400-800 mbar could feature a gravity wave pattern modulating the visible-light reflectivity and attenuating the 5-µm radiance originating from deeper levels. Strong rifting activity appears to obliterate the pattern, which can change on timescales of weeks. The NEB underwent a new expansion and contraction episode in 2016-17 with associated cyclone-anticyclone formation, which could explain why the mesoscale wave pattern was more vivid in 2017 than ever before.

Less absorbed solar energy and more internal heat for Jupiter.

The radiant energy budget and internal heat are fundamental properties of giant planets, but precise determination of these properties remains a challenge. Here, we report measurements of Jupiter's radiant energy budget and internal heat based on Cassini multi-instrument observations. Our findings reveal that Jupiter's Bond albedo and internal heat, 0.503 ± 0.012 and 7.485 ± 0.160 W m-2 respectively, are significantly larger than 0.343 ± 0.032 and 5.444 ± 0.425 Wm-2, the previous best estimates. The new results help constrain and improve the current evolutionary theories and models for Jupiter. Furthermore, the significant wavelength dependency of Jupiter's albedo implies that the radiant energy budgets and internal heat of the other giant planets in our solar system should be re-examined. Finally, the data sets of Jupiter's characteristics of reflective solar spectral irradiance provide an observational basis for the models of giant exoplanets.

Deep sequencing reveals minor protease resistance mutations in patients failing a protease inhibitor regimen.

Standard genotypic antiretroviral resistance testing, performed by bulk sequencing, does not readily detect variants that comprise <20% of the circulating HIV-1 RNA population. Nevertheless, it is valuable in selecting an antiretroviral regimen after antiretroviral failure. In patients with poor adherence, resistant variants may not reach this threshold. Therefore, deep sequencing would be potentially valuable for detecting minority resistant variants. We compared bulk sequencing and deep sequencing to detect HIV-1 drug resistance at the time of a second-line protease inhibitor (PI)-based antiretroviral regimen failure. Eligibility criteria were virologic failure (HIV-1 RNA load of >500 copies/ml) of a first-line nonnucleoside reverse transcriptase inhibitor-based regimen, with at least the M184V mutation (lamivudine resistance), and second-line failure of a lopinavir/ritonavir (LPV/r)-based regimen. An amplicon-sequencing approach on the Roche 454 system was used. Six patients with viral loads of >90,000 copies/ml and one patient with a viral load of 520 copies/ml were included. Mutations not detectable by bulk sequencing during first- and second-line failure were detected by deep sequencing during second-line failure. Low-frequency variants (>0.5% of the sequence population) harboring major protease inhibitor resistance mutations were found in 5 of 7 patients despite poor adherence to the LPV/r-based regimen. In patients with intermittent adherence to a boosted PI regimen, deep sequencing may detect minority PI-resistant variants, which likely represent early events in resistance selection. In patients with poor or intermittent adherence, there may be low evolutionary impetus for such variants to reach fixation, explaining the low prevalence of PI resistance.

HIV type 1 mutational patterns in HIV type 1 subtype C-infected long-term survivors in Karonga District Malawi: further analysis and correction.

Here we present new sequence data from HIV-1 subtype C-infected long-term survivors (LTS) from Karonga District, Malawi. Gag and env sequence data were produced from nine individuals each of whom has been HIV-1 positive for more than 20 years. We show that the three amino acid deletion in gag p17 previously described from these LTS is not real and was a result of an alignment error. We find that the use of dried blood spots for DNA-based studies is limited after storage for 20 years. We also show some unlikely amino acid changes in env C2-V3 in LTS over time and different patterns of genetic divergence among LTS. Although no clear association between mutations and survival could be shown, amino acid changes that are present in more than one LTS may, in the future, be shown to be important.

Phylogenetic relationships of the marine Haplosclerida (Phylum Porifera) employing ribosomal (28S rRNA) and mitochondrial (cox1, nad1) gene sequence data.

The systematics of the poriferan Order Haplosclerida (Class Demospongiae) has been under scrutiny for a number of years without resolution. Molecular data suggests that the order needs revision at all taxonomic levels. Here, we provide a comprehensive view of the phylogenetic relationships of the marine Haplosclerida using many species from across the order, and three gene regions. Gene trees generated using 28S rRNA, nad1 and cox1 gene data, under maximum likelihood and Bayesian approaches, are highly congruent and suggest the presence of four clades. Clade A is comprised primarily of species of Haliclona and Callyspongia, and clade B is comprised of H. simulans and H. vansoesti (Family Chalinidae), Amphimedon queenslandica (Family Niphatidae) and Tabulocalyx (Family Phloeodictyidae), Clade C is comprised primarily of members of the Families Petrosiidae and Niphatidae, while Clade D is comprised of Aka species. The polyphletic nature of the suborders, families and genera described in other studies is also found here.

Drug resistance mutations in drug-naive HIV type 1 subtype C-infected individuals from rural Malawi.

In this preliminary study we show that in 2008, 3 years after antiretroviral therapy was introduced into the Karonga District, Malawi, a greater than expected number of drug-naive individuals have been infected with HIV-1 subtype C virus harboring major and minor drug resistance mutations (DRMs). From a sample size of 40 reverse transcriptase (RT) consensus sequences from drug-naive individuals we found five showing NRTI and four showing NNRTI mutations with one individual showing both. From 29 protease consensus sequences, again from drug-naive individuals, we found evidence of minor DRMs in three. Additional major and minor DRMs were found in clonal sequences from a number of individuals that were not present in the original consensus sequences. This clearly illustrates the importance of sequencing multiple HIV-1 variants from individuals to fully assess drug resistance.

Emergence, dominance, and possible decline of CXCR4 chemokine receptor usage during the course of HIV infection.

Binding to a chemokine receptor, either CCR5 or CXCR4, by the gp120 glycoprotein is an essential step in the pathway by which HIV enters host cells. Recently, CCR5 antagonists have been developed that obstruct binding of CCR5 by gp120, thus inhibiting host cell entry. Resistance to such CCR5 antagonists may emerge, however, through the selection of viral strains capable of utilizing CXCR4 receptors. This study explores the evolutionary context of emergence, and in many cases decline, of dominant CXCR4-usage (X4) during disease progression within a number of individuals. Of seven individuals exhibiting a switch to dominant CXCR4 usage, such dominance is transient in five of them with CCR5-usage (R5) re-emerging to dominate the viral population later in disease progression. Three individuals conform to documented X4 transience in that the re-emergence of R5 dominance is an outgrowth from the predominant R5 strain. However, in two individuals we observe a novel pathway for R5 re-emergence in that R5 strains emerge to dominate late in disease progression through continued evolution of the X4 population. This suggests that the molecular mechanism of such switches between R5 and X4-usage is strain specific and that no single mechanism is shared between individuals. These findings have implications for the understanding of the mechanisms of potential emergence of resistance to CCR5 antagonists through use of the CXCR4 receptor and support the importance to have an appropriately optimized background therapy for use with entry inhibitors and, as for all HAART, to monitor drug resistance in a comprehensive manner.

A study of the coevolutionary patterns operating within the env gene of the HIV-1 group M subtypes.

The env gene of human immunodeficiency virus (HIV) is a functionally important gene responsible for the production of protein products (gp120 and gp41) involved in host cell recognition, binding, and entry. This occurs through a complex and, as yet, not fully understood process of protein-protein interaction and within and between protein functional communication. Exposure on the surface of active HIV virions means the gp120-gp41 complexes are subjected to intense immune system pressure and have, therefore, evolved mechanisms to avoid neutralization. Using protein-coding sequences representing all the HIV type-1 (HIV-1) group M subtypes, we have identified amino acids within the env gene whose evolution is inextricably linked over the entire HIV-1 group M epidemic. We identified 848 pairs of coevolving residues (involving 263 out of 764 amino acid sites), which represent 0.29% of all possible pairs. Of the coevolving pairs, 68% were significantly correlated by hydrophobicity, molecular weight, or both hydrophobicity and molecular weight. Subsequent grouping of coevolving pairs resulted in the identification of 290 groups of amino acid residues, with the size of these groups ranging from 2 to 10 amino acid residues. Many of these dependencies are correlated by function including CD4 binding, coreceptor binding, glycosylation, and protein-protein interaction. This analysis provides important information regarding the functional dependencies observed within all the HIV-1 group M subtypes and may assist in the identification of functional protein domains and therapeutic targets within the HIV-1 env gene.

Functional coevolutionary networks of the Hsp70-Hop-Hsp90 system revealed through computational analyses.

Currently, the identification of groups of amino acid residues that are important in the function, structure, or interaction of a protein can be both costly and prohibitively complex, involving vast numbers of mutagenesis experiments. Here, we present the application of a novel computational method, which identifies the presence of coevolution in a data set, thereby enabling the a priori identification of amino acid residues that play an important role in protein function. We have applied this method to the heat shock protein (Hsp) protein-folding system, studying the network between Hsp70, Hsp90, and Hop (heat shock-organizing protein). Our analysis has identified functional residues within the tetratricopeptide repeat (TPR) 1 and 2A domains in Hop, previously shown to be interacting with Hsp70 and Hsp90, respectively. Further, we have identified significant residues elsewhere in Hop within domains that have been recently proposed as being important for Hop interaction with Hsp70 and/or Hsp90. In addition, several amino acid sites present in groups of coevolution were identified as 3-dimensionally or linearly proximal to functionally important sites or domains. Based on our results, we also investigate a further functional domain within Hop, between TPR1 and TPR2A, which we suggest as being functionally important in the interaction of Hop with both Hsp70 and Hsp90 whether directly or otherwise. Our method has identified all the previously characterized functionally important regions in this system, thereby indicating the power of this method in the a priori identification of important regions for site-directed mutagenesis studies.