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The establishment of a virus infection is the result of the pathogen's ability to replicate in a hostile environment generated by the host's immune system. Here, we found that ISG15 restricts Dengue and Zika viruses' replication through the stabilization of its binding partner USP18. ISG15 expression was necessary to control DV replication driven by both autocrine and paracrine type one interferon (IFN-I) signaling. Moreover, USP18 competes with NS5-mediated STAT2 degradation, a major mechanism for establishment of flavivirus infection. Strikingly, reconstitution of USP18 in ISG15-deficient cells was sufficient to restore the STAT2's stability and restrict virus growth, suggesting that the IFNAR-mediated ISG15 activity is also antiviral. Our results add a novel layer of complexity in the virus/host interaction interface and suggest that NS5 has a narrow window of opportunity to degrade STAT2, therefore suppressing host's IFN-I mediated response and promoting virus replication.

A recent outbreak of Zika virus in Brazil has led to a simultaneous increase in reports of neonatal microcephaly. Zika targets cerebral neural precursors, a cell population essential for cortical development, but the cause of this neurotropism remains obscure. Here we report that the neural RNA-binding protein Musashi-1 (MSI1) interacts with the Zika genome and enables viral replication. Zika infection disrupts the binding of MSI1 to its endogenous targets, thereby deregulating expression of factors implicated in neural stem cell function.We further show that MSI1 is highly expressed in neural progenitors of the human embryonic brain and is mutated in individuals with autosomal recessive primary microcephaly. Selective MSI1 expression in neural precursors could therefore explain the exceptional vulnerability of these cells to Zika infection.

The establishment of a virus infection is the result of the pathogen's ability to replicate in a hostile environment generated by the host's immune system. Here, we found that ISG15 restricts Dengue and Zika viruses' replication through the stabilization of its binding partner USP18. ISG15 expression was necessary to control DV replication driven by both autocrine and paracrine type one interferon (IFN-I) signaling. Moreover, USP18 competes with NS5-mediated STAT2 degradation, a major mechanism for establishment of flavivirus infection. Strikingly, reconstitution of USP18 in ISG15-deficient cells was sufficient to restore the cells' immune response and restrict virus growth, suggesting that the IFNAR-mediated ISG15 activity is also antiviral. Our results add a novel layer of complexity in the virus/host interaction interface and suggest that NS5 has a narrow window of opportunity to degrade STAT2, therefore suppressing host's IFN-I mediated response and promoting virus replication. Footnotes * Minor text changes.

Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorithms, trained in a diverse multinational cohort of 1280 patients to localize parietal pleura/lung parenchyma followed by classification of COVID-19 pneumonia, can achieve up to 90.8% accuracy, with 84% sensitivity and 93% specificity, as evaluated in an independent test set (not included in training and validation) of 1337 patients. Normal controls included chest CTs from oncology, emergency, and pneumonia-related indications. The false positive rate in 140 patients with laboratory confirmed other (non COVID-19) pneumonias was 10%. AI-based algorithms can readily identify CT scans with COVID-19 associated pneumonia, as well as distinguish non-COVID related pneumonias with high specificity in diverse patient populations. Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Here, the authors present a multinational study on the application of deep learning algorithms for COVID-19 diagnosis against multiple lung conditions as controls.

Midostaurin, an oral multitargeted kinase inhibitor, is active in patients with a FLT3 mutation. Among patients with acute myeloid leukemia and this mutation, the addition of midostaurin to standard chemotherapy appeared to improve long-term outcomes.

Converting biomass-based feedstocks into polymers not only reduces our reliance on fossil fuels, but also furnishes multiple opportunities to design biorenewable polymers with targeted properties and functionalities. Here we report a series of high glass transition temperature ( T g up to 184 °C) polyesters derived from sugar-based furan derivatives as well as a joint experimental and theoretical study of substituent effects on their thermal properties. Surprisingly, we find that polymers with moderate steric hindrance exhibit the highest T g values. Through a detailed Ramachandran-type analysis of the rotational flexibility of the polymer backbone, we find that additional steric hindrance does not necessarily increase chain stiffness in these polyesters. We attribute this interesting structure-property relationship to a complex interplay between methyl-induced steric strain and the concerted rotations along the polymer backbone. We believe that our findings provide key insight into the relationship between structure and thermal properties across a range of synthetic polymers. Biorenewable feedstocks allow the design of polymers with targeted properties and functionalities. Here the authors report a series of high glass transition temperature sugar-based polyesters and investigate how substituents affect their thermal properties.

The authors present inferences of diapycnal diffusivity from a compilation of over 5200 microstructure profiles. As microstructure observations are sparse, these are supplemented with indirect measurements of mixing obtained from (i) Thorpe-scale overturns from moored profilers, a finescale parameterization applied to (ii) shipboard observations of upper-ocean shear, (iii) strain as measured by profiling floats, and (iv) shear and strain from full-depth lowered acoustic Doppler current profilers (LADCP) and CTD profiles. Vertical profiles of the turbulent dissipation rate are bottom enhanced over rough topography and abrupt, isolated ridges. The geography of depth-integrated dissipation rate shows spatial variability related to internal wave generation, suggesting one direct energy pathway to turbulence. The global-averaged diapycnal diffusivity below 1000-m depth is O(10−4) m2 s−1 and above 1000-m depth is O(10−5) m2 s−1. The compiled microstructure observations sample a wide range of internal wave power inputs and topographic roughness, providing a dataset with which to estimate a representative global-averaged dissipation rate and diffusivity. However, there is strong regional variability in the ratio between local internal wave generation and local dissipation. In some regions, the depth-integrated dissipation rate is comparable to the estimated power input into the local internal wave field. In a few cases, more internal wave power is dissipated than locally generated, suggesting remote internal wave sources. However, at most locations the total power lost through turbulent dissipation is less than the input into the local internal wave field. This suggests dissipation elsewhere, such as continental margins.

Chest X-ray plays a key role in diagnosis and management of COVID-19 patients and imaging features associated with clinical elements may assist with the development or validation of automated image analysis tools. We aimed to identify associations between clinical and radiographic features as well as to assess the feasibility of deep learning applied to chest X-rays in the setting of an acute COVID-19 outbreak. A retrospective study of X-rays, clinical, and laboratory data was performed from 48 SARS-CoV-2 RT-PCR positive patients (age 60±17 years, 15 women) between February 22 and March 6, 2020 from a tertiary care hospital in Milan, Italy. Sixty-five chest X-rays were reviewed by two radiologists for alveolar and interstitial opacities and classified by severity on a scale from 0 to 3. Clinical factors (age, symptoms, comorbidities) were investigated for association with opacity severity and also with placement of central line or endotracheal tube. Deep learning models were then trained for two tasks: lung segmentation and opacity detection. Imaging characteristics were compared to clinical datapoints using the unpaired student's t-test or Mann-Whitney U test. Cohen's kappa analysis was used to evaluate the concordance of deep learning to conventional radiologist interpretation. Fifty-six percent of patients presented with alveolar opacities, 73% had interstitial opacities, and 23% had normal X-rays. The presence of alveolar or interstitial opacities was statistically correlated with age (P = 0.008) and comorbidities (P = 0.005). The extent of alveolar or interstitial opacities on baseline X-ray was significantly associated with the presence of endotracheal tube (P = 0.0008 and P = 0.049) or central line (P = 0.003 and P = 0.007). In comparison to human interpretation, the deep learning model achieved a kappa concordance of 0.51 for alveolar opacities and 0.71 for interstitial opacities. Chest X-ray analysis in an acute COVID-19 outbreak showed that the severity of opacities was associated with advanced age, comorbidities, as well as acuity of care. Artificial intelligence tools based upon deep learning of COVID-19 chest X-rays are feasible in the acute outbreak setting.

Anaeromyxobacter dehalogenans strain 2CP-C is a versaphilic delta-Proteobacterium distributed throughout many diverse soil and sediment environments. 16S rRNA gene phylogenetic analysis groups A. dehalogenans together with the myxobacteria, which have distinguishing characteristics including strictly aerobic metabolism, sporulation, fruiting body formation, and surface motility. Analysis of the 5.01 Mb strain 2CP-C genome substantiated that this organism is a myxobacterium but shares genotypic traits with the anaerobic majority of the delta-Proteobacteria (i.e., the Desulfuromonadales). Reflective of its respiratory versatility, strain 2CP-C possesses 68 genes coding for putative c-type cytochromes, including one gene with 40 heme binding motifs. Consistent with its relatedness to the myxobacteria, surface motility was observed in strain 2CP-C and multiple types of motility genes are present, including 28 genes for gliding, adventurous (A-) motility and 17 genes for type IV pilus-based motility (i.e., social (S-) motility) that all have homologs in Myxococcus xanthus. Although A. dehalogenans shares many metabolic traits with the anaerobic majority of the delta-Proteobacteria, strain 2CP-C grows under microaerophilic conditions and possesses detoxification systems for reactive oxygen species. Accordingly, two gene clusters coding for NADH dehydrogenase subunits and two cytochrome oxidase gene clusters in strain 2CP-C are similar to those in M. xanthus. Remarkably, strain 2CP-C possesses a third NADH dehydrogenase gene cluster and a cytochrome cbb(3) oxidase gene cluster, apparently acquired through ancient horizontal gene transfer from a strictly anaerobic green sulfur bacterium. The mosaic nature of the A. dehalogenans strain 2CP-C genome suggests that the metabolically versatile, anaerobic members of the delta-Proteobacteria may have descended from aerobic ancestors with complex lifestyles.

HIV-1 virions assemble at the plasma membrane of mammalian cells and recruit the endosomal sorting complex required for transport (ESCRT) machinery to enable particle release. However, little is known about the temporal and spatial organization of ESCRT protein recruitment. Using multiple-color live-cell total internal reflection fluorescence microscopy, we observed that the ESCRT-I protein Tsg101 is recruited together with Gag to the sites of HIV-1 assembly, whereas later-acting ESCRT proteins (Chmp4b and Vps4A) are recruited sequentially, once Gag assembly is completed. Chmp4b, a protein that is required to mediate particle scission, is recruited to HIV-1 assembly sites ∼10 s before the ATPase Vps4A. Using two-color superresolution imaging, we observed that the ESCRT machinery (Tsg101, Alix, and Chmp4b/c proteins) is positioned at the periphery of the nascent virions, with the Tsg101 assemblages positioned closer to the Gag assemblages than Alix, Chmp4b, or Chmp4c. These results are consistent with the notion that the ESCRT machinery is recruited transiently to the neck of the assembling particle and is thus present at the appropriate time and place to mediate fission between the nascent virus and the plasma membrane.