Shadowing in Inelastic Scattering of Muons on Carbon, Calcium and Lead at Low XBj

Nuclear shadowing is observed in the per-nucleon cross-sections of positive muons on carbon, calcium and lead as compared to deuterium. The data were taken by Fermilab experiment E665 using inelastically scattered muons of mean incident momentum 470 GeV/c. Cross-section ratios are presented in the kinematic region 0.0001 < XBj <0.56 and 0.1 < Q**2 < 80 GeVc. The data are consistent with no significant nu or Q**2 dependence at fixed XBj. As XBj decreases, the size of the shadowing effect, as well as its A dependence, are found to approach the corresponding measurements in photoproduction.Comment: 22 pages, incl. 6 figures, to be published in Z. Phys.

New constraints on gamma-ray burst jet geometry and relativistic shock physics

We use high–quality, multi-band observations of Swift GRB120404A, from γ-ray to radio frequencies, together with the new hydrodynamics code of van Eerten et al. (2012) to test the standard synchrotron shock model. The evolution of the radio and optical afterglow, with its prominent optical rebrightening at trest � 260–2600 s, is remarkably well modelled by a decelerating jet viewed close to the jet edge, combined with some early re–energization of the shock. We thus constrain the geometry of the jet with half–opening and viewing angles of 23◦ and 21◦ respectively and suggest that wide jets viewed off-axis are more common in GRBs than previously thought. We also derive the fireball microphysics parameters ǫB = 2.4 × 10−4 and ǫe = 9.3 × 10−2 and a circumburst density of n = 240 cm−3. The ability to self–consistently model the microphysics parameters and jet geometry in this way offers an alternative to trying to identify elusive canonical jet breaks at late times. The mismatch between the observed and model-predicted X–ray fluxes is explained by the local rather than the global cooling approximation in the synchrotron radiation model, constraining the microphysics of particle acceleration taking place in a relativistic shock and, in turn, emphasising the need for a more realistic treatment of cooling in future developments of theoretical models. Finally, our interpretation of the optical peak as due to the passage of the forward shock synchrotron frequency highlights the importance of high quality multi–band data to prevent some optical peaks from being erroneously attributed to the onset of fireball deceleration

Phasevarions Mediate Random Switching of Gene Expression in Pathogenic Neisseria

Many host-adapted bacterial pathogens contain DNA methyltransferases (mod genes) that are subject to phase-variable expression (high-frequency reversible ON/OFF switching of gene expression). In Haemophilus influenzae, the random switching of the modA gene controls expression of a phase-variable regulon of genes (a “phasevarion”), via differential methylation of the genome in the modA ON and OFF states. Phase-variable mod genes are also present in Neisseria meningitidis and Neisseria gonorrhoeae, suggesting that phasevarions may occur in these important human pathogens. Phylogenetic studies on phase-variable mod genes associated with type III restriction modification (R-M) systems revealed that these organisms have two distinct mod genes—modA and modB. There are also distinct alleles of modA (abundant: modA11, 12, 13; minor: modA4, 15, 18) and modB (modB1, 2). These alleles differ only in their DNA recognition domain. ModA11 was only found in N. meningitidis and modA13 only in N. gonorrhoeae. The recognition site for the modA13 methyltransferase in N. gonorrhoeae strain FA1090 was identified as 5′-AGAAA-3′. Mutant strains lacking the modA11, 12 or 13 genes were made in N. meningitidis and N. gonorrhoeae and their phenotype analyzed in comparison to a corresponding mod ON wild-type strain. Microarray analysis revealed that in all three modA alleles multiple genes were either upregulated or downregulated, some of which were virulence-associated. For example, in N. meningitidis MC58 (modA11), differentially expressed genes included those encoding the candidate vaccine antigens lactoferrin binding proteins A and B. Functional studies using N. gonorrhoeae FA1090 and the clinical isolate O1G1370 confirmed that modA13 ON and OFF strains have distinct phenotypes in antimicrobial resistance, in a primary human cervical epithelial cell model of infection, and in biofilm formation. This study, in conjunction with our previous work in H. influenzae, indicates that phasevarions may be a common strategy used by host-adapted bacterial pathogens to randomly switch between “differentiated” cell types

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods

SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

BACKGROUND: Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. METHODS: In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FINDINGS: Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. INTERPRETATION: The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. FUNDING: This study has been supported by ISARIC4C and PHOSP-COVID consortia. ISARIC4C is supported by grants from the National Institute for Health and Care Research and the Medical Research Council. Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research. The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research. The funders were not involved in the study design, interpretation of data or the writing of this manuscript