Mass measurements of neutron-deficient Y, Zr, and Nb isotopes and their impact on rp and νp nucleosynthesis processes

© 2018 The Authors. Published by Elsevier B.V. This manuscript is made available under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence (CC BY-NC-ND 4.0). For further details please see: https://creativecommons.org/licenses/by-nc-nd/4.0/Using isochronous mass spectrometry at the experimental storage ring CSRe in Lanzhou, the masses of 82Zr and 84Nb were measured for the first time with an uncertainty of ∼10 keV, and the masses of 79Y, 81Zr, and 83Nb were re-determined with a higher precision. The latter are significantly less bound than their literature values. Our new and accurate masses remove the irregularities of the mass surface in this region of the nuclear chart. Our results do not support the predicted island of pronounced low α separation energies for neutron-deficient Mo and Tc isotopes, making the formation of Zr–Nb cycle in the rp-process unlikely. The new proton separation energy of 83Nb was determined to be 490(400) keV smaller than that in the Atomic Mass Evaluation 2012. This partly removes the overproduction of the p-nucleus 84Sr relative to the neutron-deficient molybdenum isotopes in the previous νp-process simulations.Peer reviewe

Type I and III Interferon Productions Are Impaired in X-Linked Agammaglobulinemia Patients Toward Poliovirus but Not Influenza Virus

BackgroundX-linked agammaglobulinemia (XLA) is a primary immunodeficiency caused by Bruton’s tyrosine kinase (BTK) mutation. Patients are susceptible to severe enterovirus infections. The underlying mechanism remains unknown. BTK is involved in toll-like receptors pathway, which initiates antiviral responses including interferon (IFN) productions.ObjectiveTo demonstrate type I and III IFN productions in dendritic cells of XLA patients is decreased in response to oral poliovirus vaccine (OPV) but not H1N1 virus.MethodsMonocyte-derived dendritic cells (MoDCs) were derived from nine XLA patients aged 22–32 years old and 23 buffy coats from Hong Kong Red Cross blood donors. LFM-A13 was used to inhibit BTK. OPV Sabin type 1 and H1N1 influenza virus were used to stimulate MoDCs with RPMI as mock stimulation. The antiviral cytokine productions and phenotypic maturation of MoDCs were determined 24 h post-stimulation. OPV RNA was determined at 0, 6, 12, and 24 h post-stimulation.ResultsUpon OPV stimulation, IFN-α2, IFN-β, and IFN-λ1 productions in MoDCs from XLA patients and BTK-inhibited MoDCs of healthy controls were significantly lower than that from healthy controls. Whereas upon H1N1 stimulation, the IFN-α2, IFN-β, and IFN-λ1 productions were similar in MoDCs from XLA patients, BTK-inhibited MoDCs of healthy controls and healthy controls. The mean fluorescent intensities (MFI) of CD83, CD86, and MHC-II in MoDCs from XLA patients in response to OPV was similar to that in response to mock stimulation, while the MFI of CD83, CD86, and MHC-II were significantly higher in response to H1N1 stimulation than that in response to mock stimulation. Whereas, the MFI of CD83, CD86, and MHC-II in MoDCs of healthy controls were significantly higher in response to both OPV and H1N1 stimulation compared to that in response to mock stimulation.ConclusionProduction of type I and III IFN in response to OPV was deficient in MoDCs from XLA patients, but was normal in response to H1N1 due to deficient BTK function. Moreover, phenotypic maturation of MoDCs from XLA patients was impaired in response to OPV but not to H1N1. These selective impairments may account for the unique susceptibility of XLA patients toward severe enterovirus infections

Stochastic Growth Equations and Reparametrization Invariance

It is shown that, by imposing reparametrization invariance, one may derive a variety of stochastic equations describing the dynamics of surface growth and identify the physical processes responsible for the various terms. This approach provides a particularly transparent way to obtain continuum growth equations for interfaces. It is straightforward to derive equations which describe the coarse grained evolution of discrete lattice models and analyze their small gradient expansion. In this way, the authors identify the basic mechanisms which lead to the most commonly used growth equations. The advantages of this formulation of growth processes is that it allows one to go beyond the frequently used no-overhang approximation. The reparametrization invariant form also displays explicitly the conservation laws for the specific process and all the symmetries with respect to space-time transformations which are usually lost in the small gradient expansion. Finally, it is observed, that the knowledge of the full equation of motion, beyond the lowest order gradient expansion, might be relevant in problems where the usual perturbative renormalization methods fail.Comment: 42 pages, Revtex, no figures. To appear in Rev. of Mod. Phy

Dendritic and T Cell Response to Influenza is Normal in the Patients with X-Linked Agammaglobulinemia

Introduction Influenza virus is a potential cause of severe disease in the immunocompromised. X-linked agammaglobu-linemia (XLA) is a primary immunodeficiency characterized by the lack of immunoglobulin, B cells, and plasma cells, secondary to mutation in Bruton’s tyrosine kinase (Btk) gene

Coevolved mutations reveal distinct architectures for two core proteins in the bacterial flagellar motor

Switching of bacterial flagellar rotation is caused by large domain movements of the FliG protein triggered by binding of the signal protein CheY to FliM. FliG and FliM form adjacent multi-subunit arrays within the basal body C-ring. The movements alter the interaction of the FliG C-terminal (FliGC) "torque" helix with the stator complexes. Atomic models based on the Salmonella entrovar C-ring electron microscopy reconstruction have implications for switching, but lack consensus on the relative locations of the FliG armadillo (ARM) domains (amino-terminal (FliGN), middle (FliGM) and FliGC) as well as changes during chemotaxis. The generality of the Salmonella model is challenged by the variation in motor morphology and response between species. We studied coevolved residue mutations to determine the unifying elements of switch architecture. Residue interactions, measured by their coevolution, were formalized as a network, guided by structural data. Our measurements reveal a common design with dedicated switch and motor modules. The FliM middle domain (FliMM) has extensive connectivity most simply explained by conserved intra and inter-subunit contacts. In contrast, FliG has patchy, complex architecture. Conserved structural motifs form interacting nodes in the coevolution network that wire FliMM to the FliGC C-terminal, four-helix motor module (C3-6). FliG C3-6 coevolution is organized around the torque helix, differently from other ARM domains. The nodes form separated, surface-proximal patches that are targeted by deleterious mutations as in other allosteric systems. The dominant node is formed by the EHPQ motif at the FliMMFliGM contact interface and adjacent helix residues at a central location within FliGM. The node interacts with nodes in the N-terminal FliGc α-helix triad (ARM-C) and FliGN. ARM-C, separated from C3-6 by the MFVF motif, has poor intra-network connectivity consistent with its variable orientation revealed by structural data. ARM-C could be the convertor element that provides mechanistic and species diversity.JK was supported by Medical Research Council grant U117581331. SK was supported by seed funds from Lahore University of Managment Sciences (LUMS) and the Molecular Biology Consortium

Nucleocytoplasmic transport: a thermodynamic mechanism

The nuclear pore supports molecular communication between cytoplasm and nucleus in eukaryotic cells. Selective transport of proteins is mediated by soluble receptors, whose regulation by the small GTPase Ran leads to cargo accumulation in, or depletion from the nucleus, i.e., nuclear import or nuclear export. We consider the operation of this transport system by a combined analytical and experimental approach. Provocative predictions of a simple model were tested using cell-free nuclei reconstituted in Xenopus egg extract, a system well suited to quantitative studies. We found that accumulation capacity is limited, so that introduction of one import cargo leads to egress of another. Clearly, the pore per se does not determine transport directionality. Moreover, different cargo reach a similar ratio of nuclear to cytoplasmic concentration in steady-state. The model shows that this ratio should in fact be independent of the receptor-cargo affinity, though kinetics may be strongly influenced. Numerical conservation of the system components highlights a conflict between the observations and the popular concept of transport cycles. We suggest that chemical partitioning provides a framework to understand the capacity to generate concentration gradients by equilibration of the receptor-cargo intermediary.Comment: in press at HFSP Journal, vol 3 16 text pages, 1 table, 4 figures, plus Supplementary Material include

A community-powered search of machine learning strategy space to find NMR property prediction models

The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions. For physical scientists wishing to apply ML strategies to a particular domain, it can be difficult to assess in advance what strategy to adopt within a vast space of possibilities. Here we outline the results of an online community-powered effort to swarm search the space of ML strategies and develop algorithms for predicting atomic-pairwise nuclear magnetic resonance (NMR) properties in molecules. Using an open-source dataset, we worked with Kaggle to design and host a 3-month competition which received 47,800 ML model predictions from 2,700 teams in 84 countries. Within 3 weeks, the Kaggle community produced models with comparable accuracy to our best previously published "in-house" efforts. A meta-ensemble model constructed as a linear combination of the top predictions has a prediction accuracy which exceeds that of any individual model, 7-19x better than our previous state-of-the-art. The results highlight the potential of transformer architectures for predicting quantum mechanical (QM) molecular properties