Effective field theory and the quark model

We analyze the connections between the quark model (QM) and the description of hadrons in the low-momentum limit of heavy-baryon effective field theory in QCD. By using a three-flavor-index representation for the effective baryon fields, we show that the ``nonrelativistic'' constituent QM for baryon masses and moments is completely equivalent through O(m_s) to a parametrization of the relativistic field theory in a general spin--flavor basis. The flavor and spin variables can be identified with those of effective valence quarks. Conversely, the spin-flavor description clarifies the structure and dynamical interpretation of the chiral expansion in effective field theory, and provides a direct connection between the field theory and the semirelativistic models for hadrons used in successful dynamical calculations. This allows dynamical information to be incorporated directly into the chiral expansion. We find, for example, that the striking success of the additive QM for baryon magnetic moments is a consequence of the relative smallness of the non-additive spin-dependent corrections.Comment: 25 pages, revtex, no figure

Analysis of dynamical corrections to baryon magnetic moments

We present and analyze QCD corrections to the baryon magnetic moments in terms of the one-, two-, and three-body operators which appear in the effective field theory developed in our recent papers. The main corrections are extended Thomas-type corrections associated with the confining interactions in the baryon. We investigate the contributions of low-lying angular excitations to the moments quantitatively and show that they are completely negligible. When the QCD corrections are combined with the non-quark model contributions of the meson loops, we obtain a model which describes the moments within a mean deviation of 0.04 $\mu_N$. The nontrivial interplay of the two types of corrections to the quark-model moments is analyzed in detail, and explains why the quark model is so successful. In the course of these calculations, we parametrize the general spin structure of the $j={1/2}^+$ baryon wave functions in a form which clearly displays the symmetry properties and the internal angular momentum content of the wave functions, and allows us to use spin-trace methods to calculate the many spin matrix elements which appear in the expressions for the moments. This representation may be useful elsewhere.Comment: 32 pages, 3 figures, submitted to Phys. Rev.

High Energy Hadron-Nucleus Cross Sections and Their Extrapolation to Cosmic Ray Energies

Old models of the scattering of composite systems based on the Glauber model of multiple diffraction are applied to hadron-nucleus scattering. We obtain an excellent fit with only two free parameters to the highest energy hadron-nucleus data available. Because of the quality of the fit and the simplicity of the model it is argued that it should continue to be reliable up to the highest cosmic ray energies. Logarithmic extrapolations of proton-proton and proton-antiproton data are used to calculate the proton-air cross sections at very high energy. Finally, it is observed that if the exponential behavior of the proton-antiproton diffraction peak continues into the few TeV energy range it will violate partial wave unitarity. We propose a simple modification that will guarantee unitarity throughout the cosmic ray energy region.Comment: 8 pages, 9 postscript figures. This manuscript replaces a partial manuscript incorrectly submitte

New Particles Working Group Report of the Snowmass 2013 Community Summer Study

This report summarizes the work of the Energy Frontier New Physics working group of the 2013 Community Summer Study (Snowmass)

Baryon masses in a loop expansion with form factor

We show that the average multiplet masses in the baryon octet and decuplet can be fitted with an average error of only $0.5\pm 0.3$ MeV in a meson loop expansion with chiral SU(6) couplings, with the hadrons treated as composite particles using a baryon-meson form factor. The form factor suppresses unphysical short distance effects and leads to a controllable expansion. We find, in contrast to the results of standard chiral perturbation theory, that pion loops are as important as kaon or eta loops as would be expected when only intermediate- and long-distance contributions are retained. We also find that the contributions of decuplet intermediate states are important in the calculation of the masses, and those states must be included explicitly in a consistent theory. These results agree with those of our recent loop-expansion analysis of the baryon magnetic moments. We show, finally, that the parts of the loop contributions that change the tree-level structure of the baryon masses are small, but largely account for the violations of the baryon mass sum rules which hold at tree level.Comment: 20 pages, 2 figures, submitted to Phys. Rev. D. Title changed, the introduction and discussion of the results rewritte

Universal prediction of cell-cycle position using transfer learning.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadBackground: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data. Results: Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell-cycle embedding using a fixed reference dataset and project new data into this reference embedding, an approach that overcomes key limitations of learning a dataset-dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species, and even sequencing assays. Conclusions: Tricycle generalizes across datasets and is highly scalable and applicable to atlas-level single-cell RNA-seq data. Keywords: Cell cycle; Single-cell RNA-sequencing; Transfer learning.Chan Zuckerberg Initiative DAF Silicon Valley Community Foundation United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of General Medical Sciences (NIGMS) Appeared in source as:National Institute of General Medical Sciences of the National Institutes of Health National Science Foundation (NSF) National Institute of Agin Maryland Stem Cell Research Foundation Kavli Neurodiscovery Institute Johns Hopkins Provost Award Program BRAIN Initiative United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Neurological Disorders & Stroke (NINDS) Appeared in source as:National Institute of Neurological Disorder

The Goldstone boson equivalence theorem with fermions

The calculation of the leading electroweak corrections to physical transition matrix elements in powers of $M_H^2/v^2$ can be greatly simplified in the limit $M_H^2\gg M_W^2,\, M_Z^2$ through the use of the Goldstone boson equivalence theorem. This theorem allows the vector bosons $W^\pm$ and $Z$ to be replaced by the associated scalar Goldstone bosons $w^\pm$, $z$ which appear in the symmetry breaking sector of the Standard Model in the limit of vanishing gauge couplings. In the present paper, we extend the equivalence theorem systematically to include the Yukawa interactions between the fermions and the Higgs and Goldstone bosons of the Standard Model. The corresponding Lagrangian ${\cal L}_{EQT}$ is given, and is formally renormalized to all orders. The renormalization conditions are formulated both to make connection with physical observables and to satisfy the requirements underlying the equivalence theorem. As an application of this framework, we calculate the dominant radiative corrections to fermionic Higgs decays at one loop including the virtual effects of a heavy top quark. We apply the result to the decays $H\rightarrow t\bar{t}$ and $H\rightarrow b\bar{b}$, and find that the equivalence theorem results including fermions are quite accurate numerically for Higgs-boson masses $M_H> 400\,(350)$ GeV, respectively, even for $m_t=175$ GeV.Comment: 32 pages, uses LaTeX2e, epsf and rotate, 7 figures included as separate uuencoded packed file. A complete PostScript version can also be obtained from http://www.physik.tu-muenchen.de/tumphy/d/T30d/PAPERS/TUM-HEP-227-95.ps.g

Ago2 Immunoprecipitation Identifies Predicted MicroRNAs in Human Embryonic Stem Cells and Neural Precursors

MicroRNAs are required for maintenance of pluripotency as well as differentiation, but since more microRNAs have been computationally predicted in genome than have been found, there are likely to be undiscovered microRNAs expressed early in stem cell differentiation.SOLiD ultra-deep sequencing identified >10(7) unique small RNAs from human embryonic stem cells (hESC) and neural-restricted precursors that were fit to a model of microRNA biogenesis to computationally predict 818 new microRNA genes. These predicted genomic loci are associated with chromatin patterns of modified histones that are predictive of regulated gene expression. 146 of the predicted microRNAs were enriched in Ago2-containing complexes along with 609 known microRNAs, demonstrating association with a functional RISC complex. This Ago2 IP-selected subset was consistently expressed in four independent hESC lines and exhibited complex patterns of regulation over development similar to previously-known microRNAs, including pluripotency-specific expression in both hESC and iPS cells. More than 30% of the Ago2 IP-enriched predicted microRNAs are new members of existing families since they share seed sequences with known microRNAs.Extending the classic definition of microRNAs, this large number of new microRNA genes, the majority of which are less conserved than their canonical counterparts, likely represent evolutionarily recent regulators of early differentiation. The enrichment in Ago2 containing complexes, the presence of chromatin marks indicative of regulated gene expression, and differential expression over development all support the identification of 146 new microRNAs active during early hESC differentiation

SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the rapidly unfolding coronavirus disease 2019 (COVID-19) pandemic1,2. Clinical manifestations of COVID-19 vary, ranging from asymptomatic infection to respiratory failure. The mechanisms that determine such variable outcomes remain unresolved. Here we investigated CD4+ T cells that are reactive against the spike glycoprotein of SARS-CoV-2 in the peripheral blood of patients with COVID-19 and SARS-CoV-2-unexposed healthy donors. We detected spike-reactive CD4+ T cells not only in 83% of patients with COVID-19 but also in 35% of healthy donors. Spike-reactive CD4+ T cells in healthy donors were primarily active against C-terminal epitopes in the spike protein, which show a higher homology to spike glycoproteins of human endemic coronaviruses, compared with N-terminal epitopes. Spike-protein-reactive T cell lines generated from SARS-CoV-2-naive healthy donors responded similarly to the C-terminal region of the spike proteins of the human endemic coronaviruses 229E and OC43, as well as that of SARS-CoV-2. This results indicate that spike-protein cross-reactive T cells are present, which were probably generated during previous encounters with endemic coronaviruses. The effect of pre-existing SARS-CoV-2 cross-reactive T cells on clinical outcomes remains to be determined in larger cohorts. However, the presence of spike-protein cross-reactive T cells in a considerable fraction of the general population may affect the dynamics of the current pandemic, and has important implications for the design and analysis of upcoming trials investigating COVID-19 vaccines

Gene co-regulation by Fezf2 selects neurotransmitter identity and connectivity of corticospinal neurons

The neocortex contains an unparalleled diversity of neuronal subtypes, each defined by distinct traits that are developmentally acquired under the control of subtype-specific and pan-neuronal genes. The regulatory logic that orchestrates the expression of these unique combinations of genes is unknown for any class of cortical neuron. Here, we report that Fezf2 is a selector gene able to regulate the expression of gene sets that collectively define mouse corticospinal motor neurons (CSMN). We find that Fezf2 directly induces the glutamatergic identity of CSMN via activation of Vglut1 (Slc17a7) and inhibits a GABAergic fate by repressing transcription of Gad1. In addition, we identify the axon guidance receptor EphB1 as a target of Fezf2 necessary to execute the ipsilateral extension of the corticospinal tract. Our data indicate that co-regulated expression of neuron subtype–specific and pan-neuronal gene batteries by a single transcription factor is one component of the regulatory logic responsible for the establishment of CSMN identity