Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Towards an understanding of neuroscience for science educators

Advances in neuroscience have brought new insights to the development of cognitive functions. These data are of considerable interest to educators concerned with how students learn. This review documents some of the recent findings in neuroscience, which is richer in describing cognitive functions than affective aspects of learning. A brief overview is presented here of the techniques used to generate data from imaging and how these findings have the possibility to inform educators. There are implications for considering the impact of neuroscience at all levels of education – from the classroom teacher and practitioner to policy. This relatively new cross-disciplinary area of research implies a need for educators and scientists to engage with each other. What questions are emerging through such dialogues between educators and scientists are likely to shed light on, for example, reward, motivation, working memory, learning difficulties, bilingualism and child development. The sciences of learning are entering a new paradigm

Astronomical Distance Determination in the Space Age: Secondary Distance Indicators

The formal division of the distance indicators into primary and secondary leads to difficulties in description of methods which can actually be used in two ways: with, and without the support of the other methods for scaling. Thus instead of concentrating on the scaling requirement we concentrate on all methods of distance determination to extragalactic sources which are designated, at least formally, to use for individual sources. Among those, the Supernovae Ia is clearly the leader due to its enormous success in determination of the expansion rate of the Universe. However, new methods are rapidly developing, and there is also a progress in more traditional methods. We give a general overview of the methods but we mostly concentrate on the most recent developments in each field, and future expectations. © 2018, The Author(s)

Physical Processes in Star Formation

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00693-8.Star formation is a complex multi-scale phenomenon that is of significant importance for astrophysics in general. Stars and star formation are key pillars in observational astronomy from local star forming regions in the Milky Way up to high-redshift galaxies. From a theoretical perspective, star formation and feedback processes (radiation, winds, and supernovae) play a pivotal role in advancing our understanding of the physical processes at work, both individually and of their interactions. In this review we will give an overview of the main processes that are important for the understanding of star formation. We start with an observationally motivated view on star formation from a global perspective and outline the general paradigm of the life-cycle of molecular clouds, in which star formation is the key process to close the cycle. After that we focus on the thermal and chemical aspects in star forming regions, discuss turbulence and magnetic fields as well as gravitational forces. Finally, we review the most important stellar feedback mechanisms.Peer reviewedFinal Accepted Versio

The C-terminal extension landscape of naturally presented HLA-I ligands.

HLA-I molecules play a central role in antigen presentation. They typically bind 9- to 12-mer peptides, and their canonical binding mode involves anchor residues at the second and last positions of their ligands. To investigate potential noncanonical binding modes, we collected in-depth and accurate HLA peptidomics datasets covering 54 HLA-I alleles and developed algorithms to analyze these data. Our results reveal frequent (442 unique peptides) and statistically significant C-terminal extensions for at least eight alleles, including the common HLA-A03:01, HLA-A31:01, and HLA-A68:01. High resolution crystal structure of HLA-A68:01 with such a ligand uncovers structural changes taking place to accommodate C-terminal extensions and helps unraveling sequence and structural properties predictive of the presence of these extensions. Scanning viral proteomes with the C-terminal extension motifs identifies many putative epitopes and we demonstrate direct recognition by human CD8 <sup>+</sup> T cells of a 10-mer epitope from cytomegalovirus predicted to follow the C-terminal extension binding mode

Bedside formulation of a personalized multi-neoantigen vaccine against mammary carcinoma.

Harnessing the immune system to purposely recognize and destroy tumors represents a significant breakthrough in clinical oncology. Non-synonymous mutations (neoantigenic peptides) were identified as powerful cancer targets. This knowledge can be exploited for further improvements of active immunotherapies, including cancer vaccines, as T cells specific for neoantigens are not attenuated by immune tolerance mechanism and do not harm healthy tissues. The current study aimed at developing an optimized multitarget vaccine using short or long neoantigenic peptides utilizing virus-like particles (VLPs) as an efficient vaccine platform. Mutations of murine mammary carcinoma cells were identified by integrating mass spectrometry-based immunopeptidomics and whole exome sequencing. Neoantigenic peptides were synthesized and covalently linked to virus-like nanoparticles using a Cu-free click chemistry method for easy preparation of vaccines against mouse mammary carcinoma. As compared with short peptides, vaccination with long peptides was superior in the generation of neoantigen-specific CD4 <sup>+</sup> and CD8 <sup>+</sup> T cells, which readily produced interferon gamma (IFN-γ) and tumor-necrosis factor α (TNF-α). The resulting anti-tumor effect was associated with favorable immune re-polarization in the tumor microenvironment through reduction of myeloid-derived suppressor cells. Vaccination with long neoantigenic peptides also decreased post-surgical tumor recurrence and metastases, and prolonged mouse survival, despite the tumor's low mutational burden. Integrating mass spectrometry-based immunopeptidomics and whole exome sequencing is an efficient approach for identifying neoantigenic peptides. Our multitarget VLP-based vaccine shows a promising anti-tumor effect in an aggressive murine mammary carcinoma model. Future clinical application using this strategy is readily feasible and practical, as click chemistry coupling of personalized synthetic peptides to the nanoparticles can be done at the bedside directly before injection