Mobility of the SecA 2-helix-finger is not essential for polypeptide translocation via the SecYEG complex

The bacterial ATPase SecA and protein channel complex SecYEG form the core of an essential protein translocation machinery. The nature of the conformational changes induced by each stage of the hydrolytic cycle of ATP and how they are coupled to protein translocation are not well understood. The structure of the SecA–SecYEG complex revealed a 2-helix-finger (2HF) of SecA in an ideal position to contact the substrate protein and push it through the membrane. Surprisingly, immobilization of this finger at the edge of the protein channel had no effect on translocation, whereas its imposition inside the channel blocked transport. This analysis resolves the stoichiometry of the active complex, demonstrating that after the initiation process translocation requires only one copy each of SecA and SecYEG. The results also have important implications on the mechanism of energy transduction and the power stroke driving transport. Evidently, the 2HF is not a highly mobile transducing element of polypeptide translocation

Limits on the ultra-bright Fast Radio Burst population from the CHIME Pathfinder

We present results from a new incoherent-beam Fast Radio Burst (FRB) search on the Canadian Hydrogen Intensity Mapping Experiment (CHIME) Pathfinder. Its large instantaneous field of view (FoV) and relative thermal insensitivity allow us to probe the ultra-bright tail of the FRB distribution, and to test a recent claim that this distribution's slope, $\alpha\equiv-\frac{\partial \log N}{\partial \log S}$, is quite small. A 256-input incoherent beamformer was deployed on the CHIME Pathfinder for this purpose. If the FRB distribution were described by a single power-law with $\alpha=0.7$, we would expect an FRB detection every few days, making this the fastest survey on sky at present. We collected 1268 hours of data, amounting to one of the largest exposures of any FRB survey, with over 2.4\,$\times$\,10$^5$\,deg$^2$\,hrs. Having seen no bursts, we have constrained the rate of extremely bright events to $<\!13$\,sky$^{-1}$\,day$^{-1}$ above $\sim$\,220$\sqrt{(\tau/\rm ms)}$ Jy\,ms for $\tau$ between 1.3 and 100\,ms, at 400--800\,MHz. The non-detection also allows us to rule out $\alpha\lesssim0.9$ with 95$\%$ confidence, after marginalizing over uncertainties in the GBT rate at 700--900\,MHz, though we show that for a cosmological population and a large dynamic range in flux density, $\alpha$ is brightness-dependent. Since FRBs now extend to large enough distances that non-Euclidean effects are significant, there is still expected to be a dearth of faint events and relative excess of bright events. Nevertheless we have constrained the allowed number of ultra-intense FRBs. While this does not have significant implications for deeper, large-FoV surveys like full CHIME and APERTIF, it does have important consequences for other wide-field, small dish experiments

Difference-frequency generation with quantum-limited efficiency in triply-resonant nonlinear cavities

We present a comprehensive study of second-order nonlinear difference frequency generation in triply resonant cavities using a theoretical framework based on coupled-mode theory. We show that optimal quantum-limited conversion efficiency can be achieved at any pump power when the powers at the pump and idler frequencies satisfy a critical relationship. We demonstrate the existence of a broad parameter range in which all triply-resonant DFG processes exhibit monostable conversion. We also demonstrate the existence of a geometry-dependent bistable region.Comment: 10 pages, 3 figure

Colored Resonant Signals at the LHC: Largest Rate and Simplest Topology

We study the colored resonance production at the LHC in a most general approach. We classify the possible colored resonances based on group theory decomposition, and construct their effective interactions with light partons. The production cross section from annihilation of valence quarks or gluons may be on the order of 400 - 1000 pb at LHC energies for a mass of 1 TeV with nominal couplings, leading to the largest production rates for new physics at the TeV scale, and simplest event topology with dijet final states. We apply the new dijet data from the LHC experiments to put bounds on various possible colored resonant states. The current bounds range from 0.9 to 2.7 TeV. The formulation is readily applicable for future searches including other decay modes.Comment: 29 pages, 9 figures. References updated and additional K-factors include

Improving the sensitivity of Higgs boson searches in the golden channel

Leptonic decays of the Higgs boson in the ZZ* channel yield what is known as the golden channel due to its clean signature and good total invariant mass resolution. In addition, the full kinematic distribution of the decay products can be reconstructed, which, nonetheless, is not taken into account in traditional search strategy relying only on measurements of the total invariant mass. In this work we implement a type of multivariate analysis known as the matrix element method, which exploits differences in the full production and decay matrix elements between the Higgs boson and the dominant irreducible background from q bar{q} -> ZZ*. Analytic expressions of the differential distributions for both the signal and the background are also presented. We perform a study for the Large Hadron Collider at sqrt{s}=7 TeV for Higgs masses between 175 and 350 GeV. We find that, with an integrated luminosity of 2.5 fb^-1 or higher, improvements in the order of 10 - 20 % could be obtained for both discovery significance and exclusion limits in the high mass region, where the differences in the angular correlations between signal and background are most pronounced.Comment: 31 pages, 8 figures. v2: Minus signs in definitions of angles corrected. Typos fixed. Reference added. Cosmetic changes to Figure 4. Additional sentence added for clarificatio

The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer.

Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM -/- patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment