397 research outputs found

    Interaction of the tetracyclines with double-stranded RNAs of random base sequence: new perspectives on the target and mechanism of action

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    The 16S rRNA binding mechanism proposed for the antibacterial action of the tetracyclines does not explain their mechanism of action against non-bacterial pathogens. In addition, several contradictory base pairs have been proposed as their binding sites on the 16S rRNA. This study investigated the binding of minocycline and doxycycline to short double-stranded RNAs (dsRNAs) of random base sequences. These tetracyclines caused a dose-dependent decrease in the fluorescence intensities of 6-carboxyfluorescein (FAM)-labelled dsRNA and ethidium bromide (EtBr)-stained dsRNA, indicating that both drugs bind to dsRNA of random base sequence in a manner that is competitive with the binding of EtBr and other nucleic acid ligands often used as stains. This effect was observable in the presence of Mg2+. The binding of the tetracyclines to dsRNA changed features of the fluorescence emission spectra of the drugs and the CD spectra of the RNA, and inhibited RNase III cleavage of the dsRNA. These results indicate that the double-stranded structures of RNAs may have a more important role in their interaction with the tetracyclines than the specific base pairs, which had hitherto been the subject of much investigation. Given the diverse functions of cellular RNAs, the binding of the tetracyclines to their double-stranded helixes may alter the normal processing and functioning of the various biological processes they regulate. This could help to explain the wide range of action of the tetracyclines against various pathogens and disease condition

    Testing a Neural Network for Anomaly Detection in the CMS Level-1 Global Trigger test crate during Run 3

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    We present the deployment and testing of an autoencoder trained for unbiased detection of new physics signatures in the CMS Global Trigger test crate during LHC Run 3. The GT test crate is a copy of the main GT system, receiving the same input data, but whose output is not used to trigger the readout of CMS, providing a platform for thorough testing of new trigger algorithms on live data, but without interrupting data taking. We describe the integration of the DNN into the GT test crate, and the monitoring, testing, and validation of the algorithm during proton collisions.We present the deployment and testing of an autoencoder trained for unbiased detection of new physics signatures in the CMS Level-1 Global Trigger (GT) test crate during LHC Run 3. The GT test crate is a copy of the main GT system, receiving the same input data, but whose output is not used to trigger the readout of CMS, providing a platform for thorough testing of new trigger algorithms on live data, but without interrupting data taking. We describe the integration of the Neural Network into the GT test crate, and the monitoring, testing, and validation of the algorithm during proton collisions

    UM Semester Abroad - Student Talks

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    Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s\sqrt{s} = 5.02 TeV

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    International audienceThe inclusive jet cross section is measured as a function of jet transverse momentum pTp_\mathrm{T} and rapidity yy. The measurement is performed using proton-proton collision data at s\sqrt{s} = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb‚ąí1^{-1}. The jets are reconstructed with the anti-kTk_\mathrm{T} algorithm using a distance parameter of RR = 0.4, within the rapidity interval ‚ą£y‚ą£\lvert y\rvert<\lt 2, and across the kinematic range 0.06 <\ltpTp_\mathrm{T}<\lt 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling őĪS\alpha_\mathrm{S}

    Measurement of the Drell-Yan forward-backward asymmetry at high dilepton masses in proton-proton collisions at s\sqrt{s} = 13 TeV