Publications by authors named "M M Rantanen"

Transient receptor potential vanilloid (TRPV) 4 is involved in signaling pathways specifically mediating pain and inflammation, making it a promising target for the treatment of various painful and inflammatory conditions. However, only one drug candidate targeting TRPV4 has entered the clinical trials. To identify potential TRPV4 inhibitors for drug development, we screened a library of ion channel-modulating compounds using both structure- and ligand-based virtual screening approaches.

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Article Synopsis
  • The study focuses on detecting multijet signatures from proton-proton collisions at a high energy of 13 TeV, analyzing a dataset totaling 128 fb^{-1}.
  • A special data scouting method is utilized to pick out events with low combined momentum in jets.
  • This research is pioneering in its investigation of electroweak particle production in R-parity violating supersymmetric models, particularly examining hadronically decaying mass-degenerate higgsinos, and it broadens the limits on the existence of R-parity violating top squarks and gluinos.
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The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.

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The first search for the Z boson decay to ττμμ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138  fb^{-1}. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.

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Natural stilbenoids, polyphenolic compounds notably found in Scots pine and Norway spruce, have been shown to exhibit analgesic and anti-inflammatory effects through the TRPA1 channel, making them promising hits for the development of novel agents to treat inflammatory diseases and pain. In this study, we computationally investigated the putative binding sites of natural stilbenoids at the TRPA1 channel. Specifically, we employed molecular docking and MD simulation approaches to explore three known ligand binding sites at TRPA1.

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