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Showing 1–6 of 6 results
Advanced filters: Author: Lorenzo Landini Clear advanced filters

  • Endometriosis affects over 60% of women, leading to widespread pain. Here, the authors show that blocking C5a receptor (C5aR1) in Schwann cells reduces pain by inhibiting pathways that trigger inflammation, oxidative stress, and nerve sensitivity, revealing a potential therapeutic target in endometriosis pain management.

    • Mustafa Titiz
    • Lorenzo Landini
    • Francesco De Logu
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-15

  • Non-steroidal anti-inflammatory drugs (NSAIDs) are known to alleviate pain by reducing inflammation. To the contrary, here, the authors show that selective inhibition of the prostaglandin E2 receptor (EP2) in Schwann cells eliminates pain without disrupting the protective and healing functions of inflammation.

    • Romina Nassini
    • Lorenzo Landini
    • Pierangelo Geppetti
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-19

  • Quantum systems exhibit vastly different properties depending on their dimensionality. An experimental study with ultracold bosons now tracks quantum correlation properties during the crossover from two dimensions to one dimension.

    • Yanliang Guo
    • Hepeng Yao
    • Hanns-Christoph Nägerl
    Research
    Nature Physics
    Volume: 20, P: 934-938

  • The mechanism of CGRP-evoked peripheral pain is unclear. Here, the authors show that the CGRP-mediated neuronal/Schwann cell pathway mediates allodynia associated with neurogenic inflammation, contributing to the algesic action of CGRP in mice.

    • Francesco De Logu
    • Romina Nassini
    • Pierangelo Geppetti
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-19

  • Modern neutrino experiments require precise tuning of energy response parameters, a task complicated by the parameters’ nonlinear behavior and strong correlations. The authors present neural density estimators using normalizing flows and transformers integrating them with Bayesian nested sampling to achieve near-zero systematic biases and uncertainties limited only by statistics, offering a flexible framework for particle physics applications

    • Arsenii Gavrikov
    • Andrea Serafini
    • Lucia Votano
    ResearchOpen Access
    Communications Physics
    Volume: 9, P: 1-18