Publications by authors named "E L Panova"

Article Synopsis
  • mRNA-based therapies have gained popularity over the last decade, particularly highlighted by their role in mass COVID-19 vaccination, leading to further research into antiviral and anti-cancer vaccines and genetic treatments.
  • Lipid nanoparticles (LNPs) are crucial for mRNA delivery, and adaptable LNP systems are needed to better control how mRNA is taken up and expressed in target cells.
  • New cationic lipid formulations (2X3 and 2X7) have shown effective mRNA delivery in lab cells and live mice, demonstrating prolonged gene activity and localized expression in muscles, pointing to their potential for long-term therapeutic applications.
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We report two complexes [Cu(L)] () and [Cu(L)] () (HL = -cyclohexyl-3-methoxysalicylideneimine, HL = -cyclohexyl-3-ethoxysalicylideneimine). The ligands in both complexes are -1,5-N,O-coordinated, yielding a square planar CuNO coordination core. The molecule of is planar with two cyclohexyl groups oriented to the opposite sites of the planar part of a molecule, while the molecule of is significantly bent with two cyclohexyl groups oriented to the same convex site of a molecule.

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Single-domain antibodies (sdAbs, VHHs, or nanobodies) are a promising tool for the treatment of both infectious and somatic diseases. Their small size greatly simplifies any genetic engineering manipulations. Such antibodies have the ability to bind hard-to-reach antigenic epitopes through long parts of the variable chains, the third complementarity-determining regions (CDR3s).

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When entering the phase of big data processing and statistical inferences in experimental physics, the efficient use of machine learning methods may require optimal data preprocessing methods and, in particular, optimal balance between details and noise. In experimental studies of strong-field quantum electrodynamics with intense lasers, this balance concerns data binning for the observed distributions of particles and photons. Here we analyze the aspect of binning with respect to different machine learning methods (Support Vector Machine (SVM), Gradient Boosting Trees (GBT), Fully-Connected Neural Network (FCNN), Convolutional Neural Network (CNN)) using numerical simulations that mimic expected properties of upcoming experiments.

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Beginning in the 1860s, two major centers of neurology and psychiatry arose in Russia: Imperial Moscow University (IMU) and Imperial Medical and Surgical Academy in St. Petersburg (IMSA). Both centers were strongly influenced by Leading Western European schools and specialists, through the clinical and research training regimes of both Russian universities, strongly influenced these centers of learning.

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