93 research outputs found
Activity-dependent plasticity of transmitter release from nerve terminals in rat fast and slow muscles
Available under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported license.Peer reviewedPublisher PD
Chern - Simons Gauge Field Theory of Two - Dimensional Ferromagnets
A Chern-Simons gauged Nonlinear Schr\"odinger Equation is derived from the
continuous Heisenberg model in 2+1 dimensions. The corresponding planar magnets
can be analyzed whithin the anyon theory. Thus, we show that static magnetic
vortices correspond to the self-dual Chern - Simons solitons and are described
by the Liouville equation. The related magnetic topological charge is
associated with the electric charge of anyons. Furthermore, vortex - antivortex
configurations are described by the sinh-Gordon equation and its conformally
invariant extension. Physical consequences of these results are discussed.Comment: 15 pages, Plain TeX, Lecce, June 199
Pilot study of transcranial photobiomodulation of lymphatic clearance of beta-amyloid from the mouse brain: breakthrough strategies for non-pharmacologic therapy of Alzheimer's disease
In this pilot study, we analyzed effects of transcranial photobiomodulation (tPBM, 1267 nm, 32 J/cm2) on clearance of beta-amyloid (Aβ) from the mouse brain. The immunohistochemical and confocal data clearly demonstrate the significant reduction of deposition of Aβ plaques in mice after tPBM vs. untreated animals. The behavior tests showed that tPBM improved the cognitive, memory and neurological status of mice with Alzheimer’s disease (AD). Using of our original method based on optical coherence tomography (OCT) analysis of clearance of gold nanorods (GNRs) from the brain, we proposed possible mechanism underlying tPBM-stimulating effects on clearance of Aβ via the lymphatic system of the brain and the neck. These results open breakthrough strategies for a non-pharmacological therapy of Alzheimer’s disease and clearly demonstrate that tPBM might be a promising therapeutic target for preventing or delaying Alzheimer’s disease
RESEARCH OF THE ABSORPTION AND EMISSION SPECTRA OF VARIOUS SUBSTANCES
In modern science and technology, to determine the chemical composition of substances, use a variety of different methods. Among these methods, one of the important places is spectral analysis. In order to obtain and investigate the emission spectrum of the substance, a device was developed that was controlled from a PC. The device is mobile and can be used with a portable laptop in arctic expeditions
Discovery of potent, novel, non-toxic anti-malarial compounds via quantum modelling, virtual screening and in vitro experimental validation
<p>Abstract</p> <p>Background</p> <p>Developing resistance towards existing anti-malarial therapies emphasize the urgent need for new therapeutic options. Additionally, many malaria drugs in use today have high toxicity and low therapeutic indices. Gradient Biomodeling, LLC has developed a quantum-model search technology that uses quantum similarity and does not depend explicitly on chemical structure, as molecules are rigorously described in fundamental quantum attributes related to individual pharmacological properties. Therapeutic activity, as well as toxicity and other essential properties can be analysed and optimized simultaneously, independently of one another. Such methodology is suitable for a search of novel, non-toxic, active anti-malarial compounds.</p> <p>Methods</p> <p>A set of innovative algorithms is used for the fast calculation and interpretation of electron-density attributes of molecular structures at the quantum level for rapid discovery of prospective pharmaceuticals. Potency and efficacy, as well as additional physicochemical, metabolic, pharmacokinetic, safety, permeability and other properties were characterized by the procedure. Once quantum models are developed and experimentally validated, the methodology provides a straightforward implementation for lead discovery, compound optimizzation and <it>de novo </it>molecular design.</p> <p>Results</p> <p>Starting with a diverse training set of 26 well-known anti-malarial agents combined with 1730 moderately active and inactive molecules, novel compounds that have strong anti-malarial activity, low cytotoxicity and structural dissimilarity from the training set were discovered and experimentally validated. Twelve compounds were identified <it>in silico </it>and tested <it>in vitro</it>; eight of them showed anti-malarial activity (IC50 ≤ 10 μM), with six being very effective (IC50 ≤ 1 μM), and four exhibiting low nanomolar potency. The most active compounds were also tested for mammalian cytotoxicity and found to be non-toxic, with a therapeutic index of more than 6,900 for the most active compound.</p> <p>Conclusions</p> <p>Gradient's metric modelling approach and electron-density molecular representations can be powerful tools in the discovery and design of novel anti-malarial compounds. Since the quantum models are agnostic of the particular biological target, the technology can account for different mechanisms of action and be used for <it>de novo </it>design of small molecules with activity against not only the asexual phase of the malaria parasite, but also against the liver stage of the parasite development, which may lead to true causal prophylaxis.</p
Complex networks theory for analyzing metabolic networks
One of the main tasks of post-genomic informatics is to systematically
investigate all molecules and their interactions within a living cell so as to
understand how these molecules and the interactions between them relate to the
function of the organism, while networks are appropriate abstract description
of all kinds of interactions. In the past few years, great achievement has been
made in developing theory of complex networks for revealing the organizing
principles that govern the formation and evolution of various complex
biological, technological and social networks. This paper reviews the
accomplishments in constructing genome-based metabolic networks and describes
how the theory of complex networks is applied to analyze metabolic networks.Comment: 13 pages, 2 figure
An Allosteric Mechanism for Switching between Parallel Tracks in Mammalian Sulfur Metabolism
Methionine (Met) is an essential amino acid that is needed for the synthesis of S-adenosylmethionine (AdoMet), the major biological methylating agent. Methionine used for AdoMet synthesis can be replenished via remethylation of homocysteine. Alternatively, homocysteine can be converted to cysteine via the transsulfuration pathway. Aberrations in methionine metabolism are associated with a number of complex diseases, including cancer, anemia, and neurodegenerative diseases. The concentration of methionine in blood and in organs is tightly regulated. Liver plays a key role in buffering blood methionine levels, and an interesting feature of its metabolism is that parallel tracks exist for the synthesis and utilization of AdoMet. To elucidate the molecular mechanism that controls metabolic fluxes in liver methionine metabolism, we have studied the dependencies of AdoMet concentration and methionine consumption rate on methionine concentration in native murine hepatocytes at physiologically relevant concentrations (40–400 µM). We find that both [AdoMet] and methionine consumption rates do not change gradually with an increase in [Met] but rise sharply (∼10-fold) in the narrow Met interval from 50 to 100 µM. Analysis of our experimental data using a mathematical model reveals that the sharp increase in [AdoMet] and the methionine consumption rate observed within the trigger zone are associated with metabolic switching from methionine conservation to disposal, regulated allosterically by switching between parallel pathways. This regulatory switch is triggered by [Met] and provides a mechanism for stabilization of methionine levels in blood over wide variations in dietary methionine intake
Observation of decays using the 2019-2022 Belle II data sample
We present a measurement of the branching fractions of four decay modes. The measurement is based on data from
SuperKEKB electron-positron collisions at the resonance
collected with the Belle II detector and corresponding to an integrated
luminosity of . The event yields are extracted from fits
to the distributions of the difference between expected and observed meson
energy to separate signal and background, and are efficiency-corrected as a
function of the invariant mass of the system. We find the branching
fractions to be: where the first uncertainty is statistical and
the second systematic. These results include the first observation of
, , and decays and a significant improvement in the precision
of compared to previous measurements
Reconstruction of decays identified using hadronic decays of the recoil meson in 2019 -- 2021 Belle II data
We present results on the semileptonic decays and in a sample corresponding to
189.9/fb of Belle II data at the SuperKEKB collider. Signal decays
are identified using full reconstruction of the recoil meson in hadronic
final states. We determine the total branching fractions via fits to the
distributions of the square of the "missing" mass in the event and the dipion
mass in the signal candidate and find and where the dominant
systematic uncertainty comes from modeling the nonresonant contribution
Search for an invisible in a final state with two muons and missing energy at Belle II
The extension of the standard model predicts the existence
of a lepton-flavor-universality-violating boson that couples only
to the heavier lepton families. We search for such a through its
invisible decay in the process . We use a
sample of electron-positron collisions at a center-of-mass energy of 10.58GeV
collected by the Belle II experiment in 2019-2020, corresponding to an
integrated luminosity of 79.7fb. We find no excess over the expected
standard-model background. We set 90-confidence-level upper limits on the
cross section for this process as well as on the coupling of the model, which
ranges from at low masses to 1 at
masses of 8
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