Search results for "Biological physics"

showing 10 items of 153 documents

Diamond Magnetic Microscopy of Malarial Hemozoin Nanocrystals.

2019

Magnetic microscopy of malarial hemozoin nanocrystals was performed using optically detected magnetic resonance imaging of near-surface diamond nitrogen-vacancy centers. Hemozoin crystals were extracted from $Plasmodium$-$falciparum$-infected human blood cells and studied alongside synthetic hemozoin crystals. The stray magnetic fields produced by individual crystals were imaged at room temperature as a function of applied field up to 350 mT. More than 100 nanocrystals were analyzed, revealing the distribution of their magnetic properties. Most crystals ($96\%$) exhibit a linear dependence of stray field magnitude on applied field, confirming hemozoin's paramagnetic nature. A volume magneti…

Materials scienceFOS: Physical sciencesGeneral Physics and AstronomyNanoparticleBioengineering02 engineering and technology01 natural sciencesArticleCrystalParamagnetismRare DiseasesEngineeringMesoscale and Nanoscale Physics (cond-mat.mes-hall)parasitic diseases0103 physical sciencesMicroscopyNanotechnologyPhysics - Biological Physics010306 general physicsSaturation (magnetic)Condensed Matter - Mesoscale and Nanoscale PhysicsHemozoin021001 nanoscience & nanotechnologyMagnetic susceptibility3. Good healthMalariaVector-Borne DiseasesInfectious DiseasesGood Health and Well BeingBiological Physics (physics.bio-ph)Chemical physicsPhysical Sciences0210 nano-technologySuperparamagnetism
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Gyrification from constrained cortical expansion

2014

The exterior of the mammalian brain - the cerebral cortex - has a conserved layered structure whose thickness varies little across species. However, selection pressures over evolutionary time scales have led to cortices that have a large surface area to volume ratio in some organisms, with the result that the brain is strongly convoluted into sulci and gyri. Here we show that the gyrification can arise as a nonlinear consequence of a simple mechanical instability driven by tangential expansion of the gray matter constrained by the white matter. A physical mimic of the process using a layered swelling gel captures the essence of the mechanism, and numerical simulations of the brain treated a…

Models AnatomicCompressive StrengthModels NeurologicalLissencephalyFOS: Physical sciencesGeometryPattern Formation and Solitons (nlin.PS)Condensed Matter - Soft Condensed MatterNerve Fibers MyelinatedWhite matterNeural PathwaysPolymicrogyriamedicineHumansDimethylpolysiloxanesPhysics - Biological PhysicsTissues and Organs (q-bio.TO)GyrificationCell ProliferationPhysicsCerebral CortexNeuronsMultidisciplinaryta114PachygyriaQuantitative Biology - Tissues and OrgansAnatomymedicine.diseaseNonlinear Sciences - Pattern Formation and SolitonsElasticitymedicine.anatomical_structureCerebral cortexBiological Physics (physics.bio-ph)FOS: Biological sciencesBrain sizePhysical SciencesSoft Condensed Matter (cond-mat.soft)Stress MechanicalBrain morphogenesisGels
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Dynamics of the Selkov oscillator.

2018

A classical example of a mathematical model for oscillations in a biological system is the Selkov oscillator, which is a simple description of glycolysis. It is a system of two ordinary differential equations which, when expressed in dimensionless variables, depends on two parameters. Surprisingly it appears that no complete rigorous analysis of the dynamics of this model has ever been given. In this paper several properties of the dynamics of solutions of the model are established. With a view to studying unbounded solutions a thorough analysis of the Poincar\'e compactification of the system is given. It is proved that for any values of the parameters there are solutions which tend to inf…

Statistics and ProbabilityPeriodicityQuantitative Biology - Subcellular ProcessesClassical exampleFOS: Physical sciencesDynamical Systems (math.DS)01 natural sciencesModels BiologicalGeneral Biochemistry Genetics and Molecular Biology010305 fluids & plasmassymbols.namesake0103 physical sciencesFOS: MathematicsPhysics - Biological PhysicsMathematics - Dynamical Systems0101 mathematicsSubcellular Processes (q-bio.SC)MathematicsGeneral Immunology and MicrobiologyCompactification (physics)Applied Mathematics010102 general mathematicsMathematical analysisGeneral MedicineMathematical ConceptsKineticsMonotone polygonBiological Physics (physics.bio-ph)FOS: Biological sciencesModeling and SimulationBounded functionOrdinary differential equationPoincaré conjecturesymbolsGeneral Agricultural and Biological SciencesGlycolysisDimensionless quantityMathematical biosciences
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Counting individual 41Ca atoms with a magneto-optical trap

2003

Atom Trap Trace Analysis (ATTA), a novel method based upon laser trapping and cooling, is used to count individual atoms of 41Ca present in biomedical samples with isotopic abundance levels between 10^-8 and 10^-10. ATTA is calibrated against Resonance Ionization Mass Spectrometry, demonstrating a good agreement between the two methods. The present ATTA system has a counting efficiency of 2x10^-7. Within one hour of observation time, its 3-sigma detection limit on the isotopic abundance of 41Ca reaches 4.5x10^-10.

Atomic Physics (physics.atom-ph)Biological Physics (physics.bio-ph)FOS: Physical sciencesPhysics - Biological PhysicsPhysics - Atomic Physics
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Anomalous surface diffusion of protons on lipid membranes.

2014

AbstractThe cellular energy machinery depends on the presence and properties of protons at or in the vicinity of lipid membranes. To asses the energetics and mobility of a proton near a membrane, we simulated an excess proton near a solvated DMPC bilayer at 323 K, using a recently developed method to include the Grotthuss proton shuttling mechanism in classical molecular dynamics simulations. We obtained a proton surface affinity of −13.0 ± 0.5 kJ mol−1. The proton interacted strongly with both lipid headgroup and linker carbonyl oxygens. Furthermore, the surface diffusion of the proton was anomalous, with a subdiffusive regime over the first few nanoseconds, followed by a superdiffusive re…

Surface diffusionPhysics::Biological PhysicsProtonChemistryBilayerLipid BilayersBiophysicsDiffusionQuantitative Biology::Subcellular ProcessesMolecular dynamicsCrystallographymolecular-dynamics simulationsMembraneDiffusion processChemical physicsphosphatidylcholine bilayersRestricted DiffusionChannels and TransportersProtonsDiffusion (business)Dimyristoylphosphatidylcholineta116
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Retrieving infinite numbers of patterns in a spin-glass model of immune networks

2013

The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…

0301 basic medicineSimilarity (geometry)Spin glassComputer sciencestatistical mechanicFOS: Physical sciencesGeneral Physics and AstronomyNetwork topologyTopology01 natural sciencesQuantitative Biology::Cell Behavior03 medical and health sciencesCell Behavior (q-bio.CB)0103 physical sciencesattractor neural-networks; statistical mechanics; brain networks; Physics and Astronomy (all)Physics - Biological Physics010306 general physicsAssociative propertybrain networkArtificial neural networkMechanism (biology)ErgodicityDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksAcquired immune system030104 developmental biologyBiological Physics (physics.bio-ph)FOS: Biological sciencesattractor neural-networkQuantitative Biology - Cell Behavior
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Excitonic energy level structure and pigment-protein interactions in the recombinant water-soluble chlorophyll protein. II. Spectral hole-burning exp…

2011

Persistent spectral hole burning at 4.5 K has been used to investigate the excitonic energy level structure and the excited state dynamics of the recombinant class-IIa water-soluble chlorophyll-binding protein (WSCP) from cauliflower. The hole-burned spectra are composed of four main features: (i) a narrow zero-phonon hole (ZPH) at the burn wavelength, (ii) a number of vibrational ZPHs, (iii) a broad low-energy hole at ~665 and ~683 nm for chlorophyll b- and chlorophyll a-WSCP, respectively, and (iv) a second satellite hole at ~658 and ~673 nm for chlorophyll b- and chlorophyll a-WSCP, respectively. The doublet of broad satellite holes is assigned to an excitonically coupled chlorophyll dim…

ChlorophyllChlorophyll aExcitonAnalytical chemistryLight-Harvesting Protein ComplexesElectronsBrassicaVibrationSpectral linechemistry.chemical_compoundMaterials ChemistryPhysical and Theoretical ChemistryPhysics::Biological PhysicsChlorophyll AWaterFluorescenceRecombinant ProteinsSurfaces Coatings and FilmsWavelengthSpectrometry FluorescencechemistryExcited stateChlorophyllSpectral hole burningThermodynamicsAtomic physicsThe journal of physical chemistry. B
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Counterion-Mediated Crossing of the Cyanine Limit in Crystals and Fluid Solution: Bond Length Alternation and Spectral Broadening Unveiled by Quantum…

2020

Absorption spectra of cyanine⊕·Br⊖ salts show a remarkable solvent dependence in non/polar solvents, exhibiting narrow, sharp band shapes in dichloromethane but broad features in toluene; this chan...

chemistry.chemical_classificationPhysics::Biological PhysicsQuantitative Biology::BiomoleculesAbsorption spectroscopyGeneral Chemistry010402 general chemistry01 natural sciencesBiochemistryQuantum chemistryCatalysis0104 chemical sciencesCondensed Matter::Soft Condensed MatterSolventchemistry.chemical_compoundColloid and Surface ChemistryFluid solutionchemistryChemical physicsPhysics::Chemical PhysicsCounterionCyanineDoppler broadeningDichloromethane
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Non-equilibrium Markov state modeling of periodically driven biomolecules

2019

Molecular dynamics simulations allow to study the structure and dynamics of single biomolecules in microscopic detail. However, many processes occur on time scales beyond the reach of fully atomistic simulations and require coarse-grained multiscale models. While systematic approaches to construct such models have become available, these typically rely on microscopic dynamics that obey detailed balance. In vivo, however, biomolecules are constantly driven away from equilibrium in order to perform specific functions and thus break detailed balance. Here we introduce a method to construct Markov state models for systems that are driven through periodically changing one (or several) external p…

Computer scienceFOS: Physical sciencesGeneral Physics and AstronomyMarkov processMolecular Dynamics Simulation010402 general chemistry01 natural sciencesMolecular dynamicssymbols.namesake0103 physical sciencesPhysics - Biological PhysicsStatistical physicsPhysical and Theoretical ChemistryCondensed Matter - Statistical Mechanicschemistry.chemical_classificationQuantitative Biology::BiomoleculesStatistical Mechanics (cond-mat.stat-mech)010304 chemical physicsMarkov chainBiomoleculeMolecular biophysicsDetailed balanceDipeptidesComputational Physics (physics.comp-ph)Markov Chains0104 chemical sciencesModels ChemicalchemistryBiological Physics (physics.bio-ph)Benchmark (computing)symbolsState (computer science)Physics - Computational PhysicsThe Journal of Chemical Physics
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A PHENOMENOLOGICAL OPERATOR DESCRIPTION OF INTERACTIONS BETWEEN POPULATIONS WITH APPLICATIONS TO MIGRATION

2013

We adopt an operatorial method based on the so-called creation, annihilation and number operators in the description of different systems in which two populations interact and move in a two-dimensional region. In particular, we discuss diffusion processes modeled by a quadratic hamiltonian. This general procedure will be adopted, in particular, in the description of migration phenomena. With respect to our previous analogous results, we use here fermionic operators since they automatically implement an upper bound for the population densities.

Heisenberg-like dynamicsComputer scienceApplied MathematicsPopulations and Evolution (q-bio.PE)FOS: Physical sciencesDynamics of competing populations with diffusion; Fermionic operators; Heisenberg-like dynamicsUpper and lower boundssymbols.namesakeQuadratic equationOperator (computer programming)Biological Physics (physics.bio-ph)Particle number operatorFOS: Biological sciencesModeling and SimulationsymbolsPhysics - Biological PhysicsStatistical physicsQuantitative Biology - Populations and EvolutionHamiltonian (quantum mechanics)Settore MAT/07 - Fisica MatematicaDynamics of competing populations with diffusionquantum tools for classical systemsFermionic operatorsMathematical Models and Methods in Applied Sciences
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