Photocatalytic, antimicrobial and antibiofilm activities of MgFe2O4 magnetic nanoparticles.

This study reports the antibacterial and antibiofilm activities of Magnesium ferrite nanoparticles (MgFe2O4) against gram-positive and gram-negative bacteria. The photocatalytic degradation of Carbol Fuchsin (CF) dye (a class of dyestuffs that are resistant to biodegradation) under the influence of UV-light irradiation is also studied. The crystalline magnesium ferrite (MgFe2O4) nanoparticles were synthesized using the co-precipitation method. The morphology of the resulting nanocomposite was examined using scanning electron microscopy (SEM), while transmission electron microscopy (TEM) was employed for further characterization of particle morphology and size. Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) were utilized to analyze the crystalline structure, chemical composition, and surface area, respectively. Optical properties were evaluated using UV-Vis spectroscopy. The UV-assisted photocatalytic performance of MgFe2O4 nanoparticles was assessed by studying the decolorization of Carbol fuchsin (CF) azo dye. The crystallite size of the MgFe2O4 nanoparticles at the (311) plane, the most prominent peak, was determined to be 28.5 nm. The photocatalytic degradation of 10 ppm CF using 15 mg of MgFe2O4 nanoparticles resulted in a significant 96% reduction after 135 min at ambient temperature (25 °C) and a pH value of 9. Additionally, MgFe2O4 nanoparticles exhibited potent antibacterial activity against E. coli and S. aureus in a dose dependent manner with maximum utilized concentration of 30 µg/ml. Specifically, MgFe2O4 nanoparticles demonstrated substantial antibacterial activity via disk diffusion and microbroth dilution tests with zones of inhibition and minimum inhibitory concentrations (MIC) for E. coli (26.0 mm, 1.25 µg/ml) and S. aureus (23.0 mm, 2.5 µg/ml), respectively. Moreover, 10.0 µg/ml of MgFe2O4 nanoparticles elicited marked percent reduction in biofilm formation by E. coli (89%) followed by S. aureus (78.5%) after treatment. In conclusion, MgFe2O4 nanoparticles demonstrated efficient dye removal capabilities along with significant antimicrobial and antibiofilm activity against gram-positive and gram-negative bacterial strains suggesting their potential as promising antimicrobial and detoxifying agents.

The cellular architecture of memory modules in Drosophila supports stochastic input integration.

The ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within the Drosophila mushroom body (MB), the fly's center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-α3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit.

Altered neuronal excitability in a Hodgkin-Huxley model incorporating channelopathies of the delayed rectifier potassium channel.

Channelopathies involving acquired or genetic modifications of the delayed rectifier K+ channel Kv1.1 include phenotypes characterized by enhanced neuronal excitability. Affected Kv1.1 channels exhibit combinations of altered expression, voltage sensitivity, and rates of activation and deactivation. Computational modeling and analysis can reveal the potential of particular channelopathies to alter neuronal excitability. A dynamical systems approach was taken to study the excitability and underlying dynamical structure of the Hodgkin-Huxley (HH) model of neural excitation as properties of the delayed rectifier K+ channel were altered. Bifurcation patterns of the HH model were determined as the amplitude of steady injection current was varied simultaneously with single parameters describing the delayed rectifier rates of activation and deactivation, maximal conductance, and voltage sensitivity. Relatively modest changes in the properties of the delayed rectifier K+ channel analogous to what is described for its channelopathies alter the bifurcation structure of the HH model and profoundly modify excitability of the HH model. Channelopathies associated with Kv1.1 can reduce the threshold for onset of neural activity. These studies also demonstrate how pathological delayed rectifier K+ channels could lead to the observation of the generalized Hopf bifurcation and, perhaps, other variants of the Hopf bifurcation. The observed bifurcation patterns collectively demonstrate that properties of the nominal delayed rectifier in the HH model appear optimized to permit activation of the HH model over the broadest possible range of input currents.

Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study.

Patient-specific models of the ventricular myocardium, combined with the computational power to run rapid simulations, are approaching the level where they could be used for personalized cardiovascular medicine. A major remaining challenge is determining model parameters from available patient data, especially for models of the Purkinje-myocardial junctions (PMJs): the sites of initial ventricular electrical activation. There are no non-invasive methods for localizing PMJs in patients, and the relationship between the standard clinical ECG and PMJ model parameters is underexplored. Thus, this study aimed to determine the sensitivity of the QRS complex of the ECG to the anatomical location and regional number of PMJs. The QRS complex was simulated using an image-based human torso and biventricular model, and cardiac electrophysiology was simulated using Cardioid. The PMJs were modeled as discrete current injection stimuli, and the location and number of stimuli were varied within initial activation regions based on published experiments. Results indicate that the QRS complex features were most sensitive to the presence or absence of four "seed" stimuli, and adjusting locations of nearby "regional" stimuli provided finer tuning. Decreasing number of regional stimuli by an order of magnitude resulted in virtually no change in the QRS complex. Thus, a minimal 12-stimuli configuration was identified that resulted in physiological excitation, defined by QRS complex feature metrics and ventricular excitation pattern. Overall, the sensitivity results suggest that parameterizing PMJ location, rather than number, be given significantly higher priority in future studies creating personalized ventricular models from patient-derived ECGs.

Lattice Modeling of Early-Age Behavior of Structural Concrete.

The susceptibility of structural concrete to early-age cracking depends on material composition, methods of processing, structural boundary conditions, and a variety of environmental factors. Computational modeling offers a means for identifying primary factors and strategies for reducing cracking potential. Herein, lattice models are shown to be adept at simulating the thermal-hygral-mechanical phenomena that influence early-age cracking. In particular, this paper presents a lattice-based approach that utilizes a model of cementitious materials hydration to control the development of concrete properties, including stiffness, strength, and creep resistance. The approach is validated and used to simulate early-age cracking in concrete bridge decks. Structural configuration plays a key role in determining the magnitude and distribution of stresses caused by volume instabilities of the concrete material. Under restrained conditions, both thermal and hygral effects are found to be primary contributors to cracking potential.