Pharmacoeconomic evaluation of diabetic nephropathic patients attending nephrology department in a tertiary care hospital.

AIMS: To evaluate the cost of pharmacotherapy and its determinants in diabetic nephropathy (DN) in the nephrology department of a tertiary care hospital. MATERIALS AND METHODS: A prospective observational study was conducted among adult patients visiting nephrology outpatient department (February-July 2015). Data on demography, investigations, and medications prescribed, direct cost and indirect costs were analyzed. We used Chi-squared test for categorical variables and multivariate linear regression analysis to identify determinants of cost of pharmacotherapy and total cost. RESULTS: Of 100 patients, 50 were above 60 years and 75 were male. Ninety-seven patients had hypertension, which was the most common comorbidity. The majority (60 patients) belonged to Stage 5 DN and 59 patients were on dialysis. The mean number of drugs per patient was 7.60 ± 2.44. The total monthly cost per patient amounted to INR 24,203.27 with total direct cost of INR 21,013.90 (87%) and indirect cost of INR 3189.30 (13%). The monthly cost of dialysis and pharmacotherapy per patient were INR 9060.00 (37%) and INR 2535.98 (11%), respectively. Stage of DN (unstandardized coefficient, B = 7553.96, 95% confidence interval [CI] [6175.09-8932.82], P < 0.001) was a significant determinant of total cost. Number of drugs (B = 636.694, 95% CI [335.670-937.718], P < 0.001) and stage of DN (B = 852.986, 95% CI [297.043-1408.928], P = 0.003) were predictors of cost of pharmacotherapy. CONCLUSION: Stage of DN and number of drugs prescribed were major determinants of cost of pharmacotherapy.

Dynamical behavior of the vascular endothelial growth factor: biological implications.

The vascular endothelial growth factor (VEGF) seems to be the most important regulator of physiological and pathological angiogenesis, being, for this reason, a favorite target for therapies against angiogenesis-related diseases. VEGF is a homodimer in which the monomers are formed by beta-strands interconnected on the poles by three loops. A recent work showed that an intimate relationship between loops-1 and -3 is required for high affinity binding to the receptors (Kiba et al., J Biol Chem 2003;278:13453-13461). In this work, we report the results of a 10-ns molecular dynamics simulation of VEGF. We analyzed the dynamical behavior of the protein (using a dynamical cross-correlation map) and found that it is governed by a high degree of correlation between the motions of the loops. We also performed a principal component analysis and found an overall motion in which the opposite poles are projected against each other, just like the movement of the wings of a butterfly. From the biological point of view, it is likely that this motion would facilitate receptor binding since VEGF must enter a restricted cavity formed by the two subunits of the receptor.

Information transfer in entrained cortical neurons.

Cortical interneurons connected by gap junctions can provide a synchronized inhibitory drive that can entrain pyramidal cells. This was studied in a single-compartment Hodgkin-Huxley-type model neuron that was entrained by periodic inhibitory inputs with low jitter in the input spike times (i.e. high precision), and a variable but large number of presynaptic spikes on each cycle. During entrainment the Shannon entropy of the output spike times was reduced sharply compared with its value outside entrainment. Surprisingly, however, the information transfer as measured by the mutual information between the number of inhibitory inputs in a cycle and the phase lag of the subsequent output spike was significantly increased during entrainment. This increase was due to the reduced contribution of the internal correlations to the output variability. These theoretical predictions were supported by experimental recordings from the rat neocortex and hippocampus in vitro.

A dynamical model of kinesin-microtubule motility assays.

A two-dimensional stochastic model for the dynamics of microtubules in gliding-assay experiments is presented here, which includes the viscous drag acting on the moving fiber and the interaction with the kinesins. For this purpose, we model kinesin as a spring, and explicitly use parameter values to characterize the model from experimental data. We numerically compute the mean attachment lifetimes of all motors, the total force exerted on the microtubules at all times, the effects of a distribution in the motor speeds, and also the mean velocity of a microtubule in a gliding assay. We find quantitative agreement with the results of J. Howard, A. J. Hudspeth, and R. D. Vale, Nature. 342:154-158. We perform additional numerical analysis of the individual motors, and show how cancellation of the forces exerted by the many motors creates a resultant longitudinal force much smaller than the maximum force that could be exerted by a single motor. We also examine the effects of inhomogeneities in the motor-speeds. Finally, we present a simple theoretical model for microtubules dynamics in gliding assays. We show that the model can be analytically solved in the limit of few motors attached to the microtubule and in the opposite limit of high motor density. We find that the speed of the microtubule goes like the mean speed of the motors in good quantitative agreement with the experimental and numerical results.

Computational model of carbachol-induced delta, theta, and gamma oscillations in the hippocampus.

Field potential recordings from the rat hippocampus in vivo contain distinct frequency bands of activity, including delta (0.5-2 Hz), theta (4-12 Hz), and gamma (30-80 Hz), that are correlated with the behavioral state of the animal. The cholinergic agonist carbachol (CCH) induces oscillations in the delta (CCH-delta), theta (CCH-theta), and gamma (CCH-gamma) frequency ranges in the hippocampal slice preparation, eliciting asynchronous CCH-theta, synchronous CCH-delta, and synchronous CCH-theta with increasing CCH concentration (Fellous and Seinowski, Hippocampus 2000;1 0:187-197). In a network model of area CA3, the time scale for CCH-delta corresponded to the decay constant of the gating variable of the calcium-dependent potassium (K-AHP) current, that of CCH-theta to an intrinsic subthreshold membrane potential oscillation of the pyramidal cells, and that of CCH-gamma to the decay constant of GABAergic inhibitory synaptic potentials onto the pyramidal cells. In model simulations, the known physiological effects of carbachol on the muscarinic and K-AHP currents, and on the strengths of excitatory postsynaptic potentials, reproduced transitions from asynchronous CCH-theta to CCH-delta and from CCH-delta to synchronous CCH-theta. The simulations also exhibited the interspersed CCH-gamma/CCH-delta and CCH-gamma/CCH-theta that were observed in experiments. The model, in addition, predicted an oscillatory state with all three frequency bands present, which has not yet been observed experimentally.

Three-dimensional Josephson-junction arrays in the quantum regime.

We study the quantum phase transition properties of a three-dimensional periodic array of Josephson junctions with charging energy that includes both the self and mutual junction capacitances. We use the phase fluctuation algebra between number and phase operators, given by the Euclidean group E2, and we effectively map the problem onto a solvable quantum generalization of the spherical model. We obtain a phase diagram as a function of temperature, Josephson coupling, and charging energy. We also analyze the corresponding fluctuation conductivity and its universal scaling form in the vicinity of the zero-temperature quantum critical point.

Synchronous clusters in a noisy inhibitory neural network.

We study the stability and information encoding capacity of synchronized states in a neuronal network model that represents part of thalamic circuitry. Our model neurons have a Hodgkin-Huxley-type low-threshold calcium channel, display postinhibitory rebound, and are connected via GABAergic inhibitory synapses. We find that there is a threshold in synaptic strength, tau(c), below which there are no stable spiking network states. Above threshold the stable spiking state is a cluster state, where different groups of neurons fire consecutively, and each neuron fires with the same cluster each time. Weak noise destabilizes this state, but stronger noise drives the system into a different, self-organized, stochastically synchronized state. Neuronal firing is still organized in clusters, but individual neurons can hop from cluster to cluster. Noise can actually induce and sustain such a state below the threshold of synaptic strength. We do find a qualitative difference in the firing patterns between small (approximately 10 neurons) and large (approximately 1000 neurons) networks. We determine the information content of the spike trains in terms of two separate contributions: the spike-time jitter around cluster firing times, and the hopping from cluster to cluster. We quantify the information loss due to temporally correlated interspike intervals. Recent experiments on the locust olfactory system and striatal neurons suggest that the nervous system may actually use these two channels to encode separate and unique information.

Robust gamma oscillations in networks of inhibitory hippocampal interneurons.

Recent experiments suggest that inhibitory networks of interneurons can synchronize the neuronal discharge in in vitro hippocampal slices. Subsequent theoretical work has shown that strong synchronization by mutual inhibition is only moderately robust against neuronal heterogeneities in the current drive, provided by activation of metabotropic glutamate receptors. In vivo neurons display greater variability in the interspike intervals due to the presence of synaptic noise. Noise and heterogeneity affect synchronization properties differently. In this paper we study, using model simulations, how robust synchronization can be in the presence of synaptic noise and neuronal heterogeneity. We find that stochastic weak synchronization (SWS) (i.e. when neurons spike within a short interval from each other, but not necessarily at each period) is produced with at least a minimum amount of noise and that it is much more robust than strong synchronization (i.e. when neurons spike at each period). The statistics produced by the SWS population discharge are consistent with previous experimental data. We also find robust SWS in the gamma-frequency range (20-80 Hz) for a stronger synaptic coupling compared with previous models and for networks with 10-1000 neurons.

Comparison of current-driven and conductance-driven neocortical model neurons with Hodgkin-Huxley voltage-gated channels.

Intrinsic noise and random synaptic inputs generate a fluctuating current across neuron membranes. We determine the statistics of the output spike train of a biophysical model neuron as a function of the mean and variance of the fluctuating current, when the current is white noise, or when it derives from Poisson trains of excitatory and inhibitory postsynaptic conductances. In the first case, the firing rate increases with increasing variance of the current, whereas in the latter case it decreases. In contrast, the firing rate is independent of variance (for constant mean) in the commonly used random walk, and perfect integrate-and-fire models for spike generation. The model neuron can be in the current-dominated state, representative of neurons in the in vitro slice preparation, or in the fluctuation-dominated state, representative of in vivo neurons. We discuss the functional relevance of these states to cortical information processing.

Pauli principle and chaos in a magnetized disk.

We present results of a detailed quantum-mechanical study of a gas of N noninteracting electrons confined to a circular boundary and subject to homogeneous dc plus ac magnetic fields [B=B(dc)+B(ac)f(t), with f(t+2pi/omega(0))=f(t)]. We earlier found a one-particle classical phase diagram of the (scaled) Larmor frequency omega;(c)=omega(c)/omega(0) vs epsilon=B(ac)/B(dc) that separates regular from chaotic regimes. We also showed that the quantum spectrum statistics changed from Poisson to Gaussian orthogonal ensembles in the transition from classically integrable to chaotic dynamics. Here we find that, as a function of N and (epsilon,omega(c)), there are clear quantum signatures in the magnetic response, when going from the single-particle classically regular to chaotic regimes. In the quasi-integrable regime the magnetization nonmonotonically oscillates between diamagnetic and paramagnetic as a function of N. We quantitatively understand this behavior from a perturbation theory analysis. In the chaotic regime, however, we find that the magnetization oscillates as a function of N but it is always diamagnetic. Equivalent results are also presented for the orbital currents. We also find that the time-averaged energy grows as N2 in the quasi-integrable regime but changes to a linear N dependence in the chaotic regime. In contrast, the results with Bose statistics are akin to the single-particle case and thus different from the fermionic case. We also give an estimate of possible experimental parameters where our results may be seen in semiconductor quantum dot billiards.

Probability distributions of thermodynamic affinities for heterogeneous receptor populations.

A statistical approach to characterize the thermodynamic affinity distributions of heterogeneous receptor populations in terms of stoichiometric binding constants is presented. The use of stoichiometric density distributions provides a novel description of ligand binding systems. The distributions of stoichiometric constants, Ti(Ki)'s, are obtained assuming that the distribution of site constants N(k) is known. It is found that in the case of heterogeneous systems with multivalent receptors, N(k) is an average over all the Ti(Ki)'s even when there are positive or negative site-site interactions. It is seen that in the absence or in the presence of site-site interactions the mean and the variance of the Ki's can be derived from a Scatchard plot. Some of these results are particularly applicable to bivalent heterogeneous antibody populations and other results are applicable to bivalent heterogeneous systems with different binding sites.

Intracardiac blood flow velocities and cardiac output in normal fetuses: a prospective pulsed Doppler echocardiographic study.

Two dimensional and pulsed Doppler echocardiographic studies were performed in human fetuses with the aim to establish normal values for blood flow velocities and cardiac output in Indian subjects. Thirteen pregnant mothers were prospectively followed up at 4 weeks interval from 19 to 40 weeks of gestation. Blood flow velocity spectra across aortic, pulmonary, mitral and tricuspid valves were analyzed to obtain peak flow velocity (cm/sec) and velocity time integral. Aortic and pulmonary diameters were measured at the valve level from two dimensional echocardiographic images and ventricular stroke volume calculated. The values were plotted against fetal age (weeks) and fetal weight (gms). Our results showed that there is a linear increase of the measured Doppler data, with increasing gestational age and weight. These values may be used as a reference for the Indian population.