Dmitry D. Postnov

Adaptation to shift work: physiologically based modeling of the effects of lighting and shifts' start time.

Shift work has become an integral part of our life with almost 20% of the population being involved in different shift schedules in developed countries. However, the atypical work times, especially the night shifts, are associated with reduced quality and quantity of sleep that leads to increase of sleepiness often culminating in accidents. It has been demonstrated that shift workers’ sleepiness can be improved by a proper scheduling of light exposure and optimizing shifts timing. Here, an integrated physiologically-based model of sleep-wake cycles is used to predict adaptation to shift work in different light conditions and for different shift start times for a schedule of four consecutive days of work. The integrated model combines a model of the ascending arousal system in the brain that controls the sleep-wake switch and a human circadian pacemaker model. To validate the application of the integrated model and demonstrate its utility, its dynamics are adjusted to achieve a fit to published experimental results showing adaptation of night shift workers (n = 8) in conditions of either bright or regular lighting. Further, the model is used to predict the shift workers’ adaptation to the same shift schedule, but for conditions not considered in the experiment. The model demonstrates that the intensity of shift light can be reduced fourfold from that used in the experiment and still produce good adaptation to night work. The model predicts that sleepiness of the workers during night shifts on a protocol with either bright or regular lighting can be significantly improved by starting the shift earlier in the night, e.g.; at 21∶00 instead of 00∶00. Finally, the study predicts that people of the same chronotype, i.e. with identical sleep times in normal conditions, can have drastically different responses to shift work depending on their intrinsic circadian and homeostatic parameters.

Effects of Rotation Interval on Sleepiness and Circadian Dynamics on Forward Rotating 3-Shift Systems

A physiologically based mathematical model of sleep-wake cycles is used to examine the effects of shift rotation interval (RI) (i.e., the number of days spent on each shift) on sleepiness and circadian dynamics on forward rotating 3-shift schedules. The effects of the schedule start time on the mean shift sleepiness are also demonstrated but are weak compared to the effects of RI. The dynamics are studied for a parameter set adjusted to match a most common natural sleep pattern (i.e., sleep between 0000 and 0800) and for common light conditions (i.e., 350 lux of shift lighting, 200 lux of daylight, 100 lux of artificial lighting during nighttime, and 0 lux during sleep). Mean shift sleepiness on a rotating schedule is found to increase with RI, reach maximum at intermediate RI=6 d, and then decrease. Complete entrainment to shifts within the schedules is not achieved at RI≤10 d. However, circadian oscillations synchronize to the rotation cycles, with RI=1,2 d and RI≥6 d demonstrating regular periodic changes of the circadian rhythm. At rapid rotation, circadian phase stays within a small 4-h interval, whereas slow rotation leads to around-the-clock transitions of the circadian phase with constantly delayed sleep times. Schedules with RI=3-5 d are not able to entrain the circadian rhythms, even in the absence of external circadian disturbances like social commitments and days off. To understand the circadian dynamics on the rotating shift schedules, a shift response map is developed, showing the direction of circadian change (i.e., delay or advance) depending on the relation between the shift start time and actual circadian phase. The map predicts that the un-entrained dynamics come from multiple transitions between advance and delay behavior on the shifts in the schedules. These are primarily caused by the imbalance between the amount of delay and advance on the different shift types within the schedule. Finally, it is argued that shift response maps can aid in the development of shift schedules with desired circadian characteristics.

Estimation of vessel diameter and blood flow dynamics from laser speckle images

Laser speckle imaging is a rapidly developing method to study changes of blood velocity in the vascular networks. However, to assess blood flow and vascular responses it is crucial to measure vessel diameter in addition to blood velocity dynamics. We suggest an algorithm that allows for dynamical masking of a vessel position and measurements of its diameter from laser speckle images. This approach demonstrates high reliability and stability.

Intravital investigation of rat mesenteric small artery tone and blood flow

Substantial information on rat mesenteric small artery physiology and pharmacology based on in vitro experiments is available. Little is known about the relevance of this for artery function in vivo. We here present an intravital model where rat mesenteric small artery diameters are studied under isolated and controlled conditions in situ with simultaneous measurement of blood flow. The responses of the isolated arteries vary with the anaesthetic used, and they are quantitatively but not qualitatively different from the responses seen in vitro.

Laser speckle imaging of intra organ drug distribution

Laminar flow in arteries causes streaming and uneven distribution of infused agents within the organ. This may lead to misinterpretation of experimental results and affect treatment outcomes. We monitor dynamical changes of superficial cortical blood flow in the rat kidney following different routes of administration of the vasoconstrictor angiotensin II. Our analysis reveals the appearance of large scale oscillations of the blood flow caused by inhomogeneous intra organ drug distribution.

Modeling of Kidney Hemodynamics: Probability-Based Topology of an Arterial Network

Through regulation of the extracellular fluid volume, the kidneys provide important long-term regulation of blood pressure. At the level of the individual functional unit (the nephron), pressure and flow control involves two different mechanisms that both produce oscillations. The nephrons are arranged in a complex branching structure that delivers blood to each nephron and, at the same time, provides a basis for an interaction between adjacent nephrons. The functional consequences of this interaction are not understood, and at present it is not possible to address this question experimentally. We provide experimental data and a new modeling approach to clarify this problem. To resolve details of microvascular structure, we collected 3D data from more than 150 afferent arterioles in an optically cleared rat kidney. Using these results together with published micro-computed tomography (μCT) data we develop an algorithm for generating the renal arterial network. We then introduce a mathematical model describing blood flow dynamics and nephron to nephron interaction in the network. The model includes an implementation of electrical signal propagation along a vascular wall. Simulation results show that the renal arterial architecture plays an important role in maintaining adequate pressure levels and the self-sustained dynamics of nephrons.

Laser speckle analysis of retinal vascular dynamics.

Studies of vascular responses are usually performed on isolated vessels or on single vessels in vivo. This allows for precise measurements of diameter or blood flow. However, dynamical responses of the whole microvascular network are difficult to access experimentally. We suggest to use full-field laser speckle imaging to evaluate vascular responses of the retinal network. Image segmentation and vessel recognition algorithms together with response mapping allow us to analyze diameter changes and blood flow responses in the intact retinal network upon systemic administration of the vasoconstrictor angiotensin II, the vasodilator acetylcholine or on the changing level of anesthesia in in vivo rat preparations.

Improved detectability of microcirculatory dynamics by laser speckle flowmetry

Mechanisms of renal autoregulation generate oscillations in arterial blood flow at several characteristic frequencies. Full-field laser speckle flowmetry provides a real-time imaging of superficial blood microcirculation. The possibility to detect changes in oscillatory dynamics is an important issue in biomedical applications. In this paper we show how laser power density affects quality of the recorded signal and improves detectability of temporal changes in microvascular perfusion.

Monitoring of rhythms in laser speckle data

While the laser speckle imaging (LSI) is a powerful tool for multiple biomedical applications, such as monitoring of the blood flow, in many cases it can provide additional information when combined with spatio-temporal rhythm analysis. We demonstrate the application of Graphics Processing Units (GPU)-based rhythm analysis for the post processing of LSI data, discuss the relevant structure of GPU-based computations, test the proposed technique on surrogate 3D data, and apply this approach to kidney blood flow autoregulation. Experiments with surrogate data demonstrate the ability of the method to extract information about oscillation patterns from noisy data, as well as to detect the moving source of the rhythm. The analysis of kidney data allow us to detect and to localize the dynamics arising from autoregulation processes at the level of individual nephrons (tubuloglomerular feedback (TGF) rhythm), as well as to distinguish between the TGF-active and the TGF-silent zones.

Architecture of the rat nephron-arterial network: Analysis with micro-computed tomography

Among solid organs, the kidneys vascular network stands out, because each nephron has two distinct capillary structures in series and because tubuloglomerular feedback, one of the mechanisms responsible for blood flow autoregulation, is specific to renal tubules. Tubuloglomerular feedback and the myogenic mechanism, acting jointly, autoregulate single-nephron blood flow. Each generates a self-sustained periodic oscillation and an oscillating electrical signal that propagates upstream along arterioles. Similar electrical signals from other nephrons interact, allowing nephron synchronization. Experimental measurements show synchronization over fields of a few nephrons; simulations based on a simplified network structure that could obscure complex interactions predict more widespread synchronization. To permit more realistic simulations, we made a cast of blood vessels in a rat kidney, performed micro-computed tomography at 2.5-μm resolution, and recorded three-dimensional coordinates of arteries, afferent arterioles, and glomeruli. Nonterminal branches of arcuate arteries form treelike structures requiring two to six bifurcations to reach terminal branches at the tree tops. Terminal arterial structures were either paired branches at the tops of the arterial trees, from which 52.6% of all afferent arterioles originated, or unpaired arteries not at the tree tops, yielding the other 22.9%; the other 24.5% originated directly from nonterminal arteries. Afferent arterioles near the corticomedullary boundary were longer than those farther away, suggesting that juxtamedullary nephrons have longer afferent arterioles. The distance separating origins of pairs of afferent arterioles varied randomly. The results suggest an irregular-network tree structure with vascular nodes, where arteriolar activity and local blood pressure interact.