A Quantitative Assessment of Cerebral Hemodynamic Perturbations Associated with Long R-R Intervals in Atrial Fibrillation: A Pilot-Case-Based Experience.

Background and Objectives: Atrial fibrillation (AF) results in systemic hemodynamic perturbations which impact cerebral circulation, possibly contributing to the development of dementia. However, evidence documenting effects in cerebral perfusion is scarce. The aim of this study is to provide a quantitative characterization of the magnitude and time course of the cerebral hemodynamic response to the short hypotensive events associated with long R-R intervals, as detected by near-infrared spectroscopy (NIRS). Materials and Methods: Cerebral NIRS signals and arterial blood pressure were continuously recorded along with an electrocardiogram in twelve patients with AF undergoing elective electrical cardioversion (ECV). The top 0.5-2.5% longest R-R intervals during AF were identified in each patient and used as triggers to carry out the triggered averaging of hemodynamic signals. The average curves were then characterized in terms of the latency, magnitude, and duration of the observed effects, and the possible occurrence of an overshoot was also investigated. Results: The triggered averages revealed that long R-R intervals produced a significant drop in diastolic blood pressure (-13.7 ± 6.1 mmHg) associated with an immediate drop in cerebral blood volume (THI: -0.92 ± 0.46%, lasting 1.9 ± 0.8 s), followed by a longer-lasting decrease in cerebral oxygenation (TOI: -0.79 ± 0.37%, lasting 5.2 ± 0.9 s, p < 0.01). The recovery of the TOI was generally followed by an overshoot (+1.06 ± 0.12%). These effects were progressively attenuated in response to R-R intervals of a shorter duration. Conclusions: Long R-R intervals cause a detectable and consistent cerebral hemodynamic response which concerns both cerebral blood volume and oxygenation and outlasts the duration of the systemic perturbation. These effects are compatible with the activation of dynamic autoregulatory mechanisms in response to the hypotensive stimulus.

A review of multiscale 0D-1D computational modeling of coronary circulation with applications to cardiac arrhythmias.

Computational hemodynamics is becoming an increasingly important tool in clinical applications and surgical procedures involving the cardiovascular system. Aim of this review is to provide a compact summary of state of the art 0D-1D multiscale models of the arterial coronary system, with particular attention to applications related to cardiac arrhythmias, whose effects on the coronary circulation remain so far poorly understood. The focus on 0D-1D models only is motivated by the competitive computational cost, the reliability of the outcomes for the whole cardiovascular system, and the ability to directly account for cardiac arrhythmias. The analyzed studies show that cardiac arrhythmias by their own are able to promote significant alterations of the coronary hemodynamics, with a worse scenario as the mean heart rate (HR) increases. The present review can stimulate future investigation, both in computational and clinical research, devoted to the hemodynamic effects induced by cardiac arrhythmias on the coronary circulation.

Increased beat-to-beat variability of cerebral microcirculatory perfusion during atrial fibrillation: a near-infrared spectroscopy study.

AIMS: Atrial fibrillation (AFib) is associated with cognitive decline/dementia, independently from clinical strokes or transient ischaemic attacks (TIA). Recent in silico data suggested that AFib may induce transient critical haemodynamic events in the cerebral microcirculation. The aim of this study is to use non-invasive spatially resolved cerebral near-infrared spectroscopy (SRS-NIRS) to investigate in vivo beat-to-beat microcirculatory perfusion during AFib and after sinus rhythm (SR) restoration. METHODS AND RESULTS: Cerebral SRS-NIRS with high-frequency sampling (20 Hz) and non-invasive systemic haemodynamic monitoring were recorded before and after elective electrical cardioversion (ECV) for AFib or atrial flutter (AFL). To assess beat-to-beat effects of the rhythm status, the frequency distribution of inter-beat differences in tissue haemoglobin index (THI), a proxy of microcirculatory cerebral perfusion, was compared before and after SR restoration. Fifty-three AFib/AFL patients (mean age 69 ± 8 years, 79% males) were ultimately enrolled. Cardioversion was successful in restoring SR in 51 (96%) patients. In front of a non-significant decrease in arterial blood pressure extreme events between pre- and post-ECV measurements, a significant decrease of both hypoperfusive and hyperperfusive/hypertensive microcirculatory events was observed after SR restoration (P < 0.001 and P = 0.041, respectively). CONCLUSION: The present is the first in vivo demonstration that SR restoration by ECV significantly reduces the burden of extreme single-beat haemodynamic events in cerebral microcirculation. Future studies are needed to assess whether SR maintenance might slow long-term AFib-correlated cognitive decline/dementia.

Stochastic ice stream dynamics.

Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.

Spatial Distribution of the International Food Prices: Unexpected Heterogeneity and Randomness.

Global food prices are typically analysed in a time-series framework. We complement this approach by focusing on the spatial price dispersion of the country-pair bilateral trade in the international food trade network (IFTN), for ten relevant commodities. The main purposes are to verify if the Law of One Price (LOP) holds and to investigate the emergence of randomness in the price-formation mechanism. We distinguish between the "internal" variance, which indicates the magnitude of price discrimination, and the "external" variance, that is a measure of price dispersion. We find that, for some commodities, spatial price dispersion is remarkable and persistent over time (i.e., failure of the LOP) and that there exists a strict correlation between price spikes and peaks in spatial price variability. We test whether the price distribution can be replicated through a stochastic process of extraction. Surprisingly, the actual distribution of prices, for several commodities, is well described by a random distribution. Then, the process of data aggregation is not neutral because the information at the micro-level scale might be lost at the macro-scale, due to the complexity of the IFTN. Finally, we discuss some possible economic explanations of these outcomes and the main methodological, environmental, and policy consequences.

Impact of seasonal forcing on reactive ecological systems.

Our focus is on the short-term dynamics of reactive ecological systems which are stable in the long term. In these systems, perturbations can exhibit significant transient amplifications before asymptotically decaying. This peculiar behavior has attracted increasing attention. However, reactive systems have so far been investigated assuming that external environmental characteristics remain constant, although environmental conditions (e.g., temperature, moisture, water availability, etc.) can undergo substantial changes due to seasonal cycles. In order to fill this gap, we propose applying the adjoint non-modal analysis to study the impact of seasonal variations of environmental conditions on reactive systems. This tool allows the transient dynamics of a perturbation affecting non-autonomous ecological systems to be described. To show the potential of this approach, a seasonally forced prey-predator model with a Holling II type functional response is studied as an exemplifying case. We demonstrate that seasonalities can greatly affect the transient dynamics of the system.

From time-series to complex networks: Application to the cerebrovascular flow patterns in atrial fibrillation.

A network-based approach is presented to investigate the cerebrovascular flow patterns during atrial fibrillation (AF) with respect to normal sinus rhythm (NSR). AF, the most common cardiac arrhythmia with faster and irregular beating, has been recently and independently associated with the increased risk of dementia. However, the underlying hemodynamic mechanisms relating the two pathologies remain mainly undetermined so far; thus, the contribution of modeling and refined statistical tools is valuable. Pressure and flow rate temporal series in NSR and AF are here evaluated along representative cerebral sites (from carotid arteries to capillary brain circulation), exploiting reliable artificially built signals recently obtained from an in silico approach. The complex network analysis evidences, in a synthetic and original way, a dramatic signal variation towards the distal/capillary cerebral regions during AF, which has no counterpart in NSR conditions. At the large artery level, networks obtained from both AF and NSR hemodynamic signals exhibit elongated and chained features, which are typical of pseudo-periodic series. These aspects are almost completely lost towards the microcirculation during AF, where the networks are topologically more circular and present random-like characteristics. As a consequence, all the physiological phenomena at the microcerebral level ruled by periodicity-such as regular perfusion, mean pressure per beat, and average nutrient supply at the cellular level-can be strongly compromised, since the AF hemodynamic signals assume irregular behaviour and random-like features. Through a powerful approach which is complementary to the classical statistical tools, the present findings further strengthen the potential link between AF hemodynamic and cognitive decline.

Indicators of collapse in systems undergoing unsustainable growth.

Unsustainable growth is typical of systems that rely on a finite pool of non-renewable resources that are tapped until they are depleted. The decrease in resource availability eventually leads these systems to a decline. Here we investigate the dynamics of systems that exhibit unsustainable growth and are prone to a collapse to an alternative ("degraded") state. For these systems the possible imminent occurrence of a collapse is difficult to avert because they keep growing as they approach the transition point. It is therefore important to identify some early warning signs that can be used to predict whether the system is approaching a critical and likely irreversible transition to an undesired and degraded state. This study evaluates whether existing theories of precursors of phase transitions based on the critical slowing down phenomenon are applicable as leading indicators of state shift in unsustainable growth dynamics. It is found that such indicators fail to serve as reliable early warning signs of the system's collapse.

Can diversity in root architecture explain plant water use efficiency? A modeling study.

Drought stress is a dominant constraint to crop production. Breeding crops with adapted root systems for effective uptake of water represents a novel strategy to increase crop drought resistance. Due to complex interaction between root traits and high diversity of hydrological conditions, modeling provides important information for trait based selection. In this work we use a root architecture model combined with a soil-hydrological model to analyze whether there is a root system ideotype of general adaptation to drought or water uptake efficiency of root systems is a function of specific hydrological conditions. This was done by modeling transpiration of 48 root architectures in 16 drought scenarios with distinct soil textures, rainfall distributions, and initial soil moisture availability. We find that the efficiency in water uptake of root architecture is strictly dependent on the hydrological scenario. Even dense and deep root systems are not superior in water uptake under all hydrological scenarios. Our results demonstrate that mere architectural description is insufficient to find root systems of optimum functionality. We find that in environments with sufficient rainfall before the growing season, root depth represents the key trait for the exploration of stored water, especially in fine soils. Root density, instead, especially near the soil surface, becomes the most relevant trait for exploiting soil moisture when plant water supply is mainly provided by rainfall events during the root system development. We therefore concluded that trait based root breeding has to consider root systems with specific adaptation to the hydrology of the target environment.

Effect of water table fluctuations on phreatophytic root distribution.

The vertical root distribution of riparian vegetation plays a relevant role in soil water balance, in the partition of water fluxes into evaporation and transpiration, in the biogeochemistry of hyporheic corridors, in river morphodynamics evolution, and in bioengineering applications. The aim of this work is to assess the effect of the stochastic variability of the river level on the root distribution of phreatophytic plants. A function describing the vertical root profile has been analytically obtained by coupling a white shot noise representation of the river level variability to a description of the dynamics of root growth and decay. The root profile depends on easily determined parameters, linked to stream dynamics, vegetation and soil characteristics. The riparian vegetation of a river characterized by a high variability turns out to have a rooting system spread over larger depths, but with shallower mean root depths. In contrast, a lower river variability determines root profiles with higher mean root depths.