Analysis of microvascular blood flow and oxygenation: Discrimination between two haemodynamic steady states using nonlinear measures and multiscale analysis

Causal discovery using compression-complexity measures

Causal inference is one of the most fundamental problems across all domains of science. We address the problem of inferring a causal direction from two observed discrete symbolic sequences X and Y. We present a framework which relies on lossless compressors for inferring context-free grammars (CFGs) from sequence pairs and quantifies the extent to which the grammar inferred from one sequence compresses the other sequence. We infer X causes Y if the grammar inferred from X better compresses Y than in the other direction. To put this notion to practice, we propose three models that use the Compression-Complexity Measures (CCMs) - Lempel-Ziv (LZ) complexity and Effort-To-Compress (ETC) to infer CFGs and discover causal directions without demanding temporal structures. We evaluate these models on synthetic and real-world benchmarks and empirically observe performances competitive with current state-of-the-art methods. Lastly, we present two unique applications of the proposed models for causal inference directly from pairs of genome sequences belonging to the SARS-CoV-2 virus. Using numerous sequences, we show that our models capture causal information exchanged between genome sequence pairs, presenting novel opportunities for addressing key issues in sequence analysis to investigate the evolution of virulence and pathogenicity in future applications.

Effects of Future Information and Trajectory Complexity on Kinematic Signal and Muscle Activation during Visual-Motor Tracking

Visual-motor tracking movement is a common and essential behavior in daily life. However, the contribution of future information to visual-motor tracking performance is not well understood in current research. In this study, the visual-motor tracking performance with and without future-trajectories was compared. Meanwhile, three task demands were designed to investigate their impact. Eighteen healthy young participants were recruited and instructed to track a target on a screen by stretching/flexing their elbow joint. The kinematic signals (elbow joint angle) and surface electromyographic (EMG) signals of biceps and triceps were recorded. The normalized integrated jerk (NIJ) and fuzzy approximate entropy (fApEn) of the joint trajectories, as well as the multiscale fuzzy approximate entropy (MSfApEn) values of the EMG signals, were calculated. Accordingly, the NIJ values with the future-trajectory were significantly lower than those without future-trajectory (p-value < 0.01). The smoother movement with future-trajectories might be related to the increasing reliance of feedforward control. When the task demands increased, the fApEn values of joint trajectories increased significantly, as well as the MSfApEn of EMG signals (p-value < 0.05). These findings enrich our understanding about visual-motor control with future information.

Dysregulated Neurovascular Control Underlies Declining Microvascular Functionality in People With Non-alcoholic Fatty Liver Disease (NAFLD) at Risk of Liver Fibrosis

Background/Aims

Increasing evidence shows that non-alcoholic fatty liver disease (NAFLD) is associated with dysregulation of microvascular perfusion independently of established cardio-metabolic risk factors. We investigated whether hepatic manifestations of NAFLD such as liver fibrosis and liver fat are associated with microvascular hemodynamics through dysregulation of neurovascular control.

Methods

Microvascular dilator (post-occlusive reactive hyperemia) and sympathetically mediated constrictor (deep inspiratory breath-hold) responses were measured at the forearm and finger, respectively, using laser Doppler fluximetry. Non-linear complexity-based analysis was used to assess the information content and variability of the resting blood flux (BF) signals, attributable to oscillatory flow-motion activity, and over multiple sampling frequencies.

Results

Measurements were made in 189 adults (113 men) with NAFLD, with (n = 65) and without (n = 124) type 2 diabetes mellitus (T2DM), age = 50.9 ± 11.7 years (mean ± SD). Microvascular dilator and constrictor capacity were both negatively associated with age (r = −0.178, p = 0.014, and r = −0.201, p = 0.007, respectively) and enhanced liver fibrosis (ELF) score (r = −0.155, p = 0.038 and r = −0.418, p < 0.0001, respectively). There was no association with measures of liver fat, obesity or T2DM. Lempel-Ziv complexity (LZC) and sample entropy (SE) of the BF signal measured at the two skin sites were associated negatively with age (p < 0.01 and p < 0.001) and positively with ELF score (p < 0.05 and p < 0.0001). In individuals with an ELF score ≥7.8 the influence of both neurogenic and respiratory flow-motion activity on LZC was up-rated (p < 0.0001).

Conclusion

Altered microvascular network functionality occurs in adults with NAFLD suggesting a mechanistic role for dysregulated neurovascular control in individuals at risk of severe liver fibrosis.

Race-specific differences in the phase coherence between blood flow and oxygenation: A simultaneous NIRS, white light spectroscopy and LDF study

Race-specific differences in the level of glycated hemoglobin are well known. However, these differences were detected by invasive measurement of mean oxygenation, and their understanding remains far from complete. Given that oxygen is delivered to the cells by hemoglobin through the cardiovascular system, a possible approach is to investigate the phase coherence between blood flow and oxygen transportation. Here we introduce a noninvasive optical method based on simultaneous recordings using NIRS, white light spectroscopy and LDF, combined with wavelet-based phase coherence analysis. Signals were recorded simultaneously for individuals in two groups of healthy subjects, 16 from Sub-Saharan Africa (BA group) and 16 Europeans (CA group). It was found that the power of myogenic oscillations in oxygenated and de-oxygenated hemoglobin is higher in the BA group, but that the phase coherence between blood flow and oxygen saturation, or blood flow and hemoglobin concentrations is higher in the CA group.

Attractor Reconstruction Analysis for Blood Flow Signals

Attractor reconstruction analysis has been previously used to determine changes in the shape and variability of fairly periodic signals such as arterial blood pressure signals and electroencephalogram signals, providing a two-dimensional attractor with features like density and symmetry. Since BF signals are fairly periodic and quasi-stationary, we set out to investigate whether attractor reconstruction method could be applied in signals derived from the microvascular perfusion. We describe the basis and the implementation of attractor reconstruction analysis of the microvascular blood flux (BF) signals recorded from the skin of 15 healthy male volunteers, age 29.2 ± 8.1y (mean ± SD). The efficacy of attractor reconstruction analysis (ARA) as a potential method of identifying changes in the microvascular function is evaluated in two haemodynamic steady states, at 33°C, and during warming at 43°C to generate a local thermal hyperaemia (LTH). Our findings show a significant drop of the maximal density derived from the ARA, during increased flow and that there was good discrimination of the blood flow signals between the two haemodynamic steady states, having good classification accuracy (80%). This study shows that ARA of BF signals can identify different microvascular functional states and thus has a potential for the clinical assessment and diagnosis of pathophysiological condition.

Impact of local thermal stimulation on the correlation between oxygen saturation and speed-resolved blood perfusion

The physiologically important relationship between oxygen saturation and blood flow is not entirely understood, particularly with regard to the multiple velocity components of flow and temperature. While our previous studies used classic laser Doppler flowmetry combined with an enhanced perfusion probe to assess local blood flow following thermal stimulation, oxygen saturation signals were not assessed. Thus, the current study used multiscale entropy (MSE) and multiscale fuzzy entropy (MFE) to measure the complexity of oxygen saturation signals following thermal stimulation in healthy subjects. The results indicate that thermal stimulation increases oxygen saturation and affects the measured signal complexity in a temperature-dependent fashion. Furthermore, stimulus temperature not only affects the correlation between speed-resolved blood perfusion and oxygen saturation, but also the correlation between the complexity area indices (CAI) of the two signals. These results reflect the complexity of local regulation and adaptation processes in response to stimuli at different temperatures.

Multiscale, multidomain analysis of microvascular flow dynamics

NEW FINDINGS

What is the topic of this review? We describe a range of techniques in the time, frequency and information domains and their application alone and together for the analysis of blood flux signals acquired using laser Doppler fluximetry. What advances does it highlight? This review highlights the idea of using quantitative measures in different domains and scales to gain a better mechanistic understanding of the complex behaviours in the microcirculation.

ABSTRACT

To date, time- and frequency-domain metrics of signals acquired through laser Doppler fluximetry have been unable to provide consistent and robust measures of the changes that occur in the microcirculation in healthy individuals at rest or in response to a provocation, or in patient cohorts. Recent studies have shown that in many disease states, such as metabolic and cardiovascular disease, there appears to be a reduction in the adaptive capabilities of the microvascular network and a consequent reduction in physiological information content. Here, we introduce non-linear measures for assessing the information content of fluximetry signals and demonstrate how they can yield deeper understanding of network behaviour. In addition, we show how these methods may be adapted to accommodate the multiple time scales modulating blood flow and how they can be used in combination with time- and frequency-domain metrics to discriminate more effectively between the different mechanistic influences on network properties.

Enhanced flow-motion complexity of skin microvascular perfusion in Sherpas and lowlanders during ascent to high altitude

An increased and more effective microvascular perfusion is postulated to play a key role in the physiological adaptation of Sherpa highlanders to the hypobaric hypoxia encountered at high altitude. To investigate this, we used Lempel-Ziv complexity (LZC) analysis to explore the spatiotemporal dynamics of the variability of the skin microvascular blood flux (BF) signals measured at the forearm and finger, in 32 lowlanders (LL) and 46 Sherpa highlanders (SH) during the Xtreme Everest 2 expedition. Measurements were made at baseline (BL) (LL: London 35 m; SH: Kathmandu 1300 m) and at Everest base camp (LL and SH: EBC 5,300 m). We found that BF signal content increased with ascent to EBC in both SH and LL. At both altitudes, LZC of the BF signals was significantly higher in SH, and was related to local slow-wave flow-motion activity over multiple spatial and temporal scales. In SH, BF LZC was also positively associated with LZC of the simultaneously measured tissue oxygenation signals. These data provide robust mechanistic information of microvascular network functionality and flexibility during hypoxic exposure on ascent to high altitude. They demonstrate the importance of a sustained heterogeneity of network perfusion, associated with local vaso-control mechanisms, to effective tissue oxygenation during hypobaric hypoxia.

Exploring the relationship between the speed-resolved perfusion of blood flux and HRV following different thermal stimulations using MSE and MFE analyses

Our previous study employed the classic laser Doppler flux (LDF) to explore the complexity of local blood flow signals and their relationship with heart rate variability (HRV). However, microcirculation blood flow is composed of different velocity components. To investigate the complexity of local speed-resolved perfusion and HRV following stimulation with different temperatures in healthy subjects, multiscale entropy (MSE) and multiscale fuzzy entropy (MFE) were used to measure the complexity of local speed-resolved perfusion signals. MSE was also used to evaluate the complexity of HRV. The results indicated that thermal stimulation increased all components of local speed-resolved perfusion and that stimulation with different temperatures resulted in different changes in the complexity area index. However, the same stimulation had no effect on the MSE of HRV. Further research showed that 44°C thermal stimulation resulted in a weak correlation between the composite speed-resolved perfusion and the HRV complexity. The current study provides a new approach for studying the relationship between speed-resolved perfusion signals and cardiac function.

Multi-domain analysis of microvascular flow motion dynamics in NAFLD

OBJECTIVE

To determine whether analysis of microvascular network perfusion using complexity-based methods can discriminate between groups of individuals at an increased risk of developing CVD.

METHODS

Data were obtained from laser Doppler recordings of skin blood flux at the forearm in 50 participants with non-alcoholic fatty liver disease grouped for absence (n = 28) or presence (n = 14) of type 2 diabetes and use of calcium channel blocker medication (n = 8). Power spectral density was evaluated and Lempel-Ziv complexity determined to quantify signal information content at single and multiple time-scales to account for the different processes modulating network perfusion.

RESULTS

Complexity was associated with dilatory capacity and respiration and negatively with baseline blood flux and cardiac band power. The relationship between the modulators of flowmotion and complexity of blood flux is shown to change with time-scale improving discrimination between groups. Multiscale Lempel-Ziv achieved best classification accuracy of 86.1%.

CONCLUSIONS

Time and frequency domain measures alone are insufficient to discriminate between groups. As cardiovascular disease risk increases, the degree of complexity of the blood flux signal reduces, indicative of a reduced temporal activity and heterogeneous distribution of blood flow within the microvascular network sampled. Complexity-based methods, particularly multiscale variants, are shown to have good discriminatory capabilities.