Complexity and emergent phenomena

Chronic pain as an emergent property of a complex system and the potential roles of psychedelic therapies

Despite research advances and urgent calls by national and global health organizations, clinical outcomes for millions of people suffering with chronic pain remain poor. We suggest bringing the lens of complexity science to this problem, conceptualizing chronic pain as an emergent property of a complex biopsychosocial system. We frame pain-related physiology, neuroscience, developmental psychology, learning, and epigenetics as components and mini-systems that interact together and with changing socioenvironmental conditions, as an overarching complex system that gives rise to the emergent phenomenon of chronic pain. We postulate that the behavior of complex systems may help to explain persistence of chronic pain despite current treatments. From this perspective, chronic pain may benefit from therapies that can be both disruptive and adaptive at higher orders within the complex system. We explore psychedelic-assisted therapies and how these may overlap with and complement mindfulness-based approaches to this end. Both mindfulness and psychedelic therapies have been shown to have transdiagnostic value, due in part to disruptive effects on rigid cognitive, emotional, and behavioral patterns as well their ability to promote neuroplasticity. Psychedelic therapies may hold unique promise for the management of chronic pain.

The protective effect of inhaled corticosteroid on lung inflammation and breathing pattern complexity in a rat model of asthma

Asthma is a heterogeneous disease in which the complexity of the breathing pattern reduces as the severity of the disease increases. Since the pathophysiological basis of reduced breathing pattern complexity in asthma is unclear, in this study, we investigated the effect of reducing inflammation using an inhaled corticosteroid (fluticasone propionate) on the breathing pattern of a rat model of asthma. Detrended fluctuation analysis, sample entropy, and cross-sample entropy analysis of both inter-breath interval and respiratory volume time series showed that early treatment with inhaled corticosteroids not only diminishes lung inflammation and airway hyper-responsiveness, but also has a protective effect against the reduction of breathing pattern complexity due to asthma. However, late treatment had a partial effect on asthma-induced respiratory pattern changes. Since inflammation is a key factor in shifting breathing dynamics away from normal fluctuations, these findings further emphasize the importance of early treatment of asthma with corticosteroids.

Assessment of Heterogeneity in Lung Structure and Function During Mechanical Ventilation: A Review of Methodologies

The mammalian lung is characterized by heterogeneity in both its structure and function, by incorporating an asymmetric branching airway tree optimized for maintenance of efficient ventilation, perfusion, and gas exchange. Despite potential benefits of naturally occurring heterogeneity in the lungs, there may also be detrimental effects arising from pathologic processes, which may result in deficiencies in gas transport and exchange. Regardless of etiology, pathologic heterogeneity results in the maldistribution of regional ventilation and perfusion, impairments in gas exchange, and increased work of breathing. In extreme situations, heterogeneity may result in respiratory failure, necessitating support with a mechanical ventilator. This review will present a summary of measurement techniques for assessing and quantifying heterogeneity in respiratory system structure and function during mechanical ventilation. These methods have been grouped according to four broad categories: (1) inverse modeling of heterogeneous mechanical function; (2) capnography and washout techniques to measure heterogeneity of gas transport; (3) measurements of heterogeneous deformation on the surface of the lung; and finally (4) imaging techniques used to observe spatially-distributed ventilation or regional deformation. Each technique varies with regard to spatial and temporal resolution, degrees of invasiveness, risks posed to patients, as well as suitability for clinical implementation. Nonetheless, each technique provides a unique perspective on the manifestations and consequences of mechanical heterogeneity in the diseased lung.

Temporal variations in the pattern of breathing: techniques, sources, and applications to translational sciences

The breathing process possesses a complex variability caused in part by the respiratory central pattern generator in the brainstem; however, it also arises from chemical and mechanical feedback control loops, network reorganization and network sharing with nonrespiratory motor acts, as well as inputs from cortical and subcortical systems. The notion that respiratory fluctuations contain hidden information has prompted scientists to decipher respiratory signals to better understand the fundamental mechanisms of respiratory pattern generation, interactions with emotion, influences on the cortical neuronal networks associated with cognition, and changes in variability in healthy and disease-carrying individuals. Respiration can be used to express and control emotion. Furthermore, respiration appears to organize brain-wide network oscillations via cross-frequency coupling, optimizing cognitive performance. With the aid of information theory-based techniques and machine learning, the hidden information can be translated into a form usable in clinical practice for diagnosis, emotion recognition, and mental conditioning.

Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease

Chest CT is often used for localizing and quantitating pathologies associated with chronic obstructive pulmonary disease (COPD). While simple measurements of areas and volumes of emphysema and airway structure are common, these methods do not capture the structural complexity of the COPD lung. Since the concept of fractals has been successfully applied to evaluate complexity of the lung, this review is aimed at describing the fractal properties of airway disease, emphysema, and vascular abnormalities in COPD. An object forms a fractal if it exhibits the property of self-similarity at different length scales of evaluations. This fractal property is governed by power-law functions characterized by the fractal dimension (FD). Power-laws can also manifest in other statistical descriptors of structure such as the size distribution of emphysema clusters characterized by the power-law exponent D. Although D is not the same as FD of emphysematous clusters, it is a useful index to characterize the spatial pattern of disease progression and predict clinical outcomes in patients with COPD. The FD of the airway tree shape and the D of the size distribution of airway branches have been proposed indexes of structural assessment and clinical predictions. Simulations are also useful to understand the mechanism of disease progression. Therefore, the power-law and fractal analysis of the parenchyma and airways, especially when combined with computer simulations, could lead to a better understanding of the structural alterations during the progression of COPD and help identify subjects at a high risk of severe COPD.

Development and validation of a sample entropy-based method to identify complex patient-ventilator interactions during mechanical ventilation

Patient-ventilator asynchronies can be detected by close monitoring of ventilator screens by clinicians or through automated algorithms. However, detecting complex patient-ventilator interactions (CP-VI), consisting of changes in the respiratory rate and/or clusters of asynchronies, is a challenge. Sample Entropy (SE) of airway flow (SE-Flow) and airway pressure (SE-Paw) waveforms obtained from 27 critically ill patients was used to develop and validate an automated algorithm for detecting CP-VI. The algorithm's performance was compared versus the gold standard (the ventilator's waveform recordings for CP-VI were scored visually by three experts; Fleiss' kappa = 0.90 (0.87-0.93)). A repeated holdout cross-validation procedure using the Matthews correlation coefficient (MCC) as a measure of effectiveness was used for optimization of different combinations of SE settings (embedding dimension, m, and tolerance value, r), derived SE features (mean and maximum values), and the thresholds of change (Th) from patient's own baseline SE value. The most accurate results were obtained using the maximum values of SE-Flow (m = 2, r = 0.2, Th = 25%) and SE-Paw (m = 4, r = 0.2, Th = 30%) which report MCCs of 0.85 (0.78-0.86) and 0.78 (0.78-0.85), and accuracies of 0.93 (0.89-0.93) and 0.89 (0.89-0.93), respectively. This approach promises an improvement in the accurate detection of CP-VI, and future study of their clinical implications.

Are Synapse-Like Structures a Possible Way for Crosstalk of Cancer with Its Microenvironment?

The failure of therapies directed at targets within cancer cells highlight the necessity for a paradigm change in cancer therapy. The attention of researchers has shifted towards the disruption of cancer cell interactions with the tumor microenvironment. A typical example of such a disruption is the immune checkpoint cancer therapy that disrupts interactions between the immune and the cancer cells. The interaction of cancer antigens with T cells occurs in the immunological synapses. This is characterized by several special features, i.e., the proximity of the immune cells and their target cells, strong intercellular adhesion, and secretion of signaling cytokines into the intercellular cleft. Earlier, we hypothesized that the cancer-associated fibroblasts interacting with cancer cells through a synapse-like adhesion might play an important role in cancer tumors. Studies of the interactions between cancer cells and cancer-associated fibroblasts showed that their clusterization on the membrane surface determined their strength and specificity. The hundreds of interacting pairs are involved in the binding that may indicate the formation of synapse-like structures. These interactions may be responsible for successful metastasis of cancer cells, and their identification and disruption may open new therapeutic possibilities.

Entropy Analysis for the Evaluation of Respiratory Changes Due to Asbestos Exposure and Associated Smoking

Breathing is a complex rhythmic motor act, which is created by integrating different inputs to the respiratory centres. Analysing nonlinear fluctuations in breathing may provide clinically relevant information in patients with complex illnesses, such as asbestosis. We evaluated the effect of exposition to asbestos on the complexity of the respiratory system by investigating the respiratory impedance sample entropy (SampEnZrs) and recurrence period density entropy (RPDEnZrs). Similar analyses were performed by evaluating the airflow pattern sample entropy (SampEnV') and recurrence period density entropy (RPDEnV'). Groups of 34 controls and 34 asbestos-exposed patients were evaluated in the respiratory impedance entropy analysis, while groups of 34 controls and 30 asbestos-exposed patients were investigated in the analysis of airflow entropy. Asbestos exposition introduced a significant reduction of RPDEnV' in non-smoker patients (p < 0.0004), which suggests that the airflow pattern becomes less complex in these patients. Smoker patients also presented a reduction in RPDEnV' (p < 0.05). These finding are consistent with the reduction in respiratory system adaptability to daily life activities observed in these patients. It was observed a significant reduction in SampEnV' in smoker patients in comparison with non-smokers (p < 0.02). Diagnostic accuracy evaluations in the whole group of patients (including non-smokers and smokers) indicated that RPDEnV' might be useful in the diagnosis of respiratory abnormalities in asbestos-exposed patients, showing an accuracy of 72.0%. In specific groups of non-smokers, RPDEnV' also presented adequate accuracy (79.0%), while in smoker patients, SampEnV' and RPDEnV' presented adequate accuracy (70.7% and 70.2%, respectively). Taken together, these results suggest that entropy analysis may provide an early and sensitive functional indicator of interstitial asbestosis.

Unsolvable Problems of Biology: It Is Impossible to Create Two Identical Organisms, to Defeat Cancer, or to Map Organisms onto Their Genomes

The review is devoted to unsolvable problems of biology. 1) Problems unsolvable due to stochastic mutations occurring during DNA replication that make it impossible to create two identical organisms or even two identical complex cells (Sverdlov, E. D. (2009) Biochemistry (Moscow), 74, 939-944) and to "defeat" cancer. 2) Problems unsolvable due to multiple interactions in complex systems leading to the appearance of unpredictable emergent properties that prevent establishment of unambiguous relationships between the genetic architecture and phenotypic manifestation of the genome and make impossible to predict with certainty responses of the organism, its parts, or pathological processes to external factors. 3) Problems unsolvable because of the uncertainty principle and observer effect in biology, due to which it is impossible to obtain adequate information about cells in their tissue microenvironment by isolating and analyzing individual cells. In particular, we cannot draw conclusions on the properties of stem cells in their niches based on the properties of stem cell cultures. A strategy is proposed for constructing the pattern most closely approximated to the relationship of genotypes with their phenotypes by designing networks of intermediate phenotypes (endophenotypes).

Effect of Rho-kinase inhibition on complexity of breathing pattern in a guinea pig model of asthma

Asthma represents an episodic and fluctuating behavior characterized with decreased complexity of respiratory dynamics. Several evidence indicate that asthma severity or control is associated with alteration in variability of lung function. The pathophysiological basis of alteration in complexity of breathing pattern in asthma has remained poorly understood. Regarding the point that Rho-kinase is involved in pathophysiology of asthma, in present study we investigated the effect of Rho-kinase inhibition on complexity of respiratory dynamics in a guinea pig model of asthma. Male Dunkin Hartley guinea pigs were exposed to 12 series of inhalations with ovalbumin or saline. Animals were treated by the Rho-kinase inhibitor Y-27632 (1mM aerosols) prior to each allergen challenge. We recorded respiration of conscious animals using whole-body plethysmography. Exposure to ovalbumin induced lung inflammation, airway hyperresponsiveness and remodeling including goblet cell hyperplasia, increase in the thickness of airways smooth muscles and subepithelial collagen deposition. Complexity analysis of respiratory dynamics revealed a dramatic decrease in irregularity of respiratory rhythm representing less complexity in asthmatic guinea pigs. Inhibition of Rho-kinase reduced the airway remodeling and hyperreponsiveness, but had no significant effect on lung inflammation and complexity of respiratory dynamics in asthmatic animals. It seems that airway hyperresponsiveness and remodeling do not significantly affect the complexity of respiratory dynamics. Our results suggest that inflammation might be the probable cause of shift in the respiratory dynamics away from the normal fluctuation in asthma.

Systems Biology and Clinical Practice in Respiratory Medicine. The Twain Shall Meet

Respiratory diseases are highly complex, being driven by host-environment interactions and manifested by inflammatory, structural, and functional abnormalities that vary over time. Traditional reductionist approaches have contributed vastly to our knowledge of biological systems in health and disease to date; however, they are insufficient to provide an understanding of the behavior of the system as a whole. In this Pulmonary Perspective, we discuss systems biology approaches, especially but not limited to the study of the lung as a complex system. Such integrative approaches take into account the large number of dynamic subunits and their interactions found in biological systems. Borrowing methods from physics and mathematics, it is possible to study the collective behavior of these systems over time and in a multidimensional manner. We first examine the physiological basis for complexity in the respiratory system and its implications for disease. We then expand on the potential applications of systems biology methods to study complex systems, within the context of diagnosis and monitoring of respiratory diseases including asthma, chronic obstructive pulmonary disease (COPD), and critical illness. We summarize the significant advances made in recent years using systems approaches for disease phenotyping, applied to data ranging from the molecular to clinical level, obtained from large-scale asthma and COPD networks. We describe new studies using temporal complexity patterns to characterize asthma and COPD and predict exacerbations as well as predict adverse outcomes in critical care. We highlight new methods that are emerging with this approach and discuss remaining questions that merit greater attention in the field.

Multidimensional Complexity of Cancer. Simple Solutions Are Needed

Cancer is a complex system. Tumor complexity is determined not only by genetic and epigenetic heterogeneity, but also by a huge number of interactions between cancer and normal cells. The heterogeneity and complexity of a tumor causes failure of molecular targeting therapy as a tool for fighting cancer. This review considers the concepts of malignant tumors as organisms that have common characteristics despite all heterogeneity. This leads to the idea that one of the most promising strategies for fighting cancer is the use of the patient's immune system.

Entropy Production and the Pressure-Volume Curve of the Lung

We investigate analytically the production of entropy during a breathing cycle in healthy and diseased lungs. First, we calculate entropy production in healthy lungs by applying the laws of thermodynamics to the well-known transpulmonary pressure–volume (P–V) curves of the lung under the assumption that lung tissue behaves as an entropic spring similar to rubber. The bulk modulus, B, of the lung is also derived from these calculations. Second, we extend this approach to elastic recoil disorders of the lung such as occur in pulmonary fibrosis and emphysema. These diseases are characterized by particular alterations in the P–V relationship. For example, in fibrotic lungs B increases monotonically with disease progression, while in emphysema the opposite occurs. These diseases can thus be mimicked simply by making appropriate adjustments to the parameters of the P–V curve. Using Clausius's formalism, we show that entropy production, ΔS, is related to the hysteresis area, ΔA, enclosed by the P–V curve during a breathing cycle, namely, ΔS=ΔA∕T, where T is the body temperature. Although ΔA is highly dependent on the disease, such formula applies to healthy as well as diseased lungs, regardless of the disease stage. Finally, we use an ansatz to predict analytically the entropy produced by the fibrotic and emphysematous lungs.

Classification of Asthma Based on Nonlinear Analysis of Breathing Pattern

Normal human breathing exhibits complex variability in both respiratory rhythm and volume. Analyzing such nonlinear fluctuations may provide clinically relevant information in patients with complex illnesses such as asthma. We compared the cycle-by-cycle fluctuations of inter-breath interval (IBI) and lung volume (LV) among healthy volunteers and patients with various types of asthma. Continuous respiratory datasets were collected from forty age-matched men including 10 healthy volunteers, 10 patients with controlled atopic asthma, 10 patients with uncontrolled atopic asthma, and 10 patients with uncontrolled non-atopic asthma during 60 min spontaneous breathing. Complexity of breathing pattern was quantified by calculating detrended fluctuation analysis, largest Lyapunov exponents, sample entropy, and cross-sample entropy. The IBI as well as LV fluctuations showed decreased long-range correlation, increased regularity and reduced sensitivity to initial conditions in patients with asthma, particularly in uncontrolled state. Our results also showed a strong synchronization between the IBI and LV in patients with uncontrolled asthma. Receiver operating characteristic (ROC) curve analysis showed that nonlinear analysis of breathing pattern has a diagnostic value in asthma and can be used in differentiating uncontrolled from controlled and non-atopic from atopic asthma. We suggest that complexity analysis of breathing dynamics may represent a novel physiologic marker to facilitate diagnosis and management of patients with asthma. However, future studies are needed to increase the validity of the study and to improve these novel methods for better patient management.

Facing the challenge of mammalian neural microcircuits: taking a few breaths may help

Breathing in mammals is a seemingly straightforward behaviour controlled by the brain. A brainstem nucleus called the preBötzinger Complex sits at the core of the neural circuit generating respiratory rhythm. Despite the discovery of this microcircuit almost 25 years ago, the mechanisms controlling breathing remain elusive. Given the apparent simplicity and well-defined nature of regulatory breathing behaviour, the identification of much of the circuitry, and the ability to study breathing in vitro as well as in vivo, many neuroscientists and physiologists are surprised that respiratory rhythm generation is still not well understood. Our view is that conventional rhythmogenic mechanisms involving pacemakers, inhibition or bursting are problematic and that simplifying assumptions commonly made for many vertebrate neural circuits ignore consequential detail. We propose that novel emergent mechanisms govern the generation of respiratory rhythm. That a mammalian function as basic as rhythm generation arises from complex and dynamic molecular, synaptic and neuronal interactions within a diverse neural microcircuit highlights the challenges in understanding neural control of mammalian behaviours, many (considerably) more elaborate than breathing. We suggest that the neural circuit controlling breathing is inimitably tractable and may inspire general strategies for elucidating other neural microcircuits.

Airflow pattern complexity during resting breathing in patients with COPD: effect of airway obstruction

We investigated the influence of airway obstruction in the complexity of the airflow pattern in COPD and its use as a marker of disease activity. The sample entropy (SampEnV') and the variability (SDV') of the airflow pattern were measured in a group of 88 subjects with various levels of airway obstruction. Airway obstruction resulted in a reduction in the SampEnV' (p<0.0001) that was significantly correlated with spirometric indices of airway obstruction (R=0.50, p<0.001). The early adverse effects in mild airway obstruction were detected by the SampEnV' with an accuracy of 84%. SDV' increased with airway obstruction (p<0.002). We conclude that (1) the airflow patterns in COPD exhibit reduced complexity compared with healthy subjects; (2) this reduction in complexity is proportional to airway obstruction; and (3) the evaluation of SampEnV' may provide novel respiratory biomarkers suitable to facilitate the diagnosis of respiratory abnormalities in COPD.

Fluctuation analysis of respiratory impedance waveform in asthmatic patients: effect of airway obstruction

Fluctuation analysis has great potential to contribute to pulmonary clinical science and practice. We evaluated the relationship between asthma and the respiratory impedance recurrence period density entropy (RPDEnZrs) and the variability (SDZrs). A non-invasive and simple protocol for assessing respiratory mechanics during spontaneous breathing was used in a group of 74 subjects with various levels of airway obstruction. Airway obstruction resulted in a reduction in the RPDEnZrs that was significantly correlated with both spirometric indices of airway obstruction (R = 0.48, p < 0.0001) and mean respiratory impedance (R = -0.83, p < 0.0001). These results suggest that the impedance pattern becomes less complex in asthmatic patients, which may explain the reduction in respiratory systems' adaptability to daily life activities. Preliminary evaluations indicate that RPDEnZrs may contribute to the asthma diagnosis, presenting accuracies of 82 and 87 % in patients with moderate and severe airway obstruction, respectively. On the other hand, SDZrs increased with obstruction (p < 0.0001) and was inversely correlated with spirometric indices of obstruction (R = -0.42, p = 0.0003) and directly associated with mean impedance (R = 0.88, p < 0.0001). This analysis contributes to elucidate previous studies and identified respiratory changes in patients with moderate and severe obstruction with an adequate accuracy (85 and 87 %, respectively).