Noise suppression in stochastic genetic circuits using PID controllers.

Inside individual cells, protein population counts are subject to molecular noise due to low copy numbers and the inherent probabilistic nature of biochemical processes. We investigate the effectiveness of proportional, integral and derivative (PID) based feedback controllers to suppress protein count fluctuations originating from two noise sources: bursty expression of the protein, and external disturbance in protein synthesis. Designs of biochemical reactions that function as PID controllers are discussed, with particular focus on individual controllers separately, and the corresponding closed-loop system is analyzed for stochastic controller realizations. Our results show that proportional controllers are effective in buffering protein copy number fluctuations from both noise sources, but this noise suppression comes at the cost of reduced static sensitivity of the output to the input signal. In contrast, integral feedback has no effect on the protein noise level from stochastic expression, but significantly minimizes the impact of external disturbances, particularly when the disturbance comes at low frequencies. Counter-intuitively, integral feedback is found to amplify external disturbances at intermediate frequencies. Next, we discuss the design of a coupled feedforward-feedback biochemical circuit that approximately functions as a derivate controller. Analysis using both analytical methods and Monte Carlo simulations reveals that this derivative controller effectively buffers output fluctuations from bursty stochastic expression, while maintaining the static input-output sensitivity of the open-loop system. In summary, this study provides a systematic stochastic analysis of biochemical controllers, and paves the way for their synthetic design and implementation to minimize deleterious fluctuations in gene product levels.

Personalized hypertension management based on serial assessment and telemedicine (PHMA): a cluster randomize controlled trial protocol in Anhui, China.

BACKGROUND: Despite tremendous investment worldwide, hypertension treatment and control rates remain low. The complexity and long-term dynamics of influencing factors make personalized management inevitable and challenging. This protocol describes Personalized Hypertension Management in Anhui, China (PHMA), a project that uses a package of innovative approaches in tailoring interventions to individual patient's dynamic complications and contexts. METHODS/DESIGN: PHMA strives to reduce hypertension harms by eight "objective behaviors" (e.g., self-monitoring and reporting, healthy diet, physical exercise/activities). These objective behaviors are promoted through five intervention measures: support for self- monitoring, supervised machine communications, daily education or reminder messages, weekly blood pressure notification, and quarterly signed feedback. PHMA uses ten categories and over 300 variables in selecting and refining intervention procedures and content for individual patients. Efficacy of the intervention package is evaluated using a cluster randomized controlled trial design involving a total of 60 site communities and 3352 hypertension patients. Primary measure for the evaluation is systolic and diastolic blood pressure; while secondary evaluation measures include quality of life (EQ5D-5L), occurrence of hypertension-related complications (such as cerebral hemorrhage, coronary heart disease, myocardial or cerebral infarction), healthcare utilization and scores of objective behaviors. DISCUSSION: PHMA uses novel, low cost and sustainable approaches to tailor interventions to the dynamic conditions and contexts of individual patients. Unlike contemporary approaches to hypertension management which are mainly population based, each participant patient in PHMA applies a unique intervention package and all messages, feedbacks and other materials sent out to individual patients are different from each other. PHMA is the first project that adopts comprehensive tailoring and if proved effective, it should have important implications for future research, practice and policy-making. Trial registration ISRCTN10999269. July 17, 2020; https://doi.org/10.1186/ISRCTN10999269 .

Assessment of Robustness to Temperature in a Negative Feedback Loop and a Feedforward Loop.

Robustness to temperature variation is an important specification in biomolecular circuit design. While the cancellation of parametric temperature dependencies has been shown to improve the temperature robustness of the period in a synthetic oscillator design, the performance of other biomolecular circuit designs in different temperature conditions is relatively unclear. Using a combination of experimental measurements and mathematical models, we assessed the temperature robustness of two biomolecular circuit motifs-a negative feedback loop and a feedforward loop. We found that the measured responses of both the circuits changed with temperature, both in the amplitude and in the transient response. We also found that, in addition to the cancellation of parametric temperature dependencies, certain parameter regimes could facilitate the temperature robustness of the negative feedback loop, although at a performance cost. We discuss these parameter regimes in the context of the measured data for the negative feedback loop. These results should help develop a framework for assessing and designing temperature robustness in biomolecular circuits.

Thirst as an ingestive behavior: A brief review on physiology and assessment.

BACKGROUND: Thirst is a sensation normally aroused by a lack of water and associated with a desire to drink more fluid. AIM: The aims of this brief review are twofold: (a) to summarize the thirst mechanism in how it is initiated and diminished, and (b) to describe techniques to assess human thirst accurately in a variety of situations. DISCUSSION: Thirst is maintained via a feedback-controlled mechanism, regulated by central and peripheral factors, as well as social and psychological cues. Most studies of thirst have focused on the initiation of water intake and the neural mechanisms responsible for this vital behavior. Less attention has been paid to the stimuli and mechanisms that terminate a bout of drinking and limit fluid ingestion, such as oropharyngeal and gastric signals, coupled with osmotic sensations. Thirst perception is typically assessed by subjective ratings using a variety of questionnaires, rankings, or visual analog scales. However, the appropriate perceptual tool may not always be used for the correct assessment of thirst perception. CONCLUSIONS: In considering the many factors involved in thirst arousal and inhibition, similar questions need to be considered for the correct assessment of this ingestive behavior.

Piecing together the role of a spatial assembly intervention in preschoolers' spatial and mathematics learning: Influences of gesture, spatial language, and socioeconomic status.

Spatial skills are associated with mathematics skills, but it is unclear if spatial training transfers to mathematics skills for preschoolers, especially from underserved communities. The current study tested (a) whether spatial training benefited preschoolers' spatial and mathematics skills, (b) if the type of feedback provided during spatial training differentially influenced children's spatial and mathematics skills, and (c) if the spatial training's effects varied by socioeconomic status (SES). Preschoolers (N = 187) were randomly assigned to either a 'business-as-usual' control or one of three spatial training groups (modeling and feedback [MF]; gesture feedback [GF]; spatial language feedback [SLF]). Three-year-olds were trained to construct puzzles to match a model composed of various geometric shapes. New models were created similar to the 2-dimensional trials of the Test of Spatial Assembly (TOSA). Training was given once per week for 5 weeks. Preschoolers were pretested and posttested on 2D and 3D TOSA trials, spatial vocabulary, shape identification, and 2 mathematics assessments. Results indicate that first, any spatial training improved preschoolers' 2D TOSA performance, although a significant interaction with SES indicated improvement was driven by low-SES children. Furthermore, low-SES children showed greatest gains on the 2D TOSA with MF and GF. Second, MF and GF improved low-SES children's performance on the 3D TOSA. Third, only low-SES children with MF saw improvements in far-transfer to mathematics (Woodcock-Johnson: Applied Problems, but not the Test of Early Mathematical Ability). Results indicate that, especially for low-income learners, spatial training can improve children's early spatial and mathematics skills. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Design of Intermittent Control for Cortisol Secretion Under Time-Varying Demand and Holding Cost Constraints.

OBJECTIVE: We take the release of stress hormone cortisol as a part of an intermittent control feedback system in contrast to the existing continuous models. By modeling cortisol secretion as an impulsive system, we design an impulsive controller as opposed to a continuous controller for adjusting cortisol levels while maintaining the blood cortisol levels within bounds that satisfy circadian demand and cost constraints. METHODS: We develop an analytical approach along with an algorithm for identifying both the timing and amplitude of the control. RESULTS: The model and the algorithm are tested by two examples to illustrate that the proposed approach achieves impulsive control and that the obtained blood cortisol levels render the circadian rhythm and the ultradian rhythm consistent with the known physiology of cortisol secretion. CONCLUSIONS: The approach successfully achieves the desired circadian impulsive control, which has great potential to be used in personalizing the medications in order to control the cortisol levels optimally. SIGNIFICANCE: This type of bioinspired intermittent controllers can be employed for designing noncontinuous controllers in treating Addisonian disease, which is caused by the adrenal deficiency.

Promoter Activity Buffering Reduces the Fitness Cost of Misregulation.

Organisms regulate gene expression through changes in the activity of transcription factors (TFs). In yeast, the response of genes to changes in TF activity is generally assumed to be encoded in the promoter. To directly test this assumption, we chose 42 genes and, for each, replaced the promoter with a synthetic inducible promoter and measured how protein expression changes as a function of TF activity. Most genes exhibited gene-specific TF dose-response curves not due to differences in mRNA stability, translation, or protein stability. Instead, most genes have an intrinsic ability to buffer the effects of promoter activity. This can be encoded in the open reading frame and the 3' end of genes and can be implemented by both autoregulatory feedback and by titration of limiting trans regulators. We show experimentally and computationally that, when misexpression of a gene is deleterious, this buffering insulates cells from fitness defects due to misregulation.

Limits of noise for autoregulated gene expression.

Gene expression is influenced by extrinsic noise (involving a fluctuating environment of cellular processes) and intrinsic noise (referring to fluctuations within a cell under constant environment). We study the standard model of gene expression including an (in-)active gene, mRNA and protein. Gene expression is regulated in the sense that the protein feeds back and either represses (negative feedback) or enhances (positive feedback) its production at the stage of transcription. While it is well-known that negative (positive) feedback reduces (increases) intrinsic noise, we give a precise result on the resulting fluctuations in protein numbers. The technique we use is an extension of the Langevin approximation and is an application of a central limit theorem under stochastic averaging for Markov jump processes (Kang et al. in Ann Appl Probab 24:721-759, 2014). We find that (under our scaling and in equilibrium), negative feedback leads to a reduction in the Fano factor of at most 2, while the noise under positive feedback is potentially unbounded. The fit with simulations is very good and improves on known approximations.

High Cooperativity in Negative Feedback can Amplify Noisy Gene Expression.

Burst-like synthesis of protein is a significant source of cell-to-cell variability in protein levels. Negative feedback is a common example of a regulatory mechanism by which such stochasticity can be controlled. Here we consider a specific kind of negative feedback, which makes bursts smaller in the excess of protein. Increasing the strength of the feedback may lead to dramatically different outcomes depending on a key parameter, the noise load, which is defined as the squared coefficient of variation the protein exhibits in the absence of feedback. Combining stochastic simulation with asymptotic analysis, we identify a critical value of noise load: for noise loads smaller than critical, the coefficient of variation remains bounded with increasing feedback strength; contrastingly, if the noise load is larger than critical, the coefficient of variation diverges to infinity in the limit of ever greater feedback strengths. Interestingly, feedbacks with lower cooperativities have higher critical noise loads, suggesting that they can be preferable for controlling noisy proteins.

Digital signaling network drives the assembly of the AIM2-ASC inflammasome.

The AIM2-ASC inflammasome is a filamentous signaling platform essential for mounting host defense against cytoplasmic dsDNA arising not only from invading pathogens but also from damaged organelles. Currently, the design principles of its underlying signaling network remain poorly understood at the molecular level. We show here that longer dsDNA is more effective in inducing AIM2 assembly, its self-propagation, and downstream ASC polymerization. This observation is related to the increased probability of forming the base of AIM2 filaments, and indicates that the assembly discerns small dsDNA as noise at each signaling step. Filaments assembled by receptor AIM2, downstream ASC, and their joint complex all persist regardless of dsDNA, consequently generating sustained signal amplification and hysteresis. Furthermore, multiple positive feedback loops reinforce the assembly, as AIM2 and ASC filaments accelerate the assembly of nascent AIM2 with or without dsDNA. Together with a quantitative model of the assembly, our results indicate that an ultrasensitive digital circuit drives the assembly of the AIM2-ASC inflammasome.

Gonadotropin-Releasing Hormone (GnRH) Neuron Excitability Is Regulated by Estradiol Feedback and Kisspeptin.

Gonadotropin-releasing hormone (GnRH) neurons produce the central output controlling fertility and are regulated by steroid feedback. A switch from estradiol negative to positive feedback initiates the GnRH surge, ultimately triggering ovulation. This occurs on a daily basis in ovariectomized, estradiol-treated (OVX+E) mice; GnRH neurons are suppressed in the morning and activated in the afternoon. To test the hypotheses that estradiol and time of day signals alter GnRH neuron responsiveness to stimuli, GFP-identified GnRH neurons in brain slices from OVX+E or OVX female mice were recorded during the morning or afternoon. No differences were observed in baseline membrane potential. Current-clamp revealed GnRH neurons fired more action potentials in response to current injection during positive feedback relative to all other groups, which were not different from each other despite reports of differing ionic conductances. Kisspeptin increased GnRH neuron response in cells from OVX and OVX+E mice in the morning but not afternoon. Paradoxically, excitability in kisspeptin knock-out mice was similar to the maximum observed in control mice but was unchanged by time of day or estradiol. A mathematical model applying a Markov Chain Monte Carlo method to estimate probability distributions for estradiol- and time of day-dependent parameters was used to predict intrinsic properties underlying excitability changes. A single identifiable distribution of solutions accounted for similar GnRH neuron excitability in all groups other than positive feedback despite different underlying conductance properties; this was attributable to interdependence of voltage-gated potassium channel properties. In contrast, redundant solutions may explain positive feedback, perhaps indicative of the importance of this state for species survival.SIGNIFICANCE STATEMENT Infertility affects 15%-20% of couples; failure to ovulate is a common cause. Understanding how the brain controls ovulation is critical for new developments in both infertility treatment and contraception. Gonadotropin-releasing hormone (GnRH) neurons are the final common pathway for central neural control of ovulation. We studied how estradiol feedback regulates GnRH excitability, a key determinant of neural firing rate using laboratory and computational approaches. GnRH excitability is upregulated during positive feedback, perhaps driving increased neural firing rate at this time. Kisspeptin increased GnRH excitability and was essential for estradiol regulation of excitability. Modeling predicts that multiple combinations of changes to GnRH intrinsic conductances can produce the firing response in positive feedback, suggesting the brain has many ways to induce ovulation.

Costs of task allocation with local feedback: Effects of colony size and extra workers in social insects and other multi-agent systems.

Adaptive collective systems are common in biology and beyond. Typically, such systems require a task allocation algorithm: a mechanism or rule-set by which individuals select particular roles. Here we study the performance of such task allocation mechanisms measured in terms of the time for individuals to allocate to tasks. We ask: (1) Is task allocation fundamentally difficult, and thus costly? (2) Does the performance of task allocation mechanisms depend on the number of individuals? And (3) what other parameters may affect their efficiency? We use techniques from distributed computing theory to develop a model of a social insect colony, where workers have to be allocated to a set of tasks; however, our model is generalizable to other systems. We show, first, that the ability of workers to quickly assess demand for work in tasks they are not currently engaged in crucially affects whether task allocation is quickly achieved or not. This indicates that in social insect tasks such as thermoregulation, where temperature may provide a global and near instantaneous stimulus to measure the need for cooling, for example, it should be easy to match the number of workers to the need for work. In other tasks, such as nest repair, it may be impossible for workers not directly at the work site to know that this task needs more workers. We argue that this affects whether task allocation mechanisms are under strong selection. Second, we show that colony size does not affect task allocation performance under our assumptions. This implies that when effects of colony size are found, they are not inherent in the process of task allocation itself, but due to processes not modeled here, such as higher variation in task demand for smaller colonies, benefits of specialized workers, or constant overhead costs. Third, we show that the ratio of the number of available workers to the workload crucially affects performance. Thus, workers in excess of those needed to complete all tasks improve task allocation performance. This provides a potential explanation for the phenomenon that social insect colonies commonly contain inactive workers: these may be a 'surplus' set of workers that improves colony function by speeding up optimal allocation of workers to tasks. Overall our study shows how limitations at the individual level can affect group level outcomes, and suggests new hypotheses that can be explored empirically.

Gene length as a regulator for ribosome recruitment and protein synthesis: theoretical insights.

Protein synthesis rates are determined, at the translational level, by properties of the transcript's sequence. The efficiency of an mRNA can be tuned by varying the ribosome binding sites controlling the recruitment of the ribosomes, or the codon usage establishing the speed of protein elongation. In this work we propose transcript length as a further key determinant of translation efficiency. Based on a physical model that considers the kinetics of ribosomes advancing on the mRNA and diffusing in its surrounding, as well as mRNA circularisation and ribosome drop-off, we explain how the transcript length may play a central role in establishing ribosome recruitment and the overall translation rate of an mRNA. According to our results, the proximity of the 3' end to the ribosomal recruitment site of the mRNA could induce a feedback in the translation process that would favour the recycling of ribosomes. We also demonstrate how this process may be involved in shaping the experimental ribosome density-gene length dependence. Finally, we argue that cells could exploit this mechanism to adjust and balance the usage of its ribosomal resources.

Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation.

BACKGROUND: Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters identifying the underlying systems. METHODS: Standing balance behaviour of 20 healthy young participants was measured using continuous rotations of the support surface (SS). The dynamic balance behaviour obtained with CLSIT was expressed by sensitivity functions of the ankle torque, body sway and muscle activation of the lower legs to the SS rotation. Balance control models, 1) without activation dynamics, 2) with activation dynamics and 3) with activation dynamics and acceleration feedback, were fitted on the data of all possible combinations of the 3 sensitivity functions. The reliability of the estimated model parameters was represented by the mean relative standard errors of the mean (mSEM) of the estimated parameters, expressed for the basic parameters, the activation dynamics parameters and the acceleration feedback parameter. To investigate the accuracy, a model validation study was performed using simulated data obtained with a comprehensive balance control model. The accuracy of the estimated model parameters was described by the mean relative difference (mDIFF) between the estimated parameters and original parameters. RESULTS: The experimental data showed a low mSEM of the basic parameters, activation dynamics parameters and acceleration feedback parameter by adding muscle activation in combination with activation dynamics and acceleration feedback to the fitted model. From the simulated data, the mDIFF of the basic parameters varied from 22.2-22.4% when estimated using the torque and body sway sensitivity functions. Adding the activation dynamics, acceleration feedback and muscle activation improved mDIFF to 13.1-15.1%. CONCLUSIONS: Adding the muscle activation in combination with the activation dynamics and acceleration feedback to CLSIT improves the accuracy and reliability of the estimated parameters and gives the possibility to separate the neural time delay, electromechanical delay and the intrinsic and reflexive dynamics. To diagnose impaired balance more specifically, it is recommended to add electromyography (EMG) to body sway (with or without torque) measurements in the assessment of the underlying systems.

How likely are oscillations in a genetic feedback loop with delay?

Some genetic control networks display temporal oscillations as a result of delays in their homeostatic control. A relevant question about these systems is whether the oscillating regime is a rare feature, or it corresponds to a sizeable volume of the space of parameters. The answer is not trivial mainly due to the large number of parameters controlling the rate equations which describe the network. We have developed an efficient sampling scheme of the parameter space, based on a Monte Carlo algorithm, and applied it to a two-node system with delay, characterised by a 8-dimension parameter space. The result is that the volume fraction of the parameter space associated with oscillations is small but not negligible, and it is weakly dependent on the duration of the delay. The most critical parameter to control oscillations is the coupling production rates, which must have opposite sign, giving rise to a negative feedback loop. The oscillating regions are connected except along the equilibrium constants between the two species, not allowing neutral evolution along this parameter.

Applied Interventions in the Prevention and Treatment of Obesity Through the Research of Professor Jane Wardle.

PURPOSE OF REVIEW: Obesity presents a challenge for practitioners, policy makers, researchers and for those with obesity themselves. This review focuses on psychological approaches to its management and prevention in children and adults. RECENT FINDINGS: Through exploring the work of the late Professor Jane Wardle, we look at the earliest behavioural treatment approaches and how psychological theory has been used to develop more contemporary approaches, for example incorporating genetic feedback and habit formation theory into interventions. We also explore how Jane has challenged thinking about the causal pathways of obesity in relation to eating behaviour. Beyond academic work, Jane was an advocate of developing interventions which had real-world applications. Therefore, we discuss how she not only developed new interventions but also made these widely available and the charity that she established.

A stochastic analysis of autoregulation of gene expression.

This paper analyzes, in the context of a prokaryotic cell, the stochastic variability of the number of proteins when there is a control of gene expression by an autoregulation scheme. The goal of this work is to estimate the efficiency of the regulation to limit the fluctuations of the number of copies of a given protein. The autoregulation considered in this paper relies mainly on a negative feedback: the proteins are repressors of their own gene expression. The efficiency of a production process without feedback control is compared to a production process with an autoregulation of the gene expression assuming that both of them produce the same average number of proteins. The main characteristic used for the comparison is the standard deviation of the number of proteins at equilibrium. With a Markovian representation and a simple model of repression, we prove that, under a scaling regime, the repression mechanism follows a Hill repression scheme with an hyperbolic control. An explicit asymptotic expression of the variance of the number of proteins under this regulation mechanism is obtained. Simulations are used to study other aspects of autoregulation such as the rate of convergence to equilibrium of the production process and the case where the control of the production process of proteins is achieved via the inhibition of mRNAs.

The Neural Mechanism Exploration of Adaptive Motor Control: Dynamical Economic Cell Allocation in the Primary Motor Cortex.

Adaptive flexibility is of significance for the smooth and efficient movements in goal attainment. However, the underlying work mechanism of the cerebral cortex in adaptive motor control still remains unclear. How does the cerebral cortex organize and coordinate the activity of a large population of cells in the implementation of various motor strategies? To explore this issue, single-unit activities from the M1 region and kinematic data were recorded simultaneously in monkeys performing 3D reach-to-grasp tasks with different perturbations. Varying motor control strategies were employed and achieved in different perturbed tasks, via the dynamic allocation of cells to modulate specific movement parameters. An economic principle was proposed for the first time to describe a basic rule for cell allocation in the primary motor cortex. This principle, defined as the Dynamic Economic Cell Allocation Mechanism (DECAM), guarantees benefit maximization in cell allocation under limited neuronal resources, and avoids committing resources to uneconomic investments for unreliable factors with no or little revenue. That is to say, the cells recruited are always preferentially allocated to those factors with reliable return; otherwise, the cells are dispatched to respond to other factors about task. The findings of this study might partially reveal the working mechanisms underlying the role of the cerebral cortex in adaptive motor control, wherein is also of significance for the design of future intelligent brain-machine interfaces and rehabilitation device.

Functional Assessment of a Myoelectric Postural Controller and Multi-Functional Prosthetic Hand by Persons With Trans-Radial Limb Loss.

The functional assessment of myoelectric control algorithms by persons with amputation promotes the overarching goal of the field of prosthetic limb design: to replace what was lost. However, many studies use experimental paradigms with virtual interfaces and able-bodied subjects that do not capture the challenges of a clinical implementation with an amputee population. A myoelectric control system must be robust to variable physiology, loading effects of the prosthesis on the limb, and limb position effects during dynamic tasks. Here persons with transradial limb loss performed activities of daily living using a postural controller and multi-functional prosthetic hand in order to verify that the postural controller was robust to these clinical challenges. The Southampton Hand Assessment Procedure was performed by persons with limb loss and able-bodied subjects. The results indicate that persons with limb loss and able-limbed subjects achieved the same performance and therefore that the clinical challenges were overcome. Persons with limb loss achieved 55% of physiological hand function on average. Also, the postural controller is compared to other state of the art myoelectric controllers and prosthetic hands previously tested. This work confirms that the postural controller is potentially a clinically-viable method to control myoelectric multi-functional prosthetic hands.

Are Nonlinear Model-Free Conditional Entropy Approaches for the Assessment of Cardiac Control Complexity Superior to the Linear Model-Based One?

OBJECTIVE: We test the hypothesis that the linear model-based (MB) approach for the estimation of conditional entropy (CE) can be utilized to assess the complexity of the cardiac control in healthy individuals. METHODS: An MB estimate of CE was tested in an experimental protocol (i.e., the graded head-up tilt) known to produce a gradual decrease of cardiac control complexity as a result of the progressive vagal withdrawal and concomitant sympathetic activation. The MB approach was compared with traditionally exploited nonlinear model-free (MF) techniques such as corrected approximate entropy, sample entropy, corrected CE, two k -nearest-neighbor CE procedures and permutation CE. Electrocardiogram was recorded in 17 healthy subjects at rest in supine position and during head-up tilt with table angles of 15°, 30°, 45°, 60°, and 75°. Heart period (HP) was derived as the temporal distance between two consecutive R-wave peaks and analysis was carried out over stationary sequences of 256 successive HPs. RESULTS: The performance of the MB method in following the progressive decrease of HP complexity with tilt table angles was in line with those of MF approaches and the MB index was remarkably correlated with the MF ones. CONCLUSION: The MB approach can be utilized to monitor the changes of the complexity of the cardiac control, thus speeding up dramatically the CE calculation. SIGNIFICANCE: The remarkable performance of the MB approach challenges the notion, generally assumed in cardiac control complexity analysis based on CE, about the need of MF techniques and could allow real-time applications.