Spike propagation mapping reveals effective connectivity and predicts surgical outcome in epilepsy.

Neurosurgical intervention is the best available treatment for selected patients with drug resistant epilepsy. For these patients, surgical planning requires biomarkers that delineate the epileptogenic zone, the brain area that is indispensable for the generation of seizures. Interictal spikes recorded with electrophysiological techniques are considered key biomarkers of epilepsy. Yet, they lack specificity, mostly because they propagate across brain areas forming networks. Understanding the relationship between interictal spike propagation and functional connections among the involved brain areas may help develop novel biomarkers that can delineate the epileptogenic zone with high precision. Here, we reveal the relationship between spike propagation and effective connectivity among onset and areas of spread and assess the prognostic value of resecting these areas. We analysed intracranial EEG data from 43 children with drug resistant epilepsy who underwent invasive monitoring for neurosurgical planning. Using electric source imaging, we mapped spike propagation in the source domain and identified three zones: onset, early-spread and late-spread. For each zone, we calculated the overlap and distance from surgical resection. We then estimated a virtual sensor for each zone and the direction of information flow among them via Granger causality. Finally, we compared the prognostic value of resecting these zones, the clinically-defined seizure onset zone and the spike onset on intracranial EEG channels by estimating their overlap with resection. We observed a spike propagation in source space for 37 patients with a median duration of 95 ms (interquartile range: 34-206), a spatial displacement of 14 cm (7.5-22 cm) and a velocity of 0.5 m/s (0.3-0.8 m/s). In patients with good surgical outcome (25 patients, Engel I), the onset had higher overlap with resection [96% (40-100%)] than early-spread [86% (34-100%), P = 0.01] and late-spread [59% (12-100%), P = 0.002], and it was also closer to resection than late-spread [5 mm versus 9 mm, P = 0.007]. We found an information flow from onset to early-spread in 66% of patients with good outcomes, and from early-spread to onset in 50% of patients with poor outcome. Finally, resection of spike onset, but not area of spike spread or the seizure onset zone, predicted outcome with positive predictive value of 79% and negative predictive value of 56% (P = 0.04). Spatiotemporal mapping of spike propagation reveals information flow from onset to areas of spread in epilepsy brain. Surgical resection of the spike onset disrupts the epileptogenic network and may render patients with drug resistant epilepsy seizure-free without having to wait for a seizure to occur during intracranial monitoring.

Role of inhibin B in detecting recurrence of granulosa cell tumors of the ovary in postmenopausal patients.

INTRODUCTION: Several biomarkers have been proposed for the detection of recurrences in adult-type granulosa cell tumors of the ovary. Here we validate the value of inhibin B in detecting recurrences and investigate its role in guiding follow-up examinations and treatment strategies in postmenopausal patients with ovarian adult-type granulosa cell tumors. METHODS: Data from 140 patients with a diagnosis of adult-type granulosa cell tumor of the ovary referred to the European Institute of Oncology of Milan from January 1996 to March 2016 were retrospectively collected. Among these, we selected data from 47 postmenopausal women for whom serial inhibin B measurements and related imaging examinations were performed according to the follow-up program, with a total of 315 serum inhibin B samples, together with the corresponding clinical examination, and 180 imaging examinations, confirming the presence or absence of macroscopic disease. RESULTS: At a cut-off of 7 pg/mL, inhibin B levels were significantly correlated with the presence/absence of disease (p<0.01), with a sensitivity of 98.8% (95% confidence interval (CI) 95.8% to 99.9%) and a specificity of 88.9% (95% CI 82.6% to 93.5%). Further, inhibin B was positively correlated with the size of the lesion, and levels were significantly higher in patients with larger lesions also at a cut-off size of 3 cm (total diameter). Logistic regression showed that 15.6 pg/mL, 44.6 pg/mL, and 73.6 pg/mL inhibin B corresponded to 25%, 50%, and 75% probability of having an abnormal computer tomography scan, respectively. CONCLUSIONS: Our results confirmed that inhibin B is a sensitive and specific marker for adult-type granulosa cell tumors of the ovary that may be used during follow-up for detection of recurrences. Moreover, it could guide clinicians in the decision regarding when to perform imaging, avoiding redundant interventional tests in the absence of clinical suspicion.

A note on stress-driven anisotropic diffusion and its role in active deformable media.

We introduce a new model to describe diffusion processes within active deformable media. Our general theoretical framework is based on physical and mathematical considerations, and it suggests to employ diffusion tensors directly influenced by the coupling with mechanical stress. The proposed generalised reaction-diffusion-mechanics model reveals that initially isotropic and homogeneous diffusion tensors turn into inhomogeneous and anisotropic quantities due to the intrinsic structure of the nonlinear coupling. We study the physical properties leading to these effects, and investigate mathematical conditions for its occurrence. Together, the mathematical model and the numerical results obtained using a mixed-primal finite element method, clearly support relevant consequences of stress-driven diffusion into anisotropy patterns, drifting, and conduction velocity of the resulting excitation waves. Our findings also indicate the applicability of this novel approach in the description of mechano-electric feedback in actively deforming bio-materials such as the cardiac tissue.

Mathematical modeling of gap junction coupling and electrical activity in human ß-cells.

Coordinated insulin secretion is controlled by electrical coupling of pancreatic ß-cells due to connexin-36 gap junctions. Gap junction coupling not only synchronizes the heterogeneous ß-cell population, but can also modify the electrical behavior of the cells. These phenomena have been widely studied with mathematical models based on data from mouse ß-cells. However, it is now known that human ß-cell electrophysiology shows important differences to its rodent counterpart, and although human pancreatic islets express connexin-36 and show evidence of ß-cell coupling, these aspects have been little investigated in human ß-cells. Here we investigate theoretically, the gap junction coupling strength required for synchronizing electrical activity in a small cluster of cells simulated with a recent mathematical model of human ß-cell electrophysiology. We find a lower limit for the coupling strength of approximately 20 pS (i.e., normalized to cell size, ∼2 pS pF(-1)) below which spiking electrical activity is asynchronous. To confront this theoretical lower bound with data, we use our model to estimate from an experimental patch clamp recording that the coupling strength is approximately 100-200 pS (10-20 pS pF(-1)), similar to previous estimates in mouse ß-cells. We then investigate the role of gap junction coupling in synchronizing and modifying other forms of electrical activity in human ß-cell clusters. We find that electrical coupling can prolong the period of rapid bursting electrical activity, and synchronize metabolically driven slow bursting, in particular when the metabolic oscillators are in phase. Our results show that realistic coupling conductances are sufficient to promote synchrony in small clusters of human ß-cells as observed experimentally, and provide motivation for further detailed studies of electrical coupling in human pancreatic islets.

The role of coherence in emergent behavior of biological systems.

In his research activity, Emilio Del Giudice explored the possibility to move towards a unified view of some long-range dynamics in nature, ranging from quantum field theory in physics up to biology. Such a view is adopted in this contribution by discussing a mathematical model for synchronized electrical behavior of pancreatic beta cells. The stochasticity is a fundamental component of the physiological synchronized behavior of this system. On the contrary, in a pathological type I diabetes scenario, the cells are destroyed by the autoimmune system and their coherent behavior is lost. This phenomenology conceptually links to ideas of coherent dynamics in quantum physics. Possible implications both for physical sciences and for the epistemology of life sciences are outlined.

Mechanistic insights into hypothermic ventricular fibrillation: the role of temperature and tissue size.

AIMS: Hypothermia is well known to be pro-arrhythmic, yet it has beneficial effects as a resuscitation therapy and valuable during intracardiac surgeries. Therefore, we aim to study the mechanisms that induce fibrillation during hypothermia. A better understanding of the complex spatiotemporal dynamics of heart tissue as a function of temperature will be useful in managing the benefits and risks of hypothermia. METHODS AND RESULTS: We perform two-dimensional numerical simulations by using a minimal model of cardiac action potential propagation fine-tuned on experimental measurements. The model includes thermal factors acting on the ionic currents and the gating variables to correctly reproduce experimentally recorded restitution curves at different temperatures. Simulations are implemented using WebGL, which allows long simulations to be performed as they run close to real time. We describe (i) why fibrillation is easier to induce at low temperatures, (ii) that there is a minimum size required for fibrillation that depends on temperature, (iii) why the frequency of fibrillation decreases with decreasing temperature, and (iv) that regional cooling may be an anti-arrhythmic therapy for small tissue sizes however it may be pro-arrhythmic for large tissue sizes. CONCLUSION: Using a mathematical cardiac cell model, we are able to reproduce experimental observations, quantitative experimental results, and discuss possible mechanisms and implications of electrophysiological changes during hypothermia.

Biophysical modeling of the whole-cell dynamics of C. elegans motor and interneurons families.

The nematode Caenorhabditis elegans is a widely used model organism for neuroscience. Although its nervous system has been fully reconstructed, the physiological bases of single-neuron functioning are still poorly explored. Recently, many efforts have been dedicated to measuring signals from C. elegans neurons, revealing a rich repertoire of dynamics, including bistable responses, graded responses, and action potentials. Still, biophysical models able to reproduce such a broad range of electrical responses lack. Realistic electrophysiological descriptions started to be developed only recently, merging gene expression data with electrophysiological recordings, but with a large variety of cells yet to be modeled. In this work, we contribute to filling this gap by providing biophysically accurate models of six classes of C. elegans neurons, the AIY, RIM, and AVA interneurons, and the VA, VB, and VD motor neurons. We test our models by comparing computational and experimental time series and simulate knockout neurons, to identify the biophysical mechanisms at the basis of inter and motor neuron functioning. Our models represent a step forward toward the modeling of C. elegans neuronal networks and virtual experiments on the nematode nervous system.

A cross species thermoelectric and spatiotemporal analysis of alternans in live explanted hearts using dual voltage-calcium fluorescence optical mapping.

Objective.Temperature plays a crucial role in influencing the spatiotemporal dynamics of the heart. Electrical instabilities due to specific thermal conditions typically lead to early period-doubling bifurcations and beat-to-beat alternans. These pro-arrhythmic phenomena manifest in voltage and calcium traces, resulting in compromised contractile behaviors. In such intricate scenario, dual optical mapping technique was used to uncover unexplored multi-scale and nonlinear couplings, essential for early detection and understanding of cardiac arrhythmia.Approach.We propose a methodological analysis of synchronized voltage-calcium signals for detecting alternans, restitution curves, and spatiotemporal alternans patterns under different thermal conditions, based on integral features calculation. To validate our approach, we conducted a cross-species investigation involving rabbit and guinea pig epicardial ventricular surfaces and human endocardial tissue under pacing-down protocols.Main results.We show that the proposed integral feature, as the area under the curve, could be an easily applicable indicator that may enhance the predictability of the onset and progression of cardiac alternans. Insights into spatiotemporal correlation analysis of characteristic spatial lengths across different heart species were further provided.Significance.Exploring cross-species thermoelectric features contributes to understanding temperature-dependent proarrhythmic regimes and their implications on coupled spatiotemporal voltage-calcium dynamics. The findings provide preliminary insights and potential strategies for enhancing arrhythmia detection and treatment.

Multilevel synchronization of human ß-cells networks.

ß-cells within the endocrine pancreas are fundamental for glucose, lipid and protein homeostasis. Gap junctions between cells constitute the primary coupling mechanism through which cells synchronize their electrical and metabolic activities. This evidence is still only partially investigated through models and numerical simulations. In this contribution, we explore the effect of combined electrical and metabolic coupling in ß-cell clusters using a detailed biophysical model. We add heterogeneity and stochasticity to realistically reproduce ß-cell dynamics and study networks mimicking arrangements of ß-cells within human pancreatic islets. Model simulations are performed over different couplings and heterogeneities, analyzing emerging synchronization at the membrane potential, calcium, and metabolites levels. To describe network synchronization, we use the formalism of multiplex networks and investigate functional network properties and multiplex synchronization motifs over the structural, electrical, and metabolic layers. Our results show that metabolic coupling can support slow wave propagation in human islets, that combined electrical and metabolic synchronization is realized in small aggregates, and that metabolic long-range correlation is more pronounced with respect to the electrical one.

Assessment of tools for RNA secondary structure prediction and extraction: a final-user perspective.

The study of RNA structure is fundamental to clarify the RNA molecular functioning. The flexible RNA nature, the huge number of expressed RNAs, and the variety of functions make it challenging to obtain a quantity of structural information comparable to what is already available for proteins. The in silico prediction of RNA 3D structures is of particular relevance, to understand the fundamental features of the structure-function relationship, because the 3D structure drives the molecular interaction with DNA or protein complexes. The quality of the prediction of the RNA 3D structure is determined by the knowledge of a properly predicted or measured secondary structure. In this paper, we comparatively evaluate computational tools to model RNA secondary structure, focusing our investigation, among the dozens of methods in literature, on tools which are freely available and implemented in web-server versions, providing a more direct access to the final users, not necessarily bioinformatics experts. Our focus is on assessing performances for long sequences, with the final aim of selecting best methods for perspective lncRNAs investigation. Indeed, among RNAs, the non-coding and long non-coding RNAs (lncRNAs, with sequence length larger than 200 nts) assume special relevance, due to their function in regulatory mechanisms, which is still largely unexplored in the case of lncRNAs. As lncRNA experimental structures are at present missing, other families of large RNAs are here used as test cases, to establish the reliability of predictive bioinformatics tools and their perspective applicability to the case of lncRNAs.Communicated by Ramaswamy H. Sarma.

Innovative Characterization of Alternans Onset and Development in Dual Voltage-Calcium Whole-Heart Optical Mapping Signals at Multiple Thermal States.

Cardiac electrical dynamics show complex space-time instabilities, like period-doubling bifurcation and beat-to-beat alternans, known to occur as pro-arrhythmic phenomena and linked to membrane voltage and intracellular calcium kinetics. Besides, cellular ionic dynamics are critically affected by temperature oscillations, further enhancing the complexity of such arrhythmias precursors that lead to irregular cardiac contraction. In this complex scenario, fluorescence dual optical mapping techniques allow the unveiling of nonlinear and multi-scale couplings. In this contribution, we propose a novel methodological analysis of synchronous dual voltage-calcium traces obtained from whole rabbit hearts for (i) detecting alternans onset and evolution, (ii) characterizing novel restitution curves, and (iii) defining spatio-temporal alternans patterns at four thermal states. We validate our approach against well-accepted analyses considering complete pacing-down restitution protocols. The proposed methodology computes integral features, e.g., area under the curve, suggesting that a novel, easy-to-use indicator, may advance predictability on alternans onset and evolution, further providing insights into spatio-temporal cardiac analyses.Clinical Relevance- This work introduces new methods for the early detection of cardiac alternans onset and development as precursors of arrhythmias and fibrillation at different temperatures.

Modeling of olfactory transduction in AWCON neuron via coupled electrical-calcium dynamics.

Amphid wing "C" (AWC) neurons are among the most important and studied neurons of the nematode Caenorhabditis elegans. In this work, we unify the existing electrical and intracellular calcium dynamics descriptions to obtain a biophysically accurate model of olfactory transduction in AWCON neurons. We study the membrane voltage and the intracellular calcium dynamics at different exposure times and odorant concentrations to grasp a complete picture of AWCON functioning. Moreover, we investigate the complex cascade of biochemical processes that allow AWC activation upon odor removal. We analyze the behavior of the different components of the models and, by suppressing them selectively, we extrapolate their contribution to the overall neuron response and study the resilience of the dynamical system. Our results are all in agreement with the available experimental data. Therefore, we provide an accurate mathematical and biophysical model for studying olfactory signal processing in C. elegans.

Multiscale and Multiphysics Modeling of Anisotropic Cardiac RFCA: Experimental-Based Model Calibration via Multi-Point Temperature Measurements.

Radiofrequency catheter ablation (RFCA) is the mainstream treatment for drug-refractory cardiac fibrillation. Multiple studies demonstrated that incorrect dosage of radiofrequency energy to the myocardium could lead to uncontrolled tissue damage or treatment failure, with the consequent need for unplanned reoperations. Monitoring tissue temperature during thermal therapy and predicting the extent of lesions may improve treatment efficacy. Cardiac computational modeling represents a viable tool for identifying optimal RFCA settings, though predictability issues still limit a widespread usage of such a technology in clinical scenarios. We aim to fill this gap by assessing the influence of the intrinsic myocardial microstructure on the thermo-electric behavior at the tissue level. By performing multi-point temperature measurements on ex-vivo swine cardiac tissue samples, the experimental characterization of myocardial thermal anisotropy allowed us to assemble a fine-tuned thermo-electric material model of the cardiac tissue. We implemented a multiphysics and multiscale computational framework, encompassing thermo-electric anisotropic conduction, phase-lagging for heat transfer, and a three-state dynamical system for cellular death and lesion estimation. Our analysis resulted in a remarkable agreement between ex-vivo measurements and numerical results. Accordingly, we identified myocardium anisotropy as the driving effect on the outcomes of hyperthermic treatments. Furthermore, we characterized the complex nonlinear couplings regulating tissue behavior during RFCA, discussing model calibration, limitations, and perspectives.

Optical Ultrastructure of Large Mammalian Hearts Recovers Discordant Alternans by In Silico Data Assimilation.

Understanding and predicting the mechanisms promoting the onset and sustainability of cardiac arrhythmias represent a primary concern in the scientific and medical communities still today. Despite the long-lasting effort in clinical and physico-mathematical research, a critical aspect to be fully characterized and unveiled is represented by spatiotemporal alternans patterns of cardiac excitation. The identification of discordant alternans and higher-order alternating rhythms by advanced data analyses as well as their prediction by reliable mathematical models represents a major avenue of research for a broad and multidisciplinary scientific community. Current limitations concern two primary aspects: 1) robust and general-purpose feature extraction techniques and 2) in silico data assimilation within reliable and predictive mathematical models. Here, we address both aspects. At first, we extend our previous works on Fourier transformation imaging (FFI), applying the technique to whole-ventricle fluorescence optical mapping. Overall, we identify complex spatial patterns of voltage alternans and characterize higher-order rhythms by a frequency-series analysis. Then, we integrate the optical ultrastructure obtained by FFI analysis within a fine-tuned electrophysiological mathematical model of the cardiac action potential. We build up a novel data assimilation procedure demonstrating its reliability in reproducing complex alternans patterns in two-dimensional computational domains. Finally, we prove that the FFI approach applied to both experimental and simulated signals recovers the same information, thus closing the loop between the experiment, data analysis, and numerical simulations.

A Simulation Study of the Effects of His Bundle Pacing in Left Bundle Branch Block.

His bundle pacing (HBP) has emerged as a feasible alternative to right (RVP) and biventricular pacing (BVP) for Cardiac Resynchronization Therapy (CRT). This study sought to assess, in ex-vivo experimental models, the optimal setup for HBP in terms of electrode placement and pacing protocol to achieve superior electrical synchrony in the case of complete His-Purkinje block and left bundle branch block (LBBB). We developed a 3D model of His bundle and bundle branches, embedded in a patient-specific biventricular heart model reconstructed from CT images. A monodomain reaction-diffusion model was adopted to describe the propagation of cardiac action potential, and a custom procedure was developed to compute pseudo-ECGs. Experimental measurements of tip electrode potential waveforms have been performed on ex-vivo swine myocardium to determine the appropriate boundary condition for delivering the electrical stimulus in the numerical model. An extended parametric analysis, investigating the effect of the electrode orientation and helix length, pacing protocol, and atrioventricular delay, allowed us to determine the optimal setup for HBP therapy. Both selective (S-HBP) and non-selective (NS-HBP) His bundle pacing were tested, as the variable anatomical location of the His bundle can result in the activation of the surrounding myocardium. Our study indicates a perpendicular placement of the electrode as the most advantageous for restoring the physiological function of the His-Purkinje system. We found that higher-energy protocols can compensate for the effects of an angled placement though concurring to potential tip fibrosis. Promisingly, we also revealed that an increased electrode helix length can provide optimal resynchronization even with low-energy pacing protocols. Our results provide informative guidance for implant procedure and therapy optimization, which will hopefully have clinical implications further improving the procedural success rates and patients' quality of life, due to reduced incidence of lead revision and onset of complications.

Correction: Biophysical modeling of C. elegans neurons: Single ion currents and whole-cell dynamics of AWCon and RMD.

[This corrects the article DOI: 10.1371/journal.pone.0218738.].

Thermal effects on cardiac alternans onset and development: A spatiotemporal correlation analysis.

Alternans of cardiac action potential duration represent critical precursors for the development of life-threatening arrhythmias and sudden cardiac death. The system's thermal state affects these electrical disorders requiring additional theoretical and experimental efforts to improve a patient-specific clinical understanding. In such a scenario, we generalize a recent work from Loppini et al. [Phys. Rev. E 100, 020201(R) (2019)PREHBM2470-004510.1103/PhysRevE.100.020201] by performing an extended spatiotemporal correlation study. We consider high-resolution optical mapping recordings of canine ventricular wedges' electrical activity at different temperatures and pacing frequencies. We aim to recommend the extracted characteristic length as a potential predictive index of cardiac alternans onset and evolution within a wide range of system states. In particular, we show that a reduction of temperature results in a drop of the characteristic length, confirming the impact of thermal instabilities on cardiac dynamics. Moreover, we theoretically investigate the use of such an index to identify and predict different alternans regimes. Finally, we propose a constitutive phenomenological law linking conduction velocity, characteristic length, and temperature in view of future numerical investigations.

Electric Source Imaging on Intracranial EEG Localizes Spatiotemporal Propagation of Interictal Spikes in Children with Epilepsy.

Interictal epileptiform discharges (IEDs) serve as sensitive but not specific biomarkers of epilepsy that can delineate the epileptogenic zone (EZ) in patients with drug resistant epilepsy (DRE) undergoing surgery. Intracranial EEG (icEEG) studies have shown that IEDs propagate in time across large areas of the brain. The onset of this propagation is regarded as a more specific biomarker of epilepsy than areas of spread. Yet, the limited spatial resolution of icEEG does not allow to identify the onset of this activity with high precision. Here, we propose a new method of mapping the spatiotemporal propagation of IEDs (and identify its onset) by using Electrical Source Imaging (ESI) on icEEG bypassing the spatial limitations of icEEG. We validated our method on icEEG recordings from 8 children with DRE who underwent surgery with good outcome (Engel score =1). On each icEEG channel, we detected IEDs and identified the propagation onset using an automated algorithm. We localized the propagation of IEDs with dynamic Statistical Parametric Mapping (dSPM) using a time-sliding window approach. We defined two brain regions: the ESI-onset and ESI-spread zone. We estimated the overlap of these regions with resection volume (in percentage), which served as the gold-standard of the EZ. We also estimated the mean distance of these regions from resection and clinically defined seizure onset zone (SOZ). We observed spatio-temporal propagation of IEDs in all patients across several channels (98 [85-102]) with a mean duration of 155 ms [96-186 ms]. A higher overlap with resection was seen for the ESI-onset zone compared to spread (73.3 % [ 47.4-100 %], 36.5 % [20.3-59.9 %], p = 0.008). The distance of the ESI-onset from resection was shorter compared to the ESI-spread zone (4.3 mm [3.4-5.5 mm], 7.4 mm [6.0-20.6 mm], p = 0.008) and the same trend was observed for the distance from the SOZ (11.9 mm [7.2-15.1 mm], 20.6 mm [15.4-27.2 mm], p = 0.02). These findings show that our method can map the spatiotemporal propagation of IEDs and de-lineate its onset, which is a reliable and focal biomarker of the EZ in children with DRE.Clinical Relevance - ESI on icEEG recordings of children with DRE can localize the spikes propagation phenomenon and help in the delineation of the EZ.

From Syndemic Lesson after COVID-19 Pandemic to a "Systemic Clinical Risk Management" Proposal in the Perspective of the Ethics of Job Well Done.

The syndemic framework proposed by the 2021-2030 World Health Organization (WHO) action plan for patient safety and the introduction of enabling technologies in health services involve a more effective interpretation of the data to understand causation. Based on the Systemic Theory, this communication proposes the "Systemic Clinical Risk Management" (SCRM) to improve the Quality of Care and Patient Safety. This is a new Clinical Risk Management model capable of developing the ability to observe and synthesize different elements in ways that lead to in-depth interventions to achieve solutions aligned with the sustainable development of health services. In order to avoid uncontrolled decision-making related to the use of enabling technologies, we devised an internal Learning Algorithm Risk Management (LARM) level based on a Bayesian approach. Moreover, according to the ethics of Job Well Done, the SCRM, instead of giving an opinion on events that have already occurred, proposes a bioethical co-working because it suggests the best way to act from a scientific point of view.

Breaking down calcium timing in heterogenous cells populations.

Calcium controls a large number of cellular processes at different scales. Decades of studies have pointed out the importance of calcium signaling in regulating differentiation, apoptosis, mitosis and functions such as secretion, muscle contraction and memory. The space-time structure of calcium signaling is central to this complex regulation. In particular, cells within organisms behave as clocks beating their own biological time, although in several cases they can synchronize across long distances leading to an emergent space-time dynamics which is central for single cell and organ functioning. We use a mathematical model built on published experimental data of hepatic non-excitable cells, analyzing emerging calcium dynamics of cells clusters composed both of normally functioning cells and pathological aggregates. Calcium oscillations are investigated by varying the severity of dysfunction and size of pathological aggregate. We show how strong and localized heterogeneity in cellular properties can profoundly alter organized calcium dynamics leading to sub-populations of cells which create their own coordinated dynamical organization. Our simulations of Ca2+ signals reveal how cell behaviors differ and are related to intrinsic time signals. Such different cells clusters dynamically influence each other so that non-physiological although organized calcium patterns are generated. This new reorganization of calcium activity may possibly be a precursor of cancer initiation.