Excitation–contraction coupling in cardiac myocytes requires calcium influx through L-type calcium channels in the sarcolemma, which gates calcium release through sarcoplasmic reticulum ryanodine receptors in a process known as calcium-induced calcium release, producing a myoplasmic calcium transient and enabling cardiomyocyte contraction. The spatio-temporal dynamics of calcium release, buffering, and reuptake into the sarcoplasmic reticulum play a central role in excitation–contraction coupling in both normal and diseased cardiac myocytes. However, further quantitative understanding of these cells’ calcium machinery and the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease requires accurate knowledge of cardiac ultrastructure, protein distribution and subcellular function. As current imaging techniques are limited in spatial resolution, limiting insight into changes in calcium handling, computational models of excitation–contraction coupling have been increasingly employed to probe these structure–function relationships. This review will focus on the development of structural models of cardiac calcium dynamics at the subcellular level, orienting the reader broadly towards the development of models of subcellular calcium handling in cardiomyocytes. Specific focus will be given to progress in recent years in terms of multi-scale modeling employing resolved spatial models of subcellular calcium machinery. A review of the state-of-the-art will be followed by a review of emergent insights into calcium-dependent etiologies in heart disease and, finally, we will offer a perspective on future directions for related computational modeling and simulation efforts. Excitation–contraction coupling (ECC) in cardiomyocytes requires calcium (Ca) influx through L-type Ca channels (LCCs) in the sarcolemma, which initiates Ca release through ryanodine receptors (RyRs) clustered in the terminal cisternae of the sarcoplasmic reticulum  in a process known as Ca-induced Ca release (CICR). Ca influx via an a intracellular Ca transient (CaT), enabling cardiomyocyte contraction. Ca is removed from the myoplasm, ending the CaT, via the sarco/endoplasmic reticulum Ca-ATPase (SERCA) and by the sarcolemmal Na–Ca exchanger (NCX) as well as the Ca pump (CaP). All RyRs and associated jSR structures that can be activated as a distinct unit are denominated the “calcium release unit” (CRU).1 . Atrial cardiomyocytes from large mammals have been shown to have well-developed t-tubular networks; however, species differences and specifically a lack of defined t-tubular structure in atria myocytes from small mammals has historically led to atrial t-tubules being overlooked. The t-tubular system plays a central role in the synchronization of Ca signaling and ECC in many striated muscle cells; disruption of the t-network contributes to dyssynchronous Ca release and impaired contraction.37 CICR in small dyads gives rise to high gain through positive feedback , but the spatial distribution and relative isolation of CRUs allows for sequential recruitment and graded release. The restricted number of molecules in each CRU can mean that approximating dynamics as continuous is inappropriate: processes therein may be better described by stochastic as opposed to deterministic models. Many earlier models of the cardiac action potential did not include descriptions of CICR that accounted for these local mechanisms.8The spatio-temporal dynamics of CICR, buffering, and reuptake into the SR play a central role in ECC in both normal and diseased cardiac myocytes. In cardiac myocytes, it has been proposed that 5–15 LCCs embedded in the sarcolemma appose 50–200 clustered RyRs as distinct structures9 short-lived, local increases in intracellular Ca via triggered SR release are known as Ca sparks, which regulate the generation of whole-cell CaT and ECC. For example, spontaneous Ca sparks have durations of 10–100 ms, allowing SR Ca uptake to keep pace with release, a process which cannot happen during a complete triggered release event. Long-lasting sparks with durations of several hundred milliseconds to seconds, so-called “embers,” are also widely observed. Experiments have shown that the transition from normal to long-lasting sparks can occur when RyRs open probability is reduced.10 Dysfunction in Ca handling is central to a number of cardiac pathologies (including heart failure (HF) and atrial fibrillation (AF)) and may lead to mechanical dysfunction as well as arrhythmia. Disruption of dyadic structure is thought to be largely responsible for changes in Ca handling; we will delve further into these aspects in later sections of this review. Further quantitative understanding of cardiomyocytes’ Ca machinery and the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease thus requires accurate knowledge of cardiac ultrastructure, protein distribution and subcellular function. As current imaging techniques are limited in the spatial resolution to which changes in Ca can be detected, computational models of ECC have thus been increasingly employed to probe these structure–function relationships. Mathematical modeling of ECC in cardiomyocytes is a fundamentally multi-scale problem: it involves gradients on the spatial scale of 100 nm or even less in dyadic clefts and concentration profiles along the 100 µm of the whole cell, as well as the submillisecond timescale of local concentration changes and the change of SR Ca content within tens of seconds.Ca signaling in the CRU is a fundamentally discrete process;11 nor will the explicit roles of oxidative stress or CaMKII signaling.13 Others have also offered excellent reviews of modeling of myocardial Ca at different spatial scales from the perspective of parameter sensitivity analysis,14 which will not be the primary focus at present. Instead, the present review will orient the reader broadly towards the development of models of subcellular Ca handling in cardiomyocytes. We will place specific focus on progress in recent years in terms of multi-scale modeling employing resolved spatial models of subcellular calcium machinery. A review of the state-of-the-art will be followed by a review of emergent insights into calcium-dependent etiologies in heart disease and, finally, will offer a perspective on future directions for related computational modeling and simulation efforts.This review will focus on the development of structural mathematical models of cardiac Ca dynamics. While of importance for select cardiac pathologies, in general the role of mutation and protein dysfunction or dysregulation will not be treated in detail here, nor will the study of targets or putative drug therapies for Ca handling dysfunction take a major role. Discussion of mitochondrial electrodynamics and signaling, though offering critical insight, will not be treated here and have been reviewed elsewhere,Mathematical modeling of the physiology of both atrial and ventricular cardiomyocytes is a broad field including several mathematical formalisms. For the convenience of the less-familiar reader, we here offer a brief review of a few common computational modeling terms used in the present review. Something which is discretely valued is constant over a spatial or temporal interval, while one that is continuous would have smoothly varying values in time and space; binary in this context refers to an all-or-nothing phenomenon. A compartment refers to a restricted virtual space in the mathematical model which represents a volume considered to be separate from a common or bulk space in the interior of the cell. A deterministic model refers to a system wherein no randomness is involved in calculation of its future states. A deterministic model will thus always produce the same output from a given input, while stochasticity refers to event or system that includes uncertainty in outputs because of random variation in one or more inputs over time. Markov processes are stochastic processes that satisty the property of “memorylessness;” the concept is that one can make predictions for the future based only on the present state, with the future and past as independent. Monte Carlo simulations are used to model the probability of different outcomes in processes that cannot easily be predicted because of stochastic inputs. In a single trial, a range of values (probability distribution) is substituted for a number for any factor that has inherent uncertainty; with many, many trials, each using a different set of random values, a complete picture of probable outcomes is obtained. The probability density function (arising from statistics) is a function used to specify the probability of a random variable falling within a particular range of values, as opposed to taking on any one value.16 a brief orientation follows. Movement and dynamics of Ca ions in the dyad have often been described by assigning continuously valued Ca concentrations to one or more dyadic compartments; several models have been based upon deterministic representations (without stochasticity) wherein CRUs were lumped into a single “common pool.”1719 As the RyRs in this common pool are activated via influx of Ca through LCCs, the strong positive feedback of CICR ensures that the pooled release units activate completely, resulting in coordinated, binary calcium release. Ventricular cardiomyocytes, however, display a graded response to trigger Ca in vivo: as the amount of trigger Ca from LCCs goes up, so does release via the SR through the RyRs. While some of the deterministic computational models do simulate graded release, these require an artificial mechanism to do so.8 Stern20 demonstrated that high-gain graded release could not be simulated via common-pool means, but that modeling CRU including local CICR triggers and recruitment of a neighborhood cluster of RyRs permitted graded response; this was also later demonstrated in a more physiological model.21 Thus, a sufficient increase in dyadic subspace Ca following local LCC opening causes apposed RyRs to open; specifically, then, stochastic recruitment of neighboring CRU results in graded release: the so-called “local control”-type model. These stochastic properties of the system can be reduced to a representative Markov model based on principles of timescale decomposition. The RyRs and LCCs are often modeled via Markov state models, as reviewed elsewhere16  conditioned on the CRU state. Modeling CRU activity using this probability density approach avoids resolution of precise spatial aspects of global Ca signaling, but represents heterogeneous local Ca signals in a population of dyadic subspaces and junctional SR depletion domains with reasonable accuracy.27 Both approaches to modeling local control of ECC produce high-gain Ca release that is graded with changes in membrane potential, phenomena not exhibited by common pool models. Other non-spatially resolved models of local control have linked the processes of subcellular Ca machinery to whole cell behavior.29Local control models of Ca release wherein interactions between LCCs and RyRs are simulated stochastically are able to reconstruct the key physiological phenomena of both graded Ca release and high CICR gain,30 In recent decades, there has been much additional evidence that the control of CICR is contingent upon local Ca in the immediate vicinity of the CRU, rather than on the whole-cell Ca.32 This tight, local regulation of CICR is made possible by the clustering of LCCs and RyRs into discrete couplons, rendering them sensitive to local rather than global Ca. While Ca sparks represent the “unit” of Ca release from large arrays of RyRs in the CRU, Ca “blinks” represent the Ca depletion signal produced in the terminal cisternae of the jSR. Furthermore, so-called quarky Ca release observes release events smaller than sparks at a level substructural to the CRU.33 In other words, macroscopic Ca release events are intrinsically controlled by the type and number of individual LCCs and RyRs in the CRU, the relative spatial localization of the two channel types and geometry of this functionally significant nanodomain, as well as the organization of the CRUs at the cell level.The local nature of the ECC control mechanism was not clear until the discovery of Ca sparks by Cheng et al.23 consisted of a single LCC closely apposed to a cluster of RyRs in a region of jSR. While simple, the stochastic current descriptions for RyRs and LCCs sought to lend insight to the question of Ca spark termination via the novel “sticky cluster” model, meaning a model that incorporated the “sticky” cooperativity between adjacent RyRs. Next efforts employed explicitly spatially-resolved single CRUs; one study to investigate the effects of action potential prolongation in a model of murine HF used a rectangular space with dimensions 100 nm × 100 nm and a dyadic cleft space of 12 nm between the t-tubular and SR membranes, analysis revealed that Ca spark amplitude and rise time were highly dependent on the number of activated channels (LCCs and RyRs) and their packing within the CRU, though not very sensitive to other cleft dimensions.34 More detailed was a study by our groups which developed a three-dimensional computational model of a single dyad, modeled as a cylindrical disk,36 with CRUs of two sizes: 25 or 100 RyRs per CRU, with RyRs positioned in a highly regular two-dimensional lattice grid.6 In a follow-up study on whether RyR function promoted slowing of Ca release in murine HF, the sticky cluster model was re-parameterized37 and, rather than incorporate a highly regular RyR geometry in the CRU, was extended to include subclusters in a CRU in addition to one “mother cluster.” All subclusters were connected with the mother cluster through diffusion but not with each other, and Ca sparks were initiated by opening one RyR in the mother cluster.38An early model of Sobie et al.39 used a schematic model of a cluster of coupled RyRs in a cardiac ventricular cell of length of 150 µm, with 2 µm spatial resolution40 to study intracellular Ca alternans (see Section 3.3) by coupling model elements via Ca diffusion between neighboring cytoplasmic and network SR spaces. The more complex model of Rovetti et al.41 developed a quasi-two-dimensional spatially-distributed Ca cycling model via network of 100 by 100 CRU which included a network SR (nSR) domain and a myoplasmic domain coupled via SR Ca release and uptake. The model comprises a CRU network coupled via Ca diffusion in each domain. Each CRU contained a jSR diffusively connected to the nSR, and a dyadic space diffusively connected to the myoplasm, as well as stochastic LCCs (5 channels per CRU) and RyRs (100 channels per CRU). Gaur et al.42 developed an initial multi-scale model of a spatially distributed mammalian ventricular myocyte consisting of 10,000 diffusively coupled CRU, with the number of stochastic LCCs and RyRs in a dyad as 15 and 100, respectively, to investigate how microscopic changes in dyadic properties including detubulation in HF, can affect whole-cell behavior. A recent model of ECC in the mouse cardiac ventricular myocyte, developed to further elucidate the physiologic consequences of leaky RyRs, included a three-dimensional spatial implementation of the same group’s local control model, representing a single sarcomere centered on a z-line and containing equally distributed CRU (inter-CRU distance is 600 nm).43 Cannell and Laver45 have recently employed with others a cylindrical model of the dyad with a t-tubule at the center to investigate control and termination of CICR via the SR; importantly, this model permits calcium gradients within the CRU.Computational models have additionally moved towards the level of the whole myocyte, generally stepping up dimension and complexity in geometry. Tao et al.46 has not yet been taken into account in several models; instead, models have assumed wave-like CICR propagation of Ca into the cell interior. Given cell-type potential differences in ultrastructure, the “z-plane” distribution of RyRs was modeled radially, rather as a regular grid in one study, to monitor the three-dimensional diffusion of Ca along a portion of the cell.47 Another model of the human atrial cardiomyocyte48 included a spatial representation of Ca-handling based on longitudinal division into ~2µm wide segments, and in the transverse division into ~1µm long domains, as based on the model of Grandi et al.49Others have used similar approaches to examine local Ca in the atrial myocyte. The observation of variable t-tubule density in atrial myocytes5054 The model and its iterations include a three-dimensional network of 19,305 (65 × 27 × 11) CRUs with CRU spacing at 1.84 µm  and 0.9 µm (transverse direction), corresponding to a ventricular cell of dimension ~ 120 × 25 × 10 μm3. CRUs are coupled via Ca diffusion in the cytosolic space and SR. Each CRU contains five subvolumes: the nSR, jSR, dyadic space or proximal space, a submembrane space, and a cytosolic space. While spatially resolved, each CRU incorporates a cluster of 100 RyR channels and 10 LCCs, both simulated using random Markov transitions: cluster size is fixed, other aspects of CRU geometry not taken into account, and the CRU is considered a common-pool with respect to [Ca] gradients. Others have used a similar approach, but simplified the three-dimensional problem to a two-dimensional model of a cardiac myocyte,55 similar to the work by Izu et al.56 Recently, Sato et al.57 expanded upon the work of Restrepo et al. with RyR clusters of a few to several hundred RyRs, varying the number of functional RyRs in a single cluster, diffusion within the SR network, diffusion between network and junctional SR, cytosolic Ca diffusion, SERCA uptake activity, and RyR open probability. To address the need for explicit representation of CRU geometry, Hake et al.58 developed novel tools to generate computational geometry from electron tomographic images and created a detailed computational model of a single CRU. Ca diffusion was modeled within the SR and the cytosol to examine the effects of localization and density of the NCX, SERCA, and CSQN. Others have developed high-resolution imaging and analysis approaches to measure the three-dimensional distribution of immunolabeled proteins with confocal microscopy in cardiomyocytes as both RyRs and t-tubular system distributions show large variation from the simple grid geometries assumed in previous work; this three-dimensional RyR cluster distribution has been used to construct a model of stochastic Ca dynamics in a myocyte.59Physiologically detailed models of subcellular Ca cycling including a three-dimensional network of ~20,000 CRU at the level of the whole ventricular cell have been developed by Restrepo and colleagues.60 Another recent study introduced a new concept for a multi-scale mathematical model of CICR and whole cardiomyocyte electrophysiology. This incorporated stochastic simulation of individual LCCs and RyRs, spatially detailed concentration dynamics in dyadic clefts, rabbit membrane potential dynamics, and a system of partial differential equations (PDEs) for intracellular and SR free Ca as well as Ca-buffering, and resolved concentration gradients from the level of the dyad to the whole-cell level by using a quasi-static approximation in CRU.61Computational models at present seek to combine the data emergent from newer imaging technologies to gain multi-scale insight into calcium-driven processes. Spatial point process statistics techniques were recently developed to simulate the spatial distribution of RyR clusters, combining confocal-scale (~200 nm) data of RyR clusters with three-dimensional electron microscopy data (~30 nm) of myofibrils and mitochondria, both collected from adult rat left ventricular myocytes. This hybrid-scale spatial model was employed in reaction–diffusion Ca simulations during the rising phase of the CaT.62 Furthermore, models incorporating realistic CRU distributions permitted Ca waves that spread axially along the cell at observed velocities, demonstrating that spatial features of the CRU distribution on multiple length scales critically affects intracellular Ca dynamics.59 A recent study showed that RyRs positioned axially helped propagate Ca waves in the axial direction.63 Greenstein et al.29 generalized an earlier analytical approach for deriving simplified mechanistic models of CICR to formulate an integrative model of the canine cardiac myocyte, which was used to study the role of local redundancy in LCC channel gating and the role of dyad configuration on ECC. Simulations suggested that the characteristic steep rise in ECC gain observed at hyperpolarized potentials is a result of increased functional coupling between LCCs and RyRs.Multi-scale computational models of subcellular Ca handling have offered a wealth of mechanistic insight into the cardiomyocytes’ function in the normal heart. To illustrate, models of stochastic molecular signaling between LCCs and RyRs describing known features of dyad geometry, including key dyadic proteins and electrodiffusive movement of individual Ca ions enabled investigation of how local Ca signaling is influenced by the dyad structure. The geometry of the individual RyR may indeed function to restrict the diffusion of and to “funnel” Ca ions to activation-binding sites on the RyRs, increasing RyR open probability and ECC gain.64 The model resolves the multiple single opening events that do not result in a Ca spark , and also shows that a single RyR release event can trigger others via CICR and that once ~12% of RyRs are open, a spark usually follows. The termination of a calcium spark has been an active research topic for many years with several hypotheses proposed; the reader is referred to an excellent recent review.65 The spatial arrangement of RyRs within clusters has a major influence on the frequency of Ca sparks. The probability of a Ca spark occurring when a single RyR in the cluster opens spontaneously can be predicted from the precise spatial arrangement of the RyRs; function follows directly from structure, in this case. A computational model of the dyadic cleft which specified the spatial localization of LCCs and RyRs revealed that reaction specificity and efficiency are regulated by microdomain geometry as well as the physical separation of signaling molecules into functional complexes. Both Ca spark amplitude and rise time were found to be highly dependent on the concentration of activated channels in the CRU microdomain and on the intermembrane separation channel packing .34 Previous model studies also have predicted that the duration of the spark is determined by the local CRU geometry, as well as the localization and density of Ca-handling proteins.58 It has been newly demonstrated that long-lasting Ca sparks emerge as a collective dynamical behavior of a network of diffusively coupled CRU; there exists an optimal range of RyR open probability favoring long-lasting sparks.54 Another recent study employed a spatially resolved mathematical model of subcellular Ca cycling to examine how Ca spark duration is influenced by the number of functional RyRs in a junctional cluster and other SR Ca-handling properties; if the number of RyRs is under a certain threshold, it is difficult to maintain consecutive openings and stochastic attrition terminates Ca release while, if the number of RyRs in a cluster is too large, the depletion of Ca from the jSR terminates release. It was found that protracted Ca release events require small RyR clusters and sufficiently rapid intra-SR Ca diffusion.57Modeling and simulation has permitted detailed insight into Ca spark generation in normal function. The Williams et al. model for calcium dynamics in the rat ventricular myocyte includes 20,000 CRU consisting of clusters of stochastically gated RyRs.30 Spontaneous increase in [Ca] can occur at a single or multiple CRU within a cell and can lead to propagation throughout the myoplasm in a wave-like pattern. Cheng et al.66 speculated that Ca waves arose from the collective firing of Ca sparks; that Ca released in a dyad can diffuse and trigger Ca release in adjacent dyads, forming traveling waves. The nature of this propagating mechanism means that a wave travels at a finite velocity. This is therefore dissimilar to the CaT evoked by an action potential, which is a whole-cell release event, coordinated by depolarization-activated Ca entry through LCCs.67 Ca waves are a natural consequence of CICR; the evolution of Ca wave models reflects the growth of knowledge of ECC in muscle. The appearance of Ca waves may lead to whole-cell depolarization and triggering of an action potential, as these may activate inward currents such as that carried by the NCX.68 Thus, there exists a putative link between Ca waves and triggered activity leading to initiation of dangerous arrhythmias; experimental studies have demonstrated that abnormal Ca cycling is a critical factor in the development of focal excitations.69 Spatially-resolved cell models have shown that the time needed to form cluster of sufficient size to elicit a Ca wave, as well as the critical cluster size, becomes smaller as SR Ca load and diastolic myoplasmic Ca increases.52 A separate study in a similar model effected sensitivity analyses to study physiological parameter effects on global Ca waves: computed results were in agreement with confocal microscopy imaging, and found that the current flow amplitude through the CRU affected dynamic properties of Ca waves more significantly than the duration of this current, and that longitudinal and transverse separation of CRU affected the longitudinal velocity and amplitude of Ca waves significantly.55Intracellular Ca waves are a form of Ca signaling executed in many cell types and can occur in cardiac myocytes during Ca overload.50 showed that luminal (SR-side) gating of the RyRs mediated by CSQN can cause calcium transient alternans regardless of the steepness of the release–load relationship: alternans were caused by a beat-to-beat alternation in the number of refractory RyR channels and could occur with or without diastolic SR calcium content alternans. The same group showed that ion channel stochasticity at the level of a single CRU can influence the whole-cell alternans. Depending on the sign and magnitude of Ca–voltage coupling, Ca alternans can be spatially synchronized or desynchronized, and in or out of phase with action potential duration alternans. Calcium alternans can, for instance, be spatially synchronized but out of phase with action potential duration alternans.51 The concurrent model of Tao et al.39 found that alternans of systolic Ca were generated by propagating Ca waves sustained through alternation of SR Ca content, implicating additional mechanisms for intracellular Ca alternans in addition to refractoriness of LCCs or RyRs under rapid pacing. Rovetti et al.41 showed that Ca alternans emerge as a collective behavior of Ca sparks, determined by the CRU network, via three Rs: “randomness” (of Ca spark activation), “refractoriness” (of a CRU after a Ca spark), and “recruitment” (Ca sparks inducing Ca sparks in adjacent CRUs). Nivala et al.53 later employed the ventricular myocyte couplon network model to study how SR Ca load and other physiological parameters, such as RyR sensitivity, SR uptake rate, NCX current, and Ca buffering affect Ca alternans in the context of the 3R theory, and found that alternans only occurs for an intermediate range of the SR Ca load, and the underlying mechanism can be explained via its effects on the three Rs .Cellular CaT alternans are beat-to-beat alternations in the peak cytosolic calcium concentration exhibited by cardiac cells during rapid electrical stimulation or under pathological conditions. CaT alternans promote action potential duration alternans, which have been linked to the onset of life-threatening ventricular arrhythmias. Ca alternans in cardiac myocytes have been shown in many experimental studies, and the mechanisms remain incompletely understood. The ability to link microscopic properties of CRU to whole cell behavior is thus a powerful tool to investigate the arrhythmogenic role of abnormal Ca dynamics in cardiac disease. A study employing the multi-scale model of Restrepo et al.7073 and arrhythmogenic Ca waves resulting from heterogeneities in subcellular Ca alternans have been implicated as a mechanism in atrial dysrhythmia.74 Studying structure–function relationships and aberrant calcium handling in AF is complicated, however, by the fact that there are significant species-based differences in ultrastructure; whereas many large mammals, including humans, evince t-tubules in atrial cells,76 smaller mammals may not, and regional differences introduce further heterogeneity. The potential import of the t-tubular network in large mammal atrial EC coupling, despite the likely profound importance in subcellular Ca dynamics in these cells, has largely been overlooked thus far, and is an active subject in emerging modeling approaches at date of publication. Some human atrial myocytes do lack t-tubules (and thus compose an easily discretized structure as a starting point) and contain SR of both the junctional and non-junctional types, both of which have RyRs. An innovative mathematical modeling approach allowing detailed characterization of Ca movement within the three-dimensional volume of an atrial myocyte, displaying the centripetal Ca waves that occur within atrial myocytes during EC coupling and demonstrated that altering the strength of Ca release, RyR refractoriness, the magnitude of initiating stimulus, or the introduction of stochastic Ca channel activity could cause the nucleation of proarrhythmic traveling Ca waves.47 An influential combined experimental-computational study in human atrial cardiomyocytes from patients in sinus rhythm or with paroxysmal AF (pAF) showed increases in SR Ca leak and incidence of delayed after-depolarizations in pAF, underpinned by increased inactivation (phosphorylation) of the SERCA inhibitor protein phospholamban in pAF , and increased RyR expression and single-channel open probability. Computational modeling indicated that both RyR dysregulation and enhanced SERCA promoted SR Ca leak and spontaneous SR Ca-release events, causing delayed afterdepolarization and potential triggered activity in pAF.48 In addition, while Torres et al.77 developed a model including the spatial arrangement of the sarcolemma including t-tubular system in ventricular myocytes, their findings were explained by a modified local control model, which constrained the region of regenerative activation of non-junctional RyR clusters, which may prove useful for describing ECC in AF cardiac myocytes, with a sparse t-system More recent work into RyR cluster fragmentation and redistribution in persistent AF78 motivate the further use of computational models to elucidate the role of structural disturbance in atrial dysrhythmia.Electrical, structural, and Ca handling remodeling contribute to the perpetuation and progression of AF. Evidence has suggested a role for Ca leak and spontaneous SR Ca release events at several stages of disease progression,79 Cardiomyocytes from failing hearts exhibit a characteristic slowing of the rising phase of the CaT and additionally exhibit spatially nonuniform or dyssynchronous SR Ca release. A combined experimental/computational study from our groups used a computational model of the dyad to investigate the contribution of AP prolongation in a murine model of HF; ultimately, the study found that dyssynchronous Ca release in HF mouse myocytes does not result from electrical remodeling, but rather other factors, such as t-tubule reorganization  investigated effects of t-tubule disruption and other HF remodeling factors  on Ca alternans. While others have seen that detubulation reduces the likelihood of sparks,6 in this model, disruption removed LCCs from the associated CRUs, and resulted in orphaned RyR clusters, providing increased opportunity for spark-induced Ca sparks to occur.2 The authors found that this t-tubular disruption promoted Ca alternans by two distinct mechanisms (1)  by both CRU refractoriness and inter-CRU coupling, and (2) in the context of down-regulated SERCA, alternans was caused by an SR Ca load-dependent mechanism, independent of CRU refractoriness. The authors concluded that the mechanisms of Ca alternans for normal and down-regulated SERCA are different, and that t-tubular disruption promotes Ca alternans by both mechanisms, which may contribute to alternans at different stages of HF.81The abnormalities in Ca handling occur at nearly every point of Ca cycling in the failing heart cell, including activation and termination of SR Ca release, diastolic SR Ca leak, and SR Ca uptake.82 Clearly, advancing computational models via spatially resolved approaches now relies in part upon advances in experimental and imaging technologies which permit leaps in computational models.83Multi-scale meshes are key for computational studies of structure–function relationships in ECC. An early study aimed at developing an approach for spatial reconstruction of structures involved in calcium handling reconstructed clusters of RyRs together with the sarcolemma as based on dual labeling and three-dimensional confocal imaging of myocytes, leading to three-dimensional stacks of cross-sections; digital image processing was applied to deconvolve, filter, and segment image stacks.85 Three-dimensional electron microscopy technologies such as electron tomography have been able to determine realistic nanogeometries of membrane junctions  and associated t-tubules. Labeling with antibodies has allowed examination of the three-dimensional distribution of RyRs with confocal microscopy,86 revealing couplon geometries later used in detailed computational models.45 At the same time, super-resolution light microscopy has gone beyond the diffraction limit to determine the distribution of smaller dyadic molecules, such as LCCs, at unprecedented resolutions, offering insight into the central machinery controlling cardiac ECC via calcium signaling.87 Computational models built upon such technologies are able to furnish unprecedented insight.58Advances in microscopic imaging technologies such as serial block face scanning electron microscopy (SBF-SEM) now allow description of new micro-domain in cardiomyocytes.88 Other recent approaches have combined fluorescence resonance energy transfer (FRET), simulated-annealing , cryo-electron microscopy, and crystallographic data to locate a biosensor peptide bound to RyR Ca channels89 and have targeted a new sensitive Ca biosensor to the junctional space, where it co-localized with t-tubules and RyRs, allowing selective visualization and measurement of nanodomain Ca dynamics in intact cells.90 These multi-scale experimental and imaging approaches will offer mechanistic insights into CRU RyR operations in health and in disease states, and additionally offer potential for future inclusion in mechanistic computational modeling. Furthermore, emerging super-resolution single-molecule localization microscopy (SMLM) techniques offer an order of magnitude improvement over resolution of conventional fluorescence light microscopy; nanometer-scale distributions of multiple molecular targets can be resolved. In conjunction with the next generation of electron microscopy, SMLM has allowed the visualization and quantification of intricate t-tubule morphologies within large areas of muscle cells at unprecedented levels of detail, as recently reviewed.91 Novel and emerging imaging methods will enable the incorporation of detailed subcellular structural and functional information into the next generation of computational models (Correlated light and electron microscopic (CLEM) imaging is a powerful method wherein each imaging mode provides unique information for dissecting cell and tissue function at high resolution.l models , providiIn the present review, we have focused on the development of structural models of cardiac Ca dynamics, introducing the reader to the development of models of subcellular Ca handling in cardiomyocytes, with specific focus on progress in recent years. Computational modeling and simulation have helped to uncover the extent to which macroscopic Ca release events are intrinsically controlled by the type and number of individual LCCs and RyRs in the CRU, the relative spatial localization of the two channel types and the geometry of this functionally significant nanodomain, as well as the role of CRU organization at the cell level.Computational models have additionally moved towards the level of the whole myocyte, generally stepping up dimension and complexity in geometry. Both subcellular models investigating spark dynamics at the level of the single CRU and physiologically detailed models of whole-cell subcellular Ca cycling including networks thousands of CRU have been developed, at present seeking to combine the data emergent from newer imaging technologies to gain multi-scale insight into calcium-driven processes. This research has offered new knowledge into Ca spark termination, and, most recently, long-lasting Ca sparks. Structural distribution of CRU have additionally been shown to affect dynamics of Ca waves. Biophysical models have furthermore been employed to show that Ca alternans emerges as a collective behavior of Ca sparks, determined by the CRU network, via randomness of Ca spark activation, refractoriness of a CRU after a Ca spark, and recruitment, inducing Ca sparks in adjacent CRUs. Other computational strategies have offered new insight in the context of AF, wherein research revealed the role of RyR cluster fragmentation and redistribution on Ca remodeling in persistent AF, as well as HF, where the role of t-tubular disruption on electrical abnormalities  has been studied.Finally, novel labeling and imaging techniques now permit selective visualization at the nanodomain in intact cardiac myocytes, offering needed intelligence into Ca operations in health and disease, as well as a platform for the next generation of mechanistic computational models. These emerging multi-modality experimental methods will enable incorporation of detailed subcellular structural as well as functional information, providing powerful new computational tools for insight into the dynamics underpinning excitation and contraction in the heart.


Human parvovirus 4 (‘PARV4’) is a small DNA tetraparvovirus, first reported in 2005. In some populations, PARV4 infection is uncommon, and evidence of exposure is found only in individuals with risk factors for parenteral infection who are infected with other blood-borne viruses. In other settings, seroprevalence studies suggest an endemic, age-associated transmission pattern, independent of any specific risk factors. The clinical impact of PARV4 infection remains uncertain, but reported disease associations include an influenza-like syndrome, encephalitis, acceleration of HIV disease, and foetal hydrops. In this review, we set out to report progress updates from the recent literature, focusing on the investigation of cohorts in different geographical settings, now including insights from Asia, the Middle East, and South America, and discussing whether attributes of viral or host populations underpin the striking differences in epidemiology. We review progress in understanding viral phylogeny and biology, approaches to diagnostics, and insights that might be gained from studies of closely related animal pathogens. Crucial questions about pathogenicity remain unanswered, but we highlight new evidence supporting a possible link between PARV4 and an encephalitis syndrome. The unequivocal evidence that PARV4 is endemic in certain populations should drive ongoing research efforts to understand risk factors and routes of transmission and to gain new insights into the impact of this virus on human health. PARV4 is a small non-enveloped, single-stranded DNA virus with a genome of approximately 5 kb, translated as two major and two minor open reading frames. Classified as a member of the genusTetraparvovirus, in the familyParvoviridae (sub-familyParvovirinae), it sits phylogenetically alongside porcine and bovine hokoviruses3, while its closest human-tropic relatives are well-characterised B19V (genusErythroparvovirus) and human bocaviruses (genusBocavirus) (Human parvovirus 4 (‘PARV4’) was first described in 2005avirus) .4, but elsewhere is found confined only to certain high-risk groups5. The first reported identification of PARV4 was from an injecting drug user with hepatitis B virus (HBV) infection, who was screened for viral infections following presentation with influenza-like symptoms1. Based on this index case, subsequent studies in North America and Western Europe focused mainly on groups with risk factors for parenteral infection and those infected with other blood-borne viruses (BBVs). In these settings, a clear picture has emerged in which PARV4 infections are consistently and strongly associated with HIV, HBV and HCV, mostly in the setting of persons who inject drugs (PWIDs) and those with a history of multiple transfusion10. Despite attempts to identify it outside this setting, infection has not been detected in household contacts of seropositive individuals11 and is infrequent in the general population12.Ongoing investigation of PARV4 is being driven mainly by several intriguing features of its distribution: it is endemic in certain geographic areas15. Acute infections associated with viraemia were detected at a frequency of 8.5% among young children in Ghana16.However, groups working in Africa have reported a completely different population epidemiology: in this setting, the detection frequency of PARV4 IgG (indicative of current or past exposure) ranges from 30% to 50% in the general population, without any consistent relationship with BBVsThe clinical syndromes that have been described in association with PARV4 are summarised in2, although we have also drawn upon some older references where they are fundamental in supporting our current understanding. Crucially, there are still many gaps in the story; therefore, we have also set out to identify and highlight important questions for future study.This article seeks to summarise recent advances that have been made in understanding and characterising the epidemiology, immunology, phylogeny, and pathophysiology of PARV4. We have maintained a primary focus on updates made since our previous review of the topic in 201418, the Middle East19, and South America21; we have summarised these data inThe most substantial updates to the PARV4 literature are studies to determine the prevalence of infection in geographic areas that had not previously been represented. This includes new studies in Scandinavia19. However, in this study, the background prevalence of viraemia in healthy blood donors was also high at 17%19. Higher seroprevalence was also reported in Scandinavian subjects in the setting of HIV infection; the PARV4 IgG detection frequency was 8% among HIV-positive children17, while the background population seropositivity rate was less than 1% in adults and absent in children22. Stratification of risk factors in a French study reported the highest PARV4 prevalence in PWIDs, especially among those who were HIV-infected, but also among men who have sex with men (MSM), particularly those likely to have been exposed in the 1980s12.Based on the strong relationship between PARV4 and HIV, HBV, and HCV co-infection in North American and European populations, several studies have compared PARV4 exposure (screening for PARV4 IgG or DNA or both) in HIV-positive and HIV-negative groups in different settings. In Iran, HIV infection (with or without HCV co-infection) was reported to be associated with a high prevalence of PARV4 viraemia (35%)23. Although vertical transmission has previously been demonstrated in another setting24, there was no concordance between maternal and child serostatus, suggesting that maternal transmission is probably not a major contributor to the overall burden of infection in South Africa23. The clear trend towards increasing acquisition with age is consistent with a broader environmental source of PARV4 infection.Our own study of a cohort of mothers and children in Kimberley, South Africa, was comparable to previous reports from sub-Saharan Africa in finding an overall PARV4 seroprevalence of 37% with no evidence that HIV infection was a risk factor21. Among 113 subjects with HTLV-1 infection, seven (6%) were positive for PARV4 DNA, two of whom also had HIV or HCV infection or both. Based on a history of blood transfusion in one of these individuals, it was postulated that this represents the most likely route of acquisition of all three viruses. However, the remaining five cases had no other co-infecting BBVs and no history of injecting drug use or blood transfusion, leading to the conclusion that other transmission routes of PARV4 transmission may also be operating21. Another study published by the same group identified PARV4 viraemia in 2–5% of individuals either donating blood or receiving transfusions of blood products20. Neither of these Brazilian studies screened for PARV4 IgG, so the prevalence of PARV4 exposure in this setting remains unknown21.A potential association between PARV4 exposure and infection with another BBV, human T-cell lymphotrophic virus (HTLV), was described in a Brazilian study5. Relatively few new PARV4 sequences have been reported over the period that we have reviewed, and although incremental additions to the sequence database have been made over recent years  but show relatively restricted sequence variability; in both the non-structural (NS) and capsid-encoding genome regions, there is less than 3% amino acid (8–9% nucleotide) sequence divergence between genotypes  has been identified in European and North American cohorts•13. We have recently derived full-length PARV4 sequences from an adult and child in South Africa (GenBank accession numbers KU871314 and KU871315), which cluster together with genotype-3 sequences.Genotype-3 has been consistently identified from African cohorts33. Among a small cohort of health-care workers, IgG seropositivity was strikingly high at 60%; half of these had a positive IgM that was sustained over the study period, and viraemia was detected at one of several sampling time-points33. In the second study, this time focusing on a high-risk PWID cohort, IgM was reported as remaining positive for up to 21 months31. Meanwhile,in vitro experiments have demonstrated a sustained high-magnitudeex vivo CD8+ T-cell response to PARV4 NS peptide34. Prolonged IgM-positivity and sustained high-magnitude T-cell responses together suggest a sustained or relapsing/remitting exposure to viral antigen. Tissue homing and sites of latency are unknown, but existing data suggest that bone marrow, the respiratory tract, liver and gut might represent potential sites of viral replication36. Skin has also been highlighted as a potential reservoir site for B19V37, although—to the best of our knowledge—no study has investigated this as a site of PARV4 replication. The role of capsid proteins in parvovirus infections has been recently reviewed38, although there are no specific functional or structural data for PARV4.Various reports provide preliminary evidence that PARV4 may not be completely cleared after acute infection, suggesting that it has the potential for latency and reactivation. Two studies in Taiwan have sought to describe serological responses to PARV4 infection by undertaking longitudinal follow-up of their cohortsTo date, determining the clinical impact (if any) of PARV4 infection remains perhaps the most uncertain area of research into this virus, despite the medical importance of establishing such disease associations. A wide range of potential infection outcomes has been proposed  and blood of two39. However, it remains uncertain whether PARV was actually the agent of the observed disease, or a bystander that was coincidentally detected in a highly exposed population. Neither this nor the previous study32 included a control group in which the background incidence of PARV4 infections could have been evaluated. It is additionally possible that detection of PARV4 DNA in CSF in these two studies simply represents reactivation of the virus in the central nervous system in the context of other pathology.The most significant addition to the literature builds on an earlier report linking PARV4 with an encephalitis syndrome in Bellary, South India40. One of these is to use ‘mixture models’, which estimate population seroprevalence from the complete screened dataset rather than classifying each individual sample as positive or negative40. Application of these new analytical methods to existing PARV4 serosurvey datasets has yet to be performed but may refine prevalence estimates and allow for better comparison between studies.One approach to the determination of PARV4 serostatus is to use an enzyme-linked immunosorbent assay (ELISA)-based approach with an optical density read-out that is calibrated as positive or negative. However, the choice of a fixed cut-off above which threshold samples are termed ‘positive’ can be problematic and evidently has bearing on the final estimation of prevalence; the choice of this threshold evidently affects sensitivity and specificity of the test, and may need to be altered in light of the consideration of the primary reason for screening (diagnosis versus seroepidemiology). This effect is exemplified by recently published simulations, alongside discussion of alternative approaches that set out to quantify population prevalence41. The authors report that their method reliably discriminates between PARV4 genotypes, and use quantitative PCR to measure viraemia41.A novel polymerase chain reaction (PCR) assay for genotyping and quantifying PARV4 was published in 201442. Although modern procedures for viral inactivation may effectively remove parvovirus infectivity, PARV4 is more robust than B19V to heat and other virus inactivation methods used in blood product manufacture, and there is ongoing discussion about the need to implement donation screening for PARV4 DNA and/or to enhance measures to ensure that the virus is eradicated from blood products for transfusion45.Consistently high detection frequencies of anti-PARV4 antibodies in sera of haemophiliac individuals provide strong evidence for some transmission via the use of clotting factor concentrates10. However, the results of such studies are disparate, as a previous study from the same group did find PARV4-positive pools46. Studies outside the UK that have screened blood donors by PCR have found frequencies of 0% in Italy35; 3–4% in Brazil20, Thailand9, and North America25; and as high as 17% in Iran19.Blood donors have been screened as a component of several studies  has been associated with foetal loss in pigs in China52.There is increasing evidence that infections with porcine and bovine hokoviruses are endemic in both wild and domestic animals; most of these recent animal data are simply detection studies and do not provide any new data about pathogenicity. These include the frequent detection of porcine hokovirus in hunted wild boar in Portugal53. However, since most of the suggested pathogenicity has been attributed to protoparvoviruses or copiparvoviruses, we cannot necessarily infer any significance to tetraparvoviruses. Nevertheless, the widespread isolation of parvoviruses, particularly from domestic animals, should raise concerns about the potential risk of inter-species transmission events leading to the possibility of more pathogenic viruses crossing into human populations.As livestock pathogens, these organisms are potentially implicated as a cause of significant economic losses in agriculture52. In the longer term, this kind of study may provide further insights into the nature and mechanism of host-virus interactions.A recent study of microRNA expression in porcine parvovirus infection describes upregulation of microRNAs that are known to be immune system regulatorsAs this review illustrates, our understanding of PARV4 continues to advance gradually, but there are still many important unresolved questions, and the significance of this infection to human health remains uncertain. The striking difference in population epidemiology in developed and developing countries currently remains unexplained, and it is uncertain to what extent differences in virus properties or host characteristics account for the marked differences in population seroprevalence. For the former, it is plausible that genotype-specific amino acid substitutions underpin differences in the route, mechanism, or efficiency of transmission. From the host side, it is possible that differences in human genetics, prevalent co-infections, or environmental, behavioural, or iatrogenic exposure account for differences in seroprevalence and risk factors between continents.in vitro system is still needed to help us understand the biology of PARV4 in more detail, including characterisation of tissue tropism, productivity of cellular infection, the influence of co-infecting viruses, and the mechanisms underlying viral suppression by the immune system.Ongoing diligent scrutiny of carefully characterised clinical cohorts will be required to cement any associations with human disease; this may require larger collaborative efforts than have been undertaken to date. An35. Secondly, we know that viral infections are relevant to the host in more diverse ways than just the effects of primary infection; they may shape immune ontogeny, influence the outcomes of infection with other pathogens54, and drive or control oncogenesis. Understanding viral biology also allows us to draw on these agents as a resource for vaccine design, as exemplified by the adenovirus constructs used in vaccine trials for HIV56 and HCV57.This review highlights a number of compelling arguments in favour of advancing our understanding of PARV4. Firstly, this agent is endemic in some human populations; even if pathology emerges in only a small subset of infected individuals, this may still be important in terms of overall case numbers. Putative associations with significant pathology may be particularly relevant for certain vulnerable groups, including those with other chronic viral infection , those with solid organ or bone marrow transplantation, and recipients of human blood or tissue transplantTherefore, whether PARV4 turns out to be an innocent bystander or an elusive human pathogen, there are robust reasons for advocating ongoing clinical and research efforts to further our understanding of epidemiology and the current and future potential significance to human health.B19V, parvovirus B19; BBV, blood-borne virus; CSF, cerebrospinal fluid; HBV, hepatitis B virus; HCV, hepatitis C virus; HIV, human immunodeficiency virus; HTLV, human T-cell lymphotrophic virus; NS, non-structural; PARV4, human parvovirus 4; PCR, polymerase chain reaction; PWID, person who injects drugs.


Cellular senescence is a potent tumour suppressor mechanism whereby cells irreversibly exit from the cell cycle in response to excessive cellular stress such as DNA damage or oncogene activation. Senescence thus prevents uncontrolled proliferation and tumourigenesis. Senescent cells however maintain a pro-growth pheno-type which in the absence of proliferation drives increased cell size, increased organelle content (including mitochondria and lysosomes) and secretion of pro-inflammatory signals , 2. The in vivo with age and the highly inflammatory nature of these cells may negatively impact the surrounding cells and tissues. Clearance of p16-positive (senescent) cells improves both health- and life-span in rodent models [Both mTORC1 and senescence are intimately linked to aging and age-related phenotypes . The burt models  while rat models . TherefoDespite the central role for mTORC1 activity in cell senescence, the mechanisms controlling mTORC1 and how it supports the strong pro-growth phenotype are unknown. In proliferating cells, mitogenic signals including growth factors, energy and amino acid availability tightly regulate the activity of mTORC1 to balance anabolic  and catabolic (autophagy) processes . We demoWe have only just begun to unravel the complex rewiring that occurs during senescence to drive this insensitivity but evidence suggests that changes in both growth factor pathways and autophagy-dependent amino acid availability contribute. Firstly, growth factor signalling through the PI3K/Akt pathway persists in starved senescent cells. This is driven, via poorly understood mechanisms, by hypopolarisation of the plasma membrane which causes defects in primary cilia formation. As a result, the mTORC1 negative regulator, TSC2 is not robustly recruited to lysosomes and mTORC1 remains active. Interestingly, hypopolarisa-tion of the plasma membrane directly contributes to the acquisition of senescence since long term treatment to maintain plasma membrane potential delays the onset of replicative senescence. It's not clear how this reduced membrane potential occurs, for example whether it is simply due to increased cell size , or reduced energy, or imbalance of NADP(H)/ROS levels. How hypopolarisation of the plasma membrane subsequently leads to a failure of cilia growth and persistent signalling through PI3K/Akt pathway, is also not clear. Growth factor defects downstream of cilia have been reported previously . One hypSecondly, autophagy appears to play a complex and somewhat contradictory role in senescence, similar to that seen in many cancers. Senescent cells have elevated levels of autophagy in basal conditions and we demonstrated that this elevated autophagy supports mTORC1 activity and maintains more mTORC1 at lysosomes compared to control cells. At the same time, persistent mTORC1 signalling restrains autophagy to non-toxic levels. Inhibition of mTORC1 or perturbation of autophagy leads to senescent cell death indicating that they rely on mTORC1 and autophagy for their survival in stress conditions. More studies are required to tease out the exact mechanisms of this cell death and it will be interesting to try and mechanistically uncouple or directly link mTORC1 and autophagy defects in senescence.in vivo.Understanding the basic mechanisms driving cellular aging is an increasingly important question in biomedicine today. Interventions to improve healthspan could have far reaching societal and economic impacts. Insights from cell senescence are equally important to those studying basic mechanisms of cell growth, aging and cancer biologists. In addition, our findings suggest that mechanisms described in senescence could also be of interest in the study of ciliopathies. While we continue to work out the basic mechanism driving and supporting senescence, one of the most acute questions that remains to be answered is whether coupling dietary interventions and direct targeting of mTORC1/autophagy can be exploited to promote the clearance of senescent cells


Tumors in the pituitary gland are typically benign but cause serious morbidity due to compression of neighboring structures and hormonal disruptions. Overall, therapy efficiency remains suboptimal with negative impact on health and comfort of life, including considerable risk of therapy resistance and tumor recurrence. To date, little is known on the pathogenesis of pituitary tumors. Stem cells may represent important forces in this process. The pituitary tumors may contain a driving tumor stem cell population while the resident tissue stem cells may be directly or indirectly linked to tumor development and growth. Here, we will briefly summarize recent studies that afforded a glance behind the scenes of this stem cell connection. A better knowledge of the mechanisms underlying pituitary tumorigenesis is essential to identify more efficacious treatment modalities and improve clinical management. Pituitary tumors represent the most common intracranial tumor type , 2. AlthDespite sizeable benefit of current treatment procedures, including transsphenoidal resection, irradiation, and medicines, therapy efficiency remains suboptimal with important negative impact on health and quality of life , 6–8. MoAs of today, little is known on the molecular and cellular underpinnings of pituitary tumorigenesis , 2, 6. AIn this Perspective, we will discuss the potential stem cell connection of pituitary tumors from three angles. First, we briefly describe recent findings pointing to the presence of putative “tumor stem cells.” Then, we give a short overview of what is known on the behavior of the tissue’s own stem cells during tumorigenesis in the gland, thereby revealing possible links. Finally, we bring together findings on pathways generally known to regulate (tumor) stem cells.During the last decades, cancer stem cells (CSC) were identified in various types of cancer –11. CSC in vitro property of stem cells) displaying expression of some general stemness markers (like nestin and CD133) and possessing some—although limited—differentiation capacity . These cells had higher sphere-forming capacity and elevated SOX2 gene expression. An earlier study already reported elevated gene and protein levels of SOX2 in a putative TSC population, as identified by side population (SP) efflux capacity for Hoechst dye   . Senescence may explain why pituitary tumors typically remain benign (Drd2−/−) mouse model (Drd2−/− mice develop prolactinomas and it was observed that the Drd2−/− pituitaries have a greater proportion of SP cells and of proliferating (Ki67+) SOX2+ cells than control pituitary tissue  . Efficiell line)   predicting a poor in vivo growth propensity. Moreover, being from benign tumors, TSC may need to be implanted in their natural habitat to enable propagation; however, it is technically very difficult to implant cells orthotopically in the pituitary region. Nevertheless, conclusive identification and characterization of an unambiguous TSC population would significantly deepen our knowledge on the as yet poorly understood mechanisms of pituitary tumor pathogenesis and unveil potential novel targets for therapeutic interventions.Taken together, particular TSC candidates in pituitary tumors have been advanced, but definitive evidence of self-renewable and serially transplantable tumor-initiating cells that regrow the original tumor with high(-er) efficiency, has not yet been provided Table . It shouWhat is the position of the pituitary’s own resident stem cells in the process of tumorigenesis in the gland? Are these stem cells directly involved in generating and growing the pituitary tumors (thus in generating the TSC), or do they become activated because of the threatening tumorigenic event in their tissue? Recent studies revealed that pituitary stem cells are activated in other kinds of jeopardizing events occurring in the pituitary like cell-ablation injury –43. Here+) cells or in SOX2+ pituitary stem cells induced a transient proliferative response in the SOX2+ cell population  showed that the mutant β-catenin-expressing SOX2+ cells did not directly give rise to the ACP tumor, but induced the tumor and promoted the proliferation of the surrounding (tumor) cells (Table via the production of paracrine factors belonging to key (stemness) pathways  (+ and PRL+) pituitary cells, indicating the importance of the (mutated) stem cells as paracrine signaling center (+ cells in human PCP (known to predominantly harbor BRAF mutations), and advanced the hypothesis that these cells may be driving the growth of the tumor because they represent the major proliferative cell population within the tumor  at this early age (+ lineage-derived and SOX2+ cells in the close proximity of tumors developing in the pituitary intermediate lobe (IL) of mutant retinoblastoma (+/−Rb) mice   , 32. Intg center  Table 1+ cells ohe tumor . This asme study . Howeverarly age  (Table 1/−) mice , thus suell zone  (Table 1atients) , suggest+ lineage tracing in the −/−Drd2 mouse model developing prolactinomas in the AP. The SOX2+ cell progeny  increased in abundance during tumor development and growth, but co-localization of YFP and PRL was low, indicating that the large majority of the tumor (PRL+) cells did not descend from the SOX2+ (stem) cells , the mammalian index securin, in early endocrine pituitary progenitor cells  leads to the eventual development of uni- or pluri-hormonal microadenomas . These findings suggest that early pituitary progenitor cells have the capacity to directly give rise to tumors, although a paracrine impact was not excluded  Table 11. TransgTaken together, recent studies provide arguments that the pituitary stem cells may be involved in the process of tumor development and growth in the gland. The stem cell activation, as, for instance, due to genetic mutations in the cells, may lead to paracrine stimulation of the proliferative activity of neighboring cells. The stem cell activation may also represent a defense reaction to the tumorigenic event occurring in the other cell population(s) in the gland, which may paradoxically feed the tumor by paracrine influences. On the other hand, pituitary tumors (or at least certain histotypes) may directly descend from (mutated) tissue stem cells as shown in tumors of other tissues –18. LineGiven their long-lived self-renewal potency, tissue stem cells must be kept innocuous by strict regulatory control. From the studies described above, pituitary stem cells appear to reside in an activated state during tumorigenesis in the gland. This activation may be due to, or associated with, aberrant activity of the signaling pathways regulating the stem cells. Knowledge on aberrant functioning of these pathways in pituitary tumorigenesis is scarce. Here, we summarize what is known about the major stem cell signaling pathways  in pituitary tumors, and where investigations have been conducted, in the candidate TSC populations Table .NOTCH3 and JAG1 expression was found upregulated in NFPA in comparison to normal human pituitary tissue  was found in the human pituitary tumor SP (+ cell populations) showed increased expression of DLL1, JAG2, NOTCH1, and NOTCH4  in the SP compared to the predominant non-SP cells   in comparison to normal pituitary tissue  , 4, 32. y tissue , 56. By y tissue .CDH1, CLDN1) and a corresponding increase in mesenchymal markers  as well as EMT mediators  and regulators   .GLI1 was found to be overexpressed in somatotropinomas and corticotropinomas   , 56, 66,and SHH) . Transge. However, available studies are still scarce and current pituitary tumor mouse models do not highly recapitulate the human disease. Many more stem cell lineage tracing studies are needed to convincingly unravel the stem cell link(s), which also may be different according to pituitary tumor type. Alternatively, specific ablation of the stem cells  woulAnimal experiments were approved by the KU Leuven Ethical Committee.HV compiled the literature data and wrote the manuscript. HR compiled the data for part of the review, and provided the figure for which she performed the experiments.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


ASDs are characterized by deficits in both social behavior and cognitive function. There is a strong genetic basis underlying ASDs that is highly heterogeneous; however, multiple studies have highlighted the involvement of key processes, including neurogenesis, neurite growth, synaptogenesis and synaptic plasticity in the pathophysiology of neurodevelopmental disorders. In this review article, we focus on the major genes and signaling pathways implicated in ASD and discuss the cellular, molecular and functional studies that have shed light on common dysregulated pathways using HighlightsAutism spectrum disorder (ASD) has a prevalence of 1 in 68 children in the United States.ASDs are highly heterogeneous in their genetic basis.ASDs share common features at the cellular and molecular levels in the brain.Most ASD genes are implicated in neurogenesis, structural maturation, synaptogenesis and function. Autism spectrum disorder (ASD) comprises a heterogeneous class of neurodevelopmental disorders characterized by impaired social interactions, restrictive interests and repetitive behaviors Landa, . ASD typThe human brain contains about 86 billion neurons making trillions of connections  gene database shows that ASD causative genes display vast diversity involving up to one thousand genes , T-Box Brain Protein 1 (TBR1), and Fragile X Mental Retardation 1 (FMR1), have also been linked to ASD , will migrate in an “inside-out” fashion to establish the six layered neocortex. This mode of migration forms deeper layer neurons first, followed by later born neurons that migrate to form the outer cortical layers  gene was the first gene to be clearly associated with macrocephaly in ASD  was identified through surveys of de novo variants linked to ASD . MCPH1 is a gene expressed during fetal development and mutations in MCPH1 produce microcephaly  is a condition that displays with significantly reduced head circumference that develops during the prenatal period  is involved in orientation of the mitotic spindle, regulation of mitosis and cytokinesis  are associated with microcephaly and other cortical abnormalities in humans  encodes a brain-specific T-box transcription factor, which plays an important role in neurodevelopment and migration and has been identified as a causative gene for ASD , which has been identified as an ASD and ID associated gene  were found to be implicated in ASD and epilepsy  is a neuronal cell surface antigen that regulates neuron-glia interactions that plays a major role in neuron migration  is involved with the regulation of neuron proliferation, migration, and intracellular transport as part of the Lis1/Nde/Ndel1/cytoplasmic dynein complex  was the first gene identified with an involvement in disrupted neuron migration  genes are part of the homeodomain transcription factor family which is related to the Drosophila distal-less (Dll) gene  is an X-linked gene that codes for a protein that functions as a transcriptional repressor and an activator  is the gene underlying the disorder Fragile X syndrome (FXS), which results in ID with 15%–30% of patients also displaying ASD phenotypes , a GTPase. In agreement with this, Rac1 was found to bind FMRP and affect dendrite arborization, indicating that FMRP’s role in dendrite morphogenesis could in part be through its interaction with Rac1 , a binding partner of FMRP, is a protein that has recently generated interest as its genetic locus is chr15q11.2, a susceptibility area in ASD. When bound to FMRP, CYFIP1 can inhibit translation and regulates actin dynamics. This can therefore regulate the growth and removal, as well as the labiality and morphology of spines  produce neurofibromas and between 30% and 65% of children with NF1 mutations display learning disabilities and display significantly higher rates of autism, suggesting a causal relationship to autism  is the causative gene for Angelman syndrome, a developmental disorder characterized by language impairments, ataxia, ID and hyperactivity  belongs to the family of MAP kinase kinase kinases (MAPKKK) and is located in chromosome 16, an area associated with increased ASD-risk  and release of neurotransmitter is crucial for proper signal transmission to the postsynaptic neuron. The postsynapse is characterized by the presence of receptors that bind neurotransmitters released from the presynapse, which initiates signaling cascades that ultimately propagate the electrical signal in postsynaptic neuron. Receptors are clustered in a region called the postsynaptic density (PSD) in the excitatory synapse.Synapses are classified as excitatory and inhibitory, depending on whether they use glutamate or γ-aminobutyric acid (GABA) as their main neurotransmitter, respectively. Additionally, the formation and structure of excitatory and inhibitory synapses is uniquely different. Whereas excitatory synapses made on dendritic spines, inhibitory synapses are formed directly on the dendritic shaft. Additionally, both excitatory and inhibitory synapses have distinct proteomic profiles to specialize each synapse with the appropriate receptors and signaling molecules. Synaptic dysfunctions, whether they arise from functional mutations in pre- or postsynaptic proteins, are a common underlying pathology in ASD and are discussed in detail below.NRXN) are synaptic adhesion proteins that localize to the membrane of the presynapse and bind Neuroligins (NLGNs), which are localized on the postsynaptic membrane. There are three genes within the NRXN family  with multiple mutations or copy number variations having been identified in NRXN family members in ASD diagnoses  frequency  are a family of presynaptic proteins involved in vesicle-mediated neurotransmitter release and neurite outgrowth  have been identified in a family with epilepsy and autistic phenotypes, suggesting its link as a causative factor for ASD  are cell adhesion proteins that localize to the postsynaptic membrane and play an integral function in synapse formation via binding their presynaptic partners, NRXNs. In humans NLGN family is composed of five genes (NLGN1/2/3/4/4Y). The large extracellular domain of Nlgns have a high sequence similarity to acetylcholinesterase and is required to bind to β-Nrxn during synapse formation  through its SH3 domain  show multiple behavioral and molecular abnormalities that are linked to ASD pathology. DLG4 KO mice display impaired communication and social interactions, decreased motor coordination, as well as increased anxiety and repetitive behaviors. Additionally, DLG4 KO mice display defects in dendritic spine morphology in the amygdala and aberrant expression of multiple synapse-related genes in the forebrain  is an important postsynaptic scaffolding protein that localizes to excitatory synapses. PSD-95 is composed of three PDZ domains that target it to the postsynapse, an SH3 domain, and a guanylate kinase domain on its C-terminal. Nlgn, NMDARs and potassium channels all interact with the PDZ domains on PSD-95. PSD-95 localizes to spine heads in excitatory synapses and has been shown to promote synapse stabilization. The E3 ubiquitin ligase, murine double minute-2 (Mdm2) ubiquitinates PSD-95 and subsequently binds with protocadherin-10 (Pcdh10), sending it to the proteasome to be degraded. Pcdh10 is an ASD-linked gene  gene have been reported in subsets of patients with ASD  are transmembrane proteins that function in cell-cell adhesion and play roles in neuron migration, dendritic growth, spine morphology, synaptogenesis and synapse remodeling  show no impairments in synaptic plasticity, indicating that impaired synaptic plasticity correlates with the delayed deficits observed in human RTT patients  mRNA in autistic cerebellar Purkinje cells has been identified in human autism samples  is a negative feedback response that serves to compensate for changes in network activity (Turrigiano et al., ASD is diagnosed at the behavioral level with the presentation of its core phenotypes of impaired social interactions, restrictive interests and repetitive behaviors. Although the etiological factors of ASD are highly heterogeneous, recent research has strongly pointed to common cellular events that are impaired in ASD, including neurogenesis, morphogenesis, synapse maturation and synaptic plasticity. In this regard, loss-, or gain-, of-function mutations in single genes that are causative for ASD have given researchers unique opportunities to make important mechanistic insights. A common theme emerging within the field is that in the developing brain, alterations in dendritic growth, synapse formation and synaptic function result in neuronal network dysfunction, ultimately leading to complex social and cognitive dysfunction. Further elucidation into these pathways, as well as advancements in gene therapies and targeted drugs to modulate these processes, could provide exciting and promising new therapies for the treatment of ASDs.JG and H-YM wrote and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.