Sudden cardiac death (SCD) remains the leading cause of death worldwide and is responsible for up to 20% of all deaths in the USA (Benjamin et al., 2019; Deo and Albert, 2012). The incidence of SCD increases exponentially with age, which poses a growing problem as the portion of the US population 65 years or older is estimated to increase to 15% by 2030 (Benjamin et al., 2019; Partridge et al., 2018). The vast majority of SCDs are caused by ventricular tachycardia/ventricular fibrillation (VT/VF) subsequent to myocardial infarction (MI) (Kolettis, 2013). Immediate clinical reperfusion interventions can limit the extent of acute ischemic injury and acute arrhythmic mortality post-MI, however progressive tissue remodeling in the days-to-years post-MI can establish a substrate and trigger for potentially lethal arrhythmias (Mendonca Costa et al., 2018). This tissue remodeling process is well described in young animals (van den Borne et al., 2010), but less is known about what changes to this process occur with age and how these changes increase risk of arrhythmia initiation and propagation.

We have previously characterized the efficacy of the New Zealand White rabbit as a model of the aging human heart. We showed that the aging rabbit heart recapitulates cardiac dysfunctions observed in aging humans, including aortic stiffening, reduced ventricular compliance, increased interstitial fibrosis, abnormal conduction in the His-Purkinje system, and lower thresholds for induced ventricular arrhythmias (Cooper et al., 2012). We also demonstrated defects in autophagy and mitochondrial function in isolated aged rabbit myocytes resulting in increased mitochondrial reactive oxygen species which oxidized the ryanodine receptor and promoted spontaneous Ca²⁺ release (Cooper et al., 2013; Murphy et al., 2019). To better investigate the interaction between post-MI tissue remodeling and arrhythmogenesis with age, we have established a minimally invasive surgical procedure to reproducibly infarct the rabbit heart regardless of age or variable coronary anatomy, whereby an embolic coil occludes the left coronary artery (Morrissey et al., 2017). Infarction by this method results in electrophysiological remodeling characteristic of human MI, including functional reentry anchored at the infarct border zone (IBZ), reduction in ejection fraction, and lower thresholds for monomorphic VT induced by programmed stimulation (Morrissey et al., 2017; Ziv et al., 2012).

Cellular senescence is a stress response characterized by irreversible proliferation arrest, resistance to apoptosis, and secretion of a collection of inflammatory cytokines, growth factors, and proteases termed the senescence-associated secretory phenotype (SASP) (Coppé et al., 2010; Rodier et al., 2009; Campisi and Robert, 2014). Transient senescence plays beneficial roles in young animals in wound healing by limiting fibrosis, in tumor suppression, and in development (Wang et al., 2011; Storer et al., 2013; Demaria et al., 2014). However, senescent cells accumulate with age in many tissues and accelerate many aging-associated pathologies in a paracrine manner via SASP-mediated chronic inflammatory signaling and/or in a juxtacrine manner via transfer of intracellular proteins to neighboring cells (Prata et al., 2018; Vicente et al., 2016; Burton and Krizhanovsky, 2014; Shibamoto et al., 2019; Kirschner et al., 2020; Biran et al., 2015). Genetic or pharmacological elimination of senescent cells with age slows the onset and progression of many aging pathologies, including atherosclerosis, diabetes, idiopathic pulmonary fibrosis, osteoarthritis, and neurodegenerative diseases (Baker et al., 2016; Baker et al., 2011; Childs et al., 2015; Zhu et al., 2015; Chang et al., 2016; Kim and Kim, 2019; Kirkland et al., 2017; van Deursen, 2019; Kirkland and Tchkonia, 2017).

In the adult infarcted wild-type mouse heart, senescent cells arise in the scar and IBZ around day 3 post-MI and are largely cleared by day 7 (Shibamoto et al., 2019; Zhu et al., 2013). Most of these senescent cells are cardiac myofibroblasts, the main cell type responsible for secreting extracellular matrix components forming the scar. This observation is consistent with epidermal wound studies in mice, suggesting a role for transient myofibroblast senescence as a normal part of the wound healing process in limiting fibrosis (Demaria et al., 2014). Infarction of adult constitutive p53 KO mice, in which senescence induction is impeded, results in increased fibrosis and decreased inflammation in the scar 7 days post-MI (Zhu et al., 2013). In a cell culture model of isolated mouse cardiac fibroblasts, senescent cardiac fibroblasts limit the proliferation of non-senescent cardiac fibroblasts in a juxtacrine but not paracrine fashion (Shibamoto et al., 2019). These results suggest a beneficial role for transient myofibroblast senescence in limiting fibrosis post-MI. Conversely, insights toward a pathological role of chronic cardiac senescence come from aging mouse models of MI. Treatment of aged mice with the senolytic drug navitoclax (i.e. a drug that specifically eliminates senescent cells) before or after MI significantly reduces senescence burden, improves cardiac function, mitigates cardiac remodeling, and reduces scar size post-MI, although the effects on arrhythmias has not been studied to our knowledge (Dookun et al., 2020). These results suggest that acute induction of senescence followed by timely clearance limits excess scarring, but persistence of cardiac senescence as seen with age can promote cardiac fibrogenesis and worsen cardiac function and might lead to increased risk of arrhythmias. Although these findings in mice are important, the mechanisms underlying a relationship between age-associated senescence and arrhythmogenesis is not well understood, particularly in an animal model like the rabbit whose cardiac electrophysiology is more functionally relevant to humans than that of mice.

Potential pro-arrhythmic effects of senescent cells could occur through a paracrine fashion via SASP components. Indeed, treatment of isolated rat and mouse cardiomyocytes with exogenous SASP components including IL-6, IL-1β, and TNF-α have pro-arrhythmic effects in ion channel remodeling (Francis Stuart et al., 2016; Aromolaran et al., 2018). Senescent myofibroblasts might be able to interfere with cardiomyocyte electrophysiology from relatively long distances through chronic inflammatory signaling. Alternatively, the direct cell-cell coupling via gap junctions of senescent myofibroblasts to cardiomyocytes at the IBZ might alter their electrophysiology more than coupling with non-senescent myofibroblasts. Such a process would establish regional heterogeneities in ion channel activity, action potential duration (APD), and other electrophysiological factors anchored at the IBZ that would permit reentrant current and therefore VT/VF.

We hypothesized that aged infarcted rabbits experience a persistence of senescent myofibroblasts in the scar and IBZ compared to young, and that these senescent myofibroblasts act in a paracrine or juxtacrine fashion to induce pro-arrhythmic remodeling in IBZ cardiomyocytes. Here, we demonstrate that aged rabbits compared to young exhibit increased peri-procedural deaths mostly due to VT/VF, consistent with prolongation of APD and alternans at the IBZ associated with higher frequency VF. We observed no difference in the size of the scar or IBZ geometry over the first 12 weeks post-MI between young and aged rabbits. However, whereas senescent cells in the young rabbit scar were largely cleared by 3 weeks post-MI, senescence of mostly myofibroblasts remained high in the aged rabbits up to 12 weeks post-MI and correlated with increased local expression of inflammatory cytokines. In ventricular tissue samples from aged infarcted human patients, we observed elevated levels of senescence markers, and most senescent cells appeared to be myofibroblasts. Using primary adult rabbit cardiac fibroblasts, we induced senescence via treatment with the drug etoposide. With this method, we did not observe any effect of exogenous or co-cultured conditioned media from senescent cardiac fibroblasts on the I_Kr current or APD of treated rabbit myocytes compared to conditioned media from proliferating cardiac fibroblasts. However, in both aged rabbit and human cardiac tissue, we observed senescent cardiac myofibroblasts in close proximity to IBZ myocytes, with the gap junction protein Cx43 appearing to couple the cells. Previous studies in rabbits have demonstrated a role for Cx43 in the coupling of myocytes and fibroblasts as evidenced by dye transfer and optogenetic studies (Camelliti et al., 2004a; Camelliti et al., 2004b; Schultz et al., 2019). Based on our electrophysiological and volumetric measurements of senescent and non-senescent fibroblasts, we performed computational modeling which suggested that coupling of myocytes with senescent cardiac myofibroblasts would result in prolongation of APD and lower thresholds for conduction block. Altogether, our results indicate a pathological role for the persistence of senescent cardiac myofibroblasts in directly exacerbating arrhythmogenesis at least via a direct cell-cell interaction through gap junctions with age post-MI. These findings suggest that targeted elimination of senescent cells post-MI could be an effective therapeutic method to mitigate senescence burden and combat arrhythmias in aged infarcted individuals.

Although the age-associated accumulation of senescent cells and the related detriments to cardiac function and chronic inflammation have been previously described (Walaszczyk et al., 2019), the relationship between senescence arising during and after scar formation post-MI and arrhythmogenesis is not well understood. Our experiments show that accumulation of senescent myofibroblasts in the scar is associated with a tissue microenvironment more susceptible to cardiac arrhythmias and elevated inflammatory signaling. Additionally, our findings suggest that senescent myofibroblasts in the IBZ may be exerting pro-arrhythmic effects on surviving myocytes in a cell-cell interaction mediated by myocyte-fibroblast coupling via gap junctions. We propose that persistence of senescent myofibroblasts is a major driver of arrhythmogenic tissue remodeling with age post-MI, and that the timely pharmacological elimination of senescent cells might alleviate risk of arrhythmias particularly in elderly infarcted patients.

From our MI surgical procedures, we observed significantly increased mortality of aged rabbits mostly due to peri-procedural VT/VF (Figure 1). These results are consistent with the age-associated increase in out-of-hospital mortality from cardiac arrhythmias resulting from MI (Benjamin et al., 2019). The reason for this increase in peri-procedural mortality with age is likely related to our previous observations of increased interstitial fibrosis, disorganization of the His-Purkinje system, and altered myocyte Ca²⁺ handling with age in non-infarcted aged rabbits, in that these age-associated changes likely increase peri-procedural mortality by lowering the threshold for arrhythmias triggered by the acute ischemic insult (Cooper et al., 2012; Murphy et al., 2019; Terentyev et al., 2014). Based on our previous observations showing low levels of senescence in non-infarcted young and aged rabbits (not shown), we posit that senescence likely does not play a role in peri-procedural arrhythmias.

The anatomical characteristics of the scar, including scar size, functional IBZ area, and dense and interstitial fibrosis, could influence age-associated differences in arrhythmogenesis. However, the fact that we did not observe any significant difference in the timecourse of scar size, IBZ area, and overall or interstitial fibrosis suggests that age-associated changes in other cellular processes, including cellular senescence, are driving the increase arrhythmogenicity that we observe from optical mapping studies. Our findings of overall scar size are consistent with our previous study showing 30% infarcted area of the left ventricle from our MI surgical procedure, and the present data suggest no epicardial infarct expansion occurs over time in young or aged rabbits. (Morrissey et al., 2017).

Electrophysiological remodeling at the IBZ includes separation of myocyte bundles via interstitial and replacement fibrosis and significant disruptions of APD and reductions in conduction velocity, myocyte-myocyte coupling, and anisotropy ultimately permitting unidirectional conduction block, sustained reentry, and subsequent VT/VF (Kolettis, 2013; Rutherford et al., 2012; Di Diego and Antzelevitch, 2011). Although these changes are well characterized in young animal models, we sought to investigate age-associated changes in these processes and their underlying mechanisms. From our optical mapping studies, we observed aged rabbit hearts 3 weeks post-MI exhibited more extreme arrhythmogenic remodeling at the IBZ compared to young, including relative prolongation of APD as compared to the RZ, spatially discordant alternans near the IBZ at relatively slow heart rate, and higher frequency of sustained spontaneous VF following burst pacing. These pathological characteristics indicate that aged rabbits undergo remodeling at the IBZ differently than young animals, culminating in a stronger substrate for arrhythmias anchored at the IBZ. Specifically, prolonged APD near the IBZ has been shown to facilitate a reentrant circuit around the scar (Campos et al., 2019). Meanwhile, in young rabbits, the significantly shorter APD at the IBZ compared to the RZ and scar can also induce and maintain arrhythmia through increasing APD dispersion and AP conduction block. This finding of shortened APD in the border zone of young rabbits is consistent with previous data using relatively young Yucatan minipigs (Hegyi et al., 2018). However, young infarcted rabbits experience less arrhythmias than aged infarcted rabbits, as indicated by the lack of observed voltage alternans at slow heart rate and slower VF frequency. The observation of similarly slower conduction velocity at the IBZ relative to the RZ in both young and aged rabbits is consistent with our histological observations showing no difference in the number or length of IBZ protrusions (Figure 2B).

The accumulation of senescent cells in many tissues has been shown to exacerbate age-associated pathologies via paracrine or juxtacrine mechanisms. Studies in mice have demonstrated increased senescence in the scar post-MI with age, the pharmacological clearance of which limits scar size and improves cardiac function and outcome (Walaszczyk et al., 2019). However, little is known about whether these findings translate to large animal models with more electrophysiological relevance to the human heart, or the mechanisms through which senescent cells might promote arrhythmogenesis in the aged infarcted heart. Here, we show that cellular senescence as measured by SA-β-gal and γH2AX staining between young and aged rabbits is similar for the first 2 weeks post-MI but persists in aged rabbits at 3 and up to 12 weeks post-MI in the scar (Figure 4A–E) and is associated with higher local expression of inflammatory SASP factors (Figure 4H). Consistent with previous findings from our group and others (Zhu et al., 2013), we found very few SA-β-gal-positive cells in the RZ of young or aged rabbits. These data, along with our previous results assessing young and aged non-infarcted rabbits, suggest a low baseline of senescence in the normal young and aged rabbit heart which is reasonable considering the relatively low proliferation of myocardial cells under baseline conditions. The similarly low levels of SA-β-gal in young and aged rabbits 2 weeks post-sham infarction indicate that the age-associated significant difference in senescence post-MI was not an artifact of the MI procedure. Additionally, we did not observe any evidence of senescent cardiomyocytes in young or aged rabbits at any timepoint (Figure 4C, bottom) as well as from human ventricular tissues samples from SA-β-gal staining, which differs from previous reports of mouse tissue (Anderson et al., 2019). This important observation suggests that the rabbit heart could be a more appropriate animal model than the mouse to study the effects of cardiac aging relevant to humans. Interestingly, we observed no difference in either total fibrosis of the LV free wall or interstitial fibrosis over time between young and aged rabbits even though we observed persistence of senescence in the aged rabbit heart over time compared to young. It is well known that the content of the SASP changes over time and depending on cell type and the induction source, and so it is possible that pro-fibrotic and anti-fibrotic SASP factors are present in functionally equivalent amounts ultimately resulting in no difference in fibrosis. This hypothesis is supported by our RT-qPCR data, indicating upregulation in expression of the pro-fibrotic factors TGF-β, TIMP1, and TIMP2 as well as anti-fibrotic factor MMP9. Further investigation into this hypothesis is warranted.

From our immunofluorescence staining, the high degree of αSMA signal in young and aged rabbits at 1 and 2 weeks post-MI and the subsequent decrease in αSMA signal is consistent with genetic lineage tracing studies in mice which suggest that myofibroblasts remain present in the scar but lose αSMA expression (Fu et al., 2018). Our observation that the percent of γH2AX+ cells that are αSMA+ remains high at 2 weeks post-MI when αSMA signal begins to decline suggests that most of the senescent cells present in the scar are αSMA+ myofibroblasts that lose αSMA expression after 2 weeks post-MI. This observation is consistent with previous studies characterizing the identity of senescent cells in the scar post-MI in mice (Zhu et al., 2013; Meyer et al., 2016). The relatively lower percent of CD31+ cells at any timepoint between young and aged rabbits is consistent with previous reports of cellular composition in the scar (Pinto et al., 2016). The small percent of γH2AX+ foci that were CD31+ reinforces our conclusion that myofibroblasts are the majority of cells undergoing senescence in the young and aged heart post-MI.

Our RT-qPCR data of young and aged rabbits 3 weeks post-MI further demonstrates differences between the senescence profiles of the aged rabbit and the aged mouse. Consistent with our SA-β-gal and γH2AX data, we observed an increase in the expression of p16, p21, and p53 in aged rabbits compared to young. However, the only SASP factors for which we measured a significant change in expression in the scar zone between young and aged were CXCL2 and TIMP2, whereas the contents of the cardiac SASP were largely different between young and aged mice (albeit with a non-canonical SASP) (Anderson et al., 2019). Given these results, special attention should be placed on conclusions for the relevance of senescence studies performed in mice in regard to their clinical relevance for humans. Similar to our SA-β-gal data, we observed a similar but lower magnitude of changes in overall expression between the young and aged rabbit IBZ, and no differences in senescence and SASP gene expression between the young and aged RZ. The significant decrease in IL-6 expression in the aged IBZ compared to young IBZ is interesting, however senescence and SASP signatures are known to be variable depending on cell line and senescence induction method, and this decrease in IL-6 expression has also been observed in studies of young and aged non-infarcted murine myocytes (Anderson et al., 2019). Overall, our data suggest that senescence and the inflammatory SASP is largely confined to the scar.

To investigate the clinical relevance of our observations of persistent senescence in the aged infarcted rabbit heart, we measured senescence in aged infarcted human ventricular frozen sections. We observed a relatively high percent of cells in the scar exhibited nuclei with three or more γH2AX foci (Figure 5C), indicating the presence of senescent cells in the human tissue, which may contribute to arrhythmogenic tissue remodeling leading to increased incidence of potentially lethal arrhythmias in the chronic phase post-MI. These γH2AX senescence data are similar to what we observed in the aged rabbit 12 weeks post-MI. From our αSMA analysis of human tissue, we observed a high percent of cells were αSMA+ unlike the progressive decrease in αSMA+ cells over time that we observed in the young and aged rabbits. Because the specific timing of MI is difficult to diagnose especially out-of-hospital, we are unable to ascertain how long post-MI the samples were at time of death. If senescent cells indeed persist in the aged human scar as we hypothesize, it is possible that growth factors like TGF-β in the chronic SASP activate fibroblasts in the months-to-years post-MI. Alternatively, the content of the SASP could differ from what we observe in rabbits, contributing to differential activation of myofibroblasts. Similar to our observations in young and aged rabbits, our γH2AX and αSMA double immunofluorescence assays indicate that the majority of cells with three or more γH2AX nuclear foci were also αSMA+, further suggesting that myofibroblasts are the predominant cell type undergoing senescence. Relatively fewer cells with three or more γH2AX nuclear foci were either vWF+ or CD68+, consistent with previous reports in mice, suggesting relatively fewer senescent cells are endothelial cells or macrophages, respectively (Zhu et al., 2013).

To better study the mechanisms by which senescence might be promoting arrhythmias with age post-MI, we established an in vitro method to induce senescence in adult rabbit cardiac fibroblasts. Low doses of the drug etoposide induced senescence, measured by SA-β-gal and γH2AX staining as well as RT-qPCR in a time-depending manner, with the vast majority of cells positive for senescence markers after 12 days of treatment with 20 μM etoposide (Figure 6). These data establish a platform to future studies screening the efficacy of senolytic drugs to eliminate senescent cells post-MI.

To investigate whether senescent cells might have a paracrine effect on myocytes, we treated primary isolated myocytes from 3-week-old rabbits with conditioned media harvested from proliferating (proliferating-CM) or senescent (SASP-CM) fibroblasts (Figure 7). From our patch clamping studies, we observed no significant difference in I_Kr current or in APD between proliferating-CM or SASP-CM groups. Separately, we co-cultured isolated myocytes with proliferating or senescent cardiac fibroblasts for longer durations and also found no significant difference in I_Kr or APD. These findings suggest that senescent rabbit fibroblasts likely do not act in a paracrine manner to disrupt the electrophysiology of rabbit myocytes, but further study is needed to verify this. Because we are limited by the number of commercially available assays to determine the specific contents of the rabbit SASP, we are unable to exclude the possibility that the conditioned media lacked physiologically relevant levels of SASP factors to induce a significant effect. Besides, components in the media used or the absence thereof might have blunted a paracrine effect. One could also envisage that degradation of conditioned media occurred between harvest and treatment, as well as potential issues with incubation period and responsiveness of the 3-week-old myocytes to the SASP. Additionally, transfer of the cells from the conditioned media to the patch clamping media might have allowed for rapid recovery of the cardiomyocytes prior to patch clamp recording, which would not be detectable from the data presented.

We next investigated whether senescent fibroblasts might directly couple with myocytes at the IBZ to influence pathological electrophysiological remodeling. Homo- and hetero-typic coupling occurs in the healthy and diseased heart via connexins, including Cx43 (Kohl and Gourdie, 2014). We observed a significantly higher percentage of senescent cells neighboring IBZ myocytes in aged rabbits 3 weeks post-MI compared to young. Our immunofluorescence studies suggest that Cx43 facilitates homocellular coupling between senescent adult rabbit cardiac fibroblasts, as well as heterocellular coupling between senescent myofibroblasts and myocytes at the IBZ of aged rabbits and human frozen sections.

Our computational modeling of proliferating and senescent myofibroblasts as well as simulations of cardiomyocyte-myofibroblast interactions in young and aged tissue shed critical light for explaining mechanisms by which senescent myofibroblasts might promote arrhythmogenic tissue remodeling with age post-MI. Although electrical remodeling in the IBZ is a complex phenomenon with multiple contributing factors, our results indicate that myocyte-fibroblast interaction becomes a potential contributor to arrhythmogenesis in the aged MI condition. A large, flattened morphology is one of the hallmark characteristics of senescent cells in other models (Kuilman et al., 2010), and we observed this for cardiac myofibroblasts both in vitro and in vivo. The larger size of senescent myofibroblasts likely explains the greater extrapolated values for in vivo capacitance, and all differences in modeling between proliferating and senescent myofibroblasts are driven by the larger capacitance of senescent myofibroblasts. Importantly, the prolongation in APD from our modeling of aged condition relative to young is consistent with our optical mapping findings from young and aged rabbits 3 weeks post-MI and validates the relevance of our modeling. From our S1S2 modeling under young and aged conditions, we would predict that aged rabbits would have higher risks for conduction block than young rabbits. Although we did not observe a significant difference in the CL at which VF was induced, VF frequencies were higher and heterogeneous in the IBZ (Figure 3D), suggesting that the prolongation of APD in myocytes coupled to senescent myofibroblasts would result in lower threshold for conduction block and wavebreak, overall driving faster VF frequency. These observations are consistent with our hypothesis that myocyte coupling to senescent myofibroblasts in the IBZ of aged rabbits leads to pro-arrhythmic electrophysiological remodeling and increases risk of reentrant current anchored to the IBZ.

In summary, we have characterized an age-associated accumulation of senescent myofibroblasts in the aged infarcted rabbit heart, and our findings suggest that these senescent cells remodel the electrophysiology of IBZ myocytes at least via direct myocyte-fibroblast coupling mediated by Cx43, which would increase risk of cardiac arrhythmias. Previous studies have shown that pharmacological elimination of senescent cells with age via the senolytic drug navitoclax limits cardiac fibrosis in infarcted and non-infarcted mice and improves the survival and cardiac function of infarcted young and aged mice, but little is known about the effects of senescence on arrhythmogenesis with age (Walaszczyk et al., 2019; Anderson et al., 2019). Our findings demonstrate an important role of persistent senescence in arrhythmogenesis with age post-MI, suggesting the use of senolytic therapy to mitigate senescence burden with age might be promising strategy to mitigate chronic arrhythmias in aged infarcted individuals.

All data generated or analyzed during this study are included in the provided Source Data file.

1. 1. Anderson R
   2. Lagnado A
   3. Maggiorani D
   4. Walaszczyk A
   5. Dookun E
   6. Chapman J
   7. Birch J
   8. Salmonowicz H
   9. Ogrodnik M
   10. Jurk D
   11. Proctor C
   12. Correia-Melo C
   13. Victorelli S
   14. Fielder E
   15. Berlinguer-Palmini R
   16. Owens A
   17. Greaves LC
   18. Kolsky KL
   19. Parini A
   20. Douin-Echinard V
   21. LeBrasseur NK
   22. Arthur HM
   23. Tual-Chalot S
   24. Schafer MJ
   25. Roos CM
   26. Miller JD
   27. Robertson N
   28. Mann J
   29. Adams PD
   30. Tchkonia T
   31. Kirkland JL
   32. Mialet-Perez J
   33. Richardson GD
   34. Passos JF

   (2019) Length-independent Telomere damage drives post-mitotic cardiomyocyte Senescence

   The EMBO Journal 38:e100492.

   https://doi.org/10.15252/embj.2018100492

   • PubMed
   • Google Scholar
2. 1. Aromolaran AS
   2. Srivastava U
   3. Alí A
   4. Chahine M
   5. Lazaro D
   6. El-Sherif N
   7. Capecchi PL
   8. Laghi-Pasini F
   9. Lazzerini PE
   10. Boutjdir M

   (2018) Interleukin-6 inhibition of hERG underlies risk for acquired long QT in cardiac and systemic inflammation

   PLOS ONE 13:e0208321.

   https://doi.org/10.1371/journal.pone.0208321

   • PubMed
   • Google Scholar
3. 1. Axford-Gatley RA
   2. Wilson GJ

   (1988)

   The "border zone" in myocardial infarction. An ultrastructural study in the dog using an electron-dense blood flow marker

   The American Journal of Pathology 131:452–464.

   • PubMed
   • Google Scholar
4. 1. Baker DJ
   2. Wijshake T
   3. Tchkonia T
   4. LeBrasseur NK
   5. Childs BG
   6. van de Sluis B
   7. Kirkland JL
   8. van Deursen JM

   (2011) Clearance of P16Ink4A-positive Senescent cells delays ageing-associated disorders

   Nature 479:232–236.

   https://doi.org/10.1038/nature10600

   • PubMed
   • Google Scholar
5. 1. Baker DJ
   2. Childs BG
   3. Durik M
   4. Wijers ME
   5. Sieben CJ
   6. Zhong J
   7. Saltness RA
   8. Jeganathan KB
   9. Verzosa GC
   10. Pezeshki A
   11. Khazaie K
   12. Miller JD
   13. van Deursen JM

   (2016) Naturally occurring P16(Ink4A)-Positive cells shorten healthy LifeSpan

   Nature 530:184–189.

   https://doi.org/10.1038/nature16932

   • PubMed
   • Google Scholar
6. 1. Bandyopadhyay D
   2. Gatza C
   3. Donehower LA
   4. Medrano EE

   (2005) Analysis of cellular Senescence in culture in vivo: the Senescence-associated beta-Galactosidase assay

   Current Protocols in Cell Biology Chapter 18:18.

   https://doi.org/10.1002/0471143030.cb1809s27

   • PubMed
   • Google Scholar
7. 1. Banville I
   2. Gray RA

   (2002) Effect of action potential duration and conduction velocity restitution and their spatial dispersion on Alternans and the stability of arrhythmias

   Journal of Cardiovascular Electrophysiology 13:1141–1149.

   https://doi.org/10.1046/j.1540-8167.2002.01141.x

   • PubMed
   • Google Scholar
8. 1. Benjamin EJ
   2. Muntner P
   3. Alonso A
   4. Bittencourt MS
   5. Callaway CW
   6. Carson AP
   7. Chamberlain AM
   8. Chang AR
   9. Cheng S
   10. Das SR
   11. Delling FN
   12. Djousse L
   13. Elkind MSV
   14. Ferguson JF
   15. Fornage M
   16. Jordan LC
   17. Khan SS
   18. Kissela BM
   19. Knutson KL
   20. Kwan TW
   21. Lackland DT
   22. Lewis TT
   23. Lichtman JH
   24. Longenecker CT
   25. Loop MS
   26. Lutsey PL
   27. Martin SS
   28. Matsushita K
   29. Moran AE
   30. Mussolino ME
   31. O’Flaherty M
   32. Pandey A
   33. Perak AM
   34. Rosamond WD
   35. Roth GA
   36. Sampson UKA
   37. Satou GM
   38. Schroeder EB
   39. Shah SH
   40. Spartano NL
   41. Stokes A
   42. Tirschwell DL
   43. Tsao CW
   44. Turakhia MP
   45. VanWagner LB
   46. Wilkins JT
   47. Wong SS
   48. Virani SS
   49. On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee

   (2019) Heart disease and stroke Statistics-2019 update: A report from the American heart Association

   Circulation 139:e56–e528.

   https://doi.org/10.1161/CIR.0000000000000659

   • Google Scholar
9. 1. Biran A
   2. Perelmutter M
   3. Gal H
   4. Burton DGA
   5. Ovadya Y
   6. Vadai E
   7. Geiger T
   8. Krizhanovsky V

   (2015) Senescent cells communicate via Intercellular protein transfer

   Genes & Development 29:791–802.

   https://doi.org/10.1101/gad.259341.115

   • PubMed
   • Google Scholar
10. 1. Brunner M
    2. Peng X
    3. Liu GX
    4. Ren X-Q
    5. Ziv O
    6. Choi B-R
    7. Mathur R
    8. Hajjiri M
    9. Odening KE
    10. Steinberg E
    11. Folco EJ
    12. Pringa E
    13. Centracchio J
    14. Macharzina RR
    15. Donahay T
    16. Schofield L
    17. Rana N
    18. Kirk M
    19. Mitchell GF
    20. Poppas A
    21. Zehender M
    22. Koren G

    (2008) Mechanisms of cardiac arrhythmias and sudden death in transgenic rabbits with long QT syndrome

    The Journal of Clinical Investigation 118:2246–2259.

    https://doi.org/10.1172/JCI33578

    • PubMed
    • Google Scholar
11. 1. Burton DGA
    2. Krizhanovsky V

    (2014) Physiological and pathological consequences of cellular Senescence

    Cellular and Molecular Life Sciences 71:4373–4386.

    https://doi.org/10.1007/s00018-014-1691-3

    • PubMed
    • Google Scholar
12. 1. Camelliti P
    2. Devlin GP
    3. Matthews KG
    4. Kohl P
    5. Green CR

    (2004a) Spatially and temporally distinct expression of fibroblast Connexins after sheep ventricular infarction

    Cardiovascular Research 62:415–425.

    https://doi.org/10.1016/j.cardiores.2004.01.027

    • PubMed
    • Google Scholar
13. 1. Camelliti P
    2. Green CR
    3. LeGrice I
    4. Kohl P

    (2004b) Fibroblast network in rabbit Sinoatrial node: structural and functional identification of homogeneous and heterogeneous cell coupling

    Circulation Research 94:828–835.

    https://doi.org/10.1161/01.RES.0000122382.19400.14

    • PubMed
    • Google Scholar
14. 1. Campisi J
    2. Robert L

    (2014) Cell Senescence: role in aging and age-related diseases

    Interdisciplinary Topics in Gerontology 39:45–61.

    https://doi.org/10.1159/000358899

    • PubMed
    • Google Scholar
15. 1. Campos FO
    2. Whitaker J
    3. Neji R
    4. Roujol S
    5. O’Neill M
    6. Plank G
    7. Bishop MJ

    (2019) Factors promoting conduction slowing as substrates for block and reentry in Infarcted hearts

    Biophysical Journal 117:2361–2374.

    https://doi.org/10.1016/j.bpj.2019.08.008

    • PubMed
    • Google Scholar
16. 1. Chang J
    2. Wang Y
    3. Shao L
    4. Laberge R-M
    5. Demaria M
    6. Campisi J
    7. Janakiraman K
    8. Sharpless NE
    9. Ding S
    10. Feng W
    11. Luo Y
    12. Wang X
    13. Aykin-Burns N
    14. Krager K
    15. Ponnappan U
    16. Hauer-Jensen M
    17. Meng A
    18. Zhou D

    (2016) Clearance of Senescent cells by Abt263 Rejuvenates aged hematopoietic stem cells in mice

    Nature Medicine 22:78–83.

    https://doi.org/10.1038/nm.4010

    • PubMed
    • Google Scholar
17. 1. Childs BG
    2. Durik M
    3. Baker DJ
    4. van Deursen JM

    (2015) Cellular Senescence in aging and age-related disease: from mechanisms to therapy

    Nature Medicine 21:1424–1435.

    https://doi.org/10.1038/nm.4000

    • PubMed
    • Google Scholar
18. 1. Childs BG
    2. Bussian TJ
    3. Baker DJ

    (2019) Cellular identification and Quantification of Senescence-associated beta-Galactosidase activity in vivo

    Methods in Molecular Biology 1896:31–38.

    https://doi.org/10.1007/978-1-4939-8931-7_4

    • PubMed
    • Google Scholar
19. 1. Choi BR
    2. Jang W
    3. Salama G

    (2007) Spatially discordant voltage Alternans cause Wavebreaks in ventricular fibrillation

    Heart Rhythm 4:1057–1068.

    https://doi.org/10.1016/j.hrthm.2007.03.037

    • Google Scholar
20. 1. Cooper LL
    2. Odening KE
    3. Hwang MS
    4. Chaves L
    5. Schofield L
    6. Taylor CA
    7. Gemignani AS
    8. Mitchell GF
    9. Forder JR
    10. Choi BR
    11. Koren G

    (2012) Electromechanical and structural alterations in the aging rabbit heart and aorta

    American Journal of Physiology. Heart and Circulatory Physiology 302:H1625–H1635.

    https://doi.org/10.1152/ajpheart.00960.2011

    • PubMed
    • Google Scholar
21. 1. Cooper LL
    2. Li W
    3. Lu Y
    4. Centracchio J
    5. Terentyeva R
    6. Koren G
    7. Terentyev D

    (2013) Redox modification of Ryanodine receptors by mitochondria-derived reactive oxygen species contributes to aberrant Ca2+ handling in ageing rabbit hearts

    The Journal of Physiology 591:5895–5911.

    https://doi.org/10.1113/jphysiol.2013.260521

    • PubMed
    • Google Scholar
22. 1. Coppé J-P
    2. Desprez P-Y
    3. Krtolica A
    4. Campisi J

    (2010) The Senescence-associated Secretory phenotype: the dark side of tumor suppression

    Annual Review of Pathology 5:99–118.

    https://doi.org/10.1146/annurev-pathol-121808-102144

    • PubMed
    • Google Scholar
23. 1. Dai W
    2. Jiang Y
    3. Chen K
    4. Qiu J
    5. Sun J
    6. Zhang W
    7. Zhou X
    8. Huang N
    9. Li Y
    10. Li W

    (2017) Effect of etoposide-induced alteration of the Mdm2-RB signaling pathway on cellular Senescence in A549 lung adenocarcinoma cells

    Oncology Letters 14:3935–3940.

    https://doi.org/10.3892/ol.2017.6684

    • PubMed
    • Google Scholar
24. 1. Debacq-Chainiaux F
    2. Erusalimsky JD
    3. Campisi J
    4. Toussaint O

    (2009) Protocols to detect Senescence-associated beta-Galactosidase (SA-Betagal) activity, a biomarker of Senescent cells in culture and in vivo

    Nature Protocols 4:1798–1806.

    https://doi.org/10.1038/nprot.2009.191

    • PubMed
    • Google Scholar
25. 1. Demaria M
    2. Ohtani N
    3. Youssef SA
    4. Rodier F
    5. Toussaint W
    6. Mitchell JR
    7. Laberge R-M
    8. Vijg J
    9. Van Steeg H
    10. Dollé MET
    11. Hoeijmakers JHJ
    12. de Bruin A
    13. Hara E
    14. Campisi J

    (2014) An essential role for Senescent cells in optimal wound healing through secretion of PDGF-AA

    Developmental Cell 31:722–733.

    https://doi.org/10.1016/j.devcel.2014.11.012

    • PubMed
    • Google Scholar
26. 1. Deo R
    2. Albert CM

    (2012) Epidemiology and Genetics of sudden cardiac death

    Circulation 125:620–637.

    https://doi.org/10.1161/CIRCULATIONAHA.111.023838

    • Google Scholar
27. 1. Di Diego JM
    2. Antzelevitch C

    (2011) Ischemic ventricular arrhythmias: experimental models and their clinical relevance

    Heart Rhythm 8:1963–1968.

    https://doi.org/10.1016/j.hrthm.2011.06.036

    • Google Scholar
28. 1. Dimri GP
    2. Lee X
    3. Basile G
    4. Acosta M
    5. Scott G
    6. Roskelley C
    7. Medrano EE
    8. Linskens M
    9. Rubelj I
    10. Pereira-Smith O

    (1995) A biomarker that identifies Senescent human cells in culture and in aging skin in vivo

    PNAS 92:9363–9367.

    https://doi.org/10.1073/pnas.92.20.9363

    • PubMed
    • Google Scholar
29. 1. Dookun E
    2. Walaszczyk A
    3. Redgrave R
    4. Palmowski P
    5. Tual-Chalot S
    6. Suwana A
    7. Chapman J
    8. Jirkovsky E
    9. Donastorg Sosa L
    10. Gill E
    11. Yausep OE
    12. Santin Y
    13. Mialet-Perez J
    14. Andrew Owens W
    15. Grieve D
    16. Spyridopoulos I
    17. Taggart M
    18. Arthur HM
    19. Passos JF
    20. Richardson GD

    (2020) Clearance of Senescent cells during cardiac ischemia-reperfusion injury improves recovery

    Aging Cell 19:e13249.

    https://doi.org/10.1111/acel.13249

    • PubMed
    • Google Scholar
30. 1. Fischer AH
    2. Jacobson KA
    3. Rose J
    4. Zeller R

    (2008) Hematoxylin and Eosin staining of tissue and cell sections

    CSH Protocols 2008:db.

    https://doi.org/10.1101/pdb.prot4986

    • PubMed
    • Google Scholar
31. 1. Francis Stuart SD
    2. De Jesus NM
    3. Lindsey ML
    4. Ripplinger CM

    (2016) The crossroads of inflammation, fibrosis, and arrhythmia following myocardial infarction

    Journal of Molecular and Cellular Cardiology 91:114–122.

    https://doi.org/10.1016/j.yjmcc.2015.12.024

    • PubMed
    • Google Scholar
32. 1. Fu X
    2. Khalil H
    3. Kanisicak O
    4. Boyer JG
    5. Vagnozzi RJ
    6. Maliken BD
    7. Sargent MA
    8. Prasad V
    9. Valiente-Alandi I
    10. Blaxall BC
    11. Molkentin JD

    (2018) Specialized fibroblast differentiated States underlie scar formation in the Infarcted mouse heart

    Journal of Clinical Investigation 128:2127–2143.

    https://doi.org/10.1172/JCI98215

    • Google Scholar
33. 1. Furman D
    2. Campisi J
    3. Verdin E
    4. Carrera-Bastos P
    5. Targ S
    6. Franceschi C
    7. Ferrucci L
    8. Gilroy DW
    9. Fasano A
    10. Miller GW
    11. Miller AH
    12. Mantovani A
    13. Weyand CM
    14. Barzilai N
    15. Goronzy JJ
    16. Rando TA
    17. Effros RB
    18. Lucia A
    19. Kleinstreuer N
    20. Slavich GM

    (2019) Chronic inflammation in the etiology of disease across the life span

    Nature Medicine 25:1822–1832.

    https://doi.org/10.1038/s41591-019-0675-0

    • Google Scholar
34. 1. Hayashi H
    2. Shiferaw Y
    3. Sato D
    4. Nihei M
    5. Lin S-F
    6. Chen P-S
    7. Garfinkel A
    8. Weiss JN
    9. Qu Z

    (2007) Dynamic origin of spatially discordant Alternans in cardiac tissue

    Biophysical Journal 92:448–460.

    https://doi.org/10.1529/biophysj.106.091009

    • PubMed
    • Google Scholar
35. 1. Hegyi B
    2. Bossuyt J
    3. Griffiths LG
    4. Shimkunas R
    5. Coulibaly Z
    6. Jian Z
    7. Grimsrud KN
    8. Sondergaard CS
    9. Ginsburg KS
    10. Chiamvimonvat N
    11. Belardinelli L
    12. Varró A
    13. Papp JG
    14. Pollesello P
    15. Levijoki J
    16. Izu LT
    17. Boyd WD
    18. Bányász T
    19. Bers DM
    20. Chen-Izu Y

    (2018) Complex electrophysiological remodeling in postinfarction ischemic heart failure

    PNAS 115:E3036–E3044.

    https://doi.org/10.1073/pnas.1718211115

    • PubMed
    • Google Scholar
36. 1. Holness CL
    2. Simmons DL

    (1993)

    Molecular cloning of Cd68, a human macrophage marker related to lysosomal Glycoproteins

    Blood 81:1607–1613.

    • PubMed
    • Google Scholar
37. 1. Ito T
    2. Teo YV
    3. Evans SA
    4. Neretti N
    5. Sedivy JM

    (2018) Regulation of cellular Senescence by Polycomb Chromatin modifiers through distinct DNA Damage- and Histone methylation-dependent pathways

    Cell Reports 22:3480–3492.

    https://doi.org/10.1016/j.celrep.2018.03.002

    • PubMed
    • Google Scholar
38. 1. Jun JI
    2. Lau LF

    (2018) Resolution of organ fibrosis

    The Journal of Clinical Investigation 128:97–107.

    https://doi.org/10.1172/JCI93563

    • PubMed
    • Google Scholar
39. 1. Kabakov AY
    2. Sengun E
    3. Lu Y
    4. Roder K
    5. Bronk P
    6. Baggett B
    7. Turan NN
    8. Moshal KS
    9. Koren G

    (2021) Three-week old rabbit ventricular cardiomyocytes as a novel system to study cardiac Excitation and EC coupling

    Frontiers in Physiology 12:672360.

    https://doi.org/10.3389/fphys.2021.672360

    • PubMed
    • Google Scholar
40. 1. Kanisicak O
    2. Khalil H
    3. Ivey MJ
    4. Karch J
    5. Maliken BD
    6. Correll RN
    7. Brody MJ
    8. J Lin S-C
    9. Aronow BJ
    10. Tallquist MD
    11. Molkentin JD

    (2016) Genetic lineage tracing defines Myofibroblast origin and function in the injured heart

    Nature Communications 7:12260.

    https://doi.org/10.1038/ncomms12260

    • PubMed
    • Google Scholar
41. 1. Kim TY
    2. Kunitomo Y
    3. Pfeiffer Z
    4. Patel D
    5. Hwang J
    6. Harrison K
    7. Patel B
    8. Jeng P
    9. Ziv O
    10. Lu Y
    11. Peng X
    12. Qu Z
    13. Koren G
    14. Choi B-R

    (2015) Complex Excitation Dynamics underlie polymorphic ventricular tachycardia in a transgenic rabbit model of long QT syndrome type 1

    Heart Rhythm 12:220–228.

    https://doi.org/10.1016/j.hrthm.2014.10.003

    • PubMed
    • Google Scholar
42. 1. Kim TY
    2. Jeng P
    3. Hwang J
    4. Pfeiffer Z
    5. Patel D
    6. Cooper LL
    7. Kossidas K
    8. Centracchio J
    9. Peng X
    10. Koren G
    11. Qu Z
    12. Choi BR

    (2019) Short-long heart rate variation increases dispersion of action potential duration in long QT type 2 transgenic rabbit model

    Scientific Reports 9:14849.

    https://doi.org/10.1038/s41598-019-51230-9

    • PubMed
    • Google Scholar
43. 1. Kim EC
    2. Kim JR

    (2019) Senotherapeutics: emerging strategy for healthy aging and age-related disease

    BMB Reports 52:47–55.

    https://doi.org/10.5483/BMBRep.2019.52.1.293

    • PubMed
    • Google Scholar
44. 1. Kirkland JL
    2. Tchkonia T

    (2017) Cellular Senescence: A Translational perspective

    EBioMedicine 21:21–28.

    https://doi.org/10.1016/j.ebiom.2017.04.013

    • PubMed
    • Google Scholar
45. 1. Kirkland JL
    2. Tchkonia T
    3. Zhu Y
    4. Niedernhofer LJ
    5. Robbins PD

    (2017) The clinical potential of Senolytic drugs

    Journal of the American Geriatrics Society 65:2297–2301.

    https://doi.org/10.1111/jgs.14969

    • PubMed
    • Google Scholar
46. 1. Kirschner K
    2. Rattanavirotkul N
    3. Quince MF
    4. Chandra T

    (2020) Functional heterogeneity in Senescence

    Biochemical Society Transactions 48:765–773.

    https://doi.org/10.1042/BST20190109

    • PubMed
    • Google Scholar
47. 1. Kohl P
    2. Gourdie RG

    (2014) Fibroblast-Myocyte Electrotonic coupling: does it occur in native cardiac tissue

    Journal of Molecular and Cellular Cardiology 70:37–46.

    https://doi.org/10.1016/j.yjmcc.2013.12.024

    • Google Scholar
48. 1. Kolettis TM

    (2013) Coronary artery disease and ventricular tachyarrhythmia: pathophysiology and treatment

    Current Opinion in Pharmacology 13:210–217.

    https://doi.org/10.1016/j.coph.2013.01.001

    • PubMed
    • Google Scholar
49. 1. Kostecki GM
    2. Shi Y
    3. Chen CS
    4. Reich DH
    5. Entcheva E
    6. Tung L

    (2021) Optogenetic current in Myofibroblasts acutely alters electrophysiology and conduction of Co-cultured cardiomyocytes

    Scientific Reports 11:4430.

    https://doi.org/10.1038/s41598-021-83398-4

    • PubMed
    • Google Scholar
50. 1. Kuilman T
    2. Michaloglou C
    3. Mooi WJ
    4. Peeper DS

    (2010) The essence of Senescence

    Genes & Development 24:2463–2479.

    https://doi.org/10.1101/gad.1971610

    • Google Scholar
51. 1. Liu W
    2. Kim TY
    3. Huang X
    4. Liu MB
    5. Koren G
    6. Choi B-R
    7. Qu Z

    (2018) Mechanisms linking T-wave Alternans to spontaneous initiation of ventricular arrhythmias in rabbit models of long QT syndrome

    The Journal of Physiology 596:1341–1355.

    https://doi.org/10.1113/JP275492

    • PubMed
    • Google Scholar
52. 1. Mahajan A
    2. Shiferaw Y
    3. Sato D
    4. Baher A
    5. Olcese R
    6. Xie L-H
    7. Yang M-J
    8. Chen P-S
    9. Restrepo JG
    10. Karma A
    11. Garfinkel A
    12. Qu Z
    13. Weiss JN

    (2008) A rabbit ventricular action potential model replicating cardiac Dynamics at rapid heart rates

    Biophysical Journal 94:392–410.

    https://doi.org/10.1529/biophysj.106.98160

    • PubMed
    • Google Scholar
53. 1. Maity B
    2. Sheff D
    3. Fisher RA

    (2013) Immunostaining: detection of signaling protein location in tissues, cells and subcellular compartments

    Methods in Cell Biology 113:81–105.

    https://doi.org/10.1016/B978-0-12-407239-8.00005-7

    • PubMed
    • Google Scholar
54. 1. Mendonca Costa C
    2. Plank G
    3. Rinaldi CA
    4. Niederer SA
    5. Bishop MJ

    (2018) Modeling the electrophysiological properties of the infarct border zone

    Frontiers in Physiology 9:356.

    https://doi.org/10.3389/fphys.2018.00356

    • PubMed
    • Google Scholar
55. 1. Meyer K
    2. Hodwin B
    3. Ramanujam D
    4. Engelhardt S
    5. Sarikas A

    (2016) Essential role for premature Senescence of Myofibroblasts in myocardial fibrosis

    Journal of the American College of Cardiology 67:2018–2028.

    https://doi.org/10.1016/j.jacc.2016.02.047

    • PubMed
    • Google Scholar
56. 1. Morrissey PJ
    2. Murphy KR
    3. Daley JM
    4. Schofield L
    5. Turan NN
    6. Arunachalam K
    7. Abbott JD
    8. Koren G

    (2017) A novel method of standardized myocardial infarction in aged rabbits

    American Journal of Physiology. Heart and Circulatory Physiology 312:H959–H967.

    https://doi.org/10.1152/ajpheart.00582.2016

    • PubMed
    • Google Scholar
57. 1. Murphy KR
    2. Baggett B
    3. Cooper LL
    4. Lu Y
    5. O-Uchi J
    6. Sedivy JM
    7. Terentyev D
    8. Koren G

    (2019) Enhancing Autophagy diminishes aberrant Ca(2+) homeostasis and Arrhythmogenesis in aging rabbit hearts

    Frontiers in Physiology 10:1277.

    https://doi.org/10.3389/fphys.2019.01277

    • PubMed
    • Google Scholar
58. 1. Narita M

    (2019) Juxtacrine regulation of cellular Senescence

    BMB Reports 52:3–4.

    https://doi.org/10.5483/BMBRep.2019.52.1.289

    • PubMed
    • Google Scholar
59. 1. Nelson G
    2. Wordsworth J
    3. Wang C
    4. Jurk D
    5. Lawless C
    6. Martin-Ruiz C
    7. von Zglinicki T

    (2012) A Senescent cell bystander effect: Senescence-induced Senescence

    Aging Cell 11:345–349.

    https://doi.org/10.1111/j.1474-9726.2012.00795.x

    • PubMed
    • Google Scholar
60. 1. Nelson G
    2. Kucheryavenko O
    3. Wordsworth J
    4. von Zglinicki T

    (2018) The Senescent bystander effect is caused by ROS-activated NF-kappaB signalling

    Mechanisms of Ageing and Development 170:30–36.

    https://doi.org/10.1016/j.mad.2017.08.005

    • PubMed
    • Google Scholar
61. 1. Neuschl V
    2. Berecova Z
    3. Madaric J
    4. Simkova J
    5. Glezlova A
    6. Hatala R

    (2018) Structural assessment of myocardial infarction scars and left ventricular function with cardiac magnetic resonance imaging in patients at high risk of sudden cardiac death

    Bratislavske Lekarske Listy 119:259–264.

    https://doi.org/10.4149/BLL_2018_048

    • PubMed
    • Google Scholar
62. 1. Partridge L
    2. Deelen J
    3. Slagboom PE

    (2018) Facing up to the global challenges of ageing

    Nature 561:45–56.

    https://doi.org/10.1038/s41586-018-0457-8

    • PubMed
    • Google Scholar
63. 1. Pilbrow AP
    2. Ellmers LJ
    3. Black MA
    4. Moravec CS
    5. Sweet WE
    6. Troughton RW
    7. Richards AM
    8. Frampton CM
    9. Cameron VA

    (2008) Genomic selection of reference genes for real-time PCR in human myocardium

    BMC Medical Genomics 1:64.

    https://doi.org/10.1186/1755-8794-1-64

    • PubMed
    • Google Scholar
64. 1. Pinto AR
    2. Ilinykh A
    3. Ivey MJ
    4. Kuwabara JT
    5. D’Antoni ML
    6. Debuque R
    7. Chandran A
    8. Wang L
    9. Arora K
    10. Rosenthal NA
    11. Tallquist MD

    (2016) Revisiting cardiac cellular composition

    Circulation Research 118:400–409.

    https://doi.org/10.1161/CIRCRESAHA.115.307778

    • PubMed
    • Google Scholar
65. 1. Prabhu SD
    2. Frangogiannis NG

    (2016) The biological basis for cardiac repair after myocardial infarction: from inflammation to fibrosis

    Circulation Research 119:91–112.

    https://doi.org/10.1161/CIRCRESAHA.116.303577

    • PubMed
    • Google Scholar
66. 1. Prata L
    2. Ovsyannikova IG
    3. Tchkonia T
    4. Kirkland JL

    (2018) Senescent cell clearance by the immune system: emerging therapeutic opportunities

    Seminars in Immunology 40:101275.

    https://doi.org/10.1016/j.smim.2019.04.003

    • PubMed
    • Google Scholar
67. 1. Pusztaszeri MP
    2. Seelentag W
    3. Bosman FT

    (2006) Immunohistochemical expression of endothelial markers Cd31, Cd34, von Willebrand factor, and Fli-1 in normal human tissues

    The Journal of Histochemistry and Cytochemistry 54:385–395.

    https://doi.org/10.1369/jhc.4A6514.2005

    • PubMed
    • Google Scholar
68. 1. Quinn TA
    2. Camelliti P
    3. Rog-Zielinska EA
    4. Siedlecka U
    5. Poggioli T
    6. O’Toole ET
    7. Knöpfel T
    8. Kohl P

    (2016) Electrotonic coupling of Excitable and Nonexcitable cells in the heart revealed by Optogenetics

    PNAS 113:14852–14857.

    https://doi.org/10.1073/pnas.1611184114

    • PubMed
    • Google Scholar
69. 1. Richardson WJ
    2. Clarke SA
    3. Quinn TA
    4. Holmes JW

    (2015) Physiological implications of myocardial scar structure

    Comprehensive Physiology 5:1877–1909.

    https://doi.org/10.1002/cphy.c140067

    • PubMed
    • Google Scholar
70. 1. Richardson WJ
    2. Holmes JW

    (2015) Why is infarct expansion such an elusive therapeutic target

    Journal of Cardiovascular Translational Research 8:421–430.

    https://doi.org/10.1007/s12265-015-9652-2

    • PubMed
    • Google Scholar
71. 1. Rodier F
    2. Coppé J-P
    3. Patil CK
    4. Hoeijmakers WAM
    5. Muñoz DP
    6. Raza SR
    7. Freund A
    8. Campeau E
    9. Davalos AR
    10. Campisi J

    (2009) Persistent DNA damage signalling triggers Senescence-associated inflammatory cytokine secretion

    Nature Cell Biology 11:973–979.

    https://doi.org/10.1038/ncb1909

    • Google Scholar
72. 1. Rutherford SL
    2. Trew ML
    3. Sands GB
    4. LeGrice IJ
    5. Smaill BH

    (2012) High-resolution 3-dimensional reconstruction of the infarct border zone: impact of structural remodeling on electrical activation

    Circulation Research 111:301–311.

    https://doi.org/10.1161/CIRCRESAHA.111.260943

    • PubMed
    • Google Scholar
73. 1. Schultz F
    2. Swiatlowska P
    3. Alvarez-Laviada A
    4. Sanchez-Alonso JL
    5. Song Q
    6. de Vries AAF
    7. Pijnappels DA
    8. Ongstad E
    9. Braga VMM
    10. Entcheva E
    11. Gourdie RG
    12. Miragoli M
    13. Gorelik J

    (2019) Cardiomyocyte-Myofibroblast contact dynamism is modulated by Connexin-43

    FASEB Journal 33:10453–10468.

    https://doi.org/10.1096/fj.201802740RR

    • PubMed
    • Google Scholar
74. 1. Shibamoto M
    2. Higo T
    3. Naito AT
    4. Nakagawa A
    5. Sumida T
    6. Okada K
    7. Sakai T
    8. Kuramoto Y
    9. Yamaguchi T
    10. Ito M
    11. Masumura Y
    12. Higo S
    13. Lee J-K
    14. Hikoso S
    15. Komuro I
    16. Sakata Y

    (2019) Activation of DNA damage response and cellular Senescence in cardiac fibroblasts limit cardiac fibrosis after myocardial infarction

    International Heart Journal 60:944–957.

    https://doi.org/10.1536/ihj.18-701

    • PubMed
    • Google Scholar
75. Software

    1. Soepriatna A

    (2023) Ap_Analysis_Routines_Cardiotoxicity_Microtissues, version swh:1:rev:3172027cbd78883c5c6e464524afea6fa213cfad

    Software Hertiage.

    https://archive.softwareheritage.org/swh:1:dir:1215bd4f21667b9a30baf5a38e50c76ec810c5eb;origin=https://github.com/arvinsoepriatna/AP_Analysis_Routines_Cardiotoxicity_Microtissues;visit=swh:1:snp:ae9c3fb75ef9fd93e883fbae4dc0c938eb9481b4;anchor=swh:1:rev:3172027cbd78883c5c6e464524afea6fa213cfad
76. 1. Storer M
    2. Mas A
    3. Robert-Moreno A
    4. Pecoraro M
    5. Ortells MC
    6. Di Giacomo V
    7. Yosef R
    8. Pilpel N
    9. Krizhanovsky V
    10. Sharpe J
    11. Keyes WM

    (2013) Senescence is a developmental mechanism that contributes to embryonic growth and Patterning

    Cell 155:1119–1130.

    https://doi.org/10.1016/j.cell.2013.10.041

    • PubMed
    • Google Scholar
77. 1. Tallquist MD

    (2020) Cardiac fibroblast diversity

    Annual Review of Physiology 82:63–78.

    https://doi.org/10.1146/annurev-physiol-021119-034527

    • PubMed
    • Google Scholar
78. 1. Terentyev D
    2. Rees CM
    3. Li W
    4. Cooper LL
    5. Jindal HK
    6. Peng X
    7. Lu Y
    8. Terentyeva R
    9. Odening KE
    10. Daley J
    11. Bist K
    12. Choi B-R
    13. Karma A
    14. Koren G

    (2014) Hyperphosphorylation of Ryrs underlies triggered activity in transgenic rabbit model of Lqt2 syndrome

    Circulation Research 115:919–928.

    https://doi.org/10.1161/CIRCRESAHA.115.305146

    • PubMed
    • Google Scholar
79. 1. van den Borne SWM
    2. Diez J
    3. Blankesteijn WM
    4. Verjans J
    5. Hofstra L
    6. Narula J

    (2010) Myocardial remodeling after infarction: the role of Myofibroblasts

    Nature Reviews. Cardiology 7:30–37.

    https://doi.org/10.1038/nrcardio.2009.199

    • PubMed
    • Google Scholar
80. 1. van Deursen JM

    (2019) Senolytic therapies for healthy longevity

    Science 364:636–637.

    https://doi.org/10.1126/science.aaw1299

    • PubMed
    • Google Scholar
81. 1. Vicente R
    2. Mausset-Bonnefont A-L
    3. Jorgensen C
    4. Louis-Plence P
    5. Brondello J-M

    (2016) Cellular Senescence impact on immune cell fate and function

    Aging Cell 15:400–406.

    https://doi.org/10.1111/acel.12455

    • PubMed
    • Google Scholar
82. 1. Walaszczyk A
    2. Dookun E
    3. Redgrave R
    4. Tual-Chalot S
    5. Victorelli S
    6. Spyridopoulos I
    7. Owens A
    8. Arthur HM
    9. Passos JF
    10. Richardson GD

    (2019) Pharmacological clearance of Senescent cells improves survival and recovery in aged mice following acute myocardial infarction

    Aging Cell 18:e12945.

    https://doi.org/10.1111/acel.12945

    • PubMed
    • Google Scholar
83. 1. Wang Y
    2. Suh Y-A
    3. Fuller MY
    4. Jackson JG
    5. Xiong S
    6. Terzian T
    7. Quintás-Cardama A
    8. Bankson JA
    9. El-Naggar AK
    10. Lozano G

    (2011) Restoring expression of wild-type P53 suppresses tumor growth but does not cause tumor regression in mice with a P53 Missense Mutation

    Journal of Clinical Investigation 121:893–904.

    https://doi.org/10.1172/JCI44504

    • Google Scholar
84. 1. Zhang P
    2. Li T
    3. Griffith BP
    4. Wu ZJ

    (2014) Multiscale characterization of impact of infarct size on myocardial remodeling in an Ovine infarct model

    Cells Tissues Organs 200:349–362.

    https://doi.org/10.1159/000435875

    • Google Scholar
85. 1. Zhu F
    2. Li Y
    3. Zhang J
    4. Piao C
    5. Liu T
    6. Li H-H
    7. Du J

    (2013) Senescent cardiac fibroblast is critical for cardiac fibrosis after myocardial infarction

    PLOS ONE 8:e74535.

    https://doi.org/10.1371/journal.pone.0074535

    • PubMed
    • Google Scholar
86. 1. Zhu Y
    2. Tchkonia T
    3. Pirtskhalava T
    4. Gower AC
    5. Ding H
    6. Giorgadze N
    7. Palmer AK
    8. Ikeno Y
    9. Hubbard GB
    10. Lenburg M
    11. O’Hara SP
    12. LaRusso NF
    13. Miller JD
    14. Roos CM
    15. Verzosa GC
    16. LeBrasseur NK
    17. Wren JD
    18. Farr JN
    19. Khosla S
    20. Stout MB
    21. McGowan SJ
    22. Fuhrmann-Stroissnigg H
    23. Gurkar AU
    24. Zhao J
    25. Colangelo D
    26. Dorronsoro A
    27. Ling YY
    28. Barghouthy AS
    29. Navarro DC
    30. Sano T
    31. Robbins PD
    32. Niedernhofer LJ
    33. Kirkland JL

    (2015) The Achilles' heel of Senescent cells: from Transcriptome to Senolytic drugs

    Aging Cell 14:644–658.

    https://doi.org/10.1111/acel.12344

    • PubMed
    • Google Scholar
87. 1. Ziv O
    2. Schofield L
    3. Lau E
    4. Chaves L
    5. Patel D
    6. Jeng P
    7. Peng X
    8. Choi B-R
    9. Koren G

    (2012) A novel, minimally invasive, segmental myocardial infarction with a clear healed infarct Borderzone in rabbits

    American Journal of Physiology-Heart and Circulatory Physiology 302:H2321–H2330.

    https://doi.org/10.1152/ajpheart.00031.2012

    • Google Scholar

Author details

1. Brett C Baggett

   1. Brown University, Providence, United States
   2. Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Contributed equally with

   Kevin R Murphy and Elif Sengun

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2227-0004

2. Kevin R Murphy

   1. Brown University, Providence, United States
   2. Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Brett C Baggett and Elif Sengun

   Competing interests

   No competing interests declared

3. Elif Sengun

   1. Brown University, Providence, United States
   2. Cardiovascular Research Center, Rhode Island Hospital, Providence, United States
   3. Department of Pharmacology, Institute of Graduate Studies in Health Sciences, Istanbul University, Istanbul, Turkey

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – review and editing

   Contributed equally with

   Brett C Baggett and Kevin R Murphy

   Competing interests

   No competing interests declared

4. Eric Mi

   1. Brown University, Providence, United States
   2. Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

5. Yueming Cao

   1. Brown University, Providence, United States
   2. Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Data curation

   Competing interests

   No competing interests declared

6. Nilufer N Turan

   Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Resources, Data curation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

7. Yichun Lu

   Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Resources, Data curation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

8. Lorraine Schofield

   Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Resources, Data curation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

9. Tae Yun Kim

   Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Investigation, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

10. Anatoli Y Kabakov

    1. Brown University, Providence, United States
    2. Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

    Contribution

    Conceptualization, Resources, Data curation, Software, Formal analysis, Investigation, Visualization, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

11. Peter Bronk

    Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

    Contribution

    Conceptualization, Resources, Data curation, Software, Formal analysis, Investigation, Visualization, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-9067-2016

12. Zhilin Qu

    School of Medicine, University of California, Los Angeles, Los Angeles, United States

    Contribution

    Conceptualization, Resources, Data curation, Software, Formal analysis, Visualization, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

13. Patrizia Camelliti

    School of Biosciences and Medicine, University of Surrey, Guildford, United Kingdom

    Contribution

    Conceptualization, Resources, Supervision, Writing – review and editing

    Competing interests

    No competing interests declared

14. Patrycja Dubielecka

    1. Brown University, Providence, United States
    2. Department of Hematology, Rhode Island Hospital, Providence, United States

    Contribution

    Conceptualization, Resources, Supervision, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-3987-0647

15. Dmitry Terentyev

    Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

    Contribution

    Conceptualization, Resources, Supervision, Writing – review and editing

    Competing interests

    No competing interests declared

16. Federica del Monte

    Medical University of South Carolina, Charleston, United States

    Contribution

    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Visualization, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

17. Bum-Rak Choi

    Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

    Contribution

    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Visualization, Methodology, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

18. John Sedivy

    Brown University, Providence, United States

    Contribution

    Conceptualization, Resources, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing, Provided critical input in in vitro experiments and overall experimental design

    Competing interests

    No competing interests declared

19. Gideon Koren

    1. Brown University, Providence, United States
    2. Cardiovascular Research Center, Rhode Island Hospital, Providence, United States

    Contribution

    Conceptualization, Resources, Software, Supervision, Funding acquisition, Investigation, Methodology, Writing – original draft, Project administration, Writing – review and editing, Supervised all experiments and writing of the article

    For correspondence

    gideon_koren@brown.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-6211-5837

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