In a Frontiers article titled “Myocardial Contractility: Historical and Contemporary Considerations,” (Muir and Hamlin, 2020, p1) noted,

They recommended “a modern definition of myocardial contractility as the preload, afterload and length-independent intrinsic kinetically controlled, chemo-mechanical processes responsible for the development of force and velocity” (p1). This definition is insightful but vague. Facing the many issues in the definition of MC, we previously proposed understanding it comprehensively through three dimensions: capacity, adaptability, and ability (Geloian and Kuang, 2023). Since the term “three dimensions” could mislead readers into perceiving MC as a 3-D structural concept, this article will instead adopt the term “three functional domains of MC.” In this framework, capacity, adaptability, and ability are no longer described as three dimensions of MC but rather as three interwoven functional domains, each contributing uniquely to the dynamic behavior of myocardial contraction. In response to Muir and Hamlin (2020) and to further develop our three-domain conceptualization of MC, we apply the concept of complex adaptive system (CAS) to advance the understanding of MC by the following steps.

First, we comprehensively address and analyze the many issues with the existing definitions and classify the issues into five groups. Through this conceptual analysis process, why the definition of MC should include the three domains becomes clear.

Second, we address the rationales to conceptualize MC from a broader scope, further develop the three-domain conceptualization of MC into a dynamic open framework that illustrates the internal functional organization of MC, and explain how the framework improves diagnostic and therapeutic strategies. This framework eliminates all the issues we address and puts the three domains and their components in place; moreover, it elaborates on the rich connotations of Muir and Hamlin’s modern definition, making it clear and complete.

Third, we present the theoretical and practical significance/implications of several new conceptual developments in this article.

Finally, considering the complex MC or the framework as a system, we briefly highlight its system-level properties that apply to all three domains and their implications.

This article advances the understanding of MC, promotes the CAS way of thinking to study complex biological systems, and is of both conceptual and practical value in research on cardiac muscle contraction, exercise training, and clinical practice.

A complex adaptive system (CAS) consists of networks of interacting components, or agents, that display emergent properties and resilience (Holland, 2006; Carmichael and Hadžikadić, 2019). These systems can adapt to internal and external perturbations. All biological systems, including cells, tissues, organs, and entire organisms, are CASs (Janson, 2012). The heart functions as a cardiac CAS, comprising right and left atrial CASs and right and left ventricular CASs, with cardiomyocytes (cellular CASs) as agents.

An emergent property is a characteristic or behavior of a CAS that arises from the complex interactions of its components but often cannot be predicted by examining the components in isolation. Emergent properties are central to understanding a CAS as they emphasize how collective behavior results from multi-level interactions rather than isolated components. Examples are provided in Section 1.3 below.

Nonlinear dynamics, or nonlinearity, is an important property of a CAS. The system’s response to internal or external perturbations is often unpredictable from the properties of the components alone; it may respond proportionately or disproportionately or have no response (Ladyman et al., 2013).

Inotropy refers solely to the force (F) of muscle contraction (Muir and Hamlin, 2020).

Clinotropy refers solely to the velocity (V) of muscle contraction (Muir and Hamlin, 2020).

Ca²⁺ modulators are extrinsic factors that increase or decrease Ca²⁺ transient levels in the cytosol during muscle contraction, including sympathetic tone, cardiac glycosides, and β-blockers. These extrinsic factors are typically termed “inotropic factors.” They also affect the speed and duration of Ca²⁺ transient, influencing both force (F) and velocity (V), making “Ca²⁺ modulators” a more accurate term. An increase in sympathetic tone and/or an administration of cardiac glycosides are positive Ca²⁺ modulators, and β-blockers are negative Ca²⁺ modulators.

Preload varies in definition based on context: for the whole heart, it often refers to end-diastolic volume (EDV) or pressure (EDP), while for myocardial tissue, it involves the initial fiber length or stretch. In vitro, preload can be seen as the load stretching the fiber, though it is often approximated using initial fiber length, resting tension, or sarcomere length. As this article focuses on myocardial tissue, these proxies are appropriate for preload measurement.

Afterload is the resistance the heart must overcome to eject blood during systole, mainly determined by aortic pressure, vascular resistance, and aortic valve properties. At the myocardial level, it reflects the force myocardial fibers generate to shorten against an opposing load after contraction begins. Afterload can be better understood by examining the mechanics of muscle contraction and how muscle fibers respond to varying external loads:

• Isometric contraction: Muscle develops tension without shortening, as the load exceeds its ability to contract.

3-imEFs refers to the collective grouping of three types of immediate, extrinsic factors that modulate the production of F and/or V: preload, Ca²⁺ modulator, Afterload. Why these three types of extrinsic factors are grouped as 3-imEFs will become clear later.

Heart rate and cardiac oxygen consumption rate are emergent properties of the entire heart. Cardiac performance may refer to the performance of the entire heart, but it more frequently refers to the performance of the left ventricle. End diastolic volume, end systolic volume, peak systolic ventricular pressure, stroke volume, ejection fraction, cardiac output, pressure-volume loop, and end systolic pressure-volume relationship (ESPVR) are emergent properties that apply to the left ventricle. They describe cardiac performance from different aspects.

Myocardial tissue has both passive and active emergent properties. Passive properties, like structural integrity and viscoelasticity, require minimal energy. Active properties are self-reinforcing processes (e.g., automaticity, excitability, and conductivity) or significant energy-dependent processes (e.g., Ca²⁺ handling, ATP production, and muscle contraction). Muscle contraction, an active property, involves contraction, relaxation, and fatigue resistance, emerging at the myocardial tissue level (multiple cardiomyocytes) rather than the whole heart. MC reflects the collective contractility of cardiomyocytes, which share structural and functional similarities but also exhibit adaptive heterogeneities (Michel et al., 2022) that influence tissue-level MC. Thus, MC is not a simple algebraic summation of individual cellular contractility.

Heart or left ventricular-level parameters like stroke volume, ejection fraction, P-V loop, and ESPVR are emergent properties of the heart that may not directly reflect MC at the tissue level. For example, if some cardiomyocytes lose contractility due to ischemia but adjacent cells compensate, normal cardiac output may persist, illustrating the nonlinear response of the cardiac CAS to internal perturbations.

This issue is reflected in the following descriptions:

• MC is “a somewhat vague but clinically useful term that distinguishes a better-performing heart from a poorly performing one” (Boulpaep, 2017, p528).

These descriptions at least reflect that MC is not simple but complex.

This situation is very common (Muir and Hamlin, 2020). A few examples are given below.

• “There are numerous techniques which attempt to quantify inotropy (or myocardial contractility)” (Smith and Madigan, 2013, p580).

It will become clear that contractility encompasses much more than inotropy.

Etymologically speaking, inotropy means F (Muir and Hamlin, 2020). It does not encompass V (clinotropy). F generated by myocardial tissue has two components: length-dependent (F_L) and Ca²⁺-dependent (F_Ca; Pieske et al., 1998), as shown in Figure 1. Hence, etymologically, logically, and conceptually, inotropy as F encompasses both F_L and F_Ca. However, it is quite common that only F_Ca is considered inotropy:

• “A modification of the contractile ability of muscle at the cellular level, independent of loading conditions, is said to be a modification of the inotropic state or contractility of the muscle” (Rhoades and Bell, 2018, p893).

In practical application, many inotropic agents are drugs that influence the level of Ca²⁺ transient such as β-agonists, β-blockers, and cardiac glycosides; many inotropic therapies are intended to increase F_Ca (a result of an increase in Ca²⁺ transient) (Marks, 2013; Yang et al., 2023; Arfaras-Melainis et al., 2023). Cardiac physiologists, pharmacologists, clinicians, and others should discuss this issue to reach a consensus. If inotropy encompasses both F_L and F_Ca, then inotropic factors or agents should be changed to Ca²⁺ modulators as we do in this article. If inotropy refers to F_Ca only, then we should redefine inotropy as F_Ca.

Muir and Hamlin (2020) noted that some consider MC the intrinsic ability of the heart to generate F and shortening independent of preload and afterload at a fixed heart rate, while others consider V_max against zero afterload to be equal to the complete measure of it, and still others consider contractility not only the ability of the heart to develop F but also the ability to generate V. Muir and Hamlin (2020) agree with the third option, but it is unclear what “ability” is and whether it is dependent on or independent of extrinsic factors (preload, afterload, heart rate, etc.). In addition, ventricular-level properties are used to describe tissue-level contractility, which is fine if all myocytes are healthy, but if a fraction of myocytes do not function well, using the ventricular-level properties to describe contractility at the myocardial tissue level is inappropriate.

In our opinion, F and V represent different manifestations of myocardial tissue’s ability, and as we will explore later, the complexity of contractility cannot be reduced to a simple ability. This is why we propose that “ability” is just one domain of MC (Geloian and Kuang, 2023) and should be differentiated from the higher-level ability and properties of the heart (e.g., pumping, pressure, stroke volume, ejection fraction, etc.).

MC is commonly considered the heart muscle’s intrinsic contractile property or intrinsic ability to generate force and shorten; the intrinsic property is considered independent of the extrinsic preload and afterload (Muir and Hamlin, 2020). This view is self-contradictory because myocardial tissue’s ability (F and/or V) is highly extrinsic factor-dependent (addressed below); in terms of MC, what factors can be considered intrinsic have not yet been explicitly identified, nor has whether intrinsic factors can be independent of extrinsic factors. We address these issues below.

Necessity: The complexity of MC is evident, with two common tendencies in the literature: defining MC within a purely mechanical scope and oversimplifying it with a single index or sentence. Among the works reviewed, Blinks and Jewell (1972) provided the most comprehensive analysis within the mechanical framework but ultimately concluded that a rigorous definition of MC was impossible. We align with Einstein’s insight that “no problem can be solved from the same level of consciousness that created it,” emphasizing the need for a higher-level, broader conceptualization of MC through a CAS perspective. Furthermore, myocardial contraction is characterized by MC, relaxation, and high resistance to fatigue, with MC as a key emergent property. However, current definitions mostly reflect only the ability domain, focusing on the output (F and/or V), which fails to fully characterize myocardial contraction. A more comprehensive approach must include how resources are allocated, utilized, and how ability emerges.

Feasibility: In the previous section, we reasoned out the three functional domains of MC. With a further explanation of the nonlinear relationships among these domains, the framework can be established.

Suitability: The suffixes “-ity” in capacity and “-ility” in adaptability and ability trace back to the Latin “-itas” or “-itās,” meaning the state, quality, or condition of something. This etymology underscores the suitability of “contractility” as an umbrella or comprehensive term for these three domains, each representing a distinct but interconnected aspect of MC as an active emergent property characterizing a single contraction.

The relationships among the three functional domains of MC for a single contraction can be abstracted as a sequence: regulated capacity/resource Allocation, regulated resource Utilization, and regulated final Output (ability domain); “regulated” reflects the role of the adaptability domain throughout the process. This functional sequence is defined as the A-U-O pattern, depicted in Figure 2.

Five points should be noted. First, the MC framework naturally applies to an individual cardiomyocyte to describe cellular contractility. Second, since the three domains in the framework are shared by all cardiomyocytes, it can be extended to describe MC at the myocardial tissue level. However, third, when applying it to the tissue level, the heterogeneities among cardiomyocytes are not taken into consideration, which is a limitation of the MC framework. Another limitation is that only the outputs of the ability domain are measurable (as primary P₀, V_max, F, and V and secondary F-V, F-L relationships, etc.), so evaluations of the performances of the capacity/resource and adaptability domains are not possible currently. However, the MC framework can guide research and clinical practice toward this direction, as described in the next section. Fourth, MC itself can be considered a functional CAS affiliated with myocardial contraction. It is an open system, subject to corrections, modifications, and new developments because myocardial contraction is extremely complex. Finally, although MC is an active property of muscle contraction, it cannot be isolated from the passive properties of the myocardial tissue but is influenced by them.

Aboelkassem and Trayanova (2019) modeled tropomyosin dynamics using a multi-well energy landscape. Their mathematical approach offers theoretical support to our conceptual and qualitative CAS approach to MC and a valuable foundation for future quantitative modeling of our framework, particularly in understanding how Ca²⁺ modulators influence the functional states of the myocardium.

Identifying the primary and secondary changes in the three domains informs training or therapeutic strategies. For example, during acute exercise, MC is primarily enhanced through the adaptability and ability domains, while the capacity/resource domain remains unchanged. The adaptability domain regulates β-adrenergic stimulation, increasing Ca²⁺ transient amplitude, speed, and calcium sensitivity, which enhances resource utilization without altering the capacity of all resources. This results in a non-linear enhancement of the output of the ability domain to meet the increased metabolic demand. In contrast, ischemia primarily affects the capacity domain and possibly the adaptability domain, leading to a decline in ability. Structural damage and oxygen deprivation reduce filament availability, ATP production, and Ca²⁺ handling efficiency, compromising the capacity/resource domain. Simultaneously, the adaptability domain becomes dysregulated, as excessive sympathetic activation attempts to compensate but eventually results in impaired calcium handling. Despite the initial injury, functional decline in the ability domain is non-linear, as compensatory mechanisms can temporarily preserve myocardial output before functional collapse. These examples highlight the non-linear interactions among the three domains, where adaptability can optimize performance without changing the capacity of the resource domain, while disruptions in capacity can trigger disproportionate functional decline.

Clinically, this framework suggests that positive inotropic agents, commonly used to increase MC in heart failure, may worsen ischemic injury. By amplifying calcium influx and cross-bridge cycling, these agents increase oxygen demand and cellular stress, potentially accelerating damage in already compromised tissue, similar to the way driving a worn-out car engine at maximum speed risks further structural damage. This view highlights the need for interventions that preserve capacity and optimize adaptability rather than merely enhancing contraction force as follows.

During ischemia, microvascular dysfunction is a new emergent property (consequence). Even after reperfusion, microcirculatory disturbances can persist, contributing to ongoing injury and adverse remodeling (Hausenloy and Yellon, 2013). Mechanisms such as endothelial injury and nitric oxide dysregulation provide opportunities for targeted therapies, including agents that restore endothelial function or promote angiogenesis (Wang and He, 2020). Similarly, ischemia-induced metabolic shifts from aerobic to anaerobic metabolism, with lactate accumulation and ATP depletion, can impair contractility and lead to further injury. Metabolic interventions, such as glucose- and fatty acid-based therapies, have been explored as adjunctive strategies to protect ischemic myocardium (Taegtmeyer, 2004; Jaswal et al., 2011).

Figure 3 further illustrates that positioning MC at the myocardial tissue level precisely defines its role: characterizing myocardial contraction comprehensively. So far, the heart- or ventricular-level parameters (stroke volume, ejection fraction, ESPVR, etc.) are confused with the tissue-level MC, which is disadvantageous for personalized and precise medicine. Figure 3 also explicitly differentiates what output of the whole heart is goal-directed and what outputs serve regulatory roles. This differentiation better illustrates the layered, non-linear dynamics between the myocardium and the levels beyond it.

Within the MC framework, all issues discussed in the previous section are eliminated. As shown above, MC and cardiac performance are clearly differentiated. And the framework clarifies and extends Muir and Hamlin’s (2020) modern definition by clearly distinguishing adaptability from ability. Their description of “preload, afterload, and length-independent intrinsic” maps to the capacity/resource domain, while their “kinetically controlled, chemo-mechanical processes responsible for force and velocity” merges adaptability with ability. Our three-domain framework separates adaptability and ability, providing greater clarity and also incorporating long-term chronic adaptation.

The concept of cardiac reserve is commonly used to describe the heart’s ability to increase contractile performance under stress, often linked to Ca²⁺ handling mechanisms and β-adrenergic stimulation at the whole-heart level. It primarily reflects a functional (not structural) reserve used to augment contractility in response to increased demands. At the myocardial tissue level, a similar concept can be described as myocardial reserve, which refers to the tissue’s functional capacity to enhance contractility when needed. Our capacity domain is broader, encompassing not only this functional reserve but also structural resources (e.g., the total number of myosin heads and actin binding sites) and functional resources (e.g., Ca²⁺ handling capacity and ATP availability). It represents the total intrinsic resources available for contraction, independent of their recruitment during a single contraction cycle.

A critical distinction lies in the nonlinear relationship between myocardial reserve (tissue level) and cardiac reserve (whole-heart level). A reduction in myocardial reserve due to localized dysfunction, such as ischemia, may not immediately lower cardiac reserve due to compensatory mechanisms like increased recruitment of healthy myocardial regions. However, once these mechanisms reach their limits, further reductions in myocardial reserve can result in a disproportionate decline in cardiac reserve. This difference emphasizes the importance of conceptualizing MC from the perspective of a complex adaptive system (CAS). Recognizing nonlinear dynamics and emergent properties is crucial for accurately assessing MC and understanding how tissue-level impairments can influence whole-heart performance.

Grouping preload, Ca²⁺ modulators, and afterload as the three immediate extrinsic factors (3-imEFs) is necessary for three reasons: First, they are indeed acute extrinsic factors modulating the capacity/resource domain to generate functional ability, distinct from long-term influences. Second, this article is the first to present their sequential roles from possibility to feasibility to realizability in a complete time-series progression (Table 1), advancing the theoretical understanding of MC beyond experimental studies. Third, despite their sequential importance in completing a contraction, textbooks and literature often list only preload and afterload as extrinsic factors, while contractility remains vaguely defined as an intrinsic factor. Omitting Ca²⁺ modulators as a parallel extrinsic factor equivalent to preload and afterload reveals a logical gap. By defining them as 3-imEFs, we place Ca²⁺ modulators in their proper context, addressing this gap and completing a systematic, time-sequenced view of a single muscle contraction.

In the coordinates, the non-linear dynamics of a process means that any change of the framework must involve changes in the X-axis (resource flow) and/or the Y-axis (functional state); however, a change in the X-axis and/or Y-axis may not always result in a change in the overall function, unless critical thresholds are reached. For example, a membrane potential increase may only trigger an action potential if a threshold is crossed, while the oxygen dissociation curve shows that hemoglobin saturation changes minimally at high O₂ partial pressure but shifts dramatically in the mid-range. Similarly, research and clinical practice should focus on identifying the pivotal thresholds where small changes can trigger disproportionate effects, aiding early intervention strategies. In summary, recognizing non-linearity helps maximize efficiency, achieving greater impact with minimal input—an insight with relevance beyond MC.

The A-U-O (Allocation-Utilization-Output) pattern is natural, logical, and internally consistent, making it potentially applicable beyond the MC framework. For example, in gene expression, regulated genetic resource Allocation (epigenetically selected gene expression) is followed by regulated Utilization (transcription) and then the regulated Output as structural and functional phenotypes. Similarly, the primary goal of glomerular blood flow regulation is to maintain a normal glomerular filtration rate (GFR, goal-directed Output). This is achieved by renal autoregulation, initially modulating afferent arteriole tone (Allocation and Utilization of afferent arterioles and nephrons). When these mechanisms are insufficient due to a significant drop in renal blood flow, it is possible that resource Allocation expands to include efferent arterioles to constrict (Utilization). So, it is still likely to maintain the normal GFR Output even the normal RPF cannot be maintained (Denton et al., 2000; Kuang et al., 2024).

The efficiency of MC (Mechanical energy produced during muscle contraction/Total energy expenditure, Gibbs and Barclay, 1998; Han et al., 2022) should be considered an emergent property because it is not just about energy expenditure (e.g., ATP use during cross-bridge cycling and Ca²⁺ reuptake) but an outcome of the dynamic integration of the capacity, adaptability, and ability domains.

Understanding efficiency as a system-level emergent property has several implications. It could help tailor treatments for cardiac conditions like heart failure by focusing not just on energy usage (e.g., ATP production) but also on enhancing muscle capacity and adaptability. Drugs and therapies could target multiple pathways for improved heart function. Exercise training programs could be designed to optimize muscle adaptability and ability, improving overall performance, rather than focusing solely on energy efficiency. Studying the various patterns of adaptive heterogeneity is a challenging but necessary task to deepen the understanding of cardiac performance.

In mammals, all body cells, including cardiomyocytes, have intrinsic circadian clocks that regulate various cellular processes, synchronizing with the central circadian clock in the hypothalamus, which coordinates biological rhythms throughout the body (Durgan and Young, 2010; Martino and Young, 2015; Crnko et al., 2019; Lal et al., 2024). These intrinsic clocks influence cellular functions like metabolism, gene expression, epigenetic regulation, and signaling. Consequently, all domains of MC should be circadian rhythm-dependent, with contractile function varying throughout the day. Maximal isometric tension in the human heart typically peaks during the late afternoon or early evening, aligned with peak circadian gene expression (Malik et al., 2020; Lal et al., 2024). By aligning research experiments, exercise training, drug administration, and so forth with the natural circadian rhythm, it is possible to optimize outcomes, enhance efficacy, and reduce risks in cardiovascular health management.

Cardiac muscle function is history-dependent, meaning its current function is influenced by its prior activity or conditions. For example, the Bowditch effect (staircase phenomenon or frequency-dependent activation) illustrates how an increase in heart rate (or stimulation frequency) leads to a gradual enhancement of contraction strength, largely attributed to increased Ca²⁺ availability in the cardiomyocytes (Endoh, 2004; Usman et al., 2023). The Frank-Starling mechanism is another example of history-dependent myocardial function. It demonstrates that a previous increase in ventricular filling (preload) enhances subsequent contraction strength by optimizing actin-myosin overlap within the sarcomeres. The history-dependent nature of myocardial function highlights the value of progressive adaptation in exercise training and preventing overtraining and maladaptive changes in the heart. Future researchers can place an explicit focus on optimizing the ability domain of MC through optimizing the adaptability domain, which encompasses more efficient utilization of the capacity/resource domain.

Cellular activities or events, such as enzyme activities, signal transduction pathways, protein folding and stability, membrane fluidity, and gene expression, are temperature-dependent. Hence, temperature changes influence all three domains of MC. Both external and internal heat affect the heart’s thermal environment (Gambassi et al., 1994; Dietrichs et al., 2019). In general, as the temperature rises, the rate of biochemical reactions increases, which can enhance the contractile performance of cardiac muscles by accelerating the rate of cross-bridge cycling between actin and myosin filaments. However, excessively high temperatures may lead to protein denaturation and impaired cardiac function. Conversely, lower temperatures generally slow down these biochemical processes, reducing the rate of contraction and the force generated (Fenton et al., 2013). This temperature-dependency is crucial for understanding the physiological limits of myocardial function under varying thermal conditions and can have significant implications for clinical settings where body temperature deviates from normal ranges (Moghadamnia et al., 2017).

In terms of the system-level properties of MC, the following points need to be addressed. First, due to the interconnectedness and interdependence of the functions from the molecular level to the cellular, myocardial tissue, and heart levels, these system-level properties may be shared by all levels of functions in the heart and thus may be extended to be the system-level properties of the entire heart. Second, the four properties highlighted above are not exclusive. Third, the previous two points can be exemplified using the concept of adaptability, which can be applied to all levels in the heart, manifested as adaptive changes in some signal transduction pathways, epigenetic regulation, functions of cardiomyocytes, myocardial tissues, and the entire heart. Finally, when the term “adaptability” is used, it is necessary to provide the scope or level at which it applies. The adaptability domain in the MC framework (Figure 2) applies specifically to the MC framework and is responsible for the allocation and utilization of the capacity/resource domain and production of the ability of the myocardium.