1. Introduction

A human exploration mission to Mars will undoubtedly be considered an enormous technologic triumph. However, the greatest barriers for such a mission are probably those concerning physiology rather than technology. It is uncertain how the human body will respond to a prolonged journey in microgravity and then adapt to the 0.38 G forces and environmental conditions of Mars. It is also unknown how to best manage common medical problems or respond to the inevitable medical emergency in the context of this adapted physiology (Williams 2003; Summers et al. 2005; Baisden et al. 2008; Williams et al. 2009).

In the past, physicians applied common earth-based clinical practices and judgment in their approach to solving medical problems in space (Williams 2003). Space medicine practitioners have currently embraced a more evidence-based approached using the accumulated medical experience learned from 40 years of spaceflight missions as well as a growing foundation of space related biomedical research (Williams 2003; Williams et al 2009). However, as we face the challenge of interplanetary travel, there are no prior experiences and a dearth of relevant research as it relates to an understanding of how human physiology is expected to adapt to the gravity of Mars during an extended stay (Buckey 1999; Haddy 2007). It also seems implausible that the physiologic state of the human body subjected to gravitational forces positioned somewhere between the magnitude of Earth’s gravity and microgravity can be considered as a simple linear extrapolation between these two conditions. The use of ground-based analogues to study the biomedical impact of sub-earth gravity states has been very limited due to the difficulties in developing models that are realistic for all physiologic systems --cardiovascular, bone, muscle, etc. (Pavy-Le Traon 1997; Nicogossian AE et al. 1994)). With a wealth of available information concerning human physiologic responses and adaptations to Earth and microgravity environments, scientists are looking for a way to extrapolate between these experiences to predict the expected acclimatization to a long-term Mars habitation (Davis 1998; Buckey 1999; Haddy 2007; Baisden 2008; Hawkey 2005).

Current advances in modern computer technology have allowed for the development of complex mathematical models and simulations of human biology that can be used to analyze mechanisms of physiologic adaptations and pathophysiologic functioning (Montani et al.1989; Summers et al. 1996; Summers 1998). Consideration of such computer-based simulation and systems analysis methodologies as a possible alternative to actual medical experience or ground-based analogues has been recommended by space medicine experts (Perino et al. 1993; Nicogossian 1994; White 2003; Williams 2003). Even the IOM Review of NASA’s Bioastronautics Roadmap suggests that digital models and simulations could play an important role in the evaluation and mitigation of risks to humans in space (Longnecker 2006). This approach is of particular value under circumstances where there is no relevant prior knowledge available and no means for attaining this information. In this paper we derive a theoretical construct using the methodology computer modeling through which adaptations of human physiology to the Mars environment can be generally predicted. We also examine whether these predictions follow those extrapolated from previous microgravity and earth based medical experiences or present a whole new physiologic framework for medical decision making.

2. Methods

The NASA Digital Astronaut (see appendix) was used to predict some specific physiologic adaptations of humans to the Mars gravity environment and compared to those from the literature determined experimentally in microgravity and on earth. The results of these predictions and experimental findings were plotted graphically to examine if the Mars parameters could be readily extrapolated from the microgravity and earth-based experience.

The Mars adapted physiology model was then placed in a state of simulated acute decompensated heart failure (ADHF) and common earth-based medical management principles were applied (Summers et al. 2009c). The model parameter outputs were monitored for evidence of systemic decompensation and clinical severity and risk scores were calculated (Lee et al. 2003).

Three specific target physiologic variables (plasma volume, central venous pressure, and red blood cell volume) were chosen for the analysis. These variables were chosen because:

2a. In Silico investigational protocol. The Digital Astronaut was used in computer simulation studies to theoretically examine the functioning of a Mars environment-physiology interface within an in silico environment (Summers et al 1996; Summers 2008a). The analytic procedure involved recreating the conditions expected to be experienced on Mars (0.38 G, habitat environment, etc.) for a virtual subject in a dynamic computer simulation. The experience of Earth, microgravity and lunar gravity environments were also simulated so that these predicted physiologic changes could be included in the analysis. The virtual subject was allowed to adapt to each of these gravitational environments for a period of one month. The generic virtual subject used in the simulations was a normalized 70 kilogram male with no previous pathology. Overall sequential changes in the target physiologic parameters were recorded during the time course of the simulated protocol. For the ADHF simulation the ventricular contractility was reduced to 30% of normal for both the Mars and Earth conditions and again sequential changes in the target physiologic parameters and vital signs were recorded as markers of clinical decompensation. These values were used to calculate an EFFECT heart failure physiologic severity and risk score (Lee et al. 2003) as an indicator of the relative clinical severity of the subject in these different gravity environments. The responsiveness of each of these simulated ADHF conditions to management with loop diuretics (80 mg of single dose intravenous furosemide) was also examined.

3. Results

The results of the simulations are portrayed graphically figures 1-3. These figures show the relations between predicted values for plasma volumes, right atrial pressures, and red blood cell volumes are shown for the various gravitational environments of Earth, Moon, Mars and microgravity. The validation comparisons for Earth and microgravity conditions have been previously published (Summers 2008). The true values for the Moon and Mars adaptations are still unknown. It is important to note the nonlinear nature of these relations.

The clinical simulations study demonstrated less lung fluid accumulation during heart failure in microgravity as compared to a terrestrial experience but with a worse overall heart failure physiologic severity score (97 vs 93).

The Mars adapted virtual subject physiology results only slightly differed from those seen during the Earth simulation (< 10%) with almost no difference in clinical severity scoring (96.3). The heart failure in microgravity was also significantly less responsive to therapeutics than both the Earth and Mars adapted virtual subjects with 27% less diuresis over the 1st hour of treatment.

4. Discussion

When NASA flight engineers determine the optimal path and orbit that should be taken when a spacecraft approaches Mars, these decisions will be based upon the calculations of mathematical models and computer simulations that are constructed using well known physical relations and theoretical constructs. These models can provide very precise determinations as to the impact the Mars gravitational environment will have upon the spacecraft. Similarly, our predictions of the physiologic responses of astronauts in the Mars gravity environment should be guided by sophisticated quantitative models. Simulation studies presented in this paper using the Digital Astronaut suggest that our prior spaceflight biomedical experiences in the microgravity environment cannot be simply extrapolated to provide accurate predictions of human physiologic adaptations during a prolonged Mars habitation.

When a system under study is complex, nonlinear or involves homeostatic feedback mechanisms, as is the case for most human systems physiology, it is imperative that the description and analysis must also reflect a high degree of sophistication (Coleman 1975; Kootsey 1987; Summers et al. 1996; Summers 1998). Simple verbal descriptions of homeostatic biological systems can be inadequate because of the difference between the sequential nature of language and the simultaneous character of biologic processes. Likewise, even detailed visual models are unable to capture the dynamic quality of physiologic systems analysis. Mathematical models and simulations have been used for many years to study and predict physiologic phenomena and to assist in the understanding of disease processes (Guyton et al 1969 & 1999, Summers 1997). While these models are surely limited by the inevitable probability that there is missing information and detail necessary for complete certainty in their predictive power, the results of such simulations are likely better than speculative estimations based upon a more qualitative perspective.

From a simple observation of the results of the simulation studies it appears there is a nonlinear relationship between variations in gravitational environments and the physiologic adaptations of the target parameters. However, the curvature is of varying degrees and directions implying that the complexities of the physiologic infrastructure and controls systems are definitely involved in the adaptations. It is interesting to note that the right atrial pressure relationship is not nearly as curvilinear as that for plasma volume or red blood cell volume. This finding is likely the result of a more direct influence of gravitational forces on the outcome of this parameter. In fact, it has been considered that the specific influence of gravity on the rotation of the chest wall and its effect on pleural and cardiac transmural pressures is a major direct determinant of the set point for right atrial pressure (Edyvean et al. 1991; White et al. 1998). This finding suggests that the further removed a physiologic parameter’s homeostatic set point is from a direct influence by gravitational forces then the more biologic plasticity may impact the adaptation.

The differences in the simulated pathophysiologic condition reflect an additional degree of complexity that might occur when the systems is deranged. Microgravity exposure has been shown to result in a general systemic dehydration and could be somewhat protective against edema formation (Platts et al. 2009). The application of even fractional gravity to the system restores a general hydrostatic gradient throughout the body and dramatically changes the setpoint values for key physiologic parameters. The adjustments in renal hemodynamics and neurohormonal state seen in microgravity reflecting a relative hypovolemia along the cardiorenal axis are greatly ameliorated in the Mars gravity. This is evident in the lack of renal resistance to loop diuretics in the Mars gravity as was seen in the microgravity simulations. Gender differences are to be expected and modify these findings due to the increased propensity for orthostatic stress seen in women as compared to men (Ilescu et al. 2009; Platts et al. 2009; Summers et al. 2002; Summers et al. 2010). Since the proposed mechanism for this orthostasis seems to be initiated by physical factors and gravity induced hydrostatic forces, the outcomes for women in the Mars environment would be expected to also follow a nonlinear construct for adaptation though perhaps more pronounced. However, it is uncertain if this same framework would apply for all physiologic variables in women.

In the simulations performed in this study, the Mars adapted values of key parameters were predicted. Beyond the determination of specific predicted values for these few parameters, the goal of the current analysis was to determine if physiologic adaptations to gravitational environments follow a consistent and sequentially linear pattern between the 1G force of earth and those found in microgravity. This exercise may assist scientists and physicians with future predictions of the physiological adaptations to a Mars habitation and help guide clinicians in their expectations of the human risks of such an endeavor. In this way the analysis could serve as a general theoretical framework from which to think about medical management of participants in a Mars mission.

The importance of having the appropriate theoretical framework for medical decision making is demonstrated in the clinical simulation. It has been previously shown that prolonged spaceflight can potentially result in a diminution of cardiac function (Summers et al. 2007; Summers et al. 2008b). Previous simulation studies based on experimental evidences during spaceflight suggest that the optimal management of ADHF in the microgravity environment would be decidedly different from the standards of care presently used on earth (Summers et al. 2006, Summers et al. 2007, Summers et al. 2008b, Summers et al. 2009c). The results of the current simulation studies for ADHF in the Mars condition are very similar to the earth practices even though the Mars gravity is less than half of that experienced on earth. This finding suggests that a theoretical conception of a nonlinear adaptation of human physiology to gravity environments certainly changes the clinical perspective and could impact medical management decision making in the context of a Mars condition.

With further maturation and validation, the Digital Astronaut might become a valuable tool in medical planning considerations for a Mars mission. If a lunar habitation is used for Mars mission staging, physiologic measures obtained in this partial G environment could be used to further test and validate the model and provide assurance for the Mars predictions. The system could then be used to examine human interfacing with a Mars habitat and to understand the special physiologic adaptations and countermeasures required for an extended mission (Summers et al. 2009b). The Digital Astronaut could also then be used by Earth based clinical personnel to assist in providing medical advice to Mars explorers and predicting responses to treatment using a systems analysis approach in the context of a Mars adapted human physiology (Williams et al. 2000; White et al. 2003).

A manned mission to Mars will undoubtedly require sophisticated planning and detailed logistical strategies that optimize the potential for a successful journey. Likewise, the technology and equipment used during a Mars habitation will be carefully vetted with regard to efficiency and functionality. The impact that such a mission will have on the complexities of the physiology of the humans making this voyage will be the most difficult to predict.

The Digital Astronaut model is a product of the NASA Digital Astronaut Project and is a special adaptation of an existing computer model of human physiology developed at the University of Mississippi Medical Center over the past 40 years (Guyton 1969 & 1999; Coleman 1979; Abram et al. 2007; Summers et al. 2008a). The model contains over 6000 variables of biologic interactions and encompasses a variety of physiologic processes of interest to humans during spaceflight. These processes incorporate a variety of biologic elements and the adaptation of these systems to variations in gravitational conditions. The mathematical framework of the model is constructed around the concept of a hierarchy of control in which relationships are based primarily on a foundation of first principles (i.e. mass balances, physical forces). Physiologic relationships derived from the evidence-based literature are represented as function curves within the model structure. Different physiologic systems and body organs are connected through feedback and feedforward loops in the form of algebraic and differential equations to create a global homeostatic system (Abram et al. 2007). The model and software support system allows scientists to perform systems analyses and theoretical hypothesis testing on specific research questions (Montani et al. 1989).