D
Workshop Manuscripts

PREDICTING AND PROTECTING PERFORMANCE USING METABOLIC MONITORING STRATEGIES: IT’S ALL WET STUFF ANYWAY, ISN’T IT?

COL Karl E.Friedl, U.S. Army Research Institute of Environmental Medicine

The ultimate reductionistic view of the Military Operational Medicine Research Program (MOMRP) centers on metabolism as the answer to all questions. For every problem we are trying to solve in the MOMRP, we will someday complete the connection to a metabolic basis. This includes soldier performance problems that range from extended physical stamina to sustaining optimal mood and behavior. While this first-principles approach is not likely to provide many near-term solutions to MOMRP problems, we can exploit the emerging physiology to develop monitoring technologies. Insight into this metabolic activity should help predict individual status and physiological reserve. This is based on the premise that these metabolic processes are the basis of the responses that allow organisms to survive in the face of environmental challenges and are the earliest indicators of a change in physiological status. This calls for a thoughtful review of currently known regulatory mechanisms that suggest promising predictive markers of status and impending failure of adaptive response capabilities. We should also consider applications of the most promising monitoring technologies that are currently available. The focus of this workshop is to address: what are the best metabolic targets for monitoring and what are the most promising monitoring technologies?

This information is needed for predictions about the readiness status of individuals in training and in operational settings where human performance is important. We have formidable monitoring capabilities on military systems, but lack real-time information on the status of our own troops. This serves U.S. de-



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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance D Workshop Manuscripts PREDICTING AND PROTECTING PERFORMANCE USING METABOLIC MONITORING STRATEGIES: IT’S ALL WET STUFF ANYWAY, ISN’T IT? COL Karl E.Friedl, U.S. Army Research Institute of Environmental Medicine The ultimate reductionistic view of the Military Operational Medicine Research Program (MOMRP) centers on metabolism as the answer to all questions. For every problem we are trying to solve in the MOMRP, we will someday complete the connection to a metabolic basis. This includes soldier performance problems that range from extended physical stamina to sustaining optimal mood and behavior. While this first-principles approach is not likely to provide many near-term solutions to MOMRP problems, we can exploit the emerging physiology to develop monitoring technologies. Insight into this metabolic activity should help predict individual status and physiological reserve. This is based on the premise that these metabolic processes are the basis of the responses that allow organisms to survive in the face of environmental challenges and are the earliest indicators of a change in physiological status. This calls for a thoughtful review of currently known regulatory mechanisms that suggest promising predictive markers of status and impending failure of adaptive response capabilities. We should also consider applications of the most promising monitoring technologies that are currently available. The focus of this workshop is to address: what are the best metabolic targets for monitoring and what are the most promising monitoring technologies? This information is needed for predictions about the readiness status of individuals in training and in operational settings where human performance is important. We have formidable monitoring capabilities on military systems, but lack real-time information on the status of our own troops. This serves U.S. de-

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance fense priorities to “assure readiness of the Armed Forces” and to “transform the Department of Defense” (including experimenting with new approaches to warfare). RESEARCH REQUIREMENTS FOR PHYSIOLOGICAL MONITORING Monitoring soldier status has become increasingly important because of new lethal and complex technologies that require high reliability of the human operator and new tactics that reduce line-of-sight contact with team members and increase geographical distance and isolation. No longer is soldier monitoring just a nice-to-have technological replacement for common sense or for good leadership that includes understanding the signs of soldier limits. Soldiers may not know they are reaching dangerous levels of overheating and dehydration and, if they are fully encapsulated in protective suits and operating in a remote site, their team leaders also may not know they are heading for trouble. An alert to the individual on their future helmet visor display and/or an automatic “911” message to their squad leader can provoke a prompt intervention and save a mission. The Navy is designing ships with substantially reduced crew sizes, which calls for greater reliance on each individual. Monitoring the status of these sailors becomes especially important if they are incapacitated in an isolated crew compartment during high-risk damage control operations, such as fighting fires or flooding. The concept of the Reduced Ships-Crew by Virtual Presence is for smart ships to continuously receive data on the status of the ship, as well as on the crew within the ship (Street et al., 2002). Today’s high performance aircraft can easily exceed the limits of human physiological tolerances, and one concept for physiological monitoring includes detection of an approaching loss of consciousness to trigger an automatic take over of the controls (Forster et al., 1994). This calls for a rapidly responsive system that, with high reliability, identifies a major lapse in pilot capabilities. Monitoring in training is at least as important as in operational environments. It may be most useful for leaders to use physiological monitoring to learn the limits of their own soldiers during training operations. Then, during an actual operational mission, they might use monitoring only for specific warnings about real-time status. Other aspects of metabolic monitoring may not require a wearable system, but simply periodic testing to determine, for example, if individuals have reached a high state of bone and muscle remodeling during their training and can reduce a high probability of injury by resting the next day. This kind of feedback will be broadly useful to learning limits of individuals and units. Physiological monitoring is being explored for a wide variety of other military applications, including the forensic “black box” flight recorder-type of analysis of a pilot’s mental state after a class A accident, in order to prevent future accidents (Forster, 2002). There is also a need for overall “whole body”

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance health markers for easy assessment of global indices of service members’ health at regular intervals throughout their career. This could eventually represent some combination of psychological and physiological health, using markers such as brain metabolites monitored via magnetic resonance spectroscopy (MRS) scans, whole-body oxidative stress load assessments, and mitochondrial redox potential of critical brain cells. RECENT EVOLUTION OF MONITORING RESEARCH Physiological monitoring concepts are not new, but the measurement technologies have advanced more rapidly than our understanding of what the measurements mean to health and performance. Fifty years ago, the Office of Naval Research and the Army Surgeon General cooperatively studied infantrymen in combat to identify metabolic predictors of mental status (Davis et al., 1952). Using neuropsychological testing (including visual flicker fusion and auditory flutter fusion tests) and blood and urine testing, they assessed hydration status, adrenal stress markers, and corresponding changes in cognitive functioning. Studies by the Air Force explored the use of an electroencephalogram (EEG) to monitor pilot performance as early as the 1950s (Sem-Jacobsen, 1959). Current studies are examining many of the same factors and relationships that were tested in the studies 50 years ago. Although these newer empirical studies have some technological advantages, most notably electronic computing power, the studies have largely relied on available technologies instead of exploring the most suitable measurement targets and developing specifically needed monitoring technology. Many of the available technologies are simply telemetered applications of clinical monitoring systems, limiting advances to spin offs from standards of medical care. We have spent too much time trying to find uses for new measurement technologies instead of pushing the development of technology to systematically test what we understand about physiology and to predict outcomes of greatest importance. The greatest barrier to advances in performance monitoring has been the lack of suitably defined performance outcome measures. Until recently, aviator performance has been the most extensively studied model for physiological monitoring. Military aviators have been a logical focus because of the need (i.e., the high costs associated with catastrophic performance failures) and because of the experimental advantages. Performance outcome measures are better defined for aviator tasks, especially the ultimate outcome of successful landing versus disaster. The cockpit also provides a friendly setting for clunky prototype monitoring systems that are power hungry and tethered to heavy equipment. Aviator studies can provide early proof of concept for systems that are later reduced in size, weight, power, and invasiveness for untethered applications in soldiers, marines, and sailors. Nevertheless, the aviator monitoring studies are not generalizable without the further development of performance assessment methods and metrics.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance Without suitable performance measures, results from lab-based studies cannot be translated into militarily relevant outcomes. These measures are also needed for field studies that are otherwise forced to rely on simple dichotomies of “no bad outcome” or catastrophic failure (e.g., heat stroke, serious injury, or mission failure). The MOMRP has invested heavily in the development and standardization of practical neuropsychological tests (e.g., the Automated Neuropsychological Assessment Metric) (Kane and Kay, 1992), and current field studies are attempting to link these test results with military performance. For example, simple reaction time remained impaired following sports concussions in military cadets even after they were cleared for return to duty by clinical criteria; the significance of this finding to other performance measures is being further investigated. Cold water immersion reliably affected the matching-to-sample test; what this means to Navy diver performance capabilities is also being further investigated (Thomas et al., 1989). One eventual monitoring application would be to embed informative tests into common military tasks that could be monitored in order to obtain unobtrusive periodic assessments of an individual’s performance status. We are currently sponsoring a Department of Defense (DOD) review of methods and metrics for performance assessment that synthesizes the current state of the knowledge on militarily relevant performance assessments and models (Ness et al., In preparation). We have also launched a new research initiative on the development of military performance assessment methods based on measures of neurological function, such as voice stress analysis and eye saccades (Science Technology Evaluation Package 3.C). Physiological monitoring moved from a research sidelight to a central objective in the Army research program under the guidance of Dr. Fred Hegge in 1996. The goal of the Warfighter Physiological Status Monitoring (WPSM) initiative is to make real-time performance predictions that leaders can use to assess the readiness status of their forces. The concept is to develop a soldier-acceptable, minimally invasive sensor set with on-the-soldier analysis. The output (which can be queried for further information) will be a simple “green” (within normal limits), “amber” (physiological challenges are present), or “red” (systems have failed and the soldier is a casualty). This relies on the vast trove of environmental physiology and psychological data collected and modeled in DOD research programs for many years. A key feature of the approach is that these systems must also learn the usual range of responses for its soldier, accounting for individual variability. Currently, WPSM is a research “tool kit” to learn more about normal and abnormal physiological signals encountered in real soldier environments; these include a range of responses that routinely exceed those that can be obtained in an ethically developed experimental laboratory setting. WPSM will ultimately be reduced to the minimal sensor set needed for highly reliable and important predictions. Reed Hoyt currently leads this program with the development of experimental signal acquisition and data handling systems and data collection studies with marines and soldiers in challenging training environments (Hoyt et al., 1997a, 2001). The immediate requirements

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance for WPSM are to provide status for thermal strain, live-dead detection, sleep history, and energy expenditure for the Land Warrior system. In later iterations of this system (e.g., the Objective Force Warrior), more sophisticated monitoring capabilities and performance predictions are planned that will also include early casualty triage capabilities. EXAMPLES OF CURRENT RESEARCH EFFORTS, AND LEVERAGING FROM RELATED PROGRAMS We have chosen several critical areas for review: hydration and heat production, substrate utilization and energy metabolism, muscle and bone remodeling, and brain function. These traditionally separate research areas are interrelated through metabolic processes. For example, exertional rhabdomyolysis has elements of hydration and heat exposure, energy flux, and muscle remodeling, with early effects on mental status (Gardner and Kark, 1994). The topics are also closely interrelated through common measures that might signal changes in one or more of these physiological categories. For example, shivering may indicate a variety of threats that, when combined with one or two other measurements, can unambiguously distinguish impending hypothermia risk, exposure to a neurotoxic chemical, or intense psychological fear. Brain function reflected in cognitive, mood, or psychomotor measures (e.g., speed of mental processing, irritability, and marksmanship) may be a common and sensitive marker of deficits of all the other stressors and functional deficits of interest. These may include each of the topics in this workshop, including carbohydrate metabolism in physical exhaustion (Frier, 2001), dehydration or significant fluid shifts such as those observed in the brain with acute mountain sickness (Singh et al., 1990), and perhaps even cytokine-mediated changes in brain function following intense muscular exertion (Febbraio and Pedersen, 2002). Brain function is both an early indicator of many stressors of concern and a direct reflection of specific performance capabilities. Early changes to defend critical functions are likely to be more promising prognostic indicators than awaiting change in the critical function itself (e.g., blood glucose, serum osmolality, core body temperature). The critical function may be so well defended, such as serum osmolality and sodium concentration, that when a significant change is detected, homeostatic mechanisms have failed and the individual is already a casualty. Earlier changes in interstitial fluid or osmoregulatory hormones may signal a heroic defense against a threat to intravascular volume, even while other measures appear to indicate that all is still well. There are also conditions under which the critical function measurement, such as body temperature, may have a wider range of “normal” at performance extremes in healthy individuals than previously recognized. This reflects highly appropriate compensation to sustain peak performance, defying definitive classification of an impending performance failure until regulatory mechanisms fail. For example, core body temperature may be as low as 35°C at the circadian

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance TABLE D-1 Technology Forecast for Practical Metabolic Assessment Measures (Measured Endpoints and Conceivable Technologies) Past Presenta Energy balance and fuel availability   Blood and urine biochemistry Ratings of perceived exertion Home test glucose monitors, lab tests   “Gluco-watch” Activity-based predictions Reverse iontophoresis, actigraphy Brain metabolic function   Paper and pencil tests   Computerized neuropsychological testing EEG spectral analysis Palm-top test, dry electrodes in a hat band Hydration and water balance   Urine specific gravity   Balance based on intake and predicted losses Whole body water estimates Instrumented canteen/camelbak, bioelectrical resistance Bone and muscle turnover   Loss of strength and delayed onset muscle soreness “Hot spots” Thermography   Specific blood and urinary markers (e.g., telopeptides, myoglobin, CPK, IGF-1) Lab tests a EEG=electroencephalogram, CPK=creatine phosphokinase, IGF-1=insulin-like growth factor-1. nadir in Ranger students who have lost most of their insulative fat and have metabolically adjusted to a reduced energy intake (Hoyt et al., 1997b), and it may be sustained at 40°C for several hours in marathoners during their race (Maron et al., 1977). Monitoring the signs of compensation (e.g., changes in heat flux, activation of sweating or shivering mechanisms, cardiac responses, and mental functioning) may predict a trajectory to danger (amber) well in advance of the unambiguous changes in core body temperature (red). Bone and muscle turnover studies are important to the military to solve near-term problems of high rates of injury during physical training, most importantly during the rapid train-up phase of the 8- to 12-week initial entry training course conducted in every service (half of all female soldiers incur musculoskeletal injury during basic training). A peak incidence of stress fractures by about the third week of training was hypothesized to be associated with high rates of bone remodeling stimulated by the training. This led to a major Army

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance Near Futureb Far Futurec   Subdermal continuous glucose, lactate, pH, free fatty acids Semi-invasive implantable sensors and “tattoos”   Functional outcome (e.g., EMG, nerve conduction, changes in thermal flux) Noninvasive physiological sensors built into clothing   Saccades and pupil responses Voice analysis Task embedded psychological tests Doppler etc. in soldier helmet/spectacles   Sweat/exhaled cytokines Volatile compounds/pheromones Brain blood flow Chemical nose, respiratory sampling, personal intrahelmet brain imaging systems   Intercellular fluid assessment Whole body water changes Subdermal wicks, boot-sensor body weight tracking with electrolyte and BIA sensors   Changes in skin properties Endocrine changes in defense of water volume Skin mechanical/electrical changes, semi-invasive sensing of osmoregulatory hormones   Sweat markers of calcium and protein metabolism Altered biomechanics Practical field test systems   Changes in redox status Regional metabolism/blood flow changes Deep muscle biochemical sensors b BIA=bioelectrical impedance analysis. c EMG=electromyogram. study that examined the benefits of a physical training rest period in the third week of training (Popovich et al., 2000). Unfortunately, this did not modify the injury profile, suggesting a more complicated pathogenesis, including individual variability. The development of specific markers of susceptibility and impending injury in individuals is still urgently needed. Table D-1 suggests some of the outcomes that might be logical targets for monitoring within the next decade and some of the technologies that exist or could be developed for such monitoring. The boundary between current and near-term approaches is slightly blurred by the overlap of current technologies that require far more validation and projected near-term technologies that are just beginning to demonstrate promise. For example, fitness for duty based on various peripheral indicators of brain function is an important but elusive goal. In the past, there was a hope that performance could be predicted from recent sleep history measured by wrist-worn actigraphy (Redmond and Hegge, 1985); the current status of fatigue-performance models is too immature and individual

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance responses to this single measure are too variable to make this useful by itself (Friedl et al., In press). Potentially noninvasive measurement methods that could be mounted in a helmet, such as pupillometry and saccadic eye movements, are being explored but have so far not held up well compared with lab measures such as the psychomotor vigilance task (Russo et al., 2003). A method developed by the National Aeronautics and Space Administration (NASA) that follows slow eye closure (“droopy” eyelids) shows great promise, but will have to be proven in a helmet-type platform that keeps the monitor in line with the subject’s eyes (Dinges et al., 1998). Voice analysis is specifically affected by emotional load in soldiers, returning to normal with psychological adaptation even while general activation (e.g., accelerated heart rate) continues (Wittels et al., 2002); however, this measure has not yet been demonstrated to correspond to specific performance decrements. EEG analyses in fatigued subjects or during sustained vigilance tasks have been studied in at least three military laboratories and show promise, but they remain to be demonstrated as strong predictors of impending deficits (Caldwell et al., 2002). Far-future technologies are concepts that might be achievable but have not been seriously explored and remain “marks on the wall.” Mitochondrial redox state in specific brain tissues has been suggested as the key marker of brain function status, based on the importance of neural cell bioenergetics. Perhaps the far-future final common pathway to monitor would be something like this and everyone will submit to a minor transsphenoidal surgical procedure for a rice grain-sized monitor of brain status! Intracerebral monitoring of energy-related metabolites is being done with neurosurgical patients now to follow acute conditions involving hypoxia and ischemia. As we learn more about what we need to measure, the technologists may be able to develop the noninvasive monitoring devices to our emerging specifications. For example, with the higher powered magnets, researchers are now detecting glutamate peaks in MRS brain pixels. An elevated frontal lobe glutamate might signify a range of acute metabolic insults that would be very important to detect and countermand. We now have transcranial magnetic stimulation systems that operate with very low power; why not a technology for brain spectroscopy built into a helmet in the future? Nearer term approaches to monitoring brain metabolic activity includes applications of existing near infrared and Doppler probes to estimate fron lobe activity and monitor middle cerebral artery blood flow (Hitchcock et al., 2003). The current military research programs are leveraged with special Congressional appropriations that accelerate basic metabolic research in specific topic areas. The Bone Health and Military Medical Readiness research program (supported by the National Osteoporosis and Related Bone Disorders Coalition) is focused on the improved understanding of bone remodeling processes and includes projects that are exploring markers of impending stress fracture injury. The Technologies for Metabolic Monitoring research program (supported by the Juvenile Diabetes Research Foundation) is testing novel approaches to measure functional outcomes related to biochemical status and energy metabolism, nota-

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance bly glucose regulation, but including also the development of lactate sensors and the exploration of physiological indicators of metabolic status. Projects supported by the Force Health Protection research program examine methods to monitor global health status in soldiers, including the use of breath condensates to measure cytokines and other markers of lung function following blast or toxic inhalation exposures. Two large projects are assessing the association of brain magnetic resonance spectroscopy measures (Schuff et al., 1999) and symptom reporting in chronic multisymptom illnesses to determine objective markers of well-being. Another program is dedicated to the investigation of eye saccades and pupil responses as indices of fatigue and fitness for duty, as described in a recent review by Major General (ret.) Gary Rapmund (2002). The Neurotoxin Exposure Treatment Research Program (sponsored by the Parkinson’s Action Network) includes exploration of voice analysis and neuropsychological testing methods for early detection of neurological changes. Disclaimer: The opinions and assertions expressed in this paper are those of the author and do not necessarily express the official views of the Department of the Army or other Services. REFERENCES Caldwell JA, Hall KC, Erickson BS. 2002. EEG data collected from helicopter pilots in flight are sufficiently sensitive to detect increased fatigue from sleep deprivation. Int J Aviation Psychol 12:19–32. Davis SW, Elmadjian F, Hanson LF, Liddell HS, Zilinsky AA, Johnston ME, Killbuck JH, Pace N, Schaffer FL, Walker EL, Minard D, Kolovos ER, Longley GH. 1952. A Study of Combat Stress, Korea 1952. Technical Memorandum ORO-T-41(FEC). Chevy Chase, MD: Operations Research Office, The Johns Hopkins University. Dinges DF, Mallis MM, Maislin G, Powell JW. 1998. Evaluation of Techniques for Ocular Measurement as an Index of Fatigue and the Basis for Alertness Management. Technical Report DOT-HS-808–762. Washington, DC: National Highway Traffic Safety Administration. Febbraio MA, Pedersen BK. 2002. Muscle-derived interleukin-6: Mechanisms for activation and possible biological roles. FASEB J 16:1335–1347. Forster EM. 2002. Safety of Flight: The Physiologic Aspect of the Weapon System. Patuxent River, MD: Naval Air Warfare Center Aircraft Division. Forster EM, Morrison JG, Hitchcock EM, Scerbo MW. 1994. Physiologic Instrumentation in the Naval Air Warfare Center Human-use Centrifuge to Determine the Effects of Cumulative +Gz on Cognitive Performance. Technical Report NAWCADWAR-956006–4.6. Warminster, PA: Naval Air Warfare Center Aircraft Division. Friedl KE, Mallis MM, Ahlers ST, Popkin SM, Larkin W. In press. Research requirements for operational decision making using fatigue and performance. Aviat Space Environ Med.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance Frier BM. 2001. Hypoglycaemia and cognitive function in diabetes. UCP Suppl 123:30–37. Gardner JW, Kark JA. 1994. Fatal rhabdomyolysis presenting as mild heat illness in military training. Mil Med 159:160–163. Hitchcock EM, Warm JS, Matthews G, Dember WN, Shear PK, Tripp LD, Mayleben DW, Parasuraman R. 2003. Automation cueing modulates cerebral blood flow and vigilance in a simulated air traffic control task. Theor Issues Ergon Sci 4:89–112. Hoyt RW, Buller M, Redin MS, Poor RD, Oliver SR. 1997a. Soldier Physiological Monitoring—Results of Dismounted Battlespace Battle Lab Concept Experimentation Program Field Study. Natick, MA: U.S. Army Research Institute of Environmental Medicine. Hoyt RW, Young AJ, Matthew WT, Kain JE, Buller M. 1997b. Warfighter Physiological Status Monitoring (WPSM): Body Core Temperatures During 96 h of Swamp Phase Ranger Training. Natick, MA: U.S. Army Research Institute of Environmental Medicine. Hoyt RW, Buller MJ, DeLany JP, Stultz D, Warren K. 2001. Warfighter Physiological Status Monitoring (WPSM): Energy Balance and Thermal Status During a 10-day Cold Weather U.S. Marine Corps Infantry Officer Course Field Exercise. Technical Note. Natick, MA: U.S. Army Research Institute of Environmental Medicine. Kane RL, Kay GG. 1992. Computerized assessment in neuropsychology: A review of tests and test batteries. Neuropsychol Rev 3:1–117. Maron MB, Wagner JA, Horvath SM. 1977. Thermoregulatory responses during competitive marathon running. J Appl Physiol 42:909–914. Popovich RM, Gardner JW, Potter R, Knapik JJ, Jones BH. 2000. Effect of rest from running on overuse injuries in army basic training. Am J Prev Med 18:147–155. Rapmund G. 2002. The limits of human performance: A point of view. Aviat Space Environ Med 73:508–514. Redmond DP, Hegge FW. 1985. Observations on the design and specification of a wrist-worn human activity monitoring system. Behav Res Methods Instrum Comput 17:659–669. Russo M, Thomas M, Thorne D, Sing H, Redmond D, Rowland L, Johnson D, Hall S, Krichmar J, Balkin T. 2003. Oculomotor impairment during chronic partial sleep deprivation. Clin Neurophysiol 114:723–736. Schuff N, Amend DL, Knowlton R, Norman D, Fein G, Weiner MW. 1999. Age-related metabolite changes and volume loss in the hippocampus by magnetic resonance spectroscopy and imaging. Neurobiol Aging 20:279–285. Sem-Jacobsen CW. 1959. Electroencephalographic study of pilot stresses in flight. J Aviat Med 30:787–801.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance Singh MV, Rawal SB, Tyagi AK. 1990. Body fluid status on induction, reinduction and prolonged stay at high altitude of human volunteers. Int J Biometeorol 34:93–97. Street TT, Nguyen X, Williams FW. 2002. Wireless Communication Technologies on Ex-USS Shadwell. Technical Report NRL/MR/6180–02–8631. Washington, DC: Naval Research Laboratory. Thomas JR, Ahlers ST, House JF, Schrot J. 1989. Repeated exposure to moderate cold impairs matching-to-sample performance. Aviat Space Environ Med 60:1063–1067. Wittels P, Johannes B, Enne R, Kirsch K, Gunga HC. 2002. Voice monitoring to measure emotional load during short-term stress. Eur J Appl Physiol 87:278–282. CURRENT STATUS OF FIELD APPLICATIONS OF PHYSIOLOGICAL MONITORING FOR THE DISMOUNTED SOLDIER Reed W.Hoyt, COL Karl E.Friedl, U.S. Army Research Institute of Environmental Medicine The dismounted warfighter’s workplace is fairly unique within the variety of occupational challenges encountered by the American population. Modern foot soldiers commonly engage in intense, mentally and physically demanding 3- to 10-day missions, often in rugged terrain or complex urban settings. These warriors carry heavy loads (35–65 kg) and are often food and sleep restricted. Environmental conditions—ambient temperature, humidity, wind speed, solar load, and barometric pressure—can vary widely. Consider as recent examples of the operational environment the desert heat conditions of the Persian Gulf, the cold, wet weather in Bosnia, and the cold and high altitude challenges in the mountains of Afghanistan. WARFIGHTER PHYSIOLOGICAL STATUS MONITORING CONCEPT Why is physiological monitoring in the field needed? Wearable metabolic and physiological status monitoring can play important roles in: (a) sustaining physical and mental performance, (b) reducing the likelihood of nonbattle injuries, such as heat stroke, frostbite, and acute mountain sickness, and (c) improving casualty management in remote situations. Ambulatory warfighter physiological status monitoring (WPSM) technologies are being developed to provide useful performance and health status indicators for warfighters, medics, commanders, and logisticians. The goal is to

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance FIGURE D-40 Signaling pathways in adaptive processes. (Adams et al., 2002); (2) intermittent resistance overload training (RT), in which the target muscle is trained with a specified contraction regimen spanning 1 or 2 training sessions (Haddad and Adams, 2002); and (3) the model of spinal isolation (SI) in which the target muscles are rendered almost completely inactive by midthoracic/sacral spinal cord transectioning that is coupled to a dorsal rhizotomy procedure. This procedure eliminates all sensory and higher center input to the motor unit pool of the lower extremity muscles, while keeping the muscle-nerve connections intact (Huey et al., 2001). This latter model, in essence, provides a “ground zero” catabolic reference state to which the anabolic mechanical overload paradigms can be compared. METHODS AND MATERIALS All the animal projects involved adult female rats. Functional overload and resistance training procedures were as described in detail elsewhere (Adams et al., 2002; Baldwin and Haddad, 2001; Haddad and Adams, 2002). The spinal isolation model involved surgical procedures as described by (Huey et al.,

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance 2001). The biochemical/molecular analyses of marker protein phosphorylation, RNA concentration, and mRNA levels (via reverse transcriptase-polymerase chain reaction techniques) for specific genes were adapted from procedures described previously (Adams et al., 2002; Haddad and Adams, 2002). For comparative purposes, we report some initial findings (unpublished results) on humans that have undergone a combination of limb unloading plus resistance training in an attempt to ameliorate the atrophy that occurs in unloaded human skeletal muscle (Carrithers et al., In press). RESULTS AND DISCUSSION Early Events Leading to Net Protein Accumulation in Response to Mechanical Loading Previous studies show that infusing physiological levels of insulin-like growth factor-1 directly into the muscle can induce significant hypertrophy within several days (Adams and McCue, 1998). The question is whether a mechanical stimulus, in and of itself, can induce rapid increases in muscle-derived IGF-1 expression in muscle thereby stimulating compensatory growth. If such a response occurs, it would suggest the involvement of an autocrine/paracrine process in the anabolic cascade following mechanical loading. As shown in Figure D-41, there is a rapid increase in mRNA expression for both IGF-1, and a variant isoform of IGF-1 (Adams et al., 1999, 2002) called mechanical growth factor in response to functional overload. This response occurs early in the adaptive response, and it is seen in both FO and isometric RT paradigms (Adams et al., 2002; Haddad and Adams, 2002; Huey et al., 2001) suggesting that growth factors are likely playing a key role in inducing anabolic responses in muscle under conditions that produce high mechanical stress on the muscle. In addition to the response of growth factors, we also determined if there are rapid adaptive changes in the machinery that translates mature mRNA into protein (Figure D-39). Therefore, we examined levels of total RNA in skeletal muscle, since approximately 85 percent of the RNA pool exists as ribosomal RNA. Ribosomal RNA provides the scaffolding to which the mature mRNA is attached, providing the template for synthesizing the encoded protein. As shown in Figure D-42, there is a rapid increase in the concentration and content of total RNA in response to FO, suggesting that this is an important adaptive response to provide the machinery for producing more protein. Based on the above observations, it is apparent that there are early events occurring to enable the muscle to enter into an anabolic state. Therefore, it was of interest to determine if adaptive changes occur in the pathways that are considered to be rate limiting steps in protein synthesis (e.g., the initiation steps in protein translation). We examined two different but complementary markers of this process. The first involves the phosphorylation of p70S6 kinase (pS6K). When this kinase is phosphorylated, it increases phosphorylation/activity levels of other proteins involved in the translation of mRNAs encoding proteins

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance FIGURE D-41 Soleus insulin-like growth factor-1 (IGF-1) and mechanical growth factor (MGF) mRNA expression in response to overload.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance FIGURE D-42 Soleus total RNA concentration and content in response to overload.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance FIGURE D-43 Phosphorylation level of pS6K (A) and 4EBP-1 (B) in overloaded soleus.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance comprising the ribosomal machinery. As shown in Figure D-43A, there was a marked increase in the phosphorylation state of pS6K indicative that this pathway was activated. This observation is also consistent with the increase in total RNA presented in Figure D-42. Also, we examined the phosphorylation state of another marker of protein initiation (e.g., eukaryotic initiation factor 4E bind-ing protein, or 4EBP-1). This factor normally functions as a negative regulator of the formation of the 43 kD pre-initiation complex that is essential for protein translation. However, when 4EBP-1 undergoes increased phosphorylation, it dissociates from the protein, eIF4E, a key protein subunit that is necessary for the 43S complex to form so that the initiation process can occur. As presented in Figure D-43B, 4EBP-1 also undergoes increased phophorylation at the early stages of mechanical loading, which is also indicative that protein initiation processes are being activated. Thus, we have demonstrated that there are several molecular markers that can serve as early-event signaling molecules to predict that the muscle is entering a state of positive protein balance. All of the markers that have been identified above to predict that an anabolic state is occurring in response to functional overload show similar adaptive responses when the mechanical stimulus is intermittent, rather than continuous. For example, when isometric resistant training paradigms are imposed on the muscle, the muscle responds in a way similar to that seen in the functional overload paradigm (Haddad and Adams, 2002). Early Responses of Molecular Markers During Muscle Atrophy In response to anabolic stimuli, do inactivity paradigms that induce marked degrees of muscle atrophy cause the opposite responses of those markers presented above? The answer to this question appears to be negative, since some of the markers (IGF-1, p6SK, 4EBP-1) that are highly responsive to mechanical loading either are maintained at normal levels or show some level of increased expression or increased activity when the target muscles undergo rapid atrophy in response to SI (Haddad et al., submitted). Instead, there appears to be a different set of molecular markers that are highly sensitive to the unloading state. First, at the onset of muscle unloading, there is a decrease in the transcriptional activity of key genes that encode important structural/functional proteins that comprise the sarcomere machinery, that is, the system that produces contraction (e.g., myosin heavy chain and actin). This is depicted in Figure D-44, which shows that transcriptional activity of actin as well as the slow type I MHC gene (which predominates in load-sensitive muscle cells) are significantly reduced. Second, there is a reduction in total RNA and specific mRNA expression for both actin and total MHC. These responses are indicative of a reduction in both the substrate and the machinery necessary for carrying out translation of key proteins. Third, genes encoding enzymes that are involved in the process of protein ubiquitination are up-regulated (Figure D-45). These enzymes define the process whereby specific proteins become targeted for degradation by the

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance FIGURE D-44 Type I myocin heavy chain (MHC) (A) and actin (B) pre-mRNA expression in control and 8 days SI soleus muscle. Pre-mRNA is the nascent transcriptional product and changes in its expression represent changes in gene transcriptional activity. proteasome system, which is the major pathway for protein degradation in muscle cells. These collective responses provide a mechanism to rapidly reduce muscle mass by decreasing the ability of the muscle to accumulate protein while increasing the processes for decreasing protein pools, thereby creating a catabolic state and net protein loss. Since those processes that regulate factors such as IGF-1 and the phosphorylation of pS6K and 4EBP-1 do not appear to be down-regulated, it is apparent that the loss of muscle protein is not necessarily the result of a “shutting down” of those processes that cause muscle cell enlargement. Thus, one must focus on a different set of molecular markers to distinguish a net catabolic state from that which defines a net anabolic state in predicting a protein balance profile of the muscle under different physiological conditions. Do the Molecular Responses Seen in Animal Models Have Relevance to Adaptation in Human Muscle? While there is abundant evidence that there are viable human models (e.g., resistance training, bed rest, and the unique model of unilateral limb suspension [ULLS] that can mimic, to a certain extent, the gross responses seen in animal models of hypertrophy and of atrophy), questions arise as to whether acute

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance FIGURE D-45 Degradation marker mRNAs expression in soleus in response to SI. changes in the mechanical stress imposed on human skeletal muscle induce the same type of responses as reported herein for rodent muscle. In an attempt to address this issue, we performed preliminary analyses in conjunction with Dr. Per Tesch at the Karolinska Institute in Stockholm (Carrithers et al., In press) on selected molecular markers in biopsy samples obtained from three groups of subjects (n=8 each): (1) a group subjected to ULLS for 3 weeks (left limb unloaded, right limb ambulatory), (2) a group of subjects subjected to ULLS plus a resistance training paradigm (Carrithers et al., In press), and (3) a group

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance FIGURE D-46 Changes in total RNA concentration (A), total myocin heavy chain (MHC) (B) and actin (C) mRNA expression in human muscle when subjected to unilateral limb suspension (ULLS), resistance exercise (RE) or ULLS+RE.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance as seen for ULLS-trained group. The results indicated that the ULLS caused a of fully ambulatory subjects that received the same resistance training paradigm reduction in strength and muscle mass in the suspended limb. This response was attenuated in the ULLS plus resistance-trained group. The resistance training of the ambulatory subjects did not significantly enhance muscle mass or muscle strength beyond that which was observed for the ULLS plus trained group. Biopsies were obtained on each subject at the beginning and end of the experimental protocol. As presented in Figure D-46A, there was a deficit in the pre- and post-change in muscle total RNA concentration for the ULLS versus the two resistance-trained groups. Also there were net deficits in both the MHC and actin mRNA responses in the ULLS group versus that seen for the two resistance trained groups (Figures D-46B and D-46C). Thus, we propose that the same general adaptive processes that operate in the muscles of animal models also are seen in human subjects when they are exposed to perturbations that alter the homeostasis of the skeletal muscles under different loading states. SUMMARY AND CONCLUSION In this report we have demonstrated that skeletal muscle of both animal and human subjects possess a high level of plasticity (ability to change in response to altered environment) of gene expression in response to altered states of loading and/or mechanical stress. This phenomenon makes it possible to establish molecular marker profiles based on adaptive responses to acute disruptions in muscle homeostasis that predict impending alterations in catabolic and anabolic states that affect outcomes in the net protein balance in muscle cells. This information paves the way for the eventual development of technologies with the capability of monitoring the muscle’s molecular status for predicting outcomes to paradigms that may have either a positive or negative impact on the structure and function of the skeletal muscle system. This research was supported by a grant from the National Space Biomedical Research Institute (NCC9–78–70) and National Institutes of Health grants AR 30346 (KMB) and AR 45594 (GRA). REFERENCES Adams GR. 2002. Autocrine/paracrine IGF-1 and skeletal muscle adaptation. J Appl Physiol 93:1159–1167. Adams GR, McCue SA. 1998. Localized infusion of IGF-1 results in skeletal muscle hypertrophy in rats. J Appl Physiol 84:1716–1722. Adams GR, Haddad F, Baldwin KM. 1999. The time course of changes in markers of myogenesis in overloaded rat skeletal muscles. J Appl Physiol 87:1705–1712.

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Monitoring Metabolic Status: Predicting Decrements in Physiological and Cognitive Performance Adams GR, Caiozzo VJ, Haddad F, Baldwin KM. 2002. Cellular and molecular responses to increased skeletal muscle loading following irradiation. Am J Physiol Cell Physiol 283:C1182-C1195. Baldwin KM, Haddad F. 2001. The effects of different activity and inactivity paradigms on myosin heavy chain gene expression in striated muscle. J Appl Physiol 90:345–357. Booth FW, Baldwin KM. 1996. Muscle plasticity: Energy demand/supply processes. In: Rowell LB, Shepherd JT, eds. American Physiological Society Handbook of Physiology: Section 12. Exercise: Regulation and Integration of Multiple Systems. New York: Oxford University Press. Pp. 1075–1123. Carrithers JA, Tesch PA, Trieschmann J, Ekberg A, Trappe TA. In press. Skeletal muscle protein composition following 5 weeks of ULLS and resistance exercise countermeasures. J Grav Physiol. Haddad F, Adams GR. 2002. Acute cellular and molecular responses to resistance exercise. J Appl Physiol 93:394–403. Huey KA, Roy RR, Baldwin KM, Edgerton VR. 2001. Time dependent effects of inactivity on myosin heavy chain gene expression in antigravity skeletal muscles. Muscle and Nerve 24:517–527.