The Society for Integrative and Comparative Biology
Contrasting Tactics in Motor Control by Vertebrates and Arthropods1
1 Department of Biological Sciences, Louisiana State University, Baton Rouge Louisiana 70808
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Vertebrates and arthropods share the common problem of controlling a rigid, articulated skeleton using neurally-controlled, striated muscle. Since this condition has arisen independently in the two groups, there is no reason to assume, a priori, that the control mechanisms used by the two groups will be the same. Indeed, there appear to be fundamental differences in the tactics used by the two groups. Insects and crustaceans use small numbers of heterogeneous motoneurons, while vertebrates (mammals especially) use many, more homogeneous, motor axons. In particular, arthropods make extensive use of peripheral neuromodulation to alter the properties of both neuromuscular junctions and muscle fibers. There has been little consideration of the functional consequences of these differences. I suggest that, faced with a size constraint on the number of motor units available, arthropods use peripheral modulation of muscle properties to achieve the flexibility and dynamic range that vertebrates achieve through recruitment of motor units.
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INTRODUCTION |
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"All this may merely reflect the state of our ignorance about even so intensely studied a process as neuromuscular transmission. There may be unknown functional features of the structurally simple junctions that have secondarily evolved to give them equal capabilities: there are many paths to biological success." (Hoyle, 1983a
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HOW DOES AN ANIMAL POSITION ITS BODY IN SPACE? |
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Without getting bogged down in questions of intent or consciousness, we can assume that, at some level, the animal "wants" to be in a specific location or a specific posture at a specific point in time. This follows simply from the assumption that the animal is an autonomous agent with some control over these factors. How then, does it reach the desired state? Probably, if it is a metazoan, it exercises some arrangement of contractile apparatus—muscles—in a pattern of activity which is consistent with the desired goal. But how does a nervous system, the originator of behavior in any mechanistic world view, produce this pattern? Does it have preprogramed patterns built-in, the combined product of iterated random variation and natural selection? Does it produce random motion, and simply stop when it manages to achieve the desired result, perhaps storing this information for use the next time that particular movement is required? (Note the implicit requirement here for sensory feedback.) How much advance information does a nervous system have about the manner in which a given muscle will respond to a particular set of commands? How much (un)reliability is distributed through the system and what effects does this have on the manner in which the system functions? These are all questions of interest to students of motor control. Answering them, however, is proving to be a difficult matter. It is not yet clear how much of this difficulty is caused by the inherent complexity of the system(s) and how much by variation between the different systems that are commonly studied.
Vertebrates and arthropods share the common problem of controlling a rigid, articulated skeleton using neurally-controlled, striated muscle. Since this condition has arisen independently in the two groups (Brusca and Brusca, 1990), there is no reason to assume, a priori, that the control mechanism(s) used by the two groups will be the same. In fact, the data suggest that they are quite different. In the following discussion, it will be useful to distinguish between motor control "tactics"—the mechanisms an organism uses to control individual muscles, and motor control "strategies"—those overall aspects of motor behavior which the organism attempts to control. To tip my hand (and reveal my prejudices), I intend to argue that vertebrates and arthropods appear to use fundamentally different motor control tactics: insects and crustaceans use small numbers of heterogeneous motoneurons—a system with a strong labeled-line component. Vertebrates (mammals especially), on the other hand, use many, more homogeneous, motor axons—a system with a weak labeled-line component. Hoyle (1983a), Aidley (1989), and others have previously pointed out the basic differences between the two groups in the ways in which they produce gradation of muscle tension, but there has been little consideration of the functional consequences of, or the reasons behind, these differences.
The question of the motor control strategies employed by the two groups is a thorny one. Surveying the literature reveals that it is not at all clear which variable(s) the CNS monitors during the planning or execution of movement (see e.g., Heuer et al., 1985; Prochazka, 1989; Winters and Crago, 2000). Fortunately, my arguments are relatively independent of the motor control strategy used by a particular group.
Despite the apparent differences produced by an internal versus an external skeleton, the control problems faced by the two groups are formally the same. In each case, the control strategy must act to maintain, or to change in the desired fashion, the position of some part of the animal's body. For the present purpose, it doesn't matter what variable the CNS uses to monitor position: muscle length or tension, joint angle, skeletal strain, or even visual monitoring, would all suffice. What is required is some signal that the limb is, or is not, in the required position. A measure of the difference between the present and required positions—the "error signal" of an engineering feedback controller— is probably not essential, but certainly useful. The overall strategy must then make use of this information and, via the appropriate tactics, make the required adjustments.
Consider a limb which is free to rotate in a plane about a single joint. The limb is supplied with a single extensor muscle and a single flexor, all other joints are considered rigid, and the objective of the CNS is to maintain the position of the limb. The torque about the joint is therefore determined by the combination of the unbalanced force (if any) between the two muscles, and the load on the limb. In the static case, there are obviously an infinite number of combinations of input to the two muscles which can result in stability, the only physical constraint being that the limb's load be opposed by the unbalanced force between the two muscles. (Of course, there are physiological constraints which place upper bounds on various aspects of the system, such as muscle tension.) From the point of view of energy conservation, the optimal solution is the one which has zero input to one muscle, and input to its antagonist which is just sufficient to balance the load on the limb.
It is an open question in biology right now whether we should expect the system to operate in such an optimal matter. However, it's not an unreasonable working hypothesis, as deviations from it could suggest that we look for possible advantages from the non-energy conserving solution (see Gould and Lewontin, 1979; Parker and Maynard Smith, 1990, for opposing viewpoints on this problem). The truly optimal solution would be one in which no energy need be expended to maintain joint position. Indeed, such a situation may exist in some arthropods. Yox et al. (1982) found that the resting tension level in limb muscles in both a cockroach and a crab was sufficient to support the weight of the animals. A significant component of this resting tension is probably supplied by passive elastic elements of the limb: connective tissue, tendons, and perhaps even friction in the joints. It is unlikely, however, that this type of mechanism is available to animals above a certain size. The reason for this is the well-known problem of scaling: Properties of most of the elastic elements, and the muscle itself, will scale according to their cross-sectional area, but the load which must be borne will scale according to volume. Even granting that a given organism is small enough to make use of this type of passive support, there will still be many occasions in which it is necessary to change the degree of tension across the joint, even in a purely postural context. For instance, as a crab moves from water onto land, buoyancy no longer supports some of its weight, and the passive tension will no longer be sufficient to support its body.
Assuming then, that some active tension is required of the limb, what options are available?
(Lest I be accused of erecting a straw man in the following argument, I will concede here that several of the mechanisms ascribed to arthropod systems— polyneuronal innervation, graded contractions—are found, and may be common, in fish, amphibians, reptiles, and mammalian extra-ocular muscles [Hoyle, 1983a]. The question is not so much why arthropods use these mechanisms, as why mammals, predominately, do not.)
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GRADATION OF MUSCLE FORCE IN MAMMALS |
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Since the first half of the twentieth century, it has been recognized that mammalian muscles regulate the amount of force produced in skeletal muscles, at least partly, through the recruitment of motor units (see Stuart et al., [2001]
for an insightful historical perspective on this literature). In the modern sense, a "motor unit" is a single motoneuron and all of the muscle fibers which it innervates (Burke, 1981). Each muscle fiber is innervated by only one, excitatory, motoneuron, and almost all mammalian skeletal muscle fibers produce all-or-none action potentials. Depending on the size of the muscle, mammalian skeletal muscles are typically composed of several hundred motor units, with each motor unit possessing from tens to several thousands of muscle fibers (Table 1). As is generally the case in biology, the properties of the individual motor units form a continuum. At one end of this spectrum, motoneurons of "small" motor units innervate small numbers of muscle fibers, have low thresholds for activation, and evoke relatively slow, low force contractions which are fatigue-resistant. At the other end, motoneurons of "large" motor units innervate a great many muscle fibers, have high thresholds for activation, and evoke fast, strong contractions which fatigue rapidly. The range of twitch contraction amplitudes among motor units is on the order of 100 (i.e., the strongest unit produces a twitch approximately 100x the size of the smallest), while the range of twitch durations is on the order of 2–5 (Burke, 1981). By increasing the level of input to the total pool of motoneurons, not only are individual motor units driven at greater frequencies, which produces a slight increase in tension through tetany, but progressively larger motoneurons are recruited, which individually innervate greater numbers of muscle fibers, and hence produce greater amounts of tension. This is the "size principle" of Henneman (1957, 1980). Because of the differences in muscle fiber type associated with different motor units, it also ensures that the most readily fatigued muscle fibers are used only during maximal exertions.
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This orderly recruitment occurs fairly simply, albeit elegantly, because of the fact that the larger motoneurons have higher thresholds—larger somata represent larger electrical loads and require correspondingly more synaptic current to drive the membrane at the spike initiation zone to threshold (Jack et al., 1983
; Heckman and Binder, 1988). Developmentally, this situation probably arises through the fact that larger motoneurons can supply a greater amount of trophic factors, and thus support a greater number of muscle fibers (Henneman, 1980). This method of organization has the added advantage of substantially linearizing the mechanical output of the muscle when expressed as a function of the input to the motoneuron pool. Despite the fact that individual motor units are inherently non-linear in their input-output characteristics, when large numbers are grouped together and driven simultaneously, the resulting ensemble has both a wide linear dynamic range, and improved stability (Inbar and Ginat, 1983).
In addition to the differences in excitability amongst motoneurons, there are also differences in membrane properties that affect the repetitive firing properties of the cells. In particular, the relationship between synaptic drive and firing frequency, and the degree of spike frequency adaptation, not only have strong effects on the pattern of activation of the muscle, but differ between the motor units of relatively fast and slow muscles (Kernell et al., 1999). These properties are also subject to considerable modulation by a variety of interneuronal and neuromodulatory inputs (Kernell et al., 1999).
It is somewhat surprising that we still do not understand the relative contributions made by recruitment and frequency coding in the control of muscle force (Fuglevand et al., 1993). The major difficulty is the technical one of recording from enough motor units during the production of a natural contraction to separate the effects of recruitment from frequency coding. The experimental evidence suggests that frequency coding may be relatively more important in small muscles where fine regulation over muscle force is important, whereas recruitment may be more important in large power muscles (Kukulka and Clamann, 1981; De Luca et al., 1982). Simulation studies, however, showed that a predominately recruitment-based tactic reproduced experimental data much better than one with a substantial frequency coding component (Fuglevand et al., 1993).
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GRADATION OF MUSCLE FORCE IN ARTHROPODS |
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Contrast the situation in a typical arthropod muscle. Vertebrate-style recruitment at the motor unit level is a limited option, simply because there are very few motor units available. Most arthropod muscles are innervated by only one, two, or three, motoneurons (Hoyle, 1983a
). The number can range up to thirteen (Phillips, 1980), but is generally much smaller. A "typical" arthropod muscle will receive input from a "slow" motoneuron, which produces small, facilitating EPSPs in the muscle, a "fast" motoneuron, which produces large, depressing EPSPs, and an inhibitory motoneuron, which produces IPSPs (Hoyle, 1978; Rathmayer and Erxleben, 1983). Again, these examples should be seen as the endpoints of a continuum, with any of the intermediate possibilities also likely to be present. Individual muscle fibers may be innervated by one or both of the excitatory neurons, and generally receive inhibitory input as well. This combination of polyneuronal and inhibitory innervation makes the vertebrate concept of a motor unit difficult to apply to arthropods.
Arthropod muscle fibers are much more heterogeneous than those of mammals (Atwood, 1973; Hoyle, 1983a). The range of twitch forces is on the order of 10 to 100, while the range of twitch times is closer to 100 or 1,000. There is a similar broad range of excitability of muscle fibers: some are inexcitable, producing only passive membrane responses, some produce all-or-none action potentials, but the majority lie between these extremes, producing locally active, graded responses (Hoyle, 1983a). Most muscles appear to have fibers spanning this entire range. Graded membrane responses allow individual arthropod muscle fibers to produce contractions which are graded as well; increasing levels of depolarization result in contractions of increasing size. Graded contractions can also summate temporally, making contraction strength a function of stimulus frequency (Atwood, 1973). The combination of these individual properties with polyneuronal innervation means that the range of behavior for any individual muscle fiber in an arthropod is much greater than that of a mammalian muscle fiber. Furthermore, the contraction produced by the whole muscle is extremely sensitive to not only the frequency of motoneuronal input, but precisely which units are active.
While there have been several reports of a "size principle" operating in arthropods (e.g., Davis [1971]; Hinkle and Camhi [1972]; but see Wiens [1976] for a clear exception), there does not seem to be a clear physiological explanation of why this should be so. The explanation given above with regard to the vertebrate system clearly does not apply, because in arthropod motoneurons the soma is relatively electrically isolated from the signal processing regions in the neuropil. This difficulty is compounded by the fact that a given neuron may have multiple spike initiation zones (Heitler and Goodman, 1978) and so the physical location of synaptic input may determine its relative weighting. It is of course possible that some other neuronal property related to excitability is systematically correlated with axon diameter (the "size" measured in the aforementioned studies), but it is more likely that there is occasionally a fortuitous correlation between recruitment order and fibre diameter. Such a correlation could be consistent from preparation to preparation, given the invariant nature of many arthropod neurons. Furthermore, simple recruitment based on size in a system with few units produces very nonlinear input-output characteristics. Arthropod motor systems can smooth out some of this nonlinearity by their use of frequency coding to partially control tension production (Hoyle, 1983a). This method of control, however, leads to a new set of problems. Chief amongst them is the fact that it places high demands on the ability of the system to maintain constant levels of input to the muscle—if tension is coded in terms of frequency and frequency varies, so will the tension. This is likely to be a particular problem for arthropods, which, due to allometric considerations, are relatively ‘overpowered’ in terms of muscle mass, relative to vertebrates. Some of the variation will be smoothed out by the fact that the temporal coding characteristics of the muscle membrane and tension output are slow, and will filter out high frequency variation in the input. Arthropod motoneurons also have a wider dynamic firing range than vertebrate motoneurons (Table 1), due mainly to their lack of a large after-hyperpolarization (Burrows, 1996). Then there is the difficulty created by facilitation of the EPSPs of slow motoneurons: the size of the response can be a function of duration of input, as well as of action potential frequency (see also Morris and Hooper, 1997).
Many arthropod muscles also receive either direct or indirect neuromodulatory input. This may come in the form of specific projections to the muscle, as in the octopaminergic DUM neurons (Burrows, 1996) or peptide-containing motoneurons (O'Shea, 1985) of many insects, or as more widespread delivery of substances released locally or systemically into the circulation (Calabrese, 1989; Worden, 1998; Hooper et al., 1999). Sensitivity of skeletal muscles to neuromodulators appears to be ubiquitous in arthropods, with effects running the gamut from enhancement or attenuation of force magnitude to increases or decreases in contraction and relaxation times (Hoyle, 1983b). An indication of their probable importance is that the number of peptides with possible neuromodulatory actions in insects is over one hundred, representing about 20 families based on sequence homology (Burrows, 1996).
This of course begs the question of a precise meaning for the term ‘modulatory’ in the context of arthropod motor control. Hoyle (1985, p. 215) defined a neuromodulator as "a neuroactive substance which is released in the general vicinity of a group of synapses and affects synaptic transmission by pre- or postsynaptic action, or both." More recently though, Kupfermann (1991) has examined the functional roles of cotransmission without differentiating between transmitters and modulators. This is a reflection of the fact that as our knowledge of the roles played by neuroactIve substances has increased, so has our appreciation of their diversity. I have previously argued (Belanger and Orchard, 1988) that it is not profitable to arbitrarily pigeonhole transmitter substances (see Katz [1999] for a more thorough discussion). Rather they should be regarded as representing a continuous spectrum of properties, in which the categories of transmitter, modulator, and hormone, all shade into one another without clear distinctions between them. Indeed, Kupfermann (1991) has suggested, probably correctly, that most neurons are likely to release more than one physiologically-important transmitter, and O'Shea (1985) has argued that most arthropod motoneurons may be peptidergic, releasing cotransmitters along with classical transmitters.
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WHY ARE THERE DIFFERENCES BETWEEN ARTHROPODS AND MAMMALS? |
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Answering the question of why these differences exist may shed light on functional properties of motor systems. In evolutionary terms, the two groups are both very successful, so it is clear that each has found a workable solution to the problem of regulating muscle force. It might be argued that mammals are more capable of fine motor movements, and this could have driven the evolution of their control system. This argument sounds suspiciously chordate-o-centric, and it is difficult to imagine experimental evidence which might support it. Indeed, work on targeted limb movements in locusts (Matheson and Dürr, 2003
) suggests that insects can be capable of as much precision in motor control as mammals. Furthermore, it is generally considered in the mammalian motor control literature that frequency coding can produce finer control than can recruitment (Kukulka and Clamann, 1981; De Luca et al., 1982).
The commonly cited reason for the use of frequency coding in arthropods is a size constraint: these animals simply do not have the room for hundreds of motoneurons per muscle (Hoyle, 1983a; Biewener, 2003). This is an unsatisfying explanation, however. There is considerable overlap between the smaller mammals and the largest arthropods, particularly crustaceans. Certainly the earliest arthropods faced such a size constraint, but if more motoneurons per se were advantageous, one might predict an increase in the number of motoneurons with arthropod size, and this is not seen. More importantly, it seems that larger numbers of motoneurons per muscle is a condition that predates the vertebrates. Echinoderms are considered the invertebrate group most closely related to the vertebrates (Brusca and Brusca, 1990). The literature on echinoderm neurobiology is sparse, but one of the few studies available found that the pharyngeal retractor muscle of the holothurian Cucumaria has perhaps 700 motor units (Pople and Ewer, 1954). This is clearly an opportunity for natural selection to produce some mechanism for recruitment of these units. Unfortunately, there is no strong evidence for or against the use of a size principle in these organisms. This is obviously a group in major need of attention from comparative physiologists.
The complementary question to be asked is why muscle modulation seems so unimportant in skeletal muscles of vertebrates. There is certainly experimental evidence for modulation of muscle properties by epinephrine in slow twitch fibers of the cat soleus (Bowman and Zaimis, 1958), and calcitonin-gene related peptide has been shown to modulate neuromuscular transmission in the frog (Van Der Kloot et al., 1998). These observations, however, seem to be the "exceptions that prove the rule." Thirteen years ago, my observation that vertebrates didn't seem to use peripheral modulation in the control of skeletal muscle (Belanger, 1992) engendered the response "give the vertebrate motor control biologists time to catch up" (Ed Arbas, personal communication). An increasing emphasis on "interphyletic awareness" (Stuart, 1985), at the time raised the possibility that this apparent difference would soon be overturned by appropriate experiments. This has not transpired. Despite the large amounts of recent work on similarities in modulation of both motoneurons and premotor interneurons in vertebrates and invertebrates (reviewed in Worden [1998], Stein et al. [1997], and Kiehn et al. [1998]), similar data have not been forthcoming on peripheral modulation of skeletal muscle properties in vertebrates. My own lab has screened an array of peptides (proctolin, a number of RFamides) for effects on frog gastrocnemius muscle, and found none (J. H. Belanger, unpublished observations). The RFamides, at least, have neuromodulatory actions in a variety of vertebrate systems, so these seemed likely candidates on the basis of their activity in arthropod muscle. It is entirely possible, of course, that experimenters have simply not tried the right compound on the right muscle.
The dichotomy is emphasized by the fact that vertebrate cardiac and smooth muscles are both heavily modulated, as they are in arthropods (Hoyle, 1983a). By virtue of its anatomy and function, cardiac muscle cannot use recruitment or frequency coding to alter muscle contractions. Changes in muscle contractility, then, are driven by autonomic input (neuromodulation) or circulating hormones (Berne and Levy, 1998). The reasons for the widespread modulation of smooth muscle are less clear. It is tempting to consider the issue in light of the fact that vertebrate smooth muscles show a fiber heterogeneity comparable to that seen in arthropod skeletal muscles (Atwood, 1973; Hoyle, 1983a).
The parsimonious explanation for these findings seems to be that arthropods use peripheral modulation to achieve the flexibility and dynamic range for which vertebrates use motor unit recruitment. Instead of a general increase in the level of input to the motoneuron pool, arthropods appear to rely heavily on altering the input to specific units within the pool. Neurons which release cotransmitters can act as gain-increasing elements, effectively increasing the size of recruited units without activating more muscle fibers. What does this say about the role being played by cotransmitters? Historically, the most frequent explanation given for their presence is that cotransmitters increase the efficiency of the system, allowing a given amount of tension to be produced by far fewer action potentials (e.g., Bishop et al., 1987). However, energy efficiency need not be the major driving force behind the evolution of neural systems. In the one case with which I am familiar where a cost/benefit analysis was performed, a sensory system was shown to use the most reliable, but also the most metabolically-expensive, circuit design (van Hateren and Laughlin, 1990).
More recent studies have emphasized the flexibility that peripheral modulation gives to, particularly, invertebrate muscles (Hooper et al., 1999; Brezina et al., 2000). I would suggest that cotransmitters represent a solution to the size constraint on the motoneuron pool. Early arthropods must, by virtue of their smaller size, have had both fewer muscle fibers and fewer motoneurons. This placed severe restrictions on the number of motor units which they could possess, and prohibited the evolution of a mammalian-style control system. As an alternative, the evolution of cotransmitter-releasing neurons allowed for an alteration in the properties of all of the currently active motor units (e.g., increased or decreased amplitude, speed, or duration, of contraction).
To use the terminology of Brezina et al. (2000) the neuromuscular transform of vertebrate skeletal muscle appears to be relatively fixed. This should simplify the problems faced by the central circuitry in predicting muscle output to a given input (see Loeb, 1999), and may have been the selective pressure driving evolution of the recruitment tactic. In contrast, the neuromuscular transform in arthropods is much more variable, which would seem to place greater demands on the central circuitry controlling the muscles in arthropods. As a first approximation, it seems that a similar integration of information is taking place, in mammals, at the plasma membrane of premotor interneurons or motoneurons, and, in arthropods, at the calcium concentration in the muscle myoplasm.
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FINAL THOUGHTS |
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Do these differences imply that we can learn nothing about mammalian motor control from arthropod studies? Of course not. Without exception, every trick discovered in invertebrate nervous systems (action potentials based on ionic gradients, graded synaptic transmission, non-spiking neurons, neuromodulation, etc.) has later been found in mammalian systems. And the fact that the important computations are taking place at a technically accessible site means that arthropod motor control is likely to be the place where we first really understand the strategies underlying motor control.
The "simple system" concept, so popular with a generation of neuroethologists, is slowly fading. It's being replaced by a realization that many invertebrate systems, despite being seemingly comprised of fewer elements, aren't all that much simpler. To be sure, they're different. They accomplish the same tasks with a similar complement of elements. They use many of these elements in novel, frequently as-yet-to-be-determined ways. Invertebrate neurobiology is going to be a fun place to work for some time to come.
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ACKNOWLEDGMENTS |
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I thank the late Ed Arbas for his insightful comments on an embryonic version of this manuscript. We miss you, man.
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FOOTNOTES |
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1 From the Symposium Recent Developments in Neurobiology presented at the Annual Meeting of the Society for Integrative and Comparative Biology, 5–9 January 2004, at New Orleans, Louisiana.
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