Simple Peer Review Article on Circadian Rhythm and Somatosensory

New Results

The Modulation of Hurting by Cyclic and Sleep-Dependent Processes: A Review of the Experimental Evidence

, Jennifer A. Crodelle , Sofia H. Piltz , View ORCID Profile Natalia Toporikova , Paige Ferguson , Victoria Booth

doi: https://doi.org/10.1101/098269

Abstruse

This proceedings paper is the first in a serial of three papers developing mathematical models for the complex relationship betwixt hurting and the sleep-wake cycle. Hither, we briefly review what is known near the relationship between hurting and the sleep-wake bike in humans and laboratory rodents in an attempt to identify constraints for the models. While it is well accepted that sleep behavior is regulated by a daily (circadian) timekeeping organization and homeostatic sleep drive, the joint modulation of these 2 primary biological processes on pain sensitivity has not been considered. Under experimental conditions, pain sensitivity varies across the 24 h day, with highest sensitivity occurring during the evening in humans. Pain sensitivity is also modulated by sleep behavior, with hurting sensitivity increasing in response to the build up of homeostatic sleep pressure level following sleep impecuniousness or sleep disruption. To explore the interaction between these two biological processes using modeling, we get-go compare the magnitude of their effects across a variety of experimental pain studies in humans. To do this comparison, we normalize the results from experimental hurting studies relative to the range of physiologicallymeaningful stimulation levels. Post-obit this normalization, we find that the estimated bear on of the daily rhythm and of sleep deprivation on experimental pain measurements is surprisingly consistent across different pain modalities. We also review show documenting the impact of cyclic rhythms and slumber deprivation on the neural circuitry in the spinal string underlying hurting sensation. The label of sleep-dependent and cyclic influences on pain sensitivity in this review paper is used to develop and constrain the mathematical models introduced in the two companion manufactures.

i Introduction: A savage cycle

The feel of hurting has a complex relationship with the sleep-wake bicycle. Pain serves two important purposes: to motivate individuals to escape and avoid physical insult and to assist in healing by promoting the protection and immobilization of injured body parts. This first purpose necessitates rapid response and arousal, 2 processes that are suppressed past sleep, whereas the 2nd purpose is closely tied to the concept of rest. Thus pain makes u.s. tired (promotes the homeostatic bulldoze to sleep), and increased sensitivity to pain during the night is coordinated with our daily cyclic rhythm to promote immobilization and healing during the residuum catamenia [3]. All the same, the presence of pain is arousing and tin inhibit our ability to initiate and maintain slumber, especially the deeper recuperative stages of sleep [23]. When sleep is disrupted or limited, the perception of pain farther intensifies, healing is delayed, and pathological processes promoting the development of chronic pain can proceed unchecked [12]. Within clinical settings, this progression of events can create a barbarous bike of inadequate pain management [23], which is further complicated by similarly strong interdependencies between the sleep-wake bike and the effectiveness of well-nigh forms of analgesia [3, 12, 23].

The development and analysis of mathematical models of this vicious bike tin can pb to better understanding of the interactions betwixt sleep and pain, which could meliorate pain management. In this article, we review the experimental and clinical evidence documenting the modulation of pain by sleep and circadian processes in humans and animals and innovate a novel analysis of this data that is used to justify and constrain the mathematical models introduced in the companion articles.

2 What is pain?

"Hurting is an unpleasant sensory and emotional experience associated with bodily or potential tissue damage, or described in terms of such damage" according to the International Clan for the Study of Pain [26]. Pain can be caused by different types of actual or potential tissue impairment, including adverse temperature weather (heat, common cold), intense mechanical stimulation or pressure, electric shock, constricted vasculature, or chemical irritation, as well as processes generated within the body, such every bit inflammation and pathological nerve damage (neuropathy). Pain can exist derived experimentally or from natural conditions, and can occur on a variety of fourth dimension scales. Experimental studies of "astute" pain sensitivity typically induce brief ("phasic"), localized, superficial pain to peripheral tissues. Such cursory stimulation actually consists of two sensations: a fast, abrupt pain and a slower, dull pain. Occasionally, experimental studies will induce longer duration ("tonic") acute pain that can last for hours [24]. Within clinical settings, chronic pain atmospheric condition can last for months or years.

As at that place are different types of pain that can be felt, there are unlike ways in which the body receives and processes pain signals. Sensory neurons (afferent neurons) in the peripheral nervous system sense stimuli and send that information to the spinal cord for processing. These neurons and their nerve fibers are specialized for detecting innocuous or noxious stimuli. Not-painful bear upon sensations are transmitted by Aβ afferent fibers while there are two major classes of nociceptive (pain-receptive) afferent fibers: Aδ and C. Medium diameter Aδ fibers mediate localized, precipitous, fast hurting sensations, while small diameter C fibers mediate the more diffuse and duller deadening hurting sensations [11]. The "fast hurting" Aδ fibers are wrapped in a fat sheath called myelin that allows for rapid transmission of signals, at speeds of 4 to thirty yard/sec. This is also true for the Aβ fibers. In dissimilarity, the "slow pain" C fibers are not myelinated and, due to their small diameter, transmit signals at speeds of less than two thousand/sec [24].

Different types of nerve fibers report to different areas in the spinal string. In general, sensory neurons have their cell bodies in the dorsal root ganglia, a cluster of nerve cell bodies located in the spinal cord. Primary afferent fibers morphologically differ from other nerve fibers in that their axons and dendrites, usually responsible for sending and receiving signals, respectively, have equivalent biochemical makeup and thus these neurons tin can send and receive signals through both their axons and dendrites [1]. Signals in these afferent fibers are transmitted to the dorsal horn of the spinal cord, an area that is responsible for receiving information from the sensory neurons, processing it, and sending signals up to the encephalon. The dorsal horn contains many populations of neurons, including excitatory and inhibitory interneurons. One such population of neurons in the dorsal horn, called the Wide Dynamic Range (WDR) neurons, receive direct inputs from the touch on and nociceptive afferent fibers likewise as inputs from interneuron populations, and found the primary output from the dorsal horn to the brain. Equally such, pain intensity is correlated with the firing rate and the duration of firing of the WDR neurons.

Since pain is both an unpleasant sensory and emotional experience, pain-related input from the spinal string engages multiple neural circuits in the brain, including the brainstem, thalamus, and cortex. These circuits involve a wide range of neurotransmitter systems, including the well-studied opioid system. Many of these college-level cognitive and emotional responses to pain exert their influence over pain perception via descending projections to the dorsal horn of the spinal cord. This "top-down" feedback on sensory processing can act to either inhibit or facilitate pain sensation, substantially providing a "gate" for the transmission of nociceptive information to the brain [25]. Thus, there is a tradition of modeling pain processing by focusing exclusively on spinal cord circuitry.

iii The relationship between the sleep wheel and pain sensitivity in humans

The daily timing of slumber is widely accepted as an interaction between two contained processes: a homeostatic drive to sleep, which builds up over the course of wakefulness in a saturating mode and dissipates during slumber, and a cyclic timing organisation, which rhythmically influences the levels of sleep drive required to initiate and maintain sleep [8]. When exploring the literature documenting the relationship betwixt sleep and hurting, we institute that the influences of both circadian rhythms and homeostatic slumber drive were rarely measured inside the aforementioned experiment, despite ample evidence that both processes modulate pain sensitivity [three, 12, 23]. Instead, experimental studies tended to fall into two wide categories. In one variety of experiment, pain perception was measured across the solar day (24 hours) in subjects maintaining their normal sleep schedule. Therefore, the information in these experiments should stand for a combination of the influences of time-of-solar day and a normal small-scale sixteen-hr build-upwardly of homeostatic sleep drive during waking and viii hr dissipation of homeostatic sleep drive during sleep. In the other variety of experiment, subjects were slumber deprived for ane-3 nights or had their sleep restricted to less than a typical eight hours, and hurting perception was recorded at various times. In these experiments, there should be a large build upwardly of homeostatic sleep drive, the furnishings of which may be more or less obvious at unlike times of day due to circadian modulation. Nosotros review these two forms of information below and innovate a novel analysis of the data that allows a comparing of results from these two categories of experiments and from studies using different pain modalities. For the sake of simplicity, we focus primarily on data derived from studies using pain modalities of experimentally-induced cursory (acute/phasic), superficial pain to peripheral tissues.

3.one In that location is a daily rhythm in experimental hurting sensitivity in humans

Hurting sensitivity follows a daily cycle in many clinical conditions [3], just information technology is currently unclear how much of that rhythmicity is derived from daily fluctuation in the underlying causes driving the pain (for example, nocturnal release of oxytocin induces contractions during labor) versus rhythmicity in the neural processing of pain. Inside the experimental pain literature, rhythmic influences on pain sensation occur regardless of whether hurting responses are measured subjectively or considerately [vii, 2, 9, 36], suggesting that the rhythmic modulation of pain responses occurs at a basic physiological level. This rhythmic modulation of hurting sensitivity increases with pain intensity [xv,20,9], so that the more intense the pain is overall, the greater the modify in the person's sensitivity to the pain across the twenty-four hour period. Rhythmic influences on pain sensitivity are detectable in experiments involving a variety of different kinds of painful stimuli, including cold, heat, current, pressure, and ischemia (Table ane, Table 2). These stimuli are found to be virtually painful during hours of the day when experimental subjects are likely to be tired – late afternoon, evening, and night (Table i).

Table 1:

Studies measuring daily rhythms in experimental human being hurting sensitivity. Note that these studies focus on cursory (acute, phasic) superficial pain in peripheral tissues. Clock hours are in armed services fourth dimension (0:00-24:00). Abbreviations: DT: Detection threshold, PT: Pain threshold, PRT: Pair response threshold, PS: Hurting sensitivity (intensity ratings), PTT: Pain tolerance threshold, IT: Intervention threshold, NFR: Nociceptive flexion reflex, EP: Somatosensory evoked potential (EEG).

Table ii:

Studies measuring daily rhythms in experimental human pain sensitivity that have been reviewed in previous publications [15, three] but that nosotros were either personally unable to review or found to be unreliable.

To better narrate this rhythm, we synthetic a prototypical "daily pain sensitivity" function past drawing information from four loftier-quality experiments that measured pain sensitivity at multiple time points around the 24-hr twenty-four hours using diverse testing procedures:

1. The threshold for nociceptive pain reflex in response to electrical electric current (n=5, [ii]), an objective mensurate of pain sensitivity. In this study, measurements were taken from the same subjects every 4 hours inside a sequent 24 hour laboratory written report (beginning at xiii:00). The study states that subjects lived in "unproblematic weather condition of social synchronization (08:00-23:00)" and remained in bed during night measurements.

2. The threshold for tooth hurting in response to cold (n=79, [31]), and the threshold for molar hurting in response to electrical stimulation (n=56, [31]). In this big study, measurements were taken from the same subjects every 3 hrs across a 24 hr day. From the methods, it is unclear whether these measurements were completed consecutively, but in a follow-upward report in the same paper using a smaller sample size they replicate their results using measurements taken at 24+ 60 minutes intervals. During the tests, the subjects maintained their normal living cycles.

3. The threshold for forearm pain in response to heat (n=39, [32]). In this big study, measurements were taken from the same subjects at 4 time points beyond a 24 60 minutes day (8:00, 13:00, 18:00, 23:00). In women, this procedure was repeated at iii different points beyond their menstrual wheel (days 7, 15, and 23). During the experiment, subjects maintained their normal daily routine (sleeping hours 24:00-seven:00).

For each study, we but had access to the summary data presented in the figures. Using these data, nosotros standardized the pain measurements by converting them to percent of hateful (or the mesor of the depicted rhythm). For ease of use, we inverted measures of pain threshold to pain sensitivity so that low pain threshold corresponded to high pain sensitivity. Thus, in our function, high measurement values are associated with greater pain. Fourth dimension was standardized in relation to either scheduled or estimated morn wake fourth dimension in order to organize the data in a manner more akin to the "zeitgeber fourth dimension" used in slumber and circadian literature.

Post-obit these transformations, the information collectively formed a tight curve that resembled a sinusoid. To produce a smoothed version of the bend for later use equally our model input, we used the loess function in R 3.2.1 (loess{stats}), R Cadre Team 2014), which is a form of local polynomial regression that resembles a "vertical sliding window that moves beyond the horizontal scale centrality of the scatterplot" [18].The benefit of using loess() is that it does not presume a functional form for the relationship betwixt 10 and Y and therefore, to some degree, "allows the information to speak for themselves"[xviii]. A traditional equation with coefficients is not produced. In that location is a parameter (blastoff, sometimes called bridge) that controls the degree of smoothing via the width of the sliding window. The larger the alpha value, the smoother the bend. If blastoff is too small, overfitting is possible.We used the default (blastoff=0.75). In that location is besides a parameter (lambda) that specifies the caste of the polynomial. We used lambda = 2, meaning that quadratic equations were used, which tin can ameliorate capture "peaks" and "valleys" (local minima/maxima) in the data [18]. Using this unbiased approach, we still found that the output curve strongly resembled a simple sinusoid (R2loess=0.64, Effigy one).

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Fig. 1:

Prototypical human "daily hurting sensitivity" curve constructed from summarized data from 4 high-quality experimental studies of pain responses [2,31, 32]. Time was standardized in relation to either scheduled or estimated morning wake fourth dimension (time of wake = 0). Each bespeak represents the mean value for that time point as derived from the published figures in each study, converted to a percentage of the report'due south overall mean (or the mesor of the depicted rhythm). For ease of employ, we inverted measures of hurting threshold, so that low hurting thresholds are presented in the graph as high "pain sensitivity". The smoothed curve was produced using an unbiased loess{stat} regression in R.

We hypothesize that this best-fit bend represents an average daily rhythm in hurting sensitivity for humans and that the rhythm is affected by both homeostatic sleep drive and a circadian rhythm in pain sensitivity. The curve has a sharp peak in pain sensitivity occurring shut to sleep onset (eighteen hours following wake, or approximately 1am) and so decreases during the night. This is consistent with an event of homeostatic sleep drive on hurting sensitivity, and fits previous demonstrations that mental fatigue tin decrease pain threshold (i.e., increase hurting sensitivity) past 8 – x% [7]. The curve besides has a distinct trough in hurting sensitivity in the afternoon (following nine hours of wake, or approximately 4pm). This pattern does not fit what would be expected due to an upshot of homeostatic slumber drive and instead suggests the influence of a circadian rhythm.

3.ii Homeostatic sleep drive increases pain sensitivity in humans

Within the clinical literature, there are at least 14 studies demonstrating that the experience and intensity of hurting correlate with sleep duration or quality [12]. However, the causal nature of this relationship is best evaluated within controlled experiments, and these experimental results have been broad-ranging. Within human experiments, sleep deprivation or restriction produced no effect on experimental hurting [x, 39], pocket-sized 2 – 10% increases in hurting [29, 21, 37], or much larger eighteen – 118% increases in pain [43, 34, 38]. The multifariousness of these effects may exist due to the diversity of slumber protocols used (every bit suggested by [38]) or the cognitive and emotional context accompanying each experiment (due east.g., [39]). Even inside a item protocol, the intensity or quality of experimental pain may make up one's mind the impact of slumber deprivation, with i study observing increases in experimental pain that ranged from 6 – 118% depending on the method used to inflict and measure hurting [38] (Tabular array 3).

Table 3:

The estimated bear on of sleep deprivation on experimental pain tin vary greatly across experimental pain measures within the same study [38]. In this study, the responses of xiv healthy subjects to v different measurements of evoked pain were assessed subsequently a night of undisturbed sleep (command) and afterwards a night of total sleep deprivation (Total Sleep Dep). The alter in response is measured as a percentage of the command response.

All the same, we noted that much of the variability in hurting sensitivity across studies could be deemed for past the method of normalization used to compare information. For example, when using percentage alter every bit our standardized unit, we can artificially encounter a larger issue of sleep deprivation on common cold pain threshold if the original units are in degrees Celsius instead of in degrees Fahrenheit (Tabular array 4).

Table 4:

An example of why information technology is hard to compare magnitude of consequence beyond dissimilar units for measuring pain [38]. Changes in the threshold temperature for evoked pain by cold stimulus to the paw was measured after a night of undisturbed sleep (control) and after a night of total sleep deprivation (Full Sleep Dep). When measured as a percentage of the control response, the same change in response is computed every bit a larger percentage change when degrees Celsius are used compared to degrees Farenheit.

Similarly, across studies, the effect of sleep deprivation in pct alter units was consistently larger on common cold pain threshold than on heat pain threshold, merely because the temperature values for common cold pain threshold under the control condition were lower, making the denominator in the percentage change equation (i.e. (change from control threshold temperature) / (control threshold temperature)) smaller. Besides, percentage change increases in subjective rating scales were well-nigh e'er exaggerated, since ratings from control subjects were often extremely low, making the denominator in the per centum alter equation diminutive.

The typical rationale for using percentage change units for comparing data of different units is the idea that the biological impact of changes in the unit depends on its initial values. For instance, if a disease condition increases the number of mRNA transcripts for a particular gene from 100 to 110, this is likely to matter more biologically than an increment from g to 1010. It is non articulate that this logic holds true for the units used in hurting research (as indicated by the particularly irrational examples above). What is likely to matter more than biologically is the percentage of the range of stimulation possible before tissue is genuinely damaged. For example, in a heat threshold experiment, you would expect that pain sensation might reflect a range of temperatures between physiological levels (37 degrees C) and a level of oestrus that rapidly causes damage (threescore degrees C) [51]. In that case, a drop in hurting threshold of 3 degrees would embrace 13% of the full range of hurting sensation possible ((three degrees)/(sixty-37 degrees C)=0.13). This is a much more interpretable value than just saying that a drib in pain threshold from 49 degrees in controls to 46 degrees following sleep impecuniousness is a vi% change from the original pain threshold ((49-46 degrees)/49 degrees=0.061).

Using this logic, we found that the data documenting the touch of sleep impecuniousness on experimental hurting was much more consequent than information technology initially appeared. For the different experimental pain measures used in the study of [38], we determined minimum and maximum response values corresponding to the absence of stimulation and the value when tissue impairment would occur, respectively. The full range of response values was computed as the difference between the maximum and minimum response values.We then computed the observed deviation in response values between the command and full sleep deprivation weather condition, equally listed in Tabular array 3, as a percent of the total range of stimulation. Computed in this way, all experimental pain measures signal that sleep impecuniousness increases pain by ∼ 5 – 12% of the total range of painful stimulation (Tabular array 5).

Table 5:

Within a report, the estimated affect of slumber impecuniousness on experimental pain is quite consistent if the data are normalized every bit a percentage of the full estimated range for painful awareness in that modality [38]. The observed difference in response values between the command and total sleep deprivation conditions, every bit listed in Table 3, was computed every bit a percentage of the total range of stimulation response values.

To apply this logic to multiple studies on the effects of sleep deprivation and cyclic modulation of pain, we estimated minimum and maximum stimulation levels necessary to produce a total range of pain responses to a number of unlike experimental pain modalities, as well as typical hurting thresholds (Table 6). From these measurements, we computed the range of physiologically-meaningful stimulation as the difference between the maximum and minimum values, and the range of painful stimulation as the difference betwixt the maximum and pain threshold values. Nosotros then normalized the results across studies by converting changes in hurting response values to percentage changes within the full range of physiologically-meaningful stimulation or percentage changes within the range of painful stimulation. Following this normalization, the magnitudes of the effects of sleep deprivation and daily rhythms were less variable across studies. This implied that normalizing data based on per centum changes within the range of painful stimulation was superior to using a uncomplicated percent of the mean. (However, delight annotation that the information necessary to perform this improved normalization were not available for all studies - for example, several studies used to construct Figure i). Using this improved normalization method, we likewise plant that the magnitude of the effects of slumber deprivation and daily rhythms were roughly equivalent (Table 7). Specifically, we found that, on average, evoked hurting responses, measured relative to the range of painful stimulation, varied past approximately 14% due to daily rhythms and past approximately 13% in response to sleep deprivation.

Table 6:

Determining the range of painful stimulation possible within human experimental pain studies before the occurrence of tissue damage, as well as the typical threshold for hurting sensation. Sources for computations: a: http://www.ehs.neu.edu/laboratory_safety/fact_sheets/-cryogenic_liquids; b: [51]; c: [41]; d: Maximum for Instrument, the typical mA eliciting nociceptive pain reflex by someone who is under full general anesthesia for surgery [46]; e: Pressure of virtually 100 lb/in² (7 kg/cm²) is required to penetrate the epidermis (1 kg/cm² = 98.07 kPA) [4]; f: Maximum for Instrument [38]; yard: Maximum for Test, rated "Very potent pain" by all participants [15]; h: [38]; i: [43];j: [2];k: [xx].

Table 7:

Experimental results illustrating the furnishings of daily rhythm and sleep impecuniousness on pain thresholds in humans for multiple pain modalities. These results are normalized with respect to the range of physiologically-meaningful or painful stimulation computed in Tabular array half dozen. Across studies, the estimated touch of the daily rhythm and sleep deprivation on experimental pain is quite consistent if the data are normalized as a percentage of either the estimated range for physiologicallymeaningful sensation or painful sensation in that modality.

iii.3 A cross-species comparison: circadian rhythms and homeostatic sleep drive influence pain sensitivity in laboratory rodents

The vast majority of what is known regarding the influence of circadian rhythms and slumber-wake cycles on pain processing circuitry comes from studies on laboratory rodents. In order to properly compare these data with that of humans, it is important to understand that the circadian and sleep systems of laboratory rodents differ from humans in several cardinal ways. To begin with, laboratory mice and rats are nocturnal, which means that nigh of their wakefulness occurs at night and about of their sleep occurs during the day. They are also polyphasic sleepers, which means that they sleep in short, multi-minute bouts, interrupted by waking, and rarely exhibit consolidated wakefulness that extends across several hours. Despite their unconsolidated wake and sleep, they even so more often than not showroom a progressive build-upwards of homeostatic sleep drive beyond the nighttime active flow, and dissipation during the daytime residual period [44].

Like to humans, at that place is clear evidence that pain awareness in laboratory rodents is modulated by both time-of-day [28, half-dozen, 35, 52, 13, 33, 22, 42, nineteen] and sleep impecuniousness [17, 49, 48, 47, 45, 27]. Unlike humans, we can easily place laboratory rodents into constant environmental atmospheric condition and thus exist able to demonstrate with certainty that the influence of time-of-day on pain sensation is due to an endogenous cyclic clock instead of elementary passive responses to a rhythmic environment [33]. However, the timing of the daily superlative in pain sensitivity varies in different strains of inbred rodents past equally much as 12 hours [6], making it sometimes difficult to draw generalized conclusions virtually the influence of cyclic rhythms on pain sensitivity. Another notable departure between humans and rodents is that the elapsing of slumber deprivation necessary to detect an consequence on pain responses is much smaller, since rodents typically do non showroom consolidated wakefulness on the scale of multiple hours.

four Cyclic rhythms and homeostatic sleep drive modulate hurting neural circuitry

The neural location for the circadian modulation of hurting begins at the most fundamental level of the pain circuitry: sensory afferent input into the spinal cord. Within the dorsal root ganglia, which are the neural structures that contain the cell bodies for the sensory afferent neurons, in that location is articulate evidence for endogenous circadian rhythmicity. The dorsal root ganglia rhythmically express a full complement of clock genes, which are the genes responsible for generating daily rhythmicity throughout the body [52]. The dorsal root ganglia also demonstrate rhythmic expression of genes necessary for synaptic transmission, including voltage-gated calcium channel subunits [22] and NMDA glutamate receptor subunits [52]. However, since the dorsal root ganglia contain the jail cell bodies for a wide multifariousness of afferent neurons, it could be argued that measuring rhythmicity in the dorsal root ganglia as a whole does not necessarily bespeak that the nociceptors responsible for pain transmission are rhythmic. Ii pieces of show suggest otherwise. First, an estimated 82% of afferents are nociceptors [xi], thus it is likely that the majority of mRNA nerveless from the dorsal root ganglia in these experiments represents mRNA from pain transmitting cells. Second, researchers have discovered rhythmic expression of the mRNA and protein for Substance P, a neurotransmitter of import for pain-signaling from C fibers [52]. Therefore, it is likely that the nociceptive afferent neurons themselves are rhythmic. That said, the jail cell bodies for the not-nociceptive fibers in the dorsal root ganglia probably also contain endogenous rhythmicity. In homo studies the influence of fourth dimension-of-day on non-baneful mechanical sensitivity, which is conveyed by Aβ fibers, differs from that of painful stimuli, which is conveyed by Aδ and C fibers, with the rhythm in mechanical sensitivity peaking in the late afternoon (xv:00-18:00) and the rhythm in pain sensitivity peaking in the center of the dark (between midnight and 03:00 [31]).

The height-down inhibition of pain processing in the dorsal horn also exhibits a daily rhythm. In humans, placebos best alleviate pain in the early on afternoon [31]. In laboratory rodents, there is a daily rhythm in the force of stress-induced analgesia and endogenous opioid-release, and this rhythm persists under constant environmental conditions [33, fifty]. Opioid receptors in the brainstem, which are important for analgesia, showroom a strong daily rhythm [42]. However, it is possible that these daily rhythms in the top-downwards inhibition of pain practice not correspond direct influences of the circadian clock, but instead are a response to the rhythmic build-up and dissipation of homeostatic sleep drive across the day. In support of this theory, there is stiff evidence demonstrating that sleep deprivation influences the highest levels of pain processing. Sleep impecuniousness is already well known to disproportionately bear upon the free energy and resource-needy cortex. Therefore, it is unsurprising that slumber deprivation in humans eliminates distraction-based analgesia [43] and decreases cardinal hurting modulation [16, 5]. Fifty-fifty tiptop-down pain inhibition originating from lower levels of the central nervous organization is crippled by sleep impecuniousness, including diffuse noxious inhibitory controls in humans [39, 16] and stress-induced hyperalgesia in rodents [45]. Pharmacological manipulations that mimic top-down pain inhibition, such equally morphine, are ineffective following severe slumber deprivation [45, 27].

Slumber impecuniousness can as well alter more cardinal levels of pain processing in the spinal string, including neurotransmission via glutamate (mGLUR5, NMDA), GABA, and NOS, as well as the passive spread of electrical potential via astrocytic gap junctions and the product of reactive oxygen species [49, 48, 47]. Despite these effects, under conditions in which the acme-down inhibition of hurting is minimal, in that location seems to exist less evidence that homeostatic sleep drive influences pain processing. For example, there is some evidence that sleep impecuniousness may not bear on the processing of fast pain (Aδ input). Cortical responses to fast pain actually diminish post-obit sleep restriction [43], and, for faster reflexive behaviors (such as tail withdrawal latency), sleep impecuniousness effects are sometimes non constitute [49]. Besides, homeostatic sleep drive does non seem to contribute much to the typical daily rhythm in acute pain sensitivity in rodents. For instance, experiments performed in mice with a disquisitional mutation in the essential clock gene Per2 show a complete emptying of daily rhythms in acute pain nether typical housing weather condition [30, 52], despite maintaining elevated nocturnal activeness in response to the laboratory lightdark cycle [40], and thus presumably also retaining a daily rhythm in the build-upwardly and dissipation of homeostatic sleep drive.

In the case of more severe or chronic pain, the influences of homeostatic sleep bulldoze on top-downward inhibition may be more relevant. For example, Per2 mutant mice continued to exhibit daily rhythms in inflammatory pain in a manner that matched a predicted build-up and dissipation of homeostatic sleep drive in response to nocturnal behavioral patterns [52]. Both inflammatory and neuropathic weather are also characterized by a viii– 12 hour shift in the phasing of daily rhythms in pain sensitivity [52, 42, 22, 14], which may correspond an increased influence of homeostatic drive on the top-down inhibition of pain when pain is extended over a longer time scale.

five Discussion

In summary, in that location is a substantial body of work documenting the effects of both daily rhythms and sleep impecuniousness on acute pain sensitivity under experimental conditions in humans and rodents. These results appear divergent at offset glance, but upon closer inspection seem to mostly agree that peak acute/phasic pain sensitivity in humans occurs during the evening. Our data analysis reveals that the influence of both daily rhythms in pain sensitivity and 24 hours of slumber deprivation typically modify pain sensitivity under experimental conditions by 13 – 14% of the full range of painful stimulation. Other studies suggest that the influence of daily rhythms and sleep deprivation may increase with pain intensity. Where these effects originate physiologically is a more recent source of discussion, but it is likely that they represent the intersecting influence of homeostatic sleep drive and the circadian timekeeping system on the central nervous system. At that place is clear evidence for circadian effects at the level of the spinal cord and there are equally articulate furnishings for sleepdependent modulation of the summit-down inhibition of hurting, although it is possible that both processes influence all levels of the central nervous system. Finally, the effect of circadian rhythms and homeostatic sleep force per unit area on pain sensitivity may differ depending on the type of pain measured, with data clearly indicating that slower C cobweb input and tonic pain sensitivity are influenced by both endogenous circadian rhythms and homeostatic sleep bulldoze, whereas fast Aδ input and faster reflexive hurting measures may be less susceptible.

In the companion manufactures, we introduce two mathematical models to investigate the articulation modulation of the circadian rhythm and homeostatic slumber bulldoze on pain. These models address pain at two different levels: at the organismal level every bit the experience of pain sensitivity and at the neural level as the firing rates of hurting processing circuits in the spinal string.

The organismal-level model addresses a clear gap in our current cognition: the lack of experimental information measuring the dissociated influence of circadian rhythms and homeostatic slumber drive on pain sensitivity in humans, as would be obtained from a forced desynchrony or constant routine protocol. To address this gap, we adjust the ceremonial of a archetype mathematical model for the regulation of sleep behavior past the circadian rhythm and homeostatic slumber drive, called the Two Procedure model [8], to simulate the interaction of these 2 processes on pain sensitivity. The data assay presented hither is used to define a generic "daily pain sensitivity" part (Figure ane), which we decompose into two independent circadian and homeostatic components (Process C and Process Due south) using a range of potential relative magnitudes constrained to produce results resembling the normalized information in Tabular array 7. Then nosotros utilize this model to simulate the resultant changes in the daily pain sensitivity rhythm in response to a variety of altered sleep schedules: sleep deprivation, slumber restriction, and shift work.

The neural-level model is based on the circuitry in the dorsal horn of the spinal string consisting of synaptically coupled populations of excitatory and inhibitory interneurons that procedure input signals in the principal afferent fibers and influence the output signal of the WDR neurons. The temporal contour of inputs on the dissimilar types of afferent fibers and excitability properties of the included neuronal populations are constrained by experimental results. We validate the model by replicating experimentally observed phenomena of A cobweb inhibition of pain and wind-upward. We then use the model to investigate mechanisms for the observed stage shift in circadian rhythmicity of pain that occurs with neuropathic pain conditions.

In determination, while experimental testify indicates both circadian and sleepdependent effects on daily pain rhythms, dissecting their interactions that contribute to changes in pain rhythms nether varying normal or pathological conditions is difficult experimentally. The mathematical models developed in this series of papers provide frameworks to incorporate the known experimental results of these effects and to investigate their potential interactions nether different conditions. By addressing both the behavioral and cellular levels, these models are useful tools to identify how the primary biological processes of sleep, circadian rhythmicity and pain interact.

6 Acknowledgements

This piece of work was conducted as a part of A Inquiry Collaboration Workshop for Women in Mathematical Biology at the National Plant for Mathematical and Biological Synthesis, sponsored by the National Science Foundation through NSF Award DBI-1300426, with boosted support from The University of Tennessee, Knoxville. This work was additionally partially supported by the following sources: NSF Award DMS-1412119 (VB), NSF RTG grant DMS-1344962 (JC) and the Pritzker Neuropsychiatric Disorders Research Consortium (MH). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and practise not necessarily reflect the views of the National Scientific discipline Foundation.

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Source: https://www.biorxiv.org/content/10.1101/098269v1.full

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