Addressing Pain before it becomes chronic

It is estimated that 50-60% of patients do not receive adequate pain control after surgical or other invasive medical procedures.1,2 Not surprisingly when this pain is not addressed properly there are significant increases in morbidity as well as increases in short-term and long-term medical costs.1,3-9 Some estimate that approximately 116 million individuals suffer from either acute or chronic pain that is not managed properly.10 While there are various, somewhat arbitrary, time periods assigned to the development of chronic pain the general definition is pain that persists beyond the expected period of healing for a given injury. There are two major types of chronic pain: nociceptive, which results due to nocieptor activation (pain receptors) and neuropathic, which results due to damage to the spinal cord or periphery sensory neurons.

One of the initial problems with addressing pain management is the method that is used to evaluate the intensity of pain. While numerous criticisms have been levied against the standard pain numerical reporting system because of its subjective non-uniform nature (a 5 out of 10 for pain for person A may be much different than a 5 out of 10 for person B), little attention is paid to tracking changes in pain progression. Typically post-operative pain is characterized by one or two visits by a nurse with assignment of some pain medication. Basically the pain is viewed as a somewhat static condition that will persist at the recorded level for the duration of the day if not treated by medication. Therefore, one way of better managing pain requires more attentive inquiry regarding how pain is progressing in a patient over the course of a day. Instead of once or twice, inquiries should be made every hour during a normal diurnal time frame for tracking changes. This method will also assist in improving pain management by creating a more reliable evaluation metric for specific treatments. Some seek to measure pain by looking at how certain metabolites change in the bloodstream with time, but with currently limited knowledge of threshold concentrations it is difficult to judge how effective such a strategy would be.

Another problem with pain management is addressing the development of chronic pain. The first question is whether the development of chronic pain stems from improper pain management shortly after surgery or a traumatic event created by improper/inefficient surgery? Based on existing statistics outlining how much long-term pain the population appears to be suffering from it is unlikely that improper/inefficient surgery is the cause of a majority of the chronic pain development. Therefore, this increase in experienced longer-term pain in the population is more than likely due to improper pain management. Unfortunately the current treatment methodology must be flawed in some way because it draws concern that these inconsistencies in effectively dealing with pain arise despite an increase in the overall use of opioids to manage pain.11-14.

While the use of multi-modal analgesia strategies has created sufficient levels of hope in better managing pain, most notably reducing side effects, this hope has not created significantly better long-term outcomes for a majority of people. The inability to attain the potential of multi-modal analgesia is largely due to the large number of variables involved in researching the effectiveness of various technique combinations (dose levels, surgery type, specific genetic factors, analgesic agents, etc.). Basically the individuality demanded by the development and application process reduces a large potential for streamlining and standardizing multi-modal analgesia strategies.

One of the hallmark symptoms of pain is hyperalgesia, which is an increase in pain sensitivity/perception in response to pain inducing stimuli. The typical cause of hyperalgesia is amplification and prolonged nociceptive excitation. Pursuant to this development there is evidence to suggest that current pain management techniques are short-term gain and long-term loss when it comes to addressing pain. One of the most popular choices to managing pain are opioids, especially for acute and chronic cancer pain, but opioids have also started to expand to chronic non-malignant pain. Opioids operate by binding to one of their seventeen different receptors, but three (Mu, Kappa and Delta) are largely responsible for the pain reduction ability of most opioids. Interaction with mu opioid receptors (MOR) either directly or as agonists is the most common pain management pathway. While MORs are expressed on numerous types of neurons the most important with regards to the propagation of pain appear to be the primary sensory neurons called small-sized (C-fiber) and medium sized (A-fiber, specifically Adelta) in the dorsal root ganglia (DRGs).14-17

When molecules interact with MORs they induce presynaptic inhibition that prevents N-type calcium channels from opening, which release neurotransmitters contacting with superficial dorsal horn neurons.18-20 Additional inhibition occurs through activation of G protein-coupled inwardly rectifying potassium channels on dorsal horn neurons resulting in hyperpolarization.20,21 Basically these opioid agonists are effective at addressing pain because of this dual neutralization methodology. Note that there is also some belief of indirect neutralization methods like immune cell activation of opioid receptors.22,23

Unfortunately improper activation of MORs can result in counteracting excitatory activity through the up-regulation of pronociceptive pathways,24,25 which leads to hyperalgesic effects. This specific outcome has been labeled opioid-induced hyperalgesia (OIH). OIH is characterized by increased probabilities for pain in general leading to increased probabilities for the development of chronic pain and tolerance to opioids, which decreases the ability to treat that chronic pain. There is concern that OIH routinely develops into chronic pain due to abrupt inappropriate withdrawals of opioids leading to long-term potentiation (LTP) in the spinal cord. This LTP response is thought to derive from massive activation of NMDA receptor glutamate responses with potential dependency on spinal cord-based TRPV1-expressing afferents along with substance P and chemokines.26-29 OIH can either be acute or chronic.30,31

Focus is applied to spinal cord and DRG LTP because it can develop due to electrical stimulation of appropriate afferents or noxious stimulation (nerve injury or inflammation).27,31-33 One common place for LTP augmentation is at synapses between nociceptive afferents and neurokinin 1 (NK1) receptor expressing projection neurons in lamina I.27 These projection neurons are principally responsible for sending pain signals to the brain.31,34-35 In addition there is similar pharmacology between LTP generation and long-term hyperalgesia.27 Finally LTP development at synapses between C-fibers and superficial dorsal horn neuron is induced by abrupt withdrawal of opioids.26 This is an important distinction because medication in general is typically only administered until symptoms subside. Unfortunately in most situations, including opioid treatment, suddenly stopping medication can result in negative biological consequences.

OIH can ‘leak’ over into the spinal cord by promoting the activation and translocation of protein kinase C, nitric oxide and cholecystokinin and in worst-case scenarios this development can lead to neuronal apoptosis further increasing pain reception problems.36-39 In some respects OIH could be viewed as initially nociceptive and eventually progresses into a neuropathic element.

However, all of this information is still indirect because LTP in the spinal cord with a relation to pain has not been studied directly.27 The lack of direct testing leaves an open question regarding spinal LTP length and how it fully influences the development of chronic pain. LTP for a given group of neurons can last for hours, days, months or a lifetime, but indirect evidence suggests LTP in the spinal cord lasts for several days.27 In this light chronic pain is thought to develop from inhibition of endogenous anti-nociceptive systems or intermittent low-level nociceptive input from periphery neurons. For example pain threshold reduction LTP is also perpetuated to a chronic level through the decreased activity of endogenous anti-nociceptive systems, thus reducing the ‘natural’ abatement adding chronic pain development.

One of tricky elements with addressing OIH is differentiating it from opioid tolerance. When increasing the opioid dosage for treatment of chronic pain the reason for the increase must be identified between opioid tolerance or OIH. In situations of tolerance it may be appropriate to increase opioid concentration depending on the severity of the pain, but in OIH more opioids would result in greater probability of pain. The most common strategy for treating OIH is to cease opioid treatment and substitute a non-opioid analgesic. Unfortunately non-opioid analgesics are typically not as effective as opioids and have their own side effects thus reducing the ability to manage pain.

Differences in analgesic treatment ability has lead to some rotational methodologies where opioids are used for a time and then replaced by non-opioids before a return again to opioids in an attempt to manage pain, but avoid compounding side effects from either treatment. Obviously the success of weaning a patient off of opioids as a means to treat OIH is based on the rate of OIH progression. Unfortunately it is difficult to assess the rate of advancement of OIH in a given patient. However, interestingly enough the future of managing chronic pain may not be developing a new pill or new multi-modal analgesia strategy, but instead developing a strategy where chronic pain does not develop in the first place.

A critical element in the pathway development for OIH is matrix metalloprotease (MMP) concentration. MMPs are a multigene family of tightly regulated zinc-dependent enzymes that maintain homeostasis through their role in tissue degradation and repair.40,41 The two MMPs that appear to play the most prominent roles in pain development are MMP-2 and MMP-9. MMP-9 is frequently released after nerve injury and directs the cleavage of IL-1b.14 Continued cleavage of IL-1b is then governed through a positive feedback mechanism with MMP-2.14,40 There is also suggestion that MMP-9 can interact with NMDA receptors NR1 and NR2B through integrin-beta1 and NO pathways.41 However, MMP-9 influence only seems to occur over a very short time frame (< 24 hrs) for after OIH acquisition to role played by MMP-9 seems to lessen significantly.14

Morphine is one of the most commonly utilized drugs for pain management and is frequently regarded as the standard for comparing the effectiveness of other pain management drugs. Due to its interaction with the μ-opioid receptor morphine chiefly influences in the posterior amygdala, hypothalamus, thalamus, nucleus caudatus and putamen with some associated action in the laminae I and II of the spinal cord. The effects of morphine interaction with its receptor are analgesia and sedation, but can also result in physical dependence.

While morphine is a commonly used pain management drug, its action may have a more detrimental long-term effect in that its interaction with opioid receptors leads to induction of rapid MMP-9 up-regulation. The initial up-regulation occurs in the DRG neurons, not in the spinal cord, and activates pro-nociceptive pathways from the DRG, most notable the cleavage of IL-1b.14 The increased concentration of MMP-9 is not derived from mRNA increases, but translational regulation instead.14 MMP-9 up-regulation does occur in the spinal cord after sustained morphine exposure and could play a role in opioid-induced withdrawal symptoms.41 In some context this biological response could be the body attempting to neutralize the synthetic (non-natural) neutralization of pain possibly in effort to ensure that the mind recognizes that the pain is occurring in effort to cease the pain creating activity, ward off its future application or begin/speed the healing process because pain usually involves some form of injury.

One of the chief aspects of hyperalgesia is the augmentation of Adelta fibers from mechanically insensitive (silent) to mechanically sensitive. This process occurs at high probability in two separate areas: first, during the surgery itself due to cutting an incision and second from MMP-9 up-regulation.42,43 Incision derived hyperalgesia does not rely on NMDA receptor activation, but instead its ‘sister’ receptor a-amino-3-hydroxy-5-methyl-4-isoxazole-propionate (AMPA).30,42 This sensitivity increase applies not simply to pain invoking stimuli, but also non-pain inducing mechanical stimuli due to a reduced mechanical response threshold in Adelta fibers.43 Reduced mechanical response also translates into a much larger spontaneous activity (up from 0% to 38% in Adelta afferents and from 0% to 40% in C-fibers).43 This spontaneous activity may play a role in the facilitation of chronic pain through LTP or mechanical sensitization of nociceptors. Inflammation also is though to reduce this spontaneous firing threshold.44,45 In both scenarios the reduced mechanical response threshold decreases gradually to a new equilibrium instead of all at once. This gradual reduction may play a role in the capriciousness of chronic pain development (different people may have different new equilibriums that are obtained at different rates).

Under most circumstances the application of a NMDA antagonist like ketamine can prevent OIH, but such action also reduces the pain neutralization ability of the administered opioid and studies looking at the benefit of combining opioids and NMDA antagonists have resulted in mixed results.46 Include that result with the significant psychotomimetic side effects (sedation, confusion, and lack of coordination) associated with NMDA antagonists and these types of opioid antagonists are typically only used to address opioid overdoses. Part of the problem with using NMDA antagonists to treat pain directly outside of combination with an opioid is that different molecular organizations of the NMDA receptors due to the three different subtypes, each having multiple isoforms, which results in different binding affinities.47

New strategies for short-circuiting the development of the OIH or other chronic pain pathways could be addressed through two different means. First, prevention of IL-1b cleavage, which is a downstream agent in the pain development pathway, will reduce hyperexcitability of sensory neurons by inhibiting potassium channel opening and increasing sodium channel opening.48-50 A similar alternative would be to prevent IL-1b binding by use of a IL-1 receptor antagonist. Second, the elimination of MMP-2 or MMP-9 could treat chronic pain for MMP-2 appears to be a maintenance pain molecule of some sorts whereas MMP-9 seems to be a trigger.

Some believe one strategy to prevent the development of neuropathic pain is to utilize loco-regional anaesthesia techniques over general anaesthesia.30 Some of the loco-regional agents that are hypothesized to be useful are μ-opioid receptor agonists and clonidine along with antagonists at T-type VGCCs and GABAA receptors.27 At least for major morbidities, the data looks promising for the results of several meta-analyses suggest that use of loco-regional analgesia or continuous paravertebral blockade is associated with decreased risk of postoperative pulmonary complications in patients undergoing upper abdominal and thoracic surgical procedures.51,52

The preoperative use of loco-regional analgesia is also associated with a reduction in respiratory complications after major abdominal surgery, although the effect of loco-regional analgesia might not be as prominent as it was previously, partly because the incidence of respiratory complication has progressively decreased during past years.53 Meta-analyses in patients undergoing high-risk cardiothoracic and vascular procedures suggest that use of preoperative thoracic loco-regional analgesia might decrease pulmonary complications, cardiac dysrhythmias, and overall cardiac complications.54,55 So even if current loco-regional analgesia techniques do not have any significant pain reduction characteristics they have some positive benefits.

However, there may be an even better means to amplify loco-regional anaesthesia through the use of MMP-2 and/or 9 inhibitors in the anaesthesia prior to surgery. By preventing MMP-2/9 activity during the pain inducing surgery itself, it may prevent the pain cascade from initiating at any significant level, thus eliminating the need to large amounts of pain control and the potential for the development of OIH. For example NOV manipulation can inhibit MMP-2 expression in the DHSC and MMP-9 expression in DRG and the spinal cord.56 Under normal pain conditions NOV is down-regulated in DRG and DHSC. One means to increase NOV expression is treat individuals with dexamethasone. However, caution must be taken before utilizing the increase of NOV or a similar agent as a treatment possibility because its influence has different effects on different cells. There is little information regarding what negative side effects may stem from applying MMP2/9 inhibitors immediately prior to surgery, so studies must be done to determine their nature and severity. One important consideration is to create the proper balance of inhibition because of the positive role MMP-9 has in wound healing.57

Overall pain management continues to be problematic in society. With the continued increases in OIH development it is more difficult because unless strict controls are established a common means to treat pain can become a catalyst for its further development. Unfortunately patients have a tendency not to be logical and practical when it comes to pain management for when a person is in pain they tend to do stupid things. It could be a great boon to pain management to develop a strategy to neutralize chronic pain before it even fully develops allowing other analgesia elements to be moved to a secondary strategy to treat more extreme conditions. The pre-surgical inhibition of MMP2/9 could have the potential to be such a strategy.



Citations:

1. Chapman, R, et Al. “Postoperative pain trajectories in cardiac surgery patients.” Pain Research and Treatment. 2012. Article ID 608359. doi:10.1155/2012/608359

2. Wheeler, M, et Al. “Adverse events associated with postoperative opioid analgesia: a systematic review.” Journal of Pain. 2002. 3(3):159–180.

3. Oderda, G, et Al. “Opioid-related adverse drug events in surgical hospitalizations: impact on costs and length of stay.” Ann Pharmacother. 2007. 41:400–06.

4. Ballantyne, J, et Al. “The comparative effects of postoperative analgesic therapies on pulmonary outcome: cumulative meta-analyses of randomized, controlled trials.” Anesthesia and Analgesia. 1998. 86(3): 598–612.

5. Rodgers, A, et Al. “Reduction of postoperative mortality and morbidity with epidural or spinal anaesthesia: results from overview of randomised trials.” The British Medical Journal. 2000. 321(7275):1493–1497.

6. Beattie, W, Badner, N, and Choi, P. “Epidural analgesia reduces postoperative myocardial infarction: a meta-analysis.” Anesthesia and Analgesia. 2001. 93(4):853–858.

7. Holte, K and Kehlet, H. “Effect of postoperative epidural analgesia on surgical outcome.” Minerva Anestesiologica. 2002. 68(4):157–161.

8. Marret, E, Remy, C and Bonnet, F. “Postoperative Pain Forum Group. Meta-analysis of epidural analgesia versus parenteral opioid analgesia after colorectal surgery.” Br J Surg. 2007. 94:665–73.

9. Fischer, H, et Al. “A procedure-specifi c systematic review and consensus recommendations for postoperative analgesia following total knee arthroplasty.” Anaesthesia. 2008. 63:1105–23.

10. Institute of Medicine of the National Academies Report (2011). Relieving Pain in America: A Blueprint for Transforming Prevention, Care Education, and Research. Washington DC: The National Academies Press.

11. Frasco, P, Sprung, J and Trentman, T. “The impact of the joint commission for accreditation of healthcare organizations pain initiative on perioperative opiate consumption and recovery room length of stay.” Anesth Analg. 2005. 100:162–68.

12. Zaslansky, R, et Al. “Tracking the effects of policy changes in prescribing analgesics in one emergency department: a 10-year analysis.” Eur J Emerg Med. 2010. 17:56–58.

13. Manchikanti, L, et Al. “Therapeutic use, abuse, and non-medical use of opioids: a ten-year perspective.” Pain Physician. 2010. 13:401–35.

14. Liu, Y, et Al. “Acute morphine induces matrix metalloproteinase-9 up-regulation in primary sensory neurons to mask opioid-induced analgesia in mice.” Molecular Pain. 2012. 8:19-36.

15. Ji, R, et Al. “Expression of mu-, delta-, and kappa-opioid receptor-like immunoreactivities in rat dorsal root ganglia after carrageenan-induced inflammation.” J. Neurosci. 1995. 15:8156-8166.

16. Wang, H, et Al. “Coexpression of delta- and mu-opioid receptors in nociceptive sensory neurons.” PNAS. 2010. 107:13117-13122.

17. Lee, C, et Al. “Dynamic temporal and spatial regulation of mu opioid receptor expression in primary afferent neurons following spinal nerve injury.” Eur J. Pain. 2011. 15:669-675.

18. Heinke, B, Gingl, E, and Sandkühler, J. “Multiple Targets of mu-Opioid Receptor-Mediated Presynaptic Inhibition at Primary Afferent A{delta}- and C-Fibers.” J. Neurosci. 2011. 31:1313-1322.

19. Kohno, T, et Al. “Actions of opioids on excitatory and inhibitory transmission in substantia gelatinosa of adult rat spinal cord.” J. Physiol. 1999. 518(3):803-813.

20. Kohno, T, et Al. “Peripheral axonal injury results in reduced mu opioid receptor pre- and post-synaptic action in the spinal cord.” Pain. 2005. 117:77-87.

21. Yoshimura, M, North, R. “Substantia gelatinosa neurones hyperpolarized in vitro by enkephalin.” Nature. 1983. 305:529-530.

22. Mousa, S, et Al. “Beta-Endorphin-containing memory-cells and mu-opioid receptors undergo transport to peripheral inflamed tissue.” J. Neuroimmunol. 2001. 115:71-78.

23. Stein, C, et Al. “Peripheral mechanisms of pain and analgesia.” Brain Res Rev. 2009. 60:90-113.

24. Angst, M, Clark, J. “Opioid-induced hyperalgesia: a qualitative systematic review.” Anesthesiology. 2006. 104:570-587.

25. Mao, J, Price, D, and Mayer, D. “Mechanisms of hyperalgesia and morphine tolerance: a current view of their possible interactions.” Pain. 1995. 62:259-274.

26. Drdla, R, et Al. “Induction of synaptic long-term potentiation after opioid withdrawal.” Science. 2009. 325:207-210.

27. Ruscheweyh, R et Al. “Long-term potentiation in spinal nociceptive pathways as a novel target for pain therapy.” Molecular Pain. 2011. 7:20-57.

28. Chen, Y, Geis, C, and Sommer, C. “Activation of TRPV1 contributes to morphine tolerance: involvement of the mitogen-activated protein kinase signaling pathway.” J. Neurosci. 2008. 28:5836-5845.

29. Ma, W, et Al. “Morphine treatment induced calcitonin gene-related peptide and substance P increases in cultured dorsal root ganglion neurons.” Neuroscience. 2000. 99:529-539.

30. Wu, C and Raja, S. “Treatment of acute postoperative pain.” The Lancet. 2011. 377:2215–25.

31. Ikeda, H, et Al. “Synaptic amplifier of inflammatory pain in the spinal dorsal horn.” Science. 2006. 312:1659-1662.

32. Zhang, H, et Al. “Acute nerve injury induces long-term potentiation of C-fiber evoked field potentials in spinal dorsal horn of intact rat.” Sheng Li Xue Bao. 2004. 56:591-596.

33. Sandkühler, J and Liu, X. “Induction of long-term potentiation at spinal synapses by noxious stimulation or nerve injury.” Eur J Neurosci. 1998. 10:2476-2480.

34. Nichols, M, et Al. “Transmission of chronic nociception by spinal neurons expressing the substance P receptor.” Science. 1999. 286:1558-1561.

35. Mantyh, P, et Al. “Inhibition of hyperalgesia by ablation of lamina I spinal neurons expressing the substance P receptor.” Science. 1997. 278:275-279.

36. Mayer, D, et Al. “Cellular mechanisms of neuropathic pain, morphine tolerance, and their interactions.” PNAS. 1999. 96:7731– 6.

37. Chen, L and Huang, L. “Sustained potentiation of NMDA receptormediated
glutamate responses through activation of protein kinase C by u-opioids.” Neuron. 1991. 7:319 –26.

38. Chen, L, and Huang, L. “Protein kinase C reduces Mg2+ block of NMDA-receptor channels as a mechanism of modulation.” Nature. 1992. 356:521–3.

39. Mao, J, Price, D and Mayer, D. “Thermal hyperalgesia in association with the development of morphine tolerance in rats: roles of excitatory amino acid receptors and protein kinase C.” J. Neurosci. 1994. 14:2301–12.

40. Ribeiro, A, et Al. “Expression of matrix metalloproteinases, type IV collagen, and interleukin-10 in rabbits treated with morphine after lamellar keratectomy.” Veterinary Ophthalmology. 2012. 15(3):153-163.

41. Liu, W, et Al. “Spinal matrix metalloproteinase-9 contributes to physical dependence on morphine in mice.” J. Neurosci. 2010. 30:7613-7623.

42. Zahn, P, Umali, E and Brennan, T. “Intrathecal non-NMDA excitatory amino acid receptor antagonists inhibit pain behaviors in a rat model of postoperative pain.” Pain. 1998. 74:213–23.

43. Pogatzki, E, Gabhart, G and Brennan, T. “Characterization of Adelta- and C-Fibers Innervating the Plantar Rat Hindpaw One Day After an Incision.” J. Neurophysiol. 2002. 87:721-731.

44. Ahlgren, S, White, D and Levine, J. “Increased responsiveness of sensory neurons in the saphenous nerve of the streptozotocin-diabetic rat.” J Neurophysiol. 1992. 68:2077–2085.

45. Kocher, L, et Al. “The effect of carrageenan-induced inflammation on the sensitivity of unmyelinated skin nociceptors in the rat.” Pain. 1987. 29:363–373.

46. Van Elstraete, A, et Al. “A Single Dose of Intrathecal Morphine in Rats Induces Long-Lasting Hyperalgesia: The Protective Effect of Prior Administration of Ketamine.” Anesth Analg. 2005. 101:1750 –6.

47. Paoletti, P and Neyton, J. “NMDA receptor subunits: function and pharmacology.” Curr Opin Pharmacol. 2007. 7(1):39–47.

48. Takeda, M, et Al. “Enhanced excitability of nociceptive trigeminal ganglion neurons by satellite glial cytokine following peripheral inflammation.” Pain. 2007. 129:155-166.

49. Binshtok, A, et Al. “Nociceptors are interleukin-1beta sensors.” J. Neurosci. 2008.
28:14062-14073.

50. Takeda, M, et Al. “Activation of interleukin-1beta receptor suppresses the voltage-gated potassium currents in the small-diameter trigeminal ganglion neurons following peripheral inflammation.” Pain. 2008. 139:594-602.

51. Marret, E, et Al. “Meta-analysis of intravenous lidocaine and postoperative recovery after abdominal surgery.” Br J Surg. 2008. 95:1331–38.

52. Hudcova, J, et Al. “Patient controlled opioid analgesia versus conventional opioid analgesia for postoperative pain.” Cochrane Database Syst Rev. 2006. 4:CD003348.

53. Wijeysundera, D, et Al. “Epidural anaesthesia and survival after intermediate-to-high risk non-cardiac surgery: a population-based cohort study.” Lancet. 2008. 372:562–69.

54. Wu, C, et Al. “Effect of postoperative epidural analgesia on morbidity and mortality following surgery in medicare patients.” Reg Anesth Pain Med. 2004. 29:525–33.

55. Liu, S and Wu, C. “Effect of postoperative analgesia on major postoperative complications: a systematic update of the evidence.” Anesth Analg. 2007. 104:689–702.

56. Kular, L, et Al. “NOV/CCN3 attenuates inflammatory pain through regulation of matrix metalloproteinases-2 and –9.” Journal of Neuroinflammation. 2012. 9:36-55.

57. Broadbent, E, et Al. “Psychological stress impairs early wound repair following surgery.” Psychosomatic Medicine. 2003. 65:865-869.

Digging into Anesthesia and the Potential Risks and Counter-Measures to Application

Anesthesia has always been an interesting aspect of the medical profession. The use of anesthetics has facilitated the evolution of medical surgery by eliminating physiological responses to the pain and the stress of surgery. However, despite significant advances in medical technology and understanding, knowledge regarding the action of anesthetics remains shrouded in mystery even for those that specialize in their application. Different mechanisms of action have been proposed, but there is little certainty with regards to how anesthetics induce immobility, amnesia and loss of conscious awareness in the patient. Discovering how these influences occur would be an important step to the development of new anesthetics that provide the surgical benefits of current anesthetics without the potential side effects, which would open the door to more surgical options on higher risk groups such as the elderly and young children.

Development of new anesthetics used to be something far on the back burner of science because currently used anesthetics appeared to be working fine; however, recent studies have demonstrated that in certain target groups, most notably young children and the elderly, that the use of anesthetics may increase the probability of learning disabilities. Whether or not learning disabilities are attributable specifically to anesthesia on children has yet to be determined, but just an inkling of a relationship is enough to lead some parents into a protectionist stance holding off surgeries that would be beneficial, but not essential to their children. Such a mindset regarding the behavior of parents is not farfetched when considering the actions of some parents in response to the pertinent myth of autism being related to vaccination. Therefore, an alternative anesthetic or application methodology needs to be developed because young children cannot go without surgery entirely, but also need to have the safest surgery possible.

To maximize the effectiveness of an alternative method, the mechanism behind anesthetic function must be better understood. The best place to start appears to be identification of how anesthetics induce loss of consciousness. Anesthetics fall into two main categories: intravenous agents used to induce anesthesia and volatile agents used to maintain anesthesia. Fortunately current empirical evidence seems to suggest that both intravenous and volatile agents share the same general neurological path of action, but each agent does have unique sites of action as well. This similar function is useful because volatile agents are typically easier to work with than intravenous agents to generate empirical data.

The first significant clinical information regarding anesthetics came from Overton and Meyer who both noted that the more potent the anesthetic the more soluble it was in olive oil.1,2,3 This observation generated the correlation between anesthetic potency and oil solubility.4 This information originated the ‘unitary hypothesis’ which stated that inhaled anesthetics influenced lipid bilayer properties and that influence some how brought on anesthesia.5 This interaction with the lipid bilayer in the unitary hypothesis is thought to be non-specific.5 However, one downside to this theory was that any detected changes were small and required anesthetic concentrations much larger than those required to induce anesthesia which implied greater complexity.6

Unfortunately for the ‘unitary hypothesis’ there is various evidence that is thought to disprove it. For example the lipid change has been associated with a lipid change analogous to a change of 1-2 degrees C in body temperature or a small fever.5 However, a fever does not facilitate anesthesia apart from anesthetic agents. Also there are other molecules that generate similar lipid changes without any trace of anesthesia.7 In addition there are molecular exceptions to the lipid interaction behavior predicted by unitary hypothesis and Meyer-Overton rules. These ‘non-immobilizers’ fail to quell motor reflexes despite having the appropriate chemical properties.8,9 Although there are some issues regarding some of the experimental methods associated with these studies, largely with the use of dipalmitoylphosphatidylcholine, it seems unlikely that the information is of such significant error that their conclusions could be considered wrong on a general level.5,9 That is lipid changes may be a small part of the final anesthesia result, but seem unable to induce anesthesia alone.

Although the unitary hypothesis and other theories involving influences in the lipid bilayer affecting anesthesia may not be favored at the moment, studies have brought to light some interesting behavior between anesthetics and the lipid bilayer. For example anesthetic molecules distribute unevenly across the lipid bilayer drawn to more amphiphilic regions vs. the hydrophobic interior, which implies that stiff hydrophobic molecules should have less potency than molecules with a greater level of flexibility.10,11 Also this uneven distribution can influence the phosphocholine dipole in certain anesthetics like halothane, which can in turn influence voltage gated ion channels coupling interaction between lipid and protein mechanisms.12

Despite any positive evidence for lipid based theories, protein-anesthetic interaction is still the favored choice among a vast majority of scientists when discussing possible mechanisms for anesthetic action partly because empirical systems designed without lipids can mimic anesthetic pharmacodynamics.5 Unfortunately if a protein interaction is involved the generic methodology to locate the ligand receptor on the protein appears to be inapplicable. Anesthetics are small, volatile and do not appear to be amenable to conventional assays as clinical EC50 values are in the low millimolar range5,13 which suggests low affinity binding and ligand-receptor interaction times that span milliseconds or lower. Note that EC50 is defined as the concentration of an agent that provides a half-maximal activation of a target in vitro.9 Due to this limitation two criteria are commonly used to further judge anesthetic action, plausibility and sensitivity.5

Plausibility usually looks at the extent of inhibition of excitatory action or enhancement of inhibitory action in neurons through the suppression of glutamate or acetylcholine neurotransmitter release or the activation of GABA or glycine release respectively.5 Plausibility is a precursor to sensitivity in that for sensitivity to be relevant, plausibility must first exist. Sensitivity comes into play when an anesthetic both inhibits excitatory activity and enhances inhibitory activity.5 In this instance sensitivity is used to determine which influences is more prominent because depression of excitatory activity can occur independently of inhibitory enhancement. Typically the sensitivity value is related back to an EC50 value, which although low can sometimes be used to differentiate action between anesthetics.5

Through sensitivity analysis inhibitory ligand-gated channels have demonstrated more influence in the action of various anesthetics over other types of channels and inhibition of excitatory action.14 Enhancement of inhibitory action through either GABA or glycine makes sense, but how do they influence these channels? There are two possible explanations for this action. First, inhibitory ligand channels have specific receptors where anesthetics bind to induce influence, similar to agonists and antagonists. However, it is unlikely to assume that receptors for multiple anesthetics exist in a population or configuration to influence such a variety of inhibitory processes, thus if an anesthetic type receptor exists it would have to be well conserved and have a general structure that facilitates binding of multiple anesthetics. The fact that anesthetics are not naturally occurring in the body limits the probability for the existence of such a receptor.

Note that the above statement relates to anesthetics binding to the same type or group of receptors (their own unique receptor). Some anesthetics do bind to existing receptors on specific proteins. For example isoflurane is able to bind picrotoxinin receptors, which is a drug that binds within the channel lumen of the GABAA receptor in attempt to reduce the probability of convulsions.15,16 Despite these few shared sites the probability that isoflurane is able to consistently bind to the same site as something like propofol is extremely remote.

The second option is an alteration of protein function through a reduction in protein flexibility by reducing the national global dynamics of the protein. How such action is accomplished requires first understanding how proteins act both alone and in consort with anesthetics. Proteins are not static structures, but undergo constant random thermal driven motion within a stable equilibrium structure (basically they can only undergo a finite number of conformational changes which are afforded by the particular structure of the protein). Possible protein motions range from single bond fluctuations to entire folded domains and secondary structures. This random motion persists until it is prevented by some form of chemical or structure impediment like an appropriate ligand binding to a given receptor on the protein.

However, receptors are not the only position in a protein where outside molecules can influence change in protein dynamics. Even in their tertiary structures proteins have pockets of void space, which are commonly referred to as ‘cavities’.5,17,18 These empty regions of space typically influence how the protein dynamics proceed. It is believed that some of these ‘cavities’ are large enough that anesthetics are able to enter them and become temporarily trapped restricting the ability of the given protein to continue its natural dynamic shift between conformational states.18 This trapping mechanism may explain the low EC50 values. Overton-Meyer correlation action is the top candidate for how the cavities interact with anesthetics.5 Further evidence to support the ‘cavity’ theory is that the more potent an anesthetic the greater its polarity which is thought to increase affinity for these cavities.5

Unfortunately there is a potential significant hole in the cavity theory in that how does restricting the protein dynamics lead to unconsciousness? For example if a particular anesthetic enters the cavity of a GABAA receptor (a post-synaptic receptor that facilitates influx of chloride ions that lowers the probability of neuronal firing), conventional wisdom states that for that receptor to enhance inhibition the new less dynamic receptor structure must increase the probability of GABA binding. For such a probability increase to occur the remaining conformational switches, if more than one is still possible, must be at a greater binding ratio than those available before the anesthetic is administered. To better illustrate this fact, suppose a non-anesthetic influenced GABAA receptor moves between 50 different states where 20 of those states can bind GABA. If an anesthetic in the cavity resulted in only 25 states at least 11 of those states would need to bind GABA for the cavity theory to make sense.

Even assuming the above example actually occurs, the disconcerting question of why would over half of the GABAA receptors behave in such a way remains. Why is it more probable for 11 of the 25 states to bind GABA instead of 5 of the 25 states? This question is especially pertinent to the consistency of anesthetics. Anesthetics do not have a 60% probability of success instead they have a 95+% probability of success. Their action is not some randomized infiltration of the cavities which determines a situation where one GABAA receptor may have a binding capacity at 4 of the 28 possible states, but another GABAA receptor may have a binding capacity at 20 of the 22 possible states.

Therefore, if occupation of the cavities does create this probability of action advantage across different people then there must be some level of consistency in infiltration and structure. Basically the anesthetic must only be able to enter the cavity from certain conformational structures and locks in a given structure set that increases the probability of action. The simplest means to accomplish the probability increase is lock the receptor into a single static state that allows GABA binding. However, for such a reality to be plausible the cavity relationship to both the receptor class and the anesthetic would have to be evolutionarily conserved. Unfortunately such a notion creates a problem in that anesthetics are not naturally occurring in the body. In fact the body has its own means, largely through inhibitory agonists and excitatory antagonists, to regulate excitatory actions in neurons. So why would these receptors have specific conserved behavior in response to molecules they normally would not have encountered? The best solution may be that the size and charge of the anesthetic results in a generic lock. No conserved design is present instead anesthetic action can almost be simply regarded as a form of ‘dumb luck’.

Although it would be helpful to have a baseline understanding of the how consciousness manifests itself in the brain, such a goal is still under large and controversial investigation especially regarding what level of coherence is required to ensure consciousness. Overall such a discussion is better left for another time. However, there is one significant element that all theories of consciousness agree on, consciousness seems to require EEG coherence in the γ frequency range (20 to 80 Hz).9

The issue of whether consciousness is triggered from a particular area of the brain versus sufficient coherence in firing between different areas of the brain is an interesting question because if anesthetics are able to breakdown coherence to induce unconsciousness then certain responses may be reactivated without regaining consciousness. If possible this reactivation regiment could be used as a counter-measure to filter out some of the side effects for anesthesia. For example suppose learning difficulties are caused due to loss of coherence in a given region of the brain, but loss of coherence in that given region is not required for unconsciousness. If so a secondary drug could be applied to block de-coherence of this region which would lessen the negative influence of anesthetics. The first step may have already been accomplished in demonstrating a loss of coherence due to the action of anesthetics.19,20,21 Unfortunately as a meaningful strategy the relevant information to apply a safe counter-measure seems very far away with the current knowledge about consciousness.

With all of that said and the complicated nature of understanding anesthesia both through chemical interaction and the realm of consciousness, why is the study of anesthesia important? As previously alluded to one of the principle issues regarding the use of anesthetics has always been whether or not the application of chemicals that induce a state of unconsciousness facilitate detrimental side effects in the brain. Bolstering the concern have been studies in mice and non-human primates that have demonstrated significant levels of apoptosis in neurons after exposure to anesthesia.22,23,24,25,26 The results of these studies were contingent on two critical factors: first, the age of the test subject, the younger the subject the higher the probability of both permanent damage and the extent of that damage. Second, the duration and amount of exposure was critical in the total probability for and amount of damage. In general neuronal damage occurred if the subject was still within the age range that allotted potential neurogenesis and/or synaptogenesis.

Although these studies are disconcerting, there have been many previous studies in other model organisms regarding other physical or mental states that have drawn certain conclusions that have not translated to humans. Therefore, although young mice may suffer detrimental conditions under anesthesia there is no reason to assume that young children suffer the same way. At one point in time that attitude was valid, however, now there may be reason to be more concerned about exposing young children to anesthesia. In the past there was no significant study of how anesthesia affected young children, but Wilder et Al,27 presents evidence that the above conditions responsible for neuronal damage in rats and non-human primates also translate to young children.

The study in question identified neuronal damage from anesthesia through the severity and frequency of any learning disabilities suffered by those individuals in the study. Learning disabilities were classified as problems with one or more basic psychological processes involved in understanding or using spoken or written language possibly manifested in difficulty to listen, think, speak, read, write, spell or perform mathematical computations.27 The subjects in the study that underwent surgery did so before the age of four. The ceiling of age was selected at four because the period of synaptogenesis is thought to occur though a child’s third year of life.28 The conclusions from the study identified, similar to previous studies in mice and non-human primates, that both a sufficient dose and exposure to multiple anesthetics were required to generate a significant increase in the probability to generate a learning disorder.27

Of course this study only provides some level of evidence between exposure to anesthetics at a young age and the probability of developing a learning disorder, it was unable to demonstrate a conclusive link between the two. In addition there are some lingering questions regarding the study. For example the authors admit that a broad criteria was established for diagnosing a learning disability in an attempt to maximize the number of children with learning disabilities to detect effects, which could artificially increase the correlation ratio. However, it is unlikely that redefining learning disability in this case would significantly change the general conclusion that anesthesia does have an influence on increasing the probability of developing a learning disability. In the end changing the parameters that define a learning disability would only change the magnitude of the effect, not the fact that the effect exists. One interesting note in using a broad definition of learning disability is that the study was unable to identify any shading; that it was more probable that anesthesia would result in one specific learning disability over another. Of course such a bias must exist for it to be detected and it is unclear whether or not such bias exists in the first place.

There are also questions regarding the general health of those children diagnosed with learning disabilities after anesthesia utilized surgery vs. those children that did not require surgery. This is an important point to note because it is reasonable to suggest that children that need to have surgery at such a young age probably have more health problems than those children that do not have to have such surgery. With these additional health problems, one can reason that a level of co-morbidity extending from these additional conditions could explain the future learning disabilities instead of the anesthesia.

Although co-morbidity concerns are a rational counter-hypothesis, there is reason to believe that in this particular situation it is not applicable because of two salient points. First, the authors conclude that there was no connection or trend associated with the overall health (number or severity of conditions) of the children and the probability of developing a learning disability. Second, only a few of the conditions that required surgery originated as or even evolved into brain conditions. It is difficult to blame a kidney condition for a learning disability. So, similar to a new branding of ‘learning disability’ co-morbidity could alter the severity of the influence of the anesthetic, but it is unlikely that the general result would change.

So for the moment assume that this study has a level validity in that it connects three different species, mice, non-human primates and humans in which young still neuronally developing members of these species have a higher probability of brain damage when exposed to anesthesia than members that are not exposed to anesthesia. How does such a detrimental result occur?

One avenue to better understand anesthesia and its problems is look at it through the scope of sleep. Sleep and anesthesia are very similar with regards to their outward projected state of consciousness. However, a myriad of empirical information identify sleep as critical to the learning process whereas anesthesia may generate an increased probability of creating learning disabilities. What differences exist between these processes that could account for this apparent 180-degree switch?

As previously discussed learning is one of the crux issues between natural sleep and loss of consciousness due to anesthesia. Differentiating between these states is important to understand where significant differences arise that could explain the different outcomes with regards to learning. There are two major types of sleep states that receive a brunt of the research attention, Slow Wave Sleep (SWS) and Rapid Eye Movement (REM). Both of these states are important for the growth and survival of humans, but what is their role in learning?

To begin sleep consists of two major phases: Non-Rapid Eye Movement (NREM) and Rapid Eye Movement (REM). The components of the NREM cycle dominate the sleep cycle and consists of three different stages conveniently labeled I, II and III. NREM used to be divided into four different stages, but recently the American Academy of Sleep Medicine changed the total cycle allotment by removing stage IV expanding stage III to cover both its originally defined stage and stage four.29 These stages are commonly defined by three different empirical measures: brain wave activity measured by an electroencephalogram (EEG), muscle tone measured by an electromyogram (EMG) and eye movement which can be viewed visually or more specifically measured with an electrooculogram (EOG).29 Of the three an EEG is most commonly used to differentiate transition between different states.

With regards to sleep an EEG identifies brain waves in four different patterns: beta, alpha, theta and delta. When awake beta waves dominate mixed in with a few alpha waves, almost no theta waves and zero delta waves. The key characteristics of beta waves are they possess the highest frequency and lowest amplitude of the four waves and are the most de-synchronous (no consistency in pattern for multiple occurrences). This de-synchronous behavior is commonly explained due to the variety of neuronal firings that occur during a given period of individual neuronal activation due to the different sensory information that can be processed at a given time based on differentiating experience.

Alpha waves become more prominent when individuals focus on single activities, especially when that activity is not strenuous like meditation. Not surprisingly alpha waves have a longer period, greater amplitude and greater synchronicity in behavior.

Stage I begins NREM where alpha waves give way to theta waves. The reason alpha waves dominate leading up to sleep is that rarely do healthy individuals fall asleep when fully awake, instead there is a period of rest (the generic lying in bed with the lights off thinking). Sleep in Stage I is very weak and individuals rarely displace time when they wake from the first cycle of Stage I sleep (basically they think they did not fall asleep).

Entrance into and maintenance of Stage II is characterized by ‘sleep spindles’ and K-complexes, which are bundled together with a greater number of theta waves. Sleep spindles are spontaneous increases in wave frequency and K complexes are single spontaneous increases in wave amplitude.29 Although deeper than Stage I most individuals can still be quickly aroused while in Stage II.

SWS is represented by Stage III NREM sleep and is often referred to as deep sleep. The defining characteristic of Stage III sleep is the arrival of delta waves. Officially Stage III is defined as an epoch consisting of 20% or more of slow wave (delta) sleep.29 Stage III sleep marks the only stage of NREM sleep where dreaming has a reasonable, albeit small, probability of occurrence. The typical means of entering SWS is the activation of serotonergic neurons in the raphe system. These neurons are activated through thalamocortical neuron firing.

The length of SWS is largely influenced by the total time a subject is awake prior to entering SWS.30 This result suggests that SWS plays a critical role in the sleep process. In fact benzodiazepines and other sedatives actually decrease the total time in SWS despite increasing the total amount of sleep duration. Further exploration of the relationship between SWS and chemicals like benzodiazepines could be an important consideration between learning and SWS in young children.

The second major phase of sleep is REM which usually occurs some time after entrance into Stage III of NREM sleep. REM sleep commonly replaces Stage I sleep as the sleep cycle renews.29 REM sleep can be further broken down into two distinct states of sleep, tonic and phasic.29 The major criteria for REM sleep are fluttering/rapid eye movement, a rapid and low voltage EEG and muscle paralysis. Muscle paralysis is caused through the inhibition of motor neurons due to the release of MOA-A and MOA-B which breakdown monoamine based neurotransmitters which are largely responsible for depolarizing these motor neurons.29

For a normal adult REM sleep comprises approximately 20-25% of total sleep or about 90-120 minutes for an 8-hr sleep period.29 Early cycles of REM sleep are shorter and get longer in individual duration as the night continues. The total percentage of REM sleep is generally inversely proportional to an individual’s age where younger individuals have a much higher total percentage of REM sleep. This relationship between age and REM sleep is one of the reasons REM sleep was theorized to play a significant role in learning and knowledge acquisition because it is easier for younger individuals to learn and have more learning opportunities. Although most associate REM sleep and learning in some context, there are some that believe in the niche theory that instead of reinforcing new neuronal connections made earlier in the day, REM sleep organizes a controlled ‘pruning’ of neuronal connections, basically facilitating the ‘unlearning’ of certain knowledge.31 REM sleep is also thought to aid in the enhancement of short-term creativity largely thought through the reorganization of specific neuronal hierarchies due to the lack of acetylcholine and norepinephrine feedback.29

Whether or not it is directly connected to learning or some unrelated neuronal function, long-term elimination of REM sleep has demonstrated a negative influence to the survivability of an individual. Also there have been a number of studies that have demonstrated that sleep deprivation has a significant negative affect on learning, thus in some shape and form sleep is required for proper learning and memory consolidation. So the chief issue relates to what portions of sleep govern what aspects of learning.

Note that in no shape and form is the sole purpose of sleep only to aid in memory consolidation, there are clearly other reasons and causes for sleep, but memory consolidation in some respect occurs during sleep. Also for the purpose of this discussion there are two different aspects to learning: first, there is memory consolidation of simple tasks and second there is memory consolidation and synaptogenesis for complex tasks.

Anesthesia demonstrates bi-stability between cortical and thalamic neurons and slow oscillations (< 1 Hz) between up and down states.32,33 Some argue that this bi-stability creates gaps in the ability of the brain to integrate and process information. For example when conscious applied transcranial magnetic stimulation (TMS) generates a response of approximately 300 ms34 versus a response of 150 ms when in non-REM sleep.35 The difference in this response implies a loss of integration between neurons.

The length of sleep required for learning has never been considered an issue because of the general understanding that proper homeostasis of the biological system was best maintained by sleeping at least 7-8 hours over a 24-hour period. Despite this overlap due to general biological needs, some researchers have explored the issue regarding how much sleep is actually required to augment learning. One particular study identified that only 60 to 90 minutes of sleep were required to emulate results in a texture discrimination tests generated from fully rested test subjects.36 However, these limited periods of sleep need to include entrance into both SWS and REM sleep in order to generate an improvement in results.

In fact that study concluded that sleep periods that entered SWS but not REM eliminated deterioration in performance seen in sleep deprived subjects but did not produce actual improvement. Naps that entered both SWS and REM eliminated deterioration in performance and improved performance. This result suggests that SWS may serve to stabilize performance in learning related tasks and REM may actually facilitate performance improvement.36 Also there is reason to believe that nap-dependent learning has a retinotopic specificity similar to that reported for overnight improvement.36

Also it was interpreted that a 90-minute nap can produce as much improvement as a night of sleep and a nap followed by a night of sleep provides as much benefit as two nights of sleep.36 However, it must be noted that the evidence suggesting such a conclusion did not test beyond two days and did not test with consecutive nights of just napping with no long-term sleep. Thus, one cannot conclude whether or not long-term sleep is required to gain long-term improvement in learning. Also the testing used a relatively easy testing method to demonstrate improved learning, thus there is no evidence to suggest that napping affords the same ability to solve complex problems as overnight sleep.

Most accept that sleep does improve procedural memory, but unfortunately in the past there have been some issues regarding the influence of sleep on declarative memory and whether this improvement occurs in REM or NREM sleep. These issues arise largely due to questions about acute fatigue immediately after sleep deprivation and not controlling for circadian rhythms when attempting to differentiate between the drop-off in performance due to sleep deprivation and improvement due to REM sleep in non-sleep deprived subjects.37,38,39

In addition to the concerns regarding circadian rhythms and acute fatigue, there are questions regarding the ability to produce evidence to support the involvement of REM sleep in memory consolidation.37 There are two general schools of thought for providing evidence to support the aforementioned claim: first, learning during waking hours should increase the amount of REM sleep; second, preventing REM sleep should significantly limits the ability to consolidate memories.

The motivation behind the first mindset is that increased learning will require more memory consolidation leading to greater total duration of REM sleep. Critics of this evidence collection method cite that unless the test animal is learning a specifically assigned task, there is no way to confirm that test animal is increasing knowledge acquisition over a given period of time because an animal is continuously learning. With regards to training the test animal to learn a specific task, critics content that the common techniques applied to teaching the task are flawed, leaving them unable to confirm a genuine increased REM sleep duration.37,38 For instance an increased level of stress derived from shock avoidance or confusion/trepidation associated with appetitive reinforcement methodologies could facilitate emotional or psychological changes that could influence the rate and quality of sleep for the test animal reducing the probability of any viable trend from the study.

Overall most critics seem to avoid suggesting a potential simple means of demonstrating some form of connection between increased learning and increased REM sleep, the introduction of harmless new stimuli. For example adding an exercise wheel to a gerbil’s living environment without previous exposure. If there were any significant changes in REM sleep, it would be easier to identify those changes in the first few days after the introduction of the wheel and eventual use of the wheel because the gerbil would learn the purpose and correct operation of the wheel. The lack of any forced hardships (additional stress, food or water deprivation, etc.) removes the concern that any changes are driven by those possible negative feedbacks from forced learning. The lack of specificity of the learning would allow researchers to identify general pattern changes in REM sleep without having to worry about associating specific learning techniques to specific changes.

Similar tests could be devised in human subjects by instructing individuals in various hands-on tasks where knowledge was lacking. For example teaching a group of individuals that know nothing about automotive care how to change a tire or change an oil filter would provide a new interactive task to increase the knowledge base of the individual. The selection of the type of activity may be where experimenters go wrong in human subjects for instead of testing with hands-on new task experiments the subjects are asked to take exams covering various subjects. The exam environment may not be conducive to learning because of the inherent stress involved (no matter how many times an individual is told a particular test is meaningless/without consequence rarely will that individual think of a test that way) and the rote characteristics of the information in the exam.

Some have extended the relation of REM sleep and learning beyond learning new information to sheer intelligence. That is individuals with higher IQs should experience more REM sleep than those with lower IQs. Clearly any attempt to create a correlation between these two elements is fraught with difficulties as structural changes in the brain unrelated to intelligence may govern the inherent amount of REM sleep an individual experiences. Ironically of the most noted studies one could not identify a correlation between intelligence and REM sleep.40,41

On its face the hypothesis that higher IQ would require greater amounts of REM sleep seems to make sense. However, as previously mentioned SWS sleep seems to be more responsible for general maintenance of memory and intelligence than REM sleep.36 New memory formations would require an increased level of synaptogenesis and that process could occur in REM sleep. Unfortunately for experimenters, for higher IQ individuals most of that IQ was more than likely developed very early in life, thus there may be a slightly higher level of general maintenance required, but less opportunity to form new connections relative to an individual with a lower IQ. Basically for higher IQ individuals there would be a higher probability of forming new connections whereas lower IQ individuals have a greater number of new connections that could be made. Therefore, in controlled environments if REM sleep was involved in memory consolidation and learning through synaptogenesis, there would be a higher probability of an increase in REM sleep in the lower IQ individuals not higher IQ individuals.

This idea is better illustrated through the following analogy. It stands to reason that higher IQ individuals have more neuronal connections than those with lower IQs. These connections, typically created by greater dendrite formation and extension, can be regarded as roads. In a controlled environment where both a higher and lower IQ individual are learning the same information it can be assumed that roads A, B, C, D and E need to be constructed to successfully acquire the knowledge. For the higher IQ individual there is a higher probability that one or more of these roads was previously constructed related to another separate task acquired earlier in life, a task that the lower IQ individual does not have knowledge of. Thus, the higher IQ individual may only need to construct roads A, B, D and E to acquire the knowledge. This reduced construction amount reduces the total time required in REM sleep due to higher efficiency and fewer required road construction.

Despite the possibility of increased REM sleep in lower IQ individuals, overall it is probably unlikely that any correlation will be derived simply due to the principle of over-saturation. One issue that may not have been considered is whether or not REM sleep time is overdrawn relative to the amount that is needed. Remember that evolution does not look to create the perfect system, just one that gets the job done. Perhaps all the REM sleep that an individual with a 180 IQ needs is 40 minutes vs. 30 minutes for an individual with 130 IQ or even visa-versa, but both individuals receive an average of 100 minutes of REM sleep a night through natural processes. Thus, the required amount of REM sleep for both individuals is already received making it extremely difficult to differentiate any difference between the two based solely on intelligence.

Two important structures in the brain when considering memory are the hippocampus and the amygdala. Although believed to play a role in most memory functions the hippocampus is thought to have a specific focus on spatial memory processing and memory retention.30 The amygdala also plays an important role in memory formation, especially memories which significant emotional context.42 Due to their involvement in memory consolidation it stands to reason that it would be useful to further study these two brain elements regarding their role in sleep. First off, from an evolutionary standpoint the larger the amygdala and to a smaller effect the hippocampus the longer a creature will experience an average amount of NREM sleep.30,43,44

During SWS neuronal firings move from the amygdala and hippocampus to neocortical sites where the amygdala is the key region governing the anatomical change in sleep-derived memory consolidation.30,45 One currently explored model for memory consolidation considers that the initial neuronal firing originates from the hippocampus and amygdala during SWS (when sleep derived memory consolidation occurs) and travels to neocortical sites. Then during REM sleep the ‘information’ encoded in this firing is relayed through the neocortex and eventually reflects back to the amygdala near the end of REM sleep.30 The importance of the hippocampus and amygdala neuronal firing in the consolidation of memories during sleep requires that greater memory capacity have more neuronal connections in each region which may account for the difference in size across species. Thus the unique roles of NREM sleep vs. REM sleep may also play an important role regarding the function and size of these regions.30

For example there appears to be no significant correlation between the size of the neocortex and sleep duration unlike that seen for the amygdala and hippocampus.45,46 This difference could be explained by the fact that the neocortex seems to function more actively during REM sleep than NREM sleep, thus if REM sleep and NREM sleep have different functions related to memory consolidation, a break in size relationships would make more sense. One explanation relates REM sleep to sleep intensity in that larger brains engage in relatively more REM sleep,46 however, whether or not that relationship is maintained intra-specially instead of just inter-specially remains to be seen.

One of the principle criticisms lobbied against the function of sleep and its role in memory consolidation is the use of MAO inhibitors and their ability to eliminate the REM sleep portion of the sleep cycle. MAO inhibitors disallow the oxidation of monoamines by monoamine oxidases. The oxidation of monoamines is an important regulatory control in neurons because of the aforementioned role of neurotransmitters dopamine, serotonin and norepinephrine in the onset and maintenance of sleep.29 In particular REM sleep is driven by the absence of monoamines due to MAO. Thus, with the elimination of REM sleep opponents of memory consolidation theories believe that significant memory impairment would result in individuals taking MAOs. Some even go so far to argue that use of MAO inhibitors results in memory improvement.47,48

However, as previously theorized in his discussion, most of the general memory consolidation that an individual would experience and require for the average day does not take place during REM sleep, but instead takes place during NREM sleep most likely during SWS. REM sleep instead could be responsible for complex learning and memory consolidation of those particular skills, elements that would be more difficult to determine a lack of in patients taking MAO inhibitors. Overall it is unlikely that there is no memory consolidation in REM sleep due to ongoing processes of synaptogenesis and synapse pruning (unlearning), but that vast majority of memory consolidation seems to occur during SWS sleep instead of REM sleep.

It may seem like a tall order but a general theory behind why and how sleep occurs will be important to determining the difference between natural sleep onset and anesthesia driven sleep onset. The chief purpose of sleep seems to function on a restorative nature for the brain, especially because sleep deprivation affects cognitive functioning more than physical functioning.49 Various theories have been proposed to the nature of this restorative methodology be it a lack of direct (glucose) or an indirect (glycogen) energy,50 a buildup of too much neuronal activity threatening a critical collapse51 or the accumulation of various metabolites.19 Currently the critical collapse theory is new and does not have much direct evidence to support it. Also if correct such a theory does little to help differentiate a significant difference between anesthesia and natural sleep, so there will be no more discussion of it here.

Although this particular post will not get into the unique differences between the sleep theories relating to a lack of glycogen vs. a build-up of certain metabolites, note that in general the overall premise governing each theory is relatively the same. Certain chemical quotes are met which generates a cascade of responses that steadily increase the probability of sleep induction. Therefore, this similarity will be utilized when discussing how either theory relates back to differences in anesthetic induced unconsciousness.

Assume for a moment that either the metabolite theory or the glycogen theory for sleep is correct. Why then is the amount of sleep one seems to require inversely proportional to age (babies require lots of sleep seniors require very little)? There appear to be two possibilities. First, the rate of sleep inducing metabolite synthesis is faster/slower glycogen synthesis in younger individuals, thus the probability rate for sleep induction increases faster. Second, as one ages the probability rates for sleep induction decrease, thus requiring more metabolite/less glycogen to generate a significant probability of sleep.

Note it is more rational to utilize sleep probabilities than a threshold value because of the existence of sleep deprivation. Basically as one fails to sleep the probability of falling asleep increases. It is inappropriate to think about the trigger of sleep as a 0% probability of action that almost immediately becomes 100% after passing a certain point. Certainly the probability of sleep becomes 100% after a certain progression, but various other probability values are also present during the ascent to 100%. To ensure clarity think of it this way: the probability of falling asleep is less than 1% for any period of continuous consciousness less than 22 hours. Then the probability of sleep increases 2% for each 15 minutes awake after 22 hours.

Overall the first option seems to be more plausible because rate of metabolite synthesis/glycogen expenditure could change based on changes in neuronal growth and mapping. This explanation makes sense in the fact that neuronal plasticity and growth occur at a more frequent pace in younger individuals. However, the second option also has a level of validity in that tolerance levels with respect to the probability of sleep could increase as one ages. As the brain becomes more complex in its wiring (more neuronal connections are made as one ages from infancy to adulthood) there could be an increase in the amount of metabolites required to increase the probability of sleep.

It could be at this point where the difference in learning between sleep and anesthesia diverge. Natural sleep occurs through the gradual build-up of metabolites/loss of glycogen through the course of a given day. Although it does make sense that there could be changes in the rate of synthesis due to undertaking certain tasks, more than likely those that are mentally taxing, none of these tasks change the synthesis rate to a point where sleep is induced immediately. Also the progressive advance of a lack of glycogen or metabolite concentration increase creates a control system where these elements are not at saturation.

However, anesthesia involves using molecules that appear to induce much more rapid changes to induce a state of unconsciousness. Unfortunately application of anesthetics result in a cascade reaction that initiate unconsciousness through an alternative pathway, probably the cavity methodology. To continue the state of unconsciousness anesthetics must be consistently applied, thus removing any natural flexibility from the neuronal response to the unconscious process. The reason adults are less susceptible to brain damage from exposure to anesthesia may be due to an increase in tolerance levels. Also the fact that there is limited synaptogenesis in the adult brain also may play a role because the neurons on average are more robust than those in the young child.

With that said a basic summary of anesthetic action and the role it plays in sleep can be generated as followed:

- Normal sleep functions by moving from a wakeful generally desynchronized state to a NREM sleep state that is highly synchronized to a REM sleep state that appears desynchronized, but is carefully synchronized to test current neuronal connections and ‘sprout’ new ones through synaptogenesis.

- With regards to memory standard generic memories not requiring complex or higher order brain function are consolidated in NREM sleep. In REM sleep dreams could be used as a procedure to eliminate erroneous or inefficient neuronal connections. Also during REM sleep new neuronal connections are generated and strengthened thinking through synaptogenesis. These new connections are shaded to higher order thinking and problem solving. For example if an individual learned a new skill, like changing the oil in his/her car, this information would be consolidated during REM sleep through new neuronal connections instead of consolidated in NREM sleep. NREM sleep consolidation usually involves more low skill techniques or rote information similar to those used in experimental testing.

- The most probable means through which anesthesia work is the ‘cavity’ theory. As previously mentioned in the ‘cavity’ theory anesthetic molecules get trapped in the void spaces between molecules that make up the proteins that govern receptors which allow various ions to depolarize or hyperpolarize a given neuron. Normally these proteins are in a dynamic state oscillating between many different conformations. When molecules bind at specific receptor sites on a protein, they temporarily limit this oscillatory nature which allows the respective ion channel to significantly increase the probability of opening facilitating depolarization or hyperpolarization. When anesthetic molecules inhabit these void spaces it also heavily restricts the dynamic nature of these receptors which locks them into a single conformation. This conformation is able to produce an effect similar to the loss of consciousness seen in NREM sleep.

- Although similar to NREM sleep in outcome, the type of loss of consciousness produced by anesthesia does not result in any specific synchronization by different neurons. Instead of producing a unique and efficient synchronization to facilitate unconsciousness, anesthesia forces each receptor into a specific position inducing unconsciousness on a single neuron basis. This lack of synchronization in the induction of unconsciousness strips the neurons from any control. Due to the fact that individuals must remain exposed to anesthesia over the course of the surgery due to small ‘binding’ efficiencies there is no relief from this forced unconscious non-natural state because the anesthetic operates as a limiting factor saturation point. Basically natural sleep induces an unconscious state through a finesse using specific controlled firings and inhibitions whereas anesthesia induces an unconscious state through brute force.

- Considering the aspect of neuronal damage in young children and non-human species there are two primary rationalities. First, the typical culprit in neuronal apoptotic situations with no outside pathogenic component is excitotoxicity. A neuron becomes depolarized far longer than normal which allows for the excessive influx of calcium which later leads to activation of certain calcium dependent secondary messengers that eventually result in apoptosis. However, for anesthesia related apoptosis excitotoxicity does not seem to be a valid rationality because in addition to an increase in inhibitory responses, application of anesthesia also reduces the NMDA and AMPA activity (excessive NMDA activity is a critical precursor for excitotoxicity) in an inhibitory (GABA/glycine) independent manner.52 With increased inhibitory action and decreased excitatory action (both dependent and independent of inhibitory action) it is unlikely that excitotoxicity is responsible for neuronal death.

- The second rationality is that the neuronal death comes from an efficiency strategy. For the brain if a neuron is not actively firing when it is perceived that it should then the brain will typically get rid of it in an attempt to limit collateral damage thinking that something is wrong with the neuron. Under anesthesia large quantities of neurons are not firing over extended periods of time, which may lead the brain to begin the process of eliminating them. It is likely that such a process during regular sleep does not occur because of cycling between the calm controlled synchronized state of NREM sleep and the excited more de-synchronized state of REM sleep. In contrast anesthesia locks a patent in a single quasi-NREM sleep state.

- The reason why neuronal apoptosis is so harmful to young children and infants over adults that receive anesthesia is the issue of redundancy. In young children loss of neurons through apoptosis or any other means is more devastating because their loss severely reduces the probability of any future connections that may hub from that neuron. Returning to the road example, in young children typically there is only one road initially constructed from point A to point B. Once at point B, construction can take place from point B to points C – E. Later roads could be constructed from points C - E to point A creating a secondary path between point A and point B. However, if point B is damaged before a road can be constructed between point A and B, it makes little sense to construct a road to point B. Thus, it will be more difficult to construct roads to points C – E and from those points back to point A. In adults those roads have already been constructed thus the potential loss of point B is immaterial to those roads connecting point A with points C – E. In fact the traffic on the roads between point B and other points may be so significant that even after point B is destroyed there would be interest in rebuilding point B. In children if point B is destroyed before significant ‘traffic’ can be consistently generated between point B and other points there is less interest in rebuilding point B because it would be viewed with little value.

It is unfortunate that excitotoxicity does not appear to be the principle reason for the apoptosis in young creatures when exposed due to exposure to anesthetics because an interesting strategy to combating these results could have been to add a treatment of memantine to the anesthetic regiment. The action of memantine was previously discussed in the Alzheimer’s disease post. Of course memantine has a history in anti-cancer and Alzheimer’s disease treatment so there is little information regarding its affect on young children, thus testing would have to be done to ensure that any deleterious affects are insignificant. However, if side effects were limited it could have been an effective strategy to reduce neuronal damage.

Unfortunately if ‘lack of use’ apoptosis is the reason behind the possible increase in learning disabilities attributed to anesthetic use in children, then there does not appear to be a drug avenue for use. For example trying to force an intermittent dual cycle like normal sleep by adding MOA agonists or some other stimulant would more than likely lead to disaster. Such a strategy would not have the necessary level of finesse because either the anesthetic and stimulant would be competing with each other more than likely creating pockets of excitation and inhibition in the brain such could cause more damage than just the anesthetic alone or stopping administration of the anesthetic during surgery and adding a stimulant could likely induce the body’s stress response.

Overall there is still a significant way to go before the scientific community can be confident in its handling of anesthesia and its related actors; however, with medical technologies improving the ability of physicians to diagnosis and even operate on young children, understanding the risks associated with the application of anesthesia and how to counteract these risks is an important aspect in ensuring a successful surgery. Also a better understanding of the inherent action of anesthetics may increase the base knowledge regarding human consciousness.

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Citations

1. Meyer, H. “Welche eigenschaft der anästhetica bedingt ihre narkotische wirkung?” Arch. Exp. Pathol. Pharmakol. (Naunyn-Schmiedeberg’s) 1899. 42: 109–118.

2.. Overton, E. “Studien über die Narkose, zugleich ein Beitrag zur allgemeinen.” Pharmakologie (Gustav Fischer, Jena, 1901).

3. Miller, K. “Molecular mechanisms by which general anaesthetics act.” Mechanisms of drugs in anaesthesia. Hodder and Stoughton. 1993. 191–200.

4. Richards, C.D. “Critical evaluation of the lipid hypotheses of anesthetic action.” Molecular Mechanisms of Anesthesia. Raven Press. 1980. 337–351.

5. Eckenhoff, R. “Promiscuous Ligands and Attractive Cavities - How do the inhaled anesthetics work?” Molecular Interventions. 2001. 1(5): 258-268.

6. Franks, N, and Lieb, W. “Molecular and cellular mechanisms of general anaesthesia.” Nature. 1994. 367: 607–614.

7. Buck, K, Miller, A, and Harris, R. “Fluidization of brain membranes by A2C does not produce anesthesia and does not augment muscimolstimulated 36 Cl-influx.” European J. Pharmacol. 1989. 160: 359–367.

8. Koblin, D, et, Al. “Polyhalogenated and perfluorinated compounds that disobey the Meyer-Overton hypothesis.” Anesth. Analg. 1994. 79: 1043–1048.

9. Rudolph, U, and Antkowiak, B. “Molecular and Neuronal Substrates for General Anaesthetics.” Nature Reviews – Neuroscience. 2004. 5: 709-720.

10. Baber, J, Ellena, J, and Cafiso, D. “Distribution of general anesthetics in phospholipid bilayers determined using 2H NMR and 1H-1H NOE spectroscopy.” Biochemistry. 1995. 34: 6533–6539.

11. Xu, Y, and Tang, P. “Amphiphilic sites for general anesthetic action? Evidence from 129Xe-[1H] intermolecular nuclear Overhauser effects.” Biochim. Biophys. Acta. 1997. 1323: 154–162.

12. Koubi, L, et, Al. “Distribution of halothane in a DPPC bilayer from molecular dynamics simulations.” Biophys. J. 2000. 78: 800–811.

13. Franks, N, and Lieb, W. “Temperature dependence of the potency of the volatile general anesthetics: Implications for in vitro experiments.” Anesthesiology 1996. 84: 716–720.

14. Harrison, N, et, Al. “Positive modulation of human gamma-aminobutyric acid type A and glycine receptors by the inhalation anesthetic isoflurane.” Mol. Pharmacol.1993. 44: 628–632.

15. Edwards, D, and Lees, G. Modulation of a recombinant invertebrate g-aminobutyric acid receptor chloride channel complex by isoflurane: effects of a point mutation in the M2 domain. Br J Pharmacol. 1997.122: 726 –32.

16. Gurley, D, et, Al. Point mutations in the M2 region of the , , or  subunit of the GABAA channels that abolish block by picrotoxin. Receptors Channels. 1995. 3: 13–20.

17. Brunori, M, et, Al. “The role of cavities in protein dynamics: Crystal structure of a photolytic intermediate of a mutant myoglobin.” PNAS. 2000. 97: 2058–2063.

18. Carugo, O, and Argos, P. “Accessibility to internal cavities and ligand binding sites monitored by protein crystallographic thermal factors.” Proteins. 1998. 31: 201–213.

19. Alkire, M, Hudetz, A, and Tononi, G. “Consciousness and Anesthesia.” Science. 2008. 322(5903): 876–880.

20. Miller J, and Ferrendelli, J. “Characterization of GABAergic seizure regulation in the midline thalamus.” Neuropharmacology. 1990/ 29(7): 649-655.

21. Angel, A. “Central neuronal pathways and the process of anaesthesia.” Br J Anaesth. 1993. 71(1): 148-63.

22. Jevtovic-Todorovic, V, Benshoff, N, and Olney, J. “Ketamine potentiates cerebrocortical damage induced by the common anesthetic agent nitrous oxide in adult rats.” Br. J. Pharmacol. 2000. 130: 1692-1698.

23. Olney, J, Wozniak, D, and Jevtovic-Todorovic, V. “Drug-induced apoptotic neurodegeneration in the developing brain.” Brain Pathol. 2002. 12: 488-498.

24. Jevtovic-Todorovic, V, et, Al. “Early exposure to common anesthetic agents causes widespread neurodegeneration in the developing rat brain and persistent learning deficits.” J Neurosci. 2003. 23: 876–82.

25. Mellon, D, Simone, A, and Rappaport, B. “Use of Anesthetic Agents in Neonates and Young Children.” Anesthesia & Analgesia. 2007. 104:3 509-520.

26. Slikker, W, et, Al. “Ketamine-induced neuronal cell death in the perinatal rhesus monkey.” Toxicol Sci. 2007. 98: 145-158.

27. Wilder, R, et, Al. “Early Exposure to Anesthesia and Learning Disabilities in a Population-based Birth Cohort.” Anesthesiology. 2009. 110: 796–804.

28. Rice, D, Barone, S Jr. “Critical periods of vulnerability for the developing nervous system: Evidence from humans and animal models.” Environ Health Perspect. 2000. 108:3. 511–33.

29. Wikipedia Entry on Sleep; http://en.wikipedia.org/wiki/Sleep;

30. Capellini, I, et, Al. “Does sleep play a role in memory consolidation? A comparative test.” PloS One. 2009. 4(2): e4609.

31. Crick, F, and Mitchison, G. “The function of dream sleep.” Nature. 1983. 30(14): 113-114.

32. Williams, S, et, Al. “The ‘window’ component of the low threshold Ca2+ current produces input signal amplification and bistability in cat and rate thalamocoritical neurons.” J. Physiol. 1997. 505: 689-705.

33. Fuentealba, P, et, Al. “Membrane bistability in thalamic reticular neurons during spindle oscillations.” J. Neurophysiol. 2005. 93: 294-304.

34. Massimini M, et, Al. “Triggering sleep slow waves by transcranial magnetic stimulation.” PNAS. 104(20): 8496-8501.

35. Massimini M, et, Al. “Breakdown of cortical effective connectivity during sleep.” Science. 2005. 309(5744): 2228-2232.

35. Mednick, S, Nakayama, K, Stickgold, R. “Sleep-dependent learning: a nap is as good as a night.” Nature Neuroscience. 2003. 7(6): 697-698.

36. Siegel, J. “The REM sleep-memory consolidation hypothesis.” Science. 2001. 294: 1058–1063.

37. Smith, C. “Sleep states and memory processes in humans: Procedural versus declarative memory systems.” Sleep Med. Rev. 2001. 5: 491–506.

38. Vertes, R. “Memory consolidation in sleep: Dream or reality.” Neuron. 2004. 44: 135–148.

39. Mayes, S, et, Al. “Non-significance of sleep relative to IQ and neuropsychological scores in predicting academic achievement.” Journal of Developmental and Behavioral Pediatrics. 2008. 29(3): 206-212.

40. Smith, C, Nixon, M, Nader, R. “Post-training increases in REM sleep intensity implicate REM sleep in memory processing and provide a biological marker of learning potential.” Learn. Mem. 2004. 11: 714-719.

41. Josselyn, S, Kida, S, Silva, A. “Inducible repression of CREB function disrupts amygdala-dependent memory.” Neurobiol Learn Mem. 2004. 82: 159-163.

42. Buzsaki, G. “Memory consolidation during sleep: a neurophysiological perspective. J. Sleep Res. Suppl. 1998. 7: 17-23.

43. Roth, T, and Pravosudov, V. “Hippocampal volumes and neuron numbers increase along a gradient of environmental harshness: a large-scale comparison.” Proc R Soc, Lond B. 2008. 276: 401-405.

44. Yoo, S, et, Al. “The human emotional brain without sleep – a prefrontal amygdala disconnect.” Current Biology. 2007. 17: 877-878.

45. Lesku, J, et, Al. “A phylogenetic analysis of sleep architecture in mammals: the integration for anatomy, physiology and ecology. Am Nat. 2006. 168.

46. Georgotas, A, Reisberg, B, Ferris, S. “First results on the effects of MAO inhibition on cognitive functioning in elderly depressed patients.” Archives of Gerontology and Geriatrics. 1983. 2: 249-263.

47. Vertes, R, and Eastman, K. “The case against memory consolidation in REM sleep.” Behavioral and Brain Sciences. 2000. 23(6): 867-876.

48. Horne, J. “Sleep function, with particular reference to sleep deprivation. Ann. Clin. Res. 1985. 17: 199-208.

49. Benington, J, and Heller, C. “Restoration of brain energy metabolism as the function of sleep.” Progress in Neurobiology 1995. 45: 347-360.

50. Pearlmutter, B, Houghton, C, Tilbury, S. “A new hypothesis for sleep: tuning for criticality.” 2006.