Monthly Archives: November 2023

M2 receptors also modulate synaptic transmission in cortical circuits affecting the pyramidal neurons

For the tests of the rapidity of the transition from regular alcohol use to alcohol dependence as a function of the age onset of regular alcohol use, those who become regular alcohol users in the youngest age range were much more likely to become alcohol dependent either in the same age range or the subsequent age range than those who become regular alcohol users in the age ranges 16–17 or 18–19 years . Viewing this from a slightly different perspective, the fraction of those who transition from alcohol use to alcohol dependence in less than 2 years in the oldest age range is much smaller than that in the youngest age range. A Cochran–Armitage trend test of this phenomenon shows a p value of less than 8 9 10-5 for the hypothesis of no trend.There were age-related trends in the genotypic distributions of those who became alcohol dependent in any of the four age ranges in the illicit drug sub-sample. For the first trend test, of the change of genotypic distribution with age of those who became alcohol dependent at any age, the hypothesis of no trend could be rejected at a 0.003 level for rs978437, rs7800170, and rs1824024, SNPs which were significant for alcohol dependence in the entire population, and at a 0.035 level for rs2061174 and rs2350786. This means that in those who became alcohol dependent, having two copies of the major allele was the prevalent condition for who became alcohol dependent in the earliest age range, while not having two copies of the major allele was the prevalent condition of those who become alcohol dependent in the oldest age range. For the second trend test, of the change of genotypic distribution with time from initiation of alcohol use to time of alcohol dependence of those who began regular alcohol use in the youngest age range and who became alcohol dependent at any age, the hypothesis of no trend could be rejected at a 0.025 level for all of the SNPs. This means that in those who became immediately alcohol dependent, having two copies of the major allele was the prevalent condition,vertical grow shelf system while in those who took the longest to become alcohol dependent, not having two copies of the major allele was the prevalent condition. The results are presented in Table 4. This suggests a genetic influence on the rapidity of the transition from regular alcohol use to alcohol dependence among those who become regular alcohol users in the earliest age range.

The pattern of significance of the ERO and SNP factors for the onset of regular alcohol use and of alcohol dependence is different between the youngest and oldest age ranges within the entire sample, as is evident in Table 2. These differences are primarily the result of differences between the populations of regular alcohol users in the two age ranges. The proportion of the at-risk sample who become regular users of alcohol increased from 15 to 43 % between the two age ranges. Biological factors are significant in both the onset of regular alcohol use and of alcohol dependence in the youngest age range. The prevalence of regular drinking in the oldest age range has eliminated the effect of the biological factors in its onset; only the onset of alcohol dependence is affected by biological factors. In the older age range, since it is likely that much of the onset of alcohol dependence is driven by past drinking, particularly since relatively few of those who become alcohol dependent in the oldest age range have been drinking for a short time, those factors which are significant for regular alcohol use in the youngest age range are significant for alcohol dependence. Furthermore, it is likely that a biologically specific sub-population of the youngest group particularly sensitive to the effects of alcohol has been effectively eliminated from the at-risk group in the oldest age range . In the illicit drug use sub-sample in the youngest age range, CHRM2 is a greater factor for the onset of alcohol dependence than in the entire sample. However, EROs are not a factor in the onset of alcohol dependence in this group. The range of ERO values in the illicit drug use sub-sample does not differentiate those who become alcohol dependent from those who do not, although ERO values differentiate the illicit drug sub-sample from their complement in the entire sample. The illicit drug use sample shows greater and more extensive genetic effects than the entire sample, since the result of selecting the illicit drug use sub-sample is to remove those subjects whose alcohol dependence is unlikely to be genetically affected from the analysis. In examining the results of the logistic regression analysis of the transition from regular alcohol use to alcohol dependence in the youngest age range, the U-shaped effect of the duration of drinking suggests the presence of two distinct factors, one a susceptibility to rapidly become dependent subsequent to the onset of regular alcohol use and the other a gradual effect of continued alcohol consumption.

The masking of the ERO effect by the rising component of the duration factor suggests that ERO is associated with a long term behavior pattern involving substance abuse. The absence of a genotypic effect is the result of including all those who become alcohol dependent in the analysis, not just those in the genetically more vulnerable, as can be observed by comparing the under 16 results between the regular alcohol user group and the illicit drug user group. In summary, for the youngest age range the pattern of significance of the ERO and SNP phenotypes for the onset of regular alcohol use and of alcohol dependence, as well as the pattern of significance in the transition from alcohol use to alcohol dependence suggests that delta ERO value indexes an element of propensity to use drugs to excess, while the CHRM2 SNPs index an age related effect of alcohol consumption on the brain with the behavioral outcome of dependence, as we explain below. We view the age-varying genotypic effect of the CHRM2 SNPs as an instance of a gene–environment interaction. In our case the immediate genotypic effects are upon the activation level of the type 2 muscarinic receptors and the environment is the neuroanatomic and neurophysiological context in which the action of the muscarinic receptors is taking place. This environment undergoes significant changes as the brain develops from the early teens into the early twenties, as we have noted above. In the transition from alcohol non-use to regular use of alcohol to alcohol dependence, we note that alcohol consumption has significant effects on the development of addiction in adolescent animals and humans . The cholinergic M2 receptor gene belongs to a family of muscarinic acetylcholine G-protein coupled receptors with five known subtypes . The M2 receptors in the mesolimbic dopaminergic system play a significant role in modulating the level of dopamine release . This has a important effect in governing the reward system ,vertical growing companies including modulating the effects of alcohol on it . It is not possible to determine the precise nature of the interaction between the genotypic effect on the cholinergic M2 receptors and the age-varying neuroanatomic/neurophysiologcial environment given the data at our disposal.

Given the age-related patterns of genotypic action we have described above, it is possible that the effect of alcohol consumption on the brain varies with the genotype of the cholinergic M2 receptors and the age of onset of regular drinking. Specifically, when alcohol is consumed regularly in the youngest age range, perhaps better described as a particular stage in brain maturation centered in this age range, the addiction producing effects on those who have two copies of the major allele are accelerated compared to those who do not, leading to rapid transition from regular alcohol use to alcohol dependence. [This may be in part responsible for the ‘‘telescoping of trajectory’’ effects reported in Hussong et al. .] Those without two copies of the major allele may take longer to manifest the effects of alcohol use. As the age of the initiation of alcohol use increases, it appears that the cumulative risk for alcohol dependence when carried into the adult years is greater in those without two copies of the major allele than in those with two copies. We draw this last conclusion on the basis of the trend tests on our own data and the results of the studies of Wang et al. and Dick et al. . In those who become regular users of alcohol under the age of 16, a majority of those who became alcohol dependent within two years had the risk genotype; the majority of those who become alcohol dependent four years or more after their onset of regular drinking did not have the initial risk genotype. A contributing factor to the age specificity of the effect of the CHRM2 SNPs could be a frailty effect. The frailty effect would play a role if there were relatively easy access to alcohol in the youngest age range, at least for those most at risk. Among those who have the major alleles, those who are genetically most vulnerable become alcohol dependent rapidly, leaving only those who have some protective factor. Thus risk for those with the major alleles will decrease with age, since those without the protective factors will have become alcohol dependent, leaving primarily those with protective factors at potential risk. We also note that if the illicit drug user population had easier access to alcohol than the entire population as a whole, the greater genetic effects seen in the illicit drug user sub-sample might in part be the result of a gene– environment interaction, akin to those described in Dick and Kendler , in which looser social controls over behavior accentuate genetic effects. Since 80 % of the illicit drug use sub-sample are from COGA rather than community families, this is a plausible hypothesis. The specific environment of the most vulnerable group is more likely to accentuate genetic effects, rather than to diminish them.We found that SNPs reported to be significant in adults were significant in adolescents in this sample, particularly for those in the youngest age ranges, and for those who had ever used an illicit drug. However, in our results, the major allele was the risk allele, while in the results of Wang et al. and consequently of Dick et al. , the minor allele was the risk allele. Our results do not contradict those of Wang et al. and Dick et al. ; the results are mutually consistent. Instead, they reveal a novel age-specific risk factor undetectable by solely examining the condition of alcohol dependence rather than its age of onset. In view of the age differences between the sample studied in this paper, and the sample used in the studies of Wang et al. and Dick et al. it is not possible that they should contradict one another. In the Wang et al. study, about 5 % of the alcohol dependent subjects had ages of onset of less than 16 years of age. This is too small a fraction to have an effect on the results. As we noted in our discussion of the trend tests, in our study the genotypic distributions of the alcohol dependent subjects change with age of onset. While we do not observe a significant SNP effect in the oldest age range with DTSA, the fraction of subjects with the minor allele in those who become alcohol dependent is greater than the fraction of subjects with the minor allele in those who do not become alcohol dependent . This trend acts to produce a similar genotypic distributions for alcohol dependent and non alcohol dependent subjects when considered regardless of age of onset. In terms of the methodology, DTSA requires that there be differences in genotypic distributions between alcohol dependent and non alcohol dependent subjects to give a statistically significant results for a SNP; this is not true for the family based method used by Wang et al. . Our interpretation is that family based studies are more powerful than the type of association study employed here; the absence of a distributional difference does not mean that there is no genetic effect.

The mention of normal compartments and the normal neurologic exam suggests that a neurologic cause is unlikely

We do not understand the reasons for this discrepancy, but possible explanations include the weak antinociceptive activity of oleylethanolamide or small changes in rearing conditions, which may strongly affect behavioral responses in mice. Local and systemic administration of palmitylethanolamide alleviated pain behaviors elicited by a diverse group of chemical irritants, which included formalin, acetic acid, kaolin and magnesium sulfate. In all cases, treatment with the cannabinoid CB receptor antagonist SR144528 2 Žbut not of the cannabinoid CB receptor antagonist 1 . SR141716A prevented the effects of palmitylethanolamide, indicating that a common mechanism may be involved in these responses. Such broad antinociceptive properties strengthen the hypothesis that palmitylethanolamide may play a key role in the intrinsic control of pain initiation. Moreover, these properties support the notion that the putative receptor activated by palmitylethanolamide may provide a useful target for analgesic drug Ž development Calignano et al., 1998, 2000; Piomelli et al., . 2000 . Further support to this proposal comes from the fact that palmitylethanolamide may exert both analgesic Ž . Calignano et al., 1998; Jaggar et al., 1998; present study Ž and anti-inflammatory effects Benvenuti et al., 1968; Facci . et al., 1995; Mazzari et al., 1996 . Thus, drugs aimed at the putative palmitylethanolamide receptor might offer the advantage of combining these two complementary therapeutic properties. Additional experiments are needed, however, to unequivocally establish whether the analgesic and anti-inflammatory actions of palmitylethanolamide are mediated by the same putative receptor blocked by SR144528. Despite its ability to attenuate a variety of phasic pain responses,pipp racks such as those elicited by formalin and magnesium sulfate, palmitylethanolamide had no effect on capsaicin-induced nocifensive behavior.

Capsaicin, the active principle in chili pepper, is thought to produce pain by selectively activating VR1-type vanilloid receptors on pe- Ž ripheral sensory fibers Caterina et al., 1997; Szallasi and . Blumberg, 1999; Davis et al., 2000 . Accordingly, the fact that palmitylethanolamide did not inhibit capsaicin-induced pain at doses that completely prevented other nociceptive responses suggests that palmitylethanolamide does not directly interfere with nociceptor-mediated pain transmission. In keeping with this possibility, palmityl- Ž ethanolamide had no effect on thermal nociception Table . 1 , which is also thought to require phasic nociceptor Ž . activation Besson and Chaouch, 1987 . By contrast, and in agreement with the presence of cannabinoid CB recep- 1 Ž . tors in sensory neurons Hohmann and Herkenham, 1999 , we report here that anandamide inhibits capsaicin nociception. Moreover, in previous studies, we have shown that anandamide prevents thermal nociception and that this effect is also blocked by the cannabinoid CB antagonist 1 Ž . SR141716A Beltramo et al., 1997 . A plausible explanation for our findings is that anandamide and palmitylethanolamide exert their peripheral antinociceptive effects by interacting with different molecular and cellular targets. According to this hypothesis, anandamide may activate cannabinoid CB receptors located on capsaicin-sensitive 1 primary afferents, resulting in the decreased responsiveness of these afferents to noxious stimuli. Palmitylethanolamide, on the other hand, may stimulate an uncharacterized receptor, blocked by SR144528 and located on non-neuronal peripheral cells or capsaic in-insensitive neurons. The existence of distinct molecular and cellular targets for anandamide and palmitylethanolamide might also account for the synergistic effects displayed by these compounds on formalin-evoked or kaolin-evoked nocicep-tion. Whether or not these speculations turn out to be correct, the analgesic properties of palmitylethanolamide and anandamide underscore the important functions served by these lipid messengers in pain signaling, and the potential interest of the A 19-year-old female was brought to the emergency department by emergency medical services with complaints of generalized weakness, an inability to move her extremities, and near syncope. The patient stated that she began feeling generalized weakness that morning, which she initially attributed to her “sleeping position.” Over the day the weakness worsened, culminating in difficulty or inability to move her extremities and a near syncopal episode.

The patient stated she had attempted to stand up from a seated position when she “felt like [she] was going to pass out.” The patient called 911 for assistance. On further discussion, the patient revealed she had experienced one similar episode of weakness earlier in the year, but this had resolved spontaneously and was not as severe. She does not have a primary care physician and she had never sought care for this complaint. The patient said she noticed generalized abdominal pain, nausea, and constipation, associated with each of these episodes of weakness and light headedness. She denied any recent illnesses. She stated she treats her bipolar disorder with daily cannabis and consumes alcohol daily as well. University of Maryland Medical Center, Department of Emergency Medicine, Baltimore, Maryland University of Maryland School of Medicine, Department of Emergency Medicine, Baltimore, Maryland University of Maryland School of Medicine, Department of Epidemiology and Public Health, Baltimore, Maryland.The patient had a history of anxiety, depression, migraines, and normocytic anemia. Surgical history included an adenoidectomy and tonsillectomy as a child. She had no pertinent family history. Her social history included daily alcohol use, drinking a total of 1.75 liters of vodka over a two-week period. She started smoking when she was 16 years old, smoking a pack per day, but quit a year prior to presentation. The patient smoked cannabis daily. Her only medication was ferrous sulfate 325 milligrams daily. She had no known drug or environmental allergies. On physical exam, the patient was alert and in no acute distress but appeared tired. She was able to stand unassisted. At the time of triage, she was afebrile , her heart rate was 40 beats per minute, she was breathing 20 times per minute, her blood pressure was 115/90 millimeters of mercury, and she had an oxygen saturation of 98% on room air. She weighed 77.3 kilograms and was 1.65 meters tall . She was well developed, well nourished and speaking in complete sentences without accessory muscle use. She was oriented as to person, place and time. She was without sensory deficits and had normal muscle tone. Her strength was 4/5 with elbow flexion and extension, hand grip, knee flexion and extension, and ankle dorsi- and plantar-flexion bilaterally. Deep tendon reflexes were 2+ for the bilateral brachioradialis and patellar reflexes.

No clonus could be provoked. She did not have any cranial nerve defects, and she had a normal gait and station. She had normal range of motion of all four extremities, and she did not have any edema. Her lower extremity compartments were soft in both the thighs and the lower legs bilaterally. She exhibited tenderness around her bilateral shoulders and shins. Her head was normocephalic and without signs of injury. Her oropharynx was clear and moist, and her pupils were equal, round, and reactive to light. Her conjunctiva and extraocular motions were normal. Her neck was supple and had a full range of motion, without jugular venous distention or adenopathy. On cardiovascular exam the patient was bradycardic with a regular rhythm, and she had a normal S1/S2 without gallops, friction rubs, or murmurs. On auscultation her breath sounds were clear without wheezes, rales or rhonchi. Her abdomen was non-distended, soft and non-tender throughout with normal bowel sounds. Her skin was warm and dry, and her capillary refill was less than two seconds. She did not have any rashes. Her mood, affect, and behavior were normal. The patient’s electrocardiogram is shown . The results of the patient’s initial laboratory evaluation are shown in Table 1. A test was ordered, and a diagnosis was made.This case involved a young woman with episodic weakness. She reported near syncope, transient extremity paralysis, and generalized weakness. She reported associated nausea, abdominal pain, and constipation. She also reported regular substance use in the form of marijuana and alcohol. Her review of systems was otherwise unremarkable, and notably it was negative for recent illness or gastrointestinal distress outside of this episode. With this in mind, I began to formulate a differential diagnosis. Episodic weakness, particularly extremity paralysis,rack of clones suggests metabolic and electrolyte derangements such as hypokalemic periodic paralysis. Weakness may also suggest a primary neurologic condition, including Guillain-Barré syndrome, multiple sclerosis, and other demyelinating disorders. The patient’s near syncope may be due to orthostatic hypotension or neurocardiogenic causes. Her GI symptoms could be due to a broad array of abdominal conditions, but her substance use suggests these symptoms may be related to an ingestion. The patient’s bradycardia could be due to disseminated Lyme disease, myocarditis, or other etiologies of heart block. More information is required. I used the information provided by her physical exam to further refine my differential diagnosis. Her physical exam was notable for a tired-appearing female with bradycardia. Pertinent negative findings included that the compartments of the legs were noted to be soft, clinically excluding a compartment syndrome. Additionally, the patient had no focal neurologic deficits based on the documented neurologic exam. Several findings, including cerebellar signs were not documented, but the patient was noted to have normal gait and station. Further, the case did not provide any imaging studies – notably, there was no neuroimaging included.

The patient’s ECG showed a sinus bradycardia with sinus arrhythmia, short QTc with T-wave inversions in aVR and V1, and U waves, but it did not show a heart block. I then reviewed the patient’s laboratory findings. She was noted to have a mild anemia, elevated creatine kinase with myoglobinuria, hematuria, proteinuria, and urinary findings consistent with a urinary tract infection. Additionally, she has multiple electrolyte derangements, including hypokalemia, hyperchloremia with acidosis, hypermagnesemia and hypophosphatemia. She had an elevated creatinine and a mild transaminitis. These laboratory findings suggest her symptoms are due to a metabolic derangement. This patient had a non-anion gap metabolic acidosis. The differential diagnosis for non-anion gap metabolic acidosis includes diarrhea, intestinal fistulae, renal tubular acidosis , ureteroileostomy, ureterosigmoidostomy, toluene use, ketoacidosis, D-lactic acidosis, and administration of chloriderich solutions. After cross-referencing this with the case details, some of these diagnoses can be eliminated based on the history, exam, and review of systems. Specifically, the patient reported constipation, thereby eliminating diarrhea as a cause. She also had no surgical history, hence eliminating ureteroileostomy and ureterosigmoidostomy as causes. Although her diet is not mentioned, there is no reported history of abnormal ingestion of food or fluids; so I reasonably eliminated chloride-rich solution ingestion as a cause. This left proximal and distal RTA, toluene use, ketoacidosis, and D-lactic acidosis as diagnoses under consideration. When cross-referencing these with the case details and laboratory findings once again, some options were not consistent with the presentation. Specifically, there was no ketonuria making ketoacidosis unlikely. Lactic acidosis is a result of a hypoperfusion state, and the clinical case did not provide any evidence of hypoperfusion making this unlikely as well. There were some additional laboratory findings outside of the metabolic panel that needed to be considered. Namely, the patient’s hemoglobin and hematocrit were slightly abnormal . Also, she had an elevated creatine kinase and myoglobin as well as slight elevation in her aspartate transaminase. Her urine also showed some hematuria, pyuria, and proteinuria as well as findings of nitrites and leukocyte esterase. When these labs are considered in conjunction with the metabolic abnormalities, my differential diagnosis now included hypokalemic periodic paralysis, rhabdomyolysis, adrenal insufficiency, proximal and distal RTA, inflammatory myopathy, and poisoning . Adrenal insufficiency can cause metabolic derangements and presents with symptoms including fatigue, weight loss, GI complaints, and myalgias, and may also include psychiatric symptoms. In primary adrenal insufficiency, the potassium is high and sodium is low, which is not consistent with this case. In secondary or tertiary adrenal insufficiency, potassium is normal or low, sodium can be high or low, and chloride is normal with a low glucose.These are not consistent with the findings in this case either; so I eliminated adrenal insufficiency from my differential diagnosis. Inflammatory myopathies present with muscle weakness, cardiac involvement, and laboratory findings including elevated serum creatinine kinase and elevated myoglobin levels in both urine and serum. These patients usually present with acute onset of “antisynthetase syndrome,” constitutional symptoms, Raynaud’s phenomenon, and a nonerosive arthritis.While the laboratory findings here were consistent with a possible myopathy, the clinical presentation was not classic, making this a less likely possibility. Another consideration was rhabdomyolysis potentially resulting from compartment syndrome. Compartment syndrome occurs from increased fascial compartment pressure with subsequent tissue hypoperfusion, which can lead to muscle necrosis and rhabdomyolysis.

A response button that could register a mouse click was underneath each of the two boxes

The task consisted of 20 discrete choices between a smaller immediate reward presented in a box on the left side of the screen and an 80¢ delay reward presented in a box on the right side of the screen . At the top center of the screen was a box displaying total earnings on the task. On any trial, if the smaller sooner reward was selected with a single mouse click, the response options disappeared and a button appeared that stated “Click here to bank your amount.” Upon a single mouse click on this button, that amount was dispensed from the coin dispenser, and the total earnings box was updated. If the delayed 80¢ was selected, the response options disappeared and a number in the middle of screen counted down the number of seconds to wait . When the delay elapsed, a button appeared that required the participant to click to “bank” the 80 cents, at which point the coins were delivered and the total earnings were updated. When money was delivered, participants removed the coins from the dispensing tray and dropped them into a glass jar. There were 5 blocks of 4 trials each, with each block associated with a different delay for the 80 cent reward. The delays were 5, 10, 20, 40, and 80 s, and followed an increasing order across blocks. On the first trial of each block, the immediate reward size was 40¢ . The smaller reward was then adjusted within the block using a “decreasing adjustment” algorithm, which has been used in previous human studies involving hypothetical rewards . Specifically, the smaller sooner reward was adjusted by 20, 10, and 5¢ on Trials 2, 3, and 4 of the block, respectively, in the direction that would move choice toward indifference . The indifference point was defined as the value that would have been presented on a 5th trial had the algorithm continued . Indifference points therefore varied by increments of 2.5¢,vertical grow rack and were divided by 80¢ to be expressed as the proportion of the larger reinforcer. Indifference points were expressed as a proportion of the larger later reward .

A waiting period was imposed after the final trial to prevent participants from choosing the smaller immediate reward to end the task or session sooner . Participants were told before beginning the task that the total duration of the task would be independent of the choices made during the task, although participants were not explicitly told about the waiting period at the end of the task that was responsible for ensuring approximately equal task duration. The waiting period was defined as 660 s minus the sum of all larger reward delays that the participant experienced throughout the task. Although this manipulation ensured that total programmed waiting time did not substantially differ across participants, differences in participant response latency nonetheless allowed for some variability in total task time. At the end of the task, participants exchanged whole dollar amounts of coins for paper currency.The schizophrenia and control groups had qualitatively similar DD functions, but quantitatively, the schizophrenia group showed a significantly greater DD than controls on the experiential task, and normal DD on the hypothetical task. The schizophrenia group’s performance on the DD tasks was generally not associated with a range of potential confounds. In addition, test-retest reliability was examined for the schizophrenia group and was good on both tasks. These findings provide the first evidence of impaired DD in schizophrenia using an experiential paradigm that parallels tasks used in animal research much more closely than conventional human paradigms. While not all aspects of reward processing are impaired in schizophrenia , these findings suggest alterations do extend to a delay discounting context that involves real rewards and real delay periods. As described below, the schizophrenia group’s pattern of altered experiential and normal hypothetical DD likely reflects the fact the these tasks differed on several key dimensions, including reward type , reward magnitude , and delay time frame . Regarding qualitative analyses, the shape and orderliness of the DD data were generally similar across groups. In line with a prior report , the schizophrenia group showed typical hyperbolic discounting functions across tasks. Further, a large majority demonstrated orderly data for both DD tasks. The proportion with less-orderly data on the hypothetical, though not the experiential, task was significantly larger than controls.

However, the main study findings were unchanged after removing the subset of participants from both groups with less-orderly data. In this first study of experiential DD in schizophrenia, the schizophrenia group showed quantitatively greater discounting than controls for actual monetary rewards delivered in real time. Diminished discounting on this and similar experiential tasks has been reported in other clinical populations, including cocaine dependence, ADHD, and smokers . Experiential tasks appear to tap into a rather different aspect of DD than hypothetical tasks. For example, the correlation between hypothetical and experiential DD tasks was relatively small in both groups. Several studies have also reported relatively low convergence between these tasks and one found altered experiential but not hypothetical discounting in ADHD . There were no quantitative group differences for the hypothetical DD task and this study included the largest schizophrenia and control samples examined to date. Our finding on this task is consistent with two prior studies , but inconsistent with four others that found greater hypothetical DD in schizophrenia . The rather substantial methodological differences across the few DD studies make it difficult to pinpoint why three studies found normal DD but four did not. Since all prior studies included chronically ill samples, and all except one examined outpatients, the discrepancies across studies are not attributable to these participant characteristics. However, the tasks and data analytic approaches varied widely. For example, across the seven studies, the maximum delayed reward magnitude ranged from $86 to $1000, and the maximum delayed reward duration ranged from a few months up to 50 years. Further research will want to systematically assess the impact of these parameters on hypothetical DD in schizophrenia. For example, it could be informative to examine how individuals with schizophrenia perform on a hypothetical task with reward magnitudes and delay intervals that correspond to those in the experiential task. The current study considered a wide range of potentially confounding factors on DD and found that their impact was small. The only relevant factor was smoking status.

Smokers showed greater hypothetical DD than non-smokers, which converges with prior findings from the general population and schizophrenia . However, we still found the pattern of altered experiential and normal hypothetical DD in schizophrenia when we limited our analyses to non-smokers. There were no significant associations between DD and other substances, symptoms, or anti-psychotic medication dosages. Given the conceptual link between reward processing and negative symptoms , it is somewhat puzzling that alterations in DD, particularly on the experiential task, did not significantly correlate with higher clinically rated negative symptoms. Although some studies have found that neuroscience-based reward and decision making tasks are associated with negative symptoms a number of studies by our group and others failed to detect such relationships . The reason for these discrepancies is not year clear. We have suggested that there are complex intervening steps on the causal pathway between the relatively discrete processes measured by decision-making tasks and the broad aspects of experience and behavior that are captured by clinical rating scales,cannabis grow racks which may substantially diminish direct correlations . DD also showed no significant associations with global or particular domains of neurocognition. This does not support prior suggestions that DD disturbances in schizophrenia reflect problems in the representation and maintenance of reward value . The schizophrenia group’s pattern of altered experiential but normal hypothetical DD was also not attributable to differences in the test-retest reliabilities of the tasks. The test-retest correlations of approximately .70 for both tasks are similar to prior reports in healthy samples and the group means showed good stability across occasions. These findings, in conjunction with the lack of associations with symptoms, suggest the DD tasks are measuring relatively stable traits among individuals with schizophrenia. These properties support the use of the experiential DD task as a performance measure of decision-making impairment in clinical trials for schizophrenia . Its potential usefulness for clinical trials is bolstered by evidence that it is sensitive to state-related changes, such as sleep deprivation, dopamine agonist administration in Parkinson’s disease, alcohol administration, and methylphenidate administration in ADHD . One might have expected the schizophrenia group to show greater difficulties for hypothetical, distant rewards in light impaired abstract thinking and longer-term prospection associated with this disorder . However, the pattern found in the current study may relate to participant and task characteristics. Regarding participant characteristics, since schizophrenia is associated with decreased SES and many in the schizophrenia group were receiving limited fixed incomes, the schizophrenia group may have valued immediately available, real rewards more than controls. This possibility is bolstered by our finding that the schizophrenia group assigned higher value ratings than controls for the lowest value but similar ratings for the highest value on the subjective valuation of money index, and with previous research showing greater discounting in lower income adults . Although individual differences in subjective valuation ratings did not significantly correlate with performance on the DD tasks, this factor remains a possible contributor . Regarding task characteristics, Paglieri postulated key differences between hypothetical tasks and experiential tasks, beyond reward magnitude and delay length.

Whereas hypothetical tasks merely involve postponing receipt of a reward with no constraints on how subjects spend their time during the intervening delay, the waiting period in experiential tasks comes with associated costs. These include direct costs, such as boredom or discomfort, and opportunity costs, such as valuable activities that the participant could be engaged in if not forced to wait. The relevance of such costs was demonstrated in a recent study that found DD rates increased as an orderly function of the constraints on what people could do during the delay interval on a hypothetical task . Perhaps the individuals with schizophrenia in our study were hyper-responsive to the associated costs of doing nothing in the delay period and experienced alterations in their cost/benefit calculations. For example, schizophrenia is associated with an elevated tendency to experience negative affect/arousal and boredom , as well as altered decision-making on tasks that involve weighing the relative effort expenditure costs against monetary rewards . Studies that manipulate the constraints, or obtain subjective ratings/ psychophysiological measures, during delay intervals could shed light on the possible impact of these costs in DD in schizophrenia. Strengths of the current study include the large clinical sample, use of two different types of DD tasks, rigorous evaluation of data integrity, examination of many potential confounds, and evaluation of test-retest reliability. However, the study has some limitations and highlights areas in need of further study. First, participants with schizophrenia were taking medications at clinical dosages. Although dosage equivalents were not related to DD, the impact of medications remains unclear. Second, the schizophrenia sample was chronically ill and it is unknown whether similar DD patterns would be evident in younger or high-risk samples. Third, the order of delay discounting task administration was not counterbalanced, so we are unable to examine potential order effects. Fourth, although performance on the tasks was not related to subjective valuation of money, we did not obtain objective measures to evaluate whether income or socio-economic status was associated with DD task performance. Fifth, this study only assessed monetary rewards and it is unknown whether similar patterns would be found for other primary or secondary reinforcers. Sixth, although the schizophrenia group showed normal performance on the hypothetical DD task, we cannot tell if the normal choice patterns were achieved through abnormal neural processes. For example, a small fMRI study reported that individuals with schizophrenia showed an abnormal hypo-activation in some regions and hyper-activation in others while making DD decisions . Further attention to these issues can help clarify the nature of impaired reward processing and decision-making in schizophrenia. General Scientific Summary: Delay discounting refers to whether one is willing to forego a smaller, sooner reward for the sake of a larger, later reward. This study found that people with schizophrenia showed a greater preference for smaller, sooner rewards than healthy comparison participants on a DD task that involved making choices about actual monetary rewards provided in real time.

Various explanations can be offered as to why the results for nicotine dependence severity were non-significant

After the medication period, participants who were eligible for the MRI session were selected at random, given an additional three days of medication, and scanned within those three days. To our knowledge, no studies to date have tested the effects of varenicline and naltrexone on structural MRI measures; however, to ensure that there were no significant gray matter differences between the medication groups, we conducted a whole-brain one-way between-subjects ANOVA . A total of 40 subjects participated in the neuroimaging study. The Institutional Review Board of University of California, Los Angeles, approved all procedures for the study. Participants were administered the Alcohol Dependence Scale , the FTND, and the 30-day Timeline Follow-back . The ADS is a 25-item self-report measure that identifies elements of alcohol dependence severity over the past 12 months, such as withdrawal symptoms and impaired control over alcohol use on a scored scale with a range of zero to 47. The FTND is a six-item self-report measure that captures features of nicotine dependence severity on a scored scale of zero to 10, and questions on this measure are not confined to a specific time frame of substance use. The TLFB assessed the daily amount of alcoholic drinks and cigarettes participants consumed in the past 30 days before the scan, from which mean drinks/drinking day and cigarettes/day were calculated. Previous research has indicated that gray matter tissue can regenerate within 14 days of alcohol abstinence in alcohol dependent patients and that gray matter regeneration is most profound within the first week to month of abstinence . Given these findings, we examined whether days to last drinking day before the imaging session correlated with gray matter density at the whole-brain level. Days to last drinking day was computed for each participant based on the TLFB information collected at the time of image acquisition. The analysis conducted included days to last drinking day as a predictor variable and age, gender, ICV, and ADS scores as covariates of interest.

Furthermore,indoor grow shelves to understand whether any of the effects were related to cannabis use within the current sample, we examined the relationship between frequency of cannabis use and drinking and nicotine variables using nonparametric Spearman’s correlations. Cannabis use was assessed using a single-item categorical question asking, “On average, how often do you smoke marijuana?”The purpose of the present study was to examine the relationship between quantity of alcohol/nicotine use and alcohol/nicotine dependence severity with gray matter density in heavy drinking smokers. Previous studies have focused primarily on alcohol users but have not excluded participants for nicotine use . Similarly, some prior studies that examined nicotine users did not establish exclusionary criteria based on alcohol use . These studies make it difficult to ascertain whether alcohol or nicotine use/dependence account for previous findings, as their individual contributions to gray matter structure or brain activity were not examined. Thus, it is critical to investigate the unique contributions of alcohol and nicotine use to brain morphometry in heavy drinking smokers. We hypothesized that there would be gray matter reductions in areas such as the ACC, dorsal striatum, and insula. Multiple regression analyses revealed that ADS scores significantly predicted gray matter density in the hypothalamus and right superior frontal gyrus and thus, the results differed from our initial hypotheses. Contrary to our expectations, there were no significant relationships with respect to quantity of alcohol use or nicotine dependence and quantity of cigarette use variables. The hypothalamus is part of the hypothalamic-pituitary-adrenal axis, which has been consistently shown to be dysregulated in individuals with AUD . HPA-axis dysregulation in alcohol-dependent individuals is marked by elevated blood glucocorticoid levels , which is associated with impairments in various brain regions, such as the prefrontal cortex, hippocampus, and the mesolimbic reward pathway . Impairments in these regions can lead to utilization of habit-based forms of learning or memory over goaldirected forms and profound cognitive memory impairments .

The current findings indicating ADS was negatively related to hypothalamic volume in heavy drinking smokers may suggest alterations in hypothalamic gray matter density that could be associated with changes in HPA-axis functioning and related cognitive impairments. Studies that integrate measures of gray matter density, cognitive functioning and markers of HPA-axis functioning in heavy drinking smokers are needed to clarify these associations. Moreover, several studies have linked hypothalamic gray matter degradation to the presence of Korsakoff Syndrome . These findings suggest that the development of Korsakoff Syndrome may exist on a spectrum, with hypothalamic gray matter atrophy acting as a relevant biomarker. Thus, our findings support the notion that alcohol dependence severity is related to gray matter degradation observed in the progression of uncomplicated alcoholism to Korsakoff syndrome. However, in a recent study of almost 3,000 Dutch nationals, it was demonstrated that alcohol use was associated with dysregulation in the HPA-axis system while alcohol dependence status was not . Given these contrasting findings from our study, it is necessary to further explore the respective contributions of alcohol use and dependence to the dysregulation of the HPA-axis system. The finding that higher ADS scores were negatively related to gray matter density in the superior frontal gyrus is supported by numerous previous studies indicating lower frontal gray matter density in alcohol users . In a review paper discussing the construct of impulsivity, areas of the PFC, such as the ventromedial and dorsolateral PFC, were posited to be involved in the neural circuitry of delay-related decision making and inhibitory control . Broadly speaking, it is possible that gray matter degradation in the frontal cortex is related to behavioral inhibition and decision making deficits in alcohol dependence , but further research is needed to shed light on how specific features of impulsivity relate to the gray matter atrophy observed in AUD.not excluded participants for nicotine use . Similarly, some prior studies that examined nicotine users did not establish exclusionary criteria based on alcohol use . These studies make it difficult to ascertain whether alcohol or nicotine use/dependence account for previous findings, as their individual contributions to gray matter structure or brain activity were not examined. Thus, it is critical to investigate the unique contributions of alcohol and nicotine use to brain morphometry in heavy drinking smokers.

We hypothesized that there would be gray matter reductions in areas such as the ACC, dorsal striatum, and insula. Multiple regression analyses revealed that ADS scores significantly predicted gray matter density in the hypothalamus and right superior frontal gyrus and thus, the results differed from our initial hypotheses. Contrary to our expectations, there were no significant relationships with respect to quantity of alcohol use or nicotine dependence and quantity of cigarette use variables. The hypothalamus is part of the hypothalamic-pituitary-adrenal axis, which has been consistently shown to be dysregulated in individuals with AUD . HPA-axis dysregulation in alcohol-dependent individuals is marked by elevated blood glucocorticoid levels , which is associated with impairments in various brain regions, such as the prefrontal cortex, hippocampus, and the mesolimbic reward pathway . Impairments in these regions can lead to utilization of habit-based forms of learning or memory over goaldirected forms and profound cognitive memory impairments . The current findings indicating ADS was negatively related to hypothalamic volume in heavy drinking smokers may suggest alterations in hypothalamic gray matter density that could be associated with changes in HPA-axis functioning and related cognitive impairments. Studies that integrate measures of gray matter density,planting growing rack cognitive functioning and markers of HPA-axis functioning in heavy drinking smokers are needed to clarify these associations. Moreover, several studies have linked hypothalamic gray matter degradation to the presence of Korsakoff Syndrome . These findings suggest that the development of Korsakoff Syndrome may exist on a spectrum, with hypothalamic gray matter atrophy acting as a relevant biomarker. Thus, our findings support the notion that alcohol dependence severity is related to gray matter degradation observed in the progression of uncomplicated alcoholism to Korsakoff syndrome. However, in a recent study of almost 3,000 Dutch nationals, it was demonstrated that alcohol use was associated with dysregulation in the HPA-axis system while alcohol dependence status was not . Given these contrasting findings from our study, it is necessary to further explore the respective contributions of alcohol use and dependence to the dysregulation of the HPA-axis system. The finding that higher ADS scores were negatively related to gray matter density in the superior frontal gyrus is supported by numerous previous studies indicating lower frontal gray matter density in alcohol users . In a review paper discussing the construct of impulsivity, areas of the PFC, such as the ventromedial and dorsolateral PFC, were posited to be involved in the neural circuitry of delay-related decision making and inhibitory control . Broadly speaking, it is possible that gray matter degradation in the frontal cortex is related to behavioral inhibition and decision making deficits in alcohol dependence , but further research is needed to shed light on how specific features of impulsivity relate to the gray matter atrophy observed in AUD.The FTND has fewer items than the ADS, so it is possible that lower variance of FTND scores made it difficult to detect relationships with gray matter density. It is also possible that nicotine dependence severity is not related to gray matter structure in the brain to the same extent as alcohol dependence severity. While several regions, such as the ACC, left dorsal striatum/insula, right dorsal striatum/insula, and the posterior cingulate cortex were identified as exhibiting gray matter atrophy in a meta-analysis of alcohol dependent individuals , a meta-analysis of chronic cigarette smokers only found the left ACC to show gray matter atrophy across several studies . The discrepancy may suggest differences between the two substances with respect to biological manifestations in the brain. However, previous studies found that smoking alcohol dependent individuals had significantly decreased cortical thickness in the insula and ACC when compared to nonsmoking alcohol dependent individuals .

Additionally, heavy drinking smokers were found to have significantly smaller temporal lobe and total gray matter volumes when compared to non-smoking heavy drinkers . Dissimilar to those studies, quantity of nicotine use or dependence severity were not found to significantly contribute to gray matter density in the current study. Given that Durazzo, Mon, Gazdzinski, and Meyerhoff included a sample with an average FTND score of 5.4 and participants who smoked an average of 20 cigarettes per day, while the present sample had an average FTND score of 3.69 and participants smoked an average of 14.56 cigarettes per day, it is possible that differences in nicotine dependence severity and quantity of use between the current and previous studies explain the discrepant findings. Previous research has found significant gray matter reduction in recovering alcohol users immediately before undergoing detoxification . This effect is ameliorated in abstaining light drinkers and abstaining recovering alcoholics versus relapsing recovering alcoholics . These findings support the notion that gray matter degradation effects could be attributable to the length of time between the last day an individual consumed alcohol and when he/she was scanned. The significant positive correlation between days to last drinking day and gray matter density in the left postcentral gyrus is consistent with the hypothesis that alcohol may cause dehydration and thus, volumetric reductions in the brain that are, in turn, ameliorated with short-term cessation of alcohol use. However, given that days to last drinking day was not related to gray matter density in the regions related to alcohol dependence severity, it is unlikely that recent alcohol use affected the current results. While our findings demonstrate the unique contribution of alcohol dependence severity to gray matter density in heavy drinking smokers, there are various limitations that should be noted. First, there was no matched control group to the comorbid users in this study. Although the multiple regression approach permits the investigation of specific contributions of alcohol and nicotine dependence and quantity of use to gray matter density, a control group would help ascertain whether the regions identified as significantly relating to alcohol dependence severity also differ in gray matter density from healthy controls. Second, the dependence severity and quantity of use measures did not encompass the exact same time frame, which may have resulted in relationships detected for dependence severity and gray matter density, but not quantity of use and gray matter density.

Health service utilization was also significantly greater among OUDs than among nonOUDs

As is noted in Table 5, the demographic variables significantly differentiate OUDs from non-OUDs, though the effect sizes for these variables are quite small. Diagnostic data, particularly variables of barbiturate abuse/dependence, unspecified drug abuse/dependence, and poly substance drug dependence had strong effect sizes in differentiating OUDs from non-OUDs. The amount of short-acting opioid, measured in morphine equivalent units, dispensed was a better predictor than the amount of long-acting opioid. It should be noted that the magnitude and the directionality of the odds ratios in Table 5 differ from the bivariate comparisons in Table 3; in modeling multiple variables simultaneously, bivariate relationships are subject to change. Finally, ten interactions remained in this model, primarily involving the aforementioned variables of short-acting opioids dispensed, unspecified drug dependence, poly substance dependence, and barbiturate dependence. Participant age, inpatient mental health admissions, and mental health inpatient days were also present in the significant interaction variables.The detection of opioid misuse is an important step in addressing the public health problems of prescription drug abuse, dependence, diversion, and overdose. Although previous studies have identified some of the factors that place individuals at greater risk for misuse of opioids, this investigation benefits from a comprehensive database that has illuminated more differences between those who develop opioid use disorders and those who receive an initial prescription but do not develop a diagnosis of opioid dependence or abuse. Additionally, this study may be useful in providing health plans with a method for monitoring claims data that may assist in detecting members who are at risk for substance misuse, potentially providing relevant feedback to medical providers. The current study replicates the findings of previous studies that being male and younger are associated with increased risk of becoming an OUD; an additional significant difference captured in this dataset is that those who were OUDs are less likely to be the primary insured individual,shelf grow light and are more likely to be a dependent or spouse/partner of the primary insured. OUDs significantly differed from non-OUDs in a number of other areas, as well.

The prescription patterns for opioids were quite different between these groups, with OUDs receiving a larger supply of opioids, paying a significantly higher copayment for opioids, and receiving more short-acting opioids than non-OUDs. The directionality of this relationship is unclear from this study; it is possible that particular prescribing patterns place individuals at greater risk for developing a problem with opioids, but it is also possible that OUDs are more likely to request short-acting, and a greater number of, medications from a health care provider. This finding was present among inpatient and outpatient clinics, emergency department, general medical care, and mental health specialty care visits. As with the relationship between opioid prescribing and misuse, the directionality of this relationship is also unclear. OUDs are likely to be at risk for other health problems that may co-occur with their opioid misuse; depression, anxiety, infections, metabolic difficulties, and injuries are all possible correlates of opioid misuse. Conversely, individuals who have other health problems may start to use opioids, and to misuse them, as a means of coping with their difficulties, such as chronic pain or mental health difficulties. The patterns of medication usage help to clarify, to some extent, the differences between OUDs and non-OUDs. OUDs are more likely to be receiving treatment for anxiety, depression, chronic pain, and many other conditions than non-OUDs. The mathematical modeling of opioid misuse, and the resultant predictors of misuse that were identified in the final model, underscore the relationship between mental health, other substance misuse, and opioid abuse/dependence. It is noteworthy that of the different models that were tested to identify OUDs, diagnostic and mental health care variables rose to be among the most robust predictors. This finding has implications for future research and practice. In settings that serve individuals at high risk for opioid misuse, collecting data on co-occurring mental health conditions, mental health treatment history, and psychotropic medication usage is imperative in identifying those who may be at risk for developing an opioid use disorder. Those identified as at-risk may benefit from indicated prevention programs that educate individuals about signs of prescription drug misuse and the relationship between opioid use and mental health conditions.

Treating co-occurring mental health difficulties is an important part of addressing the health of individuals who are prescribed opioids. Variables that significantly predicted OUDs must, in some cases, be interpreted within the context of significant interactions that were identified through CHAID analysis. Due to the atheoretical nature of CHAID analysis, the significant interactions were not anticipated prior to the analytic process; however, several variables frequently appeared in the significant interaction terms. Implications of these interactions include, for example, the finding that the impact of receiving short-acting opioids depends on co-occurring substance use diagnoses when predicting OUDs. These interactions may be of clinical utility in identifying individuals, through data readily available to health plans, who are at risk for OUDs and may benefit from prevention efforts. The model developed in this study was designed for use in the entire population of patients in the database, regardless of where they live. Given the significant regional differences in the distribution of diagnosed OUDs, future studies should test the model at the regional level to determine whether location impacts model performance. This investigation has a number of limitations that prevent broader conclusions from being drawn about opioid abuse and dependence. The key limitations are the use of an existing data set and the reliance on a physician’s diagnosis of abuse and dependence. Many individuals may develop an opioid use disorder that does not come to the attention of their physician. Those who have a diagnosis of abuse or dependence may represent an unusual opioid using population, in that they may have either talked with their physician directly about a potential problem or have such florid difficulties with misuse that it is evident to their health care provider or providers. The operationalization of cooccurring mental health and other substance use disorders as any lifetime diagnosis is also a limitation of this study, as important temporal relationships between opioid misuse and other mental health problems cannot be established. Given the possible bidirectional development of such difficulties, the research team did not specify a priori any time frame for co-occurring disorders, though such analysis could be an important line of future research in this area.

The primary strengths of this study are the large sample size, the comprehensive number of variables regarding study participants, and the use of claims data, the likes of which may be generally available to health plans for use in their own risk stratification and intervention. Those interested in the prediction of opioid misuse may not have all of the significant variables present in their data sets, and thus may not be able to directly apply the particular mathematical model created here. To summarize, the detection of opioid misuse has important implications for public health; better identification of individuals at risk may help to reduce morbidity and mortality that is often associated with opioid use disorders. The current study made use of a large, comprehensive data set that may aid researchers and clinicians in their attempts to address this important issue. For decades it was believed that the effects of the main active ingredient in cannabis, delta-9-tetrahydrocannabinol ,hydroponic shelf were due to alterations of cellular membrane structure. However, in the late 1980s, due to the availability of new synthetic CB receptor agonists, it was first suggested that specific CB receptors exist . Soon after, the first CB receptor was sequenced and cloned . This receptor, named CB1, is highly expressed in the brain and mediates most, if not all, of the psychoactive/central effects of cannabis. A short time later, a second CB receptor, named CB2, was discovered . Until recently it was thought that CB2 receptors were present only in the periphery and did not mediate any central effect of CBs, but recent findings suggest that CB2 receptors are present at low levels in some areas of the brain . On the basis of studies showing certain behavioural and pharmacological effects of CB ligands that could not be explained exclusively by CB1 and CB2 receptors, it has also been hypothesized that additional non-CB1 and non-CB2 receptors might exist . The potential involvement of CB2 and non-CB1 and non-CB2 receptors in central effects of CBs needs further investigation and is not discussed in the present review. CB1 receptors are the most abundant G-protein-coupled receptors found in the brain . They are metabotropic receptors coupled to Gi/o proteins, whose activation results in inhibition of adenylyl cyclase activity and in a consequent decrease in cytosolic cAMP content, closure of Ca2 þ channels, opening of K þ channels and stimulation of kinases that phosphorylate tyrosine, serine and threonine residues in proteins . CB1 receptors are localized preferentially at the presynaptic level and, thus, it is believed that they inhibit the release of glutamate, GABA and other neurotransmitters . The localization of CB1 receptors in the brain is consistent with the known central effects of CBs, with highest concentrations in areas involved in memory , motor coordination and emotionality .

In the dopaminergic mesolimbic system, the best known circuit involved in motivational processes , average to high concentrations of CB1 receptors are found in the terminal region, the striatum, whereas low concentrations of CB1 receptors are found in the origin, the ventral tegmental area . These relatively low concentrations in the VTA do not necessarily indicate that CBs do not have important actions in this area. Several lines of evidence indicate that CB1 receptor agonists have strong modulating effects on VTA neuron activity and that CBs can produce rewarding effects when directly injected into this structure . It should be noted that anandamide, along with a variety of other lipids, can also activate transient receptor potential vanilloid type 1 vanilloid receptors . However, the role of these receptor channels in the behavioural and neurochemical effects of anandamide in brain reward processes remains largely undefined .In the early 1990s, anandamide and 2-arachidonoylglycerol  were discovered and characterized as the first endogenous ligands for CB receptors. Subsequently, other possible endocannabinoids have been proposed, such as noladin ether , virodhamine and arachidonoyldopamine , but their natural occurrence and their roles are still unclear. Anandamide and 2-AG have different structures, different biosynthesis and degradation pathways and, in addition, appear to be formed under different conditions and to be differently affected by several manipulations, including pharmacological stimulation, as reviewed elsewhere . In addition, a recent paper has shown that anandamide inhibits the metabolism and the effects of 2-AG levels in the stiratum . Thus, it has been proposed that anandamide and 2-AG might play different roles in physiological and pathophysiological conditions . A peculiarity of the endocannabinoids, which makes them an interesting target for the discovery of new drugs, is that they are not present in vesicular stores but instead, are formed ‘on demand’ and undergo rapid metabolic deactivation, so that drugs that target this system would act predominantly when and where altered levels of endocannabinoids are present .CB1 receptors appear to play an important role in brain reward processes. One long-standing line of evidence for the role for CB1 receptors in brain reward processes is that CB1 receptor agonists, such as the active ingredient in cannabis, THC, have rewarding effects in humans and animals . The reinforcing effects of THC have been extensively reviewed elsewhere . Here, we focus on recent evidence for a modulatory role of endocannabinoids on the rewarding effects of drugs of abuse, food and electric brain stimulation.CB1 receptor agonists, such as THC, WIN 55,212-2 and HU-210, can facilitate the rewarding effects of drugs. For example, administration of THC or WIN 55,212-2 increases the reinforcing effects of heroin , nicotine and alcohol . Concerning psychostimulants, one study in rats has shown that administration of WIN 55,212-2 decreased self-administration of cocaine under a fixed-ratio schedule . However, as a decrease in the number of drug injections self-administered under a FR1 schedule can be interpreted either as a decrease or an increase in reinforcing efficacy , definitive conclusions cannot be drawn from these experiments.

Heavy drinkers also had more BOLD response compared to controls in the left VMPFC during anticipation

Relevant covariates thought to affect risk-taking performance and self-report of risk-taking were entered as covariates on Block 1 of the regression analyses. These included: age, family history of alcoholism, average # of alcoholic drinks per month, # of binge episodes in the prior 3 months, # of days/month of cannabis use in prior 3 months. BOLD response signal change variables for each ROI were entered on Block 2. The R 2 ∆ for the second step represented the degree to which BOLD activation was associated with baseline risk-taking performance or self-report of risk taking behavior, above and beyond the covariates listed in Step 1. There were a total of 28 tests run for Hypothesis 3 . Alpha was set at 0.05 for each test, as this was the first fMRI study of risk-taking in adolescent alcohol users and the analyses for Hypothesis 3 were considered exploratory. However, it should be noted that the probability of Type I error is increased due to the large number of tests that were run. The goals of this study were to use fMRI to: identify brain regions where neural activation associated with three separate stages of risky decision-making differed between heavy drinking adolescents and controls; examine whether neural activity associated with risky decision-making changed across a five-week period of abstinence and whether the trajectory of change over time differed for heavy drinkers vs. controls; and determine whether neural activation in regions showing baseline group differences during risky decision-making could predict differences in neuropsychological functioning , risk-taking performance, or self-report of risk taking behavior and impulsivity. Both ROI and whole-brain analyses were conducted to examine neural functioning in brain regions expected to activate during risky decision making as well as brain regions not implicated as fundamental, but which may still be relevant. With regard to group differences in neural activation patterns in ROIs at baseline ,grow systems for weed heavy drinkers showed less BOLD response relative to controls in the right insula during the anticipation phase of decision-making when previous balloon trials had popped.

Although it was originally hypothesized that heavy drinking adolescents would show increased activation in the insula during this stage of decision-making, the finding of reduced activation fits with previous investigations that suggest the insula is primarily involved in the experience of loss avoidance . With this interpretation, it may be that heavy drinkers were less concerned with avoiding further losses than controls, even when faced with a reminder of loss from the previous trial. During the experience of negative outcome evaluation , heavy drinkers showed increased activation in bilateral regions of the VMPFC compared to nondrinkers. This result is consistent with expectation given the widely replicated findings outlining the VMPFC as central to reward processing . Specifically, studies have suggested that the VMPFC is involved in encoding the reward value of a choice , with greater activation associated with appraisals of a higher valued item or result . While it was expected that heavy drinkers would show increased activation in the VMPFC relative to controls during evaluation of both “win” and “loss” outcomes, this effect was only observed during the evaluation of “loss” outcomes. Thus, it is possible that heavy drinkers and controls experience “winning” similarly; however, heavy drinkers may be less affected by negative outcomes, finding them more rewarding. This explanation is consistent with findings from Bogg and colleagues’ study, in which participants with greater recent alcohol consumption showed greater medial prefrontal cortex activity while experiencing outcomes achieved through riskier behavior . With regard to changes in BOLD activation during the stages of risky decision making across the five-week period of abstinence , findings were mixed. In brain regions where differences in BOLD activation were observed at baseline , no between-group differences were evident after two to three weeks of abstinence. This pattern of change was anticipated, though group differences were not expected to be non-significant until the third time point . However, the observed pattern is consistent with results of the preliminary study by Pulido and colleagues , in which baseline BOLD activation differences between heavy drinkers and controls to an alcohol cue reactivity task were non-existent in most brain regions after two to three weeks of abstinence. On the other hand, some surprising group differences in the trajectory of BOLD response to risky decision-making across the five-week abstinence period were seen.

Specifically, controls showed increasing activation over time in the right anterior cingulate during the pre-response assessment phase of decision-making, while heavy drinkers did not show changes over time in this region during this phase of decision-making. Instead, heavy drinkers showed increasing activation over time in the right ventromedial prefrontal cortex/anterior cingulate during the anticipation phase of decision-making, while controls did not show this change. The anterior cingulate has been linked with a variety of separate functions at different stages in the decision-making process. Specifically, during the pre-response assessment phase of decision-making, it has been shown to have a primary role in cognitive control processes such as error and performance monitoring . During anticipation of reward and reward evaluation, the anterior cingulate has also shown high reactivity, particularly when there is a higher degree of effort that must be undertaken to “earn” a reward . Other studies have suggested that, like the insula, the anterior cingulate is associated with loss aversion during the anticipation of risks, with greater activation observed as the probability of a negative outcome increases . Thus, increasing BOLD response in the anterior cingulate over time during the pre-response assessment phase may be indicative of learning, or an increased attention to cognitive strategies for optimal performance on the task as participants become increasingly comfortable with the task format. As controls showed this pattern but heavy drinkers did not, it is possible that heavy drinkers did not increase attention to cognitive strategies/performance monitoring over repeated assessments to the same degree as controls. Similarly, increased BOLD response in the VMPFC/anterior cingulate during the anticipation phase of decision-making may be indicative of increasing loss aversion or greater attention to the probability of loss with increasing abstinence. As the heavy drinkers showed this pattern but controls did not, this suggests that alcohol may alter brain functioning in regions responsible for aversion to loss which in turn, could contribute to greater risk taking; in addition, short-term abstinence may contribute to neural recovery in these regions. Other regions of the brain demonstrated main effects of group on BOLD response averaged across time points, indicating that some neural functioning differences between heavy drinkers and controls persisted across the abstinence period. Specifically, heavy drinkers had less BOLD response relative to controls in bilateral regions of the DLPFC during the pre-response assessment phase of the task , in the left insula during anticipation , and in the right VMPFC during anticipation .

The finding that heavy drinkers exhibited hyporeactivity relative to controls in the DLPFC during pre-response assessment is consistent with expectation as well as with previous studies indicating that adolescents engage the DLPFC to a lesser extent than do adults during risky decision-making . In addition,cannabis indoor grow system hypore activity in widespread brain regions during a risky decision-making task has been observed in a sample of adolescent males with substance use problems who had been abstinent from substances for at least 30 days. It is important to note that all adolescents in this sample had comorbid conduct disorder, so it is impossible to determine whether the observed neural abnormalities resulted from substance use, psychiatric factors, or both. The finding that heavy drinkers displayed decreased left insular activity averaged across time points during anticipation is consistent with between-group differences in baseline BOLD response observed in this study, where heavy drinkers showed decreased right insular activity during anticipation, when previous balloons had popped. However, it is interesting that differences in right insular activity did not persist across the abstinence period as is observed in the left insula. This may be because the left insular activity was observed after previous “winning” trials while the right insular activity was observed after previous “loss” trials . If insular activity represents a marker for loss aversion, it may be that loss aversion is triggered more quickly when the memory of loss is more salient. In other words, heavy drinkers may continue to be less averse to loss during anticipation of an uncertain outcome when the memory of a recent reward is more salient. The finding that heavy drinkers showed increased left VMPFC activity averaged across time points during anticipation is consistent with the idea that adolescent heavy alcohol users may pay greater attention to the potential rewarding properties of an uncertain outcome compared to nondrinkers. This interpretation also fits with the possibility that alcohol use may alter neural functioning patterns related to reward sensitivity, and that these alterations may persist for longer periods than do alterations related to loss aversion. However, the finding that controls had greater BOLD response than heavy drinkers averaged across time in the right VMPFC during anticipation is somewhat surprising as we might expect the opposite pattern. With regard to baseline BOLD response as a predictor of executive functioning, risk-taking task performance, and self-report of risk-taking and impulsive behavior , baseline BOLD response during risky decision-making was not associated with executive functioning performance or performance on the risk-taking task.

However, greater activation in the VMPFC during negative outcome evaluation was predictive of self-report of greater risk-taking in the naturalistic environment. This is consistent with other studies that have reported similar relationships between BOLD response and ratings of risk-taking in adolescents. For example, Galvan and colleagues found that BOLD response in the nucleus accumbens during a reward processing task was positively correlated with adolescents’ ratings of both the likelihood of engaging in risky behaviors in the near future and ratings of anticipated positive consequences as a result of such risky behavior. Nucleus accumbens activity was negatively correlated with ratings of anticipated negative consequences of risky behavior. Findings from the exploratory whole-brain analysis suggest that heavy drinkers and controls may show differential neural response to risky decision-making in regions not identified as ROIs. During the baseline anticipation phase, heavy drinkers showed less BOLD response than controls in the right middle frontal gyrus and left anterior cingulate . During the baseline outcome evaluation phase, heavy drinkers showed greater BOLD response than controls in bilateral middle temporal and cingulate gyrus, right supramarginal gyrus, inferior/medial/superior frontal, and precentral gyrus areas. These baseline group differences were not evident after two to three weeks of abstinence, except for the right middle frontal gyrus during anticipation, where BOLD response was greater for controls, averaged across time points. During the pre-response assessment phase of decision-making, controls showed greater BOLD response than heavy drinkers averaged across time points, in widespread regions including bilateral medial temporal, inferior parietal, inferior/middle/medial frontal, anterior cingulate, right thalamus, and right superior frontal areas. In contrast, during the anticipation phase, heavy drinkers showed more BOLD response relative to controls averaged across time points in bilateral cingulate cortices, middle/inferior frontal regions, and occipital areas. During outcome evaluation, heavy drinkers showed greater BOLD response relative to controls averaged across time points in bilateral inferior/middle/medial frontal, right inferior parietal, right superior temporal, left occipital, and left thalamic regions. Overall, results of the whole brain analysis provide evidence that there are other regions implicated in the stages of risky decision-making, which show neural functioning differences between heavy drinkers and controls. Some neural functioning differences in these areas appear to resolve after two to three weeks of abstinence, while others persist for at least 4+ weeks. Some limitations should be mentioned. First, among the heavy drinking adolescents, there was considerable variability in the reported length of abstinence from alcohol prior to entering the study. Although the ideal length of abstinence at study entrance was between 4-10 days, some subjects reported much longer periods of abstinence , while others reported shorter periods . Although the mean number of days of reported abstinence in the heavy drinking group was consistent with the ideal length of abstinence it is possible that the variability may have skewed the results.

A respiratory virus panel was collected from five patients and it was negative in all of them

Exclusion criteria were gastrointestinal and central nervous system manifestations without interstitial pulmonary involvement, ingestions of cannabinoids, duplicate visits, and if it was unclear whether vaping device was used or not. We used descriptive statistics to analyze the data. Median and interquartile range were calculated for continuous variables, and proportions were calculated with 95% confidence intervals for categorical variables. The study was approved by the Loma Linda University Institutional Review Board.We identified 16 encounters with the ICD-10 codes for EVALI during the one-year period. Using the exclusion criteria mentioned in the Methods section, we excluded seven patients. Four of these patients presented with CNS manifestations and vomiting without pulmonary involvement. In one patient, the history of vaping was unclear. One patient had ingested cannabinoids without vaping. Two encounters were excluded because they were duplicate visits. Of the seven patients included in the analysis, six were male. The median age was 16 years . The median weight in our series was 70 kilograms . The medians for vital signs recorded in the ED were the following: temperature of 100.2º Fahrenheit ; respiratory rate 24 breaths per minute ; oxygen saturation, 90% ; heart rate 130 beats per minute ; systolic blood pressure 128 millimeters of mercury ; and diastolic blood pressure 76 mm HG . Three patients had documented fever in the ED. The most common symptoms reported in our study were cough, shortness of breath, and vomiting, each occurring separately in five patients. Three patients presented with chest pain. Two patients presented with altered mental status in the form of unresponsiveness, with one patient requiring intubation. The other unresponsive patient, a 16-year-old male, returned to a normal mentation with bag-valve-mask ventilation and naloxone but required high-flow nasal cannula for shortness of breath. On physical examination, accessory muscle use was the most common finding, reported in four patients. Rales were appreciated in two patients,cannabis grow supplies while no patients were found to have wheezing . In our study, six patients presented with respiratory failure. Four required HFNC.

One patient was intubated; one patient required simple nasal cannula oxygen at two liters per minute; and one patient maintained normal oxygen saturations in room air during his ED visit and was discharged home. A brief clinical presentation, summary of findings on imaging, and type of respiratory support needed are summarized in Table 2. Five patients were admitted to the pediatric intensive care unit, and one patient was admitted to the normal pediatric unit. The median hospital length of stay was six days . All patients were discharged with no comorbidities or deaths reported. Six patients were treated with steroids. The median duration of treatment with steroids during admission and after discharge was nine days . Our patients had a variety of laboratory tests ordered. Most common were complete blood count, respiratory virus panel, respiratory cultures, and urine drug screen. All patients had a complete blood count, and the median for white cell count was 16 thousand cells per cubic millimeter .Respiratory cultures were collected from two patients and both resulted negative. A urine drug screen was performed for six patients and was positive for cannabinoids in all six . Three patients followed up at different intervals in the pulmonology clinic . Spirometry showed normal results in all three patients at that time. Case 1 followed up one week after discharge, at which time spirometry showed evidence of obstructive lung disease, which returned to normal at three-month follow-up visit. No repeat imaging was performed for that patient. Case 2 followed up six weeks after discharge with near-complete resolution of ground-glass appearance on repeat CT and normal spirometry. Case 4 followed up two weeks after discharge with improvement in lung opacities on repeat radiograph and normal spirometry. All three patients had received steroids for 10 days when they were originally diagnosed with EVALI. No follow-up data was available for the remaining four patients.EVALI was an emerging disease entity in 2019. In our case series, we describe adolescents diagnosed with EVALI and their clinical course in the ED and the hospital. In our study, the most common symptoms of cough, shortness of breath, and vomiting presented with an equal frequency of 71%. In a study by Layden et al, shortness of breath and cough was noticed in 85% of patients and vomiting in 61%; whereas, according to Belgaev et al, 90% of patients in their study presented with gastrointestinal and respiratory symptoms.

In a report by the CDC, 85% of the EVALI population had respiratory symptoms and 57% had GI symptoms.The results of our study are similar to previous literature in suggesting that respiratory and GI symptoms are common in patients with EVALI. According to Balgaev et al, 67% of patients had clinical and radiological improvement with residual findings on radiological and pulmonary function tests at time of followup.In our study, the three patients who had documented follow-up visits had normal spirometry without residual deficits. Only two of those patients had repeat imaging, and both showed improvement without residual abnormalities. E-cigarette liquids and aerosols have been shown to contain a variety of chemical constituents including flavors that can be cytotoxic to human pulmonary fibroblasts and stem cells.Exposure to heavy metals such as chromium, nickel, and lead has also been reported.None of our patients were tested for heavy metal exposure. Most of the delivery systems have nicotine in them, with one cartridge providing the nicotine equivalent to a pack of cigarettes.In addition to nicotine, e-cigarette devices can be used to deliver THC-based oils.According to Trivers et al, one-third of the adolescents who used e-cigarettes had used cannabinoids in their e-cigarettes.In our patients with EVALI, urinary drug screen was positive for cannabinoids in all patients. One caveat is that we do not know whether our patients used only THC-containing products or a combination of nicotine and THC-containing products. In our case series, the majority of patients presented with pulmonary disease requiring respiratory support and intensive care unit admission. None of these patients developed acute respiratory distress syndrome . We likely did not see this disease process due to our small sample size, as Layden et al reported ARDS development in several of their examined cases.In our series, we did not evaluate the pathologic pulmonary changes in different patients. In other case reports, different pathophysiologic patterns of pulmonary involvement, in the form of diffuse alveolar hemorrhage, exogenous lipoid pneumonia, acute eosinophilic pneumonia, or hypersensitivity pneumonitis have been identified.Although the mechanism of EVALI is not clearly understood, the CDC suggests the use of steroids for treatment.According to a series of patients in Illinois, 51% of those patients had improvement in symptoms after the administration of steroids.In another study, patients showed clinical and radiological improvement following the use of antibiotics and steroids.In our study, six patients received steroids and six patients received antibiotics; three of those patients followed up in clinics with normal spirometry. But this evidence is not sufficient to establish that use of steroids or antibiotics is beneficial in EVALI.

There are several limitations of our study. First, because it was a retrospective chart review we could not establish causation. Second,cannabis growing equipment all data may not have been recorded on all patients . We might have missed some if the ICD-10 codes were not correct on the chart. Only three had documented follow-up, so we don’t know whether the other four had any comorbidities after their hospitalization. Third, we had a small number of patients. Fourth, this was a single-center study; so results may not be generalizable to other hospitals with different patient demographics.A neurobiological model of risk-taking suggests that differential timing in the maturation of the brain networks associated with emotional processing and cognitive control may predispose adolescents to risky behavior, including alcohol and other substance use. Heavy alcohol use during adolescence has been shown to alter normative brain functioning, though it remains unknown whether alterations normalize with sustained abstinence or persist after cessation of use. The present study utilized fMRI to examine the effects of heavy alcohol use and short-term abstinence on adolescent neural functioning during a risky decision-making task. Heavy drinking adolescents and non-users completed three neuroimaging assessments, spaced two weeks apart . Adolescents abstained from alcohol and other substances for the duration of the study, confirmed through regular urinalysis screenings. During scanning, participants completed a modified Balloon Analog Risk Task to inflate balloons by entering a fixed number of “pumps”. Adolescents earned 1cent/pump unless the balloon popped according to a predetermined value; a higher pump number represented a riskier choice. Relevant neuroanatomical regions of interest were identified for each phase of decision making and between-group differences in blood oxygenated level dependent response were assessed at baseline. In addition, longitudinal analyses examined the main effects and interaction of Group and Time on BOLD response across the five-week period of abstinence.These differences were no longer evident at either follow-up time point. However, significant main effects of Group and interaction effects were observed in other regions. Overall, these findings highlight differential neural functioning during risky decision-making in heavy drinking adolescents and non-users. While group differences in BOLD response observed at baseline were no longer apparent after two weeks of abstinence, other differences persisted across a five-week period of sustained abstinence. This pattern of results suggests that alterations in neural functioning commonly observed in adolescent alcohol users may result from a combination of acute changes related to use as well as pre-existing vulnerabilities. Conversely, some brain functioning abnormalities may reverse after longer periods of abstinence. It is well established that adolescents are more likely to engage in risky behaviors compared to adults or younger children, and that rates of behaviors such as substance use, unsafe sexual activity, dangerous driving, and involvement in criminal activity emerge, increase, and peak during adolescence . Statistics from the Center for Disease Control and Prevention’s “Youth Risk Behavior Surveillance Survey” indicate that in 2011, 24% of adolescents in grades 9-12 knowingly rode in a car at least once with a driver who had been drinking alcohol, 22% of adolescents reported engaging in binge drinking activities , and of the 34% of adolescents who defined themselves as “sexually active,” 40% reported that they did not use a condom the last time they had sexual intercourse. Risk-taking is a complex and dynamic construct, yet not all adolescents are risk-takers. Studies have investigated individual differences in personality, sex, cognitive performance, and emotion regulation abilities, as well as complex socio-cultural influences in attempts to explain why some adolescents may be more likely to take risks than others. Recently, research has highlighted a neurobiological component that may underlie the trajectory of risk-taking commonly observed during adolescent development . This explanatory model derives from the rapidly changing nature of the adolescent brain, specifically in regions thought to play a role in risky decision-making and cognitive control.Alcohol use is a behavior that goes hand in hand with risk-taking; thus, it is no surprise that rates of alcohol consumption also rapidly increase during adolescence, with 65% of 12th graders endorsing some alcohol use over the past year, compared to only 29% of 8th graders. Self-reports of past-year “drunkenness” also increase by more than 30% between 8th and 12th grades, with 12% of 8th graders and 44% of 12th graders endorsing this behavior . Heavy episodic drinking is common among this age group, with 25% of high school seniors reporting at least one binge drinking episode within the past two weeks. In addition to increased binge drinking behavior, substance-related clinical disorders begin to emerge during adolescence, with 5% of youth ages 12 to 17 meeting diagnostic criteria for an alcohol use disorder . Cognitive decision-making capacity has been implicated as an important mechanism in the development of adolescent risk-taking behavior. Moore and Gullone define a “risky” behavior as “any behavior that involves potential negative consequences or loss, but is balanced in some way by perceived positive consequences or gain”. A behavior is considered more “risky” if the potential negative consequences outweigh the perceived positive consequences.

ROI selection was limited to one due to insufficient power to detect incremental model improvement with multiple ROIs

To address this gap in the literature and to further integrate neuroimaging and human laboratory paradigms for AUD, the current study examines whether alcohol taste cue-induced ventral striatum activation predicts subsequent oral alcohol self-administration in the laboratory. These secondary analyses are conducted in a within-subjects design whereby the same participants completed an fMRI cue-reactivity task followed by an alcohol-self administration task . As striatal activation is thought to underlie craving responses , we hypothesized that those with greater ventral striatum activation would consume their first drink faster than those with lower activation. Similarly, as previous research has demonstrated that mesolimbic activity predicts real-world heavy drinking, we hypothesized that ventral striatum activation would also be positively associated with the total number of drinks consumed during the self-administration paradigm. For the taste cues paradigm, information regarding image acquisition parameters and preprocessing steps are available in Supplementary Materials and are derived from the primary manuscript . The main contrast of interest was the difference in activation corresponding to alcohol taste delivery and water delivery across the two task runs , for each within-subject medication condition. Consistent with previous studies examining relationships among ventral striatum activity, subjective response to alcohol, and drinking behavior , an anatomical bilateral ventral striatum region of interest was defined using the Harvard-Oxford atlas in standard MNI space and was transformed into participants’ respective native space using FSL’s FLIRT . This ROI was selected because ventral striatum is most consistently elicited in alcohol cue and taste reactivity paradigms, as well as most frequently associated with behavioral measures and treatment response .The mean contrast estimate values were extracted from this region for each subject and used in mixed models for group-level analysis . The self-administration paradigm yielded two outcome measures: latency to first drink ,cannabis grower and total number of drinks consumed during the session . To examine the relationship between alcohol taste-induced neural activation and self-administration, multilevel mixed poisson and cox proportional hazard models were the primary analyses for total number of drinks and latency to first drink, respectively.

Frailty models were fitted using a penalized partial likelihood approach available in SAS 9.4 . Primary analyses examined effects of variables of interest, including medication condition , alcohol consumption , and OPRM1. Due to concerns of over parameterization given the limited sample size, additional covariates of interest were individually included in separate models to determine whether main effects of ventral striatum would be altered. Alpha corrections were not utilized in this exploratory study due to limited sample size and constrained power. Tests of proportional hazards are included in Supplementary Materials and Figures S1a-S1d. Survival plots for latency to first drink, controlling for covariates within the final model , were generated to further explore ventral striatum activation in predicting latency to first drink. Of note, a dichotomous median-split ventral striatum variable was created for ease of visualization of these relationships, but ventral striatum activation was included as a continuous variable in all models.The distribution of latencies to first drink was non-normal. Across medication conditions, 52% of individuals refrained from drinking throughout the paradigm, 29% consumed a drink within the first three minutes of the paradigm, and 19% of individuals consumed their first drink at some point during the remainder of the session. Cox regressions for latency to first drink indicated a significant effect of ventral striatum activation, Wald χ2 = 2.88, p = 0.05, such that those with lower ventral striatum activation exhibited longer latencies to first drink . Significant covariates included medication condition, Wald χ2 = 5.99, p = 0.01, such that naltrexone was associated with longer latency to first drink. OPRM1 was also significant, Wald χ2 = 3.31, p = 0.03, such that Asn40Asn homozygotes exhibited shorter latency to first drink. Other covariates of interest were not associated with latency to first drink . There were also no interactions of medication X gender on self-administration outcomes. This study examined the relationship between alcohol cue-induced ventral striatum activation and alcohol self-administration in the laboratory. Results from this heavy-drinking sample of East Asians indicated that higher ventral striatum activation was associated with a shorter latency to first self-administered drink. Similarly, ventral striatum activation was positively associated with the total number of drinks consumed during the self-administration paradigm in this sample.

These results remained significant after controlling for severity of drinking patterns, OPRM1, and medication condition. Overall, this is the first study to examine whether neuroimaging outcomes of interest can predict responses within laboratory paradigms commonly used in the alcohol literature. This foundational work adds important validity to the hypothesized interplay between neural bases of alcohol craving and behavioral measures of alcohol seeking, namely alcohol self-administration in the human laboratory. These associations contribute to a growing literature on the translational value of neuroimaging paradigms in alcohol treatment, particularly in elucidating potential mechanisms through which self-administration paradigms in AUD research are related to real world alcohol consumption . Such work is aligned with current efforts in behavioral treatments utilizing neuroimaging to study mechanisms of behavior change for substance use disorders; identifying those individuals with severe orbitofrontal cortex deficits, for instance, may be useful in guiding them away from treatments focused on increasing the salience of future negative consequences of substance use . In a similar fashion, adjunctive fMRI has been used to train individuals with substance use disorders through resonance-based breathing to reduce visual processing of drug cues and increase activation in areas implicated in internally directed cognition . Elucidating the translational value of these various experimental paradigms is strongly indicated, as AUD medications can exhibit differential results based on the utilized paradigm and such variability may in turn inform precision medicine efforts. Expanding the study of interexperimental paradigms may also shed light on aspects of alcohol consumption unique to individual paradigms. For instance, a greater understanding of individuals’ experiences in the transition between the first and subsequent drinks may be an important point of clinical interventions when discussing naltrexone use. While the primary aim of this study was not focused on genetic determinants of self-administration, it is notable that genotypes encoding the binding potential of mu-opioid receptors were associated with self-administration outcomes. While it is theorized that individuals with at least one copy of the G-allele for OPRM1 exhibit greater vulnerability to developing AUD, meta-analyses have been mixed, with findings that such an association may not be reliable , are population specific ,or that G-allele confers a modest protective effect on general substance dependence in European ancestry cohorts .

In this study, G-allele carriers of OPRM1 exhibited lower total consumption relative to A-allele carriers at a statistical trend level, as well as slower latency to first drink. This finding is consistent with the primary analyses for this data , which indicated that G-allele carriers of OPRM1 also reported less severe drinking history and lower AUDIT scores compared to Asn40 homozygotes and may, in turn, help to explain these findings. In sum, we accounted for genetic factors in these analyses given their theoretical and practical salience ,growing cannabis outdoors particularly in this population . And while the genetic findings are notable and largely consistent with the literature, the primary focus on the study is on the fMRI to human laboratory association. This is the area in which the present analyses make a substantive contribution to the literature by supporting a long hypothesized, yet rarely tested, association between brain and behavior. Finally, this study identified significant effects of naltrexone in increasing latency to first drink and decreasing total alcohol consumption. Notably, while these contrast the primary study results from which the data are derived the current study is a secondary analysis of a sub-sample of participants who had completed both neuroimaging sessions. While inclusion of VS activation may have helped to improve model fit, the primary study had greater power in order to test pharmacogenetic effects. For these reasons, while it is possible that consideration of neuroimaging outcomes help elucidate AUD pharmacotherapy effects, replication using larger samples is warranted. On balance, this study should be interpreted in light of its strengths and limitations. Strengths included assessment of multiple experimental procedures used in the medication development literature and consideration of multiple psychiatric and genetic predictors of self-administration in the statistical analyses. Another strength is the test of hypothesis at the within subjects level of analysis. As argued by Curran and Bauer , several psychological processes which are inherently within-person processes, such as the relationship between how one’s brain processes alcohol cues and how much s/he wants to drink in the future, are presumed to be explained in between-subjects models, when in fact, within-subject analyses provide a more representative test of the process at hand . Thus, a within-subjects approach represents a more robust, and methodologically adequate, test of the association between brain and behavior. One of the most important limitations of the current study is a constrained sample and power; given the exploratory nature of this study, alpha corrections were not implemented. A limitation of the taste cues fMRI paradigm used in this study is that it was modified to reduce trial duration in order to increase the number of trials for analysis; in contrast to the original task , a whole-brain analysis of the task did not elicit significant clusters of mesocorticolimbic, including ventral striatum, activation. Therefore, replication using other tasks that more strongly elicit ventral striatum activation are needed, both to induce significant enough variability to test medication effects and also to translate such effects into another subsequent experimental modality.

Variations of the Monetary Incentive Delay task that administer beer may be particularly useful in disentangling whether anticipation, relative to receipt, of alcohol taste are differently discriminant in predicting self-administration Relatedly, the taste cues paradigm was limited to the choice of red or white wine, which did not always correspond with participants’ drink of choice; while this correspondence was not a significant covariate in self-administration outcomes, administering drink of choice may increase external validity of the imaging task. Another potential weakness is that medication effects from the primary manuscripts were null; future studies are needed to corroborate that medication effects are consistent across paradigms, particularly in identifying significant such effects. An additional warranted question is whether such consistency of medication effects in laboratory studies would translate directly to clinical outcomes and treatment-seeking populations. Lastly, the “priming dose” that preceded the self-administration period was higher than the usual 0.03 g/dl reported in the literature. While the higher priming dose of alcohol in this study did not suppress alcohol self-administration, it may be interpreted differently in that participants were seeking to self-administer to reach high levels of BrAC, perhaps binge-like levels. If that was the case, results would remain highly relevant and consistent with recent efforts to phenotype binge-drinking in the human laboratory . Limitations notwithstanding, the present findings provide proof-of-concept that neuroimaging and laboratory paradigms may be closely linked. Further, neuroimaging may be a useful tool to explore in greater detail how different paradigms are related to real world consumption behavior. Future studies are warranted to replicate the current results and to identify, refine, and implement translational paradigms in AUD research.In the European Union and the United States, 3,4-methylenedioxymethamphetamine is currently a schedule I controlled substance . The interest in MDMA use in psychiatry has solidified and is growing following publications of results from multiple controlled trials including a Phase 3 study for MDMA assisted therapy for post-traumatic stress disorder . MDMA’s psychoactive properties are due to multiple mechanisms that modulate monoamine neurotransmission, including release and reuptake of serotonin, dopamine and norepinephrine . Proposed therapeutic mechanisms of MDMA may include increased ability to confront upsetting memories, supporting fear-extinction learning and increased interpersonal closeness . Adverse events observed in controlled trials included transient hypertension, muscle tightness, decreased appetite, nausea, hyperhidrosis and feeling cold . Serotonin syndrome is a potentially life-threatening condition resulting from serotonergic over-activity at synapses of the central and peripheral nervous systems usually involving serotonergic medications . SS manifests itself through a range of mild to severe symptoms. Mild symptoms include akathisia and tremors, and severe symptoms include hyperthermia and muscular rigidity, which can be life-threatening .

To definitively address this issue would require a blocking study in humans to estimate VND

We also found that attentional bias to threat mediated the relation between CB1 receptor availability in the amygdala and severity of threat symptomatology. These results extend a growing body of research demonstrating an association between trauma-related disorders such as PTSD, MDD, and GAD, and attentional bias to threat by implicating the CB1 receptor system as a key neurobiological underpinning of this endophenotype and its concomitant phenotypic expression of trauma-related threat symptomatology, particularly hyperarousal symptoms. They further suggest that attentional bias to threat may mediate the association between CB1 receptor availability in the amygdala and threat symptomatology, with greater CB1 receptor availability being linked to greater attentional bias to threat that is in turn linked to greater severity of threat symptomatology. Results of the current study build on extant neurobiological studies that have implicated the endocannabinoid system in the amygdala as an important modulator of anxiety , as well as functional activation of the amygdala in mediating attentional bias to threat among individuals with PTSD . Specifically, results of this study suggest that CB1 receptor availability in the amygdala may directly mediate this endophenotype and its associated phenotypic expression of trauma-related threat symptomatology. Preclinical work suggests that the activation of membrane glucocorticoid receptors appears to engage a G-protein-mediated cascade through the activation of Gs proteins that, in turn, increases the activity of cAMP and protein kinase A. This increase in protein kinase A appears to induce the rapid synthesis of an endocannabinoid signal through an as yet unknown mechanism that may be an increase in intracellular calcium signaling that is then released from principal neurons in the amygdala and activates CB1 receptors localized on the terminals of GABAergic neurons in the amygdala. It should be noted, however,vertical grow rack that other mechanisms than CB1 receptor stimulation by anandamide could contribute to the etiology of attentional bias to threat and threat symptomatology.

First, the two endocannabinoids anandamide and 2-arachidonoylglycerol have differential roles in endocannabinoid and have distinctly different metabolic pathways for anandamide and monoacylglycerollipase for 2-arachidonoylglycerol; . To date, the relative contribution of these two endocannabinoids and their pathways in the modulation of anxiety remains unclear. Furthermore, recent evidence suggests that CB1 receptor signaling varies across brain regions , and that diverse effects of anandamide–CB1 receptor signaling mechanisms are evident even within the extended amygdala . Finally, the actions of anandamide are not restricted to CB1 receptors, as endocannabinoids also act on CB2 receptors , GPR55 , transient receptor potential vanilloid type 1 channels , and other G-protein subtypes . Although additional research is needed to further evaluate how the endocannabinoid system mediates attentional bias to threat, the results of this study suggest that greater CB1 receptor availability in the amygdala, as well as lower levels of peripheral anandamide, are associated with a greater attentional bias to threat in trauma-exposed individuals. However, we acknowledge, that no human studies that we are aware of have found that anandamide concentrations directly influence CB1 receptor availability, and hence additional work is needed to ascertain how these variables are causally related. Nevertheless, the present data extend prior work linking attentional bias to threat to hyperarousal symptoms to suggest that the CB1 receptor system in the amygdala is implicated in modulating attentional bias to threat that is in turn linked to the transdiagnostic and dimensional phenotypic expression of trauma-related threat symptomatology. Further research will be useful in further elucidating molecular mechanisms that account for the observed association between CB1 receptor availability and the endophenotypic and phenotypic expression of threat processing in humans. An important question to be addressed in future work is whether pharmacotherapies that act on catabolic enzymes for endocannabinoids may be useful in the prevention and treatment of endophenotypic and phenotypic aspects of trauma-related threat symptomatology. Emerging evidence supports the potential utility of such targets, suggesting that variation in the FAAH gene is linked to reduced expression of FAAH that consequently results in elevations in circulating levels of anadamide , as well as decreased amygdala response to threat and more rapid habituation of the amygdala to repeated threat .

Notably, elevating anandamide levels via FAAH inhibition appear to provide a more circumscribed spectrum of behavioral effects than blocking MAGL that could potentially result in a more beneficial side effect profile, as anandamide is less prone to CB1 receptor desensitization and resultant behavioral tolerance . These classes of compounds are currently being investigated for their potential efficacy in treating mood and anxiety disorders. Given that core aspects of threat symptomatology such as hyperarousal are key drivers of more disabling aspects of the trauma-related phenotype such as emotional numbing , pharmacotherapeutic targeting of threat symptomatology in symptomatic trauma survivors may have utility in reducing the chronicity and morbidity of trauma-related psychiatric disorders such as PTSD, MDD, and GAD. Methodological limitations of this study must be noted. First, we studied a cohort of individuals with heterogeneous trauma histories. Although this is typical for most PTSD studies and we endeavored to recruit individuals who represented a broad and representative spectrum of traumarelated psychopathology, additional studies of samples with noncivilian trauma histories will be useful in extending these results. Second, 95% confidence intervals for coefficients in the mediation analysis were markedly wide, and hence additional studies in larger samples will be useful in ascertaining magnitudes of the observed associations. Third, we observed a high correlation between threat and loss symptomatology that may call into question the extent to which these symptom clusters reflect separable components of trauma-related psychopathology that are uniquely related to CB1 receptor availability in the amygdala and attentional bias to threat. Nevertheless, high correlations among symptom clusters of trauma-related psychopathology are not uncommon, with confirmatory factor analytic studies of substantially larger samples often observing inter correlations among symptom clusters 40.80 . Furthermore, the finding that CB1 receptor availability in the amygdala was associated only with threat, but not loss symptomatology, suggests greater specificity of association that accords with prior work . Fourth, it is important to recognize that our outcome measure in this study, VT, represents specific plus non-displaceable binding. Because of the lack of a suitable reference region devoid of CB1, we and others using different CB1 receptor ligands cannot directly calculate binding potential , a measure of specific binding. Thus, an implicit assumption in the interpretation of our results is that there are no group differences in VND, the distribution volume of non displaceable tracer uptake.

An alternative assumption would be that the magnitude of non displaceable binding is small compared with the total binding. To the best of our knowledge, such data are not currently available because of the lack of suitable selective CB1 antagonist drugs approved for human use. Blocking data with the CB1 receptor antagonist rimonabant in baboons , however,commercial vertical growing systems did show a large reduction in tracer uptake, suggesting that a substantial fraction of VT can be attributed to specific binding. Notwithstanding these limitations, the results of this study provide the first known in vivo molecular evidence of how a candidate neuroreceptor system—CB1—relates to attentional bias to threat and the dimensional expression of trauma-related psychopathology. Results revealed that greater CB1 receptor availability in the amygdala is associated with increased attentional bias to threat, as well as the phenotypic expression of threat-related symptomatology, particularly hyperarousal symptoms. Given that these results were based on a relatively small sample, further research in larger, transdiagnostic cohorts with elevated threat symptomatology will be useful in evaluating the generalizability of these results, as well as in examining the efficacy of candidate pharmacotherapies that target the anandamide–CB1 receptor system in mitigating both the endophenotypic and phenotypic expression of threat symptomatology in symptomatic trauma survivors.Recent large genome-wide association studies of substance use disorder phenotypes consistently show that there is only modest overlap [rg=0.38–0.77 ] between genetic factors that influence alcohol consumption and alcohol use disorder [AUD, ], whereas smoking and nicotine dependence are almost genetically identical [rg=0.95 ]. Importantly, the alcohol consumption and use disorder studies show divergent patterns of genetic association with other diseases . Whereas alcohol consumption is genetically correlated with higher educational attainment, lower body mass index and lower risk of coronary heart disease and type 2 diabetes; AUD and aspects of alcohol misuse share genetic associations with psychiatric disorders . In contrast, genetic correlation analyses show consistent associations of both CPD and ND with higher risks of psychiatric disorders, lower educational attainment, and higher risks of coronary heart disease or its predisposing factors . Sample sizes for GWAS of consumption phenotypes range from thousands to more than a million subjects from healthy volunteer collections, primarily from the GSCAN consortium, including UK Bio-bank and 23andMe, and the Million Veterans Program ; however, past GWAS of dependence phenotypes and genetic correlation analyses included smaller samples of some high-risk populations . Both ascertainment strategies can introduce bias. In this short communication, we are leveraging GWAS data from well-powered studies of consumption and misuse/dependence phenotypes.

Unlike previous studies, we focus largely on the UKB to control for potential selection biases, but also comparing results from non-UKB cohorts, and perform genetic correlations within a medical-center cohort from Vanderbilt University Medical Center . These analyses provide an evaluation of the degree to which the more easily and broadly obtained consumption phenotypes are good proxies for alcohol misuse and nicotine dependence. We used GWAS summary statistics largely from the UKB to control for potential selection biases that may differ across different cohorts. For alcohol phenotypes, we used GWAS summary statistics for alcohol consumption and misuse via the AUDIT from our previous work [UKB, N=121, 604 ]. For smoking phenotypes, we used GWAS summary statistics for CPD from GSCAN, for which 45.7% were UKB participants. For ND, we used GWAS summary statistics from 244,890 UKB participants with an International Classification of Disease code for ND . Because our measure of ND was binary, unlike all of our other quantitative variables, we also included data from a quantitative measure , available only from non-UKB cohorts in the Nicotine Dependence GenOmics consortium ]. We computed polygenic risk scores for the four alcohol and nicotine phenotypes using the PRS-CS “auto” version for each of the 66,915 genotyped individuals of European descent in BioVU. BioVU is one of the largest biobanks in the United States, consisting of electronic health record data from the Vanderbilt University Medical Center on ∼250,000 patients captured from 1990 to 2017. Genotyping and QC of this sample have been described elsewhere . In the genotyped BioVU sample, we fitted a logistic regression model to each of 1,335 case/control disease phenotypes to estimate the odds of each diagnosis given the PRS, after adjustment for sex, median age of the longitudinal electronic health record measurements, and first ten principal components of ancestry. Phenome-wide association study analyses were run using the PheWAS R package v0.12 . We required the presence of 100 cases with at least two or more ICD codes that mapped to a PheWAS disease category to assign “case” status. We used the standard Benjamini—Hochberg False Discovery Rate to correct for multiple testing. This threshold, however, is likely conservative because it incorrectly assumes independence between phecodes. To explore whether pleiotropic effects of the PRS were mediated by the diagnosis of tobacco use disorder , we also conducted PheWAS analyses using TUD as an additional covariate for each PRS. In addition, we repeated the PheWAS analyses using AUD diagnoses as additional covariates for each PRS. PRSs for both alcohol consumption and misuse were associated with AUD in BioVU . Of 1,335 phenotypes, PRSs for alcohol misuse were positively associated with other mental disorders, including mood disorders, major depressive disorder, bipolar disorder, and suicidal ideation or attempt, replicating previous findings using a PRS of a clinical alcohol dependence /AUD measure . In contrast, and replicating previous associations, alcohol consumption was negatively genetically correlated with metabolic conditions, such as type 2 diabetes and obesity. Adjusting the associations between alcohol consumption and metabolic disorders for AUD or TUD did not meaningfully change the magnitude of these associations, although the magnitude of the p-values increased slightly for some associations . Similarly, adjusting the associations with alcohol misuse use for AUD or TUD increased the magnitude of the p-value but the effect sizes remained largely unchanged .

The MA+ groups had higher rates of all other lifetime substance use disorders than the MA-groups

Further, poorer sleep quality among PWH with comorbid lifetime MA use disorder was associated with a number of neurobehavioral functional outcomes, including decreased physical and mental life quality, IADL dependence, unemployment and clinician-rated functional disability. As expected, lifetime MA use disorder was negatively associated with sleep quality; however, this finding was isolated to PWH and independent of recent MA use. In addition, MA use characteristics did not differ by HIV serostatus, suggesting sleep among PWH may be specifically related to the effects of nonrecent MA use. Prior studies have demonstrated detrimental effects of MA on neurobehavioral health specific to PWH, including neurocognitive impairment and associated everyday life consequences such as unemployment and difficulties performing activities of daily living . It is possible that disrupted sleep may mediate the link between MA and functional outcomes, although longitudinal studies are needed to determine causality. Depressive symptoms in the HIV+/MA+ group are also consistent with prior research . While depressive symptoms were also associated with global PSQI scores, as expected, this did not attenuate the relationship between MA and global PSQI scores in PWH, suggesting additional mechanisms underlying MA-related sleep disturbance independent of mood. One explanation for our findings is the combined, long-term CNS effects of excessive MA use and HIV on brain structures and/or pathways responsible for sleep regulation. While MA’s major mechanism of action is through increased activity of the mesolimbic dopamine system , emerging evidence supports that GABA-ergic dysfunction results from abuse of amphetamines . Projection systems of GABA include the reticular nucleus of the thalamus to the rostral brainstem reticular formation, a structure critical for sleep regulation. Further, GABA also promotes sleep via hypothalamic projections that inhibit serotonergic, noradrenergic, histaminergic,vertical grow racks and cholinergic arousal systems . Future studies linking GABA to MA use and sleep quality are necessary to establish this theoretical mechanism of action. Also, while the lack of evidence of sleep disturbance in the very small HIV−/MA+ group would not support long-term effects of MA use on CNS mechanisms important for sleep, a much larger subject sample would be needed to draw any confident conclusions about HIV−/MA+ individuals.

Prior literature on the prevalence of sleep disturbance in PWH is variable and comparisons between demographically matched, HIV serostaus groups on sleep quality is lacking. In a meta-analysis of self-reported sleep disturbance in PWH, the overall prevalence was 58% . No comparisons have been made with HIV-uninfected individuals from the same population to determine whether this prevalence is higher than in this type of comparison group. The current findings suggest HIV status alone may not elicit poor perception of sleep, however, fragmented sleep has been identified in chronic health conditions even without the patient’s perception of poor sleep . Consistent with prior literature , detectable HIV RNA was associated with poorer perceived sleep quality in our multiple regression analyses, but the specific mechanism for this association could not be established. Other literature has suggested that HIV infection is linked to objective sleep measurements, including reduced slow wave sleep and reduced rapid eye movement latency . However, studies have failed to detect similar associations between HIV disease severity and objective sleep measurements , highlighting the uncertainty to which HIV infection, by itself, may contribute to reductions in sleep quality. The study has several limitations. First, the data are cross-sectional and cannot determine causality. Lifetime MA use disorder is suspected to precede self-reported poor sleep within the last 30 days, however, such self-reported sleep disturbances may be longstanding and could even have served as a precursor to problematic substance use . Thus, future longitudinal evaluations or with increased sample size, the use of structural equation modeling, would be helpful in better determining the timing, duration, and directionality of associations between MA use disorders and sleep. This goes alongside our report of neurobehavioral outcomes associated with problematic sleep within PWH with a history of MA use disorder. While theoretically, sleep should have some influence on function, it is also possible that there is some unique third variable quality within the HIV+/MA+ group that leads to both poor sleep and poor neurobehavioral outcomes. Again, a longitudinal research design or a larger sample size may help in teasing out the directionality of our findings. Second, the small sample size of the HIV−/MA+ group hinders our ability to detect statistically significant associations between MA use and other findings with the HIV− participants.

For example, the difference between HIV+/MA+ and HIV−/MA+ groups on global PSQI was not statistically significant , yet the effect size suggests a nontrivial difference . While our sample did not demonstrate an interaction between HIV and MA possibily due to this limitation, this relationship may exist. Further, while lifetime MA use disorder independently contributed to sleep quality in PWH, we did not observe a recent MA use effect on sleep. We should note that this too may be due to low power, with very few participants reporting use in the last 30 days. It is also important to highlight the complexity of poly substance use in the context of a cross-sectional, retrospective study. Despite this, lifetime MA use disorder was retained in the multiple regression model, while the other substances did not. Due to limited data on participants who met criteria for a current substance use disorder or other measurements of current substance use parameters, our finding cannot speak to other potential factors associated with poly substance use that may explain differences in sleep between MA+ and MA− groups. Future studies to formally investigate poly substance use in more detail is needed to futher confirm our findings. In addition, we did not find associations between age, sex, or sexual orientation on sleep quality, which is contrary to well established literature on these topics . We suspect that the presence of other clinical risk factors for poor sleep, including those identified in this study , may be masking the detection of these variables traditionally known to impact sleep quality. There also remains the possibility that other unmeasured factors such as homelessness and/or SES may account for the observed relationship that MA was related to sleep in PWH that should be explored further in future studies. Lastly, the PSQI questionnaire is based on self-report, which is subject to recall and reporting bias. While there is merit in characterizing perceived sleep quality in vulnerable populations, as even the perception of poor sleep can influence mood and physical health , subjective measurements are just one facet of sleep quality and the inclusion of objective measurements such as actigraphy would enhance understanding of sleep in PWH and substance using populations. Importantly, the global PSQI score demonstrates strong sensitivity and specificity in distinguishing good from poor sleepers among the general population . While the sensitivity in detecting an insomnia diagnosis in PWH remains high , the specificity drops considerably . This suggests that the PSQI may not just be capturing sleep quality in PWH and raises the question as to whether items such as “trouble staying awake during the day” or “trouble keeping enthusiasm” are purely a function of poor sleep or a result of HIV-infection, prescribed medications, and/or associated psychosocial factors. Studies investigating the quality of the PSQI sub-components in capturing sleep quality within PWH using factor analyses may be a natural next step for future research. For people with substance use disorders,vertical grow rack system denial of untoward consequences from their actions is common and can affect commitment to treatment. In 2019, 96% of untreated individuals with a substance use disorder in the previous year denied needing treatment.

Psychodynamic approaches toward addiction encourage accountability and minimizing denial; and 12-step programs, such as Alcoholics Anonymous, target denial by encouraging clients to acknowledge that they have lost control over addictive behavior, with a focus on accountability-centered goals. Among participants who had polysubstance misuse and attended Alcoholics Anonymous or Narcotics Anonymous, the number of days in attendance was associated with decreased self-deception measured in a followup assessment.The transtheoretical model of behavior change likewise posits that changing addictive behavior relies on a transition from lack of recognition that a problem exists to increased awareness and motivation to change.The rostral anterior cingulate cortex , which participates in self-related processing, including self-awareness, has been implicated in personal relevance of drug-related stimuli, as is the ventromedial prefrontal cortex, which contributes to decision making.In an fMRI study, denial of methamphetamine-related problems was negatively related to resting-state connectivity between the rACC and precuneus.Among participants who met diagnostic criteria for Methamphetamine Dependence ,denial of methamphetamine-related problems correlated negatively with overall cognitive function and with rACC connectivity to frontal lobe regions, including the precentral gyri, left ventromedial prefrontal cortex, and left orbitofrontal cortex.These data implicate the rACC and its connections in a person’s ability to acknowledge problematic aspects of their substance use. One of the most important clinical measurements, the diagnosis of a substance use disorder, involves clinical judgment, but self-reports are very important. Structured diagnostic interviews, such as the Structured Clinical Interview for DSM-IV or Mini-International Neuropsychiatric Interview , query self-reports of symptoms indicating craving, tolerance, withdrawal, and interference with activities of daily living. Although interview guidelines encourage the use of referral notes, records, and observations of friends and family,diagnosis often relies on interview with the client alone. In these interviews, denial of problems related to substance use is common and can alter diagnosis. This study sought to clarify how a diagnostic measure of Methamphetamine Dependence that relies on self-report is related to a participant’s denial of his or her addiction problem. Participants comprised a sample of 69 individuals who acknowledged enough symptoms on the SCID to meet criteria for the diagnosis of Methamphetamine Dependence. They also completed the University Rhode Island Change Assessment Scale , which assesses motivation for change by providing scores on 4 stages of change: Precontemplation, Contemplation, Action and Maintenance. The Precontemplation score measures the respondent’s denial that their drug problem warrants change and is based on a transtheoretical model of addiction.In a prior study, the Precontemplation score was positively related to years of heavy methamphetamine use and arrests for drug offenses, supporting the notion that high scores reflect denial rather than the absence of problems. We hypothesized the Precontemplation score would correlate negatively with symptom severity, confounding the diagnosis.A quasi-experimental, non-intervention design was employed using secondary data analysis. Other studies of the parent dataset have been published.Participants, recruited using internet and local newspaper advertisements, provided written informed consent, following the guidelines of the UCLA Office for Protection of Research Subjects. This analysis included data from 69 participants. Detailed inclusion/exclusion criteria are published.In brief, participants were fluent in English, met criteria for Methamphetamine Dependence but not diagnoses related to drugs other than methamphetamine, cannabis, or tobacco; or for any Axis-I psychiatric disorders other than those related to drug abuse . They had a positive urine test for methamphetamine at screening but were not seeking treatment and were otherwise healthy. Participants received monetary payment for their time.The opioid crisis has had a substantial effect on women who are pregnant and parenting, focusing both public health and policymaker attention on opioids and on other substance use in pregnancy and postpartum. The number of pregnant women with an opioid use disorder diagnosis at delivery quadrupled from 1999 to 2014,1 and the incidence of neonatal opioid withdrawal syndrome increased nearly seven-fold from 2000 to 2014. Alcohol use remains common, with 1 of 9 pregnant women endorsing past 30 day use, one third of whom reported binge drinking.Cannabis use is increasing, with daily or near-daily cannabis use in pregnancy increasing from <1% in 2002 to nearly 3.5% in 2017.Stimulant use, specifically methamphetamine, doubled in pregnancy from 2008 to 2015.These trends have contributed to an increase in drug-related deaths among women in general and during pregnancy and postpartum in particular, with overdose among the leading causes of maternal death in the US today.Furthermore, the child welfare system response to substance use in pregnancy is straining already-limited resources. From 2011 to 2017, the number of infants entering the U.S. foster care system grew by almost 10,000, and at least half of infant placements are associated with parental substance use.Below, we review the change over time in state-level policy environments around substance use in pregnancy and contrast the policy response with the principles and guidance from professional societies and federal agencies.