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Consistent with other studies,a longer history of cigarette smoking predicted worsening respiratory symptoms and decreased chances of improvement, independent of P30D cigarette smoking, underlining the importance of cigarette smoke exposure in the development or worsening of respiratory symptoms. The consequences of cigarette use were the same regardless of which additional tobacco products were used. As shown previously, dual users of cigarettes and e-cigarettes smoked cigarettes as frequently as exclusive cigarette smokers,their respiratory response to cigarette smoking intensity was essentially the same as exclusive cigarette users, and they had indistinguishable risk for symptom worsening.We found no evidence to support the idea that dual use of cigarettes and e-cigarettes carries higher risk for respiratory symptom worsening compared to exclusive cigarettes for the symptom outcomes we examined. This contrasts with increased risk of dual use in the analyses of PATH Study data reported by Reddy et al,an analysis that involved a different period , and adjusted only for demographics; we doubt the finding reported by Reddy would have remained statistically significant after adjustment for the multiple confounders included in the present analysis. In contrast, respiratory symptom risk for exclusive users of other tobacco products was significantly lower than for cigarettes, and was largely not significantly different from never or former tobacco users. The finding for e-cigarettes contradicts two cross-sectional studies of tobacco use and respiratory symptoms, one using PATH Study W2 data18 and one using W3 data,greenhouse tables both concluding that there was an association between e-cigarette use and wheezing. These studies examined the association with each item on the respiratory index and neither adjusted for cigarette smoking history or marijuana use.Based on the present study findings— lack of a crude dose-response for e-cigarette frequency illustrated in Figure 2 and the confounding analysis in Table 2—we conclude that the reported associations in these papers were likely spurious, primarily because of the failure to adjust for cigarette smoking history.

Our supplemental materials include a method for determining cigarette pack-years from PATH Study data to support the inclusion of this important confounder by other users of these data. The longitudinal results seem contradictory if the reference of focus is never users—ecigarette users are significantly more likely to have symptoms worsen at one cut-off level and significantly more likely to have symptoms improve at another—an example of how results for ecigarette users may be sensitive to how health outcomes are determined. But another viewpoint is that potentially reduced harm tobacco products are judged also by how health risks of the product compare to the health risks for cigarette smokers. With cigarette users as the referent category, the analysis suggests that exclusive e-cigarette users are less likely to have their respiratory symptoms worsen, along with consistent findings , than they are more likely to have their symptoms improve. In sum, with respect to short-term changes in functionally-important respiratory symptoms, the results suggest risk for exclusive e-cigarette users are intermediate–increased harm compared to never tobacco users, but reduced harm compared to cigarette users. Cigar smokers had consistently lower risk for functionally-important respiratory symptoms compared to exclusive cigarette smokers, as was previously reported for some of the single respiratory symptom items in another PATH Study report.Cigar smoking has been associated with higher mortality from respiratory disease and lung cancer,increased risk for diagnosis of lung cancer and COPD,decreased lung function and airflow obstruction,and respiratory symptoms.In all studies including cigarette smokers, risks associated with cigars were lower than for cigarettes; former cigarette smokers switching to cigars had higher risk vs. those who had smoked only cigars.Respiratory symptom risk among hookah smokers has not been studied extensively but was intermediate between never smokers and cigarette smokers in one study.Lower symptom risk with exclusive cigar use may be explained by reduced smoke inhalation.In contrast to cigarettes, cigar tobacco is fermented, and many cigars are smoked with lower frequency.

Cigar smokers also tend to inhale less deeply because of smoke alkalinity which also enhances oral nicotine absorption. Only 15% of exclusive cigar smokers reportactively inhaling the smoke, compared to two-thirds for users of both cigars and cigarettes .Marijuana was associated with functionally-important respiratory symptoms, consistent with 8 of 10 previous studies.The findings are backed by research involving dual users of marijuana and cigarettes showing higher puff volumes, deeper inhalation, and greater tar retention from marijuana vs. cigarettes,animal research documenting pulmonary cell changes with chronic marijuana smoking, and prospective research showing changes in lung function among marijuana smokers.One study showing an association between e-cigarette use and cough among young never cigarette smokers, failed to adjust for marijuana use in the multivariable model . Another study of adult PATH Study W4 data found vaping with marijuana to be associated with wheezing , consistent with our findings.Two other studies of youth, one using PATH Study data, have shown that the e-cigarette—respiratory outcome is confounded by marijuana use and marijuana vaping.Clinicians need to be aware of the association between marijuana use and respiratory symptoms as use increases.The study strengths include a nationally representative sample, a validated respiratory outcome related to functional impairment, and adjustment for multiple confounding influences. Limitations include small numbers in some product groups, increasing the probability of a chance finding. Because switching from cigarette smoking to exclusive e-cigarette use is an uncommon event, randomized e-cigarette switching trials may be required to better assess how e-cigarette substitution affects wheezing symptoms among adult cigarette smokers. Risk of marijuana smoking on respiratory symptoms may be underestimated because marijuana use may have included non-combustible products.Relying on self-report of COPD may have resulted in some who were unaware of their diagnosis being retained in the study.

The findings relate only to short-term changes in wheezing and nighttime cough, not other bothersome symptoms , longer-term symptom effects, relation to respiratory disease onset, or vaping-related acute lung injury—medical issues that underline concern about any inhaled product use. The analysis included many comparisons and nevertheless employed a p-value of 0.05; the associations reported should be confirmed in other samples. Finally, future analyses with the latest available data from the PATH Study may provide a more refined look at the questions addressed in the present study. In summary, this study of a nationally representative sample of US adults without severe respiratory disease found an association between cigarette smoking and functionally-important respiratory symptoms – and substantially less evidence of associations between respiratory symptoms and exclusive non-cigarette tobacco product use. Early use of substances has been associated with more severe addictions and subsequent poor treatment outcomes . Early age at first substance use can lead to different addiction use trajectories, including early-onset and severe SUD symptoms persisting into adulthood, early-onset in adolescence that improves in adulthood,vertical farming and SUD symptoms emerging later with varying degrees of severity and persistence . Additionally, early age at first substance use not only negatively impacts mental health outcomes, but it also influences the addiction recovery process. Earlier age at inaugural substance use exerts a significant influence on later severe SUDs and constitutes a risk factor for comorbid mental health issues . Early age at first substance use can also extend the addiction recovery process , influence relapse frequency , and suicide attempts . To date, available evidence on associations between age at first substance use and later SUD varied across study populations, and research conducted in regions other than North America and Europe, especially sub-Saharan Africa is scarce . However, the majority of SSA countries is disproportionally affected by fragile security and armed conflicts ; which are among factors for proliferation of psychoactive substances in the region . This dearth of research may obstruct interventions toward the growing substance use issues, such as alcohol use disorders and subsequent deaths among youth in Africa .

Globally, substantial evidence links first alcohol use, before 18 years old, with higher alcohol and other drug disorders . In Canada, individuals consuming alcohol between the ages of 11 and 14 had more risk for developing alcohol disorders compared with those who started drinking alcohol after the age of 19 . Donoghue et al. in a study conducted in the UK likewise found a strong association between age of the first alcohol consumption, before the age of 15, tobacco use, lower quality of life, and emergency room admissions for alcohol use disorders among adolescents. Similarly, a recent systematic review of prospective studies highlighted the impact of early first alcohol use on future alcohol use disorders . In a birth cohort study, Newton-Howes and Boden demonstrated that early age of first drug use significantly increased the risk for later alcohol use disorders, nicotine dependence, and illicit drug dependence. However, after controlling for covariate factors, such as family living standards, ethnicity, and childhood sexual abuse, earlier first substance use was found to have no significant associations with these SUDs . In an Australian study, young age substance exposure was associated with later polydrug use, such as methamphetamine and heroin . In contrast to the above evidence, other research found no statistically significant associations between early-age substance use and later SUD . A few studies conducted in SSA reported the age at onset of only two types of psychoactive substances, alcohol , and tobacco . In youth tobacco surveys from nine Western Africa countries, Veeranki et al. found that the age of smoking onset was as early as 7 years old. Osaki et al. in a Tanzanian secondary school and college students aged 15–24 found that the age of alcohol consumption was as early as 10 years old. Contextual factors for alcohol use onset included exposure to a stressful environment, social events, and home alcohol consumption under the influence of parents, relatives, peers, and intimate partners . Likewise, a systematic review for cross-country comparison by Townsend et al. demonstrated that tobacco use primarily began in late adolescence and early adulthood in SSA. However, Townsend et al. found no association between tobacco use and socioeconomic status or urban/rural difference. The strength of the association be-tween first substance use to SUD seems to be moderated by contextual factors. Variations in the strength of associations between first substance use and SUD may be partially explained by environmental factors, such as life adversity and conflict-related psychology strains . In the recent UK Millennium Cohort Study of 10,498 11-year-old participants, having a friend who drank was a strong risk factor for increased alcohol use patterns . Besides, McCann et al. indicated that relationships, including higher levels of parental control and lower levels of child openness to parents, were linked with less frequent alcohol use. Furthermore, child-hood traumatic experiences in the forms of severe and mild physical abuse significantly correlated with an earlier age at first alcohol consumption, as well as illicit and poly drug use . Other factors, such as premorbid cognitive deficit early-age major depression , bipolar disorders , and impulse control influence early-age substance use and addiction trajectory following first substance. Additionally, interactions between premorbid mental health deficits and the effects of substance use on cognitive development may influence the early substance use onset and rapid spirals into substance dependence . Overall, there is little and inconsistent evidence on the association between early age at first substance use and later severe addiction issues worldwide. While the associations between PTSD and SUD are well documented, little is known about how young age substance use coupled to PTSD contributes to later severe addiction. Likewise, PTSD has been studied somewhat in SSA and substantially in Rwanda ; however, there is minimal data on associated substance misuse. The identified studies focused on a few substances and did not examine the transition from first use to addiction and contributors to later addiction severity. The study used consecutive sampling techniques to screen 362 participants who were referred to the study, only 342 of whom were eligible, and 315 consented to participate in the study. Given that addiction issues do not have any known seasonal fluctuations, consecutive sampling was the most reliable form of non-probability sampling, which can achieve a representative sample within a short time . Participants were included in the sample if they were aged 18 years old and over, had been diagnosed with any substance use disorder, presented for intake or relapse assessment, able to answer questions, and willingly provided consent.

The other case involved tacalcitol ointment as the inciting agent. In addition, we recently encountered a second case of oral vitamin D-induced acute pancreatitis , which we are currently examining. Early use of substances has been associated with more severe addictions and subsequent poor treatment outcomes . Early age at first substance use can lead to different addiction use trajectories, including early-onset and severe SUD symptoms persisting into adulthood, early-onset in adolescence that improves in adulthood, and SUD symptoms emerging later with varying degrees of severity and persistence . Additionally, early age at first substance use not only negatively impacts mental health outcomes, but it also influences the addiction recovery process. Earlier age at inaugural substance use exerts a significant influence on later severe SUDs and constitutes a risk factor for comorbid mental health issues . Early age at first substance use can also extend the addiction recovery process , influence relapse frequency , and suicide attempts . To date, available evidence on associations between age at first substance use and later SUD varied across study populations, and research conducted in regions other than North America and Europe, especially sub-Saharan Africa is scarce . However, the majority of SSA countries is disproportionally affected by fragile security and armed conflicts ; which are among factors for proliferation of psychoactive substances in the region . This dearth of research may obstruct interventions toward the growing substance use issues, such as alcohol use disorders and subsequent deaths among youth in Africa . Globally, substantial evidence links first alcohol use,vertical hydroponic garden before 18 years old, with higher alcohol and other drug disorders . In Canada, individuals consuming alcohol between the ages of 11 and 14 had more risk for developing alcohol disorders compared with those who started drinking alcohol after the age of 19 .

Donoghue et al. in a study conducted in the UK likewise found a strong association between age of the first alcohol consumption, before the age of 15, tobacco use, lower quality of life, and emergency room admissions for alcohol use disorders among adolescents. Similarly, a recent systematic review of prospective studies highlighted the impact of early first alcohol use on future alcohol use disorders . In a birth cohort study, Newton-Howes and Boden demonstrated that early age of first drug use significantly increased the risk for later alcohol use disorders, nicotine dependence, and illicit drug dependence. However, after controlling for covariate factors, such as family living standards, ethnicity, and childhood sexual abuse, earlier first substance use was found to have no significant associations with these SUDs . In an Australian study, young age substance exposure was associated with later poly drug use, such as methamphetamine and heroin . In contrast to the above evidence, other research found no statistically significant associations between early-age substance use and later SUD . A few studies conducted in SSA reported the age at onset of only two types of psychoactive substances, alcohol , and tobacco . In youth tobacco surveys from nine Western Africa countries, Veeranki et al. found that the age of smoking onset was as early as 7 years old. Osaki et al. in a Tanzanian secondary school and college students aged 15–24 found that the age of alcohol consumption was as early as 10 years old. Contextual factors for alcohol use onset included exposure to a stressful environment, social events, and home alcohol consumption under the influence of parents, relatives, peers, and intimate partners . Likewise, a systematic review for cross-country comparison by Townsend et al. demon-strated that tobacco use primarily began in late adolescence and early adulthood in SSA. However, Townsend et al. found no association between tobacco use and socioeconomic status or urban/rural difference.

The strength of the association be-tween first substance use to SUD seems to be moderated by contextual factors. Variations in the strength of associations between first substance use and SUD may be partially explained by environmental factors, such as life adversity and conflict-related psychology strains . In the recent UK Millennium Cohort Study of 10,498 11-year-old participants, having a friend who drank was a strong risk factor for increased alcohol use patterns . Besides, McCann et al. indicated that relationships, including higher levels of parental control and lower levels of child openness to parents, were linked with less frequent alcohol use. Furthermore, child-hood traumatic experiences in the forms of severe and mild physical abuse significantly correlated with an earlier age at first alcohol consumption, as well as illicit and poly drug use . Other factors, such as premorbid cognitive deficit early-age major depression , bipolar disorders , and impulse control influence early-age substance use and addiction trajectory following first substance. Additionally, interactions between premorbid mental health deficits and the effects of substance use on cognitive development may influence the early substance use onset and rapid spirals into substance dependence . Overall, there is little and inconsistent evidence on the association between early age at first substance use and later severe addiction issues worldwide. While the associations between PTSD and SUD are well documented, little is known about how young age substance use coupled to PTSD contributes to later severe addiction. Likewise, PTSD has been studied somewhat in SSA and substantially in Rwanda ; however, there is minimal data on associated substance misuse. The identified studies focused on a few substances and did not examine the transition from first use to addiction and contributors to later addiction severity.Addiction severity was measured using the Addiction Severity Index lite version . The ASI assesses disturbances during the previous 30 days across seven domains, including medical status, employment/occupation status, alcohol use, drug use, legal status, family/social status, and psychiatric status. Calculations of addiction severity weight were guided by the ASI composites score weighting instructions .

The total score on all seven composites is seven, i.e., a maximum score of one at each composite, and a high overall rating indicates severe addiction problems. This ASI weighting procedure for each of addiction severity areas has been validated and showed significant convergent validity and has a high predictive validity . The study that tested the scale found good reliability with an alpha coefficient of at least 0.70 across all composites . The present study had an overall Cronbach’s alpha coefficient of α 0.68.Data analysis was conducted in IBM Statistical Package for Social Sciences, 26th version. Initially, analyses consisted of conducting descriptive statistics for sociodemographic variables and bivariate analyses between addiction severity and potential confounding variables, including the level of education in years , areas of residence, sex, motives,plant bench indoor living with active alcohol, and non-prescribed drugs using one-way analysis of variance . Then, a hierarchical regression model consisted of entering the age at first substance use, followed by the other variables, PTSD as well as the level of education, area of residency, as both of which showed significant bivariate relationships with addiction severity. Regression diagnostics were performed to check whether there were potential violations of the linear regression assumptions.The present study examined the extent to which age, motives for the first substance use, and PTSD influence later addiction severity. The study results demonstrate that first substance use occurs as early as 5 years old. Half of the sample have had their initial psychoactive substance before or at their 18th birthday. The majority of participants were male , which suggests that fewer female participants sought addiction services in Rwandan mental health settings during the study period. This gender difference in addiction service utilization may require further exploration. The study results also suggest that the Rwandan clinical cohort had the first substance use 2 years earlier compared with other SSA populations . Among the study participants, substance use patterns could be as severe as using seven different types of psychoactive substances, and up to nearly three times daily. The identified substance patterns are worrisome because of potential increases in risks for negative neurobiological changes that result from regular substance and polydrug use, especially before the brain fully matures. Such brain changes have the potential to contribute to maladaptive cognition, motivation, and affective states throughout a person’s entire lifetime . In many ways, the study results support previous studies which indicated that early-age exposure to substance use increases risks for severe addiction. The results suggest that delayed first substance use may be associated with a significant reduction of risks for addiction severity. Such risks may vary with the type of substance consumed. Previous research has shown significant associations between poor mental health outcomes, such as psychosis onset, and age at onset of cannabis use but not of alcohol use . Progressing from first cannabis use to cannabis use disorders takes a shorter time than for alcohol and nicotine, whereas poly substance use speeds up transitions to addiction disorders . By establishing the contribution of age at first substance use and addiction severity, these results reinforce previous findings on the progression of addiction trajectories following the first substance use .

The study also supports previous evidence on increased risks for poly substance use among individuals exposed to earlier psychoactive drug use . As such, the present study results call for research testing the effectiveness of health promotion and prevention interventions aimed at delaying the age of exposure to first substance use. The implementation of such interventions may face difficulties since drinking cultural norms, in some SSA countries, permit alcohol drink during childhood, especially at family social events. Moreover, long-term instability predominant in SSA countries may add to the complexity of earlier substance use. Long-term instability may lead to the absence of adults moderating how and when young people can drink and use of a substance to self-medicating for post traumatic disorders. The present study further underscores the influence of PTSD on later complications of addiction problems after early-age first substance use. Besides, coupling PTSD and young age at first substance use indicate a statistically significant increase in addiction severity . The identified increase in variance explained by PTSD emphasizes that PTSD is a significant predictor of later addiction severity among individuals who face early substance use problems. These results are consistent with previous research, which associated early childhood experience of trauma with early substance use onset and transition to poly drug use . Additionally, previous handful evidence has consistently established associations between SUD and PTSD and provided explanatory hypotheses underlying these associations. Given that at SSA populations such Rwandans had experienced horrific events , these results may be interpreted through well-documented risky use of psychoactive substances for coping with post disaster distress . However, it is challenging to delineate which of the two conditions occurs first because SUD and PTSD affect the stress processing system. Chronic SUD, such as alcohol use disorders, increased individual vulnerability to PTSD due to alcohol related defects of endocrinal response to distress events and reduced cortisol release . On the other hand, PTSD influences neurotransmitters changes, such as serotonin, in the hypothalamic-pituitary-adrenaline axis, which have been linked to risks for worsened SUD . The identified positive association between level of education and addiction severity may be partially explained by the Rwandan cultural and conception of mental illness.Thus, educated people may find it challenging to seek early help for their SUD due to fear of being subject to attached stigma and use psychoactive substances as self-medication.The present study, to our knowledge, is the first to investigate the contributions of age, motives for first substance use, and post traumatic distress to later addiction problems using a clinical sample in sub-Saharan Africa. The study used a compelling alternative to the random sampling strategy, recruiting every participant presenting for inpatient addiction care in two existing settings over 8 months. This study has a few limitations, including relying on self-reported data that may be prone to recall and social desirability biases. However, we attempted to minimize these biases by collecting data through face-to-face semi-structured interviews conducted by trained and qualified mental health professionals who were not part of a healthcare circle .The state of California has the second-lowest smoking prevalence in the United States . For more than 30 years, the state has devoted tobacco tax revenues to building community capacity, changing social norms about tobacco, and providing support for local tobacco control programs.

However, college students are a heterogeneous population, and not all require the same level of intervention . To our knowledge, no one has examined the influence of an alcohol intervention on marijuana use when alcohol interventions are provided sequentially in the context of stepped care, in which individuals who do not respond to an initial, low-intensity level of treatment are provided a more intensive treatment . The purpose of the current study was to examine marijuana use in the context of a stepped care intervention for alcohol use.We conducted a secondary analysis of data from a randomized clinical trial implementing stepped care with mandated college students . In this study, all participants received a brief advice session administered by a peer counselor. Participants who continued to drink in a risky manner six weeks following the BA session were randomly assigned to either BMI or AO conditions . Step 2 participants who completed the BMI as opposed to AO reported greater reductions in alcohol-related consequences at all follow-up assessments . We tested three hypotheses to examine whether interventions that reduce alcohol-related outcomes may also reduce marijuana use. First, because dual marijuana and alcohol users consume higher levels of alcohol use and experience more alcohol-related consequences , we hypothesized that marijuana users would report higher HED frequency, peak blood alcohol content , and alcohol related consequences in the 6 weeks following a BA session, after controlling for their pre-BA drinking behavior. Second, we hypothesized that heavy-drinking marijuana users who did not respond to the BA session and, therefore, were randomized to a Step 2 BMI or AO would report worse alcohol-related outcomes at 3-, 6-, and 9-month follow-ups than non-users. Third,rolling benches canada we examined whether marijuana users changed their marijuana use frequency at any of the three assessment time points following the Step 2 BMI. Examination of marijuana use in this context will improve our understanding of whether marijuana use lessens the efficacy of alcohol interventions, even when delivered sequentially in stepped care.

Furthermore, it will inform future intervention efforts aimed at reducing both alcohol and marijuana use.Participants indicated how many times they used marijuana in the past 30 days at baseline and at each follow-up assessment time point. Because marijuana use was highly zero-inflated , and due to our interest in whether being a marijuana user influenced intervention outcomes, dichotomous variables were created to group individuals into user versus non-user for use in analyses to compare these subgroups.To determine if participants who completed Step 1 of the intervention would also complete Step 2, participants reported the number of times they engaged in heavy episodic drinking , defined as consumption of 5+ drinks for males , in the past month. The maximum number of drinks consumed during their highest drinking event in the past month and the amount of time spent drinking during this episode were used to calculate the students’ estimated peak blood alcohol concentration using the Matthews and Miller equation and an average metabolism rate of 0.017 g/dL per hour.Alcohol-related consequences were assessed using the Brief Young Adult Alcohol Consequences Questionnaire , a 24-item subset of the 48-item Young Adult Alcohol Consequences Questionnaire . Dichotomous items are summed for a total number of consequences experienced in the past month. The B-YAACQ is reliable and sensitive to changes in alcohol use over time and has demonstrated high internal consistency in research with college students . In this study, the B-YYACQ demonstrated good internal consistency at baseline, 6-week and follow-up assessments .First, distributions of outcome variables were examined, and outliers falling three standard deviations above the mean were recoded to the highest non-outlying value plus one , resolving initial non-normality in outcomes. Demographic information and descriptive statistics for the outcome variables were calculated . To examine marijuana users’ drinking behavior following BA for alcohol misuse , multiple regression models were run to predict each alcohol outcome variable at the 6- week assessment from baseline marijuana user status , controlling for gender and the corresponding alcohol outcome assessed at baseline.

To test hypotheses 2 and 3, hierarchical linear models were run in the HLM 7.01 program , using full maximum likelihood estimation. HLM is ideal for data nested within participants across time, for testing between-person effects and within-person effects on outcomes. An additional advantage of HLM is its flexibility in handling missing data at the within-person level, allowing us to retain for analysis any participant that contributed at least one follow-up assessment. We interpreted models that relied on robust standard errors in the determination of effect significance. All intercepts and slopes were specified as random in order to account for individual variation in both mean levels of the outcomes and time-varying associations. Fully unconditional HLM models were run first in order to determine intraclass correlations for each outcome. ICCs provided information on the percentage of variation in each outcome at both the between- and within-person level. Next, three dummy coded time components were created for inclusion at Level 1. The first was coded and therefore allowed examination of the impact of effects on change in the outcome variable from baseline to the first followup, the second was coded to model the impact of effects on change in the outcome variable from baseline to the second follow-up , and the third was coded in order to estimate the impact of effects on change in the outcome variable from the first to the third follow-up . In the context of these three dummy codes, effects on the intercept represent effects when all time effects are equal to 0 . Of note, as all participants received a BA session in the interim between the true baseline and 6-week assessment, marijuana user status at the 6-week assessment was used as the baseline for these analyses .To address hypothesis 2 , Level 2 effects for marijuana user status, treatment condition, and the interaction between marijuana user status and treatment condition were regressed on the three time components. Following recommendations of Aiken and West , prior to forming interactions, marijuana user status and treatment condition were recoded using effects coding ,flood table to remove collinearity with interaction terms so that all main effects of time could be evaluated in the context of models including interactions. To control for potential baseline group differences, we also regressed marijuana user status and treatment condition on the intercept. To address hypothesis 3 [i.e., whether treatment group impacts marijuana use frequency at any of the three follow-up time points, among those who reported marijuana use at 6-week pre-BMI assessment], at Level 2, treatment condition was regressed on the Level 1 intercept and all three time effects of marijuana use frequency. In models for both hypotheses 2 and 3, at Level 2, gender also was included as a covariate.

Descriptive statistics for the full sample of 530 are presented in Tables 1–2. Among participants randomized to BMI or AO in Step 2 , the person-period data set was represented by 392 participants with complete baseline data , each with up to 3 follow-up assessments. Across these participants, we have complete data for a total of 1084 out of 1176 assessments . Specifically, 368 participants completed the 3- month follow-up, 349 completed the 6-month follow-up, and 367 completed the 9-month follow-up. The ICC for alcohol consequences was 0.63 meaning that 63% of the variance in consequences is due to between-person differences, while 37% is due to within-person differences across the follow-ups. The ICCs for HED frequency and pBAC were 0.53 and 0.52, respectively. In the subset of participants who reported marijuana use at the pre-BMI assessment and were therefore included in hypothesis 3 analyses, the ICC of marijuana frequency was 0.59. In all cases, a two-level model was appropriate.Multiple regression models indicated that baseline marijuana user status was not associated with changes in HED frequency, pBAC, or alcohol consequences following the BA session .Results of the HLM models predicting three alcohol outcomes at each follow-up by marijuana user status, treatment condition, and marijuana user status by condition interactions are displayed in Table 4. In the prediction of HED frequency, marijuana user status was associated with higher baseline HED frequency; however, being a marijuana user was not associated with more or less change in HED frequency between the pre-BMI assessment and any of the three follow-ups. There were no interactions between marijuana user status and treatment condition at any follow-up, suggesting that the BMI was not more or less effective for marijuana users. In the prediction of pBAC, marijuana user status was associated with higher pre-BMI pBAC. Additionally, those in the BMI condition had significantly lower pre-BMI pBACs. Controlling for these pre-BMI differences, being a marijuana user, treatment condition, and their interaction were all non-significantly associated with change in pBAC from pre-BMI to each of the follow-ups. In the prediction of alcohol consequences, being a marijuana user was associated with higher pre-BMI levels of consequences. There were no significant effects of marijuana user status, treatment condition, or their interaction on change in consequences between baseline and either the 3- or the 6- month follow-ups. At the 9-month follow-up, those in the BMI reported fewer alcohol consequences1 ; however, this was not moderated by marijuana user status. Overall, these findings suggest that collapsing across treatment condition, marijuana users had heavier alcohol consumption and consequences compared to non-users at the pre-BMI assessment, but they did not increase or decrease their consumption or consequences between pre-BMI and any of the follow-ups.

Additionally, marijuana users responded to the BMI similarly to non-marijuana users at each time point .The purpose of the current study was to examine whether heavy drinking marijuana users demonstrate poorer response to two different alcohol-focused interventions compared to non-users and to examine the efficacy of an alcohol-focused BMI on marijuana use frequency among marijuana users receiving stepped care for alcohol use. Our findings indicated that marijuana users and nonusers evidenced equivalent treatment responses to the alcohol-focused BA session and reported similar alcohol-related outcomes following the BMI. Consistent with prior research , the alcohol-focused BMI did not significantly reduce marijuana use frequency in comparison to the assessment-only group. In our sample, marijuana users did report higher alcohol consumption and problems at baseline/pre-BMI regardless of condition, and these differences between users and nonusers persisted over time. The findings of the current study are somewhat consistent with studies indicating that marijuana use does not decrease the efficacy of alcohol interventions . Although marijuana use did not necessarily lessen the efficacy of the BA and BMI sessions on alcohol use and consequences, regardless of condition, marijuana users reported higher levels of alcohol consumption and consequences at baseline and the pre-BMI assessment. These patterns suggest that heavy drinking marijuana users may still benefit from alcohol use interventions. This is especially noteworthy because dual users typically report increased consequences related to their alcohol use and may have a higher likelihood of being referred to alcohol-focused treatment or mandated to receive intervention for alcohol-related sanctions. Although heavy drinking marijuana users may demonstrate reductions in alcohol consequences following an alcohol-focused intervention , their frequency of marijuana use did not change as a result of receiving a BMI. We can posit several reasons for the participants’ continued use of marijuana, despite a decrease in alcohol-related consequences. First, the parent study found a reduction in alcohol consequences following the alcohol-focused BMI, but not a decrease in alcohol consumption. Prior research examining secondary effects of alcohol BMIs have noted a decrease in marijuana use when there was also a decrease in alcohol consumption . It could be that factors that result in students’ experiencing fewer alcohol-related consequences without changing their drinking differ from ones that would lead to reductions in alcohol or marijuana use. Although our study did not include a measure of marijuana-related consequences, future research should examine changes in marijuana consequences to investigate whether changes in alcohol-related consequences correspond with changes in marijuana consequences following alcohol-focused BMIs. Second, a lack of effects may be due to the fact that our BMI was focused solely on changing alcohol-related behaviors and did not discuss the participant’s marijuana use.

There are substantial uncertainties in the risk assessment of odorants, the greatest being how likely it is that the individual odorants monitored actually are the main contributors to the overall odor sensed. Missing the key odorants invalidates the study. OPM can help identify key odorants that have been compiled into odor wheels . The exposure measurements tend to have less uncertainty than the thresholds against which they are evaluated. ODTC50 values typically range over several orders of magnitude, and the health hazard thresholds incorporate one-to-three orders of magnitude of uncertainty factors in their extrapolation from animal data. Even under controlled conditions using test odorants, panelist threshold testing by dilutions resulted in interlaboratory variation in results up to 4-fold . Accordingly, most risk characterizations are crude, screening-level evaluations that require further refinement if thresholds are approached by exposure estimates. For the experimental and epidemiology studies, all suffer from the problem of self-reporting and the inherent variability in human response, which clearly varies by sex, age, pre-existing health conditions and prior experiences. Epidemiological studies of odor and health have notably weak exposure assessments, and experimental studies suffer the lack of standardized exposure methods and difficulty carrying out blinded studies . So far, no toxicological study has been able to separate the health effects of odors from those of the co-pollutants in the mixture . The health effects reported by residents living near odor sources may be due to odorless co-pollutants with odor serving as a marker of exposure . Few epidemiology studies, however,drying cannabis look at this possibility. Proximity to an odor source would be a determinant; however, residence distance to the source was often a poor predictor of odor induced health complaints.

The sole experimental study of odor , which was discussed in Section 4.3, could not separate the effects of odors from those of co-pollutants in the mixture.Risk perception plays a large role in how exposures to odors can lead to annoyance and outrage. Risk perception has been defined as how the exposed judge the severity of the risk and involves personal and cultural values and attitudes. Different perceptions of risk are applied to involuntary, imposed exposures, man-made sources and the unfamiliar. Odors often encompass all three of these factors. Key worries from odor exposures include long-term health ailments such as asthma or lung cancer , ability to socialize at one’s own property that is odor impacted, and potential decrease in property value . These perceived risks likely are experienced disproportionately by disadvantaged communities. The air monitoring of the community north of Denver was funded by USEPA as an environmental justice study , and a community well-being study followed shortly thereafter . Participants took an online survey four times over a year. The results at the community level showed that odor-impacted communities had no difference in well-being than the control communities. Individual results, however, showed that respondents who reported that the air was “very fresh” or “odor is highly acceptable” had higher levels of well-being. This finding supports other studies that indicate that unpleasant odors lead to annoyance, general psychological stress, and reduced quality of life. Researchers in Australia studied environmental justice and odors around Melbourne . They used a novel cluster approach to represent communities affected by odor and concluded that self-reported odor exposure correlated with indicators of socioeconomic disadvantage in the community clusters affected by odor.Large gaps exist in the dataset used to evaluate the health risks posed by odors. Chief among these is the lack of dose-response studies for total odor exposure rather than just for individual odorants.

Only a single experimental study of odor mixture exposure and health effects has been conducted . Clearly, more studies are needed, especially measuring physiological and psychological responses simultaneously so correlations can be determined. Longitudinal “before-and-after” epidemiology studies are needed to determine the magnitude of impact of installing an odor-emitting facility near a neighborhood. For example, the large health-effects study in California after the natural gas leak in Aliso Canyon would benefit from pre-leak community health data. To aid exposure assessment, analytical techniques and sampling require improvement. For one set of odorants – additives to natural gas to impart odor – broad availability of laboratories with the capability to measure sulfur compounds at sufficiently low detection limits is both a health and a safety need .In the United States, approximately 20% of adolescents and young adults have a mental health or substance misuse disorder, and these disorders account for a significant portion of the burden of disability for individuals in this age group. These behavioral disorders are associated with other areas of risk including higher rates of suicide, injury, risky sexual activity and unwanted pregnancy and low educational or work achievement. Despite the recognition of the significant short- and long-term impacts of behavioral health disorders on development and the availability of effective treatments, only about one-third of adolescents with a diagnosable behavioral disorder receive appropriate care. Rates of mental health treatment decrease further as adolescents transition into young adulthood. Of particular concern, only half of adolescents who meet criteria for “severe” impairment from a mental health disorder report having received care and only 40% of 18e25 year olds with a serious mental illness that impairs functioning report receiving treatment. On average, 10 years pass from the initial onset of a mental health disorder and seeking treatment, with younger age at onset associated with longer delays in treatment.

One approach to reducing delay in treatment and improving treatment delivery is the development of models aimed at improving recognition and treatment for behavioral health disorders in primary care settings through the integration of behavioral health services into medical settings. In the United States,ebb flow it is estimated that 84% of adolescents have an outpatient visit and 66% have a well checkup annually and 70% of young adults report having a source of primary care. Among adolescents who are seen in primary care settings, 14%e 38% have been found to meet criteria for a mental health disorder. Several studies have also shown high rates of mental health comorbidity among individuals with chronic medical illnesses commonly seen in primary care, which when present is associated with higher levels of medical symptom burden, health care costs, and worse medical outcomes. A recent meta-analysis of integrated behavioral health trials across pediatric age groups found that they had a small-to-moderate effect improving the outcomes of mental health and substance use disorders. Thus, the integration of care has the potential to improve outcomes for both behavioral and physical health. In this article, we aim to specifically review research regarding models of integrated behavioral health in primary care settings among adolescent and young adult populations with the aim of describing needed areas of research.To be included, studies had to be focused on older adolescents and/or young adults , examine patient outcomes, have a comparison group, offer an integrated or health care provider-led intervention for a behavioral health condition in primary care, be published in English, and be conducted in 2004 or later. Studies of adult populations that did not specifically examine young adults separate from the older adult population were not included. For the purposes of this review, we considered school based health clinics and college health clinics to be primary care settings. We excluded studies that recruited from the primary care setting but did not have evidence of collaboration or care delivered in that setting, as well as those conducted in the broader school setting such as classroom or campus-wide interventions. We only included those focused on treatment or secondary prevention in at-risk individuals. As the intent was to look at alcohol and illicit drug misuse, tobacco use interventions were not included. In total, when duplicates were excluded, the systematic searches identified 1,086 potential articles of which 1,032 did not meet inclusion criteria based on review of the title or abstract . We conducted full-text article reviews for the remaining 54 articles plus an additional 3 articles identified via bibliographies of identified literature for a total of 57. Of these 57, 36 articles were excluded. The reasons for exclusion included the following: pilot or feasibility trial with no comparison group , repeat use of a study sample without the presentation of new patient outcomes , intervention not in a primary care setting , not intervention trial , and no behavioral outcomes provided.

Based on full-text review, 21 trials were identified for inclusion. As detailed in Table 1, studies meeting inclusion criteria were conducted in multiple countries including the United States , Australia , New Zealand , South Africa , and multiple countries . All included studies were reviewed for quality by two independent reviewers using the US Preventive Services Task Force Quality Rating Criteria for Randomized Controlled Trials and Cohort Study Criteria . Differences in scores were subsequently reconciled via discussion between reviewers. To promote accurate comparison, studies identified in our review were organized into three groups with increasing levels of integration. Groups were determined a priori based on the framework outlined in the 2010 report on Evolving Models of Behavioral Health Integration in Primary Care: “coordinated care,” “co-located care,” and “integrated care”. In “coordinated care models,” primary care providers work with community-based behavioral health specialists to provide care. The behavioral health specialist may serve as an advisor to the primary care provider without seeing the patient or can provide direct care with a coordinated exchange of information. Educational interventions that aim to enhance primary care provider skills with support and oversight by mental health providers also fit into this category. In “co-located care models,” primary care and behavioral health providers are located in the same setting to simplify the referral process, enhance communication between providers, and remove patient barriers to care. “Integrated care” refers to models of care with a shared treatment plan between providers with both behavioral and health elements. These models often involve a multidisciplinary team working together using a predefined protocol and a “population-based approach” to tracking outcomes in order to assure improvement for the entire patient panel. Our review identified a total of 21 randomized controlled trials with behavioral health outcome measurement among adolescents and young adults: 17 in the category of “coordinated care,” 0 in the category of “co-located care,” and 4 in the category of “integrated care.” Results are discussed by category below, and details of specific studies within each category are provided in Table 1.Our review identified 17 studies meeting the criteria for “coordinated care.” Eight studies described interventions in which enhanced behavioral health care was provided by the primary care provider. One study examined provider communication skills training aimed at increasing patient and family engagement in behavioral health care and found improvements in parent-reported child functioning for minority, but not white, youth. Five studies examined the effectiveness of provider training in screening, brief motivational interviewing, and referral for substance misuse among adolescent and young adult populations and found the use of these methods to be effective in reducing alcohol or other substance misuse, increasing patient’s readiness to change substance misuse behaviors, and/or decreasing consequences of substance misuse. One additional study found that training providers to implement a behavioral health contract paired with consultation among college students reduced the frequency of drinking and driving but not overall substance misuse. A final study found that screening coupled with access to a telephone-based parenting intervention was associated with reductions in child aggressive and delinquent behaviors and attention problems. Seven studies examined technological approaches to providing behavioral health care in the primary care setting. Four examined computer-facilitated brief intervention for substance misuse for adolescent and young adults either with or without brief advice from the primary care provider and found such strategies to be effective in reducing substance misuse. In one of these studies, even a single dose of computer-facilitated motivational interviewing showed sustained effects for a year. The remaining three studies used technological interventions to improve outcomes for depression. One study examined the use of mobile health symptom-tracking technology for adolescent and young adult depression and found significant improvements in provider reported skills and patient-reported emotional self-awareness but not in mental health outcomes or treatment engagement.

The scale is 0 to 5 , and extrapolations to 0 are used to predict the ODTC50. This approach has led to good agreement with ODTC50 values from the literature. Another odor-intensity measurement system is used more widely than OPM. ASTM Standard E544 uses various vials with dilutions of n-butanol in water to assign n-butanol-equivalent concentrations to the intensity of a given sample. The upper limit of this equivalency scale appears to be the saturation limit of n-butanol in water rather than a sensory upper limit. The intensity of the odor sample is expressed in mg/L of n-butanol, with a larger value of indicating a stronger odorant. Whole-sample, undiluted total odor analysis is relatively straightforward. Determining the odor notes can lead to indications of the source and even a subset of the individual odorants. An odor-intensity rating of the overall mixture, however, is more controversial and less useful. Duration information can be added to a decision-making matrix, too. For example, a field panel made observations using OPM at three off-site and four on-site locations at a trash transfer station .As an odor mixture is diluted, the odor notes and hedonic tones change and eventually, after sufficient dilution, the concentration of the final detectable odorant drops below its odor detection threshold so the diluted sample becomes “odorless” . The amount of dilution required to reach this point is considered an indicator of the odor intensity of the initial, undiluted sample, which is problematic because the final detectable odorant may not be indicative of the odorant that dominated the odor of the undiluted sample . Relying on dilution quantities to indicate the intensity of the total odor is crude at best and misleading at worst. Further, presenting a dilution quantity as a measure related to the mass of odorants in the undiluted sample,mobile vertical rack when in reality it measures only the final detectable odorant, adds an unknown amount of uncertainty to such claims. Portable dilution instruments can be used by field investigators . In the United States, such instruments include the Nasal Ranger® and Scentroid SM100 .

Both mix the ambient air being sampled with odorless air at variable ratios.This term tends to be reserved for field measurements, while OU tends be reserved for indoor panels. Both are dilution levels and not mass-based concentrations. A mixture of odorants was tested using both devices . The Nasal Ranger®, which has settings from 2 to 60 dilutions, performed well between 3 and 30 dilutions. For the Scentroid SM100, which has set points from 3 to 101 dilutions, the settings were about half what the test actually showed, possibly due to odorant sorption to internal surfaces. Field dilution devices avoid the need for sample collection, storage and transport. They may have sorption issues, however, and appear to be better suited for low odor concentrations.Field odor measurements may also involve a panel, such as the use of OPM at an impacted school near a landfill site in California , a trash transfer station in California and a landfill in France . For the landfill study , an abbreviated version of the grid and plume methods discussed next were applied on a single day as well as OPM. The dominant odor notes were “rotten vegetable” and “rancid,” which had high or medium odor intensities. According to the landfill odor wheel, the associated odorants were fatty acids and sulfur compounds , which have very low odor thresholds. Confirmation of odorants by GC-MS-sensory was not performed. In Europe, field panels are central to the grid and plume methods . Figure 3.6 includes general guidance for such a field panel, Figure 3.7 shows how the grid method is applied, and Figure 3.8 shows how the plume method is applied. Both methods require trained panelists to decide whether they recognize an odor note selected from a list. The grid method is applied over a sufficiently long period of time to provide a representative map of the exposure of the population to recognizable odors. Field panelists write down their observations every 10 seconds for 10 minutes . If 6 of those observations are a recognized odor note, then the label “odor hour” is applied . The plume method is used to determine the area in which an odor plume can be perceived under specific meteorological conditions.

The odor-plume boundary is where the odor no longer is detectable, and panelists mark yes/no on a map as they walk through and out of the plume. Adding OPM to the grid or plume method provides an intensity scale and can indicate suspected odorants from odor wheels .To confirm and support the sensory analysis of environmental odor exposures, traditional analytical chemistry air monitoring methods are used. A substantial review of analytical and sensory methods for odor measurement was conducted previously . The methods that have advanced since then are the focus of this section . The other methods are covered briefly for completeness. The comparative advantages and disadvantages of these methods are discussed in Section 4.4. Chemical analysis is most appropriate in cases where known single odorants are responsible for an odor, as opposed to diverse mixtures of odorants. The list of odorous compounds that may be measured is virtually endless. For example, over 400 odorants were detected from swine facilities . Although the level of each odorant was low, the overall mixture led to extremely strong odor intensities. In this case and others, sensory measurements lead to better estimates of odor intensity than analytical measurements. Analytical measurements are only performed for risk assessment when method detection limits are sufficiently low to be below the hazard benchmarks of concern. To achieve such, the human nose is typically required for odor assessment. Although the identification and quantification of specific odorants does not directly indicate the potential odor nuisance, the information is useful for identifying and tracking odor sources . Further, it can help indicate the reactions leading to odorant formation, especially microbial reactions at WWTPs, landfills and composting sites.Gas chromatography, which separates and quantifies odorants, is useful for complex mixtures of chemicals at trace levels, especially on-site where concentrations are higher. Recent advances include two-dimensional and multidimensional gas chromatography , which decrease the analytical problems associated with peak overlap.

Both aid in odorant identification. Although detection reaches ppb levels , trace odorants still go undetected, as do odorants that are unstable during sample collection and transport . Identification of unknown peaks from gas chromatography is typically by mass spectrometry and its libraries of thousands of known compounds. However, even knowing the identity of an odorant does not tell how it contributes to the overall odor of a mixture. Such instruments are expensive, as is there operation and maintenance.A new, albeit even more expensive, instrument has been used for odor investigations called “selected ion flow tube mass spectrometry” . It is transportable and can detect and quantify the concentrations of 20 to 50 odorants real-time,vertical grow rack even if the levels are changing rapidly. The SIFT-MS instrument directly measures components of the air by first using chemical ionizing agents on the sample followed by mass spectrometry . The chemical ionizing agents include cations and anions . The ions are generated at the inlet by a microwave-powered ion source of moist air. The analyte concentration is found from the ratio of the product ion counts to the reagent ion counts, the flow rate, and instrument calibration. Low-ppb detection has been achieved.Gas chromatography with a sensory port , often performed in tandem with mass spectrometry , is a hybrid technique that brings together the separation of odorants and the sensitivity of the human nose. The sensory port allows the analyst to smell the eluting compounds at the same time the instrument detector makes a reading. When successful, it can indicate which odorants contribute to the total odor. Recent advances in GC-sensory methods include improved GC-port interfaces, increasing the number of simultaneous panelists , bi-dimensional GC techniques and sophisticated data processing . Disease detection is an emerging use of GC-sensory.Gas-specific sensors can target key odorants but not the total odor. They are often portable, relatively inexpensive, and continuously log data. The most common gas-specific sensors are for hydrogen sulfide and ammonia. Detection is through chemical, electrochemical, catalytic or optical signals. Some can reach ppb levels. Hydrogen sulfide, however, does not account for the entire odor nuisance. At WWTPs, hydrogen sulfide levels can be well controlled and monitored continuously, yet nuisance odor complaints persist . Benzene, a carcinogen, is a problem emitted from oil refineries and gasoline stations, as well as from the semiconductor industry. Advanced sensors using metal-oxide detectors have been developed that can work in various levels of humidity and interferants .Improved sensor technologies and advanced computational techniques have merged to produce non-specific gas-sensor arrays that try to mimic the human sense of smell. Often called an “electronic nose” or “e-nose,” a bank of up to 30 sensors generates a complex electronic signal that is processed through computer algorithms.

The result is a reading – but not a true “fingerprint” – for a known odor that then can be compared to signals from future samples to see if they match. When properly calibrated, e-noses should continuously detect the presence of odors in ambient air, estimate concentrations of odors, and attribute the odor to a specific odor source . The sensors are typically a variety of metal oxides, conducting polymers and oscillating quartz crystals; however, new sensor materials are under development continually. As with all sensors, they are subject to the effects of temperature and humidity, degradation, poisoning and the need for frequent re-calibration to address drift. It is difficult to find e-noses used outside of research laboratories , which confirmed the observation by Muñoz et al. that their initial promotion had been overly optimistic. Nonetheless, e-noses developed within laboratories, plus accompanying field tests, have led to numerous publications and several recent reviews of the emerging field. Under controlled situations, e-noses have monitored odors. Australian researchers observed that the e-nose for chicken odor worked in-shed yet was unreliable beyond the shed . Today’s e-noses function well for the context for which they are designed but do not yet cover broad environmental odor monitoring . A workgroup in Europe was launched in 2015 to develop a standard for e-noses . One area under development is stack monitoring, where the conditions are more predictable than ambient monitoring yet harsh on the equipment. Producing minimum performance standards and other essential criteria will help guide the field. Unlocking the molecular features that trigger our sense of smell may someday lead to improved e-noses. Keller et al. supplied chemoinformatic data and sensory data on 407 molecules to teams so they could develop predictive algorithms. The algorithms were tested on 69 molecules, and the results were favorable for 8 odor notes out of 19 total. With successful reverse-engineering of the smell of a molecule and then combining that with appropriate sensors, a true e-nose that fully mimics the human nose may be achieved some day. Other technologies have adopted the “e-nose” name, such as portable, fast gas chromatographs or mass spectrometers . Even “electronic mucosa” is under development. In the nasal cavity, natural mucosa acts like the stationary phase of a gas chromatography column to differentially apportion odorants. “Electronic mucosa” consists of multiple sensor arrays, each separated by gas-chromatograph-like micro columns. The rich data set obtained could predict the presence of odorants at low concentrations .No single approach can successfully address nuisance odor complaints . Human panels provide some of the strongest information yet, due to the variable perception of odors, yield inconsistent results. Chemical analysis provides confirmation of exposure to specific odorants yet may miss the key odorants. Instead of a single method, the right mix of sensory and analytical methods needs to be used . The Odor Profile Method followed by GC-sensory conformation provides one of the strongest tools today. The use of standard odorants to calibrate panelists has been advocated since the 1970s . The use of n-butanol, however, has not led to transferability of results to non-butanol odors according to a review of 412 odor measurements .

Even much slower trains of action potentials result in a buildup of Ca2 in pyramidal cell dendrites. This Ca2 level perfectly correlates with spike frequency ; therefore, it may induce endocannabinoid release in an activity-dependent manner, if coupled to a coincident activation of the IP3 cascade and releases Ca2 from intracellular stores. The probability of bursts was found to be highest at firing rates around theta frequency , and bursts at this frequency are particularly suitable for inducing LTP in hippocampal pyramidal cells . Acetylcholine release in the hippocampus is large during theta activity, and it correlates with theta power , while muscarinic receptor activation induces Ca2 transients . Therefore, theta is likely to be the behavior dependent EEG pattern that best couples burst-induced Ca2 influx with metabotropic activation of IP3/DAG synthesis. Endocannabinoid release that follows the resulting high Ca2 transients may reduce perisomatic inhibition of the burst-firing cells, which could facilitate LTP of distal dendritic synapses by allowing a more efficient back propagation of action potentials. Interestingly, acetylcholine appears to use at least three different mechanisms to enhance communication between the soma and distal dendrites: 1) it is able to close transient K channels in the apical dendrites , 2) it reduces GABA release from parvalbumin-containing basket cell terminals via presynaptic m2 receptors , and 3) it may induce endocannabinoid release to reduce inhibition deriving from the other subset of perisomatic inhibitory cells, i.e., from those that contain CCK and express presynaptic CB1 receptors . Another result of endocannabinoid-mediated down regulation of perisomatic inhibition may be that individual cells could dissociate the timing of their action potential firing from network oscillations during theta activity.

During exploratory behavior and theta activity pyramidal cells tend to fire in specific areas of their environment,grow cannabis which are called place fields . When the animal enters the place field of the recorded neuron, it starts to fire at earlier phases of the theta waves relative to the population, which was called phase precession . Burst firing starts to occur preferentially at the periphery of the place field , creating, together with muscarinic receptor acivation, ideal conditions for endocannabinoid release. This would result in a gradual down regulation of basket cell-mediated inhibition, allowing the cell to fire at earlier and earlier phases of the theta cycle. The cell could still fire phase-locked to gamma oscillation, if the other basket cell population is able to convey this effect. The timing of the presumed endocannabinoid effect also seems optimal for this function, since the onset of DSI is 1.2 s after the somatic Ca2 rise, and lasts for a few seconds, or occasionally for 10 s . Another EEG pattern accompanied by synchronous pyramidal cell firing at relatively high frequencies are the sharp-wave bursts, which occur during non-theta behaviors . These events, however, are rather short , and whether this is sufficient for endocannabinoid synthesis/release remains to be established. Nevertheless, the synchronous burst discharge of a large proportion of pyramidal cells may result in extensive Ca2 influx, activation of mGluR5 receptors, and the synthesis of IP3/DAG . The induced endocannabinoid action may start suppressing inhibition within a few hundred milliseconds, leading to down regulation of inhibition and the generation of the next sharp wave burst. The variable second messenger delay may account for the irregular occurrence of sharp waves and may explain why the same pyramidal cells initiate the subsequent bursts.Dravet syndrome is a debilitating developmental disorder typified by severe seizures and delayed onset of psychomotor deficits. The symptoms start within the first year of life with prolonged, febrile and afebrile generalized seizures in children with no overt developmental disabilities and progress to severe and often refractory epileptic encephalopathy; seizures decrease in frequency and severity with sexual maturity .

In addition to increasing the risk for sudden unexpected death in epilepsy , the medically refractory status epilepticus in DS can be life-threatening, which makes it crucial to identify drugs to reduce seizures. Additionally, the delayed social and cognitive development and movement disorders that persist even after the seizures abate contribute to long-term morbidity in DS. The quest for a viable drug to limit seizures in DS has intersected with the recent excitement over the potential use of cannabinoids as antiepileptic agents, leading to extensive anecdotal reports of the potential for cannabinoids to limit seizures in DS . Cannabinoids are active derivatives of the marijuana plant, Cannabis sativa. While Δ9 tetrahydrocannabinol acting through the cannabinoid receptor type 1 contributes to the psychoactive effects of marijuana, cannabidiol is a nonpsychoactive cannabinoid that has been proposed to limit seizures . CBD has low affinity for classic cannabinoid receptors; rather, it blocks signaling through the recently “deorphanized” cannabinoid-related G-protein receptor 55 . CBD is promiscuous and, at nanomolar to millimolar concentrations, targets several classes of transient receptor potential channels, including thermosensitive subtypes, enzymes involved in energy and endocannabinoid metabolism and sodium channel subtypes . While the anecdotal reports and emerging evidence of beneficial effects of CBD in DS are intriguing , preclinical validation of this effect is lacking. Moreover, given the multiple targets of CBD, identifying the mechanisms underlying the beneficial effects of CBD in DS can guide dosing strategies to maximize the therapeutic potential while limiting adverse outcomes. In a majority of cases, mutations in the sodium channel gene SCN1A form the genetic basis for DS . Scn1a+/− mice phenocopy human DS, exhibit both thermally induced and spontaneous seizures, and develop autism-like social deficits, which makes them an excellent model to study the mechanisms and therapeutic options in DS . The loss of function in Nav1.1 channels in Scn1a+/− mice selectively reduces sodium current and excitatory drive in GABAergic interneurons contributing to epileptogenicity.

The study by Kaplan and colleagues effectively uses the Scn1a+/− DS model to shed light on the therapeutic potential for CBD and the synaptic and receptor mechanisms involved.They find that CBD pre-treatment reduces both duration and severity of thermally-induced behavioral seizures. Similarly, DS mice examined at 3-4 weeks of age, when spontaneous seizures peak,indoor cannabis grow system showed a striking reduction in seizure frequency 4 hours following high dose CBD treatment. Additionally, CBD treatment improved deficits in social interactions, reduced defensive escapes and reduced increases in locomotion observed in DS mice. Curiously, only low dose CBD improved social interactions whereas considerably higher doses were required to limit seizures and hypermobility. The effect of CBD on synaptic excitation and inhibition was examined in dentate granule cells in ex vivo slices from DS mice by perfusing CBD at peak brain concentrations observed with high dose CBD treatment. In the presence of glutamate antagonists, CBD increased the frequency of action potential dependent inhibitory postsynaptic currents in granule cells without altering amplitude or frequency of action potential independent mini-IPSCs. Simultaneously, CBD reduced both spontaneous excitatory postsynaptic currents and granule cell excitability. CBD effects on granule cell sEPSCs and excitability were abolished by GABAA receptor antagonists suggesting that the effects of CBD on the excitatory circuit are secondary to changes in inhibition. Direct examination of parvalbumin interneurons in non-DS reporter mice, revealed that CBD reduced the minimal current needed to elicit firing and enhanced the rate of firing during suprathreshold current injections, demonstrating that CBD enhances inhibitory neuron excitability. Mechanistically, although the CB1R antagonist enhanced granule cell IPSCs, it did not occlude CBD enhancement of IPSC frequency indicating that CB1R receptors are not necessary for CBD action. In contrast, the GPR55 antagonist mimicked the effects of CBD on granule cell IPSCs and excitability and occluded CBD effects on granule cell sIPSCs and interneuron excitability. Together Kaplan and colleagues provide the first preclinical demonstration that CBD treatment could offer acute symptomatic relief in DS. The data show that high-dose CBD acts, in part, by blocking GPR55, which leads to an increase in interneuron excitability. The demonstration that CBD can suppress both seizure and autism-like symptoms in DS mice is important for the potential clinical utility of CBD to reduce both mortality and morbidity in DS. However, since the study, by design, was restricted to acute drug effects, it would be important to examine whether the effects persist with prolonged use and evaluate the potential for disease modification. The determination that GPR55 signaling contributes to CBD-mediated restoration of synaptic inhibition in DS mice provides valuable insights into the potential mechanism underlying the anticonvulsive effects of CBD. While the study addresses the ability of high-dose CBD to modify network excitability, the processes underlying the effects of low-dose CBD on behavior remain to be determined. The study revealed an exquisite dose specificity of CBD on seizures versus behavior, which is important to consider in a clinical setting. Although different molecular and circuit specific mechanisms likely underlie the high-dose and low dose-effects of CBD, it is conceivable that effects of low-dose CBD on electrical seizures may have been missed due to the exclusive focus on behavioral seizures.

GPR55 is expressed in hippocampal glutamatergic terminals where it enhances glutamate release but shows limited expression in GABAergic neurons . Whether GPR55 is selectively expressed in parvalbumin interneurons or overlaps CB1 expressing interneurons in the dentate needs to be examined to appreciate the circuit effects of CBD/GPR55 signaling. Still, mechanisms mediating GPR55 modulation of interneuron rheobase and excitability remain to be identified. Although, effect of CBD/GPR55 on action potential threshold was not determined, it is possible that GPR55 could modulate sodium channels as has been reported in recombinant systems . Detailed understanding of the molecular underpinning of anticonvulsive and behavioral effects of CBD would be crucial to mitigate DS symptoms while limiting potential off-target effects of CBD. In conclusion, Kaplan and colleagues provide the first preclinical demonstration that CBD may help alleviate seizures in a mouse model of DS validating the translational potential of CBD in patients with DS. The study identifies GPR55 as a potential target through which CBD transiently reverses the network level imbalance between synaptic excitation and inhibition observed in DS mice. The exciting finding of dose-dependent effects of CBD on DS symptoms is sure to spur additional studies on the cell-type specificity of GPR55 expression and the functional effectors underlying its modulation of active neuronal properties. The demonstration that CBD improves deficits in social interactions in DS launches an exciting therapeutic possibility of alleviating behavioral impairments that persist beyond the seizures and pave the way for mechanistic studies that could positively impact treatment of autism spectrum disorders.Treatment-seeking individuals with an alcohol use disorder exhibit a range of neurocognitive and inhibitory control deficits. A recent review describes deficits related to working memory, visuospatial functions, inhibition, and executive-based functions such as mental flexibility, problem solving, divided attention , and cognitive control.Of clinical relevance, inhibitory control deficits are greater in actively drinking alcoholics compared to controls and they predict relapse in AUD . Research has also noted deleterious effects on neurocognition from chronic cigarette smoking, the most common substance use comorbidity in AUD, with rates in treatment seeking populations estimated at 60–90% . Greater smoking severity in AUD predicted worse executive function , and smoking AUD performed worse than nonsmoking AUD on domains of auditory-verbal learning and memory, processing speed, cognitive efficiency, and working memory at one week and four weeks of abstinence . Furthermore, smoking was shown to significantly hinder recovery of visuospatial learning and processing speed in AUD . A large proportion of treatment-seeking AUD have a concurrent substance use disorder , with 1.3 million people in the United States alone in 2013 ; therefore, this group is better described as “poly substance users” , a term used in the literature to describe AUD who meet dependence criteria for additional substances . Given the cognitive and inhibitory control deficits observed in AUD studies, it is not surprising that recently detoxified individuals with a substance use dependence diagnosis on any combination of heroin, alcohol, methamphetamine, and/or cannabis also performed worse than controls on several measures of executive function, including working memory, response inhibition, cognitive flexibility, and on inhibitory control measures of decision making . Individuals with both alcohol and stimulant dependence performed worse than controls on cognitive efficiency , complex attention and memory as well as delayed discounting .

Such an “inverted U” dose-response relationship warrants further investigation but may be explained by the activation of different cannabinoid receptor types, likely possessing distinct agonist sensitivity , or by the dose-dependent engagement of excitatory or inhibitory afferent pathways of the basal forebrain, which may enhance or reduce the intrinsic activity of cholinergic neurons. In any case, the predominant effect of presynaptic CB1 receptors present on cholinergic axon terminals within the cortex is likely to be the inhibition of acetylcholine release, although such an effect alone may not entirely explain cannabinoid actions on cognition .Along with cholinergic fibers, ascending noradrenergic pathways are also sensitive to cannabinoid modulation . Norepinephrine release is inhibited by cannabinoid agonists, albeit in a species-specific manner, being reduced in human and guinea pig hippocampus and cortex, but not in rat hippocampus or mouse hippocampus, neocortex, and amygdala . These species differences are intriguing, especially in light of the highly conserved distribution of CB1 receptors on the axon terminals of hippo campal GABAergic and septohippocampal cholinergic neurons . In the rat locus coeruleus, where ascending noradrenergic pathways originate, CB1 mRNA expression is very low . Thus it would be interesting to determine whether a diverging pattern of CB1 receptor expression might explain the greater sensitivity of human and guinea pig noradrenergic transmission to cannabinoid regulation.The finding that cannabinoid agonists reduce both electrically and Ca2-evoked serotonin release in mouse brain cortical slices accords with the prevailing presynaptic localization of CB1 receptors. But whether serotonergic terminals do in fact contain such receptors is still unknown. Notably, the observed maximal reduction in serotonin release is quite low compared with other transmitters like acetylcholine or GABA . Furthermore,marijuana grow system in situ hybridization studies in the raphe nuclei have yielded inconsistent results , and immunohistochemical investigations have not yet been reported.

As we have already pointed out, CB1 receptors are located on the axon terminals of a specific GABAergic cell population in several cortical networks characterized by the expression of CCK . Therefore, it is not unexpected that cannabinoid agonists inhibit potassium-evoked CCK release in rat hippocampal slices . More surprising, however, and still unexplained, is the observation that CCK release is unchanged in the frontal cortex . This discrepancy is surprising in light of the coexpression of CB1 and CCK in the entire neocortex and in the hippocampus . In addition, the observed maximal reduction of cholecystokinin was only 40% in the hippocampus, which seems to be quite low considering the fact that nearly all CCK-containing axon terminals carry CB1 receptors in this brain region . Clarifying this point is particularly important in view of the possible interactions of CCK and anandamide in regulating anxiety and other emotional states .CB1 cannabinoid receptors are expressed by at least three different GABAergic cell populations in the striatum . Hence, cannabinoid effects on GABA release in different regions of the basal ganglia are well documented, and solid evidence for presynaptic cannabinoid receptors on GABAergic axon terminals derives from several different pharmacological approaches. Application of cannabinoid agonists to parasagittal slices of the rat midbrain causes a significant reduction of GABAA receptor-mediated currents recorded in sustantia nigra pars reticulata neurons after stimulation of the internal capsule . Comparable results were obtained in coronal midbrain sections, although in this preparation GABAergic currents are more likely to derive from local GABAergic interneurons . The presynaptic nature of these responses is supported by the increased paired pulse ratio of evoked IPSCs and by the lack of cannabinoid modulation on GABAA receptor-mediated currents elicited by bath application of GABA . In vivo experiments have provided additional insight on the roles of CB1 receptors on striatonigral GABAergic terminals . Both systemically and locally applied cannabinoid agonists increase spontaneous activity of substantia nigra pars reticulata neurons, probably by removing an ongoing GABAergic inhibition .

Moreover, striatal stimulation inhibits the firing of nigral neurons, which is also alleviated by cannabinoids. Blocking of GABAA receptors by bicuculline reverses this effect, indicating that cannabinoid treatment suppresses GABA release . Striatal stimulation also results in reduced firing of pallidal neurons, and this effect is antagonized by systemic administration of a cannabinoid agonist . Surprisingly, local administration of the compound into the globus pallidus does not reverse this effect, raising doubts as to the role of striatopallidal GABAergic projections . Although cannabinoid binding is lower in the striatum compared with its output structures, it is still quite abundant . In addition, endocannabinoid release and local cannabinoid receptors may participate in the modulation of striatal neuronal activity . Szabo´ et al. provided electrophysiological evidence that cannabinoids inhibit the amplitude of IPSCs recorded from medium spiny neurons. One presumptive site for this action is the axon terminals of intrinsic inhibitory interneurons , which provide the major inhibitory control over the activity of striatal projection neurons . The contribution of recurrent axon collaterals of medium spiny neurons cannot be excluded at present. In the shell of the nucleus accumbens, cannabimimetic agents decrease the amplitude of evoked IPSCs and increase the paired-pulse ratio, but do not alter the amplitude of miniature IPSCs, indicating a presynaptic inhibitory effect on GABA release . In situ hybridization and immunostaining studies of this region report low CB1 receptor levels , but this low signal may simply reflect a restricted distribution of the receptor to select interneuronal subtypes, as is the case elsewhere in the CNS. The important functions served by the nucleus accumbens in motivational and reward processes and the impact that cannabinoid drugs exert on such processes should encourage further studies aimed at establishing the precise localization of CB1 receptors in this structure.The glutamatergic innervation of the basal ganglia derives from three main sources. Neurons in the striatum receive glutamatergic axon terminals from cortical and thalamic projection neurons, whereas neurons in the substantia nigra pars reticulata and globus pallidus receive glutamatergic input from the subthalamic nucleus. Both pathways can be modulated by cannabimimetic agents, which inhibit excitatory postsynaptic currents in the striatum as well as the substantia nigra pars reticulata .

The increased paired-pulse ratio and coefficient of variation, together with the lack of effect of cannabinoids on response to bath-applied glutamate, support a presynaptic site of action. In addition, currents evoked by direct glutamate application are not modulated by cannabinoids, demonstrating the lack of a postsynaptic component in these effects. A recent study by Gerdeman et al. provided definitive evidence that the reduction of glutamate release in the striatum is mediated by CB1 receptors,cannabis vertical farming by showing that this effect is absent in CB1 /_x0005_ mice. Furthermore, these authors also demonstrated that the ability of cannabinoid agonists to acutely inhibit glutamate release is a crucial factor in the initiation of striatal long-term depression , a form of synaptic plasticity characterized by a persistent diminution in excitatory transmission. The cannabinoid modulation of glutamatergic neurotransmission in the globus pallidus and the substantia nigra pars reticulata may be of considerable functional importance . Indeed, in contrast to striatal GABAergic projections to the output nuclei, which are usually quiescent, the subthalamic glutamatergic innervation to these two structures is tonically active. The administration of cannabinoid agonists produces changes in the firing of pallidal and nigral neurons, which are consistent with a decrease in this intrinsic activity . It will be interesting to determine whether the endocannabinoid system plays a similar role and, if so, under which physiological circumstances. In the nucleus accumbens, cannabinoid agonists reduce the amplitude of field excitatory postsynaptic potentials as well as EPSCs recorded from medium spiny neurons in the core, but not the shell region of this nucleus . The relatively high cannabinoid concentrations required to produce these effects, and the low expression of CB1 receptors in the projection neurons of the prefrontal cortex, basolateral amygdala, and thalamus that innervate the nucleus accumbens, suggest that in this region, as in the hippocampus , cannabimimetic agents target a CB1-like receptor distinct from CB1. However, the possibility that the reduced cannabinoid sensitivity may reflect the very low expression level of CB1 receptors in glutamatergic neurons cannot be excluded, and recent experiments demonstrating that evoked EPCS are not modulated by cannabinoids in CB1 knock-out mice may also favor this explanation .The cerebellum contains one of the highest densities of CB1 receptors in the brain. Expression of these receptors in local GABAergic interneurons has been suggested by many studies, whereas Purkinje cells do not contain CB1 mRNA . Immunostainings revealed CB1-positive putative GABAergic axon terminals forming a pericellular matrix around the axon initial segment and cell body of Purkinje cells or impinging upon their dendritic tree . In accordance, GABAergic synaptic currents recorded from Purkinje cells are strongly modulated by cannabinoids.

Takahashi and Linden provided the first evidence that spontaneous IPSCs are suppressed by cannabinoid agonists. They estimated that the amplitude of action potential-dependent IPSCs is reduced by 75%, whereas the amplitude of miniature IPSCs is not affected, suggesting a presynaptic mechanism of action. Subsequent experiments using paired recording and imaging of calcium transients in inhibitory axon terminals confirmed this observation and extended it, by showing that endocannabinoids may also regulate afferent inhibitory inputs to Purkinje cells in a retrograde manner . Verifying the role of CB1 receptors, this response is absent from CB1 /_x0005_ mice .In the cerebellum, as in many other brain regions, cannabinoids can effectively modulate neurotransmission not only at inhibitory but also at excitatory synapses. Two pathways provide excitatory input to the cerebellum, the climbing fibers originating from the inferior olive and the parallel fibers deriving from local glutamatergic granule cells. Early anatomical studies reported a high density of cannabinoid binding sites in the molecular layer of the cerebellar cortex along with the expression of CB1 mRNA in granule cells , indicating, but not proving, the presence of CB1 receptors on parallel fibers. Subsequent immunohistochemical experiments supported this notion by revealing a dense CB1-positive axonal mesh work in the molecular layer . Hence, CB1 receptors are situated in a central position to modulate the excitatory input of Purkinje cells. Indeed, whole cell patch-clamp studies revealed that cannabinoids effectively decrease parallel fiber EPSCs . Experimental evidence supports a presynaptic effect, in which activation of cannabinoids results in a reduced probability of glutamate release. Neither the excitability of parallel fibers nor the response to locally applied glutamate was modified by cannabinoid receptor agonists . Moreover, although the frequency of miniature EPSCs was decreased, the amplitude was also unchanged, indicating the presynaptic localization of cannabinoid receptors. An important consequence of this phenomenon is that cannabinoids may impair cerebellar long-term depression . In addition, recent experiments uncovered that endocannabinoids also serve as retrograde signaling molecules in DSE, a phenomenon discussed in detail in section V . In contrast to the cannabinoid effects on parallel fibers, the localization of cannabinoid receptors on climbing fibers seems to be more modest. While a cannabinoidagonist strongly reduced the amplitude of parallel fiber EPSCs , EPSCs deriving from putative climbing fibers were only slightly modulated . However, experimental evidence shows that modulation of glutamate release at climbing fibers is also under the control of endocannabinoids released by the postsynaptic Purkinje cells . In this case, the role of CB1 receptors is not clear yet, because only low levels of CB1 mRNA were found in the inferior olive, where climbing fibers originate . Recent data also suggest the existence of additional cannabinoid binding sites in the cerebellum distinct from CB1, although the molecular identity and precise localization of these putative sites is still unknown .One common feature of the regulatory actions of these compounds is their ability to reduce inhibitory neurotransmission in the rostral ventromedial medulla, the PAG, and the trigeminal nucleus caudatus . Patch-clamp experiments revealed that in these three structures cannabinoid agonists reduce GABA release through a presynaptic mechanism. In the trigeminal nucleus, the release of another inhibitory transmitter, glycine, is also reduced . Although the presynaptic localization of cannabinoid receptors is confirmed by several experiments, the role of CB1 receptors remains equivocal. In addition, detailed studies clarifying the precise localization of CB1 receptors at the subcellular level in these brain areas have not yet been conducted.

The fact that the cannabinoid antagonist SR141716A prevents these effects suggests that AM404 may act by preventing anandamide inactivation and enhancing its interactions with cannabinoid receptors. Importantly, however, AM404 also can be transported inside cells , where it may reach levels that are sufficient to inhibit anandamide degradation by FAAH . The target selectivity of AM404 has been investigated in some detail. Initial studies showed that AM404 has no affinity for a panel of 36 potential targets, including G protein-coupled receptors, ligand-gated channels, and voltage-dependent channels . Subsequent work suggested, however, that AM404 may activate the capsaicin sensitive VR1 vanilloid receptor in vitro . It is unlikely that this effect occurs in vivo, since AM404 does not display any of the pharmacological properties of a vanilloid agonist . Yet, these findings underscore the need to design novel inhibitors of anandamide transport endowed with greater target selectivity. Ongoing research efforts in this direction have led to the development of several arachidonic acid derivatives that are equivalent or slightly superior to AM404 in inhibiting anandamide transport in vitro and in vivo, with effects similar to those of AM404 . Consistent with its low affinity for CB1 receptors, AM404 does not act as a direct cannabinoid agonist when administered to live animals. The compound has no antinociceptive effects in the mouse hot-plate test and does not reduce arterial blood pressure in the urethaneanesthetized guinea pig . In the same models, however, AM404 magnifies the responses elicited by exogenous anandamide, actions that are prevented by the CB1 antagonist SR141716A . Furthermore, when administered alone, AM404 reduces motor activity , attenuates apomorphine-induced yawning , decreases the levels of circulating prolactin , and alleviates the motor hyperactivity induced in the rat by striatal 3-nitropropionic acid lesions . These actions resemble those of anandamide and are blocked by SR141716A ,growing cannabis outdoors suggesting that endogenous anandamide may be involved. In keeping with this notion, systemic administration of AM404 in the rat causes a time-dependent increase in circulating anandamide levels .

The participation of anandamide in the effects of AM404 in vivo has been questioned based on the ability of this compound to interact with vanilloid receptors in vitro . Yet, the fact that SR141716A blocks the motor inhibitory actions of AM404 at doses that are selective for CB1 receptors strongly argues for a predominant, if not unique, role of the endocannabinoid system in the behavioral response to AM404 administration. Furthermore, the pharmacological properties of AM404 are very different, often opposite to those of capsaicin and other vanilloid agonists. For example, capsaicin produces pain and bronchial smooth muscle constriction , whereas AM404 has no such effect when administered alone, and in fact enhances anandamide’s analgesic and bronchodilatory actions . The ability of intraperitoneal capsaicin to inhibit movement, described by Di Marzo et al. , superficially mimics one property of AM404, but should be viewed with caution, as it most likely results from the strong visceral pain and subsequent “freezing response” elicited by capsaicin. In conclusion, current evidence suggests that AM404 may magnify the actions of anandamide primarily by inhibiting the clearance of this compound from its sites of action.Almost a decade before anandamide was discovered, Schmid and collaborators identified a hydrolase activity in rat liver that catalyzes the hydrolysis of fatty acid ethanolamides to free fatty acid and ethanolamine . That anandamide may be a substrate for such an activity was first suggested by biochemical experiments and then demonstrated by molecular cloning, heterologous expression, and genetic disruption of the enzyme involved . FAAH is an intracellular membrane-bound protein whose primary structure displays significant homology with the “amidase signature family” of enzymes . It acts as a hydrolytic enzyme for fatty acid ethanolamides such as anandamide, but also for esters such as 2-AG and primary amides such as oleamide . Site-directed mutagenesis experiments indicate that this unusually wide substrate preference may be due to a novel catalytic mechanism involving the amino acid residue lysine-142. This residue may act as a general acid catalyst, favoring the protonation and consequent detachment of reaction products from the enzyme’s active site . This mechanism was recently confirmed by the solution of the crystal structure of FAAH complexed with the active site-directed inhibitor methoxy arachidonyl fluorophosphonate .

In addition to FAAH, other enzymes may participate in the breakdown of anandamide and its fatty acid ethanolamide analogs. A PEA-hydrolyzing activity distinct from FAAH was described in rat brain membranes and human megakaryoblastic cells . This activity was purified to homogeneity from rat lung and shown to possess a marked substrate preference for PEA over anandamide . PEA does not bind to any of the known cannabinoid receptors but produces profound analgesic and anti-inflammatory effects , which are prevented by the CB2-preferring antagonist SR144528 . Future studies will undoubtedly address the relative roles of FAAH and this newly discovered enzyme in the biological disposition of PEA and anandamide. The ability of FAAH to act in reverse has generated some confusion as to the mechanism of anandamide formation. Early reports of anandamide synthesis from free arachidonate and ethanolamine have now been unambiguously attributed to the reverse of the FAAH reaction . Because high concentrations of arachidonic acid and ethanolamine are needed to drive FAAH to work in reverse, it is unlikely that this reaction plays a physiological role in anandamide generation . One possible exception is represented by the rat uterus, where substrate concentrations in the micromolar range are required for the synthetic reaction to occur, implying that FAAH or a similar enzyme might contribute to anandamide biosynthesis in this tissue .Systematic structure-activity relationship investigations have identified several general requisites for substrate recognition by FAAH. First, FAAH accommodates a wide range of fatty acid amide substrates, but reducing the number of double bonds in the fatty acid chain generally results in a decrease in hydrolysis rate . Second, replacing the ethanolamine moiety with a primary amide yields excellent substrates. For example, the rate of hydrolysis of arachidonamide is two to three times greater than anandamide’s . Third, anandamide congeners containing a tertiary nitrogen in the ethanolamine moiety are poor substrates . Fourth,introduction of a methyl group at the C2, C1, or C2 positions of anandamide yields analogs that are resistant to hydrolysis, probably due to increased steric hindrance around the carbonyl group . Fifth, substrate recognition at the FAAH active site is stereoselective, at least with fatty acid ethanolamide congeners containing a methyl group in the C1 or C2 positions .

Finally, fatty acid esters such as 2-AG also are excellent substrates for FAAH activity in vitro .Early biochemical experiments showed that FAAH activity is abundant throughout the CNS, with particularly high levels in the neocortex,mobile vertical rack the hippocampus, and the basal ganglia . Subsequent investigations have confirmed this wide distribution. Thus, in situ hybridization studies in the rat have found that FAAH mRNA expression is higher in the neocortex and hippocampus; intermediate in the cerebellum, thalamus, olfactory bulb, and striatum; and lower in the hypothalamus, brain stem, and pituitary gland . Immuno histochemical experiments suggest that large principal neurons in the cerebral cortex, hippocampus, cerebellum, and olfactory bulb have the highest levels of FAAH immunoreactivity . For example, large pyramidal neurons in the neocortex are prominently stained together with their apical and basal dendrites in layer V . Moderate immunostaining is observed also in the amygdala, the basal ganglia, the ventral and posterior thalamus, the deep cerebellar nuclei, the superior colliculus, the red nucleus, and motor neurons of the spinal cord . A more recent study reported staining of principal cells and astrocytes in various regions of the human brain . However, the protein recognized by the antibody utilized in these experiments has an apparent molecular mass of 50 kDa , which does not correspond to that of native FAAH . Many FAAH-positive neurons throughout the brain are found in close proximity to axon terminals that contain CB1 cannabinoid receptors , providing important evidence for a role of FAAH in anandamide deactivation. Yet, there are multiple other regions of the brain where there is no such correlation, a discrepancy that likely reflects the participation of FAAH in the catabolism of other bio-active fatty acid ethanolamides, such as OEA and PEA .A number of inhibitors of anandamide hydrolysis have been described, including fatty acid trifluoromethylketones, fluorophosphonates, -keto esters and -keto amides , bromoenol lactones , and nonsteroidal anti-inflflammatory drugs . These compounds lack, in general, target selectivity and biological availability; thus attempts to use them in vivo should be interpreted with caution.The first are fatty acid sulfonyl flfluorides, such as palmitylsulfonylfluoride . AM374 irreversibly inhibits FAAH activity with an IC50 of 10 nM and displays a 50-fold preference for FAAH inhibition versus CB1 receptor binding . Systemic administration of AM374 enhances the operant lever-pressing response evoked by anandamide administration, but exerts no overt behavioral effect per se , raising the possibility that AM374 may protect anandamide from peripheral metabolism but may not have access to the brain. The second group of FAAH inhibitors is represented by a series of substituted -keto-oxazolopyridines, which are both reversible and extremely potent , but whose pharmacological selectivity and in vivo properties are not yet known. The third group is constituted by a class of aryl-substituted carbamate derivatives . The most potent member of this class, the compound URB597, inhibits FAAH activity with an IC50 value of 4 nM in brain membranes and an ID50 value of 0.1 mg/kg in live rats.

This compound has 25,000-fold greater selectivity for FAAH than cannabinoid receptors, which is matched by an apparent lack of cannabimimetic effects in vivo . The pharmacological profile of URB597, which is currently under investigation, includes profound antianxiety effects accompanied by modest analgesia .The generation of mutant mice in which the faah gene was disrupted by homologous recombination has shed much light on the role of FAAH in anandamide inactivation . FAAH /_x0005_ mice cannot metabolize anandamide and are therefore extremely sensitive to the pharmacological effects of this compound: doses of anandamide that are inactive in wild-type mice exert profound cannabimimetic effects in these mutants. FAAH /_x0005_ mice also have markedly elevated brain anandamide levels and reduced nociception . This finding is consistent with the roles of anandamide in the modulation of pain sensation and is supported by the analgesic activity of FAAH inhibitors . Recently, a single nucleotide polymorphism in the human gene encoding for FAAH, which produces a proteolysis-sensitive variant of the enzyme, was found to be strongly associated with street drug and alcohol abuse . This important observation reinforces the central role played by the endocannabinoid system in the control of motivation and reward .The fact that FAAH catalyzes the hydrolysis of 2-AG along with anandamide’s has prompted the suggestion that this enzyme may be responsible for eliminating both endocannabinoids. There is, however, strong evidence against this hypothesis. First, inhibitors of FAAH activity have no effect on [3 H]2-AG hydrolysis at concentrations that completely block anandamide degradation . Second, 2-AG hydrolysis is preserved in mutant FAAH /_x0005_ mice, which do not degrade either endogenous or exogenous anandamide . In agreement with these results, a 2-AG hydrolase activity distinct from FAAH has been identified and partially purified from porcine brain . This activity likely corresponds to monoglyceride lipase , a cytosolic serine hydrolase that converts 2- and 1-monoglycerides to fatty acid and glycerol . Several findings support this conclusion . First, heterologous expression of rat brain MGL confers strong 2-AG-hydrolyzing activity and MGL immunoreactivity to HeLa cells. Second, adenovirus mediated transfer of the MGL gene in intact neurons increases MGL expression and shortens the life span of endogenously produced 2-AG, without any effect on either 2-AG synthesis or anandamide degradation. Third, MGL mRNA and protein are discretely distributed in the rat brain, with highest levels in regions where CB1 receptors are also present . The distribution of MGL in the rat hippocampus is particularly noteworthy. The high density of MGL immunore activity in the termination zones of the glutamatergic Schaffer collaterals suggests a presynaptic localization of this enzyme at CA3-CA1 synapses.

But most clients do not quit using; on the contrary, many significantly increase their daily dose, so the intervention reduces their disorder on some criteria while possibly increasing their disorder by other criteria. Figure 1F, reproduced from Cramer et al. , illustrates the kind of elaborate causal network that Borsboom, Kendler, and their colleagues have recently proposed as a more realistic model for many traits. In their framework, latent constructs neither cause observed manifestations nor does an explicit subset of observed variables constitute the latent construct . Rather, the latent construct is an emergent property of the entire network. An implication of the causal structure in Figures 1E,F is even when simple 1- factor models fit the data, the fit may be spurious in that the model assumed by the equations may be very different than the model that validly describes the processes that generated the data. Moreover, combining them in an “any two of the following” recipe will obscure the valuable information contained in that causal structure. Judging from past experience, we might expect the next DSM to surface in about a decade. So in the spirit of constant improvement, I respectfully urge DSM developers to consider pursuing, in parallel, at least three kinds of alternative DSM candidates: a pure reflective model, a pure formative model, and a pure causal network model. One of the three may emerge as superior. But diagnostic systems attempt to serve multiple goals, and it may be advantageous to use different systems for different purposes. These arguments for greater theoretical and psychometric coherence might seem to have a sort of ivory-tower fastidiousness, if not outright neuroticism. After all, the perfect is surely the enemy of the good, indoor grow cannabis and the DSM does a good job much of the time, at least as judged by the utility that clinicians and managed care organizations seem to find in it. But I think there are good practical reasons for improving the coherence of the DSM substance use.

One is that it might provide a better linkage to drug policy. A decade ago, I argued that contemporary thinking about addiction was surprisingly inconsequential for major public policy debates about drug use, or for empirical drug policy analysis . The DSM-5 probably helps to close that gap, as it emphasizes the harmful consequences that citizens care about. On the other hand, the gap between the DSM and drug science may be growing rather than shrinking. For example, a recent review of seven major scientific theories of drug addiction examines whether each theory can account for various “addictive phenomena.” Of the seven theories, four offer an account of withdrawal and three an account of tolerance – two explicit DSM criteria. Six offer accounts of relapse, and four an account of binging – two phenomena that aren’t directly mentioned in the DSM but are closely related to other DSM criteria. But all seven offer accounts of craving, a criterion that only recently entered the DSM checklist. And four address “sensitization” – which is increasingly recognized as a signature feature of the etiology of addiction but receives no mention in the DSM.Judging from past experience, we might expect the next DSM to surface in about a decade. So in the spirit of constant improvement, I respectfully urge DSM developers to consider pursuing, in parallel, at least three kinds of alternative DSM candidates: a pure reflective model, a pure formative model, and a pure causal network model. One of the three may emerge as superior. But diagnostic systems attempt to serve multiple goals, and it may be advantageous to use different systems for different purposes. These arguments for greater theoretical and psychometric coherence might seem to have a sort of ivory-tower fastidiousness, if not outright neuroticism. After all, the perfect is surely the enemy of the good, and the DSM does a good job much of the time, at least as judged by the utility that clinicians and managed care organizations seem to find in it. But I think there are good practical reasons for improving the coherence of the DSM substance use. One is that it might provide a better linkage to drug policy.

A decade ago, I argued that contemporary thinking about addiction was surprisingly inconsequential for major public policy debates about drug use, or for empirical drug policy analysis . The DSM-5 probably helps to close that gap, as it emphasizes the harmful consequences that citizens care about. On the other hand, the gap between the DSM and drug science may be growing rather than shrinking. For example, a recent review of seven major scientific theories of drug addiction examines whether each theory can account for various “addictive phenomena.” Of the seven theories, four offer an account of withdrawal and three an account of tolerance – two explicit DSM criteria. Six offer accounts of relapse, and four an account of binging – two phenomena that aren’t directly mentioned in the DSM but are closely related to other DSM criteria. But all seven offer accounts of craving, a criterion that only recently entered the DSM checklist. And four address “sensitization” – which is increasingly recognized as a signature feature of the etiology of addiction but receives no mention in the DSM.Historically, molecular genetic research on AAB has been limited to the examination of a small number of candidate genes with purported biological relevance; only recently have researchers begun to conduct atheoretical genome-wide scans for this phenotype.In our genome-wide investigation, we found that autosomal SNPs accounted for ~ 25% of the variation in a dimensional measure of AAB. Although this estimate was not statistically significant ,growing cannabis which is likely attributable to our modest sample size, it maps nicely to meta-analytic findings that additive genetic influences account for 32% of the variation in antisocial behavior.Our finding also maps to recent GCTA analyses in a community-based sample, where it was found that common genetic variation accounted for 26% of the variation in a behavioral disinhibition phenotype.No SNP reached genome-wide significance in our GWAS of AAB. Our most associated SNP, rs4728702, was located in ABCB1 on chromosome. In our gene-based tests, ABCB1 was significant at the genome-wide level; however, we did not find an association for this gene in our replication sample. In expression analyses, we also found that ABCB1 is robustly expressed in human brain. This provides some biologically plausible evidence that ABCB1 variation could be associated with behavioral outcomes.

ABCB1 codes for a member of the adenosine triphosphate-binding cassette transporters, ABCB1 or P-glycoprotein, which transportmolecules across cellular membranes and also across the blood– brain barrier. ABCB1 is considered a pharmacogenetic candidate gene in view of ABCB1 transporters’ ability to change drug pharmacokinetics. Variation in ABCB1 has been previously associated with a number of psychiatric phenotypes, including opioid and cannabis dependence, as well as with treatment outcomes for depression and addiction.The related rodent gene, Abcb1a, is differentially expressed in three brain regions of alcohol preferring animals compared with non-preferring animals.Furthermore, ethanol exposure changes ABCB1 expression. An in vitro study of human intestinal cells found that ethanol exposure increased messenger RNA ABCB1 expression level, and that these increases were maintained even after a week of ethanol withdrawal.Similarly, ABCB1 expression was increased in lymphoblastoid cell lines following ethanol exposure,and in rodents, Abcb1a expression was increased in the nucleus accumbens of alcohol-preferring rats following alcohol exposure.Taken as a whole, this pattern suggests that ABCB1 has pleiotropic effects across a number of externalizing spectrum behaviors/disorders, and that its expression is affected by ethanol exposure. The former is consistent with findings from the twin and molecular genetics literature, demonstrating that common externalizing disorders and behaviors share genetic influences,and that this shared genetic factor is highly heritable .Supplementary analyses in our own sample were consistent with this hypothesis, and we found evidence that ABCB1 variation was associated with alcohol and cocaine dependence criterion counts. However, we did not find associations between ABCB1 and marijuana or opioid dependence criterion counts. We also found evidence for enrichment across multiple canonical pathways and gene ontologies including cytokine activity, Jak-STAT signaling pathway, toll-like receptor signaling pathway, antigen processing and presentation, cytokine receptor binding and natural killer cell-mediated cytotoxicity. Although the immediate biological relevance of these categories to AAB is not clear, these enrichment findings include many immune-related pathways and may be best interpreted in light of the associations among AAB and alcohol, cannabis, cocaine and opioid dependence criterion counts in the sample. Immune and inflammatory pathways have been hypothesized to be associated with psychiatric disorders across the internalizing and externalizing spectra.For example, it is known that alcohol alters cytokine activity,induces changes in neuroimmune signaling in the brain and that alcohol dependence is associated with low-grade systemic inflammation.

Likewise, the monocytes of individuals who are cocaine dependent show decreased expression of tumor necrosis factor-α and interleukin-6 proinflammatory cytokines in response to a bacterial ligand relative to controls.Four of the top genes to emerge in our analysis are genes for type I interferon , which reside in a cluster on chromosome 9p. Previous studies demonstrate that interferon A treatment of hepatitis C patients can induce multiple psychiatric symptoms including depression51 and impulsivity.Although we did not find significant enrichment for these pathways in our replication sample, these results add preliminary evidence to a growing literature that variation in genes in immune-relevant pathways may predispose individuals to AAB and closely related behaviors. The present study expands upon the initial AAB GWAS by Tielbeek et al. as well as more recently published GWAS of a behavioral disinhibition phenotype,in two important ways. First, we used a case–control sample where the cases met criteria for alcohol dependence. By virtue of the association between alcohol dependence and AAB, and the relatively high rates of individuals meeting clinical cutoffs for criterion A for ASPD in the present sample compared with American population-based prevalence estimates, it is likely that the sample was enriched for genetic variants predisposing individuals toward externalizing spectrum behaviors such as AAB. Previous work indicates that the genetic influences on AAB completely overlap with the genetic influences on alcohol dependence, other drug abuse/dependence and conduct disorder—that is, AAB does not have unique genetic influences above and beyond those shared with these other externalizing disorders.In view of this, gene identification efforts for AAB are likely to be more successful in more severely affected samples or in samples where participants high in AAB also tend to have comorbid alcohol or substance-use disorders, such as the COGA sample. In contrast, for example, only 6% of the participants in the Tielbeek et al. community-based sample met their nondiagnostic AAB case criteria. This sample may also have had low rates of comorbid alcohol and other drug diagnoses, limiting the ability to find genome-wide significant effects. Second, we used a dimensional measure of AAB, which is more powerful than a binary diagnostic variable, and better represents the underlying dimensional structure of AAB.These differences may explain, in part, why we were able to detect a significant genetic association in the present sample.First, our sample size was relatively small. Second, because the COGA case–control alcohol dependence sample is highly affected by AAB, the findings emerging from our study may not generalize to lower-risk populations or other types of high-risk populations. Our null replication attempt may be attributable, in part, to the replication sample being relatively less affected than the discovery sample. There are other instances where genetic associations for externalizing behaviors have replicated within highly affected samples, but not less-affected samples. For example, GABRA2 is associated with alcohol dependence in samples where alcohol-dependent cases came from clinically recruited samples and families densely affected by alcoholism,but not community-based samples.A sample recruited for this purpose is likely to be enriched for genetic variation that predisposes individuals to a range of externalizing behavior problems, including AAB;however, whether our findings generalize to other populations at high risk for AAB is unknown. Third, because we limited the current analyses to European-Americans, our results may not generalize to other racial and ethnic groups. Fourth, similar to all psychiatric outcomes, antisocial behavior has a developmental component, and evidence from the twin literature suggests that there are genetic influences on adolescent and adult antisocial behavior that are distinct from genetic influences on child antisocial behavior.

Importantly, we examined the association of alcohol use and ART adherence in the context of other important variables such as use of other substances , major depressive disorder , global cognitive function. We hypothesized that PLWHA who are at-risk drinkers will have lower ART adherence than PLWHA who are not at-risk drinkers, and that at-risk alcohol use will still be significantly predictive of ART adherence when controlling for substance use, MDD, and global cognitive function. Participants consisted of 535 HIV-infected adults enrolled in NIH-funded research studies at the University of California, San Diego HIV Neuro behavioral Research Program from 2003 to 2015. The current study is a secondary analysis of existing data from each participant’s baseline visit at the HNRP. All participants were receiving ART at the time of the visit and reported drinking alcohol in the previous 30 days. Measures Non-adherence to ART was determined based on 1) response to part of the self-report AIDS Clinical Trial Group Questionnaire indicating any missed ART doses in the previous four days, or 2) detectable plasma HIV RNA .Alcohol use was measured using the HNRP Substance Use History form, which is a timeline follow-back measure of the amount of daily alcohol used in the previous 30 days. Participants were stratified based on the daily limit defined by the NIAAA guideline for individuals at risk for developing an AUD: >3 drinks per day for women and >4 drinks per day for men, hereafter referred to as “at-risk drinking.” Individuals who consume more than these daily limits are at a near fourfold increase risk of developing alcohol abuse and a seven fold increase risk of developing alcohol dependence compared to those who drink within those limits. Current and lifetime substance use disorders and major depressive disorder were identified via the Composite International Diagnostic Interview .

Global cognitive function was measured via a standardized battery of well-validated neurocognitive tests [see Heaton et al. for descriptions of tests in this battery]. For all neurocognitive measures,vertical grow shelf raw scores were converted to demographically adjusted T scores used to construct one summary Global Mean T score. Unadjusted association between at-risk drinking and adherence was assessed using simple logistic regression. A multi-variable logistic model was used to regress the adherence measure on at-risk drinking adjusted for covariates. Potential covariates included demographic characteristics ; current AUD and current cannabis use; lifetime AUD; lifetime substance use disorder for cannabis, cocaine, hallucinogens, inhalants, methamphetamine, opioids, phencyclidine , sedatives, and other substances combined; current and lifetime major depressive disorder ; global cognitive function; estimated years of HIV infection; and ART regimen type. Current use disorders for substances other than alcohol and cannabis were not considered in this analysis because of low frequencies of participants with such diagnoses. Covariates were considered for inclusion into a multi-variable model if they either showed an association with the adherence measure or differed between drinking level groups at a 0.10 significance level. Group comparisons were done with two-sample t-tests for numeric covariates and chi-square or Fisher’s exact tests for categorical covariates. Backward model selection was applied and the final model was chosen to include only the predictor of primary interest and the covariates with pvalues less than 0.05. Odds ratio was used as the effect size for the strength of these associations, such that OR>1 would indicate a predictor’s association with higher odds of adherence. All analyses were performed using R version 3.2.1 statistical software .Seventy-nine participants endorsed missing an ART dose in the last four days, 46 of whom also had detectable plasma viral load. An additional 192 participants had detectable plasma viral load without reporting a missed ART dose in the last four days. Based on our criteria determining ART non-adherence , 271 participants were identified as ART non-adherent.

See Table 1 for a full list of sample characteristics. Approximately a quarter of the cohort met the criterion for at-risk drinking . Table 2 shows comparisons of demographic, psychiatric, and substance use characteristics between the two drinking level groups. Participants meeting the criterion for at-risk drinking were younger, less educated, and more likely to be diagnosed with lifetime alcohol use and lifetime cocaine use disorders. Table 3 lists results of univariable and multi-variable analyses. In unadjusted analyses, the at-risk drinking group was associated with significantly lower odds of adherence . 57.1% of the participants in the at-risk drinking group were identified as non-adherent compared to 40.3% of the participants in the not at-risk drinking group . Among covariates, older age, greater education, absence of lifetime cocaine substance use disorder and absence of lifetime MDD were associated with greater adherence at a 0.10 significance level. These covariates were included into multi-variable model selection along with three additional covariates that differed by group at a 0.10 level . Following the stepwise procedure, the final model included only at-risk drinking and education. The effects for the remaining covariates did not achieve a 0.05 significance level in the  multi-variable analysis. The adjusted effect of at-risk drinking remained significant . Education wasthe only other significant predictor, with OR=1.09, p=0.009 per one year increase. See Figure 2 for odds ratios and corresponding confidence intervals for at-risk drinking and education in the final model. Understanding the factors associated with ART non-adherence is critical for developing strategies to improve patient outcomes for those living with HIV/AIDS. Although alcohol use is broadly associated with worse ART adherence among PLWHA, there is little existing literature on the level of alcohol use that portends ART non-adherence. Results of the current study showed that persons with lower education and persons who meet the NIAAA criteria for at-risk drinking, which indicate consumption of a high level of alcohol per day, are more likely to be ART non-adherent compared to not-at-risk drinkers. This finding is consistent with the studies that have found a positive relationship between level of alcohol use and non-adherence to medications in samples of HIV-positive and HIV-negative participants . The most notable of those found that regardless of HIV status, binge drinking veterans were more likely to be non-adherent to medications on drinking days, post-drinking days, and non-drinking days compared to non-binge drinking veterans .

They also found a temporal association within each drinking level group, meaning that participants were most likely to be non-adherent to medications on drinking days, followed by post-drinking days and non-drinking days. For non-binge drinkers, this trend was significantly stronger in HIV+ participants compared to matched HIV- participants. For binge drinkers, the strength of the trend was comparable for HIV+ and HIV- participants,cannabis grow indoor suggesting that PLWHA may be more susceptible to medication non-adherence at lower levels of alcohol consumption compared to HIV- counterparts. The current study supports and augments these previous findings by demonstrating a similar alcohol-adherence association using the widely accepted NIAAA guideline that defines a daily level of alcohol consumption that puts individuals at risk for developing an AUD. Research has shown that individuals who drink within the NIAAA limits are at a much lower risk of having an AUD compared to those who drink beyond those limits . These standard NIAAA criteria are easy to assess and are a consistent method of stratifying alcohol use severity. The criteria for binge drinking, on the other hand, are defined differently by different governmental organizations , welcoming inconsistencies across studies that use binge drinking to stratify drinking level groups. The current study demonstrates that the daily limit defined by the NIAAA guideline for at-risk drinking provides a meaningful demarcation of drinking level in the context of ART adherence among PLWHA. Notably, after consideration of all potential covariates, education was the only other significant predictor in the final logistic regression model besides drinking level. The results showed that at-risk drinking was a better predictor of ART adherence than lifetime cocaine use and methamphetamine use. Although cocaine and methamphetamine use have been shown to have associations with ART adherence , there are several potential reasons why the results of this study found these relationships non-significant. First, alcohol is more widely used in our sample, as the studies conducted at the HNRP generally exclude participants who are current users of drugs other than alcohol and marijuana. Second, it is more socially and societally acceptable to report high levels of alcohol use than it is to report use of cocaine and methamphetamine. Last, we used a more informative variable for alcohol use compared to our variables for cocaine use and methamphetamine use .

That is, the results presented here do not necessarily point to alcohol use as more detrimental to ART adherence than use of other substances. In fact, poly-substance use was very high in our sample and level of alcohol use was found to be significantly associated with lifetime cocaine SUD. A potential future direction may be to more closely examine poly-substance use in the context of level of use for each substance. Despite the lack of significant associations between ART adherence and use of other substances, education showed a strong association to ART adherence. Previous research suggests that low education may be correlated with decreased ART adherence because each is associated with health literacy . Health literacy is defined as the ability to process and understand information about health and health services in order to make the best health-related decisions . Studies of health literacy among PLWHA have shown that higher education is associated with increased health literacy and that greater health literacy is associated with health status and ART adherence . The results of the current study may suggest that PLWHA with higher education may be more likely to understand and appreciate the importance of staying adherent to their ART regimen, even in the context of at-risk drinking. Education and health literacy among PLWHA who drink alcohol, however, has yet to be studied on its own. This is an important topic for future research and subsequent development of better interventions for improving health status among PLWHA, as level of education is immutable but health literacy can be easily enhanced. There are several strengths of the current study including the large sample size and a relatively large group of at-risk drinkers; however, this study also has some limitations. First, alcohol use data are self-reported. The HNRP Substance Use History form is a retrospective self-report assessment that relies on participants’ memory of past drinking patterns. Although most studies rely on self-report to measure alcohol use, requiring participants to give day-by-day or real-time reports may be more reliable. Additionally, we were not able to calculate weekly alcohol quantity from this measure. This might have aided our classification of at-risk drinkers, as the NIAAA guideline also specifies a weekly drinking limit for at-risk drinking ; however, previous research has shown that exceeding the daily limit is associated with a much greater risk of developing an AUD compared to that of exceeding the weekly limit . We also did not administer other alcohol screening tools such as the Alcohol Use Disorders Identification Test , which may have aided our characterization of severity of participants’ drinking patterns. Our adherence measure, using either self-reported non-adherence in the last four days or plasma HIV viral load detectability, also has limitations. We attempted to overcome the social desirability bias that is expected of self-reported adherence by using plasma viral load detectability as a proxy for adherence. Although viral load detectability does not equal nonadherence, non-adherence is likely the greatest indicator of viral detectability. Other reasons for viral load detectability, including virologic failure, drug resistance, and transient viral blips, are not very common and are often associated with ART non-adherence . Further, we did not collect data on other characteristics related to viral load and ART adherence, including drug-resistant genotype, homelessness, and criminal justice history. We did, however, assess for ART regimen type, which may represent a particularly important variable in the use of viral load detectability as a proxy for adherence, as some forms of ART have longer half-lives and are thus more forgiving with missed doses. We found no differences in ART regimen type across drinking groups or adherence groups, providing further evidence in support of our use of viral load detectability as a proxy for ART adherence. Lastly, however, using viral load detectability as a proxy for ART nonadherence does not give as detailed information about medication adherence as would a real-time measure.