Ibudilast did not improve negative mood on drinking or non-drinking days, indicating that its mechanism of action may be non-mood dependent in non-treatment-seeking individuals. Ibudilast reduced the probability of HDDs over 2 weeks for non-treatment-seeking individuals relative to placebo. Ibudilast also attenuated alcohol cue-elicited activation in the VS, potentially through a dopaminergic-related mechanism. This is a critical proof-of-mechanism whereby modulation of neuroimmune signaling via ibudilast reduced the incentive salience of alcohol cues in the brain. Exploratory analyses indicated that ventral striatal activation to alcohol cues was predictive of subsequent drinking in the ibudilast group, such that individuals who had attenuated ventral striatal activation and were treated with ibudilast had the fewest number of drinks per drinking day in the week following the scan. Overall, these findings extend preclinical and human laboratory demonstrations of the efficacy of ibudilast for the treatment of AUD and suggest a potential bio-behavioral mechanism through which ibudilast acts. This study also demonstrates that ibudilast has a favorable side effect profile, even when combined with alcohol. These findings also provide novel insights into the role of neuroimmune modulation in AUD, including its effects on neural and behavioral outcomes of high clinical significance.Imagine, in the near future, you walk into a supermarket with a list of things to buy that you usually keep around the house. You walk in and go straight for the cereal aisle, because you are out of your favorite sugary “fruit loops” cereal. You approach the cereal only to double-take, because all the boxes now look the same. Instead of the colorful box you are used to, there is a plain white box with a large photo of rotting teeth that says, “Fruit Loops” in the same plain font as every other cereal box on the aisle. It just doesn’t feel right to buy the fruit loops without the normal packaging,gardening rack so you move to the next item on your list. Now imagine you decide to buy some beer for an upcoming dinner party. You walk to the beer aisle to pick out the most appealing brand. But as you approach the aisle, you realize that, like the cereal, every type of beer looks the same.

All the beer is packaged in a dark brown color with photos of failed livers and cars wrapped around telephone poles. The beers have different names, but the font and text size are identical. Instead of gravitating to the beers that look interesting, you must try to find a brand name that sounds like something your friend may like. After fifteen minutes, you get frustrated and give up. Finally, you decide to leave the store, but not before grabbing a carton of your favorite cigarettes. You approach the register and notice that again, all the tobacco products look similar. The cigarettes are packaged in an olive-green box with photos of black lungs and large warnings that say, “smoking causes cancer.” This is the last straw. You storm out of the supermarket, having spent twenty minutes shopping and coming away empty handed. The packaging was part of the fun, and it has been taken away from you. You enjoyed playing the games on the back of the fruit loops box. You loved the artistic beer packages that had the added value of convenience. Given the World Trade Organization’s recent decision to uphold plain packaging laws in Australia, this dystopian hypothetical could be a reality.Australia was the first country in the world to implement plain packaging laws for tobacco products with the Tobacco Plain Packaging Act of 20112 , and others have followed suit. Countries like Britain, France, and Hungary have already passed plain packaging laws, while others like Ireland, Canada, South Africa, New Zealand and Belgium are considering the idea.Countries that export tobacco, like Indonesia, are angered by the measures and the negative economic impact it will have. In 2013, Indonesia launched an attack on Australia’s new laws by requesting a consultation from the WTO.A five year legal battle ensued, ending in a landmark decision by the WTO that was a major blow to big tobacco.This Paper will discuss the WTO’s decision and the potential impact, whether good or bad, this decision could have moving forward. Indonesia claims that Australia’s laws contradict their obligations under three major agreements recognized by the WTO: the Agreement on Technical Barriers to Trade , the Agreement on Trade-Related Aspects of Intellectual Property Rights , and the General Agreement on Tariffs and Trade.

The following Parts will discuss the claims made under the TBT Agreement, TRIPS Agreement, and the GATT, as well as provide a prediction of the panel’s legal analysis and debate the possible impact it may have on the future of packaging and product advertising.It seeks to discourage its citizens from smoking, prevent relapse for those who have quit, and reduce overall exposure to tobacco products.In this spirit, the TPPA regulates “the retail packaging and appearance of tobacco products”, and therefore can “reduce the appeal of tobacco products . . . increase the effectiveness of health warnings . . . and reduce the ability of the retail packaging of tobacco products to mislead consumers about the harmful effects of smoking.”The TPPA enforces stringent requirements for the packaging of all tobacco products and establishes penalties and sanctions for violations.The Act regulates all tobacco products but includes specific regulations for cigarettes as well.For example, cigarette packaging must be rigid, have a matte finish, be made of cardboard, and must not be “embellished in any way, [unless] permitted by the regulations.”The color of the packaging must be a drab brown color , with the only exceptions being health warnings and brand names.The TPPA also states that no trademarks can appear on packaging except for the company name, relevant legislative materials, and any trademarks permitted by the TPPR.Further, the brand or company name must comply with specific provisions set out in the TPPR and may only appear once on the packaging.The TPPR establishes requirements for specific colors, dimensions, and features of the packaging.These regulations not only give the packaging a uniform and unattractive appearance, they also help prevent tobacco companies from misleading consumers and maximize the effectiveness of the health warnings.The color of the packaging must be “Pantone 448C,” a dull olive green and brown mixture like the color mentioned in the above hypothetical.These regulations also state that writings, other than health warnings, must be “in the typeface known as Lucida Sans . . . no larger than 10 points in size . . . in a normal weighted regular font . . . and in the colour known as Pantone Cool Gray 2C.”Indonesia cites to Articles 2.1 and 2.2 of the TBT, which fall under the “Preparation, Adoption and Application of Technical Regulations by Central Government Bodies” section of the agreement.Article 2.1 of the TBT Agreement declares that member states “shall ensure that in respect of technical regulations, products imported from the territory of any Member shall be accorded treatment no less favourable than that accorded to like products of national origin and to like products originating in any other country.”

In an earlier case, US-Clove Cigarettes , Indonesia complained that the United States violated,vertical farming equipment among other things, Article 2.1 of the TBT Agreement.28 Similar to its later complaint in Australia-Plain Packaging, Indonesia challenged U.S. regulations that were created to promote public health by dissuading tobacco use.Specifically, Indonesia challenged measures that banned flavored tobacco and clove cigarettes but not menthol cigarettes.Because Indonesia is a large producer of clove cigarettes, and the United States is a large producer of menthol cigarettes, Indonesia claimed the regulations “accorded to imported clove cigarettes less favourable treatment than that accorded to like menthol cigarettes of national origin.”This vital Appellate Body decision articulated the proper test for determining a violation of Article 2.1.According to the Appellate Body, to establish a violation of Article 2.1, “three elements must be satisfied: the measure at issue must be a technical regulation; the imported and domestic products at issue must be like products; and the treatment accorded to imported products must be less favourable than that accorded to like domestic products.”Regarding the first element, Annex 1.1 of the TBT Agreement defines the term “technical regulation” as a “[d]ocument which lays down product characteristics or their related processes and production methods, including the applicable administrative provisions, with which compliance is mandatory. It may also include or deal exclusively with terminology, symbols, packaging, marking or labelling requirements as they apply to a product, process or production method.”Because regulations in question are likely to be agreed upon as technical regulations, this element of the test need not be further discussed. The second element of the test requires that the imported and domestic products be “like.”In Clove Cigarettes, the Appellate Body addressed the meaning of like products in the context of Article 2.1.Although it agreed that menthol cigarettes and clove cigarettes were like products, it disagreed with the way the Panel came to that conclusion.According to the Appellate Body, the Panel erred in focusing on “the purposes of the technical regulation at issue, as separate from the competitive relationship between and among the products.”The proper analysis of like products must take into consideration the context of “Article 2.1 itself . . . other provisions of the TBT Agreement . . . the TBT Agreement as a whole, and . . . Article III:4 of the GATT 1994, as well as the object and purpose of the TBT Agreement . . . ”When viewed in this context, the test for likeness should be “based on the competitive relationship between and among the products . . . ”The third element, that “the treatment accorded to imported products must be less favourable than that accorded to like domestic products”, was also addressed by the Appellate Body in Clove Ciga-rettes.The Appellate Body first noted that, in the context of the TBT Agreement, Article 2.1’s “treatment no less favorable” requirement prohibits both de jure and de facto discrimination.However, to analyze Article 2.1 in the context of the similarly worded Article III:4 of the GATT, the Appellate Body noted that any examination of an Article 2.1 violation “should seek to ascertain whether the technical regulation at issue modifies the conditions of competition in the market of the regulating Member to the detriment of the group of imported products vis-à-vis the group of like domestic products.”In light of these conflicting ideas, the Appellate Body concluded that where measures do not “de jure discriminate against imports, the existence of a detrimental impact on competitive opportunities for the group of imported vis-à-vis the group of domestic like products is not dispositive of less favourable treatment under Article 2.1.”Instead, the correct approach is to “analyze whether the detrimental impact on imports stems exclusively from a legitimate regulatory distinction rather than reflecting discrimination against the group of imported products.”A detrimental impact stemming from a legitimate distinction is determined by careful scrutiny of the particular circumstances of the case.After careful scrutiny, the Appellate Body determined that the U.S. measure did not stem exclusively from a legitimate regulatory distinction.Specifically, the Appellate Body cited the purpose behind the measure as a reason why it was not in compliance with Article 2.1.Because the measure was enacted to deter youth smoking by banning flavored cigarettes, and menthol cigarettes are flavored, there was no reason for menthol cigarettes to be exempted.The TRIPS Agreement was also enacted as a part of the establishment of the WTO in 1995.Its purpose is to “reduce distortions and impediments to international trade . . . and to ensure that measures and procedures to enforce intellectual property rights do not themselves become barriers to legitimate trade . . . ”Indonesia cites to, inter alia, Article 3.1 in its Request for Consultations.This Part will examine Article 3.1 and its WTO jurisprudence. Article 3.1 is the “National Treatment” provision of the TRIPS Agreement, much like Article 2.1 of the TBT Agreement and Article III:4 of the GATT. Article 3.1 states, in pertinent part, that “[e]ach Member shall accord to the nationals of other Members treatment no less favourable than that it accords to its own nationals with regard to the protection of intellectual property . . . ”WTO jurisprudence on Article 3.1 is scant, but one dispute heard by the Panel, EC-Trademarks and Geographical Indications, discusses the application of Article 3.1 in detail.

Complete results are available upon request. Two sets of temperament by monitoring interactions replicated across both substance use and intention variables – those involving effortful control and depressive mood. Results suggested that parental monitoring had very little association with substance use intentions and substance use in 9th grade for adolescents with high levels of effortful control in 5th grade. However, parental monitoring was a significant predictor of these variables when adolescents were low in effortful control. Likewise, monitoring was primarily a protective factor when depressed mood was relatively high in 5th grade. These interactions are illustrated in Figures 1 and Figure 2. In short, there were indications that parental monitoring might be most relevant for youth with dispositional tendencies associated with substance use. We then evaluated concurrent relations using 9th grade data. Selected results are presented in Table 6. Significant results were restricted to the substance use intention variable, but the effortful control and depressive mood pattern was replicated. In general, the significant patterns were consistent with the prospective analyses and indicated that monitoring was a stronger predictor for youth with temperamental dispositions that placed them at risk for greater substance use . However, these interactions were restricted to only one substance use variable, and thus should be viewed with caution. We investigated the prospective influence of temperament and parental monitoring on substance use using data from a longitudinal study of Mexican-origin youth and their families. We focused on willingness to use substances , expectations for positive outcomes , and lifetime use of alcohol, cigarettes, and other drugs. The rates of substance use in this sample were similar to what has been reported for Hispanic adolescents in nationally representative surveys . Specifically, around 40% of participants had tried a substance at least once by 9th grade , and furthermore, considerably more participants had tried a substance by 9th grade compared to 5th grade. These rates are thus also similar to what has been reported for European American and African American adolescents,pruning cannabis and higher than what has been reported for Asian American adolescents .

As expected, low effortful control and high aggressive tendencies assessed in 5th grade were the most robust predictors of substance use variables in 9th grade. These findings fit with previous research indicating that temperamental traits related to impulsivity are associated with substance use . Moreover, these associations held while controlling for previous levels of the substance use variables in 5th grade . This finding is consistent with White and colleagues’ suggestion that aggression serves as a risk factor for future substance use irrespective of previous use. These longitudinal findings are particularly noteworthy because Mexican Americans are the largest and fastest growing ethnic minority group in the United States, yet this population has received relatively little attention in research on the temperamental correlates of substance use. Beyond finding evidence that temperament prospectively predicts substance use, we also examined the main and interactive effects of parenting monitoring. Consistent with previous research , child-reported parental monitoring in 5th grade was associated with 9th grade substance use variables, even after controlling for prior levels. In contrast, parent reports of monitoring had only concurrent associations with substance use variables. Although the greater predictive power of child reports could simply reflect shared method biases, we believe that a pure methodological explanation is unlikely to fully account for the findings. Instead, we suspect that youth perceptions of parental behaviors are especially salient developmental considerations when attempting to understand risk for substance use. Youth who believe their behavior is being monitored will likely behave differently than youth who do not believe there is surveillance of their behaviors. Indeed, beliefs about parental behaviors and values might be more consequential than actual parental behaviors and values for understanding adolescent substance use. This is consistent with Voisine and colleagues’ suggestion that parental injunctive norms are more effective in preventing substance use than parental monitoring per se.

Nonetheless, further research is needed to better understand the relative importance of child vs. parent reported monitoring for substance use outcomes. We found a number of significant interactions between temperament and child-reported parental monitoring. Most notably, both effortful control and depressive mood interacted with monitoring in 5th grade to predict intentions and use in 9th grade. These interaction effects suggest that parental monitoring is a protective factor for youth with the temperamental tendencies associated with risk for substance use. Considered from another perspective, the interaction effects suggest that certain temperamental traits are risk factors for substance use when parental monitoring is low, but not when it is high. Either interpretation is consistent with the findings and points to a similar conclusion about how temperament and parenting work together to increase risk for early substance use. Being raised in a home with a perception of minimal monitoring by parents may be a more salient risk factor for substance use for those adolescents with dispositional proclivities toward substance use, and possessing a disposition toward substance use may be a stronger risk factor when youth do not believe they are closely monitored by their parents. The broader developmental consideration is that temperamental factors and family variables should be considered jointly in models that attempt to understand early risk for substance use. Although the current study was notable for its multi-informant longitudinal design, and for the size and ethnic composition of the sample, there are limitations that merit consideration. For instance, our ability to detect effects for surgency was hampered by the low reliability of the scale in the 5th grade; thus, results involving surgency should be interpreted with caution. Also, we relied exclusively on youth reports of their substance use, intentions, and expectancies. However, intentions and expectancies are inherently subjective variables and are thus best assessed via self-report. Likewise, focal youth might be in the best position to report on their actual use given understandable motivations to hide substance use from parents, teachers, and other potential informants. In closing, we found evidence from a longitudinal study of Mexican-origin youth that temperament and parental monitoring assessed in 5th grade are prospectively related to substances use outcomes in 9th grade.

These findings are important because they suggest that theoretical models concerning the influence of temperament on substance use can be applied to adolescents of Mexican origin. Indeed, we suspect that factors like temperament and parental monitoring have transcontextual validity to the extent that they are risk factors for early substance use for a diverse range of youth. Of particular importance, we also found that relatively high levels of perceived monitoring might attenuate some of the risks associated with dispositional tendencies toward substance use. Although the current results should be replicated, we suggest that future intervention and prevention efforts could be enhanced by attending to individual differences in temperament. Such attention might be especially important when considering efforts to increase parental monitoring. Alcohol remains the most commonly used substance of abuse during adolescence and young adulthood. The act of binge drinking, often defined as the consumption of greater than either 4 or 5 drinks in a given drinking episode,dry room is of particular concern in youth given the host of associated negative consequences and potential for neurological alterations to the developing adolescent brain . Approximately 17% of 12th graders and 33% of college-aged young adults reported recent binge drinking, defined as the consumption of 5 or more drinks in a row at least once in the two weeks prior to assessment . Notably, almost 1% of adolescents aged 12 to 17 and 10% of young adults aged 18 to 25 engage in binge drinking episodes frequently, averaging more than once per week over the previous 30 days . Frequent binge drinking during adolescence is associated with elevations in multiple risk factors, including adolescent drug use, antisociality, and parent alcoholism , as well as a number of negative consequences in adulthood such as alcohol use disorder diagnosis, drug use, psychiatric morbidity, homelessness, legal problems, accidents, and lower social class . Importantly, many of these elevated risks are greater for those who frequently binge drink during adolescence, as opposed to those who are infrequent/moderate binge drinkers , suggesting that the frequency with which one binges during adolescence is an important factor in future alcohol-related outcomes. Thus, given the known neurotoxicity of alcohol at higher doses , efforts to predict who is at risk of drinking at these frequent high levels during the critical period of neurodevelopment are warranted.In line with this, diminished inhibitory control during adolescence is consistently implicated as a risk factor for future alcohol and substance use . Successful inhibitory control likely involves the ventral attention, fronto-parietal and fronto-striatal networks, including regions such as the inferior frontal gyrus extending to the insula, cingulate and paracingulate gyri, superior parietal gyrus, and basal ganglia structures , suggesting deficiencies in these networks may serve as correlates of alcohol-related risk prior to binge drinking onset . Longitudinal functional magnetic resonance imaging studies of adolescents have identified several neural aberrations during inhibition, as measured on the Go/No-go task, as significant predictors of greater alcohol and substance use, even in the absence of behavioral differences on the tasks . Specifically, greater left angular gyrus and less ventromedial prefrontal blood-oxygen-leveldependent activation during no-go correct rejection vs. go trials in 16 to 19 yearolds was found to predict higher levels of alcohol and substance use and dependence symptoms over an 18-month follow-up.

This effect was especially pronounced for adolescents who were high frequency substance users at baseline . In an analysis of 12–14 year-olds scanned prior to the onset of alcohol use and followed up about 4.2 years later, less BOLD response in regions including the right inferior frontal gyrus, left dorsal and medial frontal areas during no-go correct rejection vs. baseline trials was found to differentiate between those who transitioned to alcohol use from those who remained continuous controls ; however, the activation in those regions was found to be associated with attention problems at follow-up, and not substance use outcomes per se, suggesting the groups may have differed on multiple related factors. In an additional longitudinal analysis of 11–16 year-olds, with follow-up approximately 3 years later, adolescents who transitioned into drinking by follow-up exhibited less BOLD response during no-go correct rejection vs. go trials at baseline in bilateral middle frontal gyri, left putamen, right inferior parietal lobule, and left cerebellar regions. Yet increased activation was observed after the onset of heavy drinking in all regions except the putamen, as compared to matched continuous non-drinkers who displayed decreased activation in these regions at follow-up . These results suggest alcohol-exposure may increase engagement of these neural networks in order to successfully inhibit prepotent responses; however, the degree of alcohol exposure required to produce this change has yet to be investigated. Taken together, the current literature implies the presence of a pre-existing neural inhibition risk profile for future alcohol and substance use, along with a potential for additional alcohol and substance-related disturbances in normal neural inhibitory maturation processes. However, the neural underpinnings subserving the transition from moderate, arguably even “normative”, alcohol use behavior in adolescence to the extremely high-risk pattern of frequent binge drinking have not been determined. Thus, the present study seeks to prospectively predict the time to transition to high-risk frequent binge drinking from the neural patterns of successful inhibitory control in a single sample of adolescents who were already engaged in moderate alcohol use. Given the broad set of inhibitory-related regions identified in the earlier literature, a whole-brain exploratory approach was used for the present analysis, with a general hypothesis of alcohol risk-related activation to fall within the fronto-parietal and fronto-striatal networks. No directionality was hypothesized for the present analyses given the mixed results of the literature and the novelty of the current inquiry. Current study data was culled from a larger, ongoing longitudinal substance use and neuroimaging project . Participants at baseline were healthy 12–14 year-olds, recruited through schools in the San Diego area, with very minimal to no experience with alcohol or drugs. Exclusionary criteria for the parent study at baseline included: premature birth prior to the 35th gestational week; report of prenatal alcohol or illicit drug exposure; history of any DSM-IV Axis I or neurological disorder; psychoactive medication use; loss of consciousness or head trauma; learning disability or mental retardation; chronic medical illness; history of alcohol use ; history of drug use ; non-correctable sensory problems; and inadequate English comprehension.

The public-use NSDUH provides estimates of the prevalence of past-month use and past-year initiation of marijuana, available separately for age groups of 12-17, 18-25, and 26 years of age and older. Representative state-level data broken down by two-year averages is available from. Table 2.3 provides summary statistics for the marijuana use measures and state level covariates used in the NSDUH analysis. Comparing mean differences, MML states with a positive number of registered medical marijuana patients have higher levels of past-month cannabis users for all age groups than states without MMLs. However, MML states on average are more likely to have decriminalized marijuana,have higher cigarette taxes, and consist of populations that are on average younger and more male. As such characteristics are potentially correlated with prevalence of recreational cannabis use, all regressions control for the state covariates listed in Table 2.3. There are some limitations to this dataset. Firstly, the public-use NSDUH data is only available in two-year averages; thus the registration rate data may not correspond exactly with the marijuana outcome data, leading to a loss of precision for these estimates.22 Secondly, the NSDUH measures of substance use are self-reported. If individuals are more likely to report marijuana consumption truthfully based on legality, analysis of the effects of legal market size compared to MML enactment should be less subject to reporting bias. However, if reporting is driven by perceived changes in social approval, growth in the legal market size may induce changes in reporting behavior. Section 2.6 and Appendix D- provide supporting evidence that the self-reported marijuana use measure captures true changes in consumption. Despite these problems, the NSDUH is the only publicly available dataset that provides representative state-level estimates of marijuana consumption for all individuals aged 12 and older.

Additionally, the NSDUH Restricted-use Data Analysis System provides state-level estimates for perceptions about marijuana,heavy duty propagation trays which are used in section 2.6 to examine the mechanisms by which changes in the legal market affect adolescent marijuana use.Figure 2.2 presents descriptive evidence of changes in marijuana consumption over time. Trends in past-month use and past-year initiation are plotted by age groups and by strictness of state MML supply regulation. All trends are normalized such that the prevalence measure is zero for 2007-2008, the years just prior to the Ogden Memo. For all age groups, marijuana consumption increases in MML states after the Ogden Memo. For youths and young adults, these increases are largest in MML states with loose supply regulations, while loose and strict MML states saw similar growth rates for older adults. For adolescents aged 12-17, there is a sharp drop in consumption in MML states with loose regulations following the Cole Memo; for adults, consumption does not decrease after the Cole Memo but trends in use flatten. To examine whether these patterns in marijuana consumption are driven by growth in medical marijuana availability, Table 2.4 reports the first-stage and reduced form estimates of the differential effects of the Ogden and Cole Memos in MML states with lax supply restrictions on registration rates and the prevalence of marijuana consumption. The first-stage results of Table 2.4 are replicated from Column of Table 2.2 and are discussed in section 2.2.4. The F-test for excluded instruments takes a value of 52.3, mitigating any concerns of finite sample bias due to weak instruments . The reduced form results for past-month use and past-year initiation by age group have the expected signs, though the instruments have less predictive power for past-year marijuana initiation. Since this approach identifies effects off of changes in a monthly time series, ex-ante the results for past-month use are expected to perform better than the results for past-year initiation. Table 2.5 reports the estimated effects of growth in the legal medical marijuana market on marijuana consumption, showing results separately by age group for preva-lence of past-month marijuana use and past-year initiation.

To test whether these effects are driven by omitted variables influencing both legal and illegal use, the second-stage results of the instrumental variables analysis are compared to the OLS estimates. The results indicate that growth in medical marijuana registration rates significantly increases marijuana consumption for all age groups, with the largest effects for older adults. An additional one percentage point of the adult population registering as medical marijuana patients predicts a significant 6% increase in the share of 12-17 year olds reporting past-month marijuana use, a 7-8% increase for 18-25 year olds, and a 20% increase for older adults. The effects on past-year initiation are similar but smaller in magnitude, indicating a 1-5% increase in the share of 12-17 year-olds reporting past-year initiation, a 6% increase for 18-25 year olds, and a 12-18% increase for adults over age 25. Additionally, these estimates support that using registration rates as an exogenous measure of the size of the legal marijuana market does not produce biased estimates. The IV estimates are neither qualitatively nor statistically different than those from OLS, suggesting that changes in registration rates and recreational use are not being driven by some unobserved factor correlated with both recreational and medical demand. This conclusion will hold if the instruments are indeed excludable, supporting evidence of which is presented next. The exclusion restriction will be violated if changes in federal enforcement due to the Ogden and Cole Memos had differential effects on demand in states with lax compared to strict production restrictions through any channel other than supply. For example, the exclusion restriction would be violated if, when federal enforcement was removed and registration rates increased, local governments in strictly regulated states devoted more resources toward prosecuting users than state governments in states with loose regulations. I provide evidence that this did not occur in Figure 2.3, which plots changes in per user state marijuana possession arrest rates against changes in registration rates. Results are shown separately for juveniles and adults. There is no apparent correlation between legal market growth and state enforcement for either strict or loose regulatory regimes.

Another potential violation of the exclusion restriction would occur if, prior to the Ogden Memo, the expected user risks of federal prosecution were higher in states with loose compared to strict supply regulations. To address this, I first show that the actual risk of a marijuana user facing federal enforcement is very low. The federal government has never devoted substantial resources toward prosecuting individuals for simple marijuana possession. Figure 2.4 shows from fiscal year 1996 through 2012, less than 4% of federal prosecutions for marijuana-related offenses have been for simple possession.24 Between 1996 and 2012, the annual average of federal prosecutions for marijuana possession was 224 compared to 6,259 for sales. Focusing on enforcement against medical marijuana specifically, reports suggest there were fewer than 20 federal prosecutions of medical marijuana users or growers from 1996-2005 and about the same number from 2005-2009; this enforcement was almost exclusively directed toward large-scale producers in California. While the actual probability of federal prosecution was low, uncertainty among potential medical marijuana users about whether the federal government could access registry data may still have stifled demand. This deterrent was likely far greater in California than in other states,vertical cannabis as federal prosecution against suppliers was concentrated in California. Vickovic ’s analysis of news article mentions of medical marijuana showed that almost all articles about federal enforcement prior to the Ogden Memo were about dispensary raids in California, and the majority of these articles were published by local sources. Thus, it may be the case that the Ogden Memo led to a relatively larger shift in demand in California compared to other MML states.25 To address these concerns, Table 2.6 reports the results of the instrumental variable specification excluding California. The results for past-month use are unchanged, but the effect of legal market growth on past-year initiation for adolescents becomes small and insignificant and shows evidence of endogeneity. These results are consistent with past-month use serving as a better measure to detect short-run changes in marijuana access, while past-year initiation may better reflect longer-run changes in social approval or risk perceptions. In the regressions without state-specific trends, both registration rates and the categorical variable for MML enactment have positive effects on marijuana consumption, though the effects of the categorical MML variable are only significant for adults over age 25. However, after including state-specific linear trends to account for state differences in preexisting paths of marijuana use, the estimates for MML passage become small and insignificant and switch sign. In contrast, estimates of the effects of registration rates remain positive and significant for all age groups. The registration rate estimates are less sensitive to trend inclusion than those of the categorical variable. This could be due to the non-monotonicity of trends in registered patient counts or the categorical MML measure confounding preexisting trends with the dynamic effects of the policy .

Additional robustness checks of sample selection and model specification in Appendix D- support that the binary MML measure misses heterogeneous effects across states and the dynamics of these policies. There are a number of mechanisms through which MML policy, promoted as legislation to protect cannabis use for a relatively small number of individuals with chronic health conditions, might affect marijuana consumption by adolescents. If registered adult users are more visible to adolescents, youths may increase consumption due to lower perceived risks associated with social disapproval, formal sanctions, or health consequences. If growth in the legal market increases total availability, increased adolescent use may be driven by lower search costs, increased product variety, or declines in the quality-adjusted price of marijuana following the shift in supply . Sections 2.2 and 2.5 suggest that supply channels are particularly important indetermining MMLs’ effects on adolescent use. Spillover of medical marijuana supply to the illegal market serving adolescents could occur through resale or sharing of medical marijuana by legal users.27 Recent national surveys of high-school seniors show that almost 18% of past-year users report receiving some marijuana from another’s medical marijuana “prescription” ; focusing only on high-school seniors in states with MMLs, 34% of past-year users report one of their sources as another person’s medical marijuana “prescription” . This indicates substantial diversion from the legal market supplying medical marijuana patients to the illegal market supplying youths. Table 2.8 provides evidence of the mechanisms by which growth in the legal market influences cannabis consumption by youths aged 12-17 using state-level data from the NSDUH R-DAS. Columns – report effects on risk perceptions, and columns – report effects on measures of adolescent access. The outcome variable for each column is the share of youths aged 12-17 who report that: using marijuana monthly poses a “great risk,” their friends “somewhat” or “strongly” disapprove of monthly marijuana use, the maximum penalty for possession of one ounce of marijuana in their state is prison time, marijuana is “somewhat” or “very” easy to obtain, most students their age use marijuana, and they purchased marijuana in the past year. Since these measures are likely determined endogenously, these results are intended only to provide suggestive evidence. While growth in the legal market affects adolescent perceptions of both risk and availability, the results of Table 2.8 suggest that the legal market primarily affects adolescent use through changing access. A one percentage-point rise in registration rates significantly increases the share of 12-17 year-olds who believe marijuana is easy to obtain , who believe most students their age use marijuana , and who report buying marijuana in the past year ; these estimates are jointly significant with a p-value of 0.04. In contrast, estimates of the effects on risk perceptions are smaller and jointly insignificant with a p-value of 0.13. These results thus provide supporting evidence that the increases in adolescent marijuana use following medical marijuana market growth are due to supply spillovers rather than decreased risks of legal penalties or social disapproval. According to Department of Justice National Drug Threat Assessment reports, there is substantial internal movement of domestically produced marijuana, and Figure E.1 clearly illustrates that the sources of much of the marijuana trafficked domestically are the western MML states of Washington, Oregon, California, and Arizona. As marijuana markets are not isolated , supply shocks in legal medical marijuana state markets likely have spillover effects on price and availability in states without MMLs or in MML states with high production costs. For the empirical results, this should bias the estimates of the effects of legal market size toward zero. Tables E.1 and E.2 use Montana as a case study to assess whether spillover of marijuana supply from states with large legal markets to other states is biasing the estimates from the primary results downward.

There are three important distinctions between California’s initiative and the earlier medical marijuana statues discussed in section 1.2.1. First, since the law stated that patients needed a doctor’s “recommendation” — not “prescription” — for medicinal marijuana, physicians did not need to violate federallaw to qualify their patients.9 Second, unlike the state medical marijuana initiatives of the 1970’s described earlier, Proposition 215 was passed during a time when federal policy was firmly engaged in the drug war and opposed to recognizing marijuana’s medicinal value. Last, California’s MML specified that patients and their caregivers could legally grow marijuana, establishing a legitimate source of supply that did not require any cooperation from the federal government. The federal response was swift. One month after Proposition 215 passed in California, then-Drug Czar Barry McCaffrey threatened to arrest any physician who recommended cannabis to their patients. A group of physicians, patients, and nonprofit organizations challenged this threat in court and succeeded. The 1997 decision in Conant v McCaffrey ruled that doctors could not be prosecuted for recommending or discussing cannabis with their patients . By the end of 2008, twelve other states had successfully passed MMLs .While these policies indicated state-level acceptance of the medicinal value of marijuana, federal opposition under the Clinton and Bush Administrations created uncertainty regarding the risks facing those who participated in the state MML program. Federal officials repeatedly stated that users and producers operating in compliance with state MML policy could still be subject to federal prosecution ,rolling benches hydroponics and federal agents conducted numerous raids of large-scale production sites, primarily in California . The election of President Barack Obama in 2008 signaled a potential shift in federal enforcement policy toward MML states.

Throughout his campaign, Obama had indicated that he would not use federal resources to try to circumvent state MMLs . On March 18, 2009, Attorney General Eric Holder issued a statement that federal authorities would cease interfering with medical marijuana dispensaries that were operating in compliance with state law . This policy of federal non-enforcement was formalized October 19, 2009, when Deputy Attorney General David Ogden issued a memorandum stating that federal enforcement priorities should not be directed against users or producers compliant with a state’s MML . While the intent was to signal a shift in drug enforcement efforts and provide reassurance to states considering liberalization, the memo did not change marijuana’s legal status at the federal level. It explicitly stated that marijuana remained illegal under federal law, and a careful reading of the Ogden Memo shows that it left substantial discretion to U.S. Attorneys in how they could choose to adopt the federal guidelines . Even if the Ogden Memo did not end up affecting the actual risk of arrest or prosecution, the widespread perception was that it would. The federal statement was hailed by mainstream media and marijuana advocacy groups as a historic step toward the enactment of national marijuana liberalization. The day of Ogden’s announcement, the largest marijuana advocacy group in the country posted to their website that the Ogden Memo marked the end of federal arrests of medical marijuana patients and raids on suppliers . In the days following the issuance of the Ogden Memo, representatives from the prominent marijuana advocacy group NORML spoke with dozens of mainstream media outlets, proclaiming that federal prosecution of state-compliant medical marijuana patients and their suppliers was now over .Similar to the experience of the early medical marijuana initiatives described in section 1.2.1, the federal signal had important effects on the way in which local governments regulated and implemented state law. For instance, New Mexico was the only state to pass an MML prior to the Ogden Memo that explicitly allowed for the establishment of state-licensed dispensaries in its initial legislation in July 2007.

One month later, the state Attorney General warned the New Mexico Department of Health that its employees could face federal prosecution for overseeing the production and distribution of medical marijuana . The first dispensary was not licensed until the day of Eric Holder’s statement in March 2009, and four licenses were issued shortly after the Ogden Memo in November 2009. All six states that passed MMLs after the Ogden Memo allowed for the operation of state-licensed dispensaries . The changing landscape of medical marijuana markets elicited federal reaction. Beginning in February 2011, U.S. Attorneys in several MML states sent letters to state officials indicating that large-scale marijuana production or distribution facilities would not be tolerated by federal policy, even if state law permitted their operation . On June 29, 2011, following a series of federal raids of medical marijuana dispensaries, Deputy Attorney General James Cole issued a memorandum to clarify the Ogden Memo and emphasize that federal resources would indeed be used to prosecute individuals involved in large-scale medical marijuana sales and distribution businesses . The Cole Memo was widely publicized as a disingenuous reversal of the Ogden Memo, and marijuana advocacy groups issued warnings that dispensaries compliant with state law would once again be federal targets .The aim of this paper is to understand how the federal memos affected medical marijuana participation within states, and to explain variation in take-up across states. The approach is thus motivated by the economic theory of program participation . Attention is limited to states that required medical marijuana patients to register with the state in order to receive the full protections afforded by state MML, since participation data in the three states with voluntary or non-existent registration programs are likely measured with substantial error .Conceptually, individuals will apply to be a medical marijuana patient if the expected benefits of applying exceed the expected costs. An individual who applies and is approved becomes a registered patient, and receives the legal protections afforded by state law.

An individual who applies and is rejected decides whether to obtain marijuana illegally or to abstain from marijuana use. Conditional on knowing about the MML’s existence, an individual then makes the decision whether or not to apply to be a medical marijuana patient. To apply for medical marijuana, an individual must first obtain a doctor’s certification that she has a medical condition that could benefit from marijuana use. The patient then must submit an application to the state authority,cannabis indoro grow system along with a registration fee. Registration must be renewed every one or two years. Registration fees represent the direct cost of applying to the medical marijuana program, but there are additional indirect costs of finding a physician to provide the necessary recommendation. This will be a function of an individual’s health status, search costs of finding a recommending physician, and state-specific regulations regarding the eligible qualifying conditions. If the application is approved, a registered patient may incur additional costs from the perceived risk of federal prosecution. Under the pre-Ogden regime, individuals may have feared that having their name on a medical marijuana registry could lead the federal government to more easily target them for prosecution. There may also be “stigma” costs from choosing to violate federal law. While in reality, the probability of facing federal prosecution for simple marijuana possession is almost non-existent, federal penalties are substantially higher than most state penalties.As evidence suggests individuals overweight low-probability events that carry heavy losses , even a small risk of federal prosecution during the pre-Ogden period may have been sufficient to deter individuals from registering for medical marijuana. If that is the case, by reducing the expected risk of federal prosecution, the Ogden Memo would be expected to increase medical marijuana participation; conversely, by re-instating perceived federal enforcement, the Cole Memo would be expected to decrease medical marijuana participation.

As the federal memos applied to all MML states, they should have similar effects on medical marijuana patient take-up in all states.In all MML states, one of the benefits of registering is protection from state prosecution for possession of marijuana. All states in the sample imposed a maximum possession limit with the initial law . Limits ranged from 1 ounce to 10 ounces of usable marijuana, though several states have passed amendments increasing these limits .Whether this benefit alone outweighs the cost of applying will depend on the perceived probability of arrest as well as the expected penalties for possession if the patient does not register. For heavier users, higher possession limits may offer additional benefits through quantity discounts or through reducing transaction costs associated with frequency of purchases. As noted in section 1.2.2, one of the most important benefits of modern MMLs in comparison to earlier policies is access to legitimate sources of marijuana. Benefits to registered patients could include decreased prices, increased quality or potency, greater product variety, and lower search costs due to increased legal availability. There is substantial variation across MML states in the regulations placed on legal supply sources. These different supply regulations will have heterogeneous effects on medical marijuana availability, and thus generate heterogeneous benefits to registered patients. Table 1.1 shows the supply regulations established by each state’s initial MML law, separately for states that passed MMLs prior to the Ogden Memo in 2009 and after . Legitimate supply sources are categorized as patient home cultivation , cultivation by a designated caregiver , state-licensed dispensaries , and de facto dispensaries or collective grows . Table 1.1 lists the access sources allowed by the state’s initial MML, but it should be noted that many of these states enacted later amendments changing these regulations. All MMLs enacted before 2009 allowed qualifying patients to grow their own cannabis, though plant limits varied. However, if patients are not already experienced growers, the start-up and maintenance costs of home cultivation likely exceed those of obtaining marijuana from the black-market. Inexperienced growers will incur the time and monetary costs of learning how to grow marijuana efficiently, produce an adequate and consistent yield, vary potency, etc. Home cultivation may not even be feasible for many patients due to physical limitations, housing issues , or difficulty finding seeds or starter plants to begin cultivation.Perhaps recognizing these limitations, early-enacting MML states that permitted home cultivation also allowed patients to designate a caregiver15 to assist with their cultivation of marijuana or to legally grow marijuana on their behalf. In states that permit caregiver cultivation, benefits to registered patients will be a function of the number of providers and production per producer, which will depend on the expected profits of legal production. Caregivers’ expected revenues increase with the number of patients they are allowed to grow for and the number of plants they are allowed to grow. Some states restricted caregivers to growing for only one patient . Other states allowed caregivers to grow for multiple patients, and a few states placed no limits on the number of patients a caregiver could serve and did not cap the amount they could grow. Many of these states had MMLs that were ambiguous with regard to group growing or storefront dispensaries and thus effectively permitted the de facto operation of largely unregulated large-scale production. Some states did not permit caregivers to grow for patients, but instead established a legal framework for the creation of state-licensed dispensaries or equivalent entities as described in Pacula, Boustead, et al. . Theoretically, the legalization of state-licensed dispensaries offered a significant benefit to patients. Patients did not need to find an individual willing to be listed as a caregiver on their application form, and could instead rely on a state-sanctioned large-scale production source. However, unlike caregivers or collectives, the number of dispensary licenses was set by MML policy, state-licensed dispensaries needed to overcome a number of regulatory hurdles before beginning distribution, and upon operation these facilities often faced substantial oversight from state authorities. The expected costs faced by legal producers will be a function of the perceived risk of arrest and prosecution. In states that required caregivers to register, fees were minimal , and if the caregiver did not exceed the MML production limits she was protected from state prosecution. However, the federal felony charge for cultivation of any amount can carry up to 5 years in prison and a $250,000 fine .

In order to mitigate the potential for nicotine withdrawal effects on cognition, smokers were allowed to smoke ad libitum prior to the assessment and were allowed to take cigarette smoking breaks as requested. Raw scores for neurocognitive measures, except the Luria-Nebraska Item 99 ratio, were converted to age-adjusted or age- and educationadjusted standardized scores via the accompanying normative data. Scaled scores and t-scores for all individual neurocognitive tests were transformed to z-scores to ease readability and interpretation of results using auniversal scaled score for neurocognitive measures. Scaled scores were subtracted by 10 and divided by 3 , while tscores were subtracted by 50 and divided by 10 . Neurocognitive domain scores are the arithmetic average of z-scores for all associated constituent measures. The cognitive efficiency domain consisted of all tests that were timed, or in which the time to complete the task influence the score achieved. For the Luria-Nebraska Item 99 measure, the number correct was divided by time required to complete the task. This ratio was used due to the low ceiling for the number of correct responses , resulting in a non-Gaussian distribution. Finally, the arithmetic average of z-scores for all individual neurocognitive measures was calculated to form a global neurocognition score for each participant. Participants completed the Barratt Impulsivity Scale-11 , a self-report impulsivity questionnaire. The BIS-11 consists of 30 items rated on a scale of “1” to “4” and provides total scores for non-planning, attentional, motor, and total impulsivity. Participants also completed the Balloon Analogue Risk Task , a computerized risk-taking task in which participants pump up balloons to earn increasing monetary reward,microgreens shelving with the potential for loss if a balloon overinflates and explodes. The BART yields a score for the adjusted number of pumps , with higher scores indicating a higher propensity for risk-taking.

Participants also completed the Iowa Gambling Task , a task of decision-making in which participants choose cards from four decks with the goal of winning as much money as possible. The IGT yields a raw Net Total score for each participant based on his or her selections. Raw scores were converted to the demographically-corrected T scores, with higher T scores indicating better decision-making skills.All statistical analyses were performed with SPSS version 22 . Generalized linear models were used in all analyses, employing maximum likelihood parameter estimation, and followed up by pairwise group comparisons; a chi-square statistic and corresponding p-value are generated for each parameter estimate. Three statistical models were tested: primary cross-sectional models compared PSU to AUD at one month of abstinence and included fixed predictors of group ; secondary cross-sectional models investigated potential smoking effects in PSU and AUD at one month of abstinence and included fixed predictors of group , smoking status and the interaction term of group-by-smoking status; and longitudinal models explored change in neurocognition within PSU between approximately 29 days and 128 days of abstinence ; predictors included smoking status , time , and the time-by-smoking status interaction term. Patient characteristics of PSU and AUD at baseline were compared using univariate analysis of covariance for continuous variables and Fisher’s exact test for categorical variables. Polysubstance users and AUD differed in education, gender, AMNART, hepatitis C frequency, and proportion of individuals on prescribed psychoactive medication; these variables were entered as covariates in our generalized linear models comparing AUD and PSU at baseline. Potential covariates and interaction terms were trimmed from the final model when not predictive of the outcome variable. The proportion of study participants reporting a family history of alcohol problems was not significantly different between PSU and AUD . We accounted for the multiplicity of measures by correcting alpha levels via a modified Bonferroni procedure .

This approach considers the mean correlation between variables and the number of tests in the adjustment of alpha levels. All alpha levels were adjusted for both traditional neurocognitive assessment and BIS-11 and their average inter-correlation coefficients in primary and secondary models and in tertiary models . The corresponding adjusted alpha levels for primary and secondary models were p ≤ 0.013 for neurocognitive domains and p ≤ 0.027 for self-reported impulsivity. The corresponding adjusted alpha levels for tertiary models, which included PSU only, were p ≤ 0.011 for neurocognitive domains and p ≤ 0.017 for BIS-11. Alpha levels for risk-taking and decision-making were not adjusted as these are individual tasks measuring separate domains of executive function. Effect sizes for mean differences between groups were calculated with Cohen’s d . We correlated cognitive functioning, risk-taking, decisionmaking and self-reported impulsivity measures to alcohol use in PSU and AUD, and to cocaine, and marijuana use in PSU only at baseline. Since these were exploratory correlations, we chose a less restrictive alpha level of 0.05. As shown in Table 3, and after co-varying for significant differences in AMNART, PSU performed significantly worse than AUD on auditory-verbal memory [x2 = 12.16, p < 0.001, ES = 0.72], and PSU exhibited strong trends to worse performance than AUD on intelligence [x2 = 4.08, p = 0.043, ES = 1.05] and auditory-verbal learning [x2 = 4.62, p = 0.032, ES = 0.54]. For all other domains except fine motor skills, PSU showed numerically lower scores than AUD with effect sizes up to 0.76 but no statistically significant group differences after covariate correction . When smoking status was included as a factor in the cross-sectional group analyses of neurocognitive domains, neither significant group-by-smoking interactions nor main effects of smoking were observed. In addition, gender was not a significant predictor of neurocognitive performance at one month of abstinence, except for fine motor skills which were worse in female than male substance users. Removing the two women from our PSU analyses did not significantly change any of our results. Polysubstance users exhibited trends to worse decision-making than AUD [x2 = 3.64, p = 0.056, ES = 0.33]; the groups were not significantly different on risk-taking .

No significant group-by-smoking interactions or main effects for smoking were observed on either IGT or BART. Polysubstance users self-reported significantly higher BIS-11 total and nonplanning impulsivity, a measure of cognitive control, than AUD , and being on a prescribed psychoactive medication significantly predicted higher total and nonplanning impulsivity. With smoking status included in the analyses, no significant group-by-smoking interactions were observed for any of the BIS-11 measures. However, self-reported motor impulsivity showed a trend for a group-by-smoking interaction [x2 = 3.259, p = 0.071], a significant main effect for group [x2 = 2.005, p = 0.006], and a trend for a smoking effect [x2 = 1.499, p = 0.066]. Follow-up pairwise comparisons showed significantly higher motor impulsivity in smoking PSU compared to both smoking and nonsmoking AUD . Between baseline and follow-up, neurocognitive functions in abstinent PSU improved markedly in the following domains: general intelligence, cognitive efficiency, executive function, working memory, and visuospatial skills , and weaker improvements were observed for global cognition and processing speed . Abstinent PSU did not change significantly in the domains of learning and memory or fine motor skills. Preliminary analyses indicate that the lack of significant changes in the domains of visuospatial memory and fine motor skills were related to significant time-by-smoking status interactions ,greenhouse tables where only nonsmokers increased on fine motor skills and only smokers improved on visuospatial memory. The BART scores increased significantly with abstinence , whereas the IGT scores did not change during abstinence. Self-reported total and motor impulsivity decreased significantly with abstinence and the nonplanning score tended to decrease . The following changes were observed when restricting our longitudinal analysis to only those 17 PSU with baseline and follow-up data: general intelligence, executive function, working memory , visuospatial skills , global cognition , and processing speed . The 19 PSU not studied longitudinally differed from our abstinent PSU restudied on lifetime years of cocaine use . PSU not restudied performed significantly worse at baseline than abstinent PSU on cognitive efficiency, processing speed, and visuospatial learning . Furthermore, they did not differ significantly on years of education, AMNART, tobacco use severity, and proportions of smokers or family members with problem drinking, or the proportion of individuals taking a prescribed psychoactive medication.In PSU, more lifetime years drinking correlated with worse performance on domains of cognitive efficiency, executive function, intelligence, processing speed, visuospatial skills, and global cognition . More cocaine consumed per month over lifetime correlated with worse performance on executive function and greater attentional impulsivity .

More marijuana consumed per month over lifetime correlated with worse performance on fine motor skills and tended to correlate with higher BIS-11 motor impulsivity ; in addition, more marijuana use in the year preceding the study correlated with higher nonplanning and total impulsivity. Interestingly, more lifetime years of amphetamine use correlated with better performance on fine motor skills, executive function, visuospatial skills, and global cognition . Similar to the associations found in PSU, more lifetime years drinking in AUD correlated with worse performance on cognitive efficiency, visuospatial skills, and global cognition , and worse performance on visuospatial memory correlated with greater monthly alcohol consumption averaged over the year preceding assessment and over lifetime . In addition, longer duration of alcohol use in AUD was related to worse auditory-verbal learning and memory . Earlier age of onset of heavy drinking in AUD was associated with worse decision-making .Our primary aim was to compare neurocognitive functioning and inhibitory control in onemonth-abstinent PSU and AUD. Polysubstance users at one month of abstinence showed decrements on a wide range of neurocognitive and inhibitory control measures compared to normed measures. The decrements in neurocognition ranged in magnitude from 0.2 to 1.4 standard deviation units below a zscore of zero, with deficits >1 standard deviation below the mean observed for visuospatial memory and visuospatial learning. In comparisons to AUD, PSU performed significantly worse on measures assessing auditory-verbal memory, and tended to perform worse on measures of auditory-verbal learning and general intelligence. Chronic cigarette smoking status did not significantly moderate cross-sectional neurocognitive group differences at baseline. In addition, PSU exhibited worse decision-making and higher self-reported impulsivity than AUD , signaling potentially greater risk of relapse for PSU than AUD . Being on a prescribed psychoactive medication related to higher self-reported impulsivity in PSU. For both PSU and AUD, more lifetime years drinking were associated with worse performance on global cognition, cognitive efficiency, general intelligence, and visuospatial skills. Within PSU only, greater substance use quantities related to worse performance on executive function and fine motor skills, as well as to higher self-reported impulsivity. Neurocognitive deficits in AUD have been described extensively. However, corresponding reports in PSU are rare and very few studies compared PSU to AUD during early abstinence on such a wide range of neurocognitive and inhibitory control measures as administered here . To our knowledge, no previous reports have specifically shown PSU to perform worse than AUD on domains of auditory-verbal learning and general intelligence at one month of abstinence. Our studies confirmed previous findings of worse auditory-verbal memory and inhibitory control in individuals with a comorbid alcohol and stimulant use disorder compared to those with an AUD, and findings of no differences between the groups on measures of cognitive efficiency . Some of the cross-sectional neurocognitive and inhibitory control deficits described in this PSU cohort are associated with previously described morphometric abnormalities in primarily prefrontal brain regions of a subsample of this PSU cohort with neuroimaging data . Our neurocognitive findings also further complement studies in subsamples of this PSU cohort that exhibit prefrontal cortical deficits measured by magnetic resonance spectroscopy and cortical blood flow . Our secondary aim was to explore if PSU demonstrate improvements on neurocognitive functioning and inhibitory control measures between one and four months of abstinence from all substances except tobacco. Polysubstance users showed significant improvements on the majority of cognitive domains assessed here, particularly cognitive efficiency, executive function, working memory, self-reported impulsivity, but an unexpected increase in risk-taking behavior . By contrast, no significant changes were observed for learning and memory domains, which were also worst at baseline, resulting in deficits in visuospatial learning and visuospatial memory at four months of abstinence of more than 0.9 standard deviation units below a z-score of zero. There were also indications for significant time-by-smoking status interactions for visuospatial memory and fine motor skills, however these analyses have to be interpreted with caution and considered very preliminary, considering the small sample sizes of smoking and nonsmoking PSU at followup.

In many P450- catalyzed reactions in biosynthesis, the substrate radical can migrate to other atoms in the molecule through internal reactions and delocalization through π-bonds. This can lead to rearrangement of the carbon skeleton, as well as oxygen atom incorporation at distal positions from the initial abstraction site. In some cases, the Fe–OH can abstract a second hydrogen atom from the substrate to generate a second radical in the substrate that can recombine with the first one to terminate the reaction cycle. In this scenario, no oxygen atom is incorporated yet molecular oxygen is consumed. An additional feature of some bio-synthetic P450s is the ability to iteratively oxidize a substrate, either at a single carbon or at nearby atoms. For example, it is not uncommon to find a single P450 that can perform the six-electron oxidation of a methyl group into a carboxylic acid in both fungal and plant bio-synthetic pathways. One notable example of P450 catalysis in this review is the secologanin synthase found in the strictosidine bio-synthetic pathway that ultimately leads to ibogaine .The substrate is loganin which contains the iridoid core. SLS performs hydrogen abstraction followed by oxygen rebound at the methyl group on the cyclopentanol ring to give a primary hydroxyl group. This species then undergoes a Grob fragmentationlike reaction to cleave the C–C bond which reveals both an aldehyde and a terminal olefin in the product secologanin .This aldehyde then participates in the aforementioned Pictet-Spengler reaction with tryptamine to give strictosidine . Hence, although this example illustrates a “standard” P450 reaction, the hydroxylation modification triggers a significant skeletal rearrangement. A second example that illustrates oxidation without oxygen incorporation is found in the morphine bio-synthetic pathway, in which the salutaridine synthase catalyzes the phenyl coupling in R-reticuline to yield salutaridine.A radical addition mechanism is currently favored for this reaction: hydrogen abstraction from one of the phenol group generates an oxygen radical that is delocalized throughout the aromatic ring. The carbon radical then adds into the isoquinoline ring and recombines with the second radical that is generated by the P450 through the second hydrogen abstraction step. This forms a C–C bond that couples the two phenolic rings and gives rise to the rigidified morphinan scaffold of salutaridine that is found in morphine and related opioids.

In reality, psychoactive natural products are produced as complex mixtures of metabolites and frequently have partially undefined compositions.Variability in growth conditions, in addition to pests, disease, agrochemicals,vertical grow and climate may introduce further inconsistencies in product composition.In the event that a single psychoactive constituent is desired by the consumer and isolation from the native host is costly, total synthesis may be one strategy to establish a robust supply chain. In the last two decades, advances in DNA technologies have resulted in the development of an alternative production strategy: synthetic biology.Synthetic biologists use genetic tools to build designed biological systems with useful functionality. Whether or not synthetic biology can produce a viable process depends on the economic, environmental, and societal cost of alternative production strategies. However, as novel DNA-related technologies continue to arise, capabilities of molecular biologists are expected to expand. In 2010, Gibson assembly,DNA microarraysand zinc-finger nucleases were considered state-of-the-art. A PhD student that graduated in 2020, however, would have witnessed cost-efficient gene synthesis,66 RNA-seq,and CRISPR/ Cas968 emerge as routine. The substantial unrealized potential of synthetic biology is evidenced by continued investments across industry and academia. As these technologies expand, successful refactoring of a bio-synthetic pathway relies on the use of well-characterized “genetic parts” – these DNA-based elements permit coordinated expression of genes of interest in a heterologous host.Following the standardization of genetic engineering protocols and genetic parts, reliable metabolic engineering techniques have been established that enable improvements in engineered systems. The general methodology for synthetic biology-based heterologous production of natural products is outlined in Fig. 6. First, a bio-synthetic pathway must be elucidated such that a heterologous production strategy can be envisaged. Second, an appropriate bio-synthetic chassis must be selected. Finally, the engineer must iterate through the design, build, test, learn cycle until sufficiently high titers, production rates, and yields are reached.

Biocatalytic production methods benefit greatly from fully elucidated bio-synthetic pathways; a single missing bio-synthetic step may completely derail heterologous production efforts. Identification of natural product bio-synthetic logic is the primary focus of Sections 2 – 5. Early bio-synthetic investigations involved demonstrating that isotope labeled precursors could be site-specifically incorporated into final products, which provided connections between primary metabolism and natural product biogenesis. Now, genomic sequencing and synthetic biology tool kits permit gene knockouts in the native host or expression in a heterologous host for functional analysis. “Reconstitution” of the activity of a recombinantly expressed enzyme activity in vitro affords the most unequivocal evidence of a bio-synthetic sequence. It should be mentioned that availability of transcriptomics data has provided a quantum leap in the ability to identify candidate enzymes, particularly in unclustered plant pathways. Whereas bacterial and fungal bio-synthetic pathways are frequently colocalized in a “gene cluster,” examples of clustered plant pathways are scarce.Meanwhile, the differential abundance of RNA across plant tissues and cultivars gives metabolic engineers precise spatiotemporal gene expression data, which can be mined for information about bio-synthetic pathways. In recent years, RNA-Seq has been used to identify a wide range of plant natural product biosyntheses, including a number of key conversions in psychoactive natural product pathways.For instance, Facchini and coworkers utilized RNA-Seq to discover neopinone isomerase, which catalyzes a reaction previously believed to occur spontaneously in morphine biosynthesis.As an additional example, Luo et al. identified a functional prenyltransferase enabling cannabinoid production in S. cerevisiae by interrogating Cannabis sativa transcriptome data.In some cases, a bio-synthetic step from the native organism cannot be identified, or functional expression of a known pathway gene may not be feasible in a given organism. In this event, bioprospecting or mining the genomes of alternative organisms to identify functional proteins that carry out key reactions has been successfully applied. For example, incorporation of genes from Gallus gallus and Rattus norvegicus in place of missing or non-functional yeast metabolic steps was a crucial advancement in the development of MIA and BIA producing strains.

Alternatively, protein engineering strategies may be employed to alter the regiospecificity or substrate specificity of other wellcharacterized proteins in order to generate de novo suitable replacements for missing or nonfunctional steps. Dueber and coworkers employed this method to engineer a L-tyrosine hydroxylase, which normally requires a cofactor not produced in yeast, and used the evolved enzyme to produce a morphine precursor.The field of directed evolution is now well established,which can be implemented prior to DBTL or integrated into the DBTL pipeline. Following partial or complete pathway elucidation, a bio-synthetic strategy may be designed. For many psychoactive natural products, especially those which can be easily constructed from primary metabolites, de novo production from minimal media will provide the most cost-efficient route to a final product. Stephanopoulos and coworkers recently highlighted an alternative approach: the use of a late-stage pathway entry point to circumvent troublesome early bio-synthetic steps.Such “mixed carbon” feeding strategies may prove useful if an intermediate is commercially available or accessible via facile chemical synthesis. Efficient uptake of the late-stage entry point is another requirement, as transport limitations may prevent efficient substrate incorporation. The terms bio-transformation and bio-conversion are commonly used to refer to this type of hybrid synthetic approach,vertical outdoor farming which has been leveraged in the biosynthesis of psilocybin81 and an ibogaine precursor.Lastly, many in silico pathway design algorithms have been described in recent years, which perform automated retrobio-synthetic analyses to predict novel or optimized pathways.This approach has been successfully applied to primary metabolic products, highlighting the demand for continued investigation of secondary metabolic pathways. Machine-learning technologies linked to databases of reactions using automated DBTL are predicted to play a role in the future of natural product bio-manufacturing.A critical parameter in the successful refactoring of a natural product pathway is the selection of a suitable bio-synthetic chassis. Five representative bio-synthetic chasses are shown in Fig. 6. The model bacterium Escherichia coli has become a foundation of biotechnology as a DNA bearing model organism. E. coli laboratory strains have been customized for plasmid propagation and protein expression. Production of drugs with relatively short bio-synthetic pathways has been shown,with stepwise mixed-strain cultures leveraged for longer pathways.Saccharomyces cerevisiae was initially the subject of genetic studies, but has become a favorite organism in academia to demonstrate heterologous production of an impressive variety of plant or fungus-derived psychoactive drugs.The model ascomycete Aspergillus nidulans has also been used for the production of bio-active molecules due to its robust secondary metabolism and ability to splice fungal introns.Nicotiana benthamiana has proven useful in characterizing and reconstituting difficult plant pathways, and is particularly attractive due to the well-established and modular transient gene expression technologies.The fifth chassis is synthetic biochemistry, wherein long-lived “cell-free” enzymatic reactions have enabled high-titer flux through lengthy bio-synthetic pathways.One must carefully consider the features of a given pathway before deciding if a particular chassis meets the bio-synthetic requirements. Many natural product pathways evolved in the context of highly specialized organelles, cells, or tissues.In this case, pathway compartmentalization may be required in order to sequester reactive bio-synthetic intermediates from endogenous metabolism.

Currently, sub-cellular localization is possible through the use of organelle-targeting peptide signals fused to the N-terminus of pathway enzymes, or the use of intracellular protein scaffolds. The recent production of tropane alkaloids in yeast required extensive localization across six sub-cellular locations.Tissue specific pathway localization in multicellular model organisms has yet to be employed but will require the implementation of intercellular metabolite transport. Special attention must be given to enzymes that are membrane associated, including the cytochrome P450s.Even in the most appropriate chassis, functional expression of trafficked proteins may require extensive engineering. Galanie et al. employed a protein chimera strategy to ameliorate improper processing of a P450 for opioid biosynthesis in yeast.Solubilization of membrane anchored P450s has been successfully demonstrated, but a general strategy guaranteeing functional soluble expression of P450s is still a major technological hurdle.It is also important to consider the primary metabolite building blocks required for construction of the secondary metabolite to be produced. Individual organisms exhibit variable fluxes towards given metabolic pools, dictating initial maximum titers prior to strain engineering. To address this limitation, “metabolic chassis strains” – strains with increased flux towards dedicated natural product building blocks – have been developed. Microbial chasses for the production of N-methylpyrrolinium strictosidine -reticuline and a number of other psychoactive natural product precursors have been established in the last decade. The availability of a robust synthetic biology toolkit is another important factor to consider when selecting a production host. An ideal suite of molecular biology tools permits accurate and rapid genomic edits, precisely controlled gene expression, and diversity generation using libraries of genetic parts. More industrially “robust” organisms may also be utilized. These may be proprietary strains that outperform laboratory strains, but oftentimes lack the synthetic biology toolkit characteristic of the previously described model organisms. Proprietary methods may be developed for rational engineering, or random mutagenesis may be employed for non-rational diversity generation. Additional properties of robust chasses are faster growth, resistance to contamination, and a tailored metabolic profile. Predictable scalability and ease of downstream purification costs should also be considered when assessing platform commercialization.For academic purposes, however, it is most common to recapitulate bio-synthetic pathways in model organisms as a proof-of-concept. Iterative design methodologies are now commonplace in deploying synthetic biology-based engineering. In natural product production chasses, first generation strain prototypes almost never produce compounds in sufficient quantities to compete with alternative production strategies. As a result, many iterations of design, build, test, and learn are required before a process is cost competitive. The industrial feasibility of bio-process is often measured by titer , rate , and yield as these metrics relate to cost of goods sold .In addition to improving titers on the strain engineering front, large improvements in productivity can be made through bio-process engineering, which has benefitted immensely from automated design of experiment methodologies. The ability to iterate through the DBTL process is dependent on the bio-synthetic chassis, engineering strategy, and screening strategy, among other factors. Novel metabolic engineering approaches aim to reduce the cost or duration of some aspect of the DBTL cycle.As previously mentioned, “automated design” and “machine learning” technologies have only recently been deployed in metabolic engineering studies. Thus, we focus below on methodologies which streamline the “build” and “test” phases of iterative design.

Frequency of marijuana use was significantly associated with race/ethnicity and age, such that participants who identified as white and who were under age 21 at the time of assessment reported more days of marijuana use. The main effect of time was not significant, indicating that days of marijuana use was stable over 3 years of observation, consistent with the descriptive statistics in Table 1. The post-legalization slope term was also not significant, indicating that the trajectory of marijuana use for the post-legalization segment of the model did not differ from the overall trajectory.Table 3 shows the final model evaluating the impact of legalization on associations between demographic variables and frequency of marijuana use over time. We found that age and racial/ethnic identity continued to predict marijuana use frequency, but that the strength of those associations did not change over time or following legalization. In contrast, we found significant interactions of sex with both time and legalization. To better understand these interactions, we removed sex from the model and evaluated associations between time, legalization, and marijuana use frequency separately for men and women. These analyses indicated that marijuana use frequency generally decreased over time for male participants , but also increased nonsignificantly following legalization . In contrast, female participants reported increasing marijuana use frequency over time overall, but with a non-signficant decrease after legalization . Examinatin of adjusted means suggested that, in both cases,hydroponic rack system the non-significant effect of legalization was a reflection of an initial post-legalization increase followed by a reversion to the previous trend of decreasing use over time for men and increasing use for women. Table 4 shows the results of the model examining substance use predictors.

There was a positive association between alcohol frequency and marijuana frequency, but this did not vary by time or after legalization. In contrast, we found that the associations between both cigarette frequency and e-cigarette frequency and marijuana frequency over time were moderated by legalization. To clarify these interactions, we removed legalization from the model and examined associations before and after legalization. These simple effects tests showed that, before legalization, there was a consistent positive association between cigarette and marijuana use frequencies that did not vary over time . However, this association declined over time following legalization . In contrast, the association between e-cigarette frequency and marijuana frequency was significant at baseline but declined over time prior to legalization . However, following legalization there was a consistent positive association betweent the two . Finally, we evaluated the extent to which the total number of days of marijuana use prior to legalization predicted days of marijuana use after legalization, and if so whether this varied by time. Age, sex, and race were included as covariates but none were significantly associated with marijuana use after legalization in this model. We found a significant main effect and interaction with time . The former indicates that those who reported more cumulative days of marijuana use prior to 2018 also reported more days of marijuana use at the first assessments they completed in 2018, while the latter indicates that this association grew stronger over subsequent observations.We set out to examine whether frequency of marijuana use changed following legalization of recreational sales in California. We also planned to test whether post-legalization trajectories of marijuana frequency would be associated with sex, age, race/ethnicity, alcohol or tobacco use, or pre-legalization marijuana frequency. We utilized a sample of young adults who were non- and never-daily cigarette smokers at the time of enrollment. This sample has multiple advantages compared with others that are available. Unlike most national datasets, we were able to evaluate change over time in a specific cohort. Additionally, assessment occurred at specific, quarterly intervals. Thus, in addition to providing more assessments within each year, it was possible to pinpoint each assessment to before or after changes in legal status. Additionally, the analytic approach allowed us to include participants who were enrolled at different points prior to legalization and thus had completed varying numbers of assessments at that point.

Contrary to our expectations, frequency of marijuana use did not change significantly after legalization, and was stable throughout three years of observation. Participants who were younger and who identified as White reported more days of marijuana use; these associations were consistent over time and did not change with legalization. Sex differences were also noted, with men reporting decreasing and women increasing marijuana use frequency over time, though this association was not significantly related to legalization. This difference is contrary to previous research suggesting greater use among men , though more recent data suggest that this discrepancy is shrinking . Our findings are consistent with evidence that use may escalate more quickly among women . Women appear to be more sensitive to the rewarding effects of cannabis use , and thus may be more vulnerable to increasing use after initiation and/or when barriers to use are reduced. We also found that associations of both cigarette and e-cigarette frequency with marijuana frequency over time were moderated by legalization. More specifically, the association between marijuana and cigarette use became weaker following legalization, while the marijuana-e-cigarette assocation showed the opposite pattern. Frequency of alcohol consumption was consistently associated with marijuana use over time and did not change with legalization. Finally, we found that those who reported more frequent marijuana use prior to legalization tended to do the same afterward, particularly at later assessment points. Although frequency of of marijuana use was associated with both cigarette and e-cigarette use, the post-legalization findings suggest that co-use of e-cigarettes and marijuana may increase when the latter is legalized. One potential explanation for this could be that many young adults perceive vaping and marijuana use as conferring little risk , in which case legalization may have removed an important barrier to use. In combination with the finding that marijuana use was more common among those under age 21, this suggests that enforcement of minimum age laws may be an important component of limiting use of both marijuana and e-cigarettes. Our finding of no overall change in marijuana frequency is consistent with reports suggesting little impact of medical marijuana laws on use in California . It is notable that we found that those who used marijuana more frequently prior to 2018 reported greater increases in use from 2018 onward.

On one hand this is encouraging in that it suggests that lighter and non-users of marijuana were not necessarily encouraged to use as a result of legalization. On the other hand, it appears that those who were already more regular users may have tended to increase consumption, potentially increasing vulnerability to the risks associated with marijuana use. In contrast to previous studies , we found participants who endorsed greater frequency of marijuana use had greater frequency of use of tobacco products. Following legalization this was particularly true for e-cigarettes. The specific mechanism for this association is uncertain,rolling benches canada but there are multiple possibilities. First, it may be that relaxing restrictions on a specific substance reduces substance-specific concerns about harm , which then generalizes to other drugs. Alternatively, the association can be explained by use of products that deliver both drugs at the same time , or newer vaporizing devices that may do so separately. It is plausible that innovations in nicotine vaping devices encourages marijuana vaping, promoting diversified marijuana product use and synergistically increasing use of both products. This is consistent with the strengthening association between marijuana and e-cigarette use frequencies postlegalization. The association could also be a reflection of contextual or environmental influences . The possibility that lessening marijuana barriers increases tobacco use is concerning given evidence that co-use is associated with psychosocial distress , health problems , nicotine dependence , and tobacco cessation failure . The present study has several limitations. It is a secondary analysis of a naturalistic study of young adult tobacco users, which limited the specificity of marijuana-related measures and may have yielded a sample with disproportionately frequent marijuana use. There is a strong need for additional studies that include outcomes beyond simply quantity, freuqency or prevalence of use . The design may limit generalizability to other young adult samples. Another limitation is reliance on self-reported substance use data, though evidence suggests self-report tends to be accurate in observational studies, given the lack of strong demand characteristics . Additionally, self-reported data include only some days during 2015–2019 and may not be representative of use during the entirety of this period. Finally, while the study captured self-reported use of marijuana and nicotine/tobacco products before and after legalized sales of recreational marijuana began in California, we did not directly evaluate access to marijuana retail outlets or other methods of product acquisition.

Estimates of recent marijuana use in HIV-seropositive individuals have ranged from 14% to 33% , which contrasts with the 2% to 9.5% prevalence estimates in the general United States population . Importantly, prevalence of daily or near daily marijuana use has steadily increased in recent years in the general United States population and in HIV+ persons . Randomized controlled trials and observational studies of HIV+ persons indicate therapeutic benefits of cannabinoids – the active components in marijuana – in reducing pain, nausea, insomnia and improving appetite and mood symptoms . However, marijuana use has been associated with decline in cognitive function . Marijuana might influence cognitive function via the actions of tetrahydrocannabidiol – the main psychoactive cannabinoid in marijuana – on cannabinoid receptor 1, located on specific brain regions including the hippocampus, cerebellum, basal ganglia, amygdala and prefrontal cortex , which are involved in cognition . Therefore, activation of CBR1 by THC in these regions could have effects on cognitive function . Not surprisingly, the associations between marijuana use and cognitive functions has received increased attention. There is convincing evidence that acute intoxication with marijuana impairs cognitive function in multiple domains including executive functioning, processing speed, attention and working memory—with the most consistent deficits found in learning and memory functions . However, whether these deficits endure past periods of intoxication , following periods of abstinence, or in the long-term is less clear. Most cannabinoids, including THC are fat soluble and are easily stored in body fat for prolonged periods of time and are slowly released back into the circulation , a property that potentially supports the hypothesis of residual effects of cannabis on cognitive function. Two meta-analytic studies have synthesized findings of studies assessing residual effects of marijuana use on cognitive function. The first study observed statistically significant negative effects of marijuana use on learning and forgetting domains, of modest effect size . The second more recent study, found small deficits in multiple domains including forgetting/retrieval, abstraction/executive function, attention, motor skills and verbal/language, but, when the analysis was limited to studies with at least 125 days of abstinence, no significant effect of marijuana on any cognitive domain was observed . Notwithstanding, majority of the literature on marijuana use and cognitive function have been cross-sectional with modest sample sizes. Furthermore, the literature among HIV+ individuals has been scant. HIV+ individuals are vulnerable to cognitive impairments via direct effects of the virus and indirect effects of comorbid conditions highly prevalent among HIV+ individuals . Cognitive function deficits are common among HIV+ individuals even with highly active antiretroviral therapy  and have been associated with medication nonadherence . Thus, any potential negative effects of marijuana on cognitive function may be more pronounced among HIV+ individuals. To date, the relatively small literature on marijuana use and cognitive function in HIV+ individuals have focused on current use . With, 29 U.S. states passing laws allowing medical and/or recreational marijuana use, and most state medical marijuana laws listing HIV/AIDS as condition that could benefit from medical marijuana , there is a need for additional evidence on the impact of marijuana use on cognitive function, including its long-term impact, and the magnitude and clinical importance of any effects. The Multicenter AIDS Cohort Study has continuously collected data on marijuana use since its inception in 1984/1985 and evaluated cognitive function for 26 years and thus represents an ideal opportunity to study the long-term effects of marijuana use on cognitive function of HIV+ individuals. The aim of the current study is to evaluate associations between current and cumulative exposure to marijuana and changes in measures of cognitive processing speed and flexibility among HIV+ and HIV-seronegative participants in the MACS.

Organic farms make up 6.5% of California dairies and are overrepresented in our sample ; however, this overrepresentation has the advantage of providing more accurate estimates for management practices from this sector of California’s dairy industry. The mean percentage of calves housed individually on dairies in our study of California dairieswas similar to the proportion of dairies that reported housing calves individually in the survey of California dairies by Love et al. , but larger than the mean nationally . Given the similar order of magnitude in breed distribution and other factors, such as organic status and individual calf housing, results of our study could be extrapolated to dairies in California and elsewhere that fall within the study herds’ description and climate.Case definitions for BRD vary widely between studies and, therefore, any comparisons of results should be interpreted with caution. Some studies rely on treatment records by dairy staff, whereas others use certain clinical signs for diagnosis, which may also differ between studies. Most epidemiological studies on BRD in dairy calves report incidence rates rather than prevalence. Lago et al. found a prevalence of 14.3% in 225 dairy calves housed in barns in the winter in Wisconsin and diagnosed with the Wisconsin BRD scoring system for preweaned calves. Buczinski et al. found a median prevalence of 8% in the summer and 15% in the winter for lung consolidation diagnosed by ultrasound, consistent with BRD in preweaned calves in 39 dairy herds in Québec. Indoor housing and poor ventilation are associated with BRD, so the higher prevalence in the Wisconsin and Québec studies in the winter is not unexpected . Both Buczinski et al. and Lago et al. reported a gradual increase in prevalence from birth to the sixth and seventh week of life, respectively; we observed a similar rise in prevalence,hydroponic tables canada which continued until 65 d of age . The fact that most of the calves in the current study were housed outdoors may explain the lower prevalence observed of 6.9%, comparable to what Buczinski et al. observed in the summer. Distributions of the percent of cases by age stratified by breed or region are shown in Supplemental Figures S2 and S3 , respectively.

Even though we observed lower prevalence in the NSJV region compared with the other regions of the state, region was not significantly associated with BRD when adjusting for other factors in the multivariable model. We observed lower prevalence in herds between 1,000 and 3,999 milking cows compared with herds with fewer than 250 or more than 4,000 milking cows. Likewise, we found no association between herd size and BRD in the final model. Little evidence exists in the literature to support associations of breed or herd size with BRD. A previous study found a higher risk of preweaning calf pneumonia in Ottawa for increasing number of calvings per farm per year . No interpretation for this result was offered by the authors and it may not be relevant to the large California dairy farms of today.In the current study, we observed positive associations of calves housed in hutches made from metal components and BRD. In a study based on the same data set, the prevalence of BRD observed in calves housed in wooden hutches was similar to the prevalence of calves housed in metal hutches . However, in NCA, BRD prevalence for calves housed in hutches or pens made of metal was significantly higher compared with those housed in wooden hutches . Furthermore, a longitudinal study of 11,300 preweaned calves in California showed that calves housed in hutches made of a combination of wood and metal were at higher risk of BRD compared with calves housed in hutches made of wood only . Calf-to-calf contact in the age group over 75 d was also significantly associated with BRD. Results of past studies on the effects of hutch type on calf health were mainly focused on the effect of plastic type hutches or available space. Calvo-Lorenzo et al. housed calves in wooden hutches of 3 sizes between April and July in California to assess the effect of hutch space on health, performance, and respiratory immunity. Calves were raised in conventional California-style wooden hutches and allowed either 1.23, 1.85, or 3.71 m2 /head of space. Those authors concluded that increased space may improve pulmonary immunity and health, although it was not apparent which component of the increased space allowance environment influenced the finding. We did not observe an association of hutch space with BRD in the present study, possibly because hutch material may be the more important component associated with BRD. The temperature in plastic hutches can average 5 to 10°C higher than in wooden hutches and ventilation is comparatively poor, leading to accumulation of heat, carbon dioxide, and humidity . Several studies have compared the effect of plastic hutch types on performance and health outcomes in dairy calves, and although agreement exists that plastic hutches increase heat stress, none have found significant associations with adverse health outcomes .

No references regarding the effect of metal style hutches were found in the literature, but heat stress and possibly cold stress are likely associated with metal hutches and may explain the current study findings. Specifically, 69% of metal hutches housing individual calves on 9 dairies in the current study also had metal roofs, whereas 31% on 13 dairies had no roof but were under a shed or other shade structure. The difference in health outcomes between hutch types should be researched further, ideally using an experimental study design comparing a limited number of hutch designs, including hutches made from metal components. The large number of different hutch designs in our study made it difficult to elucidate the association between hutch material and BRD and has resulted in large confidence intervals around estimates. The current study identified a positive association between calf-to-calf contact and BRD in calves older than 75 d. Callan and Garry recommend spacing hutches at least 1.2 m apart to prevent calf-to-calf contact and transmission of respiratory pathogens. A distance of 1.2 m between hutches was rarely, if at all, the case on the California dairies visited for our study, and the feasibility of this strategy and its cost in terms of land needed to raise the same number of calves may be a challenging constraint. In calves that are close to weaning age , housing- or nutrition-related factors may be less important; thus, calf-to-calf contact with animals shedding pathogens may become a more important factor for their BRD status. Lagoon flush water could be a source of noxious gases that may irritate respiratory mucous membranes, making calves susceptible for opportunistic infections with commensals. The role of lagoon water on a dairy as a source of infective agents has mainly been studied with respect to enteric pathogens, including Mycobacterium avium ssp. paratuberculosis, Salmonella spp. and Escherichia coli and its effect on antimicrobial resistance in some of the pathogens . Alhamlan et al. found members of the Flaviviridae in lagoon water samples, a family of viruses that contains bovine viral diarrhea virus . Although the viruses were not categorized to the species level in Alhamlan et al. , it is conceivable that lagoon water could be a potential source for exposure to respiratory pathogens if used as flush water, especially if aerosolized particles are created,microgreen rack for sale potentially resulting in inhalation of pathogens.

If flush water is close enough to hutch floors, calves could also be able to ingest or have direct exposure of oral or nasal mucosae to pathogens. In addition to BVDV, bovine coronavirus is shed via feces and could cause respiratory disease in calves. The significance of lagoon water as a source of pathogenicity with respect to BRD should be further evaluated. We also observed a negative association between the presence of an additional shade structure over the hutch area and BRD. Shade could reduce heat stress as well as protect from rain or frost, resulting in lower odds of BRD. The association between shade and BRD was not observed for shade structures with 1 to 4 sidewalls, which could be due to an offset of the benefits due to a lack of ventilation. Coleman et al. studied the effect of supplemental shade structures over polyethylene calf hutches in Alabama during the summer on feed consumption, growth, calf stress, and bedding contamination. Their study found no differences between groups in terms of health-related outcomes, but humidity and coliform counts in bedding were higher in shaded hutches, which may be due to the difference in climate between the 2 states, specifically the higher humidity in Alabama during the summer months.Feeding pasteurized milk versus nonpasteurized milk, including milk replacer, was associated with reduced BRD prevalence. Numerous studies have underlined the importance of pasteurizing milk fed to dairy calves for the prevention of enteric disease as well as exposure to potential respiratory pathogens . Mycoplasma spp. are mastitis pathogens that can be shed by clinically or subclinically infected cows and can colonize the nasopharynx of calves fed the milk resulting in otitis and respiratory disease . Mycoplasma and other bacterial pathogens ingested in the milk can also spread hematogenously to the lungs, where they cause respiratory disease . A study from Spain found decreased morbidity and mortality in calves with adequate transfer of passive immunity during the first 3 wk of life that were fed heat-treated colostrum and pasteurized milk versus those that received nonheat-treated colostrum and nonpasteurized milk . A separate study by Godden et al. found a higher risk of pneumonia in calves fed milk replacer than for calves fed pasteurized waste milk. Those authors argued that the improved immune function was attributable to higher energy and protein intake or the presence of medium-chain fatty acids in the whole milk, which have shown antimicrobial effects in pigs. We also observed a negative association of feeding a diet consisting of at least 90% saleable milk for at least 7 d at time of farm visit with BRD versus any other milk diet, including waste milk or milk replacer. Several studies have evaluated the effect of milk intake volume on calf performance . Medrano-Galarza et al. found no associations between within-pen prevalence of BRD and peak milk allowance in a study of majority Holstein group-housed dairy calves fed with automated milk feeders. However, calves in that study were fed at least 4 L per calf per day before and at least 6 L per calf per day after introduction to the group pen. A different study, similarly found no difference in incidence of BRD between Holstein calves fed a maximum of 6 or 8 L of milk replacer per day in a randomized trial comparing performance and health response of dairy calves offered different milk replacer allowances . Higher amount and quality of milk replacer fed was found to be associated with superior immune function in Jersey calves . The group of Holstein calves fed ≤2.84 L of milk or replacer per day in our study was fed less than the lowest amounts supplied to calves in the above-mentioned studies and were likely not able to consume enough starter to meet their nutrient requirements for growth and development if they were under 2 mo old . Results in our study showed increased odds of BRD for Holstein calves fed ≤2.84 L and decreased odds of BRD in Jersey calves fed >5.68 L of milk or replacer, which may reflect the effects of nutrition on immune function but should be interpreted with caution due to the relatively small samples in those categories, resulting in large confidence intervals for estimates. Restricting the analysis to calves ≤75 d of age did not change the sign or statistical significance of contrasts except for the comparison of >5.68 to ≤2.84 L of milk or replacer in Jersey calves, which became nonsignificant . Future research should quantify the benefits of saleable milk compared with waste milk or milk replacer further, as well as how the association with BRD is modified by pasteurization and amount of milk fed in the major dairy breeds.The current study found no significant associations between calf or dam vaccination status for respiratory pathogens and BRD in the study population.

All statistical analyses were completed using R statistical software . The purpose of this pilot study was to examine the association between non-daily and daily MJ use patterns on sleep patterns in young adults recruited from the community. Daily MJ users endorsed more sleep disturbance on the PSQI and ISI than non-daily users. These results are consistent with previous studies showing an association between sleep disturbance and heavy MJ use in adults. Of note, however, was our finding that nondaily MJ users and non-users had similar sleep indices. Daytime sleepiness and chronotype did not differ across our three groups. This study provides new information about the relationship between MJ use patterns, mood, sleep, and daytime functioning. We found that the proportion of persons reporting a clinically significant PSQI threshold of >5, which distinguishes good from poor sleepers, was lowest among non-daily users and highest among the daily users . We also found that these non-daily users tended to use MJ mostly at nighttime, whereas daily users smoked considerably more MJ on use days and used during the day and the evening. The effects of MJ on sleep in intermittent users may be similar, in part, to that of alcohol where improvements in sleep continuity measures have been reported with intermittent use, whereas daily use results in the worsening of sleep. However, methodological differences in previous marijuana studies limit definitive support. While a review of 39 research studies on the effects of cannabis on sleep revealed that cannabis may interrupt sleep patterns and result in non-restorative sleep,commercial greenhouse supplies objective polysomnography in heavy MJ users show normal sleep patterns during periods of cannabis use.

One possible explanation for the study findings is that individuals habituate to the sleep inducing effects of cannabis after continued use. In addition, our finding that non-users had similar ISI scores to non-daily users, and that a lower proportion reached clinical criteria for insomnia, suggests that sleep disturbance, which is common in this age group, may not be increased by non-daily MJ use. Because this is not a MJ administration trial, this remains speculative. The clinical significance of the lower ISI score in non-daily users is likely minimal, as all scores <10 typically reflect sub threshold insomnia. Our findings suggest that anxiety is significantly related to scores on the PSQI. Persons with anxiety may be using MJ to mitigate their sleep symptoms. This is consistent with the literature, where MJ is the most commonly used illicit substance in individuals with anxiety disorders 40 and where higher MJ use has been associated with higher rates of anxiety. Lev Ran et al. found that when adjusting for any concurrent mood disorder, there was a significant impact of regular, but not occasional, use of cannabis on mental health-related quality of life in participants with anxiety disorders. It remains possible that our ISI scores might have been higher in the daily MJ users because MJ was contributing to anxiety, which in turn may have exacerbated the severity of insomnia. We found gender effects on our PSQI and ISI scores, but not on ESS or MEQ scores. The relationship between insomnia and gender was expected as insomnia is more common in females than in males in non-substance using populations. Lev-Ran et al. found that compared to non-users, occasional MJ users had poorer mental health scores in females, but not among males. These findings suggest that MJ use patterns may affect females differently given their increased risk of both insomnia and depression. MJ has been shown to affect women more significantly than men on neuropsychological tasks.We expected that there would be more evening chronotypes in the daily MJ use category, because evening chronotypes have been shown to be more likely to use alcohol, to have poor impulse control, depression, and difficulty falling asleep.

However, our MEQ results did not differ between non-users, non-daily and, or daily users. This finding is consistent with results of one study which utilized the Horne Ostberg questionnaire to assess chronotype in MJ users and reported that there were no chronotype differences between heavy MJ users and non-users. Our study is among others to examine chronotype among persons who are primarily MJ users where the influence of concurrent heavy alcohol use has been mitigated. While the relationship between chronotype and substance use is likely multifactorial, future studies might consider exploring whether evening chronotypes may be more likely to use alcohol or MJ. Our study had several limitations. First, daily MJ users in this study were heavy users, therefore, we are unable to know if the sleep reports of daily users are a result of frequency of use or quantity of use. Future studies might try to recruit daily MJ users who smoke minimally, perhaps only at night to “treat” sleep disturbance. Second, participants selfreported MJ use and sleep indices. Third, given the cross-sectional nature of this study, we are unable to assess causality. Fourth, the size of our sample increases the risk of Type 1 error, missing associations that might have been seen in a larger study. Fifth, the absence of significant difference between the non-user and user groups may have been due to low power, as the non-user group had a lower number than user groups. Sixth, we did not quantify the use patterns beyond the past month. Therefore there may have been users in our non-user groups that could have quit more than one month ago. Seventh, the sample may not be representative of this population for two reasons. Even though we recruited MJ users and non-user controls from a larger study on alcohol and marijuana, our exclusion criteria may have been too limiting. In addition, given the high rate of unemployment and low rate of high school graduates in our study sample, this study sample may not be representative of this demographic. Eighth, the non-using control sample in this study was recruited from a larger study, which may have affected statistical assumptions for comparing the MJ user group with the HC group. Lastly, a formal diagnosis of insomnia was not conducted in this study and therefore associations with insomnia based on the ISI should be interpreted cautiously. With the increasing availability of MJ and an increasing number of individuals using it for insomnia with the belief that MJ use improves sleep, our study suggests that daily use may not in fact improve sleep, although this study cannot est. Large scale studies assessing the impact of MJ on sleep are warranted.

In 1996, California became the first state to legalize medical marijuana. Known officially as the Compassionate Use Act, Proposition 215 allowed patients and caregivers to cultivate and possess marijuana for medical use. The campaign in favor of Proposition 215 focused on the benefits for seriously ill patients. Claiming that the Proposition “sends our children the false message that marijuana is safe and healthy,” the campaign against the Proposition focused on anti-drug education . Neither side addressed potential public health consequences. If Proposition 215 led to an increase in marijuana use, for example, might it also lead to higher rates of all injury deaths , including deaths from assault , deaths from motor vehicle crashes ,cannabis dry rack and—the subject of the present study—deaths from suicide ? Such consequences assume that medical and recreational users are similar. With one exception, the evidence supports this assumption. Since most California medical users were introduced to marijuana as recreational users, for example, it is reasonable to assume that the user-types have similar socioeconomic backgrounds . Compared with recreational users, however, California’s medical users were more likely to report early health problems or disabilities that would warrant medical use . Although Proposition 215 was drafted so loosely that it effectively legalized all uses of marijuana , marijuana use by California juveniles, who were not eligible for medical marijuana certificates, did not increase following Proposition 215 . Nevertheless, at the national level, during a 15-year period when a majority of states loosened their control of medical marijuana, the U.S. suicide rate rose by 24 percent , prompting many to question how legalization and suicide might be linked. The systematic evidence connecting this trend to the availability of medical marijuana is ambiguous, however. Rylander, Valdez, and Nussbaum , for example, find no correlation between a state’s suicide rate and the number of medical marijuana cardholders in the state. Similarly, comparing suicide before and after a state enacts a medical marijuana law, Grucza et al. find no change in a state’s suicide rate. In contrast, Anderson, Rees, and Sabia report a 10.8 percent reduction in suicides averaged across all medical marijuana states. Attributing a suicide trend to the availability of medical marijuana raises questions about the potential mechanisms at play. What theoretical mechanisms could lead us to expect a relationship between the availability of medical marijuana and suicide? Could these mechanisms be more salient for certain types of suicides than others? If the expected relationship is observed, what methodological rules could be used to support a causal interpretation of the relationship? We address these questions in order. Sociological theories of suicide follow Durkheim’s dictum that “suicide varies inversely with the degree of integration of the social groups of which the individual forms a part” . Institutions that successfully integrate the individual, providing a sense of belonging to the community, inhibit suicide. When institutions break down, so do the community ties that might otherwise inhibit suicide atrophy; and suicide increases.

Durkheim used cross-sectional correlations between suicide and the strength of religious, familial, and socioeconomic institutions to demonstrate his theory. The theory has been used to investigate relationships between suicide and unemployment, , poverty and income inequality , divorce and family structure , immigration and cultural assimilation , and cohort size . Regardless of focus, research largely advances a motivational argument for understanding variation in suicide rates across place or time. Although legalization of medical marijuana is likely to affect a range of societal institutions, the indirect effects through these institutions are expected to accrue gradually. Individual-level direct effects, in contrast, are expected to be realized abruptly. A more appropriate individuallevel theory for explaining the relationship between medical marijuana and suicide posits suicide risk as the product of motivation and opportunity factors. Holding motivation constant, suicide risk responds to changes in opportunity. Holding opportunity constant, risk responds to changes in motivation. Chew and McCleary use motivation/ opportunity mechanisms to explain lifecourse changes in suicide. Kubrin and Wadsworth use motivation/opportunity mechanisms to explain the effects of socioeconomic factors and firearms availability on race-specific suicide. Wadsworth, Kubrin, and Herting use motivation/opportunity mechanisms to explain suicide trends for young Black males. Consistent with this literature, we argue that if medical marijuana affects suicide risk, it must do so through one or both pathways. Mental health theories operate through a motivation pathway. The psychiatric consensus is that suicide is related to depression, anxiety, and other treatable disorders . If marijuana alleviates the acute stress associated with these disorders, then we expect suicide risk to decrease following legalization of medical marijuana. The evidence for this is mixed, however . Whereas medical users report that alleviation of acute symptoms of these disorders was a primary motivation for permit applications , a systematic review by Walsh et al. reported that this was not consistently observed across credible studies. Of course, marijuana use itself may constitute a risk factor for suicide apart from alleviating symptoms related to depression and anxiety, at least among some populations and for some levels of suicidality .A meta-analysis by Darvishi, Farhadi, Haghtalab, and Poorolajal supports the strong consensus that alcohol use disorder “significantly increases the risk of suicidal ideation, suicide attempt, and completed suicide.” With respect to medical marijuana, of course, the theoretical prediction depends on whether marijuana is used in addition to or instead of alcohol. If marijuana and alcohol use are combined, one might expect no change in suicide risk or even an increase in suicide following legalization. If marijuana replaces alcohol, on the other hand, one might expect a decrease in suicide risk following legalization.

While perceptions of benefits and addiction were not related to use in this study, perceptions of greater health and social risks were associated with lesser odds of using marijuana. Other studies have also found risk perceptions related to use . The fact that perceptions of benefits were not related to use is surprising as other studies have found perceptions of benefits to predict use . It is possible that perceived social norms are more important drivers of adolescents’ decisions to use marijuana than perceived risks and benefits despite the fact that these constructs are linked . While perceptions of benefits of marijuana were not related to use, seeing messages about the good things or benefits of marijuana use was associated with a 6% greater odds of use. In contrast, despite adolescents seeing ads for both risks and benefits of marijuana, messages regarding risks were not related to use. It is possible that individuals who use marijuana are actively seeking and more aware of messages related to benefits of marijuana use. There are limitations to this study. The data are self-reported. Further, given the cross sectional nature of our data, we cannot suggest a causal relationship between factors associated with marijuana use and marijuana use itself. Additionally, some of the factors associated with marijuana use have a confidence interval approaching 1.0. Finally, these data were collected throughout Northern and Southern California and thus are not nationally representative. Despite these limitations, this is one of the few studies to assess perceptions of social norms, risks and benefits for marijuana, blunts, and cigarettes. Additionally, this study assessed how these factors as well as awareness of social media are related to marijuana use. Results from this study offer a number of important public health implications,drying cannabis particularly as states move towards legalization of marijuana for recreational use. As this occurs, states need to take adolescents’ perceptions of risks, benefits, social norms, and peer influences into account.

Though there is mixed evidence on how legalization impacts adolescent marijuana use, advocates for marijuana legalization argue that legalization itself does not increase use among youth . However, there is no evidence that legalization alone does anything to decrease use or access among adolescents. The results from this study have a number of implications for prevention strategies. Perceived rates of marijuana use among friends is higher than participant self-reported use rates and reported national averages of adolescent use. This finding is similar to findings in the alcohol use literature, which finds that youth and young adults tend to overestimate rates of binge drinking. Importantly, dispelling this misperception has been used effectively in a number of social norms campaigns focused on reducing binge drinking in college campuses . This suggests that using a similar social norms marketing approach, in which youth learn that rates of marijuana use among peers are much lower than they think, may be a useful strategy to prevent use. In this study, both perceived friend use and having seen positive messages about marijuana was associated with greater odds that an adolescent used marijuana. These findings also suggest the need for marketing, education and intervention strategies that specifically tackle social acceptability and peer use. This study also shows that adolescents perceive marijuana and blunts to be significantly less harmful than cigarettes, despite the fact that all of these products are combustible smoking products. Additionally, despite the fact that blunts have nicotine, adolescents did not perceive these to be more addictive than marijuana. These findings suggest that there is also a need for educational and marketing campaigns that realistically address what the risks of marijuana and blunt use are for both youth and adults, including risks of addiction. National, state, and local public health agencies should consider lessons learned from regulatory and informational strategies that have been used in tobacco control, and should implement such strategies before legalization occurs .

Aquaculture, which is the farming of aquatic organisms including algae, invertebrates, and vertebrates, has been one of the fastest growing agriculture sectors for the past 40 years . Demand for seafood has continually grown with global fish production in 2018 at around 179 million metric tons , of which 82 MMT comes from aquaculture . While 86.5% of total finfish production occurs in inland freshwater systems, with the majority in Asia , marine culture has the highest growth potential with 2% of oceans being suitable for fish farming . For marine aquaculture growth, Australia, Argentina, India, Mexico, and the United States have the greatest potential based on suitable habitat . Freshwater finfish production has primarily been driven by carp, catfish, and tilapia, while marine fish production is dominated by Atlantic salmon which has a freshwater hatchery stage. Despite the recognized opportunities for marine finfish aquaculture production, very few marine fish species have been successful compared to freshwater fish, due in part to the inability to spawn and produce quality fingerlings in captivity. This has led to the common practice of catching wild juveniles and their transfer to captive rearing environments. In recent years, however, certain high value marine species, including the yellow tail kingfish Seriola lalandi, have been successfully reared in the lab . The Seriola genus, within the family Carangidae, contains several species of yellow tail that are globally distributed across broad temperature range . S. lalandi, is reared in temperate waters across the Pacific Ocean in Japan , Australia , New Zealand , Chile , and North America . Fish, unlike mammals, are not thought to inherit their microbiome vertically. Understanding the factors which influence microbiome development in fish is an important first step in mitigating disease and promoting health. One of the primary challenges in marine fish hatcheries is poor survival rate which is often attributed to a combination of disease and nutrition . Even in the wild, the survival rate for fish larvae is 44× higher for freshwater fish as compared to marine .

Wild marine fish, particularly temperate coastal pelagics like Seriola spp. , are exposed to wide ranges in environmental variables such as temperature, oxygen, and nutrients both diurnally with vertical migration for feeding and temporally with changing seasons. The mucosal microbiome of coastal pelagics is highly differentiated across body sites, primarily in the gill, skin, digesta, and gut tissue with the microbiome on external sites most influenced by these changing environmental variables . In mammals, both phylogeny and diet influence gut microbiome development ,ebb flow whereas fish microbiomes are influenced more by environmental variables including habitat, trophic level, phylogeny, and diet . Diet also varies widely by development stage particularly in the larval to fry stages . While mammals have a significant proportion of their gut microbiome colonized or inherited vertically from the mother during birth , the initial establishment of the gut microbiome in fish is less understood. Even fewer studies have sought to identify the source colonizers of gill and skin communities. Microbial colonization throughout development of the fish is a function of both exposure and host selection. At the earliest stage, bacteria which form biofilms on the outside of the egg eventually can colonize both external and internal mucosal sites of freshly hatched larvae upon ingestion of the yolk sac . Marine fish differ from freshwater fish in that they must drink vast quantities of water to maintain osmoregulation, which in turn provides a large source of potential microbes for gut colonization . The first live feeds the larvae consume, which in hatchery settings are often artemia and rotifers, also contribute to the gut microbiome development . In larval YTK, S. lalandi, gut microbiome composition and density changes most when transitioning from a live rotifer feed to pellet based feeds around 30 days post hatch with many of the gut microbes having anti-microbial functionality . In a study assessing gut enteritis in farmed S. lalandi from seapens, gill, and skin microbiomes correlated with disease state suggesting these communities were either responding to overall health decline or contributing to stress . For a freshwater hatchery, the tank side and tank water were shown to significantly influence the skin and gut microbiomes of Atlantic salmon . Despite the array of studies evaluating impacts of various husbandry methods on microbiome composition of mucosal sites , there is a lack of information for how microbiomes on surfaces in the built environment directly contribute to marine fish. To evaluate how the collective hatchery microbiome influences the mucosal microbiome of a marine fish, we investigated the economically important YTK S. lalandi. This study sought to answer three primary questions: Are body sites differentially influenced by the BE or feed microbiome?, What surfaces within a hatchery environment contribute to the mucosal microbiome of the fish?, and Does the BE and feed microbiome source contribution vary across age and development of the fish? To answer these questions, we sampled the mucosal microbiomes of 92 fish across three broad development stages . Specifically, we used 16S rRNA amplicon sequencing of microbial communities from the fish together with various hatchery surfaces including tank water, tank side, inlet water pipe, air stones, and air diffusers along with feed used in all stages of production.

To our knowledge this is the first study to quantify and compare the relationship of the BE microbiome with the fish microbiome across multiple age classes of a marine fish. All sampling events occurred in June of 2018 in Port Stephens Australia at the Department of Primary Industries New South Wales. Two broad sampling regimes were carried out . A total of 92 “YTK” were sampled in Port Stephens, Australia. In the first experiment, gill and skin swabs were sampled from a total of 36 living fish across three different indoor rearing condition tanks along with corresponding BE samples including tank water, the tank side, inlet pipes, and air diffusers. These fish were all siblings and 130 days post hatch “dph.” Fish were reared in either a flow through system “FT,” a traditional moving bed bioreactor “MBBR” Recirculating Aquaculture Systems “RAS,” or a modified BioGill RAS. Fish were reared at a max of 25 kg/m3 fed at a maximum of 0.5 kg food/day/m3 and reared in 10 m3 tanks. Additional details can be found in the white paper . Fish were non-lethally sampled during routine biometric measurements where individuals were weighed and measured. Prior to taking the weight and length, the skin and gill of each fish was swabbed using a cotton swab [Puritan] and placed directly into a 2 ml PowerSoil tube. For these three tank conditions, “BE” samples were taken from the tank water, swab of tank side , swab of air diffuser, swab of air stone, and swab of inlet water pipe. For the two RAS tanks, an additional inlet water sample was taken which represents cleaned water . Comparisons were made to determine if there was a relationship between the external fish mucosal sites and the BE and if so how that varied across the water filtration or rearing system. For the second experiment, fish were sampled cross sectionally at different ages including 43 dph , 137 dph , and 430 dph . Fish at 430 dph included fish sampled from an ocean net pen along with fish which were transferred from an ocean net pen back to an indoor system. For the age comparison cohort, three body sites were sampled including the gill, skin, and digesta “allochthonous” samples along with corresponding BE samples described in experiment 1. The BE “built environment” samples included tank water, inlet pipe, airstone, air diffuser, and tank side. Specifically 12 fish were similarly non-lethally sampled from three different age classes: 43, 137, and 430 dph from indoor tanks. The 430 dph fish from the indoor tank were initially reared indoor until 245 dph following methods described by Stewart Fielder et al. and then transferred to ocean netpens where they were grown for 106 days. At 351 dph, they were then transported back to the indoor system where they were held until sampled at 430 dph. An additional 20 fish at 430 dph from the seapen were harvested for another experiment and opportunistically sampled. All fish were measured for length and mass with condition factor calculated. A total of 92 fish were sampled across the two experiments.