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.

The relationship between the use of these two substances has a basis in the biological connection between them, as the endogenous opioid system is an underlying mechanism for several behavioral outcomes related to nicotine . Like marijuana, nicotine is involved in anti-nociception via endogenous opioid system mediation, suggesting that nicotine is used for the selfmedication of pain ; and in fact, nicotine heightens the anti-nociceptive effects of both opioids and marijuana . Several studies have documented common use patterns among tobacco, marijuana, and opioids/PPRs . For example, a prospective study of NESARC data demonstrated that early-onset of smoking cigarettes increased the odds of beginning opioid use and that frequency of both cigarette and marijuana use increased the odds of beginning opioid use, re-initiating opioid use after previously stopping, and continuing opioid use among current users . Thus, the three substances share anti-nociceptive actions mediated by the endogenous opioid system, and evidence indicates that marijuana and nicotine use predict opioid use among adults. From 2003 to 2012, NSDUH data revealed a significant increase in the co-use of marijuana and tobacco . Further, smoking tobacco is significantly associated with cannabis dependence . Given the national trend toward marijuana legalization, co-use is likely to increase. Cigarette smokers and marijuana users are a crucial population to study, as nicotine and marijuana share mechanisms of action with each other and with opioids, and use of each substance has been shown to be associated with use of opioids/PPRs . However, whether there is an association between prevalence of marijuana and PPR use among current smokers has not been determined. The present study addresses this gap by using the Tobacco Attitudes and Beliefs Survey II to investigate the relationship between marijuana use and PPR use among current cigarette smokers. This study examines 1) the likelihood of PPR use by marijuana use and 2) the frequency of marijuana use and current PPR use.

Findings may help elucidate whether marijuana use is associated with PPR use, and if so,pot for cannabis whether marijuana is used as a substitute or complement to PPR use. This is a cross sectional analysis of data from the TABS II, a web-based longitudinal survey of U.S. adult former and current cigarette smokers, aged 24 years old and older. The survey included topics such as individuals’ use of tobacco, tobacco-related products, marijuana, and other substances including PPRs. The present analysis used demographic data from Wave 1 from August 2015 . Wave 3 data were collected in August 2016 and included survey items on marijuana use and new items on PPR use . Surveys were administered by Qualtrics, which uses a combination of online panels to establish national samples from which survey participants can be randomly selected. Qualtrics invited potential participants to take the survey via an email notification and offered them a $10 incentive to complete each survey wave. For Wave 1, 2,378 individuals clicked on the survey link, and 819 went on to complete the survey, yielding a completion rate of 34.4% . Current smokers were included in the current analysis. The TABS II project was approved by the UCSF Institutional Review Board. Cigarette use.—Participants were categorized as a current cigarette smoker if they responded “yes” to the question, “Are you a current cigarette smoker?” and if they responded with any number of days greater than 0 for the question “During the last 7 days, on about how many days did you smoke cigarettes, even 1 or 2 puffs” or to the question “During the last 7 days, on about how many days did you smoke menthol cigarettes, even 1 or two puffs.” The question “On average, how many cigarettes a day do you smoke?” was used to control for cigarette consumption in the analysis of the relationship between cannabis use and PPR use. Marijuana use.—Definitions of each user type were: “never users,” never used marijuana in their lifetime; “ever” users, used marijuana at least once in their lifetime, but not in the past 30 days; and “current” users, used marijuana in the past 30 days. If participants answered the question “During the last 30 days, on about how many days did you use marijuana, even 1 or 2 puffs?” with any number above 0, they were classified as a current user. If participants responded with “I have never tried marijuana” to the question asking “Which of the following forms of marijuana have you EVER used?” then they were classified as a never user.

If they responded to this question with any other option besides “Don’t know/refused” and if they were not categorized as a current user, they were classified as an ever user. For the analysis involving frequency of marijuana use as a continuous variable, responses to the question “During the last 30 days, on about how many days did you use marijuana, even 1 or 2 puffs?” were used. Medical marijuana lawstatus in state of residence.—Participants were categorized as: 1) no legal medical marijuana in state of residence, 2) legal medical marijuana for less than 10 years in state of residence, or 3) legal medical marijuana for 10 or more years in state of residence. PPR use.—PPR users were categorized as “never” users if they reported they had never used PPRs in their lifetime, as “ever” users if they had used PPRs but not in the past 30 days, and “current” users if they had used PPRs in the past 30 days. If participants selected “Prescription pain relievers” for the following two questions, they were classified as current PPR users: 1) “Have you EVER used any of the following substances? Mark all that apply” and 2) “Have you used any of the following substances in the PAST 30 DAYS? Mark all that apply.” If participants selected “Prescription pain relievers” in the first question , but did not select them in the second question , then they were classified as ever users. If they did not select “Prescription pain relievers” in the question inquiring about ever use, they were classified as never users. Statistical Analysis—Descriptive analyses were used to test for normality. Chi-square tests were used for categorical variables , and an ANOVA was used for the continuous variables to compare sample characteristics between marijuana never users, ever users, and current users. For PPR status, a Bonferroni adjustment was made to account for multiple comparisons. A logistic regression was used to examine whether the frequency of marijuana use influenced PPR use among current marijuana users. SAS University Edition, which contains SAS Studio 3.6 and SAS 9.4, was used for all analyses.Participants ranged in age from 24 to 88 years old . The majority were female and Caucasian . On average,pot for growing marijuana participants smoked over 15 cigarettes per day . Table 1 presents demographic information and PPR status stratified by marijuana use. Chi-square tests and an ANOVA revealed no significant differences in sample characteristics across marijuana never, ever, and current users.

A significant difference was found between marijuana never, ever,and current users for PPR status . We tested three comparisons using SAS proc multest, which provides Bonferroni adjusted p values. A significant difference remained for the following PPR use groups: never vs. ever and never vs. current .As shown in Table 2, logistic regression was used to further examine the relationship between marijuana and PPR use, with PPR current use set as the reference category for the criterion variable and marijuana never use set as the reference category for the predictor variable. The model was adjusted for all sample characteristics, and compared to marijuana never users, both marijuana ever users and current users were more likely to have used PPRs in the past 30 days, with ever users having an AOR=2.58 and current users having an AOR=3.38 . A logistic regression was used to investigate the relationship between the frequency of marijuana use among current marijuana users and PPR use, and no significant results were found . Results suggest that adult current cigarette smokers have differential use of PPRs depending on their use of marijuana. Those who were current and ever marijuana users were over 2–3 times more likely to have used PPRs in the past 30 days, respectively, when compared to cigarette smokers who never used marijuana. Results support the findings of previous studies that addressed a possible complementary effect of marijuana use with PPR use. Novak, Peiper, and Zarkin analyzed NSDUH data in 2003 and 2013 and found that greater marijuana use was associated with more frequent PPR use. An analysis of NESARC data found higher levels of marijuana and cigarette use predicted initiation, re-initiation, and sustained opioid use ; and another study using NESARC data determined that marijuana use was associated with an elevated risk of using nonmedical prescription opioids three years later . Two Swedish teams found similar results. One study found a positive association between use of marijuana and unauthorized use of PPRs . In a re-analysis of a Swedish national household survey, non-medical PPR use was associated with both frequent cigarette smoking and marijuana use . Studies with adolescent and young adult samples found non-medical use of PPRs is associated with marijuana use . Though longitudinal studies are needed to make definitive conclusions about the nature of the relationship between marijuana and PPR use among cigarette smokers, the interface among biological effects of PPRs, marijuana, and nicotine could influence the strength and direction of this relationship. For one, PPRs and marijuana share anti-nociceptive effects, the two substances act on some of the same brain regions, and THC partly exerts its analgesic influence by relying on opioid receptors . Nicotine additionally interacts with the opioid system, and the systems have almost identical influences in key pleasure-sensing areas of the brain . Therefore, the behavioral responses to nicotine use and withdrawal are likely affected by the opioid system .

As with marijuana and opioids, nicotine has antinociceptive actions . Consequently, the interconnected neural activity and biological effects of nicotine, marijuana, and opioids could play a role in the relationship between PPR and marijuana use among cigarette smokers. Another explanation for the higher likelihood of current PPR use among ever and current marijuana users in cigarette smokers could be that some participants had used marijuana and/or PPRs to reduce pain symptoms. Epidemiologic and prospective cohort studies point to a relationship between smoking and chronic pain, with smokers having a greater likelihood of developing chronic pain disorders than non-smokers . And the most frequently reported reason for adult misuse of PPRs in 2015 was to alleviate physical pain . Our results do not support prior findings of a negative association between marijuana and PPR use. Boehnke, Litinas, and Clauw report that among individuals with chronic pain, use of medical marijuana was negatively associated with opioid use. Further, legalization of medical marijuana has been correlated with a drop in the number of hospitalizations attributed to opioid dependence/abuse and PPR ODs, and a decline in opioid OD mortality rates . States with medical marijuana dispensaries also report fewer PPR ODs, a reduction in PPR treatment admissions, and a decline in opioid-related deaths . However, none of these studies stratified their results by cigarette smoking status. As such, it is possible that the inclusion of only current cigarette smokers in the present study could help explain the discrepancy between the present findings and other results. Of note, studies investigating the effect of marijuana use on opioid/PPR use vary in their sample composition , use of covariates , and outcome measures . This variation in study design is likely responsible for some of the discrepant findings in the extant literature. As previous studies have not stratified their analyses by cigarette smoking status, our study provides an important and unique contribution to current evidence, and this dynamic helps to explain why our findings differ from those that found a negative relationship between marijuana and PPR use. We did not find a significant association between PPR use and frequency of marijuana use among current marijuana users. Our findings align with those of Lucas et al. , who determined that among Canadian medical marijuana users, there was no association between frequency of marijuana use and illicit drug substitution, though this finding is attenuated because their analysis was not stratified by cigarette use status. On the other hand, our findings contrast with those of Arterberry et al. , who reported that frequency of marijuana and cigarette use was predictive of opioid use among an adult sample in the NESARC. This dissimilarity may be due to differences in study design.

Several sources could be promoting misperceptions that marijuana use is safe and beneficial for pregnant and breastfeeding women. One potential source is social media, through which misinformation about maternal marijuana use receives increasing spread, attention, and engagement. Analyses of Twitter communications suggest an increasing engagement with misinformation about benefits of marijuana use during pregnancy and breastfeeding . The proliferation of online support groups advocating benefits of use while pregnant and breastfeeding suggests growing popularity in beliefs that marijuana is a safe and affordable treatment for discomfort, depression, and morning sickness ; that it is safe because it is plant-based and natural; and that it facilitates breastfeeding. Qualitative interviews with pregnant women have documented these beliefs but systematic, quantitative examinations of endorsements of these beliefs in communities remain lacking. Another potential source of misperceptions is the legalization of marijuana for recreational and medicinal use in a growing number of states and regions. This trend could foster expectations that marijuana must be a safe substance if it is legal to use and it must be healthy if it is prescribed for medicinal purposes such as pain and depression. Among pregnant women, risk perceptions about the use of marijuana during pregnancy have decreased in recent years and these decreases might partly explain the increases in marijuana use by pregnant and breastfeeding women . If maternal marijuana use is expected to rise in line with the increases in beliefs about its safety and benefits,mobile grow system then it is essential to determine which beliefs about specific risks and benefits are commonly held and which cultural and social groups are prone to misconceptions.

This information can be used to identify specific beliefs to address and target audiences for health communications aimed at promoting informed decisions about using marijuana by pregnant and breastfeeding women.Whereas it is important to understand beliefs about maternal marijuana use held by adults across societies, understanding beliefs held by vulnerable populations hold particular importance given the likely health disparities if risk-elevating beliefs common within these communities are not addressed through health communications and interventions. The San Joaquin Valley is home to vulnerable, underserved communities that struggle with significant health disparities and lack of access to health care resources . Latinos make up the majority of residents and, more generally, represent one of the fastest growing ethnic groups in the United States . Latinos face numerous adversities that heighten their risk of substance use and have seen the most growth in marijuana use across ethnicities in the U.S. , further indicating the need to understand and target misconceptions within these communities.There is a paucity of evidence, and particularly quantitative data, on the beliefs about marijuana use while pregnant and breastfeeding held by community members, and particularly those residing in vulnerable and underserved communities. The aims of the present study were to address these research gaps by surveying community residents, with an emphasis on recruiting Latino, rural, and disadvantaged residents into the sample, to gather information about their beliefs regarding marijuana use by pregnant and breastfeeding women. The survey was designed to inform two primary research questions: What beliefs about the risks and benefits of marijuana use when pregnant or breastfeeding are commonly held by adults representing these rural and vulnerable populations? And How do these beliefs vary as a function of gender, ethnicity, marijuana use, and parental status? While the study aims are primarily exploratory, we made general predictions based on prior findings of social group differences in marijuana risk perceptions, substance use beliefs, or health risk perceptions more generally.

We predicted that risk beliefs would be lower and benefits beliefs would be higher for participants who had ever used marijuana and who had used marijuana in the past six months relative to those who had not ; participants who were not of Latino ethnicity relative to Latino participants ; male relative to female participants ; and participants who were not parents relative to parents .A network of 8 promotores de salud and 20 research assistants were trained to recruit and administer the survey to residents from counties within the San Joaquin Valley, California. The promotores network enhanced opportunities to recruit “hard to reach” community members, including those who reside in isolated geographic regions. Spanish-speaking promotores and research assistants provided Spanish versions of the survey to those who preferred it. The Spanish surveys were translated and back-translated by trained translators and then validated through focus groups with Spanish-speaking promotores. Promotores and research assistants recruited residents attending local events , community organizations , organizations serving parents , and home visits by promotores to community clients. Data collection took place between April 2019 and November 2019. Promotores and research assistants distributed informational fyers inviting adults aged 18 and older to participate in a 15–20-min survey about their views on marijuana use during pregnancy and breastfeeding. Participants who could not read or write in English or Spanish were offered the opportunity to have it read to them; three participants completed the survey in this manner. Upon completion, participants received debriefng information and a $20 gift card in a Table 2 presents rates of agreement with statements about benefits and risks of marijuana use while pregnant or breastfeeding for the total sample. A slight majority were either neutral about or agreed with the statement that using marijuana while pregnant helps to reduce pain and discomfort whereas 49% disagreed with this statement. In contrast, a strong majority of participants disagreed that marijuana use during pregnancy helps to reduce depression, has no lasting harms for the baby, is safe because it is plant-based and natural, and helps to reduce morning sickness and nausea.

Over 60% of participants agreed that use during pregnancy poses risks to the baby including attention and learning difficulties, lowered IQ, THC addiction, behavioral problems, brain damage, preterm birth, low birth weight,mobile vertical rack and pregnancy complications. Proportions who were neutral or disagreed with these statements ranged from 29.0% for risk of behavioral problems to 39.0% for risks of preterm birth and low birth weight. Comparable patterns of agreement emerged for beliefs about use while breastfeeding. A slight majority were neutral about or agreed that it helps to reduce pain and discomfort whereas a majority disagreed with the other five statements about benefits. Proportions of participants who were neutral or agreed with these five statements ranged from 24.7% for use helps calm the baby to 44.2% for use helps reduce depression. Over 60% agreed that use while breastfeeding poses risks to the baby including attention and learning difficulties, lowered IQ, THC addiction, behavioral problems, and brain damage. Proportions of participants who were neutral or disagreed with these statements ranged from 29.0% for risk of attention and learning difficulties to 31.9% for risk of brain damage. In response to items assessing beliefs about the presence and effects of THC in breast milk, 65.6% of participants believed that THC passes to the baby and has negative effects on the baby whereas 21.0% believed it passes to the baby and has positive effects on the baby and 13.4% believed that none to some THC passes to the baby and has no effect on the baby. Only 20% of participants gave the most scientifically accurate response that THC lasts in breast milk for 6 days to 2 weeks; 42% believed it lasts 0 h to 2 days and 37.3% believed it stayed in breast milk permanently.We used χ2 tests to determine differences in agreement with potential risks and benefits of marijuana use during pregnancy and breastfeeding as a function of marijuana use, Latino ethnicity, gender, and parental status. Table 3 presents the proportions of agreement with benefits and risk statements by participants who had ever versus never used marijuana. As predicted, those who had ever used marijuana were significantly more likely to be neutral about or agree with all statements about potential benefits of marijuana use while pregnant or breastfeeding, and to be neutral about or disagree with all statements about potential health risks of marijuana use while pregnant or breastfeeding. Analyses of differences between participants who had used marijuana in the past 6 months and those who had not revealed similar patterns of group differences.

Those who had used marijuana in the past 6 months reported higher agreement with all benefits statements and lower agreement with all risk statements for marijuana use in pregnancy and while breastfeeding . Latino and non-Latino participants were generally comparable in their agreement about benefits and risks of marijuana use while pregnant and breastfeeding, with the following exceptions in which, as predicted, Latino participants reported relatively more health-cautious beliefs . Fewer Latino than non-Latino respondents endorsed the beliefs that marijuana use during pregnancy reduces pain and discomfort and that it reduces morning sickness and nausea, and more Latino than non-Latino respondents agreed that use could lower a child’s IQ. For statements about marijuana use while breastfeeding, fewer Latino than non-Latino respondents were neutral about or agreed that it helps calm the baby and more Latino than non-Latino respondents believed that use increases the risk of attention and learning difficulties.In terms of gender differences, predictions that benefits beliefs would be higher and risk beliefs would be lower for male than female respondents were supported for 10 of the 24 beliefs . More males than females agreed that marijuana use during pregnancy reduces pain and discomfort whereas more females than males agreed that marijuana use during pregnancy increases the risks of preterm birth and low birth weight. With respect to marijuana use during breastfeeding, more males than females agreed that it helps to reduce pain and depression, poses no lasting harms to the baby, is safe because marijuana is plant-based and natural, and increases a mother’s milk supply. In contrast, more females than males indicated agreement that use during breastfeeding can lead to infant THC addiction and increase the risk of behavior problems.The present study revealed distinctive patterns of beliefs about marijuana use while pregnant and breastfeeding in a sample of residents in primarily rural, Latino-majority, and disadvantaged communities in California, a state that has legalized the use of marijuana for recreational and medicinal purposes. Taken together, the levels of endorsement of beliefs about benefits of use and lack of endorsement of beliefs about risks to infant health and well-being highlight the need for public health education about risks of maternal marijuana use in these communities and identify specific beliefs and community groups to prioritize in these educational efforts. Overall, the most common beliefs regarding marijuana use both during pregnancy and while breastfeeding are that it helps to reduce pain and depression. These beliefs are not supported by empirical research. In contrast with modest support that cannabis can reduce pain for people with chronic pain conditions , evidence that it reduces pain sensitivity is inconsistent , and research on the effects of marijuana on pain during pregnancy and while breastfeeding remains lacking. For depression, the evidence base suggests that cannabis can worsen rather than improve depression and, to our knowledge, no studies have tested its impact on depressive symptoms for pregnant and breastfeeding women. Almost 30% of participants reported neutral or positive beliefs that marijuana reduces nausea during pregnancy, another belief that is not empirically supported. Although some evidence suggests that cannabis can aid in pain relief and nausea in cancer patients , it is also positively linked with episodes of nausea and vomiting in cancer patients and the general public . Despite perceptions that cannabis reduces nausea during pregnancy and prevalent advice from cannabis dispensaries to use cannabis to alleviate pregnancy-related nausea , evidence remains lacking. In addition to the substantial endorsement of beliefs that use provides symptom relief for maternal users, up to 25% of participants were neutral about or agreed that it is safe because it is plant-based and natural and that it poses no lasting harms to the infant. Beliefs that use while breastfeeding helps calm the baby received the least endorsement, suggesting that it might be given lower priority in health communications and guidelines. Overall, these survey results are consistent with qualitative findings of benefit beliefs held by pregnant women and demonstrate that they are shared by community members more generally.

SWM task reaction time and accuracy data were collected during scanning and composite scores were calculated to provide a single, comprehensive measure of performance and use fewer degrees of freedom in analyses, providing more statistical power . Reaction-time data and accuracy measures were converted into z-scores, and reaction-time z-scores were subtracted from accuracy z-scores to compute the performance composite score. Using this approach, high accuracy would result in a high positive z-score, while low reaction time, which is better, would result in a high negative zscore. Therefore subtraction of the negative reaction time z-score from the positive accuracy zscore would yield a positive index indicating high overall performance Imaging Data. Imaging data from each teen were processed as in our prior studies using Analysis of Functional NeuroImages . Time series data were corrected for motion. Number of removed repetitions and average movement in each direction throughout the task were examined in relation to group, task, and interactions using correlational analyses. The average percent of repetitions removed for excessive motion during the task was 8%, resulting in 92% retained for analyses. There were no significant differences between groups in bulk motion in any of the six movement directions . The average rotational movement throughout the task for MJ users was 0.04, 0.14, and 0.05 degrees for roll, pitch, and yaw, respectively. In controls the average rotational movement throughout the task was 0.07, 0.13, and 0.06 degrees for roll, pitch, and yaw, respectively. Among MJ users, the average translational movement was 0.11, 0.05, and 0.08 mm for superior, left, and posterior, respectively; the average translational movement of controls was 0.14, 0.06, and 0.07 mm for superior, left, and posterior, respectively. There was a significant group difference in the roll direction = 2.35, p = 0.03, although such movements were quite small. Next,grow cannabis fMRI data were deconvolved with a reference function that coded the hypothesized BOLD signal for each task condition .

Controlling for linear trends, spin history effects, and delays in hemodynamic response, we computed for each brain voxel a fit coefficient that represented the relationship between the observed and hypothesized signal change for contrasts between SWM and vigilance conditions . These functional datasets were warped into standard space , resampled into 3 mm3 voxels and smoothed with a 5 mm Gaussian filter. Statistical Analyses. Regression analyses determined the variability in brain response accounted for by group, task performance, and their interaction. These group level analyses were performed in each voxel of the brain and examined the BOLD response contrast between SWM and vigilance. To control for Type I error, we only interpreted significant effects in clusters of 50 contiguous significant voxels , yielding an overall clusterwise α = .05, determined by Monte Carlo simulations . Exploratory follow-up regression analyses were performed to determine the nature of the group by performance interaction. A main effect of group revealed that marijuana users showed significantly greater activation than controls in a cluster encompassing the right basal ganglia, as well as in a second cluster encompassing the right precuneus, postcentral gyrus, and superior parietal lobule 7) and in the left precuneus and superior parietal lobule . There was no region in which marijuana users demonstrated reduced activation compared to controls . Across all subjects, both users and controls, behavioral performance data positively predicted activation in seven clusters : right middle temporal gyrus, parahippocampal gyrus, and inferior temporal gyrus; right cerebellar tonsil; right inferior parietal lobule, supramarginal gyrus, angular gyrus, and middle temporal gyrus; left middle temporal gyrus and superior temporal gyrus; left middle occipital gyrus, middle temporal gyrus, and inferior temporal gyrus; right middle frontal gyrus; and left middle frontal gyrus and inferior frontal gyrus. There were no regions in which performance was negatively associated with brain response .

A group by performance interaction was found in five clusters : left superior temporal lobule, left superior temporal gyrus and left middle temporal gyrus; right temporal gyrus and right uncus; left anterior cingulate; left uncus and left parahippocampal gyrus; and right thalamus and right pulvinar. However, findings were re-examined using movement as a covariate, and all findings remained unchanged . Performance and BOLD response data were checked for outliers, and none were found. Cases appearing as possible outliers on scatter plots were removed and analyses were redone; results remained unchanged. Both groups were checked for outliers on mood measures; although neither group contained an outlier on the BDI, the marijuana group contained one outlier on the Hamilton Anxiety Rating Scale. Analyses were re-run excluding this subject and results remained unchanged.This study examined the association between behavioral performance and brain response during a SWM task among 16- to 18-year-old marijuana users and controls after 28 days of abstinence. Results suggest that, in general, marijuana-using teens performed similarly on SWM than controls, perhaps due to the low difficulty level of the task , which approached ceiling effects. This has been observed in fMRI studies of SWM in adult marijuana users . However, specific localization and intensity of response varied between the MJ users and controls, with MJ users showing more performance-related activation in certain regions and less in others. These differential patterns emerged despite similar overall task performance across groups, suggesting an alternate relationship between task performance and brain activity among marijuana users. MJ users showed significantly more activation than controls in the right basal ganglia, an area associated with skill learning . Since the subjects were only allowed to practice the task once before entering the scanner, it is possible that the MJ users were still in the skill learning process during imaging.

The other two clusters, which were significantly more activated in marijuana users than controls, were the right and left parietal lobes. Bilateral parietal regions have been implicated in attention, spatial perception, imagery, working memory, special encoding, episodic retrieval, skill learning monitoring, organization, and planning during working memory . It is possible that there is compensatory neural effort in these areas, as observed in SWM studies of adult marijuana users . The performance data positively related to activation in several areas, and did not negatively associate with brain response in any region. Performance was positively associated with activation in the left and right temporal regions, which are associated with verbal mechanisms and episodic, nonverbal working memory and retrieval, respectively . This suggests that good task performance may be related to using multiple memory modalities. High-scorers showed more activation in the bilateral prefrontal and bilateral parietal regions that have been shown to activate during SWM tasks in youths . The performance by group interactions were the focus of this study and yielded the most interesting results. In particular,indoor cannabis grow system an interaction in the left superior temporal gyrus suggested a positive association in the users and a negative association in the controls. This may imply that the MJ users used more of a verbal strategy to achieve high task performance scores than the controls. This is interesting when considering the previous findings of deficits in verbal learning and IQ in marijuana using adolescents compared to controls . Furthermore, the right superior temporal gyrus showed an interaction where users had a negative association and controls had a positive association. Previous studies have shown this area to be involved in poorer recognition of previously seen words . This would support the notion that users are relying on a verbal strategy so that better performance linked to a decrease in activation in the right superior temporal gyrus. Moreover, an interaction in the right thalamus and pulvinar showed a negative association in the users and a positive association in the controls. These sub-cortical structures have shown an association with spatial neglect when damaged . It is interesting that these areas have a negative association in users and a positive association in controls, and may suggest that marijuana users utilize less spatial strategies than controls. The nature of the interaction revealed a positive association in marijuana users and a negative association in controls in the left anterior cingulate. This region has been linked to attention, decision-making, cue response, and response monitoring . It may be that good performing marijuana users are making a more conscious decision to react to task cues than controls, who may be reacting more automatically. The left parahippocampal gyrus demonstrated an interaction of negative association in marijuana users and positive association for controls. This region is involved in working memory and is recruited when the temporal lobe is not in use . Since marijuana users are using more energy in the left temporal lobe as their performance increases, higher scoring subjects may rely less on the parahippocampal gyrus. The distinct interactions viewed in these different areas of the brain can mean that different systems are at work, and as one part of a system decreases in action, the other area of the system increases in activation.

Previous studies suggest that subjects who do not use traditional strategies for specific tasks showed an increased extent of activation and recruitment of additional areas, specifically verbal areas, to accomplish the task . More specifically, the pattern of results suggests that marijuana users may apply a verbal strategy to the task when achieving higher scores. It is possible that this alternative way of using the brain may be less efficient; this would explain the greater overall activation in users versus controls and recruitment of other brain regions as a compensation method. A recent review also found that multiple neuroimaging studies of marijuana users pointed toward recruitment of compensatory regions as well as task-related regions to achieve task demands . A possible limitation to this study is the interpretation of a difference in fMRI activation between experimental groups. It is possible that alternative neural pathway use is more dynamic and versatile. It is unclear whether the results are an adverse effect of the marijuana use or merely a benign difference. Further studies that more carefully describe the relationships between task performance and brain response will clarify this question. Another limitation of the current study is that most marijuana users were also moderately heavy alcohol drinkers. While these participants are representative of the population of adolescent marijuana users, most of whom also consume alcohol , it is nonetheless difficult to disentangle the effects that may be related to alcohol use. Alcohol use correlated with brain response in the right thalamus and pulvinar in the current study, but results remained significant even when accounting for alcohol use, and alcohol use did not correlate to activation in any other significant regions. Our previous research identified brain response abnormalities among marijuana users above and beyond those demonstrated by users of alcohol alone , supporting the hypothesis of marijuana-specific differences in brain response, even among teens who are heavy drinkers. Future studies should attempt to clarify the differential and interactive impact of concomitant alcohol and marijuana use on brain functioning on adolescents. Furthermore, lifetime marijuana use episodes were associated with activation in the right uncus and superior temporal gyrus. Future analyses could further investigate the associations of other brain regions, as well as neuropsychological performance, with lifetime use episodes. These subtle differenced among users may provide additional insight into the mechanisms involved with prolonged abstinence from marijuana. Future studies should also focus on investigating the nature of interactions in other domains of cognition to test if other types of tasks show these patterns. If a user’s neural differences are actually a compensatory tool, then a more difficult task may overcome their compensation abilities, therefore resulting in performance deficits. In addition, a parametric manipulation of working memory load could help specify degree of compensatory activation in marijuana users compared to controls, as marijuana users may reach a limit earlier than controls. Further studies could also explore which mechanisms and strategies subjects utilize during the tasks through qualitative data investigation. Recreational marijuana commercialization is gaining momentum in the US. Among the 11 states and Washington DC that have legalized recreational marijuana since 2012, retail markets have been opened or anticipated in 10 states, where over a quarter of the US population live. The presence of recreational marijuana dispensaries increased rapidly following the commercialization. Children are at a high risk of initiating marijuana use and developing adverse consequences related to marijuana.