Hemp Growing

All scenes include background music and audio effects consistent with the scene and the participants’interaction. The NTP Cue VR paradigm begins with 3 “test scenes,” which are approximately 3 minutes in duration, depending on participant comfort and abilities with the VR hardware. The first scene is the Practice Room. This is a square room with cubes systematically placed around corners of the room. The participants are asked to gaze at each of the boxes to confirm that the eye-tracking is functioning as intended. Then, the participants are asked to practice using the controllers to teleport to 4 different locations in the room. The second scene is the Practice Slider room, which instructs the participants how to answer the survey questions and provides the opportunity to practice adjusting the slider to answer the scales. The third test scene is the Blink Calibration room. In this scene, the participants are asked to blink 5 times after being prompted by an audio signal. The purpose of this room is to collect pupil diameter data when the participants actively blink to assist with increasing the accuracy of blink detection algorithms. Following the completion of the initial test scenes, the 2 mood surveys are presented, and the 6 scenes are pseudorandomized within scene type such that the general scene order is maintained . The participants are then placed in each scene for 5 minutes. The entire paradigm is approximately 30 minutes in duration.There are 2 types of data recorded within each scene, regular time series and event-based data that is recorded at event onset. Regular time series data are collected at every 10-millisecond interval , independent of the frame time. The following data are recorded periodically: timestamp, raw gaze intersection point,vertical agriculture position and forward direction of the participants’ headset, and pupil diameter and eye openness .

The following events and corresponding timestamps are recorded when they occur: blinks, including number of blinks and the object of gaze at the time of the blink; button presses on the controller, including time, button pressed, and object of interaction ; and object of gaze when eye gaze switches to a new object.However, this raycasting method did not perform well in our experiments, especially for very small objects, owing to the limited precision and accuracy of the eye tracker, microsaccades, etc. Therefore, for small objects of interest, we utilized the G2OM algorithm provided by the Tobii XR SDK, which is a machine learning–based object selection algorithm that aims to improve small object– and fast-moving object–tracking. Based on our testing, this algorithm improved object selection over the naïve method but still lacked selection quality. Thus, to further improve object selection, we introduced an additional mechanism to “lock” the object selection when an object is manipulated such that whenever a participant actively picks up a virtual object, the object selection algorithm will always select the picked object until the participant releases the object. If the participant is not interacting with an object, the G2OM algorithm is employed, or if no small objects are within the field, naïve raycasting is employed. To calculate eye-gaze statistics toward active and neutral cue objects, 4 dictionaries corresponding to 4 different types of objects are initialized prior to the start of participant involvement in the paradigm. These dictionaries are then used to store the cumulating gaze fixation or dwell time durations as values for individual objects belonging to each object and type. When a participant gazes at an object, the object is searched in the dictionary on the basis of its name and type. If the object was encountered before, the current fixation time is added to its cumulative fixation time. If the object had not been encountered before, a new entry is created for the object.

The fixation time is then calculated as the difference between the timestamp of current entry and that of the next line of entry. Following the completion of the paradigm, total fixation time indices are produced, which reflect the sum of values within each dictionary . The mean fixation time indices are also created, which reflect the total fixation time divided by the number of objects gazed at by the participant. Initially, we tested a measurement of eye openness, as calculated by the HTC SRanipal SDK, as an indicator for blink detection. However, given the lack of established thresholds of eye openness for blink detection, we instead chose to rely on estimates of pupil diameter. Consistent with previous studies, an eyeblink is herein defined as complete eyelid closure with the pupil covered for 50-500 milliseconds. For any given time point, we consider a missing pupil diameter reading as a possible complete eyelid closure where the pupil is completely covered by the eyelid. These eye closure durations are blink candidates. If either pupil is covered for less than 50 milliseconds, the candidate is discarded as it is more likely owing to noise or an eye tracker limitation. If either pupil is covered for more than 500 milliseconds, the candidate is also discarded as this is more consistent with a micro-sleep. Using this blink detection definition, the blink count for the majority of the current participants fell within 12-40 blinks per minute, which appears to align with the consensus of spontaneous blink rates in the literature.Following consent procedures, participants undergo an extensive clinical interview and complete several self-report questionnaires covering demographic, psychological health , and substance use domains. The TLFB has high test-retest reliability for intervals ranging from 30 to 360 days prior to the interview date, with an intraclass correlation coefficient=0.92 for “Total number of cigarettes smoked per interval”. Thus, past 90-day NTP use episode count from the TLFB was used in the quantitative analyses presented below.

All study interview and self-report data were collected and managed using REDCap electronic data capture tools hosted at the University of California, San Diego. Participants then undergo the NTP Cue VR paradigm,hydroponic stands which includes repeated assessments of subjective nicotine craving and scene relevance to the individual participant . Upon completion of the paradigm, additional assessments on VR-related outcomes such as VR presence and VR-related simulator or motion sickness are administered. The IPQ total score was calculated using a simple averaging method to obtain a single average perceived presence score ranging 0-100. Similarly, the SSQ was scored in concordance with procedures outlined to assess VR-specific sickness , which involves a simple averaging method to obtain a single average sickness score with a range of 0-100. These analyses include the first 31 participants to complete the study protocol; however, data were missing for some subjects on a subset of indices owing to technological difficulties . Owing to safety restrictions related to COVID-19, no biological verification of abstinence was conducted. Group differences are not being investigated in the present pilot analyses since the goal of this study is to describe the development and general validity of the paradigm and to maximize statistical power. Statistical analyses were conducted using a repeated measures t test or Pearson correlation framework. The threshold of significance was set at P<.05 for all analyses. SPSS Statistics for Windows software was used for all analyses. This report describes our approach to the development of a novel NTP cue VR paradigm designed to simultaneously induce and assess potential eye-based objective correlates of nicotine craving in naturalistic and translatable virtual settings. The preliminary statistical analyses support the potential of this paradigm in its ability to induce subjective craving while instilling a moderate sense of presence in the virtual world and only low levels of VR-related sickness. The preliminary results outline a potential context-specific effect of NTP-related attentional bias and pupil dilation in this pilot sample. Consistent with the literature on attentional bias and pupil dilation, we observed greater Active NTP versus Neutral control cue-related effects in 2 of the 3 Active scenes . The similarity observed in the pattern of effects between attentional bias and pupil dilation provides early evidence of a potential cross-validation of these metrics. No effects were observed for the EBR metric; however, the size of this effect, if present at all, may be smaller than we are currently able to detect with the limited sample. The observed reversal of attentional bias and pupil dilation toward neutral cues in the Driving scene warrants further investigation, given the large effect size. Potential explanations for this include the presence of especially engaging neutral cues in the Driving scene, as a 360° video of a busy city street is presented in the background, which participants report as entertaining to watch. Despite the overall bias toward neutral cues reflected in the global attentional bias metric, and within the Driving scene alone, participants with greater attentional bias toward NTP cues were found to endorse greater NTP use in the previous 90 days.

This effect appears to be driven by the higher-frequency NTP users in our sample and is consistent with the literature supporting the validity of attentional bias as a clinically important indicator of nicotine addiction. Additional analyses are planned to assess direct and indirect relationships between scene eye-related outcomes and relevance to the individual, scene-specific craving level, randomization of scenes, engagement with specific cues, and NTP use groups once more data are collected. This pilot study has several strengths and limitations. Strengths include the development of a cutting-edge VR cue-reactivity task that incorporates the latest technological advances in graphic design to increase translatability to the real-world and simultaneous assessment of multiple potential eye-related indices of cue-reactivity in a 3D virtual environment. Limitations include the absence of biological verification to confirm self-reported NTP use and the inability to investigate NTP use profiles in the analyses owing to limited power. Importantly, given the limited sample size, we caution against over interpretation of our results. It remains unknown whether the absence of significant results, particularly with respect to the correlations between objective eye-related indices and subjective craving ratings, are the result of limited power to detect these relationships or true independence of these indices. However, we believe that the general pattern of scene-related effects on attentional bias and pupil dilation are encouraging and warrant further study. The identification of reliable objective correlates of craving would allow for greater examination of the underlying neurobiological processes involved, and inform new avenues for the development of psychological and pharmacological treatments.PATTERNS OF ALCOHOL intake vary dramatically over the lifespan, with the heaviest drinking and steepest trajectory of increasing alcohol problems typically observed in the mid-teens to mid-20s . In the United States, a person’s first drink is likely to occur at about age 15, and by age 18, 70% of people have consumed alcohol, 35% were ever intoxicated, and 24% admitted to consuming 5 or more drinks on an occasion . It has been estimated that the first drink in the United Kingdom may occur closer to age 14, with 70% of students in that age range having consumed alcohol . Thus, heavy drinking during adolescence may be especially prominent in the United Kingdom, which ranks near the top among 35 European countries regarding several measures of drunkenness . One common alcohol-related adverse consequence is an alcohol-related blackout , defined as not being able to remember parts or entire periods of events that occurred while drinking and awake . Almost 50% of drinkers, including college students, have ever experienced an ARB , as have 80% of individuals with alcohol use disorders . The high rate of blackouts in people with AUDs prompted the inclusion of these phenomena in alcohol questionnaires and interviews , but their prevalence in non-AUD drinkers resulted in their omission from most AUD diagnostic criteria . Blood alcohol concentrations >0.300 g/dl are associated with a 60% rate of ARBs, especially for en bloc events, although fragmentary blackouts are observed with BACs as low as ≥0.06 g/dl . Higher drinking frequencies also relate to blackouts, perhaps reflecting their association with higher quantities . In addition, the rate of ARBs may be higher in individuals consuming other drugs that affect brain functioning . Thus, alcohol quantities and frequencies and the use of substances other than alcohol are important characteristics to consider as predictors of ARBs.

The data sources for our index of American libertarian conservatism originate from the Rand Corporation’s TL-354 state-level estimates of firearms per household, data from the Tax Foundation giving the highest marginal tax rate for each state, and data from the National Council of State Legislatures on the stringency of state laws regulating the private use of cannabis. The data for our index of American social conservatism includes CDC/Guttmacher Institute data on the number of abortion clinics by state per million residents, Public Religion Research Institute data on pre-Obergefell restrictions on samesex marriage, and the JRANK Legal Encyclopedia’s rating of U.S. state-level support for the legality of prayer in public schools. Table 1 presents summary statistics of our variables, showing differences in characteristics and COVID-safety behaviors, cases, and deaths between counties above and below a 50% county-level Trump vote in the 2020 election. On average counties with a majority Trump vote are 3.5 years older, have $5,473 lower median household income lower income, have a smaller percentage of Black, Latino, and Asian residents, have economies that are more oriented toward manufacturing and less toward services, and have somewhat poorer baseline health, ranking about 2.7 percentile points below the mean of non-Trump counties. Raw differences in mask-wearing show a 17.1 percentage point difference in means for mask-wearing between Trump and non-Trump counties,grow rack 0.50σ lower rate of sheltering at home, 12.9 percentage point lower rate of COVID vaccination, and a 1.12σ lower COVID-safety index, all significant at p < 0.001.

Raw differences in health outcomes show an additional 2,300 COVID cases and 53.4 additional deaths per 100,000 residents across counties, also both significant at p < 0.001. Figure 2 shows spacial correlations across U.S. counties by 2020 presidential voting, COVID-safety behaviors, and COVID deaths per 100,000. Figure 3 provides a series of plots by state that show self-reported mask-wearing by county-level Trump voter support. In nearly each map, the blue dots lie to the northwest of red dots, which show higher levels of county voter support for President Trump and lower rates of mask-wearing. Table 2 provides the results of our state-level fixed-effect estimations in which we regress COVID-safety behaviors on the 2020 Trump vote, controlling for county characteristics. All estimates use U.S. state-level fixed effects so that identification is off differences in the Trump vote and COVID-safety behaviors between counties within a given state. Our results examine three COVID-safety variables: county-level mask-wearing, sheltering at home, and COVID-vaccination rates. We aggregate these three variables into a COVIDsafety index using the method of Kling et al. , which is the standardized sum of each of these three individually standardized variables. The results in Column 1 of Table 2 suggest that a 10 percentage point increase in the county Trump vote is associated with a 3.9 percentage point decrease in the number of people in a county stating that they wear a mask ”all the time” in public . Column 2 shows a tightly estimated coefficient close to zero for sheltering at home. Column 3 indicates that a 10 percentage point increase in the county Trump vote is associated with a 5.1 percentage point decrease in the vaccination rate . A visualization of the significant mask-wearing and vaccination results are shown over the scatter plots provided in Figures 4A and 4B, respectively. Our estimates in Column 4 suggests that a 10 percentage point increase in the county Trump vote is associated with a 0.23σdecline in our COVID-safety index.

Estimates on control variables across columns indicate that COVID-safety behavior generally increases with county median age, median income, percent Latino, percent Asian American, percent employed in manufacturing, education and health, and baseline level of county health. In general the controlled estimates display COVID-safety behavior associations with the Trump vote that are lower than raw differences between Trump and non-Trump counties, but differences by the county Trump vote remain and are highly significant. The exception is the sheltering-at-home variable, which we do not find to be affected by the Trump vote once age, income, and other county level covariates are controlled.Table 3 shows the relationship between the county-level 2020 Trump vote and COVID cases and deaths. Vaccines began to be widely available in the U.S. roughly toward the end of February 2021, and columns 1 and 2 show the impacts on COVID cases, pre- and post-vaccine respectively. Here results indicate that a 10 percentage point increase in the county Trump vote is associated with 789 additional cases per 100,000 residents in roughly the first year of the pandemic in the U.S., and 1,394 additional cases in the pandemic’s first twenty months . Columns 3 and 4 of Table 3 show outcomes for COVID deaths pre- and post-vaccine, where a 10 percentage point increase in the county Trump vote is associated with 11.5 additional COVID deaths per 100,000 residents in the pre-vaccine first year of the pandemic and 27.6 additional COVID deaths per 100,000 country residents in the first twenty months of the pandemic . A visualization of these results is provided in Figures 5A and 5B. A comparison of the pre- and post-vaccine results in Table 3 is important because February 2021 represents both the first month after President Trump’s departure from office as well as the month during which U.S. vaccination rates most quickly accelerated among the general public. The differences between columns 1-2 and 3-4 show that the statistical relationship between Trump support and COVID infections and deaths not only failed to narrow after February 2021, but actually grew, rising from about 65.7 added cases and 0.96 deaths per month during the first twelve months of the pandemic to 76.2 cases and 2.00 deaths per month during the subsequent eight months.

This divergence may have occurred because the easing of public restrictions that accompanied the vaccination-availability phase of the pandemic may have actually elevated risks to the unvaccinated and those not wearing masks in public spaces, a phenomenon likely exacerbated by the deepening political polarization over COVID safety behaviors. How confident can we be that the higher rates of COVID infection in Trump-supporting counties resulted from reduced COVID-safety behavior? The largest and most influential controlled study to date estimating the causal effects of mask-wearing on COVID infection is the extensive randomized trail carried out by Abaluck et al. , who report results from a mask-wearing intervention implemented among 342,183 adults across 600 villages in Bangladesh. The Abaluck et al. study, referenced worldwide by governments as both motivation and guide for COVID-safety behavior, reports that the 27.9 percentage point difference between treatment and control groups, created by those induced to wear masks through the experiment, reduced symptomatic COVID infection in the treatment population by 0.91 percentage points within a two-month time-frame,greenhouse grow tables or that every single percentage point increase in mask-wearing reduced COVID cases by an average of 0.016 percentage points per month. Our results for the United States associate a 10 percentage point increase in the county-level Trump vote with a 5.11 percentage point reduction in mask-wearing and an increase in COVID cases of 1.39 percentage points over a twenty-month time-frame, or that every percentage point increase in mask-wearing reduced COVID cases by an average of 0.014 percentage points per month. Our non-controlled U.S. results are thus remarkably similar to the Abaluck et al. controlled estimates of the causal effect of mask-wearing on symptomatic COVID cases, and they suggest that higher levels of COVID infection in the high Trump-vote counties are unlikely to be due to unobserved county characteristics but rather are substantially mediated by differences in COVID-safety behaviors.In this section we ascertain to what degree the COVID-safety behaviors are specifically tied to a political identity specifically tied to Trump voter support relative to two traditional strains of conservatism in the United States: American social conservatism and American libertarian conservatism, which for many decades have formed key parts of the conservative political coalition embodied within the Republican party. Our Social Conservatism index is made up of three standardized and equally weighted state-level variables representing political issues strongly tied to social-conservative concerns in the United States. They include 1) the availability of abortion, given in terms of clinics per million residents; 2) restrictions on same-sex marriage, existing before federal legalization under the Obergefell v. Hodges, 576 U.S. 644 2015 Supreme Court ruling; and 3) the degree of support for public prayer in schools, as given from ratings by the JRANK Legal Encyclopedia.

Our Libertarian Conservatism index also consists of three standardized and equally weighted variables, representing issues of concern to libertarian conservatives, which embody a preference for minimal taxation, regulation, and interference in personal freedoms and private life by government: 1) low state taxes at the highest income brackets; 2) estimated per-capita firearms ownership; 3) the stringency of state laws regulating the private use of Cannabis. Consistent with the procedure of Kling et al. , after summing each standardized variable within the index, each index itself is then itself subsequently standardized. Table 4 shows our estimates in which we compare associations of our Libertarian Conservatism index, Social Conservatism indices, and Trump voter support with COVID safety behaviors, cases and deaths. To facilitate comparisons with these indices, we also standardize our Trump-vote variable. Overall, results show that once the Trump 2020 vote is taken into account, the Social Conservatism index and Libertarian Conservatism indices have very little systematic explanatory power over COVID-safety behaviors, cases and deaths. In these estimations, a one-standard deviation difference in Trump support decreases mask-wearing by 5.2 percentage points . While the Social Conservatism index is also statistically significant , it explains less than half the variation of Trump support.While neither standardized Trump support nor the Social Conservatism index is statistically significant in explaining sheltering at home, the Libertarian Conservatism index is actually positive and modestly significant . For vaccination rates, a one standard deviation difference in Trump support reduces the percent of adults vaccinated by 7.9 percentage points while the Social Conservatism and Libertarian Conservatism indices have the unexpected positive sign . The aggregated COVID-safety index shows that a one-standard deviation increase in Trump support decreases COVID-safety behavior by 0.45σ . Once Trump support is controlled, Libertarian Conservatism is actually positive with about half the effect but in the direction of increased COVID safety. As is the COVID-safety index, COVID cases and deaths are strongly associated with the 2020 Trump vote but are insignificantly associated with Social Conservatism and Libertarian Conservatism indices. A one-standard deviation increase in Trump voter support increases COVID cases by 2,075 per 100,000 and COVID deaths by 52.4 per 100,000 residents. These results are consistent with the fact that there are relatively weak historical ties between, for example, an anti-vaccination stance and traditional American conservatism. Indeed, some such as Berezow and Campbell trace the anti-vaccination movement to the political left rather than the political right, although there is evidence that in the last decade that anti-vaccination stances have migrated from the libertarian left toward the libertarian right . Rather than being closely tied to conservative ideology per se, numerous both pre- and post-COVID studies find the factor most strongly tied to an anti-vaccine stance to be a belief in conspiracy theories . A number of papers have linked reduced levels of COVID-safety behaviors to the Trump presidency itself . In a quantitative study of behavioral responses to social media activity, Germani and Biller-Andorno find Twitter posts by President Trump to be the strongest driver of information contradicting established scientific evidence regarding the COVID vaccines. Thus rather than originating from a particular strain of traditional American conservatism, this body of evidence taken together with our results in Table 4 strongly suggest an identity more specifically related to Trump political support to principally drive differences in COVID-safety behaviors, along with the accompanying COVID infections and deaths. that bleed across state lines. As a robustness check, we estimate our models in Tables 2, 3, and 4 with Conley standard errors that account for large spatial correlations in COVID cases and deaths. Using longitudinal and latitudinal coordinates, we employ a Bartlett linear decay of the spatial error correlation to a distance of 500 kilometers from the center of each county. In estimations without state-fixed effects, we account for spatially correlated errors 500 km from the center of each state.

Nevertheless, several lines of research suggest that individuals with substance use disorders, including MA users , have higher densities of D3 receptor levels in striatal and extrastriatal brain regions than those who do not frequently abuse drugs . Thus, it seems probable that the lower [18F]fally pride BPND among MA users primarily reflects lower D2 receptor availability in this group compared to controls. An additional limitation includes the possibility of competition with endogenous dopamine influencing [18F]fally pride BPND . That IQ was not assessed is also a limitation, because IQ has been found to be significantly correlated with delay discounting , and a group difference in the former could therefore overshadow the true group difference in the latter. There are also some caveats that should be considered when interpreting the results of this study. First, the MCQ has limited ability to provide precise estimates of discount rates for individuals who discount very steeply. That is, the choice items only probe preference up to a maximum k-equivalence value of 0.25, and this value was assigned as a conservative estimate of discount rate to individuals whose calculated k value was predicted to exceed this value . Second, BPND values were highly correlated across all VOIs examined in both groups of participants, which limits the ability to draw conclusions regarding the relative importance of D2 /D3 receptor availability in specific brain regions to discount rate. Finally, as there is some evidence that abstinence from drugs can increase temporal discounting among addicted individuals , it is possible that abstinence from MA may have amplified the difference in discount rate between MA users and controls. The results of this study may help to explain why low striatal D2 /D3 receptor availability is associated with poor treatment response among individuals with MA dependence and cocaine dependence . This view seems reasonable given that steep temporal discounting has also been linked with poor treatment response among cocainedependent individuals , and predicts relapse among smokers .

The present results lend empirical support to a theoretical model in which Trifilieff and Martinez propose that,cannabis dry rack “low D2 receptor levels and dopamine transmission in the ventral striatum lead to impulsive behavior, including the choice for smaller, immediate rewards over larger, but delayed or more effortful, rewards, which may represent an underlying behavioral pattern in addiction.” Consistent with this model, we found evidence of a negative correlation between discount rate and D2 / D3 receptor availability in the limbic striatal subdivision . The correlation in the limbic striatum did not reach statistical significance, possibly due to the high D3 /D2 receptor ratio in this region and partial volume effects. An important question for future research is to determine whether interventions that increase D2 /D3 receptor availability can reduce temporal discounting, at least among those with low D2 /D3 receptor availability. Pharmacological interventions could prove useful to this end. For example, varenicline increases striatal D2 /D3 receptor availability in rats , and in a study of human smokers, males treated with varenicline showed lower temporal discounting than placebo-treated controls . This finding is compelling considering that dorsal striatal D2 /D3 receptor availability is lower in male smokers compared to nonsmoker controls . There also is evidence that rimonabant increases striatal D2 /D3 receptor availability , and can decrease discounting of delayed rewards in rats . Nonpharmacological approaches may be useful as well, as there is preliminary evidence that intensive exercise can increase striatal D2 /D3 receptor availability in MA-dependent individuals and patients with early-stage Parkinson’s disease . Similarly, in a mouse model of Parkinson’s disease, higher striatal D2 /D3 receptor availability and D2 receptor expression was noted among those exposed to high-intensity exercise relative to non-exercising controls . Establishing a causal link between D2 /D3 receptor availability and temporal discounting is likely to have significant clinical implications.

This is because there is evidence that interventions that reduce temporal discounting are useful for treating disorders that are associated with both steep discounting and low striatal D2 /D3 receptor availability. For instance, contingency management decreases discounting among cocaine-dependent individuals and smokers , and methylphenidate decreases discounting in children with attention-deficit hyperactivity disorder . More importantly, greater reductions in discounting predict a greater likelihood of protracted abstinence among cocaine users and smokers . Thus, if a causative link between D2 /D3 receptor availability and temporal discounting is established, it may lead to the development of novel D2 /D3 -targeted interventions which could be used to more effectively treat a variety of disorders. In conclusion, the results of this study indicate that low D2 / D3 receptor availability is associated with steep temporal discounting. This link may explain why some individuals choose to continue using drugs despite knowledge of their future negative consequences, and could help to guide strategies for treating substance abuse and other psychiatric disorders.To date, this is the largest SC case series describing MABCHMINACA toxicity. In the fall of 2014, MAB-CHMINACA was responsible for more than 125 patients seeking hospital care in Baton Rouge, LA.It is a highly potent SC, which was just recently added to the Schedule 1 Controlled Substance Act in late 2015.The clinical manifestations observed in these patients appear similar to those described with other SC toxicities.The exact mechanism of MAB-CHMINACA toxicity is unknown. Affinities of SCs and their metabolites are multi-fold higher at the CB1 and CB2 receptors than that of Δ-9 THC and are thought responsible for such severe clinical manifestations.CB1 receptors are mostly located in the brain and regulate the central nervous system effects of Δ-9 THC and other cannabinoids; they are also expressed peripherally in adipocytes and skeletal muscle.The identification of CB1 receptors presynaptically on GABA and glutamatergic terminals with increased excitatory and decreased inhibitory tone may be responsible.Other postulated mechanisms include activation of non-cannabinoid receptors and drug-drug synergistic effects.Some patients demonstrated stimulant and serotonergic agent use as detected by comprehensive urine drug LC/ MS testing that could have contributed to their clinical presentation, such as sympathomimetic or serotonergic toxidromes. However, this was not universal and would not explain the fairly consistent clinical presentation of all of these patients.

Further, the relative concentrations of MABCHMINACA do not necessarily correlate with toxicity and may demonstrate the potential lipophilic distribution of the drug to tissue at the time of blood draw. For example, patient #11 had a relatively low concentration, yet expired. Interestingly, post-mortem analysis of a patient who died from MAB-CHMINACA toxicity demonstrated a relatively low amount in the adipose tissue, atypical of other SCs. The authors hypothesized the compound may require time to distribute to that tissue, and that may have been the salient issue regarding patient #11 given the length of time from medical attention.Limitations in real-time detection by routine toxicologic immunoassay screening appear to be a factor in SC use.The reasons for the abrupt, recent increase in exposures, however, remain unclear. The celebration of “4/20” correlated with this surge and might have influenced users. Management of the SC-intoxicated patient centers on meticulous supportive care, as no specific antidote currently exists. Decontamination is of little value. Given their beneficial pharmacokinetic profile, administration of benzodiazepines titrated to clinical effect can control agitation, delirium,hyperthermia and seizures. Cooling measures without antipyretic administration can also be implemented for hyperthermic patients.Endotracheal intubation may be required for the severely intoxicated patient.Serotonin plays a crucial role in emotional processes. A considerable number of imaging studies involving pictures of emotional faces show that changes in serotonergic function are associated with changes in amygdala reactivity when viewing negative facial expressions: Acute tryptophan depletion, which reduces central serotonin synthesis,planting racks leads to higher amygdala activity when processing negative face expressions . Several studies have found that acute/subacute SSRI intervention leads to a decrease in amygdala activation . Further, when the cerebral serotonin level is pharmacologically enhanced by a three-week intervention with a selective serotonin reuptake inhibitor , the ensuing decreased cerebral [11C]SB207145- PET binding in response to pharmacologically increased brain serotonin levels is associated with lower threat-related amygdala reactivity . Whereas it is relatively clear that induction of acute and subacute changes in serotonin neurotransmission leads to changes in emotional processing, less is known about how the neural processing of emotional information is affected by chronic cerebral serotonin depletion. Ecstasy, or 3,4-methylene-dioxymethamphetamine is a widely used recreational drug that has immediate effects in terms of improved mood and feelings of empathy . In this paper, we will use the term “ecstasy” when referring to the recreational human, and “MDMA” when referring to experimental human/animal studies. MDMA exerts its primary effects on the serotonin neurotransmitter system, in particular by reversing normal serotonin transporter function and hence releasing serotonin from the storage vesicles into the synaptic cleft . Animal studies show that repeated exposure to moderate and high doses of MDMA is associated with a reduction in cerebral serotonin levels and a decreased number of SERT binding sites. In humans, prolonged recreational use of ecstasy is also associated with reductions in SERT in both cortical and sub-cortical brain areas .

Most , although not all , molecular imaging studies show that the accumulated lifetime intake of ecstasy correlates negatively with SERT binding, supporting a dose-dependent relationship between recreational ecstasy use and reductions in SERT binding. Thus, it also seems plausible that in humans, an ecstasy-associated reduction in SERT is associated with reduced cerebral serotonin levels, and that the SERT changes may even result from chronically reduced serotonin levels. Additional support for serotonin depletion in recreational ecstasy use comes from the finding of increased levels of the post-synaptic serotonin 2A receptor in most , although not all , studies where ecstasy users have had their serotonin 2A receptors measured. Importantly, lowering brain serotonin levels in preclinical models leads to low SERT combined with high serotonin 2A receptor levels, and low SERT has also been found to be associated with high serotonin 2A receptor levels in humans . The reduction in subcortical SERT binding in ecstasy users seems to be reversible, since a positive correlation with time of abstinence from ecstasy intake has been observed . Taken together, data from these preclinical and clinical studies indicate that there is a causal relationship between ecstasy intake and effects on the serotonergic system. Reduced SERT and serotonin after MDMA/ecstasy exposure in combination with the observed correlation between serotonin depletion and reduced SERT binding in animal studies makes it plausible that SERT binding can be regarded as a representation of the extent of chronic—but most likely reversible—serotonin depletion in long-term ecstasy users. With MDMA being an interesting and promising candidate as adjunct to psychotherapy for treatment of post-traumatic stress disorder and possibly other conditions as well , it is important to explore the possible long-term impact of this drug on serotonergic neurotransmission, as well as the functional consequences of this. Although the multiple and not always pure MDMA doses used recreationally differ from the only few—and pure—doses employed in therapy, recreational use of MDMA/ ecstasy can serve as a model for the long-term effect of repeated doses. In the present study, we used functional magnetic resonance imaging to investigate the functional effects of long-term recreational ecstasy use, representing a model of long-term serotonin depletion, on the neural basis of emotional responses in the amygdala. We hypothesized that amygdala engagement to aversive stimuli would show a positive correlation with accumulated lifetime ecstasy use; a negative correlation with SERT binding, as assessed with positron emission tomography imaging, in the amygdala; and a negative correlation with time since last use of ecstasy, suggesting recovery of amygdala response. The degree of serotonin depletion as reflected by cerebral SERT binding was assessed with PET and the selective SERT radioligand, 11C-DASB, as described in more detail by Erritzoe et al. . In short, PET data were acquired on a GE-Advance scanner as a dynamic 90-minute emission recording after intravenous injection of the radiotracer, 11C-DASB. There was maximum of 1.6 months between the 11C-DASB PET and the fMRI experiment ; approximately half of the group had PET before MRI, and vice versa. The vast majority was scanned within one to two weeks; only two were scanned with an interval of more than a month. For each participant, a mean SERT binding value from the amygdala was calculated.

The optimal understanding of how ARBs develop requires considering a range of characteristics, preferably in a prospective study . The complex relationships with which multiple factors relate to ARB risks may indicate opportunities for more focused and efficient prevention by identifying subgroups most likely to experience ARBs and who are most likely to gain from programs aimed at decreasing heavy drinking. The larger study from which these data were extracted and a smaller investigation at another university indicated that active education about alcohol-related risk factors are associated with less intense future drinking. In the current study, the significant active education group vs. control group main effect in Table 4 supports the conclusion that decreases in maximum drinks seen with participation in the educational videos were also associated with lower levels of ARBs over time . Thus, universities and other institutions interested in decreasing the risk for ARBs and associated problems might consider developing similar education programs and focusing their efforts on subgroups of subjects with the highest ARB risk. As is true for all research, it is important to recognize caveats regarding the current work. The data were extracted from a larger study evaluating different ways of decreasing heavy drinking among students, and consistent with a prior report focusing on heavy drinking , exposure to active intervention affected ARB rates, a factor that complicates interpretation of results. However, as shown in Table 4, the current results remained robust when prevention group assignment was used as a covariate in the mixeddesign ANOVA. The relationships among ethnicity, LR and changes in drinking over time are the focus of several other papers and, due to space constraints, are not discussed in detail here . Also regarding the larger study,greenhouse benches the subjects were from a single California university, and the generalizability of results to other settings needs to be established, including gathering data on additional ethnic minorities as our analyses were limited to EA, Hispanic and Asian individuals.

Next, the data were gathered on-line rather than in person by research staff with whom students had no personal contact, a step that might have affected the veracity of the responses, but the level of impact or direction of effect cannot be determined. Also regarding the larger study from which these data were extracted, to maximize the number of students receiving educational videos only 13% of the subjects were controls, and differences in numbers of subjects across groups may have impacted on current results. While the time frame for the current study was 55 weeks and the proportion of subjects reporting ARBs during this interval approached 50% in females, ARBs occur over many years and longer term follow ups are needed. In addition, the short time frame of reporting for the prior month for each assessment resulted in relatively low numbers of ARBs per individual per evaluation.Additional caveats are worth noting. All information about ethnic identity and blackouts involved self-reports, which may underestimate ARBs because heavy drinking can interfere with accurate recognition of whether an ARB occurred. It is also important to recognize that while the SRE has proven to be a robust predictor of future heavy drinking and alcohol problems, the present analyses did not control for years of drinking, the type of beverage consumed or other covariates. However, prior studies demonstrated that the relationship of SRE scores to heavy drinking and related consequences remained robust even after controlling for sex, weight, marijuana use or smoking histories and operated similarly in 12- year-old subjects with recent drinking onsets and in young adults . Finally, there are important subgroups among EA, Asian and Hispanic populations, which, reflecting our sample size, could not be evaluated, and additional risk factors associated with ARBs were not included in analyses. These caveats aside, the present findings indicate that the propensity toward ARBs goes beyond the amount of alcohol consumed and is related to interrelationships among ethnicities, sex, and the sensitivity to alcohol. There are important differences among subgroups of students regarding how characteristics contribute to the ARB risk. Understanding how these interrelationships operate can be important in identifying who carries the highest risk and in creating focused and efficient prevention programs.

Adolescent use of electronic vapor products , including electronic cigarettes, vaporizers, and vape pens—with and without nicotine—is an emergent public health epidemic in the U.S.Vaping nicotine during adolescence is associated with increased risk for cigarette smoking initiation and co-use of alcohol, cannabis, and other substances.Vape products not containing nicotine may also have negative health effects, although these effects are not well understood.For example, evidence suggests that vape cartridges with THC may be related to recent outbreaks of severe lung injury in the U.S5 and flavored e-liquid found in vape products with and without THC contain health harming toxins.Since 2011, past 30-day prevalence of adolescent vaping has increased steadily, peaking in 2019 at approximately 30%.7,8 Although adolescent vaping prevalence dropped to approximately 20% in 2020, it remains high.Given the potential negative health consequences associated with vaping, adolescent vaping prevention must be a public health priority. Ideally, prevention efforts will target the most vulnerable, however, there is a limited evidence base regarding differences in vulnerability across adolescent groups. One group that may be at high risk for vaping is transgender adolescents. By transgender, we mean adolescents whose gender identity is not aligned with their sex assigned at birth, and by cisgender, we mean adolescents whose gender identity aligns with their sex assigned a birth. Although limited, research with nationally-representative and population-based surveys finds transgender adolescents are more likely to smoke combustible cigarettes and vape than their cisgender peers.The model posits that chronic exposure to multilevel gender minority-related prejudice and discrimination predisposes transgender and other gender minority people to excess stress and in turn, negative health outcomes and health disparities. Indeed, past research has found tobacco- and substance use related disparities among transgender adolescents may be related to violence and victimization, community norms favoring substance use, and targeting of LGBTQ people by tobacco and alcohol companies.

While examinations of gender identity disparities in adolescent tobacco use—vaping in particular—are uncommon,grower equipment even less is known about how these disparities vary by race/ethnicity, i.e., disparities at the intersection of gender identity and race/ethnicity. Indeed, vaping among transgender adolescents of color may differ significantly from their non-Latinx white peers given exposure to multiple and intersecting individual, interpersonal, and structural level forms of racism and cisgenderism. These intersecting, multiplicative experiences of racism and cisgenderism, and resultant stress and coping can be understood through the lens of intersectionality. A theoretical framework rooted in Black feminist thought, intersectionality examines relationships between macro-level interlocking systems of power and individual-level experiences and behaviors across multiple social positions .As a tool, intersectionality provides a lens through which researchers can elucidate and explain population health disparities across multiple axes of social positions, centering the notion that “social categories are not independent and unidimensional but rather multiple, interdependent, and mutually constitutive” .Given a dearth of evidence on vaping and vaping disparities among transgender adolescents of color, the present study examines the prevalence of adolescent vaping at the intersections of gender identity and race/ethnicity in a population-based sample of adolescents in California secondary schools. We tested the hypothesis that gender identity and race/ethnicity interact such that transgender adolescents of color would evidence greater frequency of vaping compared to cisgender white adolescents . This information may provide a starting point for advancing understanding of vaping disparities among transgender adolescents of diverse races/ethnicities and informing vaping prevention and control initiatives. Data for this study come from the California Healthy Kids Survey collected in 2017-2018 and 2018-2019. One of the largest of its kind in the U.S., the CHKS is administered via paper/pencil or electronically to adolescents in California schools on a variety of health domains, including tobacco and substance use, and sociodemographics, including gender identity, ethnicity, and race. School districts receiving subsidies from the California Department of Education are required to administer the CHKS at least biennially in 7th and 9th grades and strongly encouraged to administer it in 5th and 11th grades. Districts not receiving subsidies participate voluntarily. Parents/guardians provide active, written consent for children in 5th grade and passive consent for children in 7th grade and above to participate. Student participation is voluntary and anonymous.For years 2017-2018 and 2018-2019, approximately 75% of California school districts administered the survey at least once , 39% of which administered it twice .Our main independent variables were gender identity and race/ethnicity. Gender identity was measured with the question, “Some people describe themselves as transgender when their sex at birth does not match the way they think or feel about their gender. Are you transgender?”. We categorized participants into three gender identity categories based on their response to the question: Cisgender , Transgender , and Unsure of Gender Identity . We categorized race/ethnicity based on participant responses to two separate questions: “Are you of Hispanic or Latino origin” , and “What is your race?” . Participants who indicated a Hispanic or Latino ethnicity were categorized as “Latinx” regardless of the race they endorsed. Participants who did not indicate a Latinx identity were categorized as non-Latinx white , non-Latinx Black or African American , non-Latinx Asian , non-Latinx American Indian or Alaskan Native , non-Latinx Native Hawaiian or Pacific Islander , and non-Latinx multiracial .

Our outcome variable was number of days vaped in the past 30-days, i.e., vaping frequency, measured with the item: “During the past 30 days, on how many days did you use electronic cigarettes, e-cigarettes, or other vaping device such as juul, e-hookah, hookah pens, or vape pens? ”. Past research on adolescent vaping has tended to examine vaping as a binary outcome . To allow for greater detail in modeling frequency, we re-categorized this variable on an integer ordinal scale of 0 days , 1 day , 2-9 days , and 10 or more days vaping in the past 30-days. Based on prior research finding differential patterns in vaping or other tobacco product use among adolescents by specific sociodemographic factors,we included the following potential confounders in analyses: grade, parental education, and sexual orientation. We coded grade into four categories to capture typical groupings in the U.S. context and aid model convergence: 6th -8 th , 9th -10th , 11th -12th , and other/non-traditional. Of note, the majority of adolescents participating in the CHKS are in grades 7th, 9th, and 11th; however a small proportion of students participating in the 2017-18 or 2018-19 survey indicated that they were in 6th, 8th, 10th, or 12th grade which may mean they completed the survey during a class that is primarily open to students in grades 7th, 9th , or 11th, or that their school administered the survey to all grades. We coded parental education into five categories: did not graduate from high school, graduated from high school, attended some college, graduate college, or “don’t know”, and sexual orientation into six categories: heterosexual/straight, gay/lesbian, bisexual, not sure, other , or declined to answer. Our analytical goal was to test the hypothesis that disparities in vaping frequency would be magnified among transgender adolescents of color relative to cisgender white adolescents. We pooled data from the CHKS 2017-2018 and 2018-2019 waves to increase sample size in smaller racial/ethnic and gender identity subcategories and to ensure that the maximum number of schools across the state could be included in the analysis given most schools participate biennially as opposed to annually. We restricted analyses to data from adolescents in grades 6th and above , as the 5th grade survey does not ask about gender identity or substance use . We excluded data from 26 schools that did not collect gender identity . Compared to adolescents attending schools that collected gender identity, adolescents attending schools that did not collect gender identity were less likely to report any past 30-day vaping , and more likely to identify as white and report their parents graduated from college . We further excluded observations collected via a shortened version of the survey which lacked items on substance use . Per recommendations from the survey administrator WestEd, we then excluded observations considered implausible or impossible responses and/or endorsement of an item indicating that some or all survey items were answered dishonestly .

These new analyses used generalized psychophysiological interactions , a technique that allows for the examination of connectivity between two brain areas as a specific function of the task of interest. gPPI was developed to allow for the use of more than two task conditions in the same model while also improving model fit . The evaluations were centered around two hypotheses. Hypothesis 1 is based on observations from fMRI studies of young individuals who did not have an AUD history prior to testing where regional BOLD differences were observed during placebo conditions. This prediction states that compared with high LR individuals, those with less intense response to modest alcohol doses will demonstrate lower levels of functional connectivity between the amygdala and PFC when processing emotion-laden faces. Further, we predict negatively valenced emotions will elicit a greater decrease in connectivity relative to positively valenced emotions . Given prior studies demonstrating changes to brain functional connectivity following alcohol administration, Hypothesis 2 states that low LR individuals will have lower levels of functional connectivity following alcohol for negatively valenced emotions compared with high LR individuals.In the original study from which the current data were extracted , a survey was distributed to randomly selected 18 to 25-year-old European American and white Hispanic students at the University of California, San Diego, using methods approved by the UCSD Institutional Review Board. This questionnaire gathered information on demography, substance use, and DSM-IV psychiatric disorders using questions extracted from the Semi-Structured Assessment for the Genetics of Alcoholism interview . To be included in the fMRI protocol described below, subjects were limited to those who were: right-handed; had no history of brain trauma or epilepsy; no history of alcohol or drug dependence; no current major psychiatric disorder; were not pregnant; and had no irremovable body metal. A laboratory-based alcohol challenge was then used to establish an individual’s LR.

After confirming zero baseline breath alcohol concentrations ,container for growing weed subjects drank alcohol over a 10-min period given as a 20% by volume solution in a room-temperature carbonated beverage, a protocol that produced approximately equivalent BrACs across sexes . We used a median split on self-report scores from the Subjective High Assessment Scale during the alcohol challenge to determine low versus high LR in both the prior study and the present secondary analysis of those data. Once the LR status was confirmed through the initial alcohol challenge, two MRI sessions were scheduled on nonconsecutive days within 1 week of each other whenever possible. Alcohol and placebo sessions were carried out in an MRI scanner where participants received, in random order, the same alcohol dose as in the laboratory session or placebo in sessions that included the Hariri emotional face recognition task . Complete data required for functional connectivity analyses were available from 216 fMRI scans across placebo and alcohol challenge sessions for 108 individuals. The subjects were comprised of 54 pairs of low- and high-LR participants who were matched on sex, demography, drinking frequency and usual quantities, as well as tobacco and cannabis use. The data presented here were extracted from the Hariri emotional face recognition task, which was presented to participants in the MRI scanner 60 min post-beverage consumption during placebo and alcohol fMRI sessions. The task was measured at a time close to the peak BrAC during the average alcohol session. At this point of the alcohol session, the alcohol levels were similar in the LR groups.We used a modified version of the Hariri emotional face-processing task . Participants were presented with a target face and two probe faces for 5 s, with instructions to match the probe and emotional expression of the target by pressing a button in a block design. Each block had six consecutive trials where faces were either angry, fearful, or happy. Additionally, a sensorimotor control condition was used where vertical or horizontal ovals or circles were presented for six consecutive trials in block with instructions to match the shape of the probe to the target. Each block of emotion condition and the sensorimotor control condition were presented three times in a pseudorandomized order. The task began with an 8-s fixation period and had interspersed 12-s fixation periods between each block.

There were 18 trials for each condition yielding 512 s total task time. Figure 1 illustrates the timing of the task with examples from the first two blocks . We recorded accuracy and reaction time during the task to confirm the task was carried out correctly .The Analysis of Functional Neuro Images software package was used for preprocessing data and gPPI analyses. All T1-weighted images were skull-stripped and warped into Talairach Tournoux atlas space using a 12-parameter affine transformation. Next, functional data were visually inspected for scanner artifacts. To correct for small movements over time, image repetitions were registered to a selected base volume via AFNI’s 3dvolreg program. The time series of the motion parameters were used in the linear regression analysis of individual data to control for spin history effects . Functional data were then transformed into the participant’s anatomical space and aligned to standard space using the previously computed anatomical transformation matrix and smoothed with a 4-mm FWHM Gaussian kernel.The general linear models used reference vectors for the task conditions convolved with the hemodynamic response function. Estimated motion and linear, quadratic, and cubic trends were also included as nuisance variables. The resulting model generated scaled beta coefficient maps representing the mean percent BOLD signal change for each condition of the task relative to baseline.Functional connectivity analyses were conducted using gPPI with anatomical-defined seeds in the left and right amygdala. Seed regions were chosen using Neurosynth , a meta-analytic tool for selecting fMRI activation coordinates from a database of studies , where we examined studies using tasks of emotional faces to elicit amygdala activation. Specifically, we created a 5-mm sphere around the coordinates X = −26, Y = 6, Z = −14 and resampled to the template space of our fMRI scans. Visual inspection of these seeds ensured that they were anatomically constrained to the amygdala using the Talairach Tournoux atlas. For each participant, the average time series of the BOLD signal was extracted for each seed, and trends were removed. A one parameter gamma model was used to estimate the hemodynamic response function of the task and a deconvolution of the seed’s time series with this function was calculated using the 3dTfitter AFNI program yielding scaled coefficients. PPI regressor interaction terms for each condition of the Hariri task were computed by multiplying the mean time series of the de-convolved seed with the condition vector of interest, and then convolved with a gamma basis function using the AFNI program Waver.Separate voxel-wise GLMs were conducted for each bilateral amygdala seed. Each GLM contained the PPI regressors, the physiological regressor , the psychological regressors , and nuisance variables .

Each seed’s connectivity with other brain areas was examined separately. Whole-brain between-group differences in functional connectivity were estimated using mixed-effects ANOVAs with the AFNI 3dANOVA3 program where the within-subject factor was alcohol/placebo condition and the between-subjects’ factor was Low/High LR. We applied a cluster correction to guard against identifying false positive areas for potential functional connectivity differences. Specifically, we estimated the noise in our fMRI volumes using 3dFWHMx in AFNI and used that information to apply a cluster-size threshold of α = 0.01 for a given voxel-wise threshold of α = 0.01 to protect our α at a 0.01 level using the 3dClustSim AFNI program. Using this approach,cannabis drying the minimum volume for a significant cluster in our analyses was set at 448 µl or seven contiguous significant voxels.Connectivity analyses were carried out examining LR groups during the alcohol and placebo conditions using left and right amygdala seeds. Clusters showing significant LR, alcohol, or LR-by-alcohol interaction effects in functional connectivity differences in response to fearful, angry, and happy faces are described below and detailed in Table 2. Specifically, Table 2 lists brain regions, associated Brodmann area , peak activation, Talairach coordinates, and volume for each significant cluster. Figure 2 illustrates the pattern of functional connectivity main effects for exemplar regions, while Figure 3 illustrates the pattern of functional connectivity interaction effects for exemplar regions. For all significant clusters we also ran ANCOVA models covarying for sex and did not find any significant effect of sex in our results.During angry faces, using the left amygdala seed, the differences between low and high responders illustrate that low LR participants had lower functional connectivity in several cortical regions compared with high LR participants in both placebo and alcohol conditions. This was observed in the left medial frontal gyrus, bilateral ventral anterior cingulate, bilateral posterior cingulate, and left supramarginal gyrus. Using the right amygdala seed, the main effects of LR during processing of angry faces were identical to left amygdala such that low LR participants had diminished functional connectivity as compared to high LR participants in both placebo and alcohol conditions in the bilateral posterior cingulate. In contrast, during happy faces, significant effects were observed only with the right amygdala seed where, opposite to the LR main effects pattern observed for angry faces, low LR participants had greater functional connectivity compared with high LR participants in the right dorsal anterior cingulate gyrus and right caudate.During angry faces, within the right precuneus, lower functional connectivity was observed with the left amygdala following alcohol compared with placebo in low LR individuals, but increased connectivity following alcohol was found in high LR individuals. Interactions during processing of happy faces were characterized as a decrease in functional connectivity with right amygdala following alcohol as compared to placebo in low LR individuals, but increased connectivity following alcohol in high LR individuals in left middle frontal gyrus regions; a pattern similar to the interaction observed during angry faces.The main goal of these analyses was to expand upon the findings of Paulus et al. by evaluating LR group differences in functional connectivity. This is the first demonstration of differences in connectivity between low and high LR individuals, results that might help explain why drinkers with low LRs might require greater cognitive effort to perform optimally on some tasks. Consistent with our hypotheses, in the current analyses the most prominent patterns found were attenuation of amygdala connectivity with cortical regions in low LR participants, both during placebo and in response to alcohol, relative to high LR participants while viewing angry faces. Additionally, comparing alcohol and placebo sessions, low LR individuals exhibited decreased functional connectivity in response to alcohol, whereas high LR individuals showed increased functional connectivity while viewing both angry and happy faces. The present findings add to the regional brain changes originally reported by Paulus et al. . While those authors found no difference in amygdala regional activation patterns across LR groups, we found several differences in functional connectivity with the amygdala that varied depending on the valence of facial affect being decoded. Thus, BOLD signal changes in the cortex in response to an emotional processing task in low versus high LR individuals might reflect aberrant functional connectivity in corticoamygdalar circuits. These functional connectivity differences were observed in relatively highly functioning individuals from a nonclinical sample, some of whom carried an enhanced risk for alcohol problems through a low LR but none of whom had yet developed an AUD. Along with a growing body of evidence that the low LR phenotype is characterized by CNS differences relative to their high LR peers , these emotional processing data suggest that low LR individuals may have an altered neurobiological process in which they recognize some negative or positive social cues through decoding facial affect. It is also possible that given the pattern of brain regions in the frontal lobe, anterior cingulate, and insular cortex that showed altered amygdala functional connectivity, as well as regional BOLD signal changes in the insula, low LR individuals may have an impaired ability to recognize intoxication, or the rewarding aspects of alcohol, in social situations. Functional connections between the amygdala and cortical regions play important roles in processing human emotions. For example, connections between the PFC and amygdala facilitate the cortex’s top-down regulation in decoding emotional stimuli , allowing appraisals based on affective information to moderate goal-directed behaviors .

We ranked the continuous traits based on their heritability and performed a genome wide association of the top six with the Efficient and Parallelizable Association Container Toolbox. This would be expected to reduce the loss of power due to multiple testing of hundreds of phenotypes. The family Carnobacteriacea was excluded from the GWAS analyses since it was highly correlated with the genus Granulicatella and the latter has a more refined taxonomic resolution. It is well established that continuous traits afford greater power in both twin studies and in GWAS. Therefore, although some categorical phenotypes showed high twin heritability , for GWAS we only studied continuous traits. The analyses were all controlled for age, sex, and sequencing run among other covariates . Analysis was done independently with individuals from the two major different ancestry groups of the unrelated sample, European and Admixture. Due to the limited size of the admixture sample, only the European sample is discussed and the admixture was only considered for the meta-GWAS discussed below. To control for population stratification a kinship matrix created from all the chromosomes and the first ten principal components from the LD-pruned SNPs were included as covariates . To control for the fact that 6 traits were tested, the genome wide significance level was lowered to 8.33e-09 . Using this threshold, we found that the genus Granulicatella was significantly associated with the SNP chr7:110,659,581 within an intron of the IMMP2L gene on chromosome 7. This gene is known to be involved in mitochondrial protein trafficking. The regional Manhattan Plots in Fig. 4b show that the peak locus includes SNPs of decreasing r2 values around the peak SNP lending greater confidence to the association. Without a replication sample this result is provisional but potentially interesting. Using PLINK 1.9, which takes categorical imputed genotypes rather than the probabilistic dosage calls produced by imputation as input,hydroponic tables canada produced results consistent with this association showing the association is independent of underlying computational method.

A comparison of the 100 SNPs with lowest P values in each of the six phenotypes examined in the European sample revealed that 7 SNPs were held in common between at least two of the phenotypes. Bray Curtis PCo2, Unweighted UniFrac PCo2, and Weighted PCo2, all β- diversity measures, were most often shared . After the initial analyses of the 6 most heritable traits, a GWAS was completed in the remaining 64 continuous traits in the European sample. We have used a relatively conservative approach to controlling for population stratification . To evaluate if this may have produced false negatives, we repeated the GWAS with EPACTS kinship only, PLINK 10 PCs, and GCTA LOCO . Each consistently identified the same SNP at chr7:110,659,581 significantly associated with the trait along with nearby SNPs in high LD associated as well . No additional significant SNPs were identified consistent with the hypothesis that stratification methodology had little effect on identifying the top SNPs and that we were not “over filtering” with rigorous kinship controls. For completeness, we then carried out a GWAS analyses for the remaining 64 continuous microbial phenotypes using the EPACTS kinship only analyses adjusting significance for the additional multiple testing and found no SNPs to be significantly associated. This is perhaps not surprising given the relatively small sample size .The size of the ADM sample made it unlikely to produce statistically significant results. To glean useful information from it we combined it with the EUR data described using a meta-analysis approach that can effectively deal with population issues inherent in mixing samples of different populations. METAL is such a meta-analysis package that takes as input individual SNP P values and the direction of their effects weighted by the sample size to arrive at composite P values. The test statistics were also corrected for population stratification . The METAL analysis identified the same suggestive significant SNP on chromosome 7 that was associated with Granulicatella abundance in the EUR GWAS . However, due to the small size of the ADM sample, this SNP did not survive quality filtering in the METAL analysis and so was not a factor in the METAL analysis outcome. Analyses of Unweighted Principal Coordinate 3 yielded a SNP on chromosome 12 that reached genome wide significance in the same direction for the combined sample, though it was not robust to multiple testing correction .

Again, the regional Manhattan Plots in Fig. 5c show the peak locus includes SNPs of decreasing r2 around the peak SNP consistent with the association. The minor allele C, was shown to be consistent with lower PCo3 z-scored values . The most promising single SNP association occurred with the phenotype defined as the abundance of the genus Granulicatella. We reanalyzed the association data with the gene-based tool Knowledge-based mining system for Genome-Wide Genetic studies involved in protein processing associated with mitochondrial import and a non-coding antisense RNA INHBA- AS1 . A SNP in INHBA-AS1 had been previously identified in a dental caries GWAS along with a loci in the INHBA gene. INHBA is thought to be important to tooth development, which could have potential interesting implications to the oral micro-biome. The meta-GWAS results on the PCo3 of Unweighted UniFrac most highly associated region was the gene LIN7A on chromosome.It was possible that tobacco or other factors influenced our observation of genetic association. For example, Streptococcus abundance, a highly heritable phenotype, has also been shown to change in smokers. In addition other substances could potentially change the oral micro-biome. Among these alcohol and marijuana, though these effects have yet to be determined. However, marijuana use is correlated with poor oral health, which is often indicative of changes in the oral microbiota. We had available the self-reported tobacco, alcohol and marijuana use in 92% of our subjects for the previous six months. We therefore repeated the analyses using the three substances as covariates . As seen in Additional file 2: Figures. S15 and S16, controlling for tobacco/alcohol/marijuana use had negligible impact on the top hit on chromosome 7 for the genus Granulicatella . For the 6 highly heritable continuous traits that were analyzed, both with and without substance use covariates, results appear to be consistent with and without substance .We have shown that microbe abundance and some aspects of the microbial population structure are influenced by heritable traits in saliva.

We have ranked the “most heritable” traits using ACE/ADE modeling and GCTA-based SNP heritability and carried out an unbiased GWAS on the 6 most heritable traits. One SNP on chromosome 7 in the gene IMMPL2 reached genome-wide significance. Another gene IINHBA-AS1 on chromosome 7 achieved genome-wide significance when analyzed by KGG4 that relies on a composite association score including all SNPs in each known gene. The significance of these associations was not influenced by “p-hacking” statistical biases common in GWAS because phenotype choice was not based on previous association tests. This approach is a model for using heritability to reduce the multiple testing problems seen in many GWAS reports and it could be the method of choice in the design of GWAS studies in which sample size may be limited. Bray-Curtis, Weighted UniFrac,microgreen rack for sale and to a lesser extent Unweighted UniFrac β-diversity demonstrate that many components of the micro-biome community are heritable . While a shared environment and behavioral habits contribute to a more similar micro-biome , such studies did not control well for the clear genetic influences in their populations. When we examined the differences among MZ and DZ cotwins and age-matched unrelated individuals that we were confident cohabitated , the genetic influences remain clear. It is significant that the genetic effects are detected using measures that include all detectable OTUs. To assess heritable influences of individual microbial components, we carried out intraclass correlation analyses that show that heritability extends across nearly all observed taxa individually . The one exception is in the fusobacteria where ICC does not distinguish MZ and DZ. Possibly these organisms, known to be “bridges” between early and late colonizers on gum and tooth surfaces, may not have interaction with host proteins and could lack human genetic influences. GWAS of complex traits on relatively small samples is problematic due to the lack of statistical power. The influence of individual genes on traits that have multiple genetic components may be small. Moreover, the micro-biome is a highly complex population with interacting networks of bacteria that all may have multiple interactions with the host. A variety of covarying network modeling approaches have demonstrated how complex these communities are. It has been shown that assuming the number of causal variants and their frequency spectra for a pair of traits are similar, more heritable traits are more likely to be detectable in GWAS. Therefore we focused on those micro-biome endophenotypes with greatest additive genetic heritability for GWAS. Both ACE/ADE modeling and GCTA SNP heritability are suited to this approach. The microbial phenotypes with greatest additive genetic influence in the ACE/ADE model on the entire twin cohort were the abundance of the OTU4483015 that corresponds to an unnamed species of Granulicatella and PCo2 of Bray Curtis . The influence of additive genetics was variable depending on the trait when comparing the full sample to heritability only among cotwins that cohabitate . The variation in estimates may reflect environmental effects or loss of power between the full sample and the cohabitating sample . This again points to the complex nature of the microbe-host interactions in primarily aerobic and anaerobic environments and how human genetic influences must also be complex. As a further test of heritability prior to GWAS, we examined SNP-based heritability in our unrelated sample with GCTA. A positive correlation was observed between the ACE/ADE and GCTA ‘heritability’ estimates for continuous traits in both the full twin sample and the EUR sample . Previous studies have demonstrated that large samples are needed to produce results reaching statistical significance using GCTA.

In their original paper Yang et al. showed that while increasing the sample size does decrease the error bars of the heritability estimates, the heritability estimates themselves remain relatively stable. While the GCTA estimate was not significant upon correction for multiple testing, the positive correlation between the unrelated individuals and the twin studies provides support for the conclusion that for these continuous traits genetic variation influences microbial populations. A GWAS analysis with the six most heritable continuous traits determined from the twin modeling was carried out in the European populations . The GWAS of the abundance of the genus Granulicatella identified a genome wide significant SNP on chr7 . This SNP is located in an intron of the IMMP2L gene. The GWAS meta-analyses combining the EUR and ADM samples using METAL with the same 6 traits showed no new information about the chr7 SNP due to its low frequency in the ADM population but did produce an additional association with suggestive significance, chr12:82,166,911 for the phenotype Unweighted UniFrac PCo3, though it was not robust to correction for multiple testing. This SNP is located in the gene LIN7A that is widely expressed in endothelial cells. Markers in LD with the top SNPs were also highly associated with the phenotype, but in addition, markers of somewhat lower LD that were nearby also displayed elevated significance for both hits. This provides an argument that these loci may not be due purely to chance . To be adequately powered one must have a large sample size or the single SNP effect must be very large. However, most complex traits are polygenetic and so many loci with small effects account for the variation of the trait. Therefore, where sample size is limited, it may be difficult to observe significant SNP associations. To address this, it is possible to use biological information to inform analyses and increase statistical power. This may be done by aggregating the association of multiple SNPs known to be present within a known gene. By this approach, the possibly small effects of all SNPs in the gene are combined and then the association of the entire gene may be determined. Even if no single SNP is found to be genome-wide significant the combined SNP contributions across the gene may be. One widely used gene-based GWAS analysis method is the Knowledge-based mining system for Genome-wide Genetic Studies.

Furthermore, these cytokines promoted T cell proliferation and cytokine production even in the absence of stimulation by DC . However, the addition of IL-7 to DC:T cell co-cultures had a dramatic effect on T cell proliferation, maturation and cytokine production that was restricted in part to co-cultures containing THC-DC. These studies suggest that the immuno regulatory effects of THC might be counterbalanced by the presence of a combination of DC activating signals and the production of cytokines by other cell types present in the local immune environment. In summary, our experiments demonstrate that human monocytes express functional cannabinoid receptors, even if they are not detectable on the cell surface, and that exposure to THC alters their capacity to differentiate into immuno stimulatory DC with prominent effects on antigen uptake and presentation, expression of costimulatory molecules, and production of IL-12. The end result is the generation of DC that fail to stimulate T cell proliferation or promote maturation into functional effector/memory T cells. While the effects are relatively potent when studied in isolation in vitro, there may be a number of immuno regulatory factors that could counteract or moderate the impact of cannabinoid exposure in vivo. The functional role that marijuana smoking has on host immunity and the response to immune challenges in vivo remains to be clarified. Cannabis sativa extracts have been used for centuries both as therapeutic agents and recreational drugs, primarily due to their ability to regulate neurobehavioral processes including memory, mood and appetite. The spectra of possible therapeutic uses of marijuana and its active constituents, the cannabinoids, range from handling nausea,cannabis grow system vomiting and cachexia to treatment of chronic pain, glaucoma, epileptic seizures, Parkinsonian tremor as well as multiple sclerosis. Amongst the 60 different cannabinoids identified from Cannabis preparations, D9 – tetrahydrocannabinol , the major psychoactive Cannabis constituent, and the non-psychoactive cannabidiol are the most abundant and important.

Many of the beneficial effects of cannabinoids have been attributed to their potent immuno suppressive and anti-inflammatory properties. Additionally, cannabinoids are known to possess pro-apoptotic, neuroprotective and anti-tumor properties. To date, two cannabinoid receptors have been characterized: the CB1 and the CB2 receptors. The CB1 receptor is highly expressed in neural cells and mediates the psychoactive and addictive activities of cannabinoids, while the CB2 receptor is abundantly present in the periphery including the immune system and is involved in cannabinoid immuno modulation.THC binds to both of these receptors with similar efficiency and hasbeen reported to have effects on both the nervous and the immune systems. In the last years, attention has been turned to several other phytocannabinoids, most notably to CBD. CBD displays a diversity of actions, including anticonvulsive, sedative, hypnotic, antipsychotic, anti-inflammatory and neuroprotective properties. CBD, unlike THC, is not an efficient ligand of either CB1 or CB2 and therefore, is devoid of the unwanted psychotropic effects characteristic of marijuana or THC. Thus, the effects of CBD are probably mediated through other receptors/targets, as described below and elsewhere . Phytocannabinoids were reported to affect various populations of immune cells. Both THC and CBD have been shown to decrease cytokine production in human immune cell lines and to suppress T cell proliferation and their effector functions. In response to stimulation with the bacterial endotoxin lipopolysaccharide , both monocytes and microglial cultures treated with either THC or CBD produce lower levels of cytokines such as tumor necrosis factor a , interleukin-1a , IL-1b and IL-6. However, the molecular mechanisms involved in these cannabinoid-mediated effects are not yet fully characterized. Eljaschewitsch et al.,showed that activation of CB1 and/or CB2 receptors in the murine microglial BV-2 cell line leads to rapid induction of mitogen-activated protein kinase phosphatase-1 and that this event switches off MAPK signal transduction which was activated by LPS stimulation. Altered adenosine signaling has been reported as a potential non-cannabinoid receptor mechanism by which CBD, but less so THC, can decrease inflammation. Other studies identified the nuclear receptor peroxisome proliferator-activated receptor c as a novel intracellular target, which mediates the cannabinoid-associated immunosuppression in a manner that is independent of the known cannabinoid receptors CB1 and CB2.

Other targets including the G-protein-coupled receptors GPR55 and GPR18 as well as the transient receptor potential channels were also suggested. Microglial cells are the resident macrophage-like cells of the CNS. They are highly ramified cells and their processes are very dynamic under non-pathological conditions, actively scanning their environment. These cells have important roles in brain’s innate immunity and neuronal homeostasis as well as in neuro inflammatory pathologies. Microglia can be activated by infection, injury or by endogenously released neurotoxic factors and their activation is associated with the production and secretion of a variety of compounds such as cytokines, reactive oxygen species , reactive nitrogen species, matrix metalloproteinases and prostaglandins. Although microglial activation is considered a protective mechanism involved in the clearance of pathogen infection and in regulating tissue repair and recovery, excessive or chronic activation can lead to harmful effects. Interestingly, the mechanisms that give rise to either the protective or the damaging microglial phenotypes are not fully elucidated. Enhancing the microglial-mediated innate immunity in the CNS and/or preventing the harmful effects associated with their chronic activation may offer new therapeutic approaches for the treatment of brain injury and neurodegenerative diseases. One of the most potent stimuli for microglia activation is the bacterial endotoxin LPS, that mimics infection by Gram-negative bacteria. LPS activates intracellular signaling pathways in a complex way leading to secretion of cytokines and to over expression of several markers of the immune response. Previous studies reported that LPS stimulation induces gene expression of TNFa, IL-1b, IL-6, iNOS and COX-2 as well as the production of NO and PGE2 in primary and BV-2 microglial cell cultures. We reported that CBD reduces the activity of the NF-kB pathway and upregulates the activation of STAT3 transcription factor in LPSstimulated BV-2 cells, and that both CBD and THC decrease the activation of the LPS-induced STAT1 transcription factor, a key player in IFNb-dependent pro-inflammatory processes. Moreover, performing comparative microarray analysis of genome-wide mRNA levels in the BV-2 cells, we reported that CBD, but less so THC, shows a specific gene expression profile associated with oxidative stress and glutathione depletion involving the GCN2/eIF2a/p8/ATF4/Chop-Trib3 pathway. Furthermore, the CBD-stimulated genes were shown to be controlled by nuclear factors known to be involved in regulation of stress response and inflammation, mainly via the -Nrf2/ Atf4 system and the Nrf2/Hmox axis.

We reported that CBD, but less so THC, affects the expression of genes involved in zinc homeostasis, suggesting that the regulation of zinc levels could have an important role through which CBD may exert its antioxidant and anti-inflammatory effects [14]. Although the inhibitory functions of cannabinoids on LPS activated NF-kB and IFN-b/STAT pro-inflammatory pathways and on the secretion of selected cytokines in BV-2 microglial cells has been studied, a genome-wide search for cannabinoid molecular targets in LPS-activated BV-2 cells has not yet been performed. We have, therefore, performed gene array studies and comparative gene profiling analysis of BV-2 cells treated with LPS, CBD+LPS or THC+LPS. This approach allowed us to analyze the changes induced by CBD and THC on gene expression patterns in LPS-treated BV-2 cells and to explore the genome wide interaction network affected by these treatments. In this regard,marijuana grow system a structured network knowledge-based approach to analyze genome-wide transcriptional responses in the context of known functional interactions among proteins, small molecules and phenotypes has been established. We applied this analysis to show the interactions and signaling networks elicited by the cannabinoids in LPS-stimulated BV-2 cells. Our results show that CBD is a potent modulator of microglial activation. Identification of the CBD- and THC-regulated genes and related networks provides a molecular basis for understanding the effects of these cannabinoids on LPS-activated microglia.BV-2 microglial cells were pretreated for 2 h with either THC or CBD followed by the addition of LPS to the incubation medium for another 4 h.The choice of these time points for transcriptional profiling was guided by our previous studies as well as by other reports which investigated the general temporal pattern of microglial activation by LPS. Moreover, according to our previous results, neither THC nor CBD treatments significantly affected the viability of the BV-2 microglial cells during this 6 h period. The RNA prepared from these samples was analyzed for changes in transcriptional levels using the MouseRef- 8 v1.1 Expression BeadChip Illumina Arrays. Each of these arrays has .24,000 mouse targets based on the NCBI mouse Reference Sequence Database, including 16,287 constitutive exons/islands based on the splice variants in the mouse transcriptome and NCBI LocusLink databases. The results of the analyses of the arrays showed that 32% of the transcripts were consistently ‘‘present’’ in the BV-2 RNA samples across all arrays. Moreover, clustering based on inter-array Pearson correlation coefficient indicated no batch effects. Microarray analysis based on a threshold of p# 0.005, revealed that a total of 22% of the Illumina gene set was differentially regulated across treatments. Of these, 1319 gene probe sets were upregulated and 1829 transcripts were down regulated by the LPS treatment ; and from these numbers of genes, 400 transcripts were found to be upregulated and 145 down regulated by LPS by 2-fold or more. When the fold change was set on $3-fold , we found that 226 gene products were upregulated and 33 were down regulated by LPS . The vast majority of the LPS-affected transcripts represented genes that were exclusively responsive to LPS stimulation, and not to treatment with CBD alone or THC alone . the CBD+LPS treatment was analyzed, 1381 gene probe sets were upregulated and 1666 transcripts were down regulated by CBD+LPS . From these numbers of genes, 379 gene products were found to be upregulated and 489 down regulated exclusively as a response to the combination of CBD+LPS and not affected by LPS or CBD alone . When the fold change was set on $2-fold, 502 transcripts were upregulated and 297 gene probe sets were down regulated by the CBD+LPS treatment .When LPS was applied in the presence of THC, 1216 gene probe sets were upregulated and 1638 transcripts were down regulated; and from these, 424 transcripts were found to be upregulated and 149 down regulated by 2-fold or more . From the 1216 upregulated genes, 157 transcripts were exclusively responsive to THC+LPS treatment alone and from the 1638 down regulated transcripts, 285 gene probes were affected only when THC and LPS were together . When the fold change was set on $3-fold, we found that 230 gene products were upregulated by CBD+LPS and 236 transcripts by THC+LPS whereas 51 gene products were down regulated by CBD+LPS and 31 transcripts by THC+LPS . Our results also reveal that from the 5338 transcripts found to be differentially regulated by the various treatments , 680 gene probe sets were found to be upregulated by CBD alone and 58 gene products by THC alone. CBD had also a much larger effect compared to THC on the number of down regulated genes, 524 gene products were down regulated by CBD and 36 by THC . The groups of LPS-upregulated and down regulated genes that showed a change in expression of $2-fold in either direction were subjected to gene ontology analysis allowing functional annotation using the DAVID Bio-informatics Resources and the KEGG pathways . All major Biological Processes, Cellular Components and Molecular Functions within GO for the LPS-upregulated transcripts, were for the most part, genes associated with the immune and defense responses as well as apoptosis and cell death. KEGG database analysis included genes related to Toll-like receptor pathways and antigen processing as well as to the MAPK pathways. IPA global functional analysis of the LPS-upregulated and down regulated genes confirmed the DAVID representation of genes within IPAspecific GO categories . IPA global functional analysis of the LPS-upregulated transcripts show gene products mainly implicated in cell-to-cell signaling, cellular movements, growth and proliferation, as well as cell death, immune response and signaling, including genes involved in the NF-kB pathway and in the activation of the liver X receptor/retinoic X receptor . The largest subsets of down regulated transcripts included genes known to be involved in the regulation of macro-molecules and nucleotide metabolism, differentiation and development as well as regulation of gene expression and transcription .

For each setting, the vape pen was operated until approximately 100 mg of VEA had been consumed; this consumption was typically achieved within 10–20 puffs. In instances where more puffs were required, the vape pen was allowed to rest at 20 puffs for 10–20 minutes to prevent overheating of the battery. Condensed emission products were dissolved in 1 mL of ACN, with 10 μL of 1, 3, 5-TCB solution added to each sample as an internal standard for chemical analysis. Emissions were analyzed immediately after collection or stored at -80˚C to prevent any aging effects.To determine the impact of the device on the degradation of e-liquids, pure pyrolysis of VEA oil was simulated using a tube furnace reactor system . The schematic of the set up for these experiments is shown in S2 Fig in S1 File. An alumina crucible containing 100 mg of VEA standard oil was weighed, and then placed into a high temperature quartz tube furnace capable of reaching temperatures as high as 1200˚C. The tube furnace was initially set to 23˚C, then ramped to each temperature setting at a rate of 10˚C min-1, and then held at the target temperature for 75 minutes to allow for VEA oil to be evenly heated. Inert argon gas was flowed through the system at a rate of 0.18 L min-1 to carry the VEA pyrolysis products into cold trap apparatus kept at -40˚C. After 75 minutes, the tube furnace was programed to return to room temperature before the alumina crucible was removed and re-weighed to determine the amount of VEA that was consumed. Pyrolysis products condensed in the cold trap were dissolved in 1 mL of ACN and concentrated to 100 μL using a gentle N2 gas stream. Then, 10 μL of 1, 3, 5-TCB solution was added to each sample as an internal standard for chemical analysis.Large molecular weight and non-polar degradation products were analyzed by directly injecting 2 μL of sample into an Agilent J&W DB-5MS column for separation. A solvent delay of 6 min was used; the GC was initially set to 60˚C for 1 min, then ramped to 150˚C at a rate of 3˚C min-1, held at 150˚C for 2 min, ramped to 310˚C at a rate of 20˚C min-1, and then held at 310˚C for 5 min.

Smaller molecular weight,outdoor cannabis grow polar degradation products were analyzed by directly injecting 2 μL of sample into a Rtx-VMS fused silica column . A solvent delay of 6 min was used. The GC was set to 35˚C for 1 min, ramped to 240˚C at a rate of 10˚C min-1, and held 4 min. The detailed procedures for the operation of GC/MS can be found in a previous publication.Degradation products were identified using the NIST 2008 mass spectral database. Compounds with probability 50% and match factor scores 800 were considered as good matches. For compounds that were suspected to be present in our spectra but could not be identified using the NIST library due to lack of available standards, Quantum Chemistry Electron Ionization Mass Spectrometry was used to simulate theoretical EI mass spectra of molecules.The detailed procedures for QCEIMS calculations can be found in the supporting information. Peak abundances were normalized to the 1,3,5-TCB internal standard for quantification.Fig 1 shows the temperature profiles of the e-cigarette coil and VEA oil in the cartridge operated at each voltage setting. Peak coil temperature at each voltage setting was fairly consistent between each measurement with no significant increase after consecutive use, which agrees with previous reports. Though the starting temperature after 1 min of rest increased slightly with subsequent measurements, the starting temperature never exceeded 33˚C. In contrast, the temperature of the oil in the cartridge increased with each subsequent measurement until seeming to plateau. The peak temperatures of both the coil and the oil were then taken and plotted as a function of voltage, as shown in Fig 2. Coil temperature showed a strong positive linear relationship with applied voltage , whereas oil temperature increased linearly with voltage until 41˚C , where the peak temperatures at 4.3 and 4.8 V do not significantly differ. This is likely due to the specific heat capacity of VEA; at higher voltages. Visible discoloration to the oil and wick could be seen during temperature measurements, indicating that the specific heat capacity of the oil in the cartridges may have been exceeded and part of the stored VEA may have been transformed before it is vaped .The total ion chromatographs obtained from GC/MS analysis of VEA vaping emissions produced at each temperature setting are shown in Fig 3. Overall, clear temperature dependent degradation of VEA vaping emissions can be seen as the amount and abundance of degradation products substantially increases with increasing coil temperature.

Analysis of the GC/MS results revealed 19 compounds that were able to be tentatively identified based on consistent NIST MS spectral library match scores of 800 or greater. One other compound, 1-pristene, was not found in the NIST library and thus was identified based on comparison with previously reported mass spectra and a mass spectrum generated with the QCEIMS program that found signature fragments of m/z 266, 111, and 126, which are consistent with our results . A summary of the identified compounds and chemical information identified from PubChem can be found in the supporting information . Many of the products described here, such as phytol, 2,3,5-trimethyl-1,4-benzenediol and 2-hydroxy-4-methoxy-3,6-dimethyl benzaldehyde, have not been previously detected from VEA vaping to our knowledge. An isomer of 2,3,5-trimethyl-1,4-benzenediol has also recently been identified as a substantial VEA degradation product at temperatures 220˚C. Authentic standards were purchased for 2-methyl-1-heptene, phytol, and 2,3,5-trimethyl-1,4-benzenediol to confirm identities of observed products . Other compounds, such as vitamin E, DQ, DHQ, 1-pristene, and 3,7,11-trimethyl-1-dodecanol, have been consistently identified as VEA decomposition products . Several products, such as DHQMA or ketene, that have been previously reported in VEA vaping emissions could not be found in our spectra, likely due to the limitations of the emission collection and analysis method described in section 3.4. A heat map of the mass fractions of degradation products generated at each temperature is shown in Fig 4. Products that contribute to the majority of the observed VEA degradation were separated from the total heat map to better visualize the change in each concentration as a function of temperature. VEA, 1-pristene, and 3,7,11-trimethyl- 1-dodecanol were found to be the most dominant vaping emission products at all of temperature settings, while other compounds, such as duroquinone, durohydroquinone, and 2-methyl-1-heptene steadily increase in concentration as temperature increases. Furthermore, certain compounds including 2,3,5-trimethyl-1,4-benzenediol, 2,6-dimethyl-1,6-heptadiene, 3,7-dimethyl-1-octene, and 3-methyl-1-octene are not produced in concentrations above the detection limit of our instrument until 322˚C, which suggests a potential risk that users who operated vaping devices at lower temperatures would not be exposed to. However, while most identified compounds appear to increase in concentration as temperature increases, phytol and 2,6,10-trimethyl-dodecane are produced at detectable levels at 176 and 237˚C but cannot be found at higher temperatures.

Another recent study has also detected production of phytol when vitamin E were heated in a microchamber/thermal extractor at 250˚C . It is possible that at these compounds are stable at lower temperatures but begin to break down into degradation products themselves as the temperature increases. Another important pattern to note is the increase in compounds that may pose a risk of oxidative damage to lungs, such as DQ and 2,3,5-trimethyl-1,4-benzenediol, at higher concentrations. While not investigated in this study, prior research has shown that increased temperature may result in the enhanced emission of carbonyl-containing compounds when vaping e-liquids containing propylene glycol and glycerin. Thus, vaping VEA at greater temperature settings may also carry the risk of exposure to highly electrophilic molecules and subsequent oxidative lung injury. In order to better understand the interactions between temperature and the generated emission products, a Pearson correlation analysis was performed . Overall,vertical grow system all but four of the identified compounds were strongly correlated with temperature . Compounds such as DQ, 1-pristene, 2-methyl-1-heptene, 2-hydroxy-4-methoxy-3,6-dimethyl benzaldehyde, and 2,6-dimethyl-1,6-heptadiene, were very well correlated with temperature , indicating a strong increase in concentration as temperature increases. VEA and phytol, in contrast, were strongly anti-correlated with temperature , while VE and 2,6,10-trimethyl-dodecane were moderately anti-correlated with temperature . In addition, VEA was found to be weakly to strongly anti-correlated with all degradation products excepting phytol and VE, which demonstrate a strong positive correlation . These results support our analysis of the mass fractions, indicating that as temperature increases, thermal decomposition of VEA is heightened. Further analysis of the correlations between degradation products shows that phytol is strongly anti-correlated with all VEA degradation products with the exception of 2,6,10-trimethyl-dodecane, which was found to have a strong positive correlation with phytol . Phytol was also found to be strongly correlated with VEA , likely because as more VEA was evaporated during the vaping process, the greater the chance of degradation into phytol. These relationships further suggest that while some degradation products may be stable at high temperatures, phytol may further decompose into shorter-chain alcohols, alkanes, and alkenes and enhance the production of VEA vaping emission products. Phytol is known both as a precursor for the synthesis of VE and vitamin K12, as well as a byproduct of chlorophyll degradation . Inhalation of aerosolized phytol has previously been shown to induce lung injury in exposed rats. In addition, phytol is a long chain alkyl alcohol compound, meaning that it has the potential to induce damage to the membrane of cells in a biological system. Overall, the toxicity of phytol raises questions about the safety of vaping not only VEA but cannabis-containing vape products that may result in phytol production.

These results clearly indicate that the product distributions of VEA vaping emissions are highly dependent on the operating temperature of the vape pen. As a result, the exposure for vape users operating the same e-cigarette products at different temperatures may differ significantly.Previous reports of VEA pyrolysis indicate that VEA begins to degrade starting at ~200–240˚C. However, our results clearly demonstrate degradation of VEA and formation of products such as DQ at 176˚C, indicating that the device itself may play a larger role in the decomposition of VEA than initially anticipated. Previous study in our lab has also found substantial formation of DQ at 218˚C–several hundred degrees lower than what has been predicted. To further understand if the device itself may impact the thermal degradation of VEA, pure pyrolysis of VEA oil was carried out using a tube furnace reactor. After 75 minutes, the average mass loss of VEA heated at 176, 237, 322, and 356˚C was found to be 0.11 ± 0.091, 0.37 ± 0.11, 3.7 ± 0.072 and 7.1 ± 0.0016 mg of VEA consumed. At 176 and 237˚C, VEA was fairly stable; substantial consumption of VEA oil was not observed until the two higher temperatures, despite clear consumption at all temperatures during the vaping collection. Fig 6 demonstrates the product distribution of VEA degradation products collected and analyzed using GC/MS. Here, we did not observe substantial thermal decomposition of VEA when heated at 176˚C for 75 minutes, which greatly contrasts with the degradation of VEA at 176˚C for only 4 s during the vaping collection. At 237˚C, the parent VEA molecule was the only detectable emission product, indicating that VEA again did not degrade at this lower temperature, though 237˚C was enough to evaporate VEA so that it could be collected in the cold trap. Degradation products were only detectable from samples collected at 322 and 356˚C, though the number of products and abundance of observed peaks are drastically reduced when compared to the vaping emissions. It should be noted that the tube furnace is capable of heating VEA at more accurate and consistent temperatures than the vape pen itself, which often saw temperature fluctuations that may influence results. The stark difference in product distribution provides evidence that VEA vaping emissions may not be the result of pure pyrolysis alone. Instead, external factors such as the device elements themselves or environmental interactions may play a role in the catalysis of VEA degradation.

Diffusion-weighted MRI of tissues provides a quantitative measure of the apparent diffusion coefficient of water, instead of estimations of water mobility from relaxation measurement that include the influence of translational mobility, composition and other factors . In addition, a spatially resolved map of the apparent diffusion coefficient of water can be obtained, which could help to understand and quantify the development of disorders such as CI within the tissue. MRI has been used to gain insight into early phases of different post harvest physiological disorders before the manifestation of external symptoms . These include core breakdown in pear water core disorder , internal browning and mealiness in apple . There are few reports where MRI was used to detect the early stages of CI in sensitive produce. In persimmon, MR images of cold-stored fruit were distinct from those stored at ambient temperature . In zucchini squash , MRI provided enough data to act as a predictor of where water soaking would occur in the epidermis after the cold-storage. These studies both indicated that MRI has great potential for studying CI in fruit tissues. Tomato is one of the most important horticultural crops both economically and as a genomics, molecular, biochemical, and physiological model for biological processes occurring in fleshy fruits . Like most subtropical fruit, tomato is susceptible to CI. Studies with tomato fruit could leverage existing functional genomics resources to pinpoint the molecular basis of this trait. To our knowledge, MRI has not been used to study CI in this species. We used the dwarf cultivar ‘Micro-Tom’ because it is the functional genomics model for tomato . Its high-density growth, short life cycle and concentrated fruit-set makes it possible to obtain harvests of 500 fruit or more per square meter per year . Because tomato post harvest studies can be hampered by biological variability ,cannabis grow lights the availability of numerous, similarly aged fruit makes Micro-Tom a convenient experimental model for post harvest studies .

Furthermore, we have previously characterized Micro-Tom fruit physiological response to a range of post harvest chilling temperature-time combinations , and used this information to design a metabolomics investigation of CI. This has established a baseline with this cultivar for the further CI studies we exploit here. The specific objective of this study was to determine if MRI could detect some of the earliest physiological changes that accompany CI in tomato fruit. Current methods of assessing the occurrence and severity of CI are: time consuming , destructive , or occur only after the activation of secondary, downstream events . These methods are time-proven and are indispensable, but there is a need for non-destructive methods with equivalent or better sensitivity to those currently used. MRI potentially offers such advantages and could be an important complementary tool for studying incipient CI. We show that MRI can provide spatio-temporal resolution of chilling induced changes in MicroTom tomato fruit prior to development of downstream symptoms.Chilled fruit were removed from 0 ◦C and allowed to slowly warm to 20 ◦C before CO2 and ethylene production were measured.These jars were sealed for 1 h and a 1-mL sample of the head space was withdrawn using a syringe and its CO2 concentration was measured with an infrared gas analyzer as previously described . Ethylene production was measured from a 2.5 mL sample of the head-space using a Gas Chromatograph equipped with a flame ionization detector. These two samples were taken within 30 s of each other from the same jar.Each fruit was cut into four radial segments, cleaned of adhering locular tissue, washed for 5 s in running tap water, blotted dry, and one segment was placed in each sector of a 4-sectored Petri dish under aseptic conditions. The dishes were placed in plastic tubs lined with wet paper towels and loosely covered with aluminum foil. The tubs were held at 12.5 ◦C for 18 h to produce ‘aged’ tissue, i.e., to allow the tissue to overcome the wound-induced alterations in membrane permeability . After transferring to room temperature for 1 h, the four aged segments from each Petri dish were put into a 50 mL plastic centrifuge tube containing 20 mL of an aqueous solution of 0.2 M mannitol.

Preliminary experiments determined that 0.2 M was isotonic for these excised radial segments The conductivity of the bathing solution was measured with an Extech Model 480 digital conductivity meter every 5 min for 30 min and then less frequently for 180 min with gently shaken between readings. After 3 h the tubes were capped, frozen at −20 ◦C and warmed to room temperature and frozen and thawed twice before the total conductivity of the solution was measured at room temperature after 1 h of shaking. Ion leakage was expressed as percent of total and plotted over time. The linear increase in ion leakage from 0.5 to 2.0 h was used to calculate the rate of ion leakage .The aim of this study was to examine the extent to which MRI could detect changes in chilled Micro-Tom tomato fruit. Based on our previous data using Micro-Tom , fruit were stored at 0 ◦C in the dark for 0 , 1, or 2 weeks, and the fruit that were chilled for 2 weeks were held for 1 week at 20 ◦C. The onset of CI was evaluated using changes in respiration, ethylene evolution and ion leakage . One week of chilling increased all of these indicators to levels that were maintained during an additional week of cold-storage . In fruit transferred to 20 ◦C after 2 weeks of chilling, the rate of respiration returned to that of the pre-chilling levels, ion leakage remained at the same elevated levels and ethylene production continued to increase. A sustained rise in ethylene production upon warming after chilling is characteristic many chilling sensitive tissue . MRI provided data that allowed the spatial resolution of the internal changes in chilling-induced fruit that were not available using conventional methods. ADC maps of an equatorial section of a tomato are shown in Fig. 1a. These heat maps indicate changes in water mobility, which increased during and after chilling; presumably because of chilling-induced disintegration of membrane integrity. After chilling at 0 ◦C for one week, the amount of voxels in the entire fruit in the yellow-red range increased compared with that of the non-chilled fruit . This general trend continued during two weeks of cold storage .

However, when these fruit were transferred to 20 ◦C, the number of yellow-red voxels throughout the slice decreased in the pericarp, but less so in the center of the fruit. Quantitative data better illustrate differences among tissues . When compared with the pericarp,cannabis grow tent the inner tissues showed higher signal frequencies at greater ADCs after 2 weeks refrigeration followed by room temperature storage relative to the controls . D-values were calculated for the whole fruit in order to make comparisons with ethylene and respiration data obtained from whole fruit. These values were higher in one week-chilled fruit compared with other storage periods . After two weeks at 0 ◦C and with further storage at 20 ◦C, the D-values were similar to the control . An increase after 1 week of chilling was also observed in carbon dioxide, ethylene evolution, and ion leakage . However, while these criteria remained higher than those in the non-chilled control fruit, the D-values declined relative to those in the control . The mean D-values of distinct spatial regions of the fruit were then calculated. No changes from the control were recorded in the pericarp after chilling for 1 or 2 weeks at 0 ◦C . However, after an additional week of storage at 20 ◦C, D-values decreased to levels observed in the non-chilled control. This may be indicative of the ability of marginally chilled tissue to repair the chilling-induced physiological damage that accumulated during chilling when warmed to non-chilling temperatures . There was little correspondence between changes in these D-values and changes in membrane ion leakage values; which were both derived from pericarp tissue . Ion leakage increased after cold exposure while Dvalues did not. There was some variability in pericarp ADC-values as mentioned earlier; cold-stored fruit varied compared to those reconditioned at 20 ◦C . Even when percent membrane permeability in the pericarp was considered over shorter time intervals, e.g., 15, 25 min, etc., changes due to chilling were still asynchronous with pericarp D-values . For the interior columella and locular tissues, the D-values increased after 1 week of chilling and remained at this elevated level for the remainder of the storage period . This response was significantly different from that of the pericarp. When the controls were compared to fruit kept in the cold for 1 and 2 weeks, D-values for interior tissue correlated reasonably well with changes in respiration and ethylene production . However the inner fruit D-values showed an identical pattern to changes in ion leakage, which is a destructive assessment of pericarp changes . This suggests two possibilities: that each individual assay acts as a proxy for similar underlying biological processes, but that they each encapsulate some divergent mechanisms, or that in response to cold, the pericarp and inner fruit may be modulated in different temporal time frames with varying amplitudes.Membrane disintegration and the subsequent physiological changes in chilled fruit may promote higher water mobility detected as increased D-values. Interpretation of these data suggest that the sensitivity and responsiveness to chilling differs between the pericarp and core tissues. This may arise due to the physical distance from the epidermis to the fruit center. An endogenous temperature gradient may be imposed across the fruit creating an inherent delay in the response and any subsequent adaptation to cold, between pericarp and core tissues. Although this possibility cannot be ruled out, the relatively small diameter of Micro-Tom fruit should minimize this effect.

Of more importance may be the heterogeneous nature of the fruit tissues. Differences in their physiochemical properties and functionalities could produce different biological outcomes to chilling. The realization that fruit responses to cold are asynchronous should inform our view when designing and interpreting data from experiments to study chilling injury. The aim of the experiments described here was to explore basic fruit post harvest biology using MRI and thereby gain new insight into CI.While not fast enough for commercial use,the MRI scan time of 27 min were still much faster than the more than 3 h needed to measure respiration, ethylene evolution and ion leakage. In addition to being faster, MRI also provides spatially resolved data. A long-term goal would be to refine this technology to enable its practical application as an economical, robust and rapid on-line detector of post harvest disorders in packinghouses or even along the supply chain. This would allow each stakeholder to have better control over produce quality. Examining the response of different cultivars that vary in fruit size, pericarp thickness, ratio of columella to locular tissues, and sugar to acid content, and to a variety of low temperature in cubations will also be necessary to facilitate MRI’s adoption in commercial settings.Tomato is the world’s second largest vegetable crop rich in nutrients. Tomato fruit development includes three stages. The first stage is characterized by an increase in cell number and starch accumulation, followed by cell enlargement with starch degradation and soluble sugar accumulation in the second stage. Fruit ripening is the last stage, associated with the accumulation of soluble sugars, carotenoids, organic acids, and volatile organic compounds in fruits. The chlorophyll accumulation and photosynthetic activity of green fruits influence the nutritional components and flavor of ripening tomato fruits. Some genes have been reported to affect chlorophyll accumulation, chloroplast development and fruit quality. As negative regulators, DE-ETIOLATED 1/high pigment 2 and UV-DAMAGED DNA-BINDING PROTEIN 1/ high pigment 1 are involved in chloroplast formation and chlorophyll accumulation in tomato fruits. The tomato GOLDEN2-LIKE transcription factors SlGLK1 and SlGLK2 play an important role in chloroplast formation and chlorophyll accumulation.Evidence suggests that the SlGLK2 gene is predominantly expressed in fruits and that the latitudinal gradient of SlGLK2 expression influences the production of unevenly colored tomato fruits. Over expression of the APRR2- LIKE gene, the closest homolog of SlGLK2, increased the size and number of chloroplasts and enhanced chlorophyll accumulation in green tomato fruits.

However, during follow-up the ICBT group had relatively greater increases in percent-network abstinent, and greater decreases in mean-network drug use and percent-network using drugs. Effects of group, time, and group x time were not statistically significant for self efficacy or the remaining social network variables. Overall the two treatment groups had few differences on process variables, with the exception of social network drug use. Finally, the effect of time was negative and statistically significant for controlled context , indicating an overall decrease over time in the proportion of time spent in controlled contexts, a trend that did not differ between treatment groups. We then examined whether self-efficacy and social network variables prospectively predicted post-treatment alcohol and drug use. Separate HLMS for each process variable tested associations with substance use outcomes , controlling for previously mentioned covariates. Each time-varying predictor was lagged and decomposed into two distinct variables to disaggregate between-person and within-person effects on PDD and PDDRG. Social network variables were substance-specific, with network drinking predicting PDD and network drug use predicting PDDRG. Results of these models are displayed in Table 10. With one exception , all between-person effects were statistically significant. Moreover, individuals with social networks characterized by lower mean use and a lower percentage of regular users had lower PDD and PDDRG during follow-up, and those with greater percent-network abstinent from drinking had lower PDD. For within-person effects, greater mean network drinking and greater percent-network drinking predicted PDD, indicating that fluctuations from the person- mean in these variables predicted drinking in the next 3 months. We then determined whether the amount of time spent in controlled contexts was associated with post-treatment substance use.

These HLMs tested the time-varying effect of controlled context on concurrent PDD and PDDRG, controlling for identical covariates as previous models. The results, displayed in Table 10,cannabis drying racks indicate that a greater proportion of time spent in controlled contexts was associated with significantly lower PDD and PDDRG during these same periods. At month 18 veterans with 0% days controlled had an estimated PDD of 18.19. Estimated PDD was lower for those at the mean of controlled context , and even lower for those 1 standard deviation above the mean . These results confirmed that the percentage of time spent in controlled contexts was significantly and negatively associated with frequency of current substance use. Final models included interactions between lagged process variables and controlled context, to test hypotheses that percent-days in controlled context would moderate the effects of lagged process variables on PDD and PDDRG. As displayed in Table 10, between-person effects for each social network drinking variable interacted significantly with controlled context to predict future PDD. Also, between-person effects for mean network drug use and percent-network regularly using drugs interacted with controlled context to predict future PDDRG. As displayed in Figure 1, social network effects on future PDD and PDDRG were weaker when time in controlled context was high. Controlled context did not significantly moderate self efficacy or within-person effects. Overall, these results indicate that social network characteristics of veterans with substance dependence and MDD predicted future drinking and drug use, but these predictive effects were weakened when veterans lived in controlled contexts for extended periods of time. Prior studies of determinants of post-treatment substance use have not typically focused on individuals with SUDs and co-occurring psychiatric disorders, despite high rates of these co-occurring disorders in many clinical settings . Co-occurring MDD is particularly common, and individuals with SUD and MDD typically have poorer outcomes following treatment and may receive less benefit from therapeutic mechanisms of change . Because they represent a large proportion of patients receiving substance dependence treatment and have a greater risk of poor outcomes, it is critically important to examine determinants of post-treatment substance use within this population.

In a sample of veterans who had received group outpatient psychotherapy for substance dependence and MDD, we examined self-efficacy and network substance use, the effects of controlled contexts, and their interaction in the prediction of post-treatment drinking and drug use. In this sample with substance dependence and MDD, individuals with greater self-efficacy had lower future drinking and drug use during the year following treatment. Self-efficacy has predicted post-treatment use across various substances and treatment settings , and our study extends these findings to patients with substance dependence and MDD. By separating the between-person and within-person components of self-efficacy, we demonstrated that generally maintaining higher self efficacy was protective against future substance use, while time-specific fluctuations in self-efficacy were less critical. Prior studies with this sample revealed that baseline self efficacy predicted time to relapse and self-efficacy increased significantly during treatment . Our results were encouraging in finding that during the year following treatment, self-efficacy did not decrease significantly and continued to predict substance use. Moreover, post-treatment self-efficacy was similar between ICBT and TSF, suggesting that self-efficacy can be sustained similarly following cognitive-behavioral or professionally-led, 12-step based interventions, replicating prior research . Our results support the value of abstinence self-efficacy for patients with substance dependence and MDD, and provide a strong rationale for investigating factors related to increasing self-efficacy within this population. Substance-specific social network variables were also predictive of post-treatment substance use. For both alcohol and drugs, future frequency of use was lower for individuals who generally had 1) lower average network use and 2) a lower proportion of regular users in their network. Furthermore, having a network with a greater density of non-drinking individuals predicted lower future drinking.

These social network characteristics have previously predicted drinking outcomes in alcohol-dependent samples , but our study is first to demonstrate these findings in patients with substance dependence and MDD. Social network effects at the within-person level were also predictive of substance use. More specifically, when individuals had increases from their own norm of average network drinking or proportion of regular drinkers, they drank more frequently in the future. It is likely that these interpersonal factors operate in multiple ways to influence future drinking . The presence of alcohol or other drinkers represent conditioned cues that elicit craving or other precipitants to drinking, and associating with drinkers may increase exposure to substances or undermine patients’ sobriety efforts via changes in outcome expectancies. Treatment protocols designed explicitly to change social networks have demonstrated long term efficacy in the treatment of alcohol dependence . These interventions have not been tested in patients with co-occurring psychiatric disoders, and our study suggests these interventions could be effective in patients with substance dependence and MDD. This study also found that post-treatment substance use depended on the level of constraint in the living environment. During follow-up over half of our sample had some time in “controlled contexts” at an average of 39% of days in these environments. As hypothesized, when patients spent a greater percentage of time in controlled contexts defined by limited access to substances or negative consequences for use, they had lower frequency of drinking and drug use. Moreover, controlled context acted as a moderator,cannabis grow tray such that social network influences were more predictive of future alcohol and drug use when the environment did not restricted. Social network effects were attenuated for veterans at the highest levels of controlled context, suggesting these contexts do assist in buffering against the maladaptive influence of substance use within the network. Research indicates that patients with substance dependence and MDD are especially likely to utilize inpatient/residential services . The role of environment is rarely examined in treatment outcome studies, which is surprising given theoretical interest in considering intrapersonal and interpersonal processes within environmental context . Our results suggest the level of constraint in the environment is an important construct to consider in future studies. While some 3 controlled contexts may have resulted from adverse events , the most common contexts utilized were residential sober living facilities. Our results suggest patients with substance dependence and MDD who cannot sustain more protective social networks may benefit most from these constrained environments. While this study has important research and clinical implications, its limitations should be noted. The immediate generalizability of these findings is limited due to the demographic characteristics of this veteran sample, which was heavily comprised of Caucasian males. While this is a common limitation of many clinical trials of treatments for addictive disorders , replication in more diverse samples is needed before broader generalizations can be made. Our social network measure did not capture important features of social support examined in prior studies , such as whether network members were supportive of our patients’ abstinence efforts. Furthermore, network members’ use patterns were reported as perceived by study participants, and may not be a completely accurate assessment of their substance use patterns. While the effects of controlled contexts were in the expected direction, context alone may not fully explain our findings as this variable could be confounded with other unmeasured characteristics that are also strong determinants of abstinence.

While this study identified variables that predict post treatment substance use in adults with co-occurring substance dependence and MDD, underlying mechanisms have not yet been identified, which would explain how patients sustained greater levels of self-efficacy and lower levels of network substance use. As such, it will be important for future studies to explore whether specific processes of treatment assist patients in maintaining greater levels of these proximal variables following the conclusion of formal intervention. Study 3 has been submitted for publication in Alcoholism: Clinical and Experimental Research, as following: Worley, M.J., Tate, S.R., & Brown, S.A. Self efficacy, social networks, and the moderating effects of context following treatment for co-occurring substance dependence and depression. The dissertation author was the primary author of this manuscript under review. Many individuals with alcohol or drug dependence have deficits in neurocognitive abilities such as executive functioning and problem solving , verbal or non-verbal memory , cognitive efficiency , and attention , whether these deficits are due to the neurotoxic effects of substance use, preexisting characteristics, or some combination of both . In clinical settings these deficits are especially prevalent as 30-80% of patients enter treatment with some neurocognitive impairment . Although modest recovery in neurocognition is possible, these changes are often not clinically significant and many deficits do not remit even after periods of extended abstinence . Because neurocognitive impairment is so common and persistent, there is a strong rationale for examining whether impairment relates to treatment outcomes within the substance-dependent population. Another factor that may compound these neurocognitive deficits is the presence of other psychiatric conditions. Comorbid psychiatric disorders are common in the substance-dependent population , especially among patients in treatment settings . Major depression is recognized as the most common Axis I condition, and patients with comorbid MDD typically have poorer outcomes from treatment for alcohol or drug dependence . Importantly, MDD is also associated with deficits in working memory, attention, verbal memory, verbal fluency, and processing speed . Consequently, the joint effects of substance dependence and MDD on cognition may be worse than in either disorder alone, as with comorbid substance dependence and bipolar disorder . Despite the prevalence of comorbid substance dependence and MDD and the deficits associated with both conditions, the effects of neurocognitive impairment in patients receiving treatment for substance dependence and MDD have not previously been examined. Psychological treatments for substance dependence often require patients to learn and retain new information, inhibit prepotent responses, engage in future-oriented behavior, and plan behavioral coping strategies. Theoretically, patients with neurocognitive deficits would be less adept at internalizing and engaging in these skills, leading to poorer outcomes from psychotherapy. Some studies support this hypothesis, as patients with poorer cognitive functioning had greater substance use or lower retention in cognitive-behavioral therapy . However, these effects have not been consistent across studies, as many investigations failed to find associations between neurocognition and substance use during or following treatment . While some methodological differences exist between these studies , it is equivocal whether cognitively-impaired patients have poorer outcomes from substance dependence treatment. An important distinction within this literature is whether neurocognitive impairment is best examined as a direct predictor of outcome, or whether different model specifications are more ideal for testing relations with substance use . This notion is supported by studies demonstrating that impairment does not predict outcomes directly, but impacts substance use indirectly through therapeutic mechanisms of change.