Cannabis Grow

Such risk assessment approaches can and have been applied to environmental odors. Unlike risk assessment of toxic chemicals, odor studies can include human panels. Risk assessment is directly applicable to the investigation of health risks from odors .The objective of this thesis is to conduct a critical literature evaluation, supplemented with interviews of odor experts and investigators, of scientific methods to investigate environmental odors and assess their health impacts. The overall aim is to improve the state of knowledge of a complex, multidisciplinary topic. In an effort to further advance the field of odor investigation, advice and concepts from the overlapping field of risk assessment will be applied, when appropriate. A review of the health impacts of environmental odors, which is information frequently requested by the public during odor investigations, concludes the review. The focus of this thesis is on nuisance odor investigations of existing facilities rather than predictive modeling used for permits of new or modified facilities. Much has already been written and reviewed on such predictive dispersion models and odor mapping . While such modeling is the most common approach, other approaches include maximum separation distance, maximum emission, plant grow table maximum annoyance and best technology requirements . It is likely that, in large part, the poor track record of these approaches has led to the need for nuisance odor investigations.

Indoor sources of odors are also beyond the scope of this thesis, as are occupational exposures to odors, except for the final chapter on health effects where the information is highly valuable for public health. Odors from emergencies and accidents are also not central to the thesis. The thesis is organized around increasing use of risk assessment to inform nuisance odor investigation. Chapter 2 on regulations and techniques used around the world to investigate nuisance odor complaints only employs some of the basic risk assessment concepts. Chapter 3 on odor exposure assessment falls within the risk assessment framework. Chapter 4 on the health risks from environmental odors is entirely consistent with and reliant upon risk assessment. Each chapter also identifies best practices, gaps in current knowledge and provides suggestions on how such gaps could be filled. Chapters 2 to 4 are presented as journal-ready publications. Chapter 5 ends the thesis with concluding remarks. Fugitive emissions from such industries can lead to odor complaints due to the extremely low sensory thresholds. Further, upsets and their associated larger releases are especially problematic at oil refineries , where it can take a long time to fix the problem. Historically, odors have been regulated under public nuisance law or when permitting a new or modified facility by conducting dispersion modeling within a theoretical odor impact assessment. The latter approach is outside the scope of this paper because it has been reviewed elsewhere . The use of dispersion modeling within a theoretical odor impact assessment has only achieved partial success as evidenced by the ongoing volume of odor complaints. Odor as regulated under public nuisance law for existing facilities, rather than proposed new or modified facilities, is the focus of this paper. Public nuisance law originated in British Common Law. Such law distinguishes between “private nuisance” and “public nuisance” . Almost always, nuisance odor complaints fall under the latter category rather than individual rights .

To address nuisance odor complaints, regulators may set subjective or objective standards. Based on population-based health studies of toxic air pollutants, objective standards have been set for pollutants. Odors, however, are multidimensional and require difficult-to-enforce standards. Unsurprisingly, the setting of odor standards varies greatly throughout the world and depends heavily on the industrial sector, type of activity generating the odor and level of public outcry. Applying public nuisance law to odors has been criticized : “A direct measure of annoyance is typically made by an inspector or authorized officer of the state, and if there are no complaints there is by definition, no problem. The inherent subjectivity built into the approach is a problem, as is its susceptibility to political influence or community pressure. It lacks continuity of regulation for both the community and the industry concerned and does not offer a ‘target’ for the design and management of odor control systems.” As an alternative, odor intensity limits have been set in some jurisdictions. Such limits remain sensory-based, bringing with them the inherent variability in human responses to odors, and typically are set at a certain number of volumes of odorless air required to dilute one volume of sample air until the odor is no longer detected by 50% of panelists . Dynamic dilution olfactometry, which requires a dilution instrument and evaluation by a trained panel, is typically used to set this limit.A team of Brazilian and Australian researchers published a recent, comprehensive review of odor regulations from around the world . Their survey of 28 countries primarily focused on the dispersion modeling and criteria applied to new and modified facilities emitting odorous gases. Such regulations typically set limits to emissions and setback distances based on the theoretical calculations of odor impact. They often also require that “best available technology” be implemented.

This regulatory approach is not the focus of this paper; nonetheless, the authors also covered, to a lesser degree, regulations and methods to investigate odor complaints from existing facilities, which have been tabulated .The U.S. federal government, under the Clean Air Act, does not regulate odors as airborne pollutants. That leaves odor regulation to the states. Odor regulations in 42 of the 50 states are addressed by nuisance law . The federal government, however, has provided general guidance regarding nuisance odors and their impacts . The National Research Council and the National Academies of Sciences, Engineering, and Medicine provide scientific guidance to the federal government. In the 1970s, the NRC pioneered guidance on odors . The conclusion was that odors would be difficult to regulate due to their variable adverse effects on people, standards would not be widely accepted and the two sets of data are difficult to relate toeach other, costly and time consuming. If enacted, odor standards would need to be related to a measurement of odor perception that is compared with the intensity of a specified concentration of a standard reference odorant. Duration and frequency of exposure, as well as offensiveness, should be considered. In 2014, the Agency for Toxic Substances and Disease Registry launched a web page to provide a series of documents and videos dedicated to environmental odor effects and management,hydroponic table including a reference list of 684 odorants and their sensory descriptors . For this list, ATSDR initially compiled a list of chemicals that the food and beverage industries use in production. ATSDR then added other chemicals that trained professionals or large numbers of people agree have a distinctive odor. Similar odor information has also been compiled by researchers into odor wheels . A distinctive odor can indicate the potential source and even the specific key odorants. This has helped solve odor complaint problems from landfills, trash transfer stations , composting facilities and wastewater treatment plants .Based on the information gathered from around the world, a targeted literature search and phone interviews of odor experts and air inspectors were conducted to provide current perspectives on odor investigations. Literature searches were conducted online and at the University of California, Los Angeles, and California Air Resources Board physical libraries. The focus was post-2010, and when relevant articles or books were found the “cited by” function was used to find even more up-to-date information. A California-specific literature search was conducted as well. Reviews of the latest approaches to odor investigation were sought. Finally, relevant websites and posted materials not typically available in scientific journals were searched.

To collect the latest information on nuisance odor investigations from California’s air districts and international experts, phone interviews were conducted. The interviewees’ insights were gathered and any available guidance documents and relevant case studies were requested.CARB has a long history of addressing nuisance odor complaints. In the 1970s, questionnaires were used to collect information from residents near pulp mills on exposure to the odor and on health and annoyance reactions . In general, the frequency with which odor was noticed and the frequency and intensity with which respondents were bothered by the odor were correlated with perceived odor intensity and frequency as measured by dynamic dilution olfactometry within each community. More recently, an agreement was formed between CARB and the local air districts regarding the handling of odor complaints . It stated that CARB handles mobile source odor complaints and, for stationary sources, the local air district is phoned as soon as possible, but at least within one business day. It then gives local air districts 15 working days after receipt of the CARB letter to provide a written complaint resolution or summary progress report. Finally, CARB agreed to subscribe to an over-the-phone verbal translation service that it would make available to the local air districts. Several of the local air districts were contacted to gather information on how they currently investigate nuisance odor complaints. The information gathered is summarized next. One observation during the interviews was that CARB trains the air district staff on smokestack opacity measurements using their own eyes . Training regarding environmental odor evaluation could be developed as well. A key phrase is “considerable number of persons,” which is evaluated case-by-case but generally falls into 6 to 10 complaints within a 24-hour period for a notice of violation. Rule 402 does not apply to agricultural operations. In 2008, SCAQMD Rule 410 took effect to address odors from trash transfer stations and material recovery facilities. Sufficiently large facilities were required to have an approved odor management plan with extra requirements for even larger facilities. In 2009, a panel of 10 air inspectors used odor profiling to evaluate a trash transfer station . Based on the observed odors, specific odorants were suggested and then confirmed analytically. In 2017, SCAQMD adopted Rule 415 to address odors from rendering facilities . The rule requires building enclosures with ventilation to odor control systems for odorous operations and best management practices, such as covers for trucks and trailers and time limits for moving materials during the receiving and rendering process. Also in 2017, Rule 1430 was adopted to reduce odors from grinding operations at metal forging facilities . Four confirmed odor complaints over six months trigger additional odor management controls, such as enclosures. A conversation with air inspectors covered how nuisance odor complaints are currently investigated. Air inspectors use their own noses to confirm the complaint, which does not necessarily need to match the complainant’s description of the odor. Each person’s ability to describe odors varies too greatly to require consistent descriptions. Rather, sensing that “something” is there is sufficient. The next step is to identify the source and move upwind to verify that the odor is not coming from elsewhere.They are trained on how to respond by pairing junior staff with more senior mentors. For more complex odors, monitoring and meteorological data are used. Hydrogen sulfide monitors have been used for direct measurements and SUMMA evacuated canisters and Tedlar™ bags have been used to collected air samples. Sometimes a SUMMA canister is given to a complainant to collect a sample over time. Wind direction, speed and temperature are measured using a hand-held Kestrel 1000 meter, and the cloudiness and weather are noted. More sophistical meteorological data has been used to calculate the back-trajectory of odor plumes using data from the National Weather Service in Meso West plus the HYSPLIT dispersion model. Odor investigation data is captured in an in-house database that is rather old and does not allow for easy queries. Since 2010, the number of odor complaints per year has risen from around 3,400 to 7,500, decreasing in 2017 to 6,000 . Odor complaints are received by phone or via their website, which is also available through their app.No electronic nose technology is currently used although a report surveyed dozens of emerging technologies . The authors noted that e-noses were primarily used for quality control for food and other products, and that a large effort would be required for field tests for environmental odor detection.

The identified increase in variance explained by PTSD emphasizes that PTSD is a significant predictor of later addiction severity among individuals who face early substance use problems. These results are consistent with previous research, which associated early childhood experience of trauma with early substance use onset and transition to poly drug use . Additionally, previous handful evidence has consistently established associations between SUD and PTSD and provided explanatory hypotheses underlying these associations. Given that at SSA populations such Rwandans had experienced horrific events , these results may be interpreted through well-documented risky use of psychoactive substances for coping with post disaster distress . However, it is challenging to delineate which of the two conditions occurs first because SUD and PTSD affect the stress processing system. Chronic SUD, such as alcohol use disorders, increased individual vulnerability to PTSD due to alcohol related defects of endocrinal response to distress events and reduced cortisol release . On the other hand, PTSD influences neurotransmitters changes, such as serotonin, in the hypothalamic-pituitary-adrenaline axis, which have been linked to risks for worsened SUD . The identified positive association between level of education and addiction severity may be partially explained by the Rwandan cultural and conception of mental illness. Cultural expectations are strict on the use of alcohol that interferes with social and professional functioning . Thus,vertical hydroponic garden educated people may find it challenging to seek early help for their SUD due to fear of being subject to attached stigma and use psychoactive substances as self-medication.

The present study, to our knowledge, is the first to investigate the contributions of age, motives for first substance use, and post traumatic distress to later addiction problems using a clinical sample in sub-Saharan Africa. The study used a compelling alternative to the random sampling strategy, recruiting every participant presenting for inpatient addiction care in two existing settings over 8 months. This study has a few limitations, including relying on self-reported data that may be prone to recall and social desirability biases. However, we attempted to minimize these biases by collecting data through face-to-face semi-structured interviews conducted by trained and qualified mental health professionals who were not part of a healthcare circle .Underlying its clinical symptomatology, schizophrenia is characterized by a disturbance in the regulated processing of environmental information . Especially notable are impairments in identifying and responding to stimuli that are either salient or novel. The P300 event-related potential is a physiological index of the cognitive processes elicited by such task-relevant or novel deviant stimuli.However, the scalp-recorded P300 response to an auditory target stimulus – also referred to as P3b to differentiate it from the P3a orienting response to novelty – arises primarily from inferior parietal and supramarginal cortical regions . Reduced amplitude of this response is one of the most robust physiological abnormalities associated with schizophrenia, being replicated across hundreds of studies with a relatively large effect size . Although P300 amplitude varies to a certain extent with fluctuations in clinical symptomatology , it also exhibits characteristics of a trait-like disease marker. The measure has relatively high test-retest reliability , and the patient deficit persists regardless of the level of acute symptomatology or psychotropic medication . There is also strong evidence implicating a genetic contribution to P300 amplitude in both healthy subjects and patients . Thus, P300 amplitude meets the essential criteria for a schizophrenia endophenotype .

Historically, an impediment to the utility of the P300 as a schizophrenia biomarker has been its lack of specificity. P300 is disrupted in a variety of neuropsychiatric disorders associated with cognitive impairment. These include, among others, Alzheimer’s disease , alcoholism and affective illness . Additionally, the P300 response is influenced by a variety of factors, independent of clinical diagnosis. Most notable among these are age and sex; P300 amplitude is smaller, overall, in men and exhibits both reduced amplitude and prolonged latency in the elderly . It is also altered by both the acute and chronic administration of various psychoactive substances. P300 amplitude is smaller in active smokers compared to nonsmokers, and this decrement reflects both the current number of cigarettes smoked per day and the number of years of continuous smoking . It is similarly reduced following acute administration of marijuana , alcohol , and cocaine , and among chronic users of these substances . In contrast, the effect of antipsychotic medications, among schizophrenia patients, appears to be relatively inconsequential . Another potentially important factor that has only rarely been considered is race or ethnicity, and the little evidence that exists concerning this has been inconclusive . Given the frequent co-occurrence of schizophrenia with other co-morbid neuropsychiatric and substance use disorders, as well as the differences in smoking prevalence and racial stratification that is often found in schizophrenia patient vs. healthy control samples, a comprehensive understanding of the impact of such modulating factors is critical to enhancing the utility of P300 as a disease-specific schizophrenia biomarker. Recently, with the advent of studies of the schizophrenia prodrome, the importance of the P300 as a putative biomarker has taken on added significance. There is now substantial evidence that P300 amplitude is reduced in “high-risk” individuals with prodromal symptoms, prior to illness onset . Importantly, within a high-risk cohort, P300 appears to be a sensitive predictor of which individuals will, in fact, transition to frank psychosis. Moreover, the degree of impairment indicates the proximity of illness onset . The greater the magnitude of the amplitude reduction, the more likely that psychosis onset is imminent. P300 amplitude assessment may, therefore,plant bench indoor play an important part in the clinical evaluation of at-risk individuals.

However P300 studies have thus far been confined primarily to academic neurophysiology laboratories, and data analyses have been limited primarily to between-group comparisons of measures acquired in one laboratory under identical conditions. It is thus unclear whether specific values obtained in one experimental setting can be compared or co-mingled with values obtained in another setting under less-than identical conditions. The ability to aggregate quantitative data across multiple sites is critical to the strategy employed by the Consortium on the Genetics of Schizophrenia to identify the genetic substrates of disease endophenotypes. It is also critical to the utility of this measure as a specific predictive biomarker of impending psychosis. The purpose of the current analysis was therefore, first, to determine if a standardized P300 data acquisition system could be successfully deployed to multiple settings without on-site electrophysiology expertise. We assessed the overall usability of the ERP data and the ability to detect known schizophrenia deficits. We also considered the consistency of measurements across five COGS-2 sites, and examined various socio-demographic modulating factors that can contribute to measurement variability. As noted, a careful understanding of the quantitative impact of these modulating factors is an important prerequisite to any interpretation of a specific set of measurements. Healthy control subjects and schizophrenia patients were enrolled in the COGS-2 endophenotype study at 5 sites, as detailed in the introductory article of this Special Issue . Briefly, all participants were assessed using a modified version of the Structured Clinical Interview for DSM-IV-TR , Modules A-E . All patients met criteria for either SZ or schizo affective disorder, depressed subtype. HCS were excluded for any history of a psychotic disorder in either themselves or a 1 st-degree relative, a current Axis I mood disorder, a Cluster A Axis II disorder, or current psychoactive medication use. Subjects were also excluded for any medical or neurological condition that could interfere with endophenotype assessment, history of substance abuse in the past month or substance dependence in the past 6 months, or a positive toxicology screen at the time of testing. Clinical and demographic characteristics of the P300 sample are presented, by site, in Table 1. Specific past substance related diagnoses are detailed in Table 2. Adjunctive psychoactive medications used by patients are listed in Table 3. In addition to the structured clinical interview and the various endophenotype measures, all subjects were assessed with the Mini-Mental Status Examination and the Global Assessment of Functioning Scale . Patients were further assessed with two measures of functional capacity: the 15-item clinician rated Scale of Functioning, and the UCSD Performance-based Skills Assessment-Brief , which directly assesses an individual’s capacity in multiple domains of everyday functioning through the use of props and standardized skill performance tests.

There were significant group differences in age , sex and racial composition . There were also significant site differences for each of these measures, and group × site interactions for age and sex. As expected, patients and controls differed on education, GAF, and MMSE scores. There were also significant main effects of site and group × site interactions for both GAF and MMSE. Site differences were also evident for rates of past substance use, major depressive disorder, and nicotine use. Among patients, site differences were observed for duration of illness, age of onset, and current symptomatology . This variability indicates that different sites drew their samples from different socio-demographic and clinical pools. The auditory P300 was conducted as the last task of the COGS-2 battery, following completion of the Mismatch Negativity experiment described by Light et al. . A San Diego Instruments 2-channel ERP-LAB system with a pre-set P300 module was used for stimulus presentation and EEG recording. One channel recorded EEG activity at the vertex referenced to the left mastoid process . A second channel recorded eye movement activity from electrodes placed mid superior and lateral to the right orbit . A ground electrode was placed on the right mastoid. All electrode impedances were below 5kΩ. The Cz electrode location represented a compromise between the preferred electrode placements for MMN and P300 recordings, given the limitations of the 2-channel recording system and the need to dedicate one of these to the EOG. Subjects were seated in front of a computer monitor and directed to fixate their gaze on the center screen. A hearing test was conducted to ensure >40 dB hearing threshold bilaterally at 1000Hz. Subjects were instructed to press the button on a hand-held counter whenever they heard a 1500 Hz target tone amid a stream of 1000 Hz tones. They were given a brief practice period to ensure initial task comprehension and compliance. Unfortunately, the experimental hardware did not allow further real-time monitoring of button-press responses over the course of the experiment. Subjects were then presented a series of 400 tones, including 62 random targets. The ERP system digitally sampled the EEG at 1000 Hz and wrote 1400 ms of data for each stimulus trial, beginning 100 ms prior to stimulus onset. At the conclusion of the experiment, the number of button presses was recorded from the counter. Raw EEG data from all 5 COGS-2 sites were uploaded to a centralized database. Quality assurance data review and analysis was then conducted by a single investigator who was blind to all demographic and diagnostic information. EEG data were processed using Brain Vision Analyzer 1.5 . Data were digitally filtered between 0.1 and 30 Hz and eye movement artifact was removed using an automated algorithm . Intervals with additional EEG artifact were excluded from further analysis. Remaining trials were then sorted and combined to form separate average ERP wave forms for the target and frequent tone conditions. These were baseline corrected relative to the 100ms pre-stim interval and visually inspected to determine the presence or absence of reliably identifiable ERP components. A highly conservative, stringent, approach to data inclusion was employed. Data without an unambiguous N100/P200 response to the frequent tone, or a reliably identifiable P300 response to the target were excluded. Subjects were also excluded if their target count deviated by more than 20 from the actual number of 62, regardless of the quality of EEG data, since appropriate task engagement could not be documented. For the remaining subjects, P300 amplitude and latency were measured from the peak target response between 250 and 400 ms. . P300 amplitude and latency differences were analyzed in two separate general linear models , with diagnosis, sex and test site as categorical factors and age as a continuous predictor. Significant main effects and interactions were parsed with post-hoc paired contrasts. The effects of various modulating factors were then initially assessed by adding these individually as separate additional factors to the original model.

The increasing use of more discreet forms of vaping, particularly JUUL , may also have had an impact on social media engagement about vaping behavior, though more research is needed. Also, the associated health risks of vaping were relatively unknown during the study period, though the outbreak of EVALI in 2019 may have generated more attention and possible concern among users about potential health risks of vaping, though these conversations were not detected in this study . Importantly, most tweets that included conversations about tobacco products and behavior expressed positive sentiment. Though unclear from these preliminary results, the influence of “party culture” on college campuses, the opportunities to experiment and initiate with forms of substance abuse behavior, and the immediacy of pleasure from substance use may outweigh concerns, including those relating to long-term health risks, among college students in the United States as observed in this user sentiment . Interestingly, though marijuana tweets exhibited the highest proportion of positive tweets, they also exhibited the highest proportion of neutral tweets and the lowest proportion of tweets with negative sentiment. This finding may suggest relative homogeneity regarding marijuana attitudes, possibly as a consequence of debate regarding marijuana legalization during this time period. As the majority of all sentiment-containing tweets were positive, results from this study may suggest that outreach efforts to raise awareness about the health risks of tobacco and ATPs on college campuses may have limited resonance.

However, these preliminary data also suggest discrepancies in sentiment between tobacco products,vertical agriculture as well as differences in sentiment toward smoking across California universities. Therefore, policymakers and health promotion advocates should consider tailoring policy implementation and health communication for specific college students in California based upon evidence of latent receptivity toward anti-tobacco approaches and existing community sentiment toward smoking behaviors as detected in this study. Furthermore, future studies should more explicitly assess user reaction and sentiment to debate, communication and implementation of state-level policies that both legalize and restrict use of tobacco and smoking products, as well as how these macro policies interact with campus-specific smoke free policy perceptions for different tobacco, marijuana, and e-cigarette product categories. For example, actionable insights based on preliminary findings from this study indicate that users generally express more positive sentiment about tobacco use and smoking behavior. This may necessitate the use of campus-based health promotion and education activities that focus on reducing appeal of these products, such as restricting any form of marketing and promotion in or near campus communities. This should be coupled with broader state legislation to further restrict marketing and promotion that targets young adults and college communities. Further, perceived penalties for violating smoke- and tobacco-free campus policies may also impact compliance based on socioeconomic factors. For example, one user from UC Riverside tweeted, “other places might be more lenient, but UCs have a shitty tobacco and smoking policy and I got caught and now it’s over” [emphasis added to denote correction of misspelling].

Hence, data-driven approaches to assess receptivity and the impact enforcement has on smoking behavior should be built into smoke free program implementation iteratively. Importantly, the breakdown of smoking-related tweets between numerous college campuses as detected in this study presents challenges with respect to whether the distribution of tweet characteristics accurately reflects distributions in the underlying college populations. Nevertheless, similar work has been conducted which presents correlational evidence between characteristics of geospatially-specific social media posts and characteristics of populations in those areas . Furthermore, as over half of college students in California are between the ages of 18 and 24 , academic and demographic distributions of tobacco consumption within colleges may be the consequence of socioeconomic disparities in childhood and potential effects of these disparities on attitudes about smoking among parents, high schools, and/or neighborhoods that warrant further study . Results from our study are limited in generalizability, though complement work by others on examining the impact of tobacco free policies on US college campuses. This includes a recent study from 2020 of small colleges in Massachusetts that found that a college with a smoke-free policy had significantly more anti smoking attitude than a control campus, but did not have lower rates of smoking itself . Relatedly, a separate earlier study from 2005 that analyzed undergraduates in Texas found that campuses with preventive education programs had lower odds of smoking, whereas designated smoking areas and cessations programs were associated with higher odds of smoking . Collectively, these prior studies and our own work helps to better characterize knowledge, attitudes and behaviors of college campus communities toward smoking, as well as the smoke-free policies attempting to discourage smoking, which in turn should aid in the development of more targeted approaches to educate college-aged populations about the health harms of tobacco and also enable better implementation of anti-tobacco policies in these critical populations.

This study was exploratory in nature and collected social media messages for which latitude and longitude coordinates could be collected from the Twitter API, but this data collection methodology is limited to collecting messages from Twitter users that enabled geolocation, a specific limitation to generating a more generalizable dataset on Twitter as it is estimated that only 1% of all tweets are geocoded . Hence, the dataset used in this study after filtering for keywords was small and likely biased, limiting the generalizability of results. This method of data collection may have introduced bias in the types of tweets collected, thereby limiting the generalizability of findings as the majority of Twitter users do not geolocate their posts. Potential sampling biases for Twitter include oversampling for certain geographic areas,hydroponics flood table filtering for specific features , and the limitations of the Twitter public streaming API in lieu of other data collection approaches . Future studies should examine the use of multiple Twitter APIs to generate a more representative Twitter dataset and compliment findings with other traditional sources of data to generate findings that are more robust and generalizable, as well as use complementary Twitter and social media datasets made publicly available by other researchers. specific to identification of Twitter users and conversations associated with colleges and universities, using keyword searches, and selecting accounts affiliated with higher education should be explored in future studies. Also, inclusion criteria required tweets to be posted from college campuses, which would not have accounted for variability in smoking related tweets from off-campus housing or areas/neighborhoods at the borders of campus properties where college students may reside. Furthermore, though the study design permitted searches of the Twitter API to return different volume of tweets for different keywords, there was a smaller number of original keywords for substances containing marijuana/cannabis than those for e-cigarettes or products containing tobacco due to our purposeful filtering for tobacco and alternative tobacco product keywords . Additionally, the majority of tweets analyzed for this study were from 2015, a period prior to major public scrutiny about default privacy settings for location sharing on Twitter . Finally, this study is an ecological study and should therefore be considered hypothesis generating and not generalizable to individuals on college campuses until further studies among individuals confirm these correlational findings. Post traumatic stress disorder is an anxiety disorder that can develop following exposure to traumatic life events. Central clinical features of PTSD include a persistent, heightened experience of alarm and distress, as well as a failure of extinction processes to diminish the emotional impact of traumatic memories. Investigation of the neural mechanisms that underlie fear acquisition, consolidation, and extinction may thus enhance our understanding of the neurobiological basis of PTSD, and open opportunities for mechanism-based drug discovery and development of the next-generation pharmacotherapies for this disabling disorder. The process by which emotionally-aversive memories become consolidated is recognized to be an interaction between glucocorticoid hormones and norepinephrine, both of which are released in response to stress. The primary component of this response appears to be a noradrenergic signal that is necessary for encoding emotionally salient information.

The hyperconsolidation of traumatic memories in PTSD is driven by a glucocorticoid-hormone facilitated potentiation of norepinephrine inputs to the basolateral amygdala. Recent work has revealed that this glucocorticoid action is mediated by cannabinoid type-1 receptors, a mechanism that is critical for the consolidation of aversive memories and thus implicates CB1 receptors in the etiology of PTSD. Moreover, there is an emerging body of evidence demonstrating an important role for CB1 receptor-mediated endocannabinoid signaling in the extinction of aversive memories. Augmenting levels of anandamide in the amygdala modulates short-term fear extinction, thereby resulting in long-term reduction in fear and highlighting the endocannabinoid system as a candidate system for developing novel pharmacotherapies for PTSD. CB1 receptors are the most abundant G-protein-coupled receptors in the central nervous system, and are found in high concentrations within an amygdala-hippocampal-cortico striatal circuit responsible for processing and storing fear-related memories and coordinating fear-related behaviors. Animal studies have shown that chronic stress is associated with decreased brain levels of the endocannabinoid anandamide and CB1 receptor adaptations, which in turn give rise to an anxious/depressive phenotype. However, it is not clear whether these animal findings apply to PTSD in humans. The development of a CB1 receptor selective radio tracer—[11C]OMAR22—now makes it possible for the first time to conduct a quantitative assessment of in vivo CB1 receptor availability using positron emission tomography . In the current study, we hypothesized that, relative to healthy non-trauma-exposed and trauma-exposed controls , individuals with PTSD would have increased CB1 receptor availability. In light of data from animal studies, we further predicted more pronounced CB1 receptor elevations in women than men with PTSD. A TC group free of lifetime PTSD or other psychiatric illness was recruited in order to assess the relation between trauma exposure alone and CB1 receptor availability. We also assessed peripheral levels of the endocannabinoids anandamide and 2-arachidonoylglycerol ; levels of the fatty acid ethanolamides oleoylethanolamide and palmitoylethanolamide ; and cortisol. We expected to find lower anandamide and cortisol levels in the PTSD group relative to the HC and TC groups. Finally, psychiatrically relevant biomarkers for PTSD are important yet elusive contributors towards accurate diagnosis and improved clinical care for trauma survivors. We predicted that measures of CB1 receptor availability, anandamide and cortisol would accurately categorize a majority of participants with regard to PTSD diagnostic status relative to healthy and trauma-exposed controls. Participants were recruited via public advertisements seeking individuals with non-combat trauma histories and healthy control participants with and without lifetime histories of trauma.In addition, none were receiving psychotherapy at the time of scanning. The protocol was approved by the New York University Institutional Review Board, the Yale University School of Medicine Human Investigation Committee, the Yale University Magnetic Resonance Research Center, and the Yale New Haven Hospital Radiation Safety Committee. After providing written informed consent, participants underwent a thorough medical and psychiatric evaluation that included physical examination, electrocardiogram, standard blood chemistry and hematology laboratory tests, urine analysis and toxicology, followed by a magnetic resonance imaging scan and a resting PET scan with the CB1 receptor antagonist radiotracer [11C]OMAR. Psychiatric diagnoses were made using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition – Text Revision criteria and the Structured Clinical Interview for DSM-IV , which was administered by an experienced psychiatric clinician. PTSD symptom severity was assessed using the Clinician-Administered PTSD Scale for DSM-IV and trauma history was assessed using the Traumatic Life Events Questionnaire. Only traumatic events meeting DSM-IV-TR PTSD criterion A1 for severe trauma exposure, as well as criterion A2, which confirms the emotional response to the trauma , were counted towards participants’ trauma history in this study. Additional assessments included the Hamilton Rating Scale for Anxiety, the Montgomery-Åsberg Depression Rating Scale, the Alcohol Module of the Addiction Severity Index and the Fagerström Test for Nicotine Dependence. To meet TC inclusion criteria, individuals must have been exposed to at least one potentially traumatic event that met DSM-IV-TR PTSD Criteria A1 and A2, but have no lifetime PTSD or other Axis I diagnosis. Participants with significant medical or neurological conditions, substance abuse within 12 months of the PET scan, a lifetime history of substance dependence , or history of head injury with loss of consciousness were excluded from the study.

Each of the four types of sub stances, as well as daily use of tobacco and the number of substance use classes endorsed , were explored in secondary analyses. DSM-IV abuse or dependence was based on a positive parent or child report with the Diagnostic Interview Schedule for Children version 2.3/3.0 at the 6- and 8-year follow-up assessments. The DISC includes both lifetime and past year diagnoses. The Diagnostic Interview Schedule-IV was used at the 8-year follow-up for 18 + year-olds . SUD was defined as the lifetime presence of any abuse or dependence . Additional analyses explored SUD for alcohol, tobacco, and cannabis/other drugs separately. All patients in this study provided informed written consent as approved by the NIH Ethics Committee.A sample of 560 inpatients and outpatients with severe SUD from Central Kentucky psychiatric facilities was collected during a pharmacogenetics investigation. Patient interviews and medical record information were used by the research nurse to assess the Clinician Rating of Alcohol and Drug Use Disorder that provides a score from 1 = abstinence to 5 = severe dependence. Scores of 3 and higher are pathological and were considered positive in our analyses. All drugs were combined into one rating. Descriptions of the training provided to research nurses to assess the CRAUD and CRDUD were published elsewhere. DNA was available from 533 of 560 study subjects. Of the 533 subjects with available DNA, 53% were male, 82% were Caucasian, 16% were African American, and 2% were from other ethnicities.

Additional clinical information for this sample has been described elsewhere and included: clinical diagnosis obtained from medical records, prior psychiatric history, history of daily smoking,grow rack systems reviews of current and psychiatric medication use, and body mass index . All participants in the Kentucky study provided informed written consent as approved by the University of Kentucky IRB.Association studies of ADGRL3 variants with ADHD, ODD, CD, response to stimulant treatment and severity outcome have been published elsewhere for the Paisa and Spanish populations. We used ARPA to build a predictive framework to forecast the behavioral outcome of children with ADHD, suitable for translational applications. Our goal was to test the hypothesis that ADGRL3 variants predisposing to ADHD also increase the risk of co-morbid disruptive symptoms, including SUD. ARPA is a tree-based method widely used in predictive analyses because it accounts for non-linear and interaction effects, offers fast solutions to reveal hidden complex substructures and provides truly non-biased statistically significant analyses of high-dimension, seemingly unrelated data. In a visionary manuscript, D.C. Rao suggested that recursive-partitioning techniques could be useful for genetic dissection of complex traits. ARPA accounts for the effect of hidden interactions better than alternative methods, and is independent of the type of data and of the type of data distribution. Furthermore, results supplied by tree-based analytics are easy to interpret visually and logically. Therefore, to generate the most comprehensive andparsimonious classificatory model to predict the sus ceptibility to disruptive behaviors, we applied ARPA using a set of different modules implemented in the Salford Predictive Modeler® software, namely, Classifica tion and Regression Trees , Random Forest, and TreeNet .

One important advantage of SPM when compared to other available data mining software is its ability to use raw data with sparse or empty cells, a problem frequently encountered in genetic data. Briefly, CART is a non-parametric approach whereby a series of recursive subdivisions separate the data by dichotomization. The aim is to identify, at each partition step, the best predictive variable and its best corresponding splitting value while optimizing a splitting statistical criterion, so that the dataset can be successfully split into increasingly homogeneous subgroups. We used a battery of different statistical criteria as splitting rules to deter mine the splitting rule, maximally decreasing the relative cost of the tree while increasing the prediction accuracy of target variable categories. The best split at each dichotomous node was chosen by either a measure of between-node dissimilarity or iterative hypothesis testing of all possible splits to find the most homogeneous split . Similarly, we used a wide range of empirical probabilities to model numerous scenarios recreating the distribution of the targeted variable categories in the population. Following this iterative process, each terminal node was assigned to a class out come. To avoid finishing with an over-fitted CART predictive model , and to ensure that the final splits were well substantiated, we applied tree pruning. During the procedure, predictor variables that were close competitors were pruned to eliminate redundant commonalities among variables, so the most parsimonious tree would have the lowest misclassification rate for an individual not included in the original data. Additionally, we applied the Random Forest methodology using a bagging strategy to exactly identify the most important set of variables predicting disruptive behaviors. The RF strategy differs from CART in the use of a limited number of variables to derive each node while creating hundreds to thousands of trees. This strategy has proved to be immune to the over fitting generated by CART. In RF, variables that appeared repeatedly as predictors in the trees were identified. The misclassification rate was recorded for each approach. The TreeNet strategy was used as a complement to the CART and RF strategies because it reaches a level of accuracy that is usually not attainable by single models such as CART or by ensembles such as bagging.

The TreeNet algorithm generates thousands of small decision trees built in a sequential error-correcting process converging on an accurate model.To derive honest assessments of the derived models and have a better view of their performance on future unseen data, we applied a cross-validation strategy where both training with all the data and then indirectly testing with all the data were performed. To do so, we randomly divided the data into separate partitions of differ entsizes. This strategy allowed us to review the stability of results across multiple replications. We used a 10-fold cross-validation as implemented in the SPM software. A fixed-effects meta-analysis of the overall fraction of correctly classified individuals using the derived models from each of the four samples was applied to derive a general perspective of the SUD predictive capacity of this demographic-clinical-genetic framework.A series of predictive models were built on our data using combinations of the following criteria: the rules of splitting ; the priors; the size of the terminal nodes; the costs; the depth of branching; and the size of the folds for cross-validation,rolling flood tables to maximize the accuracy of the derived classification tree while considering class assignment, tree pruning, testing and cross-validation. A parsimonious and informative reconstructed predictive tree derived from CART for the Paisa sample revealed demographic , clinical , and genetic variables . The importance of these variables was corroborated, and their potential over fitting discarded by the TreeNet analyses that revealed a set of predictors for SUD containing those derived by CART . This predictive model displays good sensitivity and specificity as shown by areas under the receiver-operating characteristic curve during TreeNet cross-validation using folding . The proportions of misclassification for SUD cases in the cross-validation experiment for the learning and testing data were 0.124 and 0.177, respectively . In the case of the Spanish sample, a parsimonious and informative tree was reconstructed with CART revealing demographic , clinical , and genetic variables.This predictive model displayed good sensitivity and specificity as shown by areas under the ROC curve of 0.911 and 0.897 for learning and testing samples, respectively, during TreeNet cross-validation using folding . The proportions of misclassification for SUD cases obtained by TreeNet analysis for learning and testing data were 0.151 and 0.175, respectively . As in the previous cohorts, for the MTA sample we derived a parsimonious and informative predictive tree with CART depicting demographic , and genetic variables . The TreeNet analyses revealed a set of predictors for SUD containing those derived by CART . This predictive model displays good sensitivity and specificity as showed by AUC of 0.808 and 0.643 for learning and testing samples, respectively, during TreeNet cross-validation using folding . The proportions of misclassification for SUD cases obtained by TreeNet analysis for learning and testing data were 0.314 and 0.358, respectively . Finally, for the Kentucky sample, we derived a parsimonious and informative predictive tree with CART involving demographic , clinical and schizophrenia diagnosis, and genetic variables .

The TreeNet analyses revealed a set of predictors for SUD containing those derived by CART . This predictive model displays good sensitivity and specificity as showed by AUC of 0.811 and 0.744 for learning and testing samples, respectively, during TreeNet cross validation using folding . The proportions of misclassifification for SUD cases obtained by TreeNet analysis for learning and testing data were 0.285 and 0.252, respectively . The results from the RF analysis were consistent with those produced by TreeNet cross-validation using folding. A fixed-effects meta-analysis for overall accuracy returned a value of 0.727 , suggesting potential eventual clinical utility of predictive values. Overall, ADGRL3 marker rs4860437 was the most important variant predicting susceptibility to SUD, a commonality suggesting that these networks may be accurate in predicting the development of SUD based on ADGRL3 genotypes. We conducted independent analyses for alcohol or nicotine dependence and compared these results with those of our composite SUD phenotype, as defined by the disjunctive presence of substance use phenotypes and explained by likely common neuropathophysiological mechanisms. In general, across cohorts, we found significant alcohol and nicotine risk variants, some of which have reasonably high odd ratios . For instance, in the Spain sample, marker rs2271339 conferred significant risk to nicotine use: the heterozygote genotype A/G confers 43% increased risk of being diagnosed with nicotine use . In the same vein, we found in the Paisa sample that the heterozygote A/T genotype for rs1456862 confers 83% increased risk to nicotine use than the A/A genotype. Regarding alcohol use, we found in the Paisas that the heterozygote C/T genotype for rs2159140 confers susceptibility, whereas the C/C geno type does not . Supplemental Fig. 1 shows the ROC curves of nicotine and alcohol use prediction in the Paisa sample. Note that the AUC is greater than 0.7 in both cases, which suggests a straight performance of markers rs1456862 and rs2159140 in predicting nicotine and alcohol use, respectively. To determine the significance of improvement of pre diction when genetic markers are introduced in the ARPA-based predictive model for SUD, we compared the performance measures across all cohorts under two dis junctive scenarios: inclusion of genetic markers or not. We found that including genetic markers improved the performance measures of the resulting ARPA-based obtained for the Paisa sample: the AUC was 90% when genetic information was included versus 78.8% when it was not . Improvements were also observed in the correct classification rate for the Spanish and Paisa samples, the sensitivity values in all samples, the specificity in the Spanish and Paisa samples, and the lift in the Paisa sample . Similar results were observed for the MTA and Kentucky samples, where including genetic information in the predictive model for SUD drastically improved these performance measures .SUD genetic epidemiological studies across multiple substances have been plagued with inconsistency in the replication of genetic association results. This may be due to reasons such as: small effect size of variants expected to influence the SUD phenotype, as with any complex disease;insufficient power to detect significant associations due to small sample size;phenotypic heterogeneity of SUD across samples that may reflect different disease stages or multiple subtypes ; genetic heterogeneity arising from distinct risk genes sets; ethnicity inconsistencies between discovery and replication samples;and comorbidity with other psychiatric conditions with shared genetic and environmental architecture. Consequently, additional studies are required to identify new SUD candidate genes and to help dissect genetic contributions in the context of complex interactions with co-morbid conditions. In this study, we present a demographic, clinical and genetic framework generated using ARPA that is able to predict the risk of developing SUD. Interestingly, marker rs4860437 showed a differential splitting pattern in the Paisa, Spain, and Kentucky cohorts. For instance, in Fig. 1a, rs4860437 splits into and T/T; in Fig. 2a, the same variable splits into and G/T; and in Fig. 4a, it splits into and G/G. The most parsimonious and plausible explanation of this splitting pattern is the presence of genomic variability surrounding this proxy marker, reflecting ancestral composition. Future studies of genomic regions surrounding rs4860437 might reveal a cryptic mechanism.

However, a 2015 review of 225 Android apps for quitting smoking found that most provide simplistic tools ; use of tailoring was limited, although positively related to app popularity and user ratings of quality .Notably, one randomized trial found that a simpler, direct texting program outperformed a smoking cessation app . Social media. Social media, such as Twitter and Facebook, are being explored for delivering cessation treatment. In the United States, 74% of online adults use social media, 80% of whom are seeking health information, and a majority access the sites daily . A promising technology, efforts to sustain engagement are key and can be challenging; like predecessor technologies such as bulletin boards and listservs, initial interest may be high but then tends to wane . There is preliminary evidence, however, of good acceptability and efficacy. Using Twitter, small, private groups of 20 smokers, who interact for 100 days, have been studied. The intervention seeds the groups with twice-daily automessages to encourage group sharing and support.Similar efforts are being developed on Facebook, with a focus on engaging young adults into cessation treatment. In a randomized trial, a novel Facebook smoking cessation intervention increased abstinence at the end of treatment, although effects were not sustained out to 1-year follow-up .Having tried and failed to quit smoking in the past,planting racks smokers may not initially publicize their quit attempts within their main social circle . With social media sites that are largely uncurated or expert moderated, however, users should be forewarned that inaccurate information may be posted. For example, online communities may encourage use of non–evidence-based treatments .

A heterogeneous group of emerging applications and knowledge gaps remain concerning best strategies for maximizing the reach and efficacy of mobile technologies for treating nicotine addiction as well as the comparative effectiveness relative to in-person approaches.Monetary incentives that reward outcome or engagement have been evaluated in 33 trials, with a meta-analysis finding evidence of increased abstinence that persisted after the incentives ceased . The level of the incentives ranged from zero to between $45 and $1185, with no clear direction of effect by level of incentive. Conditional payments outperformed non conditional payments. Findings from a subgroup analysis of eight trials conducted with smokers with substance use problems were consistent with the overall analysis. A summary of nine trials with pregnant smokers reported more than twofold greater odds of abstinence at longest follow-up assessment . The findings are particularly important given the substantial health harms of smoking to mother and baby and that, currently, there is no other effective cessation intervention for pregnant smokers.While counseling and psychosocial treatments help promote cessation, medications that address the neuropharmacological effects of nicotine and nicotine withdrawal further enhance the likelihood of quitting. E-cigarettes, which allow continued self-administration of nicotine without combustion, can also promote quitting smoking. Smoking cessation guidelines, such as those from the U.S. Public Health Service and National Cancer Center Network, recommend smoking cessation medications for all daily smokers where feasible and safe . Pharmacotherapy can be considered fornondaily smokers as well, although there are few clinical trials to guide treatment in this group. The mechanism of benefit innondaily smokers would be reduction of nicotine reward from cigarettes by nicotinic receptor desensitization or antagonism, as discussed below. Table 2 presents the FDA-approved smoking cessation medications, including dosing guidelines, advantages, disadvantages, adverse effects, and precautions. FDA-approved medications are NRT in the form of gum, patches, lozenge, nasal spray and inhaler, varenicline, and bupropion. Nicotine gums, lozenges, and patches are available over the counter in the United States, while the nicotine nasal spray, nicotine inhaler, varenicline, and bupropion are by prescription only.

Nicotine mouth spray is available outside of the United States and has evidence of acceptability, efficacy, and safety, including with minimal behavioral support . In general, medications serve to make smokers more comfortable while they learn to live and cope with daily cues/triggers and life stressors without smoking cigarettes. There are three main mechanisms by which medications can facilitate smoking cessation: reduction of nicotine withdrawal symptoms, reduction of the rewarding effects of nicotine from smoking by blocking or desensitizing nicotine receptors, and providing an alternative source of nicotine with the desired pharmacologic effect previously provided by nicotine from cigarettes. NRT medications are not as satisfying as cigarette smoking because of slower absorption of nicotine; nicotine delivery from e-cigarettes can resemble that of a cigarette, and these devices tend to be much more satisfying. Most smoking cessation medications are recommended for 8 to 12 weeks, although use for 6 months or longer may be necessary to achieve optimal quit rates. It makes sense to use medications to support smoking cessation for as long as the individual feels at risk for relapse. For those switching to e-cigarettes as a less harmful substitute for cigarette smoking, use sometimes continues for many months or years.Nicotine medications consist of purified nicotine that is administered to ameliorate symptoms of physical dependence on nicotine. The particular actions of different products vary according to route of administration and rate of nicotine absorption into the bloodstream. For example, nicotine patches deliver nicotine slowly, relieving nicotine withdrawal symptoms and reducing positive effects of cigarette smoking, without providing much, if any, direct positive effects of nicotine. Nicotine gums, lozenges, sprays, and inhalers deliver nic otine more rapidly, providing some acute nicotine effects that may serve as a substitute for smoking a cigarette. Combining a short-acting with a long-acting NRT results in superior quit rates compared to any NRT product alone and is recommended as a first-line treatment .

NRT products are marketed in different strengths, with higher doses recommended for more dependent smokers based on the number of cigarettes smoked per day or time to first cigarette upon wakening. A 2019 Cochrane review concluded that 4-mg gum is more effective than 2-mg gum in more highly dependent smokers and that 21-mg patch is more effective than 14-mg patch in general . While clinical trials do not demonstrate superiority of 42- to 21-mg dose nicotine patch, some clinicians do use high-dose patch for smokers with particularly severe withdrawal symptoms. Tapering of nicotine doses over time is an option for nicotine patches but does not appear to affect outcome in clinical trials. All forms of NRT have shown similar efficacy in clinical trials , increasing quit rates by 50 to 100% compared to behavioral treatment alone. For the NRTs, compliance is greatest with nicotine patches,sub irrigation cannabis lower with gum and lozenge, and lowest with the nasal spray and inhaler.Some smokers experience nicotine patch–related insomnia and/or abnormal dreams and do better removing the patch at bedtime. Use of patches for 16 or 24 hours is equally effective in promoting quitting smoking. The pharmacokinetics of nicotine gum, lozenge, and inhaler are similar, with gradual absorption of relatively low doses of nicotine over 15 to 30 min. Use every 1 to 2 hours provides the best pharmacologic response. The nicotine inhaler is a plastic device inhaled like a cigarette but delivers nicotine to the oropharyngeal area rather than to the lungs, which explains its slow absorption. All oral nicotine products have an alkaline pH, which results in a high proportion of nicotine in the free base form, which is rapidly absorbed across mucous membranes. Acidicbever ages reduce the pH and reduce nicotine absorption and should be avoided for >10 min before using oral NRT products. The nicotine nasal spray is absorbed much faster than the other rapid-release products, most closely resembling a cigarette. More dependent smokers may find nicotine nasal spray to be more effective than other NRT products for smoking cessation. The spray is associated with more local toxicity, including a burning sensation, watery eyes, and sneezing; however, tolerance develops to these effects with regular use of the spray over 1 to 2 days.

Overall, NRT products are well tolerated and present few safety concerns. Safety concerns with NRT are primarily skin irritation with patches, gastrointestinal symptoms with oral products, and nasal/throat burning and irritation with nasal spray. Nicotine’s car diovascular effects raised concern about NRT cardiovascular safety. Nicotine enhances sympathetic neural activity, resulting in increased heart rate, constriction of blood vessels, induction of proatherogenic lipid profiles , development of insulin resistance, and possible promotion of arrhythmias . Cigarette smoke delivers not only nicotine but also many oxidants, prothrombotic and other toxic chemicals, making smoking much more toxic than nicotine alone. Clinical trials and other stud ies of NRT in patients with cardiovascular disease find no increase in adverse cardiovascular events due to NRT .Varenicline is a partial agonist at the nicotinic a4b2 receptor, the major receptor mediating nicotine addiction. Varenicline both activates and blocks the effects of nicotine on the a4b2 receptor . The agonist effect serves to reduce withdrawal symptoms, while the antagonist effects reduce the rewarding effects of nicotine from cigarette smoke. Varenicline treatment before smoking cessation is often associated with reduced smoking, presumably because smoking is less satisfying, an effect that can promote subsequent cessation. In clinical trials, varenicline is more effective than bupropion or nicotine patch in promoting smoking cessation and is comparably effective to combined NRT . The EAGLES trial, the largest smoking cessation trial conducted with 8000 smokers, directly com pared varenicline, bupropion, nicotine patch, and placebo. Varenicline outperformed all conditions; bupropion and nicotine patch were comparable to each other and were significantly better than placebo . EAGLES included smokers without and with psychiatric diagnoses. Quit rates were higher in those without psychiatric diagnoses, but the relative efficacy of the various treatments was similar. Extended treatment with varenicline for 6 months is superior to the standard 12-week treatment and is recommended for smokers who feel at risk of relapse . The most common adverse effect of varenicline is nausea, which is dose related and to which tolerance develops over time. Concern about nausea is the rationale for starting at lower doses for a week before starting the full dose . Some smokers cannot tolerate the normal dose but do well on continued use of the lower dose. Anecdotal reports of neuropsy chiatric adverse effects of varenicline used for smoking cessation have been reported, prompting a black box warning in the label after the drug was marketed . The putative neuropsychiatric side effects included depression, psychosis, and suicide, with potentially higher risk in smokers with psychiatric disease. However, the EAGLES trial found no evidence of increased neuropsychiatric adverse events for varenicline or bupropion relative to nicotine patch or placebo, in smokers with or without psychiatric illness, and in 2016, the black box warnings were removed for both varenicline and bupropion . Varenicline has been shown to enhance smoking cessation in patients with cardio vascular disease, including stable coronary heart disease and acute coronary syndrome . Concern was raised about possible cardiovascular toxicity due to the nicotine-like effects of varenicline and anecdotal reports of adverse cardiovascular events, but several meta analyses, a large retrospective cohort study, and clinical trials in smokers with cardiovascular disease, as well as the EAGLES trial, showed no increase in cardiovascular risk . Varenicline has also been found efficacious for cessation of smokeless tobacco use .Bupropion is a stimulant drug originally marketed as an antidepres sant. Bupropion blocks neuronal uptake of dopamine and norepinephrine and has antagonist activity on the a4b2 nicotinic receptor. By blocking reuptake, bupropion increases brain levels of dopamine and norepinephrine, simulating effects of nicotine. Bupropion is marketed for smoking cessation as a sustained-release prepara tion. The drug works in both depressed and non-depressed smok ers. The usual duration of bupropion treatment is 12 weeks, but extended bupropion therapy for a year reduces relapse and enhances long-term quit rates . With lower quit rates, bupropion is considered to be second-line, after combination NRT and varenicline. The main adverse effects of bupropion relate to its nervous system stimulant actions. Some smokers are intolerant to bupropion because of anxiety, agitation, and insomnia. Bupropion reduces the seizure threshold and should not be used in smokers who are at risk for seizures. In overdose, bupropion causes tachycardia and hyper tension, but there is no evidence of increased cardiovascular events in smokers with preexisting stable cardiovascular disease .

Of note, CGRP plasma levels positively correlate with headache intensity and timing , and CGRP intravenous infusion causes migraine-like symptoms in migraine patients . The acute treatment of migraine relies on compounds specifically developed for the disease, such as the triptans . In contrast, prophylactic treatment has relied on drugs originally developed for other disorders, such as antihypertensive or antiepileptic drugs. Unfortunately, all of these compounds are only moderately effective, with side effects that limit adherence . The identification of CGRP as causative in migraine events has led to the development of different therapeutic strategies to specifically treat or prevent migraine. Four monoclonal antibodies targeting CGRP or its receptor have been approved by the U.S. Food and Drug Agency or the European Medicine Agency for the prophylactic treatment of migraine . With their extended time to reach the maximal concentration and long plasma elimination time , mAbs have proven to be effective. mAbs are relatively large molecules that usually do not cross the blood–brain barrier, so that they are more likely to act outside of the brain. Sites of action include the meningeal vasculature and certainly also the trigeminal ganglion, which is not protected by the blood–brain barrier . The results of a recent retrospective longitudinal study suggested that pa tients discontinued use of prophylactic therapies when they initiated CGRP receptor antagonist therapy with erenumab. Adherence to these novel therapies is higher than to the older medications,ebb and flow suggesting an increased real-world effectiveness . However, a proportion of migraine patients do not experience benefit from CGRP targeted treatments, suggesting the involvement of other pathways in migraine.

A preliminary study has indicated that those who do not benefit from their current CGRP-targeted therapy fare better by switching antibody class, but more rigorous double-blind studies are necessary . Gepants are small molecule CGRP receptor antagonists. The development of the so-called first-generation gepants was halted because of pharmacokinetic limitations or hepatotoxicity , but the second generation appears to be safe and tolerable, with several different compounds already FDA approved. Zavegepant is currently under clinical investigation for acute treatment or prophylaxis of migraine. Gepants with different pharma cokinetics along with mAbs could provide a continuum between acute and prophylactic approaches. Although these drugs all are effective in prophylactic or acute migraine treatment, real-life efficacy, long-term safety, and durability of the effects remain to be established. OA affects about 9.6% of older men and 18% of older women . Cartilage degradation is a hallmark of OA, with pain and reduced joint functionality. Treatment of OA pain remains an unmet medical need. This pain probably stems from the inflammatory response and release of inflammatory cytokines, including NGF. Indeed, NGF is present in sub-chondral bone of the human tibial plateau, cartilage, and synovium in OA and rheumatoid arthritis . Increased synovial NGF immunoreactivity, along with synovitis and morpholog ical changes in chondrocytes, also has been associated with symptomatic knee OA . It has become clearer that the NGF/TrkA pathway has a central role during the development of pain in OA , which has prompted research into therapeutic strategies targeting NGF in both animal studies and clinical trials . Pre clinical studies have shown encouraging results. Although several anti-NGF mAbs have been tested in the clinical setting, only fasinumab is currently in clinical development for treatment of painful lower extremity OA and low back pain . Tanezumab is another anti-NGF mAb, but its testing was stopped by the manufacturer in late 2021. Initially, following a proof-of-concept study showing improvement in joint pain and functionality , tanezumab was administered intravenously with and without NSAIDs . After the treatment, patients with knee or hip OA had significant pain reduction and improvement in joint function compared to either placebo or NSAID alone.

In 2010, however, the clinical development program for anti-NGF antibodies was put on hold after several serious adverse events emerged resembling joint osteo necrosis or rapidly progressive OA in patients treated with higher doses of both NGF antagonists alone or combined with NSAID. A detailed analysis identified most of these events as RPOA. This disorder is considered to be an accelerated form of OA leading to joint replacement. After a second clinical hold because of unclear and suspected peripheral neuropathy, clinical trials were eventually continued. Addi tional phase III studies with fasinumab and tanezumab were continued with a subcutaneous formulation. As in the previous studies with an intravenous formulation, these results also showed significantly reduced joint pain, but adverse events including RPOA were still present with the higher dose. The mechanism behind the development of RPOA is not completely understood, and the FDA and EMA both rejected approval of tanezumab for the treatment of OA pain, leading to the termination of the clinical tanezumab program in 2021. However, targeting patients with chronic low back pain and excluding medium to severe OA might be a promising alternative strategy for anti-NGF regimens. Fasinumab has completed phase II/III studies in patients with knee OA. Fasinumab also resulted in significant reduction in joint pain, with similar incidences of RPOA. Currently, studies with fasinumab at 1 mg every 4 weeks and 1 mg every 8 weeks are underway, and results should be reported soon. In summary, inhibition of NGF by systemic administration of antibodies appears to reduce pain and improve function in individuals with lower extremity OA. If fasinumab is approved, a longer acting non-opioid alternative will be available for the treatment of OA or perhaps chronic low back pain. CGRP and NGF have been successfully targeted in chronic pain pa thologies. In contrast, SP has not been as promising, and the results of studies are variable, preventing definite conclusions. SP is expressed in the spinal ganglion and released after stimulation of primary nociceptive neurons. SP binds the neurokinin-1 receptor found in the CNS , on the trigeminal and spinal ganglia , and immune cells, such as lymphocytes, macrophages, and mast cells .

SP leads to inflammation with vasodilation and edema after repetitive stimulation and anti-dromal transport with release at the nociceptor. In this way, SP causes neurogenic inflammation with recruitment of immune cells and the release of pro-inflammatory mediators . Genetic studies have pointed towards the role of the SP/NK-1 pathway in the development of pain. For instance,dry racks the absence of the NK-1 receptor in mice does not alter the perception of acute pain, but pain wind-up was absent. Furthermore, African naked mole rats have limited SP fibers in the skin and are not susceptible to some types of pain . Consequently, NK-1 receptor antagonists were developed with the idea of blocking SP neurotransmission . Although these antagonists showed promising results in animal models, results of clinical studies were disappointing . Aprepitant is a SP/NK-1 receptor antagonist approved as an antiemetic drug. Surprisingly, aprepitant did not show attenuation of pain after 2 weeks of treatment in patients with post-herpetic neuralgia or a decrease of sensitization in a human model of electrical hyperalgesia . This outcome raised the question of compound specificity in humans. Furthermore, blocking the NK-1 pathway might upregulate other neurotransmitters involved in nociception or activate alternative pathways such as NK-2 or NK-3. Findings of recent study suggest that SP released from primary afferents binds Mas-related G-protein–coupled receptor on mast cells, triggering the release of inflammatory mediators as well as immune cell recruitment . Thus, SP-mediated nociception involves not only the NK-1 receptor but also MrgprB2, suggesting that perhaps the other receptor should be a focus . MrgprX2, the human homolog of MrgprB2, may be a promising new target for chronic pain.

Despite our growing understanding of the pain landscape, novel treatment targets are necessary in light of the current scarcity of treatment options. Novel therapeutic regimens targeting more disease specific key molecules of chronic pain will have to be a focus in neuroscience and interdisciplinary research in rheumatology, neurology, and pain medicine. The lack of disease-specific treatment targets for chronic pain syndromes is in astounding contrast to a “mi nority” of inflammatory autoimmune diseases with targeted therapies against TNF-α, IL-1β, IL-6, IL-12/23, IL-17, IL-23, CTLA4, CD20, PDE4, or Janus kinases . Animal models of pain and the identification of novel therapeutic targets have led to development of new treatment strategies in the pre-clinical setting, but the translation into the clinic has been disappointing . Nonetheless, evidence is gradually accumulating of beneficial effects in subtypes of pain syn dromes. The poor translation between experimental models and clinical condition may trace to the clinical relevance of the model and assessment methods used . Several studies also suggest that the inflammatory response has a critical role during neuropathic and inflammatory pain by enhancing the expression or release of prostaglandins, sympathetic amines, endothelin, and NGF . With neurogenic in flammatory pain, target molecules can be related to inflammation itself or to pain, and it is crucial to evaluate the underlying inflammatory mechanisms. One of the mediators of inflammation in pain is TNF-α, a classical pro-inflammatory cytokine that enhances release of second order pro-inflammatory cytokines, such as IL-6 and other mediators, amplifying the inflammatory response . Like several other cytokines, IL-6 exerts its effects through JAK/signal transducer activation . A meta-analysis revealed that JAK inhibitors used for joint pain from rheumatoid arthritis improve outcomes, but in several patients, pain persists even when inflammation is contained . Patient-reported out comes such as health assessment questionnaire responses, physical function, and patient assessment of pain showed significant improvements in patients treated with baricitinib alone and in combination with methotrexate as compared to methotrexate alone . Therapies targeting inflammation in degenerative chronic pain syndromes have failed thus far. These chronic pain syndromes do not all rely on the same pathways as systemic inflammation, but anti inflammatory regimens may be beneficial for some chronic pain syndromes. For example, anti-TNF-α antibodies have been tested in patients with knee OA, and the treatment was well tolerated, with a significant improvement in pain . However, in another clinical trial, pain did not improve in patients with hand OA that had not responded to analgesics and NSAIDs . Thus, further studies are necessary to assess the therapeutic benefits of anti inflammatory compounds. Recently, the approach to pain has included revisiting old molecules, such as cannabinoids and capsaicin, and new synthetic compounds. Results of these studies suggest that cannabis and cannabis-based molecules may be effective and improve quality of life in a variety of chronic pain conditions . Cannabinoid receptors are localized on the sensory nerve, and their dual ability to reduce inflammation and neuronal activity might be a crucial mechanism in modulating neurogenic inflammation and pain. The legal consumption of cannabis and its use for pain management are already approved in several countries, despite limited evidence of their efficacy in pain management . Further clinical studies are needed to properly assess the benefits and pitfalls of cannabis-based therapies in pain management . Another relevant treatment for pain is capsaicin, the active ingredient in chili peppers. Capsaicin targets the TRPV1 receptor, which is prominent on nociceptors containing neuropeptides, and more specifically, it is enriched in nociceptors expressing SP and CGRP.A double blind multicenter study recently showed that intra-articularly injected synthetic capsaicin yielded improvement in pain in patients with knee OA . Of note, intra-articular injection of capsaicin did not cause side effects, as seen with the subcutaneous or intravenous administration of anti-NGF compounds. However, high doses of capsaicin can desensitize nociceptors, causing the loss of axon terminals . Another emerging therapeutic target candidate for chronic pain is BDNF, a crucial modulator of nociception. Although BDNF expression can contribute to plasticity in spinal neurons during controllable pain, spinal injury or chronic pain can lead to an altered response to BDNF, triggering central sensitization and pain hypersensitivity . Sustained BDNF levels may show noxious properties with chronic pain . Pro-inflammatory conditions in hyperalgesia also can induce upregulation of BDNF . A recent study showed that BDNF also plays a role in OA, with synovial expression of the BDNF receptor TrkB associated with higher OA pain . However, when administered as a pharmacolog ical treatment in the CNS, BDNF showed anti-inflammatory effects, suggesting an anti-nociceptive role .

These results indicate that clinicians and researchers should give adequate consideration to which AUD criteria might be most salient in identifying older versus younger drinkers with persistent problems who might benefit from interventions and treatment. The need to consider changes in endorsement patterns of specific items in different age groups could also be important for future iterations of the DSM. The specific criterion items that change with time might be different in different populations, a question that requires further research. However, the current prospective findings across 2 generations of the SDPS using the same diagnostic instrument and led by the same research team indicate that the changes observed here are not likely to be an artifact of the measures used and support for Hypothesis 1 is likely to be observed in other populations as well. As predicted in Hypothesis 2, the prospective SDPS data revealed a decreased prevalence of endorsement of tolerance over time among probands with persistent AUDs. AUD offspring demon strated a non-significant overall pattern for decreased endorsement of this criterion over time. The pattern of decreases in tolerance over time among individuals with AUDs is consistent with several cross-sectional and retrospective investigations in the literature . One possible explanation for this decreased endorsement with increasing age might reflect how tolerance is likely to be defined in research and clinical situations where the emphasis is usually on a recent time frame.Tolerance might have occurred earlier in the drinking career and been relatively constant throughout the heavy drinking years with the result that an individual with an AUD might indicate that tolerance, while technically present, was not newly observed in the more recent past.

Another potential contributor to decreased acknowledgment of D1 over time is the fact that at older ages,cannabis grow equipment drinkers are likely to actually increase their intensity of reaction to alcohol because they experience higher blood alcohol levels per drink as a consequence of: slower oxidation of ethanol in the liver; lower body water with age related to decreased water-rich body muscle; and age-related increased GABA sensitivity However, Hypothesis 3 regarding a potential increase with age in endorsement of the criterion of withdrawal was not supported in these analyses where probands with persistent AUDs demonstrated a significant decrease, rather than an increase, in self-reported symptoms of withdrawal between ages 31 and 43.Hypothesis 3 might be more relevant to individuals with AUDs in their 50s and/or those with more medical problems compared to SDPS participants . However, the current results were similar to those of the cross-sectional general population survey by Harford et al that suggested that rates of self-reported withdrawal phenomena did not change dramatically during midlife. Hypothesis 4 predicted age-related decreasing rates of endorsement of criterion A2 that related to using alcohol in hazardous situations. Consistent with this projection, our prospective data for probands with persistent AUDs documented significant decreases in endorsement rates of A2 over time, perhaps as a consequence of decreases in most risky behaviors with increasing age . The SDPS offspring with persistent AUDs demon strated non-significant decreases in endorsement of A2 over time. Hypothesis 4 is consistent with the potentially normal distribution of the age of endorsement of this item in the general population cross-sectional study, although the adolescent data indicated no change in endorsement of hazardous use . Except for the specific criterion items described immediately above, our group did not believe there was sufficient evidence in the prior literature to support specific hypotheses for changes in rates of endorsement of the remaining AUD criterion items in individuals with persistent AUDs.

However, the current data indicated that endorsement of spending a great deal of time involved with alcohol increased significantly over time in both generations of SDPS participants with persistent AUDs. Two additional DSM criteria demonstrated significant increases of endorsements for probands with a similar direction of change in offspring. These included drinking alcohol in higher amounts or for longer periods than intended and continued drinking despite social or interpersonal problems . The non-significant results in offspring might reflect the limitation of analyses to 2 time points and the smaller sample in the younger generation. The final significant change in endorsements over time for pro bands involved decreases in A1 regarding failure to fulfill obligations because of alcohol, but no change in rates of reports of this item was noted for offspring. The decreased rate over time for probands had not been originally hypothesized, and the result might be spurious. However, one might speculate that the decreasing endorsement of A1 for AUD probands might reflect the combination of higher levels of maturity between the early 30s and mid-40s along with decreasing pressures with age of raising young children and potentially diminished worrying about seeking success in one’s vocation . Similarly, while another change was not hypothesized and any conclusions should be drawn with caution, the only criterion for which the change over time was significant for offspring but not probands was an increase in the rate of endorsement of giving up important activities due to alcohol . This result in the younger generation might reflect the mirror image of some of the same changes over time noted in pro bands where the lower level of maturity and higher levels of impulsivity in the 20s contributed to the younger participants being more likely to take time to drink rather than attend to other activities.

The current analyses focused on DSM-IV criteria, but the results might be relevant to DSM-IIIR as well. As to DSM-5, 10 of the 11 diagnostic criteria are the same across the 3 systems, and the only change in criteria occurred when DSM-5 deleted legal problems and added a new criterion involving craving . Although in prior item response theory analyses,vertical grow system legal problems and craving were both found to add relatively little information to the latent concept of the DSM diagnosis or to not fit into a continuum with the other criteria , those were largely based on cross-sectional analyses, and it is not clear whether the results of the current analyses would be similar if data on craving had been available. Another difference between the 3 DSM approaches to an AUD diagnosis is that DSM-5 required endorsement of at least 2 criteria for a diagnosis, while DSM-IIIR and DSM-IV abuse required only a single item. In light of this difference, it is noteworthy that the re-analyses of the data from Tables 2 and 3 after limiting the sample to subjects who endorsed at least 2 criteria did not produce major changes in the current results. However, direct testing of the applicability of our findings to other diagnostic systems will be important.Data from both proband and offspring samples supported Hypothesis 1, and both subgroups demonstrated increases over time in the proportions endorsing criterion D5, spending a great deal of time involved with alcohol. However, although some findings in probands were similar in offspring, patterns for other criteria followed a different course regarding significant changes in the 2 generations. Such differences across older and younger individuals with persistent AUDs are not surprising in light of prior studies that documented differences in the typical ages of onset of some alcohol problems over time . In summary, the current analyses support 2 major conclusions. First, the salience of many DSM AUD criterion items among individuals with persistent AUDs changed significantly with age in both SDPS generations. This finding occurred despite the use of the same interview instrument and the same principal investigators who pro spectively evaluated the same individuals in both generations at all relevant follow-ups. These consistencies are important because differences in each of these items can affect the pattern of diagnostic item performance . The second overarching conclusion is the relative paucity of data on the question of whether the psychopathological process involved in AUDs manifests in different ways across development in the same individuals with persistent AUDs, a question that requires more study. In the current analyses, both generations demonstrated decreases in endorsement of tolerance and an increasing prevalence of experiencing a great deal of time to obtain, use, or recover from the effects of alcohol.

There was more modest consistency across generations for endorsement of the use of alcohol in hazardous situations, but additional studies are needed to evaluate whether the specific items that change with age during persistent AUDs might differ in different populations. The relatively unique nature of the data presented here regarding changes in endorsement of specific DSM AUD items across multiple evaluations of individuals with persistent AUDs contributes to the need to emphasize some important caveats. First, the data regarding the offspring across 2 time points are especially tentative because of their relatively short follow-up. Second, it is important to remember that 2 different groups of subjects provided the data for the changes in endorsements for samples aged 21 to 27 and 31 to 43 years. Third, the samples for both AUD probands and offspring are somewhat small. Fourth, the current population is almost exclusively European American and relatively well educated, and thus, the generalizability to other ethnic and education groups is not clear. Similarly, our requirement that an AUD had to be present at multiple time points excluded subjects with less persistent AUDs and those with no alcohol diagnoses and it is possible that the current results do not rep resent a more general pattern of AUD item endorsement over time . Fifth, The SDPS selected male but not female pro bands, and no data are available on females in their fourth and fifth decades. Also, in light of the variability in the course of AUDs over time , as clinical researchers and clinicians we believe that there are assets for understanding the picture of both recent histories and vulnerabilities toward future alcohol problems from focusing on a 5-year course of alcohol problems rather than limiting our analyses to the prior 12 months as might be considered as a current condition. It is possible that a different pattern of results might have been seen with a 12-month window of alcohol problems. Next, the data collection and subsequent analyses did not include the item of craving, and thus, the applicability of the current data to DSM-5 is not clear. Finally, the data relate only to alcohol and additional studies are needed to determine the age-related patterns of changes in endorsement that are likely to be seen in individuals with other sub stance use disorders.The discovery of the cannabinoid receptors and endocannabinoid ligands has generated a great deal of interest in identifying opportunities for the development of novel cannabinergic therapeutic drugs. Such an effort was first undertaken three decades ago by a number of pharmaceutical industries, but was rewarded with only modest success. However, the newly acquired knowledge on the physiological roles of the endocannabinoid system has significantly enhanced these prospects. At the June 27, 2004 workshop”Future Directions in Cannabinoid Therapeutics II: From the Bench to the Clinic”, sponsored by the University of California Center for Medicinal Cannabis Research, we on the Scientific Planning Committee were asked to identify the areas of research with the most immediate promise for the development of novel therapeutic agents. The Committee identified four broad areas involving modulation of the endocannabinoid system as particularly promising in this regard: agonists for central CB1 cannabinoid receptors and peripheral CB2 receptors, antagonists of CB1 receptors, inhibitors of endocannabinoid deactivation, and endocannabinoid-like compounds that act through mechanisms distinct from CB1 and CB2 receptors activation. Below, we summarize the data presented at the Workshop and the consensus of its participants on the most exciting opportunities for drug discovery.BAY-387271 , a centrally acting cannabinoid agonist in Phase II clinical studies for the treatment of stroke. The interest of the pharmaceutical industry in the application of cannabinoid agonists to the treatment of pain conditions is not recent. Indeed, most of the compounds now in experimental use derive from such an interest. Historically however cannabinoid agonist development has not proved clinically fruitful, largely because of the profound psychotropic side effects of centrally active cannabinoid agonists, hence the attention given to peripherally acting cannabinoids, which exhibit significant analgesic efficacy and low central activity in animal models. Neuroprotection is a relatively new area for cannabinoid agonists, but one that appears to be already well advanced.

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

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

Given the age-related patterns of genotypic action we have described above, it is possible that the effect of alcohol consumption on the brain varies with the genotype of the cholinergic M2 receptors and the age of onset of regular drinking. specifically, when alcohol is consumed regularly in the youngest age range, perhaps better described as a particular stage in brain maturation centered in this age range, the addiction producing effects on those who have two copies of the major allele are accelerated compared to those who do not, leading to rapid transition from regular alcohol use to alcohol dependence. [This may be in part responsible for the ‘‘telescoping of trajectory’’ effects reported in Hussong et al. .] Those without two copies of the major allele may take longer to manifest the effects of alcohol use. As the age of the initiation of alcohol use increases, it appears that the cumulative risk for alcohol dependence when carried into the adult years is greater in those without two copies of the major allele than in those with two copies. We draw this last conclusion on the basis of the trend tests on our own data and the results of the studies of Wang et al.and Dick et al. . In those who become regular users of alcohol under the age of 16, a majority of those who became alcohol dependent within two years had the risk genotype; the majority of those who become alcohol dependent four years or more after their onset of regular drinking did not have the initial risk genotype.The frailty effect would play a role if there were relatively easy access to alcohol in the youngest age range, at least for those most at risk. Among those who have the major alleles, those who are genetically most vulnerable become alcohol dependent rapidly, leaving only those who have some protective factor. Thus risk for those with the major alleles will decrease with age, since those without the protective factors will have become alcohol dependent, leaving primarily those with protective factors at potential risk. We also note that if the illicit drug user population had easier access to alcohol than the entire population as a whole, the greater genetic effects seen in the illicit drug user sub-sample might in part be the result of a gene– environment interaction, akin to those described in Dick and Kendler , in which looser social controls over behavior accentuate genetic effects.

Since 80 % of the illicit drug use sub-sample are from COGA rather than community families, this is a plausible hypothesis. The specific environment of the most vulnerable group is more likely to accentuate genetic effects,cannabis grow lights rather than to diminish them.We found that SNPs reported to be significant in adults were significant in adolescents in this sample, particularly for those in the youngest age ranges, and for those who had ever used an illicit drug. However, in our results, the major allele was the risk allele, while in the results of Wang et al.and consequently of Dick et al. , the minor allele was the risk allele. Our results do not contradict those of Wang et al.and Dick et al. ; the results are mutually consistent. Instead, they reveal a novel age-specific risk factor undetectable by solely examining the condition of alcohol dependence rather than its age of onset. In view of the age differences between the sample studied in this paper, and the sample used in the studies of Wang et al.and Dick et al.it is not possible that they should contradict one another. In the Wang et al.study, about 5 % of the alcohol dependent subjects had ages of onset of less than 16 years of age. This is too small a fraction to have an effect on the results. As we noted in our discussion of the trend tests, in our study the genotypic distributions of the alcohol dependent subjects change with age of onset. While we do not observe a significant SNP effect in the oldest age range with DTSA, the fraction of subjects with the minor allele in those who become alcohol dependent is greater than the fraction of subjects with the minor allele in those who do not become alcohol dependent . This trend acts to produce a similar genotypic distributions for alcohol dependent and non alcohol dependent subjects when considered regardless of age of onset. In terms of the methodology, DTSA requires that there be differences in genotypic distributions between alcohol dependent and non alcohol dependent subjects to give a statistically significant results for a SNP; this is not true for the family based method used by Wang et al. .Our interpretation is that family based studies are more powerful than the type of association study employed here; the absence of a distributional difference does not mean that there is no genetic effect.In the age ranges and samples in which we found that ERO was significant for the onset of alcohol use or alcohol dependence, it was the lower values which characterize the risk factor, which is consistent with the results in adolescents and young adults in the studies by Rangaswamy et al. , Kamarajan et al. , and Gilmore et al. .

That no effects of regular alcohol use on ERO values were found is consistent with similar results obtained by Perlman et al. .It is important to note that the objectives of the twin studies considered here and of this study are quite different. The twin studies investigate the presence of a ‘‘disease’’ condition, although exactly which condition varies considerably among studies.The objective of this study, as a survival analysis, is to analyze the factors contributing to an event, the onset of a condition. Once the condition has come to pass, it is not of further interest in survival analysis. The genetic effects which produce the condition are only significant at the onset of the condition, and their effects persist only if the subsequent onset of the condition in other subjects is attributable to them.That is, in the longitudinal studies using multistage models, the affected subjects are retained throughout the study subsequent to their becoming affected, while in the survival analysis method used in this study, the affected subjects are removed from consideration in the study once they have become affected, and no longer influence the results. Therefore, although the use of a longitudinal multi-stage model in van Beek et al.and Baker et al.enables genetic influences to have age-specific characteristics, these effects are modeled as persisting through time as a result of an effect at a single age range. If early onset alcohol use is associated with the more genetically determined form of alcoholism then it would be expected that genetic factors leading to early drinking and dependence would be manifest. Our results are consistent with this hypothesis. The pattern of genetic results obtained here, albeit from a single gene, is weighted towards the strongest effects manifesting.Originally formulated over twenty years ago, and recently updated, the neural diathesis-stress model proposes that the hypothalamic-pituitary-adrenalaxis is the central physiological mechanism linking psychosocial stress to the onset and exacerbation of schizophrenia and related psychotic disorders . A central tenet to this model is that individuals with increased vulnerability for psychosis are more sensitive to the effects of psychosocial stressors due to abnormalities within the HPA axis which in turn contribute to dopaminergic and glutamatergic abnormalities that eventually trigger expression of psychotic illness . In support of the model, accumulated evidence indicates that patients with psychosis exhibit elevated basal cortisol relative to healthy controls , but a blunted cortisol awakening response [CAR ], the latter thought to represent a distinct HPA axis component, independent of stress-induced cortisol secretion .

For participants with regular drinking, we asked participants how many drinks they consumed in a typical day using a question modified from NSHAPC.If participants drank 5 or more equivalents in a day, we classified this as binge drinking.We asked participants to report if they had ever received treatment for use of alcohol or illicit substances. Participants self-reported their health status,which we dichotomized as fair or poor versus good, very good, or excellent. Based on the National Health and Nutrition Examination Survey , we asked participants to report whether a health care provider had told them that they had diabetes, emphysema or chronic obstructive pulmonary disease , asthma, stroke, coronary artery disease or a heart attack, congestive heart failure, cirrhosis, or cancer.We asked participants whether they had tested positive for HIV infection or had ever been told they had AIDS. To assess functional status, we asked participants if they had difficulty completing individual ADLs because of a physical, mental, emotional, or memory problem using the questionnaire developed by Katz.Using logistic regression, we assessed bivariate relationships between independent variables and the two dependent variables, moderate or greater severity alcohol symptoms , and moderate or greater severity symptoms for any illicit substance . We dichotomized race to African American versus non-African American because there were no significant differences among white, Asian, Latino, and other participants in the odds of substance use outcomes when only these participants were included. To construct multivariate models,cannabis growing equipment we selected independent variables based on bivariate relationships with p≤0.20 and performed backward stepwise elimination, retaining independent variables with multivariate p≤0.05.

As a sensitivity analysis, we created an alternate model including only participants with active illicit drug use in the previous six months to examine if participants who were scored with moderate severity symptoms for the ASSIST based on significant cravings alone differed significantly from those who were actively using.HOPE HOME participants had a median age of 58 years . Over three-quarters, 77.1%, were male, and 79.1% African American; 21.7% were veterans. Approximately a third had PTSD symptoms and 38.3% had major depressive symptoms; 22.3% had both depressive and PTSD symptoms.Nearly half experienced their first episode of homelessness after they turned 50 years old.Almost a third had ever been suspended or expelled from school.About a third experienced physical abuse as a child, while 13.2% experienced sexual abuse as a child. Approximately half experienced physical abuse as an adult, while 13.2% experienced sexual abuse as an adult. The majority, 55.7%, reported fair or poor health status, and 38.9% reported they were dependent in one or more ADLs. Almost two-thirds of our sample, 63.1% had used an illicit substance in the last 6 months, and 64.6% had moderate or greater severity symptoms for at least one illicit drug, with 14.5% reporting severe symptoms . Almost half, 49.2% had used alcohol in the last 6 months, while 25.8% had moderate or greater severity alcohol use, with 14.6% reporting severe symptoms. Approximately a tenth of HOPE HOME participants reported binge drinking and 60% drank at least three times a week to get drunk at some point in their life. For illicit drugs, the drugs most commonly used in the last 6 months included cannabis with 48.0%, cocaine with 37.7%, opioids with 7.4%, and amphetamines with 7.1%. The three most commonly reported drugs with moderate or greater severity symptoms were cocaine,cannabis,and opioids . For participants with ASSIST-defined moderate or higher severity illicit drug symptoms, 91.6% had used an illicit substance in the last six months. For cannabis, 92.7% of participants with moderate or higher severity symptoms had used that specific substance in the last 6 months: 79.5% for cocaine, 67.8% for opioids, and 67.9% for amphetamines. All participants with high severity illicit drug use, and all participants with moderate or greater severity alcohol use had used in the last 6 months. A smaller proportion reported injecting drugs in the last 6 months.

Almost a third reported moderate or greater severity symptoms for more than one illicit substance; 21.4% reported moderate or greater severity symptoms for both cannabis and cocaine. Less than a tenth of the sample used illicit non-cannabis drugs regularly, three times a week or more, prior to age 18, while 36.6% used cannabis regularly and 15.1% used alcohol regularly before age 18. 1.3.3 Multivariate Analysis In multivariate models , having been expelled or suspended from school was associated with moderate or greater severity illicit drug symptoms , as were having a history of psychiatric hospitalization,and having one’s first episode of adult homelessness prior to the age of 50 . In a multivariate model examining factors associated with moderate or greater severity alcohol symptoms, expulsion/suspension from school , male sex and the presence of major depressive symptoms were associated. Neither age, race/ethnicity, veteran status, education, PTSD symptoms, nor a history of sexual or physical abuse were associated in either model. An alternate modeling strategy that restricted moderate or greater severity illicit drug symptoms to those with active current use, as opposed to including all who met moderate severity ASSIST scores, changed p-values less than 10%. In the alternate model history of psychiatric hospitalization was no longer significant. In a sample of homeless adults aged 50 and older, we found high prevalence of substance use, with 14.5% reporting severe illicit substance symptoms compared to 6% of a sample of homeless-experienced adults of all ages engaged in primary care.When comparing current illicit substance use of HOPE HOME participants to a community-based sample that included all adults from 1996, NSHAPC, we find higher current illicit substance use, 63.1% vs. 23%.Moderate or greater severity alcohol use was high, with 25.6% of patients reporting moderate or greater severity alcohol use compared to 4.6% of adults of all ages in a VA primary care clinic.When comparing current binge drinking of HOPE HOME participants to NSHAPC, 10.3% of HOPE HOME participants reported binge drinking compared to 19% of NSHAPC participants.Approximately three-fifths of both HOPE HOME participants, and NSHAPC participants drank at least three times a week to get drunk at some point in their life.Participants were medically complex. They reported a high prevalence of chronic conditions, ADL dependencies,cannabis grow racks and poor health status, and therefore had an elevated risk of harm from substance use.

Consistent with prior research, we found that psychiatric hospitalization and depression were associated with substance use.The association between psychiatric hospitalization and illicit substance use is likely bidirectional.Individuals with SUDs may exhibit severe behavioral symptoms such as hallucinations, disorganization, or aggressive behavior that may lead to psychiatric hospitalization.The association of depressive symptoms with moderate or greater severity alcohol symptoms, and psychiatric hospitalization with moderate or greater severity illicit drug symptoms, has clinical relevance to programs designed to address substance use in older adults. An ideal program would integrate treatment of mental health conditions with substance use disorders. There are limited numbers of geriatric psychiatrists, particularly those who work in urban under served populations.They may be ill-equipped to accommodate an older adult with multiple medical comorbidities and functional dependencies. Young adult life experiences prior to age 50, specifically onset of homelessness prior to age 50, and a history of expulsion or suspension from school, were associated with participants’ later substance use. Substance use may be an important cause of homelessness for younger adults.In contrast, other causes such as medical illness, financial hardship, or loss of social support may be more likely to cause homelessness for adults who become homeless later in life.The finding that at-risk illicit drug use is associated with a history of homelessness earlier in life is germane to public health programs seeking to prevent incident homelessness in younger adults. The only factor associated with both moderate or greater alcohol and illicit substance symptoms was a history of expulsion or suspension from school. Suspension and expulsion could be a marker of early substance use.

Prior research has shown that students who attend schools that suspended or expelled for drug infractions at high rates, while controlling for substance use prevalence, were more likely to have higher prevalence of substance use at one-year follow-up.Unintended negative consequences of suspension and expulsion include disengagement from school, loss of social support, and increased risk of arrest.Adults who become homeless earlier in life tend to have more early life adverse experiences such as mental health, imprisonment, and substance use.44 It is possible that the association between suspension or expulsion from school and greater severity illicit drug and alcohol use is a reflection of the impact of early life experiences on the risk of developing risky substance use later in life. When we compare HOPE HOME participants’ illicit drug use prevalence to NSHAPC, we find higher prevalence of substance use for HOPE HOME participants, despite the HOPE HOME participants reporting on a shorter duration of time and all being age 50 and older . Our primary explanation is that adults born in the baby boom have different substance use patterns than those born in prior generations. This is supported by literature in the general population.45 However, we cannot exclude the possibility that local differences in substance use prevalence could contribute to the observed difference. Other alternative explanations are less likely. A higher percentage of HOPE HOME participants who were age 50 and older had been homeless for a year or more compared to NSHAPC adults of all ages, 67.1% vs. 55%. However, this is unlikely to account for the difference. Other data has shown that, regardless of substance use behaviors, there is a trend in increasing duration of homelessness in the United States.15 Another alternative explanation is that HOPE HOME included individuals who did not access or had limited contact with homeless services, and therefore had less access to treatment interventions. However, only 1.6% of HOPE HOME participants did not access any services in the last six months, meaning that this difference alone is unlikely to contribute to the differences we found in substance use prevalence. In spite of these possible alternate explanations, we believe that the magnitude of difference suggests that illicit substance use is higher in older homeless adults than was noted twenty years ago. The older homeless population now is made up of people born in the baby boom. Contemporary older homeless participants experienced the crack cocaine epidemic in their young adult lives. Data from the general population suggests that individuals born in the baby boom have a higher prevalence of substance use than those born in previous decades. We found lower prevalence of binge-drinking in HOPE HOME participants. The younger age distribution of NSHAPC participants may be responsible for the observed differences in binge drinking, as binge drinkers are less likely to survive to late adulthood.46 Our study has several limitations. We were not able to account for clustering of our sample among some sites as we did not have accurate counts of numbers of unique visitors at each site. We do not consider recruitment sites to be clusters because of the mobility of the population and the tendency of participants to frequent multiple venues of recruitment. Given that our sample was predominantly African American, and had a narrow age range, we were not powered to examine use by race and ethnicity, or age. A potential concern with usage of the ASSIST is that some participants were classified as having moderate severity illicit drug symptoms despite not having used that particular substance in the last 6 months, i.e. participants with remote use but active cravings for an illicit substance. The ASSIST is designed to identify patients at risk of harm from substance use and in most need of intervention. We chose to include these participants in our modelling strategy as this ASSIST score is clinically relevant. . However, one variable, history of psychiatric hospitalization, was no longer significant when excluding those without active use. With high prevalence of substance use in older homeless adults, there is increasing evidence of negative effects of substance use. When the median age of the homeless population was younger, the majority of substance use-related mortality in the homeless population occurred in younger homeless adults.However, between 2003 and 2008, older homeless adults’ mortality attributed to illicit drugs approached that of younger adults and older homeless adults’ mortality attributed to alcohol exceeded that of younger adults.

The depth of this understanding, specifically the molecular consequences of adolescent nicotine use, allows for individualized treatment plans with a greater emphasis on medication interactions, care coordination, community resources, education, and advocacy. These clinical adjustments may contribute to decreases in addiction and drug-related emergencies.Prior to drafting this manuscript, the two authors independently evaluated and summarized research articles that addressed adolescent substance use and nicotine’s impact on the developing brain and behavior. We conducted a comprehensive review of the literature using a two- to three word combination of the following keywords: adolescence, substance use, nicotinic acetylcholine receptors, gateway, reward, smoking, tobacco, nicotine, alcohol, psychostimulant, cocaine, amphetamine, cannabis, opioids. We utilized the electronic databases of PubMed and Google Scholar for research articles published in English between January 1968 and November 2018. Articles were included in the review if they discussed nicotine exposure during adolescence, drug sequence patterns, or adolescent substance use. The references from relevant articles and websites of relevant organizations were also examined for other potential sources of information. Out of 80,000 initial search results, approximately 5,000 were reviewed as relevant and non-duplicate articles. To retain focus on adolescent initiation of nicotine products, studies related to maternal tobacco or nicotine exposure were excluded. Studies evaluating other interventions were also excluded to maintain focus on nicotine’s effects on brain function and behavior. We grouped studies together according to their methodological similarities, so findings without substantial support or reproducibility were excluded. Following exclusion and careful analysis of studies based on key results, limitations,cannabis drying racks suitability of the methods to test the initial hypothesis, and quality and interpretation of the results obtained, 174 references were selected.

The use of two reviewers and two extensive electronic databases allows for a widespread range of research articles, which maximizes scientific credibility and minimizes potential bias.Reward and reinforcing efficacy are measured in animals with drug self-administration on fixed and progressive ratio schedules of reinforcement, intracranial self-stimulation, oral intake, inhalation, and/or conditioned place preference. Although common drugs of abuse, like marijuana, cocaine, alcohol, and opioids, act on different neurotransmitter systems, they all exert their reinforcing effects via the mesolimbic pathway, a dopaminergic pathway that connects the ventral tegmental area to the nucleus accumbens.The development, projections, and functions of this pathway are strongly influenced by acetylcholine, glutamate, serotonin, and GABA.Dopamine release into the nucleus accumbens regulates motivation and desire for rewarding stimuli and facilitates reward prediction.As nAChRs modulate dopamine release, the gateway hypothesis posits that adolescent nicotine exposure primes the brain’s reward system to enhance the reinforcing efficacy of drugs of abuse.Substantial epidemiological data suggest that teenagers are more vulnerable than adults to nicotine dependence following minimal tobacco exposure , and individuals who begin smoking during adolescence are more likely to experience difficulty quitting than those who start as adults.Indeed, 90 percent of adult smokers started before age 18.Event-related functional neuroimaging studies in children, adolescents, and adults suggest that children and adolescents have over-reactive reward responses and improved task performance when earning rewards, suggesting enhanced engagement in behaviors that result in immediate gratification.Animal models allow for experimenter-controlled administration of nicotine and investigation of its direct consequences on the brain and behavior through neuroimaging, biochemical assays, and behavioral tests. Early adolescent rats exposed to intravenous nicotine levels equivalent to one to two cigarettes per day for four days self-administer a greater amount of cocaine, methamphetamine, and alcohol compared to adolescent rats not exposed to nicotine, as well as compared to exposed and unexposed adults.

These data strongly suggest that adolescent nicotine use increases the reinforcing effects of other drugs. In addition, adolescent, but not adult, rodents exposed to nicotine display disruptions in hippo campal learning, long-lasting depressive phenotypes, changes in cocaine sensitivity and reward, enhanced drug-related learning, and deficits in impulse control, executive function, and cognition.Improved drug-related learning following brief nicotine exposure during early adolescence is characterized by rapid initiation and cue association of cocaine and amphetamine self-administration, which is indicative of an addictive-like phenotype and is not observed in adolescent and adult controls or adults also pretreated with nicotine.Furthermore, heightened depressive- and anxiety-like behaviors after 30 days of nicotine abstinence in mice exposed as adolescents, but not adults, indicate that nicotine exposure and withdrawal can have long term effects on emotional and cognitive functioning, particularly when nicotine exposure occurs during adolescence.The exact timing of exposure during adolescence is also significant, as nicotine’s effects are far greater during early adolescenceversus late adolescence or adulthood Behavioral alterations brought on by developmental nicotine exposure are driven by molecular mechanisms, including epigenetic influences, synaptic activity, and receptor signaling and regulation.Adolescent, but not adult, nicotine exposure in rodents results in the expression of distinct subunits of nAChRsand persistent nAChR upregulation in the midbrain, cerebral cortex, and hippocampus.Due to the role of nAChRs in neurotransmitter release and reward processing, alterations in their quantity and function influence reward behavior. In addition, brief nicotine exposure in early adolescent rats enhances cellular activity, dopamine D2 receptor signaling, and serotonin 5-HT receptor function in brain reward areas compared to adult rats also exposed to nicotine.Moreover, chronic nicotine exposure during, but not after, adolescence alters gene expression in the ventral tegmental area and stimulates hyper responsiveness of dopaminergic nerve terminals in the medial prefrontal cortex.These nicotine-induced changes in reward-related neurotransmitters and brain regions during adolescence may contribute to alterations in reward regulation and behavior. The changes in brain function and behavior from developmental nicotine exposure are long lasting and a consequence of manipulation of the brain’s reward network, including the prefrontal cortex, nucleus accumbens, ventral tegmental area, hippocampus, and basolateral amygdala.

Specifically, adult rodents exposed to nicotine as adolescents show a persistent increase in deltaFosB in the nucleus accumbens, impaired GABA signaling in the ventral tegmental area, and changes in brain morphology and gene expression in reward regions.Furthermore, adult rodents exposed to nicotine as adolescents have an increased preference for cocaine, amphetamine, opioids,hydroponic cannabis system and higher doses of nicotine.The following section reviews in greater detail the impacts of adolescent versus adult nicotine exposure on subsequent drug use in animal models.The developments of alcohol and tobacco use patterns are closely related among teenagers, but the order of progression is not universal among cultural and ethnic demographics.Alcohol and nicotine products are more frequently co-abused than consumed separately, as a survey of high school seniors revealed that 88 percent of smokers were drinkers, while 55 percent of nonsmokers were drinkers.However, tobacco use predicts subsequent alcohol use better than the reverse.Individuals who initiate smoking before age 17 are at a higher risk of alcohol abuse and dependence than those who begin after 17.These studies lead to the hypothesis that adolescent exposure to nicotine may lead to enhanced alcohol intake later in life. Adolescent susceptibility to co-use of nicotine and alcohol is also observed in rodents, as concurrent self-administration of both drugs in adolescent, but not adult, rats is reinforcing and leads to an increase in subsequent oral alcohol intake.Moreover, a different nicotine exposure paradigm promotes long-lasting increases in alcohol self-administration exclusively in nicotine treated adolescents.Nicotine exposure during adulthood can also change subsequent alcohol consumption, which indicates the influence of nicotine on alcohol reward and reinforcement; however, enhanced alcohol intake is more likely to occur if nicotine is administered prior to alcohol access.These findings collectively indicate that nicotine exposure during adolescence enhances alcohol consumption more than if the same exposure occurs later in life. In humans, adolescent exposure to nicotine influences the likelihood of other psychostimulant use, including cocaine and methamphetamine.Data from a 1994 National Household Survey on Drug Abuse report that individuals who smoked cigarettes before age 15 were up to 80 times more likely to use illegal drugs than those who did not, with cocaine being the most likely drug to be used among young cigarette smokers.

A separate study of a cohort representative of the U.S population revealed that the rate of cocaine dependence was highest among cocaine users who initiated cocaine after having smoked cigarettes , and the rate of dependence was much lower among those who initiated cocaine before smoking .Preclinical studies also demonstrate associations between adolescent nicotine exposure and psychostimulant consumption. Chronic nicotine exposure differentially alters cocaine-induced locomotor activity and intravenous cocaine self-administration in adolescent versus adult rodents.Adolescent rats exposed to nicotine become considerably more sensitized to the locomotor-activating effects of cocaine compared to non-exposed adolescents.Nicotine exposure during adolescence, but not adulthood, also encourages increased self-administration of cocaine during adulthood, suggesting that nicotine use may carry a greater risk during adolescence than adulthood.The effects of adolescent nicotine pretreatment on psychostimulant reinforcement and locomotor activity are mediated by nAChRsand serotonergicreceptors.In addition, chronic and sub-chronic nicotine-exposed adolescent rats experience greater preference for and self-administration of cocaine and methamphetamine versus saline-exposed rats.Pre-adolescent nicotine exposure in rats also leads to increased cocaine-primed reinstatement, a model of relapse behavior.In contrast, alcohol pre-exposure in rats does not influence subsequent cocaine self-administration or cocaine relapse behavior, highlighting the unique gateway effects of nicotine on psychostimulant use.In addition to the enhanced use of alcohol and psychostimulants following early nicotine use, cigarette smoking in adolescents and young adults is associated with earlier onset of cannabis use, more frequent cannabis use, and a larger number of cannabis use disorder symptoms compared to those who did not smoke cigarettes.Likewise, teens who use e-cigarettes or hookah are more than three times more likely to use marijuana, and cannabis users report that nicotine enhances the pleasurable effects of tetrahydrocannabinol , the main psychoactive constituent of marijuana that exerts its effects via cannabinoid receptors.The endocannabinoid system, which comprises cannabinoid receptors and endogenous ligands throughout the central and peripheral nervous system, plays an important role in cognition, learning and memory, pain relief, emotion, stress, and reward processing.Although little research has been done on nAChRs interactions with THC specifically during adolescence, preclinical findings in adults suggest that cholinergic and endocannabinoid systems interact to modulate reward related processes.Selective antagonism of α7 nAChRs in rats blocks the discriminative effects of THC and reduces intravenous self-administration of a cannabinoid CB1 receptor agonist .This association appears to be bidirectional, as blockade of CB1 receptors reduces nicotine self-administration in rats.THC impacts adolescents and adults distinctively, where adolescent rats experience less of THC’s anxiogenic, aversive, and locomotor-reducing effects than adult rats.Nicotine also facilitates THC’s hypothermic, antinociceptive, and hypolocomotive effects in mice.Sub-chronic nicotine exposure in adolescent rats induces long-lasting effects in cannabinoid CB1 receptors, including increases in the hippocampus and decreases in the striatum.The association between nicotine and cannabis use and the role of reward processing in both the cholinergic and endocannabinoid systems encourages the hypothesis that nicotine may encourage and perpetuate cannabis use.The endogenous opioid system is primarily involved in pain relief, reward processing, emotion, stress, and autonomic control, and consists of 3 families of receptors: mu, delta, and kappa.Opioid receptors located in the brain and periphery are activated endogenously by enkephalins, dynorphins, endorphins, and endomorphins, as well as exogenously by opioids . Enkephalins, endorphins, endomorphins, and opioids act primarily through mu opioid receptorsto reduce pain perception, while dynorphins preferentially act at kappa opioid receptorsto regulate appetite, stress, and emotion. Mu and delta opioid receptors play a critical role in drug reward, whereas the KORs participate in drug aversion.Although opioid use has not been extensively evaluated during adolescence, an abundance of clinical and preclinical evidence suggests an important bidirectional relationship between nicotine use and opioid reward.Activation of nAChRs can influence excitability of opioid-containing neurons, and nicotine-induced dopamine release in the nucleus accumbens is dependent on activation of MORs in the ventral tegmental area.Furthermore, nicotine induces a release of endogenous opioids in the brain, and repeated exposure to nicotine can alter expression and/or functioning of opioid receptors.Perhaps unsurprisingly, given the significant overlap of cholinergic and opioidergic systems, clinical data show that treatment with naloxone and naltrexone, both opioid receptor antagonists, reduces tobacco smoking and craving for tobacco smoke.In addition, opioid-dependent smokers present with more severe nicotine dependence, respond poorly to smoking cessation medications, and may have a higher risk of relapse compared to non-opioid dependent smokers.The relationship between nicotine and the opioidergic system is similarly substantial in preclinical studies, which is important given the roles of both systems in reward processing.In addition, blocking nicotinic receptors reduces rewarding effects of morphine, and activation of MORs decreases nicotine withdrawal symptoms.