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Ignorance leads to stigma, but with increased education and awareness, more are starting to be receptive of the fact that it is a general disease. Ghanaians, and most people in the world for that matter, view mental illnesses differently than physical illnesses because physical illnesses are tangible, easy to comprehend, and are generally easily treated with the right medication. People are more likely to attribute supernatural causes to things they do not understand. The average Ghanaian view is the same for both the mentally disabled and the mentally ill. Though epilepsy is a neurological condition and not a mental illness, people with epilepsy are also considered to be mentally ill in Ghana because they share the same stigma and because they have been historically treated by psychiatrists due to the lack of neurologists. The common Ghanaian perception of mental illness is changing. It was very troublesome for someone who was mentally ill, or related to someone who was mentally ill, to be married some time ago when families ran heritage checks for eligible bachelors or bachelorettes to be arranged in marriage. Now that families are becoming more independent and nuclear and the Western importance of romantic love is becoming a driving factor in marriage, a person who was mentally ill will no longer be completely disregarded as a potential mate. Also, in order to vote or become president it is written in the constitution that you “should be of sound mind, which becomes misinterpreted as denying the right to vote to anyone who has ever had a mental illness. There are many other unwritten rules that prevent the mentally ill from attaining full access to human rights. For example, a person might be evicted from an apartment if the property owner finds out that the person has, or has had, a mental illness. Although you would not be asked whether you have ever had malaria or AIDS at a job interview, it is commonplace in Ghana to ask if you have ever suffered from a mental illness,pot for growing marijuana which then becomes viable grounds for being denied the job. You can also be fired or denied a promotion if a co-worker discovers that you had or have a mental illness, though another random reason for dismissal is usually given.

Although there is no policy that denies access to school, the attitude and stigma held by peers and faculty often leads a mentally ill person to drop out of school. Up until three years ago, if there was an international event or conference planned, it was common practice for police to round up all of the wayfarers on the main streets and dump them at the psychiatric hospital or on the outskirts of town. Fortunately, Mind Freedom and Basic Needs spoke against this inhumane action and it has not occurred since. Due to a plethora of challenges the countries have to face, mental health in Africa is largely marginalized. Most African countries do not have mental health laws and the others have out dated, forty to fifty year old laws that were written when human rights were not an issue. On a scale from one to ten, Dr. Osei rated the quality of mental health care in Ghana as a four. All hospitals in Ghana are underfunded with 94% of the budget being spent on paying the necessary salaries of medical professionals and the remaining 6% going into running the hospitals. On average, the government allocates mental healthcare with 2.58% of the total health budget which is strictly limited to finance just the three psychiatric hospitals and not community care. The funding by the Ministry of Health has been unstable since 2003 because psychiatric care does not appear to address urgent, life-threatening issues. The funding is not based on needs but rather on limits set by the Ministry of Finance. Politicians in Ghana do not want to give attention to mental illness, a sickness with low morbidity, when high fatality conditions grab more national and international attention. Because of this and its stigma, mental health care receives little donations from charities. Amegatcher, Adico, and Taylor respectively rated the quality of Ghana’s mental health care on the same scale as a four, two, and five. These low scores were supported by the lack of resources and funding available to psychiatric hospitals and the lack of priority in the government’s agenda. The belief in superstition also deprives the mentally ill in Ghana of sympathy and compassion.

This combination of ignorance yields the mentally ill vulnerable to suffering human rights abuse, leading to Dr. Osei’s low rating. Fortunately or unfortunately, Dr. Osei believes that Ghana’s mental health care system is one of the best in West Africa besides maybe Nigeria. Instead of facilely increasing the number of psychiatric hospitals in Ghana, Dr. Osei wants to create 20-bed psychiatric wings in every regional hospital and 12-bed wings in every district hospital. Right now only five of ten regional hospitals have 20-bed psychiatric wings. General medical practitioners should also start receiving some training in psychiatric care so they can better treat their patients and discern when to refer them to a psychiatrist if necessary. The Chief Psychiatrist also wants to downsize the three psychiatric hospitals,container for growing weed ultimately changing Accra Psychiatric Hospital’s admittance from 1,200 to 300 patients, Pantang from 500 to 200, and Ankaful from 300 to 100 in-patients. The downsizing of the large hospitals and the creation of small wings throughout the whole country will deinstitutionalize the mental health care system in Ghana so it can ultimately focus on community care. Dr. Osei finds that many Ghanaians now believe that mentally ill patients can lead a happy, healthy life after treatment, but still there are only two rehabilitation services in all of Ghana that help reintegrate mental patients into society. These facilities are run by Catholics in Kumasi and discharged patients who permanently live near the Ashanti Region are sent there after treatment to learn some trade. Dr. Osei recommends that these services should be replicated and that there should be at least one rehabilitation resource in every region. The Pantang hospital would like to establish a Half-Way home for rehabilitation of chronic patients , start a fish pond rehabilitation project, develop an addiction outpatients clinic hot line, equip the laboratory, records, and pharmacy departments with a software, utilize a computerized data system, create a web page, expand a Drug Rehabilitation Centre, build more staff accommodation units, ensure accessibility to needed medications at the pharmacy, increase security, focus on prevention, recovery, and relapse-reducing programs and activities, and enhance staff morale by providing better incentives, training, equipment, and uniforms.

The Pantang Hospital is also working on a proposal to create an evaluation ward which would help to avoid long-stay patients and streamline the diagnosis and welfare process. In this ward the patients would be observed for a maximum of 72 hours by a specialized screening team in order to make sure the patients’ diagnoses are correct and that they require admittance into the hospital.The most recent mental health law, written in 1972 when international human rights was not much of a concern, also needs to be updated. Both the Chief Psychiatrist and Mind Freedom were involved in the drafting and advocacy of the new Mental Health Bill. The bill will address a lot of setbacks in the mental health system. If passed, the Mental Health Bill will commit the government to release more funds and resources for mental health care , train more mental health personnel including psychotherapists and counsellors, give incentive for people to work in mental health care, provide newer generation medicine, overhaul and decentralize the hospital-based system and make mental health care more community based, create an anti-stigma and education campaign, and protect the human rights of the mentally ill. Right now there are no checks for human rights abuses of the mentally ill, and this bill will make it illegal to put the mentally ill in chains and a new standard committee will work closely with prayer camps to oversee and enforce the upholding of all human rights. All in all, the Mental Health Bill will ensure effective treatment for the mentally ill and the law will serve as a standard for other African countries to follow. The bill was submitted in 2006 and did not reach parliament until the end of 2010, where it is sitting to this day. It took four years before the government bothered to address the situation simply because they did not value the issue. Mental illness is such a low priority for the government because of the stigma that exists even in the minds of politicians and because mental health disorders have a low fatality . Though mental illnesses do have a low morbidity, mentally ill people experience many years living with pain, stigma, lifestyle changes, complicated therapeutic regimes, the long-term threat of decline, and shortened life expectancy. With a lack of general funding for healthcare, more money is given to high fatality, international attention-grabbing physical diseases like malaria, AIDS, TB, cancer, etc. Now, after the advocacy from doctors and NGOs bombarded the media, the Ministry of Health is finally being forced to change their stance on mental health care. The Parliament is currently conducting consultations and is reviewing the bill to guarantee that fragmentation of the mental system is what is best for Ghana. Mind Freedom and Dr. Osei hope that the bill will be passed by June 2011, and if it is not, then Dr. Osei flippantly said he will personally march all of his patients at the Accra Psychiatric Hospital down to the Parliament building to fight for their rights. Dr. Osei hopes that the long struggling advocacy for mental health improvement will not lose steam and keep pushing until the bill is passed and even after to ensure the implementation of the law. Immediately after the bill is passed, he advises that a mental health board needs to be established with the purpose of overseeing the implementation of the bills requirements and the training of judiciaries, policemen, mental health personnel, nurses, and traditional faith healers in the law’s policies. He wants Ghana to have state-of-the-art mental health care which delivers care to the doorsteps of every Ghanaian, provides a wide range of medicine, is part of the national health insurance scheme, employs mental health personnel of various categories, and is adequately funded and operated by motivated leaders and supported by research and evidence based data. This could be achieved by having one of the best mental health laws in the world and by removing the emphasis from hospital based care to community care. Similar to Dr. Osei, Mind Freedom thinks that Ghana’s mental health system should change from institutional care to community care. The hospitals should be decongested, CPNs should be given transportation to move between communities, newer medication should be used, and mental health workers should be given more incentives and should be covered by insurance. Most importantly, psychiatrists need to more frequently go into the community, human resource needs to increase, and medication needs to be more available. Also, the perception of mental illness needs to be worked on. Stigma makes the situation drastically worse and makes people less likely to seek treatment even when it is important to seek early treatment so the problem does not aggravate. Despite the Accra Psychiatric Hospital’s disturbing conditions and appalling lack of resources, Dr. Osei’s undaunted and resolute passion for mental health is leading the country towards progress. In the beginning of 2011, Dr. Osei launched a repatriation of 600 recovered patients, whose families could be tracked down, to be discharged and returned home. Dr. Osei oversees each case to make sure that each discharged patient is well enough to go home and that they have a family or home to return to. So far the repatriation has been successful in decongesting the hospital, as 200 patients have been discharged by March 2011 and the total of 600 is expected to be achieved by June 2011.

The dependent variable was drinks per drinking day in the last week of the study.This was the first study to evaluate the effects of ibudilast, a neuroimmune modulator, on mood and drinking outcomes in a clinical sample with AUD. Contrary to our hypothesis, ibudilast did not have a significant effect on negative mood on drinking or non-drinking days. However, in support of our hypotheses, ibudilast significantly reduced the probability of heavy drinking compared to placebo. Ibudilast also significantly attenuated alcohol cue-elicited activation in the bilateral VS. Furthermore, exploratory analyses indicated that ventral striatal activation to alcohol cues was predictive of drinking in the week following the neuroimaging scan. These results suggest a bio-behavioral mechanism through which ibudilast acts, namely, by reducing the rewarding response to alcohol cues in the brain leading to a reduction in heavy drinking per se. Unexpectedly, this study did not find support for an effect of ibudilast on negative mood or a moderating effect of baseline depressive symptomology on medication response. This contrasts with previous findings from our lab in which ibudilast improved mood response to stress and alcohol cues. The current study differs from the previous study in several important methodological variables including using a between-subjects instead of a crossover design and the use of a daily-diary mood reporting approach compared to tightly controlled human laboratory experimental paradigms. Furthermore, the current study did not directly evaluate the effect of drinking on mood, which would be more comparable to the findings reported previously. Additionally, this study recruited individuals with mild-to-severe AUD. Negative mood states and negative reinforcement driven drinking may only occur at more severe presentations of AUD; therefore,cannabis grow tent the present study may have been under powered to identify medication effects on negative mood symptoms.

Regarding the drinking outcomes in this study, IBUD significantly reduced the probability of heavy drinking compared to placebo. Specifically, individuals treated with IBUD were 45.3% less likely to drink heavily compared to individuals treated with placebo. This resulted in a 24% predicted probability of heavy drinking over the course of the study in the ibudilast group, compared with a 37% predicted probability in the placebo group. Of note, there were no significant differences in AE’s between groups, indicating that this reduction was not due to increased side effects, including nausea, in the IBUD group. There was not a significant effect of IBUD on the probability of overall drinking compared to placebo. While non-significant, the effect of IBUD for any drinking days was in the expected direction, such that individuals on IBUD were 16.9% less likely to engage in any drinking relative to placebo, but high variability in the prediction prevented conclusive statistical findings. This non-significant effect may not be surprising, as the study sample was comprised of non-treatment-seekers and therefore not motivated to abstain from drinking altogether. Rather, participants treated with IBUD reduced their heavy drinking, which produces a harm reduction benefit, particularly for those with a mild-tomoderate AUD. This finding is also consistent with preclinical studies, where treatment with ibudilast reduced ethanol intake by 50% under maintenance conditions.Importantly, the drinking results combined with the AE reports indicate that ibudilast is a safe medication for individuals who are still drinking and may want to reduce their drinking. IBUD also reduced craving on non-drinking days, at trend level, as compared to placebo. This effect supports our previous finding of a reduction in tonic craving under ibudilast during a week-long human laboratory study during which participants were instructed not to drink. This study also examined a potential bio-behavioral mechanism underlying IBUD’s action using an fMRI alcohol cue-reactivity paradigm.

IBUD attenuated alcohol cue-elicited reward activation in the VS compared to placebo. PDE4 and PDE10 are highly expressed in the striatum and negatively regulate dopaminergic signaling. Thus, inhibition of these PDEs through IBUD may reduce striatal excitability to alcohol cues. In rats IBUD reduced morphine-induced nucleus accumbens dopamine release. Moreover, IBUD has been shown to enhance the production of neurotrophic factors, including glia-derived neurotrophic factor, which is a critical survival factor for dopamine neurons. Preclinical findings indicate that infusion of GDNF normalizes dopamine levels in the ventral tegmental area and the VS and reduces alcohol seeking and alcohol consumption. In humans with AUD, GDNF levels are reduced in blood serum samples.Furthermore, in individuals with AUD, presentation of alcohol cues reduced interleukin-10, an anti-inflammatory cytokine, and the level of reduction was correlated with increased alcohol craving. Thus, though the underlying molecular mechanism is still unknown, this finding indicates that ibudilast may normalize the dopaminergic response to alcohol cues in individuals with AUD. This study has several strengths and limitations which should be considered when interpreting the results. Study strengths include the use of daily diary reporting, which captures real world drinking and minimizes recall bias, and the combination of neurobiological with behavioral and self-report methodologies. However, this study recruited a non-treatment seeking sample; therefore, these findings may not generalize to a treatment-seeking sample with AUD . An ongoing randomized controlled trial of IBUD in treatment-seeking individuals with AUD will address this open question. Relatedly, this study recruited individuals with mild-to severe AUD, which may not be representative of clinical samples. This limitation may have impacted our ability to detect medication effects that require a pathology associated with more severe AUD, which is particularly relevant for negative mood and withdrawal states. Furthermore, participants were required to have a 0.00 g/dl breath alcohol reading for each in person visit. This requirement was to ensure participant safety; however, it may have artificially reduced drinking on in-person study visit days. Of note, in the daily diary assessment,participants reported on their past day drinking for the full day and were able to begin drinking when they returned home after the study visit. Additionally, the sample size for this experimental study was modest, particularly for the fMRI outcomes.

This limited our ability to conduct additional,grow lights for cannabis whole-brain analyses which are necessary to fully elucidate the neural mechanism of ibudilast. Finally, this study did not include a fixed-dose alcohol challenge to evaluate the safety and efficacy of ibudilast in combination with alcohol and to replicate our previous work. However, given that our sample did report drinking while taking ibudilast, we believe that ibudilast can be safely taken with alcohol with limited side effects. In conclusion, this is the first combined clinical and neuroimaging study of ibudilast , a neuroimmune modulator, to treat AUD. Ibudilast did not improve negative mood on drinking or non-drinking days, indicating that its mechanism of action may be non-mood dependent in non-treatment-seeking individuals. Ibudilast reduced the probability of HDDs over 2 weeks for non-treatment-seeking individuals relative to placebo. Ibudilast also attenuated alcohol cue-elicited activation in the VS, potentially through a dopaminergic-related mechanism. This is a critical proof-of-mechanism whereby modulation of neuroimmune signaling via ibudilast reduced the incentive salience of alcohol cues in the brain. Exploratory analyses indicated that ventral striatal activation to alcohol cues was predictive of subsequent drinking in the ibudilast group, such that individuals who had attenuated ventral striatal activation and were treated with ibudilast had the fewest number of drinks per drinking day in the week following the scan. Overall, these findings extend preclinical and human laboratory demonstrations of the efficacy of ibudilast for the treatment of AUD and suggest a potential bio-behavioral mechanism through which ibudilast acts. This study also demonstrates that ibudilast has a favorable side effect profile, even when combined with alcohol. These findings also provide novel insights into the role of neuroimmune modulation in AUD, including its effects on neural and behavioral outcomes of high clinical significance.Recently, neuropsychiatric disorders have been conservatively estimated to be 14% of the global burden of disease, more than the burden of cardiovascular disease or cancer, and their conditions account for a quarter of disability adjusted life-years . The World Health Organization also estimates that 25% of the world’s population will suffer from mental, behavioural, and neurological disorders such as schizophrenia, mental retardation, alcohol and drug abuse, dementias, stress related disorders, and epilepsy during their lifetime. Mostly affecting the poor and people from developing countries, depression impinges on more than 450 million people and might become the second most important cause of disability by 2020. Despite these new insights, as the 20th century revealed Herculean advancements in somatic healthcare worldwide, the mental aspect of healthcare has remained stagnant and in some cases, gravely depreciated. Mentally ill people are some of the most vulnerable people in society. They are often subject to discrimination, social isolation and exclusion, human rights violations, and an ancient, demeaning stigma which leads to bereavement of social support, self-reproach, or the decaying or straining of important relationships. Consequences of poor mental health also include being predisposed to a variety of physical illnesses, having quality of life be reduced, having fewer opportunities for income, and having lower individual productivity, which affects total national output. Poor mental health can also account for violence, drug trafficking, child abuse, paedophilia, suicide, crime, and other social vices. Even though mental health is becoming a serious international health concern, many countries, specifically the more impoverished countries, struggle to address the inadequate amount of resources being funnelled into the nonphysical sector of health.

Low-income countries often have insufficient implementations of policies and limited mental health services confined to short staffed institutions. Furthermore, in both developed and undeveloped countries, the poor are more vulnerable to common mental disorders due to experiences of rapid social change, risks of violence, poor physical health, insecurity, and hopelessness. Women, slum dwellers, and people living in conflict, war prone, and disaster areas of civil unrest constitute a large portion of the population in developing countries, and are specifically susceptible to the burden of mental illness. For instance, 90% of the 12 million worldwide schizophrenia sufferers who do not receive adequate psychiatric services are located in developing countries. Only 50% of countries in Africa have a mental health policy, and if they do have a law, it is usually archaic and obsolete. Ninety percent of African countries have less than one psychiatrist per 100,000 people, and 70% of the countries allocate the mental health sector with less than 1% of the total health budget. Less than 60% of African countries have community mental health care while the rest are focused on psychiatric hospitals. The World Psychiatric Association suggested that the development of mental health programmes are impeded in Africa because of the scarcity of economic and staff resources, lack of awareness on the global burden of mental illness, and the stigma associated with seeking psychiatric care. Mental health has been shunned in Africa, and several reports disclose a higher prevalence of stigma in developing countries than in first world countries. Similar to many other developing countries, treatment of mental health in Ghana, West Africa is low and continues to rely on institutional care, a vestige from colonialism. In Ghana, it is roughly estimated that at least 2,816,000 people are suffering from moderate to severe mental disorders, and only 1.17% of these people receive treatment from public hospitals because only 3.4% of the total health budget is dedicated to psychiatric hospitals. Because there is one psychiatrist per 1.5 million people in the whole country, and the three major psychiatric hospitals are under-financed, congested, and under-staffed, many resort to more ever-present and more affordable, traditional or faith healing. Ghana has a deep-seated tradition of religious observance. Thus, 70– 80% of Ghanaians utilize unorthodox medicine from the 45,000 traditional healers, located in both urban and rural areas, for their vanguard healthcare despite recent advances in orthodox psychiatric services. Although research shows that mental-health patients who used spiritual healing usually reported an improvement in their condition, the quality of treatment is not easy to ensure. Sometimes in order to exorcise supposed demons, individuals are chained, flogged, or incarcerated into spiritual, prayer camps. In spite of these atrocious facts, policy-makers seem to have little concern for mental health, and focus more on physical health and population mortality. The Lunatic Asylum Ordinance of 1888, enacted by the Governor of the Gold Coast, Sir Griffith Edwards, marked the first official patronage to Ghana’s mental health services. This ordinance encouraged officials to arrest vagrant “insane people and place them in a special prison in the capital city of Accra.

Despite the success of GWAS of alcohol use the mechanisms by which these newly identified genetic associations exert their effects are largely unknown. More importantly, alcohol consumption and misuse appear to have distinct genetic architectures . Ever-larger studies, particularly those extending mere alcohol consumption phenotypes, are required to find the genetic variants that contribute towards the transition from normative alcohol use to misuse, and development of AUD.One successful application of GWAS has been their use for assigning polygenic risk scores , which provide estimates of an individual’s genetic risk of developing a given disorder. Reassuringly, PRS for alcohol use behaviors predict equivalent phenotypes in independent cohorts [e.g. alcohol consumption , AD , AUD symptoms. Johnson et al recently identified that, compared to PRS for alcohol consumption , PRS for alcohol misuse were superior predictors of a range of alcohol-related phenotypes, particularly those pertaining to the domains of misuse and dependence. These findings further illustrate that alcohol consumption alone may not be a good proxy for AUD. PRS can also be used to test specific hypotheses; for example, PRS can be used to measure how environmental, demographic, and genetic factors interact with one another. Are there developmental windows where the effects of alcohol use and misuse are more invasive? Can we identify biomarkers that would inform the transition from normative alcohol use to excessive use and dependence? For instance, the alcohol metabolizing genetic effects on alcohol use appeared to be more influential in later years of college than in earlier years ,mobile vertical rack revealing that the nature and magnitude of genetic effects vary across development.

It is worth noting important limitations of PRS analyses. First, polygenic prediction is influenced by the ancestry of the population studied. For example, PRS for AUD generated in an African American cohort explained more of the variance in AUD than PRS derived from a much larger cohort of European Americans . This illustrates that the prediction from one population to another does not perform well . Second, the method of ascertainment may bias the results. As an example, PRS for DSM-IV AD derived from a population based sample predicted increased risk for AD in other population samples but did not associate with AUD symptoms in a clinically ascertained sample . Third, the variance explained by PRS is still low, and hence PRS have limited clinical application. For example, in the largest study of alcohol consumption , the alcohol consumption PRS accounted for only ~2.5% of the variance in alcohol use in two independent datasets. Recent work suggested that predictions may improve by incorporating functional genomic information. For example, McCartney et al showed that, compared to conventional PRS, risk scores that took into account DNA methylation were better predictors of alcohol consumption. Nonetheless, the way in which such methods can be used for prevention or treatments of AUD has yet to be established. Lastly, it remains to be determined the nature of these associations. Mendelian randomization analyses can serve to further understand and explore the correlations between alcohol use behaviors and comorbid traits .Before the era of large-scale genomic research, twin and family-based studies identified a high degree of genetic overlap between the genetic risk for AUD and psychopathology by modeling correlations among family members ). With the recent development of linkage disequilibrium score regression , it is now possible to estimate the genetic correlations between specific alcohol use behaviors and a plethora of psychiatric, health and educational outcomes using GWAS summary statistics. Most notably, the genetic overlap between alcohol consumption and AD was positive but relatively modest , suggesting that, although the use of alcohol is necessary to develop AD, some of the genetic liability is specific to either levels of consumption or AD.

Another consistent finding from genetic correlation analyses has been that alcohol consumption and AUD show distinct patterns of genetic overlap with disease traits. Counterintuitively, alcohol consumption tends to correlate with desirable attributes including educational attainment and is negatively genetically correlated with coronary heart disease, type 2 diabetes and BMI . These genetic correlations are unlike those observed when analyzing alcohol dependent individuals: AD was negatively genetically correlated with educational attainment and positively genetically correlated with other psychiatric diseases, including major depressive disorder , bipolar disorder, schizophrenia and attention deficit/hyperactivity disorder . Importantly, alcohol consumption and misuse measured in the same population showed distinct patterns of genetic association with psychopathology and health outcomes . This set of findings emphasize the importance of deep phenotyping and demonstrates that alcohol consumption and problematic drinking have distinct genetic influences. Ascertainment bias may explain some of the paradoxical genetic correlations associated with alcohol consumption . Population based cohorts, such as UKB and 23andMe, are based on voluntary participation and tend to attract individuals with higher education levels and socioeconomic status than the general population and, crucially, lower levels of problem drinking. In contrast, ascertainment in the PGC and MVP cohorts was based on DSMIV AD diagnosis and ICD codes for AUD, respectively. Collider bias has been proposed to underlie some of the genetic correlations between alcohol consumption and BMI ; however, BMI has been consistently negatively correlated with alcohol use in several subsequent studies . Furthermore, it is also possible that the genetic overlap between AD and aspects of alcohol consumption are dependent on the specific patterns of drinking. For example, Polimanti et al identified a positive genetic correlation between AD and alcohol drinking quantity , but not frequency. Prior to the availability of large population studies and collaborative consortia efforts, few genes were reliably associated with AUD. The use of intermediate traits or endophenotypes has become increasingly common and hundreds of new loci have now been associated with alcohol use behaviors.

Using intermediate phenotypes also facilitates translational research; we can mimic aspects of human alcohol use using animal models, including alcohol consumption, novelty response, impulsivity,vertical grow rack withdrawal and sensitivity . Animal models provide an opportunity to evaluate the role of newly identified genes at the molecular, cellular and circuit level. We may also be able to perform human genetic studies of specific components of AUD such as DSM-IV AD criterion count and alcohol withdrawal . To date these traits have only been studied in smaller samples but this approach will be invaluable as sample sizes increase. Another challenge for AUD genetics is that AUD is a dynamic phenotype, even more so than other psychiatric conditions, and therefore may necessitate yet larger sample sizes. Everlarger studies, particularly those extending mere alcohol consumption phenotypes, are required to find the genetic variants that contribute towards the transition from normative alcohol use to misuse, and development of AUD. Furthermore, genetic risk unfolds across development, particularly during adolescence, when drug experimentation is more prominent and when the brain is most vulnerable to the deleterious effects of alcohol . The Adolescent Brain Cognitive Development , with neuroimaging, genotyping and extensive longitudinal phenotypic information including alcohol use behaviors , offers new avenues for research, namely to understand how genetic risk interacts with the environment across critical developmental windows. Population biobanks aligning genotype data from thousands of individuals to electronic health records are also promising emerging platforms to accelerate AUD genetic research . Despite these caveats, the GWAS described in Table 1 have already vastly expanded our understanding of the genetic architecture of alcohol use behaviors. It is evident that alcohol use behaviors, like all complex traits, are highly polygenic .

The proportion of variance explained by genetic variants on GWAS chips ranges from 4 to 13% . It is possible that a significant portion of the heritability can be explained by SNPs not tagged by GWAS chips, including rare variants . For instance, a recent study showed that rare variants explained 1-2% of phenotypic variance and 11-18% of total SNP heritability of substance use phenotypes . Nonetheless, rare variants are often not analyzed when calculating SNP heritability, which can lead to an underestimate of polygenic effects, as well as missing biologically relevant contributions for post-GWAS analyses . Equally important is the need to include other sources of -omics data when interpreting genetic findings, and the need to increase population diversity . Therefore, a multifaceted approach targeting both rare and common variation, including functional data, and assembling much larger datasets for meta-analyses in ethnically diverse populations, is critical for identifying the key genes and pathways important in AUD.Alcohol use disorder is a highly prevalent, chronic relapsing disorder with a high disease burden in the United States. Despite current and lifetime prevalence rates of 13.9% and 29.1%, respectively, it remains largely untreated as only 7.7% of those with 12-month and 19.8% of those with lifetime diagnoses sought treatment in 2012– 2013. In spite of low treatment rates, pharmacotherapy offers a promising treatment method for AUD. The Federal Drug Administration has approved of four medications for AUD: disulfiram , oral naltrexone , extended-release injectable naltrexone , and acamprosate. However, these currently approved pharmacotherapies are only modestly effective, so there is still a great need to develop more effective interventions. Medications development is a very costly, cumbersome, and inefficient process that can take nearly 20 years from discovery to market. In particular, the development of treatments for alcoholism has been difficult with over 20 medications having been tested in humans yet only three were able to receive FDA approval, the last of which was granted over a decade ago. Therefore, there is a pressing need to develop valid and efficient methods to decrease the cost and length of medications development to better shepherd novel compounds from the lab to dissemination. The development of novel medications for AUD is a high priority research area, but the drug development process is long and challenging, with many compounds stuck in the transition from preclinical to clinical testing, also known as the “valley of death”. Beyond the “valley of death,” there is an overall need to develop effective methodologies for efficiently running clinical trials, particularly in screening novel compounds in early phase 2 trials. Early phase 2 trials, also known as “proof-of concept” studies, help determine if a novel medication is safe, tolerable, and efficacious using clinically relevant phenotypes such as cue-induced craving or subjective response to alcohol. These trials largely incorporate human laboratory paradigms to assess medication efficacy, providing valuable information on whether or not the medication warrants a larger clinical trial. However, human laboratory paradigms have not always demonstrated translational validity and often lack the ecological validity of clinical trials where medication efficacy is established through clinically meaningful endpoints. Therefore, there are major opportunities to refine this process of screening novel medications by combining the internal validity of human laboratory models and the external validity of clinical trials. To that end, the current study aims to develop and validate a novel early efficacy paradigm to screen medications for AUD. This early efficacy paradigm is the practice quit attempt model adapted from the smoking cessation medication development literature. In the original practice quit attempt model, individuals who report intrinsic motivation to quit smoking undergo a 7-day practice quit attempt while taking study medication. Individuals with high intrinsic motivation to quit smoking fared better on active medication, compared to placebo, on increased abstinence, while individuals with low intrinsic motivation showed no effect of active medication. Additionally, the practice quit model demonstrated specificity in which bupropion, an FDA-approved medication for smoking cessation, increased number of days abstinent, whereas modafinil, a medication ineffective for smoking cessation, was no different than placebo. The success of the practice quit attempt model for screening medications for nicotine dependence provides a basis for the development of a similar approach modified for AUD. In addition to the standard procedures of the practice quit attempt, we have included an established human laboratory paradigm to ensure that the novel model will be sensitive to medication effects. The cue-reactivity paradigm measures alcohol craving by having individuals hold and smell their preferred alcoholic beverage and a control beverage. Naltrexone , which is FDA-approved for AUD, is effective at significantly reducing alcohol-cue elicited craving compared to matched placebo.Thus, our current study will include CR in order to detect medication effects on cue-induced craving which will also verify the sensitivity of the novel practice quit attempt model to those medication effects.

Our findings support the need for clinical screening for binge drinking behavior given that many adults who engage in binge drinking behavior do not meet criteria for an AUD, as well as psychoeducation and psychosocial interventions targeting the reduction of binge drinking among older PWH. Additionally, given evidence that improvements in neurocognitive functioning may be possible after sustained sobriety following AUD recovery among HIV- populations , future work is needed to understand whether this may also be true among PWH who reduce or cease binge drinking behavior.There are significant barriers to recruiting and retaining individuals with overlapping vulnerabilities in the pregnancy or postpartum period Wetherington & Roman, 1998. This may result in challenges for generalizability and therein create a relatively sparse knowledge base about the long-term outcomes for these women and their children including the environmental, mental health, physiological, and neurological factors. Filling these knowledge deficits and gaps requires ongoing assessment because research tools including those for recruitment and retention change; in addition, substance exposures in pregnancy change , thereby shifting methods to reach target populations of interest and methods to measure outcomes of interest. It is imperative for the field to identify and address engagement in research,cannabis grow equipment to ensure representation of pregnant and postpartum women that use substances. Engagement in longitudinal studies will allow a more complete understanding of maternal and child health outcomes as a result of new and emerging trends in prenatal substance exposure. Enhanced understanding of participants’ perspectives on engagement and study participation will allow researchers to more fully address this pressing research and public health need.

Prenatal exposure studies began in earnest in the 1970s, after the identification and diagnosis of fetal alcohol syndrome . Careful participant selection and comparison selection were and are necessary to classify effects of prenatal exposures. Protectionist and paternalistic regulations excluded women from health research and limited the field’s understanding about how sex and gender shape substance use and SUD . Research studies on substance exposures during pregnancy expanded rapidly in the past 30 years, in recognition of the cocaine epidemics of the 90s, and the current increases in prenatal opioid and methamphetamine exposures . Indeed, research that focused specifically on prenatal exposures and other women’s health issues has been encouraged by journal editors, policymakers, and funding agencies including the NIH Helping End Addiction Long term initiative. Despite bioethical, legal, and social concerns regarding the risks and benefits of research participation for pregnant and postpartum women who use alcohol and drugs , the inclusion of vulnerable populations who are marginalized or stigmatized in research on sensitive topics has not demonstrated undue harm or exposure to unacceptable risk, and in fact, has been associated with potential benefits, such as altruism, catharsis, and gained knowledge . Of course, it is important for researchers to adopt careful experimental design and safeguards that will uphold the principal of non-maleficence and protect vulnerable participants from harm . Exclusion of substance using populations may violate important bioethical principles of human subjects research, particularly the principles of autonomy, beneficence, and justice . Exclusion from research not only strips individuals from making decisions about their own autonomy and denies them potential benefits of participating, but also exposes them to greater societal marginalization and may ultimately place them at increased risk of harm due to deficits in critical health knowledge and exposure to inappropriate or ineffective treatments . Unfortunately, prenatal exposures to alcohol, tobacco, and other drugs are rising , with 1 in 4 pregnancies exposed to tobacco , alcohol consumption , or illicit drug use . Specifically, opioid exposed pregnancies have increased from 1.5 to 6.5 per 1000 pregnancies . Yet, cannabis exposures are the most prevalent drug exposure, with nearly 7–8% reported exposure in the first trimester .

Rising rates of substance exposure correspond to increasing health risks and adverse outcomes at great societal cost and burden to systems of health care and social services, as well as criminal justice. Notably, researchers involved in the NIDA-funded Perinatal-20 Treatment Research Demonstration Program that focused on SUD treatment for pregnant and postpartum women identified seven clinical factors that contributed to significant difficulty and complexity in the recruitment and retention of women in substance use treatment research, including as follows: severity of SUD, legal system involvement, housing instability, interpersonal relationship challenges, parenting responsibilities, employment challenges, and need for more intensive services. These difficulties with recruitment and retention contribute to additional complications for research, including biased samples of convenience recruited through referrals from social and health agencies, limited sample diversity, deviations from the research design, and ethical issues associated with risk and benefits of participation and involvement with the criminal justice or child welfare system. In particular, when research designs do not involve the possibility of direct benefit due to participation , it is important to understand the unique reasons and motivations that drive decision-making about research participation . Due to all of the aforementioned factors that potentially inhibit the inclusion and engagement of high-risk participants , it is imperative to understand the motivations for engagement in research among high-risk participants, focusing specifically on understanding motivation for research participation, factors that influence decision-making about participation, and barriers to participation.The current study reports results from a qualitative research study conducted as part of an 18-month, multi-site pilot study aimed to develop and demonstrate feasibility of an experimental design for a 10-year, prospective,cannabis cultivation technology longitudinal investigation of normative childhood brain development, beginning in pregnancy. A major aim of the 10-year study will be to determine factors that alter brain development including prenatal exposure to opioids and other psychoactive substances, as well as other prenatal and childhood environmental exposures.

This goal necessitates recruiting pregnant women previously or currently using substances, as well as a large group of pregnant women who are at low risk of prenatal substance use. Two of the primary aims of the pilot are developing and testing recruitment and retention strategies and addressing ethical and legal challenges of conducting research with a stigmatized and vulnerable population.The current qualitative study is one arm of the 5-site consortium to improve understanding, from a qualitative perspective, the continuum of engagement of low- and high risk participants in research. This manuscript focuses on the results of the distinct needs and responses of high-risk participants. Specifically, the objectives in this analysis were to address important factors that impact best practices in promoting longitudinal research to high-risk participants, enrolling high-risk participants in research, and retaining high-risk participants in research studies.Individual interviews and one focus group were conducted with a total of 41 women . Women were at high-risk of prenatal or postnatal substance use and were identified through medical clinics, other research study involvement, or SUD treatment programs. Recruitment took place across five sites in the USA located in California, Georgia, New Mexico, Ohio, and Oklahoma . High-risk pregnant and postpartum women were defined in the current study as a parenting or pregnant woman who had used alcohol and tobacco and/or had a current or past history of SUD. Some participants were currently receiving SUD treatment. Contact was made through trained research personnel located at each specific site with 41 total participants taking part in the current study. Only one focus group that included five women was combined with the individual interviews. The one focus group was conducted in New Mexico prior to group restrictions imposed due to COVID-19.Qualitative methods for the research team, study design, and analysis followed the guidelines recommended by Tong, Sainsbury, and Craig . Qualitative study recruitment began with sites contacting participants in person or by phone and describing the current study and qualitative interview process. All women who expressed interest in participating were scheduled for either a focus group or individual interview depending on whether the interview took place prior to or following COVID-19 restrictions regarding in-person gatherings.All participants gave oral informed consent. During the consent process, a brief overview of the qualitative study and all safety measures taken to ensure confidentiality were discussed. Trained qualitative research assistants collected all qualitative data from March 2020 through June 2020. Before engaging in focus groups/individual phone interviews, all participants completed an in-person or online survey that included a demographic questionnaire and watched a short video describing the protocols planned for the larger, longitudinal study including neuroimaging , neurodevelopmental, and biospecimen collection.

For the focus group, snacks were provided. Participants received a $50–75 incentive for their participation, and this varied based on site. All focus groups and individual interviews were audio-recorded and lasted approximately 45–60 min. Transcription work was conducted by qualitative team members or a transcription company, with team members crosschecking all transcripts to verify accuracy. During the transcription process, all identifying information was removed to ensure privacy. All procedures were approved by the sIRB for the 5-site consortium.Focus group and individual interview guides for the current project were developed by the first author, in conjunction with the evaluation team and other sites within the research consortium reviewing and revising the guide as needed. Focus group and individual interviews were coded individually and combined for data analysis. All coding and data analysis was conducted at one site. Recordings were transferred securely according to IRB-approved methods. It is important to note that focus group and individual data themes were examined a priori and themes were congruent and therefore data were merged.Qualitative data was analyzed using the NVivo© 11 software. Five qualitative researchers worked together to develop a codebook focused on broad themes influenced by the semi-structured interview guide. Thematic analysis was used to define specific themes within the broader categories . The codebook was developed using an agreed upon coding scheme with themes not being predetermined but rather emerging from the data. Upon completion of the codebook, two teams consisting of two qualitative researchers coded all transcriptions using developed coding templates. Cleaning of data took place as needed . Once coded, inter-coder reliability was established using simple percent agreement, which is a commonly used method for assessing reliability in qualitative studies . Average inter-coder reliability was over 85%. In the “Results” section, themes are described in more detail. The validity of the current research findings are enhanced by several design factors such as the calculation of salient factors using percentage of comments and the team-based approach used for coding. Specifically, calculating the percentage of comments from participants related to specific themes allowed the research team to ensure that themes discussed in the current paper were saturated or were discussed frequently in focus group/individual interviews. Therefore, relying on percent of comments strengthens demonstration of saturation in the current study. Further, the majority of qualitative data were collected from individual interviews rather than a focus group , which allows for a more in-depth conversation. Specifically, during individual interviews, comments were able to be probed deeply with rich content emerging throughout the qualitative data, rather than simple agreement or disagreement that often emerges from focus group data collection. Additionally, the fact that both primary researchers as well as consortium partners were involved in developing the focus group/individual interview guide is a strength, increasing the likelihood that the items on the interview guide validly and comprehensively captured the intent of the research aims.Other suggested locations included bus stops , billboards , and grocery/ convenience stores . Participants also reported that child-friendly locations and educational settings were good locations to share study information. One participant explained, “Maybe flyers at childcare centers and stuff like that, where they have the younger school-aged kids from infant to whatever. I know a lot of moms frequent those places.” When participants were asked about locations they would trust the most to receive information, it was disclosed that medical offices such as doctor offices/clinics, state agencies , and educational settings were considered most trustworthy. Participants also discussed the type of material they would recommend using to promote research studies with participants explaining they would use commercials , brochures , and radio to share information about research studies. It was also reported that using news/newspapers , online marketing strategies , and sharing information through word of mouth would be most effective. In terms of the individuals that would be best to share research study information, participants stated that study information would best come from medical personnel , friends , family members , other participants , and professionals .

The Family Smoking Prevention and Tobacco Control Act of 2009 banned the use of all natural and artificial compounds characterized as flavors in combustible cigarettes and any of their component parts to eliminate flavored tobacco products that held special appeal in the youth market. In 2020, the US FDA finalized their enforcement policy on flavored cartridge based e-cigarette products, including fruit and mint flavors, but excluded menthol and tobacco flavors.However, since this enforcement policy only applies to prefilled cartridges, flavored eliquids in bottles and refillable empty cartridges are still commercially available. Flavored products can be legally marketed in the USA if they receive a tobacco product marketing order from the FDA, and this may become common in the coming years. There is sufficient evidence to suggest that flavorings influence the perception, use, and safety of e-cigarettes.Flavor compounds,particularly sweet ones, have the potential to mask and/or ameliorate irritant and bitter sensations, such as the taste of nicotine.The route of delivery has an impact on the toxicology of a compound. Indeed, many flavor compounds have only been tested for safety following oral delivery , and to date have not been tested for inhalation safety. The potential risk of flavor compounds when inhaled rather than ingested has been demonstrated by occupational and consumer inhalation of high doses of the buttery flavor diacetyl , which leads to irreversible lung disease, namely bronchiolitis obliterans or “popcorn lung” in microwave popcorn factory workers.At one time, diacetyl was found in 70% of 159 sweet flavorings used in e-cigarettes,while a more recent study found diacetyl in only a few flavorings. Flavored e-liquids and individual flavors induce toxicity and/ or exert biological effects: Sassano et al. found vanillin is the most common flavor.The number of flavors used varies considerably across e-liquid products. Notably, in 20 e-liquids, Hua et al. found 99 different flavors.Sassano et al. studied 148 eliquids and found 100 flavor constituents.

They also found the more flavors contained in an e-liquid, the more likely it was to be cytotoxic,cannabis indoor greenhouse while concentrations of vanillin and cinnamaldehyde in e-liquids significantly correlated with toxicity.Cinnamaldehyde, was found to be >7.6 mM in multiple e-liquids, and in some cases, levels exceeded 1 M.These concentrations were sufficient to induce cytotoxicity and ciliary dysfunction. However, flavor concentrations in most e-liquids have not yet been determined. Menthol is biologically active and can activate the transient receptor potential channel in pulmonary neurons to suppress cough and irritation,making it easier to tolerate cigarette smoking. Menthol flavors are significantly more popular among African Americans and tobacco companies have marketed them accordingly.Flavorings including vanillin and cinnamaldehyde are aldehydes that have the potential to form adducts with proteins and DNA. Vanillin can also activate TRP channels to exert biological effects .They can also react with base constituents in e-liquids, leading to the formation of acetals, which can stimulate irritant receptors.Sweet and bitter taste receptors are G-protein-coupled receptors expressed in airway epithelia where they regulate innate immunity. The sweet and bitter taste receptors are expressed in the nasal passages/upper airways, while only bitter/T2R taste receptors are expressed in the lower airways.This raises the possibility that inhalation of flavor compounds may stimulate airway taste receptors and affect immune function. Their activation may disrupt innate airway defense by suppressing the release of antimicrobial peptides that are capable of killing a variety of respiratory pathogens. In the lower airways, T2R activation leads to an increase in ciliary beating and may have other physiological functions via its effects on cytoplasmic Ca2þ, a universal second messenger. There is some evidence that toxicity is cell type-dependent, suggesting that mechanistic investigations must be cell-specific.In summary, the adverse impact of flavor compounds in e-cigarettes include the potential for increased appeal of these products, particularly to the youth market, influence on patterns of use and smoking topography, changes in cell signaling, and increased cellular toxicity .PG and VG are commercially available in different mixture ratios, and the ratio of PG to VG in the e-liquid can affect taste sensation, the amount of aerosol generated, the amount of nicotine delivered, and the overall user experience.Predominantly PG-based e-liquids deliver more nicotine systemically, but taste less pleasant than VG-rich e-liquids.PG is used to deliver pharmaceuticals intravenously and while it is generally considered safe, higher PG doses can lead to metabolic acidosis, acute renal injury, and sepsis-like syndrome.

In Sprague-Dawley rats, nasally inhaled PG of up to 2.2 mg/L for 90 days led to nasal hemorrhaging. Similar short-term exposures of mice to PG/VG resulted in changes to tissue elasticity, static compliance, and airway resistance, although these effects waned after 1 month of exposure, suggesting that there may be a long-term adaptive response.In contrast, a recent study funded by Philip Morris International found that nasal exposure to PG/VG mixtures of up to 1.5 mg/L PG and 1.9 mg/L VG for 90 days had minimal effects on respiratory organs, gene transcription, proteomics, and lipid profiles in Sprague-Dawley rats.Lipid-laden macrophages were recently observed in mice that were chronically-exposed to PG/VG.While this exposure was not fatal, these mice had decreased macrophage function and were more vulnerable to influenza A infection.Mucin abnormalities correlate with a decline in forced expiratory volume in 1 s in chronic obstructive pulmonary disease patients,indicating that mucins are important biomarkers of harm. Importantly, increased MUC5AC mucin levels were also detected in human e-cigarette users’ bronchial epithelia obtained by bronchoscopy and in sputum,and these increases in MUC5AC levels could be replicated in the laboratory by exposing both primary bronchial epithelial cultures and mice airways to PG/VG.While the underlying mechanism whereby PG/VG can exert their effects are unknown, Ghosh et al. found that PG/VG rapidly alters membrane rheology.Altered membrane properties could affect a number of aspects of fundamental cell biology including endocytosis, exocytosis, and cell division. In vitro,cannabis growing equipment higher levels of both PG and VG can prevent cell growth and/or induce cell death. However, more work will be required to fully appreciate the effects of PG/ VG. The potential effects of PG/VG at the cellular level are summarized in Figure 2. The concentrations of PG and VG saw in the lung and systemically after vaping are poorly understood, and additional studies to determine PG/VG pharmacokinetics and pharmacodynamics after inhalation are required.This may subject them to chemical reactions that result in the formation of new compounds including reactive oxygen species . For example, the hydroxyl radical was produced from PG/VG at higher power settings.

Carbonyl compounds were formed in e-liquid aerosols as a result of dehydration and oxidation, and was dependent on the PG/VG ratio, the wattage used to heat the e-liquid, as well as other factors including brand, and type of e-liquid used.Exposing biological tissues to carbonyl compounds can deplete glutathione, induce DNA damage, alter ion channel function, and elicit cell death.Thus, both reactive aldehyde production and subsequent reactive aldehyde metabolism in biological tissues need to be considered. This may be particularly important since nearly 8% of the world’s population has an impaired capability to metabolize reactive aldehydes, and they may show altered responses to e-cigarette/reactive aldehyde exposure.Importantly, aldehydes can form adducts with both proteinsand DNA.Adduct binding can impair protein function, as recently noted for the short palate and nasal epithelial clone 1 , which is an innate defense protein expressed in the lung. Here, crotonaldehyde bound to SPLUNC1, which prevented it from regulating lung hydration.Similarly, acrolein can form adducts with surfactant protein A, which leads to impaired innate defense by decreasing antimicrobial activity and reducing phagocytosis by macrophages.Aldehyde adducts can also bind to DNA, leading to frame shift and base-pair substitution mutations, which may contribute to cytotoxic and genotoxic effects.These results indicate that as a result of reactive aldehyde inhalation from heat-coil aerosolization of PG/VG, the lung may be especially vulnerable to adduct formation and the associated macromolecule damage. In addition to decomposition products resulting from heating e-liquids, emissions may also contain contaminants from components of the e-cigarette device itself. These can include toxic metals such as chromium, nickel, and lead.Therefore, understanding the potential health effects of thermal decomposition products remains key to delineating the overall e-cigarette health effects.There is a common perception e-cigarettes may be safer than combustible cigarettes, since they deliver much lower levels of oxidants, volatile organic chemicals, and other noxious chemicals associated with tobacco cigarette smoke and cardiovascular risk.However, both combustible tobacco products and e-cigarettes deliver oxidants, toxic metals, and potentially toxic carbonyls, which have been associated with cardiovascular disease.Moreover, e-cigarette-derived particles are spread among a wider size range than those generated by standard cigarettes. Known toxicants in e-cigarettes may also contribute to cardiovascular damage in a different manner than toxicant-induced cardiovascular damage from combustible cigarettes. There is an urgent need to determine both the acute and the long-term effects of e-cigarettes on the hearts and blood vessels of healthy adults and children, as well as those with either risk factors for cardiovascular disease or outright cardiovascular disease and to determine the comparative safety of e-cigarettes relative to combustible cigarettes.

A summary of the potential cardiovascular biomarkers of exposure/harm following vaping are shown in Table 1 and are discussed in more detail below.E-cigarette use has been consistently connected to reductions in vascular function and damage to ECs. For example, several studies have established that e-cigarette inhalation leads to increased arterial stiffness in humans and rodents, as evidenced by increases in augmentation index and pulse wave velocity.One crossover design study compared e-cigarette vaping 6 nicotine and found that pulse wave velocity, aortic pulse pressure, augmentation index corrected for heart rate, and sub-endocardial viability ratio were all significantly increased, but only when subjects vaped with nicotine.However, another study found that inhalation of nicotine free e-cigarette vapor caused an increase in aortic pulse wave velocity and resistivity index.These results have made it unclear as to whether nicotine is required to elicit these adverse effects: Additional factors such as e-cigarette wattage, which affects toxicant production, and/or the presence of flavors may also affect arterial stiffness. In addition to arterial stiffness, e-cigarette use impaired endothelial nitric oxide synthase signaling,which could be considered a biomarker of endothelial dysfunction in several vascular diseases including hypertension and atherosclerosis. Participants exposed to e-cigarettes showed significantly reduced flow-mediated dilation of the brachial artery, demonstrating endothelial dysfunction compared to non-users.However, in a separate study, smokers who switched to e-cigarettes for one month showed an improvement in FMD, suggesting that there may be a difference between acute and chronic effects of vaping on FMD.The mechanisms by which electronic cigarettes lead to these adverse vascular effects remain incompletely defined. However, a number of studies suggested that e-cigarettes might cause ROSmediated damage, including damage to ECs.Carnevale et al. performed a crossover study of 40 healthy subjects, half of whom were smokers. The subjects were asked to smoke combustible cigarettes for 1 week and were then crossed over to e-cigarettes.Both combustible cigarettes and e-cigarettes increased markers of oxidative stress and worsened FMD after a single use. Lee et al. exposed human-induced pluri potent stem cell-derived ECs to various flavored e-cigarette liquids and assessed endothelial integrity. A cinnamon-flavored e-cigarette product was most potent in reducing cell viability and increasing ROS levels.In multiple studies, subjects who used e-cigarettes either acutely or chronically were found to have altered blood and plasma biomarkers linked to oxidative stress and cardiovascular disease, including increased myeloperoxidase,increased isoprostanes such as 8-iso-PGF2a, reduced NO bio-availability, increased levels of the oxidantgenerating enzyme nicotinamide adenine dinucleotide phosphate oxidase ,and reduced levels of the non-enzymatic antioxidant vitamin E.Anderson et al.showed that e-cigarette aerosol exposure induced ROS in vitro, which caused DNA damage and cell death. Of note, the antioxidants alpha-tocopherol and n-acetyl cysteine were effective in alleviating the damage. After e-cigarette exposure, activated ECs may have been the source of vascular ROS: Chatterjee et al. exposed serum to e-liquids and observed a NOX2-dependent increase in ROS, coupled with inhibition of NADPH oxidase 2 reduced ROS production by 75%.Kuntic et al. extended these observations and demonstrated that e-cigarette-induced ROS burden and endothelial dysfunction could be rescued by NOX2 inhibition or NOX2 gene knockout in mice.These findings were nicotine-independent, and acrolein treatment alone was capable of causing NOX2- dependent ROS production in primary murine ECs. Together, these studies link e-cigarette use with NOX2 activation, endothelial oxidative stress, and subsequent endothelial damage/dysfunction, which may contribute to adverse vascular outcomes.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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