Hemp Growing

Similar to the overall sample, frequency of past-week cannabis use in these groups returned to levels comparable to baseline for the remainder of the study period. Collectively, these findings offer new insight into patterns of cannabis use over time throughout the pandemic among U.S. adults. Our findings are broadly consistent with studies from other countries, including some European countries and Canada . In a study of adults who use cannabis in the European Union, self-reported cannabis use remained stable overall, with 42% of participants reporting no change in use between April 8 and May 25, 2020. Increases in frequency and quantity of cannabis use were larger among those who used cannabis regularly rather than occasionally . Another repeated cross-sectional study of Canadian adults showed cannabis use in the overall population remained unchanged during the pandemic between May and June 2020. Though about 50% of the individuals who reported using cannabis stated that their cannabis use had increased, the reported number of days cannabis was used in the last seven days remained stable over the study period . Other cross-sectional studies from France and Belgium at the start of national lockdowns further reported findings of overall cannabis use remaining stable . Though these findings are generally consistent with ours, comparison is limited due to the non-representative and cross-sectional nature of these studies that report changes only in the first wave of lockdowns between March and June 2020. The U.S. context of cannabis policies and access is important to consider when reflecting on factors that may have influenced these trends. The marginal changes in cannabis use among some groups early on in the pandemic may have been influenced by public health measures implemented to reduce the spread of COVID-19.

One such consideration is the role of stay-at-home orders and social distancing measures indirectly impacting behaviors among those who obtain cannabis drying racks through illicit markets or peers. For example, our data show that in states where cannabis is prohibited, days of cannabis use had a decreasing trend, although not statistically significant, over the course of the COVID-19 pandemic, with November having the greatest decrease compared to March. The study from the European Union notes that Ireland, Italy, Poland, and Portugal were the countries with the largest proportions of cannabis use reduction or stopped use, citing Italy’s restrictions on movement within regions and Portugal’s reported decrease in availability as factors in impeding access to cannabis . On the other hand, in states where medical cannabis was legally available, the level of cannabis use across the first 8 months of the pandemic was either similar to or modestly greater than baseline. Increased use in states that allow medical cannabis use may be an indicator of an exacerbation of common conditions treated with medical cannabis, including anxiety and insomnia. A prior study of US adults who use cannabis medicinally found that those with anxiety or depression reported increased use during the pandemic . Though the current study does not indicate that cannabis use increased significantly during the pandemic, there is a need to continue public health surveillance to monitor changes in cannabis use. As states expand efforts to vaccinate the larger US population and social distancing measures begin to be lifted in parts of the US, cannabis availability may return to normal for portions of the population that may have had limited access to cannabis during earlier phases of the pandemic. In the interest of further understanding the long-term effects of the pandemic on cannabis use, monitoring and further studies are needed. Future research should also explore associations between changes in cannabis use and mental health status before, during, and following the pandemic. This study has several limitations that should be considered when interpreting findings. First, the survey only included measures of quantity, contents, or mode of cannabis consumption at two time points,Waves 4 and 5.

Therefore, we are not able to understand changes in cannabis use that may be more clinically meaningful over time, such as quantity and mode of consumption. Second, there are sociodemographic characteristics known to be associated with cannabis use behaviors, such as education  and sexual or gender identity , that were not examined in this study. In addition, although most states with operational dispensaries deemed them “essential services”, there were some time-variant changes in guidelines, including capacity limits, operating curbside pick-up, and delivery, that we were not able to account for in our analyses. These quickly evolving guidelines may have impacted individual access to cannabis and potentially cannabis use behaviors within certain populations. Further, due to small sample size, some sociodemographic groups were combined in our analyses; for example, Native Hawaiian/Pacific Islanders, American Indian/Alaskan Natives, and those reporting more than one race were categorized as “Other.” It is also noted that some categories consisted of small sample sizes that may lack the statistical power to capture differences in trends across subgroups. These groups should be considered for future research to understand trends of cannabis use among these populations. Third, the analyses were conducted among individuals who ever used cannabis during the study period  and may not be representative of all adults who use cannabis. Fourth, this panel did not have data on cannabis use prior to March 10th, and therefore we were not able to identify initiators of cannabis use or capture changes in cannabis use that may have occurred before the start of lockdown measures. Fourth, although our survey weights were adjusted for non-response using baseline characteristics, they were not post stratified to account for non-response at each follow-up wave, which may have affected the representativeness of our sample and the generalizability of our findings.The therapeutic use of cannabis dates back several thousands of years, however, during the early 20th century a global trend of cannabis prohibition emerged, resulting in an almost 100 year gap in clinical use and research advancement.

Therapeutic use among patients has continued despite legal status and recent introduction of medical cannabis regulations in more than 30 countries has permitted millions of patients to legally access medical cannabis and has revived the production of medical cannabis research. There has been growing evidence of the therapeutic effects of cannabinoid-based treatments in several conditions including chemotherapy-induced nausea and vomiting, chronic pain, drug resistant epilepsy, spasticity associated to multiple sclerosis and insomnia.2 Yet access to cannabinoid-based products and clinical knowledge of effective initiation and monitoring is still poor, partly because of a lack of proper integration of healthcare settings or formal medical education. Dedicated medical cannabis facilities can provide innovative care and education, based on and for patient’s needs. They may also assist and train physicians in prescribing personalized treatments and navigating through the complex administrative and regulatory framework of medical cannabis. Various settings have been employed over time, from buyer’s or compassion clubs to dispensaries to, more recently, private medical clinics. However, there has been virtually no literature on medical cannabis care services which has also increased barriers to the production of evidence-based policies and clinic models.3,4 Canada has long been on the frontier of medical cannabis access, with the enactment of legislation in 2001 following a Supreme Court challenge to the Charter of Rights and Freedoms.5 The regulatory system has evolved over time, most recently with the legalization of non-medical or ‘recreational’ cannabis under the Cannabis Act in October 2018. However, despite this long history of medical cannabis access, significant medical stigma and persistent barriers to prescription remain. In 2014, approximately 40,000 Canadians were authorized for medical cannabis use, however an estimated 1 million were using cannabis therapeutically via illicit sources.6,7 The aim of this article is to present the care model of a successful clinic dedicated to medical cannabis treatments. The key elements related to the clinic organization and the clinical team as well as clinic statistics and critical patients’ data are described and discussed in detail. This paper also aims to inform health care providers and other medical cannabis stakeholders on the considerations of effective medical cannabis practice that can be adapted to different clinical settings and various regulatory frameworks. The main objective of any medical cannabis treatment is to provide a complementary option to traditional treatments in order to alleviate persistent symptoms and suffering associated with the patient’s condition. This is achieved through the following sub-objectives: give the patient a sense of control over their condition; improve the symptoms experienced by each patient; and improve the patient’s health-related quality of life with a minimum of treatment related adverse effects. Moreover, as a complementary or adjunctive treatment, medical cannabis treatment must be integrated with primary and speciality care to support best outcomes.

The medical cannabis grow tray clinic model was developed by the co-founding team of medical cannabis advocates, researchers and physicians to meet the needs of patients and the medical community. In early years, the stigma of being classified as a ‘pot doctor’ required peer support among the medical team and resulted in the establishment of initiatives to support clinic credibility, including rigorous clinical practice guidelines, a strict referral model, and the initiation of a research program to collect real-world evidence about patient treatment outcomes. Maintaining the credibility of medical cannabis treatments and separating myths from realities remains a core function of the clinic as a resource centre for evidence-based medical cannabis information. Each country may have specific considerations and requirements for a clinic implementation. It may be required to develop specific protocol or reporting for each patient that is prescribed medical cannabis. Developing such protocols in a peer-reviewed environment to meet the needs of common patient diagnoses and symptom expression is important to ensure compliance and clinical efficiency. Different healthcare environments may present challenges as well as sociological impacts; integration with private health insurance providers may be necessary initially to support patients who are unable to pay for clinic visits or medical cannabis treatments.A dedicated, attentive and diverse team of experts is a key aspect to medical cannabis care. The clinic has expanded from a small team of five practicing part-time physicians and one medical cannabis educator in one location to a network of four clinics across Quebec and a team of twelve consulting physicians and fifteen nurses as part of a complete staff of fifty employees. The current core clinical team consists of clinic coordinators who supervise research assistants and administrative needs, nurse coordinators and a team of nurses with both research and patient education experience and physicians from various specialities, including family physicians and specialists in pain, palliative care, endocrinology and gastroenterology.The team provides specific, comprehensive counseling to patients taking into account their individual medical condition, lifestyle and accessibility needs. In the early years of clinic development, medical cannabis advocates or educators played a critical role to support cannabis knowledge transfer and personnel training, bridging medical cannabis and healthcare experiences. To provide sufficient support and education, patients are followed by the same physician, though nursing and education support may rotate, and all notes are documented on an electronic medical record . Such a multidisciplinary approach between healthcare professionals provides for personalized, effective and efficient recommendations and the appropriate, supportive follow-up required by most patients, as it occurs in other clinical settings.9 Peer support among healthcare providers, especially physicians, across various specialities, facilitates support and mentorship within an otherwise stigmatized and controversial treatment. The initial clinic visit is an opportunity to meet the patient, confirm eligibility for cannabinoid-based treatments and provide patient education on medical cannabis. Baseline clinical data and validated questionnaires are collected and may be used for further analysis. A complete medical history is obtained by a registered and trained nurse with a focus on factors that will determine treatment recommendations including a patient’s previous cannabis experience. Consulting physicians confirm patient eligibility and treatment decisions and determine a follow-up and monitoring schedule according to a clinic-wide protocol. A medical cannabis authorization is written in accordance with federal regulations, the authorization is akin to a prescription in practice. Patient education is led by the nurse and includes discussion of treatment objectives with the patient and family, review and management of treatment expectations, careful explanation of the individualized treatment plan, titration instructions and an original patient daily diary and education booklet that cover all general information. Furthermore, a patient treatment agreement is an indispensable tool to confirm treatment objective and clinical program limitations.

To characterise country-level cannabis control policy changes, we primarily relied on Pacula et al. and Room et al. . On this basis, a distinction is made between decriminalisation , depenalisation and increase of the penalties . Going specifically into the European case, following the European Monitoring Centre for Drugs and Drug Addiction , this distinction was further refined to perform the analysis: decriminalisation through reforms that remove the prison sentences for minor offences ; depenalisation, where the offence is still criminal, but a reduction of the maximum prison sentence is operated ; depenalisation where the offence is still criminal but the likelihood of sanctions being applied is reduced by facilitating the closure of minor cases ; increase of the penalties, where the possession for personal use is a civil offence but the reform increases the penalties attached to it ; increase of the penalties, where the possession for personal use is a criminal offence and the reform increases the penalties attached to it . To better understand how the European countries included in our study have been categorised and understand each specific policy change, Table 2 provides an overview of the broad category into which the policy changes fall, the specific type of reform and a description of the situation pre- and post-reform in each country. Seven countries that did not pass any cannabis law in the observed period were used in the analysis as a control group: France, Iceland, Latvia, Malta, the Netherlands, Norway, Sweden. Four additional countries that reformed their cannabis control policies in the observed period were excluded from the analysis because the related ESPAD data were not available for all the considered years: the United Kingdom , Estonia , Luxembourg and Belgium .This paper assessed whether the cannabis grow equipment policy changes occurred in 13 European countries in the period 2001–2014 were associated with significant outcomes among adolescent students. In particular, to inform discussions about the evaluation of policy developments related to cannabis that might increase the availability of this substance within Europe, we analysed changes in the perceived availability of cannabis.

In order to check the possible association with changes in the prevalence of use of this substance among adolescent students, we differentiated between different patterns of use . This has been done in order to account for the fact that users are not equal, and that there is a group that, although restricted, is more at risk of developing cannabis-related problems, i.e. frequent users . This study contributes to clarify the scarce and inconstant literature on European states , providing important information about policy outcomes and efficacy. Moreover, differently from previous studies that simply categorised cannabis control policies into a dichotomous measure , this study takes account of the fact that there is a great diversity of forms that relaxation or increase of prohibition can take in practice , by refining the investigation following the analysis proposed by EMCDDA . In fact, ignoring the significant heterogeneity in these policies, has been highlighted to contribute to what appear to be mixed results from evaluations.In order to better interpret the results, for each country a description of the situation pre- and post-reform has been provided. By combining data from five waves of the ESPAD survey, our data include a time span of more than 15 years, covering the period before and after the implementation of each of the national drug policy reforms. Results are based on a DiD model. Regarding the availability of cannabis, we find that none of the decriminalisation and depenalisation reforms seem to be linked to an increase in the perception of easy access to this substance by the general population of students, nor it is so among non-frequent and frequent users. This finding suggests that the common assumption that cannabis availability will increase with the relaxation of prohibition might not apply to the European cases. This means that in a country like Portugal, where the personal possession of cannabis was decriminalised in 2001, the perceived availability of cannabis did not increase as a result of the reform compared to a country like France, where the possibility of incarceration for the possession of cannabis for personal use is still foreseen. Among the policy reforms increasing the penalties for cannabis personal possession, those increasing the administrative penalties attached to this offence are actually associated to a decrease in the rate of students perceiving cannabis as easy to obtain. This result might be a good indication as it has been demonstrated that those who believe they have easy access to cannabis have also a greater risk for uptake, higher consumption frequency, as well as the progression to regular use and abuse . However, the fact that among users this association persists only for the non-frequent ones, suggests that the channels of access to the substance by frequent users, such as domestic production and supply networks , might not have undergone significant modifications.

Since to our knowledge cannabis policies and changes in the perceived availability by adolescents were not previously explored in the European context, these results offer an interesting insight into the aforementioned relationship. Concerning cannabis use outcomes, our results show that only some cannabis policy reforms were associated to significant changes in the prevalence. This can be considered an important finding in itself as it confirms that there is not an automatic link between cannabis policy and use , and that other factors may play an important role. Among these, we can mention information and prevention programs, but also the actual level of implementation and enforcement of reforms . They can affect the perception of risk and knowledge of adolescents, as well the social acceptability of drug use in a country, which are in turn associated with substance use . As highlighted by a previous study conducted in Europe , the heterogeneity found in the effects of cannabis policy reforms concerning the prevalence of use highlights the importance of making distinctions between different types of cannabis users. In fact, in line with previous findings different results are obtained for different types of consumers. When considering all types of users, two categories of policies show an effect: among the more restrictive ones, only the one increasing the non-prison penalties seem to significantly reduce overall cannabis use, and among the more liberal interventions, only the one favouring the discontinuation of criminal proceedings for minor cases is linked to an increase. These results are confirmed when focusing on experimental users or excluding frequent users from the analysis. Furthermore, those reforms reducing the maximum prison penalty for cannabis possession show a positive effect on the share of experimental users only. When finally considering only frequent users, i.e. students smoking cannabis daily or almost daily, the policy effects observed before disappear and no reforms seem to have an effect. This result is not in line with the finding from Shi et al. indicating that cannabis liberalisation in Europe was associated with higher likelihood of regular use. It is instead supported by a revision of the same study that highlighted how, by implementing some statistical improvements, this association becomes statistically non-significant . The finding is also in line with some recent within-country studies conducted to analyse some form of cannabis liberalisation policies in the US .

In these studies, no discernible pattern was detected suggesting an increases in cannabis frequent use among adolescent related to the legalisation of medical marijuana. Overall, these results offer three main insights. First, the fact that some of the reforms reducing the penalties for cannabis possession are associated to an increase in some measures of adolescent cannabis use signal that those reforms might have somehow reduced stigma and perceptions of risk associated with cannabis use . This is in light of the fact that no increase was observed concerning adolescent perceived easy access to the substance, indicating the the other main factor on which the policy reforms might have acted did not change significantly. A shift in social norms regarding cannabis use may have, instead, increased cannabis use among experimental and non-frequent users . On the contrary, in those countries where the civil penalties for cannabis possession where increased , the reduction in the share of experimental and non-frequent users was coupled by a reduction in their perception of cannabis availability. This might indicate that this kind of policy was effective in reducing access through informal channels or increasing the price of this substance on the black market for those sub-populations of users. Second, it has to be considered that one fundamental reason for increasing the level of prohibition is that positive social externalities should be larger than the social costs of repression and private benefits for users . In fact, the failure in achieving this objective has lead several countries to move towards depenalisation and legalisation in recent years . Our results confirm that some of these reforms are linked to a reduction in the share of students approaching this substance, which is in line with this objective. However, the fact that no reduction is observed in the share of frequent users, who are those at higher risk, signal a limited public health impact of this approach among adolescents at higher risk, which might in turn reduce its social externalities. A similar reasoning can be applied to the Hungarian case , which applies the more severe punishments for cannabis possession, and where no significant change was observed either in the perceived availability or in the share of cannabis users following the policy reform. Finally, the absence of a significant decrease in the share of frequent cannabis users associated to any of the policy changes, might signal a limited role of policies overall in achieving results among this high-risk population. In this light, investments in evidence based adolescent substance use prevention programs would be advisable . Given the fact that we did not find any significant decrease in the perceived accessibility to cannabis for frequent users, an interesting perspective would be to focus on resilence factors, which may increase the unwillingness to use the drug,mobile grow system even when drug use opportunities are available .This study has some limitations, some of which are common to other studies using cross-sectional data, that we aim to address in future research. First, since our estimates rely on self-reported survey data, there might be the concern that changes in drug policy influence the way individuals answer the survey.

For example, if with more liberal policies and less severe punishments in place people were more prone to admit drug use when asked about it in a survey. Although issues of truthfulness are more likely to arise when surveys are administered by personal interview, whilst in our case the ESPAD survey is anonymous and self-administered respecting privacy conditions, we cannot completely rule out this hypothesis. This is one of the trade-offs that research on socially undesirable and illegal behaviours is confronted with. Second, our analysis is based on country-level prevalence measures, which do not account for individual-level factors that may confound the relationship between cannabis policy reforms and cannabis perceived availability and use among adolescents. This is because, while a number of individual-level variables are available in the last waves of the ESPAD study for many countries, they are not available for the whole time span and countries considered. Confronted with this trade-off, consistently with our research question we opted for maintaining in the analysis many countries and the largest time span possible to be able to provide an European picture. Finally, this research, as most part of the previous studies on the topic, does not include an analysis of the actual level of enforcement of the policy reforms, nor of social approval of cannabis use, due to data limitation. This is something that would be important to explore in the future, when some more information about these aspects will possibly be available. Substance use and mental illness are strongly inter-related . Several theories have been advanced to explain the bi-directional and complex relationship between these dual diagnoses, which often co-exist in the same individual. The self-medication hypothesis postulates that mental illness might contribute to substance use and addiction due to individuals using specific substances to ameliorate specific symptoms .

STRs are the gold standard for human identification  and as such they can also be applied to C. sativa for forensic purposes. Moreover, studies that included STRs C. sativa genotyping have reached promising results for forensic purposes. In 2016, a 13-locus cannabis STR method was developed and validated according to guidelines of the International Society of Forensic Genetics and the Scientific Working Group on DNA Analysis recommendations for the use of non-human DNA. Although this STR method cannot distinguish hemp from drug type, a previous study showed that groups of cannabis seizures could be associated using phylogenetic analysis demonstrating its application for intelligence purposes. Generally, when a new method is developed, interlaboratory tests were carried out to test its robustness, reliability and reproducibility. The objective of this work was to test this newly developed cannabis STR multiplex kit through an inter-laboratory exercise with different laboratories in Europe. Up to date, this is the first collaborative exercise on STR identification of C. sativa. After approval by the Italian Forensic Geneticists  society, a collaborative exercise to test a 13-locus cannabis STR was organized. Twenty-one European laboratories from different institutions, using different DNA analysis platforms, participated in the exercise.Each box contained: two cooling tablets, a self-sealing pre-PCR bag and a self-sealing postPCR bag. The pre-PCR bag contained a PCR master mix tube , a primer mix tube  and sample set tubes in three separate bags. The sample set contained three aliquots  of C. sativa DNA . The PCR master mix and the primer mix were prepared according to Houston et al.. Lastly, an aliquot of 5 µL of allelic ladder was contained in the post-PCR self-sealing bag. Protocols for PCR amplification and DNA genotyping were also provided. Participants used their standard DNA genotyping platforms, as well as the interpretation and reporting guidelines. Some reagents used in this exercise were kindly provided by Dr.

Running conditions were chosen based on standard HID STR genotyping protocols used by each laboratory. The different genetic analyzers used by each laboratory are displayed in Table 1. Different run parameters  were applied according to each laboratory protocol. For this reason, the majority of laboratories had to adjust their bin sets appropriately. Marker panels and allelic bins files for different versions of Genemapper® software  were developed and provided by the core lab to each participant laboratory. Indeed, grow tent for sale online technical support for the calibration of bins and markers according to different electrophoretic conditions was also provided. Analytical and stochastic thresholds were set according to each laboratory’s protocols and interpretation guidelines. Participating laboratories provided a table with genotyping results and the raw data sample files  with the printouts of the obtained electropherograms. Heterozygous peak height ratio  was calculated for a given locus by dividing the peak height of an allele with a lower relative fluorescence units value by the peak height of an allele with a higher RFU value in a heterozygous pair, and then multiplying this value by 100 to express the PHR as a percentage. For the PHR, the mean, standard deviation , median, minimum and maximum were calculated. The inter-loci balance was calculated as the ratio between the mean peak height for each locus and the mean peak height across all loci multiplied by 100. Stutter percentage was calculated based on the peak height of the parent allele . Stutter peaks that were in-between two alleles on + 1/− 1 stutter position were regarded as −1 stutter of the longer allele. Stutter peak average was determined and the −1/+ 1 stutter mean obtained from each laboratory were estimated. As part of a new forensic kit in-house validation the assessment of −1 and + 1 stutter unit repeat filter application was required. To identify if a peak was a true allele or a stutter, we applied stutter ratio filters for different STR loci. Peaks below that filters were considered stutters. Results from positive control, sample 1 and sample 2, each in triplicate, were utilized to determine the −1 and + 1 stutter ratio thresholds percentage. Each sample replicate was analyzed by the software GeneMapper ID-X ; no stutter filters were applied and a detection threshold was set to 30 RFU. RFUs from 3300 to 8000 data point were collected and analyzed.

For the statistical analysis, GraphPad Prism software ver. 9.0.2  was used. Mean of Peak Height and Parent Allele Stutter , −1 and + 1 Stutter Percentage Mean  were also calculated. PHLM, PHPASLM, MSLM and PSLM were used to calculatethe Average of laboratories means and peak height  and the standard error of the mean for all laboratories. The minimum peak height of parental allele with a stutter was also estimated. To determine the limits of detection for a given analytical procedure, it is necessary to determine a Minimum Distinguishable Signal , the signal at which a peak can reliably be distinguished from noise. The MDS may be considered a relative fluorescence unit or an analytical threshold  for forensic purposes. Furthermore, the detection limit at 99.7% confidence is based on the Gaussian distribution of noise peaks height and this does not consider a possible asymmetric distribution where, the correct 99.87% confidence should be applied. The background noise level detected of each instrument were compared, to evaluate their impact on the general background noise. Three negative samples  were amplified, run through capillary electrophoresis and analyzed by setting the GeneMapper™ software at 1 RFU as detection threshold. RFU data from 3300 to 8000 data point were collected. The GeneMapper data were exported to a txt file and then imported to an excel tool or GraphPad Prism software v. 9.0.2  for the analysis. The background instrument peak heights  observed in each dye channel of each laboratory were compared. The following parameters were calculated for each laboratory: Maximum Peak Height , Average Peak Height , Standard Deviation , Limit of Detection , Limit of Quantitation , Analytical Threshold . APH and AT means were used for each dye channel to calculate the Standard Error of the Mean  for each laboratory. The percentage of genotyping success was estimated to be 96% . Genotyping errors may be due to partial DNA degradation , amplification errors, stutter calculation errors, bin error and PCR artifacts such as allelic drop-out. All of these interpretation errors and artifacts can be resolved with an optimization of this methodology through an internal validation and subsequent interpretation guidelines. A locus was labeled discordant if one or more alleles were miscalled, for example, ANUCS305 locus resulted in about 10% of incorrect allele calls for both samples . A locus was labeled concordant when all alleles were correctly called, for example 4910, 9043, B05, 1528, CS1, D02, C11 and H06 loci gave a 100% of consensus allele calls among the participant laboratories . For sample 1, laboratories 2, 6, 7, 9, 11 and 13 reported incorrect allele call for a heterozygous STR loci: 9269 , 5159 , ANUCS305  and 3735 .Moreover, laboratory 6 did not produced results for three loci: 9269, ANUCS305 and 3735.

Laboratory 13 did not produce any result for loci ANUCS501 and 9269 . For sample 2, laboratories 3 and 13 encountered a problem with incorrect allele call of the 9259 heterozygous STR locus. Moreover, laboratories 5 and 6 did not produced results on loci: ANUCS501, 9269 and ANUCS305. Indeed, laboratory 6 did not produce any result on locus 3735 . The calculations of percentage of success were based on a total of 13 STR loci. Examples of typing errors are displayed in Fig. 2. The negative controls did not show any evidence of external contamination. In the case when a laboratory failed to produce results for a specific STR locus or if only one allele at a heterozygous locus was obtained, it was considered an error and not a partial result for the purpose of the study. Results with concordant calls with those of the organizers were considered correct . In summary, twenty laboratories submitted results for cannabis STRs. Eleven laboratories obtained full and concordant profiles for the two samples without errors, two laboratories obtained full and concordant profiles with one error, four laboratories completed the exercise with two errors, one laboratory committed three errors, while two laboratories completed the test with more than three errors. The success rates for cannabis STR typing ranged from 74.4% to 100% for sample 1 and from 69.2% to 100% for sample 2. Genotyping success calculations were based on the total number of loci tested by a laboratory in this study. An example of an electropherogram of this study is displayed in Fig. 3. Peak heights for the heterozygous markers were averaged and the intra locus peak height ratio  was calculated. The final average PHR was calculate by the mean PHR for each heterozygous locus of the three samples, and resulted to be 78.2% . The mean inter-loci balance was estimated to be 100,00%. The present collaborative study of the Ge.F.I.-ISFG working group allowed to demonstrate the robustness and reproducibility of a 13-locus cannabis STR multiplex system for forensic DNA profiling. Overall, each participant, using various instrumentation, polymers, size standard and arrays, generated STR profiles for each of the 13 markers. Analysis of the electropherograms, by the core laboratory, showed a concordance of more than 96%. Data misinterpretation resulted in discordance in some markers; typing was more problematic with the analysis of the ANUCS501, 9269, ANUCS305 and 3735 loci. This problem will require further investigation and all of these discordant allele calls can be resolved with, an optimized bin set, more training and experience with this multiplex STR kit. An important limitation of this study is that the analysis was conducted with cannabis DNA extracts instead of cannabis plant tissue. An important source of variation may occur during DNA extraction of different cannabis plant material. It is important to note that this STR kit cannot differentiate hemp from drug type; therefore, chloroplast DNA markers should be used for this purpose. However, using STRs,indoor tent grow cannabis seizures can be genetically associated through phylogenetic analysis of a previously established database.

Lastly, a plant generated from clonal propagation can be genetically associated to its clones using this STR kit. Future plans include: a) a collaboration between laboratories to test this kit with a new synthetic allelic ladder , to increase allele coverage and to aid in more accurate allele calls, b) studies of variation based on different extraction methods, types of tissue and various storage conditions and c) comparison of different databases. A written consensus standard for C. sativa authentication would be useful for the forensic community to establish rules and interpretation guidelines. Points to be considered for a future consensus standard include: allelic ladder, stutter filter recommendations, DNA quantitation methods, a comparative C. sativa STRs database, and troubleshooting. Finally, this inter-laboratory exercise can be considered a milestone in the identification of C. sativa samples. For centuries, cannabis has been used with many different purposes, including medicinal use.The Shennong Ben Cao Jing encyclopedia, which dates back to 2900 BC in China, recommended the seeds as treatment for pain, constipation and malaria.Additionally, the plant was used along with wine to create an anesthetic effect for patients undergoing surgery.Around 1000 AC, cannabis flowers became popular in India, providing analgesia, hypnotic, antispasmodic, and anti-inflammatory effects.In the 21st century, cannabis began to be explored by Western medicine, however only plant extracts were used,and active ingredients, both from leaves and flowers were isolated.During the 20th century, the endocannabinoid system was further understood and in the 3rd edition of the US Pharmacopoeia, in 1851, cannabis was included as a treatment for gout, rheumatism, tetanus, cholera, hysteria, depression, delirium tremens, and uterine bleedings.Cannabis was available in the US pharmacies since 1845 and was available in British pharmacies for over a century,however, because of the rise of concerns by its psychotropic effects, it was removed from the US Pharmacopeia in 1941.In 1976, the United States Controlled Substances Act classified cannabis as a Schedule I drug, meaning it had no acceptable medical use and high potential for abuse.

However, adjusting for covariates in models 2 and 3progressively attenuated the beta estimate and increased the width of the confidence intervals to include null and positive values. All other categories of self-reported cannabis use produced wide confidence intervals that include null values. Fibrinogen. In bivariate analysis, self-reported cannabis use within the past 30 days was associated with lower levels of fibrinogen compared to nonuse with confidence intervals around the beta point estimates excluding null and positive value. Like IL-6, adjusting covariates in models 2 and 3 attenuated the point estimates and widened the confidence intervals to include the null value. Full model estimates with covariate results are included in the Supplementary Material Table S3.In this analysis of nationally representative data from Wave 1 of the PATH study, there was a pattern of lower levels of biomarkers of systemic inflammation, particularly hs-CRP among respondents self-reporting recent  cannabis use compared to never use, although the wide confidence intervals around the point estimates indicated findings were not statistically significant. Furthermore, statistical tests to determine whether the association between self-reported cannabis use and biomarkers of systemic inflammation differed by sex were also not statistically significant. The findings from our study are based on a multivariable analysis that adjusted for important confounding variables, including respondent’s BMI and use of antiinflammatory medications. The potential therapeutic effects of cannabis have been proposed to be mediated via its anti-inflammatory properties . Findings from preclinical and animal studies converge to suggest that the active constituents in the cannabis plant – particularly THC and CBD induce anti-inflammatory properties . Our study found that more recent cannabis use is associated with lower levels of biomarkers of systemic inflammation is consistent with anti-inflammatory hypothesis and with findings from prior research. Data from the National Health and Nutrition Examination Survey  showed lower serum CRP levels in active cannabis users compared to never users, but only when CRP levels were below the median . Also, self-reported cannabis use was not statistically associated with lower levels of CRP in a recent analysis using data from the Adolescent to Adult Health study, after adjusting for sociodemographic characteristics, tobacco exposure, BMI and anti-inflammatory medication use .

In a recent longitudinal analysis of participants in the CARDIA cohort study, self-reported recent cannabis use was not statistically associated with lower levels of CRP, IL-6 and fibrinogen among the CARDIA sample.In sum,trimming tray most epidemiologic studies investigating the association between self-reported cannabis use and biomarkers of inflammation have found negative  associations that were non-significant with the exception of a few that reported statistically significant negative associations . The reason for the disparate findings may be related to differences in the study sample that focused on primarily African Americans  and in the set of con-founders included in the multi-variable models . Our study adjusted for important con-founders such as anti-inflammatory medication use and BMI, which these prior studies did not address in their analysis . Indeed, our study found statistically significant associations between recent cannabis use and lower levels of hs-CRP, IL-6 and fibrinogen in limited models , which was no longer statistically significant in the fully adjusted model 3, underscoring the importance of fully adjusting for important con-founders when investigating the relationships between cannabis use and inflammation. Our study extends findings from the extant literature by utilizing a large nationally representative data to analyze the association between self-reported cannabis use and three biomarkers of systemic inflammation. Although our results suggest lower levels of biomarkers of systemic inflammation in respondents self-reporting cannabis use in the past 30 days , the estimates produced had wide confidence intervals. The wide confidence intervals observed in our study might be a source of measurement error related to the imprecise measurement of cannabis. Our study relied on self-report of cannabis use, which is prone to inaccuracies. specifically, respondents may not accurately recall the last time they used cannabis, making it possible that some respondents who reported that they used cannabis within the past year, but more than 30 days ago, might have used in the past 30 days. Also, the cannabis use measurement in this analysis did not collect data on the amount and or concentrations of the different active compounds in marijuana. This is particularly relevant as emerging evidence suggest that the two primary active constituents in cannabis – tetrahydrocannabinol  and cannabidiol  – may have opposing immunomodulatory effects . Therefore, to move the field forward, better measurement of cannabis use, that includes the amount, THC and CBD content and mode of consumption  would help us ascertain the dose-response relationship between cannabis, inflammatory markers, and symptomatology and whether findings differ by THC/CBD concentrations and mode of consumption. Our study also analyzed hs-CRP data which is a more stable and sensitive molecule  than the standard CRP test. The hs-CRP assay can detect trace amounts of CRP than the standard CRP test. Although statistically non-significant, our analysis showed that the differences between recent cannabis use and other categories of cannabis use were more prominent for hs-CRP than other sensitive biomarkers of systemic inflammation. This suggests that more sensitive biomarkers of systemic inflammation should be employed in future research.

Our analysis was based on only three biomarkers of systemic inflammation; with the blood specimen to measure these biomarkers collected on a separate visit from the visit cannabis data was collected. Future studies should include a broad panel of biomarkers, particularly anti-inflammatory molecules in order to increase our understanding of the immunomodulatory effects of cannabis use. We note that mean levels of all biomarkers of systemic inflammation were higher among respondent self-reporting cannabis use within the past year, but not in the past 30-days . It is possible that this group includes respondents who recently ceased cannabis use due to illness that can drive inflammation response. The cross-sectional design of our analysis precluded the assessment of directional relationships. Specifically, a cross-sectional finding indicates a correlational association, precluding a directional or causal relationship between cannabis use and biomarkers of systemic inflammation. Therefore, future research using longitudinal and experimental designs that follow subjects across multiple time points are needed to broaden our understanding of the cannabis and inflammation relationship, specifically whether reductions in inflammatory markers mediate the association between cannabis use and reduced self-reported chronic disease symptomatology or differences in incident or recurring inflammatory-related disease .Cannabis is the most commonly used illicit drug globally, with some 250 million estimated active  users. Policy approaches for cannabis have been shifting gradually around the world recently. While criminal prohibition has been the main control framework for decades, Canada, Uruguay, and 11 US states have recently legalized non-medical cannabis use and supply, with reference to public health and safety objectives. New Zealand, alongside other jurisdictions, is actively considering a similar policy reform towards legalization of non-medical cannabis use and supply that will be decided in a public referendum in late 2020. Public opinion polls suggest an about split for and against a legalization framework as presented in the draft ‘Cannabis Legalization and Control Bill’. This proposal is very similar to Canada’s laws in: legal use age of 20 years; no public use; commercial production and retail of diverse cannabis products; and home-growing of cannabis allowed.

New Zealand, along with North America and Australia, is part of a group of ‘high-use’ countries in which 8%–15% of the population report cannabis use, the majority of whom have tried cannabis in their teens. While survey evidence is not wholly consistent, cannabis use has increased among young adults in the general population in New Zealand but declined among adolescents. Cannabis use remains concentrated among youth/young adults , with about one in three reporting recent use but its prevalence of is lower than that of alcohol and tobacco. These include: acute cognitive,psychomotor control and memory impairment ; moderately increased driving impairment increasing risks of injury/death; cannabis use disorder/dependence ; weak to moderate associations with chronic mental health problems, primarily schizophrenia and depression ; chronic bronchitis or other pulmonary problems  among those who smoke cannabis ; select adverse reproductive/maternal health outcomes  among women using cannabis during pregnancy; and possibly cardio-vascular problems among users of high-potency cannabinoid products. With notable exceptions , there are few, if any directly attributable  deaths from cannabis. The lion’s share of the cannabis-related burden of disease is attributable to cannabis-related impairment, and consequential injuries or deaths, and cannabis use disorder . The cannabis-related disease burden is substantially lower than that for alcohol, tobacco or psychostimulants. The main adverse social consequences of cannabis use can include compromised educational attainment, and adverse consequences of arrests and convictions e.g. restrictions on travel and professional disadvantage. Arrests commonly involve young and socio-economically marginalized males as a result of selective enforcement practices with related social injustices. Among youth and young adults, adverse health and social outcomes primarily occur among sub-groups of vulnerable users characterized by select, shared risks characteristics. This fact has major implications for the foci of targeted prevention of cannabis-related harms from a public health point of view, namely the need to give priority to protecting young people from the adverse effects of their youthful cannabis use on their life chances and courses. Among its essential prospective benefits, cannabis legalization allows authorities to regulate cannabis products, distribution and use. It furthermore makes it easier to directly facilitate interventions aimed at users, and specifically to systematically provide risk reduction advise  to users. Targeted or secondary prevention measures to reduce risky or harmful cannabis use have traditionally been limited, and general prevention efforts have mostly focused on reducing availability and advising against cannabis use. This, in part, because risk reduction advice has been seen as implicitly ‘endorsing’ cannabis use as an illegal activity. Recent reviews suggest some evidence for a limited impact of individual targeted risk-reduction interventions, for example, in the form of ‘brief interventions’, for cannabis use. A tailor-made population-level targeted prevention tool for cannabis use, the ‘Lower-Risk Cannabis Use Guidelines ’, was developed, originally in 2011 and updated in 2017, in anticipation of cannabis legalization in 2018 in Canada. The LRCUG embody health-focused education and ‘behavioral choice’ models that focus on risk factors for adverse harm outcomes from cannabis use, identifified by reviews of relevant scientific evidence, trim tray pollen that users can modify if they wish to reduce risk of harm with ongoing use. The LRCUG comprise a total of 10 recommendation clusters advising users on how to reduce cannabis use-related risks developed from the consensus of an international group of addiction and health scientists. Important for general uptake and dissemination, the LRCUG have been endorsed by ten leading Canadian organizations [e.g., the Canadian Medical Association [CMA], the Canadian Public Health Association [CPHA], the Canadian Society of Addiction Medicine [CSAM], among others with health, substance use and addiction focus or mandate.

They were also included in education and prevention strategies devised by different levels of governments as part of the implementation of cannabis legalization in Canada. To practically facilitate wide dissemination and uptake, a suite of customized ‘knowledge translation’ products was developed  for different target audiences and distributed jointly with key stakeholders. The LRCUG, or similar frameworks, have been adapted for use in Latin America and other jurisdictions. Based on the proposed parameters of possible legalization policy in New Zealand, and available assessments of the impact of legalization on cannabis use and harm outcomes to date in other jurisdictions, it is possible that some of these harm indicators, at least in the short-term, may increase. Given this, the LRCUG provide a ready-made, evidence-informed population health tool with the potential to reduce the risks of adverse effects among the sizeable population of cannabis users in New Zealand. Moreover, the New Zealand government’s draft legalization bill stipulates mandatory ‘harm minimization messaging’ to be provided to users at cannabis retail interfaces, for which the LRCUG provide a ready and fitting foundation or template. While the scientific evidence informing the LRCUG is evolving and will require future updating, the LRCUG’s concept and approach resemble other, established health behavior guidelines, for example targeting nutritional, cardio-vascular, sexual health promotion or related risk reduction, and – the closely topic-related – low-risk drinking guidelines in place in many English-speaking and other countries.

Cases in the deCODE sample met criteria for lifetime DSM-III-R or DSM-IV cannabis abuse or dependence or DSM-5 cannabis use disorder according to diagnoses made at the National Center of Addiction Medicine in Iceland, whereas controls were derived from the general population of Iceland . Exposure data were not available for some large groups ; therefore, controls were defined regardless of lifetime cannabis exposure across all datasets.Adverse mental health and social outcomes of cannabis use have been reported for individuals and societies . Cannabis use was associated with the use of other drugs , difficulties to reach life goals , adverse educational outcomes in adolescents , legal issues, and traffic accidents . On the one hand, there are genetic and neuro developmental risk factors ; on the other hand, there are potentially modifiable environmental risk factors of cannabis use . Parenting styles , substance use of parents and peers, academic and school related factors , and risk perception have been described as relevant psychosocial risk factors . In 2016, a global estimate by UNODC based on data from 130 countries estimated that 5.6% of the population aged 15–16 years had used cannabis at least once in the past year . In different regions of the world, the sale of cannabis has been legalized, leading to renewed interest in how this may affect cannabis use and associated factors . In Chile, a law is currently under discussion in Congress aiming to legalize home cannabis cultivation for personal recreational and/or medical use. In the past decade, there has been a public debate about legalization and important changes in legal practice to decriminalize cannabis cultivation. An increase of the prevalence of adolescent cannabis use in Chile was reported for the year 2013 compared to the years 2001–2011 . The prevalence of adolescent cannabis use in Chile was reported to be the highest in the Americas /InterAmerican Drug Abuse Control Commission , 2019. In line with the normalization theory , adolescents in countries with high prevalence of substance use are less likely to report risk factors than in countries with low prevalence.Therefore, risk and protective factors may have changed in prevalence and/or strength of association constituting new challenges for targeting prevention.

Risk and protective factors of substance use had been reported to be consistent between 1976 and 1997 in the US : several variables such as religiosity, political beliefs, truancy, and frequent evenings out were consistently linked to substance use over time among high school students. However, in the current context of marked changes of prevalence in adolescent cannabis use in Chile, the assessment of prevalence factors and their effect size over time may allow reaching a better understanding of the factors underlying the process in which the substance use is changing over time and then contributing to adjust prevention strategies and exploring if the factors associated to substance use vary across years. Factors associated with substance use in adolescents had been reported from Chile for one single year , but how these factors vary over time and in their strength of association with the prevalence of cannabis grow set up use has not been previously addressed. In Argentina, Chile and Uruguay, an increase of cannabis use in adolescents in recent years has been reported, and the association between risk perception and use has decreased. Meanwhile, perceived availability remained strongly associated with cannabis use, but other potential risk factors have not been investigated . The quantification of potential risk factors and their trends over time may allow targeting prevention strategies . The aim of the present research was to identify prevalence trends and associated factors of cannabis use in the past years among adolescents, and to assess trends of associated factors and the strength of association over time.Study participants were adolescent high-school students. The Chilean National Service of Drugs and Alcohol Use Prevention and Rehabilitation  carries out the nationwide school-based survey in students from 8th to 12th grade every two years, with a probabilistic, representative at regional  and nationwide level, stratified , multistage sampling design in clusters . The rate of reached sample was around 80% of the theoretical sample size. The detailed methodology is presented by SENDA in each survey report available online  with stability across the years from 2003 to 2017 and minimal variations. We obtained data from SENDA for the years 2003 to 2017 , 2018. SENDA offers the option of a self-administered questionnaire and a face-to-face interview. In the self-administered version, the students are supervised by a surveyor.

Once the schools and classes were defined, random samples of 20 students were selected from each classroom to participate in the survey /Inter-American Drug Abuse Control Commission , 2019.The survey questions included socio-demographic data, several types of substance use , tobacco and alcohol, perceived risk of substance use, satisfaction with school, school attendance, grades, relations with peers, teachers, and parents and extracurricular activities among others. We selected items that were consistently present across the years, relevant in practice and representing different areas of risk. The following variables were included in the analyses: 1) Cannabis use in the past year ; 2) Funding of the school: public  vs. private or mixed ; 3) gender; 4) age; 5) Use of alcohol in the past month ; 6) Use of tobacco in the past month ; 7) Age at first use of alcohol; 8) Age at first use of tobacco; 9) Unexcused absence from school  in the past year ; 10) School performance based on self-report was dichotomized as low  vs. high; 11) Sport activities, as the number of days per week doing sports as extracurricular activity; 12) Educational level of parents with three alternative categories: uncomplete secondary level, complete secondary level  and complete higher education; 13) Marital status of the parents; 14) Parental acquaintance with friends was assessed with the question, “In general, would you say that your parents  know your closest friends very well, fairly well or little?” ; 15) Parental rejection of alcohol use ; 16) Parental rejection of cannabis use ; 17) Having friends who regularly use alcohol ; 18) Having friends who regularly use cannabis ; 19) Perceived risk of cannabis use .Descriptive statistics were calculated for each year of the surveys, and for the variables: gender, age, school funding, cannabis use prevalence, alcohol and tobacco use prevalence; 95% confidence intervals  were calculated for prevalence rates. Mixed effects logistic regressions were performed for data at individual level, with data nested at the school level , and nested at the level of funding source of the schools. The multilevel logistic binomial regressions were conducted with cannabis use in the past year as dependent variable for each year separately. Adjusted odds ratios were calculated for each variable. The variables at the individual level were: Gender; age; age at first alcohol use; age at first tobacco use; alcohol use in the past month; tobacco use in the past month; perceived cannabis use risk; school performance; truancy; days of sport activities in a week; friends regularly using alcohol; friends regularly using cannabis; educational level of father and mother; parents’ marital status; parental acquaintance with friends; parental alcohol use rejection; parental cannabis use rejection.

Intraclass correlation coefficients were calculated from a null model for both the school level clusters and school funding level clusters. The command glmer of the lme4 package was used in R software to estimate the mixed effects logistic regressions. Variables with odds ratios on average higher than 1.5 across the entire time series were retained for further analyses. This threshold was introduced due to the large size of the data set and to avoid retaining significant odds ratios close to 1.0 that may be clinically irrelevant and irrelevant for prevention planning. Odds ratios smaller than 1.5 can be considered as small effect size and larger than 1.5 as moderate or large effect size . Adjusted odds ratios were calculated for the retained variables for each year of data collection to assess changes of the association over time. Also, interactions between year and each one of the retained variables were analyzed by multilevel mixed effects logistic regressions for all pooled data to assess how the associations between variables and outcomes were affected by time in each survey cycle, using the first year of the series as reference. The prevalence of the retained variables was described as trends over time. Trends of prevalence data and odds ratios over time were plotted for the retained variables and each trend was tested for its fit to linear or higher models, and the F-statistic, degrees of freedom , R-squared and p values were reported. As quality control, before the analyses, data points of participants who answered in at least two occasions in an inconsistent way for each substance were eliminated , for instance, inconsistent answers about date of last use of cannabis, lifetime use and/or use in the past month.The interaction of each one of the retained prevalence factors and year of data collection was calculated, with the year 2003 as reference. specific differences over time in the association of each factor with cannabis use were observed. For the use of alcohol in the past month, we observed a significant negative interaction from 2007 to 2017 showing a decrease of the association with cannabis use over time. For the use of tobacco in the past month, a similar pattern of negative interactions was observed between 2007 and 2015. For the factor friends who regularly use cannabis, we observed negative interactions from 2007 to 2017. For truancy, negative interactions were seen from 2009 to 2017. For low outdoor cannabis grow risk perception, the interaction for 2009 was negative, but thereafter positive. In contrast, low parental cannabis rejection was the only factor that showed positive interactions from 2007 over time until 2017 . Table 3 shows the interactions observed between years and prevalence factors.Our research showed that cannabis use among adolescents increased substantially from 2003 to 2017.

We identified the factors most strongly associated with adolescent cannabis use and present prevalence estimates over time for those prevalence factors. Furthermore, we inform the strength of association over time for each of the most important factors. Although having friends who regularly use cannabis decreased in the strength of association with cannabis use, the variable continued to have the strongest effect size. An important increase in the magnitude of association with cannabis use was seen for low parental rejection of cannabis use. Interaction analyses for each year with each of the factors associated with cannabis use, showed trends since 2007 with a decrease of the association between cannabis use and the factors alcohol use in the past month, tobacco use in the past month, cannabis use in friends, and since 2009 for truancy. However, we observed an increase in the association between cannabis use and low parental cannabis rejection since 2007. Overall, the most important prevalence factors show significant changes in the strength of association since 2007 compared to the reference year 2003. Interestingly, this precedes the major increase in the prevalence of cannabis use observed between 2011 and 2013.This study comprised nationwide survey data of more than a decade with large sample sizes. We show for the first time trends for the prevalence and the strength of association with cannabis use of possible risk factors in a Latin American country. The study also has limitations: even though the surveys were presented in a consistent way over the years, the data were based on self-reporting. Repeated cross-sectional data do not allow establishing causal links between the increase of cannabis use and the associated variables. The variables assessed in this research were mainly on the individual level and limited to the items continuously included in the national surveys over the years.In the US, the prevalence of cannabis use among adolescents in the past year increased between 1991 and 2015, while the prevalence of alcohol use decreased, and the prevalence of any other illicit substance use also decreased . In Europe from 2000 to 2015, the prevalence of cannabis use in the past month among adolescents showed heterogeneous trends in different regions: decrease in Northern Europe in linear trends, increase in Southern Europe in linear trends, decrease in Eastern Europe in a concave trend and increase in the Balkans in a convex trend.

The band positions and intensities were extracted from the spectra of the THCA/THC and CBD powder standards whereas the IR bands from the CBDA cannabinoid were taken from the mentioned reference. These spectra were additionally used and compared with the spectra of the native and decarboxylated flowers and extracts that markedly helped in the band assignments . The most abrupt spectral difference evidenced upon decarboxylation of the flowers is depicted by the increase of the intensity of the bands around 1510, 1430, 1260, 1180, 1040 and 835 cm 1 . The obtained result infer that the emerging bands most likely arise from the vibrations within the THC and CBD units whose content increased upon heating, as the presence of the corresponding acidic forms is majorly reduced. Thus, the medium band at 1510 cm 1occurs from both the CBD and THC and intensity increase upon flower decarboxylation infers increase of their content. In addition, the striking rise of the band at 1424 cm 1 is attributed to the vibrations from the THC molecules since its intensity dominates in the IR spectrum of the pure THC and the CBD lacks this IR absorption band . A similar conclusion is derived for the bands at 1267, 1038 and 835 cm 1 in the decarboxylated flower spectrum that are the strongest band in the THC and either very weak or absent in the CBD counterpart . Furthermore, the bands at 1621 and 1578 cm 1 are blue shifted in the heated samples in comparison to fresh THCA dominant flowers  and pure THCA spectrum . This outcome strongly reflects that, upon heating, the THCA conversion to THC might be successfully monitored by infrared spectroscopy even in the complex matrix. Similarly, the recent Raman spectroscopy work for non-invasive and non-destructive differentiation between hemp and cannabis attributed the bands at 1623 and 1295 cm 1 to THCA/THC species assigning the former one to their aromatic ring vibration. On contrary, the heated flowers  contracted the intensities of strong 888 and 620 cm 1 bands found in the fresh CBDA rich flowers  that are obviously attributed to the CBDA molecules. Namely, these bands are crucial to determine the presence of the CBDA compound  appearing as the strongest peaks in the pure sample. Moreover, their absence in the THCA counterpart infers that these bands are analytical signatures to follow the transformation of CBDA into CBD.

It is also worth mentioning that the IR spectra of the decarboxylated flowers made possible to discriminate between CBDA and CBD on one hand and the THCA and THC on the other. Moreover, the spectra of the decarboxylated flowers and the fabricated extracts are practically identical . Thus, the band discussion for the spectrum of the decarboxylated flower is also valid for the bands in the spectrum of the cannabis extract. This approach derived from the IR results for the native and decarboxylated flowers was further con- firmed by the chemometric model encompassing the most discriminating bands at 1580, 1430, 1183 and 1040 cm 1 as predictors for THC concentration .Fourteen MIR spectra acquired from different cannabis grow system extract samples were used to construct the calibration set whereas the remaining 20 spectra were used for the prediction set. The CBD and THC concentrations in the samples varied between 0.38– 39.2% and 18.93–86.99%, respectively . Only the spectral region of 1800–400 cm 1 was used for the statistical modeling because the ATR diamond crystal exhibit two-photon broad IR absorbance bands between 2600 and 1900 cm 1 that reduce the signal-to-noise ratio , and the MIR region above 2600 cm 1 did not contain any specific bands originating from the molecules of interest. The preliminary analysis of the models revealed that Savitskzy-Golay smoothing and the second derivative of the native MIR spectra resulted in bestfit parameters for R2Y, R2X  and Q2 . The overlaid spectra from the calibration and prediction set, colored according to the THC and CBD content of the samples are presented in Fig. 4a and b. Considering that CBD and THC were not the sole components in the extract and that the samples originated from different sources , it is logical to assume that some transformation of the spectra will be needed to separate and potentiate the specific bands with quantitative relationship to the components of interest. Therefore, in the further part, only the model based on the above mentioned transformation will be presented and discussed. Three main components were extracted from the PLS model for quantification of THC with 0.934, 0.951 and 0.909 for R2X, R2Y and Q2. The score scatter plot for this model reveals distinctive pattern of the sample variances that can be traced to the concentration of THC in the samples. Indeed, these plots reveal how the X variables are related to each other. In this model, there is a clear trend of distinction among the spectra along the t1 vector related to the THC concentration of the samples, thus pointing out the dominant role of the first component in the overall prediction capability of the model. Furthermore, the VIP plot reveals the spectral regions with the utmost importance in the regression model. The bands with VIP factor larger than 1, are usually considered as important both for explaining the variations in the X matrix as well as to correlate with the Y variables. The spectral regions around 1040, 1425, 1183 and 1577 cm 1 demonstrate the largest VIP factors in the model and should be considered as main predictors for the THC concentration. The latter could be additionally confirmed with the coefficient plot , where the mentioned spectral regions are assigned with the largest regression coefficients. The plotted results of actual  versus the predicted THC concentrations  are presented in Fig. 5d, and the RMSEE  of 4.67% indicates the fit of the observations to the model. The RMSEcv for this model is 5.25% and it is an analogous measure to RMSEE, but estimated using a cross-validation procedure.

The RMSEE and RMSEcv are descriptors for the absolute accuracy of the model, and the values reported here should be expected, taking into consideration the variable origin of the samples , number of samples, the employed concentration range, and the real limits of the analytical technique . Three main components were also extracted from the CBD quantification PLS model with 0.936, 0.991 and 0.972 for R2X, R2Y and Q2. In this model, the score scatter plot  also presents a distinctive pattern related to the CBD concentration in the samples that follow a diagonal line between both score vectors , indicating that both the first and second component has significant capabilities for prediction of the Y variable. The VIP plot  demonstrated that the same spectral regions of the previous model , with an addition of the region around 880 cm 1 . These regions bear the largest VIP factors, and at the same time, the mentioned spectral ranges are assigned with the largest regression coefficients . The plot of actual versus predicted CBD concentrations  reveals a better fit of the points relative to the previous THC model with 1.21 and 2.62% for RMSEE and RMSEcv. The predictive capabilities of both models were evaluated separately on a prediction  set of 20 extract samples of various origin and the results are presented in Fig. 6a and b. The root mean square error of prediction,  for THC and CBD PLS quantification models were 3.79 and 1.44%, respectively, thus con- firming the previous accuracy descriptors and ruling out the possible bias of the calibration models.The PLS models for the quantification of THC and CBD in decarboxylated Cannabis flowers also employed the second derivatives of the raw MIR spectra  with Savitsky-Golay smoothing. The overlaid spectra from the 45 samples used in the calibration and prediction set, colored according to the THC and CBD content of the samples are presented in Fig. 7a and b. As in the previous case, such transformation was chosen as the most optimal regarding the main fit parameters  in comparison to the raw, SNV and first order derivative MIR spectra models. Such data transformation is often considered as a necessity in cases where spectra from complex matrices are obtained and the main quantification related bands are overlapped with other components present in the sample. The THC PLS quantification model was build using transformed spectra acquired from 15 decarboxylated samples with various THC content and origin . Five main components were extracted from the model explaining 97.2% of the variations in the X-variables, and producing a high correlation coefficient R2Y = 0.992 with appropriate predictability . The score scatter plot of the second and third component vectors reveal the THC content related pattern, where the THC content increases as a function of the score in both components . The model VIP plot  exposes the bands that are related to the THC content in the flowers. The spectral regions around 1620, 1610, 1578, 1425, 1180, 1038, 1010 and 825 cm 1 which are similar to the ones reported in the extract PLS models, are also assigned with large VIP factors. The coefficient plot confirms the previous findings, where the above mentioned spectral regions with the highest VIP factors,marijuana grow system are also assigned with the highest regression coefficients . The RMSEE and RMSEEcv derived from the actual versus predicted THC concentrations plot  were 0.43 and 1.53%.

The complexity of the sample , the variability of the samples in regards to their origin and horticultural maturity, as well as the nonuniformity of the plant material and the flower-ATR crystal contact should be considered as main factors that govern the accuracy descriptors. Five main components were extracted for the PLS modeling for CBD content quantification of the Cannabis flowers with R2X = 0.969, R2Y = 0.994 and Q2 = 0.66. As in the previously described model, the score scatter plot of the second and third main components vector presents a distinctive pattern associated with the CBD content in the samples . The bands around 1440, 1185, 1100, 1010, 911, 888, and 826 cm 1 demonstrated the largest VIP factors in the MIR spectra . The mentioned bands were assigned with the highest regression coefficients , thus confirming their association with the CBD content. The actual versus predicted plot  of the samples demonstrates a satisfactory level of correlation and the accuracy model parameters RMSEE and RMSEEcv were 0.21 and 1.41%. To evaluate the predictive capability of the above mentioned PLS models for quantification of THC and CBD in decarboxylated Cannabis flowers, a separate prediction  set of 30 samples of different origin was employed. The correlation plots of actual versus predicted THC and CBD content are presented in Fig. 9a and b, and the models RMSEP was 2.32% and 1.33% for quantification of THC and CBD, respectively. The RMSEP values are in good agreement with the accuracy descriptors of the models and con- firm the presented predicting capability of the models in a separate independent set of samples.To our knowledge, this study is the first to use a validated questionnaire to assess the association between female sexual function and aspects of cannabis use including frequency, chemovar, and indication. In this survey of more than 400 women, we found a dose response relationship between increased frequency of cannabis use and reduced odds of female sexual dysfunction. In addition, while the increase in index scores was small , increased cannabis use was associated with improved sexual desire, arousal, orgasm, and overall satisfaction as well as overall improved FSFI scores as compared with less frequent users. Older women and those with more comorbidities tended to have more sexual dysfunction. Importantly, our study did not find an association between cannabis chemovar , reason for cannabis use, and female sexual function. As cannabis use has been shown to be associated with increased sexual frequency in the United States, it is possible this may cause positive effects on sexual experiences.7 Much of the research focusing on sexual function and experiences with regard to cannabis began in the 1970s and 1980s. Cannabis’ potential positive effect on female sexual function was noted as early as 1970 by Tart19 who sought to describe the common experiences of cannabis users. He noted in interviews with college students that orgasms are improved, arousal increases, and “sexual feelings are much stronger” leading to more satisfaction.

The sample size was based on power analysis and previous relevant studies.A total of 357 questionnaires were distributed between January and February 2020 during lectures and 296 questionnaires were returned . Two participants were excluded because their field of study was other than nursing. Finally, 294 respondents were included in the sample. The “Attitudes, Beliefs and Knowledge towards Medical Cannabis Questionnaire”  included 54 items for data collection purposes.Sixteen items were used to assess student attitudes and beliefs towards MC; and, twenty items assessed knowledge on MC effectiveness. MC education/training was assessed by 3 items. A section for reporting demographic, educational and personal data was included. The data collection tool used for this survey evidences internal consistency across multiple locations with Cronbach’s alpha values ranging from 0.767 to 0.831.The instrument was translated from English to Greek and back translated. Cultural adaptation of the translated version was performed by a group of experts including five academic and clinical instructors. The study was designed according to the Declaration of Helsinki and the protocol was approved by the Ethics Committee of the NKUA Department of Nursing . Permission was obtained to use the tool for data collection purposes. Each questionnaire was accompanied by a cover letter providing details about the researchers’ affiliation, contact information and study purpose. Assurance was provided about the voluntary nature of participation and anonymity of collected data. Also, it was clearly stated that returning a completed questionnaire was considered informed consent to participate in the study. Senior undergraduate participants  reported more positive attitudes towards MC use for mental health, fibromyalgia and terminal illness treatment purposes than junior undergraduate participants . Present study results provide the opportunity to compare studies elsewhere of nursing students.Moreover, other data show neutral attitudes towards MC among physicians.Differences between these studies and present Greek findings may be attributed to cultural differences and other factors including the nature and scope of prevailing legislation and regulations. Present study results evidence junior undergraduate respondents are more inclined to believe serious physical health risks are associated with cannabis use. This finding is consistent with that of Khamenka et al.,Chan et al. and Gritsenko et al. who reported the majority of undergraduate medical students believe cannabis use poses serious physical and mental health risks.

The NKUA Nursing Department offers 3rd year students a 3 h lecture on medical cannabis through an elective course titled “Psychoactive Substances”. Consequently, because of the elective nature of the course, few undergraduate students each year receive theoretical education on MC. This may partially explain the present finding that most of the undergraduate participants reported that they should receive formal education on MC laws and regulations. Moreover, undergraduate survey participants were more likely to report a need for MC academic education and clinical practice purposes than postgraduate survey participants. The dearth of MC undergraduate education has been reported in multiple locations.Undergraduate respondents, compared to postgraduates, tend to be less positive about MC effectiveness for medical conditions. Also, they report less personal cannabis use for recreational purposes. The latter issue  is consistent with the findings of Khamenka et al.among Belarus undergraduate medical students who reported less personal cannabis use. Overall, personal cannabis grow system and other substances use tends to be associated with more positive attitudes towards MC benefits. For example, in the study by Vujcic et al.,on undergraduate medical students in Belgrade, the majority of those students believed MC use is safe and associated with health benefits. This result was found associated with positive attitudes towards cannabis use legalization and personal cannabis and alcohol use. Current study postgraduate respondents were more likely, than undergraduate students, to report family member medical and/or recreational use. Moreover, most undergraduate respondents agreed that they should receive MC academic and clinical education/training, including information about laws and regulations, during their nursing studies. These results are consistent with findings of other international studies.Social workers are on the front line dealing with hurmful substance use on individual, family and society levels. The potential increase of MC use among the general population as additional states approve its use, can influence social work practice linked to substance use disorder and criminal justice, health care and child/social welfare institutions and systems.In these domains, social workers have a significant role; therefore, there is ample justification that they should be trained about MC potential benefits and harms. Changing policies and regulations are expected to position social work professionals with significant roles and responsibilities linked to MC. However, little is known about social work student attitudes and beliefs about MC- aspects that would contribute to curriculum development. The aim of this study was to assess MC attitudes and beliefs among social work students from the United States and Israel.

The MC regulations of these two countries differ; and, therefore, it is hypothesized that differences exist between the study groups in terms of the factors studied. Based on college/university level MC education,we believed a cross-national comparison of social work students will reveal MC attitude and belief differences attributed to culture and experience with MC. Drawing on research of student attitudes and beliefs about MC,a data collection instrument was modified for cross- national social work survey purposes. Questions were developed in English, translated to Hebrew and back translated to English to ensure content and vocabulary were appropriate to the students surveyed. This process involved native Hebrew and English-speaking university social work faculty members. The resulting questionnaire used in this survey consisted of 40 short and simply worded questions about MC effectiveness for various conditions, risks, benefits, treatment, training and research. Detailed information about the instrument have been recently published elsewhere.The study was conducted during the 2018–2020 academic years in two institutions of higher education – one in the southern region of Israel and the other in New Jersey . The survey also included a question about student recreation cannabis use. This was included because students’ recreational use has been found correlated with positive attitudes, beliefs and knowledge about medical cannabis including education and training.The aim of this study was to assess medical cannabis attitudes and beliefs among a cross national study cohort of social work students. Overwhelming support was found for MC and substantial acceptance of its therapeutic value. These findings are similar that found among other health professionals such as oncologists and pharmacists.The present study did not evidence any difference based on gender and students who reported personal cannabis use, compared to non-users, were more likely to recommend MC for treatment. Students, regardless of country, who used cannabis were less inclined to believe cannabis use poses serious physical or mental health risks. Finally, despite the beliefs about its use, both groups of students reported a dearth of formal education about MC. Some differences were found between the two groups of students. In most cases, US students reported more favorable attitudes toward MC than those from Israel. The decision to use US and Israeli students for comparison stems from both similarities as well as differences between the two cultures. For example, the State of Israel’s culture is distinctly US orientated; and, ’American’ values, practices, and culture influence many living conditions in the country including political traditions and economic policies among others.Moreover, despite cultural differences, both US and Israel share values that originated in Western society and guide social work studies and practice.

Future studies should include cultural factors such as student substance related norms to deepen the understanding of the similarities and differences found in the current study. There is an ethical dilemma that needs to be addressed with respect to student expressed use of cannabis for recreational purposes when they know it is not legal in areas where they are residing. In the United States, the National Association of Social Workers  Code of Ethics does not specifically address the issue of MC; however, the Code’s preamble highlights the dual focus social work professionals have on individual and society.For example, Baker & Randolph conducted a study to examine the ethical dilemmas that face social workers when they provide to clients who use MC.These researchers found that even though social workers must practice under the NASW Code of Ethics by promoting the self-determination of clients, the dispute over the medical cannabis laws creates controversy for the profession regarding this basic tenet. Furthermore, they point out that social workers should be aware of where and how their clients are acquiring MC. If the client is obtaining it illegally, this places the social worker in the ethical dilemma of knowing his/her client is breaking the law. Despite all of this, the NASW Code specifies the professional values of a social worker including service, social justice, the dignity and worth of all people, as well as the integrity of the profession. These values are also reflected in the Israeli social work code of ethics.Therefore, although there is a lack of uniformity of the acceptance of MC, under the codes of social work ethics inboth the US and Israel, it is clear that social workers have a role to serve people in need,advocate for both clients and society-at-large, and to practice in an honest and trustworthy manner.Education on MC should address medical, social, and ethical issues related to it. This will provide social work students with a comprehensive understanding of the substance and promote their ability to relate to dilemmas that might arise while addressing individuals in need. Notwithstanding their lack of knowledge and training, the vast majority of survey respondents reported that they would recommend MC for their clients. This may be explained by the fact that social workers do not have the legal competency to authorize such use ; therefore, potential professional and legal ramifications are not at stake. Indeed, previous studies reported those peoplelegally eligible to certify for MC use tend to hold more permissive and favorable attitudes about marijuana grow system use for medical conditions.Likewise, since only two universities were included in this study the findings may not be generalizable to other Israeli or US students due to age, cultural and religious differences. Similarly, the majority of Israeli respondents were undergradate students while all of the US students were graduate students. There may be differences in these two samples based on the differing academic levels. Additionally, the survey relies on self-reporting which can lead to biases from respondents that may not accurately represent their attitudes about MC.

Despite these limitations, this study provides information that can guide additional research to further explore attitudes about MC among professionals and potentially influence policy change. Medical cannabis  is legal in many countries, with much regulatory variability. The legality of MC has changed considerably over the past several decades, particularly with evidence of its value for chronic illnesses and related symptoms.1 For example, cannabis or cannabinoids have been proven to be useful for the treatment of chronic pain, chemotherapy-induced nausea and vomiting, and for improving multiple sclerosis spasticity.For nearly three decades, Israel has been officially using the substance to treat selected medical conditions. More recently, Thailand has become the first country in Southeast Asia to approve medical cannabis. As these countries move forward with the substance for medical purposes, key questions persist about the nature of knowledge, attitudes, and beliefs about MC among medical students who will become clinical practitioners, medical consultants, and health service decision-makers. For centuries, the chemicals in cannabis and cannabinoids have been used for medical purposes. The psychoactive compound of cannabis, THC or tetrahydrocannabinol, is linked to a sense of euphoria or a “feel good” condition, which may encompass positive effects for certain conditions, but is also associated with potential negative effects, such as psychotic symptoms or cognitive impairment.A second compound is cannabidiol or CBD, which is non-psychoactive and is considered to be associated with many therapeutic effects.MC has been found useful for chronic neuropathic pain,reducing chronic or neuropathic pain in advanced cancer patients, and as an adjunct to traditional analgesic therapy.Despite these positive results, the potential benefits of cannabis-based medicines for chronic neuropathic pain may be outweighed by their potential harm when used in combination with opioids.Indeed, increased anxiety and depression have been reported among such patients, including those who use tobacco, alcohol, cocaine, and sedatives.

Pre-legalization, Indigenous communities identified a lack of culturally-specific educational materials on the health effects of cannabis; these should be developed, and could be implemented as a harm reduction strategy . Increased treatment availability will also be important. Given the high prevalence of use among youth, this population may be at increased risk of developing cannabis use-related problems ; early-onset use, in addition to high frequency use and use of high-potency products, has been identified as a major risk factor for subsequent health harms . At present, evidence-based treatment options in Canada for cannabis use disorder are limited . Ensuring Indigenous Canadians’ access to treatment can begin with increased access and funding for culturally-specific mental health and addictions services, as a gap in these services has been identified by Indigenous communities . Our systematic review has several potential limitations. First, our review focused on the prevalence of cannabis use and its associated factors in Indigenous Canadians, but we restricted inclusion to publications that reported data on cannabis use prevalence. Therefore, our review may not represent the full scope of research on factors associated with cannabis use in this population. Second, publications focusing on groups other than on-reserve First Nations were limited in number and had small sample sizes, reducing the generalizability of our findings. Third, bias affecting external validity  was common among our included publications; all but two had at least one item at high risk of bias in this section. To increase the generalizability of our findings, we focused our summary of prevalence results on publications with the largest sample sizes and the fewest items at high risk of bias. Fourth, the interpretability of our findings on associated factors is limited given the largely cross-sectional nature of the available data, which renders the directionality of associations unclear.Because of the massive scale of the Covid-19 pandemic, Covid treatment research is subject to intense politicization, frequent media scrutiny, and continued public interest.

As thoroughly described in a recent JAMA Viewpoint Article , public scrutiny into drug development research has the potential to introduce a new set of incentives into the research process, which can, in turn, disrupt science-based regulation and the delivery of evidence-based treatments. These dangers became abundantly apparent through the US experience with hydroxychloroquine. When influencers and politicians began to endorse hydroxychloroquine as a treatment for Covid based upon early observational and preclinical studies, many in the public, including patients, physicians, and policy-makers, were quick to embrace hydroxychloroquine as an effective treatment, even though observational and preclinical studies are incapable of causally proving a drug’s safety or efficacy. This unearned enthusiasm for hydroxychloroquine led to shortages for those who required the drug for approved indications  and even cases of poisonings . Another observational study  subsequently found a positive association between hydroxychloroquine use and mortality as well as other adverse events, which may have made recruitment for hydroxychloroquine randomized controlled trials more challenging . Concerningly, the cacophony of contradictory observational and preclinical evidence presented in the media led some members of the public to adopt a dogmatic attachment to the drug’s effectiveness or ineffectiveness in line with their political identity . Since hydroxychloroquine was first suggested as a possible Covid treatment, a large-scale RCT, similar to what would be required for FDA drug approval, along with five smaller RCTs have all failed to find that hydroxychloroquine is an effective treatment for Covid. The authors of the large-scale RCT stated on June 5th, “this result should change medical practice worldwide and demonstrates the importance of large, randomised trials to inform decisions about both the efficacy and the safety of treatments” . Despite this causal evidence, many in the public still believe that hydroxychloroquine is an effective treatment , detracting from other potentially effective preventive measures and treatments and fueling conspiratorial theories about pharmaceutical interventions overall .Owing to the political and social history of cannabis grow facility, the safety and efficacy of medical cannabis and cannabis derived products is a political, as well as scientific, discourse. Many patients, physicians, and policy-makers want cannabis to be a safe and effective medication and are willing to endorse cannabis’ safety and efficacy with little supporting evidence . Media outlets frequently and widely cover the results of cannabis research, and like with hydroxychloroquine, many in the public are primed to accept favorable findings, regardless of their methodologies, as truth.

Because observational and preclinical studies generally take less time and cost less money than large-scale RCTs, interested parties, particularly “Big Marijuana” companies, are able to sponsor dozens of non-causal studies and publicize their findings, providing more ammunition to their political allies . The dissonance between positive observational trial results and federal cannabis prohibition have caused many in the public to form their own conclusions about the underlying motives for cannabis policy . Some become distrustful of the actors and systems instituting prohibition, including policy-makers, pharmaceutical regulators, and the pharmaceutical industry. Because their situations are similar, medical marijuana researchers can potentially learn some lessons from the experience of hydroxychloroquine researchers. Perhaps none is more important than the notion that researchers and regulators should only accept results from large-scale RCTs as evidence of a drug’s safety and efficacy regardless of political pressure or competing findings from other forms of research. Much of the harms related to hydroxychloroquine could have been averted if physicians and researchers insisted on proof of safety and efficacy from large-scale RCTs and if the FDA had imposed greater restrictions on use related to non-approved indications. Similarly, an insistence on large-scale RCTs to confirm the safety and efficacy of cannabis and cannabis-derived products, as well as stricter regulatory controls on unsubstantiated health claims made by marijuana marketers, could avert potential public health harms related to inappropriate medical cannabis use. Further, to the extent that cannabis and cannabis-derived products are truly safe and effective for certain conditions, large-scale RCTs can confirm these benefits and give policymakers, physicians, and patients the confidence to allocate appropriate treatment.To the layperson, other forms of research can appear to have equivalent or even greater value compared to large-scale RCTs . This is particularly true for observational studies. Observational studies can have thousands more participants than even large RCTs. They often use complex-sounding statistical techniques, like propensity score matching or growth models, while RCTs are statistically straightforward. Observational studies involve “real users” as opposed to clinical study test subjects. While some are aware of the concept of confounding, many can be appeased by adjustment for confounders in the analytical rather than design phase of the study. Despite their veneer of credibility, observational studies have no causal interpretations and, instead, can easily provide biased effect estimates. Large-scale RCTs are the only method that can reliably provide causal estimates of an effect . Consider, for example, a treatment that has no effect. The treatment is tested in 100 different trials, each with 1000 participants. The relationship between the treatment and the outcome of interest is confounded by 20 variables , which could be, for example, gender, race, age, height, weight, and blood pressure.

For simplicity, assume that each confounder is randomly distributed around 0.4  for those not receiving the treatment and 0.6  for those receiving the treatment. The effect size of each confounder on the outcome ranges between 0.5 and 5 , with an equal probability of either increasing or decreasing the outcome. To avoid overfitting, I include a random error centered at 0 with a standard deviation of 10. Observational researchers rarely know all potential confounders or even have access to data on all known confounders. Assume, then, that the researcher knows and collects data on, on average, 30%  of the confounders, and adjusts for all of them. Many researchers would consider an observational study with six confounders “well-controlled”, and yet it is reasonable that 10 continuous and 10 dichotomous variables confound a given relationship. However, if we simulate this circumstance, approximately 85 of the 100 trials would produce an estimate significantly different from 0, even though the treatment truly has no effect . Each of these 85 trials may be publishable in separate peer-reviewed journal publications, but none of them would be accurate. Indeed, if the research or publication process is biased in one direction, cannabis grow system it may appear that the literature consistently shows a relationship in that direction. Large-scale RCTs eliminate the dangers emerging from unknown confounders. Because participants are randomized to receive either the treatment or a control and because the sample size of both groups are large, all third variables, including known and unknown confounders, balance between groups.1 In other terms, it is not possible for potential outcomes to correlate with the treatment when the treatment is randomly assigned. In the above example, this is analogous to adjusting for all 20 known and unknown confounders. If we simulate that case, approximately 95 of the 100 trials produce results consistent with the treatment’s true effect size. Other study designs have related problems. Small-scale RCTs, for example, do not necessarily balance confounders or potential outcomes; without help from the law of large numbers, the different treatment arms can, by chance, be correlated with known and unknown confounders and potential outcomes . Many initial safety trials do not have a comparison group altogether, and so the effect can be confounded by time or disease progression. Animal models and preclinical studies frequently fail to produce comparable results in humans due to the immeasurable number of confounding biological systems . For these reasons, large-scale RCTs are almost always required for drug approval by regulatory bodies in developed countries around the world. It should be noted that, in the United States, the 21st Century Cures Act has allowed for some flexibility in the study design and statistical analyses of trials used to test new medical devices and drugs’ safety and efficacy. Even in these cases, however, FDA guidance on Bayesian analysis affirms the importance and necessity of random assignment to treatment and a sufficient sample in late-stage investigational new drug trials . It is true that, strictly speaking, large-scale RCTs are not the only way to establish causal evidence . For example, natural experiments, which exploit random or quasirandom assignment occurring in the real world, can have many of the same benefits as RCTs  and potentially better generalizability.

However, true natural experiments, particularly for the use of pharmaceutical products, are rare. Further, when a natural experiment is found, one needs to be convinced that assignment to the treatment is truly random, or at least orthogonal to potential outcomes conditional on adjusting for observed confounders, before accepting the results as causal. In virtually all cases, that argument requires at least a small leap of faith . Consequently, large-scale RCTs are the only study design that can reliably produce causal evidence. Large-scale RCTs have another key benefit over observational, early clinical, or natural experiment designs: it is challenging for researchers to intentionally bias their studies to find favorable results. For both pharmaceutical and marijuana research, researchers often have a considerable interest – financial, ideological, or otherwise – in producing findings that suggest the drugs they test are safe and effective. Dishonest researchers may, for example, selectively choose which confounders to include in their models in order to find a spurious but statistically significant result . Large-scale RCTs essentially remove the option for researchers to act in this way. Potential outcomes are balanced through the randomization procedure, and so the researcher merely has to perform some simple and straightforward analytics in order to assess whether the drug had an effect or not. She cannot purposely introduce bias into her model by omitting a confounder. Simply put, with large-scale RCTs, there is little room for dishonest researchers to play statistical games with their data. It should be noted that not all large-scale RCTs are properly formulated or conducted to produce clinically meaningful results, and the mere presence of a study that brands itself as a large-scale RCT is insufficient to determine whether a drug is safe and effective or not . For example, in trials that are inappropriately conducted, randomized groups may differ in post-randomization experiences or randomization may not be properly generated at all.

Importantly, the full-spectrum cannabis extract totally relieved thermal hyperalgesia, mechanical allodynia and withdrawal latency in CCI rats. In contrast, treatment with purified CBD or purified THC, given at the same dose existing in the extract, showed only a partial anti-nociceptive effect. Thus, this study suggests that full-spectrum cannabis extract has a better analgesic effectiveness than CBD or THC alone in rats with neuropathic pain. Intriguingly, the authors also found that the anti-nociceptive effect of the full-spectrum cannabis extract was independent of CB1 and CB2 receptors. Indeed, the anti-nociceptive effect of the full-spectrum cannabis extract was mainly due to the activation of the vanilloid receptor, TRPV1. This conclusion was supported by the finding that treatment of animals withCB1 and CB2 receptor blockers could not abolish the protective effect of the full-spectrum cannabis extract. Conversely, TRPV1 receptor antagonist, capsazepine, completely blocked the effect of full-spectrum cannabis extract suggesting a TRPV1-dependent mechanism . Overall, this study clearly demonstrated that the beneficial effects of the full-spectrum cannabis extract was superior to purified THC or CBD in the treatment of neuropathic pain and that this effect was not mediated via the classical CB receptor-mediated signaling. The anti-nociceptive effect of full-spectrum cannabis extract has been confirmed in streptozotocin-induced diabetic neuropathy in rats. Treatment of these animals with full-spectrum cannabis extract significantly ameliorated mechanical allodynia and the physiological thermal pain perception. Of importance, the observed effect was independent of hyperglycemia, suggesting a direct neuronal effect. Indeed, evidence suggests that the anti-nociceptive effect may be due to the activation of the neurotrophic factor, nerve growth factor , by one or more components within the cannabis extract. In addition to the anti-nociceptive effect, full-spectrum cannabis extract protected against oxidative stress-induced neuronal damage in these diabetic rats.

Collectively, this study supports the concept that the combination of cannabinoid and non-cannabinoid compounds, vertical grow rack as present in the aforementioned extract, produces a profound benefit in the treatment of neuropathic pain . In addition to the pre-clinical studies, full spectrum cannabis extract such as Sativex has been investigated in numerous clinical trial on patients with MS-related symptoms . These trials are either double-blind randomized placebo-controlled parallel-group trials, an uncontrolled open-label or non-interventional trials that have studied the effect Sativex as a monotherapy or as an add-on therapy on patient with MS-related symptoms. Notably, Sativex reduces neuropathic pain, muscle stiffffness and spasticity, bladder dysfunction, and improves sleep quality in MS patients. Importantly, the effect of Sativex on MS-related neuropathic pain was more pronounced when administered as an adjuvant therapy. Overall, these trials confirm the notion that full spectrum cannabis extract such as Sativex is effective for the treatment of MS-related neuropathic pain. While small scale clinical studies suggest that full-spectrum cannabis extract like Sativex is safe and effective in the treatment of MSassociated symptoms such as neuropathic pain, this might not necessarily hold true for all other cannabis products. Indeed, purified oral THC lacks beneficial effects for the treatment of neuropathic pain associated with MS . In addition, oral products with purified or high THC content produces cognitive dysfunction, undesirable psychological effects and tachycardia. Thus, care should be taken in the interpretation of the effectiveness and safety of the types of cannabis products used in treating neuropathic pain.While the major undesirable effects of THC containing products are cognitive dysfunction, particularly the loss of short-term memory consolidation, anxiety, tachycardia and hunger, these are obviously not common adverse effects of full spectrum cannabis extract like Sativex. In fact, given that full spectrum cannabis extract consists of a variety of cannabinoids and terpenes, we postulate that these cannabinoids and terpenes can help minimize the undesirable effects of THC. In support of this notion, CBD was shown to reduce unpleasant THC-induced effects such as psychological reactions, anxiety, tachycardia and hunger  through the more traditional CB receptor-mediated pathway. Indeed, the reduction of the unpleasant THC effects are mediated by the following mechanisms:  CBD appears to compete with THC for CB1 receptor binding site and acts as a CB1 receptor antagonist or reverse agonist and  CBD suppresses the activity of CYP2C and CYP3A enzymes involved in the metabolism of THC in the liver, which subsequently inhibits the hydroxylation of THC to its 11-hydroxy metabolite.

Of note, 11- OH-THC is 4 times more psychoactive compared to THC , and thus reducing the formation of 11-hydroxy metabolite by CBD should minimize the unpleasant psychological reactions of THC. In addition to CBD, α-pinene, a bicyclic monoterpene, was shown to aid the memory and minimize cognitive dysfunction via blunting the activity of acetylcholinesterase in the brain. Together, the absence of the major undesirable effects of THC is an important advantage of full spectrum cannabis extract like Sativex. Nevertheless, side effects such as somnolence, dizziness, confusion, fatigue, dry mouth, white and red buccal mucosal patches and nausea have been reported in patients on Sativex. In contrast to Sativex, the presence of CBD in some cannabis grow racks extracts, particularly the oral extracts, can sometimes exacerbate some of the psychological effects of THC  which might be due to the profound effect of CBD on the hepatic first pass metabolism of THC whereby CBD elevates the blood level of THC . Thus, oral broad spectrum CBD extract  might be safer than oral THC or THC/CBD cannabis extract products. Nevertheless, while highly purified CBD extract lack any psychoactive adverse effects, a risk of hepatotoxicity, in addition to suicidal ideation have been reported with a chronic high dose of extracted CBD. Other adverse effects such as fatigue, somnolence and gastrointestinal disturbances have been also reported.Cannabis sativa L.  is one of the oldest cultivated plants in history with multifarious applications, ranging from the textile, construction and paper industries to the nutritional, pharmaceutical and cosmetic sectors. While the stems provide cellulosic and woody fibres of very high quality, and the seeds are a rich source of fatty acids and proteins for the feed and food industries, the leaves and inflorescences are a gold-mine for phytochemicals. The rich spectrum of bioactive compounds can be exploited for several pharmaceutical applications . The plant is known for its therapeutic usage as antiemetic, analgesic, and appetite stimulant or to treat epilepsy, glaucoma, and Tourette’s syndrome . In total, a broad spectrum of more than 500 phytochemicals has been identified from the leaves, flowers, bark, seeds, and roots. This includes numerous cannabinoids, flavonoids, and terpenoids, as well as sterols , which are of industrial interest. The phytochemical spectrum, however, varies significantly with chemovar and plant part , and also with agronomic and environmental factors . Traditionally, stems, inflorescence and seeds were the most used plant parts. In medicine, the major focus has always been on cannabidiol  and Δ9 -tetrahdydrocannabinol  as bioactive compounds, which are mainly present in the flowers, as well as the leaves. Thus, the roots have been investigated less with respect to the reported pharmaceutical potential. Nonetheless, the roots have historically been used for the treatment of fever, inflammation, infections, as well as arthritis . Recently, the presence of phytocannabinoids has been reported in hairy roots for the first time, although in almost negligible amounts compared with the rest of the plant .

Naturally occurring triterpenoids are described as being of therapeutic value because of their anti-cancer, anti-inflammatory, antiulcerogenic or antiviral activities . The first characterized triterpenoids from ethanolic root extracts were friedelin and epifriedelinol, reported in 1971 . Recently β-amyrin was discovered to be accumulated in hemp roots as well . Of the identifiedtriterpenoids, friedelin seems to be the most abundant , which was reported to exhibit anti-inflammatory, antipyretic and analgesic effects in mice and rats . Triterpenoids have been extracted from cannabis roots by conventional extraction with ethanol , ethyl acetate , n-hexane, and petroleum ether . Supercritical fluid extraction  has not yet been described for triterpenoids from cannabis roots. However, the extraction with supercritical carbon dioxide in combination with EtOH has been reported for triterpenes from other plants . Furthermore, SFE can be considered an environmentally friendly and highly efficient alternative, compared with volatile solvent extraction . Antioxidant activity of naturally occurring triterpenoids has been determined in several studies. Cai et al.  observed DPPH , ABTS, and superoxide anion free radical scavenging activity in extracts from medicinal fungus S. sanghuang. In particular, friedelin, isolated from Azima tetracantha Lam. leaves showed very promising scavenging effects on DPPH, hydroxyl, superoxide, nitric oxide, and suppressive effects on lipid peroxidation . Additionally, phytosterols are known to be antioxidants and β-sitosterol, campesterol, as well as stigmasterol, have been reported to act as modest radical scavengers in solution . Currently there are no studies available on the antioxidative capacity of hemp root extracts, where triterpenoids and phytosterols have been identified. This study presents the extraction of phytochemicals from hemp roots and the identification of heretofore undescribed secondary metabolites to ascertain the exploitation potential of this plant part, which is usually treated as waste. The predominant triterpenoids friedelin and epifriedelinol were directly quantified from the root extracts of three different hemp chemovars by GC–MS/FID analysis. Moreover, the extraction efficiency of the target triterpenoids by conventional extractions with EtOH and n-hexane as well as a supercritical CO2 extraction is discussed herein for the first time. Furthermore, the influence of different harvest times and drying conditions on the triterpenoid concentration for one chemovar was monitored. In addition, in vitro  and cellular antioxidant activity assays of the ethanolic cannabis root extracts were measured for the first time, due to the reported antioxidant activities of the accumulated secondary metabolites in hemp roots. The roots of three type III Cannabis sativa L. chemovars , Futura 75 , Felina 32 , and Uso 31 , were cultivated in the fields  of BioBloom  in 2019.

The crop was planted in rows with an average plant density of 35 plants per m2 . All three chemovars were grown organically in close proximity on a 60 ha plot. For Futura 75, three individual samples, which varied in harvest times and drying conditions were analysed. The hemp roots of Futura 75 , were collected in July 2019, air dried and stored at room temperature. For comparison of chemovars, Futura 75 , Felina 32 , and Uso 31 , were harvested in August 2019 and received the same postharvest treatment as sample A. The third sample of Futura 75  was harvested on an agricultural scale in October 2019 after the vegetative period and after the harvest of the aerial parts. Sample C was heavily washed with the help of a steam cleaner and dried for 30 h at 45◦C in an agricultural drying facility and stored at room temperature until analysis. For analysis, the complete hemp roots were washed with water and chopped to smaller sized parts. The pieces were shock frozen with liquid N2 and milled by a Retsch ZM 100 with sieve  at 14,000 rpm . The pulverized material was lyophilised until constant weight and stored in a dark place for further experiments. Qualitative and quantitative analysis of the chemical constituents was carried out with an Agilent 7890A GC-System coupled to a mass detector and a flame ionization detector . An Agilent HP-5MS GCcolumn  was used for the separation. The initial flow was set to 1.3 mL/min and helium was used as a carrier gas. The samples were injected without split. The temperature program for the analysis was as follows: 1 min at 100◦C as initial conditions, 10◦C/min ramp up to 325◦C, and 15 min hold at 325◦C. The FID was operated at 350◦C. Electronic ionization  was used for the detection mass spectrometry. Source and single quad temperature were 230◦C and 150◦C. The total ion current  was measured between 35 to 750 m/z after a solvent delay of 6.5 min. The method was developed and modified according to recent literature for the separation of triterpenoids . For the quantification with GC-FID, an analytical grade standard of friedelin was purchased from Sigma-Aldrich . A stock solution  in chloroform was prepared and diluted for calibration. The triterpene epifriedelinol was expressed as mg friedelin equivalent per g dried hemp root. The identification of the compounds was performed by comparing fragmentation patterns with an intern mass spectrometric library, National Institute of Standards and Technology  database , and corresponding literature data or the purchased pure standard substance.

This approach can help to overcome the main sources of bias from classical observational approaches, by providing a more reliable estimate of the likely underlying causal relationship. There are limitations to this study that should be considered. First, the ALSPAC cohort suffers from attrition, which is higher among the socially disadvantaged . Furthermore, polygenic scores for tobacco smoking initiation were associated with drop out in the ALSPAC . We attempted to minimize the effect of drop-out by using multiple imputation, FIML, and inverse probability weighting which assume MAR missing patterns. Although it is not possible to test the MAR assumption, it was made more plausible as a number of SES variables were found to predict whether participants attended the clinic or not . Second, tobacco and cannabis use were self-reported. However, there is evidence to suggest that self-reported assessments are reliable and valid methods , and the assessment of tobacco and cannabis use yearly over 6 years in a latent variable framework helps to account for measurement error . Third, while the longitudinal approach for each substance used in this study has a number of advantages over using measures at a single timepoint, it was not possible to examine cannabis use without tobacco use as most cannabis users use cannabis in combination with tobacco . We therefore cannot rule out the possibility that observed associations between cannabis use and cognitive functioning are exacerbated by the combined use of cannabis and tobacco. Fourth, different measures of tobacco and cannabis use for the observational and MR analyses were used. Along with deriving latent classes of tobacco and cannabis use, we used the largest GWAS consortia  which has identified 341 genetic instruments for ‘smoking initiation’, and the GWAS conducted by Pasman and colleagues which identified 8 genetic instruments for lifetime cannabis use which are continuous measures. To our knowledge it is not currently possible to use a nominal exposure  and consequently the effect sizes are not directly comparable. Fifth, it is likely that both the one- and two-sample MR analyses areunderpowered. However, findings using weak instruments tend to bias findings towards the null in the two-sample setting and toward the outcome-risk association in the one-sample setting . Sixth, the main limitation of one- and two-sample MR is that the quality of the pooled results in the GWAS consortia is dependent on the individual studies.

Another limitation is that the same sample may contribute to both GWAS  which was the case in the current study as ALSPAC was in both the exposure and outcome. This will bias the MR estimate towards the observed estimate. However, as the MR found no clear evidence for an effect, this suggests it was not biased by overlapping samples. See Lawlor and colleagues  for a more comprehensive description of limitations associated with MR studies. Finally, it is possible that the direction of the association could work in both ways, that is, impairments in cognitive functioning may precede  tobacco and cannabis square pot use.We were able to include a number of measures to maximize the robustness of our findings:  ascertaining the temporal order of exposures and outcomes;  controlling for premorbid working memory and brain insults prior to measures of tobacco/cannabis use helped to reduce the possibility of cognitive impairments, or lower cognitive abilities in childhood, influencing tobacco/cannabis use; and  it is possible that a common risk factor is influencing both tobacco/cannabis use and lower cognitive function, however MR methods helps to protect against this possibility by minimizing bias from reverse causation and residual confounding.Overall, there was observational evidence that adolescent tobacco and cannabis use were associated with subsequent cognitive functioning, highlighting impairments in a range of cognitive domains, including working memory, response inhibition and emotion recognition. Our findings lend support to the developmental vulnerability hypothesis, in that, tobacco and cannabis use in adolescence, when the brain is undergoing critical development, may have neurotoxic effects. Better powered genetically informed studies are required to determine whether these associations are causal. In order to rule out the possibility of deficient cognitive functioning preceding substance in adolescence, future research should use an equally robust approach to examine the alternate hypothesis. This study lends support to public health strategies and interventions aimed at reducing tobacco and cannabis exposure in young people.In the last two decades and owing to serious adverse effects associated with the use of opiate medications and nonsteroidal anti-inflammatory drugs , the two major pharmacological groups used in pain management, more attention has been paid to cannabis-based extracts and cannabinoid-based products to fill the gap left by analgesics currently available in the clinic .

Increasing evidence from human clinical trials has demonstrated that cannabis-based therapeutics can minimize neuropathic pain intensity and provide effective remedies for chronic pain management . However, the clinical use of herbal cannabis is opposed by several limitations including the psychoactive adverse effects  and associated harm to individuals and the public health, the complex and variable chemical content with the associated lack of consistency and standardization, possible microbial and pesticidal contamination, as well as the lack of solid evidence of effectiveness. Therefore, there is a critical need for robust research on herbal cannabis and its ingredients to evaluate the medical potential of the active ingredients alone and in complex mixtures . Potentially bioactive cannabis-derived compounds not only include cannabinoids but also terpenes, which comprise more than 150compounds out of the 500 plus constituents of Cannabis Sativa, the most commonly used cannabis species . Based on the fact that different cannabis varieties are able to induce various physiological effects, as has been observed among cannabis users, the socalled “entourage effect” has been proposed to refer to the additive or synergistic contribution of terpenes to the pharmacological effects shown by cannabinoids . In a recent study that investigated the ability of terpenes found in C. Sativa to activate TRPV1 in HEK cells, a mixture of terpenes was found to remarkably promote intracellular calcium influxes. In addition, betamyrcene  and, to a lesser extent, nerolidol  were identified as the major contributors to the calcium influx activity. MC activity was completely dependent upon the presence of TRPV1 protein and thus the TRPV1 antagonist capsazeine could effectively bloke MC-induced calcium influx. Furthermore, based on molecular docking data, MC binds to TRPV1 to via a hydrophobic, non-covalent interaction . MC , a monoterpene and the most abundant terpene in cannabis, and NL , a sesquiterpene, have both demonstrated anti-nociceptive and anti-inflammatory effects . In addition to these two terpenes, betacaryophyllene  , a bicyclic sesquiterpene found in cannabis, has been reported to act as a specific agonist against cannabinoid receptor 2 , which presents in peripheral organs, outside the CNS . This interesting activity, beside other mechanisms of action, make CPh a potential therapeutic candidate in the management of neuropathic pain . However, the volatile and hydrophobic nature of these terpenes result in poor solubility and low bioavailability, limiting their in vivo pharmacological efficacy. To address these limitations, we have recently developed polymeric nanoparticles  that successfully encapsulated these three terpenes . The new nanosystems were fabricated using poly-poly , a block co-polymer of a hydrophilic chain of PEG linked to PLGA a biocompatible, biodegradable, Food and Drug Administration -approved co-polymer based .

It is anticipated that the encapsulation of the cannabis-derived terpenes in PLGA NPs will equip them with a wide range of qualities such as enhanced solubility and stability, promoted absorption by biological membranes, sustained release, and ultimately improved therapeutic efficacy . In this work we sought to study the impact of the of MC, CPh, and NL encapsulation on their potential effectiveness in pain management. To this end, we tested the terpene-loaded PEG-PLGA NPs in HEK293 cells  that express the nociceptive transient receptor potential vanilloid- 1 ion channel , a non-selective ligand-gated cation channel that is involved in the sensation of scalding heat and pain . This ion channel is a member of the TRPV subfamily of the transient receptor potential  channels, a family of membrane calcium channels that are activated by a variety of exogenous and endogenous physical and chemical stimuli . TRPV1 is identified by its responsiveness to capsaicin and its analogues , but TRPV1 also responds to noxious temperatures , low pH , and to some endogenous compounds; in particular, the endocannabinoids. TRPV1 antagonists include capsazepine and ruthenium red . TRPV1 is expressed in both peripheral and central nervous systems, predominantly in primary sensory neurons involved in pain perception, in addition to several nonneuronal cells such as immune cells and smooth muscle cells . Both antagonism and agonism of TRPV1, and other TRP channels, can induce analgesia, via inactivation and chronic desensitization of this nociceptive ion channel making it a target for pain treatment . The activation of TRPV1 leads to an influx of Ca2+ via the plasma membrane, thus generating changes in intracellular Ca2+ concentration. It was also found that TRP channels are present in intracellular organelles and control the release of intracellular Ca2+ . Influxes of Ca2+ were monitored by the fluorescent indicator Fluo-4 acetoxymethyl. We used similar experimental conditions to acquire fluorescence images of cells treated with the terpenes-loaded NPs. Additionally, the cytotoxicity of the free and encapsulated terpenes was assessed. The terpene-loaded PEG-PLGA NPs were synthesized and tested in HEK cells that express TRPV1. The calcium signaling assay utilized in this work enables the measurement of calcium influx, as a result of TRPV1 activation. Fluorescence intensity changes were monitored using Fluo-4, which was used to measure intra-cellular free Ca2+ concentrations . Our work was based on the findings of Jansen et al. who demonstrated that cannabis-derived terpenes, predominantly MC, activate TRPV1 channels inducing calcium fluxes . We obtained the HEK TRPV1 cells from the same research group. However, we had to introduce some modifications to the calcium signaling assay developed by Jansen et al. in which a more sophisticated and sensitive instrument  was employed. Thus, a higher count of cells  and higher concentrations of terpenes  were involved. Similar high concentrations of terpenes have previously been reported in the literature. For example, linalool has been found to activate human TRPA1 at an EC50 of 117 μM . In addition, the experiment duration was set to 1 h to provide enough time for drug release from NPs and trim tray for weed interaction with the receptors. Our results confirm the findings of Jansen et al. regarding free MC, and the relatively small effect of free NL on TRPV1. Moreover, this work demonstrates that the PLGA-based nano-formulations significantly enhance the calcium influx induced by the three terpenes.

In general, this improved effect may be explained by the solubilization of the lipophilic terpenes in the core of the nanocapsules, thus improving their ability to interact with the TRPV1 channels. Furthermore, the likely slow drug release, as generally observed for lipophilic substances encapsulated in PEG-PLGA NPs , may explain the time-dependent enhancement of fluorescence intensity shown by the terpene-loaded NPs. Interestingly, NL-loaded NPs demonstrated a two-phase response characterized by a small peak followed by a drastic logistic phase pattern  reaching a calcium signal similar to that exhibited by ionomycin. In fact, the two-phase response suggests that the generation of calcium signal by the encapsulated NL may be provided by a more complex mechanism. The first small peak may result from the terpene that is released immediately by the nanoparticle formulation followed by a slower but extended release of the terpene. However, as this pattern was not observed by the other two terpenes, it is also possible that the high intercellular concentration of NL achieved by the nano-formulation induces other mechanisms for increasing calcium concentration in the cytosol. One possible mechanism is the mobilization of calcium from endoplasmic reticulum in which functional TRPV1 channels are located and serve as intracellular Ca2+ release channels . A more in-depth investigation is needed to clarify the mechanism underlying effect induced by NL-loaded NPs, which is not within thescope of the current work. Moreover, the high-level responses seen by the combinations of the three terpenes may provide an evidence of a synergistic effect. It is noteworthy that shifts in intracellular Ca2+ have been found to promote cell death, through apoptotic or necrotic pathways .