Compared to the national data, the WSU sample pre-RML appears to be more white, more likely to be in a fraternity or sorority, more likely to live off campus or in a fraternity/sorority house, and less likely to live with parents. We will see based on the regressions that although these variables are associated with higher likelihood of marijuana use, they are also associated with a lower likelihood of increasing use after RML. To the extent that differences in composition between the WSU and national samples affect differences in the trend of marijuana use, we expect that such differences are likely to bias against an observed relative increase in use at WSU. We also compare pre-RML marijuana use between the WSU sample and the two national samples. Fig. 2 shows the percentage of respondents each year who have used marijuana in the past 30 days for all three samples. The NCHA national data is only through 2011.For the national NCHA data after 2011 and for the WSU data after 2012, we forecast each series based on the data through 2012. Forecasts are generated using best-fit double exponential smoothing to account both for levels and for changing trends.Both the national NCHA and NSDUH data show an increase over the period before 2012 and are consistently within 1 and 4 percentage points of each other. The WSU series starts out slightly lower than both national series but with a nearly parallel trend and remains in the range of both national series through 2012. Readers will note the relatively large increase in the WSU series between 2008 and 2010, which corresponds to changes in Washington’s MML laws. Though the magnitude is smaller, we observe an increase at this same time in both the national samples. It may be the case that national changes affected students both in and out of Washington. Any long-term effects of such national changes are reflected in the NSDUH data. The forecasts for both the WSU and the national NCHA samples are almost parallel to the actual trend in the NSDUH and the 95-percent confidence interval for each forecast contains the other forecast as well as the NSDUH actual values. It appears that the increase in marijuana use at WSU after 2008 may have been a one-time jump,grow tent indoor a proposition more fully examined in the conclusion of the paper.

It is also relevant to note that both national samples are “contaminated” with observations from WSU and from others in Washington and Colorado.9 If RML increases marijuana use for college students, as we expect, then including Washington and Colorado students in the national samples biases against finding an effect in the difference-in differences analysis.Estimates for the logit regressions on the probability of having used marijuana in the past 30 days are reported in Table 3. The far-left column shows the basic regression, controlling only for a linear trend. Column 2 shows the results of the regression with demographic controls added. Columns 3 and 4 show the results with more co-variates added, some potentially endogenous. Controlling for a predicted increase of about 1.2 percentage points each year, we find that marijuana use among WSU students increased between 2.0 and 3.5 percentage points after RML and remained higher through 2015. Each estimate across specifications is statistically different from zero with at least 95-percent confidence. We find no evidence that legal sales had an additional impact on the proportion of marijuana users. The additional change after legal sales is consistently positive but not statistically different from zero at conventional levels; t-scores for these differences range from 0.43 to 0.88 . This regression model also provides estimates of relative marijuana use among WSU students. Male students are between 2 and 7 percentage points more likely to have used marijuana than females. Black and white students are the most likely to use marijuana compared to other races with Asian students being the least likely. In results not shown , we also see a decreasing likelihood of marijuana use with age of about 3 percentage points per year after age 20. After controlling for GPA, Greek membership, residence, and international status, 1st-year undergraduates are the most likely to use marijuana by between 3 and 5 percentage points over students of other years. International students are between 4 and 7 percentage points less likely to use marijuana than domestic students. Students with a 4.0 GPA are between 3 and 10 percentage points less likely to use than other students. Students in fraternities or sororities are between 4 and 12 percentage points more likely than other students.

Finally, the likelihood of marijuana use is positively correlated with the use of tobacco, alcohol, and illegal drugs.different subgroups and present the results in To better understand the impact of RML, we repeat the analysis for Table 4. Results of these regressions are generally consistent across all four specifications for each group. For brevity, we report only the results that include controls for age, sex, race, and year in school . The proportion of each group that reported having used marijuana before 2014 is included at the bottom of each column. Though the estimates differ greatly in magnitude, and only a few of the estimates are statistically significant at conventional levels, all groups are associated with a positive increase above the trend in marijuana use after RML. The results suggest marijuana use by underage students increased at least as much as that by legal-age students after RML. The estimates for the increase in underage students’ likelihood of using marijuana are large and statistically significant with a p-value < .01, while the estimates for legal-age students are smaller and not statistically different from zero. Using a chi-squared test after estimation, the differences between the two groups’ estimates for 2014 and 2015 have p-values of 0.206 and 0.955, respectively. We also note that the difference between the estimates for 2015 and 2014 for legal-age students is marginally statistically significant with a p-value=0.081, indicating that legal-age students waited to use marijuana until after they could obtain it from authorized distributors. The subgroup analysis provides insight into which groups are driving the changes overall. There is a relatively large increase in likelihood of marijuana use for Black and Hispanic Students, although only Hispanic students showed changes that are statistically significant with a p-value < 0.05. The likelihood of marijuana use among Black and Hispanic students increased in 2014 by 15.8 and 14 percentage points, respectively. This change represents an 88-percent increase in recent users for Black students and a 93-percent increase for Hispanic students. This is 8–9 times the estimated effect for Asian and white students. This relatively large increase is made more significant by the fact that it occurs over a previously non-increasing trend for both groups. In fact, though not statistically different from zero, Black and Hispanic students are the only groups with estimated negative trends over this time.

In other words, both groups started out with a proportion of marijuana users that remained essentially constant since 2005 until RML, after which Black and Hispanic students were among the most likely students to have used marijuana. Females are the group with the next highest increase after RML that is statistically significant with a p-value < 0.05.Results from the logit regressions on the likelihood of using tobacco, alcohol, or illegal drugs are reported in Table 5. Again for brevity, we report only the results for the regressions that include controls only for age, sex, race, and year in school. For convenience, we report again the estimates for marijuana use from column 2 of Table 3. On average, the yearly trends in the likelihood of use for tobacco, alcohol, and illegal drugs are in the opposite direction and significantly smaller in magnitude than the yearly increase of 1.2 percentage points in marijuana use. No significant changes occur in 2014. In 2015, the only significant changes include a 2.4-percentage-point decrease in the likelihood of using tobacco and a 2.2-percentage-point increase in the likelihood of using other illegal drugs. These results imply a possible substitute/complement effect or a spillover effect on norms against other illegal drugs, though the changes did not occur until a full year after the major changes in marijuana use. Additionally, relative to the changes for marijuana, the changes for tobacco and illegal drugs are not as robust to alternative specifications and estimation methods . We see no evidence that RML or legal sales affected the use of alcohol. Overall, grow tent hydroponic our results do not support any systematic changes in other substances that occur parallel with changes in marijuana use. This supports a conjecture that RML was the cause of the changes we find for marijuana.Results of the OLS regressions with respect to regularity of marijuana use are presented in Table 6. In 2014, we find an increase of about 0.5 days in the past 30 days above a linear trend of between 0.13 and 0.16 days per year.This increase is statistically significant across specifications with at least 95-percent confidence. The estimates for after legal sales are smaller than for after RML and are not statistically significant at conventional levels. Though the magnitude of the estimates in 2015 are not significantly lower than in 2014, the lack of a significant increase in 2015 could indicate that the effect of RML on frequency is short-lived and the equilibrium trends in frequency are unaffected by legalization. Alternatively, this may indicate that a proportion of students who began using before legal sales of marijuana are more likely to use it more frequently than those who waited.

The calculation of the difference-in-differences estimations are reported in Table 7. Using the national NCHA forecast as a counterfactual, the estimated effect of RML is an increase of 8.6 percentage points. Using the NSDUH, the estimated effect is 9.6 percentage points. These estimates are both statistically significant with over 99-percent confidence and are 3–5 times larger than the estimated increase over a linear trend in the regressions. Although limited by not accounting for covariate changes over time, the difference-in-differences estimations suggest that the increase over a linear trend in the regressions may be a conservative estimate of the effect of RML on the likelihood of using marijuana.Substance use among young adults is a major public health concern and is associated with academic problems. The bulk of research in this area has focused on undergraduate students, as alcohol and marijuana use among this population are fairly common . In addition to academic difficulties, alcohol and marijuana use are associated with other negative consequences during the college years, including risky sexual behaviors, social and interpersonal problems, injury, and impaired driving . Longitudinal research has shown that alcohol and marijuana use during college might have long-term consequences after college graduation. Heavy drinking and marijuana use during college are associated with post-college substance abuse and dependence, unemployment, less prestigious employment, and lower income . Marijuana use during college and the immediate post-college years, particularly heavy use, is associated with several negative health outcomes at ages 24 and 27, including emotional problems, injury, illness, decreased quality of life, and less service utilization for physical and mental health problems . Degree non-completion as a consequence of substance use has been found in longitudinal studies of high school and college students. Adolescents who use alcohol, tobacco, and marijuana during ninth grade are less likely to complete high school than non-drug users . One study integrated data from three longitudinal studies and found that daily marijuana use during adolescence was significantly associated with decreased odds of both high school and college completion . In a study of college students, frequent marijuana use during the course of college was associated with increased likelihood of dropping out . Despite evidence of associations between alcohol and marijuana use and high school and undergraduate degree non-completion, the possible impact on graduate degree completion has not been explored. An increasing number of college graduates are enrolling in graduate school, with almost 40% of college graduates pursing a graduate degree within four years of graduation . However, only 50% to about 75% of those who enter graduate school ultimately complete their degree, with differences by degree type and academic discipline .

Gilman et al. used a similar multi-modal approach and found that gray matter density , shape , and volume of the left nucleus accumbens was significantly different for recreational users and controls. More specifically, in users, the left and right accumbens showed a negative relationship between shape and marijuana use frequency, such that the accumbens showed more inward deflections with more frequent recent use, as well as greater volume. However, in an attempt to replicate these findings, Weiland et al. found that the results of Gilman et al. held only when participants were not matched in terms of alcohol use. When matched for alcohol use, marijuana users and controls showed no significant effects in terms of cortical or sub-cortical morphometry. Moreover, when Weiland et al. examined the effect sizes observed in 11 prior studies, they found a net zero effect for the effects of marijuana on brain morphometry . Notably the results of the current study take into consideration the potentially confounding factors of alcohol and tobacco use as well as gender, age, and years of education. A recent paper using some of the same sample from the HCP examined how genetic vs. environmental factors might contribute to brain volume as a function of marijuana use. They found that marijuana use was associated with smaller volume of the left amygdala and right ventral striatum. However, their analyses suggested that the results for the amygdala are likely driven by shared genetic factors as compared to environmental factors as both marijuana user twins and their non-user twin showed reduced volume compared to concordant non-user twins. While the current study did not directly examine the role of genetics and shared environment in mediating the effects of marijuana on the brain, our analyses accounted for family structure. When accounting for family structure, we found no effects of marijuana on the amygdala, and a trend for a more inward deflection of the right accumbens, but no accompanying difference in volume. However, the analysis of Pagliaccio et al. trim bin tray was limited in sample size for certain sibships, in particular, monozygotic twins discordant for marijuana use.

With the upcoming complete HCP dataset consisting of 1200 participants, it will be important to update the analyses of Pagliaccio and colleagues, as well as adding sub-cortical shape as a measure, to see if a causal relationship arises with a larger sample .As the current study is not longitudinal but rather cross-sectional, it cannot speak to whether the use of marijuana causes changes in neural structures. Such an analysis will require longitudinal data as is to-be collected by the new national ABCD study funded by NIH. Nonetheless, the current study can provide hints as to potential effects of marijuana use due to its large sample size and because family structure was controlled for in the analyses. In addition, despite the 100-fold increase in the number of marijuana users from most studies and the high-quality of imaging data, the data on marijuana use history from the HCP is relatively sparse. Whereas alcohol and tobacco were assessed in terms of recent and past use, questions of marijuana use were restricted to self-report measures of the age of first use and the number of times used in the lifetime. As such, it was not possible to accurately examine the effects of duration of use or more specifically, the effects of time since last use. As noted in the Materials and methods Section, the age of first use and number of times used data was coarsely coded using relatively arbitrary ranges. In particular, the number of times used score presented widely different categories for participants to select, ranging from 1–5 times used to “more than 1000.” Moreover, no data was available regarding the recency of this use. Additionally, while tobacco and alcohol were controlled for using scores selected to best represent the impact of chronic, co-morbid substance use, it is possible that alternative metrics would change the representation of variance due to these substances. As it stands, the alcohol and tobacco use scores used in this presented significant co-variance with age of first use and times used, highlighting both the need to control for these factors and the importance of a data-set large enough to separate the effects of each variable.

While participants were excluded from the HCP for major psychiatric or neurological illness participants underwent a psychiatric screening as part of the SSAGA, and psychiatric symptoms were assessed with the NIH Toolbox and the Achenbach Adult Self-Report questionnaire . Examining the interactions of psychiatric symptoms and marijuana use was beyond the scope of the current study, but future studies should examine these effects. Previous studies have shown that adolescent marijuana use is co-morbid with a number of psychopathologies including childhood trauma , depression , attention deficit hyperactivity disorder , and psychosis . Furthermore, the HCP contains information about parental psychopathology. While much of the psychiatric information available in the HCP has less information than a targeted study of psychopathology, there is enough information for future studies to assess multivariate effects of marijuana use variables and co-morbid psychopathology and other substance use. Lastly, while the advanced imaging analyses used in this study provide powerful ways to non-invasively understand the anatomical changes occurring with a brain, they are limited in that they cannot speak to the mechanisms whereby marijuana use might influence brain structure. specifically, they cannot elucidate the microscopic changes responsible for the more macroscopic GM and WM impacts . For example, while shape changes of the accumbens and hippocampus might reflect inflammation, marijuana has been found to have anti-inflammatory properties . Macroscopic morphological changes could be caused by neuronal loss or changes in cytoarchitecture such as neuronal size, dendritic spine density, dendritic length, or synaptic protein levels . As such, morphometry studies can strongly inform where such changes are occurring, but cannot pinpoint the microscopic causes of these structural changes. It is important to note that the two major components of marijuana, Δ-9-tetrahydrocannabinol and cannabidiol , have opposite effects behaviorally, symptomatically, and in terms of functional activation of all of the regions-of-interest for the current study . With legalization of marijuana comes more accurate assays of THC and CBD concentrations, and thus, future research can and should focus on examining whether THC and CBD have dissociable effects on brain morphometry .Parkinson’s disease is the second most common neurodegenerative disorder worldwide, affecting 1e2% of the population over the age of 65.

The condition is characterised by the progressive loss of dopaminergic neurons from the substantia nigra pars compacta.There are a number of studies that link the development of PD with the exposure of certain pesticides such as rotenone.As a result, rotenone is commonly used to create in vivo and in vitro models to study the disease.H2O2 is a compound commonly used to model oxidative stress in vitro and in vivo. As mitochondrial dysfunction and oxidative stress are thought to contribute to cell death in PD, we aimed to assess the effects of both rotenone and H2O2 on SH-SY5Y neuroblastoma cells. The SH-SY5Y neuroblastoma cell line has been previously used to create a cellular model of PD.The cells share many biochemical and functional characteristics with mature dopaminergic neurons and have the ability to differentiate into adopaminergic phenotype. As tyrosine hydroxylase and dopamine seem to be central to the pathogenesis of PD and dopaminergic neurons are specifically targeted in the condition, we opted to utilise a cell line that had been transfected with human TH isoform 1.There were two main aims to be addressed in this study, firstly we aimed to compare the effects of rotenone and H2O2 treatment on cell viability and TH expression and once we had established these changes we would then assess the ability of a number of potentially neuroprotective compounds to protect against this toxicity. Cinnamon is a spice commonly used in food throughout the world. The spice has been demonstrated to have anti-diabetic and anti-inflammatory effects as well as some neuroprotective properties.For instance a previous study demonstrated that treatment with cinnamon prevented the development of PD like symptoms and pathology in 1-methyl-4-phenyl-1,2,3,6-tetra hydropyridine treated mice, however the effect of cinnamon on rotenone is yet to be investigated. Hemp seed and its oil have been used as both a food and medicine in China for at least 3000 years and hemp seed extracts have been found to demonstrate antioxidant and antiaging effects as well as improve cognitive impairment induced by chemicals in mice.In addition to all of this, epidemiological studies suggest societies that commonly use curcumin, cinnamon and hemp seed appear to demonstrate a lower incidence of PD and neurodegenerative disorders.We included the use of curcumin within our study as a positive control as this substance has been shown previously to provide protection against rotenone and H2O2 toxicity.Polygonum cuspidatum is widely distributed in the world and has been shown to possess antiviral, antimicrobial, anti-inflammatory,pollen trim tray neuroprotective, and cardioprotective properties,however these properties are yet to be investigated using a cellular model of PD.

In this study we assessed the effect of rotenone and H2O2 on SHSY5Y cell survival and TH protein expression. We also evaluated the protective effects of curcumin, cinnamaldehyde, and constituents isolated from hemp seed and polygonum cuspidatum .Methylthiazolyldiphenyl-tetrazolium bromide powder was used as a means to assess cell viability as previously described.Briefly, at the conclusion of the 24 h treatment duration, MTT was added to culture medium at a final concentration of 0.5 mg/ml and the plate was mixed gently for 1 min before 2 h incubation in a 37 C, 5% CO2 incubator. After the incubation, media was removed and 100 mL of DMSO was added to each well for 10e15 min while shaking. The intensity of the purple colour produced in each well was measured colourimetrically using a plate reader at 595 nm. The values of absorbance are expressed as a proportion of the controls.The Trypan Blue assay was used as another means of visually assessing cell viability to support the MTT assay findings. Cells were seeded into 12 well plates and treated as described above. When the treatment protocol had ended the media was removed from the wells and 30 mL of Trypan Blue was added and left for 30 s. After 30 s an image of the plate was taken using ‘Cell Pad’. While not quantitative this protocol provided a means of visually assessing the viability of cell cultures.Whole cell lysates were used for western blotting experiments to analyse total TH and Poly-ADP ribose-polymerase protein levels. Cells were seeded in a 24 well plate and treated as described above. At the end of the treatment protocol media was removed and 110 mL of 2% SDS stop buffer with inhibitors , 2% SDS, 2 mM EDTA, 1 mM Na orthovanadate, 1 mM Na fluoride, 10 mM Na pyrophosphate was added. The lysed cells were collected and heated for 10 min at 100 C. Samples were then frozen and stored at -20 C for later analysis. Samples were prepared for electrophoresis by dilution with sample buffer . Samples were run on an 8 or 10% SDS-polyacylamide gel and transferred to nitrocellulose membrane . To minimise non-specific binding membranes were blocked with 5% skim milk in Tris-buffered saline containing 0.075% tween 20 for 1.5 h at room temperature. Membranes were then incubated with anti-PARP-1 or anti-total TH antibodies for 1 h at room temperature. Blots were washed and exposed to appropriate secondary antibody for 1 h at room temperature. Blots were then exposed to enhanced chemiluminescence detection reagent for 1 h and developed using a LAS 4000 imaging system . Later, membranes were washed and then immunoblotted with b-actin antibody as a marker of the total protein loaded per lane.Quantitation of tTH and PARP-1 were normalised relative to b-actin levels.This study demonstrates that rotenone and H2O2 have markedly different effects on SH-SY5Y cells. H2O2 treatment does not appear to have any significant effect on TH protein expression and the cell death induced by H2O2 can be prevented by a number of compounds tested. In contrast, rotenone treatment was associated with an increase in TH protein levels and its toxicity could not be prevented with any of the compounds.

In the present study natural fiber composites,containing 10%,20% and 30% hemp fibers as reinforcement and mixture of virgin and recycled high density polyethylene as matrix,have been fabricated.The tensile and flexural properties of the composites are evaluated and compared with samples made of 100% virgin HDPE and 50-50 mixture of virgin and recycled HDPE.In the last years,considering the increasing environmental awareness and the introduction of new rules and regulations to reduce the environmental impact and reach sustainability,the new products must minimize the environmental impact,so the interest and the subsequent use of eco-friendly materials is grooving more and more in different application fields.This aspect is particularly relevant in the composite manufacturing field,where both synthetic fibers and petroleum polymers are still widely used.In this contest,the use of natural fibers as reinforcement is reaching an increasing attention,indeed a lot of researches have aimed on the study of a range of recyclable materials based on natural fibers such as flax,ramie,sisal,hemp and many more in order to study their possible use as interesting substitute over the conventional ones.Among various kinds of natural fibres,the hemp one is one of the most promising because of its interesting properties such as the low density,low cost and high specific mechanical properties.In addition,the hemp plant is characterized by the ability of extracting heavy metals from the soil makes and the environmental conditions required from its cultivation allow the easy growth of this plant around the world.Regarding the matrix used for the natural fibre composites manufacturing,commercial greenhouse supplies its selection is limited by the temperature at which natural fibres degrade.Both thermoset and thermoplastic polymers are coupled with natural fibres and each one highlights its peculiarity characteristics: thermoplastics are capable of being repeatedly softened by the application of heat and hardened by cooling and have the potential to be the most easily recycled,on the other hand a better emphasis of the fibres mechanical properties are generally achieved by using thermosets as matrix.

In fact,thermoset polymers are particularly attractive as matrix materials for natural fibre reinforced composite production as they generally have reactive functional groups that make them compatible with hydrophilic fibre surfaces.Among these,the epoxy is one of the most interesting polymer resins that used as matrix for the natural fibre composites shows very high mechanical properties of the final product.Several applications as interior and insulation components of hemp/epoxy composites was largely found in literature in particular in the automotive and building sectors,whilst there are few applications as structural components and few works aimed on the study of manufacturing processes to produce hemp composites characterized by low density and high specific mechanical properties.Based on this overview,this work is focused on the manufacturing of lightweight hemp/epoxy composites through a new process easily implemented in industrial production by using hemp fabrics characterized by a large mesh size.To assess their mechanical performances,tensile and bending tests were performed and coupled with FE simulations.Therefore,due to the no optimum control in the fabric superimposition,even though the fibre weight content is the same for each sample typology,the difference in the thickness vales is directly connected with the difference in the density and in the fibre volume fraction values.Ideally,considering for the B type a good alignment able to obtain the same thickness of the A type sample and also considering that the B type samples contained half number of tows then the A type,the ideal values of the density and of the fabric volume fraction should be half than the ones of the A type.Figs.8 and 9 shows the tensile and bending stress-strain curves for the specimens under investigation.The composites with density of around 0.74 g/cm3 are characterized by a tensile strength of 40 MPa and a tensile modulus of 3000 MPa,whilst the composites with a density of around 0.47 g/cm3 showed a tensile strength of 24 MPa and a tensile modulus of 1650 MPa; the tensile properties of the B type are approximately half of the ones of the A type.Looking at Fig.9,it is possible to note that all curves show the same behavior up to the failure,but when the maximum stress value was reached and then the specimens started to fail,the behavior changes.

This is observed by comparing the stress-strain curves and the type of failure of the specimens show in Fig.10.The curves of the A type show a significant drop in the stress and then a brittle failure of the specimens was observed,whilst the curves of the B type show a slighter decrease in the stress coupled with a sliding failure.This is due to the higher presence of resin on the bottom surface of the A type specimens.The composites with a density of 0.77 g/cm3 showed a bending strength of 40 MPa and a bending modulus of 3100 MPa,instead of the samples with a density of around 0.47 g/cm3 that was characterized by a bending strength of 22 MPa and a bending modulus of 1200 MPa.It is also possible to observe that the flexural mechanical response variability is in any case quite limited.However,a slightly greater value was reached for the B type specimens due to above said misalignment problems that mainly occurs for this specimen typology.This is also corroborated from the results of the FE simulations of the three-point bending tests where the eventual misalignment error was considered.Illicit marijuana use in the United States has been a longstanding public health concern for both adolescents and adults.As many as 44% of college-aged individuals endorse having used marijuana at some point in their life,and 21% of college-aged individuals report marijuana use in the past 30 days.Marijuana intoxication is associated with motor coordination deficits,euphoria,impaired temporal estimation,and a variety of other psychological phenomena.Marijuana use has also been associated with more specific cognitive deficits,even after acute intoxication has subsided,and with the development of severe psychopathology.Furthermore,chronic marijuana use has been related to adverse physiological consequences in the cardiovascular and respiratory systems.Adolescence and young adulthood represent periods of the lifespan when increased risk-taking occurs,including the use of illicit substances,such as marijuana.The combination of an innate propensity for risk-taking and use of a judgment-altering substance is a striking example of the immediate public health concern over marijuana use in young-adults.This concern is particularly pertinent in light of recent efforts in support of marijuana’s legalization in the United States.A challenge for the field is to identify which chemical systems and associated information processing networks are most affected by chronic marijuana use.

The main psychoactive component of marijuana,Δ9 -tetrahydrocannabinol,acts as an agonist in central nervous system cannabinoid receptors and in other peripheral cell types,primarily immune cells.In the CNS,CB1 receptor density is high in the basal ganglia,particularly in the dorsal striatum.Cannabinoid receptor signaling acts on multiple neurotransmitters through a variety of biochemical cascades,including inhibition of voltage-dependent calcium channels and by directly inhibiting vesicle release.Both excitatory and inhibitory neurotransmitters,including glutamate,γ-aminobutyric acid and dopamine,are either directly or indirectly affected by CB1 receptor activation.For marijuana and other drugs of abuse and dependence,the dorsal striatum has been hypothesized to play a key role in the transition from intermittent drug use to compulsive habit-based drug-taking via mechanisms that underlie long-term synaptic plasticity.Exogenous activation of CB1 receptors,as occurs with marijuana intoxication,inhibits the release of glutamate as well as GABA in both the dorsal and ventral striatum.This inhibition facilitates the development of long-term depression in the striatum,which is a critical component in the altered synaptic plasticity that accompanies drug addiction.Thus,the manner in which corticostriatal functional connectivity is altered in the context of marijuana use is of interest,as is metabolic activity within the chemical systems that contribute to those alterations.Magnetic resonance spectroscopy is a widely used tool,allowing for in vivo characterizations of various brain metabolites.MRS data is acquired either from single voxel or multiple voxels.The SVS method typically benefits from high spectral resolution and signal-to-noise ratio.MRSI has better spatial resolution compared to SVS,but typically has a much more limited spectral resolution.To the best of our knowledge,only four other studies utilizing some form of MRS to examine marijuana users have been published,and the methods of these studies are relatively heterogeneous.The existing studies are summarized in Table 1.

Individuals ages 16-to-42 years were studied with either SVS or MRSI.In two of the studies,only males were examined.In most cases,marijuana use was reported at 20 or more days per month.Lower levels of Glu,N-acetylaspartate,and myo-inositol were observed in marijuana users compared to controls in regions known to be associated with substance use,cannabis dry rack including the basal ganglia,thalamus,cingulate cortex,dorsolateral prefrontal cortex,and the striatum as well as posterior cortical regions.The methods,ages of subjects,and extent of current marijuana use in the samples tested vary considerably across studies as summarized in Table 1.As disruptions in glutamate activity have been implicated in the development of addiction,we hypothesized disruptions in glutamate concentrations in marijuana users compared to controls.Several lines of evidence suggest inhibition of glutamate excitotoxicity by marijuana.In addition,based on the MRS literature described above related to the basal ganglia of adult marijuana users and literature describing the inhibitory effects of CB1 receptors on glutamate release,we specifically hypothesized that young-adult MJU subjects would show lower levels of Glu + glutamine in the basal ganglia compared to their non-using counterparts.We did not have a specific hypothesis regarding concentrations of other metabolites given that other researchers have not concentrated their assessments on the striatum.However,the limited available literature suggested the possibility of altered mIns as well as NAA levels in users versus controls.Twenty-seven marijuana users were recruited into the study through local advertisements on the University of Minnesota-Twin Cities campus.Marijuana users’ ages ranged from 18-to-21 years,with a mean and standard deviation of 19.5 ± 0.6 years.Exclusion criteria are described below.Twenty-six healthy young adult non-users,who were participants in a large,longitudinal study of normal brain development,served as a control sample.Control participants’ ages ranged from 13-to-24 years,with a mean and standard deviation of 19.3 ± 3.1 years.The recruitment strategy for the control sample has been described elsewhere.Briefly,participants younger than 18 years of age were recruited through a database of research volunteers throughout the Metro community,through post-cards mailed to University of Minnesota civil service employees,and through local advertisements.Participants over the age of 18 years were recruited using on-campus advertisements.During the controls’ third longitudinal follow-up visit,MRS was added to the protocol as time allowed.Thus,the control sample described in this study has a broader age range than the MJU sample,a feature that was considered in the statistical approach described below.A description of the study was initially given to both the MJU and control participants over the phone.Interested participants were then invited to complete a brief phone screening to ascertain study eligibility.Exclusion criteria included major physical,neurological or psychiatric illness,substance use disorders,head injuries resulting in loss of consciousness >20 min,mental retardation,learning disabilities,current use of psychoactive medications,non-native English speaking,vision or hearing that was not normal or corrected to normal,complications at birth,current pregnancy,and MRI contraindications.Inclusion criteria for MJU participants included current use of marijuana at least five times per week for at least one year,and an age of onset of use prior to the age of 17 years.Marijuana users were also excluded if they were daily cigarette smokers,or if their alcohol use exceeded four drinks for females and five drinks for males on more than two occasions per week.Marijuana users were asked to refrain from drug use for at least 12 h prior to their visit to avoid acute intoxication during study procedures.Participants provided written informed consent and all study procedures were approved by the University of Minnesota’s Institutional Review Board.After the phone interview,eligible participants were invited to the University of Minnesota’s Center for Neurobehavioral Development for an in-person screening session to further ascertain eligibility and to verify information given over the phone.The Kiddie Schedule for Affective Disorders and Schizophrenia,Present and Lifetime version was used to assess for current or past Diagnostic and Statistical Manual,Fourth Edition axis I disorders,including childhood disorders given the relative youth of the sample.The presence or absence of DSM-IV disorders was confirmed by case consensus meetings with staff members including a license-eligible clinical psychologist.In addition,a two-subtest version of the Wechsler Abbreviated Scale of Intelligence was administered to yield estimated full scale IQ.Participants who met all inclusion criteria after the in-person interview were invited back for a comprehensive neuropsychological testing battery and an MRI scan.

As evidence for adverse consequences of marijuana use during adolescence on brain functioning accumulates,such research has the potential to improve prevention and intervention efforts through better education,thus reducing marijuana use and associated negative consequences.To guide recruitment,the Adolescent Brain Cognitive Development Study required a method for identifying children at high risk for early-onset substance use that may be utilized during the recruitment process.In this context,childhood risk refers to characteristics identified at ages 9 or 10 years that predict adverse outcomes in adolescence,and “high risk” refers to a categorical classification of some children as having increased risk compared to others.The construction of a brief measure for childhood substance use risk involves the identification of characteristics that predict early-onset substance use in mid to late adolescence.The identification and evaluation of optimal items for a brief childhood measure to serve as a high-risk screener ideally involves data from several large prospective studies with assessments initiated prior to the typical age of onset of substance use.To inform ABCD Study recruitment,secondary analyses are needed with datasets collected prior to ABCD Study initiation.In this context,a set of analyses with available data focused on a specific substance use outcome was determined to be most likely to be informative and feasible.While other substance use outcomes are also important,early-onset marijuana use is a relevant target.Marijuana is the most commonly used illicit drug by adolescents,and regular marijuana use identifies youth likely to develop cannabis use disorder.In these secondary data analyses,the definition of early-onset marijuana use was defined by the initiation of regular use as indicated in the available datasets.The studies contributing datasets were the Center for Education and Drug Abuse Research,cannabis drying the Pittsburgh Youth Study,the Pittsburgh Girls Study,and the Michigan Longitudinal Study.

In the studies contributing data to the secondary analyses described here,the definitions of regular marijuana use differed by sample due to measurement variations.The variations in the definitions of regular marijuana use were as follows: ; five or more use occasions in the past year and; six or more occasions in the past year.By efficiently identifying children at high risk for early-onset marijuana use,a brief and effective measure of childhood risk measure could be utilized as a screen to identify high risk children in prevention research,primary medical care,and mental health clinic settings.The present analyses were specifically undertaken to inform the development a childhood high risk screen for use in the ABCD Study.The ABCD Study is the National Institute of Healths’ large-scale prospective population study of the biological and environmental factors that influence young people’s ability to successfully navigate adolescence.The study has a special emphasis on the risk and protective factors that influence marijuana and other substance use,and subsequent health problems including substance use disorders.Utilizing data from previously conducted studies,the present study was thus undertaken to develop and establish the efficiency of a short measure to identify youth at high risk for early-onset marijuana use with optimal features for use in the ABCD Study.To achieve this goal,the risk level of a potential participant needs to be determined at the time of recruitment and prior to their scheduling for the extensive ABCD Study assessment protocol.Consequently,the optimal ABCD Study high risk screen has several characteristics: extreme brevity,including less than ten items; lack of sensitive items that may raise confidentiality concerns at this early stage of considering participation; consistency with prior research.These characteristics were taken into consideration in the analyses that follow.Historically,studies focusing on mental disorders such as schizophrenia,alcohol use disorder,and major depressive disorder,have used positive family history as a risk marker.Family history has been demonstrated to identify children at high risk of later substance use disorders in many prospective studies.However,a detailed family history may involve the parent being asked to disclose their own socially undesirable,embarrassing or,in some cases,illegal behavior.

There have been alternative strategies to acquire this information,such as the use of publicly available records of drunk driving or other drug offenses,or the use of hospital records to identify parental diagnosis.Obtaining such records would not be feasible in the initial recruitment phase of the ABCD Study.Regardless of the method for obtaining this information,requesting this information at the point of introducing the ABCD Study raises the real possibility that the parent will decline study involvement.Few longitudinal studies have formulated and tested measures for identifying high risk children likely to exhibit early-onset marijuana use.There have been several approaches developed for predicting substance use disorders,but relatively few have targeted the adolescent developmental period.One of the risk measures developed to identify high risk children is the SUD Transmissible Liability Index developed by Vanyukov,Tarter,Clark and colleagues,using longitudinal data from the CEDAR study.Although the TLI is sophisticated in its development,it is long,uses different portions of existing instruments,and is under copyright.In addition,the TLI did not focus on the age 15 outcome of marijuana use,and the publications did not use Receiver Operating Characteristic Area Under the Curve analyses to determine an optimal threshold score.Another screening instrument,the DSM Guided Cannabis Screen has unknown predictive value because it was constructed using cross-sectional data from a small clinical sample aged 14–59.Therefore,the current study fills a significant gap in the empirical literature.This report describes the process and results of secondary data analyses to prospectively identify a brief screening measure applicable to age 9–10-year-old children that would predict early-onset marijuana use in the 5–7 years following the initial screening measurement.To acquire data useful for developing this screening measure,we needed to identify population-based prospective studies which began assessments in late childhood,had been continued at least through ages 14–17,included marijuana use variables at both age periods,measured domains previously identified in the literature as predictive of adolescent substance use disorder outcomes,and had a sufficient number of measures in these domains that were shared across these studies so that screening validation could be replicated across different demographic groups.

The objectives of these secondary data analyses were as follows: To develop a brief screener for 9–10-year-old boys and girls to predict early-onset marijuana and other substance use in mid adolescence with demonstrated predictive utility across four longitudinal data sets; To dichotomize the outcome variable,which will reduce shrinkage,improve replicability and practical utility.; To replicate findings across construction and validation samples.The advantage of this dual analysis approach is that we could construct a screener that considers shrinkage that typically happens between construction of a screener and subsequent validation in another sample.In summary,the objective was to develop a brief and feasible approach to the identification of children at increased risk for early onset marijuana use that may inform the ABCD Study recruitment procedures.To ascertain replication of results,we used four existing longitudinal data sets.These data sets were utilized to build construction and validation samples for each sex,resulting in nine independent analyses.The four longitudinal data sets were from the CEDAR,PYS,PGS,and MLS.Where possible,we used both parent and child as informants,which is particularly important for externalizing behavior that is concealing in nature,because parents usually have less knowledge of the behavior compared to the child.The overall sample consisted of 882 boys and 368 girls.At the initiation of the study,81.3% of the boys were White,and 18.7% Non-White,and 74.7% of the girls were White,25.3% Non-White.Sample selection: Families were ascertained through two methods.The first involved recruitment through all district courts of fathers living in the area convicted for drunk driving with a biological son between the ages of 3 and 5 years old.Fathers were also required to be living with the boy and his biological mother.The second group were required to have the same family composition,but were ascertained through the same neighborhoods as the court-recruited families.Door to door canvassing was carried out to recruit two subgroups: families where neither parent met a lifetime substance use disorder diagnosis ; families where father met criteria for an alcohol use disorder but were not involved with the court.In addition to the original 3-5-year-old son and his biological parents,a female sibling within the range of 3–11,when present,was also recruited.If other siblings in the 3-11-year age range were also present in the home,they were recruited as well.Assessment at T1 for this study : average ages: 10.55 for boys and 10.61 for girls.

Where possible,we used both parent and child as informants,which is particularly important for the externalizing behaviors that are concealing in nature,because parents often are not aware of this type of child behavior.The outcome of interest was child self-report of marijuana use at about age 14.Attrition was 10%.The potential items for analyses were identified by examining prior research,prior analyses with the available datasets,greenhouse benches particularly the extensive analyses with CEDAR data,identifying pertinent items available in the four longitudinal projects used in these secondary analyses,and deliberations on the acceptability of areas of inquiry for potential participants during the recruitment process.Based on these considerations,the constructs represented by the pool of items to be considered included child externalizing behaviors,child internalizing behaviors,and parent tobacco smoking.Child externalizing behaviors.In the case of the ABCD Study design,we are projecting from ages 9–10,when marijuana use typically is minimal and not a viable risk item for screening purposes.Therefore,for candidate items on child externalizing behaviors,we considered non-substance use characteristics that other studies have found to predict early-onset substance use in mid adolescence,particularly child externalizing behaviors.Potential externalizing behaviors considered were vandalism,lying,and disobedience at school.Child internalizing behaviors.In addition,we examined whether selected internalizing behaviors augmented predictions.After examining potential internalizing items’ correlations with both the tentative screener and with the outcome variable,we initially focused on the following items : unhappy,sad or depressed; too fearful or anxious; secretive or keep things to oneself; self-conscious or easily embarrassed.After considering which internalizing items correlated with the externalizing screener at that point,we finally focused on: unhappy,sad or depressed; too fearful or anxious.Parent smoking.For candidate items on parent behaviors,parent smoking was also considered a viable candidate.This candidate item for the screener was available in the 4 study data sets.The predicted outcome was marijuana use by ages 14–15 with a frequency that indicated greater than experimental use.The available outcome categories varied across the studies,including monthly use in CEDAR,use at five times or more in the past year in the PYS and PGS,and 6 or more times during the past year in the MLS.The presence of marijuana use at or above these thresholds for the depicted ages defined “early-onset marijuana use” in these secondary analyses.The evaluations of individual items and their combinations in relations to early-onset marijuana use were undertaken with Receiver Operating Characteristic statistics.This approach is typically used in evaluating screening for diseases,with several examples in the prior literature focusing on substance use frequency in relation to adolescent substance use disorders.Using ROC statistics,the evaluation of the prediction power of a screen is usually based on a 2 by 2 table,as illustrated in Fig.1.The quality of a screen is indicated by four parameters: Sensitivity and specificity,which refer to True Positives/,and True Negatives/,respectively,and Positive predictive value and negative predictive value,which refer to True Positives/True Positives + False Positives and True Negatives/True Negatives + False Negatives,respectively.

Area Under the Curve analyses were used to establish whether the prediction is better than chance; and what the optimal cut-off is to minimize false negative and false positive errors.AUC can range from 0.5 to 1.0,when sensitivity and specificity are considered equally important.In practice,AUC tends to be lower than 1.0,meaning that one cannot correctly classify all future marijuana users or correctly classify all future non-marijuana users.The general rule is that the higher the sensitivity,the lower the specificity.Lowering the cut-off score can increase sensitivity,but with the consequence that there will be more false positives.Where sample sizes from study sites were sufficient,we created two subgroups,labeled “construction” and “validation” samples,using a randomization method,the SPSS random variable generation function.This partitioning of the samples was done to avoid idiosyncratic findings.Sufficient sample sizes were available to take this approach for CEDAR boys,PYS,and PGS,but not for CEDAR girls,MLS boys,or MLS girls.To support scale construction yet allow for validation in these limited samples,weightings were applied so that there were more subjects assigned to the construction sub-sample than to the validation sub-sample.We searched for equivalent predictor items of interest in each dataset.This is very important because we needed construct convergence among the four longitudinal datasets.We used prorating in cases where there were missing items so that we would maximize the numbers of participants.Note that sample sizes varied somewhat due to missing cases for each analysis.

Mainstream smoke was passed through a 92 mm glass fiber filter disc for particulate matter collection.To prepare the condensate samples,the respective filter pads were placed in a flask containing dimethyl sulfoxide and shaken on a wrist-action shaker for 20 min.Each condensate sample was standardized to a concentration of 30 mg total particulate matter per ml of DMSO.Cytotoxicity of the smoke condensates was determined using the lactate dehydrogenase assay and the XTT assay.The LDH assay was performed using a kit according to manufacturer’s instructions.Briefly,FE1 cells were grown in 12-well plates and exposed to 8 concentrations of 1.5–30 g/ml of MSC or 3–90 g/ml of TSC in serum free medium for 24 h r.After plates were centrifuged,an aliquot was transferred to flat-bottomed plates and the LDH Assay Mixture was added.Plates were covered with aluminum foil and incubated at room temperature for 20–30 min.1 N HCl was added and the absorbance was measured at 490 nm,with the background measured at 690 nm.The XTT assay was also performed using a kit according to manufacturer’s instructions.Briefly,FE1 cells were grown in 12-well plates and exposed to 8 concentrations of 1.5–30 g/ml of MSC or 3–90 g/ml of TSC in serum free media for 24 h.The XTT reagent was added and the plates were incubated for 2 h at 37 ◦C.The plates were mixed and the absorbance was measured at 450 nm.Absorbance at the reference wavelength of 690 nm was also read and subtracted from the 450 nm value.A reference design with arrays as blocks of size 2 was used to analyze the median signal intensities of the two-color micro-array data.The experiment included main effects of dose,time and dose-by-time interaction.Five biological replicates per condition were used for each of the eight conditions,for a total of 80 micro-arrays.Six MSC and four TSC “outlier” micro-arrays were removed based on quality control checks,cannabis vertical farming leaving a minimum of 3 replicates per group.

The background signal intensity for each array was estimated using the 1533xSLv1 negative controls present on each array.All pre-processing of the data was conducted using R.The data were normalized using the LOWESS normalization method in the R library “MAANOVA”.Differential expression between the control and exposed samples for each of the three dose levels at each of the two time points was tested using the MAANOVA library.The ANOVA model was fitted to include the main effects of dose and time,with a dose by time interaction term and the array as a blocking variable.The Fs statistic,a shrinkage estimator,was used for the gene-specific variance components,and the associated p-values for all the statistical tests were estimated using the permutation method.These p-values were then adjusted for multiple comparisons using the false discovery rate approach.The least squares mean,a function of the model parameters,was used to estimate the fold change for each pairwise comparison of the six pairwise comparisons of interest among the eight treatment-by-time groups.The micro-array data for this experiment has been submitted to the Gene Expression Omnibus repository and can be accessed under record number GSE44603.Visualization and analysis of significantly changing genes was performed using Gene Spring GX 7.3.Important pathways containing significantly expressed genes were identified using Ingenuity Pathway Analysis.Genes were assigned to functional categories using gene ontology in the Database for Annotation,Visualization and Integrated Discovery.BMD Express was used to calculate benchmark doses from gene expression data.Analyses were performed on genes that were identified as statistically significant by one-way ANOVA using four models: Hill,Power,Linear and 2◦ Polynomial.Models that described the data with the least complexity were selected.A nested chi-square test,with cutoff of 0.05,was first used to select among the linear and 2◦ polynomial model,followed by comparison of Akaike information criterion,which measured the relative goodness of fit of a statistical model,between nested models and the power model.The model with the lowest AIC was selected as the best fit.A maximum of 250 iterations and a confidence level of 0.95 were selected.For functional classifications and analyses,the resulting BMD datasets were mapped to KEGG pathways with promiscuous probes removed.BMDs that exceeded the highest exposure dose were removed from the analysis.

Eight nanograms of total RNA,from the same samples that were used for the micro-array study,were reverse transcribed to cDNA using an RT2 First Strand Kit.cDNA was mixed with the RT2 qPCR Master Mixes and aliquoted into 96-well plates containing primers for 84 pathway specific genes.Expression levels were evaluated using a CFX96 real-time Detection System.Relative gene expression was normalized to the Gapdh housekeeping gene,which remained unaffected under experimental conditions.Fold changes and statistical significance were calculated using the REST method for statistical significance.For the micro-array study,FE1 cells were exposed to 2.5,5 and10 g/ml of MSC and 25,50 and 90 g/ml of TSC.Exposed samples were compared to their matched controls,and genes were considered significantly differentially expressed if they had a fold change ≥2 with an FDR-adjusted p-value ≤0.05.A total of 1020 unique probe identifiers were significantly differentially expressed following exposure to MSC,and of these,979 were deemed “present”.Following exposure to TSC,557 probes were significantly differentially expressed and 527 were deemed “present”.Of these,356 were common to both MSC and TSC exposures.The number of significantly up- and down-regulated genes at each time point and concentration is shown in Table 1.Overall,there was an increase in the number of differentially expressed genes with increasing concentration of condensate,and there were more genes changing after the four hour recovery.At the highest concentration for both time points,cells exposed to MSC had a greater number of changing genes as compared to cells exposed to TSC.Gene expression was most altered for cells exposed to the highest concentration of MSC at the 6 + 4 h time point.Whether separated by dose or considered all together,Venn diagrams show considerable overlap in the genes that are significantly expressed at each time point following MSC or TSC exposure.Hierarchal clustering using all genes that were statistically significant revealed that the controls and the marijuana high concentration clustered independently from the rest of the samples.The remaining samples clustered first by concentration,then by condensate type,with the last branching resulting from time.When cells exposed to TSC and MSC were analyzed separately,samples clustered first by concentration and then by time point,suggesting that concentration has the largest overall effect on gene expression.For MSC,the high concentration samples were on the first main branch,followed by control,low and medium concentrations.

The results indicate that the expression profiles of the high concentration MSC exposed cells are quite distinct.For TSC,the controls branched separately from all the treatment groups.The top 10 genes with the largest overall fold changes are listed in Table 2.All of the top 10 genes were significantly up-regulated with the exception of low density lipoprotein receptor,which was down-regulated in MSC exposed cells.Of the top 10 changing genes,five genes were common to both MSC and TSC.The GO terms associated with these commongenes included multicellular organismal development,vasculogenesis,regulation of transcription,and regulation of inflammatory response.Ingenuity Pathway Analysis was used to define the pathways that were significantly altered following exposure to MSC or TSC.Fig.3 shows the overlap in all the significant pathways between the two condensate types.The top five most significantly altered pathways for cells treated with MSC or TSC are listed in Table 3.NRF2-Mediated Oxidative Stress Response was the most significant pathway for cells exposed to TSC at all concentrations and time points,with the exception of lowest concentration at time 6 + 4 h where LXR/RXR Activation was the most significant.For cells exposed to MSC,the most significantly altered pathways were Biosynthesis of Steroids,as well as NRF2-Mediated Oxidative Stress Response,Aminoacyl-tRNA Biosynthesis and HMGB1 Signaling.Some of the top five pathways were common to both the MSC and TSC including those related to oxidative stress and xenobiotic metabolism.However,inflammation pathways were more predominant for the MSC,whereas cell cycling and cancer signaling pathways were more predominant for the TSC.To further elucidate differences between the two smoke condensates,the genes that were uniquely expressed following TSC exposure or uniquely expressed following MSC exposure at the highest concentrations for the two separate time points were compared in IPA.The findings confirm the importance of inflammation and steroid biosynthesis pathways in MSC exposed cells and highlight the significance of apoptotic pathways particularly at the 6 h time point.For cells exposed to TSC,Mphase cell cycle pathways appear to be of particular importance.

Gene Ontology in the Database for Visualization,Annotation and Integrated Discovery was used to apply functional annotation to all the significantly differentially expressed genes for each condensate.The full results are shown in Supplementary Tables 1 and 2.For cells exposed to MSC,cannabis drying racks significant perturbations were associated with steroid/cholesterol/lipid biosynthesis,NOD like receptor signaling,tRNA aminoacylation,transcription regulation,unfolded protein response and DNA binding.Like MSC,cells exposed to TSC had significant perturbations in transcription regulation,unfolded protein response and DNA binding.In addition,perturbations in cell cycle,p53 signaling,oxidative stress,and cancer signaling were also noted in TSC exposed cells.Fig.5 shows the overlap of all the significantly affected on tologies between the two condensate types.Functional annotation clustering in DAVID was used to minimize redundancy in the GO terms.This analysis revealed 19 clusters with enrichment scores greater than 2 for MSC and 19 clusters for TSC.The top clusters for MSC relevant to toxicological processes include lipid/steroid biosynthesis,RNA processing,cellular response to unfolded protein,tRNA aminoacylation,and positive regulation of transcription.The top clusters for TSC relevant to toxicological processes include cellular response to unfolded protein,cell cycle,positive regulation of transcription,response to steroid hormone stimulus,and positive/negative regulation of apoptosis and cell death.To investigate early versus downstream effects,functional annotation was applied to significantly differentially expressed genes at the two separate time points.The results are shown in Supplementary Tables 5–8.For cells exposed to MSC at the 6 h time point,the analyses revealed 79 significant terms including those related to transcription activity,DNA binding,and steroid/cholesterol biosynthesis.Four KEGG pathways and 1 Biocarta pathway were also deemed significant at this time point.At the 6 + 4 h time point,76 significant terms were identified.These terms included unfolded protein response,and tRNA aminoacylation,as well as steroid/cholesterol biosynthesis which was found at the 6 h time point.Three KEGG pathways were significant at this time point including Steroid Biosynthesis,Terpenoid Backbone Biosynthesis,and Aminoacyl-tRNA Biosynthesis.Analyses of cells exposed to TSC at the 6 hr time point revealed 67 significant terms including those associated with oxidative stress,cell death,protein unfolding,transcription regulation,DNA binding and cell cycle.In addition,2 KEGG pathways were significant.At the 6 + 4 h time point,32 GO terms were identified as significant with oxidative stress being the only relevant toxicological endpoint.In addition,only one KEGG pathway was significant.

Overall for MSC,the DAVID analyses confirmed many of the significant pathways identified by IPA including steroid biosynthesis,tRNA aminoacylation,inflammation and apoptosis.In addition,the analyses highlighted transcription regulation,DNA binding and unfolded protein response as also significant.For TSC,the DAVID analyses confirmed the significance of IPA pathways related to oxidative stress and cell cycle.As with the MSC,the DAVID analyses also further highlighted the importance of transcription regulation,DNA binding and unfolded protein response,as well as cell death.Transcription regulation and DNA binding were significant terms common to both MSC and TSC at the 6 h time point,whereas no common terms existed for the two condensates at the 6 + 4 h time point.In our previous genotoxicity study we showed that MSC and TSC were both cytotoxic and genotoxic.However,quantitatively,MSC was more cytotoxic and mutagenic than TSC,and TSC appeared to induce chromosomal damage in a concentration-dependent manner whereas MSC did not.Our earlier chemical analyses of MSC and TSC noted that aside from the nicotine in tobacco and the cannabinoids in marijuana,the two smoke condensates contained mixtures of chemicals that were qualitatively similar though quantitatively different.The similarities in the chemical profiles and some of the toxicity findings suggested that the two smoke condensates might elicit somewhat comparable gene expression profiles.Hierarchal clustering of all the MSC and TSC exposed samples in the present study supported this notion and samples clustered first by concentration as opposed to smoke type.In addition,analysis of the top ten greatest gene expression changes relative to control revealed that half of the genes were common to both marijuana and tobacco.A number of previous studies have examined gene expression changes in pulmonary cells following exposure to tobacco smoke.Generally,these studies have shown that tobacco smoke stimulates xenobiotic metabolism,and that metabolized smoke constituents contribute to DNA damage.Following early insult,DNA damage leads to disruptions in the cell cycle such as arrest at the G2 checkpoint to allow time for response.Cellular response can include DNA repair,mutation induction through faulty repair or lack of repair,and programmed cell death of heavily damaged cells.

With the increase in production,advanced and standardized processing technologies,including drying,extraction and purification,are required to ensure the quality and safety of these products for food applications,as well as the processing efficiency and sustainability of hemp.Some terpenes,on the other hand,are considered generally regarded-as-safe substances,which are permitted to be added and have been used in foods.However,the incorporation of hemp terpenes in foods and preservation of terpenes during processing is still challenging,requiring further research.In recent years,many studies have been conducted to identify the functionalities and pharmaceutical values of hemp CBD and terpenes,as well as extraction technologies of CBD.However,there is currently not a comprehensive review that discusses the potential of hemp CBD and terpenes as future functional food ingredients and evaluates the available and potential processing technologies for hemp.Therefore,this article reviews the legal regulations,challenges in incorporating hemp CBD and terpenes in foods and potential solutions,as well as current research status and future prospects in processing technologies of hemp biomass.Through this review,we expect to draw a clearer image for food manufacturers and researchers on the potential of applying hemp CBD and terpenes as future functional food ingredients and provide information for standardizing and improving the processing technologies of hemp for efficient production of high quality and food-safe products.Future research needs are also identified in this article.In the hemp plant,cannabinoids mainly reside in the flowers and leaves.More specifically,they are primarily stored in the glandular and non-glandular epidermal appendages called trichomes,which are transparent glandular ‘hairs’ on the surface of inflorescence and leaves.

The cannabinoids are chemically bounded with the cell walls,secretory vesicles and fibrillar material in the secretory cavity of the disc cell.In this section,the physical properties and chemistry of CBD,cannabis growing system health benefits,potentials and associated challenges as future functional food ingredients are discussed.Chemically,cannabinoids are a type of molecules that contain terpenoids and alicyclic units.Currently,more than 120 types of cannabinoids have been found in hemp plants.Fig.3 shows the biosynthetic pathway of cannabinoids in hemp plant.The basic reaction in the cannabinoids synthesis involves the alkylation of the phenolic moiety of olivetolic acid with the terpenoid component of geranyl pyrophosphate ,which produces cannabigerolic acid ,the common precursor of all major cannabinoids in the hemp.CBGA can then convert into other cannabinoids such as tetrahydrocannabinolic acid ,cannabichromenic acid and cannabidiolic acid ,etc.,through the enzymatic catalytic reactions by THCA-synthase,CBCA-synthase and CBDA-synthase.It is worthy of mentioning that only the acidic cannabinoids exist naturally in hemp plants.According to their molecular structures,cannabinoids are non-polar,and thus have low solubility in aqueous solution.The boiling points of cannabinoids ranged from 157 °C to 220 °C,which is not volatile.However,CBD is thermally unstable and very sensitive to photolytic reaction and oxidation.The acidic form cannabinoids are not considered to be pharmacologically active since they do not affect the endocannabinoid system of human body in the same way as the neutral forms.Therefore,a decarboxylation process is usually needed to convert the CBDA to CBD,which involves the removal of a carboxyl group from the acidic molecule and the release of a CO2 under high temperature.The reaction mechanisms of the decarboxylation process are illustrated in Fig.3B.Recently,research has proven the functionalities of CBD,which include pain relief,reduction of anxiety/distress,nausea and promotion of relaxation.

In addition,since CBD is not psychoactive,it does not result in addictive effect as caused by THC.At present,there is an increasing prevalence of lifestyle induced chronic diseases,and consumers are pursuing healthier diets,seeking more functional foods reinforced with functional ingredients.Currently,the global health and wellness market is at $1.5 trillion,and is projected to increase annually at 5%–10%.In 2019,the global functional food market was $250 million,and was projected to $440 billion by 2022.Therefore,there is a high potential in this rising trend to add hemp CBD in foods or beverages as future functional food ingredients.However,there are several challenges that are limiting the development of CBD-containing foods,which involves legal regulations,consumer awareness,and technological deficiencies.Legal regulations and policies are one of the most important factors in directing the developments of markets and products.Currently,regulations on the hemp CBD varies country by country,and CBD is in the ‘grey zone’,of which the legality is not clearly defined.In the United States,the 2018 Farm Bill removed industrial hemp from the definition of marijuana,which allowed more research to be done on hemp.However,it is still prohibited in federal level to add CBD to any foods,beverages or nutrient supplements.FDA has not waived it from the illegal ingredients list due to safety concerns of the non-approved CBD products and the fact that CBD was first studied as a drug.In fact,in 2018,FDA approved the first and by far the only medicine containing CBD for the treatment of seizures associated with two rare and severe forms of epilepsy,Lennox-Gastaut syndrome and Dravet syndrome.Even though it is still not approved in federal level in the US,some food products are already in the markets in some states as they deregulated the CBD,such as tea,coffee and chocolate,etc..In Canada,cannabis is nationally legalized,but phyto-cannabinoids such as CBD is in the Prescription Drug List and cannot be legally sold in self-care natural health products or cosmetics.

Canadian Health Food Association has recently released a report,which emphasized the potential positive economic impacts of permitting CBD in NHPs,foods and beverages for the economic recovery.In Europe Union ,CBD was catalogued into ‘novel foods’ in January 2019,and the EU has required extensive testing and authorization of CBD products from food safety authorities.In addition,different countries have different standards in legalizing the THC level in the products.China was projected to be largest producer and consumer of hemp CBD,given the long cultivating traditional and production area,however,recently a national level regulation forbids any use of CBD in foods or cosmetics.The strict regulations have a significant impact on the development of the hemp industry,and the major food manufacturers are conservative in entering the CBD market.In fact,due to these strict regulations and the influence of pandemic on the global logistics,the hemp market and product development process have been significantly impacted.The hemp biomass and CBD are oversupplied in the market,and the price of CBD has hit the rock bottom in the first half of year 2021.The enthusiasm of farmers in cultivating hemp is cooling down.However,we envision that this ‘downturn’ could be temporary.With more research works done and more scientific evidence published proving the health benefits and safety of CBD,the regulations shall be more relaxed and standardized,which will be a strong booster for both the CBD-food market and in return benefit more related research to be conducted.In most cultures,the words ‘hemp’ and ‘cannabis’ are associated with ‘drugs’ and ‘illegal’,and thus are repelled.The word ‘CBD’ is still unfamiliar to most people in the world,not to mention its health benefits.Therefore,to promote the use of CBD as functional food ingredients,educating the consumers about the health benefits,safety,and its distinction from ‘drug’ is as important as the relaxing of legal regulations.At the same time,it is critical to find the right market position and target consumer groups.Currently,regular CBD consumers are buying CBD to obtain a functionality or health benefit,and usually taking it as a dietary supplement/medicine,which only represent a niche market.It is important to identify the types of foods that are compatible with CBD.Incorporating CBD into staple foods and beverages may potentially expand the consumer base,which is currently challenging and require more extensive research.The consumer needs for the CBD reinforced foods are another important factor to be considered in the product developments.For example,an afternoon pick-me-up ‘CBD-containing coffee’ or a sports drink need to be fast-responding,meanwhile it should not cause any adverse side effect to the human health.

Additionally,the food products need to be shelf-stable and maintain the activity of CBD under normal storage conditions,particularly given the fact that CBD is not a very stable substance.Besides the regulation and consumers aspects,there are currently some technological challenges that need to be resolved to add hemp CBD in foods and beverages.The types of products that can be reinforced with CBD are dependent on the physical and chemical properties of CBD.As discussed above,CBD is a highly non-polar molecule,meaning it has low aqueous solubility.Therefore,it is difficult to incorporate it into most aqueous-based food and beverage systems.Besides,recent studies have shown that the bio-accessibility of CBD is relatively poor in animal and human bodies,which may be due to the low cell penetration rate.In addition,CBD has relatively poor stability,which is affected by various factors such as temperature,humidity,pH,oxygen,light,and the solvent types,etc..Its instability suggests that CBD is vulnerable to deteriorate when it is inappropriately added to food systems or exposed under stress conditions.The oral ingestion of cannabinoids usually results in long lasting and slow effects,hydroponic rack system which is not desirable for the fast-responding needs,and is identified as an area of improvement.Currently,studies on the solubility and stability in various food and beverage systems are not well reported.The studies on the bioaccessbility of CBD in human body are also scarce.More extensive research in these aspects is urgently needed to address these challenges.The outcomes will provide scientific evidence to support the feasibility of adding CBD into foods and further prove their health benefits.Although the most of CBD-containing foods are considered illegal at present,the future can still be bright and optimistic.The 2018 Farm Bill of the U.S.opened the gate of industrial hemp to industries and researchers.Following that,more and more capital investments are putting into the hemp industry and scientific research.According to statistics,the global market size of hemp was $5.73 billion,and was expected to grow to $27.72 billion by 2028.This allows more universities and research institutions to conduct necessary research,which in return will be beneficial for the development of CBD-containing foods.Although current regulations prohibit the use of CBD as food ingredients,we envision that some regulations will ease up in the near future.This will depend on more scientific studies to be conducted and evidence that proves the health benefits and determines any side effects of CBD to human beings.In fact,United Nations has recently removed cannabis from its most rigid drug control list,the ‘Schedule IV of the 1961 Single Convention on Narcotic Drugs’,which was a huge win for the hemp industry.More organized and standardized regulations all over the world will also be helpful for the development of CBD-containing food products.In technological aspects,some studies have been conducted to improve the solubility,stability and bio-accessbility of CBD in medicine or food systems.Encapsulation,emulsification and microfluidization are being used to incorporate various bio-active compounds into food and beverage systems in the industry and offer potential solutions to the development of CBD-containing foods.

Micro-encapsulation is one possibility to improve the solubility and reduce the oxidative susceptibility of sensitive bio-active compounds,where the hydrophobic molecule is encapsulated and dispersed in aqueous phase.Feng et al.applied sesame oil as a delivery system for CBD in medicines and revealed that adding of medium-chain triglyceride improved the solubility of CBD and superior bio-availability.Lange and Schilderink found that micro-encapsulated CBD had higher CBD bio-accessibility compared to CBD-isolate without micro-encapsulation.Mozaffari et al.discovered that the CBD bio-accessbility was improved with the incorporation into a food system made of olive oil and baby food,which might be attributed to the improved efficiency of micelle forming from hydrolyzed lipids.Nanotechnology has already been applied in drug delivery systems and can be another promising solution.Durán-Lobato et al.developed cannabinoid-loaded lipid nanoparticles through solvent-emulsion evaporation and improved the stability of the products.With more relaxed regulations and more scientific research being conducted,it is envisioned that the technological challenges in the development of CBD edibles may be overcome in the future.Terpenes are another type of bio-active compounds and secondary metabolites found in hemp,which are gaining increasing interest in recent years.There are currently more than 120 terpenes already identified from hemp.The most distinct characteristic of terpenes is the smell,which depicts the unique aromatic characteristics of hemp plant and is used by the plant to repel and defense against herbivores,attract pollinators,and inhibit the microbial growth.Depending on the variety of hemp,the typical terpene contents in hemp range from 0.125% to 0.278% weight in leaves and 1.283% to 2.141% in the inflorescence on a dry basis.Although hemp is abundant in terpenes,it is not the only source.In fact,terpenes are found in lots of fruits,vegetables and herbs.Chemically,terpenes are hydrocarbons consisting of small isoprene units linked to one another to form chains.The biosynthetic pathway of terpenes is shown in Fig.4.Interestingly,terpenes and cannabinoids share a common precursor,which is the GPP,a 10-carbon molecule.As a result,the contents of terpenes and cannabinoids in the hemp are usually positively correlated.Monoterpenes are composed of two isoprenes such as pinene,limonene,myrcene etc..Sesquiterpenes consist of 3 isoprene units,such as humulene,farnesol and caryophyllene.More complex terpene molecules include triterpenes that are made of 6 isoprene units,and polyterpenes.As shown in Fig.4A,the monoterpenes and sesquiterpenes are the major terpene species found in the hemp.

The influence of the treatments with Na2CO3 and BTCA on the shives SHI-C and SHI-BTCA microstructure is clearly visible on the nano-CT scans.The removal of a part of the hemicelluloses in the case of sample SHI-C led to the partial deconstruction of the woody fibers cell wall,and general disorganization of the cells within the tissue,which is directly observed through the misorientation and waviness of the woody rays.The fiber walls were also strongly affected by grafting ,the woody rays degraded,the vessels distorted,and the tissues got fully disorganized as shown in Fig.3c.Indeed,the cellulose compartment seems the most affected,with a strong decrease,whereas the lignin content was increased,reflecting an enrichment effect.One can note that the pectin content is also higher in the BTCA sample,suggesting a selective chemical targeting of the treatment on cellulose polymers Fig.3.also shows EDX spectra of SHI-W,SHI-C,and SHI-BTCA samples before copper adsorption,highlighting the presence of sodium on the surface of hemp shives after Na2CO3 treatment and BTCA grafting.Fig.4 presents the X-ray nano-CT images and EDX spectra of the raw and modified hemp shives after copper adsorption.No significant effect of the exposition to copper on the shives’ microstructure can be detected but a major change in the EDX spectra can be observed.The data point out the presence of peaks that were not observed before the shives immersion in the copper salt solution,flood and drain tray which was assigned to copper.It is worthy to remind that EDX is a technique for surface characterization with limited penetration in matter thickness.

To better identify the spatial localization of the copper in the whole shives’ volume,a density-based segmentation of the 3D computed nanotomography images was done.The obtained images are proposed in Fig.5.The figures 5 b and d show the typical microstructure of hemp shives where the vessels are isolated or grouped by two or three,rarely by more,and then they deform one another.The vessels have a quite thin cell wall and a diameter of approximately 50 to 150 μm.They are surrounded by relatively thick-walled woody fibers with diameters of only a few μm and an irregularly polygonal section with a rounded cavity.It is evident that copper is adsorbed on all the free surfaces of the SHI-WCu sample,meaning shives external surface but also on the internal surface of the cells’ lumen.The situation is something different in the case of SHI-CCu shives where it is possible to observe that the copper is not only located on the internal surface of the cell wall bordering the lumen but also in the wall itself.This is attributed to the partial removal of the hemicelluloses in the cell wall induced by the treatment with sodium carbonate and by the micro- and nano-porosities created in the cell wall in which the aqueous solution can diffuse.Furthermore,the copper is massively adsorbed on the internal surface of the vessels’ wall bordering the lumen of the sample SHIBTCACu.The BTCA presence allowed more copper to be absorbed in these areas when compared to raw shives,which is in accordance with the results presented in Fig.1.The detailed analysis of EDX and nano-CT results showed that these two techniques were complementary in revealing the mechanism of copper adsorption on materials.In the EDX spectra ,we can observe an important decrease in the sodium peak and its replacement by copper cations,suggesting the presence of interaction by ion-exchange.In addition,some copper agglomerates are also observed in the internal part of the wall of some of the vessels,suggesting micro-precipitation during the adsorption onto the SHI-BTCA sample.So,the results point out that,even if the two treatments performed similarly in terms of copper removal,the spatial localization of copper and the adsorption mechanisms were significantly different.

FTIR and Raman spectroscopy were further used for the characterization of the shives before and after copper adsorption.The main IR and Raman absorption bands and their assignments according to the literature are summarized in Table 2 and Table 3,respectively.These bands were generally attributed to the three main shives components: cellulose,hemicelluloses,and lignin.The comparison of SHI-W and SHI-C samples shows an important difference in their IR spectra.Namely,the bands at 1730 cm− 1 and 1250 cm− 1 assigned to the stretching of unconjugated C=O groups present in hemicelluloses disappeared after the activation with sodium carbonate.This is in agreement with the data of the chemical composition and is also observed after the partial hemicellulose removal from jute fibers using alkaline treatment.When the FTIR spectrum of the SHI-BTCA sample was observed,the bands in the region 1500-1800 cm− 1 in particular those of the carboxyl and carboxylate groups ,are more intense than in the case of the two other samples which is ascribed to the esterification reaction.In addition,the comparison of SHI-W and SHI-BTCA samples also shows an important increase of the band at 1730 cm− 1 and a decrease of the band at 1250 cm− 1 corresponding to the elimination of hemicelluloses enhancing the lignin content in the material.The interpretation of Raman data indicated that the SHI-W and SHI-C spectra were similar with little differences in the intensity of the bands.On contrary,the Raman spectrum of the SHI-BTCA sample showed an important change in the intensity of the ester band at 1743 cm− 1.The comparison between the FTIR and Raman spectra before and after copper adsorption for the studied samples is shown in Fig.6.After copper adsorption,no changes were observed in the IR spectra of SHIWCu and SHI-CCu,while the spectrum of SHI-BTCACu showed an important change at 1590 cm− 1.Indeed,this band underwent a profound change in both intensity and width,and shifted to 1610 cm− 1.This data reflected the implication of the carboxylate groups on the copper removal through complexation and/or ion-exchange.By comparing the samples’ Raman spectra,we observed that the alkaline activation resulted in the disappearance of the ester band at 1743 cm− 1.The addition of copper contributed to obtain samples with a very high sensitivity to burning,resulting in spectra with enhanced background noise.

This is the reason why we had to work at 1% laser to avoid such noisy phenomena.However,it was difficult to explain the difference in the ratio between polysaccharides and lignin.In this case,we observed more lignin signals in samples containing copper.SHIBTCA gave very fluorescent samples,around 60,000 counts in comparison to 10,000 counts or less for SHI-C.For this sample,we also worked with a 1% laser both to avoid the detector’s ’ saturation and to burn the copper containing sample.The Raman spectrum for SHI-BTCACu also showed the involvement of the ester group in the removal of copper ions,confirming the presence of various interactions between them.Finally,the Raman spectra of samples after copper adsorption also revealed two bands at 1420 cm− 1 corresponding to carboxylate group and at 885 cm− 1 ,in agreement with IR data.Fig.7 compares the XPS wide-spectra of the SHI-W,SHI-C,and SHIBTCA samples before and after copper adsorption.The spectra obtained before copper adsorption are very similar showing the presence of oxygen and carbon C1s at their surfaces.Nevertheless,hydroponic tables canada the sample SHI-BTCA has an additional peak corresponding to the presence of sodium localized near the surface at 1072 eV.The presence of this element is due to the conversion of the carboxylic groups into a carboxylate by immersing the BTCA treated shives in a sodium hydrogen carbonate solution.The 1s level of carbon allows access to the different oxygen functions.The decomposition of level 1s of carbon is significantly different for sample SHI-BTCA with a strong decrease in C-O / C-OH bonds in favour of carboxylic functions.These results are in agreement with the data of the chemical composition.After copper adsorption,Fig.7 clearly indicates the disappearance of the sodium signal in the SHI-BTCA spectrum,due to the ion-exchange with copper cations.Fig.8 shows the main and satellite peaks of Cu 2p3/2 and Cu 2p1/2 after copper adsorption onto three studied samples,while Table 4 reports atomic concentrations of detected elements before and after adsorption.All three samples showed XPS peaks around 933 eV and 953 eV characteristic for Cu 2p3/2 and Cu 2p1/2,respectively.

The XPS analysis of the Cu 2p peaks showed that this element was not in the same oxidation state in all studied samples.Indeed,the detection of satellites on the 2p level of copper for the SHI-BTCACu sample makes it possible to deduce also the presence of copper at the oxidation number for 60%.These satellites are associated with the peak at 934.66 eV of the 2p3/2 level which corresponds to copper in the form of Cu2 [33].In the case of SHI-CCu and SHI-WCu,the detected copper was only in the I oxidation state.Indeed,there are no satellites,the 2p3/2 level showed only one component at about 933 eV.The measurement of the kinetic energy of the Auger transition of copper L3M45M45 at approximately 913.7 eV allowed us to calculate a modified Auger parameter value at 1846.7 eV close to the species Cu2O.This shows that the reactions involved in the removal of copper were different for each hemp sample.In order to know the rate of adsorbed copper on the surface,the atomic percentage of copper was calculated from the area of the Cu 2p peaks.SHI-BTCACu sample had the highest ratio Cu/C = 8.3,followed by SHI-CCu which ratio is 1.5.SHI-WCu sample had a very low Cu/C ratio of 0.4.These results agree with those obtained with other characterization techniques,notably on the fact that copper is well absorbed at the surface for SHI-BTCACu,which gives it this green colour.The less important Cu/C ratio for SHI-CCu confirms that,in this case,the mechanism of copper adsorption is different from those of SHI-BTCACu.Namely,the main interaction between copper and sodium carbonate activated shives is diffusion inside the particles.XANES spectroscopy provides quantitative insight into the oxidation states of copper present in materials.The XANES spectra of SHI-CCu and SHI-BTACCu display the same shape with a pre-edge at 8977.5 eV,the edge at 8991 eV,the maximum of the white line at 8996.5 eV,and a broad oscillation centered on 9052 eV.The absence of peak around 8983 eV,as found in Cu2O,shows that Cu was not detected and that Cu oxidation did not change during the Cu adsorption,it was kept as Cu.CuSO4,5H2O spectrum shows specific features such as a shoulder at 8990.0 eV and an oscillation at 9008.0 eV that are not present in hemp samples’ spectra.Moreover,the white line of CuSO4,5H2O spectra is slightly shifted toward lower energies and is more symmetric compared to that in hemp samples’ spectra.

These differences indicate that after adsorption onto hemp,Cu did not correspond to the crystalline form of CuSO4,5H2O.Furthermore,the hemp samples’ spectra are quite different from those of CuO and Cu2,corresponding to other Cu-bearing precipitates.The spectra of hemp samples are similar to the ones of Cu2+ measured in liquid phase; CuSO4 but also Cu2,another Cu complex,both when recorded in a liquid phase.The results obtained by XANES and those obtained by XPS or both Cu and Cu seems to differ.However,they are compatible and complementary as XANES at Cu K-edge sounded the bulk sample whereas XPS sounded the first atomic layers on the surface of the sample.XANES spectroscopy evidenced that most of the Cu atoms are present in Cu form in both SHI-CCu and SHI-BTCACu samples and XPS spectroscopy indicated that the external surfaces of SHI-WCu and SHI-CCu are coated by Cu2O and that the external surface of SHIBTCACu is coated by a mixture of Cu2O and Cu2,explaining this characteristic blue color.An increased interest in the acceptance of novel foods,that is,foods to which a consumer has not been previously exposed ,is borne of an increasing global population that should reach nine billion by the year 2050.Globalisation has resulted in increased exposure of the world’s population to foods from other cultures,and increased multicultural culinary experiences have altered normative perceptions for many.The increasing global population presents a challenge to food security as many traditional food production techniques will become environmentally unsustainable at the levels required to meet world food demands.Hemp foods might suitably address many food security issues.The hemp plant,Cannabis sativa,from which hemp foods are produced is environmentally sustainable due to a reported low water need and natural pest resistance ,can be economically lucrative with high yields and shorter growth cycles compared with many traditional crops ,and has many nutritional benefits.Nutritional benefits of hemp include being high in levels of plant protein,high in dietary fibre,a rich source of Omega 3 and 6,and contains all of the amino acids essential to human life.

Another benefit of hemp seeds is that they contain proteins that are rich in several essential amino acids including arginine and the sulfur-rich amino acids methionine and cysteine.Hemp contains other known beneficial and nutraceutical compounds but also some antinutrients including phytate and trypsin inhibitor that can impact on nutrient uptake especially of minerals and amino acids.However rat model studies confirm the high bio-availability of hemp proteins suggesting that the anti-nutrients may not be a major concern.A disadvantage of one of the earliest seed cultivars,FINOLA,is that the seed is about 50% smaller than other seed varieties.Comparisons between different lines are usually based on thousand seed weight.A recent comparison of 33 lines showed TSW ranged from approximately 7.5 g–23 g,with FINOLA at around 12 g,which is at the lower end of the expected range of 12–15 g for FINOLA.Seed size is not the only important consideration for seed varieties.A higher proportion of heart to hull tissue ,here called heart %,is desirable since it is the heart that attracts a higher value margin.A study of five hemp cultivars in Romania showed that heart % varied from 59.0% to 69.5%.However,current data on the heart % trait is limiting with very few published studies.Hemp hearts,also known as dehulled seed have more protein and more “digestible” fiber than whole seed and seed meal ,based on analysis of a “typical” variety.Interpretation of fiber data in food products can be difficult,due to the use of different terminology and methods.Scientific papers often report both neutral detergent fiber and acid detergent fiber ,where NDF includes cellulose,‘hemicellulose’,and lignin whereas ADF only includes cellulose and lignin,thus providing a measure of non-fermentable fiber.One disadvantage of NDF and ADF is that they underestimate the amount of total fiber,as the methods may not recover all of particular components such as pectins and gums,which can be some of the healthier fermentable fibers.However,this information is useful because it provides an indirect way to determine lignin content,trimming tray for weed and high levels of lignin can negatively affect palatability.

The nature of the non-cellulosic polysaccharides that contribute to dietary fiber in hemp has not yet been studied.One review suggests that hemp seed contain 25% starch,however the two cited references report soluble fiber and not starch.Since “detailed chemical characterization of dietary fiber is crucial to explain its effect on health” ,there is a clear knowledge gap of the nature of the polysaccharides in hemp lines grown for food.Different cell wall polysaccharides have remarkably different functional properties and these in turn influence fermentability,nutrient bio-availability and composition of gut microbes.The role of complex carbohydrates in microbiome diversity and human health is becoming clearer,and many positive effects relate to the fermentation products or short chain fatty acids such as butyrate,acetate and lactate.It has long been established that plant polysaccharides can differ in length of backbone,number and distribution of side branches and the form of each monosaccharide and pyranosyl and the linkages between them.Even within the same general class the structures can be markedly different.For example,heteroxylans from different species of Plantago have different proportions of unsubstituted xylan and linkages along the xylan backbone.It is now understood that microbes exist in cooperative metabolic networks where selected bacterial species initiate degradation and other species continue fermenting the partially degraded polysaccharides,thus supporting microbial biodiversity and a healthy colon.To fill the knowledge gap on the nature of hemp polysaccharides,we analyzed the composition of 20 different industrial hemp varieties and breeding lines that are currently available in Australia.We report analysis of 1000 seed weight,heart %,% nitrogen ,lipid profiles,lignin,phytate,and a detailed analysis of the carbohydrates in hemp heart and hull fractions including cellulose,starch,monosaccharide composition of complex carbohydrates,and soluble sugars.In addition,we use specific antibodies to investigate the distribution of plant polysaccharides in hull and heart fractions,thus providing critical information on the distribution of non-cellulosic polysaccharides in hemp seed.One hundred seed were counted out and weighed,then multiplied by 10 to provide 1000 seed weight.A single replicate of 100 seed was selected for further analysis.Hull and heart tissues were separated using a fine spatula and the separated fractions weighed.

Hull fractions were ground in a retsch mill for 30 s,and the softer heart fractions were ground in liquid nitrogen and air dried prior to analysis.These ground fractions were used for quantification of cellulose and soluble sugars and monosaccharide analysis ,lignin and starch.This research is the first detailed study of complex carbohydrates in hemp seed using a combination of chemical analysis and immunolabelling of tissue sections from a selected set of germplasm mainly sourced from Ecofibre’s seed bank.The focus of this study was on end-user/health traits where diversity of dietary complex carbohydrates is positively correlated with microbiome diversity and improved human health outcomes.The new findings on carbohydrate composition are combined with analysis of heart %,1000 seed weight,lipid composition,total protein,lignin and phytate,thus providing a foundation for selection of plant lines with improved human health attributes for expanding the hemp industry in Australia and internationally.Coefficient of variation % is a useful parameter for determining the characteristics that vary most between lines.Since the batches of seed used in this study were sourced from different regions of Australia,it is not possible to tell if the source of variation is from genotype or environment or an interaction of both.However,CV information is still useful for prioritising hemp lines for future field trials,and traits for subsequent analysis,and for identifying traits with a strong genetic component suitable for targeting in breeding programs.In the following discussion,we make the assumption that traits with a high CV have a strong genetic component,but obviously this will need to be tested in the future.There is some support for this assumption based on a hemp field trial from Canada that evaluated 11 cultivars over two years in seven different environments.Analysis of field trial data revealed that most of the traits evaluated had statistically significant genetic ,environment and G x E components,including seed protein,seed yield,plant height,biomass yield,biomass cellulose and biomass hemicellulose.

However,for the 11 varieties studied there was not a significant genetic component for biomass lignin and seed oil,but both had significant G x E components,and seed oil also had a significant environmental component.In our study,heart %,seed lignin and total lipids had a CV of <10% indicating low variability,whereas,many traits had intermediate CV ,including crystalline cellulose,hull monosaccharides ,non-resistant starch,phytate,the essential omega-3 fatty acid ALA.A few traits had high CV ,including 1000 seed weight,GLA,soluble sucrose and soluble raffinose.This information can be used to select a smaller number of appropriate lines for statistical validation of each desired trait,and used by breeders to select lines for future field trials to determine the extent of the genetic and environmental components of each trait.There is high variation in 1000 seed weight.Thousand seed weight provides an approximation of seed size,as generally the bigger the seed,the heavier it will be,although variation in the composition and ratio of heart % means that this correlation may not always hold.Furthermore,seed size does not usually correlate with overall seed yield which is key for profitability,since yield is heavily influenced by inflorescence architecture and shattering resistance.Higher heart % provides an opportunity to increase profitability,through increases in higher value hemp heart products.The heart % trait has not been widely reported for hemp,with only one published study to our knowledge,where heart % varied from 59.0% to 69.5%.Twelve of the 20 lines analyzed in this study had heart % greater than 59%.This does not guarantee that these lines are high yielding,profitable lines for current use,but rather they are potential lines for breeding,if the heart % trait has a strong genetic component.For other nuts,such as Macadamia,high heart % is called kernel recovery,and is known to be influenced by the genotype of the pollen donor.Kernel recovery in Macadamia is also sensitive to mild drought stress during nut development.To our knowledge there have not been any studies in C.sativa on what factors affect kernel recovery ,but we hypothesize that pollen donor and/or stress could be important,and should be explored in future to determine genotype by environment effects on this trait.Hemp hulls contain crystalline cellulose as the major polysaccharide ,with xylan as the next most abundant polysaccharide.The identification of xylan as a major complex carbohydrate in hemp hulls is based on monosaccharide analysis and immunolocalization analysis which demonstrates the polysaccharide is present as an unsubstituted xylan and not arabinoxylan.

The variability in hull xylose content is of significant interest to the food industry for adding value to agricultural wastes.Xylan is a source for the production of xylan oligosaccharides for prebiotics,which are non-digestible food ingredients that promote growth of bacteria in the colon and can improve health.Xylan oligosaccharides have been produced from peanut shells.The two hemp lines with the highest levels of xylose in their hulls,Frog-1 and Yunma-1 ,are likely to have higher levels of xylan than peanut shells,assuming that all the xylose is hemp is found in the xylan as suggested by immunolocalization.Hemp hulls and hearts are low in soluble sugars,with hemp hearts generally containing more soluble sugars than the hull fraction.The new data reported here is mostly consistent with a previous study that showed that sucrose was the most abundant soluble sugar.The major difference between the earlier study and this study is that they did not detect any raffinose in whole hemp seeds,whereas here raffinose was found in all 20 heart samples.This difference is puzzling since the 2018 study was able to detect raffinose in other food samples,weed trimming tray however it is not of great importance given the low levels <0.5% w/w observed in the 20 lines analyzed here.An important finding from the current study is that starch is not a major component of hemp seed,based on the trace levels of glucose in the polysaccharide fraction and <2% total starch in the six lines chosen for starch quantification.This contrasts with information in a recent review where the authors state that hemp seeds contain 25% starch.The results presented here show that the dietary fiber is not starch but predominantly xylan and pectin in hulls,with a small amount of xyloglucan and pectin in hemp hearts.This is important because it suggests that hemp will have a low glycemic index and contains a range of complex carbohydrates that could be fermented in the gut to varying degrees.This could be readily tested in future by including hemp as a protein source in human diets,because SCFAs,the products of gut fermentation,are readily detected in stools making them convenient biomarkers.Other studies adding whole seeds to human diet plans show that increases in SCFAs can be achieved in relatively short time frames.

The fate of the different cell wall polysaccharides is an area of active research,for example,xyloglucans from cranberry promote the growth of SCFA producing strains of Bifidobacterium longum.Furthermore a phenol-free xyloglucan derived oligosaccharide fraction from cranberry hulls reduces biofilm formation by strains of E.coli that cause urinary tract infections.Pectins are also substrates for gut bacteria,and although present in small amounts in hemp,they should contribute to microbiome diversity,especially as their fine-structure may be different to commonly consumed pectins such as citrus pectin.The fine-structure of the hemp carbohydrates remains to be determined,and xylan would be the obvious first target as it is the major noncellulosic polysaccharide in hemp.The hull should not be overlooked as a food source.It can be milled for example and used as a high-fiber ingredient,or better still,more emphasis could be placed on developing food products that use the whole seed.In addition to providing the best human health outcomes,use of whole seeds may have the benefit of reducing manufacturing costs and waste products generated through the dehulling process.Whole seed products would also contain lignin ,which can be perceived as a negative component.However,rather than being an inert compound,lignin is now thought to contain beneficial antioxidant activity.The mean value of lignin in hemp hulls observed in this current study was 17.6  1.0 ,which is higher than a prior study that reported a mean value of 11.2.However,the values are comparable given that our study used hemp hulls,not whole seed.The other major components of hemp hearts are proteins and lipids.The study conducted by House et al.,used a rat bio-assay to calculate protein digestibility-corrected amino acid score measurements.Importantly they showed that hemp protein had PDCAAS value equal to or greater than certain grains,nuts,and some pulses.specifically whole hemp seeds have a higher PDCAAS value than almonds and whole wheat,and hemp hearts have a higher score than lentils,pinto beans and rolled oats.