The simplest hypothesis being that B cell activation is associated with a down-regulation of the surface CB2 receptor. Alternatively, it has been reported that CB2 can form heterodimers with the CXCR4 chemokine receptor and has chemotactic properties that result in the selective homing of CB2 + and CB2 – B cells to different regions of lymphoid follicles [Basu 2013, Coke 2016]. We addressed the potential linkage between B cell activation and CB2 expression using two different approaches. CB2 is known to be expressed by B cell lymphomas and has been described as an oncogene [Jorda 2003, Perez-Gomez 2015]. We therefore examined a human B cell lymphoma cell line, SUDHL-4, that had been described to express an activated B cell phenotype. Consistent with a linkage between activation state and CB2 expression pattern, this cell line and two other lymphoma lines that exhibited an “activated” phenotype were found to exhibit high intracellular CB2 but no surface staining. In order to more directly test the linkage between B cell activation and CB2 expression pattern, we employed an in vitro model in which naïve mature human B cells obtained from umbilical vein cord blood were activated with a combination of receptor signaling and supporting cytokines [Ettinger 2005]. After 5 days in culture, the initial homogeneous population of naïve B cells had evolved into two obvious subsets: one that retained the naïve B cell phenotype and the other that exhibited an activated B cell phenotype . When examined for the expression of CB2, there was a clear distinction between these two subsets with a loss of extracellular CB2 only on the activated subset. Collectively,microgreen grow rack the evidence presented in this report points to a clear linkage between the acquisition of an “activated” B cell phenotype and specific regulation of CB2 protein expression.

With limited information regarding the nature of intracellular CB2, we employed a combination of confocal microscopy and marker co-localization studies to evaluate the distribution and location of intracellular CB2. It exhibited a diffuse but punctate pattern within the cytoplasm. This appearance was the same regardless of the type of cells studied – primary peripheral blood B cells, the SUDHL-4 cell line, or the 293T/CB2-GFP line that we had previously described [Castaneda 2013]. Using the 293T/CB2-GFP line, we compared the distribution of CB2 staining to the staining of mitochondrial and lysosomal markers. The sparse and well defined features of lysosomal staining did not match and were not pursued further. On the other hand, the punctate but diffuse pattern of mitochondrial staining shared some similarities to the pattern observed with CB2. This represented an interesting observation given our prior findings that THC can disrupt cell energetics and mitochondrial transmembrane potential in airway epithelial cells in a CB2- dependent manner [Sarafian 2008]. Along the same lines, Bernard and associates identified a similar effect on neuronal cells but ascribed this effect to intracellular CB1, which localized to mitochondria in their studies. However, there was no obvious co-localization between the CB2 receptor and mitochondrial markers when directly examined by dual staining and confocal microscopy. In summary, we can conclude that the expression of CB2 in human leukocytes appears to be specifically regulated with respect to the cellular location , the cell lineage being studied , and the state of B cell activation and differentiation . The presence of an activated phenotype on B cells is specifically associated with down-regulation of the surface CB2 receptor, a feature identified in B cells recovered from human tonsils and also observed in vitro when naïve B cells were stimulated to acquire an activated phenotype. Given the capacity for cell surface CB2 to form heterodimers with chemokine receptors and promote migration and homing and given the location of CB2 + and CB2 – B cells in different compartments within lymphoid follicles [Basu 2013, Coke 2016], it is possible that modulating surface CB2 during B cell activation plays an important role in trafficking.

The capacity for T cells, dendritic cells, and malignant B cells to respond to cannabinoids in a CB2-dependent manner has been well characterized [McKallip 2002, Roth 2015, Yuan 2002], yet these cells do not express CB2 on the cell surface. The logical conclusion is that intracellular CB2 must also be capable of mediating ligand-induced signaling and biological consequences. With the recent report byBrailoiu et al , there is now direct evidence for this. Given the high membrane solubility of cannabinoids, we hypothesize that the presence of CB2 at different locations within a cell provides a mechanism for cells to link receptor activation to different signaling and biologic consequences, resulting in an expanded functional heterogeneity of cannabinoids. The intracellular location of CB2 and the specific role of different receptors on biologic function remains to be determined but will likely be very informative in understanding cannabinoid biology. Adolescence is a time of subtle, yet dynamic brain changes that occur in the context of major physiological, psychological, and social transitions. This juncture marks a gradual shift from guided to independent functioning that is analogized in the protracted development of brain structure. Growth of the prefrontal cortex, limbic system structures, and white matter association fibers during this period are linked with more sophisticated cognitive functions and emotional processing, useful for navigating an increasingly complex psychosocial environment. Despite these developmental advances, increased tendencies toward risk-taking and heightened vulnerability to psychopathology are well known within the adolescent milieu. Owing in large part to progress and innovation in neuroimaging techniques, appreciable levels of new information on adolescent neurodevelopment are breaking ground. The potential of these methods to identify biomarkers for substance problems and targets for addiction treatment in youth are of significant value when considering the rise in adolescent alcohol and drug use and decline in perceived risk of substance exposure . What are the unique characteristics of the adolescent brain?

What neural and behavioral profiles render youth at heightened risk for substance use problems, and are neurocognitive consequences to early substance use observable? Recent efforts have explored these questions and brought us to a fuller understanding of adolescent health and interventional needs. This paper will review neurodevelopmental processes during adolescence, discuss theinfluence of substance use on neuromaturation as well as probable mechanisms by which these substances influence neural development, and briefly summarize factors that may enhance risk-taking tendencies. Finally, we will conclude with suggestions for future research directions.The developmental trajectory of grey matter follows an inverted parabolic curve, with cortical volume peaking, on average, around ages 12–14, followed by a decline in volume and thickness over adolescence . Widespread supratentorial diminutions are evident, but show temporal variance across regions . Declines begin in the striatum and sensorimotor cortices , progress rostrally to the frontal poles, then end with the dorsolateral prefrontal cortex , which is also late to myelinate . Longitudinal charting of brain volumetry from 13–22 years of age reveals specific declines in medial parietal cortex, posterior temporal and middle frontal gyri, and the cerebellum in the right hemisphere, coinciding with previous studies showing these regions to develop late into adolescence . Examination of developmental changes in cortical thickness from 8–30 years of age indicates a similar pattern of nonlinear declines, with marked thinning during adolescence. Attenuations are most notable in the parietal lobe,ebb and flow flood table and followed in effect size by medial and superior frontal regions, the cingulum, and occipital lobe . The mechanisms underlying cortical volume and thickness decline are suggested to involve selective synaptic pruning of superfluous neuronal connections, reduction in glial cells, decrease in neuropil and intra-cortical myelination . Regional variations in grey matter maturation may coincide with different patterns of cortical development, with allocortex, including the piriform area, showing primarily linear growth patterns, compared to transition cortex demonstrating a combination of linear and quadratic trajectories, and isocortex demonstrating cubic growth curves . Though the functional implications of these developmental trajectories are unclear, isocortical regions undergo more protracted development and support complex behavioral functions. Their growth curves may reflect critical periods for development of cognitive skills as well as windows of vulnerability for neurotoxic exposure or other developmental perturbations.In contrast to grey matter reductions, white matter across the adolescent years shows growth and enhancement of pathways . This is reflected in white matter volume increase, particularly in fronto-parietal regions .

Diffusion tensor imaging , a neuroimaging technique that has gained widespread use over the past decade, relies on the intrinsic diffusion properties of water molecules and has afforded a view into the more subtle micro-structural changes that occur in white matter architecture. Two common scalar variables derived from DTI are fractional anisotropy , which describes the directional variance of diffusional motion, and mean diffusivity , an indicator of the overall magnitude of diffusional motion. These measures index relationships between signal intensity changes and underlying tissue structure, and provide descriptions of white matter quality and architecture . High FA reflects greater fiber organization and coherence, myelination and/or other structural components of the axon, and low MD values suggest greater white matter density .These trends continue through early adulthood in a nearly linear manner , though recent data suggest an exponential pattern of anisotropic increase that may plateau during the late-teens to early twenties . Areas with the most prominent FA change during adolescence are the superior longitudinal fasciculus, superior corona radiata, thalamic radiations, and posterior limb of the internal capsule . Other projection and association pathways including the corticospinal tract, arcuate fasciculus, cingulum, corpus callosum, superior and mid-temporal white matter, and inferior parietal white matter show anisotropic increases as well . Changes in sub-cortical and deep grey matter fibers are more pronounced, with less change in compact white matter tracts comprising highly parallel fibers such as the internal capsule and corpus callosum . Fiber tracts constituting the fronto-temporal pathways appear to mature relatively later , though comparison of growth rates among tracts comes largely from cross-sectional data that present developmental trends. The neurobiological mechanisms contributing to FA increases and MD decreases during adolescence are not entirely understood, but examination of underlying diffusion dynamics point to some probable processes. For example, decreases in radial diffusivity , diffusion that occurs perpendicular to white matter pathways, suggests increased myelination, axonal density, and fiber compactness , but have not been uniformly observed to occur during adolescence. Similarly, changes in axial diffusivity , diffusion parallel to the fibers’ principle axis, show discrepant trends, with some studies documenting decreases , and others increases in this index . Decreases in AD may be attributable to developing axon collaterals, whereas increases may reflect growth in axon diameter, processes which are both likely to occur during adolescence. Technical and demographic differences such as imaging parameters, inter-scan intervals, age range, and gender ratios may account for divergent findings. Both grey matter volume decreases and FA increases in frontoparietal regions occur well into adolescence, suggesting a close spatiotemporal relationship . Changes in tissue morphometry are attributable to synaptic proliferation and pruning as well as myelination. Diminutions in gray matter density and concomitant brain growth in dorsal parietal and frontal regions suggest an interplay between regressive and progressive changes , and the coupling of these neurobiological processes is associated with increasingly economical neural activity .The increasing divergences in male and female physiology during adolescence are observed in sex-based differentiation of brain structure. Male children and adolescents show larger overall brain volumes , and proportionally larger amygdala and globus pallidus sizes, while females demonstrate larger caudate nuclei and cingulate gyrus volumes . Although cortical and sub-cortical grey matter volumes typically peak 1–2 years earlier in females than males , male children and adolescents show more prominent grey matter reductions and white matter volume increases with age than do females . The marked increase in white matter that occurs during adolescence is most prominent in the frontal lobe for both genders , though male children and adolescents have significantly larger volumes of white matter surrounding the lateral ventricles and caudate nuclei than females . Adolescent males also demonstrate a significantly higher rate of change in white matter volume particularly in the occipital lobe . Despite steeper white matter volume changes in males, maturation of white matter micro-structure may occur earlier in female than male adolescents .