17 research outputs found

    Regulation of Cell Surface CB2 Receptor during Human B Cell Activation and Differentiation.

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    Cannabinoid receptor type 2 (CB2) is the primary receptor pathway mediating the immunologic consequences of cannabinoids. We recently reported that human peripheral blood B cells express CB2 on both the extracellular membrane and at intracellular sites, where-as monocytes and T cells only express intracellular CB2. To better understand the pattern of CB2 expression by human B cells, we examined CD20+ B cells from three tissue sources. Both surface and intracellular expression were present and uniform in cord blood B cells, where all cells exhibited a naïve mature phenotype (IgD+/CD38Dim). While naïve mature and quiescent memory B cells (IgD-/CD38-) from tonsils and peripheral blood exhibited a similar pattern, tonsillar activated B cells (IgD-/CD38+) expressed little to no surface CB2. We hypothesized that regulation of the surface CB2 receptor may occur during B cell activation. Consistent with this, a B cell lymphoma cell line known to exhibit an activated phenotype (SUDHL-4) was found to lack cell surface CB2 but express intracellular CB2. Furthermore, in vitro activation of human cord blood resulted in a down-regulation of surface CB2 on those B cells acquiring the activated phenotype but not on those retaining IgD expression. Using a CB2 expressing cell line (293 T/CB2-GFP), confocal microscopy confirmed the presence of both cell surface expression and multifocal intracellular expression, the latter of which co-localized with endoplasmic reticulum but not with mitochondria, lysosomes, or nucleus. Our findings suggest a dynamic multi-compartment expression pattern for CB2 in B cells that is specifically modulated during the course of B cell activation

    Many Labs 2: Investigating Variation in Replicability Across Sample and Setting

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    We conducted preregistered replications of 28 classic and contemporary published findings with protocols that were peer reviewed in advance to examine variation in effect magnitudes across sample and setting. Each protocol was administered to approximately half of 125 samples and 15,305 total participants from 36 countries and territories. Using conventional statistical significance (p < .05), fifteen (54%) of the replications provided evidence in the same direction and statistically significant as the original finding. With a strict significance criterion (p < .0001), fourteen (50%) provide such evidence reflecting the extremely high powered design. Seven (25%) of the replications had effect sizes larger than the original finding and 21 (75%) had effect sizes smaller than the original finding. The median comparable Cohen’s d effect sizes for original findings was 0.60 and for replications was 0.15. Sixteen replications (57%) had small effect sizes (< .20) and 9 (32%) were in the opposite direction from the original finding. Across settings, 11 (39%) showed significant heterogeneity using the Q statistic and most of those were among the findings eliciting the largest overall effect sizes; only one effect that was near zero in the aggregate showed significant heterogeneity. Only one effect showed a Tau > 0.20 indicating moderate heterogeneity. Nine others had a Tau near or slightly above 0.10 indicating slight heterogeneity. In moderation tests, very little heterogeneity was attributable to task order, administration in lab versus online, and exploratory WEIRD versus less WEIRD culture comparisons. Cumulatively, variability in observed effect sizes was more attributable to the effect being studied than the sample or setting in which it was studied

    Data and Results (per site, etc.)

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    Data from Many Labs 2 Replication Projec

    Codebooks and Study Files

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    See the "Wiki" for more details

    Materials for Individual Studies

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    Videos Documenting Data Collection

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    Many Labs 2: Investigating Variation in Replicability Across Sample and Setting

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    We employ an expanded version of the Many Labs paradigm to investigate 28 new effects and further examine the findings from Many Labs 1

    Analysis Scripts

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    Integration of questionnaire-based risk factors improves polygenic risk scores for human coronary heart disease and type 2 diabetes

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