Types and Brands of Derived Psychoactive Cannabis Products: An Online Retail Assessment, 2023.

Background: The 2018 Farm Bill led to new types of derived psychoactive cannabis products (DPCPs) being sold throughout the United States. This study describes the new types and brands of DPCPs sold online. Materials and Methods: In May 2023, data were recorded from three top-trafficked U.S.-based DPCP retail websites, including information about each product (N=804). Results: DPCP modalities included disposable vapes (43%), edibles (29%), vape carts (18%), pre-rolls (7%), flower (2%), dabs (1%), and vape pods (<1%). Among the 118 brands, the most common were Exhale, Delta Extrax, Cake, URB, Looper, and TRE House. There were 26 different intoxicating compounds overall, the most prevalent being: Delta-8 tetrahydrocannabinol (THC), THC-P, Delta-9 THC, HHC, THC-A, Delta-10 THC, THC-H, THC-B, THC-JD, THC-X, HHC-P, and Delta-11 THC. Overall, 54% of products were blends, containing two to eight different intoxicating compounds in a single product. Discussion: This is the first study to systematically assess DPCPs sold online. Most of the DPCP market is comprised of vapes and edibles, but these products contain a wide array of compounds and blends. Data from this diverse, rapidly evolving market are needed to examine its consumer impact and inform public health policies and programs.

An end-to-end workflow for engineering of biological networks from high-level specifications.

We present a workflow for the design and production of biological networks from high-level program specifications. The workflow is based on a sequence of intermediate models that incrementally translate high-level specifications into DNA samples that implement them. We identify algorithms for translating between adjacent models and implement them as a set of software tools, organized into a four-stage toolchain: Specification, Compilation, Part Assignment, and Assembly. The specification stage begins with a Boolean logic computation specified in the Proto programming language. The compilation stage uses a library of network motifs and cellular platforms, also specified in Proto, to transform the program into an optimized Abstract Genetic Regulatory Network (AGRN) that implements the programmed behavior. The part assignment stage assigns DNA parts to the AGRN, drawing the parts from a database for the target cellular platform, to create a DNA sequence implementing the AGRN. Finally, the assembly stage computes an optimized assembly plan to create the DNA sequence from available part samples, yielding a protocol for producing a sample of engineered plasmids with robotics assistance. Our workflow is the first to automate the production of biological networks from a high-level program specification. Furthermore, the workflow's modular design allows the same program to be realized on different cellular platforms simply by swapping workflow configurations. We validated our workflow by specifying a small-molecule sensor-reporter program and verifying the resulting plasmids in both HEK 293 mammalian cells and in E. coli bacterial cells.