Abstract: A device may identify standard parameters and real-time parameters associated with content of a content type, and may process the content type, the standard parameters, and the real-time parameters, with a parameter unification model, to generate derived parameters for the content. The device may process the derived parameters and the content type, with a multi-level linear regression machine learning model, to calculate a content score for the content, and may process the derived parameters and the content score, with a linear regression machine learning model, to calculate a quantity of f-NFTs to generate for the content and a divestment ratio. The device may create a unique reference to the content, and may create an NFT for the content based on the unique reference. The device may generate the quantity of f-NFTs for the content based on the NFT, and may provide the quantity of f-NFTs to a content exchange.

Abstract: The present invention relates to methods of separating polypeptides of interest from contaminants, including DNA and undesired polypeptides, in a common fluid by precipitation of the polypeptides of interest or, alternatively, the contaminants using the combination of steric exclusion agents and charge neutralization agents.

Abstract: The present invention is a process for separating a target protein (such as a recombinant protein produced in a cell culture) from a mixture containing the target protein and contaminants (such as cell culture contaminants), by contacting the mixture with a hydrophobic adsorbent comprising branched hydrocarbon functional groups in an aqueous salt solution and collecting the unbound flow-through fraction containing the target protein. In one embodiment, the hydrophobic adsorbent may be a branched alkyl functional group. In another embodiment, the branched alkyl functional group has from 3 to 8 carbon atoms. In another embodiment, the branched alkyl functional group is a tertiary carbon atom, such as tert-butyl.