摘要:
New peptide-based Gemini compounds comprising two linked chains (a) each having: (1) a positively charged hydrophilic head, Q1 or Q2 formed from one or more amino acids and/or amines, (2) a central portion, P1 or P2, having a polypeptide backbone, and (3) a hydrophobic tail, R1 or R2, the central sections of each chain being linked together by bridge Y through residues in P1 and P2, are disclosed. Methods for their preparation and uses are also disclosed. Such uses include transfection of polynucleotides into cells in vivo.
摘要:
Spermine:peptide-based surfactant compounds are disclosed. The compounds are based on a spermine backbone with peptide groups and optionally hydrocarbyl groups linked thereto. Uses of the spermine:peptide-based surfactant compounds and methods for their production are also disclosed.
摘要:
The use of carbohydrate-based surfactant compounds having the general formula (I): wherein Y1 and Y2, which may be the same or different, are carbohydrate groups; R1 and R2, which may be the same or different, are selected from: a) hydrogen; b) C(1-24) alkyl group; c) C(1-24) alkyl carboxy group; or d) a carbon chain of 2 to 24 carbon atoms having one or more carbon/carbon double bonds, and n is from 1 to 10; for facilitating the transfer of DNA or RNA polynucleotides, or analogs thereof, into a eukaryotic or prokaryotic cell in vivo or in vitro. New carbohydrate-based surfactant compounds are also disclosed.
摘要:
Spermine:peptide-based surfactant compounds are disclosed. The compounds are based on a spermine backbone with peptide groups and optionally hydrocarbyl groups linked thereto. Uses of the spermine:peptide-based surfactant compounds and methods for their production are also disclosed.
摘要:
A system operating in a plurality of modes to provide an integrated analysis of molecular data, imaging data, and clinical data associated with a patient includes a multi-scale model, a molecular model, and a linking component. The multi-scale model is configured to generate one or more estimated multi-scale parameters based on the clinical data and the imaging data when the system operates in a first mode, and generate a model of organ functionality based on one or more inferred multi-scale parameters when the system operates in a second mode. The molecular model is configured to generate one or more first molecular findings based on a molecular network analysis of the molecular data, wherein the molecular model is constrained by the estimated parameters when the system operates in the first mode. The linking component, which is operably coupled to the multi-scale model and the molecular model, is configured to transfer the estimated multi-scale parameters from the multi-scale model to the molecular model when the system operates in the first mode, and generate, using a machine learning process, the inferred multi-scale parameters based on the molecular findings when the system operates in the second mode.
摘要:
A system operating in a plurality of modes to provide an integrated analysis of molecular data, imaging data, and clinical data associated with a patient includes a multi-scale model, a molecular model, and a linking component. The multi-scale model is configured to generate one or more estimated multi-scale parameters based on the clinical data and the imaging data when the system operates in a first mode, and generate a model of organ functionality based on one or more inferred multi-scale parameters when the system operates in a second mode. The molecular model is configured to generate one or more first molecular findings based on a molecular network analysis of the molecular data, wherein the molecular model is constrained by the estimated parameters when the system operates in the first mode. The linking component, which is operably coupled to the multi-scale model and the molecular model, is configured to transfer the estimated multi-scale parameters from the multi-scale model to the molecular model when the system operates in the first mode, and generate, using a machine learning process, the inferred multi-scale parameters based on the molecular findings when the system operates in the second mode.