Discovery of cancer immunogenic chemotherapeutics represents an emerging, highly promising direction for cancer treatment that uses a chemical drug to achieve the efficacy of both chemotherapy and immunotherapy. Herein, we report a high-throughput screening platform and the subsequent discovery of a new class of cancer immunogenic chemotherapeutic leads. Our platform integrates informatics-based activity metabolomics for the rapid identification of microbial natural products with both novel structures and potent activities.
View Article and Find Full Text PDFDiscovery of cancer immunogenic chemotherapeutics represents an emerging, highly promising direction for cancer treatment that uses a chemical drug to achieve the efficacy of both chemotherapy and immunotherapy. Herein we report a high-throughput screening platform and the subsequent discovery of a new class of cancer immunogenic chemotherapeutic leads. Our platform integrates informatics-based activity metabolomics for rapid identification of microbial natural products with both novel structures and potent activities.
View Article and Find Full Text PDFThe generalizability of machine learning (ML) models for wearable monitoring in stroke rehabilitation is often constrained by the limited scale and heterogeneity of available data. Data augmentation addresses this challenge by adding computationally derived data to real data to enrich the variability represented in the training set. Traditional augmentation methods, such as rotation, permutation, and time-warping, have shown some benefits in improving classifier performance, but often fail to produce realistic training examples.
View Article and Find Full Text PDFLife's organic molecules are built with diverse functional groups that enable biology by fine tuning intimate connections through time and space. As such, the discovery of new-to-nature functional groups can expand our understanding of the natural world and motivate new applications in biotechnology and biomedicine. Herein we report the genome-aided discovery of sulfenicin, a novel polyketide-nonribosomal peptide hybrid natural product from a marine bacterium bearing a unique acylsulfenic acid functionality.
View Article and Find Full Text PDFLasso peptides are an increasingly relevant class of peptide natural products with diverse biological activities, intriguing physical properties, and unique chemical structures. Most characterized lasso peptides have been from Actinobacteria and Proteobacteria, despite bioinformatic analyses suggesting that other bacterial taxa, particularly those from Firmicutes, are rich in biosynthetic gene clusters (BGCs) encoding lasso peptides. Herein, we report the bioinformatic identification of a lasso peptide BGC from Paenibacillus taiwanensis DSM18679 which we termed pats.
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