Electrospun fibers have gained considerable attention in drug controlled release, biological dressings, tissue repair and enzyme immobilization fields.

Natural products (NPs) have historically played a primary role in the discovery of small-molecule drugs. However, due to the advent of other methodologies and the drawbacks of NPs, the pharmaceutical industry has largely declined in interest regarding the screening of new drugs from NPs since 2000. There are many technical bottlenecks to quickly obtaining new bioactive NPs on a large scale, which has made NP-based drug discovery very time-consuming, and the first thorny problem faced by researchers is how to dereplicate NPs from crude extracts. Remarkably, with the rapid development of omics, analytical instrumentation, and artificial intelligence technology, in 2012, an efficient approach, known as tandem mass spectrometry (MS/MS)-based molecular networking (MN) analysis, was developed to avoid the rediscovery of known compounds from the complex natural mixtures. Then, in the past decade, based on the classical MN (CLMN), feature-based MN (FBMN), ion identity MN (IIMN), building blocks-based molecular network (BBMN), substructure-based MN (MS2LDA), and bioactivity-based MN (BMN) methods have been presented. In this paper, we review the basic principles, general workflow, and application examples of the methods mentioned above, to further the research and applications of these methods.

Nitroreductases (NTRs) are known to be able to metabolize nitro-substituted compounds in the presence of reduced nicotinamide adenine dinucleotide (NADH) as an electron donor. NTRs are present in a wide range of bacterial genera and, to a lesser extent, in eukaryotes hypoxic tumour cells and tumorous tissues, which makes it an appropriate biomarker for an imaging target to detect the hypoxic status of cancer cells and potential bacterial infections. To evaluate the specific activation level of NTR, great efforts have been devoted to the development of fluorescent probes to detect NTR activities using fluorogenic methods to probe its behaviour in a cellular context; however, NTR-responsive MRI contrast agents are still by far underexplored. In this study, para-nitrobenzyl substituted T1-weighted magnetic resonance imaging (MRI) contrast agent Gd-DOTA-PNB (probe 1) has been designed and explored for the possible detection of NTR. Our experimental results show that probe 1 could serve as an MRI-enhanced contrast agent for monitoring NTR activity. The in vitro response and mechanism of the NTR catalysed reduction of probe 1 have been investigated through LC-MS and MRI. Para-nitrobenzyl substituted probe 1 was catalytically reduced by NTR to the intermediate para-aminobenzyl substituted probe which then underwent a rearrangement elimination reaction to Gd-DOTA, generating the enhanced T1-weighted MR imaging. Further, LC-MS and MRI studies of living Escherichia coli have confirmed the NTR activity detection ability of probe 1 at a cellular level. This method may potentially be used for the diagnosis of bacterial infections.

Boronic acids have been widely developed as fluorescent sensors for recognition of carbohydrates, especially D-glucose, ions, catechol compounds and so on. However, few D-ribose selective boronic acid sensors have been reported, and their poor water solubility brings a lot of inconvenience to their applications. Herein we report a novel water-soluble sensor, (4-(4-((3-boronobenzamido)propyl)carbamoyl)quinolin-2-yl)boronic acid (sensor 6). The fluorescence of sensor 6 decreased by 50% when combined with 0.0146 M of D-ribose, while it increased when combined with D-mannose, D-galactose, D-fructose, D-glucosamine, sialic acid, D-sorbitol and D-arabinose, and fluorescence change was not obvious after binding to D-glucose. Therefore, this sensor may serve as a fluorescence quenching sensor for D-ribose. By processing the fluorescence binding data using the Benesi–Hildebrand equation, we found that the reciprocal of fluorescence intensity quenching showed a good linear relationship with the reciprocal of D-ribose concentration, indicating that the binding ratio of sensor 6 to D-ribose is 1 : 1. In pH titration experiments, the quenched fluorescence was most pronounced at pH 7.4, indicating that the sensor may serve to recognize D-ribose at physiological pH 7.4. Subsequently, D-ribose can also cause sensor fluorescence quenching in rabbit plasma and the rabbit plasma fluorescence interference can be excluded. These studies indicate that sensor 6 is a promising tool for detecting D-ribose.