Identification of milk adulteration by a sensor array based on cationic polymer induced aggregation of a perylene probe

Carbon quantum dot-induced developmental toxicity in Daphnia magna involves disturbance of symbiotic microorganisms

With the increasing synthesis and application of carbon quantum dots (CQDs), their prevalence as pollution in water environments has increased. However, the toxic effects of CQDs on aquatic organisms are unclear, and their environmental safety must be evaluated. Herein, Daphnia magna was used as a model organism to explore the developmental toxicity of CQDs under a full life-cycle exposure. It was found that the feeding rate and offing number of D. magna decreased with increasing CQD concentration, and the body length of D. magna showed a trend of first increasing and then decreasing. These results indicated that long-term exposure to CQDs has evident toxic effects on D. magna development. Symbiosis analysis showed that the composition of the symbiotic microbial community of D. magna was disturbed by CQDs. The abundance of microorganisms involved in the immune response of D. magna such as Rhodobacter, decreased; those involved in the inflammation such as Gemmobacter, increased; and those involved in the nitrogen cycle, such as Hydrogenophaga and Paracoccus, decreased. When D. magna was subjected to environmental pressure, host-microflora interactive immune regulation was induced. The abundance of probiotics in D. magna, such as Rhodococcus, increased in response to environmental pressure. The results of KEGG function prediction showed that the abundance of symbiotic microorganisms involved in energy absorption and metabolism was affected by CQDs. In addition, the correlation analysis showed that there was a correlation between the changes in the symbiotic microbial community and the damage to D. magna after exposure to CQDs. Thus, it is appealed that as a potential environmental pollutant, CQDs have aquatic environmental risks, and their safe application deserves attention.

Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications

The traditional sensors are designed based on the "lock-and-key" strategy with high selectivity and specificity for detecting specific analytes, which however are not suitable for detecting multiple analytes simultaneously. With the help of pattern recognition technologies, the sensor arrays excel in distinguishing subtle changes caused by multitarget analytes with similar structures in a complex system. To construct a sensor array, the multiple sensing elements are undoubtedly indispensable units that will selectively interact with targets to generate the unique "fingerprints" based on the distinct responses, enabling the identification among various analytes through pattern recognition methods. This comprehensive review mainly focuses on the construction strategies and principles of sensing elements, as well as the applications of sensor array for identification and detection of target analytes in a wide range of fields. Furthermore, the present challenges and further perspectives of sensor arrays are discussed in detail.

Comprehensive quantitation of multi-signature peptides originating from casein for the discrimination of milk from eight different animal species using LC-HRMS with stable isotope labeled peptides

Milk species adulteration has become an altering issue worldwide. In this study, a robust quantification method based on LC-HRMS for the simultaneous detection and differentiation of milk type from eight different animal species (namely: cow, water buffalo, wild yak, goat, sheep, donkey, horse, and camel) was established by detecting nine signature peptides originating from casein. The developed method was in-house validated in terms of sensitivity, accuracy, and precision. As a result, limits of quantification (LOQ) were ranging from 5 to 30 µg/L, recoveries ranged from 95.2% to 104.5%, and intra-day and inter-day variability were lower than 11.4% and 12.6%, respectively, for all the targeted peptides. Furthermore, this method was successfully applied to 46 commercial minor species' milk, in which 15 samples were false labeling. The obtained results indicate the necessity to monitor milk species adulteration in order to protect consumers from consuming misleading labeled minor species animal's milk.

A fluorescent organic nanoparticles-based sensor synthesized through hydrothermal process and its application in sensing Hg2+ of real samples and fast visual detection

The fluorescent organic nanoparticles (FONs)-based sensor has been attracting great attention in recent years. There are still big challenges in the preparation and application of FONs-based sensor. In this study, a FONs-based sensor was designed and developed through facile hydrothermal process using 3-perylenecarboxaldehyde (PlCA) as the fluorophore and L-methionine (Met) as the recognition site for mercury ions. According to the experimental results, the fluorescence intensity of the as-prepared PlCA-M would decrease when adding Hg²⁺ and the mechanism was extrapolated to be photoinduced electron transfer inducing by specific coordination interaction. The acquired PlCA-M-based sensor was used to monitor Hg²⁺ in several real samples (environmental water, tea, and apple) with the limit of detection being 60 nM. Remarkably, a visual detection device based on FONs, SDS-PAAG (sodium dodecyl sulfate polyacrylamide gel) @PlCA-M was firstly constructed and successfully used to Hg²⁺ semi-quantitation by naked eyes. In addition, the acquired FONs was applied into imaging tool for security information detection and identified as solid-state luminescent material for the first time.