Research Progress on Machine Learning Assisted Non-Targeted Screening Strategy for Identification of Fentanyl Analogs.

In recent years, the types and quantities of fentanyl analogs have increased rapidly. It has become a hotspot in the illicit drug control field of how to quickly identify novel fentanyl analogs and to shorten the blank regulatory period. At present, the identification methods of fentanyl analogs that have been developed mostly rely on reference materials to target fentanyl analogs or their metabolites with known chemical structures, but these methods face challenges when analyzing new compounds with unknown structures. In recent years, emerging machine learning technology can quickly and automatically extract valuable features from massive data, which provides inspiration for the non-targeted screening of fentanyl analogs. For example, the wide application of instruments like Raman spectroscopy, nuclear magnetic resonance spectroscopy, high resolution mass spectrometry, and other instruments can maximize the mining of the characteristic data related to fentanyl analogs in samples. Combining this data with an appropriate machine learning model, researchers may create a variety of high-performance non-targeted fentanyl identification methods. This paper reviews the recent research on the application of machine learning assisted non-targeted screening strategy for the identification of fentanyl analogs, and looks forward to the future development trend in this field.

Chiral Analysis of Lactate during Direct Contact Coculture by Single-Cell On-Probe Enzymatic Dehydrogenation Derivatization: Unraveling Metabolic Changes Caused by d-Lactate.

In vitro noncontact cell-based coculture models are frequently employed to study cell-to-cell communication. However, these models cannot accurately represent the complexity of in vivo signaling. d-Lactate is an unusual metabolite produced and released by cancer cells. The characterization of d-lactate is challenging as it shares the same mass but has much lower amounts compared with l-lactate. Herein, d-α-hydroxy acids were specifically recognized and dehydrogenated by d-α-hydroxy acid dehydrogenase. The dehydrogenation products were rapidly quaternized for enhancement of mass signals. An on-probe enzymatic dehydrogenation-derivatization method was proposed for chiral analysis of α-hydroxy acids at the single-cell level. It is a promising amplification methodology and affords over 3 orders of magnitude signal enhancement. Furthermore, direct contact coculture models were used to precisely mimic the tumor microenvironment and explore the communication between cancer and normal cells. Single-cell mass spectrometry (SCMS) was further applied to easily sample cell extracts and study the differences of the aspects of small molecule metabolism in cocultured cells. On the basis of direct contact coculture SCMS, several differential small molecule metabolites and differences of oxidative stress between cocultured and monocultured normal cells were successfully detected. Additionally, d-lactate was discovered as a valuable differential metabolite with application of the two developed methods. It may account for the cancer-associated metabolic behavior of normal cells. These changes could be relieved after d-lactate metabolism-related drug treatment. This discovery may promote the investigation of d-lactate metabolism, which may provide a novel direction for cancer therapy.

Single-Cell On-Probe Derivatization-Noncontact Nanocarbon Fiber Ionization: Unraveling Cellular Heterogeneity of Fatty Alcohol and Sterol Metabolites.

Currently in single-cell mass spectrometry, the analysis of low-abundance cell metabolites such as fatty alcohols and sterols remains a challenge. In most research studies, single-cell samples are analyzed directly after sampling. However, this workflow may exclude many effective sample pretreatment methods such as derivatization for the improvement of detection sensitivity for specific cell metabolites in a single-cell sample. Metabolites in low abundance in a cell may not be detected. Herein on-probe derivatization coupled with noncontact nanocarbon fiber ionization is proposed for sensitive fatty alcohol and sterol metabolite analysis at the single-cell level. Fatty alcohol and sterol metabolites were rapidly quaternized by the single-cell on-probe derivatization method. The reaction products were directly ionized with no postreaction processing. Furthermore, a new ionization source for noncontact nanocarbon fiber ionization was developed to show good compatibility with dichloromethane, a low-polarity solvent used in on-probe derivatization. The quaternized fatty alcohols and sterols exhibited evidently enhanced ionization efficiency in mass spectra. In applications of the developed method, seven kinds of even-numbered-carbon fatty alcohols (C12-C22) and five kinds of sterols were detected in single L-02 and HepG2 cells. Then the L-02 and HepG2 cells were readily discriminated through principal component analysis. Additionally, a rough quantitative analysis of the detected fatty alcohols and sterols in single cells was performed. The mass intensities of fatty alcohols show a significant difference between L-02 and HepG2 cells while those of sterols remain stable.

A comparative analysis of differentially expressed genes in rostral and caudal regions after spinal cord injury in rats.

The initial mechanical damage of a spinal cord injury (SCI) triggers a progressive secondary injury cascade, which is a complicated process integrating multiple systems and cells. It is crucial to explore the molecular and biological process alterations that occur after SCI for therapy development. The differences between the rostral and caudal regions around an SCI lesion have received little attention. Here, we analyzed the differentially expressed genes between rostral and caudal sites after injury to determine the biological processes in these two segments after SCI. We identified a set of differentially expressed genes, including Col3a1, Col1a1, Dcn, Fn1, Kcnk3, and Nrg1, between rostral and caudal regions at different time points following SCI. Functional enrichment analysis indicated that these genes were involved in response to mechanical stimulus, blood vessel development, and brain development. We then chose Col3a1, Col1a1, Dcn, Fn1, Kcnk3, and Nrg1 for quantitative real-time PCR and Fn1 for immunostaining validation. Our results indicate alterations in different biological events enriched in the rostral and caudal lesion areas, providing new insights into the pathology of SCI.