Elucidating the Underlying Reactivities of Alternating Current Electrosynthesis by Time-Resolved Mapping of Short-Lived Reactive Intermediates.

Alternating current (AC) electrolysis is an emerging field in synthetic chemistry, however its mechanistic studies are challenged by the effective characterization of the elusive intermediate processes. Herein, we develop an operando electrochemical mass spectrometry platform that allows time-resolved mapping of stepwise electrosynthetic reactive intermediates in both direct current and alternating current modes. By dissecting the key intermediate processes of electrochemical functionalization of arylamines, the unique reactivities of AC electrosynthesis, including minimizing the over-oxidation/reduction through the inverse process, and enabling effective reaction of short-lived intermediates generated by oxidation and reduction in paired electrolysis, were evidenced and verified. Notably, the controlled kinetics of reactive N-centered radical intermediates in multistep sequential AC electrosynthesis to minimize the competing reactions was discovered. Overall, this work provides direct evidence for the mechanism of AC electrolysis, and clarifies the underlying reasons for its high efficiency, which will benefit the rational design of AC electrosynthetic reactions.

Nontargeted metabolomics analysis of follicular fluid in patients with endometriosis provides a new direction for the study of oocyte quality.

Endometriosis is a common, estrogen-dependent chronic gynecological disease that endangers the reproductive system and systemic metabolism of patients. We aimed to investigate the differences in metabolic profiles in the follicular fluid between infertile patients with endometriosis and controls. A total of 25 infertile patients with endometriosis and 25 infertile controls who were similar in age, BMI, fertilization method and ovulation induction treatment were recruited in this study. Metabolomics analysis of follicular fluid was performed by two methods of high-performance liquid chromatography tandem mass spectrometry. There were 36 upregulated and 17 downregulated metabolites in the follicular fluid of patients in the endometriosis group. KEGG pathway analysis revealed that these metabolites were enriched in phenylalanine, tyrosine and tryptophan biosynthesis, aminoacyl-tRNA biosynthesis, phenylalanine metabolism and pyrimidine metabolism pathways. A biomarker panel consisting of 20 metabolites was constructed by random forest, with an accuracy of 0.946 and an AUC of 0.988. This study characterizes differences in follicular fluid metabolites and associated pathway profiles in infertile patients with endometriosis. These findings can provide a better comprehensive understanding of the disease and a new direction for the study of oocyte quality, as well as potential metabolic markers for the prognosis of endometriosis.

High-Coverage Four-Dimensional Data-Independent Acquisition Proteomics and Phosphoproteomics Enabled by Deep Learning-Driven Multidimensional Predictions.

Four-dimensional (4D) data-independent acquisition (DIA)-based proteomics is a promising technology. However, its full performance is restricted by the time-consuming building and limited coverage of a project-specific experimental library. Herein, we developed a versatile multifunctional deep learning model Deep4D based on self-attention that could predict the collisional cross section, retention time, fragment ion intensity, and charge state with high accuracies for both the unmodified and phosphorylated peptides and thus established the complete workflows for high-coverage 4D DIA proteomics and phosphoproteomics based on multidimensional predictions. A 4D predicted library containing ∼2 million peptides was established that could realize experimental library-free DIA analysis, and 33% more proteins were identified than using an experimental library of single-shot measurement in the example of HeLa cells. These results show the great values of the convenient high-coverage 4D DIA proteomics methods.

Lipidomic Characterization of Oocytes at Single-Cell Level Using Nanoflow Chromatography-Trapped Ion Mobility Spectrometry-Mass Spectrometry.

Mass spectrometry (MS)-based lipidomic has become a powerful tool for studying lipids in biological systems. However, lipidome analysis at the single-cell level remains a challenge. Here, we report a highly sensitive lipidomic workflow based on nanoflow liquid chromatography and trapped ion mobility spectrometry (TIMS)-MS. This approach enables the high-coverage identification of lipidome landscape at the single-oocyte level. By using the proposed method, comprehensive lipid changes in porcine oocytes during their maturation were revealed. The results provide valuable insights into the structural changes of lipid molecules during porcine oocyte maturation, highlighting the significance of sphingolipids and glycerophospholipids. This study offers a new approach to the single-cell lipidomic.