Analytical Chemistry最新文献

GlycosylatedRNAs (glycoRNAs) are involved in immune response,cellular function, gene regulation, and disease development. We reporta liquid chromatography–mass spectrometry (LC-MS) method toanalyze glycans released from glycoRNAs. The developed method includesextracting RNA from mouse liver using TRIzol, digesting proteins withproteinase K under denaturing conditions, re-extracting RNA usingTRIzol, releasing N-glycans by enzymatic digestion,enriching glycans by solid-phase extraction, and analyzing glycansby LC-MS. The method was optimized to detect low-abundance N-glycans from a purchased mixture of N-glycan standards, and 65 glycans were identified. We then appliedthe method to analyze the glycans released from the glycoRNAs in mouseliver and identified 244 N-glycans from triplicateanalyses. We also detected 40 significantly changed N-glycans in the livers of 32-week-old female and male KvB2 mice.This study establishes a simple and efficient technique for characterizing N-glycans in glycoRNAs and paves the way for future studiesto understand the function of glycoRNAs.

Increasing concerns over perfluorooctanoicacid (PFOA),a representativeper- and polyfluoroalkyl substance (PFAS) often referred to as “foreverchemicals”, underscore the urgent need for simple, rapid, andsensitive detection strategies for water monitoring. Herein, we reportan ultrasensitive colorimetric sensing platform for monitoring tracelevels of PFOA in environmental water using a highly efficient hybridnanozyme, Fe₃O₄@MWCNTs. UV–vis absorbanceanalysis confirmed that the nanozyme composite effectively catalyzesthe oxidation of chromogenic substrates, such as 3,3′,5,5′-tetramethylbenzidine(TMB), exhibiting a characteristic blue color in the presence of hydrogenperoxide (H₂O₂). Upon exposure to PFOA, theactive sites on the nanozyme interface were blocked by PFOA, suppressingTMB oxidation and resulting in a clear “Turn-off” opticalresponse. This sensing platform enabled quantitative detection ofultralow concentrations of PFOA, ranging from 10 to 1,000 ng/L, witha limit of detection (LOD) of 3.12 ng/L. This work provides a cost-effective,rapid, and practical approach for monitoring environmentally relevantPFOA concentrations in water.

Pseudomonas aeruginosa is a Gram-negativeopportunisticbacterial pathogen posing severe threat to environmental safety andhuman health. To achieve rapid and accurate detection, we developeda nanobody-based colorimetric-fluorescent dual-mode sandwich immunosensorusing natural fluorescent probe and further integrated machine learningto enhance the signal readout and improve detection sensitivity. Here,specific nanobodies toward P. aeruginosa were successfullydeveloped for the first time by biopanning against an immune phage-displayednanobody library. Natural fluorescent quinine, which possesses intrinsicfluorescence and undergoes fluorescence quenching via an internalquenching effect, was employed as the fluorescent probe. With thebaseline LODs obtained by direct fitting of the raw optical signals(9.005 × 10⁵ CFU/mL for colorimetry and 3.02 ×10³ CFU/mL for fluorescence), an XGBoost model was introducedand further reduces the LOD to 3.269 × 10³ CFU/mLand 3.96 × 10² CFU/mL, achieving a 275-fold and 7.6-foldimprovement in sensitivity, respectively. Furthermore, following abrief pre-enrichment, this method enables detection of P. aeruginosa at concentrations as low as 10 CFU/mL. Recoveriesin water samples ranged from 81.47% to 119.47%, with a coefficientof variation below 8.44%, showing good agreement with machine learningpredictions (R² = 0.957). No cross-reactivitywas observed with closely related or heterologous bacteria. This methodprovides a technical approach for the precise quantitative monitoringof P. aeruginosa in complex environments.