Cardiac troponin I (cTnI) has been regarded as a gold standard for early diagnosis and prognosis monitoring of acute myocardial infarction (AMI) in clinical practice. Owing to its low concentration in blood, accurate determination of cTnI often requires high sensitivity. However, current established point-of-care (POC) assays are insufficient to meet clinically analytical requirements due to their low sensitivity. Methods: To this end, we established a highly sensitive and reliable POC lateral flow strip based on lanthanide-doped nanoparticles (NPs) for cTnI determination in human blood samples. The capture of cTnI on the lateral flow strip was performed in a sandwich assay, where Eu 3+ -doped vanadate nanoparticles (GdVO 4 :30% Eu NPs) were used as luminescent probes to allow quantification. Results: Our platform realized the analytical sensitivity enhancement with limit-of-detection (LOD) as low as 17 pg mL −1 for cTnI detection, which was lower than the commercial counterpart; meanwhile, it displayed high specificity, excellent reproducibility and outstanding accuracy for analyzing clinical serum samples. Conclusion: Overall, this strategy provided an ultrasensitive, cost-effective and user-friendly platform for on-site cTnI detection, demonstrating the prospect of lanthanide-doped NPs-based POC diagnosis of disease-related biomarkers.
Sulfones are widely found in natural products and drug molecules. Here, we disclose a strategy for direct synthesis of sulfone compounds with diverse structures by visible-lightcatalyzed radical−radical cross-coupling of sulfonyl chlorides and trifluoroborate salts. Allyl, benzyl, vinyl, and aryl trifluoroborates can be successfully cross-coupled with (hetero)aryl and alkyl sulfonyl chlorides, respectively. This strategy features redox neutrality, good substrate generality, simple operation, and benign reaction conditions.
For the purpose of improving fault detection accuracy of aero-engine distributed control system, an optimal design method based on chaos adaptive artificial fish swarm algorithm for distributed control system fault detection observer was proposed. First, in order to better simulate the actual distributed control system, dual channel multiple packet transmission was converted to switching system and short time-varying delay was modeled as an uncertainty in system models. Then, a fault observer is designed to obtain the state-space model of error system and the chaos adaptive artificial fish swarm algorithm is introduced. Furthermore, the ratio value of the residual signal transfer function, respectively, to the unknown disturbance signal and fault signal, are regarded as the objective function, and the minimum of the objective function is optimized to get the optimal observer matrix by chaos adaptive artificial fish swarm algorithm with the constraint of error system stability. Finally, the structure and operating principle of aero-engine distributed control system semi-physical platform is introduced, and comparison is made between the simulation of fault detection optimization method and the tradition robust fault detection method on the platform. The simulation results verify that the proposed method can efficiently reduce fault positive ratio and fault negative ratio simultaneously, which can expand the selection scope of threshold value and improve accuracy of fault detection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.