ArticleACS sensors2025
Interpretating SPR-Derived Reaction Kinetics via Self-Organizing Maps for Diagnostic Applications.
Article in ACS sensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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8 authors.
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Abstract
Biosensors emerge as promising, cost-effective infectious disease diagnostics in resource-limited settings, requiring neither laboratory infrastructure nor specialized personnel. Surface plasmon resonance (SPR)-based biosensors remain preeminent for label-free, real-time analysis of biological interactions and kinetic parameter determination. Integrating Artificial Intelligence (AI), particularly self-organizing maps (SOMs), automates infection screening by projecting high-dimensional data onto topology-preserving 2D maps, offering advantages in diagnostic strategies by enabling efficient classification of infected vs healthy patients. This study presents an SPR biosensor with SOM analysis to enhance serodiagnosis of canine visceral leishmaniasis (CVL), a neglected tropical disease, whose delayed and inadequate detection in human and canine populations compromises effective disease control. The reaction kinetics of PQ20, a multiepitope chimeric protein with 20 B- and T-cell epitopes, with anti-PQ20 was evaluated. The proposed mechanism suggests two immunodominant epitopes of PQ20 through its reaction with polyclonal antibodies of
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