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In this work, a multispectral aptasensor structure, including a sub-layer and two side walls, was presented. The cells are positioned at the down and top of the structure, with the down cells oriented perpendicular to the walls and the top cells aligned parallel to the walls. The validity of the findings was verified by the utilization of a numerical simulation technique known as 3D Finite Difference Time Domain (FDTD). The biosensor under consideration exhibits sensitivities of 1093.7 nm/RIU, 754 nm/RIU, and 707.43 nm/RIU in mode III, mode II, and mode I, respectively. In the majority of instances, the quantity of analyte available is insufficient to coat the surface of the sensor thoroughly. Consequently, in this study, the evaluation of surface sensitivity was undertaken alongside bulk sensitivity. The surface sensitivity of the suggested structure for mode II in the sensor layer, with thicknesses of 10, 20, 30, and 70 nm, is measured to be 25, 78, 344, and 717.636 nm/RIU, respectively. Our design incorporates a unique arrangement of sub-layer and side walls, with cells positioned to maximize interaction with the target analyte. This innovative configuration, combined with Ag for its superior plasmonic properties, enables the detection of E. coli O157 with remarkable sensitivity.
In this work, a multispectral aptasensor structure, including a sub-layer and two side walls, was presented. The cells are positioned at the down and top of the structure, with the down cells oriented perpendicular to the walls and the top cells aligned parallel to the walls. The validity of the findings was verified by the utilization of a numerical simulation technique known as 3D Finite Difference Time Domain (FDTD). The biosensor under consideration exhibits sensitivities of 1093.7 nm/RIU, 754 nm/RIU, and 707.43 nm/RIU in mode III, mode II, and mode I, respectively. In the majority of instances, the quantity of analyte available is insufficient to coat the surface of the sensor thoroughly. Consequently, in this study, the evaluation of surface sensitivity was undertaken alongside bulk sensitivity. The surface sensitivity of the suggested structure for mode II in the sensor layer, with thicknesses of 10, 20, 30, and 70 nm, is measured to be 25, 78, 344, and 717.636 nm/RIU, respectively. Our design incorporates a unique arrangement of sub-layer and side walls, with cells positioned to maximize interaction with the target analyte. This innovative configuration, combined with Ag for its superior plasmonic properties, enables the detection of E. coli O157 with remarkable sensitivity.
Antibiotic resistance is a global health problem. The human gut microbiome is implicated in the dynamics of antibiotic resistance acquisition and transmission, with the gut microbiota thought to play a crucial role. This study aimed to determine the potential influence of the human gut bacteria microbiota on the gut resistome and the relationship between the gut microbiota and Escherichia coli resistome. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline was used to systematically review studies that characterized the gut microbiota and resistome using metagenomic analysis and/or those that reported gut E. coli resistome in healthy individuals. Changes in the diversity and abundance of the bacterial gut microbiota and the resistome across different time points and participant groups were summarized. Additionally, using E. coli resistome as a proxy for the gut resistome, the microbiota composition of the gut harboring antibiotic-resistant E. coli was examined. The findings suggest that lower bacterial microbiota diversity is likely associated with an increased abundance of the overall gut resistome. Age-related differences were observed, with younger infants exhibiting lower microbiota diversity and higher antibiotic resistance gene (ARG) abundance compared to older infants and adults. Studies that reported positive correlations between the relative abundance of Proteobacteria and ARGs were mainly driven by members within the Enterobacteriaceae family, mainly E. coli. This study also reveals that human gut microbiome studies investigating the gut resistome using metagenomic sequencing approaches in healthy individuals are uncommon.
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