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Results for “Aptamers, Nucleotide”

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PubMed2026

Aptamer-Based Platforms for Human Aging Biomarkers: Multiplexed Proteomics, Biosensors and Translational Perspectives.

Aptamer-based multiplexed proteomic platforms, especially the SOMAmer-based SomaScan assay, are widely used for large-scale discovery of circulating biomarkers relevant to human aging. This review summarizes 42 original research articles published from 2020 through 2026 in which aptamers or aptamer-derived biosensors were used to characterize aging-related biomarkers in human samples or clinically relevant human-disease contexts. The eligible literature falls into several thematic areas: whole-plasma and organ-specific proteomic aging clocks; inflammaging and senescence-associated secretory phenotype (SASP) markers; cardiovascular, metabolic, renal, hepatic, musculoskeletal and neurodegenerative biomarker panels; and aptasensor platforms for detection of individual analytes. Only a small number of studies have compared aptamer- and antibody-based platforms in the same specimens; we tabulate these and show that median between-platform agreement is low to moderate, which constrains the pooling of findings across technologies. We also make explicit an interpretive point that is usually left implicit: because proteomic clocks are trained against chronological age, their correlation with chronological age measures fit to the training target rather than biological validity, and the informative quantity is the residual age gap. In the reviewed literature, SomaScan-based studies are concentrated in cardiovascular, neurodegenerative, frailty, and proteomic aging-clock research, whereas de novo SELEX campaigns targeting aging-specific epitopes and longitudinal human validation of wearable aptasensors were not identified. The main barriers to translation are cross-platform discordance, limited replication across ancestries, under-reported pre-analytical variability, cost, and the research-use-only status of most assays.

Humans↗

PubMed2026

Artificial neural network data fusion-mediated dual-mode sensor based on Fe3O4@PdIr for Salmonellatyphimurium detection in food.

Salmonella Typhimurium (S. typhimurium) is a major foodborne pathogen that poses a serious threat to public health. In this study, a colorimetric/electrochemical dual-mode biosensor assisted by artificial neural network (ANN) was developed for the sensitive detection of S. typhimurium. Fe3O4@PdIr nanocomposites with enhanced peroxidase-like activity and electrochemical performance were prepared and conjugated with an aptamer specific to S. typhimurium to obtain Fe3O4@PdIr-Apt. Through the sandwich binding of Fe3O4@PdIr-Apt and Apt to the target, the nanocomposites were attached to microplates or Au electrodes, thereby generating colorimetric and electrochemical signals. The ANN model deeply resolved the complex nonlinear relationship between the dual signals, enabling mutual correction and ultimately performing data fusion to output a single detection result, which significantly reduced the mean square error while improving detection sensitivity and reliability. This sensor exhibited a wide linear range of 2.7-2.7 × 108 CFU/mL and a low detection limit of 1.66 CFU/mL. Additionally, this method was successfully applied to the detection of S. typhimurium in pork and milk, with a recovery rate of 95.19% ∼ 104.07%. It indicated that the constructed sensor holds great practical potential for S. typhimurium detection.

Neural Networks, Computer↗

PubMed2026

Characterizing Riboglow Probes In Vitro as the Basis for Fluorescence Lifetime Imaging In Live Mammalian Cells and Three-Dimensional Cellular Models.

Nearly 80% of the human genome is transcribed into RNA, while less than 2% encode for proteins, indicating that the majority of mammalian transcripts are noncoding and participate in diverse regulatory processes. Therefore, sensing and visualizing RNA molecules in live mammalian cell systems quantitatively are critical to understanding RNA dynamics and interactions, yet remains technically challenging, especially in complex cellular environments. Riboglow is a genetically encoded RNA biosensor in which a short RNA aptamer binds a small-molecule probe, producing a quantifiable fluorescence lifetime turn-on detectable by fluorescence lifetime imaging microscopy (FLIM). Here, we present a detailed workflow for Riboglow-FLIM, including sample preparation, image acquisition, and quantitative analysis of FLIM datasets. The goal of this protocol is to enable quantitative fluorescence lifetime-based RNA detection using Riboglow in controlled and live-cell environments. The protocol is demonstrated in vitro, where RNA dependent lifetime changes are measured, and in live mammalian cells, where FLIM acquisition, region of interest selection, and subcellular analysis are established. Successful implementation requires careful control of experimental and acquisition parameters. Key considerations for reproducible implementation are highlighted. Together, this protocol serves as a practical reference for implementing Riboglow-FLIM and quantitatively assessing RNA visualization in live cells.

Humans↗