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dc.contributor.authorPadial Jaudenes, Maria
dc.contributor.authorTabraue-Chávez, Mavys
dc.contributor.authorDetassis, Simone
dc.contributor.authorRuedas Rama, María José 
dc.contributor.authorGonzález García, María del Carmen 
dc.contributor.authorFara, Mario Antonio
dc.contributor.authorLópez Delgado, Francisco Javier
dc.contributor.authorGonzález Vera, Juan Antonio 
dc.contributor.authorGuardia Monteagudo, Juan José
dc.contributor.authorDíaz Mochón, Juan José 
dc.contributor.authorGarcía Fernández, Emilio 
dc.contributor.authorPernagallo, Salvatore
dc.contributor.authorOrte Gutiérrez, Ángel 
dc.date.accessioned2023-10-09T11:45:55Z
dc.date.available2023-10-09T11:45:55Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/10481/84916
dc.description.abstractMicroRNAs (miRs) have emerged as promising biomarkers for early disease diagnosis and personalised treatment monitoring. However, but their clinical utility has been hampered by technical limitations. Dynamic chemical labelling (DCL) based on capturing abasic PNA probes and reactive nucleobases, so-called SMART bases, is a PCR-free approach that has proven very useful for the direct interrogation of circulating miRs. In this work, we expand the palette of available tools for DCL miR detection methods with a newly synthesised SMART nucleobase, SMART-C-Eu. This nucleobase contains a stable lanthanide cryptate. Using this SMART-C-Eu base and time-gated (TG) luminescence imaging, we successfully detect and quantify miR-122-5p in human serum samples. miR-122-5p is a well-known biomarker for drug-induced liver injury. A bead-counting analysis approach improved statistical robustness and allowed the detection of miR-122-5p concentrations in the nanomolar range. Furthermore, we extend this approach to multiplexed detection of three different miRs (miR-371a-3p, miR-451a-5p, and miR-122-5p) using spectral and temporal filtering. Consistent results were obtained using machine learning algorithms for automatic bead classification. Although this technique requires further sensitivity improvements to detect miRs at lower concentrations, it represents a significant advancement in miR analysis. It offers multiplexing capabilities and the potential for automation, paving the way for more accurate and robust clinical applications in the future.es_ES
dc.description.sponsorshipEuropean Union through the H2020 diaRNAgnosis project, under grant agreement No. 101007934es_ES
dc.description.sponsorshipAgencia Estatal de Investigación (Spain) through grant PID2020-114256RB-I00 AEI/10.13039/501100011033es_ES
dc.description.sponsorshipAgencia Estatal de Investigación (Spain) through grant CTQ2017-85658-R AEI/10.13039/501100011033/FEDER “Una manera de hacer Europa”.es_ES
dc.language.isoenges_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectMicroRNAes_ES
dc.subjectmiRses_ES
dc.subjectBiomarkerses_ES
dc.subjectDynamic chemistry labelinges_ES
dc.subjectLuminescence imaginges_ES
dc.subjectMachine learning algorithmses_ES
dc.titleDataset from article 'A New Horizon in Multiplexed micro-RNA Biomarker Detection: Bridging Lifetime Filtering Imaging and Dynamic Chemistry Labeling'es_ES
dc.typedataset
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.30827/Digibug.84916
dc.publication.year2023


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