Repository logo
 
Publication

Label-free discrimination of T and B lymphocyte activation based on vibrational spectroscopy – A machine learning approach

2023Journal article Open access
Simple item page
dc.contributor.authorRamalhete, Luís
dc.contributor.authorAraújo, Rúben
dc.contributor.authorFerreira, Aníbal
dc.contributor.authorCalado, Cecília
dc.date.accessioned2024-03-22T15:02:26Z
dc.date.available2024-03-22T15:02:26Z
dc.date.issued2023
dc.description.abstractB and T-lymphocytes are major players of the specific immune system, responsible by an efficient response to target antigens. Despite the high relevance of these cells’ activation in diverse human pathophysiological pro cesses, its analysis in clinical context presents diverse constraints. In the present work, MIR spectroscopy was used to acquire the cells molecular profile in a label-free, simple, rapid, economic, and high-throughput mode. Recurring to machine learning algorithms MIR data was subsequently evaluated. Models were developed based on specific spectral bands as selected by Gini index and the Fast Correlation Based Filter. To determine if it was, possible to predict from the spectra, if B and T lymphocyte were activated, and what was the molecular fingerprint of T- or B- lymphocyte activation. The molecular composition of activated lymphocytes was so different from naïve cells, that very good pre diction models were developed with whole spectra (with AUC=0.98). Activated B lymphocytes also present a very distinct molecular profile in relation to activated T lymphocytes, leading to excellent prediction models, especially if based on target bands (AUC=0.99). The identification of critical target bands, according to the metabolic differences between B and T lymphocytes and in association with the molecular mechanism of the activation process highlighted bands associated to lipids and glycogen levels. The method developed presents therefore, appealing characteristics to promote a new diagnostic tool to analyze and discriminate B from T-lymphocytespt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationLuis Ramalhete, Ruben Araújo, Aníbal Ferreira, Cecília R.C. Calado, Label-free discrimination of T and B lymphocyte activation based on vibrational spectroscopy – A machine learning approach, Vibrational Spectroscopy, Volume 126, 2023, 103529, ISSN 0924-2031, https://doi.org/10.1016/j.vibspec.2023.103529.pt_PT
dc.identifier.doihttps://doi.org/10.1016/j.vibspec.2023.103529pt_PT
dc.identifier.issn0924-2031
dc.identifier.urihttp://hdl.handle.net/10400.21/17202
dc.language.isoengpt_PT
dc.publisherVibrational Spectroscopypt_PT
dc.relationNeproMD/ISEL/2020pt_PT
dc.relationQuality by design-centered platform for the manufacturing of CAR-engineered NK cells and extracellular vesicles for immunotherapy
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S092420312300036X?via%3Dihubpt_PT
dc.subjectB lymphocytespt_PT
dc.subjectT lymphocytespt_PT
dc.subjectMIR spectroscopypt_PT
dc.subjectCellular activationpt_PT
dc.subjectMolecular fingerprintpt_PT
dc.subjectMachine learningpt_PT
dc.titleLabel-free discrimination of T and B lymphocyte activation based on vibrational spectroscopy – A machine learning approachpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleQuality by design-centered platform for the manufacturing of CAR-engineered NK cells and extracellular vesicles for immunotherapy
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/DSAIPA%2FDS%2F0117%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEQU-EQU%2F3708%2F2021/PT
oaire.citation.endPage9pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.volume126pt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStream3599-PPCDT
person.familyNameRamalhete
person.familyNameAraújo
person.familyNameAntunes Ferreira
person.familyNameCalado
person.givenNameLuís
person.givenNameRúben Alexandre Dinis
person.givenNameManuel Aníbal
person.givenNameCecília
person.identifier2296066
person.identifier130332
person.identifier.ciencia-idDF19-022D-AA10
person.identifier.ciencia-id9A18-BFDC-ED95
person.identifier.ciencia-id2E10-C387-4982
person.identifier.ciencia-id9418-E320-3177
person.identifier.orcid0000-0002-8911-3380
person.identifier.orcid0000-0002-9369-6486
person.identifier.orcid0000-0002-3300-6033
person.identifier.orcid0000-0002-5264-9755
person.identifier.ridE-2102-2014
person.identifier.scopus-author-id57208672678
person.identifier.scopus-author-id6603163260
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication7846e088-851e-47b6-a7bd-d02c9d8f047d
relation.isAuthorOfPublication9998e940-5e65-4661-8308-afcb56d5df01
relation.isAuthorOfPublication14da9d0c-6486-42be-be91-5fc6a965533f
relation.isAuthorOfPublicatione8577257-c64c-4481-9b2b-940fedb360cc
relation.isAuthorOfPublication.latestForDiscovery7846e088-851e-47b6-a7bd-d02c9d8f047d
relation.isProjectOfPublication8f80f51c-b563-49e2-9864-a2c78479fc19
relation.isProjectOfPublication4ef05c38-8a61-43b9-8a80-ba8b7331ffca
relation.isProjectOfPublication.latestForDiscovery8f80f51c-b563-49e2-9864-a2c78479fc19

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Label.pdf
Size:
4.54 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ISEL - Eng. Quim. Biol. - Artigos