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- Label-free discrimination of T and B lymphocyte activation based on vibrational spectroscopy – A machine learning approachPublication . Ramalhete, Luís; Araújo, Rúben; Ferreira, Aníbal; Calado, CecíliaB 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-lymphocytes
- Impact of the human mesenchymal stem cells donor on conditional medium compositionPublication . Pereira, Maria João Canha; Ramalhete, Luís; Aleixo, Sandra; da Silva, Cláudia L.; Cabral, Joaquim M.S.; Calado, Cecília; Fernandes, AnaExosomes produced by Mesenchymal Stem Cells (MSCs) can represent a very appealing strategy for cell-free therapies. However, to achieve this reality it is necessary to further understand the process associated to the MSC culture when conditioned to produce exosomes. In the present work, it was evaluated how different MSC obtained from different donors may affect the conditioned media composition and how this can be influenced by the conditioned media type (DMEM versus Xeno-Free medium, XF). The molecular fingerprint of the conditioned media composition was obtained by mid-infrared (MIR) spectroscopy, as this technique reflects fundamental vibrations of a high diversity of functional chemical groups present in biological samples. It was observed by principal component analysis of the second derivative spectra of conditioned media that the media chemical composition depends more from the MSCs donor than the conditioning days. Diverse spectral regions, characteristic of defined chemical groups, enabled to discriminate the chemical composition of the media according to the MSC donor. All of this was observed in both types of media (DMEM and XF). This work is a step forward to understand how different MSC donors and conditioned media may affect the exosomes characteristics.
- Label-free discrimination of T and B lymphocyte activation based on vibrational spectroscopy: a machine learning approachPublication . Ramalhete, Luís; Araújo, Rúben; Ferreira, Aníbal; Calado, CecíliaB 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 processes, 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 prediction 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-lymphocytes.