Browsing by Author "Ferreira, Aníbal"
Now showing 1 - 8 of 8
Results Per Page
Sort Options
- Exosomes and microvesicles in kidney transplantation: the long road from trash to goldPublication . Ramalhete, Luís; Araújo, Rúben; Ferreira, Aníbal; Calado, CecíliaKidney transplantation significantly enhances the survival rate and quality of life of patients with end-stage kidney disease. The ability to predict post-transplantation rejection events in their early phases can reduce subsequent allograft loss. Therefore, it is critical to identify biomarkers of rejection processes that can be acquired on routine analysis of samples collected by non-invasive or minimally invasive procedures. It is also important to develop new therapeutic strategies that facilitate optimisation of the dose of immunotherapeutic drugs and the induction of allograft immunotolerance. This review explores the challenges and opportunities offered by extracellular vesicles (EVs) present in biofluids in the discovery of biomarkers of rejection processes, as drug carriers and in the induction of immunotolerance. Since EVs are highly complex structures and their composition is affected by the parent cell's metabolic status, the importance of defining standardised methods for isolating and characterising EVs is also discussed. Understanding the major bottlenecks associated with all these areas will promote the further investigation of EVs and their translation into a clinical setting. .
- Integration of FTIR spectroscopy and machine learning for kidney allograft rejection: a complementary diagnostic toolPublication . Ramalhete, Luís; Araújo, Rúben Alexandre Dinis; Bigotte Vieira, Miguel; Vigia, Emanuel; Aires, Inês; Ferreira, Aníbal; Calado, CecíliaKidney transplantation is a life-saving treatment for end-stage kidney disease, but allograft rejection remains a critical challenge, requiring accurate and timely diagnosis. The study aims to evaluate the integration of Fourier Transform Infrared (FTIR) spectroscopy and machine learning algorithms as a minimally invasive method to detect kidney allograft rejection and differentiate between T Cell-Mediated Rejection (TCMR) and Antibody-Mediated Rejection (AMR). Additionally, the goal is to discriminate these rejection types aiming to develop a reliable decision-making support tool. Methods: This retrospective study included 41 kidney transplant recipients and analyzed 81 serum samples matched to corresponding allograft biopsies. FTIR spectroscopy was applied to pre-biopsy serum samples, and Naïve Bayes classification models were developed to distinguish rejection from non-rejection and classify rejection types. Data preprocessing involved, e.g., atmospheric compensation, second derivative, and feature selection using Fast Correlation-Based Filter for spectral regions 600–1900 cm−1 and 2800–3400 cm−1. Model performance was assessed via area under the receiver operating characteristic curve (AUC-ROC), sensitivity, specificity, and accuracy. Results: The Naïve Bayes model achieved an AUC-ROC of 0.945 in classifying rejection versus non-rejection and AUC-ROC of 0.989 in distinguishing TCMR from AMR. Feature selection significantly improved model performance, identifying key spectral wavenumbers associated with rejection mechanisms. This approach demonstrated high sensitivity and specificity for both classification tasks. Conclusions: The integration of FTIR spectroscopy with machine learning may provide a promising, minimally invasive method for early detection and precise classification of kidney allograft rejection. Further validation in larger, more diverse populations is needed to confirm these findings’ reliability.
- 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
- 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.
- Nutritional status and overhydration: can bioimpedance spectroscopy be useful in haemodialysis patients?Publication . Garagarza, Cristina; João-Matias, Patrícia; Guerreiro, Catarina Sousa; Amaral, Tiago; Aires, Inês; Ferreira, Carina; Jorge, Cristina; Gil, Célia; Ferreira, AníbalBackground: Protein-energy wasting (PEW), associated with inflammation and overhydration, is common in haemodialysis (HD) patients and is associated with high morbidity and mortality. Objective: Assess the relationship between nutritional status, markers of inflammation and body composition through bioimpedance spectroscopy (BIS) in HD patients. Methods: This observational, cross-sectional, single centre study, carried out in an HD centre in Forte da Casa (Portugal), involved 75 patients on an HD programme. In all participating patients, the following laboratory tests were conducted: haemoglobin, albumin, C-reactive protein (CRP) and 25-hydroxyvitamin D3 [25(OH)D3]. The body mass index of all patients was calculated and a modified version of subjective global assessment (SGA) was produced for patients on dialysis. Intracellular water (ICW) and extracellular water (ECW) were measured by BIS (Body Composition Monitor®, Fresenius Medical Care®) after the HD session. In statistical analysis, Spearman’s correlation was used for the univariate analysis and linear regression for the multivariate analysis (SPSS 14.0). A P value of <.05 was considered statistically significant. Results: PEW, inversely assessed through the ICW/body weight (BW) ratio, was positively related to age (P<.001), presence of diabetes (P=.004), BMI (P=.01) and CRP (P=.008) and negatively related to albumin (p=.006) and 25(OH)D3 (P=.007). Overhydration, assessed directly through the ECW/BW ratio, was positively related with CRP (P=.009) and SGA (P=.03), and negatively with 25(OH)D3 (P=.006) and BMI (P=.01). In multivariate analysis, PEW was associated with older age (P<.001), the presence of diabetes (P=.003), lower 25(OH)D3 (P=.008), higher CRP (P=.001) and lower albumin levels (P=.004). Over-hydration was associated with higher CRP (P=.001) and lower levels of 25(OH)D3 (P=.003). Conclusions: Taking these results into account, the ICW/BW and ECW/BW ratios, assessed with BIS, have proven to be good markers of the nutritional and inflammatory status of HD patients. BIS may be a useful tool for regularly assessing the nutritional and hydration status in these patients and may allow nutritional advice to be improved and adjusted.
- Predicting cellular rejection of renal allograft based on the serum proteomic fingerprintPublication . Ramalhete, Luís; Vieira, Miguel Bigotte; Araújo, Rúben; Vigia, Emanuel; Aires, Inês; Ferreira, Aníbal; Calado, CecíliaKidney transplantation is an essential medical procedure that significantly enhances the survival rates and quality of life for patients with end-stage kidney disease. However, despite advancements in immunosuppressive therapies, allograft rejection remains a leading cause of organ loss. Notably, predictions of cellular rejection processes primarily rely on biopsy analysis, which is not routinely performed due to its invasive nature. The present work evaluates if the serum proteomic fingerprint, as acquired by Fourier Transform Infrared (FTIR) spectroscopy, can predict cellular rejection processes. We analyzed 28 serum samples, corresponding to 17 without cellular rejection processes and 11 associated with cellular rejection processes, as based on biopsy analyses. The leave-one-out-cross validation procedure of a Naïve Bayes model enabled the prediction of cellular rejection processes with high sensitivity and specificity (AUC > 0.984). The serum proteomic profile was obtained in a high-throughput mode and based on a simple, rapid, and economical procedure, making it suitable for routine analyses and large-scale studies. Consequently, the current method presents a high potential to predict cellular rejection processes translatable to clinical scenarios, and that should continue to be explored.
- Proteomics for biomarker discovery for diagnosis and prognosis of kidney transplantation rejectionPublication . Ramalhete, Luís; Araújo, Rúben; Ferreira, Aníbal; Calado, CecíliaRenal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.
- Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation RejectionPublication . Ramalhete, Luís; Araújo, Rúben; Ferreira, Aníbal; Calado, CecíliaRenal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.