Loading...
117 results
Search Results
Now showing 1 - 10 of 117
- Spectral biomarkers of genotoxicity from methanol extracts of bloodPublication . Teixeira, Hélder Paz; Ramalhete, Luís; Ladeira, Carina; Calado, CecíliaIt is relevant to develop new monitoring techniques of carcinogenic risk associated to environmental exposition to genotoxic chemicals. The conventional biomonitoring techniques are based on laborious, expensive methods as the ones requiring isolation of lymphocytes from peripheral blood, in vitro cell culture, followed by e.g. cytokinesis-block assay and microscope observation of chromosomal abnormalities. The present work evaluated an infrared spectroscopy method, based on a simple, more economic and high-throughput procedure of analysis of whole blood processed with methanol. It was possible to identify ratios of spectral bands that are statistically different between hospital professionals occupationally exposed to antineoplastic drugs, such as 5-fluorouracil and non-hospital professionals without this exposure. It was also identified ratios of spectral bands which are statistically different between participants presenting lymphocytes with chromosomal abnormalities (as micronucleus, nuclear buds and nucleoplasmatic bridges) and participants not presenting these abnormalities. The infrared spectroscopy-based method presents therefore appealing characteristics to be applied in more intensive and/or large-scale studies of monitoring genotoxic risks.
- Alternative sérum biomarkers of bacteraemia for intensive care unit patientsPublication . Araújo, Rúben; Von Rekowski, Cristiana; Bento, Luís; Fonseca, Tiago AH; Calado, CecíliaThe diagnosis of infections in hospital or clinical settings usually involves a series of time-consuming steps, including biological sample collection, culture growth of the organism isolation and subsequent characterization. For this, there are diverse infection biomarkers based on blood analysis, however, these are of limited use in patients presenting confound processes as inflammatory process as occurring at intensive care units. In this preliminary study, the application of serum analysis by FTIR spectroscopy, to predict bacteraemia in 102 critically ill patients in an ICU was evaluated. It was analysed the effect of spectra pre-processing methods and spectral sub-regions on t-distributed stochastic neighbour embedding. By optimizing Support Vector Machine (SVM) models, based on normalised second derivative spectra of a smaller subregion, it was possible to achieve a good bacteraemia predictive model with a sensitivity and specificity of 76%. Since FTIR spectra of serum is acquired in a simple, economic and rapid mode, the technique presents the potential to be a cost-effective methodology of bacteraemia identification, with special relevance in critically ill patients, where a rapid infection diagnostic will allow to avoid the unnecessary use of antibiotics, which ultimately will ease the load on already fragile patients' metabolism.
- Protein and DNA nanoparticulate multiantigenic vaccines against H. pylori: In vivo evaluationPublication . Figueiredo, Lara; Calado, Cecília; Almeida, António J.; Gonçalves, Lídia M. D.Immunisation against H. pylori is an attractive option for antibiotic resistance and reinfection situations. Strain genetic heterogeneity, and low immunogenicity of protein antigens and DNA alone are nonetheless obstacles to this approach. We developed multigenic H. pylori DNA-nanoparticle and protein-nanoparticle vaccines based on pathogenic relevance. Six antigens were chosen for the vaccine construction: CagA, VacA, HpaA, UreB, HomB and GroEL. Different combinations of CS/DS and CS/Alg /TPP nanoparticles with DNA and chimeric proteins were produced as vaccine systems. Immune responses were evaluated after i.m. and oral immunisation of BALB/c mice. Oral vaccination successfully stimulated mucosal immunity while i.m. immunisation efficiently elicited a more equilibrated cellular/humoral immune response.
- Streamlining bacterial infection diagnosis: rapid gram classification using FTIR spectroscopyPublication . Araújo, R.; Ramalhete, L.; Fonseca, T.; von Rekowski, C.; Bento, L.; Calado, CecíliaIn a hospital setting, diagnosing infections typically involves a complex process that includes the collection of biological samples and growing a culture for organism isolation, followed by its characterization. However, these methods are slow, require multiple steps and are often limited by the need of specialized equipment and skilled personnel. In this preliminary study, it was analysed the serum, by FTIR spectroscopy, of 29 critically ill COVID-19 patients in an ICU. It was analysed the effect of varied preprocessing methods and spectral sub-regions on t-SNE. Through the optimization of SVM models, it was possible to achieve a very good gram predictive model with a sensitivity and specificity of 90 and 89% respectively. As an accurate classification of bacterial strains is crucial to guide effective antimicrobial therapy and prevent the spread of multidrug-resistant bacteria, FTIR spectra, acquired in a simple, economic, and rapid mode, presents therefore the potential for development of new classification methods that would greatly enhance the ability to manage bacterial infections.
- Comparative analysis of different transformed Saccharomyces cerevisiae strains based on high- throughput Fourier transform infrared spectroscopyPublication . Sousa, Pedro N.; Calado, CecíliaThis study shows the application of the Fourier transform mid-infrared spectroscopy (FT-MIR) associated with high-throughput technology to study the biochemical fingerprints of different Saccharomyces cerevisiae strains transformed with the same expression system along the similar cultivation in bioreactor. The phenotype, as well as the cellular metabolism and recombinant cyprosin biosynthesis, were determined. The differences observed were confirmed by conventional cyprosin activity protocol, and the metabolic evolution was analyzed using high-performance liquid chromatography technique. The spectral analysis based on chemometrics tools, such as the principal component analysis, is a useful methodology for the phenotypes characterization as well as the specific metabolic states along the cultivations according to the clusters created. The ratio bands of spectra also represented a useful tool to evaluate the metabolic and biochemical differences between both expression systems, allowing to have an additional parameter to the biomolecular comparison. Therefore, high-throughput FT-MIR spectroscopy associated with multivariate data analysis represent a valuable strategy for extracting significant specific biomolecular information along the cultivation, providing a complete bioprocess analysis, once it detects slight molecular changes which it will be useful for screening and optimization process in the biotechnological or pharmaceutical industry.
- A new method to predict genotoxic effects based on serum molecular profilePublication . Araújo, Rúben; Ramalhete, Luís; Paz, Hélder; Ladeira, Carina; Calado, CecíliaIt is critical to develop new methods to assess genotoxic effects in human biomonitoring since the conventional methods are usually laborious, time-consuming, and expensive. It is aimed to evaluate if the analysis of a drop of serum by Fourier Transform Infrared spectroscopy, allow to assess genotoxic effects in occupational exposure to cytostatic drugs in hospital professionals, as obtained by the lymphocyte cytokinesis-block micronucleus assay. It was considered peripheral blood from hospital professionals exposed to cytostatic drugs (n = 22) and from a non-exposed group (n = 36). It was observed that workers occupationally exposed presented a higher number of micronuclei (p < 0.05) in lymphocytes, in relation to the non-exposed group. The serum Fourier Transform Infrared spectra from exposed workers presented diverse different peaks (p < 0.01) in relation to the non-exposed group. The hierarchical cluster analysis of serum spectra separated serum samples of the exposed group from the non-exposed group with 61% sensitivity and 88% specificity. A support vector machine model of serum spectra enables to predict exposure with high accuracy (0.91), precision (0.89), sensitivity (0.86), F1 score (0.87) and AUC (0.96). Therefore, Fourier Transform Infrared spectroscopic analysis of a drop of serum enabled to predict in a rapid and simple mode the genotoxic effects of cytostatic drugs. The method presents therefore potential for high-dimension screening of exposure of genotoxic substances, due to its simplicity and rapid setup mode.
- Antibiotic discovery: where have we come from, where do we go?Publication . Ribeiro Da Cunha, Bernardo; Fonseca, Luís P.; Calado, CecíliaGiven the increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures—platforms—that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines. During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.
- 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.
- A new method to predict genotoxic effects based on serum molecular profilePublication . Araújo, Rúben; Ramalhete, Luís; Paz, Hélder; Ladeira, Carina; Calado, CecíliaIt is critical to developing new methods to assess genotoxic effects in human biomonitoring since conventional methods are usually laborious, time-consuming, and expensive. It is aimed to evaluate if the analysis of a drop of serum by Fourier Transform Infrared spectroscopy, allows assessing genotoxic effects in occupational exposure to cytostatic drugs in hospital professionals, as obtained by the lymphocyte cytokinesis-block micronucleus assay. It was considered peripheral blood from hospital professionals exposed to cytostatic drugs (n = 22) and from a non-exposed group (n = 36). It was observed that workers occupationally exposed presented a higher number of micronuclei (p < 0.05) in lymphocytes, in relation to the non-exposed group. The serum Fourier Transform Infrared spectra from exposed workers presented diverse different peaks (p < 0.01) in relation to the non-exposed group. The hierarchical cluster analysis of serum spectra separated serum samples of the exposed group from the non-exposed group with 61% sensitivity and 88% specificity. A support vector machine model of serum spectra enables the prediction of exposure with high accuracy (0.91), precision (0.89), sensitivity (0.86), F1 score (0.87), and AUC (0.96). Therefore, Fourier Transform Infrared spectroscopic analysis of a drop of serum enabled to predict in a rapid and simple mode the genotoxic effects of cytostatic drugs. The method presents therefore potential for high-dimension screening of exposure to genotoxic substances, due to its simplicity and rapid setup mode.
- A new approach for rapid detection of bioactive compounds using MIR spectroscopy and machine learning algorithmsPublication . Sampaio, P. N.; Duarte, Fernando B.; Calado, CecíliaNowadays, microbial infections and resistance to antibiotic drugs are the biggest challenges, which threaten the health of societies. Due to several pharmacological activities associated with Cynara cardunculus, such as hepatoprotective, antioxidative, anticarcinogenic, hypocholesterolemic, antibacterial, anti-HIV, among others, extracts from seeds, leaves, and flowers were tested in Escherichia coli cells. The sensibility of the Mid-infrared (MIR) spectroscopy allowed to perform a detailed analysis of the antimicrobial action of extracts in terms of their biomolecular changes. A comparative model based on several commercial antibiotics such as metronidazole, kanamycin, clarithromycin, chloramphenicol, and ampicillin, was developed. The clustering analysis was performed using unsupervised algorithms such as Principal Component Analysis (PCA), and Kohonen Self-Organizing Maps (SOM). The extracts characterized with antioxidant activity were clustered with antibiotics and presented a promissory antimicrobial activity. According to this preliminary result, it is possible to use the MIR spectroscopy and machine learning algorithm to discover promissory bio compounds characterized by antimicrobial properties, allowing to develop a platform to discover new bioactive molecules, reducing time and costs.