Near-infrared spectroscopy and multivariate analysis as effective, fast, and cost-effective methods to discriminate Candida auris from Candida haemulonii.

Candida auris and Candida haemulonii are two emerging opportunistic pathogens that have caused an increase in clinical cases in the recent years worldwide. The differentiation of some Candida species is highly laborious, difficult, costly, and time-consuming depending on the similarity between the species. Thus, this study aimed to develop a new, faster, and less expensive methodology for differentiating between C. auris and C. haemulonii based on near-infrared (NIR) spectroscopy and multivariate analysis. C. auris CBS10913 and C. haemulonii CH02 were separated in 15 plates per species, and three isolated colonies of each plate were selected for Fourier transform near-infrared (FT-NIR) analysis, totaling 90 spectra. Subsequently, principal component analysis (PCA) and variable selection algorithms, including the successive projections algorithm (SPA) and genetic algorithm (GA) coupled with linear discriminant analysis (LDA), were employed to discern distinctive patterns among the samples. The use of PCA, SPA, and GA algorithms associated with LDA achieved 100% sensitivity and specificity for the discriminations. The SPA-LDA and GA-LDA algorithms were essential in selecting the variables (infrared wavelengths) of most importance for the models, which could be attributed to binding of cell wall structures such as polysaccharides, peptides, proteins, or molecules resulting from yeasts' metabolism. These results show the high potential of combined FT-NIR and multivariate analysis techniques for the classification of Candida-like fungi, which can contribute to faster and more effective diagnosis and treatment of patients affected by these microorganisms.

Biospectroscopy and chemometrics as an analytical tool for comparing the antibacterial mechanism of silver nanoparticles with popular antibiotics against Escherichia coli.

Despite the fact that silver nanoparticles (AgNPs) have been widely studied in medical and correlated fields, details on their mechanisms are yet to be fully understood. Herein we present the first study on the combination of infrared spectroscopy and chemometrics as an analytical tool to investigate the mechanism of action of AgNPs against Escherichia coli by comparison with popular and commercially available antibiotics. The rationale behind this study is that the selected antibiotics act on bacteria in specific and distinct manners (DNA, cell membrane, mitochondria, etc.). Hence, via multivariate analysis we were able to compare the spectra of bacteria treated with the antibiotics and AgNPs to determine the main target of the latter. Spectral comparison, exploratory analysis, clustering and classification based on infrared spectra were carried out for E. coli samples in the absence and presence (treated) of four widely known antibiotics (ampicillin, ciprofloxacin, gentamicin and sulfadiazine) as well as RA-AgNPs and ERA-AgNPs. Chemometrics models indicated an interesting similarity between infrared spectra from E. coli treated with sulfadiazine and AgNPs, in which vibrational modes associated to phosphate groups were found to be the most representative. This result suggests that both AgNPs and sulfadiazine affects DNA structural features and availability, but not necessarily through the same mechanism. This biospectroscopy-based approach opens an interesting possibility for the understanding over the mechanism of antibacterial activity of AgNPs.

Nucleophilicity of cysteine and related biothiols and the development of fluorogenic probes and other applications.

Biothiols such as l-cysteine, l-homocysteine, and glutathione play essential roles in many biological processes, and are directly associated with several health conditions. Therefore, the development of fast, selective, sensitive, and inexpensive methods for quantitatively analyzing biothiols in aqueous solution, but especially in biological samples, is a very attractive research field. In this feature review, we have approached the relevance of biothiols' nucleophilicity to develop selective fluorogenic probes. Since biothiols have considerable structural similarity, relevant strategies are in full development, including several fluorescent molecular platforms, specific receptor sites, reaction conditions, and optical responses. All of these features are properly presented and discussed. Biothiol sensing protocols are based on traditional organic chemistry reactions such as (hetero)aromatic nucleophilic substitution, addition, and substitution at carbonyl carbon, conjugate addition, and nucleophilic substitution at saturated carbon, amongst others including combined processes; furthermore, mechanistic aspects are detailed herein, including some interesting historical contexts. The feasibility of related fluorogenic probes is illustrated by analysis in complex matrices such as serum, cells, tissues, and animal models. Applications of these reactions in more complex systems such as sulfhydryl-based peptides and proteins are also presented, aiming at functionalizing and detecting these nucleophiles. Most literature cited in this review is recent; however, some other prominent works are also detailed. It is believed that this review may be accessible for many academic levels and may efficiently contribute not only to popularizing science but also to the rational development of fluorogenic probes for biothiol sensing.

Paper Spray Ionization Mass Spectrometry as a Potential Tool for Early Diagnosis of Cervical Cancer.

Squamous intraepithelial lesion is an abnormal growth of epithelial cells on the surface of the cervix that may lead to cervical cancer. Analytical protocols for the determination of squamous intraepithelial lesions are in high demand, since cervical cancer is the fourth most diagnosed cancer among women in the world. Here, paper spray ionization mass spectrometry (PSI-MS) is used to distinguish between healthy (negative for intraepithelial lesion or malignancy) and diseased (high-grade squamous intraepithelial lesion) blood plasmas. A total of 86 blood samples of different women (49 healthy samples, 37 diseased samples) were collected, and the plasmas were prepared. Then, 10 µL of each plasma sample was deposited onto triangular papers for PSI-MS analysis. No additional step of sample preparation was necessary. The interval-successive projection algorithm linear discriminant analysis (iSPA-LDA) was applied to the PSI mass spectra, showing six ions (mostly phospholipids) that were predictive of healthy and diseased plasmas. Values of 77% accuracy, 86% sensitivity, 80% positive predictive value (PPV), and 75% negative predictive value (NPV) were achieved. This study provides evidence that PSI-MS may potentially be used as a fast and simple analytical technique for the early diagnosis of cervical cancer.

Rutin-modified silver nanoparticles as a chromogenic probe for the selective detection of Fe3+ in aqueous medium.

The development of nanoprobes for selective detection of metal ions in solution has attracted great attention due to their impact on living organisms. As a contribution to this field, this paper reports the synthesis of silver nanoparticles modified with rutin in the presence of ascorbic acid and their successful use as a chromogenic probe for the selective detection of Fe3+ in aqueous solution. Limits of detection and quantification were found to be 17 nmol L-1 and 56 nmol L-1, respectively. The sensing ability is proposed to proceed via an iron-induced nanoparticle growth/aggregation mechanism. A practical approach using image analysis for quantification of Fe3+ is also described.

Mass spectrometry and multivariate analysis to classify cervical intraepithelial neoplasia from blood plasma: an untargeted lipidomic study.

Cervical cancer is still an important issue of public health since it is the fourth most frequent type of cancer in women worldwide. Much effort has been dedicated to combating this cancer, in particular by the early detection of cervical pre-cancerous lesions. For this purpose, this paper reports the use of mass spectrometry coupled with multivariate analysis as an untargeted lipidomic approach to classifying 76 blood plasma samples into negative for intraepithelial lesion or malignancy (NILM, n = 42) and squamous intraepithelial lesion (SIL, n = 34). The crude lipid extract was directly analyzed with mass spectrometry for untargeted lipidomics, followed by multivariate analysis based on the principal component analysis (PCA) and genetic algorithm (GA) with support vector machines (SVM), linear (LDA) and quadratic (QDA) discriminant analysis. PCA-SVM models outperformed LDA and QDA results, achieving sensitivity and specificity values of 80.0% and 83.3%, respectively. Five types of lipids contributing to the distinction between NILM and SIL classes were identified, including prostaglandins, phospholipids, and sphingolipids for the former condition and Tetranor-PGFM and hydroperoxide lipid for the latter. These findings highlight the potentiality of using mass spectrometry associated with chemometrics to discriminate between healthy women and those suffering from cervical pre-cancerous lesions.