Chemometric Analysis Combined with GC × GC-FID and ESI HR-MS to Evaluate Ultralow-Sulfur Diesel Stability.

Diesel has been the most employed fuel in highway and nonhighway transportation systems. Many studies over the past years have attempted to classify diesel as a stable or unstable composition since this fuel can still degrade during storage or thermal oxidative processes. Products generated because of such degradation are the reason for the formation of soluble gums and insoluble organic particulates, which in turn cause a negative influence on engine performance. This work reports a detailed composition of nonpolar and polar compounds in many ultralow-sulfur diesel (ULSD) samples by comprehensive two-dimensional gas chromatography with a flame ionization detector (GC × GC-FID) and electrospray ionization high-resolution mass spectrometry (ESI HR-MS). In addition, chemometric approaches were applied for ULSD storage stability investigation. GC × GC-FID experiments achieved the nonpolar chemical characterization for the ULSD samples, including all main hydrocarbon classes: paraffins, mono- and dinaphthenics and olefins, and aromatics. The GC × GC-FID data combined with principal component analysis (PCA) described that the separation of the samples' concerning storage stability was mainly due to the contents of mono- and diaromatic compounds in the unstable ULSD samples. Moreover, PCA was also applied to the ESI (±) data set, and the results highlight the presence of compounds belonging to O class (natural antioxidants), which decrease the rate of oxygen consumption in the fuel, characterizing it as stable composition. The basic nitrogen compounds are mostly present in the stable ULSD samples indicating that they did not affect the stability of the fuel. On the other hand, the HC classes presented pronounced abundance among unstable ULSD samples suggesting that the fuel degradation may go through the oxidation of hydrocarbons and the formation of Ox compounds as byproducts. Furthermore, MS/MS experiments point to the formation of CcHhNnOo-like precursor species, which can react with each other and lead to the formation of gums and insoluble sediments in the fuel. In summary, the results express the potential of using the GC × GC-FID and ESI (±) Orbitrap MS techniques as valuable tools for diesel stability evaluations.

Spectrochemical analysis of blood combined with chemometric techniques for detecting osteosarcopenia.

Among several complications related to physiotherapy, osteosarcopenia is one of the most frequent in elderly patients. This condition is limiting and quite harmful to the patient's health by disabling several basic musculoskeletal activities. Currently, the test to identify this health condition is complex. In this study, we use mid-infrared spectroscopy combined with chemometric techniques to identify osteosarcopenia based on blood serum samples. The purpose of this study was to evaluate the mid-infrared spectroscopy power to detect osteosarcopenia in community-dwelling older women (n = 62, 30 from patients with osteosarcopenia and 32 healthy controls). Feature reduction and selection techniques were employed in conjunction with discriminant analysis, where a principal component analysis with support vector machines (PCA-SVM) model achieved 89% accuracy to distinguish the samples from patients with osteosarcopenia. This study shows the potential of using infrared spectroscopy of blood samples to identify osteosarcopenia in a simple, fast and objective way.

Detection of terbufos in cases of intoxication by means of entomotoxicological analysis using ATR-FTIR spectroscopy combined with chemometrics.

The detection of toxic substances in larvae from carcasses in an advanced stage of decomposition may help criminal expertise in elucidating the cause of death in suspected cases of poisoning. Terbufos (Counter®) or O,O-diethyl-S-[(tert-butylsulfanyl)methyl] phosphorodithioate is an insecticide and systemic nematicide, which has very high toxicity from an acute point of view (oral LD50 in rodents ranging from 1.4 to 9.2 mg/kg) that has been marketed irregularly and indiscriminately in Brazil as a rodenticide, often being used to practice homicides. The present study aims to evaluate the use of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy to detect traces of terbufos pesticide in fly larvae (Sarcophagidae). ATR-FTIR spectra of scavenger fly larvae from control (n = 31) and intoxicated (n = 80) groups were collected and submitted to chemometric analysis by means of multivariate classification using principal component analysis with quadratic discriminant analysis (PCA-QDA), successive projections algorithm with quadratic discriminant analysis (SPA-QDA) and genetic algorithm with quadratic discriminant analysis (GA-QDA) in order to distinguish between control and intoxicated groups. All discriminant models showed sensitivity and specificity above 90%, with the GA-QDA model showing the best performance with 98.9% sensitivity and specificity. The proposed methodology proved to be sensitive and promising for the detection of terbufos in scavenger fly larvae from intoxicated rat carcasses. In addition, the non-destructive nature of the ATR-FTIR technique may be useful in preserving the forensic evidence, meeting the precepts of the chain of custody and allowing for counter-proof.

Near infrared spectroscopy (NIRS) coupled with chemometric methods to identify and estimate taxonomic relationships of flies with forensic potential (Diptera: Calliphoridae and Sarcophagidae).

Infrared spectroscopy has been gaining prominence in entomology, such as for solving taxonomic problems, sexing adult specimens, determining the age of immature specimens, detecting drugs of abuse in fly larvae, and can be an important technique in Forensic Entomology. In order to help identify the species of Calliphoridae and Sarcophagidae families, the present study aimed to evaluate the use of near infrared spectroscopy (NIRS) coupled with chemometric methods for separating fly specimens into taxonomic categories and understanding the taxonomic relationship between them. Spectra collected from nine species of flies were subjected to unsupervised principal component analysis (PCA) and hierarchical cluster analysis (HCA), in which we sought to visualize the relationship between the samples (segregation of genera and families) with subsequent identification. In PCA, the best model was achieved using five principal components (PCs), which explained 99.16% of total variance of the original data set. The first principal component (PC1) and the fourth principal component (PC4) provided the best segregation, the latter being more important in the segregation of the species Chrysomya albiceps, Lucilia eximia, and Ravinia belforti from the others. In the HCA dendrogram, there was a clear separation between the specimens by family (Calliphoridae and Sarcophagidae) and genera (Chrysomya, Lucilia, Oxysarcodexia, Peckia and Ravinia). This study shows that NIRS is efficient to identify flies' taxonomic properties, such as family and genera, providing quick evidence for the tested species identity.

Infrared spectroscopy and forensic entomology: Can this union work? A literature review.

For more than two decades, infrared spectroscopy techniques combined with multivariate analysis have been efficiently applied in several entomological fields, such as Taxonomy and Toxicology. However, little is known about its use and applicability in Forensic entomology (FE) field, with vibrational techniques such as Near-infrared spectroscopy (NIRS) and Medium-infrared spectroscopy (MIRS) underutilized in forensic sciences. Thus, this work describes the potential of NIRS, MIRS, and other spectroscopic methodologies, for entomological analysis in FE, as well as discusses its future uses for criminal or civil investigations. After a thorough research on scientific journals database, a total of 33 publications were found in scientific journals, with direct or indirect application to FE, including experimental applications of NIRS and MIRS in taxonomic discrimination of species, larval age prediction, detection of toxic substances in insects from environments or crime scenes, and detection of internal or external infestations by live or dead insects in stored products. Besides, NIRS and MIRS combined with multivariate analysis were efficient, inexpensive, fast, and non-destructive analytical tools. However, more than 51% of the spectroscopic publications are concentrated in the stored products field, and so we discuss the need for expansion and more direct application in other FE areas. We hope the number of articles continues to increase, and as NIRS and MIRS technology progress, they advance in forensic research and routine use.

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.

Advances in chemometric control of commercial diesel adulteration by kerosene using IR spectroscopy.

Adulteration is a recurrent issue found in fuel screening. Commercial diesel contamination by kerosene is highly difficult to be detected via physicochemical methods applied in market. Although the contamination may affect diesel quality and storage stability, there is a lack of efficient methodologies for this evaluation. This paper assessed the use of IR spectroscopies (MIR and NIR) coupled with partial least squares (PLS) regression, support vector machine regression (SVR), and multivariate curve resolution with alternating least squares (MCR-ALS) calibration models for quantifying and identifying the presence of kerosene adulterant in commercial diesel. Moreover, principal component analysis (PCA), successive projections algorithm (SPA), and genetic algorithm (GA) tools coupled to linear discriminant analysis were used to observe the degradation behavior of 60 samples of pure and kerosene-added diesel fuel in different concentrations over 60 days of storage. Physicochemical properties of commercial diesel with 15% kerosene remained within conformity with Brazilian screening specifications; in addition, specified tests were not able to identify changes in the blends' performance over time. By using multivariate classification, the samples of pure and contaminated fuel were accurately classified by aging level into two well-defined groups, and some spectral features related to fuel degradation products were detected. PLS and SVR were accurate to quantify kerosene in the 2.5-40% (v/v) range, reaching RMSEC < 2.59% and RMSEP < 5.56%, with high correlation between real and predicted concentrations. MCR-ALS with correlation constraint was able to identify and recover the spectral profile of commercial diesel and kerosene adulterant from the IR spectra of contaminated blends.

A novel use of infra-red spectroscopy (NIRS and ATR-FTIR) coupled with variable selection algorithms for the identification of insect species (Diptera: Sarcophagidae) of medico-legal relevance.

Unequivocal identification of fly specimens is an essential requirement in forensic entomology. Herein, a simple, non-destructive and rapid method based on two vibrational spectroscopy techniques [Near-Infrared Spectroscopy (NIRS) and attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy] coupled with variable selection techniques such as genetic algorithm-linear discriminant analysis (GA-LDA) and successive projection algorithm-linear discriminant analysis (SPA-LDA) were applied for identifying and discriminating six species of flesh flies (Diptera: Sarcophagidae) native to Neotropical regions. This novel approach is based on the unique spectral "fingerprints" of their biochemical composition. One hundred sixty (160) NIRS and FT-IR specimens (120 male, 40 female) were acquired; different pre-processing methods such as baseline correction, derivative and Savitzky-Golay smoothing were also performed. In addition, the multivariate classification accuracy results were tested based on sensitivity, specificity, positive (or precision) and negative predictive values, Youden index, positive and negative likelihood ratios. Principal components analysis (PCA) was employed for male vs. female category using NIRS, strongly showing the separation between the classes with only three principal components and 99% explained variance. Differentiation between the genera Oxysarcodexia, Peckia and Ravinia was efficiently confirmed by both techniques. In comparison with other biological methods, this approach represents an effective choice for fast and non-destructive identification in forensic entomology.

Evaluation of the bony repair in rat cranial defect using near infrared reflectance spectroscopy and discriminant analysis.

We set out to determine whether near infrared reflectance spectroscopy (NIRS) combined with principal component analysis-linear discriminant analysis (LDA) or, variable selection techniques employing successive projection algorithm or genetic algorithm (GA) could evaluate the bone repair in cranial critical-size (5 mm) defect after stimulation with collagen sponge scaffold and/or infrared low-level laser therapy directly on the local. Forty-five Winstar rats were divided into nine groups of five each, namely: group H - healthy, n = 5 (without treatment and without cranial critical-size defect), (GI positive control - n = 5, 21 days or n = 5, 30 days) without treatment and with cranial critical-size defect; (GII-n = 5, 21 days or n = 5, 30 days) cranial critical-size defect filled with collagen sponge scaffold; (GIII-n = 5, 21 days or n = 5, 30 days) cranial critical-size defect submitted to low-level laser therapy; (GIV-n = 5, 21 days or n = 5, 30 days) cranial critical-size defect submitted to combined collagen sponge scaffold + low-level laser therapy treatment. In relation to the histological analysis, the collagen sponge scaffold + low-level laser therapy treatment group (GIV) 30 days showed the best result with the presence of secondary bone, immature bone (osteoid) and newly formed connective tissue (periosteum). GA-LDA model also successfully classified control class of the others classes. Thus, the results provided by the good-quality classification model revealed the feasibility of NIRS for application to evaluation of the wound healing in rat cranial defect, thanks to the short analysis time of a few seconds and nondestructive advantages of NIRS as an alternative approach for bone repair purposes. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1160-1168, 2017.