Autism spectrum disorder (ASD) is a neurodevelopmental disorder that begins early in life and continues lifelong with strong personal and societal implications. It affects about 1%–2% of the children population in the world. The absence of auxiliary methods that can complement the clinical evaluation of ASD increases the probability of false identification of the disorder, especially in the case of very young children. In this study, analytical models for auxiliary diagnosis of ASD in children and adolescents, based on the analysis of patients’ blood serum ATR-FTIR (Attenuated Total Reflectance-Fourier Transform Infrared) spectra, were developed. The models use chemometrics (either Principal Component Analysis (PCA) or Partial Least Squares Discriminant Analysis (PLS-DA)) methods, with the infrared spectra being the X-predictor variables. The two developed models exhibit excellent classification performance for samples of ASD individuals vs. healthy controls. Interestingly, the simplest, unsupervised PCA-based model results to have a global performance identical to the more demanding, supervised (PLS-DA)-based model. The developed PCA-based model thus appears as the more economical alternative one for use in the clinical environment. Hierarchical clustering analysis performed on the full set of samples was also successful in discriminating the two groups.

Attention deficit and hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders of childhood. It affects ~10% of the world’s population of children, and about 30–50% of those diagnosed in childhood continue to show ADHD symptoms later, with 2–5% of adults having the condition. Current diagnosis of ADHD is based on the clinical evaluation of the patient, and on interviews performed by clinicians with parents and teachers of the children, which, together with the fact that it shares common symptoms and frequent comorbidities with other neurodevelopmental disorders, makes the accurate and timely diagnosis of the disorder a difficult task. Despite the large effort to identify reliable biomarkers that can be used in a clinical environment to support clinical diagnosis, this goal has never been achieved hitherto. In the present study, infrared spectroscopy was used together with multivariate statistical methods (hierarchical clustering and partial least-squares discriminant analysis) to develop a model based on the spectra of blood serum samples that is able to distinguish ADHD patients from healthy individuals. The developed model used an approach where the whole infrared spectrum (in the 3700–900 cm−1 range) was taken as a holistic imprint of the biochemical blood serum environment (spectroscopic biomarker), overcoming the need for the search of any particular chemical substance associated with the disorder (molecular biomarker). The developed model is based on a sensitive and reliable technique, which is cheap and fast, thus appearing promising to use as a complementary diagnostic tool in the clinical environment.

Fulgurites are naturally occurring structures that are formed when lightning discharges reach the ground. In this investigation, the mineralogical compositions of core and shell compartments of a rare, iron-rich fulgurite from the Mongolian Gobi Desert were investigated by X-ray diffraction and micro-Raman spectroscopy. The interpretation of the Raman data was helped by chemometric analysis, using both multivariate curve resolution (MCR) and principal component analysis (PCA), which allowed for the fast identification of the minerals present in each region of the fulgurite. In the core of the fulgurite, quartz, microcline, albite, hematite, and barite were first identified based on the Raman spectroscopy and chemometrics analyses. In contrast, in the shell compartment of the fulgurite, the detected minerals were quartz, a mixture of the K-feldspars orthoclase and microcline, albite, hematite, and goethite. The Raman spectroscopy results were confirmed by X-ray diffraction analysis of powdered samples of the two fulgurite regions, and are consistent with infrared spectroscopy data, being also in agreement with the petrographic analysis of the fulgurite, including scanning electron microscopy with backscattering electrons (SEM-BSE) and scanning electron microscopy with energy dispersive X-ray (SEM-EDX) data. The observed differences in the mineralogical composition of the core and shell regions of the studied fulgurite can be explained by taking into account the effects of both the diffusion of the melted material to the periphery of the fulgurite following the lightning and the faster cooling at the external shell region, together with the differential properties of the various minerals. The heavier materials diffused slower, leading to the concentration in the core of the fulgurite of the iron and barium containing minerals, hematite, and barite. They first underwent subsequent partial transformation into goethite due to meteoric water within the shell of the fulgurite. The faster cooling of the shell region kinetically trapped orthoclase, while the slower cooling in the core area allowed for the extensive formation of microcline, a lower temperature polymorph of orthoclase, thus justifying the prevalence of microcline in the core and a mixture of the two polymorphs in the shell. The total amount of the K-feldspars decreases only slightly in the shell, while quartz and albite appeared in somewhat larger amounts in this compartment of the fulgurite. On the other hand, at the surface of the fulgurite, barite could not be stabilized due to sulfate lost (in the form of SO2 plus O2 gaseous products). The conjugation of the performed Raman spectroscopy experiments with the chemometrics analysis (PCA and, in particular, MCR analyses) was shown to allow for the fast identification of the minerals present in the two compartments (shell and core) of the sample. This way, the XRD experiments could be done while knowing in advance the minerals that were present in the samples, strongly facilitating the data analysis, which for compositionally complex samples, such as that studied in the present investigation, would have been very much challenging, if possible.