The Saric ßic ßek howardite meteorite shower consisting of 343 documented stones occurred on September 2, 2015 in Turkey and is the first documented howardite fall. Cosmogenic isotopes show that Saric ßic ßek experienced a complex cosmic-ray exposure history, exposed during~12-14 Ma in a regolith near the surface of a parent asteroid, and that añ 1 m sized meteoroid was launched by an impact 22 AE 2 Ma ago to Earth (as did one-third of all HED meteorites). SIMS dating of zircon and baddeleyite yielded 4550.4 AE 2.5 Ma and 4553 AE 8.8 Ma crystallization ages for the basaltic magma clasts. The apatite U-Pb age of 4525 AE 17 Ma, K-Ar age of~3.9 Ga, and the U,Th-He ages of 1.8 AE 0.7 and 2.6 AE 0.3 Ga are interpreted to represent thermal metamorphic and impact-related resetting ages, respectively. Petrographic; geochemical; and O-, Cr-, and Ti-isotopic studies confirm that Saric ßic ßek belongs to the normal clan of HED meteorites. Petrographic observations and analysis of organic material indicate a small portion of carbonaceous chondrite material in the Saric ßic ßek regolith and organic contamination of the meteorite after a few days on soil. Video observations of the fall show an atmospheric entry at 17.3 AE 0.8 km s À1 from NW; fragmentations at 37, 33, 31, and 27 km altitude; and provide a pre-atmospheric orbit that is the first dynamical link between the normal HED meteorite clan and the inner Main Belt. Spectral data indicate the similarity of Saric ßic ßek with the Vesta asteroid family (V-class) spectra, a group of asteroids stretching to delivery resonances, which includes (4) Vesta. Dynamical modeling of meteoroid delivery to Earth shows that the complete disruption of ã 1 km sized Vesta family asteroid or a~10 km sized impact crater on Vesta is required to provide sufficient meteoroids ≤4 m in size to account for the influx of meteorites from this HED clan. The 16.7 km diameter Antionia impact crater on Vesta was formed on terrain of the same age as given by the 4 He retention age of Saric ßic ßek. Lunar scaling for crater production to crater counts of its ejecta blanket show it was formed~22 Ma ago.A field expedition to the area was conducted by the
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.
Seeds belonging to fourth generation mutants (M4) of Ataem-7 cultivar (A7) variety and S04-05 (S) breeding line salt-tolerant soybeans were investigated by Raman spectroscopy, complemented by chemometrics methods, in order to evaluate changes induced by mutations in the relative lipid–protein contents, and to find fast, efficient strategies for discrimination of the mutants and the control groups based on their Raman spectra. It was concluded that gamma irradiation caused an increase in the lipid to protein ratio of the studied Ataem-7 variety mutants, while it led to a decrease of this ratio in the investigated S04-05 breeding line mutants. These results were found to be in agreement with data obtained by reflectance spectrum analysis of the seeds in the full ultraviolet to near-infrared spectral region and suggest the possibility of developing strategies where gamma irradiation can be used as a tool to improve mutant soybean plants targeted to different applications, either enriched in proteins or in lipids. Ward's clustering and principal component analysis showed a clear discrimination between mutants and controls and, in the case of the studied S-type species, discrimination between the different mutants. The grouping scheme is also found to be in agreement with the compositional information extracted from the analysis of the lipid–protein contents of the different samples.
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.
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