The photoisomerization mechanism of azobenzene: a semiclassical simulation of nonadiabatic dynamics

We have simulated the photoisomerization dynamics of azobenzene, taking into account internal conversion and geometrical relaxation processes, by means of a semiclassical surface hopping approach. Both n-->pi* and pi-->pi* excitations and both cis-->trans and trans-->cis conversions have been considered. We show that in all cases the torsion around the N==N double bond is the preferred mechanism. The quantum yields measured are correctly reproduced and the observed differences are explained as a result of the competition between the inertia of the torsional motion and the premature deactivation of the excited state. Recent time-resolved spectroscopic experiments are interpreted in the light of the simulated dynamics.     

SPME-GC-MS and PTR-ToF-MS Techniques for the Profiling of the Metabolomic Pattern of VOCs and GC-MS for the Determination of the Cannabinoid Content of Three Cultivars of Cannabis sativa L. Pollen

Considering the large number of volatile molecules that characterize Cannabis sativa L., adequate investigation supported by the application of robust and effective analytical methods is essential to better understand the impact of these low- and medium-molecular-weight molecules on the entire phytocomplex. This work aimed to characterize the volatile fraction of the chemical profile of three different cultivars of Cannabis sativa L. pollen, grown in Italy, which were thoroughly investigated by the application of two complementary techniques: SPME-GC-MS and PTR-ToF-MS. Furthermore, in order to provide more information on the chemical profile of the matrices under study, the cannabinoid content of the hexane extracts was also measured by GC-MS. Until now, no similar study, in terms of survey techniques applied, has been performed on C. sativa pollen. The obtained results showed a high content of volatile molecules, which differentiated the three matrices. The data relating to the content of cannabinoids were also interesting as they showed that one of the three cultivars was richer than the others. Finally, an in-depth statistical survey was performed to better compare the investigated samples and identify the molecules that most contribute to differentiating them. The findings of this study may be useful for integrating the compositional information on C. sativa L.     

Stereoselective Epoxidation of Cyclic Dienes and Trienes by Dioxiranes

Epoxides are essential building blocks in organic chemistry. The epoxidation of unsubstituted cyclic dienes 2 , 3 , 4 and triene 5 using dimethyldioxirane ( 1a ) and its trifluoro analog 1b methyl(trifluoromethyl)dioxirane has been investigated. The excellent yields obtained (90–98%) are accompanied by outstandingly high diastereoselectivities (90–98%). Interpretation of results based upon the early idea that polar groups can direct the dioxirane attack by dipole–dipole interaction provides a likely rationale, along with a more generalized mechanistic view.     

Permutation Entropy-Based Interpretability of Convolutional Neural Network Models for Interictal EEG Discrimination of Subjects with Epileptic Seizures vs. Psychogenic Non-Epileptic Seizures

The differential diagnosis of epileptic seizures (ES) and psychogenic non-epileptic seizures (PNES) may be difficult, due to the lack of distinctive clinical features. The interictal electroencephalographic (EEG) signal may also be normal in patients with ES. Innovative diagnostic tools that exploit non-linear EEG analysis and deep learning (DL) could provide important support to physicians for clinical diagnosis. In this work, 18 patients with new-onset ES (12 males, 6 females) and 18 patients with video-recorded PNES (2 males, 16 females) with normal interictal EEG at visual inspection were enrolled. None of them was taking psychotropic drugs. A convolutional neural network (CNN) scheme using DL classification was designed to classify the two categories of subjects (ES vs. PNES). The proposed architecture performs an EEG time-frequency transformation and a classification step with a CNN. The CNN was able to classify the EEG recordings of subjects with ES vs. subjects with PNES with 94.4% accuracy. CNN provided high performance in the assigned binary classification when compared to standard learning algorithms (multi-layer perceptron, support vector machine, linear discriminant analysis and quadratic discriminant analysis). In order to interpret how the CNN achieved this performance, information theoretical analysis was carried out. Specifically, the permutation entropy (PE) of the feature maps was evaluated and compared in the two classes. The achieved results, although preliminary, encourage the use of these innovative techniques to support neurologists in early diagnoses.     

Curing of a rigid rod epoxy resin with an aliphatic diacid: an example of a lightly crosslinked liquid crystalline thermoset

By reacting a rigid rod epoxy terminated molecule (p-bis(2,3-epoxypropoxy)-α-methylstilbene) with an aliphatic carboxylic acid (decanedioic acid), a lightly crosslinked liquid crystalline network is obtained. This network exhibits a smectic-like phase. While the mesophasic structure resulted “frozen” by the crosslinks in the case of higly crosslinked liquid crystalline epoxy resins, in this case a reversible transition from the liquid crystalline to the isotropic phase is observed. Moreover, while curing the same rigid rod epoxy molecule with amines resulted in a thermoset with a nematic structure, in this case a more ordered mesophase can be obtained. Preliminary results show that it is possible to orient macroscopically the mesogenic chains by stretching thin films above the glass transition temperature (T_g) and then quickly cooling down to the glassy state. This makes this material very attractive in the field of optical applications.     

Binding models of reversible inhibitors to type-B monoamine oxidase

Interest in the inhibitors of type-B monoamine oxidase has grown in recent years, due to the evidence for multiple roles of one such agent (selegiline) in the pharmacological management of neurodegenerative disorders. A set of 130 reversible and selective inhibitors of MAO-B (including tetrazole, oxadiazolone, and oxadiazinone derivatives) were taken from the literature and subjected to a three-dimensional quantitative structure–activity relationship (3D-QSAR) study, using CoMFA and GOLPE procedures. The steric and lipophilic fields, alone and in combination, provided us with informative models and satisfactory predictions (q²=0.73). The validity of these models was checked against the 3D X-ray structure of human MAO-B. Flexible docking calculations, performed by using a new approach which took advantage from QXP and GRID computational tools, showed the diverse inhibitors to interact with MAO-B in a similar binding mode, irrespective of the heterocycle characterizing them. A significant trend of correlation was observed between estimated energies of the complexes and the experimental inhibition data.