Mechanisms for Ssp3–H functionalization of thiolacetic acid, initiated by AIBN, have been investigated by M06‐2X‐D3/ma‐def2‐TZVP method and basis set, and SMD model was employed to simulate the solvent effect of toluene. The computational results suggest that azodiisobutyronitrile (AIBN), as the radical initiator, would have an intramolecular homolytic reaction; then Ssp3–H activation of thiolacetic acid could be finished via two possible paths; the obtained thiyl radical and diyne would go through electrophilic reaction, ring‐closure reaction, and SN2 reaction to yield 3,4‐fused‐ring‐substituted thiophenes. While in the second part, the mechanism of side reaction has also been investigated, revealing that main reaction has a lower energy barrier. Localized orbital locator isosurfaces and electron spin density isosurface graphs can analyze the structures and reveal the substances.
Background Migraine is a complex disorder characterized by debilitating headaches. Despite its prevalence, its pathophysiology remains unknown, with subsequent gaps in diagnosis and treatment. We combined machine learning with connectivity analysis and applied a whole-brain network approach to identify potential targets for migraine diagnosis and treatment. Methods Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI(rfMRI), and diffusion weighted scans were obtained from 31 patients with migraine, and 17 controls. A recently developed machine learning technique, Hollow Tree Super (HoTS) was used to classify subjects into diagnostic groups based on functional connectivity (FC) and derive networks and parcels contributing to the model. PageRank centrality analysis was also performed on the structural connectome to identify changes in hubness. Results Our model attained an area under the receiver operating characteristic curve (AUC-ROC) of 0.68, which rose to 0.86 following hyperparameter tuning. FC of the language network was most predictive of the model’s classification, though patients with migraine also demonstrated differences in the accessory language, visual and medial temporal regions. Several analogous regions in the right hemisphere demonstrated changes in PageRank centrality, suggesting possible compensation. Conclusions Although our small sample size demands caution, our preliminary findings demonstrate the utility of our method in providing a network-based perspective to diagnosis and treatment of migraine.
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