Magnetic Resonance-Guided Focused Ultrasound Thalamotomy Rebalances Atypical Functional Hierarchy in Patients with Essential Tremor.

Magnetic resonance-guided focused ultrasound (MRgFUS) has brought thalamotomy back to the frontline for essential tremor (ET). As functional organization of human brain strictly follows hierarchical principles which are frequently deficient in neurological diseases, whether additional damage from MRgFUS thalamotomy induces further disruptions of ET functional scaffolds are still controversial. This study was to examine the alteration features of brain functional frameworks following MRgFUS thalamotomy in patients with ET. We retrospectively obtained preoperative (ETpre) and postoperative 6-month (ET6m) data of 30 ET patients underwent MRgFUS thalamotomy from 2018 to 2020. Their archived functional MR images were used to functional gradient comparison. Both supervised pattern learning and stepwise linear regression were conducted to associate gradient features to tremor symptoms with additional neuropathophysiological analysis. MRgFUS thalamotomy relieved 78.19% of hand tremor symptoms and induced vast global framework alteration (ET6m vs. ETpre: Cohen d = - 0.80, P < 0.001). Multiple robust alterations were identified especially in posterior cingulate cortex ([Formula: see text] ET6m vs. [Formula: see text] ETpre: Cohen d = 0.87, P = 0.048). Compared with matched health controls (HCs), its gradient distances to primary communities were significantly increased in [Formula: see text] ETpre patients with anomalous stepwise connectivity (P < 0.05 in ETpre vs. HCs), which were restored after MRgFUS thalamotomy. Both global and regional gradient features could be used for tremor symptom prediction and were linked to neuropathophysiological features of Parkinson disease and oxidative phosphorylation. MRgFUS thalamotomy not only suppress tremor symptoms but also rebalances atypical functional hierarchical architecture of ET patients.

Novel carbohydrate-triazole derivatives as potential α-glucosidase inhibitors.

A series of novel pyrano[2, 3-d]trizaole compounds were synthesized and their α-glucosidase inhibitory activities were evaluated by in vitro enzyme assay. The experimental data demonstrated that compound 10f showed up to 10-fold higher inhibition (IC5074.0 ± 1.3 µmol·L-1) than acarbose. The molecular docking revealed that compound 10f could bind to α-glucosidase via the hydrophobic, π-π stacking, and hydrogen bonding interactions. The results may benefit further structural modifications to find new and potent α-glucosidase inhibitors.

[Analysis of traditional Chinese medicine prescriptions based on support vector machine and analytic hierarchy process].

Combined use of drugs is a hot spot in the research of new drugs nowadays, and traditional Chinese medicine (TCM) is a classic practice in the combined use of drugs. In this paper, the compatibility of TCM prescriptions and the related properties of composed herbs were calculated and studied to verify and discuss the feasibility of the results in guiding compatibility. Research Group on New Drug Design, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences had established a structured database of TCM prescriptions by using traditional Chinese medicine inheritance support system (TCMISS V2.0), including 4 012 prescription compatibilities, 2 072 drug components, 381 kinds of TCM diseases, 316 kinds of TCM syndromes and 26 kinds of drug properties. On the basis of the created database above, Support Vector Machine (SVM) was used to analyze the prescription compatibility data and establish a model for predicting feasibility of drug compatibilities. Analytic Hierarchy Process (AHP) and cluster analysis were used to study the influence of drug properties in the rationality of prescription compatibility. The computational results showed that the accuracy in efficacy prediction of two data sets, i.e. prescription-disease and prescription-syndrome, was up to 90% in the linear SVM model. The macro₋averaging and micro₋averaging of the two models were around 0.92, 0.46, respectively. After AHP mapping, most of the incompatible combinations showed significant difference with other drug combinations during the clustering process in the vertical icicle, indicating that the proper machine learning algorithm can be used to lay the foundation for further exploring the combination rules in TCM and establishing more detailed drug-disease and syndrome predicting models, and provide theoretical guidance for the study of the combined use of drugs to a certain degree.