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Predicting links between the nodes of a graph has become an important Data Mining task because of its direct applications to biology, social networking, communication surveillance, and other domains. Recent literature in time-series link prediction has shown that the Vector Auto Regression (VAR) technique is one of the most accurate for this problem. In this study, we apply Support Vector Machine (SVM) to improve the VAR technique that uses an unweighted adjacency matrix along with 5 matrices: Common Neighbor (CN), Adamic-Adar (AA), Jaccard’s Coefficient (JC), Preferential Attachment (PA), and Research Allocation Index (RA). A DBLP dataset covering the years from 2003 until 2013 was collected and transformed into time-sliced graph representations. The appropriate matrices were computed from these graphs, mapped to the feature space, and then used to build baseline VAR models with lag of 2 and some corresponding SVM classifiers. Using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) as the main fitness metric, the average result of 82.04% for the VAR was improved to 84.78% with SVM. Additional experiments to handle the highly imbalanced dataset by oversampling with SMOTE and undersampling with K-means clusters, however, did not improve the average AUC-ROC of the baseline SVM.

Small molecule molecular glues can nucleate protein complexes and rewire interactomes. Molecular glues are widely used as probes for understanding functional proximity at a systems level, and the potential to instigate event-driven pharmacology has motivated their application as therapeutics. Despite advantages such as cell permeability and the potential for low off-target activity, glues are still rare when compared to canonical inhibitors in therapeutic development. Their often simple structure and specific ability to reshape protein-protein interactions pose several challenges for widespread, designer applications. Molecular glue discovery and design campaigns can find inspiration from the fields of synthetic biology and biophysics to mine chemical libraries for glue-like molecules., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

After initial failure with conventional angioplasty of a total right coronary artery occlusion, we were successful in obtaining patency using a combination of intracoronary thrombectomy and thrombolysis. This represents the first report of this technique in the therapy of total right coronary occlusions.