Verubulin

Microtubules (MTs), as structural components of the cytoskeleton, are vital for axonal transport, information processing, and signaling within the brain. Disruption of MT integrity has been associated with neurological disorders, including alcohol use disorder (AUD). This study used positron emission tomography (PET) imaging with the radiotracer [¹¹C]MPC-6827 to investigate alcohol-induced changes in MT dynamics in a nonhuman primate model of AUD. Dynamic PET scans (0-120 min) were conducted in male cynomolgus monkeys (n = 4) before and after ∼7 months of ethanol self-administration (EtOH SA). Quantitative analysis of standardized uptake values and time-activity curves demonstrated a consistent decrease in [¹¹C]MPC-6827 uptake across multiple brain regions, particularly in the amygdala, globus pallidus, and substantia innominata. Statistically significant reductions in tracer uptake were observed in early scan windows (15 and 30 min), suggesting compromised MT integrity due to chronic EtOH SA. These findings provide compelling evidence that chronic alcohol consumption induces significant changes in microtubule dynamics, potentially contributing to pathological processes underlying AUD.

Drug-induced cardiotoxicity represents one of the most common causes of attrition of drug candidates in preclinical and clinical development. For this reason, the evaluation of cardiac toxicity is essential during drug development and regulatory review. In the present study, drug-induced postmarket adverse event combinations from the FDA Adverse Event Reporting System were extracted for 2002 drugs using 243 cardiac toxicity-related preferred terms (PTs). These PTs were combined into 12 groups based on their clinical relevance to serve as training sets. The optimal classification scheme was determined using a combination of data sources that included drug labeling information, published literature, clinical study data, and postmarket surveillance data. Two commercial QSAR platforms were used to construct 12 models, including general cardiac toxicity, cardiac ischemia, heart failure, cardiac valve disease, myocardial disease, pericardial disease, structural heart disease, cardiac arrhythmia, Torsades de Pointes, long QT syndrome, atrial fibrillation and ventricular arrhythmia, and cardiac arrest. The cross-validated performance for the new models reached a sensitivity of up to 80% and negative predictivity of up to 80%. These new models covering a wide range of cardiac endpoints will provide fast, reliable, and comprehensive predictions of potential cardiotoxic compounds in drug discovery and regulatory safety assessment.