Long-term Follow-up Optical Coherence Tomography Assessment of Primary Percutaneous Coronary Intervention for Unprotected Left Main.

Background: Elective unprotected left main (ULM) percutaneous coronary intervention (PCI) has long-term mortality rates comparable to surgical revascularization, thanks to advances in drug-eluting stent (DES) design, improved PCI techniques, and frequent use of intravascular imaging. However, urgent PCI of ULM culprit lesions remains associated with high in-hospital mortality and unfavourable long-term outcomes, including DES restenosis and stent thrombosis (ST). This analysis aimed to examine the long-term outcomes and healing of DES implanted in ULM during primary PCI using high-resolution optical coherence tomography (OCT) imaging.

Sentiment classification for insider threat identification using metaheuristic optimized machine learning classifiers.

This study examines the formidable and complex challenge of insider threats to organizational security, addressing risks such as ransomware incidents, data breaches, and extortion attempts. The research involves six experiments utilizing email, HTTP, and file content data. To combat insider threats, emerging Natural Language Processing techniques are employed in conjunction with powerful Machine Learning classifiers, specifically XGBoost and AdaBoost.

Dose-Dependent Induction of Differential Seizure Phenotypes by Pilocarpine in Rats: Considerations for Translational Potential.

: Pilocarpine is used in experimental studies for testing antiepileptic drugs, but further characterization of this model is essential for its usage in testing novel drugs. The aim of our study was to study the behavioral and EEG characteristics of acute seizures caused by different doses of pilocarpine in rats. : Male Wistar rats were treated with a single intraperitoneal dose of 100 mg/kg (P100), 200 mg/kg (P200), or 300 mg/kg (P300) of pilocarpine, and epileptiform behavior and EEG changes followed within 4 h.

Electrochemical Performance of Niobium MXenes with Lanthanum.

MXenes are the newest class of two-dimensional nanomaterials characterized by large surface area, high conductivity, and hydrophilicity. To further improve their performance for use in energy storage devices, heteroatoms or functional groups can be inserted into the Mxenes' structure increasing their stability. This work proposes insertion of lanthanum atoms into niobium-MXene (Nb-MX/La) that was characterized in terms of morphogy, structure, and electrochemical behavior.