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Paddlewheel-type and half-paddlewheel-type diruthenium(II,II) complexes with 1,8-naphthyridine-2-carboxylate.
Dalton Trans
January 2025
Department of Chemistry, Graduate School of Natural Science and Technology, Shimane University, 1060, Nishikawatsu, Matsue, Shimane, 690-8504, Japan.
Paddlewheel-type diruthenium(II,II) complexes are paramagnetic with two unpaired electrons ( = 1) and can be utilized as versatile building blocks for higher-order structures, such as supramolecular complexes, coordination polymers, and metal-organic frameworks, although they are generally highly air-sensitive. In this study, we developed an air-stable paddlewheel-type diruthenium(II,II) complex with two electron-withdrawing 1,8-naphthyridine-2-carboxylate (npc) ligands, [Ru(μ-npc)(OCMe)] (1). The two acetate ligands in 1 can be replaced by other carboxylate ligands; the solvothermal reactions of 1 with benzoic acid (HOCPh) yields the heteroleptic [Ru(μ-npc)(OCPh)] (2), whereas its reaction with 1,8-naphthyridine-2-carboxylic acid (Hnpc) produces the homoleptic [Ru(μ-npc)(η-npc)] (3).
View Article and Find Full Text PDFMolecular Modeling of Vasodilatory Activity: Unveiling Novel Candidates Through Density Functional Theory, QSAR, and Molecular Dynamics.
Int J Mol Sci
November 2024
Grupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, vía Puerto Colombia, Barranquilla 081007, Colombia.
Cardiovascular diseases (CVD) pose a significant global health challenge, requiring innovative therapeutic strategies. Vasodilators, which are central to vasodilation and blood pressure reduction, play a crucial role in cardiovascular treatment. This study integrates quantitative structure- (QSAR) modeling and molecular dynamics (MD) simulations to predict the biological activity and interactions of vasodilatory compounds with the aim to repurpose drugs already known and estimateing their potential use as vasodilators.
View Article and Find Full Text PDFResilience of primary healthcare facilities: Experiences from 16 European countries during the COVID-19 pandemic. A mixed-methods study conducted by EURIPA.
Adv Clin Exp Med
December 2024
European Rural and Isolated Practitioners Association (EURIPA), Paris, France.
Background: The role of primary healthcare (PHC) during a pandemic varies across European countries. The coronavirus disease 2019 (COVID-19) pandemic has altered the working practices of family medicine doctors and impacted the resilience of healthcare systems.
Objectives: This study aimed to examine European healthcare system responses to the pandemic, focusing on rural and urban differences.
Isolated p-Block Antimony Atoms Activated CuO@Co-CN Enable High Performances for Water Splitting and Zn-Air Batteries.
Small
December 2024
Department of Nano Convergence Engineering, Jeonbuk National University, Jeonju, Jeonbuk, 54896, Republic of Korea.
This study reports an effective strategy for designing 3D electrocatalyst via the deposition of ZIF67-derived Co-CN shell layer over CuO nanoarrays to form a CuO@Co-CN hybrid, followed by incorporation with p-block Sb single atoms (CuO@Co-CN/Sb) to obtain highly activated catalytic behaviors. Inheriting both the excellent intrinsic catalytic activity of the components and their synergy, the CuO@Co-CN/Sb material serves as a high-efficiency multifunctional catalyst for overall water splitting and zinc (Zn)-air batteries. The material yields a current density of 10 mA cm at a low overpotential of 72 and 250 mV for the hydrogen evolution reaction and oxygen evolution reaction, respectively.
View Article and Find Full Text PDFDerivation and Validation of Prediction of Preterm Preeclampsia Using Machine Learning Algorithms.
Am J Perinatol
December 2024
Department of Obstetrics and Gynecology, Macon and Joan Brock Virginia Health Sciences at Old Dominion University (ODU), Norfolk, Virginia.
Article Synopsis
- * Study Design: Researchers analyzed data from the Nulliparous Pregnancy Outcomes Study, focusing on 131 factors like maternal demographics and health history, and developed several machine learning models, eventually choosing the XGBoost model for its strong performance.
- * Results: Out of 9,467 participants, 219 experienced preterm preeclampsia, with the XGBoost model achieving the highest accuracy (AUC of 0.749). The final model, based on 8 key features, showed slightly lower performance (AUC of 0.741) but
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