Coronary heart disease remains one of the leading causes of death in most countries. Healthcare improvements have seen a shift in the presentation of disease with a reducing number of ST-segment elevation myocardial infarctions (STEMIs), largely due to earlier reperfusion strategies such as percutaneous coronary intervention (PCI).  https://www.selleckchem.com/products/protac-tubulin-degrader-1.html  Stents have revolutionized the care of these patients, but the long-term effects of these devices have been brought to the fore. The conceptual and technologic evolution of these devices from bare-metal stents led to the creation and wide application of drug-eluting stents; further research introduced the idea of polymer-based resorbable stents. We look at the evolution of stents and the multiple advantages and disadvantages offered by each of the different polymers used to make stents in order to identify what the stent of the future may consist of whilst highlighting properties that are beneficial to the patient alongside the role of the surgeon, the cardiologist, engineers, chemists, and biophysicists in creating the ideal stent.Recent findings have brought forward the potential of carbon nano-species, especially nanotubes and graphene, to impart exceptional multifunctional potential to cement, offering simultaneous enhancement of mechanical, fracture mechanical and electrical properties. While available knowledge on the topic is still limited, there is a complete absence of direct comparisons of the potential of the nano-species to improve strength and toughness and provide multifunctionality to the mortars. The study offers a comprehensive overview of these potentials, for mortars modified with pure graphene nanoplatelets and carbon nanotubes at consistent, directly comparable, concentrations up to 1.2 wt.%. Testing included flexure under pure bending moments, axial compression, electrical resistivity measurements and fracture tests under three point bending configuration; the latter were also independently assessed by acoustic emission. Differences in documented properties and optimal concentrations associated with improved mechanical performance were directly compared and rationalized in terms of nanospecies morphology. Dramatic, statistically consistent improvements in fracture behavior, up to 10-fold of control values, were documented for specific nanofiller concentrations, indicating an excellent potential of the material system for contemporary smart construction applications. An exceptionally favorable comparison of acoustic emission and fracture energy data confirmed that the non-destructive technique can independently assess the fracture performance of mortars with exceptional precision.Deep eutectic solvents (DESs) represent an emergent class of green designer solvents that find numerous applications in different aspects of chemical synthesis. A particularly appealing aspect of DES systems is their simplicity of preparation, combined with inexpensive, readily available starting materials to yield solvents with appealing properties (negligible volatility, non-flammability and high solvation capacity). In the context of polymer science, DES systems not only offer an appealing route towards replacing hazardous volatile organic solvents (VOCs), but can serve multiple roles including those of solvent, monomer and templating agent-so called "polymerizable eutectics." In this review, we look at DES systems and polymerizable eutectics and their application in polymer materials synthesis, including various mechanisms of polymer formation, hydrogel design, porous monoliths, and molecularly imprinted polymers. We provide a comparative study of these systems alongside traditional synthetic approaches, highlighting not only the benefit of replacing VOCs from the perspective of environmental sustainability, but also the materials advantage with respect to mechanical and thermal properties of the polymers formed.(1) Background and objectives Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality throughout the world. In addition to genetics, increasing evidence suggests that Vitamin D (VitD) might be involved in different pathogenic mechanisms in COPD. Furthermore, the prevalence of VitD insufficiency is exceptionally high in COPD patients and increases with the severity. Based on the above, we first tested the relation between the top 10 single nucleotide polymorphisms from genome-wide association studies and the risk of COPD. Then, we investigated whether VitD levels might also have a role in COPD. A meta-analysis followed, combining our participants with previously published European and non-European populations (15,716 cases and 48,107 controls). (2) Methods 631 Lebanese participants were recruited, of which ~28% were affected with COPD. Demographic and clinical data were collected, and DNA was genotyped using Kompetitive allele-specific PCR (KASPTM). Adjusted multiple logistic regression models were used. Bonferroni corrections were also applied. The statistical power was also assessed. (3) Results Both rs6837671A>G in FAM13A and VitD levels were significantly associated with increased risk of COPD (OR = 1.75, p = 0.01, and OR = 3.10, p G in FAM13A is a trans-ethnic genetic variant that interact with VitD to affect COPD.The increasing availability of molecular data provided by next-generation sequencing (NGS) techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal cancer. Reliable and accurate predictors based on selected gene panels are urgently needed for better stratification of renal cell carcinoma (RCC) patients in order to define a personalized treatment plan. Artificial intelligence (AI) algorithms are currently in development for this purpose. Here, we reviewed studies that developed predictors based on AI algorithms for diagnosis and prognosis in renal cancer and we compared them with non-AI-based predictors. Comparing study results, it emerges that the AI prediction performance is good and slightly better than non-AI-based ones. However, there have been only minor improvements in AI predictors in terms of accuracy and the area under the receiver operating curve (AUC) over the last decade and the number of genes used had little influence on these indices. Furthermore, we highlight that different studies having the same goal obtain similar performance despite the fact they use different discriminating genes.