• Blum Austin posted an update 6 months, 2 weeks ago

    Massive hemorrhage caused by the uncontrolled release of thrombolysis drugs is a key issue of thrombolysis therapy in clinical practice. In this study, we report a near-infrared (NIR) light-triggered drug delivery system, i.e., CuS@mSiO2-PEG (CSP) nanoparticles, for the loading of a thrombolytic drug (urokinase plasminogen activators, uPA). CSP nanoparticles with the CuS nanoparticles as photothermal agents and mesoporous SiO2 for the loading of uPA were synthesized using a facile hydrothermal method. The CSP core-shell nanoparticles were demonstrated to possess excellent photothermal performance, exhibiting a photothermal conversion efficiency of up to 52.8%. Due to the mesoporous SiO2 coating, the CSP core-shell nanoparticles exhibited appropriate pore size, high pore volume, and large surface area; thus, they showed great potential to be used as drug carriers. Importantly, the release of uPA from CuS@mSiO2-PEG/uPA (CSPA) carriers can be promoted by the NIR laser irradiation. The drug loading content of uPA for the as-prepared NIR-triggered drug delivery system was calculated to be 8.2%, and the loading efficiency can be determined to be as high as 89.6%. Due to the excellent photothermal effect of CSP nanocarriers, the NIR-triggered drug delivery system can be used for infrared thermal imaging in vivo. The in vivo thrombolysis assessment demonstrated that the NIR-triggered drug delivery system showed excellent thrombolytic ability under the irradiation of an 808 nm laser, showing the combined therapy for thrombolysis. As far as we know, the CSPA core-shell nanoparticles used as NIR-triggered drug delivery systems for thrombolysis have not been reported.Photopharmacology is an emerging field that uses light to precisely control drug activity. This strategy promises to improve drug specificity for reducing off-target effects. Proteolysis-targeting chimeras (PROTACs) are an advanced technology engineered to degrade pathogenic proteins through the ubiquitin-proteasome system for disease treatment. This approach has the potential to target the undruggable proteome via event-driven pharmacology. Recently, the combination strategy of photopharmacology and PROTACs has gained tremendous momentum for its use in the discovery and development of new therapies. This review systematically focuses on PROTAC-based photopharmacology. Herein, we provide an overview of the new and vibrant research on photoPROTACs, discuss the advantages and disadvantages of this approach as a biological tool, and outline the challenges it faces in a clinical setting.In this work, titanium carbide (TiC) nanoparticles have been successfully synthesized at much lower temperatures of 500°C using cheaper starting materials, such as waste polytetrafluoroethylene (PTFE) (carbon source) and titanium and metallic sodium, than the traditional carbothermal reduction of TiO2 at 1,800°C. An XRD pattern proved the formation of face-centered cubic TiC, and TEM images showed the obtained TiC nanoparticles with an average size of approximately 50 nm. In addition, the separator coated with TiC nanoparticles as an active material of interlayer effectively mitigates the shuttling problem by taming the polysulfides in Li-S batteries compared with a traditional celgard separator. The assembled cell realizes good cycling stability with 501 mAh g-1 and a low capacity fading of 0.1% per cycle after 300 cycles at 1 C due to high utilization of the sulfur-based active species.The structural characterization of clusters or nanoparticles is essential to rationalize their size and composition-dependent properties. As experiments alone could not provide complete picture of cluster structures, so independent theoretical investigations are needed to find out a detail description of the geometric arrangement and corresponding properties of the clusters. The potential energy surfaces (PES) are explored to find several minima with an ultimate goal of locating the global minima (GM) for the clusters. Optimization algorithms, such as genetic algorithm (GA), basin hopping method and its variants, self-consistent basin-to-deformed-basin mapping, heuristic algorithm combined with the surface and interior operators (HA-SIO), fast annealing evolutionary algorithm (FAEA), random tunneling algorithm (RTA), and dynamic lattice searching (DLS) have been developed to solve the geometrical isomers in pure elemental clusters. Various model or empirical potentials (EPs) as Lennard-Jones (LJ), Born-Mayer, Gupta, Sutton-Chen, and Murrell-Mottram potentials are used to describe the bonding in different type of clusters. Due to existence of a large number of homotops in nanoalloys, genetic algorithm, basin-hopping algorithm, modified adaptive immune optimization algorithm (AIOA), evolutionary algorithm (EA), kick method and Knowledge Led Master Code (KLMC) are also used. In this review the optimization algorithms, computational techniques and accuracy of results obtained by using these mechanisms for different types of clusters will be discussed.This review will outline the recent advances in chemo-, regio-, and stereoselective (cross-) dimerization of terminal alkynes to generate 1,3-enynes using different types of iron and cobalt catalysts with altering oxidation states of the active species. In general, the used ligands have a crucial effect on the stereoselectivity of the reaction; e.g., bidentate phosphine ligands in cobalt catalysts can generate the E-configured head-to-head dimerization product, while tridentate phosphine ligands can generate either the Z-configured head-to-head dimerization product or the branched head-to-tail isomer. Furthermore, the hydroalkynylation of silyl-substituted acetylenes as donors to internal alkynes as acceptors will be discussed using cobalt and nickel catalysts.Parasitic diseases remain as unresolved health issues worldwide. While for some parasites the treatments involve drug combinations with serious side effects, for others, chemical therapies are inefficient due to the emergence of drug resistance. This urges the search for novel antiparasitic agents able to act through multiple mechanisms of action. Here, we report the first multi-target model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mt-QSAR-MLP) to virtually design and predict versatile inhibitors of proteins involved in the survival and/or infectivity of different pathogenic parasites. The mt-QSAR-MLP model exhibited high accuracy (>80%) in both training and test sets for the classification/prediction of protein inhibitors. click here Several fragments were directly extracted from the physicochemical and structural interpretations of the molecular descriptors in the mt-QSAR-MLP model. Such interpretations enabled the generation of four molecules that were predicted as multi-target inhibitors against at least three of the five parasitic proteins reported here with two of the molecules being predicted to inhibit all the proteins.

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