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Pancreatic cancer is a very aggressive disease with a dismal prognosis. The tumor microenvironment exerts immunosuppressive activities through the secretion of several cytokines, including interleukin (IL)-1. The IL-1/IL-1 receptor (IL-1R) axis is a key regulator in tumor-promoting T helper (Th)2- and Th17-type inflammation. Th2 cells are differentiated by dendritic cells endowed with Th2-polarizing capability by the thymic stromal lymphopoietin (TSLP) that is secreted by IL-1-activated cancer-associated fibroblasts (CAFs). Th17 cells are differentiated in the presence of IL-1 and other IL-1-regulated cytokines. In pancreatic cancer, the use of a recombinant IL-1R antagonist (IL1RA, anakinra, ANK) in in vitro and in vivo models has shown efficacy in targeting the IL-1/IL-1R pathway. In this study, we have developed sphingomyelin nanosystems (SNs) loaded with ANK (ANK-SNs) to compare their ability to inhibit Th2- and Th17-type inflammation with that of the free drug in vitro. We found that ANK-SNs inhibited TSLP and other pro-tumor cytokines released by CAFs at levels similar to ANK. Importantly, inhibition of IL-17 secretion by Th17 cells, but not of interferon-γ, was significantly higher, and at lower concentrations, with ANK-SNs compared to ANK. Collectively, the use of ANK-SNs might be beneficial in reducing the effective dose of the drug and its toxic effects. [ABSTRACT FROM AUTHOR]

Arylalkane-derived prodrugs of arylacetic acids are a small group of substances that have long been known for their anti-inflammatory action. Despite their ease of synthesis and good potential for the development of new potent and safe anti-inflammatory agents, this group of substances has not received much attention from researchers so far. Therefore, representative arylalkane derivatives were investigated through molecular docking techniques to verify the possible hepatic activation mode toward active metabolites by CYP1A2. In this regard, arylalkanoic acid prodrugs were docked with a crystallographic structure of human CYP1A2, in which the enzyme is co-crystallized with the selective competitive inhibitor α-naphthoflavone BHF. Of note, all the examined compounds proved capable of interacting with the enzyme active site in a manner similar to Nabumetone, thus confirming that a productive metabolic transformation is feasible. On the basis of these findings, it is possible to argue that subtle differences in the way CYP1A2 accommodates the ligands depend on the fine details of their molecular structures. Overall, these data suggest that compounds simply formed by an aromatic moiety bearing an appropriate alkane-derived chain could lead to innovative anti-inflammatory agents. [ABSTRACT FROM AUTHOR]

This paper describes the synthesis of 1,4-dihydropyridine compounds (DHPs) endowed with good muscle relaxant activity and stability to light. Six new condensed DHPs were synthesized by the microwave irradiation method. A long-chain ester moiety [2-(methacryloyloxy)ethyl] and various substituents on the phenyl ring were demonstrated to affect the muscle relaxant activity occurring in isolated rabbit gastric fundus smooth muscle strips. Forced photodegradation conditions were applied to the molecules according to the ICH rules. The degradation profile of the drugs was monitored by spectrophotometry coupled with the multivariate curve resolution technique. Formation of the oxidized pyridine derivative was observed for all the studied DHPs, except for one compound, which showed very fast degradation and formation of a second photo-product. Pharmacological tests on the molecules showed a good muscle relaxing effect, with a mechanism similar to that of nifedipine, however, proving to be more stable to light.

Letrozole is one of the most prescribed drugs for the treatment of breast cancer in post-menopausal women, and it is endowed with selective peripheral aromatase inhibitory activity. The efficacy of this drug is also a consequence of its long-lasting activity, likely due to its metabolic stability. The reactivity of cyano groups in the letrozole structure could, however, lead to chemical derivatives still endowed with residual biological activity. Herein, the chemical degradation process of the drug was studied by coupling multivariate curve resolution and spectrophotometric methodologies in order to assess a detailed kinetic profile. Three main derivatives were identified after drug exposure to different degradation conditions, consisting of acid-base and oxidative environments and stressing light. Molecular docking confirmed the capability of these compounds to accommodate into the active site of the enzyme, suggesting that the sustained inhibitory activity of letrozole may be at least in part attributed to the degradation compounds. [ABSTRACT FROM AUTHOR]

Virgin coconut oil (VCO) is a functional food with important health benefits. Its economic interest encourages fraudsters to deliberately adulterate VCO with cheap and low-quality vegetable oils for financial gain, causing health and safety problems for consumers. In this context, there is an urgent need for rapid, accurate, and precise analytical techniques to detect VCO adulteration. In this study, the use of Fourier transform infrared (FTIR) spectroscopy combined with multivariate curve resolution–alternating least squares (MCR-ALS) methodology was evaluated to verify the purity or adulteration of VCO with reference to low-cost commercial oils such as sunflower (SO), maize (MO) and peanut (PO) oils. A two-step analytical procedure was developed, where an initial control chart approach was designed to assess the purity of oil samples using the MCR-ALS score values calculated on a data set of pure and adulterated oils. The pre-treatment of the spectral data by derivatization with the Savitzky–Golay algorithm allowed to obtain the classification limits able to distinguish the pure samples with 100% of correct classifications in the external validation. In the next step, three calibration models were developed using MCR-ALS with correlation constraints for analysis of adulterated coconut oil samples in order to assess the blend composition. Different data pre-treatment strategies were tested to best extract the information contained in the sample fingerprints. The best results were achieved by derivative and standard normal variate procedures obtaining RMSEP and RE% values in the ranges of 1.79–2.66 and 6.48–8.35%, respectively. The models were optimized using a genetic algorithm (GA) to select the most important variables and the final models in the external validations gave satisfactory results in quantifying adulterants, with absolute errors and RMSEP of less than 4.6% and 1.470, respectively. [ABSTRACT FROM AUTHOR]