Enhanced oral bioavailability of levormeloxifene and raloxifene by nanoemulsion: simultaneous bioanalysis using liquid chromatography-tandem mass spectrometry.

Aim & objective: Levormeloxifene (L-ORM) and raloxifene (RAL) are selective estrogen receptor modulators used in the treatment of postmenopausal osteoporosis and breast cancer. Here, we developed and validated a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous estimation of both drugs. Materials & methods: A quality-by-design (QbD) approach was used for the optimization of the nanoemulsion, and US FDA guidelines were followed for method validation. Results: Multiple reaction monitoring transitions were used for L-ORM (459.05→98.50), RAL (475.00→112.02) and internal standard (180.10→110.2). Analytes were resolved in a C18 column with 80:20 v/v% acetonitrile (ACN), 0.1% formic acid in triple-distilled water as a mobile phase. The developed method was linear over a concentration range of 1-600 ng/ml. Pharmacokinetic results of free L-ORM-RAL and the L-ORM-RAL nanoemulsion showed Cmax of free L-ORM - 70.65 ± 16.64, free RAL 13.53 ± 2.72, L-ORM nanoemulsion 65.07 ± 14.0 and RAL-nanoemulsion 59.27 ± 17.44 ng/ml. Conclusion: Future findings will contribute to the treatment of postmenopausal osteoporosis and breast cancer using L-ORM and RAL.

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LC-MS/MS method for simultaneous estimation of raloxifene, cladrin in rat plasma: application in pharmacokinetic studies.

Aim: A newer LC-MS/MS method was developed and validated for the simultaneous quantification of raloxifene (RL) and cladrin (CL). Methodology: Both drugs were resolved in RP-18 (4.6 × 50 mm, 5 µ) Xbridge Shield column using acetonitrile and 0.1% aqueous solution of formic acid (FA) (70:30% v/v) as mobile phase by using biological matrices in female Sprague-Dawley rats using-MS/MS. Results: The developed method was found to be linear over the concentration ranges of 1-600 ng/ml, and lower limit of quantification was 1 ng/ml for RL and CL, respectively. Pharmacokinetic results of RL+CL showed Cmax = 4.23 ± 0.61, 26.97 ± 1.14 ng/ml, at Tmax(h) 5.5 ± 1.00 and 3.5 ± 1.00, respectively. Conclusion: Pharmacokinetic study results will be useful in the future for the combined delivery of RL and CL for osteoporosis treatment.

Immunometabolic impact of pancreastatin inhibitor PSTi8 in MCD induced mouse model of oxidative stress and steatohepatitis.

AIM: Pancreastatin, a dysglycemic hormone that encourages inflammation and steatosis in a variety of metabolic disorder animal models. The purpose of this study is to determine the effect of the pancreastatin inhibitor PSTi8 on immunometabolic changes in the liver of MCD-induced NASH mice. MAIN METHODS: Methionine and choline-deficient (MCD) diet was used for the development of NASH. Liver enzymes like SGOT, SGPT, and ALP and lipid profiles were also performed in the serum. Further, immunophenotyping study was performed in the liver through flowcytometer. Subsequently, Hematoxylin and Eosin, Picro Sirius Red and Masson's Trichrome staining were done to check the liver morphology and collagen staining, respectively. Inflammatory cytokines were measured through ELISA and gene expression through RT-PCR. The expression of α-SMA was examined using immunohistochemistry and immunofluorescence staining. KEY FINDINGS: PSTi8 inhibited the expression of lipogenic genes in the liver and attenuated bad cholesterol, SGOT, SGPT, and ALP in the serum. PSTi8 improved the liver morphology and attenuated collagen deposition. Subsequently, PSTi8 attenuated inflammatory M1-macrophages, CD8+T, CD4+T cells and increased anti-inflammatory M2 macrophages, T-reg and eosinophil populations in the liver. It also attenuated the expression of pro-inflammatory genes like Mcp1, Tnfα, and Il6. Apart from this, PSTi8 attenuated the oxidative stress marker, like ROS, and MDA and fibrosis marker α-SMA in the liver. It also decreased the apoptosis and ROS and MDA level in the liver. SIGNIFICANCE: Overall, these compressive studies revealed that PSTi8 exhibited beneficial effect on the liver of MCD-induced NASH mice by attenuating inflammation and oxidative stress.

Pancreastatin inhibitor PSTi8 ameliorates insulin resistance by decreasing fat accumulation and oxidative stress in high-fat diet-fed mice.

Abnormal fat accumulation, enhanced free fatty acids (FFA) release, and their metabolites cause insulin resistance (IR) in major glucose-lipid metabolic organs such as skeletal muscle and adipose tissue. However, excessive lipolysis and FFA release from adipose tissue elevate plasma FFA levels leading to oxidative stress and skeletal muscle IR. Indeed, in obese individuals, there is enhanced pro-inflammatory secretion from adipose tissue influencing insulin signaling in skeletal muscles. Here, we investigated the effect of PSTi8 on FFA-induced IR in both in vitro and in vivo models. Palmitate (Pal)-treated 3T3-L1 cells increased lipid accumulation as well as lipolysis, which reduced the insulin-stimulated glucose uptake. PSTi8 treatment significantly prevented Pal-induced lipid accumulation, and release and enhanced insulin-stimulated glucose uptake. It further reduced the release of pro-inflammatory cytokines from Pal-treated 3T3-L1 cells as well as from adipose tissue explants. In addition, PSTi8 treatment decreases M1 surface markers in Pal-treated bone marrow-derived monocytes (BMDM). PSTi8 treatment also significantly enhanced the Pal-mediated reduced skeletal muscle glucose disposal and reduced intracellular oxidative stress. In vitro effect of PSTi8 was consistent with in vivo HFD-fed mice IR model. PSTi8 treatment in HFD-fed mice significantly improved glucose metabolism and enhanced skeletal muscle insulin sensitivity with reduced adiposity and pro-inflammatory cytokines. Taken together, our results support that PSTi8 treatment can protect both adipose and skeletal muscles from FFA-induced IR.

ChemSuite: A package for chemoinformatics calculations and machine learning.

Prediction of biological and toxicological properties of small molecules using in silico approaches has become a wide practice in pharmaceutical research to lessen the cost and enhance productivity. The development of a tool "ChemSuite," a stand-alone application for chemoinformatics calculations and machine-learning model development, is reported. Availability of multi-functional features makes it widely acceptable in various fields. Force field such as UFF is incorporated in tool for optimization of molecules. Packages like RDKit, PyDPI and PaDEL help to calculate 1D, 2D and 3D descriptors and more than 10 types of fingerprints. MinMax Scaler and Z-Score algorithms are available to normalize descriptor values. Varied descriptor selection and machine-learning algorithms are available for model development. It allows the user to add their own algorithm or extend the software for various scientific purposes. It is free, open source and has user-friendly graphical interface, and it can work on all major platforms.