Nicotinic acid modulates microglial TREM-2 gene in Phytohaemagglutinin-Induced in vitro model of Alzheimer's disease like pathology.

Alzheimer's disease (AD) is a multifactorial,neurodegenerative disorder linked withextracellular amyloid beta (Aß) plaques deposition and formation of intracellular neurofibrillary tangles (NFTs). Currently, no effective therapies are available to cure AD. Neuroinflammation isa well-known hallmark in the onset and advancement of AD and triggering receptor expressed on myeloid cells-2 (TREM-2), a microglial gene, is responsible for regulating inflammatory responses and clearance of cellular debris. Loss of TREM-2functionincreases neuroinflammation associated expression of pro-inflammatory markersthus resultingin reduced clearance of Aß that further aid in disease progression.Therefore, targeting neuroinflammation is a good therapeutic approach for AD. This study aimed to determine the neuroprotective effect of nicotinic acid (NA) in vitro model of AD-like pathology induced in F-98 cell line using Phytohemagglutinin (PHA). MTT assay was employed for checking the cell viability as well as the proliferation of the cells following treatment with NA. PHA at the concentration of 10 µg/mL produces maximum plaques. The neuroprotective effect of NA was next evaluated against PHA-induced plaques and it was observed that NA reverses the damages induced by PHA i.e., by inhibiting the clustering of the cells and replacing the damaged cells with the new ones. Further, NA also increased the expression of TREM-2/DAP-12 with parallel decreased in the expression of IL-1ß, TNF-α and iNOS. It also successfully altered disease associated ADAM-10 and BACE-1 compared to PHA control. These findings suggest that NA might be considered as a good therapeutic candidate for the treatment of neurodegenerative disorders like AD.

Quantitative analysis of cephalexin in solid dosage form by Raman spectroscopy and chemometric tools.

OBJECTIVE: To use Raman Spectroscopy for qualitative and quantitative evaluation of pharmaceutical formulations of active pharmaceutical ingredient (API) of Cephalexin. SIGNIFICANCE: Raman Spectroscopy is a noninvasive, nondestructive, reliable and rapid detection technique used for various pharmaceutical drugs quantification. The present study explores the potential of Raman Spectroscopy for quantitative analysis of pharmaceutical drugs. METHOD: For qualitative and quantitative analysis of Cephalexin API, various standard samples containing less and more concentration of API than commercial tablet was prepared. To study spectral differences, the mean plot of all the samples was prepared. For qualitative analysis, Principal Component Analysis (PCA) and for quantitative analysis Partial Least Square Regression analysis (PLSR) was used. Both of these are Multivariate data analysis techniques and give reliable results as published in previous literature. RESULTS: PCA model distinguished all the Raman Spectral data related to the various Cephalexin solid dosage formulations whereas the PLSR model was used to calculate the concentration of different unknown formulations. For the PLSR model, RMSEC and RMSEP were determined to be 3.3953 and 3.8972, respectively. The prediction efficiency of this built PLSR model was found to be very good with a goodness of the model value (R2) of 0.98. The PLSR model also predicted the concentrations of Cephalexin formulations in the blind or unknown sample. CONCLUSION: These findings demonstrate that the Raman spectroscopy coupled to PLSR analysis could be regarded as a fast and effectively reliable tool for quantitative analysis of pharmaceutical drugs.

Raman Spectroscopy for the Quantitative Analysis of Solid Dosage Forms of the Active Pharmaceutical Ingredient of Febuxostat.

Raman spectroscopy has been used to characterize and quantify the solid dosage forms of the commercially available drug febuxostat. For this purpose, different formulations consisting of the febuxostat (API) and excipients with different concentrations of the API are prepared and analyzed by Raman spectroscopy to identify different spectral features related to the febuxostat API and excipients. Multivariate data analysis tools such as principal component analysis (PCA) and partial least-squares regression (PLSR) analysis are used for qualitative and quantitative analyses. PCA has been found to be useful for the qualitative monitoring of various solid dosage forms. PLSR analysis has led to the successful prediction of API concentration in the unknown samples with a sensitivity and a selectivity of 98 and 99%, respectively. Moreover, the root-mean-square error (RMSE) of calibration and validation of the PLSR model has been found to be 2.9033 and 1.35, respectively. Notably, it is found to be very helpful for the comparison between the self-made formulations of febuxostat and commercially available febuxostat tablets (40 and 80 mg) of two different brands (Gouric and Zurig). These results showed that Raman spectroscopy can be a useful and reliable technique for identifying and quantifying the active pharmaceutical ingredient (API) in commercially available solid dosage forms.