RESUMEN
Mast cells are immune cells of myeloid lineage, characterized by the presence of cytoplasmic granules. These cells play a significant role in multiple pathologies, such as urticaria and type 1 hypersensitivity reactions. Mast cells in tissue sections can be demonstrated with metachromatic stains, such as toluidine blue. Metachromatic staining of mast cells is influenced by the type of mast cell, pH of the staining solution and fixative employed. The objective of this study is to identify a simple, consistent, and reproducible toluidine blue staining method to quantify the mast cells in whole slide skin images using automated image analysis. Skin sections from naive mice and atopic dermatitis mice were stained with toluidine blue methods by Churukian-Schenk and Luna. Luna's toluidine blue staining method without the eosin counterstaining provided optimal staining of mast cells with a greater contrast to the background. The Churukian-Schenk toluidine blue method resulted in slight background staining which confounded the accurate detection and quantification of mast cells in mouse skin sections using an automated image analysis algorithm. Using the Luna toluidine blue stain, a 5-fold increase in the total number of mast cells was observed in atopic dermatitis skin samples as compared to naive mice. In summary, a simple, conventional, and reproducible toluidine blue method was identified to quantify the mast cells in mouse skin sections using an automated image analysis algorithm.
Asunto(s)
Dermatitis Atópica , Mastocitos , Animales , Dermatitis Atópica/patología , Mastocitos/química , Mastocitos/patología , Ratones , Piel/patología , Coloración y Etiquetado , Cloruro de Tolonio/análisisRESUMEN
In the present work, we report compilation and analysis of 245 drugs, including small and macromolecules approved by the U.S. FDA from 2015 until June 2020. Nearly 29% of the drugs were approved for the treatment of various types of cancers. Other major therapeutic areas of focus were infectious diseases (14%); neurological conditions (12%); and genetic, metabolic, and cardiovascular disorders (7-8% each). Itemization of the approved drugs according to the year of approval, sponsor, target, chemical class, major drug-metabolizing enzyme(s), route of administration/elimination, and drug-drug interaction liability (perpetrator or/and victim) is presented and discussed. An effort has been made to analyze the pharmacophores to identify the structural (e.g., aromatic, heterocycle, and aliphatic), elemental (e.g., boron, sulfur, fluorine, phosphorus, and deuterium), and functional group (e.g., nitro drugs) diversity among the approved drugs. Further, descriptor-based chemical space analysis of FDA approved drugs and several strategies utilized for optimizing metabolism leading to their discoveries have been emphasized. Finally, an analysis of drug-likeness for the approved drugs is presented.