Alopecia or hair loss is a complex polygenetic and psychologically devastating disease affecting millions of men and women globally. Since the gene annotation and environmental knowledge is limited for alopecia, a systematic analysis for the identification of candidate biomarkers is required that could provide potential therapeutic targets for hair loss therapy. We designed an interactive framework to perform a meta-analytical study based on differential expression analysis, systems biology, and functional proteomic investigations. We analyzed eight publicly available microarray datasets and found 12 potential candidate biomarkers including three extracellular proteins from the list of differentially expressed genes with a p-value < 0.05. After expression profiling and functional analysis, we studied protein–protein interactions and observed functional associations of source proteins including WIF1, SPON1, LYZ, GPRC5B, PTPRE, ZFP36L2, HBB, PHF15, LMCD1, KRT35 and VAV3 with target proteins including APCDD1, WNT1, WNT3A, SHH, ESRI, TGFB1, and APP. Pathway analysis of these molecules revealed their role in major physiological reactions including protein metabolism, signal transduction, WNT, BMP, EDA, NOTCH and SHH pathways. These pathways regulate hair growth, hair follicle differentiation, pigmentation, and morphogenesis. We studied the regulatory role of β-catenin, Nf-kappa B, cytokines and retinoic acid in the development of hair growth. Therefore, the differential expression of these significant proteins would affect the normal level and could cause aberrations in hair growth. Our integrative approach helps to prioritize the biomarkers that ultimately lessen the economic burden of experimental studies. It will also be valuable to discover mutants in genomic data in order to increase the identification of new biomarkers for similar problems.

This study aimed to synthesize the silver nanoparticles (SNPs) and loaded chitosan nanoparticles (LCNPs) using Euphorbia prostata based on their anticandidal activity. Antioxidant capacity and the total phenolic and total flavonoid content of plant samples and synthesized nanoparticles (NPs) were also evaluated. SNPs and LCNPs were prepared, respectively using chemical reduction of silver salt solution and ionotropic gelation method. The anticandidal activity was assessed by broth micro-dilution method and the antioxidant activity was determined using free-radical scavenging assays. The synthesized NPs after the optimization process were found to be spherical with sizes ranging from 12 to 100 nm. Spectroscopic analysis of NPs showed the appearance of peaks in prescribed wavelength ranging between 402 and 493 nm. The synthesized NPs showed potent anticandidal activity compared to the free extract. The SNPs formulations NpEPM 7.5 and NpEPMR 7.5, showed significantly low MIC values ranging between 2 and 128 µg/mL. In the case of LCNPs, NpEPM (4:1) and NpEPME (4:1) also showed lower MIC values ranging from 32 to 256 µg/mL. The plant samples as well as NPs showed antioxidant potential. In addition, plant extracts and NPs possess the potent biological potential and can be further investigated through in vivo experiments.

Acid stimulus responsive stealthy nanoparticles were prepared by utilizing three types of copolymers, i.e. acid cleavable polycaprolactone-polyethyleneimine-polyethylene glycol (PCL-PEI-PEG), acid charge reversal polycaprolactone-polyethyleneimine (PCL-PEI), and ligand containing polycaprolactone-polyethyleneimine-folate (PCL-PEI-Fol). FTIR, NMR, and UV-visible spectroscopy confirmed the formation of these copolymers. Acid cleavable property of PCL-PEI-PEG copolymer was examined by FTIR. The formation of nanoparticles was determined by DLS and SEM. Aggregation, structural destabilization, and charge reversibility of nanoparticles at low pH were evaluated by DLS, SEM, and Zeta analyzer, respectively. MTT assay was used to evaluate anticancer effect of nanoparticles. Overall, nanoparticles exhibited improved cytotoxic activity against MCF-7 cancer cells.