MicroRNAs-mediated regulation pathways in rheumatic diseases.

Rheumatoid arthritis (RA) and ankylosing spondylitis (AS) are two common rheumatic disorders marked by persistent inflammatory joint disease. Patients with RA have osteodestructive symptoms, but those with AS have osteoproliferative manifestations. Ligaments, joints, tendons, bones, and muscles are all affected by rheumatic disorders. In recent years, many epigenetic factors contributing to the pathogenesis of rheumatoid disorders have been studied. MicroRNAs (miRNAs) are small, non-coding RNA molecules implicated as potential therapeutic targets or biomarkers in rheumatic diseases. MiRNAs play a critical role in the modulation of bone homeostasis and joint remodeling by controlling fibroblast-like synoviocytes (FLSs), chondrocytes, and osteocytes. Several miRNAs have been shown to be dysregulated in rheumatic diseases, including miR-10a, 16, 17, 18a, 19, 20a, 21, 27a, 29a, 34a, 103a, 125b, 132, 137, 143, 145, 146a, 155, 192, 203, 221, 222, 301a, 346, and 548a.The major molecular pathways governed by miRNAs in these cells are Wnt, bone-morphogenic protein (BMP), nuclear factor (NF)-κB, receptor activator of NF-κB (RANK)-RANK ligand (RANKL), and macrophage colony-stimulating factor (M-CSF) receptor pathway. This review aimed to provide an overview of the most important signaling pathways controlled by miRNAs in rheumatic diseases.

Label-free discrimination of single nucleotide changes in DNA by reflectometric interference Fourier transform spectroscopy.

Phenotypic variation - such as disease susceptibility and differential drug response - has a strong genetic component. Substantial effort has therefore been made to identify causal genomic variants explaining such variation among humans. Point mutations (PMs), which are single nucleotide changes in the genome, have been identified to be the most abundant form of causal genomic variants, making them useful, reliable diagnostic markers. Methods developed to genotype PMs have moved towards solid-phase assays, which not only show greater sensitivity and specificity, but also enable scalability and faster processing time. Most current assays are, however, based on fluorescent probes, which makes them relatively expensive. To develop a more cost-effective label-free genotyping method, we used a porous silicon (PSi) base as an efficient support for DNA biosensing and coupled it with reflectometric interference Fourier transform spectroscopy (RIFTS). To assess the versatility of this approach, we tested both a single nucleotide substitution in VKORC1 (-1639G > A; rs9923231) and a single nucleotide insertion in BRCA1 (5382insC; rs80357906). We demonstrate that the PSi-RIFTS method can efficiently detect both PM types with high sensitivity where hybridization of complementary DNA can be quantifiably differentiated from mismatch and non-complementary hybridization events. In addition, we show that the PSi base with immobilized DNA not only can be re-used to type further samples, but it also remains stable for 14 days, suggesting its potential for high-throughput applications.

Optimization of Porous Silicon Conditions for DNA-based Biosensing via Reflectometric Interference Spectroscopy.

OBJECTIVE: Substantial effort has been put into designing DNA-based biosensors, which are commonly used to detect presence of known sequences including the quantification of gene expression. Porous silicon (PSi), as a nanostructured base, has been commonly used in the fabrication of optimally transducing biosensors. Given that the function of any PSi-based biosensor is highly dependent on its nanomorphology, we systematically optimized a PSi biosensor based on reflectometric interference spectroscopy (RIS) detecting the high penetrance breast cancer susceptibility gene, BRCA1. MATERIALS AND METHODS: In this experimental study, PSi pore sizes on the PSi surface were controlled for optimum filling with DNA oligonucleotides and surface roughness was optimized for obtaining higher resolution RIS patterns. In addition, the influence of two different organic electrolyte mixtures on the formation and morphology of the pores, based on various current densities and etching times on doped p-type silicon, were examined. Moreover, we introduce two cleaning processes which can efficiently remove the undesirable outer parasitic layer created during PSi formation. Results of all the optimization steps were observed by field emission scanning electron microscopy (FE-SEM). RESULTS: DNA sensing reached its optimum when PSi was formed in a two-step process in the ethanol electrolyte accompanied by removal of the parasitic layer in NaOH solution. These optimal conditions, which result in pore sizes of approximately 20 nm as well as a low surface roughness, provide a considerable RIS shift upon complementary sequence hybridization, suggesting efficient detectability. CONCLUSION: We demonstrate that the optimal conditions identified here makes PSi an attractive solid-phase DNA-based biosensing method and may be used to not only detect full complementary DNA sequences, but it may also be used for detecting point mutations such as single nucleotide substitutions and indels.