Heat shock proteins (HSPs) have been repeatedly implicated in the pathogenesis of rheumatoid arthritis (RA). The authors aimed to study applicability of heat shock protein 70 (HSPA1A) serum levels as a diagnostic factor and a severity indicator in patients with RA and to quantify cut-off point that predicts status of RA with highest specificity. A total of 76 patients with RA and 36 healthy adults were studied in this case-control analysis. Patients had a higher HSPA1A level than the control group (0.78 ± 0.13 vs. 0.12 ± 0.02 ng/mL, p = 0.006), irrespective of presence of absence of rheumatoid factor or anti-citrullinated cyclic peptide. Next, diagnostic accuracy of the HSPA1A in diagnosis of RA was evaluated (area under curve 0.71; p < 0.05). HSPA1A predicted status of having RA in levels above 0.42 ng/mL with more than 90 % specificity. In addition to diagnostic value, HSPA1A can distinguish between high disease activity (1.66 ± 0.75 ng/mL) and low (0.49 ± 0.1 ng/mL), moderate (0.52 ± 0.12 ng/mL), or remission phase (0.48 ± 0.11 ng/mL). Moreover, patients in remission still had a higher HSPA1A level compared to normal subject (0.48 ± 0.11 vs. 0.12 ± 0.02 ng/mL, p < 0.05). Our results showed that serum HSPA1A could be implemented as a specific tool to facilitate diagnosis and monitoring disease activity in patients with rheumatoid arthritis.
Quantum Cellular Automata (QCA) is an emerging technology at the nanotechnology level. Lower power consumption, higher density and higher speed nature of QCA technology are very interesting. Nowadays, many applications of QCA technology are introduced and cryptography can be an attractive application of QCA technology. The implementation of the Serpent block cipher in Quantum Cellular Automata is the main purpose of this paper. The main modules of this cryptographic algorithm are implemented in this technology and the implementation results are discussed. The two methods of S-Box design, i.e. LUT-Based and Logic-Based methods are inspected. The Serpent's S-Boxes are designed and simulated by these two methods. The simulation results are obtained from QCADesigner software.
Contribution/ OriginalityIn Iran had not been carried out any specific statistical analysis about the spatial distribution of poverty in rural areas. This study is one of few studies which have investigated the effective factors on poverty and to determine poverty map in rural areas with the use of spatial econometric approach.
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