[The expression of long non-coding RNA human leukocyte antigen complex P5(lncRNA HCP5) in synovial tissue of patients with rheumatoid arthritis is up-regulated and correlated with immune cell infiltration].

Objective To identify the potential long non-coding RNA (lncRNA) expressed in rheumatoid arthritis (RA) synovium key to RA onset and investigate its association with immune cell infiltration. Methods RA synovium data were downloaded from the GEO database and normalized. The lncRNAs key to RA onset were identified using multiple machine learning methods. Infiltration of 22 immune cell populations in RA synovium was measured by cell-type identification by estimating relative subsets of RNA transcripts (CIBER-SORT). The relationship between the key lncRNA and infiltrating immune cells was analyzed. Finally, real-time quantitative PCR was applied to validate the expression of the key lncRNA in RA synovial cells. Results lncRNA human leukocyte antigen complex P5(HCP5) was identified as the key lncRNA associated with RA onset. Infiltration analysis revealed increased abundance of CD8+ T cells, γδ T cells, and M1 macrophages while decreased abundance of M2 macrophages in RA synovial tissue. Correlation analysis demonstrated that the lncRNA HCP5 expression was positively associated with the infiltration abundance of CD8+ T cells, γδ T cells, and M1 macrophages in RA synovial tissue. Furthermore,the expression of lncRNA HCP5 in RA synovial cells was up-regulated. Conclusion lncRNA HCP5 expression is up-regulated in RA synovial tissue and potentially associated with immune cells infiltration.

Simple Strategy for Rapid and Sensitive Detection of Avian Influenza A H7N9 Virus Based on Intensity-Modulated SPR Biosensor and New Generated Antibody.

In 2013 a new reassortant avian influenza A H7N9 virus emerged in China, causing human infection with high mortality. An accurate and timely diagnosis is crucial for controlling the outbreaks of the disease. We therefore propose a simple strategy for rapidly and sensitively detecting the H7N9 virus using an intensity-modulated surface plasmon resonance (IM-SPR) biosensor integrated with a new generated monoclonal antibody. The novel antibody exhibits significant specificity to recognize H7N9 virus compared with other clinical human influenza isolates (p < 0.01). Experimentally, the detection limit of the proposed approach for H7N9 virus detection is estimated to be 144 copies/mL, which is a 20-fold increase in sensitivity compared with homemade target-captured ELISA using the identical antibody. For the measurement of mimic clinical specimens containing the H7N9 virus mixed with nasal mucosa from flu-like syndrome patients, the detection limit is calculated to be 402 copies/mL, which is better than conventional influenza detection assays; quantitative reverse transcription polymerase chain reaction (qRT-PCR) and rapid influenza diagnostic test (RIDT). Most importantly, the assay time took less than 10 min. Combined, the results of this study indicate that the proposed simple strategy demonstrates high sensitivity and time-saving in H7N9 virus detection. By incorporating a high specific recognizer, the proposed technique has the potential to be used in applications and development of other emerging or re-emerging microbe detection platforms.