Background We herein compared the diagnostic value of next-generation sequencing (NGS), bacterial culture, and serological biomarkers to detect periprosthetic joint infection (PJI) after joint replacement. Methods According to the diagnostic criteria of the Musculoskeletal Infection Society, 35 patients who underwent joint revision surgery were divided into infection (15 cases) and non-infection (20 cases) groups, and were routinely examined preoperatively for erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and D-dimer levels. All patients underwent arthrocentesis preoperatively. Synovial fluid was used for white blood cell count, white blood cell classification, bacterial culture, and NGS. Furthermore, we calculated the area under the curve (AUC) of the receiver operating characteristic curve (ROC) for ESR, CRP, PCT, IL-6, and D-dimer. Data were assessed by comparing diagnostic accuracy, sensitivity, and specificity. Results Fourteen patients showed positive results by NGS and seven showed positive bacterial culture results in the infection group; further, 18 showed negative results by NGS in the non-infection group. The AUC of ESR, D-dimer, CRP, IL-6, and PCT was 0.667, 0.572, 0.827, 0.767, and 0.808, respectively. The accuracy of NGS, bacterial culture, CRP, IL-6, and PCT was 0.91, 0.74, 0.77, 0.74, and 0.83, respectively. When comparing NGS with CRP, IL-6, PCT, and bacterial culture, differences in overall test results and those in sensitivity were statistically significant, and compared with CRP, differences in specificity were also statistically significant. In comparison with IL-6, PCT, and bacterial culture, the specificity of NGS was statistically insignificant. Conclusions Our results indicated that NGS had higher accuracy and sensitivity than the bacterial culture method and commonly used serological biomarkers for diagnosing PJI.

Long non-coding (lnc) RNAs have been associated with osteoarthritis (OA) progression. The aim of the present study was to investigate the regulatory mechanism of lncRNA LINC01385 in OA in vitro. The mRNA expression level of LINC01385, microRNA(miR)-140-3p, and Toll-like receptor 4 (TLR4) was detected using reverse transcription-quantitative PCR, while ELISA was used to determine the concentration of different inflammatory factors [tumor necrosis factor-α (TNF-α), IL-6, and prostaglandin E 2 (PGE 2 )]. The viability of human articular chondrocytes (HC-a) was measured using a MTT assay and western blot analysis was performed to quantify the protein expression level of TLR4. The associations between miR-140-3p and LINC01385/TLR4 were confirmed using a dual-luciferase reporter assay. LINC01385 mRNA expression level was increased in OA tissues and IL-1β-induced HC-a. LINC01385 knockdown and miR-140-3p mimics reduced the concentration of inflammatory factors in IL-1β-induced HC-a and promoted cell survival. In addition, it was confirmed that LINC01385 targeted miR-140-3p, while TLR4 was a target gene of miR-140-3p. Negative correlations between LINC01385 and miR-140-3p, and between miR-140-3p and TLR4 were observed in OA tissues. Low mRNA expression level of miR-140-3p and high protein expression level of TLR4 reversed the inhibitory effect of LINC01385 knockdown on the inflammatory responses of IL-1β-induced HC-a and exhibited a stimulating effect on cell viability. LINC01385 knockdown reduced the progression of OA by modulating the miR-140-3p/TLR4 axis in vitro; thus, LINC01385 may be a therapeutic target for OA.

Background Due to the extremely high sensitivity of metagenomic next-generation sequencing (mNGS) testing, even a small amount of nucleic acid fragments exposed during sampling or testing may lead to false positives, which is one of the biggest challenges in interpreting mNGS testing reports. In this study, for the first time, we experimentally detected and established Periprosthetic joint infection (PJI)-related interfering nucleic acid background microbial libraries (BML) in different medical institutions to clarify Necessity of establishing a BML in different medical institutions for the diagnosis of periprosthetic infection using mNGS. MethodsSamples were taken from 3 different acetabular reamer for hip arthroplasty in 7 different hospitals. The whole process was strictly aseptic, mNGS was performed according to standard operating procedures. The sterility of instruments was confirmed by culture method. The sequencing results of specimens from different hospitals were compared to analyze the difference of background bacteria. Bioinformatics analysis and visualization were presented through R language. ResultsA total of 26 samples were processed by mNGS, including 24 instrument swab samples, 1 blank swab control, and 1 blank water control. 254,314,707 reads were sequenced in all samples. The results showed that 1.13% of Clean Reads can be matched to pathogenic microorganism genomes, of which bacterial sequences account for 87.48%, fungal sequences account for 11.18%, parasite sequences account for 1.26%, and virus sequences account for 0.06%. The results of PCA (Principal Component Analysis) demonstrated that the distribution of bacteria on the surface of instruments was significantly different between medical institutions. Through the Venn diagram, it was found that 465 species of bacteria in all region hospitals, Liaocheng People's Hospital had a maximum of 340 species of bacteria, followed by Guanxian County People's Hospital with 169 species. The clustering heat map illustrated that the distribution of bacterial groups in three different instrument samples in the same hospital was basically the same, and the bacterial genera varied significantly among hospitals. The residual microbial nucleic acid fragments are mainly bacterial DNA and represent differences in different medical institutions.ConclusionsIt is necessary to establish independent BML in different medical institutions to improve the accuracy of mNGS on the diagnosis of PJI.