Background: The specific function of long noncoding RNAs (lncRNAs) in systemic lupus erythematosus (SLE) and the mechanism of their involvement in related pathological changes remain to be elucidated, so, in this study, we analyzed the differences in the expression profiles of lncRNAs and their mechanisms of action in SLE using full high-throughput sequencing, bioinformatics, etc. methods. Methods: We used high-throughput sequencing to detect differences in the expression profiles of lncRNAs, miRNAs, and mRNAs in PBMCs from patients with SLE at the genome-wide level. Next, we predicted target genes of 30 lincRNAs (long intergenic noncoding RNAs) by constructing a coexpression network of differential lincRNAs and mRNAs and identified the role of lincRNAs. Then, we analyzed the coexpression network of 23 optimized lincRNAs and their corresponding 353 miRNAs, evaluated the cis- and trans-effects of these lincRNAs, and performed GO and KEGG analyses of target genes. We also selected 8 lincRNAs and 2 newly discovered lncRNAs for q-PCR validation and lncRNA–miRNA–mRNA analysis. Finally, we also analyzed respectively the relation between lncRNAs and gender bias in SLE patients using RT-qPCR, the relation between Systemic Lupus Erythematosus Disease Activity Index score and the “IFN signature” using ELISA, and the relation between the differential expression of lncRNAs and a change in the number of a cell type of PBMCs in SLE patients using RT-qPCR. Results: The profiles of 1087 lncRNAs, 102 miRNAs, and 4101 mRNAs in PBMCs significantly differed between patients with SLE and healthy controls. The coexpression network analysis showed that the network contained 23 lincRNAs and 353 mRNAs. The evaluation of the cis- and trans-effects showed that the 23 lincRNAs acted on 704 target genes. GO and KEGG analyses of the target genes predicted the biological functions of the 23 lincRNAs. q-PCR validation showed 7 lincRNAs and 2 novel lncRNAs were identical to the sequencing results. The ceRNA network contained 7 validated lincRNAs, 15 miRNAs, and 155 mRNAs. In addition, the differential expression of lncRNAs may be gender dependent in SLE patients, SLE patients also exhibit a robust “IFN signature,” and PBMCs exhibiting differential expression of lncRNAs may be due to a change in the number of a cell type. Conclusion: This work determined specific lncRNAs that play important biological functions in the pathogenesis of lupus and provided a new direction for diagnosis and treatment of disease.

Objective: Sepsis remains a major cause of neonatal death. To better characterize the inflammatory response during neonatal sepsis, we compared the differences in serum cytokines and chemokines between full-term neonates with sepsis and without infection. Methods: We enrolled 40 full-term neonates with sepsis and 26 full-term neonates without infection as controls between October 2016 and June 2018. Forty cytokines /chemokines in serum were analyzed using the Luminex Bead Immunoassay System. Results: Our results showed that serum IL-6, IL-8, TNF-α, IL-1β, MIF, CXCL13, CXCL1, CXCL2, CXCL5, CXCL6, CXCL16, CCL27, CCL2, CCL8, CCL3, CCL20, CCL23, and CX3CL1 levels were significantly increased in neonates with sepsis compared to those in the control group (all p< 0.05). The levels of serum CCL20, and IL-17 were higher in late-onset sepsis (LOS) than those in early-onset sepsis (EOS) (all p< 0.05). Conversely, serum CXCL16 was lower in LOS than that in EOS (p< 0.05). Conclusion: Our findings revealed that excessive pro-inflammatory cytokines might be involved in neonatal sepsis. In addition, chemokines significantly increased the recruitment of immune cells after infection to participate in the anti-infection defense of neonates, but this could lead to damage.

Objectives: Development and validation of a single-step and accurate reverse transcriptase loop-mediated isothermal amplification technique (RT-LAMP) for rapid identification of SARS COV-2 relative to commercial quantitative reverse transcriptase real-time PCR (qRT-PCR) assays to allow prompt initiation of proper medical care and containment of virus spread. Methods: Primers showing optimal in-silico features were subjected to analytical sensitivity and specificity to assess the limit of detection (LOD) and cross-reaction with closely- and distantly-related viral species, and clinically prominent bacterial and fungal species. In order to evaluate the clinical utility, our RT-LAMP was subjected to a large number of clinical samples, including 213 negative and 47 positive patients, relative to two commercial quantitative RT-PCR assays. Results: The analytical specificity and sensitivity of our assay was 100% and 500 copies/ml when serial dilution performed in both water and sputum. Subjecting our RT-LAMP assay to clinical samples showed a high degree of specificity (99.5%), sensitivity (91.4%), positive predictive value (97.7%), and negative predictive value (98.1%) when used relative to qRT-PCR. Our RT-LAMP assay was two times faster than qRT-PCR and is storable at room temperature. A suspected case that later became positive tested positive using both our RT-LAMP and the two qRT-PCR assays, which shows the capability of our assay for screening purposes. Conclusions: We present a rapid RT-LAMP assay that could extend the capacity of laboratories to process two times more clinical samples relative to qRT-PCR and potentially could be used for high-throughput screening purposes when demand is increasing at critical situations.

Background: Platelets play a role in tumor cell growth, metastasis, and angiogenesis, and the present study aimed to evaluate diagnostic and prognostic values of platelet parameters in patients with gynecological tumors.Methods: A total of 1062 women were included. Differences of platelet parameters (platelet count [PLT], plateletcrit [PCT], mean platelet volume [MPV], platelet‐large cell rate [P‐LCR], and platelet distribution width [PDW]) between different categories were analyzed by nonparametric test. The optimal cutoff value was calculated with receiver operating characteristic analysis. Overall survivals were analyzed with Kaplan‐Meier method and log‐rank tests for univariate analysis.Results: Platelet count and PCT were significantly increased, and MPV and P‐LCR were significantly reduced in malign and benign gynecological tumor groups compared with the controls (P < .001); PDW had no significant differences. There were no significant differences in PLT, PCT, MPV, P‐LCR, and PDW between different tumor locations and pathologic types. The optimal cutoff values of PLT, PCT, MPV and P‐LCR were 274, 0.26, 10.08, and 24.8 (AUC: 0.661, 0.643, 0.593, 0.562), and PCT had preferable sensibility and specificity (50.84% and 70.42%) in predicting the presence of gynecological tumors. According to survival analysis, increased PLT (≥274 × 10⁹/L) and PCT (≥0.26), and induced MPV (<10.08 fL) and P‐LCR (<24.8%) were associated with shorter overall survival.Conclusions: Platelet count, PCT, MPV, and P‐LCR can be used as preferable auxiliary parameters for predicting the presence of gynecological tumors. Increased PLT and PCT, or decreased MPV and P‐LCR indicated a heavier tumor burden and shorter overall survival.