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BackgroundMultiple myeloma (MM) remains an incurable malignant tumor of plasma cells. Increasing evidence has reported that hypoxia and immune status contribute to the progression of MM. In this research, the prognostic value of the hypoxia–immune-related gene SLC19A1 in MM was evaluated by bioinformatics analysis.MethodRNA-sequencing (RNA-seq) data along with clinical information on MM were downloaded from the Gene Expression Omnibus (GEO) database. Consistent clustering analysis and ESTIMATE algorithms were performed to establish the MM sample subgroups related to hypoxia and immune status, respectively, based on the GSE24080 dataset. The differentially expressed analysis was performed to identify the hypoxia–immune-related genes. Subsequently, a hypoxia–immune-gene risk signature for MM patients was constructed by univariate and multivariate Cox regression analyses, which was also verified in the GSE4581 dataset. Furthermore, the mRNA expression of SLC19A1 was determined using qRT-PCR in 19 MM patients, and the correlations between the genetic expression of SLC19A1 and clinical features were further analyzed.ResultA total of 47 genes were identified as hypoxia–immune-related genes for MM. Among these genes, SLC19A1 was screened to construct a risk score model that had better predictive power for MM. The constructed prognostic signature based on SLC19A1 was verified in the GSE4581 dataset. All independent prognostic factors (age, β2-microglobulin, LDH, albumin, MRI, and gene risk score) were used to develop a nomogram that showed a better performance for predicting the survival probability of MM patients for 1–5 years. Furthermore, SLC19A1 was highly expressed in newly diagnosed and relapsed MM patients, and high expression of SLC19A1 is correlated with higher bone marrow aspiration plasma cells and β2-microglobulin levels in MM patients.ConclusionIn conclusion, our results suggest that SLC19A1 is aberrantly expressed in MM and highly expressed SLC19A1 might be a biomarker correlated with inferior prognosis. More importantly, we identified SLC19A1 as a hypoxia–immune-related gene in MM. Future functional and mechanistic studies will further clarify the roles of SLC19A1 in MM.

Legionella, a waterborne pathogen, is the main cause of Legionnaires’ disease. Therefore, timely and accurate detection and differentiation of Legionella pneumophila and non-Legionella pneumophila species is crucial. In this study, we develop an easy and rapid recombinase polymerase amplification assay combined with EuNPs-based lateral flow immunochromatography (EuNPs-LFIC-RPA) to specifically distinguish Legionella pneumophila and non-Legionella pneumophila. We designed primers based on the mip gene of Legionella pneumophila and the 5S rRNA gene of non-Legionella pneumophila. The recombinase polymerase amplification reaction could go to completion in 10 min at 37°C, and the amplification products could be detected within 5 min with EuNPs-LFIC strips. Using a florescent test strip reader, the quantitative results were achieved by reading the colored signal intensities on the strips. The sensitivity was 1.6 × 101 CFU/ml, and a linear standard linear curve plotted from the test strip reader had a correlation coefficient for the determination of Legionella pneumophila (R2 = 0.9516). Completed concordance for the presence or absence of Legionella pneumophila by EuNPs-LFIC-RPA and qPCR was 97.32% (κ = 0.79, 95% CI), according to an analysis of practical water samples (n = 112). In short, this work shows the feasibility of EuNPs-LFIC-RPA for efficient and rapid monitoring of Legionella pneumophila and non-Legionella pneumophila in water samples.

Pseudorabies virus is a typical swine alphaherpesvirus, which can cause obvious neurological disorders and reproductive failure in pigs. It is capable of evading host antiviral immune response. However, the mechanism by which many PRV proteins assist the virus to evade innate immunity is not fully understood. This study identified PRV US3 protein as a crucial antagonistic viral factor that represses interferon beta (IFN-β) expression. A in-depth study showed that US3 protein restricted type I IFN production by targeting interferon regulatory factor 3 (IRF3), a key molecule required for type I IFN induction. Additionally, US3 protein interacted with IRF3, degraded its protein expression to block the phosphorylation of IRF3. These findings suggested a novel strategy utilized by PRV to inhibit IFN-β production and escape the host innate immunity.