Uterus corpus endometrial cancer (UCEC) is associated with a high mortality rate. In this study, we examined the impact of long intergenic non-protein coding RNA 01234 (LINC01234) in the diagnosis and survival of UCEC using an open high-throughput sequencing database. The association between LINC01234 expression and UCEC clinical features was determined using the Wilcoxon rank sum test, logistic regression and Cox regression. To assess the classification effectiveness of LINC01234 in UCEC, the area under the receiver operating characteristic (ROC) curve (AUC) was performed. Then, Kaplan-Meier analysis was performed to determine the prognostic significance of LINC01234 in UCEC. The underlying regulatory mechanisms of LIN01234 were assessed using the Gene set enrichment analysis (GSEA), and the influence on immune infiltration cells was tested by the Spearman correlation method. Datebases showed LINC01234 was up-regulated in UCEC and associated with poor clinicopathologic characteristics. What’s more quantitative real time polymerase chain reaction (qRT-PCR) analyse of clinical tissue specimens, LINC01234 was actually high expression in UCEC. The results showed an AUC of 0.726, indicating that LINC01234 had a significant diagnostic value. Further, Kaplan-Meier analysis showed that high LINC01234 expression was associated with poorer progress free interval (PFI) (hazard ratio (HR): 1.68, 95% confidence interval (CI): 1.18–2.39, p = 0.004), disease-specific survival (DSS) (HR: 2.17, 95% CI: 1.29–3.67, p = 0.004), overall survival (OS) (HR: 1.81, 95% CI: 1.19–2.75, p = 0.005). Cox regression analysis showed LINC01234 expression was an independent factor for DSS. Pathway enrichment and immune infiltration analysis showed the most likely mechanisms that LINC01234 promoted tumor progression. LINC01234 demonstrated diagnostic and prognostic potential in UCEC and was shown to exert its effects via various mechanisms, including cell proliferation, spermatogenesis, angiogenesis and immune response in the tumor microenvironment, to promote tumor progression; thus, indicating that it could be a target for treating UCEC.

Previous studies have reported that genes relating to JAK-STAT pathway ( IFIH1, TYK2 and IL-10 ) conferred the susceptibility to SLE. In this study, we performed a meta-analysis (including 43 studies) to evaluate the association between IFIH1 (9288 patients and 24,040 controls), TYK2 (4928 patients and 11,536 controls), IL-10 (3623 patients and 4907 controls) polymorphisms and systemic lupus erythematosus (SLE) in a comprehensive way. We found that IFIH1 rs1990760_T allele was associated with risk of SLE in overall population under three models (allelic: P = 2.56 × 10 −11 , OR 1.135, 95% CI 1.094–1.179, dominant: P = 1.8 × 10 −8 , OR 1.203, 95% CI 1.128–1.284, recessive: P = 2.6 × 10 −7 , OR 1.163, 95% CI 1.098–1.231). A strong association had been observed between TYK2 polymorphism rs2304256_C allele and SLE in Europeans ( P = 5.82 × 10 −5 , OR 1.434, 95% CI 1.203–1.710). When coming to overall population, TYK2 rs2304256_C showed a significant association with SLE under recessive model ( P = 8.05 × 10 −3 , OR 1.314, 95% CI 1.074–1.608). However, the other two SNPs (rs12720270, rs280519) of TYK2 were not significant. The results also indicated an association between IL-10 rs1800896_G allele and SLE in Asians under recessive model ( P = 4.65 × 10 −3 , OR 2.623, 95% CI 1.346–5.115), while, IL-10 rs1800896_G had a trend of association with SLE in European population in dominant model ( P = 1.21 × 10 −2 , OR 1.375, 95% CI 1.072–1.764). In addition, we found IL-10 rs1800896 GG homozygote might be associated with increased susceptibility to SLE (GG vs AA, P = 4.65 × 10 −3 , OR 1.539, 95% CI 1.142–2.072). We concluded that IFIH1 rs1990760_T and TYK2 rs2304256_C alleles were significantly associated with SLE, and IL-10 rs1800896 GG homozygote might have an enhancement effect on SLE risk.

Precoding can effectively reduce the peak-to-average power ratio (PAPR) of the transmitted waveform but will usually degrade the bit error rate (BER) performance. In this paper, we investigate the PAPR-guaranteed BER minimization problem through precoding in uplink massive multiple input-multiple output (MIMO) systems. First, we formulate an optimization problem to minimize the BER via precoding design and derive the necessary condition of the optimal precoding matrix. Second, we discuss the BER minimization with PAPR constraint and propose a two-step distributed precoder to deal with this problem. Simulation results verify the effectiveness of the proposed precoding. Particularly, it is efficient for massive MIMO systems in terms of energy efficiency.