Background: Since December 2019, the outbreak of COVID-19 caused a large number of hospital admissions in China. Many patients with COVID-19 have symptoms of acute respiratory distress syndrome, even are in danger of death. This is the first study to evaluate dynamic changes of D-Dimer and Neutrophil-Lymphocyte Count Ratio (NLR) as a prognostic utility in patients with COVID-19 for clinical use. Methods: In a retrospective study, we collected data from 349 hospitalized patients who diagnosed as the infection of the COVID-19 in Wuhan Pulmonary Hospital. We used ROC curves and Cox regression analysis to explore critical value (optimal cutoff point associated with Youden index) and prognostic role of dynamic changes of D-Dimer and NLR.

Abstract Background Since December 2019, the outbreak of COVID-19 caused a large number of hospital admissions in China. Many patients with COVID-19 have symptoms of acute respiratory distress syndrome, even are in danger of death. This is the first study to evaluate dynamic changes of D-Dimer and Neutrophil-Lymphocyte Count Ratio (NLR) as a prognostic utility in patients with COVID-19 for clinical use.Methods In a retrospective study, we collected data from 349 hospitalized patients who diagnosed as the infection of the COVID-19 in Wuhan Pulmonary Hospital. We used ROC curves and Cox regression analysis to explore critical value (optimal cut-off point associated with Youden index) and prognostic role of dynamic changes of D-Dimer and NLR.Results 349 participants were enrolled in this study and the mortality rate of the patients with laboratory diagnosed COVID-19 was 14.9%. The initial and peak value of D-Dimer and NLR in deceased patients were higher statistically compared with survivors (P<0.001). There was a more significant upward trend of D-Dimer and NLR during hospitalization in the deceased patients, initial D-Dimer and NLR were lower than the peak tests (MD) -25.23, 95% CI:-31.81- -18.64, P <0.001; (MD) -43.73, 95% CI:-59.28- -31.17, P <0.001. The test showed a stronger correlation between hospitalization days, PCT and peak D-Dimer than initial D-Dimer. The areas under the ROC curves of peak D-Dimer and peak NLR tests were higher than the initial tests (0.94(95%CI: 0.90-0.98) vs. 0.80 (95% CI: 0.73-0.87); 0.93 (95%CI:0.90-0.96) vs. 0.86 (95%CI:0.82-0.91). The critical value of initial D-Dimer, peak D-Dimer, initial NLR and peak NLR was 0.73 mg/L, 3.78 mg/L,7.13 and 14.31 respectively. The multivariable Cox regression analysis showed that age (HR 1.04, 95% CI 1.00-1.07, P=0.01), the peak D-Dimer (HR 1.03, 95% CI 1.01-1.04, P<0.001) were prognostic factors for COVID-19 patients’ death.Conclusions To dynamically observe the ratio of D-Dimer and NLR was more valuable during the prognosis of COVID-19. The rising trend in D-Dimer and NLR, or the test results higher than the critical values may indicate a risk of death for participants with COVID-19.

Poly-adenosine diphosphate-ribose polymerase (PARP) implements posttranslational mono- or poly-ADP-ribosylation modification of target proteins. Among the known 18 members in the enormous family of PARP enzymes, several investigations about PARP1, PARP2, and PARP5a/5b have been launched in the past few decades; more specifically, PARP14 is gradually emerging as a promising drug target. An intact PARP14 (also named ARTD8 or BAL2) is constructed by macro1, macro2, macro3, WWE, and the catalytic domain. PARP14 takes advantage of nicotinamide adenine dinucleotide (NAD+) as a metabolic substrate to conduct mono-ADP-ribosylation modification on target proteins, taking part in cellular responses and signaling pathways in the immune system. Therefore, PARP14 has been considered a fascinating target for treatment of tumors and allergic inflammation. More importantly, PARP14 could be a potential target for a chemosensitizer based on the theory of synthetic lethality and its unique role in homologous recombination DNA repair. This review first gives a brief introduction on several representative PARP members. Subsequently, current literatures are presented to reveal the molecular mechanisms of PARP14 as a novel drug target for cancers (e.g., diffuse large B-cell lymphoma, multiple myeloma, prostate cancer, and hepatocellular carcinoma) and allergic inflammatory. Finally, potential PARP inhibitor-associated adverse effects are discussed. The review could be a meaningful reference for innovative drug or chemosensitizer discovery targeting to PARP14.

Osteosarcoma is a common malignancy with high mortality and poor prognosis due to lack of predictive markers. Increasing evidence has demonstrated that pseudogenes, a type of non-coding gene, play an important role in tumorigenesis. The aim of this study was to identify a prognostic pseudogene signature of osteosarcoma by machine learning. A sample of 94 osteosarcoma patients’ RNA-Seq data with clinical follow-up information was involved in the study. The survival-related pseudogenes were screened and related signature model was constructed by cox-regression analysis (univariate, lasso, and multivariate). The predictive value of the signature was further validated in different subgroups. The putative biological functions were determined by co-expression analysis. In total, 125 survival-related pseudogenes were identified and a four-pseudogene (RPL11-551L14.1, HR: 0.65 (95% CI: 0.44–0.95); RPL7AP28, HR: 0.32 (95% CI: 0.14–0.76); RP4-706A16.3, HR: 1.89 (95% CI: 1.35–2.65); RP11-326A19.5, HR: 0.52(95% CI: 0.37–0.74)) signature effectively distinguished the high- and low-risk patients, and predicted prognosis with high sensitivity and specificity (AUC: 0.878). Furthermore, the signature was applicable to patients of different genders, ages, and metastatic status. Co-expression analysis revealed the four pseudogenes are involved in regulating malignant phenotype, immune, and DNA/RNA editing. This four-pseudogene signature is not only a promising predictor of prognosis and survival, but also a potential marker for monitoring therapeutic schedule. Therefore, our findings may have potential clinical significance.

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