Full texts of 39 articles were reviewed, and 36 articles were included in the qualitative synthesis. There were eight studies eligible for meta-analysis. There was a total of 193 operations performed on patients with a concurrent COVID-19 infection and 910 performed on patients who were COVID-19 negative. The odds ratio for mortality in patients who underwent a surgical procedure while COVID-19 positive was 7.9 (95% confidence interval 3.2-19.4). This meta-analysis confirms that concurrent COVID-19 infection increases the risk of surgical mortality. The magnitude of this risk mandates that strategies are developed to mitigate the risk at both an individual and system level.This meta-analysis confirms that concurrent COVID-19 infection increases the risk of surgical mortality. The magnitude of this risk mandates that strategies are developed to mitigate the risk at both an individual and system level. This study aims to evaluate the performance of four artificial intelligence-aided diagnostic systems in identifying and measuring four types of pulmonary nodules. Four types of nodules were implanted in a commercial lung phantom. The phantom was scanned with multislice spiral computed tomography, after which four systems (A, B, C, D) were used to identify the nodules and measure their volumes. The relative volume error (RVE) of system A was the lowest for all nodules, except for small ground glass nodules (SGGNs). System C had the smallest RVE for SGGNs, -0.13 (-0.56, 0.00). In the Bland-Altman test, only systems A and C passed the consistency test, P=0.40. In terms of precision, the miss rate (MR) of system C was 0.00% for small solid nodules (SSNs), ground glass nodules (GGNs), and solid nodules (SNs) but 4.17% for SGGNs. The comparable system D MRs for SGGNs, SSNs, and GGNs were 71.30%, 25.93%, and 47.22%, respectively, the highest among all the systems. Receiver operating characteristic curve analysis indicated that system A had the best performance in recognizing SSNs and GGNs, with areas under the curve of 0.91 and 0.68. System C had the best performance for SGGNs (AUC=0.91). Among four types nodules, SGGNs are the most difficult to recognize, indicating the need to improve higher accuracy and precision of artificial systems. System A most accurately measured nodule volume. System C was most precise in recognizing all four types of nodules, especially SGGN.Among four types nodules, SGGNs are the most difficult to recognize, indicating the need to improve higher accuracy and precision of artificial systems. System A most accurately measured nodule volume. System C was most precise in recognizing all four types of nodules, especially SGGN. Sickle cell anaemia (SCA), an inherited chronic hematological disease affecting hundreds of thousand people worldwide, causes significant morbidity and reduced life expectancy about two or three decades. This study aimed to conduct a meta-analysis of the efficacy of voxelotor, 900 mg in patients with SCA. The research protocol was registered at the International Register of Prospective Systematic Reviews (PROSPERO), under the registration number CRD42020147796. ClinicalTrials.gov, Cochrane Central Register of Controlled Trials, Conference Abstracts, Google Scholar, Ovid Medline, Scopus, Web of Science, and Wiley Online Library from 2015 through July 25, 2019, and bibliographies of review articles and eligible studies. Eleven eligible studies that evaluated the effectiveness of voxelotor, 900 mg in SCA. Based on pre-specified inclusion and exclusion criteria, 2 randomized, placebo-controlled studies were included in the meta-analysis. The primary outcome measured was hemoglobin elevation, assessed in a hce to see the potential of disease-modifying effects of voxelotor.As a conclusion, voxelotor, 900 mg use significantly increased hemoglobin levels which of 1 g/dL elevation predicts a reduced risk of stroke (41%), albuminuria (53%), pulmonary arterial hypertension (57%), and mortality (64%) in recent studies. Voxelotor also reduced markers of hemolysis but failed to reach statistically significance in current evidence. Multicenter, randomized, placebo-controlled studies are on the way and will provide more evidence to see the potential of disease-modifying effects of voxelotor.Long non-coding RNAs (lncRNA) have been emerged as a novel class of molecular regulators in cancer. They are dysregulated in many types of cancer; however, there is not enough knowledge available on their expression and functional profiles. Lung cancer is the leading cause of the cancer deaths worldwide. Generally, lncRNAs may be associated with lung tumor pathogenesis and they may act as biomarkers for the cancer prognosis and diagnosis. Compared to other invasive prognostic and diagnostic methods, detection of lncRNAs might be a user-friendly and noninvasive method. Guadecitabine clinical trial In this review article, we selected 27 tumor-associated lncRNAs by literature reviewing to further discussing in detail for using as diagnostic and prognostic biomarkers in lung cancer. Also, in an in silico target analysis, the "Experimentally supported functional regulation" approach of the LncTarD web tool was used to identifying the target genes and regulatory mechanisms of the selected lncRNAs. The reports on diagnostic and prognostic potential of all selected lncRNAs were discussed. However, the target genes and regulatory mechanisms of the 22 lncRNAs were identified by in silico analysis and we found the pathways that are controlled by each target group of lncRNAs. They use epigenetic mechanisms, ceRNA mechanisms, protein interaction and sponge mechanism. Also, 10, 23, 5, and 28 target genes for each of these mechanisms were identified, respectively. Finally, each group of target genes controls 50, 12, 7, and 2 molecular pathways, respectively. In conclusion, LncRNAs could be used as biomarkers in lung cancer due to their roles in control of several signaling pathways related to lung tumors. Also, it seems that lncRNAs, which use epigenetic mechanisms for modulating a large number of pathways, could be considered as important subjects for lung cancer-related diagnostic and prognostic biomarkers.