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Argatroban Anticoagulation for Grown-up Extracorporeal Membrane Oxygenation: A Systematic Evaluation.
Background Corona Virus Disease 2019 (COVID-19) has become a global pandemic. This study established prognostic scoring models based on comorbidities and other clinical information for severe and critical patients with COVID-19. Material and Methods We retrospectively collected data from 51 patients diagnosed as severe or critical COVID-19 who were admitted between January 29, 2020, and February 18, 2020. The Charlson (CCI), Elixhauser (ECI), and age- and smoking-adjusted Charlson (ASCCI) and Elixhauser (ASECI) comorbidity indices were used to evaluate the patient outcomes. Results The mean hospital length of stay (LOS) of the COVID-19 patients was 22.82 ± 12.32 days; 19 patients (37.3%) were hospitalized for more than 24 days. Multivariate analysis identified older age (OR 1.064, P = 0.018, 95%CI 1.011-1.121) and smoking (OR 3.696, P = 0.080, 95%CI 0.856-15.955) as positive predictors of a long LOS. There were significant trends for increasing hospital LOS with increasing CCI, ASCCI, and ASECI scores (OR 57.500, P = 0.001, 95%CI 5.687-581.399; OR 71.500, P = 0.001, 95%CI 5.689-898.642; and OR 19.556, P = 0.001, 95%CI 3.315-115.372, respectively). The result was similar for the outcome of critical illness (OR 21.333, P = 0.001, 95%CI 3.565-127.672; OR 13.000, P = 0.009, 95%CI 1.921-87.990; OR 11.333, P = 0.008, 95%CI 1.859-69.080, respectively). Conclusions This study established prognostic scoring models based on comorbidities and clinical information, which may help with the graded management of patients according to prognosis score and remind physicians to pay more attention to patients with high scores.Osteosarcoma (OS) is the most common type of malignant bone tumor that affects children and adolescents. Still, the cellular and molecular mechanisms driving the development of this disease remain poorly understood. In this study, numerous dysregulated lncRNAs were identified by RNA-seq. As a result, we were able to find a novel lncRNA Lnc-MAP6-13 which is highly expressed in osteosarcoma. Using a set of approaches including gene knockdown, RT-PCR, oncogenic function assay and western blotting, we observed that knockdown of Lnc-MAP6-13 expression suppressed cell proliferation and colony formation, and promoted apoptosis in vitro. For the first time, we have identified that Lnc-MAP6-13 potentially influence the malignant behavior of osteosarcoma via Bax/Bcl-2 and Wnt/β-catenin signaling pathways. Henceforth, Lnc-MAP6-13 may provide a new molecular route of research and therapeutic applications for the diagnosis and treatment of osteosarcoma.Background Chuanxiong Rhizoma is one of the traditional Chinese medicines which have been used for years in the treatment of diabetic nephropathy (DN). However, the mechanism of Chuanxiong Rhizoma in DN has not yet been fully understood. Methods We performed network pharmacology to construct target proteins interaction network of Chuanxiong Rhizoma. Active ingredients were acquired from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. DRUGBANK database was used to predict target proteins of Chuanxiong Rhizoma. Gene ontology (GO) biological process analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were also performed for functional prediction of the target proteins. Molecular docking was applied for evaluating the drug interactions between hub targets and active ingredients. Results Twenty-eight target genes fished by 6 active ingredients of Chuanxiong Rhizoma were obtained in the study. The top 10 significant GO analyses and 6 KEGG pathways were enriched for genomic analysis. We also acquired 1366 differentially expressed genes associated with DN from GSE30528 dataset, including five target genes KCNH2, NCOA1, KDR, NR3C2 and ADRB2. Molecular docking analysis successfully combined KCNH2, NCOA1, KDR and ADRB2 to Myricanone with docking scores from 4.61 to 6.28. NR3C2 also displayed good docking scores with Wallichilide and Sitosterol (8.13 and 8.34, respectively), revealing good binding forces to active compounds of Chuanxiong Rhizoma. Conclusions Chuanxiong Rhizoma might take part in the treatment of DN through pathways associated with steroid hormone, estrogen, thyroid hormone and IL-17. KCNH2, NCOA1, KDR, ADRB2 and NR3C2 were proved to be the hub targets, which were closely related to corresponding active ingredients of Chuanxiong Rhizoma.Background Current evidence suggests an increased prevalence of iron deficiency (ID) and anemia in chronic obstructive pulmonary disease (COPD). ID and subsequent anemia can be due to iron losses via bleeding resulting in absolute ID or inflammation-driven retention of iron within macrophages resulting in functional ID and anemia of inflammation. Methods This is a retrospective analysis of 204 non-exacerbated COPD patients in outpatient care. Current definitions of absolute and functional ID were applied to determine the prevalence of ID and to analyze associations to disease severity in terms of lung function parameters and clinical symptoms. Results The studied cohort of COPD patients demonstrated a high prevalence of ID, ranging from 30 to 40% during the observation time. At the initial presentation, absolute or functional ID was found in 9.3% to 12.3% of COPD individuals, whereas combined forms of absolute and functional ID were most prevalent (25.9% of all individuals). The prevalence of ID increased during longitudinal follow-up (37 ± 15 months), and especially combined forms of ID were significantly related to anemia. Anemia prevalence ranged between 14.2% and 20.8% during the observation period and anemia was associated with lower FEV1, DLCOc, and CRP elevation. Accordingly, ID was associated with decreased FEV1, DLCOc, and an elevation in CRP. Conclusion ID is common in COPD patients, but a uniform definition for accurate diagnosis does not exist. Prevalence of functional ID and anemia increased during follow-up. N-Acetyl-DL-methionine cell line The associations of ID and anemia with reduced functional lung capacity and elevated inflammation may reflect a more severe COPD phenotype.Background Lactate dehydrogenase (LDH) has been proved to be a prognostic factor for the severity and poor outcomes of coronavirus disease 2019 (COVID-19). In most studies, patients with various levels of COVID-19 severity were pooled and analyzed which may prevent accurate evaluation of the relationship between LDH and disease progression and in-hospital death. In this study, we aimed to evaluate the association of LDH with in-hospital mortality in severe and critically ill patients with COVID-19. Methods This single-center retrospective study enrolled 119 patients. Survival curves were plotted using Kaplan-Meier method and compared by log-rank test. Multivariate Cox regression models were used to determine the independent risk factors for in-hospital mortality. Receiver-operator curves (ROCs) were constructed to evaluate the predictive accuracy of LDH and other prognostic biomarkers. Results Compared to the survival group, LDH levels in the dead group were significantly higher [559.5 (172, 7575) U/L vs 228 (117, 490) U/L, (P less then 0.
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