Risk factors for in-hospital death in 2,179 patients with acute aortic dissection.

Background: This study aims to investigate the risk factors for in-hospital death in patients with acute aortic dissection (AAD) and to provide a straightforward prediction model to assist clinicians in determining the outcome of AAD patients. Methods: Retrospective analysis was carried out on 2,179 patients admitted for AAD from March 5, 1999 to April 20, 2018 in Wuhan Union Hospital, China. The risk factors were investigated with univariate and multivariable logistic regression analysis. Results: The patients were divided into two groups: Group A, 953patients (43.7%) with type A AAD; Group B, 1,226 patients (56.3%) with type B AAD. The overall in-hospital mortality rate was 20.3% (194/953) and 4% (50/1,226) in Group A and B respectively. The multivariable analysis included the variables that were statistically significant predictors of in-hospital death (P < 0.05). In Group A, hypotension (OR = 2.01, P = 0.001) and liver dysfunction (OR = 12.95, P < 0.001) were independent risk factors. Tachycardia (OR = 6.08, P < 0.001) and liver dysfunction (OR = 6.36, P < 0.05) were independent risk factors for Group B mortality. The risk factors of Group A were assigned a score equal to their coefficients, and the score of -0.5 was the best point of the risk prediction model. Based on this analysis, we derived a predictive model to help clinicians determine the prognosis of type A AAD patients. Conclusions: This study investigate the independent factors associated with in-hospital death in patients with type A or B aortic dissection, respectively. In addition, we develop the prediction of the prognosis for type A patients and assist clinicians in choosing treatment strategies.

Prognostic impact of branch vessel involvement on organ malperfusion and mid-term survival in patients with acute type A aortic dissection.

BACKGROUND: This study aimed to investigate the impact of branch vessel involvement on organ malperfusion and mid-term survival in patients with acute type A aortic dissection (ATAAD). METHODS: Between January 2019 and December 2020, 493 consecutive patients with angiographically confirmed ATAAD were retrospectively analysed. Preoperative computed tomography angiography parameters (branch artery involvement, longitudinal extent of dissection) were reviewed. The incidence of organ malperfusion, in-hospital mortality, and mid-term outcomes of patients with and without branch vessel involvement were compared. RESULTS: Branch vessel involvement was detected in 407 patients (82.6%), and organ malperfusion was observed in 234 patients (47.5%). The incidence of organ malperfusion was significantly higher in patients with branch vessel involvement compared with patients without it (52.6% vs. 23.3%, p < 0.001). Patients with coronary artery involvement (32.5%) were more likely to manifest as clinical malperfusion, whereas it occurred only 19.4% in patients with renal artery involvement. In-hospital mortality was higher in patients with branch vessel involvement (19.9% vs. 8.1%, p = 0.010). Median follow-up time was 16.1 months. Two-year survival rate was lower in patients with branch vessel involvement (76.3% vs. 84.5%, p = 0.085) or organ malperfusion (68.3% vs. 86.0%, p < 0.001). Multivariable analysis identified cardiac, cerebral, visceral and renal malperfusion as independent predictors for in-hospital mortality. CONCLUSIONS: Only a small proportion of branch vessel involvement was associated with corresponding organ malperfusion in patients with ATAAD. Branch vessel involvement had a greater effect on short-term outcomes than mid-term survival, and organ malperfusion was related to a worse prognosis beyond it.

Effectively predicting HIV-1 protease cleavage sites by using an ensemble learning approach.

BACKGROUND: The site information of substrates that can be cleaved by human immunodeficiency virus 1 proteases (HIV-1 PRs) is of great significance for designing effective inhibitors against HIV-1 viruses. A variety of machine learning-based algorithms have been developed to predict HIV-1 PR cleavage sites by extracting relevant features from substrate sequences. However, only relying on the sequence information is not sufficient to ensure a promising performance due to the uncertainty in the way of separating the datasets used for training and testing. Moreover, the existence of noisy data, i.e., false positive and false negative cleavage sites, could negatively influence the accuracy performance. RESULTS: In this work, an ensemble learning algorithm for predicting HIV-1 PR cleavage sites, namely EM-HIV, is proposed by training a set of weak learners, i.e., biased support vector machine classifiers, with the asymmetric bagging strategy. By doing so, the impact of data imbalance and noisy data can thus be alleviated. Besides, in order to make full use of substrate sequences, the features used by EM-HIV are collected from three different coding schemes, including amino acid identities, chemical properties and variable-length coevolutionary patterns, for the purpose of constructing more relevant feature vectors of octamers. Experiment results on three independent benchmark datasets demonstrate that EM-HIV outperforms state-of-the-art prediction algorithm in terms of several evaluation metrics. Hence, EM-HIV can be regarded as a useful tool to accurately predict HIV-1 PR cleavage sites.

Decreased expression of HBA1 and HBB genes in acute myeloid leukemia patients and their inhibitory effects on growth of K562 cells.

BACKGROUND: Besides the traditional roles of HBA1 and HBB, recent findings suggest that hemoglobin genes may have roles in other contexts. OBJECTIVE: In the present study, we aim to investigate a possible tumor-suppressor role of HBA1 and HBB in acute myeloid leukemia. METHODS: Quantitative real-time PCR (RT-qPCR) was performed to detect the expression levels of HBA1 and HBB in acute myeloid leukemia patients and AML cell lines. The transfected cells were analyzed for Cell Counting Kit-8 (CCK-8), apoptosis, and cell cycle assay. RESULTS: HBA1 and HBB genes were significantly decreased in acute myeloid leukemia patients and AML cell lines. Furthermore, in vitro approaches showed that overexpression of HBA1 and HBB inhibited proliferation, induced cell apoptosis, and blocked cell cycle process at the G2/M phase in K562 cells. CONCLUSION: Our data indicated that HBA1 and HBB genes may be potential tumor-suppressor genes in acute myeloid leukemia.

Effect of elevated fasting blood glucose level on the 1-year mortality and sequelae in hospitalized COVID-19 patients: A bidirectional cohort study.

To observe the predictive effect of fasting blood glucose (FBG) level on the prognosis, clinical sequelae, and pulmonary absorption in hospitalized coronavirus disease 2019 (COVID-19) patients with and without a history of diabetes, respectively, and to evaluate the correlation between the dynamic changes of FBG and poor prognosis. In this bidirectional cohort study, we enrolled 2545 hospitalized COVID-19 patients (439 diabetics and 2106 without a diabetic history) and followed up for 1 year. The patients were divided according to the level of admission FBG. The dynamic changes of FBG were compared between the survival and the death cases. The prediction effect of FBG on 1-year mortality and sequelae was analyzed. The 1-year all cause mortality rate and in-hospital mortality rate of COVID-19 patients were J-curve correlated with FBG (p < 0.001 for both in the nondiabetic history group, p = 0.004 and p = 0.01 in the diabetic history group). FBG ≥ 7.0 mmol/L had a higher risk of developing sequelae (p = 0.025) and have slower recovery of abnormal lung scans (p < 0.001) in patients who denied a history of diabetes. Multivariable Cox regression analysis showed that FBG ≥ 7.0 mmol/L was an independent risk factor for the mortality of COVID-19 regardless of the presence or deny a history of diabetes (hazard atio [HR] = 10.63, 95% confidence interval [CI]: 7.15-15.83, p < 0.001; HR = 3.9, 95% CI: 1.56-9.77, p = 0.004, respectively). Our study shows that FBG ≥ 7.0 mmol/L can be a predictive factor of 1-year all-cause mortality in COVID-19 patients, independent of diabetes history. FBG ≥ 7.0 mmol/L has an advantage in predicting the severity, clinical sequelae, and pulmonary absorption in COVID-19 patients without a history of diabetes. Early detection, timely treatment, and strict control of blood glucose when finding hyperglycemia in COVID-19 patients (with or without diabetes) are critical for their prognosis.

One-year mortality and consequences of COVID-19 in cancer patients: A cohort study.

The 1-year mortality and health consequences of COVID-19 in cancer patients are relatively underexplored. In this multicenter cohort study, 166 COVID-19 patients with cancer were compared with 498 non-cancer COVID-19 patients and 498 non-COVID cancer patients. The 1-year all-cause mortality and hospital mortality rates in Cancer COVID-19 Cohort (30% and 20%) were significantly higher than those in COVID-19 Cohort (9% and 8%, both P < .001) and Cancer Cohort (16% and 2%, both P < 0.001). The 12-month all-cause post-discharge mortality rate in survival discharged Cancer COVID-19 Cohort (8%) was higher than that in COVID-19 Cohort (0.4%, P < .001) but similar to that in Cancer Cohort (15%, P = .084). The incidence of sequelae in Cancer COVID-19 Cohort (23%, 26/114) is similar to that in COVID-19 Cohort (30%, 130/432, P = .13). The 1-year all-cause mortality was high among patients with hematologic malignancies (59%), followed by those who have nasopharyngeal, brain, and skin tumors (45%), digestive system neoplasm (43%), and lung cancers (32%). The rate was moderate among patients with genitourinary (14%), female genital (13%), breast (11%), and thyroid tumors (0). COVID-19 patients with cancer showed a high rate of in-hospital mortality and 1-year all-cause mortality, but the 12-month all-cause post-discharge mortality rate in survival discharged cancer COVID-19 patients was similar to that in Cancer Cohort. Comparing to COVID-19 Cohort, risk stratification showed that hematologic, nasopharyngeal, brain, digestive system, and lung tumors were high risk (44% vs 9%, P < 0.001), while genitourinary, female genital, breast, and thyroid tumors had moderate risk (10% vs 9%, P = .85) in COVID-19 Cancer Cohort. Different tumor subtypes had different effects on COVID-19. But if cancer patients with COVID-19 manage to survive their COVID-19 infections, then long-term mortality appears to be similar to the cancer patients without COVID-19, and their long-term clinical sequelae were similar to the COVID-19 patients without cancer.

Predicting HIV-1 Protease Cleavage Sites With Positive-Unlabeled Learning.

Understanding the substrate specificity of HIV-1 protease plays an essential role in the prevention of HIV infection. A variety of computational models have thus been developed to predict substrate sites that are cleaved by HIV-1 protease, but most of them normally follow a supervised learning scheme to build classifiers by considering experimentally verified cleavable sites as positive samples and unknown sites as negative samples. However, certain noisy can be contained in the negative set, as false negative samples are possibly existed. Hence, the performance of the classifiers is not as accurate as they could be due to the biased prediction results. In this work, unknown substrate sites are regarded as unlabeled samples instead of negative ones. We propose a novel positive-unlabeled learning algorithm, namely PU-HIV, for an effective prediction of HIV-1 protease cleavage sites. Features used by PU-HIV are encoded from different perspectives of substrate sequences, including amino acid identities, coevolutionary patterns and chemical properties. By adjusting the weights of errors generated by positive and unlabeled samples, a biased support vector machine classifier can be built to complete the prediction task. In comparison with state-of-the-art prediction models, benchmarking experiments using cross-validation and independent tests demonstrated the superior performance of PU-HIV in terms of AUC, PR-AUC, and F-measure. Thus, with PU-HIV, it is possible to identify previously unknown, but physiologically existed substrate sites that are able to be cleaved by HIV-1 protease, thus providing valuable insights into designing novel HIV-1 protease inhibitors for HIV treatment.

Prognostic evaluation of ALIP and CD34 immunostaining in IPSS-R subgroups of myelodysplastic syndromes.

In order to evaluate the prognostic value of abnormal localisation of immature precursors (ALIP) and CD34 immunostaining in myelodysplastic syndromes (MDS), bone marrow histopathological features in 187 MDS patients were retrospectively analysed and the prognostic significance of ALIP and CD34 immunostaining on overall survival (OS) and progression to leukaemia-free survival (PFS) in total patients and different Revised-International Prognostic Scoring System (IPSS-R) subgroups were evaluated. In univariate analysis, age ≥60, ALIP, ≥5% CD34+ cells, CD34+ clusters and IPSS-R subgroups were associated with shorter OS (p = 0.027, p < 0.0001, p < 0.0001, p < 0.0001, p < 0.0001, respectively) and PFS (p = 0.029, p = 0.006, p = 0.001, p < 0.0001, p < 0.0001, respectively). Haemoglobin level had a significant impact on OS (p < 0.0001) but not on PFS (p = 0.054). In multivariate analysis, ALIP, haemoglobin level, ≥5% CD34+ cells, CD34+ clusters and IPSS-R subgroups had independent influence on OS (p = 0.012, p < 0.0001, p = 0.010, p < 0.0001, p < 0.0001, respectively), while only CD34+ clusters and IPSS-R subgroups had independent influence on PFS (p < 0.0001, p = 0.016, respectively). In different IPSS-R subgroups, ALIP could maintain its prognostic impact in lower IPSS-R risk subgroups, while ≥5% CD34+ cells and CD34+ clusters had significant prognostic value in both lower and intermediate-higher IPSS-R risk subgroups. Therefore, CD34+ clusters showed more important prognostic impact on survival and progression to leukaemia.

Dissociation of NSC606985 induces atypical ER-stress and cell death in prostate cancer cells.

Castration-resistant prostate cancer (CRPC) is a major cause of prostate cancer (Pca) death. Chemotherapy is able to improve the survival of CRPC patients. We previously found that NSC606985 (NSC), a highly water-soluble camptothecin analog, induced cell death in Pca cells via interaction with topoisomerase 1 and activation of the mitochondrial apoptotic pathway. To further elucidate the role of NSC, we studied the effect of NSC on ER-stress and its association with NSC-induced cell death in Pca cells. NSC produced a time- and dose-dependent induction of GRP78, CHOP and XBP1s mRNA, and CHOP protein expression in Pca cells including DU145, indicating an activation of ER-stress. However, unlike conventional ER-stress in which GRP78 protein is increased, NSC produced a time- and dose-dependent U-shape change in GRP78 protein in DU145 cells. The NSC-induced decrease in GRP78 protein was blocked by protease inhibitors, N-acetyl-L-leucyl-L-leucylnorleucinal (ALLN), a lysosomal protease inhibitor, and epoxomicin (EPO), a ubiquitin-protease inhibitor. ALLN, but not EPO, also partially inhibited NSC-induced cell death. However, both 4-PBA and TUDCA, two chemical chaperons that effectively reduced tunicamycin-induced ER-stress, failed to attenuate NSC-induced GRP78, CHOP and XBP1s mRNA expression and cell death. Moreover, knockdown of NSC induction of CHOP expression using a specific siRNA had no effect on NSC-induced cytochrome c release and NSC-induced cell death. These results suggest that NSC produced an atypical ER-stress that is dissociated from NSC-induced activation of the mitochondrial apoptotic pathway and NSC-induced cell death in DU145 prostate cancer cells.

Resveratrol inhibits the secretion of vascular endothelial growth factor and subsequent proliferation in human leukemia U937 cells.

This study examined the effect of resveratrol on the secretion of vascular endothelial growth factor (VEGF) and subsequent proliferation of human leukemia U937 cells, and explored the mechanisms involved. Human leukemia U937 cells were treated with resveratrol of different concentrations (12.5-200 micromol/L) for different time lengths (12-48 h). The proliferation of the U937 leukemic cells was determined by MTT assay. Apoptosis was observed by Annexin-V-FIFC/PI double staining and flow cytometry (FCM). Cells cycle was analyzed by PI staining and FCM. The content of VEGF was determined by ELISA. Human umbilical vein endothelial cells were examined for vasoformation in vitro after exposures to resveratrol of various concentrations. The results showed that resveratrol inhibited the proliferation of U937 leukemia cells in a dose-and time-dependent manner. Resveratrol induced apoptosis and S-phase cell cycle arrest in human leukemic U937 cells. Resveratrol inhibited the secretion of VEGF in U937 cells. Resveratrol inhibited the vasoformation of human vein endothelial cells in a dose-dependent manner. It was concluded that resveratrol could down-regulate the secretion of VEGF, induce apoptosis and suppress the proliferation of U937 cells.