397 research outputs found

    Enhanced oxidative stress and the glycolytic switch in superficial urothelial carcinoma of urinary bladder

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    AbstractObjectiveTo examine whether oxidative stress and the glycolytic switch are correlated to tumor grading, tumor recurrence, and disease progression in urothelial carcinoma (UC) of the urinary bladder (UB).MethodsAll surgical specimens obtained from 27 patients (each containing their UC and normal tissues of UB) were subjected to a pathological examination by computerized tomography, and a portion of each specimen was used for the analysis of molecular biomarkers. The mRNA expression levels of pyruvate dehydrogenase kinase-1 (PDK1), hypoxia-inducible factor 1 alpha (HIF-1α), lactate dehydrogenase A (LDHA), pyruvate dehydrogenase, and glucose transporter protein 1 (Glut-1) were measured using TaqMan-based real-time quantitative polymerase chain reaction. In addition, 8-hydroxy-2-deoxyguanosine (8-OHdG) and the mitochondrial DNA (mtDNA) copy number were also determined.ResultsThe 8-OHdG content and glycolytic genes expression were higher in UC of the UB than those in the normal tissues of UB, whereas the mtDNA copy number was depleted. According to the multivariate analysis, patients with Grade 3 tumors had higher expression levels of HIF-1α, LDHA, and Glut-1 than those with Grades 1 and 2 tumors. In addition, patients with locally recurrent tumors had a higher expression of HIF-1α and LDHA than those with nonrecurrent tumors. Furthermore, patients under disease progression had higher levels of HIF-1α and PDK1 than those not under disease progression.ConclusionsUC of the UB manifested that the glycolytic phenotype would reflect the Warburg effect. We suggest that the molecular mechanism in the regulation of glycolytic switch in UC of the UB might provide a specific biomarker for the future development of cancer diagnosis

    Chronic Myeloid Leukemia Patients Sensitive and Resistant to Imatinib Treatment Show Different Metabolic Responses

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    The BCR-ABL tyrosine kinase inhibitor imatinib is highly effective for chronic myeloid leukemia (CML). However, some patients gradually develop resistance to imatinib, resulting in therapeutic failure. Metabonomic and genomic profiling of patients' responses to drug interventions can provide novel information about the in vivo metabolism of low-molecular-weight compounds and extend our insight into the mechanism of drug resistance. Based on a multi-platform of high-throughput metabonomics, SNP array analysis, karyotype and mutation, the metabolic phenotypes and genomic polymorphisms of CML patients and their diverse responses to imatinib were characterized. The untreated CML patients (UCML) showed different metabolic patterns from those of healthy controls, and the discriminatory metabolites suggested the perturbed metabolism of the urea cycle, tricarboxylic acid cycle, lipid metabolism, and amino acid turnover in UCML. After imatinib treatment, patients sensitive to imatinib (SCML) and patients resistant to imatinib (RCML) had similar metabolic phenotypes to those of healthy controls and UCML, respectively. SCML showed a significant metabolic response to imatinib, with marked restoration of the perturbed metabolism. Most of the metabolites characterizing CML were adjusted to normal levels, including the intermediates of the urea cycle and tricarboxylic acid cycle (TCA). In contrast, neither cytogenetic nor metabonomic analysis indicated any positive response to imatinib in RCML. We report for the first time the associated genetic and metabonomic responses of CML patients to imatinib and show that the perturbed in vivo metabolism of UCML is independent of imatinib treatment in resistant patients. Thus, metabonomics can potentially characterize patients' sensitivity or resistance to drug intervention

    Mastering Complex Control in MOBA Games with Deep Reinforcement Learning

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    We study the reinforcement learning problem of complex action control in the Multi-player Online Battle Arena (MOBA) 1v1 games. This problem involves far more complicated state and action spaces than those of traditional 1v1 games, such as Go and Atari series, which makes it very difficult to search any policies with human-level performance. In this paper, we present a deep reinforcement learning framework to tackle this problem from the perspectives of both system and algorithm. Our system is of low coupling and high scalability, which enables efficient explorations at large scale. Our algorithm includes several novel strategies, including control dependency decoupling, action mask, target attention, and dual-clip PPO, with which our proposed actor-critic network can be effectively trained in our system. Tested on the MOBA game Honor of Kings, our AI agent, called Tencent Solo, can defeat top professional human players in full 1v1 games.Comment: AAAI 202

    Proteomics reveals the significance of vacuole Pi transporter in the adaptability of Brassica napus to Pi deprivation

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    Vacuolar Pi transporters (VPTs) have recently been identified as important regulators of cellular Pi status in Arabidopsis thaliana and Oryza sativa. In the oil crop Brassica napus, BnA09PHT5;1a and BnC09PHT5;1a are two homologs of AtPHT5;1, the vacuolar Pi influx transporter in Arabidopsis. Here, we show that Pi deficiency induces the transcription of both homologs of PHT5;1a genes in B. napus leaves. Brassica PHT5;1a double mutants (DM) had smaller shoots and higher cellular Pi concentrations than wild-type (WT, Westar 10), suggesting the potential role of BnPHT5;1a in modulating cellular Pi status in B. napus. A proteomic analysis was performed to estimate the role of BnPHT5;1a in Pi fluctuation. Results show that Pi deprivation disturbs the abundance of proteins in the physiological processes involved in carbohydrate metabolism, response to stimulus and stress in B. napus, while disruption of BnPHT5;1a genes may exacerbate these processes. Besides, the processes of cell redox homeostasis, lipid metabolic and proton transmembrane transport are supposed to be unbalanced in BnPHT5;1a DM under the -Pi condition. Noteworthy, disruption of BnPHT5;1a genes severely alters the abundance of proteins related to ATP biosynthesis, and proton/inorganic cation transmembrane under normal Pi condition, which might contribute to B. napus growth limitations. Additionally, seven new protein markers of Pi homeostasis are identified in B. napus. Taken together, this study characterizes the important regulatory role of BnPHT5;1a genes as vacuolar Pi influx transporters in Pi homeostasis in B. napus

    Observational Studies on the Association Between Post-diagnostic Metformin Use and Survival in Ovarian Cancer: A Systematic Review and Meta-Analysis

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    Objectives: To summarize and quantify the relationship between post-diagnostic metformin use and ovarian cancer (OC) survival.Methods: We systematically conducted an updated meta-analysis based on observational studies published up to December 31, 2018, identified from PubMed and Web of Science. Two team members independently extracted data and assessed the quality of each study. Summary Hazard ratios (HR) and 95% confidence intervals (CI) were calculated using a random-effects model.Results: Five cohort studies including 3,582 OC patients were included. All studies were graded as low risk of bias according to the Newcastle-Ottawa quality assessment scale. Post-diagnostic metformin use was associated with improved overall survival (summarized HR = 0.42, 95% CI = 0.31–0.56; I2 = 0%, P = 0.842) and progression-free survival (summarized HR = 0.69, 95% CI = 0.45–1.07; I2 = 61.9%, P = 0.049) of OC patients. For OC patients with diabetes, post-diagnostic metformin use was associated with improved overall survival (summarized HR = 0.51, 95% CI = 0.28–0.95; I2 = 47.6%, P = 0.149) and progression-free survival (summarized HR = 0.38, 95% CI = 0.27–0.55; I2 = 0%, P = 0.594). No significant publication bias was detected in these analyses.Conclusions: Post-diagnostic metformin use is consistently associated with better survival of OC patients regardless of diabetes status. Studies with larger sample sizes and prospective designs are required to confirm these findings and obtain detailed information, including standardized references for comparison, intensity and dose of metformin use, and further adjustment for potential confounders

    Association between serum keptin concentrations and insulin resistance: A population-based study from China

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    BACKGROUND Insulin resistance contributes to the cardio-metabolic risk. The effect of leptin in obese and overweight population on insulin resistance was seldom reported. METHODS A total of 1234 subjects (572 men and 662 women) aged ≥18 y was sampled by the procedure. Adiposity measures included BMI, waist circumference, hip circumference, WHR, upper arm circumference, triceps skinfold and body fat percentage. Serum leptin concentrations were measured by an ELISA method. The homeostasis model (HOMA-IR) was applied to estimate insulin resistance. RESULTS In men, BMI was the variable which was most strongly correlated with leptin, whereas triceps skinfold was most sensitive for women. More importantly, serum leptin levels among insulin resistant subjects were almost double compared to the subjects who had normal insulin sensitivity at the same level of adiposity in both men and women, after controlling for potential confounders. In addition, HOMA-IR increased significantly across leptin quintiles after adjustment for age, BMI, total energy intake, physical activity and smoking status in both men and women (p for trend <0.0001). CONCLUSIONS There was a significant association between HOMA-IR and serum leptin concentrations in Chinese men and women, independently of adiposity levels. This may suggest that serum leptin concentration is an important predictor of insulin resistance and other metabolic risks irrespective of obesity levels. Furthermore, leptin levels may be used to identify the cardio-metabolic risk in obese and overweight population.Hui Zuo, Zumin Shi, Baojun Yuan, Yue Dai, Gaolin Wu, Akhtar Hussai
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