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The endocrine disruptor chemicals (EDCs) are ubiquitous in the environment, and it has raised wide public concern because of the dangers of EDCs for living organisms and the environment. In order to comparatively study the effects of EDCs [17-α-ethinylestradiol (EE2), Bisphenol A (BPA) and Nonylphenol (NP)] on the expression of estrogen receptors (ERs: erα, erβ1, and erβ2) at mRNA and protein level, total 520 adult Tanichthys albonubes were exposed to E2, EE2, BPA and NP with three concentrations respectively: EE2 (1, 5, 25 ng/l), NP (10, 50, 250 μg/l), BPA (100, 500, 2,500 μg/l) for 28 days, E2 (2, 20, 200 ng/l) being as the positive control. After treatment, the brain, eye, gill, heart, liver, gut, kidney, muscle, testis, and ovary were collected, following by the real-time quantitative PCR (RT-qPCR) and western blot methods to detect the expression levels of erα, erβ1, and erβ2 in T.albonubes at mRNA and protein level. Our results showed that high expression of terα (t means T.albonubes), terβ1, and terβ2 were detected in liver, while terβ1 and terβ2 mainly expressed in the liver, intestine, kidney, muscle and testis. EE2, BPA, and NP treatment all up-regulated the expression of terα, terβ1, and terβ2 in the brain, liver, and testis, but with some variations. Similar to mRNA level, both TERα and TERβ were up-regulated by all the EE2, BPA, and NP treatment with dose-dependent effect. In conclusion, the responses of ERs of T.albonubes to the EDCs present measurability and susceptibility, which make it possible for T. albonubes to be an efficient biomarker to monitor and evaluate the pollution of endocrine disrupting chemicals in water environment.

The endocrine disruptor chemicals (EDCs) are ubiquitous in the environment, and it has raised wide public concern because of the dangers of EDCs for living organisms and the environment. In order to comparatively study the effects of EDCs [17-α-ethinylestradiol (EE

Background: Nuclear Yes-associated protein 1 (YAP1) has often been regarded as an adverse prognostic indicator in various tumors. Recent studies have associated YAP1 with unfavorable prognosis in nonsmall cell lung cancer (NSCLC). However, due to small sample sizes, the prognostic value of nuclear YAP1 in NSCLC patients is not well understood. In the present study, we evaluated the prognostic role of nuclear YAP1 in NSCLC patients via a systematic review and meta-analysis. Methods: We searched the PubMed, EMBASE, Cochrane, Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang Databases for papers investigating the prognostic significance of nuclear YAP1 expression in NSCLC patients. Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) were calculated with reference to overall survival (OS) and progression-free survival (PFS) of NSCLC patients to provide synthesized estimates of the effects of nuclear YAP1 expression. Results: Among 414 cases, higher nuclear YAP1 expression presented as a predictive factor of poorer OS (HR = 1.52; 95% CI: 1.11–2.08; P = .01; I2 = 0.0%) and decreased PFS (HR = 2.11; 95% CI: 1.52–2.93; P

Early detection of lung cancer is an effective way to improve the survival rate of patients. It is a critical step to have accurate detection of lung nodules in computed tomography (CT) images for the diagnosis of lung cancer. However, due to the heterogeneity of the lung nodules and the complexity of the surrounding environment, robust nodule detection has been a challenging task. In this study, we propose a two-stage convolutional neural network (TSCNN) architecture for lung nodule detection. The CNN architecture in the first stage is based on the improved UNet segmentation network to establish an initial detection of lung nodules. Simultaneously, in order to obtain a high recall rate without introducing excessive false positive nodules, we propose a novel sampling strategy, and use the offline hard mining idea for training and prediction according to the proposed cascaded prediction method. The CNN architecture in the second stage is based on the proposed dual pooling structure, which is built into three 3D CNN classification networks for false positive reduction. Since the network training requires a significant amount of training data, we adopt a data augmentation method based on random mask. Furthermore, we have improved the generalization ability of the false positive reduction model by means of ensemble learning. The proposed method has been experimentally verified on the LUNA dataset. Experimental results show that the proposed TSCNN architecture can obtain competitive detection performance., Comment: 29 pages, 10 figures

This study investigated the in vitro and in vivo antioxidant activities of the flavonoids rich extract from Rhodomyrtus tomentosa Hassk (R. tomentosa) berries. The in vitro antioxidant assay demonstrated that the flavonoids rich extract (62.09% rutin equivalent) extracted by ethanol and purified by AB-8 macroporous resin was strong in reducing power, superoxide radical, hydroxyl radical and DPPH radical scavenging activity, as well as inhibiting lipid peroxidation. In the in vivo assays, the flavonoids rich extract significantly enhanced the activities of antioxidant enzymes in serums of mice after they were administered with the extract. The results suggested that the flavonoids rich extract from R. tomentosa fruits possesses potent antioxidant properties. In addition, the chemical compositions of flavonoids rich extract were identified by UPLC-TOF-MS/MS. Six flavonoids were tentatively identified as myricetin, quercetin, dihydromyricetin, kaempferol, quercetin 7,4'-diglucoside and vitexin. Therefore, R. tomentosa berries could be used as a new source of antioxidant ingredient.

The study of the past, present, and future state and dynamics of the tropical natural forest cover (NFC) might help to better understand the pattern of deforestation and fragmentation as well as the influence of social and natural processes. The obtained information will support the development of effective conservation policies and strategies. In the present study, we used historical data of the road network, topography, and climatic productivity to reconstruct NFC maps of Hainan Island, China, from the 1950s to the 2010s, using the random forest algorithm. We investigated the spatial and temporal patterns of NFC change from the 1950s to the 2010s and found that it was highly dynamic in both space and time. Our data showed that grid cells with low NFC were more vulnerable to NFC decrease, suggesting that conservation actions regarding natural forests need to focus on regions with low NFC and high ecological value. We also identified the hot-spots of NFC change, which provides insights into the dynamic changes of natural forests over time.

The optimal condition of spray drying purified flavonoids extract fromR. tomentosaberries was studied by response surface methodology. The optimized condition for microencapsulation was of maltodextrin to gum Arabic ratio 1 : 1.3, total solid content 27.4%, glycerol monostearate content 0.25%, and core to coating material ratio 3 : 7, resulting in EE 91.75%. Prepared at the optimized condition, the flavonoids extract microcapsules (FEMs) were irregularly spherical particles with low moisture content (3.27%), high solubility (92.35%), and high bulk density (0.346 g/cm3). DPPH radical scavenging activity of FEMs was not decreased after spray drying (P>0.05) and higher than those in citric acid and rutin at the same concentration. Moreover, FEMs effectively retarded the oxidation of fresh lard during the 10-day storage period compared with vitamin C, nonencapsulated flavonoids extract, and rutin. Therefore, FEMs produced at the optimized condition could be used as powder ingredients with antioxidant capacities.

The TSP (Traveling Salesman Problem) genetic algorithm is very possible of destroying ever found pieces of a path. To prevent the found pieces from being destroyed, a P2P based TSP genetic algorithm P2PTSPGA which make use of gene clusters is presented. The gene cluster which stands for a series of cities is past down in whole to the offspring from their parent individuals, and is smashed after the first optimum is found to prevent the algorithm from falling into a local optimum. Experiments on CHN144 and instances of TSPLIB show that the optimal solutions are the same as the published results, except the solution 3859 for TSP225 is better than the result 3916 published up-to-date. Our experiments also show that the P2PTSPGA has a high performance in solving such TSPs that number of cities is less than 5000.