Factors associated with distant metastasis in pediatric thyroid cancer: evaluation of the SEER database

Objectives: Controversies regarding factors associated with distant metastasis in pediatric thyroid cancer remain among the scientific community. The aim of this study was to investigate factors influencing distant metastasis in pediatric thyroid cancer. Methods: We reviewed 1376 patients (aged 2 to 18 years) with thyroid cancer treated between 2003 and 2014. Data collected and analyzed included sex, race, age at diagnosis, year of diagnosis, pathological type, number of tumor foci, tumor extension, T-stage, N-stage, surgical procedure and radiation. Univariate and multivariate analyses were conducted to evaluate factors influencing distant metastasis of pediatric thyroid cancer. Results: In the univariate analysis, factors influencing distant metastasis of thyroid cancer were age at diagnosis (P 0.05). Furthermore, according to chi-squared test, younger pediatric thyroid cancer patients with higher T- and N-stages are more likely to have distant metastasis. Conclusion: Age at diagnosis, T-stage and N-stage influence distant metastasis of thyroid cancer patients aged 2 to 18 years; accordingly, more radical treatments may need to be used for patients with those risk elements

QSAR Studies on Andrographolide Derivatives as α-Glucosidase Inhibitors

Andrographolide derivatives were shown to inhibit α-glucosidase. To investigate the relationship between activities and structures of andrographolide derivatives, a training set was chosen from 25 andrographolide derivatives by the principal component analysis (PCA) method, and a quantitative structure-activity relationship (QSAR) was established by 2D and 3D QSAR methods. The cross-validation r2 (0.731) and standard error (0.225) illustrated that the 2D-QSAR model was able to identify the important molecular fragments and the cross-validation r2 (0.794) and standard error (0.127) demonstrated that the 3D-QSAR model was capable of exploring the spatial distribution of important fragments. The obtained results suggested that proposed combination of 2D and 3D QSAR models could be useful in predicting the α-glucosidase inhibiting activity of andrographolide derivatives

Condition Monitoring of Wind Turbine Based on Copula Function and Autoregressive Neural Network

The traditional wind turbine fault monitoring is often based on a single monitoring signal without considering the overall correlation between signals. A global condition monitoring method based on Copula function and autoregressive neural network is proposed for this problem. Firstly, the Copula function was used to construct the binary joint probability density function of the power and wind speed in the fault-free state of the wind turbine. The function was used as the data fusion model to output the fusion data, and a fault-free condition monitoring model based on the auto-regressive neural network in the faultless state was established. The monitoring model makes a single-step prediction of wind speed and power, and statistical analysis of the residual values of the prediction determines whether the value is abnormal, and then establishes a fault warning mechanism. The experimental results show that this method can provide early warning and effectively realize the monitoring of wind turbine condition

Condition Monitoring of Wind Turbine Based on Copula Function and Autoregressive Neural Network

The traditional wind turbine fault monitoring is often based on a single monitoring signal without considering the overall correlation between signals. A global condition monitoring method based on Copula function and autoregressive neural network is proposed for this problem. Firstly, the Copula function was used to construct the binary joint probability density function of the power and wind speed in the fault-free state of the wind turbine. The function was used as the data fusion model to output the fusion data, and a fault-free condition monitoring model based on the auto-regressive neural network in the faultless state was established. The monitoring model makes a single-step prediction of wind speed and power, and statistical analysis of the residual values of the prediction determines whether the value is abnormal, and then establishes a fault warning mechanism. The experimental results show that this method can provide early warning and effectively realize the monitoring of wind turbine condition

Spectrophotometric flow injection determination of dissolved titanium in seawater exploiting in-line nitrilotriacetic acid resin preconcentration and a long path length liquid waveguide capillary cell

A sensitive spectrophotometric method for the determination of dissolved titanium (Ti) in seawater is developed. It involves in-line preconcentration and a long path length liquid waveguide capillary cell (LWCC). Nitrilotriacetic acid (NTA) resin is used to preconcentrate Ti from ∼25 mL seawater sample at pH 1.7, and elution is accomplished with 0.8 mol L−1 hydrochloride acid. The eluted Ti solution is buffered to pH 6.0 with 1.0 mol L−1 ammonium acetate and mixed with 1.5 mmol L−1 Tiron solution. The mixture is then injected into LWCC and measured by spectrophotometry at 420 nm. Before the preconcentration step, the sample is treated with 7 mmol L−1 ascorbic acid to reduce Fe(III) to Fe(II), in order to eliminate the Fe interference. The method is not interfered by Fe(III) and Cu(II) present in seawater samples at concentrations 50-fold higher in relation to Ti, and by Cd(II), Pb(II), Cr(VI), Mn(II), Al(III), Zn(II), and Ni(II) at concentrations 100-fold higher in relation to Ti. It is time efficient (7.5 minutes per sample), sensitive (0.10 nmol L−1 detection limit), precise (1.40% measurement RSD at 1.00 nmol L−1 Ti) and is characterized by a linear range of 0.50–5.00 nmol L−1 Ti. The method was applied to analysis of natural water samples collected from the Jiulongjiang Estuary, Fujian, China. [Display omitted] •Sensitive spectrophotometric detection of dissolved Ti in seawater is developed.•NTA resin is used to preconcentrate dissolved Ti in seawater at pH 1.7.•Fe(III) is reduced to Fe(II) before resin to avoid Fe retention and interference.•In-line preconcentration and detection is realized with flow analysis and LWCC.•Estuarine dissolved Ti is analyzed and reported

Application of Minnan Folk Light and Shadow Animation in Built Environment in Object Detection Algorithm

To resolve the problems of deep convolutional neural network models with many parameters and high memory resource consumption, a lightweight network-based algorithm for building detection of Minnan folk light synthetic aperture radar (SAR) images is proposed. Firstly, based on the rotating target detection algorithm R-centernet, the Ghost ResNet network is constructed to reduce the number of model parameters by replacing the traditional convolution in the backbone network with Ghost convolution. Secondly, a channel attention module integrating width and height information is proposed to enhance the network’s ability to accurately locate salient regions in folk light images. Content-aware reassembly of features (CARAFE) up-sampling is used to replace the deconvolution module in the network to fully incorporate feature map information during up-sampling to improve target detection. Finally, the constructed dataset of rotated and annotated light and shadow SAR images is trained and tested using the improved R-centernet algorithm. The experimental results show that the improved algorithm improves the accuracy by 3.8%, the recall by 1.2% and the detection speed by 12 frames/second compared with the original R-centernet algorithm

Reconciling ASPP-p53 binding mode discrepancies through an ensemble binding framework that bridges crystallography and NMR data.

ASPP2 and iASPP bind to p53 through their conserved ANK-SH3 domains to respectively promote and inhibit p53-dependent cell apoptosis. While crystallography has indicated that these two proteins employ distinct surfaces of their ANK-SH3 domains to bind to p53, solution NMR data has suggested similar surfaces. In this study, we employed multi-scale molecular dynamics (MD) simulations combined with free energy calculations to reconcile the discrepancy in the binding modes. We demonstrated that the binding mode based solely on a single crystal structure does not enable iASPP's RT loop to engage with p53's C-terminal linker-a verified interaction. Instead, an ensemble of simulated iASPP-p53 complexes facilitates this interaction. We showed that the ensemble-average inter-protein contacting residues and NMR-detected interfacial residues qualitatively overlap on ASPP proteins, and the ensemble-average binding free energies better match experimental KD values compared to single crystallgarphy-determined binding mode. For iASPP, the sampled ensemble complexes can be grouped into two classes, resembling the binding modes determined by crystallography and solution NMR. We thus propose that crystal packing shifts the equilibrium of binding modes towards the crystallography-determined one. Lastly, we showed that the ensemble binding complexes are sensitive to p53's intrinsically disordered regions (IDRs), attesting to experimental observations that these IDRs contribute to biological functions. Our results provide a dynamic and ensemble perspective for scrutinizing these important cancer-related protein-protein interactions (PPIs)

A Model of Interaction between Nicotinamide Adenine Dinucleotide Phosphate (NADPH) Oxidase and Apocynin Analogues by Docking Method

Abstract: Some apocynin analogues have exhibited outstanding inhibition to NADPH oxidase. In this study, the key interactions between apocynin analogues and NADPH oxidase were analyzed by the docking method. The potential active site was first identified by the SiteID program combining with the key residue CYS378. Afterwards, the compounds in the training set were docked into NADPH oxidase (1K4U) under specific docking constraints to discuss the key interactions between ligands and the receptor. These key interactions were then validated by the consistence between the docking result and the experimental result of the test set. The result reveals that the Pi interaction between apocynin analogues and NADPH oxidase has a direct contribution to inhibition activities, except for H-bond formation and docking score. The key interactions might be valuable to discover and screen apocynin analogues as potent inhibitors of NADPH oxidase

Real-Time Redox Speciation of Iron in Estuarine and Coastal Surface Waters

An automated, shipboard-use system was developed for real-time speciation of iron in coastal surface waters. It comprised a towed Fish underway sampler and a modified reverse flow injection analysis system with a liquid waveguide capillary flow cell–spectrophotometric detection device. The detection was based on the reaction between ferrozine and Fe­(II). The detection limits of 0.3 and 0.7 nM were achieved for Fe­(II) and Fe­(II+III), together with their respective dynamic linear ranges of 0.5–250 and 0.9–250 nM. The system was successfully deployed and run consecutively for about 1 week during a cruise in August 2009 to the East China Sea off the Changjiang Estuary. The distribution of operationally defined field dissolvable Fe­(II) and Fe­(II+III) (expressed as Fe_a(II) and Fe_a(II+III)) in these areas was obtained, which showed that both Fe_a(II) and Fe_a(II+III) concentrations decreased with salinity when there were relatively high Fe_a(II) concentrations (up to about 120 nM) near shore. A distinct distribution of Fe_a(II) to Fe_a(II+III) ratios was also revealed, with a ratio of 0.58 in the water off Changjiang Estuary and 0.19 in the open ocean

Sedimentary DNA identifies modern and past macrophyte diversity and its environmental drivers in high‐latitude and high‐elevation lakes in Siberia and China

Arctic and alpine aquatic ecosystems are changing rapidly under recent global warming, threatening water resources by diminishing trophic status and changing biotic composition. Macrophytes play a key role in the ecology of freshwaters and we need to improve our understanding of long‐term macrophytes diversity and environmental change so far limited by the sporadic presence of macrofossils in sediments. In our study, we applied metabarcoding using the trnL P6 loop marker to retrieve macrophyte richness and composition from 179 surface‐sediment samples from arctic Siberian and alpine Chinese lakes and three representative lake cores. The surface‐sediment dataset suggests that macrophyte richness and composition are mostly affected by temperature and conductivity, with highest richness when mean July temperatures are higher than 12°C and conductivity ranges between 40 and 400 μS cm−1. Compositional turnover during the Late Pleistocene/Holocene is minor in Siberian cores and characterized by a less rich, but stable emergent macrophyte community. Richness decreases during the Last Glacial Maximum and rises during wetter and warmer climate in the Late‐glacial and Mid‐Holocene. In contrast, we detect a pronounced change from emergent to submerged taxa at 14 ka in the Tibetan alpine core, which can be explained by increasing temperature and conductivity due to glacial runoff and evaporation. Our study provides evidence for the suitability of the trnL marker to recover modern and past macrophyte diversity and its applicability for the response of macrophyte diversity to lake‐hydrochemical and climate variability predicting contrasting macrophyte changes in arctic and alpine lakes under intensified warming and human impact.Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809Second Tibetan Plateau Scientific Expedition and Research Programhttps://doi.pangaea.de/10.1594/PANGAEA.920866https://doi.org/10.5061/dryad.k6djh9w4