Sperm DNA damage is recognized as an important biomarker of male infertility. To investigate this, sperm DNA damage was assessed by the sperm chromatin dispersion （SCD） test in semen and motile ...spermatozoa harvested by combined density gradient centrifugation （DGC） and swim-up in 161 couples undergoing in vitro fertilization （IVF）. Semen analysis and sperm DNA damage results were compared between couples who did or did not achieve pregnancy. The sperm DNA damage level was significantly different between the two groups （P 〈 0.05） and was negatively correlated with IVF outcomes. Logistic regression analysis confirmed that it was an independent predictor for achieving clinical pregnancy. The effects of different levels of sperm DNA damage on IVF outcomes were also compared. There were significant differences in day 3 embryo quality, blastocyst formation rate, and implantation and pregnancy rates （P 〈 0.05）, but not in the basic fertilization rate between the two groups. Thus, sperm DNA damage as measured by the SCD appears useful for predicting the clinical pregnancy rate following IVF.
Cisplatin, a commonly used chemotherapy drug, can increase the survival rate of cancer patients. However, it often causes various side effects, including neuronal deficit-induced cognitive ...impairment. Considering that curcumin is effective in neuronal protection, the action of curcumin on cognitive improvement was evaluated in cisplatin-treated C57BL/6 mice in the present study. Our results first showed that curcumin restored impaired cognitive behaviors. Consistent with this, neurogenesis and synaptogenesis were improved by curcumin. In addition, cisplatin-induced dysfunction of apoptosis-related proteins was partly reversed by curcumin. Moreover, cisplatin-induced autophagy was enhanced by curcumin. Our results also indicated that cisplatin induced autophagy through the endoplasmic reticulum (ER) stress-mediated ATF4-Akt-mTOR signaling pathway. Curcumin activated AMPK-JNK signaling, which mediated both mTOR inhibition and Bcl-2 upregulation and in turn enhanced autophagy and suppressed apoptosis, respectively. In contrast, pretreatment with the autophagy inhibitor 3-methyladenine (3-MA) completely abolished the effects of curcumin on cognitive improvement and improved neurogenesis, synaptogenesis and autophagy. Our results show that cognitive improvement induced by curcumin during chemotherapy is mediated by the enhancement of hippocampal autophagy.
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•Curcumin attenuates the impaired cognition induced by cisplatin.•Curcumin promotes neurogenesis and synaptogenesis in the hippocampus.•Curcumin enhances autophagy in the hippocampus.•The autophagy enhanced by curcumin is mediated by AMPK-JNK signaling.•3-MA blocks the effects of curcumin on cognitive improvement in chemotherapy.
Lymph node metastasis of lung cancer is a serious problem. Therefore, there is a need for a detailed transcriptome study of metastatic lung adenocarcinoma. The lung adenocarcinoma RNA-seq data and ...the corresponding clinical information available from TCGA were analyzed. Differential expression, gradient changes, and biological pathways were carried out. Potential gene(s) associated with tumor metastasis and survival were validated by Cox regression. A total of 406 and 439 differentially expressed genes were identified for lymph node metastasis and TNM stages, respectively. Of the 296 intersection genes, 112 were associated with nodal metastasis and/or staging. Only 25 of these 112 genes with gradient changes were involved in nodal metastasis, and 13 were involved in staging. Only one gene, RN7SL494P, might be involved in lung adenocarcinoma development and poor outcome. Finally, Cox regression results verified that age, pathology classification, radiotherapy and chemotherapy are all the independent prognostic factors. In particular, RN7SL494P was further verified to be an independent factor affecting lymph node metastasis and patient survival. Furthermore, we verified the RN7SL494P function using simulation data generated by mixing cell lines of the Cancer Cell Line Encyclopedia (CCLE) and obtained consistent results. Our findings suggest a potential clinical application of the RN7SL494P as a promising marker in the evaluation of patients with primary lung adenocarcinoma, not only for predicting nodal metastasis, but also for the prognosis of the outcome.
Robust Estimators for Multipass SAR Interferometry Wang, Yuanyuan; Zhu, Xiao Xiang
IEEE transactions on geoscience and remote sensing,
2016-Feb., 2016-2-00, 20160201, Letnik:
54, Številka:
2
Journal Article
Recenzirano
Odprti dostop
This paper introduces a framework for robust parameter estimation in multipass interferometric synthetic aperture radar (InSAR), such as persistent scatterer interferometry, SAR tomography, small ...baseline subset, and SqueeSAR. These techniques involve estimation of phase history parameters with or without covariance matrix estimation. Typically, their optimal estimators are derived on the assumption of stationary complex Gaussian-distributed observations. However, their statistical robustness has not been addressed with respect to observations with nonergodic and non-Gaussian multivariate distributions. The proposed robust InSAR optimization (RIO) framework answers two fundamental questions in multipass InSAR: 1) how to optimally treat images with a large phase error, e.g., due to unmolded motion phase, uncompensated atmospheric phase, etc.; and 2) how to estimate the covariance matrix of a non-Gaussian complex InSAR multivariate, particularly those with nonstationary phase signals. For the former question, RIO employs a robust M-estimator to effectively downweight these images; and for the latter, we propose a new method, i.e., the rank M-estimator, which is robust against non-Gaussian distribution. Furthermore, it can work without the assumption of sample stationarity, which is a topic that has not previously been addressed. We demonstrate the advantages of the proposed framework for data with large phase error and heavily tailed distribution, by comparing it with state-of-the-art estimators for persistent and distributed scatterers. Substantial improvement can be achieved in terms of the variance of estimates. The proposed framework can be easily extended to other multipass InSAR techniques, particularly to those where covariance matrix estimation is vital.
Predicting individual vehicles' future locations is of great significance in location-based services. Regularity and preference are two predominant features of individual vehicles for location ...prediction. However, these two features cannot be adequately captured with existing models based on raw trajectories, due to their oversimplified view. Modeling regularity and preference entails the following challenges: 1) how to design features to accurately reflect regularity and preference with raw trajectories; and 2) how to capture regularity and preference effectively based on sparse travel behaviors. To that end, first, we design four features to represent travel regularity and preference by conducting an in-depth correlation analysis on individual vehicle trajectories. Then, we incorporate these four features in context and propose a deep neural network to jointly capture regularity and preference via explicitly retrieving the context. Specifically, our proposed model extends LSTM with memory to store all the output hidden states, which provides long-term information for retrieval to overcome the vanishing sequential dependency in sparse scenarios. To fully capture regularity and preference for prediction, a backtracking attention mechanism is designed to aggregate all the relevant historical hidden states in memory with different weights based on the regularity and preference similarity. The weighted aggregation produces a new hidden state, which is used for the final prediction. Experiments on three real-world vehicle trajectory datasets containing over 10,000 individual vehicles show that our proposed model outperforms the state-of-the-art models by 7%-10% in terms of prediction accuracy.
Highly asymmetric Au nanostructures, such as split Au nanorings and Au nanocups, exhibit attractive plasmonic properties because of their asymmetric geometries. To facilitate their plasmonic ...applications, effective and facile synthetic methods for producing asymmetric Au nanostructures with controllable sizes and uniform shapes are highly desirable. Herein, we report on an approach for the synthesis of largely asymmetric colloidal Au nanobottles with synthetically tunable overall and opening sizes. Au nanobottles with overall sizes in the range of ∼100-230 nm are obtained through sacrificial templating with differently sized PbS nano-octahedra. The opening sizes of the produced Au nanobottles can be tailored from ∼10 to ∼120 nm by either adjusting the Au/PbS molar ratio in the growth process or controlling the oxidation degree. The achieved size tunability allows the plasmon resonance wavelength of Au nanobottles to be varied in the range of ∼600-900 nm. Our uniform Au nanobottles, which possess controllable sizes, large cavity volumes, and tunable plasmon resonance wavelengths in the visible to near-infrared range, have been further applied for anticancer drug delivery and photothermal therapy. The effects of surface coating and the opening size of Au nanobottles on the drug encapsulation efficiency (EE) and initial burst drug release are systemically evaluated. A high doxorubicin EE and low initial burst drug release are realized with the dense silica-coated Au nanobottles having an opening size of 44 nm. In addition, chemo-photothermal combined therapy has been demonstrated with the doxorubicin-loaded Au nanobottles. Our results will be helpful for the design of Au nanobottles with different sizes and plasmonic properties as well as provide ample opportunities for exploring various plasmon-enabled applications of Au nanobottles.
The ubiquity of private vehicles with positioning services leaves a great deal of mobility data in the physical world, which supports abundant mobile applications in the Internet of Vehicles. Despite ...numerous desirable features that the data provide, the social relationship privacy inherent in private vehicle mobility data has gone with little notice. The relevant work that concentrates on social relation privacy either only considers the temporal and spatial features, attempts to obtain the explicit venue cooccurrence frequency statistics of mobility data, or characterizes the semantics of locations by directly matching the POI information to the location. In this paper, we propose a SEmantic-aware and Memory-Efficient scheme (SEME) for inferring social relationships from private vehicle mobility data. We determine the probability distribution of the visit purpose for each stopover location in vehicle trajectories by a probabilistic generative model with a latent variable of semantic feature vectors that embeds the semantic information, time context, and correlations. Labeling the trajectories with visit purposes, we derive a mobility feature vector for each driver with a feature learning model. Based on the mobility feature vectors, the similarity score that indicates the social connection strength can be pairwise-computed with an effective measurement, i.e., the cosine similarity. Additionally, for both scalability and computational efficiency, we convert the large-scale similarity calculation to an extended version of a maximum inner-product search problem and derive the closed-form solution of binary codes which is used to approximately solve the problem. To evaluate the performance of SEME, we conduct experiments with respect to effectiveness, efficiency, and robustness based on real-world private vehicle trajectories. The evaluation results demonstrate that our scheme improves the inference accuracy and reduces the time cost of similarity calculation.
The development of efficient bifunctional organocatalysts for the catalytic conversion of CO2 under mild conditions remains particularly challenging. Inspired by the synergistic mechanism of ...intramolecular Lewis acid‐base active sites, we report a series of bifunctional cross‐linked epoxy resin organocatalysts containing multiple active sites for the cycloaddition reaction of dilute CO2 with epoxides. These catalysts exhibit high reactivity and product selectivity (10 examples, >99 %) for the cycloaddition reactions of a variety of epoxides and CO2, and surprisingly, epichlorohydrin (ECH), can be converted under ambient temperature and pressure (25 °C, 1.0 bar) without co‐catalysts. 1H NMR, 13C NMR, 19F NMR and in situ IR studies suggest that the simultaneous and efficient activation of CO2 and epoxides is responsible for the improved catalytic activity. Upon an insightful investigation of the catalytic mechanism, this protocol will contribute to the development of efficient and environmentally friendly metal‐free catalysts.
Using crossed‐linked epoxy resin catalysts, cyclic carbonates were synthesized via simultaneous activation of carbon dioxide and epoxides. A detailed description of the mechanism for the simultaneous activation of carbon dioxide and epoxides is proposed and certified on the basis of the intensive investigations on intermolecular interactions and key intermediates.
This paper proposes novel dual‐mode substrate integrated waveguide (SIW) filter and diplexer with circular cavities, in which a pair of symmetrical metallic via perturbations is placed at different ...positions in a single cavity combining different angle of feeding lines to obtain flexible transmission response. So that multiple transmission zeros can be obtained on one or both sides of the passband. Compared with traditional structure, the proposed dual‐mode circular cavity filter and diplexer not only reduce the number of resonators and the volume of filters, but also realize the transmission in higher frequency with the existing machining precision. For verify the structure mentioned above, the dual‐mode SIW filter and diplexer are designed, fabricated, and measured in a standard printed circuit board (PCB) process at Q‐band. The filter is measured at a central frequency(CF) of 44.86 GHz with a 3 dB fractional bandwidth (FBW) of 10.2%, insertion loss (IL) is 1.9 dB, meanwhile the measured diplexer insertion losses (IL) are 2.1 and 2.4 dB in the lower and upper passbands centered at 38.3 and 44.8 GHz with the fractional bandwidths of 10.7% and 10.1%. The isolation is lower than ‐40 dB. The measured results show good agreements with the simulated ones.
NiCo2S4 flaky arrays on nickel foam were prepared hydrothermally by means of an anion-exchange method, with NiCo2O4 nanorod arrays as precursors. The as-prepared flaky structure NiCo2S4 which ...combines the advantages of both one dimensional and two dimensional materials as a binder-free supercapacitor electrode shows much enhanced electrochemical performance, with a high specific capacitance (2044Fg−1 at 1Ag−1) and good cycling stability (capacity retention of 77% after 2000 cycles), suggesting its promising application for electrochemical capacitors.
•High-performance NiCo2S4 flaky structure was grown directly on Ni foam substrate.•NiCo2S4 flaky structure exhibits a high specific capacitance of 2044Fg−1 at current density of 1Ag−1.•Unique flaky structure harnesses the merits of both one dimensional and two dimensional structure.
NiCo2S4 flaky structured arrays on nickel foam were prepared hydrothermally by means of an anion-exchange method, with NiCo2O4 nanorod arrays as precursors, and were directly applied as a binder-free supercapacitor electrode. Such a 3D structured electrode combines the advantages of both one dimensional and two dimensional materials, and can effectively improve the electrochemical performance. As a result, the as-prepared NiCo2S4 flaky structure electrode shows much enhanced electrochemical performance, with a high specific capacitance (2044Fg−1 at 1Ag−1) and good cycling stability (capacity retention of 77% after 2000 cycles), suggesting its promising application for electrochemical capacitors.
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