The G-protein-coupled estrogen receptor agonist G-1 suppresses proliferation of ovarian cancer cells by blocking tubulin polymerization.

The G-protein-coupled estrogen receptor 1 (GPER) has recently been reported to mediate the non-genomic action of estrogen in different types of cells and tissues. G-1 (1-[4-(6-bromobenzo[1,3] dioxol-5yl)-3a,4,5,9b-tetrahydro-3H-cyclopenta[c]quinolin-8-yl]-ethanone) was developed as a potent and selective agonist for GPER. G-1 has been shown to induce the expression of genes and activate pathways that facilitate cancer cell proliferation by activating GPER. Here we demonstrate that G-1 has an anticancer potential with a mechanism similar to vinca alkaloids, the commonly used chemotherapy drugs. We found that G-1 blocks tubulin polymerization and thereby interrupts microtubule assembly in ovarian cancer cells leading to the arrest of cell cycle in the prophase of mitosis and the suppression of ovarian cancer cell proliferation. G-1 treatment also induces apoptosis of ovarian cancer cells. The ability of G-1 to target microtubules to suppress ovarian cancer cell proliferation makes it a promising candidate drug for treatment of ovarian cancer

Detection of Anomalous Traffic Patterns and Insight Analysis from Bus Trajectory Data

© 2019, Springer Nature Switzerland AG. Detection of anomalous patterns from traffic data is closely related to analysis of traffic accidents, fault detection, flow management, and new infrastructure planning. Existing methods on traffic anomaly detection are modelled on taxi trajectory data and have shortcoming that the data may lose much information about actual road traffic situation, as taxi drivers can select optimal route for themselves to avoid traffic anomalies. We employ bus trajectory data as it reflects real traffic conditions on the road to detect city-wide anomalous traffic patterns and to provide broader range of insights into these anomalies. Taking these considerations, we first propose a feature visualization method by mapping extracted 3-dimensional hidden features to red-green-blue (RGB) color space with a deep sparse autoencoder (DSAE). A color trajectory (CT) is produced by encoding a trajectory with RGB colors. Then, a novel algorithm is devised to detect spatio-temporal outliers with spatial and temporal properties extracted from the CT. We also integrate the CT with the geographic information system (GIS) map to obtain insights for understanding the traffic anomaly locations, and more importantly the road influence affected by the corresponding anomalies. Our proposed method was tested on three real-world bus trajectory data sets to demonstrate the excellent performance of high detection rates and low false alarm rates

Planarian Cholinesterase: Molecular And Functional Characterization Of An Evolutionarily Ancient Enzyme To Study Organophosphorus Pesticide Toxicity

The asexual freshwater planarian Dugesia japonica has emerged as a medium-throughput alternative animal model for neurotoxicology. We have previously shown that D. japonica are sensitive to organophosphorus pesticides (OPs) and characterized the in vitro inhibition profile of planarian cholinesterase (DjChE) activity using irreversible and reversible inhibitors. We found that DjChE has intermediate features of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Here, we identify two candidate genes (Djche1 and Djche2) responsible for DjChE activity. Sequence alignment and structural homology modeling with representative vertebrate AChE and BChE sequences confirmed our structural predictions, and show that both DjChE enzymes have intermediate sized catalytic gorges and disrupted peripheral binding sites. Djche1 and Djche2 were both expressed in the planarian nervous system, as anticipated from previous activity staining, but with distinct expression profiles. To dissect how DjChE inhibition affects planarian behavior, we acutely inhibited DjChE activity by exposing animals to either an OP (diazinon) or carbamate (physostigmine) at 1 µM for 4 days. Both inhibitors delayed the reaction of planarians to heat stress. Simultaneous knockdown of both Djche genes by RNAi similarly resulted in a delayed heat stress response. Furthermore, chemical inhibition of DjChE activity increased the worms’ ability to adhere to a substrate. However, increased substrate adhesion was not observed in Djche1/Djche2 (RNAi) animals or in inhibitor-treated day 11 regenerates, suggesting this phenotype may be modulated by other mechanisms besides ChE inhibition. Together, our study characterizes DjChE expression and function, providing the basis for future studies in this system to dissect alternative mechanisms of OP toxicity

Charmless Three-Body Baryonic B Decays

Motivated by recent data on B-> p pbar K decay, we study various charmless three-body baryonic B decay modes, including Lambda pbar pi, Sigma0 pbar pi, p pbar pi, p pbar Kbar0, in a factorization approach. These modes have rates of order 10^{-6}. There are two mechanisms for the baryon pair production, current-produced and transition. The behavior of decay spectra from these baryon production mechanisms can be understood by using QCD counting rules. Predictions on rates and decay spectra can be checked in the near future.Comment: 26 pages, 9 figures; version to appear in Phys. Rev.

Spontaneous CP Violating Phase as the Phase in PMNS Matrix

We study the possibility of identifying the CP violating phases in the PMNS mixing matrix in the lepton sector and also that in the CKM mixing matrix in the quark sector with the phase responsible for the spontaneous CP violation in the Higgs potential, and some implications. Since the phase in the CKM mixing matrix is determined by experimental data, the phase in the lepton sector is therefore also fixed. The mass matrix for neutrinos is constrained leading to constraints on the Jarlskog CP violating parameter $J$, and the effective mass $$ for neutrinoless double beta decay. The Yukawa couplings are also constrained. Different ways of identifying the phases have different predictions for $\mu \to e e\bar e$ and $\tau \to l_1 l_2 \bar l_3$. Future experimental data can be used to distinguish different models.Comment: 16 pages, 3 figure

Constraints on Astro-unparticle Physics from SN 1987A

SN 1987A observations have been used to place constraints on the interactions between standard model particles and unparticles. In this study we calculate the energy loss from the supernovae core through scalar, pseudo scalar, vector, pseudo vector unparticle emission from nuclear bremsstrahlung for degenerate nuclear matter interacting through one pion exchange. In order to examine the constraints on $d_{\cal U}=1$ we considered the emission of scalar, pseudo scalar, vector, pseudo vector and tensor through the pair annihilation process $e^+e^-\to {\cal U} \gamma$. In addition we have re-examined other pair annihilation processes. The most stringent bounds on the dimensionless coupling constants for $d_{\cal U} =1$ and $\Lambda_{\cal U}= m_Z$ are obtained from nuclear bremsstrahlung process for the pseudo scalar and pseudo-vector couplings $\bigl|\lambda^{\cal P}_{0,1}\bigr|\leq 4\times 10^{-11}$ and for tensor interaction, the best limit on dimensionless coupling is obtained from $e^+ e^-\to {\cal U} \gamma$ and we get $\bigl|\lambda^{\cal T}\bigr| \leq 6\times 10^{-6}$.Comment: 12 pages, 2 postscript figure

Vehicle Detection Using Alex Net and Faster R-CNN Deep Learning Models: A Comparative Study

This paper has been presented at : 5th International Visual Informatics Conference (IVIC 2017)This paper presents a comparative study of two deep learning models used here for vehicle detection. Alex Net and Faster R-CNN are compared with the analysis of an urban video sequence. Several tests were carried to evaluate the quality of detections, failure rates and times employed to complete the detection task. The results allow to obtain important conclusions regarding the architectures and strategies used for implementing such network for the task of video detection, encouraging future research in this topic.S.A. Velastin is grateful to funding received from the Universidad Carlos III de Madrid, the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 600371, el Ministerio de Economía y Competitividad (COFUND2013-51509) and Banco Santander. The authors wish to thank Dr. Fei Yin for the code for metrics employed for evaluations. Finally, we gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPUs used for this research. The data and code used for this work is available upon request from the authors

A side-by-side comparison of Daya Bay antineutrino detectors

The Daya Bay Reactor Neutrino Experiment is designed to determine precisely the neutrino mixing angle $\theta_{13}$ with a sensitivity better than 0.01 in the parameter sin$^22\theta_{13}$ at the 90% confidence level. To achieve this goal, the collaboration will build eight functionally identical antineutrino detectors. The first two detectors have been constructed, installed and commissioned in Experimental Hall 1, with steady data-taking beginning September 23, 2011. A comparison of the data collected over the subsequent three months indicates that the detectors are functionally identical, and that detector-related systematic uncertainties exceed requirements.Comment: 24 pages, 36 figure

Observation of electron-antineutrino disappearance at Daya Bay

The Daya Bay Reactor Neutrino Experiment has measured a non-zero value for the neutrino mixing angle $\theta_{13}$ with a significance of 5.2 standard deviations. Antineutrinos from six 2.9 GW$_{\rm th}$ reactors were detected in six antineutrino detectors deployed in two near (flux-weighted baseline 470 m and 576 m) and one far (1648 m) underground experimental halls. With a 43,000 ton-GW_{\rm th}-day livetime exposure in 55 days, 10416 (80376) electron antineutrino candidates were detected at the far hall (near halls). The ratio of the observed to expected number of antineutrinos at the far hall is $R=0.940\pm 0.011({\rm stat}) \pm 0.004({\rm syst})$. A rate-only analysis finds $\sin^22\theta_{13}=0.092\pm 0.016({\rm stat})\pm0.005({\rm syst})$ in a three-neutrino framework.Comment: 5 figures. Version to appear in Phys. Rev. Let