2,247 research outputs found
Transcriptional profiling of CcpE-regulated genes in Staphylococcus aureus
AbstractThe transcriptional regulator CcpE is an important citrate-sensing regulator that modulates metabolic state, virulence factor expression, and bacterial virulence of Staphylococcus aureus (Ding et al., 2014 [1]). In this article, we report detailed methods for genome-wide transcriptional profiling of CcpE-regulated genes generated for the research article “Metabolic sensor governing bacterial virulence in Staphylococcus aureus” (Ding et al., 2014 [1]). All transcriptional profiling data was deposited to Gene Expression Omnibus (GEO) database under accession number GSE57260
Inherent Mach-Zehnder interference with "which-way" detection for single particle scattering in one dimension
We study the coherent transport of single photon in a one-dimensional
coupled-resonator-array, "non-locally" coupled to a two-level system. Since its
inherent structure is a Mach-Zehnder interferometer, we explain the destructive
interference phenomenon of the transmission spectrums according to the effect
of which-way detection. The quantum realization of the present model is a
nano-electromechanical resonator arrays with two nearest resonators coupled to
a single spin via their attached magnetic tips. Its classical simulation is a
waveguide of coupled defected cavity array with double couplings to a side
defected cavity.Comment: 5 papges, 4 figure
An architecture of internet based data processing based on multicast and anycast protocols
Most of the current web-based application systems suffer from poor performance and costly heterogeneous accessing. Distributed or replicated strategies can alleviate the problem in some degree, but there are still some problems of the distributed or replicated model, such as data synchronization, load balance, and so on. In this paper, we propose a novel architecture for Internet-based data processing system based on multicast and anycast protocols. The proposed architecture breaks the functionalities of existing data processing system, in particular, the database functionality, into several agents. These agents communicate with each other using multicast and anycast mechanisms. We show that the proposed architecture provides better scalability, robustness, automatic load balance, and performance than the current distributed architecture of Internet-based dataprocessing.<br /
Prognostic Values of Filamin-A Status for Topoisomerase II Poison Chemotherapy
Filamin-A, also called Actin Binding Protein-280, is not only an essential component of the cytoskeleton networks, but also serves as the scaffold in various signaling networks. It has been shown that filamin-A facilitates DNA repair and filamin-A proficient cells are more resistant to ionizing radiation, bleomycin, and cisplatin. In this study, we assessed the role of filamin-A in modulating cancer cell sensitivity to Topo II poisons, including etoposide and doxorubicin. Intriguingly, we found that cells with filamin-A expression are more sensitive to Topo II poisons than those with defective filamin-A, and filamin-A proficient xenograft melanomas have better response to etoposide treatment than the filamin-A deficient tumors. This is associated with more potent induction of DNA double strand breaks (DSBs) by Topo II poisons in filamin-A proficient cells than the deficient cells. Although the expression of filamin-A enables cells a slightly stronger capability to repair DSB, the net outcome is that filamin-A proficient cells bear more DSBs due to the significantly enhanced DSB induction by Topo II poisons in these cells. We further found that filamin-A proficient cells have increased drug influx and decreased drug efflux, suggesting that filamin-A modulates the intra-cellular drug kinetics of Topo II poisons to facilitate the generation of DSB after Topo II poison exposure. These data suggest a novel function of filamin-A in regulating the pharmacokinetics of Topo II poisons, and that the status of filamin-A may be used as a prognostic marker for Topo II poisons based cancer treatments
Determining the local dark matter density with LAMOST data
Measurement of the local dark matter density plays an important role in both
Galactic dynamics and dark matter direct detection experiments. However, the
estimated values from previous works are far from agreeing with each other. In
this work, we provide a well-defined observed sample with 1427 G \& K type
main-sequence stars from the LAMOST spectroscopic survey, taking into account
selection effects, volume completeness, and the stellar populations. We apply a
vertical Jeans equation method containing a single exponential stellar disk, a
razor thin gas disk, and a constant dark matter density distribution to the
sample, and obtain a total surface mass density of $\rm {78.7 ^{+3.9}_{-4.7}\
M_{\odot}\ pc^{-2}}0.0159^{+0.0047}_{-0.0057}\,\rm M_{\odot}\,\rm pc^{-3}$. We find that the
sampling density (i.e. number of stars per unit volume) of the spectroscopic
data contributes to about two-thirds of the uncertainty in the estimated
values. We discuss the effect of the tilt term in the Jeans equation and find
it has little impact on our measurement. Other issues, such as a
non-equilibrium component due to perturbations and contamination by the thick
disk population, are also discussed.Comment: 11 pages, 10 figure
Crosstalk of nervous and immune systems in pancreatic cancer
Pancreatic cancer is a highly malignant tumor known for its extremely low survival rate. The combination of genetic disorders within pancreatic cells and the tumor microenvironment contributes to the emergence and progression of this devastating disease. Extensive research has shed light on the nature of the microenvironmental cells surrounding the pancreatic cancer, including peripheral nerves and immune cells. Peripheral nerves release neuropeptides that directly target pancreatic cancer cells in a paracrine manner, while immune cells play a crucial role in eliminating cancer cells that have not evaded the immune response. Recent studies have revealed the intricate interplay between the nervous and immune systems in homeostatic condition as well as in cancer development. In this review, we aim to summarize the function of nerves in pancreatic cancer, emphasizing the significance to investigate the neural-immune crosstalk during the advancement of this malignant cancer
Zero- and Few-Shot Event Detection via Prompt-Based Meta Learning
With emerging online topics as a source for numerous new events, detecting
unseen / rare event types presents an elusive challenge for existing event
detection methods, where only limited data access is provided for training. To
address the data scarcity problem in event detection, we propose MetaEvent, a
meta learning-based framework for zero- and few-shot event detection.
Specifically, we sample training tasks from existing event types and perform
meta training to search for optimal parameters that quickly adapt to unseen
tasks. In our framework, we propose to use the cloze-based prompt and a
trigger-aware soft verbalizer to efficiently project output to unseen event
types. Moreover, we design a contrastive meta objective based on maximum mean
discrepancy (MMD) to learn class-separating features. As such, the proposed
MetaEvent can perform zero-shot event detection by mapping features to event
types without any prior knowledge. In our experiments, we demonstrate the
effectiveness of MetaEvent in both zero-shot and few-shot scenarios, where the
proposed method achieves state-of-the-art performance in extensive experiments
on benchmark datasets FewEvent and MAVEN.Comment: Accepted to ACL 202
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