360 research outputs found
Mechanism of Stochastic Resonance in a Quorum Sensing Network Regulated by Small RNAs
Bacterial quorum sensing (QS) is an important process of cell communication and more and more attention is paid to it. Moreover, the noises are ubiquitous in nature and often play positive role. In this paper, we investigate how the noise enhances the QS though the stochastic resonance (SR) and explain the mechanism of SR in this quorum sensing network. In addition, we also discuss the interaction between the small RNA and the other genes in this network and discover the biological importance
Federated Primal Dual Fixed Point Algorithm
Federated learning (FL) is a distributed learning paradigm that allows
several clients to learn a global model without sharing their private data. In
this paper, we generalize a primal dual fixed point (PDFP) \cite{PDFP} method
to federated learning setting and propose an algorithm called Federated PDFP
(FPDFP) for solving composite optimization problems. In addition, a
quantization scheme is applied to reduce the communication overhead during the
learning process. An convergence rate (where is the
communication round) of the proposed FPDFP is provided. Numerical experiments,
including graph-guided logistic regression, 3D Computed Tomography (CT)
reconstruction are considered to evaluate the proposed algorithm.Comment: 29 pages and 8 figure
外用喜疗妥致严重皮肤反应1例
Objective: To explore the clinical characteristics, diagnosis and prognosis of local severe cutaneous reactions as result of the treatment with Hirudoid. Methods: One case of severe cutaneous reactions as result of the treatment with Hirudoid was reported and the relevant literatures were reviewed. Results: The site of puncture of left arm occurred non-leakage phlebitis with local pain after chemotherapy. The patient was applied the Hirudoid to the affected areas 2 times daily. After 2 days, local skin felt a kind of burning pain and it seems to be getting worse. The skin lesions began as pruritic red macules or papules. It became swelled and bleeding after scratching. We considered that the cutaneous reactions were an allergic response to Hirudoid. We discontinued the Hirudoid and desensitization treatment was used on cure, but it failed to respond to the medical treatment. A hot compress with 50% magnesium sulphate solution can reduce swelling and alleviate pain. Scales of skin peel off and weaved the new skin after 10 days. Conclusion: The case of local severe cutaneous reactions as result of the treatment with Hirudoid is very rare. A hot compress with 50% magnesium sulphate solution can help to relieve the discomfort. 目的 探讨外用喜疗妥致严重皮肤反应的临床特征及治疗和预后。方法 报道1例外用喜疗妥致严重皮肤反应患者的临床资料并结合相关文献进行分析。结果 患者,女,60岁,化疗后穿刺部位左侧手臂出现非渗漏性静脉炎,局部疼痛。给予喜疗妥每日2次外涂。2天后,患者突感涂抹局部烧灼样疼痛,并可见大片红色斑丘疹奇痒难忍,抓挠后充血肿胀。考虑喜疗妥过敏所致,立即停用喜疗妥,并应用脱敏治疗,效果不佳,局部颜色由红色渐变为暗紫色且肿痛剧烈,给予50%硫酸镁溶液湿热敷。3天后患者症状逐渐减轻,肿胀消退,10天后患处皮肤全部脱落并被新的完好皮肤覆盖。结论 外用喜疗妥致严重皮肤反应非常罕见,50%硫酸镁溶液热敷患处皮肤,可以缓解肿痛,消除症状
Research on the X-Ray Polarization Deconstruction Method Based on Hexagonal Convolutional Neural Network
Track reconstruction algorithms are critical for polarization measurements.
In addition to traditional moment-based track reconstruction approaches,
convolutional neural networks (CNN) are a promising alternative. However,
hexagonal grid track images in gas pixel detectors (GPD) for better anisotropy
do not match the classical rectangle-based CNN, and converting the track images
from hexagonal to square results in loss of information. We developed a new
hexagonal CNN algorithm for track reconstruction and polarization estimation in
X-ray polarimeters, which was used to extract emission angles and absorption
points from photoelectron track images and predict the uncertainty of the
predicted emission angles. The simulated data of PolarLight test were used to
train and test the hexagonal CNN models. For individual energies, the hexagonal
CNN algorithm produced 15-30% improvements in modulation factor compared to
moment analysis method for 100% polarized data, and its performance was
comparable to rectangle-based CNN algorithm newly developed by IXPE team, but
at a much less computational cost.Comment: 21 pages, 12 figures, submitted to NS
Development of marker-free transgenic Jatropha plants with increased levels of seed oleic acid
<p>Abstract</p> <p>Background</p> <p><it>Jatropha curcas </it>is recognized as a new energy crop due to the presence of the high amount of oil in its seeds that can be converted into biodiesel. The quality and performance of the biodiesel depends on the chemical composition of the fatty acids present in the oil. The fatty acids profile of the oil has a direct impact on ignition quality, heat of combustion and oxidative stability. An ideal biodiesel composition should have more monounsaturated fatty acids and less polyunsaturated acids. Jatropha seed oil contains 30% to 50% polyunsaturated fatty acids (mainly linoleic acid) which negatively impacts the oxidative stability and causes high rate of nitrogen oxides emission.</p> <p>Results</p> <p>The enzyme 1-acyl-2-oleoyl-sn-glycero-3-phosphocholine delta 12-desaturase (FAD2) is the key enzyme responsible for the production of linoleic acid in plants. We identified three putative <it>delta </it><it>12 </it><it>fatty acid desaturase </it>genes in <it>Jatropha </it>(<it>JcFAD2s</it>) through genome-wide analysis and downregulated the expression of one of these genes, <it>JcFAD2-1</it>, in a seed-specific manner by RNA interference technology. The resulting <it>JcFAD2-1 </it>RNA interference transgenic plants showed a dramatic increase of oleic acid (> 78%) and a corresponding reduction in polyunsaturated fatty acids (< 3%) in its seed oil. The control <it>Jatropha </it>had around 37% oleic acid and 41% polyunsaturated fatty acids. This indicates that FAD2-1 is the major enzyme responsible for converting oleic acid to linoleic acid in <it>Jatropha</it>. Due to the changes in the fatty acids profile, the oil of the <it>JcFAD2-1 </it>RNA interference seed was estimated to yield a cetane number as high as 60.2, which is similar to the required cetane number for conventional premium diesel fuels (60) in Europe. The presence of high seed oleic acid did not have a negative impact on other <it>Jatropha </it>agronomic traits based on our preliminary data of the original plants under greenhouse conditions. Further, we developed a marker-free system to generate the transgenic <it>Jatropha </it>that will help reduce public concerns for environmental issues surrounding genetically modified plants.</p> <p>Conclusion</p> <p>In this study we produced seed-specific <it>JcFAD2-1 </it>RNA interference transgenic <it>Jatropha </it>without a selectable marker. We successfully increased the proportion of oleic acid versus linoleic in <it>Jatropha </it>through genetic engineering, enhancing the quality of its oil.</p
Fucoidan Inhibits the Growth of Hepatocellular Carcinoma Independent of Angiogenesis
Some sulphated polysaccharides can bind bFGF but are unable to present bFGF to its high-affinity receptors. Fucoidan, a sulphated polysaccharide purified from brown algae, which has been used as an anticancer drug in traditional Chinese medicine for hundreds of years, exhibits a variety of anticancer effects, including the induction of the apoptosis and autophagy of cancer cells, the inhibition of the growth of cancer cells, the induction of angiogenesis, and the improvement of antitumour immunity. Our research shows that fucoidan dose not inhibit the expressions of VEGF, bFGF, IL-8, and heparanase in HCC cells and/or tumour tissues. Moreover, fucoidan exhibited low affinity for bFGF and could not block the binding of bFGF to heparan sulphated. Although fucoidan had no effect on angiogenesis and apoptosis in vivo, this drug significantly inhibited the tumour growth and the expression of PCNA. These results suggest that fucoidan exhibits an anticancer effect in vivo at least partly through inhibition of the proliferation of HCC cells, although it is unable to suppress the angiogenesis induced by HCC
3D-IDS: Doubly Disentangled Dynamic Intrusion Detection
Network-based intrusion detection system (NIDS) monitors network traffic for
malicious activities, forming the frontline defense against increasing attacks
over information infrastructures. Although promising, our quantitative analysis
shows that existing methods perform inconsistently in declaring various unknown
attacks (e.g., 9% and 35% F1 respectively for two distinct unknown threats for
an SVM-based method) or detecting diverse known attacks (e.g., 31% F1 for the
Backdoor and 93% F1 for DDoS by a GCN-based state-of-the-art method), and
reveals that the underlying cause is entangled distributions of flow features.
This motivates us to propose 3D-IDS, a novel method that aims to tackle the
above issues through two-step feature disentanglements and a dynamic graph
diffusion scheme. Specifically, we first disentangle traffic features by a
non-parameterized optimization based on mutual information, automatically
differentiating tens and hundreds of complex features of various attacks. Such
differentiated features will be fed into a memory model to generate
representations, which are further disentangled to highlight the
attack-specific features. Finally, we use a novel graph diffusion method that
dynamically fuses the network topology for spatial-temporal aggregation in
evolving data streams. By doing so, we can effectively identify various attacks
in encrypted traffics, including unknown threats and known ones that are not
easily detected. Experiments show the superiority of our 3D-IDS. We also
demonstrate that our two-step feature disentanglements benefit the
explainability of NIDS.Comment: Accepted and appeared in the proceedings of the KDD 2023 Research
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