Syphilis among middle-aged female sex workers in China: a three-site cross-sectional study.

ObjectivesThis study addresses the lack of empirical studies about the epidemic of syphilis among middle-aged female sex workers (FSWs). The objectives of this study were to investigate prevalence of syphilis, and its potential risk factors among middle-aged FSWs in China.DesignA cross-sectional study with respondent-driven sampling (RDS).SettingA multisite study conducted at three Chinese cites (Nanning, Hefei, and Qingdao) with different levels of sexually transmitted diseases in 2014.Participants1245 middle-aged female sex workers who were over 35 years old (about 400 per study site).Main outcome measuresUnprotected commercial sex, and syphilis and HIV infection were biologically tested and measured.ResultsThe RDS-adjusted prevalence of active syphilis was 17.3% in Hefei, 9.9% in Qingdao, and 5.4% in Nanning. The RDS-adjusted prevalence of prevalent syphilis was between 6.8% and 33.6% in the three cities. The proportion of unprotected sex in the past 48 h verified by the prostate-specific antigen test (PSA) was between 27.8% and 42.4%. Multiple log-binomial regression analyses indicate that middle-aged FSWs who had 5 or more clients in the past week prior to interviews and engaged in unprotected sex were more likely to be active syphilitic cases. Middle-aged FSWs who had rural residency were less likely to be active syphilitic cases.ConclusionsIn contrast with previous studies that reported low prevalence of syphilis and high prevalence of protected sex among FSWs in China, both the prevalence of syphilis and unprotected sex were high among middle-aged FSWs. Evidence-based intervention programmes should be developed and evaluated among this vulnerable population in China and other countries with similar settings

The generalized inverses of tensors via the C-Product

This paper studies the issues about the generalized inverses of tensors under the C-Product. The aim of this paper is threefold. Firstly, this paper present the definition of the Moore-Penrose inverse, Drazin inverse of tensors under the C-Product. Moreover, the inverse along a tensor is also introduced. Secondly, this paper gives some other expressions of the generalized inverses of tensors by using several decomposition forms of tensors. Finally, the algorithms for the Moore-Penrose inverse, Drazin inverse of tensors and the inverse along a tensor are established

Identification of a novel regulatory mechanism involved in inhibition of transcription of suvivin mRNA in breast cancer cells via p21cip–mediated regulation

Purpose: To evaluate the effect of p21Cip1 on survivin transcription levels in breast carcinoma, and to investigate the potential mechanisms.Methods: Epirubicin, a p21Cip1 activator, was used to treat MCF7 cells. Under the action of normal biological functions of p53, pEGFP-C2-p21 was transfected into MCF7 cells by lipofectamine and positive clones were screened out with G418. The expression levels of p21cip1, p53 and survivin mRNA were quantitated by real-time fluorescent polymerase chain reaction (RQ-PCR). MTT assay was utilized to measure cellular viability and proliferation after transfection. Flow cytometry was employed to determine the cell cycle. Hoechst 33342 staining was carried out to assess cell apoptosis. Lastly, several transcription factor sites located at the promoter region of survivin gene, such as, sp1 site, E2F site and p300/CBP, were measured by p21 overexpression using RT-PCR.Results: Following epirubicin treatment, within 24 h, the expression levels of endogenous p21cip1 and p53 were up-regulated, whereas that of survivin was down-regulated. After transfection treatment, p21 inhibited the proliferation of MCF7 cells on days 3 and 4, and MCF7 cells overexpressed p21 mRNA, whereas the level of survivin mRNA in MCF7-p21 groups was markedly down-regulated relative to control group, but overexpression of p21 was not sufficient to cause changes in p53 gene expression. The overexpressed p21 resulted in G1/G0 phase arrest based on cell cycle analysis, but apoptosis was not induced. In addition, co-transcription factors E2F-1, sp1 and p300/CBP mRNA levels decreased significantly compared with normal p21 expression groups.Conclusion: P21cip1 may down-regulate the expression of survivin gene partially by inhibiting the expression level of HAT.Keywords: Cyclin-dependent kinase inhibitor 1, Phosphoprotein p53, Survivin, Breast carcinoma, G1/G0 phase arrest, Epirubicin, Lipofectamin

The generalized inverses of the quaternion tensor via the T-product

In this article, specific definitions of the Moore-Penrose inverse, Drazin inverse of the quaternion tensor and the inverse along two quaternion tensors are introduced under the T-product. Some characterizations, representations and properties of the defined inverses are investigated. Moreover, algorithms are established for computing the Moore-Penrose inverse, Drazin inverse of the quaternion tensor and the inverse along two quaternion tensors, respectively

SemanticCAP: Chromatin Accessibility Prediction Enhanced by Features Learning from a Language Model

A large number of inorganic and organic compounds are able to bind DNA and form complexes, among which drug-related molecules are important. Chromatin accessibility changes not only directly affects drug-DNA interactions, but also promote or inhibit the expression of critical genes associated with drug resistance by affecting the DNA binding capacity of TFs and transcriptional regulators. However, Biological experimental techniques for measuring it are expensive and time consuming. In recent years, several kinds of computational methods have been proposed to identify accessible regions of the genome. Existing computational models mostly ignore the contextual information of bases in gene sequences. To address these issues, we proposed a new solution named SemanticCAP. It introduces a gene language model which models the context of gene sequences, thus being able to provide an effective representation of a certain site in gene sequences. Basically, we merge the features provided by the gene language model into our chromatin accessibility model. During the process, we designed some methods to make feature fusion smoother. Compared with other systems under public benchmarks, our model proved to have better performance

Multi-Scale Simulation of Complex Systems: A Perspective of Integrating Knowledge and Data

Complex system simulation has been playing an irreplaceable role in understanding, predicting, and controlling diverse complex systems. In the past few decades, the multi-scale simulation technique has drawn increasing attention for its remarkable ability to overcome the challenges of complex system simulation with unknown mechanisms and expensive computational costs. In this survey, we will systematically review the literature on multi-scale simulation of complex systems from the perspective of knowledge and data. Firstly, we will present background knowledge about simulating complex system simulation and the scales in complex systems. Then, we divide the main objectives of multi-scale modeling and simulation into five categories by considering scenarios with clear scale and scenarios with unclear scale, respectively. After summarizing the general methods for multi-scale simulation based on the clues of knowledge and data, we introduce the adopted methods to achieve different objectives. Finally, we introduce the applications of multi-scale simulation in typical matter systems and social systems

Identification of DNA-protein binding residues through integration of Transformer encoder and Bi-directional Long Short-Term Memory

DNA-protein binding is crucial for the normal development and function of organisms. The significance of accurately identifying DNA-protein binding sites lies in its role in disease prevention and the development of innovative approaches to disease treatment. In the present study, we introduce a precise and robust identifier for DNA-protein binding residues. In the context of protein representation, we combine the evolutionary information of the protein, represented by its position-specific scoring matrix, with the spatial information of the protein's secondary structure, enriching the overall informational content. This approach initially employs a combination of Bi-directional Long Short-Term Memory and Transformer encoder to jointly extract the interdependencies among residues within the protein sequence. Subsequently, convolutional operations are applied to the resulting feature matrix to capture local features of the residues. Experimental results on the benchmark dataset demonstrate that our method exhibits a higher level of competitiveness when compared to contemporary classifiers. Specifically, our method achieved an MCC of 0.349, SP of 96.50%, SN of 44.03% and ACC of 94.59% on the PDNA-41 dataset

Time of Emergence of Surface Ocean Carbon Dioxide Trends in the North American Coastal Margins in Support of Ocean Acidification Observing System Design

Time of Emergence (ToE) is the time when a signal emerges from the noise of natural variability. Commonly used in climate science for the detection of anthropogenic forcing, this concept has recently been applied to geochemical variables, to assess the emerging times of anthropogenic ocean acidification (OA), mostly in the open ocean using global climate and Earth System Models. Yet studies of OA variables are scarce within costal margins, due to limited multidecadal time-series observations of carbon parameters. ToE provides important information for decision making regarding the strategic configuration of observing assets, to ensure they are optimally positioned either for signal detection and/or process elicitation and to identify the most suitable variables in discerning OA-related changes. Herein, we present a short overview of ToE estimates on an OA variable, CO2 fugacity f(CO2,sw), in the North American ocean margins, using coastal data from the Surface Ocean CO2 Atlas (SOCAT) V5. ToE suggests an average theoretical timeframe for an OA signal to emerge, of 23(±13) years, but with considerable spatial variability. Most coastal areas are experiencing additional secular and/or multi-decadal forcing(s) that modifies the OA signal, and such forcing may not be sufficiently resolved by current observations. We provide recommendations, which will help scientists and decision makers design and implement OA monitoring systems in the next decade, to address the objectives of OceanObs19 (http://www.oceanobs19.net) in support of the United Nations Decade of Ocean Science for Sustainable Development (2021–2030) (https://en.unesco.org/ocean-decade) and the Sustainable Development Goal (SDG) 14.3 (https://sustainabledevelopment.un.org/sdg14) target to “Minimize and address the impacts of OA.

Research on key architecture and model of coal mine water hazard intelligent early warning system

In order to ensure the safe production of mine threatened by water hazard, speed up the intelligent process of mine water hazard prediction and early warning technology, and improve the effect of mine water hazard prediction and early warning, based on the research status of water hazard mechanism and monitoring and early warning at home and abroad, four types of key technical issues for constructing water hazard monitoring and intelligent early warning systems are analyzed. The complexity of early warning requirements and data access standards, the classification and spatio-temporal matching of multi-source heterogeneous big data information, the intelligent processing and analysis of water hazard big data information, and the timeliness of early warning and intelligent decision information release are discussed in detail. From the perspective of early warning system resource integration and data drive, water hazard warning resources are divided into information collection resources and computing resources, water hazard warning big data information is divided into static source information and dynamic monitoring information, and data processing is divided into basic geological model data processing, numerical processing and Computational simulation and information fusion data processing divide coal mine disaster early warning into primary monitoring parameter early warning, intermediate index grading early warning, and advanced intelligent model early warning. The key technical architecture of an intelligent warning system for coal mine water hazards is proposed and analyzed. A software service architecture that meets the technical requirements is proposed, including infrastructure layer, data resource layer, application support layer, business application layer, and user presentation layer. Based on the water hazard warning construction process, a Gated Recurrent Unit algorithm warning model for water hazard monitoring data is proposed, and the network structure of the warning model is given. The forward calculation, backward propagation calculation, and weight gradient calculation methods of the warning model are studied. The classification of different types of perception data access, storage, encoding, models, construction and testing of intelligent deep learning models, and technical paths for warning information release are analyzed. It provides a reference for the intelligent construction of coal mine water hazard early warning