LncRNAs are an emerging category of non-coding RNAs. LncRNAs are usually greater than 200 nucleotides in length and do not possess protein editing capabilities. DSCAM-AS1 is a highly valued member of ...the lncRNAs family. Numerous studies have revealed the involvement of the oncogene DSCAM-AS1 in multiple biological processes, including metastasis, aggressiveness and cell proliferation. This review discusses the molecular mechanisms and clinical significance of DSCAM-AS1 in various tumor types.
This paper analyzes and summarizes current research by searching PubMed using "DSCAM-AS1" and "tumor" as keywords.
DSCAM-AS1 is a valuable tumor-associated lncRNA with significant oncogenic effects. It is abnormally expressed in a variety of cancers, such as non-small cell lung cancer, cervical cancer, osteosarcoma, colorectal cancer, breast cancer, gastric cancer and endometrial cancer. The overexpression of DSCAM-AS1 promotes cancer progression by modulating cancer cell proliferation, invasion, distant metastasis, and resistance.
DSCAM-AS1 is upregulated and acts as an oncogene in multiple tumors. As more systematic studies are performed, DSCAM-AS1 may prove to be a promising therapeutic target or tumor biomarker.
When drinking water flows into the water distribution network from a reservoir, it is exposed to the risk of accidental or deliberate contamination. Serious drinking water pollution events can ...endanger public health, bring about economic losses, and be detrimental to social stability. Therefore, it is obviously crucial to research the water contamination source identification problem, for which scholars have made considerable efforts and achieved many advances. This paper provides a comprehensive review of this problem. Firstly, some basic theoretical knowledge of the problem is introduced, including the water distribution network, sensor system, and simulation model. Then, this paper puts forward a new classification method to classify water contamination source identification methods into three categories according to the algorithms or methods used: solutions with traditional methods, heuristic methods, and machine learning methods. This paper focuses on the new approaches proposed in the past 5 years and summarizes their main work and technical challenges. Lastly, this paper suggests the future development directions of this problem.
Reducing pollutant detection time based on a reasonable sensor combination is desirable. Clean drinking water is essential to life. However, the water supply network (WSN) is a vulnerable target for ...accidental or intentional contamination due to its extensive geographic coverage, multiple points of access, backflow, infrastructure aging, and designed sabotage. Contaminants entering WSN are one of the most dangerous events that may cause sickness or even death among people. Using sensors to monitor the water quality in real time is one of the most effective ways to minimize negative consequences on public health. However, it is a challenge to deploy a limited number of sensors in a large-scale WSN. In this study, the sensor placement problem (SPP) is modeled as a sequential decision optimization problem, then an evolutionary reinforcement learning (ERL) algorithm based on domain knowledge is proposed to solve SPP. Extensive experiments have been conducted and the results show that our proposed algorithm outperforms meta-heuristic algorithms and deep reinforcement learning (DRL).
IFN regulatory factor (IRF)3 is a central regulator for IFN-β expression in different types of pathogenic infections. Mammals have various pathogenic sensors that are involved in monitoring pathogen ...intrusions. These sensors can trigger IRF3-mediated antiviral responses through different pathways. Endoplasmic reticulum-associated proteins stimulator of IFN gene (STING) and zinc finger DHHC-type containing 1 (ZDHHC1) are critical mediators of IRF3 activation in response to viral DNA infections. In this study, grass carp STING and ZDHHC1 were found to have some similar molecular features and subcellular localization, and both were upregulated upon stimulation with polyinosinic:polycytidylic acid, B-DNA, or Z-DNA. Based on these results, we suggest that grass carp STING and ZDHHC1 might possess some properties similar to their mammalian counterparts. Overexpression of ZDHHC1 and STING in
kidney cells upregulated IFN expression, whereas knockdown of IRF3 inhibited IFN activation. In addition, coimmunoprecipitation and GST pull-down assays demonstrated that STING and ZDHHC1 can interact separately with IRF3 and promote the dimerization and nuclear translocation of IRF3. Furthermore, we also found that small interfering RNA-mediated knockdown of STING could inhibit the expression of IFN and ZDHHC1 in fish cells. Similarly, knockdown of STING resulted in inhibition of the IFN promoter. In contrast, ZDHHC1 knockdown also inhibited IFN expression but had no apparent effect on STING, which indicates that STING is necessary for IFN activation through ZDHHC1. In conclusion, STING and ZDHHC1 in fish can respond to viral DNA or RNA molecules in cytoplasm, as well as activate IRF3 and, eventually, trigger IFN expression.
The real-time location of pollution sources is the process of inverting pollution sources based on the dynamic optimization model constructed by the time-varying pollution concentration detected by ...the water quality sensor. Due to the vast quantities of the water supply networks, the water quality sensors will only be placed on critical nodes, resulting in multiple solutions. However, the increased monitoring data enhances the uniqueness of the solution. Combined with the real-time location of pollution sources, this work proposed a multi-strategy dynamic multi-mode optimization algorithm based on domain knowledge, which could guide the population search and avoid trapped into local optimal. The merging mechanism was used to keep the diversity of the population and prevent sub-population clustering on the same optimal solution. The simulation results showed that the algorithm could effectively solve the real-time location problem of pollution sources in different pipe networks and pollution scenarios.
LncRNA is a kind of non-coding RNA and its research is more popular in recent years, which has more than 200 nucleotides. It plays a significant part in various biological functions, including ...chromosome modification, genome modification, transcriptional activation, transcriptional interference, and other processes. FTX, at the center of the X chromosome inactivation and it has been shown that lncRNA FTX regulates cancer cells' development, migration, and invasion in many studies.
Relevant literature was collected through the PubMed system search and is summarized in this article.
LncRNA FTX abnormally increased in tumor cells, such as liver cancer, stomach cancer, leukemia, renal cell carcinoma, colorectal cancer, glioma, osteosarcoma, etc. However, the expression level decreased in temporal lobe epilepsy, liver cirrhosis, heart failure, etc. Conclusion: FTX may be an important regulatory factor and a potential therapeutic target in cancers.
China has committed to reaching carbon neutrality by 2060, which will require a drastic cut in greenhouse gas (GHG) emissions from all sectors, including those from agricultural activities. A ...comprehensive, long-term, and spatially-precise profile of agricultural GHG emissions can help to accurately understand drivers of historical emissions and their implications for future mitigation. This study constructs province-level agricultural GHG emissions in China from 1978 to 2016. It considers primary and secondary emissions from a full range of agricultural activities related to crop farming, including crop residue open burning, rice cultivation, cropland change, cropland emissions, machinery use, nitrogen fertilizer production, and pesticide production. Annual or interpolated activity data from official sources and the latest emission factors available for China were adopted in this study. The data can be used in spatial and temporal analysis of emissions from cropping systems as well as the design of mitigation strategy in China.
In recent years, water contamination incidents have happened frequently, causing serious losses and impacts on society. Therefore, how to quickly respond to emergency pollution incidents is a ...widespread concern for academic and industry scientists. In this paper, aiming to deal with the uncertain environment and randomness of water demand, we present a method based on a deep reinforcement learning emergency scheduling algorithm combined with Lamarckian local search. This method can effectively schedule water valves and fire hydrants to isolate contaminated water and reduce the residual concentration of contaminants in water distribution networks (WDNs). Furthermore, two optimization objectives are formulated, and then multi-objective optimization and deep reinforcement learning are combined to solve this problem. A real-world WDN is employed and simulation results show that our proposed algorithm can effectively isolate contamination and reduce the risk exclosure to customers.
Urban water supply network is easily affected by intentional or occasional chemical and biological pollution, which threatens the health of consumers. In recent years, drinking water contamination ...happens occasionally, which seriously harms social stabilization and safety. Placing sensors in water supply pipes can monitor water quality in real time, which may prevent contamination accidents. However, how to reversely locate pollution sources through the detecting information from water quality sensors is a challengeable issue. Its difficulties lie in that limited sensors, massive pipe network nodes and dynamic water demand of users lead to the uncertainty, large-scale and dynamism of this optimization problem. This paper mainly studies the uncertainty problem in contaminant sources identification (CSI). The previous study of CSI supposes that hydraulic output (e.g., water demand) is known. Whereas, the inherent variability of urban water consumption brings an uncertain problem that water demand presents volatility. In this paper, the water demand of water supply network nodes simulated by Gaussian model is stochastic, and then being used to solve the problem of CSI, simulation–optimization method finds the minimum target of CSI and concentration which meet the simulation value and detected value of sensors. This paper proposes an improved genetic algorithm to solve the CSI problem under uncertainty water demand and comparative experiments are placed on two water distribution networks of different sizes.
Display omitted
•The applications and detailed advantages of organoids and organoids-on-a-chip in environmental toxicology are sufficiently considered in this review.•Organoids are frequently used in ...environmental toxicology, while organoids-on-a-chip has great potential in environmental toxicology.•Organoids-on-a-chip can make up for the shortcomings of common organoids to a certain extent.•Increased application of these new strategies in toxicology will further advance human health research.
An increasing number of harmful environmental factors are causing serious impacts on human health, and there is an urgent need to accurately identify the toxic effects and mechanisms of these harmful environmental factors. However, traditional toxicity test methods (e.g., animal models and cell lines) often fail to provide accurate results. Fortunately, organoids differentiated from stem cells can more accurately, sensitively and specifically reflect the effects of harmful environmental factors on the human body. They are also suitable for specific studies and are frequently used in environmental toxicology nowadays. As a combination of organoids and organ-on-a-chip technology, organoids-on-a-chip has great potential in environmental toxicology. It is more controllable to the physicochemical microenvironment and is not easy to be contaminated. It has higher homogeneity in the size and shape of organoids. In addition, it can achieve vascularization and exchange the nutrients and metabolic wastes in time. Multi-organoids-chip can also simulate the interactions of different organs. These advantages can facilitate better function and maturity of organoids, which can also make up for the shortcomings of common organoids to a certain extent. This review firstly discussed the limitations of traditional toxicology testing platforms, leading to the introduction of new platforms: organoids and organoids-on-a-chip. Next, the applications of different organoids and organoids-on-a-chip in environmental toxicology were summarized and prospected. Since the advantages of the new platforms have not been sufficiently considered in previous literature, we particularly emphasized them. Finally, this review also summarized the opportunities and challenges faced by organoids and organoids-on-a-chip, with the expectation that readers will gain a deeper understanding of their value in the field of environmental toxicology.
PDF
