The relationship between the individual and the collective is one of the most important topics in Confucianism. Though this concept has been widely studied, ming 名 (meaning ‘name’), one of its most ...crucial categories, has not yet been deeply explored within this theoretical domain. This article discusses four aspects of ming and their contributions to the relationship between the self and community. Firstly, Confucius’ proposition of zhengming 正名 (rectifying names or the rectification of names) implies that language, especially that of rulers or gentlemen 君子 (junzi), has a considerable impact on both ethical and political practices. In this sense, ming as language establishes a relationship between rulers and the communities they govern. Secondly, in Confucius’ use of ming, reputation also reflects the attributes of a collectivity. On one hand, reputation functions as a social evaluation system; on the other, it can also be used to shape social values. Both aspects of language and reputation can be found in Confucius’ sayings, and are essentially determined by the sound attributes of ming. Thirdly, ming is interpreted to mean “role” in the later explanations and commentaries of Analects 13.3, which signifies that each individual has their own role in the community to which they belong. The position of a social individual is determined according to their relationship with others. Simultaneously, it is also the idea of “role” that brings a hierarchical order to family, state, clan, and “all under heaven”. Finally, the relationship between ming and yi 義 (appropriateness) implies the correlation between a name and the subject to which it refers. For ethical or political participants, yi means that the name-bearer is bound to a series of demands regarding their behaviors and virtues, which can lead to a “thick” conception of the subject, that is, the role of a complex of virtues, duties, and even rights (albeit implicit). Although the meaning of ming was becoming more complicated and profound during the development of early Confucianism, it has always functioned as the bond between individual and community. In this regard, the Confucian theory of ming can contribute some insights toward the combination of Confucianism and communitarianism, and also toward the modernization of Confucianism.
Neutrophils are significant compositions of solid tumors and exert distinct functions in different types of tumors. However, the precise role of neutrophils in the progression of breast cancer (BC) ...is presently unclear. In this study, by investigating the single-cell RNA sequencing data, we identify a new neutrophil subset, C5aR1-positive neutrophils, that correlates with tumor progression and poor survival for BC patients. Furthermore, it is discovered that C5aR1-positive neutrophils enhance BC cell glycolysis via upregulating ENO1 expression. Mechanically, C5aR1-positive neutrophil-secreted IL1β and TNFα cooperatively activate ERK1/2 signaling, which phosphorylates WTAP at serine341 and thereby stabilizes WTAP protein. The stabilization of WTAP further promotes RNA m6A methylation of ENO1, impacting the glycolytic activity of BC cells. Importantly, C5aR1-positive neutrophils also promote breast cancer growth in vivo, and this effect is abolished by WTAP silencing. In clinical BC samples, increased C5aR1-positive neutrophils correlate with elevated IL1β, TNFα, and ENO1 expression. A high co-expression of C5aR1-positive neutrophil gene signature and ENO1 predicts worse prognosis of BC patients compared with a low co-expression. Collectively, our study reveals a novel subset of C5aR1-positive neutrophils that induces breast cancer glycolysis via increasing ERK1/2-WTAP-dependent m6A methylation of ENO1. These findings support the potential for exploration of C5aR1-positive neutrophils as a therapeutic target in breast cancer.
Rice bran is the main by-product of rice processing and contains approximately 64% of the nutrients in rice. Its various nutrient elements include rice bran proteins, oil, oryzanol, vitamins, ...polysaccharides,
etc.
The use of fermented technology can increase the content of bioactive peptides, promote the absorption efficiency, and further improve the functionality and added value of rice bran. In recent years, the nutritional value and function of the extracts and fermented products of rice bran have been emphatically studied. Rice bran extracts and fermentation products serve a critical role in the anti-inflammatory reaction, reducing the plasma lipid effect and increasing anti-cancer activity. Moreover, few review studies have been reported on the anti-cancer activity and potential mechanism of action of rice bran extract and its fermentation products. In this review, we focused on the anti-cancer function, mechanisms, and potential clinical usage of rice bran extracts and fermentation products in the adjuvant therapy of cancer patients.
Extracts and fermentation products of rice bran serve important roles in mediating inflammation, cell cycel, cell apotosis, and cancer prevention.
•We proposed an integrated framework combining both process-based models and data-driven approach.•The modified local model was applied to directly update and correct the output of the water quality ...model.•The scheme yields a good performance, and is less dependent on forecast horizon and good for long lead time forecasting.•It can be operated offline and efficiently reduce the time of the forecasting.
Water quality indicators can be used to characterize the status and quantify and qualify the change of aquatic ecosystems under different disturbance regimes. Although many studies have been done to develop and assess indicators and discuss interactions among them, few studies have focused on how to improve the predicted indicators and explore their variations in receiving water bodies. Accurate and effective predictions of ecological indictors are critical to better understand changes of water quality in aquatic ecosystems, especially for the real-time forecasting. Process-based water quality models can predict the spatiotemporal variations of the water quality indicators and provide useful information for policy-makers on sound management of water resources. Given their inherent constraints, however, such process models alone cannot actually guarantee perfect results since water quality models generally have a large number of parameters and involve many processes which are too complex to be efficiently calibrated. To overcome these limitations and explore a fast and efficient forecasting method for the change of water quality indictors, we proposed a new framework which combines the process-based models and data assimilation technique. Unlike most traditional approaches in which only the model parameters or initial conditions are updated or corrected and the models are run online, this framework allows the information extracted from observations and outputs of process models to be directly used in a data-driven local/modified local model. The results from the data-driven model are then assimilated into the original process model to further improve its forecasting ability. This approach can be efficiently run offline to directly correct and update the output of water quality models. We applied this framework in a real case study in Singapore. Two of the water quality indicators, namely salinity and oxygen were selected and tested against the observations, suggesting that a good performance of improving the model results and reducing computation time can be obtained. This approach is simple and efficient, especially suitable for real-time forecasting systems. Thus, it can enhance forecasting of water quality indictors and thereby facilitate the effective management of water resources.
In the paper, the achievements obtained from carrying out the policy of environmental protection price for promoting air pollution control in coal-fired power plants in China during more than a ...decade were summarized. Based on the situation of current electricity market reform, the role and effectiveness of environmental protection price for controlling the normal air pollutants, such as sulfur dioxide, nitrogen oxides, and dust in China’s coal-fired power generation plants, were investigated, including the price structure of electricity environmental protection for coal-fired power generation enterprises in different regions, generating units, and power demands. The policy suggestions were proposed, namely, the reform of electricity environmental protection price would be carried out gradually, the relationship between electricity environmental protection price policy and other environmental protection policies would be matched under the relative overcapacity condition, and the environmental protection price regulation would be integrated into other environmental policies.
Background
Triple-negative breast cancer (TNBC) remains a great challenge in clinical treatment due to a shortage of effective therapeutic targets and acquired chemoresistance. Here, we identified ...the role of an RNA-binding protein, CUG-BP Elav-like family member 6 (CELF6), in the TNBC development and paclitaxel (PTX) chemoresistance.
Methods
Stable CELF6-overexpressing cell lines were established in BT549 and MDA-MB-231 cells. Cell proliferation was determined using cell counting, two-dimensional colony formation, and MTT assay. Meanwhile, cell migration and cell invasion were detected by Transwell assay. Furthermore, the downstream target gene of CELF6 was identified and the direct interaction was further determined by luciferase reporter assay, immunoprecipitation, and RNA pull-down. Additionally, the PTX resistant cell line was established to determine the role of CELF6 in PTX resistance.
Results
CELF6 overexpression suppressed cell proliferation, cell migration, and cell invasion. Mechanistically, Fructose-Bisphosphatase 1 (FBP1) was identified as the target gene of CELF6 and stabilized by CELF6 via binding 3′UTR. CELF6 overexpression mediated inhibition in TNBC development was dependent on FBP1. Moreover, CELF6 overexpression increased the sensitivity to PTX treatment.
Conclusion
CELF6 functions as a tumor suppressor by upregulating FBP 1 expression via stabilizing its mRNA, and thereby inhibits TNBC progression.
Cellular senescence is characterized by a tumor-suppressive program as well as a pro-inflammatory secretome. Neutrophils constitute significant compositions of malignancies and play key roles in ...tumor development. However, the role of senescent neutrophils in cancer progression is presently unexplored. Here, we demonstrate that neutrophils display enhanced senescence in breast cancer patients receiving chemotherapy. The senescent neutrophils produce increased number of exosomes, which confer drug resistance to tumor cells in vitro and in vivo. Mechanistically, senescent neutrophils-derived exosomal piRNA-17560 enhances the expression of fat mass and obesity-associated protein (FTO) in breast cancer cells. The upregulation of FTO further strengthens ZEB1 transcripts stability and expression by decreasing N6-methyladenosine (m6A) RNA methylation, leading to chemoresistance and epithelial-mesenchymal transition (EMT) of tumor cells. Clinically, the level of exosomal piR-17560 correlates with poor chemotherapy response in patients with breast cancer. In addition, YTHDF2 is essential for the posttranscriptional regulation of ZEB1 by piRNA-17560/FTO signaling. Senescent neutrophils secret exosomal piR-17560 in a STAT3-dependent manner. Altogether, this study suggests that senescent neutrophils-derived exosomal piR-17560 confers chemoresistance to tumor cells and senescent neutrophils may serve as a potential therapeutic target in breast cancer.
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•An LSTM-based surface water temperature predicting method for large deep reservoirs was proposed.•Air temperature is the dominant factor for the surface water temperature.•Water ...level can influence surface water temperature in summer.
Surface water temperature (SWT) is a key indicator to characterize the ecological health of a reservoir. Many newly built large-deep reservoirs, however, lack enough SWT observation data and high-efficient SWT predicting methods for water ecosystem management. This paper proposed a Long Short-Term Memory (LSTM) based SWT predicting method by surrogating a Delft3D hydrodynamic model. The Delft3D model calibrated by a handful of measured data was used to generate 30-year daily SWT data for training the LSTM model. The LSTM model that uses the air temperature, relative humidity, radiation, and water level data as input variables, can significantly improve the efficiency of SWT prediction. The SWT predicting method was implemented in the Nuozhadu reservoir, a large deep reservoir located in southwest China. The results showed that the LSTM model could predict the SWT generated by Delft3D accurately with an R2 value of 0.99, and had a dramatic reduction in computational burden. Meanwhile, the R2 between the LSTM model results and measured data was also over 0.93. Based on the SWT predicting method, we analyzed the sensitivity of SWT to the air temperature and water level to reveal the impacts of climate change and reservoir operation policies on the SWT. The major contribution of this study is that we greatly improve the computational efficiency of the SWT predicting method so that it can easily be coupled with reservoir operation optimization models, thereby enabling reservoir managers to identify optimal operation rules simultaneously considering the water temperature targets and other targets such as hydropower generation and water supply, and to eventually support reservoir management strategies that aim to reduce the potential aquatic ecosystems risk from abnormal water temperature.
Gaussian processes (GPs) are popular models for functions, time series, and spatial fields, but direct application of GPs is computationally infeasible for large datasets. We propose a multi-scale ...Vecchia (MSV) approximation of GPs for modeling and analysis of multi-scale phenomena, which are ubiquitous in geophysical and other applications. In the MSV approach, increasingly large sets of variables capture increasingly small scales of spatial variation, to obtain an accurate approximation of the spatial dependence from very large to very fine scales. For a given set of observations, the MSV approach decomposes the data into different scales, which can be visualized to obtain insights into the underlying processes. We explore properties of the MSV approximation and propose an algorithm for automatic choice of the tuning parameters. We provide comparisons to existing approaches based on simulated data and using satellite measurements of land-surface temperature.
Abstract
Automating retrosynthesis with artificial intelligence expedites organic chemistry research in digital laboratories. However, most existing deep-learning approaches are hard to explain, like ...a “black box” with few insights. Here, we propose RetroExplainer, formulizing the retrosynthesis task into a molecular assembly process, containing several retrosynthetic actions guided by deep learning. To guarantee a robust performance of our model, we propose three units: a multi-sense and multi-scale Graph Transformer, structure-aware contrastive learning, and dynamic adaptive multi-task learning. The results on 12 large-scale benchmark datasets demonstrate the effectiveness of RetroExplainer, which outperforms the state-of-the-art single-step retrosynthesis approaches. In addition, the molecular assembly process renders our model with good interpretability, allowing for transparent decision-making and quantitative attribution. When extended to multi-step retrosynthesis planning, RetroExplainer has identified 101 pathways, in which 86.9% of the single reactions correspond to those already reported in the literature. As a result, RetroExplainer is expected to offer valuable insights for reliable, high-throughput, and high-quality organic synthesis in drug development.
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