Attribute reduction with rough sets aims to delete superfluous condition attributes from a decision system by considering the inconsistency between condition attributes and the decision labels. ...However, heterogeneous condition attributes including symbolic and real-valued ones always coexist for most decision systems and different types of attributes induce different kinds of granular structures. The existing rough set models do not have explicit mechanisms to address different kinds of granular structures reasonably and effectively. In this paper, we aim to perform attribute reduction for decision systems with symbolic and real-valued condition attributes by composing classical rough set and fuzzy rough set models. We first define a discernibility relation for every symbolic and real-valued condition attribute to characterize its discernible ability related to the decision labels. With these discernibility relations, we can develop a dependence function to measure the inconsistency between heterogeneous condition attributes and decision labels, and attribute reduction aims to keep this dependence function with a small perturbation. The proposed attribute reduction deals with heterogeneous condition attributes from the viewpoint of discernible ability and can consider the mutual effects between two types of attributes without preprocessing into single-typed ones. An algorithm to find reducts is developed and experiments are performed to demonstrate that the proposed idea is effective.
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•Geochemical baseline values of heavy metal in agricultural soil were evaluated.•The indexes of PI, EI and RI revealed that soil was moderately polluted wholly.•Apply geostatistical ...analysis, PMF and health risk model to obtain sources.•There were no significant carcinogenic and non-carcinogenic risk effects.•Agriculture, industry and traffic were the main and priority pollution sources.
To determine the heavy metal contamination of agricultural soil in the Hexi Corridor, 376 soil samples were collected and analyzed for their heavy metal content. The geochemical baseline value (GBV), single-factor pollution index (PI), ecological risk of a single heavy metal, and comprehensive ecological risk index (RI) were used to assess the degree of pollution. Geostatistical analysis, positive matrix factorization (PMF), and a health risk assessment model were used to determine the primary sources of pollution and priority sources. Although the mean Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, and Pb concentrations (2717, 62.85, 48.23, 511.6, 24827, 51.29, 26.47, 53.98, 12.39, 16.85 mg•kg−1 in the west, 3046, 72.15, 59.32, 598.1, 27614, 54.57, 29.55, 59.47, 13.63, 20.74 mg•kg−1 in the center, and 2558, 61.02, 39.67, 466.7, 22575, 39.94, 26.06, 54.81, 11.86, 20.38 mg•kg−1 in the east, respectively) did not exceed the national critical values, approximately 1% of the west As samples did exceed their critical values. The mean concentrations of the heavy metals were less than their corresponding GBVs. The PI and RI revealed that the agricultural soil was moderately polluted, at low ecological risk, and the least polluted in the center. Based on PMF, Factor 1 represented metal processing; Factor 2 represented the mixed sources of electroplating and smelting in the west and center, and the mixed sources of mining and agricultural activities in the east; Factor 3 was ascribed to agriculture; and Factor 4 was the mixed sources of atmospheric deposition and traffic emission. The main pollution source, Factor 4 in the west and east and Factor 2 in the center, had the highest percent proportion of total metals and priority pollution sources, thus contributing the most to the carcinogenic (Factor 2 in the west and Factor 3 in the center and east) and non-carcinogenic risks (Factor 2 for adults and Factor 1 for children in the west and Factor 3 in the center and east), respectively.
Hexi Corridor is the most important base of commodity grain and producing area for cash crops. However, the rapid development of agriculture and industry has inevitably led to heavy metal ...contamination in the soils. Multivariate statistical analysis, GIS-based geostatistical methods and Positive Matrix Factorization (PMF) receptor modeling techniques were used to understand the levels of heavy metals and their source apportionment for agricultural soil in Hexi Corridor. The results showed that the average concentrations of Cr, Cu, Ni, Pb and Zn were lower than the secondary standard of soil environmental quality; however, the concentrations of eight metals (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn) were higher than background values, and their corresponding enrichment factor values were significantly greater than 1. Different degrees of heavy metal pollution occurred in the agricultural soils; specifically, Ni had the most potential for impacting human health. The results from the multivariate statistical analysis and GIS-based geostatistical methods indicated both natural sources (Co and W) and anthropogenic sources (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn). To better identify pollution sources of heavy metals in the agricultural soils, the PMF model was applied. Further source apportionment revealed that enrichments of Pb and Zn were attributed to traffic sources; Cr and Ni were closely related to industrial activities, including mining, smelting, coal combustion, iron and steel production and metal processing; Zn and Cu originated from agricultural activities; and V, Ti and Mn were derived from oil- and coal-related activities.
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•PCA and kriging interpolation introduced natural and anthropogenic sources.•Ni was the most potential for human health in Hexi Corridor farmland.•Using PMF to analyze sources of heavy metals in northwestern China.•Three anthropogenic sources were identified and quantified by PMF.
Attribute reduction with rough sets is an effective technique for obtaining a compact and informative attribute set from a given dataset. However, traditional algorithms have no explicit provision ...for handling dynamic datasets where data present themselves in successive samples. Incremental algorithms for attribute reduction with rough sets have been recently introduced to handle dynamic datasets with large samples, though they have high complexity in time and space. To address the time/space complexity issue of the algorithms, this paper presents a novel incremental algorithm for attribute reduction with rough sets based on the adoption of an active sample selection process and an insight into the attribute reduction process. This algorithm first decides whether each incoming sample is useful with respect to the current dataset by the active sample selection process. A useless sample is discarded while a useful sample is selected to update a reduct. At the arrival of a useful sample, the attribute reduction process is then employed to guide how to add and/or delete attributes in the current reduct. The two processes thus constitute the theoretical framework of our algorithm. The proposed algorithm is finally experimentally shown to be efficient in time and space.
The crucial role of CD4
and CD8
T cells in shaping and controlling immune responses during immune disease and cancer development has been well established and used to achieve marked clinical ...benefits. CD3
CD4
CD8
double-negative (DN) T cells, although constituting a rare subset of peripheral T cells, are gaining interest for their roles in inflammation, immune disease and cancer. Herein, we comprehensively review the origin, distribution and functions of this unique T cell subgroup. First, we focused on characterizing multifunctional DN T cells in various immune responses. DN regulatory T cells have the capacity to prevent graft-versus-host disease and have therapeutic value for autoimmune disease. T helper-like DN T cells protect against or promote inflammation and virus infection depending on the specific settings and promote certain autoimmune disease. Notably, we clarified the role of DN tumor-infiltrating lymphocytes and outlined the potential for malignant proliferation of DN T cells. Finally, we reviewed the recent advances in the applications of DN T cell-based therapy for cancer. In conclusion, a better understanding of the heterogeneity and functions of DN T cells may help to develop DN T cells as a potential therapeutic tool for inflammation, immune disorders and cancer.
Inflammatory bowel disease (IBD) includes Crohn’s disease and ulcerative colitis and manifests as a complex and dysregulated immune response. To date, there is no cure for IBD; thus, lifelong ...administration of maintenance drugs is often necessary. Since conventional IBD treatment strategies do not target the sites of inflammation, only limited efficacy is observed with their use. Moreover, the possibility of severe side effects resulting from systemic drug redistribution is high when conventional drug treatments are used. Therefore, a straightforward disease-targeted drug delivery system is desirable. Based on the pathophysiological changes associated with IBD, novel site-specific targeted drug delivery strategies that deliver drugs directly to the inflammation sites can enhance drug accumulation and decrease side effects. This review summarizes novel inflammation targeted delivery systems in the management of IBD. It also discusses the challenges and new perspectives in this field.
Inflammasomes are a class of cytosolic protein complexes. They act as cytosolic innate immune signal receptors to sense pathogens and initiate inflammatory responses under physiological and ...pathological conditions. The NLR-family pyrin domain-containing protein 3 (NLRP3) inflammasome is the most characteristic multimeric protein complex. Its activation triggers the cleavage of pro-interleukin (IL)-1β and pro-IL-18, which are mediated by caspase-1, and secretes mature forms of these mediators from cells to promote the further inflammatory process and oxidative stress. Simultaneously, cells undergo pro-inflammatory programmed cell death, termed pyroptosis. The danger signals for activating NLRP3 inflammasome are very extensive, especially reactive oxygen species (ROS), which act as an intermediate trigger to activate NLRP3 inflammasome, exacerbating subsequent inflammatory cascades and cell damage. Vascular endothelium at the site of inflammation is actively involved in the regulation of inflammation progression with important implications for cardiovascular homeostasis as a dynamically adaptable interface. Endothelial dysfunction is a hallmark and predictor for cardiovascular ailments or adverse cardiovascular events, such as coronary artery disease, diabetes mellitus, hypertension, and hypercholesterolemia. The loss of proper endothelial function may lead to tissue swelling, chronic inflammation, and the formation of thrombi. As such, elimination of endothelial cell inflammation or activation is of clinical relevance. In this review, we provided a comprehensive perspective on the pivotal role of NLRP3 inflammasome activation in aggravating oxidative stress and endothelial dysfunction and the possible underlying mechanisms. Furthermore, we highlighted the contribution of noncoding RNAs to NLRP3 inflammasome activation-associated endothelial dysfunction, and outlined potential clinical drugs targeting NLRP3 inflammasome involved in endothelial dysfunction. Collectively, this summary provides recent developments and perspectives on how NLRP3 inflammasome interferes with endothelial dysfunction and the potential research value of NLRP3 inflammasome as a potential mediator of endothelial dysfunction.
Single-crystal heterostructured Au/BTO nanoparticles were fabricated successfully through a simple hydrothermal process. The prepared heterostructured nanoparticles were characterized by XRD, SEM, ...HRTEM, UV–vis adsorption spectroscopy and XPS. Results display that Au nanoparticles with the size of ∼5 nm loaded on the surface of the ferroelectric tetragonal phase BTO nanoparticles. The heterostructured photocatalyst showed an enhanced photocatalytic activity toward the degradation of RhB under UV light irradiation. Transient photovoltage (TPV) spectra results demonstrated that the pure BTO and Au/BTO 5.0 wt% show negative TPV signal. Moreover, TPV results demonstrated that the Au loading boosted the separation and transmission of photoinduced carriers under UV light. Furthermore, the ferroelectric polarization not only promoted the fast separation of photogenerated carriers but also prolonged the carrier lifetime. These all enhanced the photocatalytic performance.
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•Heterostructured Au@BaTiO3 nanoparticles were prepared by a hydrothermal process.•Heterostructured Au@BaTiO3 nanoparticles displayed a superior UV-light activity caused by the ferroelectric nature.•Au act as electron traps rather than generators of the photoexcited electrons.•Au boosts the separation and transmission of photoinduced carriers.
Abstract
The current understanding of lactate extends from its origins as a byproduct of glycolysis to its role in tumor metabolism, as identified by studies on the Warburg effect. The lactate ...shuttle hypothesis suggests that lactate plays an important role as a bridging signaling molecule that coordinates signaling among different cells, organs and tissues. Lactylation is a posttranslational modification initially reported by Professor Yingming Zhao’s research group in 2019. Subsequent studies confirmed that lactylation is a vital component of lactate function and is involved in tumor proliferation, neural excitation, inflammation and other biological processes. An indispensable substance for various physiological cellular functions, lactate plays a regulatory role in different aspects of energy metabolism and signal transduction. Therefore, a comprehensive review and summary of lactate is presented to clarify the role of lactate in disease and to provide a reference and direction for future research. This review offers a systematic overview of lactate homeostasis and its roles in physiological and pathological processes, as well as a comprehensive overview of the effects of lactylation in various diseases, particularly inflammation and cancer.
Salmonella Typhimurium (S. Typhimurium) infection in broiler chickens threatens public health and livestock production. In this study, we explored the effects of highly nutritious (crude protein ...21.8%, metabolizable energy 3.16 Mcal/kg) and lowly nutritious (crude protein 18.1%, metabolizable energy 2.98 Mcal/kg) diets on S. Typhimurium infection by altering the intestinal morphology and environment in broiler chickens. The highly nutritious diet significantly increased the body weight gain and reduced feed conversion ratio on day 1 to 21 (P < 0.01). The highly nutritious diets promoted the intestinal villus height, crypt depth, and their ratio to improve the intestinal epithelial maturation (P < 0.05). Highly nutritious diets significantly increased the expression of claudin-1, occludin, and NF-κB genes in the intestinal epithelium on the days of 14 and 21 (P < 0.05). S. Typhimurium activated the expression of TLR4, MyD88, and NF-κB genes to cause an inflammatory response. The S. Typhimurium can increase the activity of myeloperoxidase, which cause an inflammatory response. The S. Typhimurium significantly reduced the diversity indexes of the ileal microbiota (P < 0.05), increased the abundance of Cyanobacteria which can synthesize toxins. The highly nutritious diet group challenged with S. Typhimurium can increase the abundance of Lactobacillus in the ileum, which lead to improved intestinal health (P < 0.05). It is concluded that increasing the nutritional level of dietary is beneficial to improve the resistance to S. Typhimurium infection by altering the intestinal bacterial community.
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