Application of the partial least square regression method in determining the natural background of soil heavy metals: A case study in the Songhua River basin, China.

The "background" is an essential index for identifying anthropogenic inputs and potential ecological risks of soil heavy metals. However, the lithology of bedrock can cause significant spatial variation in the natural background of soil elements, posing considerable difficulties in estimating background values. In this study, an attempt was made to calculate the natural background through regression analysis of soil chemical composition, and reasonably evaluate the impact of lithology. A total of 1771 surface soil samples were collected from the Songhua River Basin, China, for chemical composition analysis, and the partial least square regression (PLSR) method was employed to establish the relationship between heavy metals (As, Hg, Cr, Cd, Pb, Cu, Zn, and Ni) and soil chemical composition/environmental parameters (SiO2, Al2O3, TFe2O3, MgO, CaO, K2O, Na2O, La, Y, Zr, V, Sc, Sr, Li and pH). The result shows that As, Cr, Pb, Cu, Zn, and Ni have significant linear relationships with soil chemical composition. Each of these six heavy metals obtained 1771 regression background values; some were higher than the uniform background value obtained from the boxplot, while others were lower. The regression background values recognized not only subtle anthropogenic inputs and potential ecological risks in low-background regions but also spurious contamination in high-background areas. All these indicate that the PLSR method can effectively improve the determination accuracy of the natural background of soil heavy metals. More attention should be paid to the serious anthropogenic inputs appearing in some places of the study area.

Construction of Data-Driven Performance Digital Twin for a Real-World Gas Turbine Anomaly Detection Considering Uncertainty.

Anomaly detection and failure prediction of gas turbines is of great importance for ensuring reliable operation. This work presents a novel approach for anomaly detection based on a data-driven performance digital twin of gas turbine engines. The developed digital twin consists of two parts: uncertain performance digital twin (UPDT) and fault detection capability. UPDT is a probabilistic digital representation of the expected performance behavior of real-world gas turbine engines operating under various conditions. Fault detection capability is developed based on detecting UPDT outputs that have low probability under the training distribution. A novel anomaly measure based on the first Wasserstein distance is proposed to characterize the entire flight data, and a threshold can be applied to this measure to detect anomaly flights. The proposed UPDT with uncertainty quantification is trained with the sensor data from an individual physical reality and the outcome of the UPDT is intended to deliver the health assessment and fault detection results to support operation and maintenance decision-making. The proposed method is demonstrated on a real-world dataset from a typical type of commercial turbofan engine and the result shows that the F1 score reaches a maximum of 0.99 with a threshold of 0.45. The case study demonstrated that the proposed novel anomaly detection method can effectively identify the abnormal samples, and it is also possible to isolate anomalous behavior in a single performance signal, which is helpful for further fault diagnosis once an anomaly is detected.

Role of the EM clustering method in determining the geochemical background of As and Cr in soils: a case study in the north of Changchun, China.

Determining the geochemical background for heavy metals is vital in soil management activities. Although many statistical methods for geochemical background determination have been proposed, the multi-population problem of geochemical data, primarily regional ones, derived mainly from mixing multiple populations belonging to various geological sources or processes, needs to be better addressed. In this study, the Expectation-Maximization (EM) algorithm was employed to separate multiple populations in a 1:250,000 scale regional geochemical data set of soils in a lithologically complex region in the north of Changchun, China. The data set included 3746 surface soil samples analyzed for SiO2, K2O, Al2O3, CaO, La, Rb, Y, Ti, Ce, V, Cr, and As. The potential high-risk areas of As and Cr were determined before and after the separation of multiple populations. The comparison results show that the EM clustering method can efficiently separate multiple populations and determine soil geochemical background more reasonably, thus eliminating false contamination that is easily misidentified and better revealing concealed contamination that is challenging to detect.

Environmental contamination and health risk assessment of potentially toxic trace metal elements in soils near gold mines - A global meta-analysis.

Gold mining is the most important anthropogenic source of heavy metal emissions into the environment. Researchers have been aware of the environmental impacts of gold mining activities and have conducted studies in recent years, but they have only selected one gold mining site and collected soil samples in its vicinity for analysis, which does not reflect the combined impact of all gold mining activities on the concentration of potentially toxic trace elements (PTES) in nearby soils at a global scale. In this study, 77 research papers from 24 countries were collected from 2001 to 2022, and a new dataset was developed to provide a comprehensive study of the distribution characteristics, contamination characteristics, and risk assessment of 10 PTEs (As, Cd, Cr, Co, Cu, Hg, Mn, Ni, Pb, and Zn) in soils near the deposits. The results show that the average levels of all 10 elements are higher than the global background values and are at different levels of contamination, with As, Cd, and Hg at strong contamination levels and serious ecological risks. As and Hg contribute to a greater non-carcinogenic risk to both children and adults in the vicinity of the gold mine, and the carcinogenic risks of As, Cd, and Cu are beyond the acceptable range. Gold mining on a global scale has already caused serious impacts on nearby soils and should be given adequate attention. Timely heavy metal treatment and landscape restoration of extracted gold mines and environmentally friendly approaches such as bio-mining of unexplored gold mines where adequate protection is available are of great significance.

A new desorption method of polyurethane foam for the determination of gold and a comparative study on four desorption methods based on meta-analysis.

Accurate determination of gold in geological samples is an important prerequisite and guarantee for studying geological problems. There are many methods for digestion and enrichment of gold among which polyurethane foam (PUF) enrichment after aqua regia digestion is the most commonly used in the experiments. A new method to help the relief of gold from the PUF was put forward in this study, and it was applied to four certified reference materials (CRMs) together with three previously used methods, and the optimal extraction and enrichment conditions were determined through experiments. The four methods were compared by meta-analysis, and the thiourea liberation method was superior to the other three methods because of its simple operation and high accuracy. Out of consideration for the incomplete adsorption of gold in the solution by only one piece of PUF, repetitive adsorption of gold with a second and a third piece of PUF in the solution was proposed in this study. Results show that the gold content obtained by secondary and tertiary adsorption accounts for 11.03% of the total content, and the highest can reach 20.74%. When the third adsorption was carried out, the gold content in several samples was below the detection limit. Therefore, repeated adsorption of gold in the solution is necessary, and three times of adsorption is necessary.

An inactivated recombinant rabies virus chimerically expressed RBD induces humoral and cellular immunity against SARS-CoV-2 and RABV.

Many studies suggest that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect various animals and transmit among animals, and even to humans, posing a threat to humans and animals. There is an urgent need to develop inexpensive and efficient animal vaccines to prevent and control coronavirus disease 2019 (COVID-19) in animals. Rabies virus (RABV) is another important zoonotic pathogen that infects almost all warm-blooded animals and poses a great public health threat. The present study constructed two recombinant chimeric viruses expressing the S1 and RBD proteins of the SARS-CoV-2 Wuhan01 strain based on a reverse genetic system of the RABV SRV9 strain and evaluated their immunogenicity in mice, cats and dogs. The results showed that both inactivated recombinant viruses induced durable neutralizing antibodies against SARS-CoV-2 and RABV and a strong cellular immune response in mice. Notably, inactivated SRV-nCoV-RBD induced earlier antibody production than SRV-nCoV-S1, which was maintained at high levels for longer periods. Inactivated SRV-nCoV-RBD induced neutralizing antibodies against both SARS-CoV-2 and RABV in cats and dogs, with a relatively broad-spectrum cross-neutralization capability against the SARS-CoV-2 pseudoviruses including Alpha, Beta, Gamma, Delta, and Omicron, showing potential to be used as a safe bivalent vaccine candidate against COVID-19 and rabies in animals.

A highly selective fluorescent probe for Al3+ based on bis(2-hydroxy-1-naphthaldehyde) oxaloyldihydrazone with aggregation-induced emission enhancement and gel properties.

An efficient fluorescent probe, bis(2-hydroxy-1-naphthaldehyde) oxaloyldihydrazone (1), has been prepared for the selective sensing of Al3+ over other common metal ions in water-containing media. The 1:1 stoichiometry of 1 and Al3+ was determined from Job's plot and Benesti-Hildebrand plot. The binding constant was observed as 1.6×105M-1, and the limit of detection was found to be 0.36µM, which was far below the drinking water restriction of Al3+ by EPA (the maximum allowable value is 7.4µM). In addition, the inherent AIEE features of 1 were observed upon addition of water to DMSO solution due to the restriction of the intramolecular motion, which makes the molecular conformations rigid and planar. Moreover, 1 could act as a novel gelator to form thermo-reversible supramolecular organogel with significant green emission in DMSO-H2O (v/v, 9:1) solution.

Source tracing of n-alkanes in Songhua Lake, based on correspondence analysis and geochemical index.

This paper analyzes the source of n-alkanes in sediments spanning 63 years since 1943 from Songhua Lake, using the method of correspondence analysis and geochemical index. The area of Songhua Lake is 554 km2, and its ecological problems affect hundreds of thousands of people in the basin. The concentration of total n-alkanes (C13-C36) in the sediments ranged from 20.39 to 168.35 µg/g, averaged at 72.58 µg/g, indicating that the Songhua Lake has an ecological risk of n-alkanes and should be taken seriously and protected. The analysis of geochemical indexes, including main carbon distributions (MH), LMW/HMW ratio, Paq, average chain length and so on, shows the n-alkanes in the Songhua Lake sediments are mainly derived from modern higher terrestrial plants, followed by human activities, and a small part from aquatic vascular plants and algae. Moreover, the source and sedimentary history of n-alkanes in Songhua Lake were carried out by corresponding analysis. And the correspondence analysis could be a feasible and effective means of source tracing.

Comparative Study on Two Pretreatment Processes for Chemical Phase Analysis of Gold in Geological Samples by Atomic Absorption Spectrometry.

Sample pretreatment is important for chemical phase analysis of elements. In this study, the geological samples of the Laozuoshan gold mine are chosen to pretreat by ultrasonic centrifugation and cyclotron oscillation, and the content of gold in eight chemical phases (water-soluble, ion exchange and clay adsorption, organic matter bound, iron-manganese oxide bound, naked or seminaked, carbonate bound, sulfide bound, and insoluble silicate states) is determined by atomic absorption spectrometry. The results show that the gold content of water-soluble, ion exchange and clay adsorption, iron-manganese oxide, and naked or seminaked states in the rock and ore samples is low, and some samples have high gold content of insoluble silicate states in the two methods. However, the gold content of organic matter bound, carbonate bound, and sulfide bound states obtained by ultrasonic centrifugation and cyclotron oscillation methods is significantly different. According to the X-ray fluorescence spectrometry data and the actual geological condition, the result given by the cyclotron oscillation method is more reasonable. The gold content of sulfide bound state in sediment samples is the highest and consistent with the mineral information, which could be applied to preliminarily predict the rock and ore conditions in the corresponding mining areas. In contrast with ultrasonic centrifugation, the cyclotron oscillation method has the advantages of simplicity, high efficiency, practicality, and environmental protection, and it can be better used for the determination of gold chemical phase state in geological samples by atomic absorption spectrometry.

Hyperglycaemia inhibits REG3A expression to exacerbate TLR3-mediated skin inflammation in diabetes.

Dysregulated inflammatory responses are known to impair wound healing in diabetes, but the underlying mechanisms are poorly understood. Here we show that the antimicrobial protein REG3A controls TLR3-mediated inflammation after skin injury. This control is mediated by REG3A-induced SHP-1 protein, and acts selectively on TLR3-activated JNK2. In diabetic mouse skin, hyperglycaemia inhibits the expression of IL-17-induced IL-33 via glucose glycation. The decrease in cutaneous IL-33 reduces REG3A expression in epidermal keratinocytes. The reduction in REG3A is associated with lower levels of SHP-1, which normally inhibits TLR3-induced JNK2 phosphorylation, thereby increasing inflammation in skin wounds. To our knowledge, these findings show for the first time that REG3A can modulate specific cutaneous inflammatory responses and that the decrease in cutaneous REG3A exacerbates inflammation in diabetic skin wounds.