Comprehensive source identification and apportionment analysis of five heavy metals in soils in Wenzhou City, China.

The source identification and apportionment of heavy metals (HMs) is a vital issue for restoring contaminated soil. In this study, qualitative approaches [a finite mixture distribution model (FMDM) and raster-based principal components analysis (RB-PCA)] and a quantitative approach [positive matrix factorization (PMF)] were composed to identify and apportion the sources of five HMs (Cd, Hg, As, Pb, Cr) in Wenzhou City, China, using several crucial auxiliary variables. An initial ecological risk assessment suggested that the ecological risk level in the study area was generally considered low, with the greatest contamination contributions coming from Cd and Hg. The result of the FMDM showed that Cd and Pb fit a single log-normal distribution, Hg fit a double log-normal mixed distribution, and As and Cr presented a triple log-normal distribution. Each element was identified and separated from its natural or anthropogenic sources. A map of RB-PCA combined with an analysis of corresponding auxiliary variables suggested that the three main contribution sources in the entire study area were parental materials, industrial and agricultural mixed pollution, and mining exploration activities. Each element was discussed, using the PMF model, with regard to its quantitative contributions. Parental materials contributed to all elements (Cd, Hg, As, Pb, Cr) at 89.22%, 7.31%, 35.84%, 84.81% and 27.42%, respectively. Industrial emissions and agricultural inputs mixed pollution contributed 2.94%, 80.77%, 15.93%, 4.79%, and 25.63%, respectively. Mining activities contributed 7.84%,11.92%, 48.23%, 10.40% and 46.95%, respectively, to the five HMs. Such result could be used efficiently to generate scientific decisions and strategies in terms of decision-making on regulating HM pollution in soils.

Regulation of cancer progression by circRNA and functional proteins.

Circular RNAs (circRNAs) are closed back-splicing products of precursor mRNA in eukaryotes. Compared with linear mRNAs, circRNAs have a special structure and stable expression. A large number of studies have provided different regulatory mechanisms of circRNAs in tumors. Challenges exist in understanding the control of circRNAs because of their sequence overlap with linear mRNA. Here, we survey the most recent progress regarding the regulation of circRNA biogenesis by RNA-binding proteins, one of the vital functional proteins. Furthermore, substantial circRNAs exert compelling biological roles by acting as protein sponges, by being translated themselves or regulating posttranslational modifications of proteins. This review will help further explore more types of functional proteins that interact with circRNA in cancer and reveal other unknown mechanisms of circRNA regulation.

Current Status and Temporal Trend of Potentially Toxic Elements Pollution in Agricultural Soil in the Yangtze River Delta Region: A Meta-Analysis.

Potentially toxic elements (PTEs) pollution in the agricultural soil of China, especially in developed regions such as the Yangtze River Delta (YRD) in eastern China, has received increasing attention. However, there are few studies on the long-term assessment of soil pollution by PTEs over large regions. Therefore, in this study, a meta-analysis was conducted to evaluate the current state and temporal trend of PTEs pollution in the agricultural land of the Yangtze River Delta. Based on a review of 118 studies published between 1993 and 2020, the average concentrations of Cd, Hg, As, Pb, Cr, Cu, Zn, and Ni were found to be 0.25 mg kg-1, 0.14 mg kg-1, 8.14 mg kg-1, 32.32 mg kg-1, 68.84 mg kg-1, 32.58 mg kg-1, 92.35 mg kg-1, and 29.30 mg kg-1, respectively. Among these elements, only Cd and Hg showed significant accumulation compared with their background values. The eastern Yangtze River Delta showed a relatively high ecological risk due to intensive industrial activities. The contents of Cd, Pb, and Zn in soil showed an increasing trend from 1993 to 2000 and then showed a decreasing trend. The results obtained from this study will provide guidance for the prevention and control of soil pollution in the Yangtze River Delta.

Factors Related to Nurses' Knowledge and Attitudes Toward Pain in Hospitals in Low-Income Areas.

BACKGROUND: Effective pain management is closely related to nurses' knowledge and attitudes toward pain. Limited studies have been performed related to nurses' knowledge and attitudes toward pain in hospitals in low-income areas. AIMS: This study surveyed the knowledge and attitudes of nurses toward pain management in county hospitals from low-income areas in Hunan Province, China. SETTING AND PARTICIPANTS: The study included 4,668 registered nurses working in 48 county hospitals in low-income areas in China. METHODS: A cross-sectional study examined the knowledge and attitudes of nurses with regard to pain using the Chinese version of the Knowledge and Attitude Survey Regarding Pain (KASRP) via the WeChat application. RESULTS: The 4,668 registered nurses completed the survey; of these, 43.6% indicated they had never received continuing education for pain. The mean percentage score for KASRP was (40.3 ± 7.95), and none of the respondents achieved a percentage score of >80%. Further, of the 40 items, only two had a correct rate of >80%. Continuing pain education did not significantly affect KASRP. Multiple stepwise linear regression showed that education level, ethnicity, professional title, position, and department were independent influencing factors for KASRP scores. CONCLUSION: Almost all nurses in county hospitals of low-income areas had deficiencies in various aspects of pain management knowledge. Better educated nurses with higher professional title or management position, those from the Han ethnicity, and those from the oncology department had higher mean KASRP scores. Current continuing education programs for pain did not improve the pain management capability of the nurse. High-quality and standardized pain educational programs should be implemented to improve pain management.

Spatio-temporal variation and source changes of potentially toxic elements in soil on a typical plain of the Yangtze River Delta, China (2002-2012).

The spatio-temporal variation and temporal changes in the sources of Cr, Pb, Cd, Hg, and As in soil on the Hangzhou-Jiaxing-Huzhou (H-J-H) Plain were analysed based on 4,359 soil samples collected in 2002 and 2012. Geostatistical and spatial analysis methods were used to explore the spatio-temporal variation in the pollution levels and 'pollution hotspots' for potentially toxic elements (PTEs), and the positive matrix factor model was used to quantitatively appoint and analyse temporal changes in PTE sources. The results indicated that the PTE content in most parts of the survey area were at a safe level in both 2002 and 2012, but a clearly upward trend was detected for Cr, Pb, and Cd. Moreover the pollution index for Cr, Pb, Cd, and the Nemerow composite pollution index increased in the west but decreased in the east of the H-J-H Plain from 2002 to 2012. The pollution index for Hg and As presented the opposite spatial pattern. It is obvious that there have been changes in the spatial pattern of pollution hotspots for PTEs on the H-J-H Plain from 2002 to 2012. Four sources of PTEs in soil were quantitatively appointed. In 2002, 2012, the dominant sources of Cr, Cd, Hg, and As were soil parent materials, industrial activities, atmospheric deposition and agricultural inputs, respectively. The dominant source of Pb in the soil changed from traffic emissions to soil parent materials, indicating the benefit of banning the use of leaded gasoline in China. This study highlights the importance of monitoring soil environmental quality and highlights the significance of spatio-temporal variation in PTEs in suburban zones or transitional areas undergoing rapid industrialization and urbanization, like the H-J-H Plain.

Current status, spatial features, health risks, and potential driving factors of soil heavy metal pollution in China at province level.

In this study we systematically reviewed 1203 research papers published between 2008 and 2018 in China and recorded related data on eight kinds of soil heavy metals (Cr, Pb, Cd, Hg, As, Cu, Zn, and Ni). Based on that, the pollution levels, ecological risk and health risk caused by soil heavy metals were evaluated and the pollution hot spots and potential driving factors of different heavy metals in different provinces were also identified. Results indicated accumulation of heavy metals in soils of most provinces in China compared with background values. Consistent with previous findings, the most prevalent polluted heavy metals were Cd and Hg. Polluted regions are mainly located in central, southern and southwestern China. Hunan, Guangxi, Yunnan, and Guangdong provinces were the most polluted provinces. For the potential health risk caused by heavy metals pollution, children are more likely confront with non-carcinogenic risk than adults and seniors. And children in Hunan and Guangxi province were experiencing relatively larger non-carcinogenic risk. In addition, children in part of provinces were undergoing potentially carcinogenic risks due to soil heavy metals exposure. Furthermore, in our study the 31 provinces in mainland China were divided into six subsets according to corresponding potential driving factors for heavy metal accumulation. Our study provide more comprehensive and updated information for contributing to better soil management, soil remediation, and soil contamination control in China.

The Biogenesis, Biology, and Clinical Significance of Exosomal PD-L1 in Cancer.

The exosome serves as a trafficking vehicle for transport of programmed death-ligand 1 (PD-L1) into receptor cells. In tumor microenvironment, distant tumor cells can remotely attack activated T cells by exosomal PD-L1. Here, we summerize the biogenesis and transport process of exosomal PD-L1. Then, we focus on the cancer biology of exosomal PD-L1 in immunosuppression and the mechanism by which it inhibits T cells. Finally, we highlight the prospects of exosomal PD-L1 as a tumor biomarker and its significance in immunotherapy. In addition, we discuss the new challenges faced in researching and utilizing exosomal PD-L1. This review may shed light on the exosomal PD-L1 from the bench to the clinic. Exosomes serve as trafficking vehicles for transport of programmed death-ligand 1 (PD-L1) into receptor cells. In tumor microenvironment, distant tumor cells can remotely attack activated T cells through exosomal PD-L1. Here, we have summarized the biogenesis and transport of exosomal PD-L1. Next, we focused on the cancer biology of exosomal PD-L1 in immunosuppression and the mechanism by which it inhibits T cells. Finally, we highlighted the prospects of exosomal PD-L1 as a tumor biomarker and its significance in immunotherapy. In addition, we have discussed the new challenges faced in studying and utilizing exosomal PD-L1. This review may shed light on the translation of exosomal PD-L1 from bench to clinic.

Identification of the potential risk areas for soil heavy metal pollution based on the source-sink theory.

From the perspective of the mechanism of soil pollution, it is difficult to explain the process of predicting the spatial distributions of soil heavy metal pollution using traditional geostatistical methods at a regional scale. Furthermore, few methods are available to proactively identify potential risk areas for preventing soil contamination. In this study, we selected 13 environmental factors related to the accumulation of soil heavy metals based on the source-sink theory. Then, the fuzzy k-means method in combination with the random forest (RF) method was used to classify potential risk areas. The concentrations and spatial distributions of the heavy metals were well predicted by RF, and the average values of the root mean square error of the prediction and R2 were 4.84 mg kg-1 and 0.57, respectively. The results indicated that the soil pH, fine particulate matter, and proximity to polluting enterprises significantly influenced the heavy metal pollution in soils, and the environmental variables varied significantly across the identified subregions. This study provides a theoretical basis for the sustainable management and control of soil pollution at the regional scale.

LncRNA DNAJC3-AS1 Regulates Fatty Acid Synthase via the EGFR Pathway to Promote the Progression of Colorectal Cancer.

Colorectal cancer (CRC) is one of the most common cancers worldwide. Recent studies have shown that long non-coding RNAs (lncRNAs) are involved in tumorigenesis and the development of CRC. By constructing a differential lncRNA expression profile, we screened gene chips and found that DNAJC3-AS1 was highly expressed in CRC tissues and was associated with poor prognosis in patients with CRC. Further, we proved through assays such as wound healing, colony formation, and Cell Counting Kit-8 (CCK8) that interfering with DNAJC3-AS1 could reduce the proliferation, migration, and invasion of CRC cells. Mechanically, we found that DNAJC3-AS1 regulates fatty acid synthase to promote the progression of CRC via the epidermal growth factor receptor/phosphatidylinositol 3-kinase/protein kinase B/nuclear factor κB signaling pathway. Therefore, DNAJC3-AS1 may be a new target for the diagnosis and therapy of CRC.

LncRNA SLCO4A1-AS1 predicts poor prognosis and promotes proliferation and metastasis via the EGFR/MAPK pathway in colorectal cancer.

It is universally acknowledged that long non-coding RNAs (lncRNAs) involved in tumorigenesis in human cancers. However, the function and mechanism of many lncRNAs in colorectal cancer (CRC) remain unclear. By analyzing the two sets of CRC-related gene microarrays data, downloaded from the Gene Expression Omnibus (GEO) database and the lncRNA expression in a set of RNA sequencing data, we found that lncRNA SLCO4A1-AS1 was significantly upregulated in CRC tissues. We then collected CRC tissue samples and verified that SLCO4A1-AS1 is highly expressed in CRC tissues. Furthermore, SLCO4A1-AS1 was also upregulated in the CRC cell line. In situ hybridization results showed that high expression of SLCO4A1-AS1 was associated with poor prognosis in patients with CRC. Next, we found that SLCO4A1-AS1 promoted CRC cell proliferation, migration, and invasion. Results of western blotting assays show that its mechanism may relate to the epidermal growth factor receptor (EGFR)/mitogen-activated protein kinase (MAPK) pathway. Therefore, SLCO4A1-AS1 may be a potential biomarker for CRC prognosis and a new target for colorectal cancer therapy.

A methodological framework for identifying potential sources of soil heavy metal pollution based on machine learning: A case study in the Yangtze Delta, China.

It is a great challenge to identify the many and varied sources of soil heavy metal pollution. Often little information is available regarding the anthropogenic factors and enterprises that could potentially pollute soils. In this study we use freely available geographical data from a search engine in conjunction with machine learning methodologies to identify and classify potentially polluting enterprises in the Yangtze Delta, China. The data were classified into 31 separate and four integrated industry types by five different machine learning approaches. Multinomial naive Bayesian (NB) methods achieved an accuracy of 87% and Kappa coefficient of 0.82 and were used to classify the geographic data from more than 260,000 enterprises. The relationship between the different industry classes and measurements of soil cadmium (Cd) and mercury (Hg) concentrations was explored using bivariate local Moran's I analysis. The analysis revealed areas where different industry classes had led to soil pollution. In the case of Cd, elevated concentrations also occurred in some areas because of excessive fertilization and coal mining. This study provides a new approach to investigate the interaction between anthropogenic pollution and natural sources of soil heavy metals to inform pollution control and planning decisions regarding the location of industrial sites.

Organic carbon prediction in soil cores using VNIR and MIR techniques in an alpine landscape.

Diffuse reflectance spectroscopy (DRS), including visible and near-infrared (VNIR) and mid-infrared (MIR) radiation, is a rapid, accurate and cost-effective technique for estimating soil organic carbon (SOC). We examined 24 soil cores (0-100 cm) from the Sygera Mountains on the Qinghai-Tibet Plateau, considering field-moist intact VNIR, air-dried ground VNIR and air-dried ground MIR spectra at 5-cm intervals. Preprocessed spectra were used to predict the SOC in the soil cores using partial least squares regression (PLSR) and a support vector machine (SVM). The SVM models performed better with three predictors, with the ratio of performance to inter-quartile distance (RPIQ) and R 2 values typically exceeding 1.74 and 0.73, respectively. The SVM using the DRS technique indicated accurate predictive results of SOC in each core. The RPIQ values of the shrub meadow, forest and total dataset prediction using air-dried ground VNIR were 1.97, 2.68 and 1.99, respectively; the values using field-moist intact VNIR were 1.95, 2.07 and 1.76 and those using air-dried ground MIR were 1.78, 1.96 and 1.74, respectively. We conclude that the DRS technique is an efficient and rapid method for SOC prediction and has the potential for dynamic monitoring of SOC stock density on the Qinghai-Tibet Plateau.

Sexual function in cervical cancer patients: Psychometric properties and performance of a Chinese version of the Female Sexual Function Index.

PURPOSE: This study aimed to examine the psychometric properties and performance of a Chinese version of the Female Sexual Function Index (FSFI) among a sample of Chinese women with cervical cancer. METHODS: A cross-sectional survey design was used. The respondents included 215 women with cervical cancer in an oncology hospital in China. A translated Chinese version of the FSFI was used to investigate their sexual functioning. Psychometric testing included internal consistency reliability (Cronbach's alpha coefficient and item-total correlations), test-retest reliability, construct validity (principal component analysis via oblique rotation and confirmatory factor analysis), and variability (floor and ceiling effects). RESULTS: The mean score of the total scale was 20.65 ± 4.77. The Cronbach values were .94 for the total scale, .72-.90 for the domains. Test-retest correlation coefficients over 2-4 weeks were .84 (p < .05) for the total scale, .68-.83 for the subscales. Item-total correlation coefficients ranged between .47 and .83 (p < .05). A five-factor model was identified via principal component analysis and established by confirmatory factor analysis, including desire/arousal, lubrication, orgasm, satisfaction, and pain. There was no evidence of floor or ceiling effects. CONCLUSIONS: With good psychometric properties similar to its original English version, this Chinese version of the FSFI is demonstrated to be a reliable and valid instrument that can be used to assess sexual functioning of women with cervical cancer in China. Future research is still needed to confirm its psychometric properties and performance among a large sample.

In situ measurements of organic carbon in soil profiles using vis-NIR spectroscopy on the Qinghai-Tibet plateau.

We wish to estimate the amount of carbon (C) stored in the soil at high altitudes, for which there is little information. Collecting and transporting large numbers of soil samples from such terrain are difficult, and we have therefore evaluated the feasibility of scanning with visible near-infrared (vis-NIR) spectroscopy in situ for the rapid measurement of the soil in the field. We took 28 cores (≈1 m depth and 5 cm diameter) of soil at altitudes from 2900 to 4500 m in the Sygera Mountains on the Qinghai-Tibet Plateau, China. Spectra were acquired from fresh, vertical faces 5 × 5 cm in area from the centers of the cores to give 413 spectra in all. The raw spectra were pretreated by several methods to remove noise, and statistical models were built to predict of the organic C in the samples from the spectra by partial least-squares regression (PLSR) and least-squares support vector machine (LS-SVM). The bootstrap was used to assess the uncertainty of the predictions by the several combinations of pretreatment and models. The predictions by LS-SVM from the field spectra, for which R(2) = 0.81, the root-mean-square error RMSE = 8.40, and the ratio of the interquartile distance RPIQ = 2.66, were comparable to the PLSR predictions from the laboratory spectra (R(2) = 0.85, RMSE = 7.28, RPIQ = 3.09). We conclude that vis-NIR scanning in situ in the field is a sufficiently accurate rapid means of estimating the concentration of organic C in soil profiles in this high region and perhaps elsewhere.

[Characteristics of thermal infrared hyperspectra and prediction of sand content of sandy soil].

To explore the potential of thermal infrared hyperspecra for retrieving sand content in soil, the sandy soil was measured using a 102F Fourier Transform Infrared Spectroradiometer (FTIR), and the characteristics of sandy soil's emissivity spectra were discussed based on correlation analysis and principal component analysis. Moreover, the sand contents were predicted using two modeling methods: Partial least squares regression (PLSR) and principal component regression (PCR). The results show that the Reststrahlen feature (RF) of SiO2 is obvious in the emissivity spectra of sandy soil with two large asymmetrical absorption troughs near 8.13 and 9.17 microm and two small troughs in the region of 12-13 microm. Soil emissivity becomes lower when sand content increases, this trend is more evident especially in the regions of 8-9.5 microm and 9.5-10.4 microm of which correlation coefficients are above 0.65 and 0.5 respectively, and these two regions can account for 84.07% of total emissivity variance. Predictive precision varies significantly when sand content is predicted by different modeling methods or spectral variables. The PLSR model can achieve the highest predictive precision by using first-order derivative spectra, and it's RMSE of modeling and prediction is 0.45 and 0.53 respectively, and the R2, 0.9907 and 0.9836, which means that the thermal hyperspectra has promising potential for retrieving sand content in soil.

[Analysis of lead in soil with partial least square regression (PLS) method and field portable X-ray fluorescence(FPXRF) analyzer].

In the present study, soil samples were scanned by NITON XLt920 field portable X-ray fluorescence (FPXRF) analyzer, and the relationship between the X-ray fluorescence spectra and the concentration of Pb in soil was studied. For predicating the Pb concentration in soil, a partial least square regression model (PLS)was established with 6 optimal factors and two closely relevant electron volt ranges: 10.40-10.70 keV and 12.41-12.80 keV. After cross-calibration, the correlation coefficient of value predicted by PLS model against that measured by ICP was 0.9666, and the root mean square error of prediction (RMSEP) was 0.8732. Meanwhile, the univariate linear regression and multivariate linear regression models were also built with the correlation coefficient of 0.6805 and 0.7302, respectively. Obviously, the PLS method was better than the other two methods for predication. Comparing to the conventional approach of atomic absorption spectroscopy (AAS), FPXRF has the advantages of rapidness, non-destruction and relatively low cost with the acceptable accuracy. It would be a powerful tool to decide which sample is needs for further analysis.

[Identification of tea from different regions using X-ray fluorescence].

The existence of fake tea from non-origin seriously impacts on the credibility of the famous tea. A method was developed to identify tea from difference regions on the basis of the fact that the content of heavy metals in different origin tea is varied by using X-ray fluorescence technique and pattern recognition technique. Samples from different origins were grouped respectively, and their X-ray fluorescence spectra were acquired, and then the principal components of these spectral data were calculated, and the average of the principal components of each group was used as the center of each group. The Mahalanobis distance value between a sample and the center of a group were calculated, when the Mahalanobis distance value reached minimum, the sample was classed to current group, and in this way, a sample was identified. A Niton 792 portable X-ray spectrometer was used to class 120 tea samples from Anji, Jinhua, Hangzhou and Taizhou, in zhejiang province of China. It was found that the spectra between 3 and 13 KeV and the first 4 principal components give enough information for the identification of tea from different regions,and the rate of error was 4.2%.