[Air Pollutant Spatiotemporal Evolution Characteristics and Effects on Human Health in Xi'an City].

Xi'an is the political, economic, and cultural center of northwest China with a developed industry. Air pollution incidents have brought great challenges to the high-quality development of the social economy. It is vital to study air pollution characteristics and clarify their impact on human health. In this study, we first analyzed the spatiotemporal variations in air pollutants in the study region from 2015 to 2021. Then, the air quality index (AQI), aggregate air quality index (AAQI), and health risk-based air quality index (HAQI) were used to assess health risks. Based on these, the AirQ2.2.3 model was used to quantify health effects. The results showed that the major pollutants were PM10, PM2.5, and O3. The main pollution characteristics of the study area were terrain characteristics and the mixed pollution of anthropogenic emissions. Compared to that of AQI, AAQI and HAQI showed better classification performance for pollution levels. HAQI revealed that approximately 80 % of the population was exposed to unhealthy air throughout the year in the study region. People were most exposed to unhealthy air in winter, followed by autumn and spring, and the least in summer. The AirQ2.2.3 model quantified the total mortality proportions attributable to PM2.5, PM10, SO2, CO, NO2, and O3, which were 0.99 %, 2.04 %, 0.41 %, 1.72 %, 8.76 %, and 3.67 %, respectively. The attributable proportion of mortality of the respiratory system and cardiovascular diseases was consistent with the change rule of total mortality.

Spatiotemporal evolution and multi-scale coupling effects of land-use carbon emissions and ecological environmental quality.

The coupling relationship between land-use carbon emissions (LCE) and ecological environmental quality (EEQ) is critical for regional sustainable development. Rapid urbanization promotes a notable increase in LCE, which imparts significant stress on EEQ. This study used land use and cover change (LUCC) and Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) data from the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) to evaluate LCE, applied a remote sensing ecological index (RSEI) model to calculate EEQ, and combined gravity and centroid movement trajectory models to analyze the spatiotemporal evolution characteristics of LCE and EEQ. Four-quadrant and coupling degree (CD) models were used to analyze the synergistic relationship and interaction intensity between LCE and EEQ based on three different scales of pixels, counties, and cities. The results show that: (1) LCE and EEQ exhibit clear spatial inequality distribution, and the total amount of LCE increased from 40.16 Mt. in 2000 to 131.99 Mt. in 2020; however, LCE has not yet reached peak carbon emissions. (2) From 2000 to 2020, cities with a strong correlation between LCE and EEQ showed an increasing trend, and the centroid of LCE moved sharply to Jiangxi during 2000-2005 and 2005-2010. (3) High-CD areas were primarily located in quadrant II, and low-CD areas in quadrant IV. The relationship between LCE and EEQ has improved over the past 21 years, and CD has been increasing. (4) The stability of the coupling results between LCE and EEQ was affected by different research scales; the larger the research scale is, the greater the change in the results. This study provides a scientific basis and practical scheme for LCE reduction, ecological environmental management, and regional sustainable development in the UAMRYR.

Spatiotemporal change in ecological quality and its influencing factors in the Dongjiangyuan region, China.

It is of great significance for regional ecological protection and sustainable development to quickly and effectively assess and monitor regional ecological quality and identify the factors that affect ecological quality. This paper constructs the Remote Sensing Ecological Index (RSEI) based on the Google Earth Engine (GEE) platform to analyze the spatial and temporal evolution of ecological quality in the Dongjiangyuan region from 2000 to 2020. An ecological quality trend analysis was conducted through the Theil-Sen median and Mann-Kendall tests, and the influencing factors were analyzed by using a geographically weighted regression (GWR) model. The results show that (1) the RSEI distribution can be divided into the spatiotemporal characteristics of "three highs and two lows," and the proportion of good and excellent RSEIs reached 70.78% in 2020. (2) The area with improved ecological quality covered 17.26% of the study area, while the area of degradation spanned 6.81%. The area with improved ecological quality was larger than that with degraded ecological quality because of the implementation of ecological restoration measures. (3) The global Moran's I index gradually decreased from 0.638 in 2000 to 0.478 in 2020, showing that the spatial aggregation of the RSEI became fragmented in the central and northern regions. (4) Both slope and distance from roads had positive effects on the RSEI, while population density and night-time light had negative effects on the RSEI. Precipitation and temperature had negative effects in most areas, especially in the southeastern study area. The long-term spatiotemporal assessment of ecological quality can not only help the construction and sustainable development of the region but also have reference significance for regional ecological management in China.

Primary Solitary Tuberculosis in the Hepatic Round Ligament Detected by 68Ga-FAPI PET/CT.

ABSTRACT: A 45-year-old woman recently complained of abdominal pain, poor appetite, and weight loss. Her serum ferritin, CA199, and CA242 levels were elevated. 68Ga-FAPI PET/CT revealed a subcapsular mass in the liver, which showed a significant FAPI uptake without other abnormal activity. Postoperative pathological examination confirmed tuberculosis in the hepatic round ligament.

Air pollutant spatiotemporal evolution characteristics and effects on human health in North China.

North China, the political, economic, and cultural center of China, has been greatly harmed by frequent air pollution incidents. Therefore, it is vital to study air pollution characteristics and clarify their impact on human health. In this study, we first analyzed the spatiotemporal variations of air pollutants (PM2.5, PM10, CO, SO2, NO2, and O3) in North China from 2016 to 2019. Then, the air quality index (AQI), aggregate air quality index (AAQI), and health risk based air quality index (HAQI) were used to assess health risks. Based on these, the AirQ2.2.3 model was used to quantify health effects. The results showed that the major pollutant in the cities surrounding Beijing was PM2.5, while PM10 dominated in distant cities. Annual concentrations decreased (except for O3), which is related to governmental emission reduction policies. However, O3 concentrations increased owing to the complex precursor emissions. The AQI underestimated air pollution, while the AAQI and HAQI were accurate; the latter indicated that 55% of the study region population was exposed to polluted air. The AirQ2.2.3 model quantified the total mortality proportions attributable to PM2.5, PM10, SO2, CO, NO2, and O3, which were 1.87%, 3.12%, 1.11%, 1.40%, 4.19%, and 2.52%, respectively. In high concentrations, PM10 and PM2.5 pose significant health risks. The health effects of SO2, NO2, CO, and O3 at lower concentrations were more obvious, indicating that the expected mortality rate due to low concentrations of some pollutants was much higher than that due to high concentrations of other pollutants.

Identification and validation of the prognostic value of cyclic GMP-AMP synthase-stimulator of interferon (cGAS-STING) related genes in gastric cancer.

The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway play a significant role in the production of inflammatory cytokines and type I interferons. This study aims to develop a cGAS-STING pathway-related genes (CSRs) prediction model to predict prognosis in gastric cancer (GC). In the present study, we used The Cancer Genome Atlas (TCGA), Gene Expression Omnibus databases (GEO), CIBERSORT and Tumor Immune Estimation Resource databases (TIMER). The risk model based on five hub genes (IFNB1, IFNA4, IL6, NFKB2, and TRIM25) was constructed to predict the overall survival (OS) of GC. Further univariate Cox regression (URC) and multivariate Cox regression (MCR) analyses revealed that this risk scoring model was an independent factor. The results were verified by GEO external validation set. Multiple immune pathways were assessed by Gene Set Enrichment Analysis (GSEA). TIMER analysis demonstrated that risk score strongly correlated with Macrophage, B cells and CD8 + T cells infiltration. In addition, through 'CIBERSORT' package, the higher levels of infiltration of T cell follicular assistance (P = 0.011), NK cells-activated (P = 0.034), and Dendritic cells resting (P = 0.033) exhibited in high-risk group. Kaplan-Meier (K-M) survival analysis illustrated T cells CD4 memory resting and T cells follicular helper infiltration correlated with overall survival (OS) of GC patients in TCGA and GEO databases. Altogether, the risk score model can be conveniently used to predict prognosis. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the GC immune microenvironment.Abbreviations:TCGA: The Cancer Genome Atlas databases; GEO: Gene Expression Omnibus databases; GC: Gastric cancer; CSRs: cGAS-STING pathway-related genes; DECSRs: Differential expressed cGAS-STING pathway-related genes; PCSRs: Prognosis related cGAS-STING pathway genes; URC: Univariate Cox regression analyses; MCR: Multivariate Cox regression analyses GSEA: Gene set enrichment analysis; TIIC: Tumor-infiltrating immune cell.

Spatiotemporal variations and driving factors of dust storm events in northern China based on high-temporal-resolution analysis of meteorological data (1960-2007).

Northern China is a significant source of dust source in Central Asia. Thus, high-resolution analysis of dust storms and comparison of dust sources in different regions of northern China are important to clarify the formation mechanism of East Asian dust storms and predict or even prevent such storms. Here, we analyzed spatiotemporal trends in dust storms that occurred in three main dust source regions during 1960-2007: Taklimakan Desert (western region [WR]), Badain Jaran and Tengger Deserts (middle region [MR]), and Otindag Sandy Land (eastern region [ER]). We analyzed daily dust storm frequency (DSF) at the 10-day scale (first [FTDM], middle [MTDM], and last [LTDM] 10 days of a month), and investigated the association of dust storm occurrences with meteorological factors. The 10-day DSF was greatest in the FTDM (accounting for 77.14% of monthly occurrences) in the WR, MTDM (45.85%) in the MR, and LTDM (72.12%) in the ER, showing a clear trend of movement from the WR to the ER. Temporal analysis of DSF revealed trend changes over time at annual and 10-day scales, with mutation points at 1985 and 2000. We applied single-factor and multiple-factor analyses to explore the driving mechanisms of DSF at the 10-day scale. Among single factors, a low wind-speed threshold, high solar radiation, and high evaporation were correlated with a high DSF, effectively explaining the variations in DSF at the 10-day scale; however, temperature, relative humidity, and precipitation poorly explained variations in DSF. Similarly, multiple-factor analysis using a classification and regression tree revealed that maximum wind speed was a major influencing factor of dust storm occurrence at the 10-day scale, followed by relative humidity, evaporation, and solar radiation; temperature and precipitation had weak influences. These findings help clarify the mechanisms of dust storm occurrence in East Asia.

Prediction of heavy metals in soils of an arid area based on multi-spectral data.

With the rapid and extensive development of industry and agriculture, the soil environment inevitably becomes contaminated with heavy metals, thus creating adverse environmental conditions for flora and fauna. The traditional methods for combining field sampling with laboratory analysis of soil heavy metals are limited not only because they are time-consuming and expensive, but also because they are unable to obtain adequate information about the spatial distribution characteristics of heavy metals in soil over a large area. Three hundred and ninety-four soil samples (Gobi and farmland) were collected in an arid area in Jiuquan in Northwest China and analyzed for elements concentrations. Based on these measured concentrations, as well as rapid and environmentally friendly remote sensing (multi-spectral data), stepwise multiple linear regression (SMLR) and partial least-squares regression (PLS) were combined to predict concentrations and distributions of heavy metals in the soils of the study area. Furthermore, laboratory data were used to assess the accuracy of the prediction results. Obtained results suggest that the SMLR and PLS models were able to predict the metals contents in the study area. The concentrations of Cr, Ni, V and Zn could be predicted by two regression models, while those of Cu and Mn were predicted more accurately when they were attached to the SMLR model. The spatial distribution of heavy metals derived from the two models is consistent with measured values, indicating that it is reasonable to predict the concentrations of heavy metals in the soil of the study area using the multi-spectral data.

Source apportionment of heavy metals in agricultural soil based on PMF: A case study in Hexi Corridor, northwest China.

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.

Spatio-temporal variability of particulate matter in the key part of Gansu Province, Western China.

To investigate the spatial and temporal behaviors of particulate matter in Lanzhou, Jinchang and Jiayuguan during 2014, the hourly concentrations of PM2.5 and PM10 were collected from the Ministry of Environmental Protection (MEP) in this study. The analysis indicated that the mean annual PM10 (PM2.5) concentrations during 2014 were 115 ± 52 µg/m3 (57 ± 28 µg/m3), 104 ± 75 µg/m3 (38 ± 22 µg/m3) and 114 ± 72 µg/m3 (32 ± 17 µg/m3) in Lanzhou, Jinchang and Jiayuguan, respectively, all of which exceeded the Chinese national ambient air quality II standards for PM. Higher values for both PM fractions were generally observed in spring and winter, and lower concentrations were found in summer and autumn. Besides, the trend of seasonal variation of particulate matter (PM) in each city monitoring site is consistent with the average of the corresponding cities. Anthropogenic activities along with the boundary layer height and wind scale contributed to diurnal variations in PM that varied bimodally (Lanzhou and Jinchang) or unimodally (Jiayuguan). With the arrival of dust events, the PM10 concentrations changed dramatically, and the PM10 concentrations during dust storm events were, respectively, 19, 43 and 17 times higher than the levels before dust events in Lanzhou, Jinchang and Jiayuguan. The ratios (PM2.5/PM10) were lowest, while the correlations were highest, indicating that dust events contributed more coarse than fine particles, and the sources of PM are similar during dust storms. The relationships between local meteorological parameters and PM concentrations suggest a clear association between the highest PM concentrations, with T ≤ 7 °C, and strong winds (3-4 scale). However, the effect of relative humidity is complicated, with more PM10 and PM2.5 exceedances being registered with a relative humidity of less than 40% and 40-60% in Lanzhou, while higher exceedances in Jinchang appeared at a relative humidity of 80-100%.

Galectin-1 induces invasion and the epithelial-mesenchymal transition in human gastric cancer cells via non-canonical activation of the hedgehog signaling pathway.

Galectin-1 (Gal-1) has been reported to be an independent prognostic indicator of poor survival in gastric cancer and overexpression of Gal-1 enhances the invasiveness of gastric cancer cells. However, the downstream mechanisms by which Gal-1 promotes invasion remains unclear. Moreover, the function of Gal-1 in the epithelial-mesenchymal transition (EMT) in gastric cancer has not yet been elucidated. In this study, we observed Gal-1 expression was upregulated and positively associated with metastasis and EMT markers in 162 human gastric cancer tissue specimens. In vitro studies showed Gal-1 induced invasion, the EMT phenotype and activated the non-canonical hedgehog (Hh) pathway in gastric cancer cell lines. Furthermore, our data revealed that Gal-1 modulated the non-canonical Hh pathway by increasing the transcription of glioma-associated oncogene-1 (Gli-1) via a Smoothened (SMO)-independent manner, and that upregulation of Gal-1 was strongly associated with gastric cancer metastasis. We conclude that Gal-1 promotes invasion and the EMT in gastric cancer cells via activation of the non-canonical Hh pathway, suggesting Gal-1 could represent a promising therapeutic target for the prevention and treatment of gastric cancer metastasis.

Galectin-1 from cancer-associated fibroblasts induces epithelial-mesenchymal transition through ß1 integrin-mediated upregulation of Gli1 in gastric cancer.

BACKGROUND: Gastric cancer (GC) is characterized by the excessive deposition of extracellular matrix, which is thought to contribute to this tumor's malignant behavior. Epithelial-mesenchymal transition (EMT) is regarded as a crucial contributing factor to cancer progression. Galectin-1 (Gal-1), a ß-galactoside-binding protein abundantly expressed in activated cancer-associated fibroblasts (CAFs), has been reported to be involved in GC progression and metastasis by binding to ß1 integrin, which, in turn, can bind to matrix proteins and activate intracellular cascades that mediate EMT. Increasing evidence suggests that abnormal activation of the hedgehog (Hh) signaling pathway enhances GC cell migration and invasion. The purpose of our study is to explore the role of Gal-1 in the GC progression and metastasis as well as the regulatory mechanism. METHODS: We hypothesized that Gal-1 binding to ß1 integrin would lead to paracrine signaling between CAFs and GC cells, mediating EMT by upregulating Gli1. Invasion and metastasis effects of the Gal-1 and Gli1 were evaluated using wound healing and invasion assay following transfection with mimics. Additionally, to facilitate the delineation of the role of the Hh signaling in GC, we monitored the expression level of associated proteins. We also evaluated the effects of ß1 integrin on these processes. Furthermore, Gal-1 and Gli1 expression in GC patient samples were examined by immunohistochemistry and western blot to determine the correlation between their expression and clinicopathologic characteristics. The Kaplan-Meier method and Cox proportional hazards model were used to analyze the relationship of expression with clinical outcomes. RESULTS: Gal-1 was found to induce EMT, GC cell migration and invasion. Further data showed that Gal-1 up-regulated Gli1 expression. ß1 integrin was responsible for Gal-1-induced Gli1 expression and EMT. In clinical GC tissue, it confirmed a positive relationship between Gal-1 and Gli1 expression. Importantly, their high expression is correlated to poor prognosis. CONCLUSION: Gal-1 from CAFs binds to a carbohydrate structure in ß1 integrin and plays an important role in the development of GC by inducing GC metastasis and EMT through targeting Gli1. This study highlights the potential therapeutic value of Gal-1 for suppression of GC metastasis.

Laparoscopic subtotal colectomy for synchronous triple colorectal cancer: A case report.

Synchronous colorectal cancers refer to the simultaneous occurrence of multiple colorectal tumors in a single patient, excluding any metastases from other organs. At present, radical surgery is considered the standard curative treatment; however, individualized surgical strategies depend on tumor location, the depth of invasion and the general health of the patient. In the present study, the case of a 52-year-old man who presented with a 2-month history of abdominal pain that was accompanied by intermittent hematochezia and weight loss is reported. The patient had no family history of cancer. Computed tomography (CT) of the abdomen revealed intestinal wall thickness in the transverse colon and volvulus in the hepatic flexure of colon. Colonoscopy identified 3 tumors: The first tumor was located in the descending colon with lumen stenosis ~60 cm from the anal verge, the second tumor was located in the hepatic flexure of the colon, and the third tumor was located in the sigmoid colon, 23 cm from the anal verge. Subsequently, laparoscopic subtotal colectomy was performed and all three tumors were removed, and the diagnosis was confirmed by histopathological examination. The patient did not undergo chemotherapy following surgery, due to personal reasons. Subsequent to 19 months of follow-up examinations using CT and colonoscopy every 6 months, the patient exhibited no signs of recurrence. Thus, laparoscopic subtotal colectomy represents an effective surgical approach for the treatment of synchronous colorectal cancer following imaging and endoscopic diagnosis.

Apoptosis and anergy of T cell induced by pancreatic stellate cells-derived galectin-1 in pancreatic cancer.

Galectin-1, a ß-galactoside-binding protein implicated in cancer cell immune privilege, was highly expressed in activated pancreatic stellate cells (PSCs). This study was designed to investigate the relationship between PSC-derived galectin-1 and tumor immunity in pancreatic cancer. Isolated PSCs were identified as normal pancreas cells (hNPSCs) or pancreatic cancer cells (hCaPSCs) by immunohistochemical staining for α-SMA and vimentin, and galectin-1 expression was evaluated by Western blotting and quantitative RT-PCR. Apoptosis, caspase activity, and cytokine production (IL-6, IL-10, TNF-ß, and IFN-γ) of T cells co-cultured with PSCs were evaluated, and immunohistochemical staining of galectin-1 was correlated with CD3 and clinicopathological variables in 66 pancreatic cancer and 10 normal pancreatic tissue samples. hCaPSCs exhibited higher galectin-1 expression than did hNPSCs, and hCaPSCs induced higher levels of apoptosis in T cells following co-culture. hCaPSCs activated caspase-9 and caspase-3 in the mitochondrial apoptotic pathway and stimulated secretion of Th2 cytokines (IL-6 and IL-10) but decreased secretion of Th1 cytokines (TNF-ß and IFN-γ), compared with hNPSCs. Immunohistochemical staining indicated that galectin-1 and CD3 were more highly expressed in pancreatic cancer tissue. Galectin-1 expression was highest in poorly differentiated pancreatic cancer cells and lowest in well-differentiated pancreatic cancer cells and was associated with tumor size, lymph node metastasis, differentiation, and UICC stage. However, CD3 expression showed the opposite trend and was highest in well-differentiated pancreatic cancer cells and was associated with tumor differentiation and UICC stage. High expression of galectin-1 was associated with short survival, as was low expression of CD3. hCaPSC-derived galectin-1 enhanced apoptosis and anergy of T cells in pancreatic cancer, which contributes to the immune escape of pancreatic cancer cells.