The Indispensable Roles of GMDS and GMDS-AS1 in the Advancement of Cancer: Fucosylation, Signal Pathway and Molecular Pathogenesis.

Fucosylation is facilitated by converting GDP-mannose to GDP-4-keto-6-deoxymannose, which GDP-mannose 4,6-dehydratase, a crucial enzyme in the route, carries out. One of the most prevalent glycosylation alterations linked to cancer has reportedly been identified as fucosylation. There is mounting evidence that GMDS is intimately linked to the onset and spread of cancer. Furthermore, the significance of long-chain non-coding RNAs in the development and metastasis of cancer is becoming more well-recognized, and the regulatory mechanism of lncRNAs has emerged as a prominent area of study in the biological sciences. GMDS-AS1, an antisense RNA of GMDS, was discovered to have the potential to be an oncogene. We have acquired and analyzed relevant data to understand better how GMDS-AS1 and its lncRNA work physiologically and in tumorigenesis and progression. Additionally, we have looked into the possible effects of these molecules on cancer treatment approaches and patient outcomes. The physiological roles and putative processes of GMDS and lncRNA GMDS-AS1 throughout the development and progression of tumors have been assembled and examined. We also examined how these chemicals might affect patient prognosis and cancer therapy approaches. GMDS and GMDS-AS1 were determined to be research subjects by searching and gathering pertinent studies using the PubMed system. The analysis of these research articles demonstrated the close relationship between GMDS and GMDS-AS1 and tumorigenesis and the factors that influence them. GMDS plays a vital role in regulating fucosylation. The related antisense gene GMDS-AS1 affects the biological behaviors of cancer cells through multiple pathways, including the key processes of proliferation, migration, invasion, and apoptosis, providing potential biomarkers and therapeutic targets for cancer treatment and prognosis assessment.

The Pivotal Function of SLC16A1 and SLC16A1-AS1 in Cancer Progress: Molecular Pathogenesis and Prognosis.

More than 300 membranes make up the SLC family of transporters, utilizing an ion gradient or electrochemical potential difference to move their substrates across biological membranes. The SLC16 gene family contains fourteen members. Proton-linked transportation of monocarboxylates can be promoted by the transporters MCT1, which the SLC16A1 gene family encodes. Glycolysis is constitutively up-regulated in cancer cells, and the amount of lactate produced as a result is correlated with prognosis. Further speaking, SLC16A1 plays an essential role in controlling the growth and spread of tumors, according to mounting evidence. Additionally, LncRNAs are the collective term for all genes that produce RNA transcripts longer than 200 nucleotides but do not convert into proteins. It has steadily developed into a hub for research, offering an innovative approach to tumor study as technology related to molecular biology advances. The growing study has uncovered SLC16A1-AS1, an RNA that acts as an antisense to SLC16A1, which is erroneously expressed in various types of cancers. Therefore, we compiled the most recent information on the physiological functions and underlying processes of SLC16A1 and the LncRNA SLC16A1-AS1 during tumor development to explore their impact on cancer treatment and prognosis. We compiled the most recent information on the physiological functions and underlying processes of SLC16A1 and the LncRNA SLC16A1-AS1 during tumor development to explore their impact on cancer treatment and prognosis. Relevant studies were retrieved and collected through the PubMed system. After determining SLC16A1 and SLC16A1-AS1 as the research object, we found a close relationship between SLC16A1 and tumorigenesis as well as the influencing factors through the analysis of the research articles. SLC16A1 regulates lactate chemotaxis while uncovering SLC16A1- as1 as an antisense RNA acting through multiple pathways; they affect the metabolism of tumor cells and have an impact on the prognosis of patients with various cancers.

In defense of local descriptor-based few-shot object detection.

State-of-the-art image object detection computational models require an intensive parameter fine-tuning stage (using deep convolution network, etc). with tens or hundreds of training examples. In contrast, human intelligence can robustly learn a new concept from just a few instances (i.e., few-shot detection). The distinctive perception mechanisms between these two families of systems enlighten us to revisit classical handcraft local descriptors (e.g., SIFT, HOG, etc.) as well as non-parametric visual models, which innately require no learning/training phase. Herein, we claim that the inferior performance of these local descriptors mainly results from a lack of global structure sense. To address this issue, we refine local descriptors with spatial contextual attention of neighbor affinities and then embed the local descriptors into discriminative subspace guided by Kernel-InfoNCE loss. Differing from conventional quantization of local descriptors in high-dimensional feature space or isometric dimension reduction, we actually seek a brain-inspired few-shot feature representation for the object manifold, which combines data-independent primitive representation and semantic context learning and thus helps with generalization. The obtained embeddings as pattern vectors/tensors permit us an accelerated but non-parametric visual similarity computation as the decision rule for final detection. Our approach to few-shot object detection is nearly learning-free, and experiments on remote sensing imageries (approximate 2-D affine space) confirm the efficacy of our model.

PeNet: A feature excitation learning approach to advertisement click-through rate prediction.

Since the physical meaning of the fields of the dataset is unknown, we have to use the feature interaction method to select the correlated features and exclude uncorrelated features. The current state-of-the-art methods employ various methods based on feature interaction to predict advertisement Click-Through Rate (CTR); however, the feature interaction based on potential new feature mining is rarely considered, which can provide effective assistance for feature interaction. This motivates us to investigate methods that combine potential new features and feature interactions. Thus, we propose a potential feature excitation learning network (PeNet), which is a neural network model based on feature combination and feature interaction. In PeNet, we treat the row compression and column compression of the original feature matrix as potential new features, and proposed the excitation learning mechanism that is a weighted mechanism based on residual principle. Through this excitation learning mechanism, the original embedded features and potential new features are subjected to weighted interaction based on the residual principle. Moreover, a deep neural network is exploited to iteratively learn and iteratively combine features. The excitation learning structure of PeNet neural network is well demonstrated in this paper, that is, the control flow of embedding, compression, excitation and output, which further strengthens the correlated features and weakens the uncorrelated features by compressing and expanding the features. Experimental results on multiple benchmark datasets indicate the PeNet as a general-purpose plug-in has more superior performance and better efficiency than previous state-of-the-art methods.

Comparison of the surgical outcomes of endoscopic dacryocystorhinostomy in chronic dacryocystitis with or without previous bicanalicular silicone tube intubation.

AIMS: To compare the outcomes of endoscopic dacryocystorhinostomy (En-DCR) in chronic dacryocystitis (CD) with or without previous bicanalicular silicone tube intubation (BSTI), and investigate whether previous BSTI influenced postoperative outcomes. METHODS: We conducted a retrospective review of medical records of CD patients (group A) who had previously undergone BSTI for nasolacrimal duct stenosis and an age- and sex-matched control group of CD patients (group B) without previous intubation receiving En-DCR from November 2017 to January 2022. Sixty-one patients (61 eyes) were included in group A and age- and sex-matched 122 patients (122 eyes) in group B. Dacryocystic parameters were measured by computed tomography-dacryocystography and surgical findings were recorded during surgeries. The surgical success rates of the two groups were compared at 12 months post-operation. RESULTS: The mean horizontal, sagittal, and vertical lengths were 6.06 ± 1.24, 6.03 ± 1.44, and 8.05 ± 2.00 mm, respectively, in group A and 6.33 ± 1.25, 6.26 ± 1.19, and 10.40 ± 2.45 mm, respectively, in group B. There were no differences in the horizontal or sagittal parameters between the two groups. The vertical parameter in group A was significantly lower than that in group B. Scar formation in the sac was observed in 54 patients in group A but was absent in group B. At 12 months postoperatively, the anatomical and functional success rates were 88.52 % and 85.25 %, respectively, in group A and 92.62 % and 89.34 %, respectively, in group B, with no difference between the two groups. CONCLUSION: Previous BSTI reduced dacryocyst vertical parameter and caused dacryocyst scar formation but did not affect postoperative En-DCR efficacy.

Goats with low levels of AAV antibody may serve as candidates for large animal gene therapy.

AAV vector-mediated gene therapy has been proposed as a feasible strategy for several eye diseases. However, AAV antibodies in the serum prior to treatment hinder the transduction efficiency and thus the therapeutic effect. Therefore, it is necessary to evaluate AAV antibodies in the serum before gene therapy. As large animals, goats are more closely related to humans than rodents and more economically available than nonhuman primates. Here, we first evaluated the AAV2 antibody serum level in rhesus monkeys before AAV injection. Then, we optimized a cell-based neutralizing antibody assay for detecting AAV antibodies in the serum of Saanen goats and evaluated the consistency of the cell-based neutralizing antibody assay and ELISA for goat serum antibody evaluation. The cell-based neutralizing antibody assay showed that the percentage of macaques with low antibody levels was 42.86%; however, there were no macaques with low antibody levels when the serum was evaluated by ELISA. The proportion of goats with low antibody levels was 56.67% according to the neutralizing antibody assay and 33. 33% according to the ELISA, and McNemar's test showed that the results of the two assays were not significantly different (P = 0.754), but that their consistency is poor (Kappa = 0.286, P = 0.114). Moreover, longitudinal evaluation of serum antibodies before and after intravitreal injection of AAV2 in goats revealed that the level of AAV antibodies increased and transduction inhibition subsequently increased, as reported in humans, indicating that transduction inhibition should be taken into account at different stages of gene therapy. In summary, starting with an evaluation of monkey serum antibodies, we optimized a detection method of goat serum antibodies, providing an alternative large animal model for gene therapy, and our serum antibody measurement method may be applied to other large animals.

Reducing the Risk of Benthic Algae Outbreaks by Regulating the Flow Velocity in a Simulated South-North Water Diversion Open Channel.

The reduction in open-channel flow velocity due to China's South-to-North Water Diversion Project (SNP) increases the risk of benthic algal community blooms resulting in drinking water safety issues. Consequently, it has attracted attention from all walks of life. However, regulatory measures to mitigate the risk of algal blooms and the main risk-causing factors are unclear. This study simulated the river ecosystem of the SNP channel through water diversion. Simulated gradient-increasing river flow velocity affects environmental factors and benthic algal alterations, and can be used to explore the feasibility of regulating the flow velocity to reduce the risk of algal blooms. We found that the algal biomasses in the velocity environments of 0.211 and 0.418 m/s decreased by 30.19% and 39.88%, respectively. Community structure alterations from diatoms to filamentous green algae were 75.56% and 87.53%, respectively. We observed significant differences in biodiversity, especially in terms of richness and evenness. The α diversity index of a species is influenced by physical and chemical environmental factors (especially flow velocity). Our study revealed that flow velocity is the main factor affecting the growth and outbreak of benthic algae. The risk of algal blooms in open channels can be effectively mitigated by regulating the flow velocity. This provides a theoretical basis for ensuring the water safety of large-scale water conservancy projects.

The Dual Functions of Non-Coding RNA CRNDE in Different Tumors.

Long non-coding RNA has attracted the interest of researchers as a relevant factor that can influence human cancers. As an oncogene and suppressor gene, it has numerous pathways and is closely related to the pathophysiology of human diseases. Meanwhile, it may become a novel treatment option and target for tumor treatment. CRNDE is the gene symbol for Colorectal Neoplasia Differentially Expressed (non-protein-coding) since it was found to be considerably higher in colorectal cancer when it was first discovered. It's transcribed from human chromosome 16. Many studies have shown that it is intimately linked to the etiology of many tumors and malignancies. According to the paper, the biological function and pathophysiological mechanism of CRNDE in tumors have been studied extensively in recent years. PubMed served as an essential platform for conducting literature searches and related analyses. CRNDE, a long non-coding RNA closely related to tumors, was highly expressed in many tumor cells. There were various underlying mechanisms affecting the progression of CRNDE-regulated tumorigenesis, including hepatocellular carcinoma, gastric cancer, prostate carcinoma, oral squamous cell carcinoma, breast cancer, thyroid cancer, myeloma, leukemia, melanoma, colorectal cancer, glioblastoma, osteosarcoma, cervical cancer, intrahepatic cholangiocarcinoma, nonsmall cell lung cancer, hepatoblastoma cell tumor, abdominal aortic aneurysm, nasopharyngeal carcinoma, bladder cancer, Wilms tumor, medulloblastoma, pancreatic cancer, gallbladder cancer, ovarian cancer, and renal cell carcinoma. CRNDE is involved in the processes of proliferation, migration, invasion, and inhibition of apoptosis of various cancer cells.

The microbial community and functional indicators response to flow restoration in gradient in a simulated water flume.

Flow reduction has greatly affected the river ecological systems, and it has attracted much attention. However, less attention has been paid to response to flow restoration, especially flow restoration in gradient. Flow regime of rivers may affect river functional indicators and microbial community structure. This study simulated the ecological restoration of the flow-reduced river reach by gradiently controlling the water flow and explores the ecological response of environmental functional indicators and microbial community structure to the water flow. The results showed that gross primary productivity (GPP), ecosystem respiration rate (ER) and some water quality indices such as chemical oxygen demand, total nitrogen, and total phosphorus (TP), exhibited positive ecological responses to flow restoration in gradient. GPP and ER increased by 600.1% and 500.2%, respectively. The alpha diversity indices of the microbial community increased significantly with a flow gradient restoration. Thereinto, Shannon, Simpson, Chao1, and Ace indices, respectively, increased by 16.4%, 5.6%, 8.6%, and 6.2%. Canonical correspondence analysis indicated that water flow, Dissolved oxygen and TP were the main influencing factors for changes in bacterial community structure. Microbial community structure and composition present a positive ecological response to flow restoration in gradient. This study reveals that the main variable in the restoration of the flow-reduced river reach is the flow discharge, and it provides a feasible scheme for its ecological restoration.

B-Site Fe/Re Cation-Ordering Control and Its Influence on the Magnetic Properties of Sr2FeReO6 Oxide Powders.

Double-perovskite oxide Sr2FeReO6 (SFRO) powders have promising applications in spintronics due to their half-metallicity and high Curie temperature. However, their magnetic properties suffer from the existence of anti-site defects (ASDs). Here, we report on the synthesis of SFRO powders by the sol-gel process. The B-site cationic ordering degree (η) and its influence on magnetic properties are investigated. The results demonstrate that the η value is well controlled by the annealing temperature, which is as high as 85% when annealing at 1100 °C. However, the annealing atmospheres (e.g., N2 or Ar) have little effect on the η value. At room temperature, the SFRO powders crystallize in a tetragonal crystal structure (space group I4/m). They have a relatively uniform morphology and the molar ratios of Sr, Fe, and Re elements are close to 2:1:1. XPS spectra identified that Sr, Fe, and Re elements presented as Sr2+, Fe3+, and Re5+ ions, respectively, and the O element presented as O2-. The SFRO samples annealed at 1100 °C in N2, exhibiting the highest saturation magnetization (MS = 2.61 µB/f.u. at 2 K), which was ascribed to their smallest ASD content (7.45%) with an anti-phase boundary-like morphology compared to those annealed at 1000 °C (ASDs = 10.7%) or 1200 °C (ASDs = 10.95%).

A new classification network for diagnosing Alzheimer's disease in class-imbalance MRI datasets.

Automatic identification of Alzheimer's Disease (AD) through magnetic resonance imaging (MRI) data can effectively assist to doctors diagnose and treat Alzheimer's. Current methods improve the accuracy of AD recognition, but they are insufficient to address the challenge of small interclass and large intraclass differences. Some studies attempt to embed patch-level structure in neural networks which enhance pathologic details, but the enormous size and time complexity render these methods unfavorable. Furthermore, several self-attention mechanisms fail to provide contextual information to represent discriminative regions, which limits the performance of these classifiers. In addition, the current loss function is adversely affected by outliers of class imbalance and may fall into local optimal values. Therefore, we propose a 3D Residual RepVGG Attention network (ResRepANet) stacked with several lightweight blocks to identify the MRI of brain disease, which can also trade off accuracy and flexibility. Specifically, we propose a Non-local Context Spatial Attention block (NCSA) and embed it in our proposed ResRepANet, which aggregates global contextual information in spatial features to improve semantic relevance in discriminative regions. In addition, in order to reduce the influence of outliers, we propose a Gradient Density Multiple-weighting Mechanism (GDMM) to automatically adjust the weights of each MRI image via a normalizing gradient norm. Experiments are conducted on datasets from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Australian Imaging, Biomarker and Lifestyle Flagship Study of Aging (AIBL). Experiments on both datasets show that the accuracy, sensitivity, specificity, and Area Under the Curve are consistently better than for state-of-the-art methods.

Few-Shot Text Classification with Global-Local Feature Information.

Meta-learning frameworks have been proposed to generalize machine learning models for domain adaptation without sufficient label data in computer vision. However, text classification with meta-learning is less investigated. In this paper, we propose SumFS to find global top-ranked sentences by extractive summary and improve the local vocabulary category features. The SumFS consists of three modules: (1) an unsupervised text summarizer that removes redundant information; (2) a weighting generator that associates feature words with attention scores to weight the lexical representations of words; (3) a regular meta-learning framework that trains with limited labeled data using a ridge regression classifier. In addition, a marine news dataset was established with limited label data. The performance of the algorithm was tested on THUCnews, Fudan, and marine news datasets. Experiments show that the SumFS can maintain or even improve accuracy while reducing input features. Moreover, the training time of each epoch is reduced by more than 50%.

Determining Critical Thresholds of Environmental Flow Restoration Based on Planktonic Index of Biotic Integrity (P-IBI): A Case Study in the Typical Tributaries of Poyang Lake.

Hydropower construction and climate change have aggravated river hydrological changes, which have reduced the water flow regime in the Ruhe River Basin. The reduced flow of the river seriously affected the water supply of nearby residents and the operation of the river ecosystem. Therefore, in order to alleviate the contradiction between water use for hydropower facilities and environmental water use, the urgent need is to explore the ecological flow-threshold of rivers. This study took the Fuhe River Basin as the research object, and summarized the monitoring data of eight hydrological stations from recent decades. Based on this, we explored the response law of P-IBI and flow, a tool to quickly measure the health of the ecosystem. Through the response relationship between alterations in environmental factors of the river and phytoplankton index of biotic integrity (P-IBI), it was determined that environmental flow was the dominant influencing factor of P-IBI. According to P-IBI, the threshold of environmental discharge in the Fuhe River was limited to 273~826.8 m3/s. This study established a regulatory framework for the river flow of large rivers by constructing P-IBI and determining the critical thresholds of environmental flow by constraining the constitution. These results provide a theoretical basis for better planning and improvement of river ecosystem restoration and river utilization.

Microbial community structure characteristics among different karst aquifer systems, and its potential role in modifying hydraulic properties of karst aquifers.

Little is known about how microbial activity affects the hydraulic properties of karst aquifers. To explore the potential impacts of microbial activity on the hydraulic properties of karst aquifers, microbiological analysis, heat tracer, isotope (dissolved inorganic carbon isotope, δ13CDIC) and aqueous geochemical analyses were conducted at six monitoring wells in Northern Guangdong Province, China. Greater hydraulic conductivity corresponded to a low temperature gradient to an extent; the temperature gradient in karst groundwater aquifers can reflect the degree of dissolution. Higher HCO3 - concentrations coupled with lower d-excess and pH values at B2 and B6 reflect potential microbial activity (e.g., Sulfuricurvum kujiense) causing carbonate dissolution. Microbial activity or the input of anthropogenic acids, as evidenced by significantly more positive δ13CDIC values, potentially affect carbonate dissolution in deep karst aquifers, which eventually alters hydraulic properties of karst aquifer. However, more direct evidence is needed to quantify the effects of microbial activity on carbonate dissolution in karst aquifers.

Quantifying the impacts of anthropogenic activity on chemical weathering based on source identification of hydrochemistry: the Liuxi river basin, southern China.

The impact of anthropogenic activity on chemical weathering is still an open and significant topic that requires clarification to improve the understanding of watershed evolution. We analyzed river water and rainwater samples to characterize the variation in hydrochemical characteristics and influencing factors. Samples were taken from the Liuxi River Basin (LRB), the only local drinking water supply for Guangzhou, and we studied geochemical parameters, major ions, and Si concentrations. Moreover, elemental ratios of end-members were determined and a modified-forward model was constructed to identify ion sources and estimate the chemical weathering rate (CWR) and anthropogenic input rate (AIR). Finally, we quantified the impacts of anthropogenic activity on the chemical weathering process. The results showed that the dominant hydrochemical type of river water was identified as HCO3-Ca, and rock weathering was the main contributor to river Na+, Mg2+, Ca2+ and HCO3-, whereas anthropogenic activity contributed the most to K+, Cl-, SO42-, and NO3-. The relatively high silicate weathering rate (SWR) (17.8-18.4 t per km2 per year) and AIR (37.8-60.3 t per km2 per year) were mainly attributed to erosion by nitric and sulfuric acid. The contribution rate of these acids to CWR could be regarded as a proxy quantifying the impact of anthropogenic activity on the chemical weathering process. This accounted for approximately 30% of the total SWR in the LRB. Our results demonstrate the effectiveness of hydrochemical source identification for quantifying the impacts of anthropogenic activity on chemical weathering.

Characteristics, Sources, and Risks of Polycyclic Aromatic Hydrocarbons in Topsoil and Surface Water from the Liuxi River Basin, South China.

The concentrations, composition, sources, and risks of polycyclic aromatic hydrocarbons (PAHs) in topsoil and surface water of the Liuxi River basin, south China were analyzed in this study. The total concentrations of 16 PAHs ranged from 296.26 to 888.14 ng/g in topsoil and from 156.73 to 422.03 ng/L in surface water, indicating mild pollution. The PAHs in topsoil exhibited an even spatial distribution, suggesting that they originated primarily from dry and wet deposition of transported pollutants. The concentration of PAHs in surface water did not differ significantly geographically, but the concentrations of total, three-, and four-ring PAHs were significantly lower in the Liuxi River than in its tributaries. Three- and two-ring PAHs predominated in topsoil and surface water, respectively. A correlation analysis suggested that the total organic carbon content and pH exerted a negligible effect on the spatial distribution of PAHs in topsoil, and they may have common sources. Fossil fuel combustion (particularly vehicle emissions) and coking production were the dominant sources of PAHs in topsoil, whereas those in surface water were derived from a variety of sources. The total toxic equivalent concentrations of 16 PAHs in topsoil ranged from 3.73 to 105.66 ng/g (mean, 30.93 ng/g), suggesting that exposure to the basin's topsoil does not pose a risk to the environment or public health according to the Canadian soil quality guidelines. A risk assessment revealed that the total PAH concentrations in surface water posed a low ecological risk.

Seasonal characteristics of chemical compositions and sources identification of PM2.5 in Zhuhai, China.

Fine particulate matter is associated with adverse health effects, but exactly which characteristics of PM2.5 are responsible for this is still widely debated. We evaluated seasonal dynamics of the composition and chemical characteristics of PM2.5 in Zhuhai, China. PM2.5 characteristics at five selected sites within Zhuhai city were analyzed. Sampling began on January 10, 2015, and was conducted for 1 year. The ambient mass concentration, carbon content (organic and elemental carbon, OC and EC), level of inorganic ions, and major chemical composition of PM2.5 were also determined. Average concentrations of PM2.5 were lower than the National Ambient Air Quality Standard (NAAQS) 24-h average of 65 µg/m3. The daily PM2.5 concentration in Zhuhai city exhibited clear seasonal dynamics, with higher daily PM2.5 concentrations in autumn and winter than in spring and summer. Carbon species (OC and EC) and water-soluble ions were the primary components of the PM2.5 fraction of particles. Apart from OC and EC, chemical species in PM2.5 were mainly composed of NH4+ and SO42-. There was a marked difference between the summer and winter periods: the concentrations of OC and EC in winter were roughly 3.4 and 4.0 times than those in summer, while NH4+, SO42-, NO3-, and Na+ were 3.2, 4.5, 28.0, and 5.7 times higher in winter than those in summer, respectively. The results of chemical analysis were consistent with three sources dominating PM2.5: coal combustion, biomass burning, and vehicle exhaust; road dust and construction; and from reaction of HCl and HNO3 with NH3 to form NH4Cl and NH4NO3. However, additional work is needed to improve the mass balance and to obtain the source profiles necessary to use these data for source apportionment.

Contamination, potential mobility, and origins of lead in sediment cores from the Shima River, south China.

Identifying contamination sources of environmental media and revealing their changing trends over time is useful for regional contamination control and environmental improvements. Four sediment cores (S1-S4) were collected from the Shima River to determine lead (Pb) concentrations, geochemical fractions and isotopic compositions, as well as the geochronology of core S3. The results show that Pb concentrations decreased from the upper and middle reach sites (means: 57.6, 95.9, and 97.6 mg kg-1, respectively) to the lower reach site (43.8 mg kg-1), resulting in a minimal to moderate enrichment in the sediments; enrichment increased due to anthropogenic Pb inputs at the river middle reach site since the 1990s. Sediment Pb in the geochemical fractions followed a decreasing order of reducible (47.3%) > residual (37.8%) > oxidizable (11.2%) > acid-soluble fraction (3.68%), exhibiting high mobility, further verifying the anthropogenic inputs. A descending trend in the 206Pb/207Pb ratio of the top sediments was the result of anthropogenic activities. In the present study, coal combustion, which was the major anthropogenic Pb source determined by its isotopic composition, contributed significantly (means: 18.4-60.6%) to sediment Pb based on a three end-members model. Less of a contribution (0-10.6%) was derived from vehicle exhaust. The increasing trend in the coal contribution was in accordance with that of the coal consumption in the study area. These results suggest that Pb contamination resulting from coal combustion has grown to become a major environmental issue in the study area.

Co/Fe-bimetallic organic framework-derived carbon-incorporated cobalt-ferric mixed metal phosphide as a highly efficient photocatalyst under visible light.

A new bimetallic Co/Fe-MOF was synthesized and phosphatized to produce a visible-light-active Co/Fe binary metal phosphide embedded in a mesoporous carbon matrix (denoted by CoP/Fe2P@mC). The results of X-ray diffraction and photoelectron spectroscopy, scanning electron microscopy, and transmission electron microscopy reveal the formation of CoP and Fe2P nanoparticles together with the Co and Fe metallic state. Combining the high electron-hole separation rate of Fe2P@mC, fast electron transfer of CoP@mC, and the strong adsorption of mesoporous carbon, the as-prepared CoP/Fe2P@mC catalyst exhibits substantially enhanced photocatalytic activity toward rhodamine B (RhB) degradation under visible light irradiation. Visible light harvesting efficiency is enhanced by the suitable bandgap structure of the CoP/Fe2P@mC photocatalyst. Moreover, the possible photocatalytic mechanism of CoP/Fe2P@mC toward RhB degradation was proposed on the basis of radical trapping and electron spin resonance results. This finding illustrates a potential utilization of bimetallic MOF-derived metal phosphide as a photocatalyst to remove dye pollutants in the environment.

Identification of the dominant hydrogeochemical processes and characterization of potential contaminants in groundwater in Qingyuan, China, by multivariate statistical analysis.

In karst areas, groundwater is an important water source for drinking and irrigation purposes; however, karst aquifers are vulnerable and recovery from damage is difficult. We collected surface water (pond and river water) and groundwater (hand-pump well, dug well, and borehole water) samples in Qingyuan city, China, to determine the major chemicals in the water with the primary goals of evaluating the geochemical composition, identifying the geochemical processes governing the water chemistry, and identifying the probable sources of potential contaminants in shallow and deep groundwater in the study area. The results revealed marked differences in water chemistry between shallow and deep groundwater. The groundwater composition was largely controlled by rock-water interactions, particularly the dissolution of evaporite minerals (e.g., calcite, gypsum, and anhydrite), and ion exchange processes were important drivers of the chemical compositions of groundwater in the study area. Moreover, in shallow and deep groundwater, Mg2+ and SO4 2- concentrations were increased due to the long residence time of deep groundwater, while K+ and Na+ concentrations were decreased due to anthropogenic input. Finally, factor analysis of the major and trace elements differentiated between anthropogenic and geogenic sources of potential contaminants in karst aquifers.