Anthropogenic gadolinium contaminations in the marine environment and its ecological implications.

Due to the widespread application in medicine and industry of anthropogenic gadolinium (Gdanth), the widespread of Gd anomaly in surface water has leading to disruption of the natural Gd geochemical cycle. However, challenges related to the identification and quantification of Gdanth, assessment of its impacts on marine ecosystems, and exploration of strategies for mitigating its adverse effects still exist. Meanwhile, as the major source of the Gdanth, the environmental geochemical behavior of Gd-based contrast agents (GBCAs), which are used in medical diagnostics in magnetic resonance imaging (MRI), are still poorly understood. In this review, we 1) analyzed Gd anomalies in samples from published literature worldwide, confirmed their prevalence (81.25% for sea and lake water, 72.73% for river water), 2) demonstrated that the third-order polynomial method is the preferred approach for the detection of Gdanth in surface seawater, 3) outlined the species and applications of Gdanth and its impacts on marine environment, 4) explored the process of GBCAs influx into the ocean and demonstrated the concentration of Gdanth in coral samples was mainly affected by terrestrial input GBCAs (63.75%) through Pearson correlation analysis and principle component analysis, 5) proposed effective management strategies for GBCAs at all stages from production to release into the ocean, 6) formulated an expectation for future research on marine Gdanth.

Multi-omics comprehensive analysis reveals the predictive value of N6-methyladenosine- related genes in prognosis and immune escape of bladder cancer.

BACKGROUND: N6-methyladenosine (m6A) is the most frequent RNA modification in mammals, and its role in bladder cancer (BC) remains rarely revealed. OBJECTIVE: To predict the value of m6A-related genes in prognosis and immunity in BC. METHODS: We performed multiple omics analysis of 618 TCGA and GEO patients and used principal component analysis (PCA) to calculate the m6A score for BC patients. RESULTS: We described the multiple omics status of 23 m6A methylation-related genes (MRGs), and four m6A clusters were identified, which showed significant differences in immune infiltration and biological pathways. Next, we intersected the differential genes among m6A clusters, and 11 survival-related genes were identified, which were used to calculate the m6A score for the patients. We found that the high-score (HS) group showed lower tumor mutation burden (TMB) and TP53 mutations and better prognosis than the low-score (LS) group. Lower immune infiltration, higher expression of PD-L1, PD-1, and CTLA4, and higher immune dysfunction and immune exclusion scores were identified in the LS group, suggesting a higher possibility of immune escape. Finally, the experimental verification shows that the m6A related genes, such as IGFBP1, plays an important role in the growth and metastasis of bladder cancer. CONCLUSIONS: These findings revealed the important roles of m6A MRGs in predicting prognosis, TMB status, TP53 mutation, immune functions and immunotherapeutic response in BC.

A new immune-related gene signature predicts the prognosis and immune escape of bladder cancer.

BACKGROUND: The biological roles of immune-related genes (IRGs) in bladder cancer (BC) need to be further elucidated. OBJECTIVE: To elucidate the predictive value of IRGs for prognosis and immune escape in BC. METHODS: We comprehensively analyzed the transcriptomic and clinical information of 430 cases, including 19 normal and 411 BC patients from the TCGA database, and verified 165 BC cases in the GSE13507 dataset. The risk model was constructed based on IRGs by applying LASSO Cox regression and exploring the relationship between the risk score and prognosis, gene mutations, and immune escape in BC patients. RESULTS: We identified 4 survival-related genes (PSMC1, RAC3, ROBO2 and ITGB3) among 6,196 IRGs in both the TCGA and GES13507 datasets,, which were used to establish a gene risk model by applying LASSO Cox regression. The results showed that the high-risk (HR) group was closely associated with poor survival or advanced pathological stage of BC. Furthermore, the risk score was found to be an independent risk factor for prognosis of BC patients. In addition, high-risk individuals showed a greater prevalence of TP53 mutations lower CD8+ T-cell and NK cell infiltration, higher Treg cell infiltration, higher expression of PD-L1, and higher immune exclusion scores than those in the low-risk (LR) group. Finally, the experimental verification shows that the model construction gene, especially PMSC1, plays an important role in the growth and metastasis of bladder cancer. CONCLUSIONS: These evidences revealed the vital role of IRGs in predicting prognosis, TP53 mutation and immune escape in BC patients.

Coral skeletons reveal the impacts of oil pollution on seawater chemistry in the northern South China Sea.

Oil pollution can release trace metals (TMs) with cumulative toxicity into seawater, harming marine ecosystems in the long term. However, the lack of studies has inhibited our understanding of the effects and mechanisms of oil pollution on TMs in seawater. Hence, we investigated the 10-year monthly variation of TMs in Porites coral skeletons from the northern South China Sea (SCS), complemented by spatial distribution of TMs in seawater, sediments and characterization of TMs in fuel oil. The results of principal component-multivariate linear regression showed that the total contribution of oil pollution as a source to TMs in surface seawater was 77.2%, where the residence time of TMs (Ni, V, Cr, Co, Cu, Mn, Fe, and Mo) released from oil spills in surface seawater was approximately 1.4 months. Due to the geochemical nature of the metals, their seasonal variations are controlled by tropical cyclones (Ni, V, Cr, Co, Cu, Mn, Fe, and Mo), winter monsoons (Pb, Cd, Ba, and Zn) and sea surface temperature (Sr). This study shows that coral skeletons can be used as a new tool to study marine oil pollution. This provides valuable reference data for accurately identifying and quantifying the effects of oil pollution on TMs in seawater from a spatial and temporal perspective.

Interannual variation and sources identification of heavy metals in seawater near shipping lanes: Evidence from a coral record from the northern South China Sea.

Heavy metal pollution is a serious environmental problem in the marine ecosystem. Thereinto, marine transportation activities have gradually become an important source of heavy metals in seawater. However, the lack of studies on the temporal dynamics of seawater heavy metals in marine shipping areas has hindered our understanding of the sources and transport mechanisms of heavy metals in seawater of hectic shipping waters. Therefore, we investigated the interannual resolution variation of heavy metals in Porites lutea skeletons during the past 32 years under the rapid development of the shipping sector near Weizhou Island from the northern South China Sea. Results show that most heavy metal concentrations with higher coefficients of variation (≥100 %) in the Porites coral skeletons were higher than those in the uncontaminated or less anthropogenic waters. The results of principal component analysis and multiple linear regression showed that the interannual variations of Ni, V, Cr, Co, Zn, Cu, Mn, Fe and Mo were mainly impacted by marine oil extraction and oil spills generated by shipping activities, accounting for 51.58 %. The effect of sea surface temperature accounts for 13.44 %, and controls the interannual variations of Ba and Sr. The effect of industrial pollution accounts for 13.27 %, and explains the interannual variations of Cd and Y. The fuel consumption of marine shipping accounted for 8.76 %, explaining the interannual variations of Pb. The total contribution of anthropogenic activities reached 73.61 %. The interannual variation of heavy metals indicates that hectic marine shipping activities are the dominant cause of Ni, V, Pb, Cr, Co, Zn, Cu, Mn, Fe and Mo input to surface seawater around Weizhou Island. This provided valuable data for understanding the temporal dynamics and potential sources of heavy metals in the marine environment by using coral skeletons as a high-resolution recording vehicle.

The predictive value of pyroptosis for the prognosis and immune escape of bladder cancer.

OBJECTIVE: To evaluate the predictive value of pyroptosis-related genes for the prognosis and immune escape of bladder cancer (BC). METHODS: Transcriptomic and single nucleotide polymorphisms (SNPs) data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) portal. Least absolute shrinkage and selection operator (LASSO) analysis was carried out to construct a prognostic risk model for BC patients. RESULTS: Based on the expression of 50 pyroptosis-related genes, BC patients from TCGA database were divided into two clusters, which showed significant differences in overall survival and disease specific survival. Furthermore, we intersected the differentially expressed genes between these two clusters with those identified from the GSE13507 dataset and finally identified eight survival related genes, which was used to construct a prognostic risk model by LASSO Cox regression. According to the model, the high-risk (HR) group was closely associated with poor survival or the advanced pathological stage of BC. In addition, the HR group was mainly enriched in cell cycle and immune-related pathways and had a higher TP53 mutation rate than the low-risk (LR) group. Furthermore, these two risk groups were significantly related to immune cell composition, immune cell infiltration, and immune response. Importantly, a higher expression of PD-1, PD-L1, and CTLA4 as well as higher immune exclusion scores were found in the HR group, suggesting a higher possibility of immune escape. CONCLUSION: Our studies revealed the key role of pyroptosis in predicting the prognosis, TP53 mutation, and immune escape of patients with BC.

Comprehensive Exploration of M2 Macrophages and Its Related Genes for Predicting Clinical Outcomes and Drug Sensitivity in Lung Squamous Cell Carcinoma.

Background: M2 macrophages play an important role in cancers. However, the role of M2 macrophages has not been clarified in lung squamous cell carcinoma. Methods: All the open-accessed data were downloaded from The Cancer Genome Atlas database. All the analysis was performed in the R software. The CIBERSORT algorithm was utilized to quantify the immune cell infiltration in the tumor microenvironment. LASSO regression and multivariate Cox regression analysis were carried out for the creation of the prognostic model. Pathway enrichment analysis was performed using the single sample Gene Set Enrichment Analysis (ssGSEA) and clueGO algorithm. Results: In our study, we comprehensively explored the role of M2 macrophages and its related genes in LUSC patients. We found that the patients with high M2 macrophage infiltration tend to have a worse prognosis. Also, some oncogenetic pathways were activated in the patients with high M2 macrophage infiltration. Further, a prognosis model based on six M2 macrophage-related genes was established, including TRIM58, VIPR2, CTNNA3, KIAA0408, CLEC4G, and MATN4, which showed a good prognosis prediction efficiency in both training and validation cohort. Pathway enrichment analysis showed that the pathway of allograft rejection, bile acid metabolism, coagulation, inflammatory response, IL6/JAK/STAT3 signaling, hedgehog signaling, peroxisome, and myogenesis were significantly activated in the high-risk patients. Based on the results of an investigation of immune infiltration, risk score was found to have a positive correlation with M2 macrophages and resting CD4+ memory T cells, but a negative correlation with follicular helper T cells, M1 macrophages, and Tregs. In addition, we discovered that patients in high-risk groups may respond better to immunotherapy than individuals in lower-risk groups. However, low-risk patients might be more sensitive to cisplatin. Conclusions: Our model is a powerful tool to predict LUSC patient prognosis and could indicate the sensitivity of immunotherapy and chemotherapy.

Properties and the Application of Sludge-Based Biochar in the Removal of Phosphate and Methylene Blue from Water: Effects of Acid Treating.

Sludge-based biochar could be used to remove phosphate and methylene blue (MB) from water. It is a highly efficient way to treat the sludge and contaminated water synergistically. The high ash content in sludge greatly influenced the adsorption property of the resultant biochar. In this work, the influence of carbonization-activation and acid treating on the adsorption performance of the sludge-based biochar was evaluated. The composition, structure, and surface properties of biochar were improved after acid treating. The biochar was obtained in a sequence of carbonization-activation first and then acid treating, providing the optimal adsorption property. Zn550-H and Zn750-H showed excellent adsorption capacity to phosphate and MB, respectively. The adsorption process was well described by the pseudo-first-order and pseudo-second-order kinetic models. Isothermal studies implied that it was controlled by multiple processes. What is more, sludge-based biochar performed well in the adsorption of phosphate and MB from weakly acidic to alkaline conditions, which was beneficial to utilize the sludge-based biochar in water remediation practically.