PS-MPs promotes the progression of inflammation and fibrosis in diabetic nephropathy through NLRP3/Caspase-1 and TGF-ß1/Smad2/3 signaling pathways.

BACKGROUND: Diabetic nephropathy (DN) is a prevalent chronic microvascular complication of diabetes and the leading cause of end-stage renal disease (ESRD). Understanding the progressive etiology of DN is critical for the development of effective health policies and interventions. Recent research indicated that polystyrene microplastics (PS-MPs) contaminate our diets and accumulate in various organs, including the liver, kidneys, and muscles. METHODS: In this study, ten-week-old db/db mice and db/m mice were fed. Besides, db/db mice were divided into two groups: PS-MPs group (oral administration of 0.5 µm PS-MPs) and an H2O group, and they were fed for three months. A type II diabetes model was established using db/db mice to investigate the effects of PS-MPs on body weight, blood glucose level, renal function, and renal fibrosis. RESULTS: The results demonstrated that PS-MPs significantly exacerbated various biochemical indicators of renal tissue damage, including fasting blood glucose, serum creatinine, blood urea nitrogen, and blood uric acid. Additionally, PS-MPs worsened the pathological alterations and degree of fibrosis in renal tissue. An increased oxidative stress state and elevated levels of inflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin-1ß (IL-1ß), and monocyte chemoattractant protein-1 (MCP-1) were identified. Furthermore, PS-MPs significantly enhanced renal fibrosis by inhibiting the transition from epithelial cells to mesenchymal cells, specifically through the inhibition of the TGF-ß/Smad signaling pathway. The expression levels of NOD-like receptor protein 3 (NLRP3), apoptosis-associated speck-like protein containing a CARD (ASC), Caspase-1, and cleaved Caspase-1, which are inflammasome proteins, were significantly elevated in the PS-MPs group. CONCLUSION: The findings suggested that PS-MPs could aggravate kidney injury and renal fibrosis in db/db mice by promoting NLRP3/Caspase-1 and TGF-ß1/Smads signaling pathways. These findings had implications for elucidating the role of PS-MPs in DN progression, underscoring the necessity for additional research and public health interventions.

Toxicological effects of microplastics in renal ischemia-reperfusion injury.

The widespread presence of microplastics (MPs) in the environment poses a significant threat to biological survival and human health. However, our understanding of the toxic effects of MPs on the kidneys remains limited. This study aimed to investigate the underlying mechanism of the toxic effects of MPs on the kidneys using an ischemia-reperfusion (IR) mouse model. Four-week-old ICR mice were exposed to 0.5 µm MPs for 12 weeks prior to IR injury. The results showed that MPs exposure could aggravate the IR-induced damage to renal tubules and glomeruli. Although there were no significant changes in blood urea nitrogen and serum creatinine levels 7 days after IR, MPs treatment resulted in a slight increase in both parameters. In addition, the expression levels of inflammatory factors (MCP-1 and IL-6) at the mRNA level, as well as macrophage markers (CD68 and F4/80), were significantly higher in the MPs + IR group than in the Sham group after IR. Furthermore, MPs exposure exacerbated IR-induced renal fibrosis. Importantly, the expression of pyroptosis-related genes, including NLRP3, ASC, GSDMD, cleaved caspase-1, and IL-18, was significantly upregulated by MPs, indicating that MPs exacerbate pyroptosis in the context of renal IR. In conclusion, our findings suggest that MPs exposure can aggravate renal IR-induced pyroptosis by activating NLRP3-GSDMD signaling.

Microplastics cause hepatotoxicity in diabetic mice by disrupting glucolipid metabolism via PP2A/AMPK/HNF4A and promoting fibrosis via the Wnt/ß-catenin pathway.

In recent years, microplastics (MPs) have gained significant attention as a persistent environmental pollutant resulting from the decomposition of plastics, leading to their accumulation in the human body. The liver, particularly of individuals with type 2 diabetes mellitus (T2DM), is known to be more susceptible to the adverse effects of environmental pollutants. Therefore, to investigate the potential impact of MPs on the liver of diabetic mice and elucidate the underlying toxicological mechanisms, we exposed db/db mice to 0.5 µm MPs for 3 months. Our results revealed that MPs exposure resulted in several harmful effects, including decreased body weight, disruption of liver structure and function, elevated blood glucose levels, impaired glucose tolerance, and increased glycogen accumulation in the hepatic tissue of the mice. Furthermore, MPs exposure was found to promote hepatic gluconeogenesis by perturbing the PP2A/AMPK/HNF4A signaling pathway. In addition, MPs disrupt redox balance, leading to oxidative damage in the liver. This exposure also disrupted hepatic lipid metabolism, stimulating lipid synthesis while inhibiting catabolism, ultimately resulting in the development of fatty liver. Moreover, MPs were found to induce liver fibrosis by activating the Wnt/ß-catenin signaling pathway. Furthermore, MPs influenced adaptive thermogenesis in brown fat by modulating the expression of uncoupling protein 1 (UCP1) and genes associated with mitochondrial oxidative respiration thermogenesis in brown fat. In conclusion, our study demonstrates that MPs induce oxidative damage in the liver, disturb glucose and lipid metabolism, promote hepatic fibrosis, and influence adaptive thermogenesis in brown fat in diabetic mice. These findings underscore the potential adverse effects of MPs on liver health in individuals with T2DM and highlight the importance of further research in this area.

Screening of immunotherapy-related genes in bladder cancer based on GEO datasets.

Background: As one of the most prevalent genitourinary cancers, bladder cancer (BLCA) is associated with high morbidity and mortality. Currently, limited indicators are available for early detection and diagnosis of bladder cancer, and there is a lack of specific biomarkers for evaluating the prognosis of BLCA patients. This study aims to identify critical genes that affect bladder cancer immunity to improve the diagnosis and prognosis of bladder cancer and to identify new biomarkers and targets for immunotherapy. Methods: Two GEO datasets were used to screen differentially expressed genes (DEGs). The STRING database was used to construct a protein-protein interaction network of DEGs, and plug-in APP CytoHubba in Cytoscape was used to identify critical genes in the network. GO and KEGG analyses explored the functions and pathways of differential gene enrichment. We used GEPIA to validate the expression of differential genes, their impact on patient survival, and their relationship to clinicopathological parameters. Additionally, hub genes were verified using qRT-PCR and Western blotting. Immune infiltration analysis and multiple immunohistochemistry reveal the impact of Hub genes on the tumor microenvironment. Result: We screened out 259 differential genes, and identified 10 key hub genes by the degree algorithm. Four genes (ACTA2, FLNA, TAGLN, and TPM1) were associated with overall or disease-free survival in BLCA patients and were significantly associated with clinical parameters. We experimentally confirmed that the mRNA and protein levels of these four genes were significantly decreased in bladder cancer cells. Immunoassays revealed that these four genes affect immune cell infiltration in the tumor microenvironment; they increased the polarization of M2 macrophages. Conclusion: These four genes affect the tumor microenvironment of bladder cancer, provide a new direction for tumor immunotherapy, and have significant potential in the diagnosis and prognosis of bladder cancer.

Basement Membrane-Associated lncRNA Risk Model Predicts Prognosis and Guides Clinical Treatment in Clear Cell Renal Cell Carcinoma.

The basement membrane (BM) affects the invasion and growth of malignant tumors. The role and mechanism of BM-associated lncRNAs in clear cell renal cell carcinoma (ccRCC) are unknown. In this study, we identified biomarkers of ccRCC and developed a risk model to assess patient prognosis. We downloaded transcripts and clinical data from the Cancer Genome Atlas (TCGA). Differential analysis, co-expression analysis, Cox regression analysis, and lasso regression were used to identify BM-associated prognostic lncRNAs and create a risk prediction model. We evaluated and validated the accuracy of the model using multiple methods and constructed a nomogram to predict the prognosis of ccRCC. GO, KEGG, and immunity analyses were used to explore differences in biological function. We constructed a risk model containing six BM-associated lncRNAs (LINC02154, IGFL2-AS1, NFE4, AC112715.1, AC092535.5, and AC105105.3). The risk model has higher diagnostic efficiency compared to clinical characteristics and can be used to forecast patient prognoses. We used renal cancer cells and tissue microarrays to verify the expression of lncRNAs in the risk model. We found that knocking down LINC02154 and AC112715.1 could inhibit the invasion ability of renal cancer cells. The risk model based on BM-associated lncRNAs can well predict ccRCC and guide clinical treatment.

Identification of the Prognostic Biomarkers CBX6 and CBX7 in Bladder Cancer.

BACKGROUND: Chromobox (CBX) proteins are essential components of polycomb group proteins and perform essential functions in bladder cancer (BLCA). However, research on CBX proteins is still limited, and the function of CBXs in BLCA has not been well illustrated. METHODS AND RESULTS: We analyzed the expression of CBX family members in BLCA patients from The Cancer Genome Atlas database. By Cox regression analysis and survival analysis, CBX6 and CBX7 were identified as potential prognostic factors. Subsequently, we identified genes associated with CBX6/7 and performed enrichment analysis, and they were enriched in urothelial carcinoma and transitional carcinoma. Mutation rates of TP53 and TTN correlate with expression of CBX6/7. In addition, differential analysis indicated that the roles played by CBX6 and CBX7 may be related to immune checkpoints. The CIBERSORT algorithm was used to screen out immune cells that play a role in the prognosis of bladder cancer patients. Multiplex immunohistochemistry staining confirmed a negative correlation between CBX6 and M1 macrophages, as well as a consistent alteration in CBX6 and regulatory T cells (Tregs), a positive correlation between CBX7 and resting mast cells, and a negative correlation between CBX7 and M0 macrophages. CONCLUSIONS: CBX6 and CBX7 expression levels may assist in predicting the prognosis of BLCA patients. CBX6 may contribute to a poor prognosis in patients by inhibiting M1 polarization and promoting Treg recruitment in the tumor microenvironment, while CBX7 may contribute to a better prognosis in patients by increasing resting mast cell numbers and decreasing macrophage M0 content.

A Novel Risk Model for lncRNAs Associated with Oxidative Stress Predicts Prognosis of Bladder Cancer.

Background: Oxidative stress (OS) reactions are closely related to the development and progression of bladder cancer (BCa). This project aimed to identify new potential biomarkers to predict the prognosis of BCa and improve immunotherapy. Methods: We downloaded transcriptomic information and clinical data on BCa from The Cancer Genome Atlas (TCGA). Screening for OS genes was statistically different between tumor and adjacent normal tissue. A coexpression analysis between lncRNAs and differentially expressed OS genes was performed to identify OS-related lncRNAs. Then, differentially expressed oxidative stress lncRNAs (DEOSlncRNAs) between tumors and normal tissues were identified. Univariate/multivariate Cox regression analysis was performed to select the lncRNAs for risk assessment. LASSO analysis was conducted to establish a prognostic model. The prognostic risk model could accurately predict BCa patient prognosis and reveal a close correlation with clinicopathological features. We analyzed the principal component analysis (PCA), immune microenvironment, and half-maximal inhibitory concentration (IC50) in the risk groups. Results: We constructed a model containing eight DEOSlncRNAs (AC021321.1, AC068196.1, AC008750.1, SETBP1-DT, AL590617.2, THUMPD3-AS1, AC112721.1, and NR4A1AS). The prognostic risk model showed better results in predicting the prognosis of BCa patients and was strongly correlated with clinicopathological characteristics. We found great agreement between the calibration plots and prognostic predictions in this model. The areas under the receiver operating characteristic (ROC) curve (AUCs) at 1, 3, and 5 years were 0.792, 0.804, and 0.843, respectively. This model also showed good predictive ability regarding the tumor microenvironment and tumor mutation burden. In addition, the high-risk group was more sensitive to eight therapeutic agents, and the low-risk group was more responsive to five therapeutic agents. Sixteen immune checkpoints were significantly different between the two risk groups. Conclusion: Our eight DEOSlncRNA risk models provide new insights into predicting prognosis and clinical progression in BCa patients.