Anisotropic Damage Mechanism of Coal Seam Water Injection with Multiphase Coupling.

After coal seam water injection, coal mechanical properties will change with brittleness weakening and plasticity enhancement. Aiming at the problem of coal damage caused by the coal seam water injection process, based on nonlinear pore elasticity theory and continuum damage theory, a nonlinear pore elastic damage model considering anisotropic characteristics is proposed to calculate and analyze the gas-liquid-solid multiphase coupling effect with the fully coupled finite element method during the coal seam water injection process. The research results indicate that the wetting radius of calculated results by the model agrees well with the in situ test results, and the relative errors are less than 10%. Water saturation and induced damage of the coal body in the parallel bedding direction are greater than that in the vertical bedding direction during the coal seam water injection process, which exhibits significant anisotropic characteristics. With the increasing water injection time, the induced damage of the coal body also increases near the water injection hole. Considering the inherent permeability arising with damage, it has a significant impact on both water saturation and induced damage, which also indicates that there is a strong interaction between water saturation and induced damage. The theoretical model reveals the coal damage mechanism of gas-liquid-solid multiphase coupling after coal seam water injection and provides a theoretical prediction of coal containing water characteristics in engineering practice.

Desorption Characteristics of CH4-C2H6 Mixed Gas in Heavy Hydrocarbon-Rich Coal Seams.

The gas desorption characteristics of coal are closely related to the gas content of the coal seam. The gas in heavy hydrocarbon-rich coal seams contains CH4 and C2H6 heavy hydrocarbons. However, most current research on the gas desorption characteristics of coal seams focuses on CH4 analysis, ignoring the influence of the C2H6 heavy hydrocarbon gas. To accurately determine the gas content of a heavy hydrocarbon-rich coal seam, methods based on CH4 analysis are inadequate and the desorption characteristics of CH4-C2H6 mixed gas must be clarified. This work experimentally and theoretically studies the desorption characteristics of single-component gas and CH4-C2H6 mixed gas from coal samples. The results show that increasing the adsorption-equilibrium pressure was found to increase the desorption quantity and desorption speed of single-component gas and increase the desorption quantity, desorption ratio, and diffusion coefficient of mixed gas. Under the same adsorption-equilibrium pressure, the desorption quantity and rate of single-component CH4 gas exceeded those of C2H6. The quantity and speed of mixed gas desorption increased with rising CH4 concentration and decreased with rising C2H6 concentration. The change in the mixed gas concentration during desorption reflects the distribution characteristics of light hydrocarbon components on the outer surface and heavy hydrocarbon components on the inner surface of coal. From the desorption characteristics of mixed gas, desorption models of mixed gas were obtained at different concentrations, laying a theoretical foundation for accurate determinations of gas contents in heavy hydrocarbon-rich coal seams.

CBX2 Deletion Suppresses Growth and Metastasis of Colorectal Cancer by Mettl3-p38/ERK MAPK Signalling Pathway.

Colorectal cancer (CRC) seriously endangers human health owing to its high morbidity and mortality. Previous studies have suggested that high expression of CBX2 may be associated with poor prognosis in CRC patients. However, its functional role in CRC remains to be elucidated. Herein, we found that CBX2 overexpression in colorectal cancer tissue compared with adjacent tissues. Additionally, forest maps and the nomogram model indicated that elevated CBX2 expression was an independent prognostic factor in CRC. Moreover, we confirmed that the deletion of CBX2 markedly suppressed the proliferation and migration of CRC cells in vitro and in vivo. Furthermore, downregulation of CBX2 promotes CRC cell apoptosis and hinders the cell cycle. Mechanistically, our data demonstrated that deletion of CBX2 inhibited the MAPK signaling pathway by regulating the protein levels of Mettl3. In conclusion, our study demonstrated that CBX2 is a vital tumor suppressor in CRC and could be a promising anti-cancer therapeutic target.

Identification of novel T cell proliferation patterns, potential biomarkers and therapeutic drugs in colorectal cancer.

Background: T cells are crucial components of antitumor immunity. A list of genes associated with T cell proliferation was recently identified; however, the impact of T cell proliferation-related genes (TRGs) on the prognosis and therapeutic responses of patients with colorectal cancer (CRC) remains unclear. Methods: 33 TRG expression information and clinical information of patients with CRC gathered from multiple datasets were subjected to bioinformatic analysis. Consensus clustering was used to determine the molecular subtypes associated with T cell proliferation. Utilizing the Lasso-Cox regression, a predictive signature was created and verified in external cohorts. A tumor immune environment analysis was conducted, and potential biomarkers and therapeutic drugs were identified and confirmed via in vitro and in vivo studies. Results: CRC patients were separated into two TRG clusters, and differentially expressed genes (DEGs) were identified. Patient information was divided into three different gene clusters, and the determined molecular subtypes were linked to patient survival, immune cells, and immune functions. Prognosis-associated DEGs in the three gene clusters were used to evaluate the risk score, and a predictive signature was developed. The ability of the risk score to predict patient survival and treatment response has been successfully validated using multiple datasets. To discover more possible biomarkers for CRC, the weighted gene co-expression network analysis algorithm was utilized to screen key TRG variations between groups with high- and low-risk. CDK1, BATF, IL1RN, and ITM2A were screened out as key TRGs, and the expression of key TRGs was confirmed using real-time reverse transcription polymerase chain reaction. According to the key TRGs, 7,8-benzoflavone was identified as the most significant drug molecule, and MTT, colony formation, wound healing, transwell assays, and in vivo experiments indicated that 7,8-benzoflavone significantly suppressed the proliferation and migration of CRC cells. Conclusion: T cell proliferation-based molecular subtypes and predictive signatures can be utilized to anticipate patient results, immunological landscape, and treatment response in CRC. Novel biomarker candidates and potential therapeutic drugs for CRC were identified and verified using in vitro and in vivo tests.

Robust machine-learning based prognostic index using cytotoxic T lymphocyte evasion genes highlights potential therapeutic targets in colorectal cancer.

BACKGROUND: A minute fraction of patients stands to derive substantial benefits from immunotherapy, primarily attributable to immune evasion. Our objective was to formulate a predictive signature rooted in genes associated with cytotoxic T lymphocyte evasion (CERGs), with the aim of predicting outcomes and discerning immunotherapeutic response in colorectal cancer (CRC). METHODS: 101 machine learning algorithm combinations were applied to calculate the CERGs prognostic index (CERPI) under the cross-validation framework, and patients with CRC were separated into high- and low-CERPI groups. Relationship between immune cell infiltration levels, immune-related scores, malignant phenotypes and CERPI were further analyzed. Various machine learning methods were used to identify key genes related to both patient survival and immunotherapy benefits. Expression of HOXC6, G0S2, and MX2 was evaluated and the effects of HOXC6 and G0S2 on the viability and migration of a CRC cell line were in-vitro verified. RESULTS: The CERPI demonstrated robust prognostic efficacy in predicting the overall survival of CRC patients, establishing itself as an independent predictor of patient outcomes. The low-CERPI group exhibited elevated levels of immune cell infiltration and lower scores for tumor immune dysfunction and exclusion, indicative of a greater potential benefit from immunotherapy. Moreover, there was a positive correlation between CERPI levels and malignant tumor phenotypes, suggesting that heightened CERPI expression contributes to both the occurrence and progression of tumors. Thirteen key genes were identified, and their expression patterns were scrutinized through the analysis of single-cell datasets. Notably, HOXC6, G0S2, and MX2 exhibited upregulation in both CRC cell lines and tissues. Subsequent knockdown experiments targeting G0S2 and HOXC6 resulted in a significant suppression of CRC cell viability and migration. CONCLUSION: We developed the CERPI for effectively predicting survival and response to immunotherapy in patients, and these results may provide guidance for CRC diagnosis and precise treatment.

Experimental Study on Coal and Gas Outburst Risk under Different Water Content Rates in Strong Outburst Coal Seams.

To investigate the alleviation potency of coal seam water infusion on coal and gas outburst, this paper focuses on the Qidong coal mine outburst coal seam, where outburst accidents have occurred many times, and obtains the impact of water content on outburst prediction parameters by studying the features of outburst parameters and gas desorption law under different water content rates. How water content affects outburst was also researched through the use of a self-made outburst simulation test system, and the relationship between water content and outburst intensity and critical gas pressure was studied. It can be concluded that with the rise of water content, the initial velocity of gas diffusion, the gas desorption index of drilling cuttings, and the adsorption constant a decrease, but the firmness coefficient (f) increase, and these indicators are exponentially related to the water content. Meanwhile, as the water content raises, the outburst pressure threshold increases, the outburst intensity gradually decreases, and the less likely outburst occurs. Under 0.5 MPa pressure, as the water content arose from 2.02 to 5.14%, the outburst intensity was significantly weakened, while no outburst occurred as the water content reached to 10.25%. Fitting analysis of the influence curve of outburst parameters and comparing the vital values of outburst prediction indexes finally determined that the water content rate of 5.14% could be used as a key index for water injection measures for coal and gas outburst prevention coal seam in Qidong coal mine no. 9. This research offers a guiding significance for the outburst prevention measures of water infusion in outburst coal seams and gives a feasible scheme for the safe mining of outburst coal mines.

Identification of cuproptosis-based molecular subtypes, construction of prognostic signature and characterization of immune landscape in colon cancer.

Background: Cuproptosis is a newly discovered form of cell death induced by targeting lipoacylated proteins involved in the tricarboxylic acid cycle. However, the roles of cuproptosis-related genes (CRGs) in the clinical outcomes and immune landscape of colon cancer remain unknown. Methods: We performed bioinformatics analysis of the expression data of 13 CRGs identified from a previous study and clinical information of patients with colon cancer obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Colon cancer cases were divided into two CRG clusters and prognosis-related differentially expressed genes. Patient data were separated into three corresponding distinct gene clusters, and the relationships between the risk score, patient prognosis, and immune landscape were analyzed. The identified molecular subtypes correlated with patient survival, immune cells, and immune functions. A prognostic signature based on five genes was identified, and the patients were divided into high- and low-risk groups based on the calculated risk score. A nomogram model for predicting patient survival was developed based on the risk score and other clinical features. Results: The high-risk group showed a worse prognosis, and the risk score was related to immune cell abundance, microsatellite instability, cancer stem cell index, checkpoint expression, immune escape, and response to chemotherapeutic drugs and immunotherapy. Findings related to the risk score were validated in the imvigor210 cohort of patients with metastatic urothelial cancer treated with anti-programmed cell death ligand 1. Conclusion: We demonstrated the potential of cuproptosis-based molecular subtypes and prognostic signatures for predicting patient survival and the tumor microenvironment in colon cancer. Our findings may improve the understanding of the role of cuproptosis in colon cancer and lead to the development of more effective treatment strategies.

A novel oxidative stress- and ferroptosis-related gene prognostic signature for distinguishing cold and hot tumors in colorectal cancer.

Oxidative stress and ferroptosis exhibit crosstalk in many types of human diseases, including malignant tumors. We aimed to develop an oxidative stress- and ferroptosis-related gene (OFRG) prognostic signature to predict the prognosis and therapeutic response in patients with colorectal cancer (CRC). Thirty-four insertion genes between oxidative stress-related genes and ferroptosis-related genes were identified as OFRGs. We then performed bioinformatics analysis of the expression profiles of 34 OFRGs and clinical information of patients obtained from multiple datasets. Patients with CRC were divided into three OFRG clusters, and differentially expressed genes (DEGs) between clusters were identified. OFRG clusters correlated with patient survival and immune cell infiltration. Prognosis-related DEGs in three clusters were used to calculate the risk score, and a prognostic signature was constructed according to the risk score. In this study, patients in the low-risk group had better prognosis, higher immune cell infiltration levels, and better responses to fluorouracil-based chemotherapy and immune checkpoint blockade therapy than high-risk patients; these results were successfully validated with multiple independent datasets. Thus, low-risk CRC could be defined as hot tumors and high-risk CRC could be defined as cold tumors. To further identify potential biomarkers for CRC, the expression levels of five signature genes in CRC and adjacent normal tissues were further verified via an in vitro experiment. In conclusion, we identified 34 OFRGs and constructed an OFRG-related prognostic signature, which showed excellent performance in predicting survival and therapeutic responses for patients with CRC. This could help to distinguish cold and hot tumors in CRC, and the results might be helpful for precise treatment protocols in clinical practice.

PANoptosis-based molecular clustering and prognostic signature predicts patient survival and immune landscape in colon cancer.

PANoptosis is a newly-discovered cell death pathway that involves crosstalk and co-ordination between pyroptosis, apoptosis, and necroptosis processes. However, the roles of PANoptosis-related genes (PRGs) in prognosis and immune landscape of colon cancer remain widely unknown. Here, we performed a bioinformatics analysis of expression data of nineteen PRGs identified from previous studies and clinical data of colon cancer patients obtained from TCGA and GEO databases. Colon cancer cases were divided into two PRG clusters, and prognosis-related differentially expressed genes (PRDEGs) were identified. The patient data were then separated into two corresponding distinct gene clusters, and the relationship between the risk score, patient prognosis, and immune landscape was analyzed. The identified PRGs and gene clusters correlated with patient survival and immune system and cancer-related biological processes and pathways. A prognosis signature based on seven genes was identified, and patients were divided into high-risk and low-risk groups based on the calculated risk score. A nomogram model for prediction of patient survival was also developed based on the risk score and other clinical features. Accordingly, the high-risk group showed worse prognosis, and the risk score was related to immune cell abundance, cancer stem cell (CSC) index, checkpoint expression, and response to immunotherapy and chemotherapeutic drugs. Results of quantitative real-time polymerase chain reaction (qRT-PCR) showed that LGR5 and VSIG4 were differentially expressed between normal and colon cancer samples. In conclusion, we demonstrated the potential of PANoptosis-based molecular clustering and prognostic signatures for prediction of patient survival and tumor microenvironment (TME) in colon cancer. Our findings may improve our understanding of the role of PANoptosis in colon cancer, and enable the development of more effective treatment strategies.

Extracellular Matrix-Associated Pathways Promote the Progression of Gastric Cancer by Impacting the Dendritic Cell Axis.

BACKGROUND: Gastric cancer (GC) is the third most frequent malignant tumour in the Chinese population, let alone the whole world. Recently, most prognostic models have only focused on the levels of several genes, miRNAs, lncRNAs, gene mutations, or DNA methylation; however, the activation status of biological pathways is more stable and can reflect the comprehensive inner conditions of tumours. METHODS: We collected samples from the Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) cohort and GSE62254 cohort, with a total of 594 patients. We employed GSEA to first compare the diverse activated signalling pathways between dead GC patients and living patients. The least absolute shrinkage and selection operator (LASSO) regression analysis was subsequently performed by the "glmnet" package to generate a prognostic signature. RESULTS: We extracted a total of 218 genes from the KEGG Focal Adhesion and KEGG ECM Receptor Interaction pathways, which showed significant activation in dead GC patients in two enrolled cohorts, for subsequent LASSO analysis. In the TCGA-STAD cohort, patients in the high-risk group faced a significantly poorer prognosis than those in the low-risk group (P < 0.001, HR: 4.62, 95% CI: 3.447-6.183), with an AUC of 0.694. In the GSE62254 cohort, the HR value was 4.94 (95% CI: 3.413-7.165), and the AUC value was as high as 0.834. A high-risk score and poor prognosis correlated with infiltrated dendritic cells, and the receptor of IFN-α was also positively linked with the risk score, as well as poor prognosis. GC patients with high-risk scores were more likely to respond to CTLA4 treatment but not PD1 treatment. CONCLUSION: Taken together, we established and verified an extracellular matrix prognostic model of gastric cancer patients. The model can be used to evaluate the risk of death of GC patients, as well as the response to anti-CTLA4 immunotherapy.

Molecular classification reveals the diverse genetic and prognostic features of gastric cancer: A multi-omics consensus ensemble clustering.

BACKGROUND: Globally, gastric cancer (GC) is the fifth most common tumor. It is necessary to identify novel molecular subtypes to guide patient selection for specific target therapeutic benefits. METHODS: Multi-omics data, including transcriptomics RNA-sequencing (mRNA, LncRNA, miRNA), DNA methylation, and gene mutations in the TCGA-STAD cohort were used for the clustering. Ten classical clustering algorithms were executed to recognize patients with different molecular features using the "MOVICS" package in R. The activated signaling pathways were evaluated using the single-sample gene set enrichment analysis. The differential distribution of gene mutations, copy number alterations, and tumor mutation burden was compared, and potential responses to immunotherapy and chemotherapy were also assessed. RESULTS: Two molecular subtypes (CS1 and CS2) were recognized by ten clustering algorithms with consensus ensembles. Patients in the CS1 group had a shorter average overall survival time (28.5 vs. 68.9 months, P = 0.016), and progression-free survival (19.0 vs. 63.9 months, P = 0.008) as compared to those in the CS2 group. Extracellular associated biological process activation was higher in the CS1 group, while the CS2 group displayed the enhanced activation of cell cycle-associated pathways. Significantly higher total mutation numbers and neoantigens were observed in the CS2 group, along with specific mutations in TTN, MUC16, and ARID1A. Higher infiltration of immunocytes was also observed in the CS2 group, reflective of the potential immunotherapeutic benefits. Moreover, the CS2 group could also respond to 5-fluorouracil, cisplatin, and paclitaxel. The similar diversity in clinical outcomes between CS1 and CS2 groups was successfully validated in the external cohorts, GSE62254, GSE26253, GSE15459, and GSE84437. CONCLUSION: The findings provided novel insights into the GC subtypes through integrative analysis of five -omics data by ten clustering algorithms. These could provide potential clinical therapeutic targets based on the specific molecular features.

Suspicious minds: cinematic depiction of distrust during epidemic disease outbreaks.

One key factor that appears to be crucial in the rejection of quarantines, isolation and other social controls during epidemic outbreaks is trust-or rather distrust. Much like news reporting and social media, popular culture such as fictional novels, television shows and films can influence people's trust, especially given that the information provided about an epidemic disease is sometimes seen as grounded in 'scientific fact' by societies. As well as providing information on the 'correct science' behind disease transmission, spread and illness in films and literature, popular culture can also inform societies about how to feel and how to react during epidemics-that is to say create some expectations about the kinds of societal responses that could potentially occur. In this article we closely analyse three films that centre around epidemic diseases-Contagion (Steven Soderbergh, 2011), Blindness (Fernando Meirelles, 2008) and The Painted Veil (John Curran, 2006)-in order to highlight three categories of distrust that have recently been identified and conceptualised in broader discussions regarding trust and health: institutional, social and interpersonal. These films raise two key issues about trust and social responses during epidemics. First, while certain aspects of trust are badly diminished during epidemic disease outbreaks, epidemics can also interact with pre-existing structural inequalities within society-based on race, gender or wealth-to create mixed outcomes of discord, prejudice and fear that coexist with new forms of cohesion. Second, the breakdown in trust seen at certain levels during epidemics, such as at the institutional level between communities and authorities or elites, might be mediated or negotiated, perhaps even compensated for, by heightened solidity of trust at the social level, within or between communities.