Linking Grnn And Neighborhood Selection Algorithm To Assess Land Suitability In Low-Slope Hilly Areas

Land resources in mountainous areas have become severely inadequate because of accelerated urbanization and industrialization, rational land exploitation in low-slope hilly areas can solve this issue. Under the protection of ecological security, this study applied a new method that combined generalized regression neural network (GRNN) and neighborhood selection algorithm (NSA) to evaluate the land suitability with a case study in Dali Prefecture, China. Land development potential was also measured and mapped according to the area proportion of land suitable to be exploited in each township. The results demonstrated that 2139 km2 and 871 km2 of low-slope hilly land were suitable for development of farmland and construction land, respectively. Of this resource, 1687 km2 and 419 km2 were identified as single-suitability area for farmland and construction land respectively, with 452 km2 of multi-suitability area. After trade-off analysis based on NSA, the final area suitable for development of farmland and construction land were 1909 km2 and 387 km2 respectively, with 4600 km2 restricted to development. The township development priority was determined according to the land development potential, which helped for local development planning. The methodology applied in this study provides an effective way to make decisions on land development and management in mountainous areas

Downregulation of Bmal1 Expression in Celiac Ganglia Protects against Hepatic Ischemia-Reperfusion Injury

Hepatic ischemia-reperfusion injury (HIRI) significantly contributes to liver dysfunction following liver transplantation and hepatectomy. However, the role of the celiac ganglion (CG) in HIRI remains unclear. Adeno-associated virus was used to silence Bmal1 expression in the CG of twelve beagles that were randomly assigned to the Bmal1 knockdown group (KO-Bmal1) and the control group. After four weeks, a canine HIRI model was established, and CG, liver tissue, and serum samples were collected for analysis. The virus significantly downregulated Bmal1 expression in the CG. Immunofluorescence staining confirmed a lower proportion of c-fos+ and NGF+ neurons in TH+ cells in the KO-Bmal1 group than in the control group. The KO-Bmal1 group exhibited lower Suzuki scores and serum ALT and AST levels than the control group. Bmal1 knockdown significantly reduced liver fat reserve, hepatocyte apoptosis, and liver fibrosis, and it increased liver glycogen accumulation. We also observed that Bmal1 downregulation inhibited the hepatic neurotransmitter norepinephrine, neuropeptide Y levels, and sympathetic nerve activity in HIRI. Finally, we confirmed that decreased Bmal1 expression in CG reduces TNF-α, IL-1β, and MDA levels and increases GSH levels in the liver. The downregulation of Bmal1 expression in CG suppresses neural activity and improves hepatocyte injury in the beagle model after HIRI

Image_1_The role of YAP1 in survival prediction, immune modulation, and drug response: A pan-cancer perspective.jpeg

IntroductionDysregulation of the Hippo signaling pathway has been implicated in multiple pathologies, including cancer, and YAP1 is the major effector of the pathway. In this study, we assessed the role of YAP1 in prognostic value, immunomodulation, and drug response from a pan-cancer perspective.MethodsWe compared YAP1 expression between normal and cancerous tissues and among different pathologic stages survival analysis and gene set enrichment analysis were performed. Additionally, we performed correlation analyses of YAP1 expression with RNA modification-related gene expression, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint regulator expression, and infiltration of immune cells. Correlations between YAP1 expression and IC50s (half-maximal inhibitory concentrations) of drugs in the CellMiner database were calculated.ResultsWe found that YAP1 was aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications, particularly m6A methylation. High expression of YAP1 was associated with poor survival outcomes in ACC, BLCA, LGG, LUAD, and PAAD. YAP1 expression was negatively correlated with the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, and positively correlated with the infiltration of myeloid-derived suppressor cells (MDSCs) and cancer-associated fibroblasts (CAFs) in pan-cancer. Higher YAP1 expression showed upregulation of TGF-β signaling, Hedgehog signaling, and KRAS signaling. IC50s of FDA-approved chemotherapeutic drugs capable of inhibiting DNA synthesis, including teniposide, dacarbazine, and doxorubicin, as well as inhibitors of hypoxia-inducible factor, MCL-1, ribonucleotide reductase, and FASN in clinical trials were negatively correlated with YAP1 expression.DiscussionIn conclusion, YAP1 is aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications. High expression of YAP1 is associated with poor survival outcomes in certain cancer types. YAP1 may promote tumor progression through immunosuppression, particularly by suppressing the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, as well as recruiting MDSCs and CAFs in pan-cancer. The tumor-promoting activity of YAP1 is attributed to the activation of TGF-β, Hedgehog, and KRAS signaling pathways. AZD2858 and varlitinib might be effective in cancer patients with high YAP1 expression.</p

Image_4_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Image_1_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Image_2_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Image_5_Predictors based on cuproptosis closely related to angiogenesis predict colorectal cancer recurrence.tif

Up to one-third of colorectal cancer (CRC) patients experience recurrence after radical surgery, and it is still very difficult to assess and predict the risk of recurrence. Angiogenesis is the key factor of recurrence as metastasis of CRC is closely related to copper metabolism. Expression profiling by microarray from two datasets in Gene Expression Omnibus (GEO) was selected for quality control, genome annotation, normalization, etc. The identified angiogenesis-derived and cuproptosis-related Long non-coding RNAs (lncRNAs) and clinical data were screened and used as predictors to construct a Cox regression model. The stability of the model was evaluated, and a nomogram was drawn. The samples were divided into high-risk and low-risk groups according to the linear prediction of the model, and a Kaplan–Meier survival analysis was performed. In this study, a model was established to predict the postoperative recurrence of colon cancer, which exhibits a high prediction accuracy. Furthermore, the negative correlation between cuproptosis and angiogenesis was validated in colorectal cancer cell lines and the expression of lncRNAs in vitro was examined.</p

Table_1_The role of YAP1 in survival prediction, immune modulation, and drug response: A pan-cancer perspective.xlsx

IntroductionDysregulation of the Hippo signaling pathway has been implicated in multiple pathologies, including cancer, and YAP1 is the major effector of the pathway. In this study, we assessed the role of YAP1 in prognostic value, immunomodulation, and drug response from a pan-cancer perspective.MethodsWe compared YAP1 expression between normal and cancerous tissues and among different pathologic stages survival analysis and gene set enrichment analysis were performed. Additionally, we performed correlation analyses of YAP1 expression with RNA modification-related gene expression, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint regulator expression, and infiltration of immune cells. Correlations between YAP1 expression and IC50s (half-maximal inhibitory concentrations) of drugs in the CellMiner database were calculated.ResultsWe found that YAP1 was aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications, particularly m6A methylation. High expression of YAP1 was associated with poor survival outcomes in ACC, BLCA, LGG, LUAD, and PAAD. YAP1 expression was negatively correlated with the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, and positively correlated with the infiltration of myeloid-derived suppressor cells (MDSCs) and cancer-associated fibroblasts (CAFs) in pan-cancer. Higher YAP1 expression showed upregulation of TGF-β signaling, Hedgehog signaling, and KRAS signaling. IC50s of FDA-approved chemotherapeutic drugs capable of inhibiting DNA synthesis, including teniposide, dacarbazine, and doxorubicin, as well as inhibitors of hypoxia-inducible factor, MCL-1, ribonucleotide reductase, and FASN in clinical trials were negatively correlated with YAP1 expression.DiscussionIn conclusion, YAP1 is aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications. High expression of YAP1 is associated with poor survival outcomes in certain cancer types. YAP1 may promote tumor progression through immunosuppression, particularly by suppressing the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, as well as recruiting MDSCs and CAFs in pan-cancer. The tumor-promoting activity of YAP1 is attributed to the activation of TGF-β, Hedgehog, and KRAS signaling pathways. AZD2858 and varlitinib might be effective in cancer patients with high YAP1 expression.</p