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AbstractObjectives Anesthetic drugs had been reported may impact the bio-behavior of the tumor. Propofol and sevoflurane are common anesthetics in the operation for glioblastoma (GBM). This study aims to establish a co-expression prognostic-related genes signature base on propofol and sevoflurane anesthesia to predict prognosis and immunotherapy response in GBM.Method GPM tissues with different anesthetics gene expression profiles (GSE179004) were obtained from the Gene Expression Omnibus (GEO) database. Core modules and central genes associated with propofol and sevoflurane anesthesia were identified by weighted gene coexpression network analysis (WGCNA) and establish a risk score prognostic model. Immune cell signature analysis in TCGA datasets was predicted via CIBERSORT. At last, serum methylation level of O6-methylguanine-DNA methyltransferase (MGMT) promoter was detected in GPM patient in different time during perioperative period.Results The burlywood1 group screened was significantly associated with sevoflurane-treated GBM tissue. 22 independent prognostic differential genes were construct a prognostic-related genes risk score in GBM, and showed good predictive ability. The risk score was strongly correlated with the age of the patients, but not with the sex of the patients. In addition, the differential responses to immunotherapy in high and low risk groups were analyzed, indicating that sevoflurane signature genes were consistent in the classification of gliomas. High-risk patients have high T-cell damage score and are less sensitive to immunotherapy. At last, serum methylation level of MGMT promoter was decreased in GBM patients during propofol and sevoflurane anesthesia.Conclusions Propofol and sevoflurane anesthesia associated impact on the gene expression of GBM, included the methylation level of MGMT promoter. Propofol and sevoflurane anesthesia-based risk score prognostic model, which has good prognostic power and is an independent prognostic factor in GBM patients. Therefore, this model can be used as a new biomarker for judging the prognosis of GBM patients.KEY MESSAGESPropofol and sevoflurane anesthesia-based risk score prognostic model has good prognostic power and is an independent prognostic factor in GBM patients.High Propofol and sevoflurane anesthesia-based risk score GBM patients have high T-cell damage scores and are less sensitive to immunotherapy.Serum methylation level of MGMT promoter decrease during propofol and sevoflurane anesthesia in GBM patients.

Coal mine is a complex system engineering, technical links are increasingly complex, variables are numerous, specialized division of labor is refined. Technical management is the key to solve the hidden danger and technical bottleneck in the production process of coal enterprises, which directly affects the safe development of enterprises. We expound the technology of coal mine based on the perspective of business and its decision-making purview division, management system, and put forward the organization system, business system, process, system, standard system and examination system, the architecture of the proposed business and technology management system principle, control technology for coal mine management provides a way to construct architecture clear and responsibilities clear.

The calculation of water supply is affected by many factors, such as water requirements, water-supply capacity, etc., which change with time and the environment. The traditional calculation methods are generally used under several fixed operating situations. The scenarios are too few to cover the various situations encountered in actual operations and take insufficient account of boundary conditions, such as reservoir inflow, water requirements, etc. The water-supply schemes facilitated by these methods are finite and not adaptable to the ever-changing, producing environment. Therefore, based on a traditional water supply-demand balance analysis, this study established a dynamic calculation model that takes into account different variables, such as reservoir inflow, ecological flow, and water demand. This study also constructed a dynamic simulation system based on the comprehensive, integrated platform and dynamic calculation model, which shortens the calculation period from a month to a day. The results show that the water-supply assurance rates calculated under different conditions reach higher than 93.9% for domestic and production, and higher than 50.9% for agriculture, which all exceed the design assurance rates. Additionally, the dynamic calculation model can significantly improve the calculation efficiency, playing an important role in the formulation of the project-operation plan and project-benefit evaluation.

ABSTRACT: Background: The radial forearm skin flap (RFSF) was first introduced by the Chinese scholar Guofan Yang and has since been used for nearly 40 years. The many advantages of RFSF have been investigated in this study. Case presentation: In this case, a female patient underwent RFSF surgery in 1979. In 2016 and 2018, two interviews were held to evaluate her subjective postoperative experience. In addition, overall donor site evaluation was conducted based on general health checkups and tests; tests for appearance, tactile sensitivity, muscle strength, and motor function; and CTA. Results: The flap survived well, and the donor site recovered without hand necrosis in the 1970s. In 2018, the patient was in good health condition and expressed her satisfaction with the surgery. The patient did not suffer from any postoperative complications such as diminished sensation of the donor site or donor site dysfunction; in the evaluation of hand and finger function, there was no point where functional reduction of the donor site was noted. CTA revealed compensatory blood supply with enlargement in the diameter of the ulnar and interosseous artery. Conclusion: After a nearly 40-year follow-up, the patient who underwent the first free radial forearm flap transplantation expressed satisfaction with the operative outcomes. The examination showed good results at the recipient site with little donor site deformities and good compensatory blood supply.

Hydrologic disasters often result in substantial property damage and casualties. Therefore, hydrology forecasting, especially the flooding, has become a hot research spot in all countries of the world. Based on the basic principle of flooding formation, this paper proposes a data-driven hydrology forecasting model, i.e., the CRML (Convolution Regression based on Machine Learning). This model could reflect the impact of hourly rainfall on the future flow changes and the flow changes are predicted by superimposing these impacts. First, our work is implemented on historical data onto the Xixian River Basin in Henan Province, China. Through the data filtering, the training set of our model is constructed by using the flood process selection algorithm proposed in this paper. Next, the gradient descent algorithm is used to update the weights of the model, and the optimal weights are verified by ten flooding events generated in the past ten years. Finally, the numerical results show that the qualified rates of our model in predicting flood peak flow and its arrival time is approximately 90% and 100%, respectively. Compared with the latest popular artificial intelligence schemes, our model structure is clear and concise. And combined with the physical meaning of the traditional model and machine learning technology, our model can accurately complete the task of long and short lead time hydrology forecasting.

Background/Aims: There are few effective treatment options for hypertrophic scars. MircoRNAs are a class of small, noncoding RNAs involved in multiple biological functions. Methods: Gene chip screening was used to screen out the differential expression of miRNAs in hypertrophic scars and normal tissues. Western blot and real-time PCR were used to confirm the expression of pleiotrophin (PTN) in hypertrophic scars. After analyze the correlation between PTN and miR-137 using correlation analysis, we used miRDB software to analyze the binding sites of miR-137 and PTN. Luciferase reporter gene, western blot and real-time PCR experiments were used to detect the regulatory effect of miR-137 on PTN. MTT and transwell assay were used to detect the effect of miR-137 on proliferation and metastasis. Western blot and real-time PCR were used to detect the regulatory effects of miR-137 on cyclin B1, matrix metalloproteinase 9 (MMP9), α-smooth muscle actin (α-SMA), vimentin, and type-I collagen (COL1A). Finally, miR-137 inhibitor was transfected into fibroblasts which was silent PTN, and the proliferation and migration of cells were detected by MTT and transwell. Western blot and real-time PCR were used to detect the expression of related proteins. Results: Various miRNAs was abnormal expressed in hypertrophic scars. miR-137 was decreased in hypertrophic scar, however PTN was up regulated in hypertrophic scars. miR-137 induced proliferation and metastasis in fibroblasts. This effect was accompanied by decreased expression of cyclin B1, MMP9, α-SMA, vimentin, and COL1A mediated via the target of PTN. Conclusion: Modulation of miR-137 expression in fibroblasts could provide an important therapeutic strategy for hypertrophic scars.

The aims of the study were to identify the differentially expressed genes (DEGs) between primary melanomas and metastasis melanomas (MMs), and to investigate the mechanisms of MMs. The microarray data GSE8401 including 31 primary melanomas and 52 MMs were downloaded from Gene Expression Omnibus. DEGs were identified using the Linear Models for Microarray Data package. The functional and pathway enrichment analyses were performed for DEGs. Identification of transcription factors, tumor-associated genes (TAGs), and tumor suppressor genes (TSGs) were performed with the TRANSFAC, TAG, and TSGene databases, respectively. A protein–protein interaction network was constructed using Search Tool for the Retrieval of Interacting Genes. The modules construction and analysis was performed using Molecular Complex Detection and Gene Cluster with Literature Profiles, respectively. In total, 1004 upregulated and 1008 downregulated DEGs were identified. The upregulated DEGs, such as CDK1, BRCA1, MAD2L1, and PCNA, were significantly enriched in cell cycles, DNA replication, and mismatch repair. The downregulated DEGs, such as COLIAL, COL4A5, COL18A1, and LAMC2, were enriched in cell adhesion and extracellular matrix-receptor interaction. BRCA1 was identified as a transcription factor and TSG, and COL18A1 and LAMC2 were identified as a TSG and TAG, respectively. The upregulated DEGs had higher degrees in the protein–protein interaction network and module, such as PCNA, CDK1, and MAD2L1, and the heat map showed they were clustered in the functions of cell cycle and division. These results may demonstrate the potential roles of DEGs such as CDK1, BRCA1, COL18A1, and LAMC2 in the mechanism of MM.

Articular cartilage injury and defect caused by trauma and chronic osteoarthritis vascularity are very common, while the repair of injured cartilage remains a great challenge due to its limited healing capacity. Stem cell-based tissue engineering provides a promising treatment option for injured articular cartilage because of the cells potential for multiple differentiations. However, its application has been largely limited by stem cell type, number, source, proliferation, and differentiation. We hypothesized that (1) adipose-derived stem cells are ideal seed cells for articular cartilage repair because of their accessibility and abundance and (2) the microenvironment of articular cartilage could induce adipose-derived stem cells (ADSCs) to differentiate into chondrocytes. In order to test our hypotheses, we isolated stem cells from rabbit adipose tissues and cocultured these ADSCs with rabbit articular cartilage chondrocytes. We found that when ADSCs were cocultured with chondrocytes, the proliferation of articular cartilage chondrocytes was promoted, the apoptosis of chondrocytes was inhibited, and the osteogenic and chondrogenic differentiation of ADSCs was enhanced. The study on the mechanism of this coculture system indicated that the role of this coculture system is similar to the function of TGF-β1 in the promotion of chondrocytes.

Geological faults impair tunnel stability during earthquakes. This study establishes a tunnel dynamic stability evaluation index based on load/unload response ratio (LURR) theory. It considers a seismic wave as a load/unload parameter and tunnel structure strain response as a response parameter. The rationale behind this evaluation index and the factors affecting tunnel stability across fault zones under seismic conditions are investigated. Compared to the traditional dynamic instability criterion, the LURR accurately measures the degree of structural deviation from the steady state and better determines the potential destabilization region of the structure. As the peak value of the input seismic wave increases, the LURRs of the more unstable parts increase, while the LURRs of the stable parts remain unchanged. According to LURR theory, the size of the range affected by the fault on the tunnel during an earthquake depends mainly on inherent fault properties (i.e., the dip angle, strike, and thickness), independent of the earthquake intensity. Because the LURR can theoretically be infinite, its dynamic instability threshold cannot be determined accurately. [ABSTRACT FROM AUTHOR]