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Abstract Background Disulfidptosis is a newly identified mechanism of cell death triggered by disulfide stress. Thus, gaining a comprehensive understanding of the disulfidptosis signature present in gastric cancer (GC) could greatly enhance the development of personalized treatment strategies for this disease. Methods We employed consensus clustering to identify various subtypes of disulfidptosis and examined the distinct tumor microenvironment (TME) associated with each subtype. The Disulfidptosis (Dis) score was used to quantify the subtype of disulfidptosis in each patient. Subsequently, we assessed the predictive value of Dis score in terms of GC prognosis and immune efficacy. Finally, we conducted in vitro experiments to explore the impact of Collagen X (COL10A1) on the progression of GC. Results Two disulfidptosis-associated molecular subtypes (Discluster A and B) were identified, each with distinct prognosis, tumor microenvironment (TME), immune cell infiltration, and biological pathways. Discluster A, characterized by high expression of disulfidptosis genes, exhibited a high immune score but poor prognosis. Furthermore, the Dis score proved useful in predicting the prognosis and immune response in GC patients. Those in the low Dis score group showed better prognosis and increased sensitivity to immunotherapy. Finally, our experimental findings validated that downregulation of COL10A1 expression attenuates the proliferation and migration capabilities of GC cells while promoting apoptosis. Conclusions This study demonstrates that the disulfidptosis signature can assist in risk stratification and personalized treatment for patients with GC. The results offer valuable theoretical support for anti-tumor strategies.

Indirect aggression has become a prevalent phenomenon that erodes the social media environment. Due to the expense and the difficulty in determining objectively what constitutes indirect aggression, the traditional self-reporting questionnaire is hard to be employed in the current cyber area. In this study, we present a model for predicting indirect aggression online based on pre-trained models. Building on Weibo users’ social media activities, we constructed basic, dynamic, and content features and classified indirect aggression into three subtypes: social exclusion, malicious humour, and guilt induction. We then built the prediction model by combining it with large-scale pre-trained models. The empirical evidence shows that this prediction model (ERNIE) outperforms the pre-trained models and predicts indirect aggression online much better than the models without extra pre-trained information. This study offers a practical model to predict users’ indirect aggression. Furthermore, this work contributes to a better understanding of indirect aggression behaviors and can support social media platforms’ organization and management.

To ensure a thorough examination of the high-sulfur natural gas field station vent piping, it is proposed to use numerical simulation and field combination of methods, based on the wall liquid phase aggregation and droplet erosion of high-sulfur natural gas field station low-pressure vent pipeline corrosion simulation prediction technology to carry out a study, analyze the flow field situation and liquid phase deposition in different parts of the vent pipeline, to get the corrosion-prone parts, and compared with the on-site corrosion, the accuracy of 90% is reached. The accuracy reaches 90%. Verify the application of CFD simulation in the pipeline is not easy to detect the corrosion of the parts of the pipeline has a good prediction of corrosion prone to prioritize the corrosion-prone parts of the inspection, to prevent the occurrence of corrosion accidents.

Abstract Background Ubiquitination is a critical post-translational modification which can be reversed with an enzyme family known as deubiquitinating enzymes (DUBs). It has been reported that dysregulation of deubiquitination leads to carcinogenesis. As a member of the DUBs family, proteasome 26 S subunit non-ATPase 7 (PSMD7) serves as an underlying tumour-promoting factor in multiple cancers. However, the clinical significance and biological functions of PSMD7 in pancreatic cancer (PC) remain unclear. Results In this study, we first reported frequent overexpression of PSMD7 in PC tissues, and high levels of PSMD7 were markedly linked to shorter survival and a malignant phenotype in PC patients. An array of in vitro and in vivo gain/loss-of-function tests revealed that PSMD7 facilitates the progression of PC cells. Additionally, we found that PSMD7 promotes PC cell progression by activating the Notch homolog 1 (Notch1) signalling. Interestingly, in PC cells, the inhibitory effect of PSMD7 knockdown on cellular processes was comparable to that observed upon Notch1 knockdown. Mechanistically, PSMD7 deubiquitinated and stabilised sex determining region Y (SRY)-box 2 (SOX2), a key mediator of Notch1 signalling. The stabilisation of SOX2, mediated by PSMD7, dramatically increased SOX2 protein levels, subsequently activating the Notch1 pathway. Finally, restoration of SOX2 expression abrogated the PSMD7-silenced antitumour effect. Conclusions Taken together, our work identifies and validates PSMD7 as a promoter of PC progression through augmentation of the Notch1 signalling pathway mediated by SOX2. This finding suggests that PSMD7 holds promise as a potential therapeutic target for the management of this refractory disease.

BackgroundExposure to air pollutants O3 and PM2.5 is closely related to population mortality. Most of the domestic research findings are for residents in coastal areas, and less for those in the central and western regions. ObjectiveTo investigate the acute effects of O3 and PM2.5 on the mortality of residents in a city of central China.MethodsData were collected on atmospheric pollutants, meteorological data, and population mortality in a city of central China from January 1, 2015 to June 30, 2021. Meteorological data included daily average temperature, air pressure, and relative humidity. Atmospheric pollution data included daily mean concentrations of PM2.5, PM10, SO2, NO2, and CO and maximum 8 h O3. Generalized additive model with Poisson distribution was used for estimating the relationships between air pollutants (O3 and PM2.5) and population mortality, and further stratified by age, gender, and education. ResultsThe daily maximum 8 h average concentration of O3 in the city during the study period was 94.38 μɡ·m−3 and the daily average concentration of PM2.5 was 55.56 μɡ·m−3. In the single-pollutant model, the correlations between O3 concentration and total deaths as well as deaths due to respiratory, circulatory, hypertension, coronary heart disease, and stroke were strongest at lag02, lag2, lag02, lag0, lag02, and lag0, and for every 10 μɡ·m−3 increase in concentration of O3, the associated ER (95%CI) values of daily mortality were increased by 0.09% (−0.08%–0.25%), 0.35% (0–0.71%), 0.43% (0.18%–0.68%), 0.45% (0.02%–0.91%), 0.59% (0.16%–1.02%), and 0.33% (0.01%–0.65%), respectively. The effect of O3 on total mortality was not statistically significant (P>0.05). The correlations between PM2.5 concentration and total deaths, as well as deaths due to respiratory, circulatory, hypertension, coronary heart disease, and stroke were strongest at lag1, lag5, lag01, lag05, lag04, and lag01, and for every 10 μɡ·m−3 increase in concentration of PM2.5, the associated ER (95%CI) values of daily mortality increased by 0.02% (−0.09–0.13%), 0.25% (0.01%–0.50%), 0.35% (0.16%–0.54%), 1.18% (0.59%–1.77%), 0.17% (−0.13%–0.40%), and 0.65% (0.38%–0.92%), respectively, with no statistically significant effects of PM2.5 on total mortality and mortality due to coronary heart disease (P>0.05). During warm season (from May to October), the ER (95%CI) values of total deaths per 10 μɡ·m−3 increase in O3 in male, people aged 6~65 years, people aged >65 years, and people below high school education were 0.46% (0.16%–0.75%), 0.38% (0.08%–0.68%), 0.41% (0.14%–0.66%), and 0.38% (0.14%–0.61%), respectively, while the O3 effect was not statistically significant (P>0.05) during cool season (from November to April). ConclusionsAtmospheric pollutants (O3 and PM2.5) have acute effects on mortality in the city, with the elderly, people with less than a high school education, and those with circulatory disease being more sensitive to O3 and PM2.5 exposures.

BackgroundIn recent years, our country's atmospheric particulate matter pollution has improved significantly, while ozone (O3) pollution has become increasingly serious. As a secondary pollutant, O3 is closely related to human health. ObjectiveTo study the effect of short-term exposure to ozone in ambient air on population mortality in China. MethodsA computer search with key words of "ozone or O3", "death", and "time series" in Chinese or "ozone", "mortality", and "China" in English was performed in Web of Science, PubMed, China National Knowledge Infrastructure, Wanfang, and VIP databases to find literature on effects of short-term ozone exposure on population mortality covering a time period from January 1, 1990 to December 31, 2021. According to a set of inclusion and exclusion criteria developed for this study, literaturescreening, quality evaluation, andrelevant data extraction were carried out. Finally, R 4.1.2 software was used to perform meta-analysis to estimate target effect sizes. ResultsA total of 978 articles were retrieved. According to the inclusion and exclusion criteria, 18 articles were finally included, including 39 effect size estimates. The results showed that every 10 μɡ·m−3 increase in ambient ozone concentration was associated with an increase of 0.45% (95%CI: 0.39%-0.51%), 0.50% (95%CI: 0.33%-0.68%), and 0.60% (95%CI: 0.48%-0.72%) in total, respiratory, and cardiovascular disease mortalities , respectively. The results of subgroup analysis by age, sex, and season showed that when ozone concentration increased 10 μɡ·m−3, an increase of 0.34% (95%CI: 0.17%-0.51%) in mortality was observed in the ≥ 65-year-old population, higher than 0.09% (95%CI: −0.21%-0.39%) increase in the

BackgroundPrevious studies have demonstrated that PANoptosis is strongly correlated with cancer immunity and progression. This study aimed to develop a PANoptosis-related signature (PANRS) to explore its potential value in predicting the prognosis and immunotherapy response of hepatocellular carcinoma (HCC).MethodsBased on the expression of PANoptosis-related genes, three molecular subtypes were identified. To construct a signature, the differentially expressed genes between different molecular subtypes were subjected to multivariate least absolute shrinkage and selection operator Cox regression analyses. The risk scores of patients in the training set were calculated using the signature. The patients were classified into high-risk and low-risk groups based on the median risk scores. The predictive performance of the signature was evaluated using Kaplan-Meier plotter, receiving operating characteristic curves, nomogram, and calibration curve. The results were validated using external datasets. Additionally, the correlation of the signature with the immune landscape and drug sensitivity was examined. Furthermore, the effect of LPCAT1 knockdown on HCC cell behavior was verified using in vitro experiments.ResultsThis study developed a PANRS. The risk score obtained by using the PANRS was an independent risk factor for the prognosis of patients with HCC and exhibited good prognostic predictive performance. The nomogram constructed based on the risk score and clinical information can accurately predicted the survival probability of patients with HCC. Patients with HCC in the high-risk groups have high immune scores and tend to generate an immunosuppressive microenvironment. They also exhibited a favorable response to immunotherapy, as evidenced by high tumor mutational burden, high immune checkpoint gene expression, high human leukocyte antigen gene expression, low tumor immune dysfunction and low exclusion scores. Additionally, the PANRS enabled the identification of 15 chemotherapeutic agents, including sorafenib, for patients with HCC with different risk levels, guiding clinical treatment. The signature gene LPCAT1 was upregulated in HCC cell lines. LPCAT1 knockdown markedly decreased HCC cell proliferation and migration.ConclusionPANRS can accurately predict the prognosis and immunotherapy response of patients with HCC and consequently guide individualized treatment.

Abstract Pancreatic cancer (PC) is one of the deadliest malignant tumors, and its resistance to gemcitabine chemotherapy is the primary reason for poor prognosis in patients. Ubiquitin-like protein FAT10 has recently been reported to promote tumor chemotherapy resistance. In this study, the expression of FAT10 in PC was significantly higher than that in adjacent noncancerous tissues. Increased expression of FAT10 in PC was related to a late TNM stage and decreased overall survival. Functional experiments revealed that downregulating the expression of FAT10 inhibits the proliferation and epithelial-mesenchymal transition (EMT) of PC cells, promotes the apoptosis of PC cells, and enhances sensitivity to gemcitabine chemotherapy. In addition, upregulation of FAT10 increased the expression of FOXM1 protein. The effect of downregulating FAT10 was reversed by FOXM1 overexpression, and FOXM1 knockdown inhibited EMT driven by FAT10 overexpression. Mechanistically, FAT10 stabilized the expression of FOXM1 by competing with ubiquitin to bind FOXM1 and inhibiting the ubiquitination-mediated degradation of FOXM1. In conclusion, the FAT10-FOXM1 axis is a pivotal driver of PC proliferation and gemcitabine resistance, and the results provide novel insights into chemotherapy resistance in PC.

Building occupation is common for pipelines in urban area, which likely leads to the subsidence of foundations and deformation of pipelines and induces accidents such as oil and gas leakage, even explosions. In this study, a pipeline reliability model based on stress-strength interference was established. Meanwhile, the distribution of three random parameters under building occupation, including the additional stress under building occupation, the maximum reduced stress of dangerous pipeline sections and the pipe yield strength, were analyzed based on the theory of structural reliability. In order to achieve equivalent normalization, the variables in abnormal distribution were processed according to the classic JC algorithm, and the iterative initial value of the unknown was set based on the structural linearity performance functions to improve the convergence speed and precision of the algorithm. In addition, a reliability model of gas pipeline under the occupation of framed and brick-concrete buildings based on M-JC algorithm was established, and the reliability of the occupied pipeline was analyzed by implementing the M-JC algorithm in combination with Matlab programming. As shown by the results, the reliability of pipeline sections under the occupation of the framed and brick-concrete buildings is 0.985 2 and 0.999 8, respectively, indicating that the surface overburden load has little effect on the undamaged pipeline. In addition, the error between the results of M-JC algorithm and JC algorithm is very small, with a relative error less than 1%. Generally, the research results are applicable to the analysis on reliability of pipeline under building occupation and have reference value to the safe operation of pipelines and the urban construction planning.

BackgroundHemorrhagic fever with renal syndrome (HFRS) is a significant zoonotic disease mainly transmitted by rodents. However, the determinants of its spatiotemporal patterns in Northeast China remain unclear. ObjectiveThis study aimed to investigate the spatiotemporal dynamics and epidemiological characteristics of HFRS and detect the meteorological effect of the HFRS epidemic in Northeastern China. MethodsThe HFRS cases of Northeastern China were collected from the Chinese Center for Disease Control and Prevention, and meteorological data were collected from the National Basic Geographic Information Center. Times series analyses, wavelet analysis, Geodetector model, and SARIMA model were performed to identify the epidemiological characteristics, periodical fluctuation, and meteorological effect of HFRS in Northeastern China. ResultsA total of 52,655 HFRS cases were reported in Northeastern China from 2006 to 2020, and most patients with HFRS (n=36,558, 69.43%) were aged between 30-59 years. HFRS occurred most frequently in June and November and had a significant 4- to 6-month periodicity. The explanatory power of the meteorological factors to HFRS varies from 0.15 ≤ q ≤ 0.01. In Heilongjiang province, mean temperature with a 4-month lag, mean ground temperature with a 4-month lag, and mean pressure with a 5-month lag had the most explanatory power on HFRS. In Liaoning province, mean temperature with a 1-month lag, mean ground temperature with a 1-month lag, and mean wind speed with a 4-month lag were found to have an effect on HFRS, but in Jilin province, the most important meteorological factors for HFRS were precipitation with a 6-month lag and maximum evaporation with a 5-month lag. The interaction analysis of meteorological factors mostly showed nonlinear enhancement. The SARIMA model predicted that 8,343 cases of HFRS are expected to occur in Northeastern China. ConclusionsHFRS showed significant inequality in epidemic and meteorological effects in Northeastern China, and eastern prefecture-level cities presented a high risk of epidemic. This study quantifies the hysteresis effects of different meteorological factors and prompts us to focus on the influence of ground temperature and precipitation on HFRS transmission in future studies, which could assist local health authorities in developing HFRS-climate surveillance, prevention, and control strategies targeting high-risk populations in China.

Abstract Background An increasing number of studies have shown that immune-related long noncoding RNAs (lncRNAs) do not require a unique expression level. This finding may help predict the survival and drug sensitivity of patients with colon cancer. Methods We retrieved original transcriptome and clinical data from The Cancer Genome Atlas (TCGA), sorted the data, differentiated mRNAs and lncRNAs, and then downloaded immune-related genes. Coexpression analysis predicted immune-related lncRNAs (irlncRNAs) and univariate analysis identified differentially expressed irlncRNAs (DEirlncRNAs). We have also amended the lasso pending region. Next, we compared the areas under the curve (AUCs), counted the Akaike information standard (AIC) value of the 3-year receiver operating characteristic (ROC) curve, and determined the cutoff point to establish the best model to differentiate the high or low disease risk group of colon cancer patients. Results We reevaluated the patients regarding the survival rate, clinicopathological features, tumor-infiltrating immune cells, immunosuppressive biomarkers, and chemosensitivity. A total of 155 irlncRNA pairs were confirmed, 31 of which were involved in the Cox regression model. After the colon cancer patients were regrouped according to the cutoff point, we could better distinguish the patients based on adverse survival outcomes, invasive clinicopathological features, the specific tumor immune cell infiltration status, high expression of immunosuppressive biomarkers, and low chemosensitivity. Conclusions In this study, we established a characteristic model by pairing irlncRNAs to better predict the survival rate, chemotherapy efficacy, and prognostic value of patients with colon cancer.

Algicidal bacteria can inhibit the growth of algae or lyse algal cells, thus playing roles in shaping aquatic microbial communities and maintaining the functions of aquatic ecosystems. Nevertheless, our understanding of their diversities and distributions remains limited. In this study, we collected water samples from 17 freshwater sites in 14 cities in China and screened a total of 77 algicidal bacterial strains using several prokaryotic cyanobacteria and eukaryotic algae as target strains. According to their target-specificities, these strains were classified into three subgroups, cyanobacterial algicidal bacteria, algal algicidal bacteria, and broad-target algicidal bacteria, each displaying distinctive compositions and geographical distribution patterns. They are assigned to Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes bacterial phyla, of which Pseudomonas and Bacillus are the most abundant gram-negative and gram-positive genus, respectively. A number of bacterial strains, such as Inhella inkyongensis and Massilia eburnean, are suggested as new algicidal bacteria. The diverse taxonomies, algal-inhibiting abilities and distributions of these isolates have suggested that there are rich algicidal bacterial resources in these aquatic environments. Our results provide new microbial resources for algal-bacterial interaction studies, and shed new insights into how algicidal bacteria can be used in the control of harmful algal blooms, as well as in algal biotechnology.

BackgroundTreatment of cancer with pyroptosis is an emerging strategy. Molecular subtypes based on pyroptosis-related genes(PRGs) seem to be considered more conducive to individualized therapy. It is meaningful to construct a pyroptosis molecular subtypes-related prognostic signature (PMSRPS) to predict the overall survival (OS) of patients with pancreatic adenocarcinoma(PAAD) and guide treatment.MethodsBased on the transcriptome data of 23 PRGs, consensus clustering was applied to divide the TCGA and GSE102238 combined cohort into three PRGclusters. Prognosis-related differentially expressed genes(DEGs) among PRGclusters were subjected to LASSO Cox regression analysis to determine a PMSRPS. External cohort and in vitro experiments were conducted to verify this PMSRPS. The CIBERSORT algorithm, the ESTIMATE algorithm and the Immunophenoscore (IPS) were used to analyze the infiltrating abundance of immune cells, the tumor microenvironment (TME), and the response to immunotherapy, respectively. Wilcoxon analysis was used to compare tumor mutational burden (TMB) and RNA stemness scores (RNAss) between groups. RT-qPCR and in vitro functional experiments were used for evaluating the expression and function of SFTA2.ResultsBased on three PRGclusters, 828 DEGs were obtained and a PMSRPS was subsequently constructed. In internal and external validation, patients in the high-risk group had significantly lower OS than those in the low-risk group and PMSRPS was confirmed to be an independent prognostic risk factor for patients with PAAD with good predictive performance. Immune cell infiltration abundance and TME scores indicate patients in the high-risk group have typical immunosuppressive microenvironment characteristics. Analysis of IPS suggests patients in the high-risk group responded better to novel immune checkpoint inhibitors (ICIs) than PD1/CTLA4. The high-risk group had higher TMB and RNAss. In addition, 10 potential small-molecule compounds were screened out. Finally, we found that the mRNA expression of SFTA2 gene with the highest risk coefficient in PMSRPS was significantly higher in PAAD than in paracancerous tissues, and knockdown of it significantly delayed the progression of PAAD.ConclusionsPMSRPS can well predict the prognosis, TME and immunotherapy response of patients with PAAD, identify potential drugs, and provide treatment guidance based on individual needs.

The plant-based refers to plant-based raw materials or products that are available as the source of protein and fat. Utilization and development of walnuts as a plant-based, resulting in a high-quality protein-rich walnut plant-based product: walnut protein powder and walnut peptides. Progress in research on the application of walnuts as a plant-based has been advanced, solving the problem of wasted resources and environmental pollution caused by the fact that walnut residue, a product of walnuts after oil extraction, is often thrown away as waste, or becomes animal feed or compost. This paper reviews and summarizes the research and reports on walnut plant-based at home and abroad, focusing on the application of walnut plant-based in the preparation process (enzymatic and fermentation methods) and the biological activity of the walnut protein and walnut peptide, to provide a theoretical basis for the further processing of walnuts as a walnut plant-based. It can make full use of walnut resources and play its nutritional and health care value, develop and build a series of walnut plant-based products, improve the competitiveness of walnut peptide products, turn them into treasure, and provide more powerful guidance for the development of food and medicine health industry in Yunnan.

BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies in the world, with high incidence, high malignancy, and low survival rate. Cuproptosis is a novel form of cell death mediated by lipoylated TCA cycle proteins-mediated novel cell death pathway and is highly associated with mitochondrial metabolism. However, the relationship between the expression level of cuproptosis-related genes (CRGs) and the prognosis of HCC is still unclear.MethodsCombining the HCC transcriptomic data from The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus (GEO) databases, we identified the differentially expressed cuproptosis-related genes (DECRGs) and obtained the prognosis-related DECRGs through univariate regression analysis.LASSO and multivariate COX regression analyses of these DECRGs yielded four genes that were used to construct the signature. Next, we use ROC curves to evaluate the performance of signatures. The tumor microenvironment, immune infiltration, tumor mutation load, half-maximum suppression concentration, and immunotherapy effects were also compared between the low-risk and high-risk groups. Finally, we analyzed the expression level, prognosis, and immune infiltration correlation on the four genes that constructed the model.ResultsFour DECRGs s were used to construct the signature. The ROC curves indicated that signature can better assess the prognosis of HCC patients. Patients were grouped according to the signature risk score. Patients in the low-risk group had a significantly longer survival time than those in the high-risk group. Furthermore, the tumor mutation burden (TMB) values were associated with the risk score and the higher-risk group had a higher proportion of TP53 mutations than the low-risk group.ESTIMATE analysis showed significant differences in stromal scores between the two groups.N6-methyladenosine (m6A) and multiple immune checkpoints were expressed at higher levels in the high-risk group. Then, we found that signature score correlated with chemotherapeutic drug sensitivity and immunotherapy efficacy in HCC patients. Finally, we further confirmed that the four DECRGs genes were associated with the prognosis of HCC through external validation.ConclusionsWe studied from the cuproptosis perspective and developed a new prognostic feature to predict the prognosis of HCC patients. This signature with good performance will help physicians to evaluate the overall prognosis of patients and may provide new ideas for clinical decision-making and treatment strategies.

BackgroundGenomic instability (GI) plays a crucial role in the development of various cancers including hepatocellular carcinoma. Hence, it is meaningful for us to use long non-coding RNAs related to genomic instability to construct a prognostic signature for patients with HCC.MethodsCombining the lncRNA expression profiles and somatic mutation profiles in The Cancer Genome Atlas database, we identified GI-related lncRNAs (GILncRNAs) and obtained the prognosis-related GILncRNAs through univariate regression analysis. These lncRNAs obtained risk coefficients through multivariate regression analysis for constructing GI-associated lncRNA signature (GILncSig). ROC curves were used to evaluate signature performance. The International Cancer Genomics Consortium (ICGC) cohort, and in vitro experiments were used for signature external validation. Immunotherapy efficacy, tumor microenvironments, the half-maximal inhibitory concentration (IC50), and immune infiltration were compared between the high- and low-risk groups with TIDE, ESTIMATE, pRRophetic, and ssGSEA program.ResultsFive GILncRNAs were used to construct a GILncSig. It was confirmed that the GILncSig has good prognostic evaluation performance for patients with HCC by drawing a time-dependent ROC curve. Patients were divided into high- and low-risk groups according to the GILncSig risk score. The prognosis of the low-risk group was significantly better than that of the high-risk group. Independent prognostic analysis showed that the GILncSig could independently predict the prognosis of patients with HCC. In addition, the GILncSig was correlated with the mutation rate of the HCC genome, indicating that it has the potential to measure the degree of genome instability. In GILncSig, LUCAT1 with the highest risk factor was further validated as a risk factor for HCC in vitro. The ESTIMATE analysis showed a significant difference in stromal scores and ESTIMATE scores between the two groups. Multiple immune checkpoints had higher expression levels in the high-risk group. The ssGSEA results showed higher levels of tumor-antagonizing immune cells in the low-risk group compared with the high-risk group. Finally, the GILncSig score was associated with chemotherapeutic drug sensitivity and immunotherapy efficacy of patients with HCC.ConclusionOur research indicates that GILncSig can be used for prognostic evaluation of patients with HCC and provide new insights for clinical decision-making and potential therapeutic strategies.

BackgroundGenomic instability (GI) is a critical feature of cancer which plays a key role in the occurrence and development of pancreatic adenocarcinoma (PAAD). Long non-coding RNA (LncRNA) is an emerging prognostic biomarker because it is involved in regulating GI. Recently, researchers used such GI-related LncRNAs (GILncRNAs) to establish a prognostic signature for patients with cancer and helped in predicting the overall prognosis of the patients. However, it is evident that patients with PAAD still lack such prognostic signature constructed with GILncRNA.MethodsThe present study screened GILncRNAs from 83 patients with PAAD. Prognosis-related GILncRNAs were identified by univariate Cox regression analysis. The correlation coefficients of these GILncRNAs were obtained by multivariate Cox regression analysis and used to construct a signature. The signature in the present study was then assessed through survival analysis, mutation correlation analysis, independent prognostic analysis, and clinical stratification analysis in the training set and validated in the testing as well as all TCGA set. The current study performed external clinical relevance validation of the signature and validated the effect of AC108134.2 in GILncSig on PAAD using in vitro experiments. Finally, the function of GILncRNA signature (GILncSig) dependent on Gene Ontology enrichment analysis was explored and chemotherapeutic drug sensitivity analysis was also performed.ResultsResults of the present study found that a total of 409 GILncRNAs were identified, 5 of which constituted the prognostic risk signature in this study, namely, AC095057.3, AC108134.2, AC124798.1, AL606834.1, and AC104695.4. It was found that the signature of the present study was better than others in predicting the overall survival and applied to patients with PAAD of all ages, genders, and tumor grades. Further, it was noted that the signature of the current study in the GSE102238, was correlated with tumor length, and tumor stage of patients with PAAD. In vitro, functional experiments were used in the present study to validate that AC108134.2 is associated with PAAD genomic instability and progression. Notably, results of the pRRophetic analysis in the current study showed that the high-risk group possessed reverse characteristics and was sensitive to chemotherapy.ConclusionsIn conclusion, it was evident that the GILncSig used in the present study has good prognostic performance. Therefore, the signature may become a potential sensitive biological indicator of PAAD chemotherapy, which may help in clinical decision-making and management of patients with cancer.

Due to the special physical properties of shale gas reservoirs, it is necessary to adopt unconventional and standardized technologies for its surface engineering construction. In addition, the surface engineering design of shale gas reservoirs in China faces many difficulties, such as high uncertainty of the gathering and transportation scale, poor adaptability of pipe network and station layout, difficult matching of the process equipments, and boosting production at the late stage. In view of these problems, the surface engineering construction of shale gas reservoirs should follow the principles of “standardized design, modularized construction and skid mounted equipment”. In this paper, standardized surface engineering design technologies for shale gas reservoirs were developed with the “standardized well station layout, universal process, modular function zoning, skid mounted equipment selection, intensive site design, digitized production management” as the core, after literature analysis and technology exploration were carried out. Then its application background and surface technology route were discussed with a typical shale gas field in Sichuan–Chongqing area as an example. Its surface gathering system was designed in a standardized way, including standardized process, the modularized gathering and transportation station, serialized dehydration unit and intensive layout, and remarkable effects were achieved. A flexible, practical and reliable ground production system was built, and a series of standardized technology and modularized design were completed, including cluster well platform, set station, supporting projects. In this way, a system applicable to domestic shale gas surface engineering construction is developed.