Improved Synthesis of Hollow Fiber SSZ-13 Zeolite Membranes for High-Pressure CO2/CH4 Separation.

High-silica CHA zeolite membranes are highly desired for natural gas upgrading because of their separation performance in combination with superior mechanical and chemical stability. However, the narrow synthesis condition range significantly constrains scale-up preparation. Herein, we propose a facile interzeolite conversion approach using the FAU zeolite to prepare SSZ-13 zeolite seeds, featuring a shorter induction and a longer crystallization period of the membrane synthesis on hollow fiber substrates. The membrane thickness was constant at ~3 µm over a wide span of synthesis time (24-96 h), while the selectivity (separation efficiency) was easily improved by extending the synthesis time without compromising permeance (throughput). At 0.2 MPa feed pressure and 303 K, the membranes showed an average CO2 permeance of (5.2±0.5)×10-7 mol m-2 s-1 Pa-1 (1530 GPU), with an average CO2/CH4 mixture selectivity of 143±7. Minimal defects ensure a high selectivity of 126 with a CO2 permeation flux of 0.4 mol m-2 s-1 at 6.1 MPa feed pressure, far surpassing requirements for industrial applications. The feasibility for successful scale-up of our approach was further demonstrated by the batch synthesis of 40 cm-long hollow fiber SSZ-13 zeolite membranes exhibiting CO2/CH4 mixture selectivity up to 400 (0.2 MPa feed pressure and 303 K) without using sweep gas.

Deubiquitinase PSMD7 facilitates pancreatic cancer progression through activating Nocth1 pathway via modifying SOX2 degradation.

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.

PANoptosis subtypes predict prognosis and immune efficacy in gastric cancer.

PANoptosis is a form of inflammatory programmed cell death that is regulated by the PANoptosome. This PANoptosis possesses key characteristics of pyroptosis, apoptosis, and necroptosis, yet cannot be fully explained by any of these cell death modes. The unique nature of this cell death mechanism has garnered significant interest. However, the specific role of PANoptosis-associated features in gastric cancer (GC) is still uncertain. Patients were categorized into different PAN subtypes based on the expression of genes related to the PANoptosome. We conducted a systematic analysis to investigate the variations in prognosis and tumor microenvironment (TME) among these subtypes. Furthermore, we developed a risk score, called PANoptosis-related risk score (PANS), which is constructed from genes associated with the PANoptosis. We comprehensively analyzed the correlation between PANS and GC prognosis, TME, immunotherapy efficacy and chemotherapeutic drug sensitivity. Additionally, we performed in vitro experiments to validate the impact of Keratin 7 (KRT7) on GC. We identified two PAN subtypes (PANcluster A and B). PANoptosome genes were highly expressed in PANcluster A. PANcluster A has the characteristics of favorable prognosis, abundant infiltration of anti-tumor lymphocytes, and sensitivity to immunotherapy, thus it was categorized as an immune-inflammatory type. Meanwhile, our constructed PANS can effectively predict the prognosis and immune efficacy of GC. Patients with low PANS have a good prognosis, and have the characteristics of high tumor mutation load (TMB), high microsatellite instability (MSI), low tumor purity and sensitivity to immunotherapy. In addition, PANS can also identify suitable populations for different chemotherapy drugs. Finally, we confirmed that KRT7 is highly expressed in GC. Knocking down the expression of KRT7 significantly weakens the proliferation and migration abilities of GC cells. The models based on PANoptosis signature help to identify the TME features of GC and can effectively predict the prognosis and immune efficacy of GC. Furthermore, the experimental verification results of KRT7 provide theoretical support for anti-tumor treatment.

Development of a behaviour pattern-based testing approach for coupled socioeconomic and environmental models.

Understanding the interactions between human and environmental systems is key to sustainable environmental management. Dynamically Coupled Socioeconomic system dynamics models integrated with physically-based Environmental Models (DCSEMs) are promising tools to appropriately capture the non-linear relationships between complex socioeconomic and biophysical systems, thereby supporting sustainable environmental management. However, existing approaches for testing integrated models are commonly based on the point-to-point analysis of model outputs, which is not suitable for DCSEMs that are behaviour pattern oriented. Consequently, the lack of well-defined behaviour pattern-based approaches has limited the adaptability of DCSEMs. To address this gap, this study proposes a novel behaviour pattern-based model testing approach that includes global sensitivity analysis (GSA), auto-calibration algorithms, and evaluation to assess behaviour pattern similarities between model outputs and real-world trends. The proposed approach is demonstrated through a real-world case study, in which an existing DCSEM is calibrated and evaluated to simulate water table depth in the Rechna Doab region of Pakistan. Compared to the conventional numerical point approach, the proposed approach is better suited for DCSEMs, as it replicates observed system behaviour patterns (as opposed to observed point values) over time. Furthermore, the outcomes of the Theil inequality statistical analysis and parameter distribution analysis provide evidence that the suggested approach is effective in testing and improving the performance of the DCSEM by capturing the spatial heterogeneity within the study area. The proposed behaviour-pattern testing procedure is a useful approach for model testing in data-limited, spatially-distributed DCSEMs.

Identification of molecular subtypes based on PANoptosis-related genes and construction of a signature for predicting the prognosis and response to immunotherapy response in hepatocellular carcinoma.

Background: Previous 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). Methods: Based 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. Results: This 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. Conclusion: PANRS can accurately predict the prognosis and immunotherapy response of patients with HCC and consequently guide individualized treatment.

Gut microbiota regulate migration of lymphocytes from gut to lung.

The community of microorganisms known as gut microbiota that lives in the intestine confers significant health benefits on its host, primarily in the form of immunological homeostasis regulation. Gut microbiota not only can shape immune responses in the gut but also in other organs. This review focus on the gut-lung axis. Aberrant gut microbiota development is associated with greater lung disease susceptibility and respiratory disease induced by a variety of pathogenic bacteria. They are known to cause changes in gut microbiota. Recent research has found that immune cells in the intestine migrate to distant lung to exert anti-infective effects. Moreover, evidence indicates that the gut microbiota and their metabolites influence intestinal immune cells. Therefore, we suspect that intestine-derived immune cells may play a significant role against pulmonary pathogenic infections by receiving instructions from gut microbiota.

An immunogenic cell death-related signature predicts prognosis and immunotherapy response in stomach adenocarcinoma.

The immunogenic cell death (ICD) is a specific type of regulatory cell death (RCD), which induces adaptive immunity against antigens of dead cells. ICDs have received increasing attention for their potential role in tumor microenvironment reprogramming and immunotherapy. However, the relationship between ICD-related features and stomach adenocarcinoma (STAD) prognosis, immune cell infiltration and immunotherapy remains unclear. Patients were divided into different ICD-related subtypes by consensus clustering. The differences in prognosis, Tumor microenvironment (TME), and immune checkpoint expression between different ICD-related subtypes were systematically assessed. Additionally, we constructed an ICD-related gene risk score (ICDRS). We systematically analyzed the correlation between ICDRS and prognosis, TME, immunotherapy response and drug sensitivity of gastric cancer. In addition, we explored the role of TGM2 in promoting gastric cancer progression through in vitro experiments. We identified three ICD-associated subtypes by consensus clustering. The ICD gene was highly expressed in Cluster B. Compared with the other two subtypes, Cluster B had better prognosis, higher immune response signaling activity, massive immune cell infiltration and lower tumor purity. Immune checkpoint (ICP) and human leukocyte antigen (HLA) related genes were also highly expressed in Cluster B. In addition, we found that ICDRS is an effective indicator for predicting the prognosis and immune efficacy of STAD. The low ICDRS group has the characteristics of good prognosis, high tumor mutation burden (TMB), high microsatellite instability (MSI), and sensitivity to immunotherapy, while the high ICDRS group is prone to immune escape and immunotherapy resistance. In addition, we found that down-regulating TGM2 gene can inhibit the proliferation and migration of gastric cancer cells through in vitro experiments. Our study found that the model based on ICD features is helpful to clarify the TME characteristics of STAD, and has important clinical significance for evaluating the prognosis and immunotherapy response of STAD patients. TGM2 plays an important role in the progression of STAD, suggesting that TGM2 can be used as a new target for the treatment of STAD.

The Spatiotemporal Pattern and Its Determinants of Hemorrhagic Fever With Renal Syndrome in Northeastern China: Spatiotemporal Analysis.

BACKGROUND: Hemorrhagic 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. OBJECTIVE: This study aimed to investigate the spatiotemporal dynamics and epidemiological characteristics of HFRS and detect the meteorological effect of the HFRS epidemic in Northeastern China. METHODS: The 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. RESULTS: A 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. CONCLUSIONS: HFRS 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.

Association between the NEP rs701109 polymorphism and the clinical efficacy and safety of sacubitril/valsartan in Chinese patients with heart failure.

OBJECTIVE: Sacubitril/valsartan is a commonly used medicine for treating heart failure (HF) patients, but the treatment effects significantly vary. Neprilysin (NEP) and carboxylesterase 1 (CES1) play an important role in the efficacy of sacubitril/valsartan. The purpose of this study was to explore the relationship between NEP and CES1 gene polymorphisms and the efficacy and safety of sacubitril/valsartan treatment in HF patients. METHODS: Genotyping of 10 single nucleotide polymorphisms (SNPs) of the NEP and CES1 genes in 116 HF patients was performed by the Sequenom MassARRAY method, and logistic regression and haplotype analysis were used to evaluate the associations between SNPs and the clinical efficacy and safety of sacubitril/valsartan in HF patients. RESULTS: A total of 116 Chinese patients with HF completed the whole trial, and T variations in rs701109 in NEP gene were an independent risk factor (P = 0.013, OR = 3.292, 95% CI:1.287-8.422) for the clinical efficacy of sacubitril/valsartan. Furthermore, haplotype analysis of 6 NEP SNPs (including rs701109) was performed and showed that the CGTACC and TGTACC haplotypes were significantly associated with clinical efficacy (OR = 0.095, 95%CI: 0.012-0.723, P = 0.003; OR = 5.586, 95% CI: 1.621-19.248, P = 0.005). Moreover, no association was found between SNPs of other selected genes in terms of efficacy in HF patients, and no association was observed between SNPs and symptomatic hypotension. CONCLUSION: Our results suggest an association between rs701109 and sacubitril/valsartan response in HF patients. Symptomatic hypotension is not associated with the presence of NEP polymorphisms.

Isolation and characterization of algicidal bacteria from freshwater aquatic environments in China.

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.

Construction and comprehensive analysis of a novel prognostic signature associated with pyroptosis molecular subtypes in patients with pancreatic adenocarcinoma.

Background: Treatment 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. Methods: Based 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. Results: Based 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. Conclusions: PMSRPS 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 Upregulation of GSTO2 is Associated with Colon Cancer Progression and a Poor Prognosis.

Colorectal cancer is the second-leading cause of cancer-related mortality in the United States. Glutathione S-transferase can affect the development of cancer. Glutathione S-transferase omega 2, a member of the GST family, plays an important role in many tumors. However, the role of Glutathione S-transferase omega 2 in the development of colon cancer remains unclear. Herein, our study aimed to investigate the exact role of Glutathione S-transferase omega 2 in colon cancer. We used RNA sequencing data from The Cancer Genome Atlas and the Genotype-Tissue Expression database to analyze Glutathione S-transferase omega 2 expressions. Then, we explore the protein information of Glutathione S-transferase omega 2 in the Human Protein Atlas, GeneCards, and String database. In addition, western blot and immunohistochemistry were performed to evaluate the protein levels of Glutathione S-transferase omega 2 in colon cancer tissues. We acquire data from the Gene Expression Omnibus and The Cancer Genome Atlas databases. Also, we performed relevant prognostic analyses of these data. In addition, we performed a statistical analysis of the clinical data from The Cancer Genome Atlas database and the expression level of Glutathione S-transferase omega 2. Then, we performed Cox regression analysis and found independent risk factors for prognosis in patients with colon cancer. The Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses were used to explore the potential biological functions of Glutathione S-transferase omega 2. The infiltration of colon cancer-immune cells was evaluated by the CIBERSORT method. RNA silencing was performed using siRNA constructs in HCT-116 and HT-29 cell lines. Cell Counting Kit-8 and EdU assays were performed to determine cell proliferation. Transwell experiments and scratch tests were used to determine cell migration. As for the mRNA and protein expression levels of cells, we used quantitative real-time PCR and western blot to detect them. Our research shows that Glutathione S-transferase omega 2 is overexpressed in colon cancer patients, and this overexpression is associated with a poor prognosis. The high expression of Glutathione S-transferase omega 2 is significantly correlated stage with stage, M, and N classification progression in colon cancer by statistical analysis. Univariate and multivariate Cox regression analyses showed that Glutathione S-transferase omega 2 was an independent risk factor for poor prognosis in colon cancer. In addition, we also found that Glutathione S-transferase omega 2 expression levels can affect the immune microenvironment of colon cancer cells. Gene silencing of Glutathione S-transferase omega 2 in HT-29 and HCT-116 cells significantly inhibited tumor growth and migration. In summary, we found that Glutathione S-transferase omega 2 can be used as a molecular indicator of colon cancer prognosis. In vitro, gene silencing of Glutathione S-transferase omega 2 inhibited colon cancer cells' growth and migration.

Signature construction and molecular subtype identification based on cuproptosis-related genes to predict the prognosis and immune activity of patients with hepatocellular carcinoma.

Background: Hepatocellular 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. Methods: Combining 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. Results: Four 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. Conclusions: We 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.

FAT10 promotes chemotherapeutic resistance in pancreatic cancer by inducing epithelial-mesenchymal transition via stabilization of FOXM1 expression.

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.

Identification of LncRNA Prognostic Signature Associated With Genomic Instability in Pancreatic Adenocarcinoma.

Background: Genomic 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. Methods: The 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. Results: Results 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. Conclusions: In 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.

Construction of a Novel LncRNA Signature Related to Genomic Instability to Predict the Prognosis and Immune Activity of Patients With Hepatocellular Carcinoma.

Background: Genomic 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. Methods: Combining 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. Results: Five 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. Conclusion: Our 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.

Construction of a new immune-related lncRNA model and prediction of treatment and survival prognosis of human colon cancer.

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.

An overview of walnuts application as a plant-based.

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.

Neutron emission measurement at the HL-2A tokamak device with a liquid scintillation detector.

Neutron emission measurement at the HL-2A tokamak device with a liquid scintillation detector is described. The detector was placed at a location with little structure material in the field of view, and equipped with a gain monitoring system which could provide the possibility to evaluate the gain variation as well as to correct for the detector response. Time trace of the neutron emissivity was obtained and it was consistent with the result of a standard (235)U fission chamber. During the plasma discharge the neutron yield could vary by about four orders of magnitude and the fluctuation of the detector gain was up to about 6%. Pulse height spectrum of the liquid scintillation detector was constructed and corrected with the aid of the gain monitoring system, and the correction was found to be essential for the assessment of the neutron energy spectrum. This successful measurement offered experience and confidence for the application of liquid scintillation detectors in the upcoming neutron camera system.

Removal of CdTe in acidic media by magnetic ion-exchange resin: a potential recycling methodology for cadmium telluride photovoltaic waste.

Sulfonated magnetic microspheres (PSt-DVB-SNa MPs) have been successfully prepared as adsorbents via an aqueous suspension polymerization of styrene-divinylbenzene and a sulfonation reaction successively. The resulting adsorbents were confirmed by means of Fourier transform infrared spectra (FT-IR), X-ray diffraction (XRD), transmission electron microscope (TEM), scanning electron microscope equipped with an energy dispersive spectrometer (SEM-EDS) and vibrating sample magnetometer (VSM). The leaching process of CdTe was optimized, and the removal efficiency of Cd and Te from the leaching solution was investigated. The adsorbents could directly remove all cations of Cd and Te from a highly acidic leaching solution of CdTe. The adsorption process for Cd and Te reached equilibrium in a few minutes and this process highly depended on the dosage of adsorbents and the affinity of sulfonate groups with cations. Because of its good adsorption capacity in strong acidic media, high adsorbing rate, and efficient magnetic separation from the solution, PSt-DVB-SNa MPs is expected to be an ideal material for the recycling of CdTe photovoltaic waste.