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Early detection and diagnosis are the key to successful clinical management of pancreatic cancer and improve the patient outcome. However, due to the absence of early symptoms and the aggressiveness of pancreatic cancer, its 5-year survival rate remains below 5 %. Compared to tissue samples, liquid biopsies are of particular interest in clinical settings with respect to minimal invasiveness, repeated sampling, complete representation of the entire or multi-site tumor bulks. The potential of liquid biopsies in pancreatic cancer has been demonstrated by many studies which prove that liquid biopsies are able to detect early emergency of pancreatic cancer cells, residual disease, and recurrence. More interestingly, they show potential to delineate the heterogeneity, spatial and temporal, of pancreatic cancer. However, the performance of liquid biopsies for the diagnosis varies largely across different studies depending of the technique employed and also the type and stage of the tumor. One approach to improve the detect performance of liquid biopsies is to intensively inspect circulome and to define integrated biomarkers which simultaneously profile circulating tumor cells and DNA, extracellular vesicles, and circulating DNA, or cell free DNA and proteins. Moreover, the diagnostic validity and accuracy of liquid biopsies still need to be comprehensively demonstrated and validated.

Background Recently, minimal invasive surgery (MIS) has been applied as a common therapeutic approach for treatment of hypertensive intracerebral hemorrhage (HICH). However, the efficacy and safety of MIS is still controversial compared with conservative medical treatment or conventional craniotomy. This meta-analysis aimed to systematically assess the safety and efficacy of MIS compared with conservative method and craniotomy in treating HICH patients. Methods PubMed, Embase, Web of Science, and Cochrane Controlled Trials Register were used to identify relevant studies on MIS treatment of HICH up to November 2017. This study evaluated Glasgow Outcome Scale (GOS) score, Activities of Daily Living (ADL) score, pulmonary infection rate, mortality rate, and rebleeding rate for patients who underwent MIS, or conservative method, or craniotomy. Subgroup analyses were performed to compare randomization versus non-randomization and large hematoma versus small or mild hematoma. Begg’s test and Egger’s test were used to determine the potential presence of publication bias. Results Sixteen studies consisting of 1912 patients were included in this study to compare the efficacy and safety of MIS to conservative method or craniotomy. MIS contributed to a significant improvement on the prognosis of the patients comparing with conservative group or craniotomy group. Patients undergoing MIS had a lower mortality rate when compared to those receiving conservative method. Also, MIS led to a notable reduction of rebleeding rate and an effective improvement of the patient’s quality of life by contrast with craniotomy. No obvious difference was found in terms of the pulmonary infection rate among the comparisons of three treatment methods. Randomization is not the potential source of heterogeneity, but hematoma volume may be a risk factor for post-operative mortality rate. No statistical evidence of publication bias among studies was found under most of comparison models. Conclusion This meta-analysis suggests that minimal invasive surgery is an efficient and safe method for the treatment of hypertensive intracerebral hemorrhage, which is associated with a low mortality rate and rebleeding rate, as well as a significant improvement of the prognosis and the quality life of patients when compared with conservative medical treatment or craniotomy.

Credit rating is an important part of bank credit risk management. Since the traditional radial basis function network model is more susceptible to outliers and cannot effectively process the classification data, it is very sensitive in terms of the initial center and class width of the selected model. This paper mainly studies the application of the radial basis function neural network model combined with the optimal segmentation algorithm in the personal loan credit rating model of banks or other financial institutions. The optimal segmentation algorithm is improved and applied to the training of RBF neural network parameters in this paper to increase the center and width of the class, and the center and width of the RBF network model are further improved. Finally, the adaptive selection of the number of hidden nodes is realized by using the differential objective function of the class to adjust dynamically the structure of the radial basis function network model, which is used to establish the credit rating model. The experimental results show that the improved model has higher precision when dealing with non-numeric data, and the robustness of the improved model has been improved.

The changes in China’s stock market are inseparable from the country’s economic development and macroeconomic regulation and control and have far-reaching significance in promoting China’s national economic growth. Compared with the Western developed capital market, China’s current stock market’s main smart investment strategy still has certain defects. Based on the SVM model, this paper establishes a predictive model that combines kernel parameters and parameter optimization to model. The mesh search method, genetic algorithm, and particle swarm optimization algorithm are used to optimize the parameters of the SVM under various kernel functions such as radial basis kernel function. The algorithm and particle swarm optimization algorithm optimize the parameters of the SVM to strengthen the applicability of the model in practice. The empirical results show that under the three-parameter optimization algorithms, the prediction results are higher than the random prediction accuracy, which indicates that it is effective to optimize the model by adjusting the parameters of the SVM. Among them, the SVM using the genetic algorithm parameter optimization under the radial basis kernel function shows the better prediction effect, which is the closest to the real value in the stock market forecast. The particle swarm algorithm supports the vector machine to predict the effect is slightly lower than the grid. Search method. In addition, through comparison experiments, the guess accuracy of BP neural network is worse than that of the support vector machine model before the adjustment. Finally, this paper uses the well-trained model to plan the stock smart investment plan.

MicroRNAs (miRNAs) have pivotal roles in gene regulation. Circulating miRNAs have been developed as novel candidate non-invasive biomarkers for diagnosis, prognosis, and treatment response for diseases. However, miRNAs that have causal effects on Parkinson's Disease (PD) remain largely unknown. To investigate the causal relationships between miRNAs and PD, here we conduct a Mendelian randomization (MR) study. This study utilized the summary-level data of respective genome-wide association studies (GWAS) for 2083 miRNAs and seven PD-related outcomes to comprehensively reveal the causal associations between the circulating miRNAs and PD. Two-sample MR design was deployed and the causal effects were estimated with inverse variance weighted, MR-Egger, and weighted median. Comprehensively sensitive analyses were followed, including Cochran's test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis, to validate the robustness of our results. Finally, we investigated the potential role of the MR significant miRNAs by predicting their target genes and functional enrichment analysis. Inverse variance weighted estimates suggested that two miRNAs, miR-205-5p (β = -0.46, 95%CI: -0.690 to -0.229,  = 9.3 × 10 ) and miR-6800-5p (β = -0.389, 95%CI: -0.575 to -0.202,  = 4.32 × 10 ), significantly decreased the rate of cognitive decline among PD patients. In addition, eight miRNAs were nominally associated with more than three PD-related outcomes each. No significant heterogeneity of instrumental variables or horizontal pleiotropy was found. Gene Ontology (GO) analysis showed that the targets of these causal miRNAs were significantly enriched in cell cycle, apoptotic, and aging pathways. This MR study identified two miRNAs whose genetically regulated expression might have a causal role in the development of PD dementia. Our findings provided potential miRNA biomarkers to make better and early diagnoses and risk assessments of PD.

We determined the antitumor mechanism of apatinib in glioma using a patient-derived orthotopic xenograft (PDOX) glioma mouse model and glioblastoma (GBM) cell lines. The PDOX mouse model was established using tumor tissues from two glioma patients via single-cell injections. Sixteen mice were successfully modeled and randomly divided into two equal groups ( n  = 8/group): apatinib and normal control. Survival analysis and in vivo imaging was performed to determine the effect of apatinib on glioma proliferation in vivo. Candidate genes in GBM cells that may be affected by apatinib treatment were screened using RNA-sequencing coupled with quantitative mass spectrometry, data mining of The Cancer Genome Atlas, and Chinese Glioma Genome Atlas databases, and immunohistochemistry analysis of clinical high-grade glioma pathology samples. Quantitative reverse transcription-polymerase chain reaction (qPCR), western blotting, and co-immunoprecipitation (co-IP) were performed to assess gene expression and the apatinib-mediated effect on glioma cell malignancy. Apatinib inhibited the proliferation and malignancy of glioma cells in vivo and in vitro. Thrombospondin 1 (THBS1) was identified as a potential target of apatinib that lead to inhibited glioma cell proliferation. Apatinib-mediated THBS1 downregulation in glioma cells was confirmed by qPCR and western blotting. Co-IP and mass spectrometry analysis revealed that THBS1 could interact with myosin heavy chain 9 (MYH9) in glioma cells. Simultaneous THBS1 overexpression and MYH9 knockdown suppressed glioma cell invasion and migration. These data suggest that apatinib targets THBS1 in glioma cells, potentially via MYH9, to inhibit glioma cell malignancy and may provide novel targets for glioma therapy.

Introduction The activation of STING (stimulator of interferon genes) pathway enhances antitumor immunity in small‐cell lung cancer (SCLC), while the DNA damage induced by non‐cGAMP‐based agonists is a potent inducer of STING activity. Here, we investigate the intrinsic expression of STING in cancer cells and evaluate the value of the combination of ATR and TOP1 inhibitors in enhancing antitumor immunity. Methods STING expression was assessed at mRNA and protein levels in SCLC and normal lung tissues. Transcriptomic subsets of SCLC were identified based on STING‐related genes. Distinct mutation and immunogenomic profiles of these subsets were determined. The direct antitumor efficacy and the potential of enhancing antitumor immunity of the strategy using the ATR‐TOP1‐inhibitor combination were tested in SCLC cell lines. Results The intrinsic expression of STING was significantly reduced in SCLC compared to normal lung tissues (p < 0.0001). Three STING‐related SCLC subtypes were identified in which the STING‐high subtype was associated with (1) high immune infiltration, (2) high expression of genes related to MHC and immune checkpoints, and (3) high EMT and ferroptosis score. On the contrary, the STING‐low subtype was enriched with pathways related to DNA damage response (DDR) and cell cycle progression. The association between the DDR pathway activity and the STING‐IFN innate immune response was verified by in vitro experiments in which the inhibition of ATR and TOP1 triggered the expression of genes encoding type I IFN signaling and pro‐inflammatory cytokines/chemokines in a STING‐low SCLC cell line. Conclusion Our study verifies that activation of the STING‐IFN response by ATR and TOP1 inhibitors might be a therapeutic strategy to improve the response to immune checkpoint therapy in STING‐low SCLC. Furthermore, the combinations of ATR and TOP1 inhibitors can augment tumor inflammation in STING‐low SCLC. The combination of ATR and TOP1 inhibitors in STING‐low SCLC triggered activation of the STING‐IFN response and expression of pro‐inflammatory factors, and thus might transform “cold” tumors into “hot” tumors, which are more likely to respond to systemic immunotherapy.

Background Sex-related differences in cancer epidemiology, tumor biology, immune system activity, and pharmacogenomics have been suggested to be important considerations for precision cancer control. Here we elucidated systematically sex biases in genetic variants, gene expression profiles, and immunological landscapes of lung adenocarcinoma patients (LUADs) with different ancestry and smoking status. Methods Somatic mutation and mRNA expression data of Asian and Non-Asian LUADs were obtained from public databases. Sex-biased genetic mutations, gene expression, biological pathways, and immune infiltration were identified in the context of smoking status and race. Results Among nonsmokers, male-biased mutations were prevalent in Asian LUADs, while few sex-biased mutations were detected in Non-Asian LUADs. EGFR was the only mutation whose frequency was significantly higher in females than males in both Asian and Non-Asian nonsmokers. More genes exhibited sex-biased expression in Non-Asian LUADs compared to Asian LUADs. Moreover, genes distinctly expressed in females were mainly related to immune-related pathways, whereas those in males were more involved in activation of DNA repair, E2F_targets, and MYC_targets pathways. We also detected sex-specific immune infiltration in the context of genetic variation. In EGFR -mutant LUADs, males had a significantly increased infiltration of CD8 + T cells, whereas resting CD4 + memory T cells were more abundant in females. Additionally, in KRAS -mutant LUADs, CD8 + and CD4 + T cells were more abundant in females than males. In addition, we detected all female patients with high SCGB3A2 expression were exclusively sensitive to immunotherapy, while this phenomenon was not observed in male patients. Conclusions Our findings provided evidence that sex-related molecular and cellular components are involved in shaping tumor distinct genetic and immune features, which might have important impact on personalized targeted and immune therapy.

Background Huanglian Jiedu Decoction (HLJDD) is a representative formula for clearing heat and removing toxins, and some basic studies indicated that it can improve the learning cognitive ability of Alzheimer’s disease (AD) mice, but the underlying molecular mechanism of its improvement in AD mice is still unclear, therefore, this paper delves into the mechanism of HLJDD to improve AD. Purpose This study aims to investigate whether HLJDD can improve the “central-peripheral” inflammatory microenvironment in APP/PS1 mice, and to explore its relationship with gut microbiota and NLRP3 inflammatory vesicles activation. Materials and methods In this paper, the fingerprint of HLJDD was established by high-performance liquid chromatography (HPLC) and the components of HLJDD were characterized by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-O-TOF/MS). The potential signaling pathways of HLJDD against AD were preliminarily investigated through network pharmacology. Behavioral assessment, histopathological staining, immunofluorescence staining, immunohistochemical staining, and detection of central and peripheral inflammatory factors were used to explore the improvement of AD by HLJDD, in addition to which we examined the gut microbiota and expression of relevant inflammatory proteins. Results In this study, 137 chemical constituents, including flavonoids, terpenoids, and alkaloids, were first identified in HLJDD by HPLC fingerprinting and UPLC-Q-TOF/MS. In addition, 49 components were found in the brain tissue of APP/PS1 mice and 48 components were found in the plasma of APP/PS1 mice. Network pharmacology concluded that the relevant pathways for HLJDD treatment of AD include inflammatory pathways. We found that HLJDD was effective in improving the learning memory ability of APP/PS1 mice by in vivo mouse behavioral performance. Histopathological results showed that HLJDD had the effect of reducing AD-like pathological damage, and also found that HLJDD could significantly reduce the proportion of M1 type microglia and A1 type astrocytes, and increase the proportion of M2 type microglia and A2 type astrocytes, and the treatment of HLJDD also suppressed the infiltration of CD4 + and CD8 + T-cells in the brain, and inhibited Aβ deposition and reduced the expression of inflammatory factors in the brain, and alleviated central neuroinflammation. In addition, it was also found that HLJDD was able to reduce the expression of inflammatory factors in the peripheral blood and inhibit the peripheral immune response, and the results of gut microbiota also showed changes in gut microbiota after HLJDD treatment and verified the expression of inflammatory vesicle-associated proteins in the intestines, with significant upregulation of the expression of NLRP3, caspase-1, and ASC proteins in the model group, and significant downregulation of ZO-1 and occludin proteins, and reversal of the above changes after HLJDD intervention. Conclusion Therefore, it is hypothesized that HLJDD improves the “central-peripheral” inflammatory microenvironment in APP/PS1 mice by inhibiting the activation of NLRP3 inflammatory vesicles mediated by gut microbiota.

Background Glioblastomas (GBMs) are grade IV central nervous system tumors characterized by a poor prognosis and a short median overall survival. Effective induction of GBM cell death is difficult because the GBM cell population is genetically unstable, resistant to chemotherapy and highly angiogenic. In recent studies, ubiquitin-specific protease 7 (USP7) is shown to scavenge ubiquitin from oncogenic protein substrates, so effective inhibition of USP7 may be a potential key treatment for GBM. Methods Immunohistochemistry and western blotting were used to detect the expression of USP7 in GBM tissues. In vitro apoptosis assay of USP7 inhibition was performed by western blotting, immunofluorescence, and flow cytometry. Anti-apoptotic substrates of USP7 were defined by Co-IP and TMT proteomics. Western blotting and IP were used to verify the relationship between USP7 and its substrate. In an in vivo experiment using an intracranial xenograft model in nude mice was constructed to assess the therapeutic effect of target USP7. Results Immunohistochemistry and western blotting confirmed that USP7 was significantly upregulated in glioblastoma samples. In in vitro experiments, inhibition of USP7 in GBM induced significant apoptosis. Co-IP and TMT proteomics identified a key anti-apoptotic substrate of USP7, ADP-ribosylation factor 4 (ARF4). Western blotting and IP confirmed that USP7 interacted directly with ARF4 and catalyzed the removal of the K48-linked polyubiquitinated chain that binded to ARF4. In addition, in vivo experiments revealed that USP7 inhibition significantly suppressed tumor growth and promoted the expression of apoptotic genes. Conclusions Targeted inhibition of USP7 enhances the ubiquitination of ARF4 and ultimately mediates the apoptosis of GBM cells. In a clinical sense, P5091 as a novel specific inhibitor of USP7 may be an effective approach for the treatment of GBM.