Cholecystitis is a common disease with a high incidence, and attracts much attention. It not only harms human health, but also affects quality of work and life. Therefore, the choice of a suitable treatment is badly important for patients. In this paper, a novel selection model of treatments for cholecystitis based on hybrid multiple-criteria group decision-making (MCGDM), which is helpful to choose the most suitable treatment in the case of asymmetric information between doctors and patients. Subsequently, subjective and objective criteria are comprehensively taken into account in the index system of the selection model for cholecystitis, and combines 2-tuple linguistic with quantitative data analysis. Besides, the evaluation information obtained from the patient's conditions, the treatment and the hospital's medical status, etc., including real numbers, interval numbers, and linguistic labels with multi-granularity, is more complete and real. And the 2-tuple linguistic model is used to unify the non-homogeneous information, so the treatment selection is accurate and reliable. Simultaneously, for the unknown index and criteria weight, the improved entropy weight method and the BWM (best-worst-method) are utilized to figure out the index weight and criteria weight, respectively. Further, TODIM (an acronym in Portuguese for interactive and multicriteria decision-making model) method based on the prospect theory is applied to solve the prioritization of cholecystitis treatments, and give full consideration to the decision maker of risk aversion. Eventually, an empirical study of treatment selection for cholecystitis is conducted. Sensitivity analysis and comparative analysis indicate that the proposed selection model of treatments for cholecystitis patients is reliable and effective. INDEX TERMS Cholecystitis, best-worst method (BWM), entropy weight method, 2-tuple linguistic, group decision-making (MCGDM), TODIM.

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Increasing evidence suggests that long non-coding RNAs (lncRNAs) are crucial in cancer biological processes. To investigate if lncRNA contributes to gastric cancer (GC), we conducted a bioinformatics analysis in human microarray datasets, and the results showed that lncRNA prostate cancer-associated transcript 19 (PCAT19) was upregulated in GC. Quantitative reverse-transcriptase PCR and in situ hybridization assays also revealed that PCAT19 was upregulated in GC tissues. The PCAT19 expression in GC was significantly related to tumor size, lymph node metastasis, and pathological stage. Moreover, patients with higher PCAT19 expression levels were more likely to have a poor prognosis for overall survival. The knockdown of PCAT19 by siRNA significantly suppressed the proliferation and invasion of GC cells. The cell distribution of PCAT19 in GC cells was examined by fluorescence in situ hybridization assay, and the results showed that it was mainly located in the cytoplasm. Mechanistically, PCAT19 sponges miR-429 and promotes DHX9 expression. In addition, the transcription factor SP1 is involved in PCAT19 activation. Our results demonstrate that lncRNA PCAT19 is induced by SP1 and acts as an oncogene in GC that competitively binds to miR429 and upregulates DHX9.

Background: The long non-coding RNA SNHG7 is upregulated in many types of cancer and plays a role as an oncogene. However, its overall predictive ability in human cancer prognosis has not been assessed using existing databases. Therefore, further study of its prognostic value and clinical significance in human malignancies is warranted. Methods: We systematically collected relevant literature from multiple electronic document databases about the relationship between SNHG7 expression level and prognosis in patients with solid cancers. We further screened them for eligibility. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to assess the prognostic value. Odds ratios (ORs) and their 95% CIs were collected to evaluate the relationship between the expression of SNHG7 and clinicopathological features, including lymph node metastasis (LNM), tumour size, tumour node metastasis (TNM) stage and histological grade. Results: Fourteen original studies involving 971 patients were enrolled strictly following the inclusion and exclusion criteria. The meta-analysis showed that SNHG7 expression was significantly correlated with poor overall survival (HR = 1.93, 95% CI: 1.64–2.26, p<0.001) in human cancer patients. In addition, the pooled OR indicated that overexpression of SNHG7 was associated with earlier LNM (OR = 1.83, 95% CI: 1.44–2.32; P <0.001), and advanced TNM stage (OR = 1.82, 95% CI: 1.44–2.30; P <0.001).Meanwhile, there was no significant heterogeneity between the selected studies, proving the reliability of the meta-analysis results. Conclusions: High SNHG7 expression may predict poor oncological outcomes in patients with multiple human cancers, which could be a novel prognostic biomarker of unfulfilled clinicopathological features. However, further high-quality studies are needed to verify and strengthen the clinical value of SNHG7 in different types of cancer.

There are many treatments for nasopharyngeal carcinoma (NPC), but none of them are very effective. Radiotherapy is used extensively in NPC treatment, but radioresistance is a major problem. Graphene oxide (GO) has been previously studied in cancer treatment, and this study is aimed to explore its role in radiosensitization of NPC. Therefore, graphene oxide nanosheets were prepared, and the relationship between GO and radioresistance was explored. The GO nanosheets were synthesized by a modified Hummers' method. The morphologies of the GO nanosheets were characterized by field-emission environmental scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The morphological changes and radiosensitivity of C666-1 and HK-1 cells with or without the GO nanosheets were observed by an inverted fluorescence microscopy and laser scanning confocal microscopy (LSCM). Colony formation assay and Western Blot were applied for analysis of NPC radiosensitivity. The assynthesized GO nanosheets have lateral dimensions (sizes ∼1 μm) and exhibit a thin wrinkled two-dimensional lamellar structure with slight folds and crimped edges (thickness values ∼1 nm). C666-1 cells with the GO was significantly changed the morphology of cells postirradiation. The full field of view visualized by a microscope showed the shadow of dead cells or cell debris. The synthesized graphene oxide nanosheets inhibited cell proliferation, promoted cell apoptosis, and inhibited the expression of Bcl-2 in C666-1 and HK-1 cells but increased the level of Bax. The GO nanosheets could affect the cell apoptosis and reduce the pro-survival protein Bcl-2 related to the intrinsic mitochondrial pathway. The GO nanosheets could enhance radiosensitivity, which might be a radioactive material in NPC cells.

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Background: The long non-coding RNA SNHG7 is upregulated in many types of cancer and plays a role as an oncogene. However, its overall predictive ability in human cancer prognosis has not been assessed using existing databases. Therefore, further study of its prognostic value and clinical significance in human malignancies is warranted.Methods: We systematically collected relevant literature from multiple electronic document databases about the relationship between SNHG7 expression level and prognosis in patients with solid cancers. We further screened them for eligibility. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were used to assess the prognostic value. Odds ratios (ORs) and their 95% CIs were collected to evaluate the relationship between the expression of SNHG7 and clinicopathological features, including lymph node metastasis (LNM), tumour size, tumour node metastasis (TNM) stage and histological grade.Results: Fourteen original studies involving 971 patients were enrolled strictly following the inclusion and exclusion criteria. The meta-analysis showed that SNHG7 expression was significantly correlated with poor overall survival (HR = 1.93, 95% CI: 1.64–2.26, p < 0.001) in human cancer patients. In addition, the pooled OR indicated that overexpression of SNHG7 was associated with earlier LNM (OR = 1.83, 95% CI: 1.44–2.32; P <0.001), and advanced TNM stage (OR = 1.82, 95% CI: 1.44–2.30; P <0.001).Meanwhile, there was no significant heterogeneity between the selected studies, proving the reliability of the meta-analysis results.Conclusions: High SNHG7 expression may predict poor oncological outcomes in patients with multiple human cancers, which could be a novel prognostic biomarker of unfulfilled clinicopathological features. However, further high-quality studies are needed to verify and strengthen the clinical value of SNHG7 in different types of cancer.