A sensitive impedimetric DNA biosensor for the determination of the HIV gene was developed by employing electrochemically reduced graphene oxide as a sensing platform.

Cognitive diagnostic models (CDMs) show great promise in language assessment for providing rich diagnostic information. The lack of a full understanding of second language (L2) listening subskills made model selection difficult. In search of optimal CDM(s) that could provide a better understanding of L2 listening subskills and facilitate accurate classification, this study carried a two-layer model selection. At the test level, A-CDM, LLM, and R-RUM had an acceptable and comparable model fit, suggesting mixed inter-attribute relationships of L2 listening subskills. At the item level, Mixed-CDMs were selected and confirmed the existence of mixed relationships. Mixed-CDMs had better model and person fit than G-DNIA. In addition to statistical approaches, the content analysis provided theoretical evidence to confirm and amend the item-level CDMs. It was found that semantic completeness pertaining to the attributes and item features may influence the attribute relationships. Inexplicable attribute conflicts could be a signal of suboptimal model choice. Sample size and the number of multi-attribute items should be taken into account in L2 listening cognitive diagnostic modeling studies. This study provides useful insights into the model selection and the underlying cognitive process for L2 listening tests.

Background Osteosarcoma (OS) is a type of bone cancer that occurs in children and adolescents at a rate of 5%. The purpose of this study is to explore the lncRNA GNAS-AS1 expression profile, prognosis significance in OS, and biological effect on OS cell function. Methods One hundred eight pairs of tissues were collected, and OS cell lines were purchased. lncRNA GNAS-AS1 expression in these tissues and cells were analyzed by qRT-PCR. Clinical data were analyzed using chi-square tests, Kaplan-Meier curves (log-rank test), and Cox regression. CCK-8 and transwell assay were conducted to analyze the effect of lncRNA GNAS-AS1 on cell proliferation, invasion, and migration. The downstream miRNA was presumed. Results The expression of lncRNA GNAS-AS1 was significantly increased in OS cells and tissues, and related to Enneking staging and distant metastasis. Patients with high lncRNA GNAS-AS1 expression represented shorter overall survival and was an independent prognostic predictor of OS. LncRNA GNAS-AS1 knockdown inhibited cell proliferation, migration, and invasion by regulated miR-490-3p partly at least. Conclusions LncRNA GNAS-AS1 can be used as a prognostic indicator and its inhibition suppress the development of OS, suggesting its value as novel therapeutic strategies in OS.

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