RESUMO
Scholars have argued that comprehensibility (i.e., ease of understanding), not nativelike performance, should be prioritized in second language learning, which inspired numerous studies to explore factors affecting comprehensibility. However, most of these studies did not consider potential interaction effects of these factors, resulting in a limited understanding of comprehensibility and less precise implications. This study investigates how pronunciation and lexicogrammar influences the comprehensibility of Mandarin-accented English. A total of 687 listeners were randomly allocated into six groups and rated (a) one baseline and (b) one of six experimental recordings for comprehensibility on a 9-point scale. The baseline recording, a 60 s spontaneous speech by an L1 English speaker with an American accent, was the same across groups. The six 75-s experimental recordings were the same in content but differed in (a) speakers' degree of foreign accent (American, moderate Mandarin, and heavy Mandarin) and (b) lexicogrammar (with errors vs. without errors). The study found that pronunciation and lexicogrammar interacted to influence comprehensibility. That is, whether pronunciation affected comprehensibility depended on speakers' lexicogrammar, and vice versa. The results have implications for theory-building to refine comprehensibility, as well as for pedagogy and testing priorities.
Assuntos
Percepção da Fala , Humanos , Idioma , FalaRESUMO
Long non-coding RNAs (lncRNAs) are key regulators of a range of human diseases, including various cancers, with multiple previous studies having explored lncRNA dysregulation in the context of gastric cancer (GC). The present study sought to expand upon these previous results by downloading lncRNA, mRNA, and microRNA (miRNA) expression profiles derived from 180 GC tissues and 24 normal control tissues within the Cancer Genome Atlas (TCGA) database. These datasets were then interrogated to identify GC-related differentially expressed (DE) RNAs (|fold change| ≥ 2, FDR< 0.01), leading to the identification of 1946 DE lncRNAs, 123 DE miRNAs, and 3159 DE mRNAs. These results were then used to generate a putative GC-related competitive endogenous RNA (ceRNA) network composed of 131 lncRNAs, 9 miRNAs, and 78 mRNAs. Subsequent survival analyses based upon this network revealed 17 of these lncRNAs to be significantly associated with GC patient survival (P < 0.05). Further multivariable Cox regression and lasso analyses allowed for the construction of an 8-lncRNA risk score that was able to effectively predict GC patient survival with good discriminative ability. The Kaplan-Meier Plotter database further confirmed that network hub genes that were related to these 8 lncRNAs were associated with GC patient prognosis (P < 0.05). As the ceRNA network in the present study was constructed with a focus on both disease stage and differential gene expression, it represents a key resource that will offer valuable insights into the mechanistic roles of ceRNA pathways in GC development and progression.
RESUMO
Preoperative prognostic nutritional index (PNI) has been widely used for the clinical evaluation of patients with cancer. The present study assessed the prognostic value of preoperative PNI in patients after gastric cancer (GC) radical surgery. The clinical case and follow-up data of 170 patients undergoing GC radical surgery were retrospectively analyzed. The receiver operating characteristic (ROC) curve was used to compare the predictive ability of each inflammatory index: The PNI, neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR). The correlation between the preoperative PNI and overall survival (OS) was also analyzed via Kaplan-Meier (K-M) curves and multivariate Cox regression analyses. The results revealed that the optimal PNI cut-off was 46.030. According to this cut-off value, the whole sample was divided into PNI <46.030 (low PNI group) and PNI ≥46.030 (high PNI group). These groups were comprised of 102 and 68 cases, respectively. The area under the curve value of the PNI was 0.725, which was greater than that of traditional inflammatory indices, including the NLR and LMR. K-M survival analysis revealed that the 5 year survival rate of patients in the low PNI group was significantly lower than that of patients in the high PNI group (P<0.01). Univariate analysis and Cox multiple regression model analysis demonstrated that the T stage, N stage, pathological grade and PNI were independent risk factors for the 5 year survival rate after radical gastrectomy (P<0.05). In conclusion, the preoperative PNI is an independent risk factor for 5 year survival after radical gastrectomy and has clinical value for the prognostic evaluation of patients with GC.
