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Abstract Fluency is an important, yet insufficiently understood, construct in interpreting studies. This article reports on an empirical study which explored the relationship between utterance fluency measures and raters’ perceived fluency ratings of English/Chinese consecutive interpreting. It also examined whether such relationship was consistent across interpreting directions and rater types. The results partially supported the categorization of utterance fluency into breakdown, speed and repair fluency. It was also found that mean length of unfilled pauses, phonation time ratio, mean length of run and speech rate had fairly strong correlations with perceived fluency ratings in both interpreting directions and across rater types. Among a number of competing regression models that were built to predict raters’ fluency ratings, a parsimonious model, using mean length of unfilled pauses and mean length of run as predictors, accounted for about 60% of the variance of fluency ratings in both directions and across rater types. These results are expected to help create, rewrite and modify rubrics and scalar descriptors of fluency scales in rater-mediated interpretation assessment and to inform automated scoring of fluency in interpreting.

Convolutional Neural Networks (ConvNets) have quickly become popular machine learning techniques in recent years, particularly in the classification and segmentation of medical images. One of the most prevalent types of brain cancers is glioma, and early, accurate diagnosis is essential for both treatment and survival. In this study, MRI scans were examined utilizing deep learning techniques to examine glioma diagnosis studies.In this systematic review, keywords were used to obtain English-language studies from the Arxiv, IEEE, Springer, ScienceDirect, and PubMed databases for the years 2010-2022. The material needed for review was then collected from the articles once they had been chosen based on the entry and exit criteria and in accordance with the research's goal.Finally, 77 different academic articles were chosen. According to a study of published articles, glioma brain tumors were discovered, categorized, and segmented utilizing a coordinated approach that included image collecting, pre-processing, model design and execution, and model output evaluation. The majority of investigations have used publicly accessible photo databases and already-trained algorithms. The bulk of studies have employed Dice's classification accuracy and similarity coefficient metrics to assess model performance.The results of this study indicate that glioma segmentation has received more attention from researchers than glioma detection and classification. It is advised that more research be done in the areas of glioma detection and, particularly, grading in order to be included in systems that support medical diagnosis.

Objective Limited studies have shown an association between the methyl-CpG-binding protein2 ( MeCp2) genetic polymorphisms and systemic lupus erythematosus (SLE) in different populations, but the results are inconclusive. In order to get a precise and systematic estimation, a meta-analysis was performed. Methods A systematic literature search using English and Chinese databases (PubMed/Medline, Web of Knowledge, Wanfang Data (Chinese), etc.) for the eligible studies was performed. Based on heterogeneity among studies, random- or fixed-effects models were selected to analyze the risk of SLE associated with single-nucleotide polymorphisms (SNPs) of MeCP2 genetic polymorphisms. Results A significant increased risk of both SNPs of MeCP2 genetic variances associated with SLE was found. Analysis using a fixed-effects model found an increased risk of SLE with the A allele of rs2075596 (OR = 1.41, 95% CI: 1.34 to 1.49, p < 0.001), and the random-effects model also identified a risk factor of A allele of rs2239464 (OR = 1.31, 95% CI: 1.15 to 1.49, p = 0.001). Subgroup analysis and sensitivity analysis suggested that the major source of between-study heterogeneity stemmed from the difference between diverse ethnic groups. After omitting the smallest study, no publication bias was found, which further confirmed the reliability and stability of the meta-analysis. Conclusions Mutations of SNPs ( rs2075596, rs2239464) of MeCP2 showed increased risk of developing SLE. Large-scale multicenter epidemiological studies in selected populations with other risk factors are urgently required.

The latest data show that breast, prostate, lung and colorectal cancer are the four most frequent cancers in both sexes worldwide. A number of molecular epidemiological studies have been conducted to examine the association between TNF alpha -308G/A and the risk of those cancers. However the results have been inconclusive or inconsistent. We then performed a meta-analysis to derive a precise estimation of this association. We carried out a comprehensive search in Medline, EMBASE, OVID and Chinese Biomedical Literature Database for studies using related keywords. The inclusion criteria were (i) in English or Chinese; (ii) case-control study on this association; (iii) provide usable genotype frequencies; and (iv) sufficient published data for estimating an odds ratio (OR) with 95% confidence interval (CI). ORs and 95% CIs were calculated to assess the strength of this association under homozygote comparison (AA vs GG), heterozygote comparison (GA vs GG), dominant (AA/GA vs GG) and recessive (AA vs GA/GG) genetic model comparison. Thirty case-control studies with a total number of 16,507 cases and 19,749 controls were selected for analysis. Overall, no significant association was found between this polymorphism and the risk of total four cancers (GA vs GG: OR=1.02, 95% CI=0.91-1.14, P=0.78). However, there was a significant association between this polymorphism and breast cancer risk in western populations (GA vs GG: OR=0.91, 95% CI=0.85-0.96, P=0.002). This meta-analysis also revealed that this polymorphism was not associated with susceptibility to the other three cancers.

Vertebral fracture (VF) is the most common osteoporotic fracture in postmenopausal women, although most VFs are subclinical. Prevalent VFs are a significant predictor of subsequent fracture and therefore, identification of VF improves the identification of those with high fracture risk. The aim of present study was to systematically review the literature that assessed the prevalence of VF in asymptomatic postmenopausal women, using Vertebral Fracture Assessment (VFA) by dual-energy X-ray absorptiometry.Medline, Web of Science and Cochrane databases were searched between Jan 1st, 2000 and Jan 31st, 2018, for publications in English that reported the prevalence of VFA-detected VF in asymptomatic postmenopausal women. We also searched for reports, conference papers and grey literature. Reviewers screened studies for eligibility and extracted data for included studies. Random effects meta-analyses were performed to calculate the prevalence of VF. The presence of publication bias was assessed using funnel plots by precision and Egger's Test of the Intercept.A total of 1777 articles were identified, 94 studies were fully reviewed and 28 studies (n = 25,418) met the inclusion criteria and were analyzed. More than two thirds of the studies were cross-sectional and the sample size varied widely across the studies (from 63 to 5156). The mean age ranged from 59.5 to 86.2 years old. The prevalence of osteoporosis and osteopenia varied between 6-57.0% and 25.1-58.9%, respectively. However, among women who had prevalent VFs, up to 43% had osteopenia and as many as 32% had normal bone density. The weighted pooled prevalence of VFA-detected VF in asymptomatic women was 28% (95% CI: 23%-32%).VFA is able to identify prevalent VF in asymptomatic postmenopausal women. The use of VFA identified an average of 28% of asymptomatic women with VFs, many of whom did not have a diagnosis of osteoporosis. Implementation of VFA as a routine screening tool may detect high risk women. Detection of VF might lead to pharmacological treatment in individuals who may not otherwise be treated.

In bilingual speakers, language switching might involve a change in language form, meaning, or both. However, the neural substrates of language control in the three switching conditions have not been specified. We examined bilingual speech production using a picture-naming paradigm that teased apart language and semantic switching. Bilingual participants named two serially presented pictures, which show the same or different object, with one or two languages. The three switching conditions showed distinct neural activation patterns within the prefrontal cortex. Moreover, neural substrates shared by all switching conditions were primarily found in fronto-parietal regions. Besides, forward switching (L1-to-L2) activated a more widespread neural network than backward switching (L2-to-L1). We discuss differential engagement of the cognitive control system as a function of switching type during bilingual speech production.

Hyperhomocysteinemia (HHcy) is known to increase the risk of many diseases. Factors influencing HHcy in healthy and hypertensive subjects remain under-researched.A large population-based study was conducted in 60 communities from Shenzhen, China. Responses to standardized questions on lifestyle factors and blood samples were collected from all participants after a 12-h overnight fast. Multiple linear and multivariate logistic regressions were used to explore risk factors for HHcy. Results were then compared to those from a systematic review of English-language articles listed in Pubmed, EBSCOhost, Web of Science, Embase and Cochrane libraries that investigated HHcy risk factors in healthy and hypertensive subjects.A total of 1586 healthy (Male/Female = 642/944) and 5935 hypertensive subjects (Male/Female = 2928/3007) participated in our population-based study. In logistic regression analyses, age, BMI and creatinine (Cr) were risk factors, while being female, fruit intake and physical activity were protective factors for HHcy in healthy subjects. In hypertensive subjects, seven [age, smoking, salt intake, systolic blood pressure (SBP), uric acid, triglycerides (TG), and Cr] and four [female, fruit intake, total cholesterol (TC), and glucose] factors were associated with higher and lower HHcy respectively. The review of 71 studies revealed that potential risk factors for Hcy included nutritional, physiologic, lifestyle habits, ethnicity, genetics, interactions between gene-environment, gene-gene, gene-nutritional, environment-environment, nutritional-nutritional.Our study indicates the potential importance of increasing folic acid and vitamin B supplementation, daily fruit and vegetable intake, regular exercise and refraining from tobacco smoking and alcohol consumption as preventive strategies for Hcy.

Previous research has shown that training on inhibitory control (IC) leads to functional neural plastic changes, although this effect on individuals with different levels of IC abilities has yet to be studied. Here, we examined the individual differences in IC abilities of 85 participants, who performed a Simon task while undergoing a functional magnetic resonance imaging (fMRI) scan. Participants in the experimental group followed an 8-day training session on IC between the pre- and the post-test, whereas the control group did not receive any training. The fMRI results reported that, in comparison to the control group, the training session elicited different patterns of neural adaptation between participants with high- and low-IC abilities in the experimental group. While training reduced activation levels in the supplementary motor area (SMA), bilateral thalamus, and left anterior cingulate cortex (ACC) of individuals with low-IC performance prior to the training, the same pattern was not found in participants with high-IC performance. In addition, individual differences in IC abilities before training also positively correlated with activation reduction in these brain regions after training. These results suggest that individual differences in IC abilities modulate the neural plasticity of IC, and IC training specifically enhanced neural efficiency in individuals with low-IC abilities. Our findings provide a novel perspective for investigating the functional neuroplasticity of the IC system by highlighting the interaction between individual variances in IC abilities and short-term training effects.