Search

Foreign Language Anxiety (FLA) is considered a central affective factor influencing English as a Foreign Language (EFL) learning. This study thus developed an online simulation game to create a virtually situated learning environment for reducing EFL primary school students' FLA levels and improving their English vocabulary learning. A total of 110 fifth graders from four classes participated in this study. Two classes were randomly assigned to the experimental group (N = 57) using the online simulation game, and the other two classes were the control group (N = 53) using onsite instruction. Each participant was then classified as a low, moderate, or high anxiety student based on the Foreign Language Classroom Anxiety Scale (FLCAS). This study found that, compared to the onsite instruction, the online simulation game more effectively assisted the low, moderate, and high anxiety students in reducing their FLA. Situated learning in the online simulation game made a connection between English vocabulary learning and the real world explicitly and visibly, which could further promote their English vocabulary learning. In particular, the moderate and high anxiety students' English vocabulary learning was significantly improved after the online simulation game. These results suggest that an online simulation game can create a situated learning environment that helps reduce EFL students' FLA and subsequently facilitate their English vocabulary learning.

Abstract Purpose The aim of this study was to describe the longitudinal developmental trajectories and its influencing factors of sexual activity in patients with breast cancer during treatment. Methods A prospective longitudinal study was conducted, including 225 newly diagnosed breast cancer patients in A tumor specialty three-class hospital in Southwest China. We measured sexual activity at the time of admission and diagnosis (T0) and one month (T1), three months (T2), six months (T3), and nine months (T4) after diagnosis. A trajectory analysis model (GBTM) was used to explore the changes in sexual activity in breast cancer patients. Multivariate binary logistic regression analysis was used to analyse the factors that affected the classification of sexual activity trajectories. Results The ratio of sexual activity abruptly declined from 100% at baseline to 39.1% at T1. The percentage of sexual activity was improved, from 51.4% at T2 to 63.1% at T4. The optimal model was a 2-group trajectory of sexual activity in breast cancer patients,36.6% in the “low activity group” and 63.4% in the “high activity group.” The multivariate binary logistic regression analysis revealed statistically significant and positive correlations between sexual activity and age (β = 0.085, OR = 1.089, 95%CI 1.035 ∼ 1.145, P = 0.001),libido(β = 0.774, OR = 2.168, 95%CI 1.337 ∼ 3.515, P = 0.002), vaginal lubrication(β = 1.254, OR = 33.503, 95%CI 2.000 ∼ 6.137, P

Multiple myeloma (MM) is a Ubiquitin Proteasome System (UPS)-dysfunction disease. We previously reported that high PRAME transcript levels associated with unfavorable progression free survival (PFS) in patients with no bortezomib therapy, and bortezomib-containing regimen significantly improved PFS in patients with high PRAME transcript levels, which indicated that PRAME expression was prognostic for MM patients, and was related to proteasome inhibitor treatment. However, molecular mechanisms underlying the above clinical performance remain unclear. In the present study, MM cell models with PRAME knockdown and overexpression were established, and PRAME was identified to play the role of promoting proliferation in MM cells. P-Akt signaling was found to be activated as PRAME overexpressed. As a substrate recognizing subunit (SRS) of the E3 ubiquitin ligase, PRAME targets substrate proteins and mediates their degradation. CTMP and p21 were found to be the novel targets of PRAME in the Cul2-dependent substrate recognition process. PRAME interacted with and mediated ubiquitination and degradation of CTMP and p21, which led to accumulation of p-Akt and CCND3 proteins, and thus promoted cell proliferation and increased bortezomib sensitivity in MM cells.

Artificial synapse inspired by the biological brain has great potential in the field of neuromorphic computing and artificial intelligence. The memristor is an ideal artificial synaptic device with fast operation and good tolerance. Here, we have prepared a memristor device with Au/CsPbBr3/ITO structure. The memristor device exhibits resistance switching behavior, the high and low resistance states no obvious decline after 400 switching times. The memristor device is stimulated by voltage pulses to simulate biological synaptic plasticity, such as long-term potentiation, long-term depression, pair-pulse facilitation, short-term depression, and short-term potentiation. The transformation from short-term memory to long-term memory is achieved by changing the stimulation frequency. In addition, a convolutional neural network was constructed to train/recognize MNIST handwritten data sets; a distinguished recognition accuracy of ∼96.7% on the digital image was obtained in 100 epochs, which is more accurate than other memristor-based neural networks. These results show that the memristor device based on CsPbBr3 has immense potential in the neuromorphic computing system.

Abstract The central concept of strategic benchmarking is resource management efficiency, which ultimately results in profitability. However, little is known about performance measurement from resource-based perspectives. This study uses the data envelopment analysis (DEA) model with a dynamic network structure to measure the resource management and profitability efficiencies of 287 US commercial banks from 2010 to 2020. Furthermore, we provide frontier projections and incorporate five variables, namely capital adequacy, asset quality, management quality, earning ability, and liquidity (i.e., the CAMEL ratings). The results revealed that the room for improvement in bank performance is 55.4%. In addition, we found that the CAMEL ratings of efficient banks are generally higher than those of inefficient banks, and management quality, earnings quality, and liquidity ratios positively contribute to bank performance. Moreover, big banks are generally more efficient than small banks. Overall, this study continues the current heated debate on performance measurement in the banking industry, with a particular focus on the DEA application to answer the fundamental question of why resource management efficiency reflects benchmark firms and provides insights into how efficient management of CAMEL ratings would help in improving their performance.

AIM: To explore the factors influencing individuals' willingness to participate in ophthalmic clinical trials. METHODS: A questionnaire survey was conducted from January to April 2021 among patients and their family members at Zhongshan Ophthalmic Center, Sun Yat-sen University, in Guangzhou, China. The survey gathered data on respondents' willingness, demographic and socioeconomic profiles, as well as their reasons and concerns regarding engagement in clinical trials. RESULTS: Of the 1078 residents surveyed (mean age 31.2±13.1y; 65.8% females) in Guangzhou, 749 (69.5%) expressed a willingness to participate in future ophthalmic clinical trials. Specific characteristics associated with greater willingness included a younger age, lower annual income, higher education, prior participation experience, previous ophthalmic treatment, and a better understanding of clinical trials. With the exception of age, these characteristics were significantly linked to a higher willingness. The primary barrier to participation, expressed by 64.8% of those willing and 54.4% of those unwilling, was “Uncertain efficacy”. In terms of motivations, the willing group ranked “Better therapeutic benefits” (35.0%), “Professional monitoring” (34.3%), and “Trust in healthcare professionals” (33.1%) as their top three reasons, whereas the unwilling participants indicated “Full comprehension of the protocol” (46.2%) as the key facilitator. CONCLUSION: This study reveals a substantial willingness to participate in ophthalmic clinical trials and demonstrates the predictive role of demographic and socioeconomic factors. Variations in motivators and concerns between willing and unwilling participants highlight the significance of tailored recruitment strategies. Importantly, the need for and trust in healthcare professionals stand out as powerful motivations, underscoring the importance of enhancing physician-patient relationships, adopting patient-centered communication approaches, and addressing individualized needs to improve accrual rates.

One of the main underlying etiologies of type 2 diabetes (T2DM) is insulin resistance, which is most frequently caused by obesity. Notably, the deregulation of adipokine secretion from visceral adiposity has been identified as a crucial characteristic of type 2 diabetes and obesity. Spexin is an adipokine that is released by many different tissues, including white adipocytes and the glandular stomach, and is negatively connected with the state of energy storage. This peptide acts through GALR2/3 receptors to control a wide range of metabolic processes, including inflammation, browning, lipolysis, energy expenditure, and eating behavior. Specifically, spexin can enter the hypothalamus and regulate the hypothalamic melanocortin system, which in turn balances energy expenditure and food intake. This review examines recent advances and the underlying mechanisms of spexin in obesity and T2DM. In particular, we address a range of topics from basic research to clinical findings, such as an analysis of the possible function of spexin in the hypothalamic melanocortin response, which involves reducing energy intake and increasing energy expenditure while also enhancing insulin sensitivity and glucose tolerance. Gaining more insight into the mechanisms that underlie the spexin system's control over energy metabolism and homeostasis may facilitate the development of innovative treatment approaches that focus on combating obesity and diabetes.

Abstract Cancer is a disease with molecular heterogeneity that is closely related to gene mutations and epigenetic changes. The principal histological subtype of lung cancer is non‐small cell lung cancer (NSCLC). Long noncoding RNA (lncRNA) is a kind of RNA that is without protein coding function, playing a critical role in the progression of cancer. In this research, the regulatory mechanisms of lncRNA phosphorylase kinase regulatory subunit alpha 1 antisense RNA 1 (PHKA1‐AS1) in the progression of NSCLC were explored. The increased level of N6‐methyladenosine (m6A) modification in NSCLC caused the high expression of PHKA1‐AS1. Subsequently, high‐expressed PHKA1‐AS1 significantly facilitated the proliferation and metastasis of NSCLC cells, and these effects could be reversed upon the inhibition of PHKA1‐AS1 expression, both in vivo and in vitro. Additionally, the target protein of PHKA1‐AS1 was actinin alpha 4 (ACTN4), which is known as an oncogene. Herein, PHKA1‐AS1 could enhance the protein stability of ACTN4 by inhibiting its ubiquitination degradation process, thus exerting the function of ACTN4 in promoting the progress of NSCLC. In conclusion, this research provided a theoretical basis for further exploring the potential mechanism of NSCLC metastasis and searching novel biomarkers related to the pathogenesis and progression of NSCLC.

Background: Lung adenocarcinoma (LUAD) has a complex tumor heterogeneity. Our research attempts to clearness LUAD subtypes and build a reliable prognostic signature according to the activity changes of the hallmark and immunologic gene sets. Methods: According to The Cancer Genome Atlas (TCGA) - LUAD dataset, changes in marker and immune gene activity were analyzed, followed by identification of prognosis-related differential gene sets (DGSs) and their related LUAD subtypes. Survival analysis, correlation with clinical characteristics, and immune microenvironment assessment for subtypes were performed. Moreover, the differentially expressed genes (DEGs) between different subtypes were identified, followed by the construction of a prognostic risk score (RS) model and nomogram model. The tumor mutation burden (TMB) and tumor immune dysfunction and exclusion (TIDE) of different risk groups were compared. Results: Two LUAD subtypes were determined according to the activity changes of the hallmark and immunologic gene sets. Cluster 2 had worse prognosis, more advanced tumor and clinical stages than cluster 1. Moreover, a prognostic RS signature was established using two LUAD subtype-related DEGs, which could stratify patients at different risk levels. Nomogram model incorporated RS and clinical stage exerted good prognostic performance in LUAD patients. A shorter survival time and higher TMB were observed in the high-risk patients. Conclusions: Our findings revealed that our constructed prognostic signature could exactly predict the survival status of LUAD cases, which was helpful in predicting the prognosis and guiding personalized therapeutic strategies for LUAD.

Compared with physical models, WRF-Solar, as an excellent numerical forecasting model, includes abundant novel cloud physical and dynamical processes, which enablesenable the high-frequency output of radiation components which are urgently needed by the solar energy industry. However, the popularisation of WRF-Solar in a wide range of applications, such as the estimation of diffuse radiation, suffers from unpredictable influences of cloud and aerosol optical property parameters. This study assessed the accuracy of the improved numerical weather prediction (WRF-Solar) model in simulating global and diffuse radiation. Aerosol optical properties at 550 nm, which were provided by a moderate resolution imaging spectroradiometer, were used as input to analyse the differences in accuracies obtained by the model with/without aerosol input. The sensitivity of WRF-Solar to aerosol and cloud optical properties and solar zenith angle (SZA) was analysed. The results show the superiority of WRF-Solar to WRF-Dudhia in terms of their root mean square error (RMSE) and mean absolute error (MAE). The coefficients of determination between WRF-Solar and WRF-Dudhia revealed no statistically significant difference, with values greater than 0.9 for the parent and nested domains. In addition, the relative RMSE (RRMSE%) reached 46.60%. The experiment on WRF-Solar and WRF-Dudhia revealed a negative bias for global radiation, but WRF-Solar attained a slightly lower RMSE and higher correlation coefficient than WRF-Dudhia. The WRF-Solar-simulated results on diffuse radiation under clear sky conditions were slightly poorer, with RMSE, RRMSE, mean percentage error and MAE of 181.93 W m−2, 170.52%, 93.04% and 138 W m−2, respectively. Based on Himawari-8 cloud data, statistical results on cloud optical thickness (COT) for cloudy days revealed that WRF-Solar overestimated diffuse radiation at COTs greater than 20. Moreover, when the aerosol optical depth was greater than or equal to 0.8, WRF-Solar also overestimated the diffuse radiation, with a mean difference of 58.57 W m−2. The errors of WRF-Solar simulations in global and diffuse radiation exhibited a significant dependence on the SZA. The dispersion degree of deviation increased gradually with the decrease in the SZA. Thus, WRF-Solar serves as an improved numerical tool that can provide high temporal and high-spatial-resolution solar radiation data for the prediction of photovoltaic power. Studies should explore the improvement of cumulus parameterisation schemes to enhance the accuracy of solar radiation component estimation and prediction under cloudy conditions.