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Abstract Background Despite ongoing research, the underlying causes of schizophrenia remain unclear. Aspartate and asparagine, essential amino acids, have been linked to schizophrenia in recent studies, but their causal relationship is still unclear. This study used a bidirectional two-sample Mendelian randomization (MR) method to explore the causal relationship between aspartate and asparagine with schizophrenia. Methods This study employed summary data from genome-wide association studies (GWAS) conducted on European populations to examine the correlation between aspartate and asparagine with schizophrenia. In order to investigate the causal effects of aspartate and asparagine on schizophrenia, this study conducted a two-sample bidirectional MR analysis using genetic factors as instrumental variables. Results No causal relationship was found between aspartate and schizophrenia, with an odds ratio (OR) of 1.221 (95%CI: 0.483–3.088, P-value = 0.674). Reverse MR analysis also indicated that no causal effects were found between schizophrenia and aspartate, with an OR of 0.999 (95%CI: 0.987–1.010, P-value = 0.841). There is a negative causal relationship between asparagine and schizophrenia, with an OR of 0.485 (95%CI: 0.262-0.900, P-value = 0.020). Reverse MR analysis indicates that there is no causal effect between schizophrenia and asparagine, with an OR of 1.005(95%CI: 0.999–1.011, P-value = 0.132). Conclusion This study suggests that there may be a potential risk reduction for schizophrenia with increased levels of asparagine, while also indicating the absence of a causal link between elevated or diminished levels of asparagine in individuals diagnosed with schizophrenia. There is no potential causal relationship between aspartate and schizophrenia, whether prospective or reverse MR. However, it is important to note that these associations necessitate additional research for further validation.

Objective To explore the implementation effect of scenario simulation teaching method in the clinical teaching practice of oral medicine for nursing students. Methods A total of 68 nursing students who participated in clinical internship were selected, all of whom are full-time students majoring in oral nursing. Nursing students with internship between January 2021to December 2021 were allocated into the control group, receiving a routine teaching method during clinical practice. Nursing students with internship from January 2022 to December 2022 were included as the study group, receiving the scenario simulation teaching method. To investigate nursing students' knowledge and practices of oral care, and to evaluate their satisfaction with clinical teaching environment. Results The comprehensive test score of the nursing students in the study group (94. 51±5. 02) was higher than that of the control group (89. 32±5. 93), with a significant difference (P＜0. 05). In terms of the clinical environment practice evaluation, the study group achieved higher scores than the control group in aspects of teaching methods, learning opportunities, and organizational support, and the results were statistically different (P＜0. 05). Conclusion Scenario simulation teaching improves the clinical theoretical knowledge and clinical practice level of oral medicine nursing students, and also improves the satisfaction of nursing students with clinical practice environment. (目的 探讨情景模拟教学法在口腔内科护生临床教学实践中的应用效果。方法 选取2021年1月—12月北京大学口腔医院牙体牙髓科实习的34名护生为对照组, 另选取2022年1月—12月实习的34名护生为研究组。对照组实施口腔内科常规临床护理教学法, 研究组实施情景模拟教学法。分别于入科时和出科前对两组护生进行理论与操作考核, 比较两组对临床学习环境的满意度。结果 两组出科考试成绩均高于入科时, 研究组护生综合考试成绩(94. 51±5. 02)分, 高于对照组的(89. 32±5. 93)分, 差异有统计学差异(P＜0. 05)。研究组护生对教学方法、学习机会、组织支持维度的临床学习环境评价满意度高于对照组, 差异有统计学意义(P＜0. 05)。结论 情景模拟教学不仅有助于提高口腔内科护生临床理论知识和临床操作水平, 且临床学习环境更好, 起到了教学相长的作用, 值得推广应用。)

As computer science advances, it intersects intriguingly with the realm of music acoustics, particularly in enhancing piano performance through technological means. This paper delves into an innovative approach to piano learning and creation, focusing on emotional expression’s nuances. We have devised a system capable of precise musical tone recognition and sound quality evaluation by adopting Mel Frequency Cepstral Coefficients (MFCC) for the nuanced extraction of piano sounds and integrating dynamic fuzzy neural networks. Our findings show an impressive accuracy rate, with musical tone misidentification below 2.58% and sound quality assessment errors within a 5% margin. This work not only sets a new benchmark in piano performance analysis but also paves the way for revolutionary teaching methods in music education, with profound implications for artistic instruction and emotional expression.

The piano education industry occupies a huge market. However, the automatic piano performance evaluation function has shortcomings in the existing piano education. In this paper, we first design a piano performance evaluation model based on the continuous discretization method for piano performance audio and improve the piano performance feature filtering and feature extraction methods through cubic spline interpolation and support vector regression, respectively. Secondly, a piano performance evaluation system based on music theory knowledge is studied to evaluate the user’s performance ability based on the rating of rhythm, main melody, and musicality performance of different levels of score performance audio and to achieve the purpose of assisting piano teaching. The results show that the difference between the scoring based on the continuous, discrete model and the actual level value of the player is less than 0.05, and the output of the evaluation system can achieve consistency; in the comparison experiments, the accuracy of three traditional evaluation models, BP, RNN, and LSTM, is 45%, 42%, and 75%, respectively, while the accuracy of the continuous, discrete model is 78%, with an average performance improvement of 23%. The continuous, discrete piano performance evaluation model proposed in this paper is more effective and objective in evaluating users’ piano performance ability and provides a guiding reference for performance evaluation in the piano education industry.