C-reactive protein (CRP) is an acute-phase protein produced by hepatocytes. The plasma concentration of CRP peaks around 48 hours following stimulation. A rapid decrease in CRP levels is observed when the stimuli end. Considering these characteristics of CRP, it is used to evaluate acute inflammatory responses in clinics. In addition, as it reflects the degree of surgical trauma, measuring the CRP concentration is an effective method of evaluating tissue damage depending upon the surgical method. As CRP is also an acute-phase protein in dogs, the purpose of the present study was to compare the factors related to acute inflammatory responses between dogs undergoing elective general surgery (GS) and orthopedic surgery (OS). A total of 44 healthy dogs were included in this study. The sex ratio of dogs that underwent OS was similar. Both groups showed increased CRP levels and white blood cell (WBC) counts on post-operative day (POD) 1-2. The CRP level in the OS group on POD 1-2 was significantly higher than that of the GS group and it was increased about 16-fold compared to the pre-operative value. No significant difference in WBC counts was observed between the two groups. Although a slight increase in the WBC count was observed on POD 1-2 in both groups, it was near the reference range during follow-up. Thus, measuring CRP levels can be more effective in evaluating acute inflammatory responses than WBC counts. Although a high level of post-operative serum CRP concentrations was observed in the OS group, it rapidly decreased to a level similar to the pre-operative value if there were no post-operative complications.

This study summarizes the recent cutting-edge approaches for dentin regeneration that still do not offer adequate solutions. Tertiary dentin is formed when odontoblasts are directly affected by various stimuli. Recent preclinical studies have reported that stimulation of the Wnt/β-catenin signaling pathway could facilitate the formation of reparative dentin and thereby aid in the structural and functional development of the tertiary dentin. A range of signaling pathways, including the Wnt/β-catenin pathway, is activated when dental tissues are damaged and the pulp is exposed. The application of small molecules for dentin regeneration has been suggested as a drug repositioning approach. This study reviews the role of Wnt signaling in tooth formation, particularly dentin formation and dentin regeneration. In addition, the application of the drug repositioning strategy to facilitate the development of new drugs for dentin regeneration has been discussed in this study.

Teacher professional development is critical because teachers play a pivotal role in students' positive learning experience in schools. In particular, teachers' systematic class goal-setting practice is important for their performance outcomes such as effective classroom management and student learning. This study investigates the effects of teachers' engagement in class goal-setting activities using strategies derived from Analysis, Design, Development, Implementation, and Evaluation (ADDIE) framework as a systematic guideline by exploring the relationship among the four variables: teachers' class goal-setting, their partnership with stakeholders, teacher effectiveness, and student satisfaction. By using Process analysis techniques to estimate the dual mediation model on data from 55 elementary school teachers and their 1790 students, the findings indicate the positive relationship between teachers' systematic efforts for their class goal setting and student satisfaction was fully and sequentially mediated by teachers' partnership activities with the stakeholders and perceived teacher effectiveness. The findings propose the importance of teachers' systematic goal-setting strategies in their classes, which can be developed for professional development opportunities leading to successful performance outcomes. The study also highlights the various indirect effects produced by teachers' engagement in class goal setting. The practical implications of the research as well as theoretical contributions for teachers are discussed.

This study suggests a machine learning model for predicting the production quality of free-machining 303-series stainless steel small rolling wire rods according to the manufacturing process's operation condition. The operation condition involves 37 features such as sulfur, manganese, carbon content, rolling time, and rolling temperature. The study procedure includes data preprocessing (integration and refinement), exploratory data analysis, feature selection, machine learning modeling. In the preprocessing stage, missing values and outlier are removed, and variables for the interaction between processes and quality influencing factors identified in existing studies are added. Features are selected by variable importance index of lasso regression, extreme gradient boosting (XGBoost), and random forest models. Finally, logistic regression, support vector machine, random forest, and XGBoost is developed as a classifier to predict good or defective products with new operating condition. The hyper-parameters for each model are optimized using k-fold cross validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with accuracy of 0.9929, specificity of 0.9372, F1-score of 0.9963 and logarithmic loss of 0.0209. In this study, the quality prediction model is expected to be able to efficiently perform quality management by predicting the production quality of small rolling wire rods in advance.