The metabolic reprogramming of γ-aminobutyrate in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy. The oncometabolites have been studied in OSCC, but the mechanism of metabolic reprogramming remains unclear. To identify the potential metabolic markers to distinguish malignant oral squamous cell carcinoma (OSCC) tissue from adjacent healthy tissue and study the mechanism of metabolic reprogramming in OSCC. We compared the metabolites between cancerous and paracancerous tissues of OSCC patients by 1HNMR analysis. We established OSCC derived cell lines and analyzed their difference of RNA expression by RNA sequencing. We investigated the metabolism of γ-aminobutyrate in OSCC derived cells by real time PCR and western blotting. Our data revealed that much more γ-aminobutyrate was produced in cancerous tissues of OSCC patients. The investigation based on OSCC derived cells showed that the increase of γ-aminobutyrate was promoted by the synthesis of glutamate beyond the mitochondria. In OSCC cancerous tissue derived cells, the glutamate was catalyzed to glutamine by glutamine synthetase (GLUL), and then the generated glutamine was metabolized to glutamate by glutaminase (GLS). Finally, the glutamate produced by glutamate-glutamine-glutamate cycle was converted to γ-aminobutyrate by glutamate decarboxylase 2 (GAD2). Our study is not only benefit for understanding the pathological mechanisms of OSCC, but also has application prospects for the diagnosis of OSCC.

[TAN Bayesian network modeling of online learning decision making of dental undergraduates during the COVID-19 pandemic].

PURPOSE: To perceive the dental undergraduate's policy of coping with online learning and their decision-making laws during the COVID-19 pandemic. METHODS: For dental undergraduate students from the 2016 grade to 2018 grade of Lishui University, two prospective questionnaire surveys were conducted before the online course starting and four weeks later. SPSS Modeler18.0 software was used to screen, review, and analyze the data. TAN (tree augmented naive) Bayesian network models were utilized to analyze and predict variables. Indicators like the overall prediction accuracy, receiver operating characteristic curve (ROC curve), and area under the ROC curve(AUC value) were applied to evaluate the model's predicting performances. RESULTS: The case score of each survey was 422 and 382, and the Cronbach's α coefficients of internal consistency were 0.91 and 0.82. Among the decision-making variables in the aspect of "whether to preview online learning materials", the top-two variables were "looking forward to the semester beginning" and "the validity of the network materials". In speaking of "whether the online courses meet the offline course standards", the top-three variables were "the rhythm of lecturing on live or in recorded videos", "how many online tasks', and" the data frame and organization". The overall prediction accuracy of each constructed TAN Bayesian network model was 89.42% and 87.82%, and their AUC values were 0.75 and 0.93, respectively. CONCLUSIONS: To truly make online courses comparable to the off-line curriculum, teachers should fully understand how the students cope with their online learning at first. Then, only by perceiving and recognizing the students' expectations for education, by efficiently preparing and organizing online materials with all-round, clearly-structured, vivid, comprehensible contents and moderate difficult tasks, by well interacting with students through different websites and social media, can we truly achieve " ongoing learning with suspended class".

[A survey of first molar caries among primary school students in Lishui].

PURPOSE: To elucidate school age students' oral health status in Lishui city and monitor caries tendency of their first molars. METHODS: Four hundred and forty-eight primary school students of the first and second grades were cluster sampled from the urban and suburb districts. The first molar crown caries were measured and their oral health caring measures were investigated. RESULTS: The results showed that suburb children's DMFT and first molar caries prevalence were both higher than the children in the urban district, but the time of tooth brushing was obviously lower. The results also showed the most important influencing factors of caries were tooth brushing, followed by age, districts, and gender etc. CONCLUSION: It is suggested that we should enforce the oral health care education and promotion, especially in the suburb area.