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Background/purpose: Improved communication can optimize treatment outcomes and patient satisfaction. Findings emphasize the need for tailored communication strategies based on patient characteristics. Implementing communication courses can enhance patient-centered care and reduce conflicts. Therefore, this study examined the feasibility of integrating doctor-patient communication education in Taiwan's dental education system. Materials and methods: Using interviews and questionnaires, we conducted descriptive statistics and generalized linear mixed-effects model analysis on the importance of doctor-patient communication from the dentist and patient perspectives. Results: More than 600 patient surveys and four interviewed dentists with 20+ years of experience stressed doctor-patient communication in dentistry. Patients' age and income were positively related to the emphasis on physician-patient communication but negatively associated with dental assistants' communication. Dentists valued communication education but differed in its execution and importance. Conclusion: It is recommended to initiate dentist-patient communication education during university studies and continue its practice to adapt to the changing societal dynamics. Individuals with higher socioeconomic status and older age show a greater appreciation for dentist-patient communication, potentially driven by self-promotion, thereby highlighting the diverse nature of doctor-patient relationships. Based on our findings, we suggest to implement the doctor-patient communication courses in Taiwan.

Abstract Background Drug repositioning is a very important task that provides critical information for exploring the potential efficacy of drugs. Yet developing computational models that can effectively predict drug–disease associations (DDAs) is still a challenging task. Previous studies suggest that the accuracy of DDA prediction can be improved by integrating different types of biological features. But how to conduct an effective integration remains a challenging problem for accurately discovering new indications for approved drugs. Methods In this paper, we propose a novel meta-path based graph representation learning model, namely RLFDDA, to predict potential DDAs on heterogeneous biological networks. RLFDDA first calculates drug–drug similarities and disease–disease similarities as the intrinsic biological features of drugs and diseases. A heterogeneous network is then constructed by integrating DDAs, disease–protein associations and drug–protein associations. With such a network, RLFDDA adopts a meta-path random walk model to learn the latent representations of drugs and diseases, which are concatenated to construct joint representations of drug–disease associations. As the last step, we employ the random forest classifier to predict potential DDAs with their joint representations. Results To demonstrate the effectiveness of RLFDDA, we have conducted a series of experiments on two benchmark datasets by following a ten-fold cross-validation scheme. The results show that RLFDDA yields the best performance in terms of AUC and F1-score when compared with several state-of-the-art DDAs prediction models. We have also conducted a case study on two common diseases, i.e., paclitaxel and lung tumors, and found that 7 out of top-10 diseases and 8 out of top-10 drugs have already been validated for paclitaxel and lung tumors respectively with literature evidence. Hence, the promising performance of RLFDDA may provide a new perspective for novel DDAs discovery over heterogeneous networks.

Introduction The relationship between admission time and intensive care unit (ICU) mortality is inconclusive and influenced by various factors. This study aims to estimate the effect of admission time on ICU outcomes in a tertiary teaching hospital in China by propensity score matching (PSM) and stratified analysis. Methods A total of 2,891 consecutive patients were enrolled in this study from January 1, 2009 to December 29, 2011. Multivariate logistic regression and survival analysis were performed in this retrospective study. PSM and stratified analysis were applied for confounding factors, such as Acute Physiologic and Chronic Health Evaluation II (APACHE II) score and admission types. Results Compared with office hour subgroup (n = 2,716), nighttime (NT, n = 175) subgroup had higher APACHE II scores (14 vs. 8, P < 0.001), prolonged length of stay in the ICU (42 vs. 24 h, P = 0.011), and higher percentages of medical (8.6% vs. 3.3%, P < 0.001) and emergency (59.4% vs. 12.2%, P < 0.001) patients. Moreover, NT admissions were related to higher ICU mortality [odds ratio (OR), 1.725 (95% CI 1.118-2.744), P = 0.01] and elevated mortality risk at 28 days [14.3% vs. 3.2%; OR, 1.920 (95% CI 1.171-3.150), P = 0.01]. PSM showed that admission time remained related to ICU outcome (P = 0.045) and mortality risk at 28 days [OR, 2.187 (95% CI 1.119-4.271), P = 0.022]. However, no mortality difference was found between weekend and workday admissions (P = 0.849), even if weekend admissions were more related to higher APACHE II scores compared with workday admissions. Conclusions NT admission was associated with poor ICU outcomes. This finding may be related to shortage of onsite intensivists and qualified residents during NT. The current staffing model and training system should be improved in the future. [ABSTRACT FROM AUTHOR]

To identify the side population (SP) cells from four hepatocellular carcinoma (HCC) cell lines with stepwise metastatic potentials. SP cells were sorted from HCCLM3, MHCC97-H, MHCC97-L and Hep3B by flow cytometry, and then analyzed by differentiation study, clonogenic assay, chemoresistance study and tumorigenicity assay in vivo. The expression of ABCG2 in SP cells was detected by immunocytochemistry, western blotting and real-time quantitative PCR, respectively. There was significant difference in SP proportion among HCCLM3, MHCC97-H, MHCC97-L and Hep3B (28.7 ± 1.6%, 14.5 ± 0.6%, 4.2 ± 0.4%, 0.9 ± 0.1%, respectively, P < 0.01). All the SP cells showed similar characteristics of self-renewal, high clonogenicity, remarkable chemo-resistance and high expression of ABCG2. As low as 2,000 SP cells could initiate tumors in non-obese diabetic/severe combined immunodeficiency mice successfully. SP cells purified from HCC cell lines harbors cancer stem cell-like properties, and may be related to the metastatic potentials and therapeutic-resistance of HCC. [ABSTRACT FROM AUTHOR]