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BackgroundEarly somatic embryogenesis (SE) has been recognized as an important tool for plants to propagate in vitro. However, our knowledge about the proteins involved in early SE including the callus dedifferentiation is still limited, especially in the economic woody tree – Eucalyptus.ResultsWe performed the data-independent acquisition (DIA) mass-spectrometry (MS) to study the proteins involved in early SE of two Eucalyptus species - E. camaldulensis (high regeneratively potential) and E. grandis x urophylla (low regenerative potential). Initially, the data-dependent acquisition MS produced 44,451 peptides and 9,142 proteins. While the DIA MS identified 35,207 peptides and 7,077 proteins in the stem and tissue-culture induced callus of the two Eucalyptus species. MSstat identified 2,078 and 2,807 differentially expressed proteins (DEPs) in early SE of E. camaldulensis and E. grandis x urophylla, respectively. They shared 760 upregulated and 420 downregulated proteins, including 4 transcription factors, 31 ribosomal proteins, 1 histone, 3 zinc finger proteins (ZFPs), ARF19, WOX8 and PIN1. Further, 27 and 4 DEPs were found to be involved in “photosynthesis” (ko00195) and “two-component system” (ko02020), respectively. Notably, SERK, WRKY, ZFP and ABC transporter proteins were analyzed to be related with high SE potential. By combining the miRNA and RNA-Seq results, some miRNA-mRNA/protein regulation networks might be involved in early SE of Eucalyptus, like miR160~TPP2, miR164~UXS2, miR169~COX11 and miR535~ Eucgr.E01067.ConclusionsThis is the first study of proteome profiles in early SE of Eucalyptus. The findings will improve our understanding of molecular changes and regulatory networks in early SE of Eucalyptus.

ObjectiveThis study aimed to develop a function for mapping the cancer-specific instrument (FACT–G) to a preference-based measure (EQ-5D-3L) utility index for HRQoL, in which the utility scores were generated using the Chinese value set.MethodThe data are based on a cross-sectional survey of 243 patients in China with different cancer types. Cancer patients who completed the EQ-5D-3L and the FACT-G questionnaire, and patient demographics and clinical characteristics were included in this study. Regression models were used to predict the EQ-5D-3L utility index values based on four subscale scores of the FACT-G using the ordinary least squares (OLS) model, generalized linear models (GLM), censored least absolute deviations (CLAD), Tobit model, and two-part model (TPM) regression approaches. The performance and predictive power of each model were also evaluated using r2 and adj- r2, mean absolute error (MAE) and root mean squared error (RMSE). Linear equating is a mapping technique that avoids regression to the mean.ResultsThe introduction of the square term and the interaction term improves the accuracy of the model. The social well-being subscale of the FACT-G was not associated with the EQ-5D-3L utility index, whereas, the physical, emotional, functional well-being, and FACT-G total scores were derived when mapping the FACT-G to the EQ-5D-3L utility index. For the FACT-G, the OLS model was the best at predicting mean EQ-5D-3L values among all the regression models and has 70% explanatory power for the observed EQ-5D-3L variation. Nevertheless, the OLS model overpredicted utilities for poorer health states and underestimated utilities for those with better health. The result of the OLS model, GLM, and CLAD models were similar to the MAE, MSE, and RMSE. The results showed that the mean prediction accuracy of the OLS models was higher than that of the other models, and the OLS model's linear equating predicted values were much closer to the observed values.ConclusionThe algorithm based on Chinese population development for mapping the FACT-G into the EQ-5D-3L utility index can be realized. We also recommend that OLS models be used to assess the economic evaluation of patients' health-related quality of life when the population is in moderate to good health for further cost-utility analysis in China.

ObjectiveThis study aimed to develop a function for mapping the cancer-specific instrument (FACT–G) to a preference-based measure (EQ-5D-3L) utility index for HRQoL, in which the utility scores were generated using the Chinese value set.MethodThe data are based on a cross-sectional survey of 243 patients in China with different cancer types. Cancer patients who completed the EQ-5D-3 L and the FACT-G questionnaire, and patient demographics and clinical characteristics were included in this study. Regression models were used to predict the EQ-5D-3L utility index values based on four subscale scores of the FACT-G using the ordinary least squares (OLS) model, generalized linear models (GLM), censored least absolute deviations (CLAD), Tobit model, and two-part model (TPM) regression approaches. The performance and predictive power of each model were also evaluated using r2 and adj- r2, mean absolute error (MAE) and root mean squared error (RMSE).ResultsThe introduction of the square term and the interaction term improves the accuracy of the model. The social well-being subscale of the FACT-G was not associated with the EQ-5D-3L utility index, whereas, the physical, emotional, functional well-being, and FACT-G total scores were derived when mapping the FACT-G to the EQ-5D-3L utility index. For the FACT-G, the OLS model was the best at predicting mean EQ-5D-3L values among all the regression models and has 70% explanatory power for the observed EQ-5D-3L variation. Nevertheless, the OLS model overpredicted utilities for poorer health states and underestimated utilities for those with better health. The result of the OLS model, GLM, and CLAD models were similar to the MAE, MSE, and RMSE.ConclusionThe algorithm based on Chinese population development for mapping the FACT-G into the EQ-5D-3L utility index can be realized. We also recommend that OLS models be used to assess the economic evaluation of patients' health-related quality of life when the population is in moderate to good health for further cost-utility analysis in China.

Background Information and communication technology (ICT) has been widely used in medical education as well as biomedical and population based research, however, the use of ICT in China is still insufficient. This study aimed to investigate the use, perceptions and attitudes of ICT use in biomedical and population based research among faculty members in medical universities in southern China. Methods A cross-sectional study was conducted among faculty members working in the health sciences discipline in 6 major universities in southern China. A self-completed online questionnaire was used for data collection. Findings Of 270 faculty members enrolled, 206 faculties (76%) used ICT in their work and 54% were female. Few faculty members took an online course or were trained on ICT use before. The ICT- using group was more experienced than the ICT-free group (P= 0.047). The most frequently used ICT tools were mobile phone, the Internet, non-mobile computer system, WeChat (similar to Facebook - a popular social communication tool in China) and QQ (a popular chat tool in China). The use of non-mobile computer systems, WeChat and QQ in ICT-using group was more frequent than in ICT-free group (P