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Additional file 1: Supplementary information. Text S1: Calculation of the C allocation. Text S2: FTICR-MS sample preparation. Text S3: Isopycnic density gradient centrifugation and quantitative PCR. Text S4: Amplicon high-throughput sequencing data processing. Text S5: Metagenome sequencing and data processing. Text S6: Detailed information about data analyses. Figure S1: Assessment of labeling, centrifugation, and sequencing. Figure S2: The relational dendrograms of rhizodeposits. Figure S3: Relative abundance of peanut rhizodeposits. Figure S4: Correlations between the relative abundance of main categories of peanut rhizodeposits. Figure S5: Species composition of active bacterial communities. Figure S6: Correlation between belowground carbon allocation and species richness of active bacteria. Figure S7: Significantly different bacterial genera between P1 and P5 treatments. Figure S8: Random Forest model determining the key factors affecting the biodiversity of active rhizosphere microbiome. Figure S9: Mantel test investigating the relationship between microbial structure and changes in soil physicochemical properties. Figure S10: Correlation between potential transformations and concentration of peanut rhizodeposits. Figure S11: Principal coordinate analysis on the functional potentials of active bacterial communities. Figure S12: Mantel test investigating the relationship between functional potentials of active bacterial communities and rhizodeposits composition and changes in soil physicochemical properties. Figure S13: Correlations between relative abundance of abundant differential KO functional categories and soil physicochemical properties. Figure S14: Correlation between relative abundance of differential KEGG pathways and biodiversity of active bacteria, chemodiversity of rhizodeposits, and relative abundance of main categories of rhizodeposits. Table S1: Physicochemical properties of experimental soils. Table S2: The PERMANOVA investigating the structural difference of bacterial community in different CsCl buoyant density gradient of DNA fractions. Table S3: Detailed information about primers and PCR conditions. Table S4: Data size of metagenome sequences. Table S5: Two-way ANOVA investigating the factors affecting the belowground photosynthesized C allocation, chemodiversity and potential transformations of peanut rhizodeposits. Table S6: Correlations between belowground C allocation and plant and soil physicochemical properties. Table S7: Correlations between soil physicochemical properties and rhizodeposits chemodiversity. Table S8: Two-way PERMANOVA investigating the factors affecting the composition of rhizodeposits and structure of the active bacterial community in the peanut rhizosphere.

The purpose of hierarchical medical system is to lead in terms of improving efficiency, differentiating healthcare services and promoting labor division by changing the healthcare seeking behavior. The purpose of this research aims to discuss the public awareness of hierarchical medical system in Taiwan for the reference of health policy makers. We obtained our research data using a questionnaire survey; the total number of qualified patients was 1340. This research finds that more subjects agreed to the hierarchical medical system and medical referral system, but many people still disagreed with changes to their healthcare seeking choices due to policy promotion. Subtle changes, therefore, are observed that imply a crisis in terms of the trust in healthcare. The healthcare seeking behavior will not change if there is a difference between the medical awareness of patients and policy implementation, and the government needs to be concerned with this result when making policies.

Additional file 1: Fig. S1. Soil characteristics in the rhizosphere under manure treatments. Fig. S2. The alkaline and acid phosphomonoesterase activity in the rhizosphere under manure treatments. Fig. S3. The structure of arbuscular mycorrhizal fungi, fungivorous protist and nematode communities by principal coordinate analysis. Fig. S4. The ratios of arbuscular mycorrhizal fungi to plant biomass and fungivorous nematodes to plant biomass. Fig. S5. Correlation coefficients between arbuscular mycorrhizal fungi (AMF) community (biomass, diversity, and composition), fungivorous protists and nematodes, ALP activity, AMF colonization and the expression of ZMPht1;6 gene. Fig. S6. Mean contribution of soil variables, arbuscular mycorrhizal fungi (AMF) community, protists, and nematodes to AMF colonization and expression of P transporter gene ZMPht1;6 based on random forest modelling. Table S1. The characteristics of fine roots under four manure treatments.

National Health Insurance Administration established Pharma Cloud System in July 2014. The purpose is to decrease therapeutic duplications and enhance public medication safety. Comparison will be made among individual hospitals and the administering branches of National Health Insurance Bureau (NHIB) on the statistical data on the inquiry of the cloud medication history record system to understand the result of the installation and advocacy of this system. The results show (1) there were 2,329,846 entries of data collected from the branches of the NHIB from 2015 on cloud medication history record and 50,224 entries of data from individual hospitals. (2) The inquiry rate at the branches of the NHIB was 43.2% from January to April, 2015 and at individual hospitals was 18.8%. (3) The improvement rate at the branches of the NHIB was 32.5% and at the individual hospitals was 47.0% from January to April, 2015.

The use of smart mobile devices has been getting increasingly popular. The focus of this study is an attempt to explore the development of mobile medical App by medical centers and regional hospitals of Taiwan and the function of the App for comparison. The results show indicated that many hospitals developed Apps for the public for mobile medical service, of which 26 medical centers (100%) and 72 regional hospitals (84.7%) availed appointment making service via Apps. The result indicated variance at significant level (plt; 0.01). There are 23 medical centers (88.5%) and 74 regional hospitals (87.1%) availed Apps for checking service progress. The result indicated insignificant variance level (pgt; 0.01). We can see that mobile medical service is gradually emerging as a vital issue. Yet, this is a new domain in medical service. With the mushrooming of medical applications in smart mobile devices, the medical service system is expected to be installed in these devices to enhance interactive mode of operation and inquiry services, such as medication and inquiries into physical examination results. By then, people can learn the status of their health with this system.