The Panax ginseng C.A. Meyer belonging to the Araliaceae has long been used as an herbal medicine. Although public databases are presently available for this family, no methyl jasmonate (MeJA) elicited transcriptomic information was previously reported on this species, with the exception of a few expressed sequence tags (ESTs) using the traditional Sanger method. Here, approximately 53 million clean reads of adventitious root transcriptome were separately filtered via Illumina HiSeq™2000 from two samples treated with MeJA (Pg-MeJA) and equal volumes of solvent, ethanol (Pg-Con). Jointly, a total of 71,095 all-unigenes from both samples were assembled and annotated, and based on sequence similarity search with known proteins, a total of 56,668 unigenes was obtained. Out of these annotated unigenes, 54,920 were assigned to the NCBI non-redundant protein (Nr) database, 35,448 to the Swiss-prot database, 43,051 to gene ontology (GO), and 19,986 to clusters of orthologous groups (COG). Searching in the Kyoto encyclopedia of genes and genomes (KEGG) pathway database indicated that 32,200 unigenes were mapped to 128 KEGG pathways. Moreover, we obtained several genes showing a wide range of expression levels. We also identified a total of 749 ginsenoside biosynthetic enzyme genes and 12 promising pleiotropic drug resistance (PDR) genes related to ginsenoside transport.

Aim: Shortening the length of stay (LOS) is a potential and sustainable way to relieve the pressure that type 2 diabetes mellitus (T2DM) patients placed on the public health system. Method: Multi-stage random sampling was used to obtain qualified hospitals and electronic medical records for patients discharged with T2DM in 2018. A box-cox transformation was adopted to normalize LOS. Multilevel model was used to verify hospital cluster effect on LOS variations and screen potential factors for LOS variations from both individual and hospital levels. Result: 50 hospitals and a total of 12,888 T2DM patients were included. Significant differences in LOS variations between hospitals, and a hospital cluster effect on LOS variations (t = 92.188, P<0.001) was detected. The results showed that female patients, patients with new rural cooperative’ medical insurance, hospitals with more beds, and hospitals with faster bed turnovers had shorter LOS. Conversely, elderly patients, patients with urban workers’ medical insurance, patients requiring surgery, patients with the International Classification of Diseases coded complication types E11.1, E11.2, E11.4, E11.5, and other complications cardiovascular diseases, grade III hospitals, hospitals with a lower doctor-to-nurse ratio, and hospitals with more daily visits per doctor had longer LOS. Conclusions: The evidence proved that hospital cluster effect on LOS variation did exist. Complications and patients features at individual level, as well as organization and resource characteristics at hospital level, had impacted LOS variations to varying degrees. To shorten LOS and better meet the medical demand for T2DM patients, limited health resources must be allocated and utilized rationally at hospital level, and the patients with the characteristics of longer LOS risk must be identified in time. More influencing factors on LOS variations at different levels are still worth of comprehensive exploration in the future.

Background: There have been few studies on satisfaction with integrated basic medical insurance for urban and rural residents (URRBMI), and satisfaction with URRBMI is not very high because of the complexity of its policies and differences among the insured. The aim of the present study was to explore the factors that influence satisfaction with URRBMI in China and to provide scientific suggestions to the government for how to effectively manage and improve the policy. Methods: An explanatory sequential design of mixed methods research was used. A quantitative research using a three-stage stratified cluster sampling method was used to randomly select the guardians of pupils who participated in URRBMI (n = 1335). The quantitative research was conducted to calculate the latent variables’ scores and path coefficients between latent variables using SmartPLS3.0. With public trust, public satisfaction, and perceived quality as the target variables, important-performance analysis (IPA) was used to explore the important but underperforming factors, which were the key elements to improving satisfaction with URRBMI. A purposeful sampling strategy according to satisfaction level was used to obtain qualitative research subjects from among the quantitative research subjects. A qualitative research was conducted using semi-structured interviews, and the thematic analysis method was used to summarize the interview data. Results: The three strongest paths were perceived quality to public satisfaction, with a total effect of 0.737 (t = 41.270, P < 0.001); perceived quality to perceived value, with a total effect of 0.676 (t = 31.964, P < 0.001); and public satisfaction to public trust, with a total effect of 0.634 (t = 31.305, P < 0.001). IPA revealed that public satisfaction and perceived quality were key factors for public trust and that perceived quality was of high importance for public satisfaction but had low performance. The policy quality was a determining factor for perceived quality. The qualitative research results showed that the most unsatisfactory aspect for the insured was the policy quality. Conclusions: This study found that improving quality is key to improving public satisfaction with and public trust in URRBMI. The government should improve the compensation level by broadening the channel of financing for the URRBMI fund, rationally formulating reimbursement standards, and broadening the scope of the drug catalog and the medical treatment projects. The government should establish a stable financing growth mechanism and effective methods of providing health education to improve public satisfaction and public trust.

Background: Quality is the most important factor in satisfaction. However, the existing satisfaction index model of urban and rural resident-based basic medical insurance scheme (SIM_URRBMI) lacks the segmentation of perceived quality elements, it couldn’t provide a reference for quality improvement and satisfaction promotion. This study aims to construct a revised SIM_URRBMI that can accurately and detailly measure perceived quality and provide feasible and scientific suggestions for improving the satisfaction of urban and rural residents' basic medical insurance scheme (URRBMI) in China. Methods: Based on the theoretical framework of the American Customer Satisfaction Index, the elements of perceived quality were refined through literature review and expert consultation, and a pool of alternative measurement variables was formed. A three-stage randomized stratified cluster sampling was adopted. The main decision makers of URRBMI in the families of primary school students in 8 primary schools in Changsha were selected. Both the classic test theory and the item response theory were used for measurement variables selection. The reliability and validity of the model were tested by partial least squares (PLS)-related methods. Results: A total of 1909 respondents who had URRBMI for their children were investigated. The SIM_URRBMI1.0 consists of 11 latent variables and 28 measurement variables with good reliability and validity. Among the three explanatory variables of public satisfaction, perceived quality had the largest total effect (path coefficient) (0.737). The variable with the greatest effect among the five first-order latent variables on perceived quality was the quality of the medical insurance policy (0.472). Conclusions: The SIM_URRBMI1.0 consists of 28 measurement variables and 11 latent variables. It is a reliable, valid, and standard satisfaction measurement tool for URRBMI with good prediction ability for public satisfaction. In addition, the model provides an accurate evaluation of the perceived quality, which will greatly help with performance improvement diagnosis. The most critical aspects of satisfaction improvement are optimizing the scope and proportion of reimbursement as well as setting appropriate level of deductible and capitation of URRBMI.

OBJECTIVES: This study investigated the seasonal impact of diurnal temperature range (DTR) on hospitalization rates for intracerebral hemorrhage (ICH) in middle-aged and elderly adults.METHODS: We collected data on the DTR and hospitalization records of ≥45-year-old patients with ICH in 2019 in Hunan Province, central China. Time-series analyses were performed using a distributed lag non-linear model.RESULTS: Overall, 54,690 hospitalizations for ICH were recorded. DTR showed a non-linear relationship with ICH hospitalization in both middle-aged and elderly populations (45-59 and ≥60 years, respectively). During spring, a low DTR coupled with persistently low temperatures increased ICH risk in both age groups, while a high DTR was associated with an increased risk in the middle-aged group only (relative risk [RR], 1.24; 95% confidence interval [CI], 1.21 to 1.27). In the summer, a low DTR combined with persistently high temperatures was linked to a higher risk exclusively in the middle-aged group. A high DTR in the autumn was correlated with increased risk in both age groups. In winter, either a low DTR with a continuously low temperature or a high DTR elevated the risk solely in the elderly population (RR, 1.37; 95% CI, 1.00 to 1.69). In the elderly group, the impact of DTR on hospitalization risk manifested within a 5-day period.CONCLUSIONS: The impact of DTR on ICH hospitalization risk differed significantly across seasons and between age groups. Elderly individuals demonstrated greater sensitivity to the impact of DTR. Weather forecasting services should emphasize DTR values, and interventions targeting sensitive populations are needed.