ObjectiveTo probe into the influence of the zero price margin for drugs on the revenue-expenditure structure at primary healthcare organizations.MethodsOne of the pilot districts experimenting with this system in Ningbo city was earmarked as the research object.Within this district,the data of their revenue,expenditure and surplus were collected from 20 primary healthcare organizations prior to and after the zero price margin for drugs was in place for classification analysis.ResultsThe percentage of service revenue among the total revenue has dropped from 68.34％ before the system was in place to 65.44％ after,reducing 4.24％.The percentage of drug revenue has dropped from 71.68％ before to 63.57％ after,reducing 11.31％.The percentage of service surplus has dropped from 15.81％ before to - 23.07％ after,reducing 245.94％.The total standard workload has increased 61.77％.Average medical expense per outpatient and per inpatient has reduced 32.85％ and 57.18％,from 71.44yuan and 2642.08 yuan before to 48.33 yuan and 1131.28 yuan after respectively.ConclusionThe deficit rise and higher percentage of drug revenue at primary healthcare organizations deserve attention.A comprehensive reform is recommended to establish a regular government financial support mechanism,further adjust the revenue-expenditure structure,set up the system of rational drug use,and effectively reduce the medical expense of patients.

Object To establish a method for chemical pattern recognition on the quality assessment of Radix Astragali. Methods The contents of astragaloside in 18 samples of Astragalus Linn. in different species and origins were determinated by dual-wavelength TLCS method. The developing solvent was CHCl 3-MeOH-H 2O (65∶30∶10,), the UV detection was set at ? s=390 nm; ? R=590 nm. Astragaloside was regarded as the quality assurance of medicinal Radix Astragalus. Based on the TLCS method, the chemical data were obtained. Hierarchical clustering analyses were applied to the chemical pattern recognition. Results The content of astragaloside in Astragalus mongholicus (Bge.) Hsiao and A. membranaceus (Fisch.) Bge. was relatively higher than that in the other samples. This is consistent with the Pharmacopoeia of the People's Republic of China in which the two sorts of Astragalus Linn. were regarded as goods. Conclusion This method is a practicable in the quality assessment of Radix Astragali.

OBJECTIVETo explore the mechanism of podophyllotoxin nanostructured lipid carriers (POD-NLC)-induced apoptosis of VK2/E6E7 cells mediated by endoplasmic reticulum stress (ERS).

METHODSVK2/E6E7 cells cultured in vitro were exposed to 0.125, 0.25, and 0.5 µg/ml POD-NLC or blank NLC for 24 h. The intracellular calcium concentration was measured by laser scanning confocal microscopy (LSCM), and the expression levels of GRP78, GRP94, and calpain2 mRNA and proteins in the cells were detected using RT-PCR and Western blotting.

RESULTSCompared with the control cells, the cells exposed to POD-NLC showed a concentration-dependent increase of intracellular calcium concentration (P<0.01), and the differences were statistically significant between different dose groups (P<0.05). RT-PCR and Western blotting showed that POD-NLC up-regulated GRP78, GRP94 and calpain2 mRNA and proteins expressions, which showed significant differences between blank-NLC and the control groups (P>0.05).

CONCLUSIONPOD-NLC induces apoptosis of VK2/E6E7 cells possibly by triggering the endoplasmic reticulum stress response.

Apoptosis ; Calcium ; metabolism ; Calpain ; metabolism ; Cell Line ; Endoplasmic Reticulum Stress ; HSP70 Heat-Shock Proteins ; metabolism ; Heat-Shock Proteins ; metabolism ; Humans ; Membrane Proteins ; metabolism ; Nanostructures ; chemistry ; Podophyllotoxin ; chemistry ; RNA, Messenger

The peak period of cardiovascular disease (CVD) is around the time of awakening in the morning, which may be related to the surge of sympathetic activity at the end of nocturnal sleep. This paper chose 140 participants as study object, 70 of which had occurred CVD events while the rest hadn't during a two-year follow-up period. A two-layer model was proposed to investigate whether hypnopompic heart rate variability (HRV) was informative to distinguish these two types of participants. In the proposed model, the extreme gradient boosting algorithm (XGBoost) was used to construct a classifier in the first layer. By evaluating the feature importance of the classifier, those features with larger importance were fed into the second layer to construct the final classifier. Three machine learning algorithms, i.e., XGBoost, random forest and support vector machine were employed and compared in the second layer to find out which one can achieve the highest performance. The results showed that, with the analysis of hypnopompic HRV, the XGBoost+XGBoost model achieved the best performance with an accuracy of 84.3%. Compared with conventional time-domain and frequency-domain features, those features derived from nonlinear dynamic analysis were more important to the model. Especially, modified permutation entropy at scale 1 and sample entropy at scale 3 were relatively important. This study might have significance for the prevention and diagnosis of CVD, as well as for the design of CVD-risk assessment system.
Algorithms ; Cardiovascular Diseases ; Heart Rate ; Humans ; Machine Learning ; Sleep