Objective To verify the accuracy of a Non-Contact Sleep Monitoring Mattress(NCSMM)based on body movement during sleep in assessing sleep quality of patients before neurosurgery in order to provide a more portable and efficient assessment tool for clinical staff.Methods A single-arm trial was conducted on 114 inpatients admitted in our department selected with convenience sampling.Sleep quality data of 1 night were collected through 5 sleep quality assessment tools,including NCSMM,polysomnography(PSG),Patient-Reported Outcome Measurement Information System(PROMIS)Sleep Disturbance scale,Richards-Campbell Sleep Scale(RCSQ),and a wearable device(smart watch for body movements and sleep quality monitoring).The sleep efficiency(≤85%)obtained by PSG was used as the diagnostic standard for sleep disorders.The area under the receiver operating characteristic curve(AUC),sensitivity,specificity,positive predictive value,negative predictive value,and Youden index were calculated for the other 4 tools to evaluate and compare their diagnostic effectiveness.Results The AUC value for NCSMM,PROMIS,RCSQ and smart watch was 0.788(95%CI:0.687～0.888,P<0.001),0.664(95%CI:0.543～0.784,P=0.02),0.723(95%CI:0.600～0.846,P=0.001)and 0.750(95%CI:0.654～0.846,P<0.001),respectively.The diagnostic accuracy rate was 0.774,0.559,0.742 and 0.602,with corresponding Youden index value of 0.488,0.321,0.456,and 0.459.NCSMM demonstrated the best AUC value,sensitivity and Youden index when compared with the other 3 tools.Conclusion NCSMM shows high accuracy in assessing sleep quality in pre-neurosurgery inpatients,and it is a viable portable and efficient assessment tool in clinical practice.

Objective:To screen differentially expressed genes (DEGs) associated with liver cancer by bioinformatics analysis method, and to investigate the mechanism of the minichromosome maintenance protein 2 ( MCM2) and replication factor C subunit 4 ( RFC4) genes in liver cancer in vitro. Methods:Gene expression profiling data of 80 and 36 hepatocellular carcinoma tissues and 307 and 13 cirrhotic tissues were obtained from the GSE25097 and GSE98620 datasets of the gene expression analysis (GEO) database, respectively. Gene expression profiling data of 374 liver cancer tissues and 50 normal liver tissues were downloaded from the cancer genome atlas (TCGA) database. Limma and DESeqs R software were used to process the gene expression profiling data, construct protein-protein interaction networks, and analysis the relevance of these genes to survival. Weighted gene co-expression network analysis was performed to screen out the core genes. Liver cancer SMMC7721 cells were transfected with MCM2 blank plasmid (MCM2 control group), MCM2 overexpression plasmid [MCM2 WT1 group, MCM2 WT2 (2-fold WT1) group], RFC4 blank plasmid (RFC4 control group), and RFC4 overexpression plasmid [RFC4 WT1 group, RFC4 WT2 (2-fold WT1) group], respectively. The expression of MCM2 and RFC4 in liver cancer cell lines and their transfection levels were detected by real-time fluorescence quantitative reverse transcription PCR and Western blotting. The effects of MCM2 and RFC4 on the proliferation of hepatocellular carcinoma cells were detected by MTT assay and cell cloning assay, respectively. The effects of MCM2 and RFC4 on the migration of liver cancer cells were determined by the scratch assay. The effects of MCM2 and RFC4 on liver cancer cell invasion were detected by Transwell assay.Results:By bioinformatic analysis, 9 HCC DEGs were selected, including ubiquitin conjugating enzyme E2 T ( UBE2T), aurora kinase A ( AURKA), targeting protein for Xklp2 ( TPX2), MCM2, RFC4, ribonucleoside-diphosphate reductase subunit M2 ( RRM2), serine peptidase inhibitory factor Kazal type 1 ( SPINK1), collagen type XV alpha 1 chain ( COL15A1) and C-C motif chemokine 25 ( CCL25). Among the six genes associated with clinical stages, the MCM2 and RFC4 genes were found to be strongly associated with prognosis in liver cancer. The relative protein expression of MCM2 and RFC4 in HepG2 cells (1.83±0.07, 1.44±0.09) and SMMC7721 cells (1.74±0.05, 1.43±0.08) was higher than that in MIHA cells (1.00±0.02, 1.00±0.03), and all the differences were statistically significant (all P<0.05). The relative gene expression of MCM2 and RFC4 in HepG2 cells (14.30±0.12, 5.10±0.18) and SMMC7721 cells (10.60±0.11, 7.60±0.07) was higher than that in MIHA cells (1.00±0.05, 1.00±0.03), and all the differences were statistically significant (all P<0.05). Compared with the MCM2 control group, the absorbance values [(0.28±0.01 and 0.21±0.01) vs 0.18±0.03], the number of clonal cells [(717±12 and 782±29) cells vs (389±17) cells], the percentage migration [(0.43±0.02 and 0.68±0.01) vs 0.15±0.06], and the number of cellular invasions [(933±21 and 821±11) cells vs (409±16) cells] were higher in the MCM2 WT1 and MCM2 WT2 groups, and the differences were all statistically significant (all P<0.05). Compared with the RFC4 control group, the absorbance values [(0.30±0.02 and 0.21±0.01) vs 0.17±0.02], the number of cloned cells [(571±11 and 728±9) cells vs (373±23) cells], the percentage migration [(0.75±0.11 and 0.67±0.04) vs 0.34±0.07], and the number of cell invasion [(835±26 and 818±18) cells vs (629±12) cells] were higher in the RFC4 WT1 and the RFC4 WT2 groups, and the differences were statistically significant (all P<0.05). Conclusions:MCM2 and R FC4 genes play a role in promoting tumorigenesis and growth in hepatocellular carcinoma.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Objective:To assess the impact of health insurance packaged payment in medical communities on the economicburden of patients,income and satisfaction of medical staff in counties.Methods:Using sample data from 2018-2022 from the national monitoring counties of medical communities,taking 2020 as the year of implementation of packaged payment,a double difference model was constructed with county population density and county per capita GDP as the control variables to assess the impact of packaged payment on the economic burden of patients,medical staff income and satisfaction in the county.Results:The packaged payment policy reduced the economic burden of patients to a certain extent and had a statistically significant positive effect on medical staff income in 2021,but it did not significantly increase the satisfaction of both supply and demand.Conclusion:The implementation of health insurance packaged payment of the MEC will not increase the economic burden of patients.It has a good pro-poor effect,and the income of medical staff has been improved to some extent,but there is still room for optimisation and improvement of the policy.

Diseases of ocular fundus are the leading causes of severe vision impairment or even blindness in patients worldwide, and the medical treatments are seriously limited by the difficulty of therapeutic drugs entering the fundus due to the various physiological barriers. Nano-drug delivery systems, with their nanoscale size and large surface area, can be loaded with therapeutic drugs of different physicochemical properties and modified with various surface active substances, which can not only improve the solubility and penetration of the drugs, but also protect biologic drugs from degradation and improve the biological safety and bioavailability, as well as deliver therapeutic drugs to specific ocular targets. All of these make the therapeutic potential enormous. Currently, more and more studies have been carried out to take advantage of nanomaterials for the treatment of different fundus diseases, including neurodegenerative diseases, fundus neovascularization, endophthalmitis and fundus tumors. This review analyzes the challenges and barriers faced by different routes of drug administration in the treatment of fundus diseases, the physicochemical properties of common nano-drug delivery systems that have been studied in related fields, and further summarizes the progress, advantages, limitations, and future directions of the application of various nano-drug delivery systems for the treatment of ocular fundus diseases in recent years.