Objective To explore the effect and mechanism of Slc1a2 overexpression on cognitive dysfunction in sleep-deprived mice.Methods A total of 130 mice were divided into five groups:normal sleep(NS),NS+ov-Slc1a2,sleep deprivation(SD),SD+ov-NC,and SD+ov-Slc1a2,with 26 mice in each group.The SD mice model was established using an automatic system based on a rotating rod,and overexpress Slc1a2 adenovirus was injected into the prefrontal cortex(PFC).Immunofluorescence and Western blotting were used to detect the expression of Slc1a2 in the mouse PFC.Electrophysiological tests were used to evaluate non-rapid eye movement(NREM)sleep time,rapid eye movement(REM)sleep time,and wakefulness time in mice.Real-time quantitative PCR was used to detect the expression of glutamate(Glu)and gamma-aminobutyric acid(GABA)metabolic enzymes in the mouse PFC.Whole-cell patch-clamp recording was used to detect the frequency and amplitude of miniature excitatory postsynaptic currents(mEPSC)in mouse PFC.Immunofluorescence was used to detect the proportion of GABA-positive cells in the mouse PFC.The C11-BODIPY fluorescent probe was used to detect lipid reac-tive oxygen species(ROS)levels in mouse PFC.Commercial kits were used to detect Fe2+and malondialdehyde(MDA)levels in the mouse PFC.Cognitive function in mice was evaluated using the open field,novel object recognition,and Y-maze tests.Results Compared with the NS group,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index increased significantly,while wakefulness time decreased significantly in the NS+ov-Slc1a2 group(all P＜0.05).The percentage of Slc1a2+GFAP+cells,expression of Slc1a2 protein,expression of Glul,Slc6a1,and Abat mRNA,frequency and amplitude of mEPSC,and proportion of GABA-positive cells in the PFC increased significantly,whereas lipid ROS,Fe2+,and MDA levels decreased significantly(all P＜0.05).Compared with the NS group,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index of the SD group and the SD+ov-NC group were significantly decreased,whereas wakefulness time was significantly increased(all P＜0.05).The percentage of Slc1a2+GFAP+cells,expression of Slc1a2 protein,expression of Glul,Slc6a1,and Abat mRNA,frequency and amplitude of mEPSC,and proportion of GABA-positive cells in the mouse PFC decreased significantly,whereas lipid ROS,Fe2+,and MDA levels increased significantly(all P＜0.05).Compared with the SD and SD+ov-NC groups,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index of the SD+ov-Slc1a2 group increased significantly,whereas the wakeful-ness time decreased significantly(all P＜0.05).The percentage of Slc1a2+GFAP+cells,the expression of Slc1a2 protein,the expression of Glul,Slc6a1,and Abat mRNA,the frequency and amplitude of mEPSC,and the proportion of GABA-positive cells in the mouse PFC increased significantly,whereas lipid ROS,Fe2+,and MDA levels decreased significantly(all P＜0.05).Conclusion Ectopic overexpres-sion of Slc1a2 in the PFC can improve sleep disorders in SD mice,reduce the damage caused by SD to excitatory synaptic transmission and GABAergic neuron function in the PFC,and alleviate cognitive impairment and anxiety-like behavior in these mice.Its mechanism may be related to the improvement of Glu/GABA metabolic imbalance in the PFC and inhibition of ferroptosis.

Objective To explore the effect and mechanism of Slc1a2 overexpression on cognitive dysfunction in sleep-deprived mice.Methods A total of 130 mice were divided into five groups:normal sleep(NS),NS+ov-Slc1a2,sleep deprivation(SD),SD+ov-NC,and SD+ov-Slc1a2,with 26 mice in each group.The SD mice model was established using an automatic system based on a rotating rod,and overexpress Slc1a2 adenovirus was injected into the prefrontal cortex(PFC).Immunofluorescence and Western blotting were used to detect the expression of Slc1a2 in the mouse PFC.Electrophysiological tests were used to evaluate non-rapid eye movement(NREM)sleep time,rapid eye movement(REM)sleep time,and wakefulness time in mice.Real-time quantitative PCR was used to detect the expression of glutamate(Glu)and gamma-aminobutyric acid(GABA)metabolic enzymes in the mouse PFC.Whole-cell patch-clamp recording was used to detect the frequency and amplitude of miniature excitatory postsynaptic currents(mEPSC)in mouse PFC.Immunofluorescence was used to detect the proportion of GABA-positive cells in the mouse PFC.The C11-BODIPY fluorescent probe was used to detect lipid reac-tive oxygen species(ROS)levels in mouse PFC.Commercial kits were used to detect Fe2+and malondialdehyde(MDA)levels in the mouse PFC.Cognitive function in mice was evaluated using the open field,novel object recognition,and Y-maze tests.Results Compared with the NS group,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index increased significantly,while wakefulness time decreased significantly in the NS+ov-Slc1a2 group(all P＜0.05).The percentage of Slc1a2+GFAP+cells,expression of Slc1a2 protein,expression of Glul,Slc6a1,and Abat mRNA,frequency and amplitude of mEPSC,and proportion of GABA-positive cells in the PFC increased significantly,whereas lipid ROS,Fe2+,and MDA levels decreased significantly(all P＜0.05).Compared with the NS group,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index of the SD group and the SD+ov-NC group were significantly decreased,whereas wakefulness time was significantly increased(all P＜0.05).The percentage of Slc1a2+GFAP+cells,expression of Slc1a2 protein,expression of Glul,Slc6a1,and Abat mRNA,frequency and amplitude of mEPSC,and proportion of GABA-positive cells in the mouse PFC decreased significantly,whereas lipid ROS,Fe2+,and MDA levels increased significantly(all P＜0.05).Compared with the SD and SD+ov-NC groups,the NREM sleep time,REM sleep time,central area stay time,recognition index,and novel wall selection index of the SD+ov-Slc1a2 group increased significantly,whereas the wakeful-ness time decreased significantly(all P＜0.05).The percentage of Slc1a2+GFAP+cells,the expression of Slc1a2 protein,the expression of Glul,Slc6a1,and Abat mRNA,the frequency and amplitude of mEPSC,and the proportion of GABA-positive cells in the mouse PFC increased significantly,whereas lipid ROS,Fe2+,and MDA levels decreased significantly(all P＜0.05).Conclusion Ectopic overexpres-sion of Slc1a2 in the PFC can improve sleep disorders in SD mice,reduce the damage caused by SD to excitatory synaptic transmission and GABAergic neuron function in the PFC,and alleviate cognitive impairment and anxiety-like behavior in these mice.Its mechanism may be related to the improvement of Glu/GABA metabolic imbalance in the PFC and inhibition of ferroptosis.

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.