Background and purpose:Gastric cancer,as one of the most common malignant tumors,requires early diagnosis and treatment to improve patient prognosis.This study,based on serum quantitative proteomics research of early-stage gastric cancer patients and non-gastric cancer patients,aims to identify potential diagnostic biomarkers for early gastric cancer.Methods:Serum samples from primary gastric cancer patients and healthy control individuals were collected from Lanzhou University Second Hospital between June and December 2023,following inclusion and exclusion criteria.A protein spectral library was established using Data-Dependent Acquisition(DDA)mode,and each sample was analyzed using Data-Independent Acquisition(DIA)mode.The STRING database was used to analyze protein-protein interactions of upregulated proteins in gastric cancer serum.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)were used to analyze the pathways and functional annotations of the corresponding genes.Gene expression levels in gastric cancer and non-gastric cancer tissues were analyzed using GEPIA 2,and overall survival of each gene in gastric cancer was analyzed using Kaplan-Meier Plotter.Differential gene expression in clinical gastric cancer and adjacent tissues was validated by quantitative reverse transcription polymerase chain reaction(qRT-PCR)This study was approved by the Ethics Committee of Lanzhou University Second Hospital(Ethical No.:2023A-459)and was exempt from the informed consent.Results:Finally,serum samples from 30 primary gastric cancer patients,29 healthy control individuals,along with the para-cancerous tissues from 8 patients were collected.A total of 666 intersecting proteins were identified through serum quantitative proteomics.Among them,16 proteins showed upregulated expression and 22 proteins showed downregulated expression in the gastric cancer group(P＜0.05,|FC|≥1.5).STRING database analysis showed that 10 upregulated proteins were involved in interaction networks.KEGG and GO analysis indicated that these genes were closely related to the biological processes of cancer occurrence and development.GEPIA 2 and Kaplan-Meier Plotter analysis showed that 6 genes,B2M,TAGLN2,CTSD,HSP90AB1,SH3BGRL3,and CFL1,which were highly expressed in the gastric cancer group(P＜0.05)and associated with poor prognosis.Clinical verification by qRT-PCR confirmed that TAGLN2,CTSD,SH3BGRL3,CFL1 and HSP90AB1 were highly expressed in gastric cancer tissues(P＜0.05).Conclusion:TAGLN2,CTSD,SH3BGRL3,CFL1,and HSP90AB1 have the potential to serve as clinical early gastric cancer diagnostic serum biomarkers,which may facilitate early diagnosis and treatment of gastric cancer.

Background and purpose:Gastric cancer,as one of the most common malignant tumors,requires early diagnosis and treatment to improve patient prognosis.This study,based on serum quantitative proteomics research of early-stage gastric cancer patients and non-gastric cancer patients,aims to identify potential diagnostic biomarkers for early gastric cancer.Methods:Serum samples from primary gastric cancer patients and healthy control individuals were collected from Lanzhou University Second Hospital between June and December 2023,following inclusion and exclusion criteria.A protein spectral library was established using Data-Dependent Acquisition(DDA)mode,and each sample was analyzed using Data-Independent Acquisition(DIA)mode.The STRING database was used to analyze protein-protein interactions of upregulated proteins in gastric cancer serum.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)were used to analyze the pathways and functional annotations of the corresponding genes.Gene expression levels in gastric cancer and non-gastric cancer tissues were analyzed using GEPIA 2,and overall survival of each gene in gastric cancer was analyzed using Kaplan-Meier Plotter.Differential gene expression in clinical gastric cancer and adjacent tissues was validated by quantitative reverse transcription polymerase chain reaction(qRT-PCR)This study was approved by the Ethics Committee of Lanzhou University Second Hospital(Ethical No.:2023A-459)and was exempt from the informed consent.Results:Finally,serum samples from 30 primary gastric cancer patients,29 healthy control individuals,along with the para-cancerous tissues from 8 patients were collected.A total of 666 intersecting proteins were identified through serum quantitative proteomics.Among them,16 proteins showed upregulated expression and 22 proteins showed downregulated expression in the gastric cancer group(P＜0.05,|FC|≥1.5).STRING database analysis showed that 10 upregulated proteins were involved in interaction networks.KEGG and GO analysis indicated that these genes were closely related to the biological processes of cancer occurrence and development.GEPIA 2 and Kaplan-Meier Plotter analysis showed that 6 genes,B2M,TAGLN2,CTSD,HSP90AB1,SH3BGRL3,and CFL1,which were highly expressed in the gastric cancer group(P＜0.05)and associated with poor prognosis.Clinical verification by qRT-PCR confirmed that TAGLN2,CTSD,SH3BGRL3,CFL1 and HSP90AB1 were highly expressed in gastric cancer tissues(P＜0.05).Conclusion:TAGLN2,CTSD,SH3BGRL3,CFL1,and HSP90AB1 have the potential to serve as clinical early gastric cancer diagnostic serum biomarkers,which may facilitate early diagnosis and treatment of gastric cancer.

Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.

Objective:A nationwide multi-center and large sample survey was conducted to compare the validity of the Mini International Neuropsychiatric Interview (Hypo-) Manic Episode with Mixed Features-DSM-5 Module (MINI-M) questionnaire and the Clinically Useful Depression Outcome Scale Supplemented with Questions for the DSM-5 Mixed Features Specifier (CUDOS-M) depression subscale in identifying mixed features in patients experiencing (hypo-) manic episodes.Methods:Using a convenience sampling method, 366 patients with bipolar disorder experiencing acute (hypo-) manic episodes who met the inclusion and exclusion criteria were recruited. The diagnosis of "with mixed features" was based on the DSM-5 criteria for mixed features. The predictive validity of the MINI-M questionnaire and the CUDOS-M depression subscale to screen mixed features was analyzed using the receiver operating characteristic (ROC) curve. Additionally, the difference in area under the ROC curve (AUC) between the two instruments was compared.Results:The AUC for the MINI-M questionnaire and the CUDOS-M depression subscale in screening mixed features were 0.79 (95 %CI=0.75-0.84) and 0.81 (95 %CI=0.77-0.86), respectively. There was no statistically significant difference in AUC between the two measurements ( Z=-1.19, P>0.05). Among patients with acute (hypo-) manic episodes, 45.9% (168/366) presented with mixed features according to the DSM-5 criteria, while the corresponding figures were 43.7% (160/366) using the MINI-M questionnaire (total score≥3) and 42.1% (154/366) using the CUDOS-M depression subscale (total score≥20). Screening results were comparable among the three measures. Conclusion:Mixed features are common among patients experiencing acute (hypo-) manic episodes. The MINI-M questionnaire and the CUDOS-M depression subscale demonstrate equivalent validity in identifying mixed features.

Objective:To analyze the input and output status of health resources in primary medical and health institutions and their allocation efficiency in different regions of China, and to provide an empirical basis for optimizing the allocation of primary medical and health resources in China among regions.Methods:The input index data (number of beds and number of health personnel) and output index data (number of primary medical and health institutions visits, number of family health services, number of hospital admissions) of primary medical and health institutions in China in 2020 were extracted from the China Health Statistical Yearbook 2021. Based on the BCC ( Banker, Charnes, Cooper) model of data envelopment analysis ( DEA), the Bootstrap- DEA method was used to correct bias, the allocation efficiency of primary medical and health resources in 31 provinces was calculated and the regional differences were analyzed. Results:After bias correction, the technical efficiency (TE) of resource allocation in primary medical and health institutions decreased by 0.102. The average TE score of all 31 primary medical and health institutions was 0.669, indicating a serious problem of ineffective use of technology. The TE of the eastern, central and western regions was 0.694, 0.663, and 0.649 respectively. There was obvious polarization in the central regions.Further analysis of the efficiency improvement of non DEA efficient provinces showed that 2 DEA weakly efficient provinces and 16 DEA ineffective provinces had several reference provinces for efficiency configuration improvement; The provinces that have been referenced more than 10 times were Zhejiang, Chongqing, Sichuan, and Ningxia, while the provinces that were listed as the first reference by other provinces were Ningxia, Chongqing, Zhejiang, and Tibet.Conclusions:The resource allocation efficiency of primary medical and health institutions in China is relatively low, and regional differences are obvious. The balance between different inputs and outputs should be considered when allocating the resources. Non DEA effective provinces can use DEA analysis to find the most suitable reference object and make reference improvements in the short term.

Objective:This study investigates the difference in the detection rate and symptomatology between ICD-10 and DSM-5 diagnostic criteria for bipolar disorder with mixed states.Methods:Based on the Phase Ⅰ (2012) and Phase Ⅱ (2021) databases of National Bipolar Mania Pathway Survey (BIPAS), patients with bipolar disorder were included. General demographic data, clinical characteristics, symptomatic phenotypes, and mixed characteristics were retrieved. The detection rates and symptomatic performances of patients with or without mixed states in Phase Ⅰ and Ⅱ were compared using the chi-square test.Results:For patients with mixed states, the detection rate during Phase Ⅱ (2021) using DSM-5 (18.79%, 199/1 059) criteria was significantly higher than that during Phase Ⅰ (2012) using ICD-10 (6.78%, 199/2 934; χ 2=125.05, P<0.001). Whether using ICD-10 or DSM-5 criteria, patients with mixed states had a significantly higher frequency of multiple symptomatic manifestations. Conclusion:The DSM-5 diagnostic criteria generate a high detection rate for bipolar disorder with mixed states. The clinical phenotypes of bipolar disorder with mixed states vary significantly using different diagnostic tools.

Objective:This study investigates the difference in the detection rate and symptomatology between ICD-10 and DSM-5 diagnostic criteria for bipolar disorder with mixed states.Methods:Based on the Phase Ⅰ (2012) and Phase Ⅱ (2021) databases of National Bipolar Mania Pathway Survey (BIPAS), patients with bipolar disorder were included. General demographic data, clinical characteristics, symptomatic phenotypes, and mixed characteristics were retrieved. The detection rates and symptomatic performances of patients with or without mixed states in Phase Ⅰ and Ⅱ were compared using the chi-square test.Results:For patients with mixed states, the detection rate during Phase Ⅱ (2021) using DSM-5 (18.79%, 199/1 059) criteria was significantly higher than that during Phase Ⅰ (2012) using ICD-10 (6.78%, 199/2 934; χ 2=125.05, P<0.001). Whether using ICD-10 or DSM-5 criteria, patients with mixed states had a significantly higher frequency of multiple symptomatic manifestations. Conclusion:The DSM-5 diagnostic criteria generate a high detection rate for bipolar disorder with mixed states. The clinical phenotypes of bipolar disorder with mixed states vary significantly using different diagnostic tools.