Diabetic retinopathy(DR)has emerged as the leading cause of vision loss among working-age people in many countries under the increasing prevalence of diabetes and the longevity of the population. The pathogenesis of DR is complicated and has not been fully elucidated at present, while the treatment methods of DR have not been greatly improved, mainly retinal laser photocoagulation, anti-vascular endothelial growth factor(VEGF)treatment and vitrectomy surgery. The current treatment methods not only have shortcomings, but also bring serious economic burden to patients. Therefore, new methods are needed to explore the pathogenesis of DR, discover new treatments or improve current treatments, and improve the satisfaction of DR patients. In recent years, the identification and quantification of proteins expressed in blood, retina, vitreous humor, aqueous humor, and tears of all observable DR patients and DR rats and differentially expressed proteins after drug intervention have provided new ideas for further exploring the pathogenesis, diagnosis and treatment of DR with the rise of proteomics, which put forward new insights into early detection and treatment.The proteomics of DR in recent years are reviewed, in order to provide new ideas for the diagnosis and treatment of DR.

Diabetic retinopathy(DR)has emerged as the leading cause of vision loss among working-age people in many countries under the increasing prevalence of diabetes and the longevity of the population. The pathogenesis of DR is complicated and has not been fully elucidated at present, while the treatment methods of DR have not been greatly improved, mainly retinal laser photocoagulation, anti-vascular endothelial growth factor(VEGF)treatment and vitrectomy surgery. The current treatment methods not only have shortcomings, but also bring serious economic burden to patients. Therefore, new methods are needed to explore the pathogenesis of DR, discover new treatments or improve current treatments, and improve the satisfaction of DR patients. In recent years, the identification and quantification of proteins expressed in blood, retina, vitreous humor, aqueous humor, and tears of all observable DR patients and DR rats and differentially expressed proteins after drug intervention have provided new ideas for further exploring the pathogenesis, diagnosis and treatment of DR with the rise of proteomics, which put forward new insights into early detection and treatment.The proteomics of DR in recent years are reviewed, in order to provide new ideas for the diagnosis and treatment of DR.

In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

ObjectiveTo systematically evaluate the distribution of traditional Chinese medicine（TCM） syndromes of primary osteoporosis（POP） in China by using evidence-based medicine methods， and to understand the distribution law of the syndromes. MethodChina National Knowledge Infrastructure（CNKI）， VIP Chinese Science and Technology Journal Database（VIP）， WanFang Data Knowledge Service Platform（WanFang） and China Biology Medicine（CBM） were searched to obtain representative literature， and each database was searched from the 1994 World Health Organization defined diagnostic criteria for osteoporosis until May 1， 2023. Two researchers independently screened literature according to the criteria， extracted data， and cross-checked them. Meta analysis was conducted using R4.1.3， and subgroup analysis was performed. ResultA total of 56 Chinese papers were included， involving 14 415 patients. After standardized classification of syndromes， 11 articles were excluded， and Meta analysis results of the ultimately included 45 Chinese articles showed that the distribution frequencies of liver-kidney Yin deficiency syndrome， spleen-kidney Yang deficiency syndrome and kidney deficiency and blood stasis syndrome in 12 723 patients were 27%［95% confidence interval（CI） 0.24-0.31］， 32%（95% CI 0.29-0.36）， 36%（95% CI 0.30-0.42）. Subgroup analysis showed that there was a statistically significant difference in the distribution of the three TCM syndromes in the north and south（P<0.05）. In addition， the incidence of TCM syndrome fractures in different types of POP was 15%（95% CI 0.09-0.24） for liver-kidney Yin deficiency syndrome， 20%（95% CI 0.12-0.30） for spleen-kidney Yang deficiency syndrome， and 31%（95% CI 0.25-0.39） for kidney deficiency and blood stasis syndrome. ConclusionThe distribution of syndromes in POP patients is mainly kidney deficiency， accompanied by liver and spleen dysfunction. Liver-kidney Yin deficiency syndrome， spleen-kidney Yang deficiency syndrome and kidney deficiency and blood stasis syndrome are all the main syndromes of POP and osteoporotic fractures， and kidney deficiency and blood stasis syndrome is most closely related to the development of osteoporotic fractures. The reference standards for syndrome determination among the included studies are inconsistent， and in the future， it is necessary to focus on their determination standards to obtain consensus research results， at the same time， conduct large-scale syndrome research to obtain representative research results， providing a basis for clinical practice and research.

Objective:To understand the current status and its associated factors of dual use of e-cigarettes and cigarettes among adolescents in Shandong Province and explore the reasons for dual use behavior.Methods:A self-administered survey was conducted among 7 999 middle school students who were selected by stratified multi-stage cluster sample method. Data were weighted and analyzed by the SPSS 25.0 complex program.Results:In Shandong Province, the prevalence rates of attempting and current dual use of e-cigarettes and cigarettes among adolescents appeared as 7.7% and 1.3%, respectively. Male, friends smoking, and secondhand smoke exposure in the past 7 days were risk factors for dual use. Compared with cigarette smokers, dual users have no differences in cognition and behavior in quitting smoking ( P>0.05). The main reason for dual users to smoke e-cigarettes was curiosity. Conclusions:Dual use of e-cigarettes and cigarettes is common among adolescents in Shandong Province, and its influencing factors are similar to traditional cigarettes. Dual use is not a transitional stage for smoking cessation. Dual users are more likely to continue smoking in the future, which should be paid attention and concern.

Spondyloarthritis (SpA) is a group of chronic inflammatory diseases which predominantly involve spine and/or peripheral joints. SpA can be disabling and seriously affect the quality of life and function of patients. With the increasing clinical use of targeted drug therapy, precise and standardized use becomes the focus. China's first Consensus on Targeted Drug Therapy for Spondyloarthritis was developed by National Clinical Research Center for Dermatologic and Immunologic Diseases using international norms for consensus development. The consensus addresses 13 important clinical questions, ranging from principles, patient eligibility, pre-treatment screening, treatment initiation, drug selection and switch, co-medication, to adverse event monitoring of targeted drug therapy in SpA, and recommends treatment for specific patients, playing a key role in guiding clinical practices.