Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Systemic lupus erythematosus （SLE） may lead to secondary gynecological and obstetric disorders such as decreased ovarian reserve function， menstrual abnormalities， and adverse pregnancy outcomes. Based on "bi （痹） of both body and viscera" theory， this paper proposed that the core mechanism of SLE secondary gynecological and obstetric diseases lies in the mutual transformation between "body bi" and "viscera bi"， which together affect the uterus. Physiologically， uterus forms an internal-external network with the body and viscera through the meridians and blood vessels. Pathologically， when the healthy qi is deficient， nourishment of the body and viscera is impaired； when toxins and stasis accumulate， pathogenic factors disturb the uterus through the chong （冲） and ren （任） meri-dians. The resulting obstruction in the uterus can， in turn， manifest externally and aggravate damage to the body and viscera. Therefore， the pathogenesis of SLE secondary gynecological and obstetric diseases follows a dynamic trajectory of "body bi first， body bi affecting viscera， and then bi of both body and viscera". In treatment， the principle of harmonizing and balancing the healthy qi is emphasized. The main approach is to regulate the viscera， stabilize the body， and nourish the uterus， with the coordination of nourishing the viscera through the body， thereby achieving simultaneous treatment of both body and viscera. This highlights the guiding significance of the "bi of both body and viscera" theory in preventing and treating SLE secondary gynecological and obstetric diseases.

Poly(lactic-co-glycolide)(PLGA)is a key excipient in long-acting sustained-release preparations,and its degradation properties directly affect the drug release behavior.In this study,PLGA microspheres were prepared by microfluidic techniques,and the morphology changes of the microspheres were observed by scanning electron microscopy(SEM).In alkaline environment,due to the accelerated hydrolysis of ester bonds,the surface of the microspheres was rapidly dissolved and eroded,and the degradation rate was significantly higher than that in acidic environment.High temperature accelerated the degradation of PLGA microspheres.Under neutral and alkaline conditions,the microspheres showed aggregation and adhesion.Under acidic conditions,the microspheres gradually decomposed into irregular fragments.The high ionic strength further promoted the surface corrosion of the microspheres,especially under extreme pH conditions.Simultaneously,PLGA microspheres encapsulating coumarin were prepared to simulate the microsphere formulation.The release rate of coumarin after degradation of the microspheres under different conditions was observed by measuring the absorbance with ultraviolet-visible spectrophotometry.The results were consistent with those of the blank microspheres.This study revealed that the degradation of PLGA microspheres was significantly pH-dependent,temperature sensitive and ion strength responsive.These findings not only helped to understand and optimize the long-term stability and controlled release performance of drug-carrying microspheres,but also provided a theoretical basis for further improvement of PLGA-based drug carrier design.

Objective To investigate the implementation of surveillance,prevention and control measures for healthcare-associated infection(HAI)in maternal and child healthcare(MCH)institutions,and provide policy evi-dence for optimizing HAI prevention and control in MCH institutions.Methods Stratified sampling was conducted among the MCH institutions at provincial,municipal and county levels in 8 provinces/autonomous regions.A uni-fied questionnaire was designed and the online survey was conducted through"Questionnaire Star".Results The data from 123 MCH institutions were included in the analysis.90.24％of the MCH institutions carried out compre-hensive surveillance on HAI.The ratios of MCH institutions which implemented targeted surveillance on HAI in neonatal intensive care unit(NICU),surgical site infection,multidrug-resistant organisms(MDROs)and HAI in intensive care units(non-NICU excluded)were 89.66％,85.96％,80.77％,and 74.19％,respectively.51.22％MCH institutions adopted information surveillance system on HAI cases.94.31％MCH institutions carried out surveillance on hand hygiene compliance.Over 90％MCH institutions carried out surveillance on environment hy-giene in high-risk departments.71.54％MCH institutions conducted centralized cleaning,disinfection,sterilization and supply for reusable medical instruments in the central sterile supply department(CSSD).Over 90％MCH insti-tutions established three-level pre-examination triage systems.86.18％set up transitional wards.MCH institutions generally adopted a management model with established effective communication,full appointment visits,and sepa-rate visits for special medical groups,such as registered pregnant women,high-risk newborns,healthcare groups,and long-term rehabilitation patients.However,the ratio of institutions conducting on-line follow-up visits was less than 50％.Conclusion MCH institutions have generally carried out comprehensive and targeted surveillance on HAI.Information surveillance need to be facilitated.Hand hygiene and environmental hygiene surveillance has been popularized to a certain extent at all levels of MCH institutions.The cleaning,disinfection,sterilization,and supply processes of reusable medical devices in a few MCH institutions are not standardized.Special medical populations get effective management.On-line healthcare is to be further promoted.

ObjectiveTo investigate the effects and mechanism of Zuogui Jiangtang Tongmai prescription （ZJTP） on human umbilical vein endothelial cells （HUVECs） damaged by high glucose combined with lipopolysaccharide （LPS）. MethodThe survival rate of cells was determined by cell counting kit-8 （CCK-8）， and the level of tumor necrosis factor-α （TNF-α） was determined by enzyme-linked immunosorbent assay （ELISA） to determine the optimal injury concentration and action time of LPS， as well as the optimal action concentration of ZJTP drug-containing serum. HUVECs were divided into a blank control group， a model group， a ZJTP drug-containing serum group， and an SCFA mixed liquid group. ELISA was used to detect the level of endothelin-1 （ET-1）， nitric oxide （NO）， interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and TNF-α. Western blot was performed to detect the protein expression of G protein-coupled receptor43 （GPR43）， β-suppressor protein-2 （β-arrestin-2）， nuclear factor-κB suppressor α （IκBα）， and nuclear factor κB p65 （NF-κB p65）. The nucleation of NF-κB p65 was observed by immunofluorescence staining （IF）. The role of GPR43 in the regulation of inflammatory injury was observed by means of small interfering ribonucleic acid （siRNA）. The cells after intervention were divided into an empty carrier group， a ZJTP drug-containing serum group， a Si-GPR43 group， and a Si-GPR43 + ZJTP drug-containing serum group. The content of IL-1β， IL-6， and TNF-α was detected by ELISA. The protein expression of pathways was detected by Western blot. IF was used to observe the nucleation of NF-κB p65. ResultThe optimal molding condition was 1 mg·L^-1 LPS for 24 h. The optimal drug intervention condition was 5% ZJTP drug-containing serum for 24 h. Compared with the blank control group， the content of ET-1 in the model group was significantly increased， and the content of NO was significantly decreased （P<0.01）. The levels of inflammatory factors were significantly increased （P<0.01）. The expressions of GPR43 and IκBα were significantly decreased， while the protein expressions of β-arrestin-2 and NF-κB p65 were significantly increased （P<0.01）. NF-κB p65 protein was transferred from the extranuclear to the intranuclear （P<0.01）. Compared with the model group， the content of ET-1 in the ZJTP drug-containing serum group was decreased， and the content of NO was increased （P<0.05）. The levels of inflammatory factors decreased （P<0.05）. The protein expressions of GPR43 and IκBα were increased， while the expressions of β-arrestin-2 and NF-κB p65 were decreased （P<0.05）. The amount of NF-κB p65 transferred from the intranuclear to the extranuclear decreased （P<0.01）. The mechanism study showed that compared with the Si-GPR43 group， the content of IL-1β， IL-6， and TNF-α were significantly decreased after treatment with ZJTP drug-containing serum （P<0.01）. The protein expressions of GPR43 and IκBα were significantly increased （P<0.01）， while the protein expressions of β-arrestin-2 and NF-κB p65 were significantly decreased （P<0.01）. The amount of NF-κB p65 transferred from the extranuclear to the intranuclear decreased （P<0.01）. ConclusionZJTP has a protective effect on HUVECs with high glucose and LPS-induced inflammatory injury， which may be related to the regulation of GPR43/β-arrestin-2/IκBα/NF-κB pathway.