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.

Objective:To determine the incidence of adrenal incidentalomas(AIs) in patients with diabetes mellitus and the metabolism profiles.Methods:A total of 615 hospitalized patients with diabetes mellitus in the Department of Endocrinology and Metabolism of Peking University People′s Hospital from March 2020 to May 2021 were retrospectively included in this study. AIs were screened by unenhanced chest computed tomography(CT) retrospectively and subsequently confirmed by multiplanar reconstruction. Participants′ physical indicators, metabolic profiles, and adrenal function parameters were collected. Unpaired t test, Mann-Whitney U test, and Chi-Square test were adopted to compare the metabolism profiles between diabetes mellitus patients with or without AIs. Regression models were used to estimate the correlations between AIs and the metabolism profiles such as blood glucose, blood lipids, blood pressure, and the adrenal function parameters.Results:Twenty-seven out of 615 participants were detected with AIs(4.4%). Patients with AIs had higher body mass index, waist circumference, and hip circumference than patients without AIs [(29.4±5.1)kg/m 2vs(26.8±3.8)kg/m 2,P=0.018; (102.3±11.7)cm vs(95.8±10.3)cm, P=0.002; (107.3±10.1)cm vs(101.4±7.6)cm, P=0.008]. The levels of serum uric acid and urinary albumin/creatinine ratio were also significantly increased in patients with AIs [(409.6±118.1)μmol/L vs(357.4±100.6)μmol/L, P=0.009; 21.25(7.49, 180.24)mg/g vs 8.60(4.71, 34.56)mg/g, P=0.010]. Besides, individuals with AIs were also associated with a higher risk of co-existing hypertension( P=0.045). Conclusion:The incidence of AIs in patients with diabetes is 4.4%. The presence of AIs in patients with diabetes may associated with increased risk of obesity and hypertension.

Objective:To explore the role of NK cells in allogeneic hematopoietic stem cell micro-transplantation(MST)in the treatment of patients with acute myeloid leukemia(AML).Methods:Data from 93 AML patients treated with MST at our center from 2013-2018 were retrospectively analyzed.The induction regimen was anthracycline and cytarabine combined with peripheral blood stem cells transplantation mobilization by granulocyte colony stimulating factor(GPBSC),followed by 2-4 courses of intensive treatment with medium to high doses of cytarabine combined with GPBSC after achieving complete remission(CR).The therapeutic effects of one and two courses of MST induction therapy on 42 patients who did not reach CR before transplantation were evaluated.Cox proportional hazards regression analysis was used to analyze the impact of donor NK cell dose and KIR genotype,including KIR ligand mismatch,2DS1,haplotype,and HLA-Cw ligands on survival prognosis of patients.Results:Forty-two patients received MST induction therapy,and the CR rate was 57.1％after 1 course and 73.7％after 2 courses.Multivariate analysis showed that,medium and high doses of NK cells was significantly associated with improved disease-free survival(DFS)of patients(HR=0.27,P=0.005;HR=0.21,P=0.001),and high doses of NK cells was significantly associated with improved overall survival(OS)of patients(HR=0.15,P=0.000).Donor 2DS1 positive significantly increases OS of patients(HR=0.25,P=0.011).For high-risk patients under 60 years old,patients of the donor-recipient KIR ligand mismatch group had longer DFS compared to the nonmismatch group(P=0.036);donor 2DS1 positive significantly prolonged OS of patients(P=0.009).Conclusion:NK cell dose,KIR ligand mismatch and 2DS1 influence the therapeutic effect of MST,improve the survival of AML patients.

Objective To determine the correlation and agreement of sacral ratio(SR)measured by lateral and anteroposterior radiographs in patients with anorectal malformation(ARM).Methods A retrospective analysis was conducted on the anteroposterior and lateral radiographs images of the sacral vertebrae of patients with ARM.All SR values were measured by three radiologists.Pearson's correlation coefficient were used to assess the correlation between the SR measured by lateral and anteroposterior radiographs.A weighted Kappa statistic was used to measure the agreement between how the anteroposterior and lateral SR categorized observations into risk groups.Results Of the 385 ARM patients,25 patients whose radiographs image quality was insufficient to calculate SR value were excluded.For a given pair of measurements,the mean lateral SR value was 0.08 units greater than the anteroposterior SR value[95%confidence interval(CI)0.06-0.09,P<0.01].Anteroposterior and lateral images had a moderate positive correlation(r=0.79,95%CI 0.73-0.79,P<0.01)and moderate agreement in risk categorization(Kappa=0.62,P<0.01).Anteroposterior and lateral readings conducted by all three radiologists had excellent inter-rater reliability with intraclass correlation coefficient(ICC)for anteroposterior and lateral SR of 0.88 and 0.84,respectively.Conclusion Even though the anteroposterior and lateral SR values have moderate positive correlation,the mean SR value determined by images in the lateral is 0.08 units greater than the anteroposterior.Anteroposterior and lateral SR value conclude different risk categories relatively often.The SR values measured by lateral sacral radiographs are more clinically significant than those measured by anteroposterior radiographs.