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.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.

Objective:To investigate the correlation between CHA 2DS 2-VASC score and the recurrence risk of paroxysmal atrial fibrillation after radiofrequency ablation. Methods:It was a retrospective cohort study. A total of 150 patients who underwent radiofrequency ablation for paroxysmal atrial fibrillation in Xingtai People′s Hospital from January 2017 to January 2021 were consecutively included in the study. According to the preoperative CHA 2DS 2-VASC score, patients were divided into high score group (≥3 points, n=90) and low score group (<3 points, n=60). Baseline clinical data was collected. All patients underwent circumferential pulmonary vein isolation, and those with atrial flutter before ablation also underwent tricuspid isthmus isolation. Holter and electrocardiogram examinations were performed at 3, 6 months and 1 year after ablation to evaluate whether there was recurrence of atrial fibrillation. Univariate and multivariate Cox regression was used to analyze the risk factors for recurrence of atrial fibrillation after radiofrequency ablation. Results:Among 150 patients 90 were males and 60 were females with a mean age of (64.0±3.6) years. There were no significant differences in age, sex, and proportion of hypertension, diabetes, chronic heart failure and stroke or transient ischemic attack (TIA), medication of antiarrhythmic and anticoagulant drugs between the two groups (all P>0.05). The longest duration of atrial fibrillation in the high score group was significantly longer than that in the low score group (26.0±6.1) hours vs. (10.0±2.1) hours, P<0.05). There were no patients with cardiac tamponade, atrial esophageal fistula and severe vascular puncture complications in the two groups. During the follow-up period, the recurrence rate in the high score group was significantly higher than that in the low score group (16.7% (15/90) vs. 8.3% (5/60), P<0.05). Multivariate Cox regression analysis showed that CHA 2DS 2-VASC score≥3 was an independent risk factor for atrial fibrillation recurrence in patients with paroxysmal atrial fibrillation after radiofrequency ablation ( HR=3.84, 95% CI: 1.87-7.89, P=0.02). Conclusion:CHA 2DS 2-VASC score≥3 is an independent risk factor for atrial fibrillation recurrence in patients with paroxysmal atrial fibrillation after radiofrequency ablation.

Objective To investigate the effects of zalcitabine(ddC),a mitochondrial DNA polymerase γ(POLG)inhibitor,on the migration,invasion,and to preliminarily explore mitochondrial biogenesis of human tri-ple-negative breast cancer MDA-MB-231 cells.Methods The effect of ddC on cell viability was detected using the MTT assay.The migration and invasion abilities of the cells were evaluated using the cell scratch and Transwell in-vasion assays.Cell apoptosis was determined using flow cytometry and a V-FITC/PI cell apoptosis detection kit.The protein expression of POLG,NADH dehydrogenase subunit Ⅰ(NADH1),NADH dehydrogenase subunit Ⅱ(NADH2),ATP synthase subunit 6(ATPase6),cytochrome c oxidase subunit Ⅰ(COX-1)and cytochrome c ox-idase subunit Ⅲ(COX-3)were determined using Western blot.The POLG mRNA level and mtDNA copy number were determined using qPCR.The mitochondrial content and ATP levels were determined using MitoTracker Green fluorescent probe staining and an ATP determination kit.MDA-MB-231 cells were transfected with pcDNA3.1-EG-FP-POLG plasmids to overexpress POLG.The inhibitory effects of ddC on cell migration and invasion were detected in POLG-overexpressed MDA-MB-231 cells.Results POLG expression was higher in MDA-MB-231 cells than in normal mammary epithelial cells(MCF-10A)(P＜0.01).ddC inhibited cell viability in a dose-dependent man-ner.ddC inhibited the migration(P＜0.01)and invasion(P＜0.01)of MDA-MB-231 cells;however,it dis-played no significant inhibitory effects on cell viability in normal mammary epithelial cells(MCF-10A)at the same concentration.ddC downregulated the protein(P＜0.01)and mRNA(P＜0.01)levels of POLG,reduced mtD-NA copy number(P＜0.01)and downregulated mtDNA-coded NADH1,NADH2,ATPase6,COX-1 and COX-3 protein expression(P＜0.01)in MDA-MB-231 cells.Furthermore ddC inhibited mitochondrial content(P＜0.01)and ATP(P＜0.01)levels in MDA-MB-231 cells.POLG overexpression increased the migration(P＜0.05)and invasion(P＜0.05)abilities of MDA-MB-231 cells,while ddC did not significantly inhibit the migra-tion and invasion abilities of MDA-MB-231 cells overexpressing POLG.Conclusion ddC downregulates POLG ex-pression in MDA-MB-231 cells and inhibits mitochondrial biogenesis and ATP levels,thereby inhibiting the migra-tion and invasion of MDA-MB-231 cells.

Objective:To investigate the risk factors of atrial fibrillation (AF) in patients with typical atrial flutter after radiofrequency ablation.Methods:This study was a case-control study. The clinical data of 120 patients with typical atrial flutter who underwent radiofrequency ablation in Xingtai People′s Hospital from January 2017 to January 2021 were retrospectively analyzed. Patients were followed up every 3-6 months for a period of 2 years, and AF occurred in 30 patients (25.0%). The risk factors of AF were analyzed with univariate and multivariate logistic regressions.Results:The mean age of patients was (62.0±6.5) years and 64(53.3%) were males. No patients in the two groups had complications such as cardiac tamponade, pulmonary embolism and cerebral infarction after radiofrequency ablation. Compared with non-AF patients, patients in AF group had older age and higher CHA 2DS 2-VASC score ( P<0.001). Multivariate regression analysis showed that age ( HR=1.09, 95% CI:1.01-1.17) and CHA 2DS 2-VASC score ( HR=3.84, 95% CI:1.87-7.89) were independent risk factors for the occurrence of atrial fibrillation after radiofrequency ablation in patients with atrial flutter. Conclusion:After radiofrequency ablation of typical atrial flutter, nearly 25% of patients will relapse into AF, old age and higher CHA 2DS 2-VASC score increase the risk of AF recurrent.

Objective To analyze the predictive value of dynamic changes in key factors of the toll-like receptor (TLR)/nuclear factor-κB (NF-κB) signaling axis during the perioperative period for bone infection inpatients with open fractures. Methods A total of 55 patients with open fractures who developed bone infections during the perioperative period were selected as infection group, and 110 patients with open fractures who did not develop infections during the same period were selected as non-infection group. Clinical data, pre-and post-operative serum levels of routine inflammatory markers [C-reactive protein (CRP), interleukin-6 (IL-6) and procalcitonin (PCT)] and key factors of the TLR/NF-κB signaling axis (TLR4, NF-κB) were compared between the two groups. Logistic multivariate regression analysis was used to identify risk factors for bone infection during the perioperative period in patients with open fractures. Receiver operating characteristic (ROC) curves were plotted to evaluate the predictive value of the absolute change (the absolute value of the changes was expressed as △) in the levels of key factors of the TLR/NF-κB signaling axis before and after surgery for bone infection, and these results were compared with the predictive value of routine inflammatory markers. A nomogram prediction model was developed based on the identified risk factors, and its value in predicting perioperative bone infection was analyzed. Results The time from fracture to surgery and the duration of surgery were significantly longer, and the proportion of Gustilo type Ⅲ fractures and wounds with a depth ≥2 cm was significantly higher in the infection group compared to the non-infection group (P < 0.05). At 24 h after surgery, serum CRP, IL-6, PCT, TLR4 and NF-κB levels in two groups were significantly higher than before surgery, and serum CRP, IL-6, PCT, TLR4 as well as NF-κB levels and their changes in bone infection group were significantly higher than those in the non-infection group (P < 0.05). Logistic regression analysis indicated that time from fracture to surgery, surgical duration, Gustilo type Ⅲ and wound depth ≥2 cm, and △CRP, △IL-6, △PCT, △TLR4 as well as △NF-κB were risk factors for perioperative bone infection in patients with open fractures (P < 0.05). ROC results showed that the area under the curve (AUC) of △CRP, △IL-6, △PCT, △TLR4 and △NF-κB for predicting bone infection were 0.786, 0.833, 0.772, 0.826 and 0.736, respectively. ROC curve showed that the AUC of the nomogram prediction model for perioperative bone infection was 0.893(95%CI, 0.834 to 0.952), indicating high predictive efficacy. The decision curve showed that the nomogram prediction model had a significant positive net benefit, and it had good clinical utility in predicting the risk of bone infection. Conclusion The dynamic changes of key factors of TLR/NF-κB signal axis in perioperative period of patients with open fracture have certain predictive value for postoperative bone infection. The nomogram prediction model based on the above influencing factors has good predictive value and positive clinical net benefit.

Objective:To evaluate the value of radiomics based on contrast-enhanced spectral mammography (CESM) of internal and peripheral regions combined with clinical factors in predicting benign and malignant breast lesions of breast imaging reporting and data system category 4 (BI-RADS 4).Methods:A retrospective analysis was performed on the clinical and imaging data of patients with breast lesions who were treated in Yantai Yuhuangding Hospital (Center 1) Affiliated to Qingdao University from July 2017 to July 2020 and in Fudan University Cancer Hospital (Center 2) from June 2019 to July 2020. Center 1 included 835 patients, all female, aged 17-80 (49±12) years, divided into training set (667 cases) and test set (168 cases) according to the "train-test-split" function in Python software at a ratio of 8∶2; and 49 patients were included from Center 2 as external validation set, all female, aged 34-70 (51±8) years. The radiomics features were extracted from the intralesional region (ITR), the perilesional regions of 5, 10 mm (PTR 5 mm, PTR10 mm) and the intra-and perilesional regions of 5, 10 mm (IPTR 5 mm, IPTR 10 mm) and were selected by variance filtering, SelectKBest algorithm, and least absolute shrinkage and selection operator. Then five radiomics signatures were constructed including ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, IPTR 10 mm signature. In the training set, univariable and multivariable logistic regressions were used to construct nomograms by selecting radiomics signatures and clinical factors with significant difference between benign and malignant BI-RADS type 4 breast lesions. The efficacy of nomogram in predicting benign and malignant BI-RADS 4 breast lesions was evaluated by the receiver operating characteristic curve and area under the curve (AUC). Decision curve and calibration curve were used to evaluate the net benefit and calibration capability of the nomogram.Results:The nomogram included ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, age, and BI-RADS category 4 subclassification for differentiating malignant and benign BI-RADS category 4 breast lesions and obtained AUCs of 0.94, 0.92, and 0.95 in the training set, test set, and external validation set, respectively. The calibration curve showed good agreement between the predicted probabilities and actual results and the decision curve indicated a good net benefit of the nomogram for predicting malignant BI-RADS 4 lesions in the training set, test set, and external validation set.Conclusion:The nomogram constructed from the radiomics features of the internal and surrounding regions of CESM breast lesions combined with clinical factors is attributed to differentiate benign from malignant BI-RADS category 4 breast lesions.