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 quantitatively evaluate the accuracy of data obtained from liquid-interference surfaces using an intraoral 3D scanner (IOS) integrated with a compressed airflow system, so as to provide clinical proof of accuracy for the application of the compressed airflow system-based scanning head in improving data quality on liquid-interference surfaces. METHODS: The study selected a standard model as the scanning object, adhering to the "YY/T 1818-2022 Dental Science Intraoral Digital Impression Scanner" guidelines, a standard that defined parameters for intraoral scanning. To establish a baseline for accuracy, the ATOS Q 12M scanner, known for its high precision, was used to generate true reference values. These true values served as the benchmark for evaluating the IOS performance. Building on the design of an existing scanner, a new scanning head was developed to integrate with a compressed airflow system. This new design aimed to help the IOS capture high-precision data on surfaces where liquid-interference, such as saliva, might otherwise degrade scanning accuracy. The traditional scanning method, without airflow assistance, was employed as a control group for comparison. The study included five groups in total, one control group and four experimental groups, to investigate the effects of scanning lens obstruction, airflow presence, liquid media, and the use of the new scanning head on scanning process and accuracy. Each group underwent 15 scans, generating ample data for a robust statistical comparison. By evaluating trueness and precision in each group, the study assessed the impact of the compressed airflow system on the accuracy of IOS data collected from liquid-interference surfaces. Additionally, we selected Elite and Primescan scanners as references for numerical accuracy values. RESULTS: The scanning accuracy on liquid-interference surfaces was significantly reduced in terms of both trueness and precision [Trueness: 18.5 (6.5) vs. 38.0 (6.7), P < 0.05; Precision: 19.1 (8.5) vs. 31.7 (15.0), P < 0.05]. The use of the new scanning head assisted by the compressed airflow system significantly improved the scanning accuracy [Trueness: 22.3(7.6) vs. 38.0 (6.7), P < 0.05; Precision: 25.8 (9.6) vs. 31.7 (15.0), P < 0.05]. CONCLUSION The scanning head based on the compressed airflow system can assist in improving the accuracy of data obtained from liquid-interference surfaces by the IOS.
Imaging, Three-Dimensional/methods* ; Humans ; Dental Impression Technique/instrumentation*

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To study the clinical correlation between fasting plasma glucose, lipid metabolism, prostate-specific antigen and prostate volume in patients with benign prostatic hyperplasia, and to explore the combined effect as diagnostic indicators. A total of 108 patients with benign prostatic hyperplasia treated in Beijing University of Chinese Medicine Third Affiliated Hospital from June 2021 to March 2023 were retrospectively analyzed as the hyperplasia group, and 98 healthy physical examination personnel were selected as the control group during the same period. Compare the differences in levels of fasting plasma glucose (FPG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), small and dense low-density lipoprotein cholesterol (sdLDL-C), homocysteine, lipoprotein a (LPa), prostate specific antigen (PSA), and free prostate specific antigen (fPSA) between two groups of patients. Using Pearson analysis method to analyze the correlation between the above indicators and the size of prostate volume in patients with benign prostatic hyperplasia; using multiple linear regression to analyze the influencing factors of prostate volume enlargement; draw receiver operating characteristic (ROC) curves and analyze the application value of individual and combined detection of HDL, FPG, PSA, and fPSA. The results showed that there were significant differences in HDL, FPG, PSA, and fPSA levels between the control group and the proliferative group( P<0.05). The size of prostate volume is negatively correlated with HDL( r=-0.183, P<0.05) and positively correlated with FPG ( r=0.202, P<0.05), PSA( r=0.412, P<0.05), and fPSA( r=0.425, P<0.05). The results of multiple linear regression analysis showed that HDL( P=0.000), FPG( P=0.048), PSA( P=0.044), and fPSA ( P=0.012) were risk factors for increased volume of benign prostatic hyperplasia; ROC curve analysis shows that the AUC of HDL, FPG, PSA, and fPSA combined detection is 0.823, which is better than individual detection. In conclusion,HDL, FPG, PSA, fPSA has close correlation with hyperplasia of prostate, the joint detection may has better prediction for benign prostatic hyperplasia.

OBJECTIVE To explore the correlation between early clinical auditory brainstem response and long-term temporal bone development in patients with microtia and atresia. METHODS A retrospective review of clinical data of patients with MA,including ABR examination results in infancy,temporal bone CT results in adolescence and childhood,and basic demographic information. Comparison of ABR thresholds among patients with different temporal bone development statuses. RESULTS Jahrsdoerfer score and the degree of mastoid pneumatization were negatively correlated with ABR air conduction threshold and air-bone gap. The Jahrsdoerfer high score group of patients with congenital aural atresia had significantly lower ABR air conduction threshold(P=0.011) and ABR air-bone gap(P=0.033) than the low Jahrsdoerfer score group. The air conduction threshold(P=0.005) and air-bone gap(P<0.001) of ABR in mastoid process of pneumatic group were lower than those in non-pneumatic group in all patients with MA. The ABR air-conduction threshold(P=0.002) and ABR air-bone gap(P<0.001) in the congenital aural stenosis with cholesteatoma group were higher than those in the non-cholesteatoma group. CONCLUSION For patients with MA,ABR examination in infancy not only reflects the patients' hearing status but also has predictive value for temporal bone development.

OBJECTIVE To observe the changes of static functional connectivity(sFC) and dynamic functional connectivity(dFC) of amygdala subregions in patients with bilateral idiopathic tinnitus and hearing loss(TINHL). METHODS The resting-state functional magnetic resonance imaging(fMRI) data of 30 patients with bilateral tinnitus and hearing loss and 37 normal controls(NCs) were collected to analyze the intensity changes of sFC and dFC in 8 subregions of amygdala and the whole brain in TINHL patients. RESULTS There were no significant differences in age,sex and education between the two groups. Compared with the NCs group,the sFC intensity of the right basolateral subregion and right cerebellar peduncle 1 region,the left basolateral subregion and left orbital medial frontal gyrus and left angular gyrus in TINHL group was significantly decreased. The dFC intensity of left amygdalostriatal subregion and left precuneus in TINHL group was increased,but the dFC intensity was reduced in the left basolateral subregion and right angular gyrus as well as between the right superficial subregion and right medial orbital of superior frontal gyrus. CONCLUSION Among the 8 subregions of amygdala,the bilateral basolateral subregions,the left amygdalostriatal subregion and the right superficial region shown abnormal functional connectivity with other regions of the brain,which are the important parts of emotional abnormalities in TINHL.

Objective This study aimed to explore the prognostic value of 18F-FDG PET/CT Metabolic and Heterogeneity Parameters Combined with Clinical Features Before Definitive Chemoradiotherapy(D-CRT)in predicting the prognosis of esophageal squamous cell carcinoma(ESCC)Patients.Methods A retrospective analysis was conducted on clinical data from 106 patients with ESCC who received D-CRT at the first affiliated Hospital of University of Science and Technology of China between January 2017 and December 2021.All patients underwent 18F-FDG PET/CT examination before the treatment.The primary tumor′s metabolic and heterogeneity parameters were obtained through data processing.All patients were followed up for overall survival.The Kaplan-Meier method and Cox proportional hazards models were used to analyze the association between clinical features,tumor metabo-lism and heterogeneity parameters and patient prognosis.Results The 1-and 1.5-year overall survival rates of all patients were 77.4%and 51.9%.The median survival time was 20 months.Univariate analysis showed that N stage,M stage,metabolic tumor volume,total lesion glycolysis,heterogeneity index-2(HI-2),and coefficient of variation with a threshold of 40%maximum standard uptake value(CV40%)were correlated with the prognosis of ESCC(all P<0.05).Multivariate analysis showed that N stage and CV40%were independent predictors of prognosis in patients with ESCC(P = 0.039 and P<0.001,respectively).Conclusion N stage and tumor metabolic heterogeneity parameter CV40%,which offering a degree of predictive value,are closely related to the prognosis of patients with ESCC treated with D-CRT.