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 study the improvement effect and mechanism of Shengmai powder on heart failure （HF） mice with qi-yin deficiency. METHODS The mice were randomly divided into blank group （water）， model group （water）， Shengmai powder low-， medium-， and high-dose groups [2.61， 5.22 and 10.44 g/kg （based on crude drug dosage）] and positive control group （metoprolol， 30 mg/kg）， with 10 mice in each group. Except for the blank group， all other groups were subcutaneously injected with D-galactose， and a qi-yin deficiency HF mice model was established by continuous food restriction and weight-bearing swimming. At the same time of modeling， the corresponding medicine/water was gavaged once a day for five weeks. The general state of mice was recorded and the traditional Chinese medicine （TCM） syndrome score was evaluated. Behavioral experiments were conducted to investigate the total distance of open field action， the percentage of immobility time， and the swimming exhaustion time of mice. The contents of aspartate transaminase （AST）， creatine kinase （CK） and lactate dehydrogenase （LDH） in the serum of mice were detected； cardiac function indexes [heart rate， left ventricular ejection fraction （LVEF）， left ventricular end systolic diameter （LVESD）， left ventricular end diastolic diameter （LVEDD）， left ventricular mass index and whole heart mass index] were all detected； the histopathological morphology of mice myocardium was observed； the level of cardiomyocyte apoptosis in mice was detected； mRNA expression levels of B-cell lymphoma 2 （Bcl-2）， Bcl-2 associated X protein （Bax）， and Cleaved-caspase-3 in myocardial tissue of mice were detected； the phosphorylation levels of sarcoplasmic reticulum calcium regulatory related proteins [ryanodine receptor 2 （RyR2） and phospholamban （PLB）] in myocardial tissue of mice were detected. RESULTS Compared with the blank group， the body weight， total distance of open field action， swimming exhaustion time， LVEF， LVEDD， Bcl-2 mRNA expression level in myocardial tissue and PLB protein phosphorylation level in the model group were significantly reduced/shortened （P＜0.05）； TCM syndrome score， the percentage of immobility time， heart rate， LVESD， left ventricular mass index， whole heart mass index， cardiomyocyte apoptosis rate， the contents of CK， LDH and AST in serum， mRNA expression levels of Cleaved-caspase-3 and Bax and the phosphorylation level of RyR2 protein in myocardial tissue were significantly increased （P＜0.05）； there were inflammatory cell infiltration， disordered cell arrangement and obvious myocardial interstitial fibrosis in myocardial tissue. After the intervention of Shengmai powder， most of the above quantitative indexes in mice were significantly reversed （P＜0.05）， the inflammatory cell infiltration in myocardial tissue was reduced， and the degree of fibrosis was significantly reduced. CONCLUSIONS Shengmai powder can improve cardiac function， reduce the level of cardiomyocyte apoptosis and myocardial fibrosis in HF mice with qi-yin deficiency. Its mechanism may be related to the regulation of the expression of sarcoplasmic reticulum calcium regulation related proteins.

In recent years, the incidence of multiple primary lung cancer (MPLC) has been increasing, and it cannot be ignored in clinical practice. The treatment of MPLC is still controversial, but surgical treatment is recognized as the most important treatment. However, current studies have shown that the treatment of MPLC needs to develop multimodal treatment according to different patients. This review summarizes multiple treatment method for MPLC, including surgery, ablation, chemotherapy, radiotherapy, targeted therapy, and immunotherapy in order to enhance understanding of MPLC treatment.
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Humans ; Lung Neoplasms/surgery* ; Immunotherapy ; Combined Modality Therapy

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*

In fixed prosthodontics, clear exposure of the preparation margin is the prerequisite for obtaining accurate digital impressions and improving the marginal fit of restorations. To resolve the issues associated with the cord retraction technique, such as pain, acute injury, and prolonged procedural time, this study proposes a new technology for intraoral digital impression taking with pneumatic gingival retraction. The new scanning head blows a high-speed airflow that instantaneously separates the free gingiva, locally exposing the subgingival preparation margin. Combined with the farthest point preservation stitching algorithm based on the distance from the normal vector and high-speed laser scanning photography, it achieves global preparation edge data and gingival reconstruction, realizing painless, non-invasive, and efficient precise acquisition of the preparation margin. Using this new technique, a patient with a full porcelain crown restoration on a posterior tooth was treated. The digital impression revealed a clear margin of the preparation, and the crown made from this data has a good marginal fit.