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.

Nigella sativa L. seeds have been traditionally utilized in Chinese folk medicine for centuries to treat vitiligo. This study revealed that the ethanolic extract of Nigella sativa L. (HZC) enhances melanogenesis and mitigates oxidative stress-induced cellular senescence and dysfunction in melanocytes. In accordance with established protocols, the ethanol fraction from Nigella sativa L. seeds was extracted, concentrated, and lyophilized to evaluate its herbal effects via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays, tyrosinase activity evaluation, measurement of cellular melanin contents, scratch assays, senescence-associated β-galactosidase (SA-β-gal) staining, enzyme-linked immunosorbent assay (ELISA), and Western blot analysis for expression profiling of experimentally relevant proteins. The results indicated that HZC significantly enhanced tyrosinase activity and melanin content while notably increasing the protein expression levels of Tyr, Mitf, and gp100 in B16F10 cells. Furthermore, HZC effectively mitigated oxidative stress-induced cellular senescence, improved melanocyte condition, and rectified various functional impairments associated with melanocyte dysfunction. These findings suggest that HZC increases melanin synthesis in melanocytes through the activation of the MAPK, PKA, and Wnt signaling pathways. In addition, HZC attenuates oxidative damage induced by H₂O₂ therapy by activating the nuclear factor E2-related factor 2-antioxidant response element (Nrf2-ARE) pathway and enhancing the activity of downstream antioxidant enzymes, thus preventing premature senescence and dysfunction in melanocytes.
Oxidative Stress/drug effects* ; Melanocytes/cytology* ; Cellular Senescence/drug effects* ; Nigella sativa/chemistry* ; Plant Extracts/pharmacology* ; Seeds/chemistry* ; Mice ; Animals ; Melanins/metabolism* ; Monophenol Monooxygenase/metabolism* ; Humans

Tumor cells use glycolysis to provide material and energy under hypoxic conditions to meet the energy requirements for rapid growth and proliferation， namely the Warburg effect. Even under aerobic conditions， tumor cells mainly rely on glycolysis to provide energy. Therefore， glucose transporter protein 1（GLUT1）， which is involved in the process of glucose metabolism， plays an important role in tumorigenesis， development and drug resistance， and is considered to be one of the important targets in the treatment of malignant tumors. In recent years， research on tumor glucose metabolism has gradually become a hot spot. It has been shown that various factors are involved in the regulation of tumor energy metabolism， among which the role of GLUT1 is the most critical. In this paper， the authors reviewed the latest research progress of GLUT1-targeted traditional Chinese medicine（TCM） active ingredient nano-delivery system in tumor therapy， aiming to reveal the feasibility and effectiveness of this system in the delivery of chemotherapeutic drugs. The GLUT1-targeted TCM active ingredient nano-delivery system can overcome the bottleneck of the traditional targeting strategy as well as the high-permeability long retention（EPR） effect. In summary， the authors believe that the GLUT1-targeted TCM active ingredient nano-delivery system provides a new strategy for targeted treatment of tumors and has a broad application prospect in tumor prevention and treatment.

Objective:To identify the influencing factors affecting the cosmetic facial injection treatments for cosmetic patients.Methods:Based on the purposeful sampling principle with maximum diversity and data saturation principle, patients who underwent facial injection cosmetic surgery in Plastic Surgery Hospital, Chinese Academy of Medical Sciences from June to September 2022 were selected for cross-sectional study. The qualitative study method was used to conduct semi-structured in-depth interviews with patients and collect data. After the interview, the 7-step analysis method of Colaizzi phenomenological data was used to extract the topic concepts.Results:A total of 16 patients were included, and their influencing factors for medical treatment could be divided into 5 related topics: (1) age-related; (2) occupation-related; (3) surrounding social-environment-related; (4) social media platforms contacted; (5) experience of negative appearance evaluation during adolescence.Conclusion:Many factors affect the treatment of injection patients. In the course of medical treatment, the influencing factors should be identified accurately, so as to guide patients to seek medical treatment scientifically.

Exogenous lipoid pneumonia is an inflammatory response to the lungs caused by inhaled lipid substances, which is prone to secondary bacterial infection, resulting in the formation of local abscesses, which can be life-threatening in severe cases. This paper reports a case of a 55-year-old patient with diesel aspiration, secondary to Klebsiella pneumoniae (ESBL positive) and Candida glabrata infection resulting in lung abscess formation. He was treated with a variety of antibacterial drugs for anti-infection, non-invasive ventilator ventilation, bronchoalveolar lavage, glucocorticoids, phlegm and other medical treatments. Finally, he underwent middle lobectomy for improvement and was discharged from the hospital, and he recovered well with regular follow-up.

Objective:To identify the influencing factors affecting the cosmetic facial injection treatments for cosmetic patients.Methods:Based on the purposeful sampling principle with maximum diversity and data saturation principle, patients who underwent facial injection cosmetic surgery in Plastic Surgery Hospital, Chinese Academy of Medical Sciences from June to September 2022 were selected for cross-sectional study. The qualitative study method was used to conduct semi-structured in-depth interviews with patients and collect data. After the interview, the 7-step analysis method of Colaizzi phenomenological data was used to extract the topic concepts.Results:A total of 16 patients were included, and their influencing factors for medical treatment could be divided into 5 related topics: (1) age-related; (2) occupation-related; (3) surrounding social-environment-related; (4) social media platforms contacted; (5) experience of negative appearance evaluation during adolescence.Conclusion:Many factors affect the treatment of injection patients. In the course of medical treatment, the influencing factors should be identified accurately, so as to guide patients to seek medical treatment scientifically.

Humans ; Myocardial Infarction/surgery* ; Bone Marrow Transplantation ; Bone Marrow Cells ; Ventricular Function, Left