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.

BACKGROUND: Congenital heart disease (CHD) is a leading cause of birth defect-related mortality. However, more recent CHD mortality data for China are lacking. Additionally, limited studies have evaluated sex, rural-urban, and region-specific disparities of CHD mortality in China. METHODS: We designed a population-based study using data from the Dataset of National Mortality Surveillance in China between 2008 and 2021. We calculated age-adjusted CHD mortality using the sixth census data of China in 2010 as the standard population. We assessed the temporal trends in CHD mortality by age, sex, area, and region from 2008 to 2021 using the joinpoint regression model. RESULTS: From 2008 to 2021, 33,534 deaths were attributed to CHD. The period witnessed a two-fold decrease in the age-adjusted CHD mortality from 1.61 to 0.76 per 100,000 persons (average annual percent change [AAPC] = -5.90%). Females tended to have lower age-adjusted CHD mortality than males, but with a similar decline rate from 2008 to 2021 (females: AAPC = -6.15%; males: AAPC = -5.84%). Similar AAPC values were observed among people living in urban (AAPC = -6.64%) and rural (AAPC = -6.12%) areas. Eastern regions experienced a more pronounced decrease in the age-adjusted CHD mortality (AAPC = -7.86%) than central (AAPC = -5.83%) and western regions (AAPC = -3.71%) between 2008 and 2021. Approximately half of the deaths (46.19%) due to CHD occurred during infancy. The CHD mortality rates in 2021 were lower than those in 2008 for people aged 0-39 years, with the largest decrease observed among children aged 1-4 years (AAPC = -8.26%), followed by infants (AAPC = -7.01%). CONCLUSIONS CHD mortality in China has dramatically decreased from 2008 to 2021. The slower decrease in CHD mortality in the central and western regions than in the eastern regions suggested that public health policymakers should pay more attention to health resources and health education for central and western regions.
Humans ; Heart Defects, Congenital/mortality* ; Male ; Female ; China/epidemiology* ; Infant ; Child, Preschool ; Adult ; Child ; Adolescent ; Infant, Newborn ; Middle Aged ; Young Adult ; Aged ; Rural Population

OBJECTIVES: To evaluate the causal association between circulating levels of zinc, magnesium, and other minerals and autism spectrum disorder (ASD). METHODS: A two-sample Mendelian randomization (MR) analysis was performed using summary statistics from large-scale genome-wide association studies of European populations, including 18 382 ASD cases and 27 969 controls. Genetic data for iron, calcium, and magnesium were obtained from the UK Biobank, and data for zinc and selenium were sourced from an Australian-British cohort. A total of 351 genetic instrumental variables were selected. Causal inference was performed using inverse-variance weighting as the primary analysis method. Sensitivity analyses were performed by Cochran's Q test and MR-PRESSO global test to assess the robustness of the findings. RESULTS: No statistically significant causal effect was observed for circulating zinc, magnesium, calcium, selenium, or iron levels on ASD risk (all P>0.05). The odds ratios and 95% confidence intervals from the inverse-variance weighting analysis were 0.934 (0.869-1.003) for zinc, 1.315 (0.971-1.850) for magnesium, 1.055 (0.960-1.159) for calcium, 1.015 (0.953-1.080) for selenium, and 0.946 (0.687-1.303) for iron. Sensitivity analysis revealed significant heterogeneity in the causal association between circulating calcium and ASD (P=0.006), while the effect estimate remained stable after MR-PRESSO correction (P=0.487). The causal effect estimates for the remaining minerals demonstrated good robustness. CONCLUSIONS This study did not find significant evidence supporting a causal association between circulating zinc, magnesium, calcium, selenium, or iron levels and ASD risk, providing important clues for the etiology of ASD and precision nutritional interventions.
Humans ; Mendelian Randomization Analysis ; Autism Spectrum Disorder/genetics* ; Magnesium/blood* ; Zinc/blood* ; Minerals/blood* ; Genome-Wide Association Study ; Selenium/blood*

OBJECTIVE: To explore the construction method of a resistant multiple myeloma (MM) patient-derived xenotransplantation (PDX) model. METHODS: 1.0×10⁷ MM patient-derived mononuclear cells (MNCs), 2.0×10⁶ MM.1S cells and 2.0×10⁶ NCI-H929 cells were respectively subcutaneously inoculated into NOD.CB17-Prkdc^scid Il2rg^tm1/Bcgen (B-NDG) mice with a volume of 100 μl per mouse to establish mouse model. The morphologic, phenotypic, proliferative and genetic characteristics of PDX tumor were studied by hematoxylin-eosin staining, immunohistochemical staining (IHC), cell cycle analysis, flow cytometry and fluorescence in situ hybridization (FISH). The sensitivity of PDX tumor to bortezomib and anlotinib monotherapy or in combination was investigated through cell proliferation, apoptosis and in vitro and in vivo experiments. The effects of anlotinib therapy on tumor blood vessel and cell apoptosis were analyzed by IHC, TUNEL staining and confocal fluorescence microscope. RESULTS: MM PDX model was successfully established by subcutaneously inoculating primary MNCs. The morphologic features of tumor cells from MM PDX model were similar to those of mature plasma cells. MM PDX tumor cells positively expressed CD138 and CD38, which presented 1q21 amplification, deletion of Rb1 and IgH rearrangement, and had a lower proliferative activity than MM cell lines. in vitro, PDX, MM.1S and NCI-H929 cells were treated by bortezomib and anlotinib for 24 hours, respectively. Cell viability assay showed that the IC₅₀ value of bortezomib were 5 716.486, 1.025 and 2.775 nmol/L, and IC₅₀ value of anlotinib were 5 5107.337, 0.706 and 5.13 μmol/L, respectively. Anlotinib treatment increased the apoptosis of MM.1S cells (P < 0.01), but did not affect PDX tumor cells (P >0.05). in vivo, there was no significant difference in PDX tumor growth between bortezomib monotherapy group and control group (P >0.05), while both anlotinib monotherapy and anlotinib combined with bortezomib effectively inhibited PDX tumor growth (both P < 0.05). The vascular perfusion and vascular density of PDX tumor were decreased in anlotinib treatment group (both P < 0.01). The apoptotic cells in anlotinib treatment group were increased compared with those in control group (P < 0.05). CONCLUSION Bortezomib-resistant MM PDX model can be successfully established by subcutaneous inoculation of MNCs from MM patients in B-NDG mice. This PDX model, which retains the basic biological characteristics of MM cells, can be used to study the novel therapies.
Animals ; Bortezomib ; Humans ; Multiple Myeloma/pathology* ; Mice ; Apoptosis ; Drug Resistance, Neoplasm ; Cell Line, Tumor ; Xenograft Model Antitumor Assays ; Mice, Inbred NOD ; Disease Models, Animal ; Cell Proliferation ; Transplantation, Heterologous

OBJECTIVE: This study aimed to determine the expression levels and prognostic significance of MYCN in bone marrow of adult patients with newly diagnosed acute myeloid leukemia (AML). METHODS: A total of 62 newly diagnosed patients with non-M3 AML were enrolled as the study group, and 20 healthy donors as the control group. Real-time quantitative reverse transcription-polymerase chain reaction (PCR) was performed to detect the expression level of MYCN, and the relationship between MYCN expression and prognosis of AML patients was analyzed. RESULTS: MYCN was up-regulated in newly diagnosed AML patients compared with normal controls (P < 0.001). Receiver operating characteristic (ROC) curve analysis revealed that MYCN could serve as a diagnostic biomarker for AML. Kaplan-Meier survival analysis showed that the patients with high MYCN expression had a shorter overall survival (OS) time than the patients with low MYCN expression (P =0.016). The expression level of MYCN was lower during the complete ressimion (CR) phase of AML compared to the initial diagnosis, but it returned to the initial diagnostic level or even higher during relapse phase. Multivariate Cox regression analysis showed that high expression of MYCN was an independent risk factor for OS of AML patients (P =0.021). CONCLUSION MYCN is highly expressed and associated with poor prognosis in de novo AML, which might be serve as a novel diagnostic and prognostic biomarker for adult AML.
Humans ; Leukemia, Myeloid, Acute/metabolism* ; Prognosis ; N-Myc Proto-Oncogene Protein ; Adult ; Female ; Male ; Middle Aged

OBJECTIVE: To investigate the predictive value of morphology, immunology, and cytogenetics for isocitrate dehydrogenase 1 and 2 (IDH1/2) gene mutation in newly diagnosed acute myeloid leukemia (AML) patients. METHODS: The clinical data of 186 newly diagnosed AML patients (except M3 subtype) in the First People's Hospital of Changzhou were retrospectively analyzed, and the variables associated with IDH1/2 mutation in patients were screened using LASSO regression to construct a multivariate logistic regression analysis model. The Bootstrap method was used for internal validation of the model and nomograms were used to visualize the model, and receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of the model. RESULTS: A total of 60 AML patients had IDH1/2 mutation at initial diagnosis. LASSO regression screened 9 predictive variables associated with IDH1/2 mutation, including CD7, CD56, CD11b, CD15, CD64, HLA-DR, platelet count≥50×10⁹/L, isolated +8 and normal karyotype. The nomogram and ROC curve were plotted based on the above 9 variables. The area under the ROC curve (AUC) of the training set and the validation set were 0.871 and 0.806, respectively. Internal validation showed that the nomogram had good predictive ability. CONCLUSION The prediction model based on MIC typing constructed in this study has a good predictive ability for the presence of IDH1/2 mutations in newly diagnosed AML patients and has important clinical application value when the gene mutation detection results are unavailable.
Humans ; Isocitrate Dehydrogenase/genetics* ; Leukemia, Myeloid, Acute/genetics* ; Mutation ; Retrospective Studies ; Nomograms ; Female ; Male ; ROC Curve ; Middle Aged

Objective To investigate the basic situation and occupational health conditions of nuclear medicine radiation workers in Jiangsu Province based on the research protocol developed by the Institute of Radiation Medicine, Chinese Academy of Medical Sciences for the nationwide study on the health effects of nuclear medicine radiation in China, understand the impact of occupational radiation on the physical health of nuclear medicine radiation workers, and provide a basis for improving the occupational protection of nuclear medicine radiation workers and reducing the risk of occupational radiation-related health issues. Methods A census approach was used to collect general data and occupational health information of nuclear medicine radiation workers in Jiangsu Province. The analysis focused on the abnormalities in physical examination indicators among radiation workers of different genders, ages, and working years to evaluate the health effects of occupational radiation exposure. Results The occupational health examination data of 472 nuclear medicine radiation workers were collected from 76 medical institutions in Jiangsu Province. The results showed that the detection rate of abnormal hypothyroidism in female workers (8.90%) was higher than that in male workers (2.54%) (P=0.028). With increasing working years, the detection rates of cataract and continuous decrease in white blood cell count increased (P＜0.001). The multivariate logistic regression identified working years as a risk factor for cataract and continuous decrease in white blood cell count (OR=1.59, 95%CI=1.40-3.35, P=0.0003; OR=4.15, 95%CI=3.11-29.91, P=0.0001). In addition, working years was also a risk factor for hypertension, fatty liver, and tumor (OR=2.28, 95%CI=1.51-3.47, P=8.76 × 10⁻⁵; OR=1.69, 95%CI=1.10-2.58, P=0.0145; OR=2.04, 95%CI=1.00-4.16, P=0.0469). Conclusion The study found that working in nuclear medicine could increase the risk of various radiation-related diseases, and the risk is influenced by factors such as working years.