Objective To investigate the relationship between the comorbidity of dyslipidemia, hypertension and diabetes and lifestyle of adult residents in Hebei Province in 2018, and to provide reference for the development of chronic diseases prevention measures. Methods Using data from the surveillance of chronic diseases and their risk factors among adults in Hebei in 2018, 7 711 permanent residents aged ≥18 years were selected as the research subjects. Multivariate logistic regression analysis was used to analyze the relationship between the comorbidity of dyslipidemia, hypertension, and diabetes and lifestyle in adult residents. Results A total of 7 711 subjects aged ≥18 years were included in 2018. The comorbidity rates of hypertension and dyslipidemia, diabetes and dyslipidemia, and hypertension and diabetes were 16.88%, 7.91%, and 8.13%, respectively. The comorbidity rate of hypertension, diabetes, and dyslipidemia was 22.65%. These comorbidity rates increased with age and BMI. Multivariate logistic regression results showed that male, age, overweight/obesity, physical inactivity, daily sedentary behavior time ≥5 hours, and sleep problems were risk factors for the comorbidity of the "three highs". Conclusion The prevalence of the "three highs" comorbidities is relatively high in Hebei Province, and there are multiple common risk factors. Maintaining a healthy lifestyle and implementing comprehensive prevention and control measures are the key to improving the health level of residents.

AIM: To develop a novel gene-delivery therapeutic based on CRISPR/Cas9 genome editing technology capable of specifically targeting and knocking out the VEGFA gene, thereby achieving sustained suppression of VEGFA expression in retinal pigment epithelial(RPE)cells and providing a new strategy for gene therapy in retinal neovascular diseases.METHODS:Single guide RNAs targeting the human VEGFA gene for knockout were designed, and corresponding recombinant plasmids were constructed. A novel polymer(PTEE)was used to encapsulate the plasmids to prepare a PTEE-loaded anti-VEGFA plasmid(PLAP)gene delivery system. PTEE materials at concentrations of 0.1, 0.2, 0.4, 0.8, and 1.6 μg/μL were co-incubated with ARPE-19 cells, and the biocompatibility of PTEE was evaluated using the cell counting kit-8(CCK-8)assay. Recombinant plasmids expressing green fluorescent protein(GFP)were constructed. Lipofectamine 3000 and jetOPTIMUS®DNA transfection reagents were used as control groups, and PTEE nanomaterials were used as the experimental group to encapsulate the plasmids. When the cell confluence reached 80%, the formulations were transfected into ARPE-19 and 293T cells. GFP expression was observed under light microscopy, and the transfection efficiencies of each group were compared. ARPE-19 cells were induced under hypoxia, and PLAP was transfected into the cells. The expression level of VEGFA was detected by enzyme-linked immunosorbent assay(ELISA)to evaluate the efficacy of this novel gene delivery system.RESULTS: After co-incubation of ARPE-19 cells with different concentrations of PTEE for 24 h and 48 h, no significant effect on cell viability was observed in any group. The transfection efficiency of PLAP in ARPE-19 cells was higher than that in the Lipo3000 and jetOPTIMUS groups, with statistically significant differences(P<0.01). Hypoxia for 6 h significantly induced the upregulation of VEGFA mRNA expression in ARPE-19 cells, and under hypoxic conditions, the PTEE group exhibited a significant inhibitory effect on VEGFA expression(P<0.01).CONCLUSION:PLAP exhibits favorable biocompatibility and prominent VEGFA inhibitory effects in vitro, making it a potential candidate drug for gene therapy of retinal neovascular diseases.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To analyze the prevalence of hyperuricemia (HUA) among adults in Hebei Province and its influencing factors related to comorbidities with ^“three highs^”, and to provide a theoretical basis for the prevention and control of HUA and multi-disease co-management. Methods Data were derived from the 2018 China Chronic Disease and Risk Factors Surveillance program conducted in Hebei Province. A multi-stage stratified cluster random sampling method was used to select permanent residents aged ≥18 years. All statistical analyses were adjusted for complex weighting. Design-based logistic regression was employed to analyze factors influencing HUA prevalence, and ordinal logistic regression was used to analyze the influencing factors of HUA patients and their comorbidity with ^“three highs^”. Results The prevalence of HUA among adults in Hebei Province was 10.42%, with males showing higher rates than females (P<0.05). The highest prevalence of HUA was observed in the 18-39 age group, followed by a declining trend, and a resurgence in those aged ≥70 (P<0.05). Among HUA patients with comorbidities, isolated HUA, 1 comorbidity, 2 comorbidities, and 3 comorbidities accounted for 13.94%, 33.33%, 39.17%, and 13.56%, respectively. HUA combined with hypertension and dyslipidemia represented the highest proportion (31.07%). Analysis of the influencing factors of HUA revealed that higher education levels, obesity, central obesity, and dyslipidemia increased the risk of HUA (P<0.05). Ordinal logistic regression analysis of HUA combined with three highs showed that HUA patients aged ≥50 years, overweight individuals, and those with chronic kidney disease had a higher number of patients with three highs (P<0.05). Conclusion HUA exhibits insidious onset, and it is recommended to include uric acid testing in routine physical examinations. Targeted prevention measures, such as early uric acid testing and health education, should be implemented by Hebei authorities for populations with higher education levels, obesity, central obesity, and dyslipidemia to reduce HUA incidence. Additionally, health education and regular medical check-ups are recommended for overweight HUA patients and those with chronic kidney disease to prevent comorbidities and alleviate disease burden.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

Objective To evaluate the application value of artificial intelligence (AI) in the quality control of mammographic images and explore its feasibility for improving image quality. Methods A retrospective analysis was conducted on 500 mammographic images from 125 female patients. These images were acquired in December 2024 at the Department of Radiology, Obstetrics and Gynecology Hospital of Tongji University by two junior technologists with qualification certificate for junior radiologic technologists and ≤ 2 months of independent operation. The reference standard was the evaluation by a panel of senior experts comprising one associate chief radiologist and two intermediate radiologic technologists with over 10 years of experience in mammography. The evaluation was based on nine criteria within an AI quality control system. The correlation and consistency (Kappa test) of the assessment outcomes were compared among the junior technologist group, the AI quality control group, and the panel group. Additionally, the differences in the proportions of high-, medium-, and low-quality images rated by the three groups were analyzed. After one month of AI assistance, 200 images from 50 additional patients acquired by the same two junior technologists in January 2025 were collected. The area under the receiver operating characteristic curve and 95% confidence interval (95%CI) were calculated for the assessment performance of the junior technologist group before and after AI assistance. Differences were compared using the DeLong test. Changes in the disqualification rates for the nine criteria were analyzed. Results In consistency analysis, the AI quality control group showed high consistency with the panel group across multiple key criteria, with Kappa values ranging from 0.41 to 1.00. In contrast, the consistency between the junior technologist group and the panel group was generally low, with Kappa values ranging from 0.13 to 0.49. In comparison of image quality classification, no significant differences were observed in image quality classification between the AI group and the panel group (P>0.05). However, the proportion of images rated as high quality by the junior technologist group was significantly higher, while the proportions rated as medium and low quality were significantly lower, compared to those rated by the panel group (P<0.05). After AI assistance, the area under the receiver operating characteristic curve for the assessment performance of junior technologist group increased significantly from 0.56 (95%CI: 0.51-0.61) to 0.91 (95%CI: 0.87-0.94) (P<0.001). The disqualification rates for skin folds, incomplete inclusion of the pectoralis major muscle, and nipple not in profile decreased significantly. Conclusion AI demonstrates assessment capability comparable to the panel group in mammographic quality control. AI effectively enhances the quality of images acquired by junior technologists through real-time, objective feedback.

BACKGROUND:Macrophage migration inhibitory factor(MIF)is a pleiotropic cytokine,which is secreted in different types of stem cells and can regulate the proliferation,differentiation and migration of various types of stem cells.Our previous research has confirmed that human embryonic stem cells secrete MIF and that its concentration in the culture medium is relatively stable.However,whether MIF is involved in the survival,proliferation and differentiation of human embryonic stem cells remains unclear. OBJECTIVE:To investigate the effects of MIF on survival,proliferation,and differentiation of human embryonic stem cells. METHODS:(1)Human embryonic stem cells H9 were cultured.The growth curve of cells was detected and plotted by CCK-8 assay.Enzyme-linked immunosorbent assay was used to determine the level of MIF in the medium.(2)To determine the effects of exogenous MIF on the survival and proliferation of human embryonic stem cells,different groups were established:the control group,which was cultured in stem cell medium without any modifications;the exogenous MIF group,which was treated with different concentrations(30,100,300 ng/mL)of MIF in the stem cell medium;the MIF inhibitor ISO-1 group,which was treated with different concentrations(2,7,21 μmol/L)of ISO-1 in the stem cell medium;and the MIF+ISO-1 group,which was treated with different concentrations of ISO-1 along with 100 ng/mL of MIF.Cell viability was assessed using the CCK-8 assay.(3)To further elucidate the effect of MIF gene on survival and proliferation of human embryonic stem cell,the MIF knockout H9 cell line was constructed by CRISPR-Cas 9 technology to observe the lineage establishment.(4)To determine the effect of high concentrations of MIF on human embryonic stem cell differentiation,100 ng/mL MIF and 100 ng/mL of CXCR4 neutralizing antibody were separately added to the normal stem cell culture medium.The expression levels of self-renewal factors(KLF4,c-MYC,NANOG,OCT4,and SOX2)and differentiation transcription factors(FOXA2,OTX2)were measured using real-time quantitative polymerase chain reaction,immunofluorescence staining,and western blot analysis. RESULTS AND CONCLUSION:(1)The logarithmic growth phase of H9 cells was between 3-6 days.Under normal growth conditions,human embryonic stem cells secreted MIF at a concentration of approximately 20 ng/mL,independent of cell quantity.(2)Compared to the control group,the addition of different concentrations of MIF had no effect on the proliferation of human embryonic stem cells(P>0.05).ISO-1 significantly inhibited the proliferation of human embryonic stem cells,with a stronger inhibition observed at higher concentrations of ISO-1(P<0.05).The addition of MIF in the presence of ISO-1 reduced the inhibitory effect of ISO-1(P<0.05).(3)Real-time quantitative polymerase chain reaction showed that knocking out 50%of the MIF gene resulted in a significant decrease in the growth vitality of human embryonic stem cells and failure to establish cell lines.(4)Adding 100 ng/mL exogenous MIF to the culture medium resulted in a decrease in the mRNA,protein,and fluorescence expression levels of the self-renewal transcription factor KLF4,while the mRNA,protein,and fluorescence expression levels of the differentiation factor FOXA2 increased.(5)When 100 ng/mL CXCR4 neutralizing antibody was added to the culture medium,the mRNA and protein expression levels of KLF4 increased,while the mRNA and protein expression levels of FOXA2 decreased,contrary to the expression trend observed in the MIF group.In conclusion,the endogenous secretion of MIF by human embryonic stem cells is essential for their survival.The addition of MIF to the culture medium does not promote the proliferation of human embryonic stem cells.However,it can lead to a decrease in the expression of the self-renewal factor KLF4 and an increase in the expression of the transcription factor FOXA2.This provides a clue for further investigation into the effects and mechanisms of MIF on the differentiation of human embryonic stem cells.The MIF-CXCR4 axis plays a regulatory role in this process.

Objective To investigate the association between the Chinese visceral adiposity index (CVAI) and diabetes mellitus, hypertension, diabetes mellitus or hypertension, and diabetes with hypertension among elderly people in Hebei Province. Methods In 2020, a stratified multi-stage random sampling was used to conduct questionnaire survey, physical examination and laboratory detection among permanent residents of 10 monitoring sites in Hebei Province. Logistic regression was used to analyze the association between CVAI and diabetes mellitus, hypertension, diabetes mellitus or hypertension, and diabetes with hypertension. The area under the ROC curve (AUC) was used to evaluate the predictive value of CVAI for diabetes mellitus, hypertension, diabetes mellitus or hypertension, and diabetes with hypertension. Results The detection rates of diabetes mellitus, hypertension, diabetes mellitus or hypertension, and diabetes with hypertension were 19.8%, 74.6%, 78.2%, and 16.2%, respectively. Multivariate logistic regression analysis showed that compared with the lowest quartile of CVAI group Q1, the OR (95% CI) of diabetes mellitus, hypertension, diabetes mellitus or hypertension, and diabetes with hypertension in the highest quartile Q4 group were 3.55 (2.58~4.89), 2.52 (1.92~3.31), 3.09 (2.31~4.12), and 4.92 (3.40~7.12), respectively. The ROC curve results showed that CVAI had the best predictive value in the diagnosis of diabetes with hypertension, and the optimized critical values in males and females were 128.54 and 141.88, respectively. Conclusion The detection rates of diabetes mellitus and hypertension are high in the elderly population in Hebei Province. CVAI is positively associated with the risk of diabetes mellitus, hypertension, diabetes mellitus or hypertension, and diabetes with hypertension among the elderly in Hebei. CVAI has the strongest prediction ability for diabetes with hypertension.

OBJECTIVE: To evaluate the effects of acupuncture at Hegu (LI4), Taichong (LR3) and Sanyinjiao (SP6) on pain, anxiety, intrapartum blood loss, labor stage, and neonatal outcomes in primiparas. METHODS: One hundred primiparas were randomly divided into an acupuncture group (50 cases, 1 case was eliminated) and a control group (50 cases). The conventional obstetrical nursing was given in the control group. On the basis of the intervention in the control group, acupuncture was applied at bilateral Hegu (LI4), Taichong (LR3) and Sanyinjiao (SP6) in the acupuncture group. The delivery mode and labor stage, the scores of visual analogue scale (VAS) for uterine contraction pain and Hamilton anxiety scale (HAMA) before and after acupuncture, the intrapartum/postpartum blood loss and massive hemorrhage, as well as the neonatal Apgar score after 1, 5, and 10 min of birth, were compared in the two groups. RESULTS: The cesarean section rate was 4.1% (2/49) in the acupuncture group, which was superior to 10.0% (5/50) in the control group (P<0.05). In the acupuncture group, the time of latent phase of 2-cm cervical dilation, active phase, first and second stages of labor, and total labor stage was shorter than that in the control group (P<0.001), the intrapartum blood loss and massive hemorrhage rate were lower than those in the control group (P<0.001, P<0.05). After acupuncture, the VAS and HAMA scores were decreased compared with those before acupuncture in the acupuncture group (P<0.001), the VAS and HAMA scores were increased compared with those before acupuncture in the control group (P<0.001). In the acupuncture group, the VAS and HAMA scores after acupuncture were lower than those in the control group (P<0.001), the changes of the VAS and HAMA scores before and after acupuncture were larger than those in the control group (P<0.001). There were no statistical differences in neonatal Apgar scores between the two groups (P>0.05). CONCLUSION Acupuncture at Hegu (LI4), Taichong (LR3) and Sanyinjiao (SP6) can effectively alleviate the pain and anxiety, shorten the labor stage, reduce the intrapartum blood loss and incidence rate of massive hemorrhage, and promote spontaneous delivery, thereby enhancing maternal comfort and safety in primiparas.
Humans ; Female ; Pregnancy ; Acupuncture Points ; Acupuncture Therapy ; Adult ; Young Adult ; Labor, Obstetric ; Parity

Objective: To analyze the frequency and investigate the causes of unexpected antibodies in D-negative blood donors. Methods: From January 2022 to December 2024, 3 768 D-negative blood donors sent to our laboratory were selected as research subjects. D-negative confirmation test and RhCE phenotype detection were applied by saline tube method and microcolumn gel indirect antiglobulin test (IAT), respectively. Antibody screening and identification were performed using the polybrene method and IAT column agglutination methods. Anti-D, anti-C and anti-G specificities were identified by a two-step adsorption-elution method, and the genotypes of D-negative samples were determined by RHD gene amplification, Sanger sequencing, and PacBio Single Molecule Real-Time (SMRT) sequencing. Results: Among D-negative donors, ccee and Ccee phenotypes accounted for the highest proportion, 55.68% (2 098/3 768) and 29.56% (1 114/3 768), respectively, while CcEE and CCEe phenotypes were the least, with one case detected in each, accounting for 0.03% (1/3 768). A total of 165 cases with D variant phenotype were detected, and the proportion of D variant was 4.38% (165/3 768) in the donors detected by D-negative confirmation test. Antibody screening positive blood donors were identified in 93 cases with a proportion of 2.47% (93/3 768). Antibody specificity was determined in 84 blood donors, and 9 samples showed no clear specificity. Anti-D was detected most frequently (n=68), in which 6 of them were detected having multiple antibodies, anti-D + anti-C (n=2), anti-D + anti-G(n=1), and anti-D + anti-E(n=3). The other antibodies detected were anti-E (n=1), anti-M(n=9), anti-P1 (n=3), anti-Le (n=1), and anti-HI(n=2). Fourteen cases were detected with anti-D in serological D-negative donors with C+ or E+ phenotype, in which three of them were DVI type 3 individuals and 11 cases were D negative individuals. Conclusion: The incidence of unexpected antibodies was higher in D-negative blood donors than in the total donors, with anti-D being the most common. The data provide insights for prevention and monitoring hemolytic disease of the fetus and newborn (HDFN) caused by anti-D. To ensure the safety of blood transfusion, routine unexpected antibody screening for RhD-negative blood donors is recommended to prevent the use of unexpected antibodies positive plasma in the clinic.