AIM:To investigate the effect of apoptosis stimulation protein 2(ASPP2)on the development of traumatic proliferative vitreoretinopathy(PVR)in a rabbit model.METHODS:A total of 30 New Zealand white rabbits were selected, and the right eyes of all rabbits were inflicted with a scleral penetrating wound of approximately 6 mm. Then rabbits were randomly and evenly divided into experimental and control group. The experimental group received an intravitreal injection of 0.1 mL of ARPE-19 cell suspension transfected with lentivirus-ASPP2, while the control group received an intravitreal injection of 0.1 mL of ARPE-19 cell suspension transfected with negative control lentivirus. At 1, 2, 3, and 4 wk after PVR modeling, a handheld tonometer was used to measure the intraocular pressure. Moreover, fundus photography and ocular ultrasound examination were performed to detect the retinal proliferation. At 4 wk after modeling, hematoxylin-eosin staining was used to observe the morphological retinal changes, and Western blot was used to determine the protein expressions of ASPP2 and the epithelial-mesenchymal transition(EMT)marker Vimentin in the rabbit retinas.RESULTS:At 1, 2, 3, and 4 wk after modeling, there were no significant changes in intraocular pressure within the experimental and control group of rabbit eyes, either before or after PVR modeling, the success rate of PVR modeling in the experimental group was lower than that in the control group(P<0.05), and the retinal proliferation and structural disorder was less severe in the experimental group. At 4 wk after modeling, the retinal protein expression level of ASPP2 in the experimental group was significantly higher than that in the control group(t=3.193, P=0.033), while the Vimentin protein expression level was significantly lower in the experimental group(t=-3.599, P=0.023).CONCLUSION:ASPP2 may be involved in regulating the process of EMT in retinal pigment epithelial cells, thereby delaying the development and progression of traumatic PVR in rabbit eyes.

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.

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 transcriptome sequencing results of Nelson Bay virus(NBV)-infected murine RAW264.7 mac-rophages,and to screen for differentially expressed genes(DEGs)to provide a theoretical basis for exploring the mechanism of innate immune response in reovirus infection.Methods RAW264.7 cells were infected with the NBV-Miyazaki virus strain at a multiplicity of infection(MOI)of 30.We used transcriptome sequencing technologies,with q＜0.05 and|log2FC|≥ 1,for screening the DEGs in the infection and control groups.The Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)databases were used for enrichment analysis of DEGs.Results A total of 442 genes were differentially expressed in the infection group,of which 381 genes were significantly upregulated and 61 genes were significantly downregulated.In the GO analysis,the enrichment of DEGs was primarily related to the innate immune response,defense response to viruses,cytokine production,and cell response to cytokine stimulation.In the KEGG analysis,the enrichment of DEGs were primarily related to the Toll-like receptor,retinoid acid inducible gene Ⅰ-like receptor,PI3K/Akt,and other signaling pathways.Conclusion RAW264.7 macrophages infected with the NBV-Miyazaki virus can activate pattern recognition receptors;promote the release of cytokines,chemokines,and other immune-related factors;and enhance antibody-dependent cell-mediated cytotoxicity to exert an immune effect.This study provides a theoretical basis for exploring the mechanisms of innate immu-nity during NBV-Miyazaki virus infection.

Objective To evaluate the clinical efficacy and safety of vericiguat combined with the new"Quadruple Therapy"for treating heart failure with reduced ejection fraction(HFrEF)and to explore its impact on left ventricular reverse remodeling(LVRR)in patients with different baseline characteristics.Methods A total of 87 patients with chronic heart failure treated with vericiguat at the Department of Cardiology,Nanjing Drum Tower Hospital from June 2022 to March 2024,were consecutively enrolled as the observation group.These patients were matched at 1:1 by age,sex,and left ventricular ejection fraction(LVEF)with 87 patients who received the standard quadruple therapy without vericiguat as the control group.Propensity score matching was used to further balance confounding factors,resulting in 64 patients in each group for final analysis.Changes in echocardiographic parameters,liver and kidney function,electrolyte levels,and blood pressure were analyzed at baseline and during the 6-month follow-up to assess the efficacy and safety of vericiguat.The primary efficacy endpoint was the occurrence of LVRR.Subgroup analyses were conducted based on baseline characteristics such as age and sex.Interaction analysis was utilized to evaluate the heterogeneity of vericiguat's efficacy.Results After 6 months of treatment,the vericiguat group showed significant improvements in cardiac structure and function compared to the control group.The left ventricular end-diastolic diameter was significantly reduced[-0.43(-1.00,-0.10)mm vs.-0.22(-0.53,0.02)mm,P=0.002],and the LVEF was significantly increased[8.45％(1.40％,16.50％)vs.2.75％(0,11.00％),P=0.002].The percentage of patients in the vericiguat group who achieved LVRR was significantly larger than in the control group(46.4％vs.27.4％,P=0.011).Multivariate logistic regression revealed that the combination of vericiguat was an independent predictor of LVRR(Model 2:OR=2.54,95％CI:1.29～5.01,P=0.007).The reverse remodeling effect remained consistent across different subgroups and was not significantly influenced by specific baseline characteristics(Pinteraction>0.05).Vericiguat did not affect blood pressure,liver and kidney function,or electrolyte levels,achieving satisfactory safety,despite its significantly higher incidence of gastrointestinal reactions(16.1％vs.5.7％,P<0.001).Conclusion The addition of vericiguat to the quadruple therapy significantly improves cardiac function and promotes left ventricular reverse remodeling in HFrEF patients while maintaining a favorable safety profile.

Objective:To analyze the relationship between folate and thyroid antibody in early pregnancy and adverse pregnancy outcome in pregnant women with hypothyroidism during pregnancy.Methods:The data of 97 pregnant women with hypothyroidism from Jul. 2020 to Mar. 2023 in the Obstetrics Department of Liaocheng Second People’s Hospital were retrospectively analyzed. The levels of folate, thyroglobulin antibody (TGAb) and thyroid peroxidase antibody (TPOAb) were detected in the first trimester. According to whether adverse pregnancy outcome occurred in pregnant women with hypothyroidism during pregnancy, they were divided into occurrence group and non-occurrence group. The clinical data of the occurrence group and the non-occurrence group were compared. Logistic regression was used to analyze the influencing factors of adverse pregnancy outcomes in pregnant women with hypothyroidism during pregnancy, and receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of folic acid, TGAb, TPOAb and their combination on adverse pregnancy outcomes in pregnant women with hypothyroidism during pregnancy.Results:Among 97 pregnant women, the incidence of adverse pregnancy outcome was 14.43% (14/97) .The folate level in the occurrence group was lower than non-occurrence group ( P<0.05) , and the TGAb and TPOAb levels in the occurrence group were higher than non-occurrence group ( P<0.05) . The occurrence group with alanine aminotransferase (ALT) , glutamine transpeptidase (GGT) and aspartate aminotransferase (AST) were all higher than non-occurrence group ( P<0.05) .The folate, TGAb, and TPOAb levels were factors influencing adverse pregnancy outcomes in pregnant women with hypothyroidism ( P<0.05) . The area under the curve (AUC) values of folate, TGAb, TPOAb and their combined prediction of adverse pregnancy outcomes in pregnant women with hypothyroidism during pregnancy were 0.804, 0.843, 0.799, 0.909 ( P<0.05) , while the combined three with AUC values were higher ( P<0.05) . Conclusion:The folate, TGAb and TPOAb levels in early pregnancy can be used to evaluate adverse pregnancy outcomes in hypothyroidism pregnant women, and the combination of the three has a higher evaluation value.

Kinesiophobia is prevalent among school-aged children with asthma,and severe kinesiophobia can hinder their participation in physical activities and disease control,adversely affecting their physical and mental health.This paper reviews the concept,development,assessment tools,influencing factors,and intervention strategies of kinesiophobia in school-aged children with asthma,analyzes existing challenges,and proposes directions for future research.It aims to provide insights for developing scientific and personalized intervention plans to enhance children's exercise levels and improve their quality of life.

Objective To summarize the clinical features and prognosis of children suffered from malignant solid tumors of head and neck.Methods The clinical data of children with primary malignant solid tumors located in the head and neck was retrospectively analyzed from January 2007 to December 2021 in the Department of Oncology,Beijing Children's Hospital,Capital Medical University,and the clinical features,prognostic factors were summarized.Results A total of 234 children with malignant solid tumors of head and neck were included,with a male to female ratio of 1∶0.7,aged from 3 months to 17 years and 6 months(median age 51 months).173 cases(73.9％)were treated with local painless masses.Other symptoms included snoring and facial paralysis.The proportion of rhabdomyosarcoma(RMS)was the highest(145 cases,62.0％),followed by neuroblastoma(NB)(25 cases,10.7％),Ewing sarcoma(19 cases,8.1％),etc.A total of 47 cases(20.1％)had distant metastasis.The patients received surgery,chemotherapy and radiotherapy under the mode of multidisciplinary treatment(MDT).The 3-year and 5-year overall survival(OS)were 80.8％and 75.8％,respectively,and the 3-year and 5-year progression free survival(PFS)were 64.0％and 58.9％,respectively.Tumor survivors had abnormal appearance or facial motor function(49 cases,41.2％),developmental problems or abnormal tooth loss(18 cases,15.1％),and other long-term complications that may be related to the tumor or treatment.Conclusion There are various pathologic types of pediatric head and neck malignant solid tumors,RMS and NB are the most common.Local painless mass was the most common complaint.Distant metastasis is an independent risk factor for the prognosis of head and neck malignant solid tumors.Under the MDT model,the prognosis of malignant solid tumors of the head and neck in our center was generally good.In the treatment of the tumors,the side effects and sequelae should be controlled as small as possible under the premise of long-term survival.

"Technology-consumption separation"in pricing of medical testing programs,refers to the medical testing programs in the pricing process will be the cost of technology and consumables cost accounting separately,this is the basis for large-scale centralized procurement of test reagents,for the standardization of medical testing programs to carry out,reduce the cost of medical testing programs is critical.The medical testing programs pricing"technology and consumption separation"of the connotation is deeply analyzed.It is considered that the main difficulties in the implementation of the"technology-consumption separation"in the pricing of medical testing programs are the difficulty of costing,the difficulty of calculating the use of special reagents,and the difficulty of policy implementation.The implementation of the"technology-consumption separation"in the pricing of medical testing programs are proposed from"pricing according to the current price minus the cost of specialized reagents","based on big data to measure the loss of specialized reagents"and"appropriate increase in the pricing level".