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.

Small intestinal bacterial overgrowth（SIBO）is a clinically common but poorly recognized disease with clinical symptoms that overlap with those of functional gastrointestinal disorders（FGID）. FGID is a common risk factor for the occurrence of SIBO，and its SIBO incidence rate is significantly higher than that of healthy people，and has a certain correlation. Intestinal microbiota dysbiosis（including SIBO）plays an important role in the pathophysiology of FGID. At present，the diagnosis and treatment of SIBO still face challenges，and the treatment plan of FGID is gradually introduced into the treatment of SIBO. SIBO and FGID are closely related in clinical manifestations，incidence rate，pathophysiology，treatment and other aspects，but there is little research on the relationship between them. Prospective and large-scale clinical research is still needed to improve understanding and diagnostic accuracy.This article reviews the research progress on the relationship between SIBO and FGID.

Astragaloside Ⅳ （AS-Ⅳ） is a natural triterpenoid saponin compound derived from Astragalus membranaceus and has shown significant potential in the regulation of liver diseases. This article reviews the latest research advances in AS-Ⅳ in the field of liver diseases in China and globally， and it is found that AS-Ⅳ exerts a liver-protecting effect by regulating lipid metabolism， exerting an anti-tumor/anti-inflammatory/anti-fibrotic effect， and modulating gut microbiota. Its mechanism of action involves multiple signaling pathways， such as AMPK， NLRP3， NF-κB， JAK2/STAT3， and Nrf2. These research findings provide a scientific basis for the development of liver-protecting drugs or functional foods based on the natural product AS-Ⅳ.

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.

In recent years, fibroblast activation protein inhibitor (FAPI) PET imaging, which targets the tumor microenvironment, has shown significant potential in evaluating solid tumors. Particularly, studies have demonstrated the value of 68Ga-FAPI PET in evaluation of gastric and colorectal cancer. This article reviews previous studies and provides an overview of how 68Ga-FAPI PET can be used in the diagnosis, staging, recurrence monitoring, clinical management, efficacy evaluation, and prognostic prediction of gastric and colorectal cancer, in order to provide a basis for the further utilization of this novel imaging agent, 68Ga-FAPI, in gastric and colorectal cancer.

ObjectiveTo investigate the antidepressant effects and mechanisms of total flavonoids from Cuscutae Semen （TFCC） in the mouse model of chronic unpredictable mild stress （CUMS）. MethodsFifty male 4-week-old ICR mice were randomized into five groups （n=10 per group）： blank control， model， Cuscutae Semen decoction （10.2 g·kg^-1·d^-1）， paroxetine （2.6 mg·kg^-1·d^-1）， and TFCC （173.2 mg·kg^-1·d^-1）. The other groups except the blank control group underwent chronic unpredictable mild stress （CUMS） for 4 weeks. Behavioral assessments were conducted post-modeling. Then， the model group received distilled water （10 mL·kg^-1·d^-1）， while treatment groups were administrated with respective agents via oral gavage （10 mL·kg^-1） for 4 weeks. Depression-like behaviors were evaluated by the sucrose preference test （SPT）， forced swimming test （FST）， and tail suspension test （TST）. Hippocampal neuronal morphology was observed via hematoxylin-eosin staining， and apoptosis in the brain tissue was assessed via terminal- deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was employed to measure the hippocampal levels of inflammatory cytokines ［interleukin （IL）-1β， IL-6， and TNF-α）］ and neurotransmitters ［5-hydroxytryptamine （5-HT）， dopamine （DA）， and brain-derived neurotrophic factor （BDNF）］， while the reactive oxygen species （ROS） levels were quantified via the DCFH-DA probe. Real-time PCR was performed to measure the mRNA levels of NOD-like receptor protein 3 （NLRP3）， apoptosis-associated Speck-like protein containing a CARD （ASC）， cysteinyl aspartate-specific proteinase-1 （Caspase-1）， IL-1β， and inducible nitric oxide synthase （iNOS）. Western blot was employed to evaluate the protein levels of NLRP3， ASC， Caspase-1， uncoupling protein 2 （UCP2）， and thioredoxin-interacting protein （TXNIP）. ResultsCompared with the blank control group， the model group exhibited weight loss （P<0.01）， reduced sucrose preference （P<0.01）， prolonged immobility time in FST and TST （P<0.01）， neuron disarrangement with nuclear pyknosis in hippocampal CA3 region， increased apoptosis in the brain tissue， elevated levels of IL-1β， IL-6， and TNF-α （P<0.01）， declined levels of 5-HT， DA， and BDNF （P<0.01）， increased ROS accumulation （P<0.01）， upregulated mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， down-regulated protein level of UCP2 （P<0.01）， and up-regulated protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Compared with the model group， the interventions restored sucrose preference （P<0.01）， shortened immobility time （P<0.01）， repaired hippocampal neuronal structure， reduced apoptosis， lowered the levels of inflammatory cytokines （P<0.01）， restored the levels of neurotransmitters （P<0.01）， alleviated ROS accumulation （P<0.01）， downregulated the mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， upregulated the protein level of UCP2 （P<0.01）， and reduced the protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Moreover， TFCC outperformed Cuscutae Semen decoction in ameliorating depressive behaviors. TFCC excelled in neuronal repair， neurotransmitter regulation， anti-inflammatory effects， and modulation of the UCP2/TXNIP/NLRP3 pathway （P<0.05）. ConclusionTFCC modulates the hippocampal UCP2/TXNIP/NLRP3 pathway to inhibit inflammasome activation， reduce oxidative stress， restore neurotransmitters， thus suppressing neuronal apoptosis and promoting the rearrangement and morphology recovery of hippocampal cells. It outperforms Cuscutae Semen decoction in the antidepressant efficacy.

ObjectiveTo investigate the antidepressant effects and mechanisms of total flavonoids from Cuscutae Semen （TFCC） in the mouse model of chronic unpredictable mild stress （CUMS）. MethodsFifty male 4-week-old ICR mice were randomized into five groups （n=10 per group）： blank control， model， Cuscutae Semen decoction （10.2 g·kg^-1·d^-1）， paroxetine （2.6 mg·kg^-1·d^-1）， and TFCC （173.2 mg·kg^-1·d^-1）. The other groups except the blank control group underwent chronic unpredictable mild stress （CUMS） for 4 weeks. Behavioral assessments were conducted post-modeling. Then， the model group received distilled water （10 mL·kg^-1·d^-1）， while treatment groups were administrated with respective agents via oral gavage （10 mL·kg^-1） for 4 weeks. Depression-like behaviors were evaluated by the sucrose preference test （SPT）， forced swimming test （FST）， and tail suspension test （TST）. Hippocampal neuronal morphology was observed via hematoxylin-eosin staining， and apoptosis in the brain tissue was assessed via terminal- deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling （TUNEL）. Enzyme-linked immunosorbent assay （ELISA） was employed to measure the hippocampal levels of inflammatory cytokines ［interleukin （IL）-1β， IL-6， and TNF-α）］ and neurotransmitters ［5-hydroxytryptamine （5-HT）， dopamine （DA）， and brain-derived neurotrophic factor （BDNF）］， while the reactive oxygen species （ROS） levels were quantified via the DCFH-DA probe. Real-time PCR was performed to measure the mRNA levels of NOD-like receptor protein 3 （NLRP3）， apoptosis-associated Speck-like protein containing a CARD （ASC）， cysteinyl aspartate-specific proteinase-1 （Caspase-1）， IL-1β， and inducible nitric oxide synthase （iNOS）. Western blot was employed to evaluate the protein levels of NLRP3， ASC， Caspase-1， uncoupling protein 2 （UCP2）， and thioredoxin-interacting protein （TXNIP）. ResultsCompared with the blank control group， the model group exhibited weight loss （P<0.01）， reduced sucrose preference （P<0.01）， prolonged immobility time in FST and TST （P<0.01）， neuron disarrangement with nuclear pyknosis in hippocampal CA3 region， increased apoptosis in the brain tissue， elevated levels of IL-1β， IL-6， and TNF-α （P<0.01）， declined levels of 5-HT， DA， and BDNF （P<0.01）， increased ROS accumulation （P<0.01）， upregulated mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， down-regulated protein level of UCP2 （P<0.01）， and up-regulated protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Compared with the model group， the interventions restored sucrose preference （P<0.01）， shortened immobility time （P<0.01）， repaired hippocampal neuronal structure， reduced apoptosis， lowered the levels of inflammatory cytokines （P<0.01）， restored the levels of neurotransmitters （P<0.01）， alleviated ROS accumulation （P<0.01）， downregulated the mRNA levels of NLRP3， ASC， Caspase-1， IL-1β， and iNOS （P<0.01）， upregulated the protein level of UCP2 （P<0.01）， and reduced the protein levels of NLRP3， ASC， Caspase-1， and TXNIP （P<0.01）. Moreover， TFCC outperformed Cuscutae Semen decoction in ameliorating depressive behaviors. TFCC excelled in neuronal repair， neurotransmitter regulation， anti-inflammatory effects， and modulation of the UCP2/TXNIP/NLRP3 pathway （P<0.05）. ConclusionTFCC modulates the hippocampal UCP2/TXNIP/NLRP3 pathway to inhibit inflammasome activation， reduce oxidative stress， restore neurotransmitters， thus suppressing neuronal apoptosis and promoting the rearrangement and morphology recovery of hippocampal cells. It outperforms Cuscutae Semen decoction in the antidepressant efficacy.