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 effects of different sensory integration tasks on biomechanical characteristics of the lower limbs during walking in female patients with patellofemoral pain(PFP),and exlpore the relationship between these characteristics and patellofemoral joint stress(PFJS),so as to provide a reference for the prevention of PFP recurrence.Methods A total of 36 female patients with PFP were recruited for the study,and kinematic and kinetic data were collected while the subjects were walking.The effects of baseline,tactile integration task,listening integration task and visual integration task on lower limb biomechanical characteristics was evaluated through the use of one-way ANOVA.Pearson correlation analysis was used to analyze the relationship between the above biomechanical characteristics and PFJS.Results Compared to the baseline,the step length(P=0.004)and cadence(P=0.001)of patients with PFP in the listening integration task were significantly reduced.Furthermore,both variables exhibited a negative correlation with PFJS(P<0.05).Both the hip internal rotation angle(P=0.001)and the ankle internal rotation angle(P=0.022)were significantly increased in tactile integration task.Furthermore,the aforementioned metrics were significantly and positively correlated with PFJS(P<0.05).The hip internal rotation angle(P=0.001),knee flexion angle(P=0.019),ankle inversion angle(P=0.003),and ankle plantarflexion angle(P=0.048)of patients with PFP in the visual integration task were increased.These biomechanical characteristics exhibited a positive correlation with PFJS(P<0.05).Conclusions The listening integration task decreases the step length and cadence of patients with PFP,and the tactile and visual integration tasks increase the hip and ankle internal rotation angles.On this basis,the visual integration task also increases the knee flexion angle and ankle plantarflexion angle during walking.Overall,the visual integration task has the greatest effect on gait biomechanics of female patients with PFP,and changes in these biomechanical characteristics are associated with elevated PFJS.

Objective To analyze the effects of different sensory integration tasks on biomechanical characteristics of the lower limbs during walking in female patients with patellofemoral pain(PFP),and exlpore the relationship between these characteristics and patellofemoral joint stress(PFJS),so as to provide a reference for the prevention of PFP recurrence.Methods A total of 36 female patients with PFP were recruited for the study,and kinematic and kinetic data were collected while the subjects were walking.The effects of baseline,tactile integration task,listening integration task and visual integration task on lower limb biomechanical characteristics was evaluated through the use of one-way ANOVA.Pearson correlation analysis was used to analyze the relationship between the above biomechanical characteristics and PFJS.Results Compared to the baseline,the step length(P=0.004)and cadence(P=0.001)of patients with PFP in the listening integration task were significantly reduced.Furthermore,both variables exhibited a negative correlation with PFJS(P<0.05).Both the hip internal rotation angle(P=0.001)and the ankle internal rotation angle(P=0.022)were significantly increased in tactile integration task.Furthermore,the aforementioned metrics were significantly and positively correlated with PFJS(P<0.05).The hip internal rotation angle(P=0.001),knee flexion angle(P=0.019),ankle inversion angle(P=0.003),and ankle plantarflexion angle(P=0.048)of patients with PFP in the visual integration task were increased.These biomechanical characteristics exhibited a positive correlation with PFJS(P<0.05).Conclusions The listening integration task decreases the step length and cadence of patients with PFP,and the tactile and visual integration tasks increase the hip and ankle internal rotation angles.On this basis,the visual integration task also increases the knee flexion angle and ankle plantarflexion angle during walking.Overall,the visual integration task has the greatest effect on gait biomechanics of female patients with PFP,and changes in these biomechanical characteristics are associated with elevated PFJS.

OBJECTIVE:Knee adduction moment and knee adduction angular impulse enlargement is the main biomechanical risk factor of knee osteoarthritis.According to the survey,a change in the foot progression angle could effectively change the motion mode of patients with knee osteoarthritis.However,the impact of toe-in and toe-out on knee adduction moment and knee adduction angular impulse in young and elderly patients did not reach a consensus.Therefore,this study comprehensively discussed the effect of foot progression angle on knee adduction moment and knee adduction angular impulse in different populations through meta-analysis and provided a reference for the treatment of knee osteoarthritis. METHODS:By June 2022,searches were conducted on Web of Science,EBSCO,PubMed and CNKI databases using"foot progression angle,knee adduction moment,knee adduction angular impulse,gait"as Chinese and English search terms.Self-controlled randomized controlled studies analyzing the effects of toe-in and toe-out on knee adduction moment bimodality and knee adduction angular impulse were included.The cochrane bias risk assessment tool was utilized to make a quality evaluation of the literature.Stata 15.1 software was used for subgroup analysis to determine the effect of foot progression angle on knee adduction moment and knee adduction angular impulse.Meta-regression analysis was used to further determine characteristics of outcome indicators(knee adduction moment,knee adduction angular impulse)changing with foot progression angle. RESULTS:(1)A total of 15 self-control trials and 2 randomized controlled trials(455 subjects)were included in the meta-analysis.All of the included articles were of medium to high quality.(2)The meta-analysis results showed that the toe-in gait could reduce the first peak of knee adduction moment(SMD=-0.380,95%CI:-0.710 to-0.060,P=0.022)and knee adduction angular impulse(SMD=-1.470,95%CI:-2.160 to-0.770,P<0.001)in young patients.The toe-out gait reduced the second peak of knee adduction moment(SMD=-0.720,95%CI:-1.010 to-1.440,P<0.001)in young patients.In addition,toe-in gait could reduce the first peak of knee adduction moment in elder patients(SMD=-0.550,95%CI:-0.800 to-0.300,P<0.001),but increase the second peak knee adduction moment of elderly(SMD=0.280,95%CI:-0.010 to 0.560,P=0.047).The toe-out gait could decrease the second peak knee adduction moment in this population(SMD=-0.510,95%CI:-0.830 to-0.190,P=0.002).(3)Meta-regression showed that the greater the toe-out in elderly patients,the lower the second peak knee adduction moment. CONCLUSION:(1)Toe-in reduced the first peak knee adduction moment and knee adduction angular impulse in young knee osteoarthritis patients aged 18 to 34 years.Since knee adduction moment and knee adduction angular impulse were associated with medial knee loading and knee osteoarthritis incidence,toe-in gait intervention may be a suitable rehabilitation strategy for young patients.(2)Toe-in increased the second peak of knee adduction moment in older knee osteoarthritis patients over 60 years of age,which may exacerbate knee osteoarthritis in this population.However,the second peak of knee adduction moment during walking in this population decreases as the toe-out increases,contributing to a reduction in medial knee loading,suggesting that older patients may consider using toe-out gait during walking.

OBJECTIVE:There is no consensus on which sit-up strategy to adopt in knee osteoarthritis patients of different ages.Therefore,this study evaluated the biomechanical characteristics of sit-ups in knee osteoarthritis patients of different ages compared with healthy individuals by meta-analysis system and analyzed the sit-up movement patterns of patients of different ages to provide a reference for improving the sit-up function of patients. METHODS:By March 2023,observational studies of biomechanical characteristics of sitting up in patients with knee osteoarthritis and healthy population were retrieved on PubMed,Web of Science and CNKI.Subjects were required to be patients over 50 years of age with knee osteoarthritis who had Kellgren-Lawrence severity grading≥Ⅰ on knee imaging and who had regular knee pain.Subjects were analyzed by age(50-60 years vs.over 60 years)and severity(mild to moderate patients vs.severe patients)subgroups according to inclusion and exclusion criteria.Quality assessment was performed using the modified Down and black scale.Stata 16.0 software was used to perform subgroup analysis to determine the biomechanical characteristics of sitting up in patients with knee osteoarthritis of different ages and severities. RESULTS:A total of 14 randomized controlled trials(824 subjects)were included in the meta-analysis.The mean quality score of all included literature was 76.2,with a range of 66.7 to 86.7,all of which were of medium to high quality and representative.The included studies were of moderate to high quality and representative.Meta-analysis results found that(1)compared to healthy individuals,patients with knee osteoarthritis had longer total sitting up time(SMD=0.92,95%CI:0.76-1.09),P<0.001)and longer extension phase time(SMD=0.46,95%CI:0.18-0.74,P=0.001).Compared to mild to moderate patients,the total duration increased more significantly in severe patients(P<0.001)and the duration of the extension phase increased more significantly in patients over 60 years of age than in patients 50-60 years of age(P=0.001).(2)Compared to healthy individuals,patients with knee osteoarthritis had greater sitting-up trunk flexion motion range(SMD=0.64,95%CI:0.37-0.91,P<0.001);knee flexion motion range(SMD=-0.47,95%CI:-0.70 to-0.24,P<0.001)and ankle dorsiflexion motion range(SMD=-0.32,95%CI:-0.56 to-0.08,P=0.01)were smaller.And knee flexion motion range decreased more significantly in patients over 60 years of age than in patients 50-60 years of age(P<0.001).(3)The peak hip flexion moment(SMD=-0.57,95%CI:-0.83 to-0.31,P<0.001)and peak knee extension moment(SMD=-0.83,95%CI:-1.08 to-0.59,P<0.001)were smaller in patients with knee osteoarthritis. CONCLUSION:(1)Patients with knee osteoarthritis over the age of 60 years have a longer sit-up cushion and extension phase than patients aged 50 to 60 years.The increase in total sit-up duration was also more pronounced in patients with higher severity grades.The increased length of sitting up in patients with advanced age and knee osteoarthritis severity may increase the duration of cartilage loading,exacerbate knee pain symptoms,and increase the difficulty of sitting up in this population.(2)Patients with knee osteoarthritis exhibit limited knee and ankle flexion motion range.Knee mobility is more limited in patients over 60 years of age.(3)Patients with knee osteoarthritis have reduced peak hip flexion and knee extension moments,which may be a compensatory strategy for pain relief.

Schizophrenia is a serious mental disorder that is often associated with profound impairment in patients′ daily functioning, and its etiology and pathophysiology are still to be fully elucidated. There is a pathological correlation between inflammation, brain injuries, and the pathogenesis of schizophrenia, with microglia actively participating in these processes. This review provides a comprehensive overview of the impact of microglial cells on neurodevelopment and neuroplasticity, and microglia abnormalities mediating the onset of schizophrenia by contributing to damage in different brain regions.

Schizophrenia is a serious mental disorder that is often associated with profound impairment in patients′ daily functioning, and its etiology and pathophysiology are still to be fully elucidated. There is a pathological correlation between inflammation, brain injuries, and the pathogenesis of schizophrenia, with microglia actively participating in these processes. This review provides a comprehensive overview of the impact of microglial cells on neurodevelopment and neuroplasticity, and microglia abnormalities mediating the onset of schizophrenia by contributing to damage in different brain regions.

Objective To analyze the influence of different backpack types and loads on kinematics and plantar pressure of college students during stair climbing, so as to provide references for choosing the appropriate backpack and carrying mode. Methods The Nokov infrared light point motion capture system and Podome plantar pressure system were used to analyze the differences in the range of motion ( ROM) of the trunk and lower limb joints, the kinematic parameters at the peak time, the peak pressure of each plantar partition, the contact time, the maximum pressure of the whole foot, the average pressure and the maximum contact area for 15 male college students during the support period of stair climbing. Results The 5% BW and 10% BW backpack loads reduced ROM of trunk rotation, increased ROM of ankle flexion/ extension and varus / valgus. The 10% BW backpack loads increased the peak pressure of the 1st and 3rd metatarsals bones and the maximum pressure of the whole foot ( P < 0. 05). Single-shoulder bag and handbag reduced ROM of trunk tilting and rotation, and increased ROM of ankle flexion and extension, hip flexion angle, peak pressure of foot arch and medial heel (P<0. 05). The double-shoulder bag loads increased peak pressure in the toe area (P<0. 05). Conclusions During walking on the stairs, the 5% BW and 10% BW backpack loads limited trunk rotation and increased ankle ROM. The 10% BW loads also increased the load in metatarsal area. The unilateral weight-bearing mode would make the trunk tilt to the unload side and rotate to the weight-bearing side. The pressure in toe area was higher when carrying double-shoulder bag, while single-shoulder bag and handbag mainly increased the pressure of arch foot and medial heel. It is suggested that college students choose symmetrical backpack scheme, and wisely allocate back weight to avoid the injury of foot area.