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 discuss the clinical efficacy of catheter-directed thrombolysis(CDT)in treating acute pulmonary embolism(APE).Methods A total of 215 patients with APE,who were admitted to the Second Affiliated Hospital of Shandong First Medical University of China,were enrolled in this study.Pulmonary angiography was performed in all the patients.After the location of the thrombus was identified,the pigtail catheter was rotated so as to break the thrombus into small pieces,which was followed by local infusion of thrombolytic agent urokinase to make recanalization of the occluded pulmonary artery.The postoperative clinical symptoms,blood oxygen saturation,mean pulmonary artery pressure,BNP,D-dimer,RV/LV diameter ratio were compared with their preoperative values.PESI scoring was used to evaluate the severity of the pulmonary embolism.Patients with PESI grade-Ⅲ and PESI grade-Ⅳ were classified into medium-risk group,and patients with PESI grade-V were classified into higher-risk group.Results Symptom relief immediately after surgery was observed in 210 patients,complete recanalization of pulmonary artery was achieved in 200 patients,and partial recanalization of pulmonary artery was seen in 15 patients.The preoperative mean pulmonary artery pressure,blood oxygen saturation,BNP,D-dimer,RV/LV diameter ratio were(46.24±5.32)mmHg,(90.36±3.23)％,(8 000.12±750.56)pg/mL,(7.5±2.3)mg/L and(1.63±0.22)respectively;at one week after surgery the above indicators were(26.12±3.36)mmHg,(98.74±2.12)％,(240.35±33.52)pg/mL,(1.75±0.36)mg/L and(1.11±0.13)respectively;the differences were statistically significant(all P＜0.05).In the patients who had symptoms of hemoptysis,shock and syncope before surgery,all these symptoms were completely disappeared in one week after CDT,and the symptoms of dyspnea,chest pain,and palpitations were significantly relieved after CDT,the differences were statistically significant(all P＜0.05).The difference in survival time between different PESI grade groups was statistically significant(P＜0.05).No serious postoperative complications such as severe arrhythmia,cerebral hemorrhage,or gastrointestinal bleeding occurred.Postoperative 3-month CT pulmonary angiography(CTPA)showed that the main pulmonary artery was well visualized and no thrombus-produced filling defect shadow was detected.Conclusion For the treatment of APE,CDT can promptly and rapidly open the obstructed pulmonary artery lumen,restore pulmonary artery hemodynamics,and correct hypoxemia.Therefore,CDT is a safe,effective and quick treatment for APE.

OBJECTIVE To summarize the implementation experiences of the China Hospital Association’s Clinical Pharmacist Instructor Training Program Reform， and to evaluate the effectiveness of the reform， thus continuously enhancing the quality and standards of clinical pharmacist instructor training. METHODS The study drew on project evaluation methodologies to summarize the main characteristics of the comprehensive system and new model for clinical pharmacist instructor training established through the reform by literature review. The “learning assessment” and “reaction assessment” were conducted by using Kirkpatrick’s four-level model of evaluation in order to evaluate the effectiveness of the clinical pharmacist instructor training reform through statistically processing and analyzing the performance data and teaching evaluation data of the instructor participants. Based on problem and trend analysis， the future development directions were anticipated for the reform of clinical pharmacist instructor training. RESULTS & CONCLUSIONS The latest round of clinical pharmacist instructor training reform initiated by the Chinese Hospital Association had initially established a four-pronged training system encompassing “recruitment， training， assessment， and management”. It had also forged a training 。 model “oriented towards enhancing clinical teaching competency， with practical learning and skill-based assessment conducted on clinical teaching sites as its core”. Following a period of over three years of gradual reform， the new training system and model became increasingly mature. In both 2023 and 2024， the participants achieved relatively high average total scores in their initial completion assessments [with scores of （84.05± 5.83） and （85.82±4.35） points， respectively]. They also reported a strong sense of gain from the training reform [with self- perceived gain scores of （4.80±0.44） and （4.85±0.39） points， respectively]. The operation and implementation effects of the reform were generally satisfactory. In the future， clinical pharmacist instructor training reforms should continue to address the issues remaining from the current phase， while aligning with global trends in pharmacy education and industry development. Additionally， sustained exploration and practice will be carried out around the core objective of “enhancing clinical teaching competence”.

Congenital orofacial cleft, the most common birth defect in the maxillofacial region, exhibits a wide range of prognosis depending on the severity of deformity and underlying etiology. Non-syndromic congenital orofacial clefts typically present with milder deformities and more favorable treatment outcomes, whereas syndromic congenital orofacial clefts often manifest with concomitant organ abnormalities, which pose greater challenges for treatment and result in poorer prognosis. This consensus provides an elaborate classification system for varying degrees of orofacial clefts along with corresponding diagnostic and therapeutic guidelines. Results serve as a crucial resource for families to navigate prenatal screening results or make informed decisions regarding treatment options while also contributing significantly to preventing serious birth defects within the development of population.
Humans ; Cleft Lip/diagnosis* ; Cleft Palate/diagnosis* ; Consensus ; Prenatal Diagnosis ; Female

Objective:To investigate the structural changes in the spinal cord in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and their relationship with clinical disability.Methods:This study was cross-sectional. A retrospective analysis of clinical and imaging data from 124 patients with MS (MS group), 101 patients with aquaporin-4 antibody-positive NMOSD (NMOSD group), and 110 healthy controls (HC group) from seven medical centers were conducted from January 2018 to October 2021. All subjects underwent 3D T 1WI, and the upper cervical spinal cord cross-sectional area (MUCCA) was segmented and measured. All patients completed the expanded disability status scale (EDSS) assessments at baseline and during follow-up, as well as the baseline 25-foot walk test (T25FW) and the nine-hole peg test (NHPT). Patients were classified into EDSS progression and non-progression groups based on follow-up EDSS scores. Comparisons of MUCCA among the three groups were conducted using analysis of covariance, controlling for age and sex as covariates. Pairwise comparisons between groups were performed using the HSD test. Univariate linear regression and logistic models were employed to identify candidate predictors of baseline clinical disability status or EDSS progression in the MS and NMOSD groups. L1 regularized multivariable linear regression analysis was used to determine independent predictors of baseline clinical disability status or EDSS progression. Independent predictors were then combined to establish a logistic regression model, and the model′s performance in predicting EDSS progression was evaluated using receiver operating characteristic analysis and the area under the curve (AUC). Results:A total of 144 patients completed follow-up EDSS assessments, with a follow-up duration of 3.30 (1.10, 6.42) years, including 82 patients in the MS group and 62 patients in the NMOSD group. Controlling for sex and age as covariates, the overall difference in MUCCA among the MS, NMOSD, and HC groups was statistically significant ( P=0.001). The MUCCA in the MS group was lower than that in the HC group, with a significant difference ( t=-2.54, P=0.007); the MUCCA in the NMOSD group was also lower than that in the HC group, with a significant difference ( t=-2.80, P=0.002). However, the difference in MUCCA between the MS and NMOSD groups was not statistically significant ( t=-0.40, P=0.882). In the MS group, MUCCA was an independent predictor of baseline EDSS score (β=-0.03), baseline T25FW score (β=-0.09), and baseline NHPT score (β=-0.30). In the NMOSD group, MUCCA (β=-0.08), age (β=0.06), and baseline EDSS score (β=-0.43) were independent predictors of EDSS progression, and the logistic regression model incorporating these three factors predicted EDSS progression with an AUC of 0.82. Conclusions:Significant spinal cord atrophy occurs in patients with both MS and NMOSD. Atrophy of the upper cervical spinal cord can predict the degree of disability in MS patients and the progression of clinical disability in NMOSD patients.

The occurrence of malignant tumors is related to immune evasion caused by the upregulation of immune checkpoint inhibitory receptors. T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) is a novel immune checkpoint receptor with remarkable prospects in the treatment of hematologic malignancies. In addition to acting on T cells, TIGIT can also participate in the development of hematologic malignant diseases by regulating antigen-presenting cells, but the specific mechanism of action is still unclear. This review summarizes the latest research progress in the molecular structure, inhibitory function, immunomodulatory effect of TIGIT and the mechanism by which TIGIT modulates antigen-presenting cells to participate in the pathogenesis of malignant hematological diseases, so as to provide a theoretical basis for an in-depth understanding of the immune regulatory role of TIGIT in hematologic malignant diseases.

Objective:To investigate the correlation between vitamin D levels and thyroid hormone sensitivity in euthyroid individuals.Methods:This cross-sectional study included 5 894 euthyroid individuals who underwent health examinations at the Department of Health Management, Peking Union Medical College Hospital, from December 2023 to February 2024. Thyroid feedback quantile-based index (TFQI), TSH index (TSHI), thyrotroph thyroxine resistance index (TT4RI), and the ratio of free triiodothyronine (FT3)/free thyroxine (FT4) were calculated to assess thyroid hormone sensitivity. Participants were categorized into vitamin D deficiency and non-deficiency groups based on serum 25(OH)D levels. The differences in thyroid hormone sensitivity indices and other clinical characteristics between the two groups were compared. Multivariate logistic regression models were used to analyze the association between vitamin D levels and thyroid hormone sensitivity, and stratified analysis was conducted to explore the association in different genders.Results:Among the study participants, 4 731 (80.3%) had vitamin D deficiency. Compared with the non-deficient group, the deficient group had a lower TFQI (-0.03(-0.31, 0.23) and -0.01(-0.28, 0.27)) ( Z=-2.130, P=0.033) and a higher FT3/FT4 ratio ((0.36±0.04) and (0.35±0.04)) ( t=-4.592, P<0.001). After adjusting for confounding factors including gender and age, the risk of impaired central and peripheral thyroid hormone sensitivity significantly increased in the non-deficient group (TFQI ( OR=1.16, 95% CI: 1.01-1.34); FT3/FT4 ( OR=1.23, 95% CI: 1.05-1.45)) (all, P<0.05). Conclusion:In euthyroid individuals, people with higher vitamin D levels have a higher risk of impaired thyroid hormone sensitivity.