Objective:To explore the clinical application value of artificial intelligence（AI）-assisted training in enhancing the accuracy of nuchal translucency（NT）identification，standardization of measurement，and diagnostic efficacy for abnormalities among ultrasound residents.Methods:A retrospective collection of 300 standard fetal NT ultrasound images was conducted at the Center for Medical Ultrasound，Suzhou Hospital Affiliated of Nanjing Medical University from January 2018 to June 2024. The AI model performed NT measurements and diagnoses once. Four sonographers of different seniority levels（including two resident physicians）independently conducted NT measurements and diagnoses twice. Prior to the experiment，the middle-age and resident sonographers had uniformly completed traditional theory training. Following the first independent measurements，the two resident sonographers received additional AI-assisted training，after which all 4 sonographers performed the second independent measurements. A fetal medicine expert evaluated blindly all the results and compared the differences in NT recognition accuracy，measurement standard rate and diagnosis accuracy between the middle-age sonographer（traditional training only）and two resident sonographers（traditional + AI-assisted training）.Results:For the middle-aged sonographer who only received traditional lecture-based training，the accuracy of NT recognition，standardization rate of measurement，or diagnostic accuracy were not significantly improved befroe and after the training，and the diffrence was not statistically significant（ χ2=0.189，1.887，0.326；all P>0.05）. In contrast，the second-year resident（Resident 2）and first-year resident（Resident 1），who received both traditional lecture-based training and AI training，demonstrated some improvements in the accuracy of NT measurement site recognition，though the differences were not statistically significant（ χ2=1.301，2.418；all P>0.05）. However，both residents did significant improvements in the standardization rate of NT measurement（ χ2=25.768，17.035；all P<0.05）. In terms of diagnostic accuracy，Resident 1 did significant improvement（ χ2=10.180， P<0.05），while Resident 2 also did some improvement，though the difference was not statistically significant（ χ2=2.573， P>0.05）. Conclusions:The AI-assisted training system enhances the ability of ultrasound resident sonographers to recognize，measure，and diagnose NT，providing a novel and efficient training model for standardized residency training in ultrasound specialties.

Objective To evaluate the transition rules of normal body mass index(BMI),overweight and metabolic syndrome(MetS)in patients with major depressive disorder(MDD).Methods Patients with MDD who had multiple admission records between Jan 2016 and Nov 2021 in Beijing Anding Hospital,Capital Medical University were included.Based on the overweight and metabolic syndrome status assessed at each admission,the patients were categorized into three states:normal BMI,overweight and metabolic syndrome.A multi-state Markov model was used to analyze the transition intensity and transition frequency between three states and the influence of covariates on transitions.Results A total of 892 records of 398 subjects were included,with a median age of 56 years old and 31.4% males.The median follow-up period was 40 months.The multi-state model showed that there were 494 transitions between the three states,of which 5.1% moved from normal BMI to overweight and 5.5% moved from overweight to MetS.The intensity of transition was the highest from overweight to MetS,9.52 times greater than overweight to normal BMI.After 48.53 months,MDD patients with normal BMI began to transition to MetS.For overweight MDD patients,the transition to MetS started after 8.77 months.MDD patients with normal BMI or overweight had 31.4% and 50.4% probabilities of developing Mets after 36 months.For MDD patients comorbid with MetS,the probability of staying at MetS was 51.2% after 36 months.Multivariate analysis showed that being unmarried was a risk factor against developing overweight in normal BMI MDD patients,while a higher level of education was a protective factor against developing MetS in overweight MDD patients.Conclusion MDD patients exhibited a higher intensity and risk of developing MetS,and it is not easy to reverse MetS,suggesting that BMI management and MetS intervention should be strengthened in MDD patients.

Objective To evaluate the transition rules of normal body mass index(BMI),overweight and metabolic syndrome(MetS)in patients with major depressive disorder(MDD).Methods Patients with MDD who had multiple admission records between Jan 2016 and Nov 2021 in Beijing Anding Hospital,Capital Medical University were included.Based on the overweight and metabolic syndrome status assessed at each admission,the patients were categorized into three states:normal BMI,overweight and metabolic syndrome.A multi-state Markov model was used to analyze the transition intensity and transition frequency between three states and the influence of covariates on transitions.Results A total of 892 records of 398 subjects were included,with a median age of 56 years old and 31.4% males.The median follow-up period was 40 months.The multi-state model showed that there were 494 transitions between the three states,of which 5.1% moved from normal BMI to overweight and 5.5% moved from overweight to MetS.The intensity of transition was the highest from overweight to MetS,9.52 times greater than overweight to normal BMI.After 48.53 months,MDD patients with normal BMI began to transition to MetS.For overweight MDD patients,the transition to MetS started after 8.77 months.MDD patients with normal BMI or overweight had 31.4% and 50.4% probabilities of developing Mets after 36 months.For MDD patients comorbid with MetS,the probability of staying at MetS was 51.2% after 36 months.Multivariate analysis showed that being unmarried was a risk factor against developing overweight in normal BMI MDD patients,while a higher level of education was a protective factor against developing MetS in overweight MDD patients.Conclusion MDD patients exhibited a higher intensity and risk of developing MetS,and it is not easy to reverse MetS,suggesting that BMI management and MetS intervention should be strengthened in MDD patients.

Objective:To explore the clinical application value of artificial intelligence（AI）-assisted training in enhancing the accuracy of nuchal translucency（NT）identification，standardization of measurement，and diagnostic efficacy for abnormalities among ultrasound residents.Methods:A retrospective collection of 300 standard fetal NT ultrasound images was conducted at the Center for Medical Ultrasound，Suzhou Hospital Affiliated of Nanjing Medical University from January 2018 to June 2024. The AI model performed NT measurements and diagnoses once. Four sonographers of different seniority levels（including two resident physicians）independently conducted NT measurements and diagnoses twice. Prior to the experiment，the middle-age and resident sonographers had uniformly completed traditional theory training. Following the first independent measurements，the two resident sonographers received additional AI-assisted training，after which all 4 sonographers performed the second independent measurements. A fetal medicine expert evaluated blindly all the results and compared the differences in NT recognition accuracy，measurement standard rate and diagnosis accuracy between the middle-age sonographer（traditional training only）and two resident sonographers（traditional + AI-assisted training）.Results:For the middle-aged sonographer who only received traditional lecture-based training，the accuracy of NT recognition，standardization rate of measurement，or diagnostic accuracy were not significantly improved befroe and after the training，and the diffrence was not statistically significant（ χ2=0.189，1.887，0.326；all P>0.05）. In contrast，the second-year resident（Resident 2）and first-year resident（Resident 1），who received both traditional lecture-based training and AI training，demonstrated some improvements in the accuracy of NT measurement site recognition，though the differences were not statistically significant（ χ2=1.301，2.418；all P>0.05）. However，both residents did significant improvements in the standardization rate of NT measurement（ χ2=25.768，17.035；all P<0.05）. In terms of diagnostic accuracy，Resident 1 did significant improvement（ χ2=10.180， P<0.05），while Resident 2 also did some improvement，though the difference was not statistically significant（ χ2=2.573， P>0.05）. Conclusions:The AI-assisted training system enhances the ability of ultrasound resident sonographers to recognize，measure，and diagnose NT，providing a novel and efficient training model for standardized residency training in ultrasound specialties.

Ruxolitinib， a small molecule inhibitor， selectively targets Janus kinase （JAK） by competitively binding to adenosine triphosphate on the catalytic site of the JAK1 and JAK2 domain， thereby inhibiting JAK activation and signal transducer and activator of transcription （STAT） phosphorylation and prevents the expressions of the JAK-STAT signaling pathway. Oral ruxolitinib has demonstrated promising efficacy for myelofibrosis and polycythemia vera. The topical Ruxolitinib cream， approved by the US FDA as the first non-segmental vitiligo home treatment drug， is set to be launched in domestic medical pioneer areas in August 2023 and is expected to bring about a breakthrough in the treatment of vitiligo. Clinical cases have also shown that Ruxolitinib cream has significant curative effects on atopic dermatitis， alopecia areata， and other conditions， indicating great application prospects.

Objective To investigate the dietary patterns of rural residents in the high-incidence areas of esophageal cancer (EC), and to explore the clustering and influencing factors of risk factors associated with high-incidence characteristics. Methods A special structured questionnaire was applied to conduct a face-to-face survey on the dietary patterns of rural residents in Yanting county of Sichuan Province from July to August 2021. Univariate and multivariate logistic regression models were used to analyze the influencing factors of risk factor clustering for EC. Results There were 838 valid questionnaires in this study. A total of 90.8% of rural residents used clean water such as tap water. In the past one year, the people who ate fruits and vegetables, soybean products, onions and garlic in high frequency accounted for 69.5%, 32.8% and 74.5%, respectively; the people who ate kimchi, pickled vegetables, sauerkraut, barbecue, hot food and mildew food in low frequency accounted for 59.2%, 79.6%, 68.2%, 90.3%, 80.9% and 90.3%, respectively. The clustering of risk factors for EC was found in 73.3% of residents, and the aggregation of two risk factors was the most common mode (28.2%), among which tumor history and preserved food was the main clustering pattern (4.6%). The logistic regression model revealed that the gender, age, marital status and occupation were independent influencing factors for the risk factors clustering of EC (P<0.05). Conclusion A majority of rural residents in high-incidence areas of EC in Yanting county have good eating habits, but the clustering of some risk factors is still at a high level. Gender, age, marital status, and occupation are influencing factors of the risk factors clustering of EC.

ObjectiveTo study the differences in volatile oil content of bran-processed Atractylodes lancea and its standard decoction concentrate and freeze-dried powder， as well as the differences in the types and contents of chemical components in volatile oil， and to clarify the quality value transmitting. MethodTen batches of A. lancea rhizoma were collected and prepared into raw products and bran-processed products of A. lancea， standard decoction concentrate and freeze-dried powder of bran-processed A. lancea in order to extract the volatile oil， and the transfer rate of volatile oil in each sample was calculated. Quantitative analysis of the main chemical components（β-eudesmol， atractylon， atractylodin） in each volatile oil was performed by gas chromatography（GC） on the HP-5 quartz capillary column（0.32 mm×30 m， 0.25 μm） with a flame ionization detector（FID）， a split ratio of 10∶1 and a temperature program（initial temperature at 80 ℃， hold for 1 min， rise to 150 ℃ at 10 ℃·min^-1， hold for 10 min， rise to 155 ℃ at 0.5 ℃·min^-1， hold for 5 min， rise to 240 ℃ at 8.5 ℃·min^-1， hold for 8 min）. Cluster analysis and principal component analysis（PCA） were used to explore the overall differences in types and contents of chemical components between the standard decoction concentrate and freeze-dried powder. ResultThe transfer rates of volatile oil in the bran-processed products， standard decoction concentrate and freeze-dried powder were 70.51%， 1.57% and 40.90%， respectively. The average transfer rates of β-eudesmol， atractylon and atractylodin in the volatile oil of bran-processed A. lancea were 58.45%， 48.49% and 55.64%， respectively. In the standard decoction concentrate， only β-eudesmol and atractylodin were detected， and their average transfer rates were 0.22% and 0.10%， respectively. And only β-eudesmol was detected in the freeze-dried powder with the average transfer rate of 8.37%. The results of cluster analysis and PCA showed that there are obvious differences in the types and contents of chemical components between the standard decoction concentrate and freeze-dried powder. ConclusionThe quality value transmitting between bran-processed A. lancea and its standard decoction concentrate and freeze-dried powder is stable， and if the freeze-dried powder is selected as the reference material of dispensing granules， appropriate amount of volatile oil should be added back to make it consistent with the quality of the standard decoction concentrate.

Objective:To explore the mediating effect of self-regulation fatigue between acceptance of hearing impairment and work withdrawal behavior in young and middle-aged patients with sudden deafness, so as to provide reference for the formulation of intervention measures for job withdrawal behavior.Methods:A cross-sectional survey was conducted to facilitate the selection of 326 young and middle-aged patients with sudden deafness who were treated in the Department of Otolaryngology, Head and Neck Surgery in the First Affiliated Hospital and the Second Affiliated Hospital of Air Force Military Medical University of the Chinese PLA from February 2021 to January 2022. The survey was carried out by general information questionnaire, the Revised Acceptance Disability Scale, the Self-Regulatory Fatigue Scale, and the Work Withdrawal Behavior Scale. Structural equation model method was used to analyze the mediating effect.Results:The acceptance of hearing impairment score in young and middle-aged patients with sudden deafness was (59.82 ± 10.99) points, the self-regulation fatigue score was (60.38 ± 8.84) points, and the work withdrawal behavior score was (39.06 ± 6.51) points. Self-regulation fatigue was negatively correlated with acceptance of hearing impairment ( r=-0.541, P<0.01). Work withdrawal behavior was negatively correlated with acceptance of hearing impairment ( r=-0.488, P<0.01), and was positively correlated with self-regulation fatigue ( r=0.587, P<0.01). Self-regulation fatigue played a partial mediating effect between the acceptance of hearing impairment and work withdrawal in young and middle-aged patients with sudden deafness, and the mediating effect ratio was 56.30%. Conclusions:The acceptance of hearing impairment can not only directly affect the work withdrawal behavior of young and middle-aged patients with sudden deafness, but also indirectly affect their work withdrawal behavior through self-regulation fatigue. Medical staff should pay attention to the internal relationship between the acceptance of hearing impairment, self-regulation fatigue and work withdrawal behaviors, so as to improve the acceptance of hearing impairment of patients, relieve their self-regulation fatigue, and avoid the occurrence of work withdrawal behaviors.

Objective:To construct a practical education training quality evaluation system that can monitor the entire training process for the master of public health, and to provide a basis for improving the public health education system.Methods:Based on the survey of the current status of the master of public health, combined with the literature survey, the focus group discussion and the expert forum, an evaluation system was established, and the weight coefficient of each index was determined by the analytic hierarchy process (AHP). All data were entered by Excel double-person, and matlabR2018a was used to calculate the weight, and determine the maximum characteristic root of the matrix, consistency index and consistency ratio.Results:The evaluation index system consisted of 7 first-level indicators and 24 second-level indicators. The average authority coefficient of 32 experts was 0.791. The top three items with the highest weight in the first-level indicators were mentor guidance (0.213), professional practice (0.157) and scientific research topics (0.149). The weight coefficient consistency ratio ( CR) was 0.040, showing that the consistency test passed ( CR<0.1). Conclusion:The educational quality evaluation system of the master of public health constructed by the institute is scientific, and the weight of the evaluation index reflects the focus of the postgraduate training process of the master of public health, which can provide a reference for improving the quality of public health professionals.

With continuous discovery of tumor immune targets and continuous changes in antibody research and development technology, antibody drugs are becoming more and more widely used in clinical practice. However, some targets are not only expressed on tumor cells, but also on red blood cells. Therefore, the clinical application of antibodies against the corresponding targets may interfere with the detection of blood transfusion compatibility, resulting in difficulty in blood matching or delay of blood transfusion. This consensus summarizes the current solutions for the interference of CD38 monoclonal antibody (CD38 mAb) in transfusion compatibility testing. After analyzing the advantages and disadvantages of different methods, polybrene and sulfhydryl reducing agents [dithiothreitol (DTT) or 2-mercaptoethanol (2-Me)], as a solution for CD38 mAb interference in blood compatibility testing, are recommended for Chinese patients, so as to eliminate blood transfusion interference produce by CD38 mAb and further provide a pre-transfusion workflow for clinicians and technicians in Department of Blood Transfusion.