OBJECTIVE: This study explored the job choice preferences of Center for Disease Prevention and Control (CDC) workers to provide CDC management information and recommendations for optimizing employee retention and motivation policies. METHODS: A discrete choice experiment was conducted in nine provinces across China. Seven key attributes were identified to analyze the job preferences of CDC workers. Mixed logit models, latent class models, and policy simulation tools were used. RESULTS: A valid sample of 5,944 cases was included in the analysis. All seven attributes significantly influenced the job choices of CDC workers. Heterogeneity analyses identified two main groups based on different levels of preference for attribute utility. Income-prioritizers were concerned with income and opportunities for career development, whereas bianzhi-prioritizers were concerned with bianzhi and welfare benefits. The policy simulation analysis revealed that income-prioritizers had a relatively higher sensitivity to multiple job preference incentives. CONCLUSION Income and bianzhi were the two key attributes influencing the job choices and retention preferences of CDC workers. Heterogeneity in job preferences was also identified. Based on the preference characteristics of different subgroups, policy content should be skewed to differentiate the importance of incentives.
China ; Humans ; Male ; Female ; Adult ; Centers for Disease Control and Prevention, U.S. ; Middle Aged ; Choice Behavior ; Career Choice ; Motivation

OBJECTIVE To evaluate the efficacy of oral and facial muscle functional training in treating adult obstructive sleep apnea(OSA)and to identify clinical indicators influencing treatment outcomes.METHODS Through a prospective cohort study,patients diagnosed with OSA in the study unit were recruited to undergo a 3-month myofunctional therapy,including soft palate-related muscles,tongue muscles,buccal muscles,and labial muscles in multiple muscle groups,once a day,five times a week,with the use of offline clinic guidance,and the APP program video follow up training for effective training.Data were collected on multiple dimensions including physical signs,sleep breathing monitoring parameters,and airway measurements from imaging studies.Treatment efficacy was assessed by comparing subjective and objective sleep indicators before and after training.Patients were categorized into effective and ineffective groups based on treatment outcomes.Differences in baseline clinical indicators between these groups were analyzed using univariate and multivariate regression analyses.RESULTS The study finally included 58 people,51 males and 7 females,age(38.36±8.96)years,BMI(27.14±3.68)kg/m2,AHI of the enrolled patients was reduced from(31.27±22.28)times/h pre-training to(26.27±21.38)times/h post-training,the minimum oxygen saturation was increased from(78.43±10.07)%to(80.50±10.06)%,snoring index decreased from(62.80±75.20)times/h to(36.40±43.19)times/h,and ESS score decreased from 7.00±5.31 pre-training to 5.50±3.17.By comparing the effective and ineffective groups,it was found that there was a statistically significant difference in the tongue position and ESS scores between the two groups(both P<0.05),while no significant differences were found in gender,age,neck circumference,posterior soft palate area,uvula area,posterior tongue area,or posterior epiglottic area(all P>0.05).Univariate logistic regression analysis indicated that tongue position,AHI,and ESS scores were factors affecting the efficacy of oral and facial muscle function training.Multivariate regression analysis revealed that AHI was an independent prognostic factor for this training in OSA patients.CONCLUSION Oral and facial muscle function training can improve both subjective and objective sleep breathing indices in OSA patients.Tongue position,AHI,and ESS scores may serve as prognostic factors for OSA treatment,aiding in guiding subsequent individualized intervention therapies.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

The malfunctions of Philips IQon Spectral CT System were introduced in terms of image ring artifact,failure in gantry staring and low speed in image reconstruction,with the causes being analyzed and the elimination measures put forward.References were provided for treating similar failures.

The malfunctions of Philips IQon Spectral CT System were introduced in terms of image ring artifact,failure in gantry staring and low speed in image reconstruction,with the causes being analyzed and the elimination measures put forward.References were provided for treating similar failures.

Objective To investigate the effect and mechanism of rhubarb Tangluo pill on liver injury in type 2 diabetic rats.Methods ZDF(fa/fa)rats were given high-fat diet to induce type 2 diabetes model,and were randomly divided into model group,positive control group(0.18 g·kg-1 metformin)and experimental-L,-M,-H groups(0.54,1.08 and 2.16 g·kg-1 rhubarb Tangluo pill),with 8 rats in each group.Eight ZDF(fa/+)rats were selected as control group.The control group and model group were given equal volume of pure water once a day for 12 weeks.An oral glucose tolerance test(OGTT)was performed after administration.Fasting blood glucose level,body mass and liver mass of rats were measured and liver index was calculated.The contents of glutamic-pyruvic transaminase(GPT),glutamic oxalacetic transaminase(GOT),triglyceride(TG)and total cholesterol(TC)in serum were detected.The histomorphologic changes of liver were observed by hematoxylin-eosin(HE)staining and Masson staining.The protein expression of phosphorylated insulin receptor substrate 1(p-IRS1),phosphorylated protein kinase B(p-Akt)and glucose transporter 4(GLUT4)were detected by Western blotting.Results After administration,the fasting blood glucose levels of control group,model group,positive control group and experimental-H group were(4.71±0.45),(29.9±2.97),(15.28±4.52)and(13.84±1.55)mmol·L-1,respectively;the liver index were 2.31±0.46,4.03±0.18,3.37±0.23 and 3.38±0.24;the relative expression level of p-IRS1 protein were 1.00±0.36,4.00±0.11,1.62±0.27 and 1.90±0.17,respectively;the relative expression levels of p-Akt protein were 1.00±0.25,0.21±0.04,0.73±0.15 and 0.54±0.04,respectively;GLUT4 protein relative expression levels were 1.00±0.11,0.40±0.08,0.86±0.04 and 0.70±0.06,respectively.Compared with the model group,the above indexes in the experimental-H group were statistically significant(P＜0.01,P＜0.05).Conclusion Rhubarb Tanglu pill can effectively improve glycolipid metabolism and liver injury in type 2 diabetes mellitus,and its mechanism may be related to the activation of IRS1/Akt signaling pathway.

Objective In this study,we analyzed the transcriptome sequences of Kupffer cells exposed to simulated microgravity for 3 d and conducted biological experiments to determine how microgravity initiates apoptosis in Kupffer cells. Methods Rotary cell culture system was used to construct a simulated microgravity model.GO and KEGG analyses were conducted using the DAVID database.GSEA was performed using the R language.The STRING database was used to conduct PPI analysis.qPCR was used to measure the IL1B,TNFA,CASP3,CASP9,and BCL2L11 mRNA expressions.Western Blotting was performed to detect the level of proteins CASP3 and CASP 9.Flow cytometry was used to detect apoptosis and mitochondrial membrane cells.Transmission electron microscopy was used to detect changes in the ultrastructure of Kupffer cells. Results Transcriptome Sequencing indicated that simulated microgravity affected apoptosis and the inflammatory state of Kupffer cells.Simulated microgravity improved the CASP3,CASP9,and BCL2L11 expressions in Kupffer cells.Annexin-V/PI and JC-1 assays showed that simulated microgravity promoted apoptosis in Kupffer cells.Simulated microgravity causes M1 polarization in Kupffer cells. Conclusion Our study found that simulated microgravity facilitated the apoptosis of Kupffer cells through the mitochondrial pathway and activated Kupffer cells into M1 polarization,which can secrete TNFA to promote apoptosis.

Objective To explore the application of the"learning by doing"learning theory and methods in the teaching of Obstetrics and Gynecology Nursing for undergraduate nursing students.Method By setting up an experimental group of 151 students and a control group of 152 students in the teaching of Obstetrics and Gynecology Nursing for undergraduate nursing students,practicing"learning by doing"and evaluating the teaching effect.Result The experimental group students held a positive attitude towards the implementation of"learning by doing"in the teaching of Obstetrics and Gynecology Nursing for undergraduate nursing students,with higher scores in both theoretical and skill exams than the control group(P＜0.05),and achieved good practical results.Conclusion By comparing the theoretical and skill exam scores of the experimental group and the control group,the experimental group had a higher average score than the control group(P＜0.05).The application of"learning by doing"in the teaching of Obstetrics and Gynecology Nursing for undergraduate nursing has improved students'self-learning ability and empowered their innovative and collaborative growth.

Objective To propose a method for classifying small bowel capsule endoscopy images by combining the Swin Transformer network with an improved Adapt-RandAugment data augmentation approach,aiming to enhance the accuracy and efficiency of small bowel lesion classification and recognition.Methods An Adapt-RandAugment data augmentation approach was formulated based on the RandAugment data enhancement sub-strategy and the principles of no feature loss and no distortion when enhancing small bowel capsule endoscopy images.In the publicly available Kvasir-Capsule dataset of small bowel capsule endoscopic images,the Adapt-RandAugment data augmentation approach was trained based on the Swin Transformer network,and the convolutional neural networks ResNet152 and DenseNet161 were used as the benchmarks to validate the combined Swin Transformer network and Adapt-RandAugment data augmentation approach for small bowel capsule endoscopy image classification.Results The proposed algorithm gained advantages over ResNet152 and DenseNet161 networks in the indicators,which had the macro average precision(MAC-PRE),macro average recall(MAC-REC),macro average F1 score(MAC-Fi-S)being 0.383 2,0.314 8 and 0.290 5 respectively,the micro average precision(MIC-PRE),micro average recall(MIC-REC)and micro average F1 score(MIC-Fi-S)all being 0.755 3,and the Matthews correlation coe-fficient(MCC)being 0.452 3.Conclusion The proposed small bowel capsule endoscopy image classification method based on Swin Transformer network and Adapt-RandAugment data augmentation approach behaves well in classified recognition efficiency and accuracy.[Chinese Medical Equipment Journal,2024,45(6):9-16]

MHNTs@PDA@ZIF-8 with rod-shaped core-shell structures was synthesized and used as sorbent in magnetic solid phase extraction(MSPE).MHNTs@PDA@ZIF-8-MSPE method coupled with gas chromatography-mass spectrometry(GC-MS)was employed to analyze sixteen kinds of polycyclic aromatic hydrocarbons(PAHs)in tea beverages.Vibrating sample magnetometer(VSM),Fourier transform infrared spectroscopy(FT-IR),X-ray diffraction(XRD),scanning electron microscopy(SEM)and nitrogen adsorption-desorption techniques were used to characterize the MHNTs@PDA@ZIF-8.The results demonstrated that the MHNTs@PDA@ZIF-8 exhibited significant magnetic properties and a large specific surface area.The experimental conditions that could affect MSPE were investigated,including adsorbent dosage,extraction time,desorption time,ionic strength,desorption solvent type,and desorption solvent volume.The optimal conditions were 10 mg of MHNTs@PDA@ZIF-8 as adsorbent,90 s under vortex extraction,and ultrasonic desorption for 60 s with 1 mL ofn-hexane.The sixteen kinds of PAHs showed good linearity in the concentration range of 5-500 μg/L(r2≥0.995).The limits of detection(S/N=3)and quantitation(S/N=10)were in the range of 0.1-0.8 μg/L and 0.3-2.6 μg/L,respectively.The recoveries of the method ranged from 60.9%to 114.7%,with relative standard deviations(n=3)ranging from 0.2%to 9.2%when the addition levels of sixteen kinds of PAHs were 10,50,and 100 μg/L.The method was simple,fast,sensitive and environmentally friendly,and suitable for detecting sixteen kinds of PAHs in tea beverages.