Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.

Objective:To propose a deep learning（DL）-based ultrasound imaging auxiliary tool for automatic segmentation and recognition of the brachial plexus（BP），and to enhance the accuracy and safety of clinical procedures.Methods:It was a multicenter study that collected 773 healthy subjects from Peking University Third Hospital and its branch campuses，the Third Medical Center of the Chinese PLA General Hospital，and Shanghai Eighth People's Hospital between August 2024 and February 2025. Brachial plexus（BP）images in the interscalene groove were captured used high-frequency ultrasound by senior sonographers，a dataset comprising 1 289 standardized images were constructed and the improved model（CHA-TransUNet）was trained. The test set was input into 6 different models（CHA-TransUNet，R50-Unet，TransUnet，SegFormer，SwinUnet，MISSFormer）for segmentation. Segmentation accuracy was evaluated using metrics including the Dice similarity coefficient（DSC），95% Hausdorff distance（HD95）and mean intersection over union（mIoU），and was compared with the segmentation results of 3 ultrasound physicians with varying experience levels（junior physicians and senior physicians）to validate the model's segmentation efficacy.Results:The CHA-TransUNet model established based on a dataset of 1 289 standardized images achieved segmentation results for the BP with a DSC of 90.15%，mIoU of 91.02%，and HD95 of 8.08. Its accuracy was higher than other mainstream models（DSC：90.15% vs. 87.60%，87.77%，81.35%，84.78%，84.55%），significantly better than junior physicians（DSC：90.15% vs. 68.73%， Z=-127.76， P<0.001），and approached the level of senior physician（DSC：90.15% vs. 86.15%， Z=-31.33， P=0.549）. The model demonstrated superior boundary recognition in complex anatomical structures（e.g.，C6/C7 nerve roots）compared to ultrasound physicians（junior and senior）（HD95：8.08 vs. 26.34，17.44，56.80）. Conclusions:This study proposes an analysis model for BP ultrasound images，CHA-TransUNet. This model achieves segmentation and recognition of the BP with relatively complex pathways and structures. The model exhibits high accuracy and stability，outperforming current mainstream network models and junior physicians while approaching the performance level of senior physicians. It assists junior physicians or trainees in more accurately identifying and localizing the BP.

Objective:To construct a thyroid nodule segmentation model using ultrasound dynamic images and explore its potential for assisting in the screening of thyroid nodules.Methods:A total of 126 patients with thyroid nodules（comprising 150 nodules）who were diagnosed and treated at Xuzhou Cancer Hospital from April 2024 to December 2024 were prospectively enrolled. Two-dimensional ultrasound was performed to capture short-axis and long-axis video images of thyroid nodules，forming a dynamic ultrasound image dataset. The dataset was divided into training，validation，and test sets in a ratio of 6∶1∶3. After the training loss curve converged，the model that performed well on the validation set was selected for testing. Three-fold cross-validation was employed for training and testing. All 300 ultrasound videos were divided into three subsets. In each experiment，two subsets were used as the training set，and one subset was used as the test set to evaluate the model's generalization ability. A collaborative spatiotemporal diffusion model was established based on the dynamic trends and tissue texture details of thyroid nodules. Six widely used segmentation metrics were employed to evaluate the model's application capabilities.Results:The study included 126 patients with 150 thyroid nodules，300 dynamic ultrasound images，and video lengths of 3-4 seconds per nodule，resulting in 12 312 segmented images. The size of the thyroid nodules was（10.7 ± 10.6）mm（transverse diameter）×（8.4 ± 6.3）mm（anteroposterior diameter）. Among the nodules，62（41.3%）had clear boundaries，while 88（58.7%）had indistinct boundaries；61（40.7%）exhibited regular shapes，while 89（59.3%）were irregular；66（44.0%）had a taller-than-wide aspect ratio；and 70（46.7%）showed microcalcifications. The collaborative diffusion model based on dynamic ultrasound image segmentation achieved the following scores：a Jaccard score of（69.22 ± 0.03）%，a Dice score of（79.16 ± 0.18）%，a Precision score of（86.70 ± 0.17）%，a Recall score of（77.82 ± 0.04）%，an Sα score of（85.26 ± 0.01）%，and an Eθmn score of（90.58 ± 0.17）%. Compared to other models，this model demonstrated significant improvements across all evaluation metrics，achieving the highest values in each metric with increments of over 8% and 1%，respectively. Conclusions:The collaborative diffusion model with a dynamic controller，constructed based on dynamic ultrasound images of thyroid nodules，demonstrates excellent performance in ultrasound image segmentation. It improves the accuracy of thyroid nodule screening，thereby providing a valuable auxiliary diagnostic tool for clinical practice.

Objective:To propose a deep learning（DL）-based ultrasound imaging auxiliary tool for automatic segmentation and recognition of the brachial plexus（BP），and to enhance the accuracy and safety of clinical procedures.Methods:It was a multicenter study that collected 773 healthy subjects from Peking University Third Hospital and its branch campuses，the Third Medical Center of the Chinese PLA General Hospital，and Shanghai Eighth People's Hospital between August 2024 and February 2025. Brachial plexus（BP）images in the interscalene groove were captured used high-frequency ultrasound by senior sonographers，a dataset comprising 1 289 standardized images were constructed and the improved model（CHA-TransUNet）was trained. The test set was input into 6 different models（CHA-TransUNet，R50-Unet，TransUnet，SegFormer，SwinUnet，MISSFormer）for segmentation. Segmentation accuracy was evaluated using metrics including the Dice similarity coefficient（DSC），95% Hausdorff distance（HD95）and mean intersection over union（mIoU），and was compared with the segmentation results of 3 ultrasound physicians with varying experience levels（junior physicians and senior physicians）to validate the model's segmentation efficacy.Results:The CHA-TransUNet model established based on a dataset of 1 289 standardized images achieved segmentation results for the BP with a DSC of 90.15%，mIoU of 91.02%，and HD95 of 8.08. Its accuracy was higher than other mainstream models（DSC：90.15% vs. 87.60%，87.77%，81.35%，84.78%，84.55%），significantly better than junior physicians（DSC：90.15% vs. 68.73%， Z=-127.76， P<0.001），and approached the level of senior physician（DSC：90.15% vs. 86.15%， Z=-31.33， P=0.549）. The model demonstrated superior boundary recognition in complex anatomical structures（e.g.，C6/C7 nerve roots）compared to ultrasound physicians（junior and senior）（HD95：8.08 vs. 26.34，17.44，56.80）. Conclusions:This study proposes an analysis model for BP ultrasound images，CHA-TransUNet. This model achieves segmentation and recognition of the BP with relatively complex pathways and structures. The model exhibits high accuracy and stability，outperforming current mainstream network models and junior physicians while approaching the performance level of senior physicians. It assists junior physicians or trainees in more accurately identifying and localizing the BP.

Objective:To analyze the correlation between the skin temperature changes in the radiation area and the occurrence of radiodermatitis during postoperative radiotherapy for female breast cancer and to explore the application value of skin temperature monitoring in the early warning of radiodermatitis risks.Methods:A total of 103 patients who received three-dimensional conformal radiotherapy after radical mastectomy in the Fourth Hospital of Hebei Medical University were continuously enrolled from May to November, 2022 in this study. Their skin temperature in the radiation area and radiodermatitis were recorded weekly. The relationships between relative skin temperature differences and different grades of radiodermatitis were determined. The optimal cut-off values for grade ≥ radiodermatitis were calculated, and the predictive effect was evaluated using the receiver operating characteristic (ROC) curve. Furthermore, the radiodermatitis risks under different skin temperatures were compared using binary logistic regression.Results:There was a positive correlation between the skin temperature in the radiation field and the grade of radiodermatitis. The optimal cut-off values for the average relative skin temperature difference of the chest wall (under 40 Gy/20 fractions), the maximum relative skin temperature difference of the chest wall (under 40 Gy/20 fractions), and the relative skin temperature difference of the supraclavicular block (under 30 Gy/15 fractions) were 0.45℃, 0.55℃, 0.15℃, respectively. The patients were divided into low- and high-risk groups based on the optimal cut-off values (0.45℃, 0.55℃, and 0.15℃). Binary logistic regression result showed that the risks of grade ≥ 2 radiodermatitis in the high-risk group were 5.71, 4.29, and 5.15 times those in the low-risk group, respectively ( OR = 5.71, 95% CI 1.81-17.99, P = 0.003; OR = 4.29, 95% CI 1.65-11.12, P = 0.003; OR = 5.15, 95% CI 2.16-12.31, P < 0.001). Conclusions:Skin temperature monitoring using medical infrared thermometers can be used to effectively predict the occurrence of grade ≥ 2 radiodermatitis. The skin temperature changes in the radiotherapy area should be closely observed. The risk of grade ≥ 2 radiodermatitis will increase when the mean and maximum relative temperature differences of the chest wall increase by 0.45℃ and 0.55℃, respectively under 40 Gy/20 fractions of radiotherapy or when the relative temperature differences of the supraclavicular block increases by 0.15℃ under 30 Gy/15 fractions of radiotherapy.

Objective: To develop and evaluate a beads-based light-initiated chemiluminescent assay (LICA) for quantitation of cow milk component (Bos d 5) specific IgG 4 antibody in human serum. Methods: The sIgG 4 -LICA was performed by incubated serum samples with biotinylated allergens, emission beads coated with mouse anti-human IgG 4 antibody and streptavidin-coated sensitizer beads. The reaction conditions of sIgG 4 -LICA were optimized and the analytical performance was evaluated. Results: The precision of intra-assay, within-day and inter-assay (coefficient of variation) were 1.78% to 3.13%, 6.65% to 8.41% and 7.94% to 12.30%, respectively. The functional sensitivity of this assay was 4.71 ng/mL. For the linear range, the sIgG 4 -LICA had a good linear relationship within the range between 28.13 and 1 800 ng/mL, and the linear regression equation was Y=0.98X-1.31(r 2 =0.997). Maximum dilution limit was 1∶64. The disturbing rates measured by adding hemoglobin, triacylglycerol, total bilirubin, acid resistance and biotin to human sera with different concentrations of Bos d 5 sIgG 4 were from -6.38% to 8.60%. Conclusions The sIgG 4 -LICA introduced in this study was demonstrated to have effective performance for quantitation of allergen-specific IgG 4 and can meet the need of clinical requirement.

The " Trinity" management model of refined management, PDCA cycle and quality control circle was introduced into operating room ( OR ) management at our hospital since 2017. This practice aims to improve the OR process with refined management, elevate management practice with PDCA cycle, and improve detailed efficiency with quality control circle. 2017 witnessed a significant increase of the hospital in the number of surgical procedures, the punctuality rate of anesthesia, and the punctuality rate of the first surgery, as well as OR turnaround times than 2016. This model plays an important role in improving the efficiency of the OR, thus raising business revenue of the hospital.

Objective To develop a competitive immunoassay for quantitative determination of total immunoglobin E (tIgE) in human serum based on light-initiated chemiluminescent assay (LICA).Methods The LICA-tIgE assay was performed by incubating serum samples or calibrator with anti-human IgE antibody-coated chemiluminescet beads,biotinylated human IgE and streptavidin-coated sensitizer beads.The working conditions of this assay were optimized,analytical performance was detected and the correlation of tIgE results between LICA and Beckman Coulter IMMAGE 800 was evaluated.Results The precision of intra-assay and inter-assay (coefficient of variation) ranged from 5.50％ to 7.73％ and 6.45％ to 9.90％,respectively.The functional sensitivity of this assay was 12.65 IU/mL.The recovery rates measured by adding IgE calibrators to human sera with different IgE concentrations were ranged from 104.15％ to 109.37％.The disturbing rates measured by adding total bilirubin,hemoglobin and triacylglycerol to human sera with different IgE concentrations were ranged from-4.49％ to 8.46％.Also,the tIgE results of 111 patients measured by LICA correlated well with those by Beckman Coulter IMMAGE 800 (r2 =0.959).Conclusion LICA developed in this study for detecting tIgE of human serum showed effective perfomance and could meet the basic requirements of clinical diagnostic reagents.

Objective To explore the relationship of human papilloma virus (HPV) genotype and loading dose with development of cervical intraepithelial neoplasia (CIN) or squamous cell carcinoma of the cervix ( SCC),and explore the relationship of HPV genotype and CIN or SCC.Methods One hundred and twenty four patients in Sun Yat-sen Memoral Hospital of Sun Yat-sen University with CIN or SCC from September 2005 to December 2010 were selected in this study.HPV DNA was detected by Hybrid capture Ⅱand flow-through hybridization and gene chip.The relationship between the infection of HPV and CIN or SCC was analyzed.The influencing factors of CIN or SCC were analyzed by logistic regression.Results The total detection rate of HPV was 75.8％,and it was 44.4％,70.0％,95.7％ and 76.2％ in CIN Ⅰ,CIN Ⅱ,CIN Ⅲ and SCC group,respectively.The detection rate of HPV in high-grade lesion group ( 84.5％ ) was higher than low-grade lesion group(44.4％ ).The median of HPV load decreased in order as CIN Ⅲ,SCC,CIN Ⅱ and CIN Ⅰgroup.Infection of multi-genotypes or single genotype of high-risk HPV accounted for 97.9％.In logistic regression,HPV loading dose had significant influence on degree of cervical lesion.Conclusions Infection of HPV is a main etiological factor for SCC.There is some kind of correlation between HPV loading dose and development of SCC.

Objective To find out the requirement and to evaluate the effect of post-abortion counseling and education (PACE) among unmarried abortion adolescents.Methods The subjects of the study were unmarried adolescents from 10 to 24 years of age who wanted induced abortion in the Second Affiliated Hospital of Sun Yat-sen University from December 2007 to April 2008.Totally 122 subjects received the intervention of PACE were considered as intervention group.Meanwhile,67 subjects refused the intervention of PACE were considered as no intervention group.Two groups were both investigated the requirements of PACE before abortion and were followed-up at one year after abortion.Results 97.4% (184/189) of 189 unmarried abortion adolescents were willing to receive PACE,48.1% (91/189) of them hoped to receive PACE when saw the doctor,72.0% (136/189) of them required face-to-face counseling during PACE.During the year after abortion,74% (57/77) cases in intervention group and 24% (10/41) cases in no intervention group took effective contraception (P< 0.01 ),while 1% (1/77) of intervention group and 10% (4/41) of no intervention group had unwanted pregnancy.There were significant different for the rate of unwanted pregnancy between two groups (P=0.034).Conclusion For unmarried abortion adolescents,the intervention of PACE may markedly increase the rate of effective contraception used and decrease the rate of another unwanted pregnancy.