This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.

Objective:To study the comprehensive surgical treatment of brucellosis with chest wall cysts as the main manifestation.Methods:Retrospective analysis was made on the general information epidemiological characteristics, clinical manifestations, laboratory examinations, imaging examinations, treatment and outcomes of five patients with brucellosis mainly manifested by chest wall cysts admitted to the 948 Hospital of the People's Liberation Army from July 2019 to June 2022.Results:Among the 5 patients, there were 4 males and 1 female, aged between 23 and 64 years old, with a clear history of contact with cattle and sheep. The main clinical manifestation was painless cystic masses on the chest wall. Both the serum tiger red plate agglutination test (RBPT) and the test tube agglutination test (SAT) were positive. Four cases were infected with Brucella and one case was infected with Actinobacillus pleuropneumoniae (considered as Brucella infection based on the overall condition). All patients exhibited abnormal chest wall signals (manifesting as hypointense on T1-weighted imaging and hyperintense on T2-weighted imaging) on magnetic resonance imaging(MRI), and were ultimately diagnosed with brucellosis presenting predominantly as chest wall cysts. After complete removal of the chest wall cyst through surgery, a combination treatment of rifampicin capsules and doxycycline hyclate tablets was given for 6 weeks. There were no significant adverse reactions and the wound healed in one stage. During the postoperative follow-up period of 11 - 40 months, MRI reexamination demonstrated no evidence of chest wall cyst recurrence, and all SAT results were negative. Conclusions:Patients with brucellosis presenting as chest wall cysts are clinically rare and lack specific symptoms. Surgical resection of the affected lesion combined with early, standardized, combined, and full course antimicrobial therapy results in a good prognosis for the patient.

Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

Objective:To study the comprehensive surgical treatment of brucellosis with chest wall cysts as the main manifestation.Methods:Retrospective analysis was made on the general information epidemiological characteristics, clinical manifestations, laboratory examinations, imaging examinations, treatment and outcomes of five patients with brucellosis mainly manifested by chest wall cysts admitted to the 948 Hospital of the People's Liberation Army from July 2019 to June 2022.Results:Among the 5 patients, there were 4 males and 1 female, aged between 23 and 64 years old, with a clear history of contact with cattle and sheep. The main clinical manifestation was painless cystic masses on the chest wall. Both the serum tiger red plate agglutination test (RBPT) and the test tube agglutination test (SAT) were positive. Four cases were infected with Brucella and one case was infected with Actinobacillus pleuropneumoniae (considered as Brucella infection based on the overall condition). All patients exhibited abnormal chest wall signals (manifesting as hypointense on T1-weighted imaging and hyperintense on T2-weighted imaging) on magnetic resonance imaging(MRI), and were ultimately diagnosed with brucellosis presenting predominantly as chest wall cysts. After complete removal of the chest wall cyst through surgery, a combination treatment of rifampicin capsules and doxycycline hyclate tablets was given for 6 weeks. There were no significant adverse reactions and the wound healed in one stage. During the postoperative follow-up period of 11 - 40 months, MRI reexamination demonstrated no evidence of chest wall cyst recurrence, and all SAT results were negative. Conclusions:Patients with brucellosis presenting as chest wall cysts are clinically rare and lack specific symptoms. Surgical resection of the affected lesion combined with early, standardized, combined, and full course antimicrobial therapy results in a good prognosis for the patient.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective This study aims to explore the layout and optimization of management disciplines in"Double First-Class"Traditional Chinese Medicine(TCM)universities,providing talent support and management guidance for the devel-opment of TCM.Methods Based on an overview of the development of management disciplines in TCM universities,six"Doub-le First-Class"TCM universities were selected as research subjects.Data were collected and compared using web retrieval and lit-erature research methods.Results Management disciplines in TCM universities still face challenges,such as weak foundational infrastructure and difficulties in interdisciplinary integration,insufficient faculty and suboptimal curriculum systems,and a single teaching model with a disconnect between theory and practice.Conclusion This paper proposes targeted suggestions and strate-gies for optimizing the layout of management disciplines in TCM universities,including strengthening support for management dis-ciplines and deepening TCM management characteristics,optimizing curriculum design and enhancing faculty resources,and in-novating teaching models to promote the deep integration of theory and practice.

Objective:To study echinococcosis in the population and canine Echinococcus infection in Yushu City, Qinghai Province, and to explore the current epidemic situation and main transmission species of Echinococcus. Methods:In June 2023, a multi-stage sampling method was used to select 2 villages each in Shanglaxiu Township and Longbao Town, Yushu City, Qinghai Province. Each village included at least 100 permanent residents who had lived locally for at least 1 year and were 2 years old or older as the survey subjects. Enzyme-linked immunosorbent assay (ELISA) was used to detect serum antibodies against Echinococcus larvae in the population, and B-mode ultrasound was used for abdominal organ scanning. Meanwhile, on the main roads of Shanglaxiu Township and Longbao Town, canine feces were collected in designated areas at intervals. ELISA was used to detect the antigen of canine fecal Echinococcus, and PCR was used to detect the types of parasites ( Echinococcus multilocularis, Echinococcus granulosus and Echinococcus shiquicus). Results:A total of 511 residents were investigated in Yushu City, and the positive rate of serum Echinococcus larvae antibodies in the population was 26.22% (134/511), and the detection rate of echinococcosis B-mode ultrasound was 1.37% (7/511). Among them, the detection rates of B-mode ultrasound for cystic echinococcosis (CE) and alveolar echinococcosis (AE) were 1.17% (6/511) and 0.20% (1/511), respectively. The positive rate of Echinococcus antigen in 543 canine feces detected by ELISA was 12.89% (70/543). PCR was used to test 497 canine feces, and the detection rate of Echinococcus was 3.02% (15/497). Among them, the detection rate of Echinococcus multilocularis was higher than that of Echinococcus granulosus [2.82% (14/497) vs 0.20% (1/497)], and the difference was statistically significant (χ 2 = 11.44, P < 0.001). No Echinococcus shiquicus was detected. Conclusions:The positive rates of Echinococcus larvae antibodies in the population and canine Echinococcus antigen in Yushu City, Qinghai Province are both relatively high. There is a mixed epidemic of CE and AE, with Echinococcus multilocularis being the main species.

Objective:To establish the reference intervals (RIs) of systemic immune inflammatory index (SII), platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR) and monocyte to lymphocyte ratio (MLR) in healthy pregnant women in Henan province, China.Methods:A retrospective analysis was conducted on the data of the healthy pregnant women without a history of adverse pregnancy events who participated in health check-ups from August 2016 to February 2019. A total of 4 016 healthy pregnant women were selected for establishing RIs. Data from healthy adult control group were derived from the healthy adult cohort in Henan established earlier by our team, and the Propensity Score Matching analysis was used and 3 595 healthy adult women and 3 595 healthy pregnant women to compare the indicators between the two groups. The RIs of the above indicators were established using the indirect method with a 95% confidence interval. The Tukey Rule was used to identify and remove outliers. The RIs were stratified and grouped based on the differences in each indicator during the pregnancy: SII: 3 929 cases, including 712 in the first trimester, 1 947 in the second trimester, and 1, 270 in the third trimester; PLR: 3 927 cases, no grouping; NLR: 3 925 cases, including 712 in the first trimester and 3 213 in the second and third trimesters; LMR: 3 925 cases, including 723 in the first trimester, 1 942 in the second trimester, and 1 260 in the third trimester; MLR: 3 904 cases, including 721 in the first trimester, 1 928 in the second trimester, and 1 255 in the third trimester. After the RIs were established, another 396 healthy pregnant women without a history of adverse pregnancy events who participated in health check-ups from February to April 2019 were selected for the validation of the RIs.Results:SII, NLR, LMR, MLR, and PLR differ significantly between healthy adult women and healthy pregnant women. There were significant differences in SII, LMR, and MLR among the three trimesters ( P<0.05). NLR in the first trimester was significantly lower than that in the second and third trimesters ( P<0.05), while there was no significant difference between the second and third trimester ( P=0.124). PLR only showed significant differences between the second and third trimester ( P<0.05), while no significant differences were found among the other groups. Based on the above results, the stratified RIs of each index in healthy pregnant population were established and verified. SII: first trimester (341-1 426)×10 9/L, second trimester (437-1 680)×10 9/L, third trimester (379-1 580)×10 9/L; PLR: 73-215; NLR: first trimester 1.78-5.60, second and third trimester 2.21-6.74; LMR: first trimester 2.20-6.61, second trimester 1.85-5.42, third trimester 1.63-4.82; MLR: first trimester 0.14-0.42, second trimester 0.17-0.49, third trimester 0.18-0.55. The rejection rate of 396 cases was less than 10%. Conclusions:The RIs of SII, NLR, LMR, MLR and PLR for healthy pregnant women in Hernan province of China were established and validated, and4 could be used in clinical practice.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.