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.

"Weibing" is a fundamental concept in traditional Chinese medicine (TCM), representing a transitional state characterized by diminished self-regulatory abilities without overt physiological or social dysfunction. This perspective delves into the biological foundations and quantifiable markers of Weibing, aiming to establish a research framework for early disease intervention. Here, we propose the "Health Quadrant Classification" system, which divides the state of human body into health, sub-health, disease-susceptible state, and disease. We suggest the disease-susceptible stage emerges as a pivotal point for TCM interventions. To understand the intrinsic dynamics of this state, we propose laboratory and clinical studies utilizing time-series experiments and stress-induced disease susceptibility models. At the molecular level, bio-omics technologies and bioinformatics approaches are highlighted for uncovering intricate changes during disease progression. Furthermore, we discuss the application of mathematical models and artificial intelligence in developing early warning systems to anticipate and avert the transition from health to disease. This approach resonates with TCM's preventive philosophy, emphasizing proactive health maintenance and disease prevention. Ultimately, our perspective underscores the significance of integrating modern scientific methodologies with TCM principles to propel Weibing research and early intervention strategies forward.

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.

Background:The diversity and function of gut microbiota have been regarded as crucial factors affecting human health.With the advances in genetics and epidemiology,especially the application of Mendelian randomization analysis,a novel perspective has been provided for profoundly uncovering the causal relationship between gut microbiota and duodenal ulcer.Aims:To investigate the causal relationship between gut microbiota and duodenal ulcer through two-sample Mendelian randomization analysis.Methods:Genetic variation samples of the gut microbiota were screened from the MiBioGen database.Genetic loci related to duodenal ulcer were selected as instrumental variables from genome-wide association study.The inverse-variance weighted method,weighted median method,and MR-Egger regression analysis were used to assess the causal relationship between gut microbiota and duodenal ulcer.Tests for heterogeneity and horizontal pleiotropy were conducted to ensure the stability of the results.Results:Bacteroides(OR=0.998,95%CI:0.996-1.000,P=0.014),Prevotella_7(OR=0.999,95%CI:0.998-1.000,P=0.043)and Terrisporobacter(OR=0.998,95%CI:0.997-1.000,P=0.029)exhibited negative causal relationship with duodenal ulcer,while Bifidobacterium(OR=1.001,95%CI:1.000-1.003,P=0.046),Lachnoclostridium(OR=1.002,95%CI:1.001-1.004,P=0.007)and Olsenella(OR=1.001,95%CI:1.000-1.002,P=0.018)presented positive causal relationship with duodenal ulcer.The sensitivity analysis indicated that the influences of heterogeneity and horizontal pleiotropy on the causal relationship could be excluded.Conclusions:The two-sample Mendelian randomization analysis revealed that Bacteroides,Prevotella_7 and Terrisporobacter were protective factors for duodenal ulcer,while Bifidobacterium,Lachnoclostridium and Olsenella were risk factors.

Objective To elucidate the bidirectional causal relationship between lipid profiles and colorectal cancer(CRC)by using the two-sample and two-step Mendelian randomization(MR)methods,and to explore the mediating role and proportion of immune cells as intermediary factors.Methods The pooled statistical data related to the study were screened,and 179 lipids and CRC were analyzed using two-sample and two-step MR with the inverse variance weighted method.Simultaneously,the causal effect was verified via Bayesian weighted MR.Two-step MR analysis was conducted to determine whether a mediated effect was exerted on immune cell traits.Sensitivity,heterogeneity,and pleiotropy analyses were performed to verify the reliability of the study results.Results The causal relationship between nine lipid traits and CRC was preliminarily identified,and no reverse causal effect was found(P>0.05).The validity of the results was verified via Bayesian weighted MR(P<0.05).Twenty-seven types of immune cells were suggested to exert a causal effect on CRC.The causal effect of phosphatidylcholine(O-18:2_20:4)on CRC was determined via mediation analysis(OR:0.8579,95% CI=0.7395-0.9952,P=0.0429).The CD127-mediated proportion on CD45RA+CD4+T cells was 9.14% (β=-0.1052,P=0.0155).Conclusion A causal relationship exists between lipid traits and CRC,and the intervention of CD127 on CD45RA+CD4+T cell helps phosph-atidylcholine reduce the risk of CRC.

BACKGROUND:The development of steroid-induced osteonecrosis of the femoral head is a complex process involving multiple mechanisms.There is still no standard therapeutic drug for early intervention of this disease.Current studies have shown that baicalein has various pharmacological activities such as regulating lipid metabolism,bone metabolism,apoptosis and anti-oxidative stress,which provides an idea for the prevention and treatment of steroid-induced osteonecrosis of the femoral head. OBJECTIVE:To observe the preventive effect of baicalein against steroid-induced osteonecrosis of the femoral head and to investigate its possible mechanism. METHODS:Thirty-six 10-week-old male Sprague-Dawley rats were randomly divided into three groups(n=12 per group):blank control group,model group,and baicalein intervention group.In the model group and baicalein intervention group,intraperitoneal lipopolysaccharide and intramuscular injection of methylprednisolone sodium succinate were performed for modeling,while normal saline was used as a substitute for the modeling drug in the blank control group.Baicalein 300 mg/kg was administered by gavage(once a day for 6 weeks)at the time of initial intramuscular glucocorticoid injection in the baicalein intervention group,and baicalein was replaced by normal saline in the other two groups.The serum level of malondialdehyde in rats was detected at 2 weeks of the experiment.Blood lipid indicators and bone formation metabolic markers were detected at 6 weeks of the experiment,the histomorphometric changes of the femoral head were analyzed by hematoxylin-eosin staining,anti-tartaric acid phosphatase staining and TUNEL staining,and the femoral head was subjected to Micro-CT scanning and three-dimensional reconstruction of the bone in order to analyze the alterations of bone tissue structure and parameters. RESULTS AND CONCLUSION:The serum levels of malondialdehyde,triglyceride,β-collagen type Ⅰ carboxy-terminal peptide were increased and the serum levels of bone specific alkaline phosphatase and pre-collagen type Ⅰ amino-terminal peptide were decreased in the model group compared with the blank control group(P＜0.05).The serum level of malondialdehyde decreased in the baicalein intervention group compared with the model group(P＜0.05),but there was no significant difference between the baicalein intervention group and blank control group(P＞0.05).The serum level of triglyceride was higher in the baicalein intervention group than the blank control group(P＜0.05),but had no significant difference between the baicalein intervention group and model group(P＞0.05).There were also no significant differences in the levels of bone specific alkaline phosphatase and β-collagen type Ⅰ carboxy-terminal peptide between the baicalein intervention group and the other two groups(P＞0.05).The serum level of the baicalein intervention group was lower in the baicalein intervention group than the blank control group(P＜0.05)but had no significant difference between the baicalein intervention group and model group(P＞0.05).Histomorphological analysis of the femoral head showed that the rate of bone empty lacuna,osteoclast counting and cell apoptosis rate in the femoral head of model group rats were significantly higher than those of the other two groups(P＜0.05).There was a significant increase in the number of adipocytes in the bone marrow cavity of the femoral head,bone trabeculae were thinned and sparsely arranged with more disruptions in the continuity.The incidence of osteonecrosis was higher in the model group(75%)than in the baicalein intervention group(25%;bilateral and unilateral exact significance results were both 0.05).There was also an increase in the number of adipocytes in the bone marrow cavity of the femoral head in the baicalein intervention group,and the trabecular changes were roughly similar to those in the model group.Micro-CT results showed that bone volume fraction,trabecular thickness,trabecular number,and bone mineral density decreased and trabecular separation increased in the model group compared with the blank control group(P＜0.05).Overall significant bone mass loss was observed in the model group.Bone tissue parameters in the baicalein intervention group were significantly improved than those in the model group,which were reflected in bone volume fraction,trabecular thickness and trabecular separation(P＜0.05),and trabecular number and bone mineral density had no significant difference between the baicalein intervention group and blank control group(P＞0.05).Although baicalein failed to significantly ameliorate dyslipidemia and promote bone formation in rats with steroid-induced osteonecrosis of the femoral head,it could reduce the incidence of steroid-induced osteonecrosis of the femoral head by reducing oxidative stress damage,decreasing cell apoptosis,inhibiting osteoclasts,suggesting its effectiveness in the early prevention of steroid-induced osteonecrosis of the femoral head.

Background:The diversity and function of gut microbiota have been regarded as crucial factors affecting human health.With the advances in genetics and epidemiology,especially the application of Mendelian randomization analysis,a novel perspective has been provided for profoundly uncovering the causal relationship between gut microbiota and duodenal ulcer.Aims:To investigate the causal relationship between gut microbiota and duodenal ulcer through two-sample Mendelian randomization analysis.Methods:Genetic variation samples of the gut microbiota were screened from the MiBioGen database.Genetic loci related to duodenal ulcer were selected as instrumental variables from genome-wide association study.The inverse-variance weighted method,weighted median method,and MR-Egger regression analysis were used to assess the causal relationship between gut microbiota and duodenal ulcer.Tests for heterogeneity and horizontal pleiotropy were conducted to ensure the stability of the results.Results:Bacteroides(OR=0.998,95%CI:0.996-1.000,P=0.014),Prevotella_7(OR=0.999,95%CI:0.998-1.000,P=0.043)and Terrisporobacter(OR=0.998,95%CI:0.997-1.000,P=0.029)exhibited negative causal relationship with duodenal ulcer,while Bifidobacterium(OR=1.001,95%CI:1.000-1.003,P=0.046),Lachnoclostridium(OR=1.002,95%CI:1.001-1.004,P=0.007)and Olsenella(OR=1.001,95%CI:1.000-1.002,P=0.018)presented positive causal relationship with duodenal ulcer.The sensitivity analysis indicated that the influences of heterogeneity and horizontal pleiotropy on the causal relationship could be excluded.Conclusions:The two-sample Mendelian randomization analysis revealed that Bacteroides,Prevotella_7 and Terrisporobacter were protective factors for duodenal ulcer,while Bifidobacterium,Lachnoclostridium and Olsenella were risk factors.

Objective: To analyze the survival time of people living with HIV/AIDS and related influencing factors in Sichuan province during 1991-2017. Methods: A retrospective cohort study was conducted to analyze the data of 143 988 HIV/AIDS cases. The data were collected from Chinese HIV/AIDS Comprehensive Information Management System. Life table method was used to calculate the survival proportion of the cases, and Cox proportion hazard regression model was used to identify the factors related with survival time. Results: Among 143 988 HIV/AIDS cases a total of 30 420 cases died of AIDS related diseases (21.1%) and the average survival time was 11.51 years (95%CI: 11.39-11.64). Multivariate Cox regression analysis showed that the influencing factors for the survival of HIV/AIDS cases were gender (male vs. female, HR=1.35, 95%CI: 1.32-1.40), education level (primary school or below vs. junior middle school: HR=1.15, 95%CI: 1.12-1.18), ethnic group (Han vs. other ethnic groups, HR=1.46, 95%CI: 1.41-1.52), occupation (farmer vs. other occupations: HR=1.26, 95%CI: 1.22-1.29), age (≥55 years old vs. 15-24 years old: HR=3.18, 95%CI: 3.02- 3.36), disease phase (AIDS vs. HIV infection: HR=1.44, 95%CI: 1.39-1.48), antiretroviral therapy (ART) (receiving ART vs. receiving no ART: HR=0.20, 95%CI: 0.19-0.20), and CD₄⁺T cell counts at diagnosis (>500 cells/μl vs.<200 cells/μl: HR=0.42, 95%CI: 0.40-0.45). Conclusions The average survival time of HIV/AIDS cases was 11.51 years in Sichuan during 1991- 2017. The risk factors for the survival of the cases were male, education level of primary school or below, Han ethnic group, farmer, old age at diagnosis, disease phase, The protective factors for the survival of HIV/AIDS cases were receiving ART and higher CD₄⁺ T cell counts at diagnosis.