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 To analyze the serum of patients with pancreatic cancer by fourier transform infrared spectroscopy(FTIR),explore the characteristic spectral parameters related to pancreatic cancer,and evaluate its potential clinical diagnostic value.Methods Serum samples were collected from 100 patients diagnosed with pancreatic cancer and 92 healthy volunteers at Chongming Hospital Affiliated to Shanghai Health Medical College from August 2022 to July 2023.These samples underwent FTIR and principal component analysis(PCA)to assess spectral differences between the two cohorts.The diagnostic potential of the serum spectra in distinguishing pancreatic cancer patients from healthy individuals was further evaluated using machine learning techniques,specifically support vector machine(SVM),k-nearest neighbor(kNN),and linear discriminant analysis(LDA)as classification methods.The diagnostic efficacy across various thresholds was evaluated using the receiver operating characteristic(ROC)curve.Results The findings indicate that the peak positions within the 1 090～1 070cm-1(1 076.537±15.183cm-1 vs 1 081.061±4.043cm-1),1 420～1 380 cm-1(1 399.958±1.508cm-1 vs 1 400.500±1.782cm-1),2 990～2 950cm-1(2 940.167±15.287cm-1 vs 2 945.124±7.498cm-1)and 3 500～3 000 cm-1(3 293.155±3.096cm-1 vs 3 294.893±2.582cm-1)range in the serum of individuals with pancreatic cancer exhibited a significant blue-shift compared to the healthy group and was statistically significant(t=2.265～4.236,all P<0.05),suggesting alterations in the structures of proteins,lipids and nucleic acids.Furthermore,a statistically significant disparity in peak absorption was observed between the group of patients with pancreatic cancer and the healthy group within the spectral ranges of 1 700～1 600cm-1(0.918±0.012cm-1 vs 0.858±0.021cm-1)and 3 500～3 000 cm-1(0.766±0.096cm-1 vs 0.804±0.090cm-1)(t=-24.031,2.830,all P<0.05),indicating that the protein concentration changes.PCA results showed that the PC2 axis was clearly separated,which could distinguish serum samples from patients with pancreatic cancer.Utilizing a machine learning model to differentiate the serum spectra of patients with pancreatic cancer from those of healthy controls,the sensitivity,the spesitivity,the specificity and accuracy of linear discriminant analysis(LDA)classification method were 93.2%,97.3%and 95.8%,respectively.The area under curve(AUC)as determined by ROC analysis was 0.982.Conclusion Serum spectroscopy using FTIR combined with PCA and machine learning model can be a simple,minimally invasive and reliable diagnostic test for pancreatic cancer detection.

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.

Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has been recently identified as a key role in Parkinson's disease (PD) pathogenesis. In particular, lipid peroxidation-mediated ferroptosis is considered a key event leading to the death of dopaminergic neurons. This article reviews the role of lipid peroxidation-mediated ferroptosis in PD and its involved key signaling pathways, and explores the related targeted therapeutic strategies, with the aim of providing new ideas for targeted treatment of PD.

Objectiv To investigate an autosomal dominant non-syndromic hearing loss family pedigree com-prehensively,aiming to precisely define its clinical phenotypes and uncover the underlying molecular genetic etiolo-gy.Methods A detailed interrogation of the proband's medical history and family history was conducted.Physical examinations,audiological assessments and temporal bone CT scans were performed.Genomic DNA was extracted from the peripheral blood of the proband(Ⅳ-8)for whole-exome sequencing(WES).Subsequently,candidate vari-ants identified through WES were validated among family members using Sanger sequencing.Results There were 36 individuals in 4 generations in this family pedigree,showing autosomal dominant inheritance.Among them,16 individuals presented with progressive hearing loss.Audiological examinations were completed for 13 of them,re-vealing normal hearing in three individuals(Ⅲ-1,Ⅲ-1 1,Ⅳ-4)and bilateral symmetric hearing loss of varying se-verity in the remaining ten(Ⅱ-2,Ⅱ-4,Ⅱ-10,Ⅲ-4,Ⅲ-10,Ⅲ-13,Ⅲ-14,Ⅳ-1,Ⅳ-7,Ⅳ-8),and the degree of hearing loss was related to age.WES of Ⅳ-8 revealed that she carried the variant NM_199330.2(HOMER2):c.1064 A＞G(p.Ter354Trpext10),and Sanger sequencing verified the variation at this site.Peripheral blood samples of 18 individuals in this family were collected in total.All affected individuals(Ⅱ-2,Ⅱ-4,Ⅱ-10,Ⅲ-4,Ⅲ-9,Ⅲ-10,Ⅲ-13,Ⅲ-14,Ⅳ-1,Ⅳ-7,Ⅳ-8)carried the HOMER2 c.1064 A＞G variant,except for one young member(Ⅳ-6)who had not yet developed hearing loss.Unaffected individuals(Ⅱ-5,Ⅲ-1,Ⅲ-5,Ⅲ-11,Ⅳ-2,Ⅳ-4)lacked the variant,demonstrating complete cosegregation of genotype and phenotype.According to ACMG guide-lines,this variant was classified as likely pathogenic(PM2+PP1+PM4).Conclusion The c.1064 A＞G(p.Ter354Trpext10)variant of the HOMER2 gene is the molecular genetic etiology of this hereditary deafness family pedigree.

Hemophilia is a hereditary coagulation disorder, in which patients often suffer from joint dysfunction due to recurrent joint bleeding, with the knee joint being particularly susceptible to involvement, thereby significantly impairing their ability to walk.Gait analysis, as an objective, quantitative, and comprehensive assessment tool, can be employed to accurately evaluate the walking function of patients and provide a scientific basis for the rehabilitation management of individuals with hemophilia.With the deepening of medical research, the role of gait analysis in the rehabilitation management of hemophilia is increasingly being recognized.This review article summarizes the application of gait analysis in the rehabilitation management of hemophilia, including changes in gait parameters, kinematic and kinetic characteristics of joints in patients with hemophilia, as well as the relationships between these parameters and the severity of the disease and treatment outcomes in hemophilia patients, exploring the role of gait analysis in the rehabilitation management of hemophilia to better apply it in clinical practice.

Secondary osteoporosis is common in patients with early breast cancer, manifesting as low back pain, bone and joint symptoms, and osteoporotic fractures. Bisphosphonate and denosumab can reduce the incidence of fractures by minimizing bone loss, though they differ in efficacy, treatment course, and side effects. Patients should consider the pros and cons when selecting a drug. Recent studies also focus on decreasing the incidence of bone metastases. This article reviews recent advancements in the use of these two drugs for managing bone health in early breast cancer.

ObjectiveTo analyze the epidemiological characteristics of clustered vomiting and diarrhea outbreaks in Minhang District of Shanghai, to identify the influencing factors of outbreak scale and duration of epidemic, and to provide scientific evidence for further strengthening surveillance early-warning efforts in key settings and for optimizing prevention and control measures. MethodsThe data for describing epidemiological characteristics of clustered vomitting and diarrhea outbreaks in Minhang District from 2018 to 2023 were collected, multivariable logistic regression models were applied to analyze the influencing factors for epidemic scale,and Spearman rank correlation analyses were applied to analyze the factors duration. ResultsA total of 136 clustered vomiting and diarrhea outbreaks were reported in Minhang District from 2018 to 2023, all occurring in school settings, with an overall attack rate of 0.90%. The outbreaks exhibited distinct seasonality, predominantly occurring from October to December (43.38%) and March to May (32.35%). The primary settings were preschools (45.59%) and elementary schools (44.12%), with students accounted for the majority of cases (99.48%). The predominant clinical manifestation was vomiting (90.44%), with person-to-person contact being the primary transmission route (98.53%). Norovirus genogroup Ⅱ was identified as the main pathogen (71.32%). Standardized terminal disinfection of outbreak sites (OR=0.39, 95%CI=0.20‒0.74) and effective isolation of affected classes (OR=0.23, 95%CI=0.09‒0.57) were significant protective factors for reducing outbreak scale. Both response time (r=0.64, P<0.001) and the number of case generations (r=0.71, P<0.001) showed positive correlations with outbreak duration. ConclusionSchools are the key settings for the prevention and control of clustered vomiting and diarrhea outbreaks in Minhang District, with peak occurring in autumn and spring. Early detection, timely reporting, and prompt response to outbreaks are crucial. Strengthening school-based surveillance systems and standardizing outbreak management protocols are of particular importance.

ObjectiveTo analyze the reported cases of infectious diseases across different tiers of public medical and healthcare institutions in Minhang District, Shanghai from 2013 to 2023, to investigate the status and changes in reported infectious diseases in this district from a temporal, etiological, and demographic perspectives, so as to provide a scientific basis for the construction of a hierarchica early-warning surveillance system under the grading diagnosis and treatment model in medical institutions, as well as for optimizing sentinel surveillance at facilities of different levels. MethodsA retrospective analysis was performed using surveillance data from the China Disease Prevention and Control Information System in Minhang District from 2013 to 2023. Reported infectious diseases were categorized into three categories based on transmission routes: respiratory infectious diseases, intestinal infectious diseases, and sexually transmitted and blood borne infectious diseases. According to the implementation phase of the grading diagnosis and treatment policy, the research time was divided into four time periods: 2013‒2016, 2017‒2019, 2020‒2022, and 2023. The distribution and temporal changes of reported cases of infectious diseases were compared across community health service centers (CHCs), secondary hospitals, tertiary grade-A hospitals and tertiary grade-B hospitals. Chi-square test was used for univariate analysis of differences in the number of reported cases. Quantitative data with normal distribution were analyzed using parametric tests, otherwise, Kruskal⁃Wallis H tests were used. ResultsThe proportions of total reported cases of infectious diseases in medical institutions at all levels in Minhang District, Shanghai from 2013 to 2023 were 10.66% in CHCs, 9.10% in secondary hospitals, 64.95% in tertiary grade-B hospitals, and 15.29% in tertiary grade-A hospitals, with an overall decline and then rebound trend in the reported cases. After the implementation of grading diagnosis and treatment policy, the number of reported cases in CHCs and secondary hospitals showed a trend of first decreasing and then increasing, while that in tertiary grade-B hospitals showed a steady decreasing trend and that in tertiary grade-A hospitals showed an increasing trend. In terms of the research periods divided above, a total of 10 392 cases were reported in 2013‒2016 (70.34% from tertiary grade-B hospitals and 12.59% from CHCs), including 2 922 cases of respiratory infectious diseases, 1 241 cases of intestinal infectious diseases, and 6 229 cases of sexually transmitted and blood-borne infectious diseases. Between 2017 and 2019, a total of 6 967 cases were reported (73.49% from tertiary grade-B hospitals and 11.84% from tertiary grade-A hospitals), including 2 983 cases of respiratory infectious diseases, 279 cases of intestinal infectious diseases, and 3 705 cases of sexually transmitted and blood-borne infectious diseases. Between 2020 and 2022, a total of 4 599 cases were reported (69.92% from tertiary grade-B hospitals and 24.57% from tertiary grade-A hospitals), including 1 627 cases of respiratory infectious diseases, 123 cases of intestinal infectious diseases, and 2 849 cases of sexually transmitted and blood-borne infectious diseases. In 2023, a total of 4 648 cases were reported (35.20% from tertiary grade-B hospitals and 27.50% from tertiary grade-A hospitals), including 3 165 cases of respiratory infectious diseases, 69 cases of intestinal infectious diseases, and 1 414 cases of sexually transmitted and blood-borne infectious diseases. The proportion of reported cases from tertiary grade-B hospitals was the highest in all the four research periods, but exhibited an obvious decrease in 2023. The differences in the reported cases of infectious diseases with different transmission routes among medical institutions at all levels were statistically significant (χ²=3 225.628, P<0.05). The differences in the mean age of patients among medical institutions at all levels were statistically significant (H=1 325.927, P<0.05). ConclusionThere are significant differences in the number of reported cases of infectious disease in the medical institutions at different levels. Tertiary grade-B hospitals have historically dominated the number of reported cases, but its share has declined recently. Whereas, CHCs and tertiary grade-A hospitals have played an increasingly important role in the surveillance and early warning of respiratory and intestinal infectious diseases. Therefore, it is recommended to leverage the strengths of grading diagnosis and treatment to establish targeted sentinel sites and deploy specialized teams tailored to the epidemiological characteristics of specific disease categories.

"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.