ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveTo systematically analyze the epidemiological characteristics and cause-of-death distribution among death cases with hepatitis C in Hongkou District of Shanghai, and to provide a scientific basis for optimizing healthcare resources allocation and targeted hepatitis C prevention and control measures. MethodsA retrospective cross-sectional study was conducted by integrating historical surveillance data from China Information System of Disease Prevention and Control and Shanghai Hongkou District Death Medical Registration System. Data on demographic characteristics, hepatitis C-related clinical and management records, and underlying causes of death for cases with hepatitis C between 2012 and 2024 in Hongkou District of Shanghai, were collected. Descriptive analyses were performed to analyze the epidemiological characteristics and cause-of-death distribution of death cases, and comparative analyses were conducted across different subgroups. ResultsA total of 204 hepatitis C-related deaths were identified in Hongkou District, Shanghai, from 2012 to 2024. The average age at death was (69.49±12.75) years The majority decedents were males (71.57%) and retired (73.53%). The top three underlying causes of death were malignant tumors (45.10%), cerebrovascular diseases (15.20%) and cardiovascular diseases (12.25%), collectively accounting for 72.55% of all deaths. Deaths attributed to hepatitis C accounted for 9.80% (20/204), with a mean age at death of (63.41±11.81) years. No statistically significant differences were observed in the proportion of hepatitis C-attributed deaths across different subgroups (all P>0.05). The proportion of premature deaths was 55.88% (114/204), with a mean age at death of (60.02±6.89) years. The proportion of premature deaths was higher among males (60.27%), laboratory-diagnosed patients (62.69%), patients with other liver diseases (72.06%), and those non-compliant with follow-up (70.97%) compared to their respective counterparts (all P<0.05). Additionally, homemakers /unemployed patients (100.00%) and employed patients (88.89%) had a significantly higher proportion of premature deaths compared to retired patients (42.67%) (P<0.001). There was a statistically significant difference in the distribution of causes of death between the premature death group and the non-premature death group (χ²=14.93， P=0.048). The top three causes of premature deaths were malignant tumors (50.00%), hepatitis C (12.28%) and cerebrovascular diseases (10.53%). Regarding the proportion of deaths occuring prematurely, other viral hepatitis had the highest percentage (75.00%), followed by diabetes mellitus (71.43%) and hepatitis C (70.00%). ConclusionThe majority of death cases with hepatitis C were males and retirees in Hongkou District, Shanghai. The leading cause of death was malignant tumors, while hepatitis C ranked as the fourth underlying cause, as well as served as the second leading cause of premature death following malignant tumors. Premature death was closely associated with gender, occupation, diagnostic classification, presence of other liver diseases, and follow-up compliance, highlighting the importance of enhanced health management and targeted interventions among high-risk groups.

Objective: To examine the prevalence of e-cigarette use and associated factors among primary and secondary school students in Pudong New Area, Shanghai, and to explore the pathways linking harm perception of e-cigarettes, interpersonal social influence, and attitudes toward e-cigarette use with experimentation behavior, in order to provide scientific basis for further optimizing the prevention and control strategies of e-cigarette among adolescents. Methods: From September to October 2025, a multi stage cluster random sampling method was used to select 5 144 primary and secondary school students aged 8-19 years from 47 primary and secondary schools in Pudong New Area, Shanghai, to conduct an anonymous questionnaire survey. The questionnaire collected information on e-cigarette use, harm perception of e-cigarette, interpersonal social influence, and attitudes toward e-cigarette use. The Chi-square test was applied to analyze the differences in cigarette and e-cigarette use behavior among primary and secondary school students with different demographic characteristics. Structural equation modeling (SEM) was constructed using Mplus 8.3 software, and the bootstrap method was utilized to test the mediating effects. Results: The reported rates of cigarette experimentation, e-cigarette experimentation, and current e-cigarette use among primary and secondary school students were 1.85%, 2.10%, and 0.70%, respectively. Higher reporting rates of e-cigarette experimentation were observed among boys (2.82%), secondary school students aged 16-19 (3.39%), senior high school students (3.05%), and those with weekly pocket money >100 yuan ( 6.11% ) ( χ 2=11.67, 8.61, 8.00, 54.18, all P <0.05). Structural pathway analysis results demonstrated that e-cigarette harm perception positively predicted interpersonal social influence ( β =0.61) and e-cigarette use attitude ( β = 0.53 ), and interpersonal social influence ( β =0.65) and e-cigarette use attitude ( β =0.25) further promoted e-cigarette experimentation behavior among primary and secondary school students (all P <0.01), with interpersonal social influence playing a major mediating role (indirect effect=0.40). Conclusions E-cigarette experimentation behavior among primary and secondary school students in Pudong New Area is jointly influenced by multiple psychosocial factors. Intervention strategies should strengthen interpersonal social factors such as family and peers on the basis of health education, thereby constructing a comprehensive prevention and control strategy for e-cigarette use among primary and secondary school students.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Objective: To investigate the trend in disease burden of injuries among children and adolescents in China from 1990 to 2021, so as to provide a basis for formulating prevention and control strategies and reducing this disease burden. Methods: Data on mortality, disability-adjusted life years (DALY) rate, incidence, and prevalence of injuries among children and adolescents aged <20 years in China from 1990 to 2021 were collected from the Global Burden of Disease (GBD) 2021 database. All rates were standardized using the GBD 2021 world standard population. The trend in incidence of disease burden of injuries among children and adolescents across differents genders and ages from 1990 to 2021 was evaluated using average annual percent change (AAPC). Results: From 1990 to 2021, the standardized mortality (AAPC=-5.435%), standardized DALY rate (AAPC=-5.311%), standardized incidence (AAPC=-0.466%), and standardized prevalence (AAPC=-0.810%) of injuries among children and adolescents in China showed downward trends (all P<0.05). Among these, the standardized mortality of animal contact (AAPC=-9.138%) and the standardized DALY rate of medical side effects (AAPC=-8.389%) decreased at a relatively fast pace, while the standardized incidence of falls (AAPC=0.083%) and the standardized prevalence of exposure to natural forces (AAPC=2.656%) showed upward trends (all P<0.05). The standardized mortality, standardized DALY rate, standardized incidence and standardized prevalence of injuries were higher in males than in females. The trend in males showed a downward trend (all P<0.05), consistent with the total population. The crude incidence of injuries in the group aged 15-<20 years showed an upward trend (AAPC=0.391%, P<0.05), while the trend in the group aged 10-<15 years was not statistically significant (P>0.05). The crude incidence of injuries in the groups aged 5-<10 years and <5 years showed downward trends (AAPC=-0.488% and -2.275%, both P<0.05). In 2021, the <5 years age group had the highest crude mortality and crude DALY rate of injuries, at 13.94/100 000 and 1 257.26/100 000, respectively. The 15-<20 years age group exhibited the highest crude incidence and crude prevalence, at 4 874.05/100 000and 4 050.35/100 000, respectively. Drowning and falls were major components of the disease burden across all age groups. Conclusions From 1990 to 2021, the disease burden of injuries among children and adolescents in China showed an overall downward trend. The disease burden was consistently higher in males than in females. Children aged <5 years face a high risk of fatality and disability, while adolescents aged 15-<20 years experience a high incidence and frequency of injuries. Drowning and falls were key priorities for prevention and control.

Objective To evaluate the diagnostic value of transrectal contrast-enhanced ultrasound (CEUS) for rectal cancer with intestinal stenosis caused by tumors. Methods Forty-nine patients with rectal cancer underwent transrectal CEUS and magnetic resonance imaging (MRI) before surgery.Intraoperative tumor localization and postoperative pathological results were taken as the gold standard for diagnosis.The differences in T stage,localization,and tumor length of rectal cancer were compared between the two methods. Results The total accuracy rates of transrectal CEUS and MRI in diagnosing T stage were 75.5% (36/49) and 67.3% (33/49),which had no significant difference (χ²=0.8,P=0.371).The total accuracy rates of transrectal CEUS and MRI in judging tumor localization were 79.5% (39/49) and 77.5% (38/49),which had no significant difference (χ²=0.061,P=0.806).The measurement results of tumor length in pathological examination had no significant difference from the transrectal CEUS results (t=1.42,P=0.162) but a significant difference from the MRI results (t=3.38,P=0.001).Furthermore,transrectal CEUS detected 8 (16.3%) cases of colonic polyps among the 49 patients,while MRI did not detect colon lesions. Conclusions Transrectal CEUS has good consistency with MRI in T staging and localization judgement of rectal cancer with intestinal stenosis,and this method can more accurately evaluate the tumor length and simultaneously evaluate whether there is a lesion in the entire colon at the proximal end of stenosis.It can be used as a supplementary examination before rectal cancer treatment in clinical practice.
Humans ; Rectal Neoplasms/complications* ; Male ; Middle Aged ; Female ; Aged ; Contrast Media ; Ultrasonography ; Adult ; Magnetic Resonance Imaging ; Constriction, Pathologic/diagnostic imaging* ; Aged, 80 and over ; Intestinal Obstruction/etiology*

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Objective To develop and validate an efficient and simple liquid chromatography with tandem mass spectrometry(LC-MS/MS)method for determination of polymyxin E in human plasma,and apply the established method in therapeutic drug monitoring(TDM)of polymyxin E.Methods The LC-MS/MS platform was based on AB SCIEX HPLC-4500MD system.Gradient elution was performed with 0.2％formic acid in water and 0.2％formic acid in acetonitrile.Phenomenex Kinetex XB-C18 column(100 mm × 2.1 mm,2.6 μm)were used.The analytes were detected by electrospray ionization(ESI)positive multiple reaction monitoring mode.The ion pairs for analytes(polymyxins E1,E2)and internal standard(polymyxins B1)were m/z 390.7→101.3,m/z 386.0→101.2,and m/z 402.3→101.2,respectively.Plasma samples were processed with protein precipitation method.Results Polymyxin E1 and E2 showed good linearity in the range of 0.031 2-6.24 mg/L and 0.006 15-1.23 mg/L,respectively.The within-run accuracy of polymyxin E1 and E2 in plasma ranged from 89.4％to 99.8％and 91.5％to 108.2％,respectively,while the between-run accuracy ranged from 91.8％to 104.7％and 95.6％to 105.2％,respectively.The within-run precision of polymyxin E1 and E2 in plasma ranged from 4.9％to 8.9％and 2.8％to 8.5％,respectively,while the between-run precision ranged from 4.1％to 7.6％and 4.2％to 9.8％,respectively.The average internal standard normalized matrix effect factors of polymyxins E1 and E2 were 96.9％-111.2％and 106.1％-112.8％in blank plasma samples from 6 different sources,102.5％-106.8％and 98.8％-105.2％in lipemic plasma,respectively,107.8％-108.9％and 106.9％-1 07.4％in hemolyzed plasma,respectively.The precision of matrix effects was less than 15.0％.The average recovery rate was 102.9％-107.5％for polymyxin E1 and E2,and 107.0％for internal standard polymyxin B1.The precision was less than 3.7％.Conclusions In this study,a simple and efficient LC-MS/MS method was established for determination of polymyxin E1 and E2 in human plasma,which is reliable in the therapeutic drug monitoring and pharmacokinetic study of polymyxin E.

Objective:To explore the risk factors of suicidal ideation in community residents in Shandong province,China,and to establish a prediction model and a nomogram for the risk of suicidal ideation.Methods:To-tally 11 087 community residents in Jining City,Zoucheng City,and Weifang City,Shandong Province,were recrui-ted as the study subjects.The general information questionnaire,Composite International Diagnostic Interview-3.0,General Anxiety Disorder-7,were used to collect demographic information,mental health status,family information,and lifestyle using a computer-assisted interview system to conduct face-to-face interview.LASSO regression and binary logistic regression analyses were used to develop a nomogram model of the risk of suicidal ideation.Results:Young people,female,smoking,non-new town residents,no physical exercise,difficulty approaching people,anxiety symptoms and depression were effective predictors of suicidal ideation.The area under the curve(AUC)of the training set(AUC)was 0.89(95％CI:0.85-0.93)and AUC of the validation set(AUC)was 0.83(95％CI:0.75-0.92).Conclusion:The nomogram prediction model constructed in this study on suicidal ideation in com-munity residents has a high degree of differentiation and accuracy.It could be used to screen people at high risk of suicide and provide intervention to suicidal ideation in community residents.