The chapter Zhouyu in Guoyu says "Qi of the heaven and the earth moves without losing its order." With lucidity ascending and turbidity descending， Qi moves in a normal state， and Yin and Yang consolidate the foundation of the body. The mutual interference between lucidity and turbidity leads to the disorder of Qi movement， thus causing diseases. It is a pathological state of disorder between ascending and descending， as well as between entering and exiting， gradually evolving into a state of turbidity affecting lucidity and transforming into pathogen， which can be used to interpret and analyze the core of disease pathogenesis. The theory of lucidity and turbidity is connected with the harmony of nutrient and defensive aspects， Qi circulation， and sweat pore associating with Qi movement， and it has common implications with immune responses and nutrient metabolism system， intestinal mucosal barrier function， and mitochondrial energy synthesis. Modern studies have shown that intestinal flora imbalance， bile acid receptor inactivation， macrophage polarization imbalance， epithelial-mesenchymal transition， ferroptosis and other related microscopic pathological mechanisms are involved in the development and progression of ulcerative colitis. By delving into the common meaning of the classic theory of mutual interference between lucidity and turbidity in traditional Chinese medicine and modern medical pathological mechanisms， this paper summarizes the correspondence between the micropathological mechanism and the theory of mutual interference between lucidity and turbidity in the regulation and mamagement of ulcerative colitis. The combined use of sweet and warm medicinal materials consolidates the middle Qi and activates Qi circulation， thus ascending lucidity and descending turbidity. The combined use of pungent medicinal materials for dispersing and bitter medicinal materials for descending simultaneously raises warm and clear Qi. Wind-extinguishing medicinal materials facilitate the ascending of Qi and the opening of sweat pores. Accordingly， turbidity descends and lucidity ascends. The prescriptions incorporating these medication principles are in agreement with the therapeutic approach of following the normal flow of lucidity and turbidity. This paper clarifies the scientific connotation and micropathologic mechanism of ulcerative colitis from the perspective of mutual interference between lucidity and turbidity， providing new theories and prescriptions for the clinical diagnosis， treatment， and prevention of ulcerative colitis.

Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.

OBJECTIVES: Ruptured abdominal aortic aneurysm (rAAA) is a life-threatening vascular emergency with extremely high in-hospital mortality. Open surgical repair (OSR) was historically the only treatment option but is associated with substantial trauma and perioperative risk. In recent years, endovascular repair (EVAR) has gained widespread use due to its minimally invasive nature and faster recovery, becoming the preferred option for anatomically suitable patients in many centers. However, controversy remains regarding the long-term survival benefits of EVAR compared with OSR and key prognostic factors affecting outcomes. This study aims to evaluate the clinical efficacy of OSR and EVAR for rAAA and identify independent predictors of postoperative survival to guide clinical decision-making. METHODS: A retrospective analysis was conducted on 83 patients diagnosed with rAAA and treated surgically in the Department of Vascular Surgery, the Second Xiangya Hospital of Central South University, between January 2013 and December 2022. Patients were divided into an OSR group and an EVAR group based on surgical approach. Baseline clinical characteristics, perioperative data, and follow-up outcomes were compared between groups. Long-term survival was analyzed, and univariate and multivariate Cox proportional hazards regression models were used to determine independent prognostic factors. RESULTS: Among the 83 patients, 32 (38.6%) underwent OSR and 51 (61.4%) received EVAR, with the proportion of EVAR steadily increasing to nearly 80% in the most recent 5 years. Patients in the EVAR group were older [(68.76±8.57) years vs (60.59±13.24) years, P=0.012], and had a lower proportion of males (76.5% vs 96.9%, P=0.013). EVAR significantly reduced operating time [(181.86±69.87) min vs (291.09±60.33) min] and hospital stay [(12.14±6.31) days vs (16.22±7.89) days (P<0.05)], but total hospitalization costs were markedly higher [(208 735.84±101 394.19) yuan vs (84 893.35±40 668.56) yuan, P<0.001]. There were no significant differences between groups in 30-day mortality (15.6% vs 15.7%), aneurysm-related mortality (9.4% vs 11.7%), overall mortality (28.1% vs 29.4%), or re-intervention rate (0 vs 5.9%) (P>0.05). The median follow-up time was 54.6 months (range, 12-144 months). Kaplan-Meier survival analysis showed comparable cumulative survival rates between OSR and EVAR (82.7% vs 76.2%, P=0.420). Cox regression identified hyperlipidemia [hazard ratio (HR)=2.32, 95% confidence interval (CI) 1.28 to 4.19, P=0.005] and elevated preoperative serum creatinine (HR=3.33, 95% CI 1.69 to 6.55, P<0.001) as significant predictors of poor prognosis. Both factors remained independently associated with mortality in the multivariate model (hyperlipidemia: HR=2.02, 95% CI 1.10 to 3.70; elevated serum creatinine: HR=2.77, 95% CI 1.40 to 5.47; P<0.05). CONCLUSIONS EVAR offeres advantages in operative and recovery times, though its long-term survival outcomes are comparable to OSR. A history of hyperlipidemia and elevated preoperative creatinine levels are independent predictors of poor prognosis. Surgical approach should be chosen based on anatomical feasibility and patient condition, with close management of lipid levels and renal function to improve outcomes.
Humans ; Aortic Aneurysm, Abdominal/mortality* ; Endovascular Procedures/methods* ; Retrospective Studies ; Male ; Female ; Prognosis ; Aged ; Aortic Rupture/mortality* ; Middle Aged ; Treatment Outcome ; Aged, 80 and over

Fractional flow reserve (FFR), an established modality for functionally assessing coronary artery disease, is increasingly applied to diagnose and manage lower extremity arterial disease. By incorporating functional parameters, FFR enhances revascularization precision by quantifying the hemodynamic impact of stenotic lesions, thereby overcoming limitations of conventional imaging. Key clinical applications in lower extremity disease include functional assessment in moderate intermittent claudication, post-vascular preparation strategy optimization, and predicting revascularization outcomes and complications. Advances in pressure wire and microcatheter systems, alongside non-invasive imaging-derived FFR techniques, are improving its feasibility and applicability. However, widespread adoption is challenged by the complex anatomy of the lower extremity arterial system, frequent severe calcification and diffuse disease, and a current lack of standardized FFR cutoff values. Promoting the standardized use of FFR is crucial for shifting the clinical management paradigm from anatomy-based repair toward functional reconstruction.
Humans ; Lower Extremity/blood supply* ; Peripheral Arterial Disease/diagnosis* ; Fractional Flow Reserve, Myocardial ; Endovascular Procedures/methods* ; Intermittent Claudication/physiopathology*

Sensorineural hearing loss is one of the most common sensory disorders. In recent years, auditory neuropathy spectrum disorders caused by mutations in the OTOF gene have garnered significant attention worldwide, marking it as the first deafness gene with breakthroughs in gene therapy. Most patients with OTOF gene mutations present with stable, congenital, or prelingual onset of hearing loss, which can range from severe to profound and even complete hearing loss. However, a minority of patients may exhibit mild to moderate progressive hearing loss or temperature-sensitive hearing loss. This review further explores the genotype-phenotype relationship of the OTOF gene based on reported cases in China and abroad. Additionally, we analyze the characteristics of the natural history of OTOF gene mutations within the Chinese population. This study aims to provide a reference for the clinical diagnosis, evaluation, and treatment of hearing loss associated with OTOF gene mutations.
Humans ; Mutation ; Phenotype ; Genotype ; Hearing Loss, Sensorineural/genetics* ; Membrane Proteins/genetics*

Metastasis serves as an indicator of malignancy and is a biological characteristic of carcinomas. Epithelial-mesenchymal transition (EMT) plays a key role in the promotion of tumor invasion and metastasis and in the enhancement of tumor cell aggressiveness. Prostaglandin E synthase 3 (p23) is a cochaperone for heat shock protein 90 (HSP90). Our previous study showed that p23 is an HSP90-independent transcription factor in cancer-associated inflammation. The effect and mechanism of action of p23 on lung cancer metastasis are tested in this study. By utilizing cell models in vitro and mouse tail vein metastasis models in vivo, the results provide solid evidence that p23 is critical for promoting lung cancer metastases by regulating downstream CXCL1 expression. Rather than acting independently, p23 forms a complex with RNA-binding motif protein 14 (RBM14) to facilitate EMT progression in lung cancer. Therefore, our study provides evidence for the potential role of the RBM14-p23-CXCL1-EMT axis in the metastasis of lung cancer.

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*