Budd-Chiari syndrome （BCS） is a clinical syndrome of portal vein and/or inferior vena cava （IVC） hypertension caused by obstruction of the hepatic veins and/or the IVC proximal to its opening. Previous studies have shown that there are significant differences in the etiology， clinical classification， and therapeutic strategy of BCS across different regions. In Western countries， BCS is often secondary to thrombotic disorders， especially myeloproliferative neoplasms， with hepatic vein obstruction as the main lesion； the treatment of BCS mainly follows a stepwise strategy of anticoagulation， recanalization， shunting， and liver transplantation， with relatively early timing for transjugular intrahepatic portosystemic shunt. In contrast， BCS in China mainly involves membranous obstruction of the retrohepatic IVC and mixed-type obstruction， and percutaneous transluminal angioplasty is the core treatment method for BCS. These differences may be associated with various factors such as genetic background， environmental exposure， and healthcare practice patterns， with a significant impact on clinical decision-making and prognostic assessment. This article systematically summarizes the geographic heterogeneity of BCS through a literature review， so as to provide a cross-regional diagnostic and therapeutic reference for clinicians， as well as clues and directions for international collaborative research on the regional differences of BCS in the future.

Hemoglobin (Hb) concentration is a key clinical biomarker for diagnosing and managing anemia, ischemic stroke, perioperative blood loss, and chronic diseases such as renal failure. Traditional venous blood sampling remains the gold standard due to its high accuracy, but its invasive nature limits frequent testing, real time monitoring, and large scale screening. This has driven growing interest in non-invasive Hb detection technologies over the past decade. Among these, optical methods are the most promising because of their safety, potential for continuous monitoring, and compatibility with portable or wearable devices. This paper systematically reviews major advances in optical non invasive Hb detection from the last ten years. We focus on near-infrared spectroscopy branches—photoplethysmography (PPG) and dynamic spectrum (DS)—and also cover color analysis/RGB imaging, Raman spectroscopy, and photoacoustic spectroscopy. For each technology, we explain its detection principles, analyze advantages and limitations, and summarize optimization strategies reported in recent literature. PPG, based on pulsatile blood volume changes, underpins many commercial continuous monitors. However, its accuracy is constrained by motion artifacts, individual physiological variations (e.g., skin tone, tissue thickness), and low AC signal to noise ratio. In contrast, DS—an advanced derivative of PPG—uses a differential principle to extract absorbance changes between systolic and diastolic peaks. This theoretically eliminates interference from static tissues (skin, bone, venous blood) and common mode noise (e.g., ambient light), positioning DS as a more robust framework for high precision Hb quantification. Beyond spectral methods, color analysis/RGB imaging offers a hardware minimalist approach. By analyzing images of vascular rich, thin tissues (e.g., conjunctiva, nail beds, palms), it enables Hb estimation using smartphone cameras. Recent advances have shifted from manual RGB feature extraction to deep learning models and spectral super resolution that reconstruct hyperspectral data from RGB inputs, significantly improving screening accuracy. Our academic perspective emphasizes critical and integrative analysis. We highlight persistent challenges that hinder clinical translation: profound individual biological variability (skin optics, microvascular architecture), sensitivity to measurement conditions (pressure, ambient light), and a lack of standardized validation protocols and multi center trials. A central thesis is that no single optical method is universally superior; each involves trade offs between accuracy, complexity, cost, and practicality. Looking forward, we posit that the next performance leap will come from multimodal information fusion—combining PPG, electrocardiogram (ECG), bioimpedance, or different optical modalities to compensate for individual differences and environmental noise. AI and deep learning are essential not only for image analysis but also for automated, end to end feature extraction from complex waveforms like PPG sequences. Advancing hardware (tunable lasers, quantum dot LEDs, novel sensor designs) is crucial to improve signal fidelity and portability. Finally, we advocate for clinical scenario specific optimization and rigorous standardized evaluation frameworks to gain regulatory approval (e.g., FDA, NMPA) and achieve widespread clinical acceptance. In conclusion, this review synthesizes a decade of progress. Optical non-invasive Hb detection has evolved from proof of concept studies to emerging products and validated screening tools, but the journey toward reliable, clinic ready quantitative devices continues. The convergence of smarter algorithms, fused sensing modalities, and focused clinical validation offers the most promising path to transform this potential into routine medical practice, ultimately enabling personalized, continuous, and accessible hematological management.

Objective To construct and evaluate a prognostic model for clear cell renal cell carcinoma(ccRCC)based on preoperative lipid ratios, cM0(i+)staging, and other clinical characteristics, so as to provide a precise tool for clinical prognosis assessment. Methods A retrospective analysis was conducted on the clinical data of 215 ccRCC patients treated in our hospital during May 2014 and May 2023. Lipid ratios were calculated using preoperative lipid data, and patients were divided into cM0(i+)stage or cM0 stage according to postoperative circulating tumor cells(CTCs)test results. The optimal lipid ratio and cutoff value were selected using receiver operating characteristic(ROC)curves and the X-tile method. Patients were subdivided into three groups based on the level of the low-density lipoprotein cholesterol to non-low-density lipoprotein cholesterol ratio(LNLR)and cM0(i+)staging:Group A [LNLR＞1.68 and diagnosed with cM0(i+)], Group B [LNLR＞1.68 or diagnosed with cM0(i+)], and Group C(LNLR ≤1.68 and diagnosed with cM0). Kaplan-Meier survival analysis was used to plot survival curves for patients in different groups. The log-rank test was employed to compare differences in recurrence-free survival(RFS)among the subgroups. Multivariate Cox regression analysis was conducted to identify the independent risk factors influencing RFS, and a nomogram prediction model was constructed based on these results. The predictive performance of the model was validated using ROC curves, calibration curves, and decision curves. Results ROC curves were plotted for lipid markers, and LNLR was identified as the most predictive for RFS. Its optimal cutoff point was 1. 68. Patients in Group A experienced a significantly shorter postoperative RFS. Multivariate Cox regression analysis identified preoperative LNLR, cM0(i+)staging, pathological grade, and stage as independent risk factors for RFS. A nomogram model was constructed based on these risk factors. The area under the ROC curve(AUC)for 1-, 3-, and 5-year RFS was 0.896(95% CI:0.8121-0.9627), 0.890(95%CI:0.7879-0.9641), and 0.870(95%CI:0.7697-0.9526), indicating good discriminatory ability and predictive performance. Calibration plots demonstrated good agreement between predicted and actual outcomes. Clinical decision curve analysis showed high clinical net benefit. Conclusion Preoperative LNLR level is an independent risk factor for RFS in ccRCC patients. The prognostic prediction model based on LNLR, cM0(i+)staging, patient pathological grade, and staging demonstrates good predictive performance for RFS and holds potential clinical application value.

Objective To explore the time-varying pattern of potential symptoms in breast cancer patient before and after chemotherapy,and further analyze its influencing factors,aims to provide reference for clinical nursing practice.Methods 233 cases of breast cancer in a tertiary A hospital in Ningxia from June to October,2023 were selected as the research subjects.By the general information questionnaire and the Chinese version of Anderson Symptom Assessment Scale,the potential change of symptoms of breast cancer patients undergoing chemotherapy 1-3 days before the first chemotherapy(T1,233 cases)and 7-14 days after the third or fourth chemotherapy(T2,225 cases)was analyzed.Results 225 cases of breast cancer patients completed 2 surveys,and their symptom characteristics before and after chemotherapy can be divided into 2 categories:a high symptom troubled group and a low symptom troubled group.The high-symptom troubled group has strong stability,and the probability of maintaining the original group is 85.20％,while the low-symptom troubled group is more inclined to change to the high-symptom troubled group,and the transition probability is 26.60％.Logistic regression analysis showed that the mass was located on the left side,and the patients who obtained disease knowledge mainly through the Internet were more likely to change from the high symptom troubled group to the low symptom troubled group,while the patients who were employed,with unsatisfactory sleep at night,and never exercised were more likely to change from the low symptom troubled group to the high symptom troubled group.Conclusion The symptoms of breast cancer patients before and after chemotherapy are heterogeneous.Patients who are on the job,have unsatisfied sleep at night and never exercise are more likely to change from the low-symptom troubled group to the high-symptom troubled group,which suggests that medical staff should identify potential high-risk groups at an early stage,and make full use of the predictive function of symptom characteristics to carry out individualized management based on the dynamic monitoring of symptoms according to different types of population characteristics,so as to reduce the burden of symptoms and improve their quality of life.

Objective To investigate the factors influencing the severity of cerebral white matter hyperintensity in hypertensive patients with acute cerebral infarction,and focus on the independ-ent roles of treatment adherence,advanced age,and multidimensional risk factors.Methods A single-center cross-sectional study was conducted on 262 hypertensive patients with acute cerebral infarction admitted to our department from January 2020 to June 2023.According to their score of Morisky Medication Adherence Scale(MMAS-8),they were divided into an adherence group(116 cases)and a non-adherence group(146 cases).Their demographic data,medical history,and blood pressure data were collected through electronic medical records.Fazekas score was assessed blind-ly to quantify the severity of white matter hyperintensity.MMAS-8 and Montreal Cognitive Assessment Scale(MoCA)were used to assess the behavioral indicators,and modified Rankin Scale(mRS)was employed to evaluate the neurological function.Univariate and multivariate logistic regression analyses were performed to screen the risk factors.Results There were statis-tical differences in marital status,mRS score and Fazekas score between the adherence group and the non-adherence group(P＜0.05,P＜0.01).The non-adherence group had significantly higher diastolic blood pressure than the adherence group[(87.29±7.51)mm Hg(1 mm Hg=0.133 kPa)vs(83.98±8.11)mm Hg,P=0.001].Univariate logistic regression analysis showed age of≥80 years,duration of hypertension≥5 years,systolic blood pressure,and MoCA score＜10 were no-tably correlated with severity of white matter hyperintensity(P＜0.01).Multivariate logistic re-gression analysis indicted that age of≥80 years(OR=3.305,95％CI:1.560-7.001,P=0.002),systolic blood pressure(OR=1.026,95％CI:1.008-1.044,P=0.003),MoCA score＜10(OR=5.210,95％CI:2.060-13.176,P=0.000),and treatment non-adherence(OR=2.380,95％CI:1.346-4.209,P=0.003)were independent risk factors for white matter hyperintensity severity,and duration of hypertension showed no significance in the multivariate model(P＞0.05).Conclusion Poor treatment adherence and advanced age are core factors for white matter hyper-intensity progression in hypertensive patients with acute cerebral infarction.

Aromatherapy refers to the method of using the aromatic components of plants in appropriate forms to act on the entire body or a specific area to prevent and treat diseases. Essential oils used in aromatherapy are hydrophobic liquids containing volatile aromatic molecules， such as limonene， linalool， linalool acetate， geraniol， and citronellol. These chemicals have been extensively studied and shown to have a variety of functions， including reducing anxiety， relieving depression， promoting sleep， and providing pain relief. Terpenoids are a class of organic molecules with relatively low lipid solubility. After being inhaled， they can pass through the nasal mucosa for transfer or penetrate the skin and enter the bloodstream upon local application. Some of these substances also have the ability to cross the blood-brain barrier， thereby exerting effects on the central nervous system. Currently， the academic community generally agrees that products such as essential oils and aromatherapy from aromatic plants have certain health benefits. However， the process of extracting a single component from it and successfully developing it into a drug still faces many challenges. Its safety and efficacy still need to be further verified through more rigorous and systematic experiments. This article systematically elaborated on the efficacy of aromatic substances， including plant extracts and natural small molecule compounds， in antibacterial and antiviral fields and the regulation of nervous system activity. As a result， a deeper understanding of aromatherapy was achieved. At the same time， the potential of these aromatic substances for drug development was thoroughly explored， providing important references and insights for possible future drug research and application.

Objective:To explore the clinical application of mobile-intelligent medical management system for gout patients.Methods:This study was a randomized controlled trial. One hundred and two patients with gout who visited rheumatology department of the First Hospital of Jilin University from January 2022 to October 2023 were randomly divided into study group ( n=53) and the control group ( n=49). Patients in the study group were managed by the mobil-gout(M-G) health management system which consists of a distant management plateform and an App. The body weight and blood uric acid levels were regularly self-tested by patients, and the information was sent to the system, the doctor gave feed-back advice on medication adjustment and dietary management every 2 weeks. While patients in the control group were managed following the conventional outpatient consultation mode. The serum uric acid levels, liver and kidney function tests and physical examinations were conducted on the day of enrollment and 3 and 6 months after treatment. The number of affected joints and the frequency of attacks were evaluated, and pain was assessed using the visual analog scale (VAS). The efficacy of treatment were compared between two groups. Results:After 3 and 6 months of treatment, the serum uric acid levels in study group were significantly lower than those in control group (408.0 (345.0, 450.0)μmol/L vs. 458.0 (409.0, 482.0)μmol/L, 371.0 (338.5, 409.0) μmol/L vs. 412.0 (368.5, 445.0)μmol/L; Z=3.37, 4.61, P<0.01); and VAS scores were also significantly lower than those in control group (6.66±1.46 vs. 4.68±1.80, 7.45±1.06 vs. 5.88±1.52; t=14.12, 13.72, P<0.01). After 6 months of treatment, the frequency of gout attacks in the study group was significantly lower than that in the control group ( χ2=9.30, P<0.05). As the follow-up period was extended, the average number of joints affected by gout attacks and the frequency of gout attacks in the study group showed a reducing trend compared to the control group, but the differences were not statistically significant ( P>0.05). Conclusions:The M-G medical management system can more effectively control uric acid levels and alleviate symptome for gout patients.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To report a case of tibial synovial sarcoma and review relevant literature to enhance understanding of this disease.Methods The clinical data of a patient with tibial synovial sarcoma treated at Kaifeng Central Hospital were retrospectively analyzed.A literature search was conducted in domestic and international databases,including China National Knowledge Infrastructure(CNKI),Wanfang Data,PubMed,Web of Science,and Embase,up to July 2024.Relevant literature was comprehensively reviewed to summarize the imaging and pathological characteristics,treatment,and prognosis of synovial sarcoma.Results A 29-year-old female patient was admitted with left lower extremity pain.X-ray examination revealed a proximal tibia space-occupying lesion suggestive of malignancy,and a mid-tibial space-occupying lesion considered benign.Contrast-enhanced computed tomography(CT)and plain magnetic resonance imaging(MRI)of the proximal tibial lesion also suggested malignancy.Ultrasound-guided biopsy of the proximal tibial tumor revealed a poorly differentiated malignant tumor.Immunohistochemistry results indicated monophasic synovial sarcoma,requiring genetic testing for definitive diagnosis.The patient underwent wide resection of the proximal left tibial malignancy with tumor-type artificial joint replacement,combined with curettage and bone cement filling for the left mid-tibial lesion under anesthesia.Postoperative pathology of space-occupying lesions in the proximal tibia confirmed monophasic synovial sarcoma,and fluorescence in situ hybridization(FISH)demonstrated a rupture of the synovial sarcoma translocation gene(SYT)(i.e.,SS18 positive).There was no recurrence or metastasis found in the patient during the reexamination 6 months after postoperative chemotherapy.As of July 2024,15 cases of genetically confirmed primary intraosseous synovial sarcoma have been reported internationally.Symptoms included pain and swelling,with a medical history of 1-2 years.The X-ray and CT findings showed osteolytic destruction with bone cortical discontinuity.In 13 cases,the intraosseous masses extended to the extraosseous area;in 2 cases,punctate calcifications were detected within the masses.Plain MRI scan showed iso-signal or hypo-signal on T1WI and hyper-signal,iso-signal,and hypo-signal on fat-suppressed T2WI,and enhanced MRI scan demonstrated heterogeneous enhancement.Pathological examination showed spindle-shaped cells under microscopy.Immunohistochemistry results showed positive epithelial membrane antigen(EMA),broad-spectrum cytokeratin(AE1/AE3),Ewing's sarcoma marker(CD99),and transducin-like enhancer of Split 1(TLE1).Twelve patients underwent surgical treatment;6 patients received adjuvant chemotherapy after surgery,of whom 4 developed local recurrence or distant metastasis at initial diagnosis,and 3 died during follow-up.Among the 6 patients who did not receive adjuvant chemotherapy,3 suffered from recurrence or distant metastasis.Conclusions Primary intraosseous synovial sarcoma is a rare malignant tumor with non-specific clinical manifestations.Imaging features typically include osteolytic destruction and intraosseous masses extending extraosseously,suggesting an intraosseous origin.Pathology and immunohistochemistry aid diagnosis,but definitive confirmation relies on further genetic testing.At present,the main treatment regimens for synovial sarcoma involve comprehensive therapies such as surgery and adjuvant chemotherapy,and the prognosis of patients is poor.

Hepatic fibrosis(HF)is an inevitable process for many chronic liver diseases to develop into liver cirrhosis and even liver cancer.More than 80%of hepatocellular carcinomas are formed after the process of chronic hepatitis,HF or liver cirrhosis.The immune microenvironment produced by inflammation and fi-brosis plays a significant role in promoting the occurrence and development of hepatocellular carcinoma.He-patic stellate cells(HSC),extracellular matrix(ECM),and fibroblasts are involved in the progression of HF by influencing innate immunity and adaptive immunity.This article,by analyzing the role of immune cells in HF,is expected to provide new intervention approaches and therapeutic targets for the clinical treatment of HF,thereby further enhancing the effectiveness of immunotherapy and offering safer and more effective treat-ment options for HF patients.