ObjectiveTo explore the value of the Model for End-Stage Liver Disease （MELD） 3.0 in predicting survival outcomes for patients with alcoholic cirrhosis and to establish an effective mortality prediction model. MethodsClinical data of 788 hospitalized patients who were first diagnosed with alcoholic cirrhosis at the Third Affiliated Hospital of Sun Yat-sen University between January 1， 2011 and December 31， 2019 were analyzed. Patients were followed up until December 31， 2023 and divided into survival and mortality groups based on the survival outcomes at 30 days， 90 days， 1 year， and 3 years after admission. The prognostic values of the MELD 3.0， MELD， MELD-Sodium （MELD-Na） for survival in alcoholic cirrhosis patients were assessed and compared by using the receiver operating characteristic （ROC） curve and the area under the curve （AUC）. Additional risk factors associated with mortality in alcoholic cirrhosis patients were identified， and a novel mortality prediction model based on MELD 3.0 was developed. ResultsThe AUC of the MELD 3.0 score in predicting 30-day， 90-day， 1-year， and 3-year survival was 0.823， 0.730， 0.686， and 0.658， respectively， which were superior to those of the MELD-Na （0.802， 0.708， 0.666， and 0.645， respectively） and MELD scores （0.698， 0.668， 0.654， and 0.633， respectively） （all P < 0.05）. MELD 3.0 demonstrated better performance at 30 and 90 days （AVC=0.823，0.730； both P < 0.05） than at 1 year and 3 years （AVC=0.686，0.658； both P < 0.05）. Binary logistic regression combined with LASSO regression indicated that the independent risk factors associated with the 1-year outcome included MELD 3.0， baseline ascites and hepatocellular carcinoma. A survival prediction model was then established with AUC of 0.748， sensitivity of 0.695， and specificity of 0.775. ConclusionsMELD 3.0 has a superior predictive ability for 30-day， 90-day， 1-year， and 3-year survival in patients with alcoholic cirrhosis than MELD-Na and MELD. The prediction model incorporating MELD 3.0， ascites and hepatocellular carcinoma improves the prediction of 1-year survival outcomes for alcoholic cirrhosis patients.

Objective To obtain the data of radiological diagnosis and treatment resource distribution at medical institutions of different levels and in various cities, understand the status of resource allocation, provide policy-making basis and suggestions for optimizing the allocation of radiological diagnosis and treatment resources within the province, and offer data and references for related research. Methods A basic situation questionnaire survey was conducted on radiological diagnosis and treatment institutions in Hunan Province. Data were reviewed, analyzed, and statistically processed using Excel software to understand the allocation situation of radiological diagnosis and treatment resources in Hunan Province. Results As of 2022, there were 3031 radiological diagnosis and treatment institutions, 19770 radiation workers, and 6617 pieces of radiological diagnostic and treatment equipment. There were 80 radiation treatment institutions, 49 nuclear medicine institutions, 178 interventional radiology institutions, and 3028 X-ray imaging diagnosis institutions. There were 1077 radiation workers in radiation treatment, 461 radiation workers in nuclear medicine, 3369 radiation workers in interventional radiology, and 14,863 radiation workers in X-ray imaging diagnosis. There were 135 pieces of radiation treatment equipment, 56 pieces of nuclear medicine equipment, 262 pieces of interventional radiology equipment, and 6164 pieces of X-ray imaging diagnosis equipment. Conclusion Primary and lower grade medical institutions in Hunan Province account for a relatively high proportion of the total number of medical institutions, whereas radiological diagnostic and treatment resources are predominantly concentrated in tertiary medical institutions, demonstrating a unbalanced allocation of radiological diagnosis and treatment resources in various cities. In terms of the overall allocation of radiological diagnosis and treatment resources, interventional radiology is superior to the national average, nuclear medicine and X-ray imaging diagnosis are comparable to the national averages, and radiation treatment is lower than the national average. The total GDP is not the decisive factor in determining the development of local medical levels. It is suggested that relevant authorities should improve the rationality of the planning for the allocation of radiological diagnosis and treatment resources, promote the allocation of radiological diagnosis and treatment resources to the grassroots and underdeveloped areas through various measures, and thus achieve the goal of balanced resource allocation.

OBJECTIVE: To analyze the core acupoint selection rules and syndrome-based compatibility patterns of acupuncture for autism spectrum disorder (ASD) using data mining techniques. METHODS: Relevant literature of acupuncture for ASD was retrieved from CNKI, Wanfang, VIP, PubMed, and Web of Science. After applying inclusion and exclusion criteria, a prescription database was established based on the extracted effective data. Descriptive analysis was conducted on the frequency, meridian tropism, anatomical distribution, and specific point. High-frequency acupoints were visualized using Origin software. The Apriori algorithm in IBM SPSS Modeler 18.0 was used for association rule analysis of acupoint combinations. Cluster analysis of high-frequency acupoints was performed using IBM SPSS Statistics 26.0. The relationships between high-frequency syndromes and acupoints were visualized using Cytoscape 3.10.0. RESULTS: A total of 223 studies and 452 prescriptions were included, among which 223 were based on syndrome differentiation. A total of 205 acupoints were included with a cumulative frequency of 4 067. The top five most frequently used acupoints were Baihui (GV20), Sishenzhen, Zhisanzhen, Niesanzhen, and Neiguan (PC6). Acupoints were primarily from Jin's three-needle therapy, the governor vessel, scalp acupuncture, and the foot-taiyang bladder meridian, with a high proportion of acupoints located on the head and neck and the limbs. Among specific point, five-shu points, yuan-source points, and back-shu points were most frequently used. Association rule analysis revealed that the core acupoint group was Sishenzhen-Dingshenzhen-Zhisanzhen-Niesanzhen. Cluster analysis divided the top 20 high-frequency acupoints into four categories: governor vessel activation and brain awakening group, spleen strengthening and heart nourishing group, Jin's three-needle spirit-regulating group, and kidney-reinforcing and marrow-filling group. Clinically, the main syndrome patterns were kidney essence deficiency, hyperactivity of heart and liver fire, phlegm obstructing the heart orifices, dual deficiency of heart and spleen, and liver qi stagnation. CONCLUSION The core acupoint prescriptions of acupuncture for ASD are Sishenzhen, Dingshenzhen, Zhisanzhen, and Niesanzhen. The treatment emphasizes spirit regulation and mental tranquility, guided by the principles of harmonizing multiple zang-fu organs, regulating qi and blood, unblocking qi movement, and balancing yin and yang. Syndrome-based acupoint compatibility is recommended in clinical practice.
Humans ; Acupuncture Points ; Acupuncture Therapy ; Autism Spectrum Disorder/therapy* ; Data Mining ; Meridians

Microwave thermochemotherapy (MTC) has been applied to treat lip squamous cell carcinoma (LSCC), but a deeper understanding of its therapeutic mechanisms and molecular biology is needed. To address this, we used single-cell transcriptomics (scRNA-seq) and spatial transcriptomics (ST) to highlight the pivotal role of tumor-associated neutrophils (TANs) among tumor-infiltrating immune cells and their therapeutic response to MTC. MNDA⁺ TANs with anti-tumor activity (N1-phenotype) are found to be abundantly infiltrated by MTC with benefit of increased blood perfusion, and these TANs are characterized by enhanced cytotoxicity, ameliorated hypoxia, and upregulated IL1B, activating T&NK cells and fibroblasts via IL1B-IL1R. In this highly anti-tumor immunogenic and hypoxia-reversed microenvironment under MTC, fibroblasts accumulated in the tumor front (TF) can recruit N1-TANs via CXCL2-CXCR2 and clear N2-TANs (pro-tumor phenotype) via CXCL12-CXCR4, which results in the aggregation of N1-TANs and extracellular matrix (ECM) deposition. In addition, we construct an N1-TANs marker, MX2, which positively correlates with better prognosis in LSCC patients, and employ deep learning techniques to predict expression of MX2 from hematoxylin-eosin (H&E)-stained images so as to conveniently guide decision making in clinical practice. Collectively, our findings demonstrate that the N1-TANs/fibroblasts defense wall formed in response to MTC effectively combat LSCC.
Humans ; Neutrophils/metabolism* ; Single-Cell Analysis ; Lip Neoplasms/genetics* ; Hyperthermia, Induced/methods* ; Microwaves/therapeutic use* ; Transcriptome ; Carcinoma, Squamous Cell/immunology* ; Tumor Microenvironment

Radiopharmaceuticals operate by combining radionuclides with carriers. The radiation energy emitted by radionuclides is utilized to selectively irradiate diseased tissues while minimizing damage to healthy tissues. In comparison to external beam radiation therapy, radionuclide drugs demonstrate research potential due to their biological targeting capabilities and reduced normal tissue toxicity. This article reviews the applications and research progress of radiopharmaceuticals in cancer treatment. Several key radionuclides are examined, including ²²³Ra, ⁹⁰Y, Lutetium-177 (¹⁷⁷Lu), ²¹²Pb, and Actinium-225 (²²⁵Ac). It also explores the current development trends of radiopharmaceuticals, encompassing the introduction of novel radionuclides, advancements in imaging technologies, integrated diagnosis and treatment approaches, and equipment-medication combinations. We review the progress in the development of new treatments, such as neutron capture therapy, proton therapy, and heavy ion therapy. Furthermore, we examine the challenges and breakthroughs associated with the clinical translation of radiopharmaceuticals and provide recommendations for the research and development of novel radionuclide drugs.
Humans ; Radiopharmaceuticals/therapeutic use* ; Neoplasms/radiotherapy* ; Radioisotopes/therapeutic use* ; Animals

Digital biopsy for liver diseases is characterized by the deep integration of artificial intelligence （AI） technologies and large-scale liver disease data， through which intelligent analytics are applied to support clinical decision-making and full-cycle management. This article reviews the AI technical framework based on standardized data governance and centered on multimodal large medical models， covering the application of natural language processing， knowledge map， generative AI， and large language models in the establishment of databases for specialty diseases， diagnosis， prognosis prediction， treatment， and automated medical documentation. This article also discusses the application prospects of this framework in medical education， scientific research， and healthcare management. Although this technique shows broad application potential， it still faces challenges in areas such as multi-center data integration， model interpretability， ethics， and data security. In the future， a smart ecosystem with closed-loop optimization and human-AI collaboration should be established to promote the comprehensive implementation of digital biopsy in the whole process of medicine， education， research， and management， thereby providing help for the precise prevention and control and holistic health management of liver diseases.

Objective:To construct and validate a machine learning model for preoperative prediction of perineural invasion (PNI) status in intrahepatic cholangiocarcinoma (ICC).Methods:Clincial data of 329 patients, including 245 admitted to Zhengzhou University People's Hospital from January 2018 to June 2023 and 84 admitted to the Affiliated Cancer Hospital of Zhengzhou University from January 2013 to January 2020 were retrospectively analyzed. Patients were divided into a training set ( n=231) and a validation set ( n=98). Clinicopathological data including age, gender, hepatitis B virus (HBV) infection status were collected. Predictive variables were determined using least absolute shrinkage and selection operator (LASSO) regression analysis. Six machine learning algorithms including random forest (RF), logistic regression, and linear kernel-based support vector machine were selected to construct the preoperative prediction model for PNI in ICC. Performance metrics of the model were calculated using a confusion matrix, and the final model was selected. The model performance was evaluated in the validation set. Calibration curves were plotted to evaluate the final model, and a Pareto chart was used to visualize the importance of predictive variables. Results:LASSO regression identified nine predictive variables included in the prediction model, including carbohydrate antigen 19-9 (CA19-9), HBV infection status, alkaline phosphatase, alanine aminotransferase, prothrombin time, total bilirubin, albumin, neutrophil times gamma-glutamyl transferase to lymphocyte ratio, and tumor burden score. Among the trained six models, the area under the curve (AUC) of the RF model was 0.909, with a sensitivity of 0.842 and an accuracy of 0.870. Compared with the AUC of the RF model, the AUCs of the other 5 models were lower (all P<0.05). The AUC of the RF model for predicting PNI in ICC in validation set was 0.736. Calibration curves showed good fit of the RF model's prediction of PNI in ICC in both training and validation sets. The Pareto chart showed that CA19-9 was the most important predictive variable in the model, followed by HBV infection status. Conclusion:The machine learning model based on the RF algorithm has a high accuracy in preoperative prediction of PNI status in ICC.

Objective To establish a method of LC-MS/MS for determining cordycepin(Cor)and 3′-deoxyinosine(3′-Deo)concentration in rat plasma,and to study their pharmacokinetics in rats.Methods Protein was precipitated with methanol using 2-chloadenosine(2-Chl)as an internal standard.The chromatography was performed on Kinetex C18(3 mm×100 mm,2.6 μm,Phenomenex,USA)with gradient elution in aqueous(5 mmol·L-1 ammonium acetate)-methanol solution as mobile phase.ESI ion source was used for mass spectrometry,and positive ion multiple reaction monitoring(MRM)was used for scanning detection.The pharmacokinetics of Cor and 3′-Deo after oral administration of Cor(10 mg·kg-1)were studied in rats.Results Cor at 0.5-100 ng·mL-1 and 3′-Deo at 1-200 ng·mL-1 had good linearity,and the lower limits of quantification were 0.5 and 1 ng·mL-1,respectively.After oral administration of Cor in rats,the plasma concentration of Cor was low,which was mainly converted into the metabolite 3′-Deo.The Cmax of Cor and 3′-Deo were(5.4±3.4)and(142.0±50.0)ng·mL-1,and AUC0-360min min were(658.4±459.3)and(18 034.9±4 981.1)ng·min·mL-1,respectively.Conclusion The method is simple,sensi-tive,and accurate,which is suitable for determining Cor and 3′-Deo concentration in plasma and the pharmacokinetic study.

Objective To assess the effect of ultrasonic thyroid artificial intelligence(AI)-assisted diagnostic system(AI-assisted diagnostic system)for diagnosing medullary thyroid carcinoma(MTC)compared with different physicians and taken papillary thyroid carcinoma(PTC)as the controls.Methods Totally 63 MTC,70 PTC and 62 benign thyroid nodules confirmed by pathology were enrolled.AI-assisted diagnostic system was utilized to analyze thyroid nodules and identify the likelihood of malignancy,and the probability value threshold was set at ≥0.40.All thyroid nodules were retrospectively reviewed and categorized by 3 physicians(1 senior physician,1 attending physician and 1 junior physician)according to Chinese thyroid imaging reporting and data system(C-TIRADS).The efficacy of AI-assisted diagnostic system and physicians for diagnosing MTC and PTC were evaluated.Results AI-assisted diagnostic system showed lower sensitivity,specificity,positive predictive value,negative predictive value,accuracy,and area under the curve(AUC)for diagnosing MTC and PTC compared with physicians.Significant differences of AUC were found between senior physician and AI-assisted diagnostic system,as well as between attending physician and AI-assisted diagnostic system for diagnosing MTC and PTC(all P＜0.01),while no significant difference of AUC was between junior physicians and AI-assisted diagnostic system(both P＞0.05).The sensitivity,specificity,positive predictive value,negative predictive value,accuracy and AUC for AI-assisted diagnostic system for diagnosing MTC were all lower than those for diagnosing PTC,but the AUC was not significantly different(P＞0.05).Conclusion Ultrasonic thyroid AI-assisted diagnostic system had relatively high value for diagnosing MTC.

Objective:To investigate the distribution characteristics of skeletal muscle mass and strength in the older adults over 65 years old in 18 longevity areas in China.Methods:The subjects were selected from the Healthy Aging and Biomarkers Cohort Study conducted in 18 longevity areas of China. A total of 4 662 older adults over 65 years old from a cross- sectional survey in 2021 were included in the study. The information about their sociodemographic characteristics, lifestyle, nutrient intake and other factors were collected through questionnaire surveys and physical examinations. Grip strength was measured by using professional electronic grip dynamometer. Total skeletal muscle mass (TSM) was measured using bioelectrical impedance analysis, and TSM was adjusted by height squared and BMI to obtain TSM Ht2 and TSM BMI. The proportion of individuals with low muscle mass and strength was determined according to the recommended method by the Asian Working Group for Sarcopenia (AWGS). Descriptive analysis was conducted on the population and regional distribution characteristics of people with different muscle mass and grip strength. A generalized additive model was used to analyze the age-related trends of muscle mass and grip strength. Results:The age of 4 662 study subjects was (82.69±10.54) years, men accounted for 46.85% (2 184 cases) and Han Chinese accounted for 96.27% (4 488 cases). The M( Q1, Q3) of TSM, TSM Ht2 and TSM BMI in men were 23.30 (20.50, 26.20) kg, 9.02 (8.13, 9.89) kg/m 2, and 1.01 (0.90, 1.13) kg·(kg/m 2) -1, respectively, which were all higher than those in women [TSM: 18.20 (15.70, 20.70) kg, TSM Ht2: 8.18 (7.42, 9.07) kg/m 2 and TSM BMI: 0.79 (0.69, 0.90) kg·(kg/m 2) -1], the differences were significant (all P<0.001). The grip strength of men [ M( Q1, Q3): 24.50 (17.80, 30.80) kg] was higher than that of women [ M( Q1, Q3): 15.60 (11.10, 19.90) kg], the difference was significant ( P<0.001). Southern elderly men had lower TSM and TSM Ht2 compared with northern elderly men (all P<0.001), while there was no significant regional difference in TSM BMI ( P>0.05). Southern elderly women had higher TSM Ht2 and TSM BMI compared with northern elderly women (all P<0.001), while there was no significant regional difference in TSM ( P>0.05). Furthermore, according to the method recommended by AWGS, the elderly with low muscle mass and grip strength were characterized by older age, illiteracy, being unmarried/divorced/widowed, poor chewing ability, impaired activity of daily living and living in southern region. Conclusion:There were population and regional differences in muscle mass and grip strength in the older adults over 65 years in 18 longevity areas of China, and these differences showed decreasing trends with age.