ObjectiveThis paper aims to investigate and evaluate the staged efficacy and safety of the representative empirical prescription of the “Zhu Ke Jiao” theory， Qijia Rougan prescription， combined with entecavir in the treatment of hepatic fibrosis in chronic hepatitis B. MethodsA multicenter randomized controlled clinical study was conducted， and 101 patients diagnosed with chronic hepatitis B-related hepatic fibrosis （CHB-HF） who met the diagnosis and inclusion criteria were randomly assigned to an observation group （Qijia Rougan prescription + entecavir） and a control group （entecavir）. The treatment duration was 24 weeks. Liver stiffness measurement （LSM）， fibrosis-4 index （FIB-4）， portal vein diameter， hepatitis B serology， biochemical indicators， hepatic fibrosis markers in serum ［hyaluronic acid （HA）， laminin （LN）， procollagen Ⅲ peptide （PⅢP）， and type Ⅳ collagen （Ⅳ-C）］， and traditional Chinese medicine syndrome scores were used as efficacy evaluation indicators. Efficacy assessments and explorations of different staged subgroups of Qijia Rougan prescription were conducted according to LSM values based on the Metavir pathological staging standard. ResultsA total of 98 cases were included for statistical analysis， with 49 cases in the observation group and 49 in the control group. The general data of the patients in both groups were comparable. Compared with the same group before treatment， the observation group showed a significant reduction in LSM and FIB-4 （P<0.01）， as well as notable improvements in LN， Ⅳ-C， and various TCM syndrome scores （P<0.05， P<0.01）. When compared to the control group after treatment， the observation group demonstrated significant improvements in LSM， FIB-4， and various TCM syndrome score indicators （P<0.05， P<0.01）， indicating that the observation group performed better than the control group. Subgroup analysis of the regression of hepatic fibrosis stages showed that compared to the same group before treatment， the observation group had better improvement in regression of stages F2 and F3 （P<0.05）. When compared to the control group after treatment， the observation group exhibited superior improvement in regression of stage F3 （P<0.05）. No adverse events occurred in either group during the treatment period. ConclusionCompared with entecavir alone， the combination of Qijia Rougan prescription and entecavir significantly improves the degree of hepatic fibrosis and clinical TCM symptoms in patients. The optimal intervention period is primarily during stage F3， which is a potential “interception” point of the “Zhu Ke Jiao” theory.

At present， the systematic excavation of the clinical experience and academic thought of the Sichuan school of Chinese medicine vis-à-vis its dominant disease entities remains fragmentary， and replicable paradigms are scarce. Confronted with empirical fragmentation， data heterogeneity and decision-making subjectivity， the standardised distillation， inheritance and clinical translation of these distinctive experiences has become a critical bottleneck constraining the development of the Sichuan school. The integration of artificial-intelligence technologies in data processing， pattern recognition and intelligent decision-making has rendered deep mining of traditional Chinese medicine（TCM） clinical knowledge and patterns imperative. Constructing an intelligent modern TCM diagnostic-therapeutic-evaluative system is now the obligatory route for inheritance and innovation in Chinese medicine， and simultaneously provides a technological breakthrough for intelligent decision paradigms in the dominant diseases of the Sichuan school. Accordingly， this study adopts the regional academic school as its point of entry， focuses on the dominant diseases of the Sichuan school， and proposes an innovative pathway of "four-dimensional data-multi-modal fusion-multi-agent decision-making". Specifically， four data dimensions are defined and instantiated： （Ⅰ） knowledge from classical medical literature and historical case records. （Ⅱ） objective four-diagnosis phenotypic data. （Ⅲ） master physicians' prescribing regularities. （Ⅳ） characteristic mechanisms of renowned formulae. Leveraging multi-modal data fusion and generative artificial intelligence， the entire causal chain of Famous Physicians and Renowned Formulas is explicated to reconstruct the diagnostic-therapeutic cognitive logic of the regional school. Finally， a multi-agent collective-decision model is established and refined for the dominant diseases of the Sichuan school， capable of generating precise， individualised treatment regimens and thereby advancing an intelligent diagnostic-therapeutic paradigm that delivers more efficient and accurate clinical decision support.

The chronicity of infectious diseases is an important field in the collaborative research of traditional Chinese and Western medicine. The warm disease theory of pathogen invading nutrient and blood aspects in traditional Chinese medicine （TCM） takes the struggle between healthy Qi and pathogenic Qi and cementation of Yin as the core pathogenesis， providing a unique theoretical framework for explaining the common pathology of infectious chronic diseases. This theory originated from Yin-Yang interaction in the Internal Classic and was enriched with WU Youke's theory of intruding pathogen interacting and lingering in blood vessels and YE Tianshi's theory of long-term illness entering collaterals. Combining the theory with modern medical knowledge， our team has condensed the dynamic pathogenesis model of deficiency （nutrient and blood aspects） and excess （pathogen） interacting in the blood collaterals of Yin aspect， the core feature of which is the four-dimensional interactions of cause （pathogen characteristics）， location （three Yin locations of diseases）， nature （deficiency and excess）， and potential （transmission trend）. The common pathology of infectious chronic diseases is reflected in interactions. That is， the interactions between nutrient and blood deficiency （immune exhaustion and metabolic disorder） and pathogen excess （pathogen persistence and fibrous hyperplasia） in the liver collaterals （Jueyin）， kidney collaterals （Shaoyin）， lung collaterals （Taiyin） and other blood collaterals of Yin aspect form the pathological damage characterized by immune inflammatory response-continuous tissue damage with excessive repair. Taking the inheritance and innovative development of classics as the main line， this paper systematically discusses the scientific connotation of the theory of pathogen invading nutrient and blood aspects and the paths of inheritance and innovation and clarifies the original significance of this theory in the chronic development of infectious diseases. Furthermore， taking clinical diseases as an example， this paper reflects the guiding value of this classical theory in the modern diagnosis and treatment of infectious diseases with integrated traditional Chinese and Western medicine and the application potential of this theory in solving complex medical problems through the construction of the innovative paradigm of precise diagnosis and treatment with integrated traditional Chinese and Western medicine.

Oral cancer is one of the most common malignancies in the head and neck regions. few patients benefit from current clinical therapy. Zinc finger proteins (ZNFs) are one of the largest transcription factor family proteins in the human genome. ZNFs bind to DNA, RNA, and proteins through their unique three-dimensional structure created by zinc ions to regulate gene transcription, RNA packaging, and protein folding. In recent years, the number of studies focused on the functional mechanism of ZNFs in regulating the progression of oral cancer has been increasing, with focuses on: ① ZNF677, ZNF460, ZNF154, ZNF132, ZNF281, Kaiso, and ZNF582, which regulate the invasion and metastasis of tumor cells; ② ZNF750 and PEST-containing nuclear protein (PCNP), which regulate the cell cycle; ③ ZNFs, which are involved in forming the tumor immune microenvironment, such as ZNF71 and myeloid zinc finger 1 (MZF1). For example, methylation modification modulates the reduction of ZNF677 in oral cancer and reduces the proliferation, migration, and invasion of oral cancer cells by inhibiting the protein kinase B/forkhead box O3a (AKT/FOXO3a) pathway; and ZNF460 promotes the proliferation, migration, and invasion of oral cancer cells by regulating microRNA-320a/alpha thalassemia/mental retardation, X-linked (ATRX) axis. In addition, ZNF750 inhibits the growth and metastasis of oral cancer by suppressing cell cycle transcription factor activity. Further, ZNF71 promotes the progression of oral cancer by reducing the infiltration of tumor immune cells. In this review, we will summarize the molecular mechanism, regulatory meshwork, and pro-tumor and anti-tumor roles of ZNFs in the pathogenesis of oral cancer. Our study may provide a new strategy for the diagnosis and treatment of oral cancer.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Background: The transvenous approach to the treatment of cerebral arteriovenous malformation (AVM) is difficult and requires strict blood pressure and blood flow control; however, the cure rate is very high. Appropriate blood pressure control techniques can greatly benefit these patients.Case: A 55-year-old male patient was found to have an aneurysm complicated with a cerebral AVM (length: 2.0 cm, width: 1.6 cm, height: 1.2 cm). Aneurysm embolization was considered for the first-stage surgery and transvenous AVM embolization for the second-stage surgery. Rapid ventricular pacing (RVP) provided a stable blood flow environment for the surgery, which was completed successfully. Conclusion RVP can thus provide an ideal condition for the embolization of cerebral AVM through the transvenous approach and can be a viable surgical option.

Background: The transvenous approach to the treatment of cerebral arteriovenous malformation (AVM) is difficult and requires strict blood pressure and blood flow control; however, the cure rate is very high. Appropriate blood pressure control techniques can greatly benefit these patients.Case: A 55-year-old male patient was found to have an aneurysm complicated with a cerebral AVM (length: 2.0 cm, width: 1.6 cm, height: 1.2 cm). Aneurysm embolization was considered for the first-stage surgery and transvenous AVM embolization for the second-stage surgery. Rapid ventricular pacing (RVP) provided a stable blood flow environment for the surgery, which was completed successfully. Conclusion RVP can thus provide an ideal condition for the embolization of cerebral AVM through the transvenous approach and can be a viable surgical option.

Background: The transvenous approach to the treatment of cerebral arteriovenous malformation (AVM) is difficult and requires strict blood pressure and blood flow control; however, the cure rate is very high. Appropriate blood pressure control techniques can greatly benefit these patients.Case: A 55-year-old male patient was found to have an aneurysm complicated with a cerebral AVM (length: 2.0 cm, width: 1.6 cm, height: 1.2 cm). Aneurysm embolization was considered for the first-stage surgery and transvenous AVM embolization for the second-stage surgery. Rapid ventricular pacing (RVP) provided a stable blood flow environment for the surgery, which was completed successfully. Conclusion RVP can thus provide an ideal condition for the embolization of cerebral AVM through the transvenous approach and can be a viable surgical option.

This case report describes a 68-year-old male patient diagnosed with primary hepatocellular carcinoma (HCC). After receiving Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT), the tumor significantly reduced in size, and tumor markers alpha fetoprotein (AFP) and abnormal prothrombin (PIVKA-Ⅱ) decreased. Postoperative pathological results showed minimal residual tumor cells, indicating that ⁹⁰Y-SIRT has good efficacy and safety in downstaging and conversion of HCC, thereby facilitating subsequent surgical resection.

ObjectiveTo analyze the trend of lung cancer incidence in Fenghua District, Ningbo City of Zhejiang Province from 2009 to 2023, and to estimate the age-period- cohort effects of incidence rate, so as to provide scientific basis for the formulation of lung cancer prevention and control measures in Fenghua District. MethodsJoinpoint software was utilized to analyze the trends and calculate the average annual percentage change (AAPC) of lung cancer incidence based on the tumor incidence surveillance data from Fenghua District, 2009‒2023. The age-period-cohort (APC) model for lung cancer incidence was analyzed using STATA 17.0 software, and net drift and local drift of lung cancer incidence rates were analyzed using online analytical tools. ResultsThe incidence of lung cancer in Fenghua District showed an overall upward trend from 2009 to 2023, with the standardized incidence rate increasing from 45.05/100 000 in 2009 to 108.20/100 000 in 2023(AAPC=7.05%, P<0.05). The increase in the standardized incidence rate for females (AAPC=12.72%, P<0.05) was higher than that for males (AAPC=2.97%, P<0.05). The overall net drift in lung cancer incidence for residents of Fenghua District was 11.71%, with the net drift for females (16.54%) being higher than that for males (6.64%). The local drift in lung cancer incidence among different age groups ranged from -3.37% to 35.18%. The results of APC model showed that the risk of lung cancer incidence increased and then decreased with age, with the highest age effect coefficient observed in the 65‒69 years age group at 1.08. The period effect showed a gradually increasing trend in lung cancer incidence risk with the progression of time, and the period effect coefficient in 2019‒2023 (0.46) was higher than that in 2009‒2013 (-0.39), increasing by 217.95%. The cohort effect coefficient showed a trend of first decreasing and then increasing with the expansion of the birth cohort, in which the lowest cohort effect coefficient was -1.07 observed in the birth cohort of 1964‒1968 and the highest cohort effect coefficient was 1.77 in the birth cohort of 1924‒1928. ConclusionThe incidence of lung cancer in Fenghua District shows an upward trend from 2009 to 2023, with a higher increase in incidence rates among females than that in males. The risk of lung cancer incidence exists a trend of increasing and then decreasing with age growth. With the progression of time, the risk of lung cancer incidence shows a gradually increasing trend. However, with the expansion the birth cohort, the risk of lung cancer incidence demonstrates a trend of first decreasing and then increasing.