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.

ObjectiveTo observe the clinical efficacy of the Yiqi Yangyin Huoxue prescription （YYHP） in the treatment of cathartic colon （CC） and its effects on fecal short-chain fatty acids （SCFAs）， and to explore the correlations among CC severity indicators and between these indicators and patient history. MethodsAccording to the inclusion and exclusion criteria， 98 patients meeting the diagnostic criteria of both traditional Chinese and Western medicine for CC with the syndrome of Qi-Yin deficiency complicated by blood stasis were randomly assigned to an observation group and a control group. The observation group received YYHP granules， while the control group received lactulose. Both medications were administered twice daily， one sachet each time， half an hour after breakfast and dinner， with a treatment course of 8 weeks. The primary constipation symptom score， Patient Assessment of Constipation Quality of Life （PAC-QOL） score， and TCM syndrome score were assessed before and after treatment and at the 8^th week after the end of treatment. The overall clinical effective rate， as well as the efficacy attenuation index and degree， were evaluated. Fecal SCFA levels were measured using gas chromatography-mass spectrometry （GC-MS）. Spearman correlation analysis was performed to explore the correlations among CC severity indicators and between these indicators and patient history. ResultsThe overall clinical effective rate in the observation group （95.83%） was higher than that in the control group （78.72%） （P<0.05）. After treatment， the total scores for primary constipation symptoms， PAC-QOL， and TCM syndromes decreased in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. The severity of all primary constipation symptoms was alleviated in both groups （P<0.05）. In terms of "excessive straining and difficult defecation"， "anal heaviness， incomplete evacuation， and bloating sensation"， "abdominal distension"， and "defecation frequency"， the observation group showed better efficacy than the control group （P<0.05）. Scores of the four PAC-QOL dimensions and the scores and severity of primary and secondary TCM symptoms were reduced in both groups （P<0.05）， with more significant reductions in the observation group （P<0.05）. After treatment， acetic acid， propionic acid， butyric acid， and total SCFAs in the observation group increased significantly （P<0.05）. The efficacy attenuation index and degree in the observation group were lower than those in the control group （P<0.05）. No severe adverse reactions occurred in either group， and there was no statistically significant difference in the incidence of adverse reactions between the two groups. Positive correlations of varying degrees were observed among the total scores of primary constipation symptoms， PAC-QOL， and TCM syndromes， as well as between these scores and the history of stimulant laxative use， disease duration， and age. ConclusionYYHP can effectively alleviate the primary constipation symptoms in CC patients， improve quality of life， and ameliorate TCM syndromes， with good safety. It also has the advantage of a lower rebound degree after drug withdrawal， and its mechanism may be related to increasing fecal SCFA levels. Long-term abuse of stimulant laxatives may aggravate the severity of CC and prolong the disease course.

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.

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.

The tumor microenvironment is a crucial factor in tumor occurrence and progression. The hypoxic microenvironment is widely present in tumor tissue and is a key endogenous factor accelerating tumor deterioration. The "blood stasis toxin" theory, as an emerging perspective in tumor research, is regarded as the unique "soil" in tumor progression from the perspective of traditional Chinese medicine(TCM) due to its dynamic evolution mechanism, which closely resembles the formation of the hypoxic microenvironment. Scientifically integrating TCM theories with the biological characteristics of tumors and exploring precise syndrome differentiation and treatment strategies are key to achieving comprehensive tumor prevention and control. This article focused on the hypoxic microenvironment of the tumor, elucidating its formation mechanisms and evolutionary processes and carefully analyzing the internal relationship between the "blood stasis toxin" theory and the hypoxic microenvironment. Additionally, it explored the interaction among blood stasis, toxic pathogens, and hypoxic environment and proposed micro-level prevention and treatment strategies targeting the hypoxic microenvironment based on the "blood stasis toxin" theory, aiming to provide TCM-based theoretical support and therapeutic approaches for precise regulation of the hypoxic microenvironment.
Humans ; Tumor Microenvironment/drug effects* ; Neoplasms/therapy* ; Animals ; Medicine, Chinese Traditional ; Disease Progression ; Drugs, Chinese Herbal

In recent decades, the prevalence of hyperuricemia and gout has increased dramatically due to lifestyle changes. The drugs currently recommended for hyperuricemia are associated with adverse reactions that limit their clinical use. In this study, we report that berberine (BBR) is an effective drug candidate for the treatment of hyperuricemia, with its mechanism potentially involving the modulation of gut microbiota and its metabolite, succinic acid. BBR has demonstrated good therapeutic effects in both acute and chronic animal models of hyperuricemia. In a clinical trial, oral administration of BBR for 6 months reduced blood uric acid levels in 22 participants by modulating the gut microbiota, which led to an increase in the abundance of Bacteroides and a decrease in Clostridium sensu stricto_1. Furthermore, Bacteroides fragilis was transplanted into ICR mice, and the results showed that Bacteroides fragilis exerted a therapeutic effect on uric acid similar to that of BBR. Notably, succinic acid, a metabolite of Bacteroides, significantly reduced uric acid levels. Subsequent cell and animal experiments revealed that the intestinal metabolite, succinic acid, regulated the upstream uric acid synthesis pathway in the liver by inhibiting adenosine monophosphate deaminase 2 (AMPD2), an enzyme responsible for converting adenosine monophosphate (AMP) to inosine monophosphate (IMP). This inhibition resulted in a decrease in IMP levels and an increase in phosphate levels. The reduction in IMP led to a decreased downstream production of hypoxanthine, xanthine, and uric acid. BBR also demonstrated excellent renoprotective effects, improving nephropathy associated with hyperuricemia. In summary, BBR has the potential to be an effective treatment for hyperuricemia through the gut-liver axis.

Ovulatory dysfunction (OD) is one of the main causes of infertility in women of childbearing age, which not only affects their reproductive ability, but also physical and mental health. Traditional treatment strategies have limited efficacies, and the emergence of biomedicines provides a promising alternative solution via the strategies of combining engineered design with modern advanced technology. This review explores the pathophysiological characteristics and related induction mechanisms of OD, and evaluates the current cutting-edge advances in its treatments. It emphasizes the potentials of biomedicines strategies such as hydrogels, nanoparticles and extracellular vesicles in improving therapeutic precision and efficacy. By mimicking natural physiological processes, and achieving controlled drug release, these advanced drug carriers are expected to address the challenges in ovarian microenvironment reprogramming, tissue repair, and metabolic and immune regulation. Despite the promising progress, there are still challenges in terms of biomedical complexity, differences between animal models and human physiology, and the demand for intelligent drug carriers in the therapy of OD. Future researches are mainly dedicated to developing precise personalized biomedicines in OD therapy through interdisciplinary collaboration, promoting the development of reproductive regenerative medicine.

Arson is classified as a violent crime,and often involves accelerants that significantly increase casualties and property damage.These accelerants,typically flammable liquids with low saturated vapor pressure,present volatile characteristic components in fire residues,making evidence preservation critical for accurate forensic analysis.In this study,the preservation performance of AMPAC(American KAPAC polyester sampling bags)and polyethylene(PE)evidence bags were evaluated under simulated field conditions(40 oC)through gas chromatography-mass spectrometry(GC-MS)technique,focusing on background interference,sealing integrity,and cross-contamination.The results demonstrated that AMPAC bags exhibited minimal background interference(C12?C14 alkanes detected after 3?7 days)and effective gasoline sealing,though slight losses of C2?C3 alkylbenzenes and trace cross-contamination were observed.In contrast,PE bags showed significant background hydrocarbons(C15?C19 alkanes)and pronounced gasoline component losses,including C2?C4 alkylbenzenes,naphthalenes,and indenes.Notably,severe cross-contamination of gasoline markers was detected in adjacent blank PE bags,with characteristic components such as C2?C4 alkylbenzenes,naphthalenes,methylnaphthalenes,dimethylnaphthalenes,indenes,indanes,methylindenes,and dimethylindenes identified,indicating substantial cross-contamination issues in PE evidence bags.Microstructural analysis revealed superior sealing in AMPAC bags attributed to their smooth,dense surface morphology compared to PE's rougher,porous structure.This study established a comprehensive evaluation framework for fire residue evidence containers,and found that PE bags were unsuitable for long-term gasoline evidence preservation due to compromised integrity.These findings provided critical references for forensic container selection in fire investigations.