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.

Hepatocellular carcinoma (HCC) is a lethal cancer with high morbidity rates worldwide. It is a major threat to public health in China, due to the combination of known and new risk factors, such as endemic hepatitis B virus (HBV), dietary aflatoxin exposure, and the occurrence of metabolic dysfunction-associated steatotic liver disease (MASLD). Although many methods for surveillance and multimodal therapies, such as surgery, local ablation, transarterial therapy, and new systemic agents, have been available, the survival rates of HCC remains poor. They have very limited durable responses, long post-treatment recurrence rates, and high resistance to treatment. This reflects an imperfect picture of the biological cause of the disease and a need for new mechanistic or targeted techniques. A significant characteristic of HCC, in common with other aggressive cancers, is the presence of reprogrammed, hyperactive cell metabolism. Tumor cells hijack metabolic pathways to promote their uncontrolled growth, stress survival, invasion and metastasis. While classical mechanisms such as the Warburg effect, lipid metabolism and glutamine utilization have been understood, the lysosome, which was once viewed as a static “waste disposal unit” to remove old organelles and proteins, is instead a dynamic signaling and metabolic core. The lysosomes incorporate nutrients, energy and stress signals by master regulators such as mTORC1 (activated on its surface) that balance anabolic growth and catabolic recycling to the cellular demands. In HCC, lysosomes are not passive, but are highly active and dysregulated. HCC cells upregulate lysosomes, which scavenge intracellular components via enhanced autophagy and engulf extracellular proteins via macropinocytosis, crucial for survival in the nutrient-poor, hypoxic tumor microenvironment. In addition to metabolism, lysosomes exhibit pro-invasive functions by secreting hydrolases to remodel the extracellular matrix, promote angiogenesis, and suppress stromal immune cells to foster a pro-tumor microenvironment. In a clinical context, lysosomes play an important role in therapeutic resistance: they sequester and inactivate chemotherapeutics via lysosomal sequestration, and enhanced autophagic flux protects the cell from therapy-induced damage, contributing to relapse, as lysosomal dysfunction is a key cause of treatment failure. This makes lysosomes promising yet challenging therapeutic targets in HCC. Recent preclinical and early clinical studies investigate multiple strategies to exploit the susceptibility of lysosomes: lysosome-specific agents, alkalinizing the lysosome lumen or inducing membrane permeabilization and lysosome-dependent cell death; pharmacological inhibition of key lysosomal enzymes or autophagy to impair nutrient recycling and stress adaptation; smart nanotherapeutic agents or antibody-drug conjugates, specifically activated in the acidic lysosomal environment or utilizing lysosomal pathways for efficient intracellular drug release; and combination strategies of lysosome-targeting agents with tyrosine kinase inhibitors or immunotherapy to overcome resistance and achieve synergistic antitumor effects. In summary, our review systematically presents the role of lysosomes in HCC, from metabolic reprogramming and microenvironmental adaptation to therapeutic resistance. By synthesizing the latest mechanistic insights and preclinical advances, this review highlights the indispensable role of lysosomes in the complex HCC biological network, emphasizing that an in-depth understanding of this dynamic organelle holds great promise for developing innovative, targeted therapies, offering new hope for improving the poor prognosis of global HCC patients.

Both cathartic colon （CC） and cathartic-dependent constipation （CDC） are caused by the abuse of stimulant laxatives， while their concepts are not completely the same.Starting from the disease name of CC， this article traced the origin and evolution of the concept of CC， summarizes and compared the similarities and differences between CC， CDC， and slow transit constipation （STC）， and called for strict differentiation among the three.Furthermore， this article explored the specific contents of Western medicine clinical subtypes and traditional Chinese medicine （TCM） syndrome differentiation of CDC and delved into the TCM pathogenesis of CDC according to both literature and clinical practice.The relationship between clinical subtypes and TCM syndromes was established， and the syndrome characteristics of CDC of different clinical subtypes and TCM syndromes were summarized.The recommended prescriptions for corresponding syndromes were listed.A systematic CDC diagnosis and treatment approach of "clinical subtypes-syndrome differentiation-syndrome characteristics-recommended prescriptions" was thus formed.Additionally， the paper provides an overview of current research on CDC in both Western medicine and TCM contexts， identifies future research directions， and suggests research pathways for refining and advancing CDC studies.

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.

ObjectiveTo evaluate and analyze the syndrome characteristics of Qi and Yin deficiency accompanied by Qi stagnation and blood stasis in a rhein-induced cathartic colon （CC） rat model. MethodsTwenty-four rats were divided into a normal group and a model group （CC group）. The rats were administered equal volumes of physiological saline or 2% rhein suspension by gavage to establish the model over three cycles （approximately 118 days）. The first cycle lasted 46 days， with a dosage of 12 mL·kg^-1·d^-1， administered every other day. The second cycle lasted 37 days， with a dosage of 12 mL·kg^-1·d^-1， administered for 5 consecutive days followed by 2 days of cessation. The third cycle lasted 35 days， with a dosage of 16 mL·kg^-1·d^-1， also administered for 5 consecutive days followed by 2 days of cessation. Each cycle ended when 80% of the rats no longer exhibited loose stools. Body mass， 24 h food intake， coat condition， and coat red （R）， green （G）， and blue （B） values were recorded. The open field test （OFT） was used to measure the total distance traveled to evaluate Qi deficiency. The body mass coefficient and 24 h water intake were recorded to assess Yin deficiency. The sucrose preference test （SPT） was used to determine the sucrose preference rate （SPR）， and the average speed in OFT was measured to evaluate depressive status （liver depression and Qi stagnation）. Tongue images and their R， G， and B values were recorded. Whole blood viscosity （WBV） and plasma viscosity （PV） were measured using an automatic hemorheological analyzer to evaluate blood stasis. A carbon ink propulsion test was performed to determine the intestinal transit rate （ITR） for disease model evaluation. Hematoxylin-eosin （HE） staining was used to observe histopathological changes in the colon. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of transient receptor potential ankyrin 1 （TRPA1） and tryptophan hydroxylase 1 （TPH1） in colon tissue. Western blot was used to detect the protein expression of TRPA1 and TPH1. ResultsIn terms of syndrome indicators， compared with the normal group， the body mass of the CC group decreased （P<0.05）， while 24 h food intake increased （P<0.01）. The coats of the CC group appeared withered， disheveled， and dull， and the R， G， and B values of the coat decreased （P<0.01）. The total distance traveled in OFT decreased （P<0.01）. The body mass coefficient decreased （P<0.01）， while 24 h water intake increased （P<0.05， P<0.01）. The SPR decreased （P<0.01）， and the average speed in OFT slowed （P<0.01）. The tongue appeared dark red， and the R， G， and B values of tongue images decreased （P<0.01）. WBV and PV increased （P<0.01）. Regarding disease indicators， compared with the normal group， the ITR decreased in the CC group （P<0.01）. Pathologically， HE staining showed necrosis and shedding of colonic mucosal epithelial cells， disruption of mucosal continuity， and infiltration of inflammatory cells in the lamina propria in the CC group. Semi-quantitative analysis showed increased HAI scores （P<0.05） and increased inflammatory cell counts and area proportion （P<0.05）. In terms of molecular biological indicators， compared with the normal group， the mRNA and protein expression levels of TRPA1 and TPH1 in colon tissue decreased in the CC group （P<0.05， P<0.01）. ConclusionThe rhein-induced CC rat model conforms to the traditional Chinese medicine syndrome characteristics of Qi and Yin deficiency accompanied by Qi stagnation and blood stasis.

OBJECTIVE To establish the UPLC fingerprint and the method for multi-component content determination in Jingangteng capsules， and to evaluate its quality by combining chemical pattern recognition analysis. METHODS An UPLC method was established. Separation was performed on a Zorbax SB-C 18 Rapid Resolution HD column， with acetonitrile-0.1% formic acid as the mobile phase for gradient elution.Using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicines （2012 edition）， UPLC fi ngerprints were established for 10 batches of Jingangteng capsules， and similarity was evaluated. SPSS 22.0 and SIMCA 14.1 software were used to perform hierarchial-cluster analysis and orthogonal partial least squares discriminant analysis （OPLS-DA）， respectively. The same UPLC method was employed to determine the contents of chlorogenic acid， 3，5-dihydroxy-2-methylbenzoic acid-3- O -glucoside （M1）， caffeic acid， astilbin， oxyresveratrol， quercitrin and resveratrol in the 10 batches of samples. RESULTS A total of 17 common peaks were identified in UPLC fingerprints of the 10 batches of samples， of which 7 were identified as chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol. The similarities of 10 batches of samples ranged from 0.820 to 0.985. The results of hierarchial-cluster analysis showed that 10 batches of samples were grouped into four categories： S1-S4 formed one group， S5 and S6 formed another， S7， S8 and S10 formed a third， and S9 formed a fourth， consistent with the OPLS-DA results； the variable importance projection values for peaks 7， 10， 2， 16 （resveratrol）， 13 （oxyresveratrol）， 11， 6 （caffeic acid）， 5 （M1） and 15 （quercitrin） were ＞1. Quantitative analysis results showed that the contents of chlorogenic acid， M1， caffeic acid， astilbin， oxyresveratrol， quercitrin， and resveratrol were 1.650 8-4.213 7， 0.636 2-2.161 7， 0.031 0-0.086 5， 0.239 1-1.069 3， 0.211 9-1.104 0， 0.488 8-2.399 2， and 0.164 0-0.699 8 mg/g， respectively. CONCLUSIONS UPLC fingerprint and content determination methods established in this study are simple to operate， accurate， reliable and reproducible； when combined with chemical pattern recognition analysis， they can be used to evaluate the quality of Jingangteng capsules. Nine components， such as resveratrol， oxyresveratrol， caffeic acid， M1 and quercitrin， may serve as markers of quality variation.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.