Background Gestational weight gain is closely related to maternal and infant health outcomes. Pregnant women are simultaneously exposed to four metals—lithium (Li), vanadium (V), uranium (U), and bismuth (Bi)—through inhalation of fine particulate matter and consumption of contaminated food and water. Existing studies suggest that exposure to these metals may be associated with gestational weight gain. However, no study has yet explored the complex relationships between exposure to mixtures of these four metals and weight gain at different stages of pregnancy. Objective To investigate the associations between mixed exposure to Li, V, U, and Bi in early pregnancy and the average weekly gestational weight gain during both early pregnancy and mid-to-late pregnancy. Methods This prospective study recruited eligible women in early pregnancy from an obstetrics clinic of a tertiary hospital in Jinan, China, between September 2021 and July 2023. Pre-pregnancy weight, current weight (at 11⁺⁰ to 13⁺⁶ weeks of gestation), and spot urine samples (≥5.0 mL) were collected at enrollment. Urinary concentrations of Li, V, Bi, and U were determined using inductively coupled plasma mass spectrometry. Participants were followed up in late pregnancy (≥28 weeks of gestation) to collect information on physical activity via questionnaire; weight measurements at the last antenatal visit (35⁺⁰ to 37⁺⁶ weeks of gestation) were obtained from the hospital information system. After adjusting for covariates, multiple linear regression and generalized additive models were used to assess the associations of individual metals with weekly weight gain in early pregnancy and in mid-to-late pregnancy. Bayesian kernel machine regression (BKMR) and quantile-based g-computation (Qgcomp) were applied to evaluate the joint effects of the metal mixture exposure on weekly weight gain at the two gestational stages. Results A total of 313 pregnant women were included. The geometric means of urinary Li, V, U, and Bi concentrations were 37.07, 0.20, 0.06, and 0.04 μg·L⁻¹, respectively; after creatinine adjustment, the corresponding values were 46.82, 0.25, 0.07, and 0.05 μg·g⁻¹ (Cr). The mean weekly gestational weight gain was (0.19±0.25) kg in early pregnancy and (0.53 ± 0.18) kg in mid-to-late pregnancy. Both multiple linear regression and generalized additive models showed that urinary V concentration was positively associated with average weekly gestational weight gain in early pregnancy, while no significant associations were found for other metals or for gestational weight gain in mid-to-late pregnancy. In the BKMR model with early-pregnancy weight gain as the outcome, V had the strongest association [posterior inclusion probability (PIP)=0.773]. When other metals were fixed at their medians, V showed a positive non-linear association with the outcome. A significant single-metal effect of V and its interaction with Li were observed. Compared with the 50th percentile of the metal mixture, the average weekly weight gain in early pregnancy increased by 0.016 (95%CI: 0.003, 0.029) and 0.018 (95%CI: 0.001, 0.036) at the 60th and 65th percentiles, respectively; conversely, at the 25th percentile, it decreased by 0.026 (95%CI: 0.002, 0.050). Overall, the joint effect of the metal mixture on early- pregnancy weight gain showed an upward trend. In the BKMR model for mid-to-late pregnancy gestational weight gain, all PIPs were<0.5, and no significant single-metal effects, interactions, or joint effects were identified. Qgcomp results confirmed a positive association between the metal mixture and early-pregnancy weight gain (b=0.031, 95%CI: 0.010, 0.051; P<0.01), with V contributing the highest positive weight (0.71). No significant association was found for weight gain in mid-to-late pregnancy (b=0.007, P=0.339). Conclusion Higher levels of co-exposure to the Li, V, Bi, and U metal mixture during early pregnancy may be associated with increased average weekly weight gain in early pregnancy. Among these metals, V exhibits a predominant role and appears to interact with Li. No association is observed between early-pregnancy metal mixture exposure and average weekly gestational weight gain in mid-to-late pregnancy. These findings suggest that monitoring and managing metal exposure during early pregnancy may be crucial for the rational regulation of gestational weight gain.

ObjectiveTo examine the influences of Shenfu injection on the endogenous metabolic byproducts in the myocardium of the rat model exhibiting chronic heart failure， thus deciphering the therapeutic mechanism of the Qi-reinforcing and Yang-warming method. MethodsSD rats were randomly allocated into a control group and a modeling group. Chronic heart failure with heart-Yang deficiency syndrome in rats was modeled by multi-point subcutaneous injection of isoproterenol， and the rats were fed for 14 days after modeling. The successfully modeled rats were randomized into model， Shenfu injection （6.0 mL·kg^-1）， and trimetazidine （10 mg·kg^-1） groups and treated with corresponding agents for 15 days. The control group and the model group were injected with equal doses of normal saline， and the samples were collected after the intervention was completed. Cardiac color ultrasound was performed. Hematoxylin-eosin （HE） staining was used to observe histopathological morphology， and the serum level of N-terminal pro-brain natriuretic peptide （NT-proBNP） was assessed by enzyme-linked immunosorbent assay （ELISA）. The mitochondrial morphological and structural changes of cardiomyocytes were observed by transmission electron microscopy， and the metabolic profiling was carried out by ultra high performance liquid chromatography-quantitative exactive-mass spectrometry （UHPLC-QE-MS）. Differential metabolites were screened and identified by orthogonal partial least squares-discriminant analysis （OPLS-DA） and other methods， and then the MetaboAnalyst database was used for further screening. The relevant biological pathways were obtained through pathway enrichment analysis. The receiver operating characteristic （ROC） curve was established to evaluate the diagnostic value of each potential biomarker for myocardial injury and the evaluation value for drug efficacy. ResultsThe results of color ultrasound showed that Shenfu Injection improved the cardiac function indexes of model rats （P<0.05）. The results of HE staining showed that Shenfu injection effectively alleviated the pathological phenomena such as myocardial tissue structure disorder and inflammatory cell infiltration in model rats. The results of ELISA showed that Shenfu injection effectively regulated the serum NT-proBNP level in the model rats. Transmission electron microscopy （TEM） showed that Shenfu injection effectively restored the mitochondrial morphological structure. The results of metabolomics showed that the metabolic phenotypes of myocardial samples presented markedly differences between groups. Nine differential metabolites could be significantly reversed in the Shenfu injection group， involving three metabolic pathways： pyruvate metabolism， histidine metabolism， and citric acid cycle （TCA cycle）. The results of ROC analysis showed that the area under the curve （AUC） values of all metabolites were between 0.75 and 1.0， indicating that the differential metabolites had high diagnostic accuracy for myocardial injury， and the changes in their expression levels could be used as potential markers for efficacy evaluation. ConclusionShenfu injection significantly alleviated the damage of cardiac function， myocardium， and mitochondrial structure in the rat model of chronic heart failure with heart-Yang deficiency syndrome by ameliorating energy metabolism remodeling. Reinforcing Qi and warming Yang is a key method for treating chronic heart failure with heart-Yang deficiency syndrome.

Objective: To identify the structure of the complementarity determining region (CDRs), the V(D)J rearrangement and somatic hypermutational characteristics of the heavy and light chains of a red blood cell blood group-specific monoclonal antibody. Methods: The hybridoma cell line secreting human IgM κ monoclonal anti-P antibody was used as the research object. Total RNA was extracted from cultured monoclonal cell line, and cDNA was obtained by reverse transcription PCR (RT-PCR) using random hexamers primers. It was then amplified and sequenced using primers specific for variable regions of the immunoglobulin heavy and light chains encoding the anti-P antibody. The sequences were aligned against the NCBI database using online Immunoglobulin BLAST (Ig-BLAST) tool. Results: The study determined the structure of the CDRs and framework regions (FRs) of the variable regions of human monoclonal anti-P immunoglobulin, as well as the characteristics of V(D)J rearrangement. Moreover, the closest VH, VD, and VJ germline alleles for the heavy chain and VL and VJ germline alleles for the light chain were also identified. The IgH gene rearrangment pattern of the monoclonal anti-P was IGHV6-1 * 01—IGHD5-18 02—IGHJ4 02 and IgL gene was IGκV1-12 01—IGκJ3 01. Nine base mutations occurred within the germline gene IGHV6-1 01 in variable region of heavy chain, whereas 5 base mutations were found in the germline gene IGκV1-12 01 in variable region of light chain, respectively. Conclusion: This study characterized the CDR structure in monoclonal antibody cell line targeting the high-frequency red blood cell P antigen, and provided a foundation for the construction of recombinant antibody expressing plasmids and transfomation of the immunoglobulin type.

ObjectiveTo evaluate the corrective effects of a three-stage structured Tai Chi training program on abnormal neck and shoulder posture from a biomechanical perspective. MethodsEighty-two participants with abnormal neck and shoulder posture were randomly assigned to a treatment group and a control group， with 41 participants in each group. The treatment group received three-stage structured Tai Chi training six times per week， while the control group received online health education once per week. Both interventions lasted for 12 weeks. The primary outcome cervical postural deviation angle， and the secondary outcomes including cervical loading and bilateral shoulder horizontal deviation angle， were assessed before intervention， after 6 weeks and 12 weeks of intervention. Safety was also evaluated. ResultsUltimately， 40 participants from each group were included in the analysis. In the treatment group， cervical postural deviation angle and cervical spine loading were significantly reduced after 12 weeks of intervention compared with baseline and after 6 weeks of intervention. The bilateral shoulder horizontal deviation angle decreased significantly after both 6 and 12 weeks of intervention compared with baseline （P＜0.05）. In the control group， cervical spine loading was reduced after 6 and 12 weeks of intervention compared with baseline （P＜ 0.05）. After 12 weeks of intervention， the treatment group showed lower cervical postural deviation angle and bilateral shoulder horizontal deviation angle than the control group， whereas cervical loading was higher in the treatment group after 6 weeks of intervention （P＜0.05）. Significant differences were observed between groups in the changes from baseline to week 12 for cervical postural deviation angle and bilateral shoulder horizontal deviation angle， as well as in the changes from baseline to week 6 for cervical loading and bilateral shoulder horizontal deviation angle （P＜ 0.05）. No significant adverse events occurred in either group during the intervention period. ConclusionThree-stage structured Tai Chi can effectively improve abnormal neck and shoulder posture， demonstrating good safety and feasibility.

Objective To examine the impact of climate, land use and their interaction effect on the population density of Oncomelania hupensis. Methods O. hupensis snail surveillance data in Yunnan Province from 2013 to 2022 were obtained from the National Information System for Parasitic Diseases Prevention and Control of Chinese Information System for Disease Control and Prevention, and the density of living snails was calculated in each county-level administrative district. Climate data were obtained from the China Meteorological Forcing Dataset version 2.0, and land use data were captured from the China Land Cover Dataset. The raster climate data and land use data were clipped to the administrative border of Yunnan Province in the R package version 4.5, and the climate data were resampled to a spatial resolution of 30 m × 30 m consistent with the land use data using bilinear interpolation. Annual meteorological indicators were extracted from each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022, including average temperature, maximum temperature, minimum temperature, temperature difference, average precipitation rate, maximum precipitation rate, minimum precipitation rate, downward shortwave radiation flux, downward longwave radiation flux, air pressure, wind speed, specific humidity and relative humidity. Annual land use structure and landscape pattern index in each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022 were extracted and calculated, including the proportion of areas occupied by each type of land use, patch density, largest patch index, landscape separation index, landscape fragmentation index, landscape segmentation index, contagion index, patch cohesion index, edge density, and shape index. Land use entropy index was introduced to represent the degree of habitat fragmentation and ecological niche breadth. The density of living snails and environmental factors were subjected to rank correlation analysis, and variables with no statistically significant correlation (P>0.1) were excluded. Then, a correlation coefficient matrix was constructed, and |r_s| of 0.85 and greater was defined as the threshold of high collinearity. For highly correlated variables in each group, indicators with a more biological explanatory power or a better statistical efficiency were retained. A generalized additive model (GAM) was constructed with O. hupensis snail density as a response variable and screened environmental variables as independent variables, and the model performance was evaluated using the variance explained. Results The area occupied by O. hupensis snail habitats was 1 056 to 1 680 hm² in Yunnan Province from 2013 to 2022, appearing an overall tendency towards a decline; however, the density of living snails appeared a tendency towards a slight rise. Based on the correlation coefficient matrix, 14 core explanatory variables were retained, including farmland, water bodies, bare land, impervious surface, landscape separation index, landscape fragmentation index, edge density, shape index, land use entropy index, downward longwave radiation flux, downward shortwave radiation flux, maximum temperature, minimum precipitation rate and specific humidity. Two types of GAM were constructed, including the main-effects model without interaction terms and the interaction model with interaction terms. The corrected Akaike information criterion (AICc) of the optimal main-effects model was −285.223, and the core variables included bare land, impervious surface, landscape separation index, edge density, shape index, land use entropy index and downward shortwave radiation flux. Following introduction of second-order interaction terms, the AICc value of the optimal interaction model was −345.526, and the significant interaction combinations included: farmland × impervious surface, farmland × landscape separation index, farmland × shape index, farmland × land use entropy index, impervious surface × landscape separation index, impervious surface × edge density, and shape index × downward shortwave radiation flux. The proportion of the main-effects model explaining the variation of O. hupensis snail density was 39.8%, and the explanatory power of GAM increased to 79.0% following introduction of interaction terms. Conclusion Landscape separation index, edge density, shape index and other landscape pattern indicators pose significant impacts on the intensity and direction of changes in O. hupensis snail density in Yunnan Province.

This study establishes an integrated research paradigm based on traditional Chinese medicine （TCM） theory， guided by pathological characteristics， centered on formula compatibility principles， and supported by multidisciplinary technologies， to systematically analyze the mechanisms of hepatotoxicity induced by toxic Chinese herbal medicinals and strategies for reducing toxicity through compatibility. The findings revealed that the pathomechanism aligns closely with the "liver aversion to acute irritation" theory from Inner Canon of Yellow Emperor （《黄帝内经》）. The core pathology involves an imbalance between liver's form and function， which is characterized by malnourishment of liver form due to yin-blood depletion and dysfunction in ascending-dispersing and free-flowing activities， and closely linked to modern pathological mechanisms such as microcirculatory disturbances， oxidative stress， inflammatory response， metabolic disorder and gut-liver axis dysregulation. Based on this， a multi-layered compatibility strategy for toxicity reduction is put forward， which involves using sweet medicinals to alleviate urgency， balancing the liver form and its function， and pre-regulating other organs. This provides a theoretical basis for the safe application of toxic Chinese herbal medicinals.

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.

OBJECTIVE To establish a method for simultaneous determination of venetoclax， busulfan and voriconazole in plasma of patients with acute myeloid leukemia （AML）， and apply it clinically. METHODS Plasma samples were subjected to protein precipitation using acetonitrile and subsequently analyzed by liquid chromatography-tandem mass spectrometry （LC-MS/MS） using venetoclax-D 8 ， busulfan-D 8 and posaconazole as internal standards. The separation was performed on a Phenomenex Kinetex ® C 18 column with a mobile phase composed of 0.1% formic acid solution （2 mmol/L ammonium acetate）-0.1% formic acid in acetonitrile （gradient elution） at a flow rate of 0.8 mL/min. The column temperature was set at 40 ℃， the sample size was 5 μL， and the total run time was 3.10 min. An electrospray ionization source was employed， and positive ion scanning was conducted using multiple reaction monitoring mode. The ion pairs used for quantitative analysis included m/z 868.4→636.3 （venetoclax）， m/z 264.1→151.1 （busulfan）， and m/z 350.1→224.0 （voriconazole）. The above LC-MS/MS method was adopted to determine plasma concentrations of venetoclax and voriconazole in 10 AML patients， as well as plasma concentration of busulfan in 5 patients undergoing conditioning treatment for allogeneic hematopoietic stem cell transplantation. RESULTS The linear ranges of venetoclax， busulfan and voriconazole were 50-10 000， 15-3 000 and 50-10 000 ng/mL， respectively （ R 2 ≥0.999 0）， with lower limits of quantification of 50， 15 and 50 ng/mL， respectively. The RSDs of intra-day and inter-day precision tests for all three analytes were all less than 10%， with accuracy （relative errors） ranging from －10.00% to 12.96%. The average extraction recovery ranged from 92.54% to 100.95%， and the average matrix effect was 89.98%-101.49%. Dilution reliability covered all dilution factors used in the test samples， and the absolute values of relative errors in stability tests were all≤16.25%. The plasma concentrations of venetoclax， busulfan and voriconazole in enrolled patients were 496.20-4 250.45， 233.48-2 002.28 and 475.51-5 710.18 ng/mL， respectively. CONCLUSIONS The LC-MS/MS method established in this study is rapid， sensitive and easy to operate， and can be used for the therapeutic drug monitoring of venetoclax， busulfan and voriconazole.

ObjectiveTo investigate the association of the traditional Chinese medicine （TCM） syndrome types of primary liver cancer （PLC） with clinical features and multimodal quantitative radiological features on computed tomography （CT） and magnetic resonance imaging （MRI）， and to provide a reference for the objectification of TCM syndrome differentiation and precise diagnosis and treatment. MethodsA retrospective analysis was performed for the clinical data of 312 patients who were diagnosed with PLC in The First Affiliated Hospital of Hunan University of Chinese Medicine from March 2020 to June 2025， and according to the TCM syndrome type， they were divided into stagnation of liver Qi group with 40 patients， stagnation of liver Qi and spleen deficiency group with 109 patients， Qi stagnation and blood stasis group with 62 patients， dampness-heat toxin amassment group with 81 patients， and liver-kidney Yin deficiency group with 20 patients. Clinical features and multimodal quantitative radiological features were compared between the patients with different TCM syndrome types. A one-way analysis of variance was used for comparison of normally distributed continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups； the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between multiple groups， and the Dunn’s multiple test was used for further comparison between two groups； the chi-square test was used for comparison of categorical data between groups， and the Bonferroni method was used for further comparison between two groups. ResultsThere were significant differences between the patients with different TCM syndrome types in China liver cancer staging （CNLC）， Child-Pugh class， alanine aminotransferase， aspartate aminotransferase， albumin， direct bilirubin， total bilirubin， prothrombin time， neutrophil， and albumin-bilirubin score （all P<0.05）. In the stagnation of liver Qi group， the patients with Child-Pugh class A accounted for 75.00%； among the patients with CNLC stage I PLC， the patients with stagnation of liver Qi accounted for 60.00%， and those with Qi stagnation and blood stasis syndrome accounted for 59.68%， while among the patients with CNLC stage IV PLC， the distribution proportion of dampness-heat toxin amassment （27.16%） and liver-kidney Yin deficiency （30.00%） was significantly higher than that of stagnation of liver Qi （2.50%） （all P<0.05）. Radiological examination showed that there were significant differences between the patients with different TCM syndrome types in the number of tumors， ascites， venous tumor thrombus， maximum tumor diameter， intrahepatic metastasis， and lymph node metastasis in the hepatic hilar and retroperitoneal regions （all P<0.05）. Compared with the patients with stagnation of liver Qi， the patients with liver depression and spleen deficiency or liver-kidney Yin deficiency were more likely to develop intrahepatic metastasis； the patients with liver depression and spleen deficiency， dampness-heat toxin amassment， or liver-kidney Yin deficiency were more likely to develop lymph node metastasis in the hepatic hilar and retroperitoneal regions； the patients with liver-kidney Yin deficiency were more likely to experience multiple tumors； the patients with liver depression and spleen deficiency or dampness-heat toxin amassment were more likely to develop ascites （all P<0.05）. Compared with the patients with Qi stagnation and blood stasis syndrome， the patients with liver depression and spleen deficiency had a significantly longer maximum tumor diameter and a significantly higher proportion of patients with venous tumor thrombus （both P<0.05）. Furthermore， among the 184 patients with MRI diffusion-weighted imaging sequences， the patients with dampness-heat toxin amassment or Qi stagnation and blood stasis syndrome had significantly higher ADC values and relative ADC values than those with stagnation of liver Qi （all P<0.05）. ConclusionThere are significant differences in CT/MRI radiological features and clinical features between PLC patients with different TCM syndrome types， among whom the patients with liver depression and spleen deficiency， dampness-heat toxin amassment， and liver-kidney Yin deficiency tend to exhibit progressive radiological features， and those with dampness-heat toxin amassment or Qi stagnation and blood stasis syndrome tend to have higher ADC values. These findings provide an objective basis for TCM syndrome differentiation in PLC.