Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

This paper aimed to systematically evaluate the effects of hypoxic training at different fraction of inspired oxygen (FiO₂) on body composition, glucose metabolism, and lipid metabolism in obese individuals, and to determine the optimal oxygen concentration range to provide scientific evidence for personalized and precise hypoxic exercise prescriptions. A systematic search was conducted in the Cochrane Library, PubMed, Web of Science, Embase, and CNKI databases for randomized controlled trials and pre-post intervention studies published up to March 31, 2025, involving hypoxic training interventions in obese populations. Meta-analysis was performed using RevMan 5.4 software to assess the effects of different fraction of inspired oxygen (FiO₂≤14% vs. FiO₂>14%) on BMI, body fat percentage, waist circumference, fasting blood glucose, insulin, HOMA-IR, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), with subgroup analyses based on oxygen concentration. A total of 22 studies involving 292 participants were included. Meta-analysis showed that hypoxic training significantly reduced BMI (mean difference (MD)=-2.29,95%CI: -3.42 to -1.17, P<0.000 1), body fat percentage (MD=-2.32, 95%CI: -3.16 to -1.47, P<0.001), waist circumference (MD=-3.79, 95%CI: -6.73 to -0.85, P=0.01), fasting blood glucose (MD=-3.58, 95%CI: -6.23 to -0.93, P=0.008), insulin (MD=-1.60, 95%CI: -2.98 to -0.22, P=0.02), TG (MD=-0.18, 95%CI: -0.25 to -0.12, P<0.001), and LDL-C (MD=-0.25, 95%CI: -0.39 to -0.11, P=0.000 3). Greater improvements were observed under moderate hypoxic conditions with FiO₂>14%. Changes in HOMA-IR (MD=-0.74, 95%CI: -1.52 to 0.04,P=0.06) and HDL-C (MD=-0.09, 95%CI: -0.21 to 0.02, P=0.11) were not statistically significant. Hypoxic training can significantly improve body composition, glucose metabolism, and lipid metabolism indicators in obese individuals, with greater benefits observed under moderate hypoxia (FiO>14%). As a key parameter in hypoxic exercise interventions, the precise setting of oxygen concentration is crucial for optimizing intervention outcomes.

A primary hallmark of pathological cardiac hypertrophy is excess protein synthesis due to enhanced translational activity. However, regulatory mechanisms at the translational level under cardiac stress remain poorly understood. Here we examined the translational regulations in a mouse cardiac hypertrophy model induced by transaortic constriction (TAC) and explored the conservative networks versus the translatome pattern in human dilated cardiomyopathy (DCM). The results showed that the heart weight to body weight ratio was significantly elevated, and the ejection fraction and fractional shortening significantly decreased 8 weeks after TAC. Puromycin incorporation assay showed that TAC significantly increased protein synthesis rate in the left ventricle. RNA-seq revealed 1,632 differentially expressed genes showing functional enrichment in pathways including extracellular matrix remodeling, metabolic processes, and signaling cascades associated with pathological cardiomyocyte growth. When combined with ribosome profiling analysis, we revealed that translation efficiency (TE) of 1,495 genes was enhanced, while the TE of 933 genes was inhibited following TAC. In DCM patients, 1,354 genes were upregulated versus 1,213 genes were downregulated at the translation level. Although the majority of the genes were not shared between mouse and human, we identified 93 genes, including Nos3, Kcnj8, Adcy4, Itpr1, Fasn, Scd1, etc., with highly conserved translational regulations. These genes were remarkably associated with myocardial function, signal transduction, and energy metabolism, particularly related to cGMP-PKG signaling and fatty acid metabolism. Motif analysis revealed enriched regulatory elements in the 5' untranslated regions (5'UTRs) of transcripts with differential TE, which exhibited strong cross-species sequence conservation. Our study revealed novel regulatory mechanisms at the translational level in cardiac hypertrophy and identified conserved translation-sensitive targets with potential applications to treat cardiac hypertrophy and heart failure in the clinic.
Animals ; Humans ; Cardiomegaly/physiopathology* ; Ribosomes/physiology* ; Protein Biosynthesis/physiology* ; Mice ; Cardiomyopathy, Dilated/genetics* ; Ribosome Profiling

The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Molecular Structure ; Asteraceae/chemistry* ; Chromatography, High Pressure Liquid ; Magnetic Resonance Spectroscopy

In order to compare the differences in growth and secondary metabolite accumulation of Panax quinquefolius between understory and field planting, growth indexes, photosynthetic characteristics, soil enzyme activities, secondary metabolite contents, and antioxidant activities of P. quinquefolius under different planting modes were examined and compared, and One-way analysis of variance(ANOVA) and correlation analyses were carried out by using the software SPSS 25.0 and GraphPad Prism 9.5. The Origin 2021 software was used for plotting. The results showed that compared with those under field planting, the plant height, leaf length, leaf width, photosynthetic rate, and chlorophyll content of P. quinquefolius under understory planting were significantly reduced, and arbuscular mycorrhizal fungi(AMF) infestation rate and infestation intensity, ginsenoside content, and antioxidant activity were significantly increased. The activities of inter-root soil urease, sucrase, and catalase increased, while the activities of non-inter-root soil urease and alkaline phosphatase increased. Correlation analyses showed that the plant height and leaf length of P. quinquefolius plant were significantly positively correlated with net photosynthetic rate, transpiration rate, chlorophyll content, and electron transfer rate(P<0.05), while ginsenoside content was significantly negatively correlated with net photosynthetic rate, chlorophyll content, and electron transfer rate(P<0.05) and significantly positively correlated with AMF infestation rate and infestation intensity(P<0.05). In addition, ginsenoside content was significantly positively correlated with the activities of inter-root soil sucrase, urease, and catalase(P<0.05). This study provides basic data for revealing the mechanism of secondary metabolite accumulation in P. quinquefolius under understory planting and for exploring and practicing the ecological mode of P. quinquefolius under understory planting.
Panax/microbiology* ; China ; Secondary Metabolism ; Soil/chemistry* ; Photosynthesis ; Plant Leaves/metabolism* ; Chlorophyll/metabolism* ; Mycorrhizae

This study aims to systematically characterize the targeted effects of Quanduzhong Capsules on cartilage lesions in knee osteoarthritis by integrating spatial transcriptomics data mining and animal experiments validation, thereby elucidating the related molecular mechanisms. A knee osteoarthritis model was established using Sprague-Dawley(SD) rats, via a modified Hulth method. Hematoxylin and eosin(HE) staining was employed to detect knee osteoarthritis-associated pathological changes in knee cartilage. Candidate targets of Quanduzhong Capsules were collected from the HIT 2.0 database, followed by bioinformatics analysis of spatial transcriptomics datasets(GSE254844) from cartilage tissues in clinical knee osteoarthritis patients to identify spatially specific disease genes. Furthermore, a "formula candidate targets-spatially specific genes in cartilage lesions" interaction network was constructed to explore the effects and major mechanisms of Quanduzhong Capsules in distinct cartilage regions. Experimental validation was conducted through immunohistochemistry using animal-derived biospecimens. The results indicated that Quanduzhong Capsules effectively inhibited the degenerative changes in the cartilage of affected joints in rats, which was associated with the regulation of Quanduzhong Capsules on the thioredoxin-interacting protein(TXNIP)-NOD-like receptor family pyrin domain containing 3(NLRP3)-bone morphogenetic protein receptor type 2(BMPR2)-fibronectin 1(FN1)-matrix metallopeptidase 2(MMP2) signal axis in the articular cartilage surface and superficial zones, subsequently inhibiting cartilage matrix degradation leading to oxidative stress and inflammatory diffusion. In summary, this study clarifies the spatially specific targeted effects and protective mechanisms of Quanduzhong Capsules within pathological cartilage regions in knee osteoarthritis, providing theoretical and experimental support for the clinical application of this drug in the targeted therapy on the inflamed cartilage.
Animals ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Male ; Humans ; Capsules ; Female ; Disease Models, Animal

Based on latent structure model and association rule analysis, this study investigates the prescription patterns used by professor YANG Zhong-qi in treating hypertension with traditional Chinese medicine(TCM) and infers the associated TCM syndromes, providing a reference for clinical syndrome differentiation and treatment. The observation window spanned from January 8, 2013, to June 26, 2024, during which qualified herbal decoction prescriptions meeting efficacy criteria were extracted from the outpatient medical record system of the First Affiliated Hospital of Guangzhou University of Chinese Medicine and compiled into a standardized database. Statistical analysis of high-frequency herbs included frequency counts and herbal property-channel tropism analysis. Latent structure modeling and association rule analysis were performed using R 4.3.2 and Lantern 5.0 software to identify core herbal combinations and infer TCM syndrome patterns. A total of 2 436 TCM prescriptions were included in the study, involving 263 drugs with a cumulative frequency of 29 783. High-frequency herbs comprised Uncariae Ramulus cum Uncis, Poria, Glycyrrhizae Radix et Rhizoma, Puerariae Lobatae Radix, and Alismatis Rhizoma, predominantly categorized as deficiency-tonifying, heat-clearing, and blood-activating and stasis-resolving herbs. Latent structure analysis identified 18 latent variables, 74 latent classes, 5 comprehensive clustering models, and 15 core herbal combinations, suggesting that the core syndrome clusters include liver Yang hyperactivity pattern, Yin deficiency with Yang hyperactivity pattern, phlegm-stasis intermingling pattern, and liver-kidney insufficiency pattern. Association rule analysis revealed 22 robust association rules. RESULTS:: indicate that hypertension manifests as a deficiency-rooted excess manifestation, significantly associated with functional dysregulation of the liver, lung, spleen-stomach, heart, and kidney. Key pathogenic mechanisms involve liver Yang hyperactivity, phlegm-stasis interaction, and liver-kidney insufficiency. Therapeutic strategies should prioritize liver-calming, spleen-fortifying, and deficiency-tonifying principles, supplemented by dynamic regulation of Qi-blood and Yin-Yang balance according to syndrome evolution, alongside pathogen-eliminating methods such as phlegm-resolving and stasis-dispelling. Synergistic interventions like mind-tranquilizing therapies should be tailored to individual conditions.
Hypertension/drug therapy* ; Drugs, Chinese Herbal/therapeutic use* ; Humans ; Medicine, Chinese Traditional ; Drug Prescriptions ; Latent Class Analysis

This study systematically analyzed the global research landscape, technological composition, and core patents in the field of networks target and network pharmacology, and proposes further suggestions based on the IncoPat patent citation database and VOSviewer bibliometric network visualization tool. Using patent literature metrics and scientific knowledge mapping method, technological innovation pathways, research hotspots, and future directions in this field were further revealed. In particular, this field is moving towards data-driven, intelligent, and systematic approaches. Patent analysis indicated that most patent applications in this domain focused on traditional Chinese medicine(TCM), which have provided key engineering technical approaches to explore and solve complex problems of TCM. By integrating big data and artificial intelligence technologies, network targets and network pharmacology have conferred high-precision screening and quality control of key components and targets in herbal formulations and prescriptions, accelerating the clinical translation and industrialization of TCM-based new drugs and health products with medicine-food homology. Therefore, it is essential to optimize the patent protection system and establish integrated technology platforms in this field for ensuring the competitiveness of technological achievements in research and clinical application. These efforts will advance the widespread application and high-quality development of TCM modernization, precision medicine, and innovative drug discovery.
Bibliometrics ; Patents as Topic ; Humans ; Medicine, Chinese Traditional ; Network Pharmacology/trends* ; Drugs, Chinese Herbal/pharmacology*