Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

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.

Alcoholic liver disease(ALD), a major cause of chronic liver disease worldwide, poses a serious threat to human health. Despite the availability of various drugs for treating ALD, their efficacy is often uncertain, necessitating the search for new therapeutic approaches. Traditional Chinese medicine polysaccharides have garnered increasing attention in recent years due to their versatility, high efficiency, and low side effects, and they have demonstrated significant potential in preventing and treating ALD. Emerging studies have suggested that these polysaccharides exert their therapeutic effects through multiple mechanisms, including the inhibition of oxidative stress and the regulation of lipid metabolism, gut microbiota, and programmed cell death. This review summarizes the recent research progress in the pharmacological effects and regulatory mechanisms of traditional Chinese medicine polysaccharides in treating ALD, aiming to provide a scientific basis and theoretical support for their application in the prevention and treatment of ALD.
Humans ; Liver Diseases, Alcoholic/metabolism* ; Polysaccharides/administration & dosage* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Oxidative Stress/drug effects* ; Medicine, Chinese Traditional ; Gastrointestinal Microbiome/drug effects* ; Lipid Metabolism/drug effects*

The inheritance, innovation, and development of traditional Chinese medicine(TCM) need to be based on Chinese medicinal materials. The TCM seed industry is the source of TCM production, which is related to the stable supply and quality safety of TCM. This paper summarizes the basic situation of the TCM seed industry and introduces relevant policies and regulations to TCM seeds in the seed industry and the TCM field. At present, the Management Measures of TCM Seeds and Seedlings has not yet promulgated, and TCM seeds are classified as non-major crops in the category of crops for management. This paper also describes the current situation of TCM seed and seedling system construction, which is in the development stage, from six aspects, including the construction of TCM seed industry technical support system; the establishment of TCM seed standard; the construction of germplasm resource preservation system; TCM seed testing, variety registration, and variety protection; production and management of TCM seeds; TCM seed supervision. According to the development status of the TCM seed industry, four problems are put forward, including imperfect systems and standards relevant to TCM seeds, insufficient supervision and law enforcement regarding TCM seeds, insufficient policy measures and capital investment to promote the development of the industry, and the industry's falling into a low-level cycle.Accordingly, four suggestions are provided, including improving laws, regulations, and policies, perfecting standards and norms,strengthening supervision and law enforcement, and promoting support system construction, in order to boost the high-quality development of the TCM seed industry.
Seeds/chemistry* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/standards* ; Plants, Medicinal/chemistry*

The patient, assigned female at birth and aged 1 year and 7 months, presented with clinical manifestations of 46,XY disorders of sex development. The external genitalia exhibited a severely undermasculinized phenotype. Laboratory tests and gonadal biopsy indicated poor Leydig cell function and good Sertoli cell function. Genetic testing revealed compound heterozygous mutations of c.867-2A>C and c.547G>A (p.G183R) in the LHCGR gene. The patient was ultimately diagnosed with type II Leydig cell hypoplasia. Type II Leydig cell hypoplasia presents a broad spectrum of clinical phenotypes, characterized by a lack of parallel function between Leydig cells and Sertoli cells, and significant individual variability in spermatogenesis and gender assignment. This condition should be considered when there is poor Leydig cell function but good development of Wolffian duct derivatives.
Female ; Humans ; Infant ; Disorder of Sex Development, 46,XY/genetics* ; Leydig Cells/pathology* ; Mutation ; Receptors, LH/genetics* ; Testis/abnormalities*

OBJECTIVE: To elucidate the mechanism of Banxia Houpo Decoction (BHD) in treating gastroesophageal reflux disease (GERD) by integrating and utilizing the compound analysis, network pharmacology, and empirical verification. METHODS: Ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was utilized to identify the primary compounds in BHD. Network pharmacology was employed to retrieve target genes. A GERD rat model was developed and 32 SD rats were randomly divided into model, BHD-L (3 g/kg), BHD-H (6 g/kg), and mosapride (0.75 mg/kg) groups using a random number table, 8 rats in each group. Eight rats without the construction of a GERD model were selected as the blank group. Esophageal damage was evaluated through visualization and histopathology evaluation. 5-hydroxytryptamine (5-HT) levels in serum and lower esophageal sphincter (LES) were determined by ELISA. LES contractility was measured with a force transducer, and serotonin transporter (SERT) and 5-HT4R expressions in LES were assessed by RT-PCR, Western blot, and immunofluorescence staining, respectively. RESULTS: UPLC-HRMS analysis identified 37 absorption peaks and 157 compounds in BHD. Functional enrichment identified SERT as a significant target for LES contractility. Histopathological findings indicated less severe esophageal mucosal damage in the BHD-H group compared with the model group. Although serum 5-HT levels showed no significant difference, 5-HT concentration in LES tissue was notably higher in the BHD-H group (P<0.05). Within the range from 10^-10 to 10^-7 mmol/L, LES contractility in the BHD-H and mosapride groups was significantly increased (P<0.05). Within the range from 3 × 10^-7 to 3 × 10^-6 mmol/L 5-HT, LES contractility in the BHD-H group was increased (P<0.05). No significant difference was detected within the range from 10^-5 to 10^-4 mmol/L 5-HT. Notably, SERT expression in the BHD-H group assessed by RT-PCR, Western blot, and immunofluorescence staining were significantly lower than that in the model group (all P<0.01); while 5-HT4R expression remained unchanged. CONCLUSION BHD may increase LES contractility by inhibiting SERT expression in LES tissue.
Animals ; Gastroesophageal Reflux/physiopathology* ; Drugs, Chinese Herbal/chemistry* ; Rats, Sprague-Dawley ; Network Pharmacology ; Male ; Serotonin/metabolism* ; Rats ; Disease Models, Animal ; Serotonin Plasma Membrane Transport Proteins/metabolism* ; Esophagus/drug effects*

Objective:To explore the feasibility of using low-dose computed tomography(LDCT)with deep learning reconstruction(DLR)on the chest for the screening of lung nodules,and to compare the image quality and detection rate of nodules between LDCT and routine dose CT(RDCT)-DLR.Methods:A total of 104 overweight or obese patients[body mass index(BMI)≥25 kg/m2]who received CT examination on chest due to pulmonary nodule screening from September to December 2023 were included to conduct prospective study.All patients underwent respectively RDCT(120 kV)and LDCT(100 kV)scans,all of the two scans used the modulation of automatic tube current,and adopted deep learning AI algorithm ClearInfinity to conduct reconstruction(RDCT:CI 40%,LDCT:CI 50%).Radiation dose and nodules number of them were recorded.At the T8 vertebral level,CT values(Hounsfield Units,HU)of mediastinal fat and lung parenchyma in the right lower lobe were measured,along with image noise(standard deviation,SD).The signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were subsequently calculated.Two radiologists independently performed subjective evaluations of image quality and pulmonary nodules using a Likert 4-point scale.Paired t-tests or Wilcoxon rank-sum test were employed to compare differences in radiation dose,objective image noise,and subjective scores between LDCT and RDCT.Results:A total of 104 patients were enrolled,including 54 males and 50 females,with a mean age of 52±13 years and a BMI of(27.77±2.64)kg/m2.The effective radiation dose of LDCT demonstrated a statistically significant reduction compared to RDCT(Z=-8.853,P<0.001),with a mean effective radiation dose reduction of 77.86%.The differences in lung CT value,lung noise,fat noise,lung parenchyma SNR,fat SNR and CNR of images between two groups were significant(Z=-3.022,-2.327,-4.785,-2.059,-3.765,-4.013,P<0.05),while there were not significant differences in the comparisons for fat CT value and lung parenchyma SNR(P>0.05).The image contrast,image noise,and subjective score for image quality of lung nodule of LDCT were lower than those of RDCT(t=2.877,2.387,5.096,P<0.05),but all subjective scores of that were>3,which can meet the requirements of clinical diagnosis.In terms of nodule detection,RDCT found out about 418 nodules,while LDCT found out about 421,the false positive rate of LDCT only was 0.72%.Conclusion:In overweight or obese patients,LDCT that combined with DLR algorithm on chest is equivalent to RDCT on image quality and the detection rate of lung nodule,and it significantly reduce radiation exposure on patients at the same time.

Metastasis is one of the main causes of death in lung cancer,and tumor microenvironment(TME)disorders promote the formation of Kenang and accelerate lung cancer metastasis.The theory of"Kenang"in TCM is of great significance in explaining the pathogenesis of lung cancer metastasis and guiding clinical treatment.Based on the theory of"Kenang",this article discussed the pathogenesis and treatment of TME disorder in lung cancer metastasis,and analyzed the mechanism of Kenang in the process of lung cancer metastasis based on the pathological mechanism of Kenang formation and its similarity with TME disorder,combined with modern medical research results.The dynamic pathogenesis evolution of"healthy qi deficiency-phlegm-stasis-cancerous toxin"runs through the course of Kenang and lung cancer,and is closely related to the hypoxia,angiogenesis,and inflammatory microenvironment contained in TME disorders.Therefore,this article proposed a hypothesis that TME disorder may be the key to promote the formation of Kenang and accelerate the metastasis of lung cancer.The metastasis of lung cancer should be prevented and treated by the ideas of strengthening the healthy qi and promoting qi circulation,dissolving phlegm and removing stasis,clearing heat and detoxifying,so as to provide a theoretical for the prevention and treatment of lung cancer metastasis by integrated traditional Chinese and Western medicine.

Cervical spinal cord injury without fracture-dislocation (CSCIWFD) is referred to as a special type of cervical spinal cord injury characterized by traumatic spinal cord dysfunction and no significant bony structural abnormalities on imagines. Duo to the high risk of missed diagnosis during the initial consultation, CSCIWFD may lead to progressive neurological deterioration or even complete paralysis, severely impacting patients′ prognosis. Currently, there are no established consensuses over the diagnosis and treatment of CSCIWFD, such as the lack of evidence-based standards for indications of non-surgical treatment and risk of secondary neurological injury, as well as debates over the optimal timing for surgical intervention and indications for different surgical approaches. To address these issues, the Spine Trauma Group of the Orthopedic Branch of the Chinese Medical Doctor Association organized experts in the relevant fields to formulate Diagnosis and treatment guideline for acute cervical spinal cord injury without fracture- dislocation in adults ( version 2025) . Based on evidence-based medicine and the principles of scientific rigor and clinical applicability, the guidelines proposed 11 recommendations covering terminology, diagnosis, evaluation treatment, and rehabilitation, etc., aiming to standardize the management of CSCIWFD.